MUJBSc vol.1 issue 2 by MUJBSc

THE MANCHESTER UNDERGRADUATE JOURNAL OF BIOLOGICAL SCIENCES Volume 1 Issue 2

JULY 17, 2017

Contents Opening letter

→ p. 2

Association of Slit2 Polymorphisms with Schizophrenia

→ p. 3

Investigating the role of inflammation in wound repair and regeneration using Xenopus as a model system → p. 12 The Methods and Ethics of Genetic Testing for Susceptibility to Alzheimer’s Disease → p. 25 → p. 36

Expanding the Genetic Code: Non-Proteinogenic Amino Acids

→ p. 49

Long non-coding RNA and the Regulation of Gene Expression

→ p. 57

Membrane Structures Involved in Adult Stem Cell Regulation

→ p. 71

Page

Healthy people with lethal mutations. What are the implications?

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Opening letter Alexandru Băciţa & Alexandru Ioan Vodă

This MUJBSc summer edition has expanded in article submissions compared to our first issue. We are very proud that students see the value in practicing writing and exposing their ideas to the world, not just the university. This process is not easy for an undergraduate: one must start formatting their ideas, learn about proper citation, adjust and/or reply to their feedback. We believe learning to adjust or defend your reasoning will undoubtely be an incredible skill for any student author that submits or gets published with MUJBSc.

Page

Thank you for your engagement and support!

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Association of Slit2 Polymorphisms with Schizophrenia Hui Wen Chong (huiwen_chong@hotmail.com) Faculty of Biology, Medicine and Health, The University of Manchester, U.K.

Introduction Neurogenesis and neuronal migration in the central nervous system (CNS) are steered by the balance between chemoattractants and chemorepellents in growth cone collapsing activities (Yeh et al., 2014). Disruption of this balance can alter the normal neurodevelopmental processes, leading to psychiatric disorders (Gressens, 2005), such as schizophrenia (Kim et al., 2009). Slit protein has been identified as one of the important chemorepellents which regulates axonal pathfinding and migration of dopaminergic neurons (Dugan et al., 2011) in CNS when being coupled with its receptor, Roundabout (Robo) (Brose et al., 1999). Slit homologue 2 (Slit2) originates from the Slit protein family (Itoh et al., 1998), characterized by an estimated 200kDa (Hu, 1999) that comprises 4 disulphidelinked leucine rich repeats (LRRs). The second LRR domain (D2) spans residues 271-479 (Morlot et al., 2007b), forming a concave surface which underlies an active binding site primarily for the first Ig domain (Ig1) for Robo homologue 1

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Slit homologue 2 (Slit2) is an evolutionarily conserved protein that has been proved crucial in many biological processes through the interaction with its target receptor, Roundabout homologue 1 (Robo1). Disruption of the Slit2-Robo1 signalling pathway can cause severe consequences and may be a potential contributor to the pathological hallmarks of schizophrenia. Three schizophrenia-related single nucleotide polymorphisms (SNPs), p.D285A, p.N521T and p.D651H mapping onto the Slit2 gene have been discovered and is suggested that these SNPs may lead to changes in Slit2 protein folding, hence affecting its protein stability. The underlying molecular mechanisms, however, remain unresolved. This study aims to address the association between schizophrenia and Slit2 by assessing the protein stability change caused by the listed SNPs using structural isolated protein domain and sequential whole protein models. Comparison between the three candidate SNPs showed that p.D285A had the biggest impact in reducing Slit2 protein stability, presumably due to its location on the Robo1 binding pocket in Slit2 domain 2. Further analysis showed that this hydrophilic-hydrophobic substitution on the Slit2 protein surface can be deleterious and may lead to protein aggregation. Correlation between isolated protein domain stability and

whole protein was not fully established due to methodological limitations but should be carefully considered in future studies. This study, however, has provided a novel insight into the possible underlying genetic predisposition to schizophrenia in relation to Slit2 gene mutations.

Page

Abstract

Mutations, such as the single-nucleotide polymorphism (SNP), can affect protein folding (Ode et al., 2007), stability (Lorch et al., 2000) and functionality (Yamada et al., 2006). Corresponding stability change caused by SNP can be measured via protein folding free energy change

Methods 2.1 Datasets DNA sequence of Homo sapiens Slit2 gene was obtained from UniProt (UniProt ID: O94813; Brose et al., 1999; Bateman et al., 2015) and was used to represent MD_seq). MD_iso(s) of Slit2 were obtained from the Protein Data Bank in Europe (PDBe; http://www.ebi.ac.uk/ pdbe/; Velankar et al., 2016) database: D2 (PDBe ID: 2v9s; Morlot et al., 2007b) and D3 (PDBe ID: 2v70; Morlot et al., 2007a). 2.2 SNP-based genetic linkage analysis. Information about schizophreniaassociated SNPs was retrieved from the schizophrenia exome sequencing

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Schizophrenia, characterized by rigorous episodes of abnormal social behaviour and hallucinations, is a psychiatric disorder with complex aetiology (WHO, 2016). Multiple studies have proposed that abnormalities in neurogenesis (Schoenfeld and Cameron, 2015) and dopaminergic deviations (Brisch et al., 2014), can contribute to the pathogenesis of schizophrenia although the underpinning mechanisms remain elusive. A Swedish schizophrenia casecontrol exome sequencing study (dbGaP study accession: phs000473.v2.p2; Tryka et al., 2014) identified that Slit2 may be one of the candidate risk genes for schizophrenia. However, there are only a handful of similar studies (Shi et al., 2004; Gulsuner et al., 2013) which looked into the genetic variation of Slit as a contributing factor for schizophrenia. Alteration of the Slit-Robo signaling pathway can be related to schizophrenia as it can lead to some of the mentioned disease hallmarks (Dugan et al., 2011; Schoenfeld and Cameron, 2015). Hence, studying the mutations in Slit2 can be seen as an unconventional approach to improve our understanding of schizophrenia.

(ΔΔG, ΔΔG=ΔGmutant–ΔGwildtype; O'Neil and Degrado, 1990). This study focuses on predicting ΔΔG change caused by SNPs in isolated structural Slit2 single domain (MD_iso) and whole protein, inferred from full length multidomain Slit2 protein sequence (MD_seq), using: (i) 3D protein analysis software, Kinemage, Next Generation (KiNG; Chen et al., 2009); (ii) web server-based ΔΔG prediction tools, including IMutant2.0 (Capriotti et al., 2005), IMutant3.0 (Khan and Vihinen, 2010), Site Directed Mutator (SDM; Worth et al., 2011) and PoPMuSiC (Dehouck et al., 2011). Tool selection is based on overall correlation coefficients, mean absolute error and root-mean-square deviation (Kepp, 2014), where PoPMuSiC and IMutant methods exhibit high numerical accuracy (Kepp, 2014) while SDM gives more reliable predictions on some stabilizing mutations (Worth et al., 2011). The main aims of this study are: (i) To understand the impact of SNPs on Slit2 protein stability; and (ii) To compare the effect of SNPs on isolated Slit2 protein domain and whole protein stability.

Page

(Robo1). The third Slit LRR domain (D3) spans across residues 505-713 (Morlot et al., 2007a) which may be involved in regulating protein stability and proteinprotein interactions (Kobe and Kajava, 2001; Morlot et al., 2007a) Therefore, it is possible that mutations that alter the D2 and D3 domains can have significant consequences on the downstream SlitRobo signaling pathway.

Hydrogen atoms were added to the Slit2 MD_iso crystal structures: D2 (PDBe: 2v9s) and D3 (PDBe: 2v70) for crystallographic refinement purposes, supported by MolProbidy (Version 4.3; http:// molprobity.manchester.ac.uk/; Chen et al., 2010) accustomed to default settings. Physical property changes of the proteins were analysed in KiNG (Version 2.23; http://kinemage.biochem. duke.edu/software/king.php; Chen et al., 2009). Folding free energy change (ΔΔG) of MD_iso was accessed using all 4 mutation-protein stability prediction tools mentioned (PopMuSic, SDM, iMutant2.0 and i-Mutant3.0) at default settings (25°C, pH7). Due to the lack of readily available whole structure-based resource from PDBe, MD_seq was used as the alternative to infer whole protein stability in i-Mutant2.0 and i-Mutant3.0. Quantitative output on ΔΔG was used to provide a general overview on predictive protein stability change caused by SNP.

Results and Discussion This novel study describes 3 SNPs found in the highly conserved regions of Slit2 gene (Fig. 1), which may be directly/indirectly linked to schizophrenia via the alteration of Slit2 protein stability in subsequent to SlitRobo signaling pathway disruption. Analysis of Slit2 protein physical properties change (Van der Waals force and hydrophobicity) first shows that SNP p.D285A is located on the protein surface of Slit2 D2 (PDBe: 2v9s). Despite being able to accommodate with no significant Van der Waals overlaps, the substitution of hydrophilic Asp to hydrophobic Ala on the protein surface is likely to cause aggregation of Slit2 via hydrophobic effect (Petsko and Ringe, 2004). p.D285A is subject to be deleterious and can lead to more critical consequences as it is allocated two residues away from the conserved binding site (A287) for Robo1 (Morlot et al., 2007b). Probable outcomes include decreased binding affinity (Howitt et al., 2004) and altered protein folding (Ode et al., 2007), which may lead to protein precipitation/malformation (Yamada et al., 2006). Similar to p.D285A, p.N521T and p.D651H are located on the surface of Slit2 D3 (PDBe: 2v70) (Morlot et al., 2007a). However, there are no significant physical property changes associated with both SNPs, suggesting that these polar-polar residue replacements are unlikely to cause

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

2.3 Protein stability analysis.

ΔΔG values were compared between MD_iso and MD_seq caused by single SNP, and contrasted within multiple SNPs. ΔΔG-based disease prediction was based on i-Mutant3.0 and SDM, using MD_seq and MD_iso, respectively. Statistical analyses of ΔΔG was conducted using GraphPad Prism (GraphPad Software, version 7.0, La Jolla California USA, www.graphpad. com), where significance level, α ≤ 0.05.

Page

Genebook (http://atgu.mgh.harvard.edu/ ~spurcell/genebook/; Purcell et al., 2014). SNPs within regions of 271-279 aa (D2) and 505-713 a.a (D3) were identified as SNPs of interest: p.D285A, p.N521T, p.D651A. Reference SNP ID was obtained from the University of California Santa Cruz Genome browser (UCSC; https://genome.ucsc.edu/; Kent et al., 2002), human genome assembly version 38 (hg38; Genome Reference Consortium human genome build 38, December 2013) and was reviewed at the Single Nucleotide Polymorphism Database (dbSNP; Version 141; https:// www.ncbi.nlm.nih.gov/projects/SNP/; Sherry et al., 2001) and Exome Aggregation Consortium (ExAC; Version 0.3; http://exac.broadinstitute.org/; Lek et al., 2016) to check for other diseases relevant to gene loci.

Fig. 1. Sequence alignment of human Slit2 schizophrenia-related residues with 20 mammals adapted from UCSC genome assembly, marked with red stars: (A) c.A854C (p.D285A); (B) c.A1766A (p.N521T); (C) c.G1951C (p.D651H).

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The stability and functionality of a multidomain protein are governed by several intrinsic factors, including the stability of its domains as well as the interactions between its inter-domains (Schlicker et al., 2007). It is generally known that isolated domain is less stable than its corresponding full-length protein due to the lack of stabilizing effect from proteinprotein interactions (Bhaskara and Srinivasan, 2011) but there are rare exceptions (Vieux and Barrick, 2011; Fealey et al., 2012; Bandi et al., 2014). Comparison of Î&#x201D;Î&#x201D;G values between MD_iso and MD_seq in p.D285A, p.N521T and p.D651H provided a framework to study the empirical relationship between structural difference and protein stability. Akin to

previous studies (Lechauve et al., 2009; Bhaskara and Srinivasan, 2011), MD_iso is comparatively less stable (Unpaired ttest p.N521T: t=3.952, df=4, P=0.0168; p.D651H: t=3.054, df=4, P=0.0379) than MD_seq in p.N521T and p.D651H, but not p.D285A (Unpaired t-test: t=0.152, df=4, P=0.8867) (Fig. 2). Interestingly, while p.N521T and p.D651H are reported to be destabilizing mutations in MD_iso, they are in fact, stabilizing in MD_seq (Table 1), supporting the previous finding. Subsequent SNP-based disease prediction analysis in I-Mutant3.0 and SDM indicate that p.N521T is irrelevant in disease manifestation, similar to the protein stability prediction using MD_seq (Table 1). In this case, it is suggested that whole protein is able to provide a more robust representation of protein stability than isolated protein domain, as domains can undergo conformational changes and instability

Page

protein destabilization as they are more chemically similar (Henikoff and Henikoff, 1992) and are positioned away from the Robo1 binding sites (Morlot et al., 2007b).

Comparison between ΔΔG of isolated protein domain (MD_iso) and full length protein sequence (MD_seq) caused by schizophrenia-associated SNPs: D285A, N521T and D651H

D285A

N521T

D651H

There are disputes in the case of p.D651H, however, where i-Mutant3.0 computes that this mutation is likely to be deleterious but is predicted to be stabilizing (MD_seq) and has no clinical significance as reported in dbSNP (RefSNP ID: rs755409029). Protein stability has been associated with SNP severity (Rajasekaran et al., 2008) and disease manifestation (Wang

et al., 2011). SNP-based genetic analysis on ExAC reveals that loss of function mutations in Slit2 is indeed rare (0.007%) but missense mutations are more common (66.5%). Binding sites are deemed to be evolutionarily conserved (Fig. 1) as they are often present in small numbers and are highly specific in terms of biological functions (Porter et al., 2004). Hence, variant amino acid substitutions at these regions, such as p.D285A, can potentially lead to more detrimental effects on protein structure

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Page

during the modulation of quaternary structures (Deller et al., 2016).

Fig. 2. Change in folding free energies (ΔΔG) of isolated Slit2 protein domain (MD_iso) and full length multi-domain Slit2 protein sequence (MD_seq) under the influence of schizophreniaassociated SNPs: D285A, N521T and D651H. Bar indicates mean ΔΔG ± SD (Table 1), where ΔΔG<0=stabilizing; ΔΔG>0=destabilizing. Significance between MD_iso and MD_seq for each SNP are accessed using unpaired t-test, where MD_iso of N521T and D651H are significantly less stable than their corresponding MD_seq (Unpaired t-test p.N521T: t=3.952, df=4, P=0.0168; p.D651H: t=3.054, df=4, P=0.0379) but is comparable in D285A (Unpaired t-test: t=0.152, df=4, P=0.8867). This figure also shows that ΔΔG caused by D285A is significantly higher in contrast to N521T and D651H, when measured in MD_seq (1-way ANOVA: F(2, 3)=12.84, P=0.0338).

Bandi, S., Singh, S. M. & Mallela, K. M. G. (2014). The C-terminal domain of the utrophin tandem calponin-homology domain appears to be thermodynamically and kinetically more stable than the full-length protein. Biochemistry, 53(14), 2209-2211. Bateman, A., Martin, M. J., O'Donovan, C., Magrane, M., Apweiler, R., Alpi, E., Antunes, R., Ar-Ganiska, J., Bely, B., Bingley, M., Bonilla, C., Britto, R., Bursteinas, B., Chavali, G., Cibrian-Uhalte, E., Da Silva, A., De Giorgi, M., Dogan, T., Fazzini, F., Gane, P., Cas-Tro, L. G., Garmiri, P., Hatton-Ellis, E., Hieta, R., Huntley, R., Legge, D., Liu, W. D., Luo, J., MacDougall, A., Mutowo, P., Nightin-Gale, A., Orchard, S., Pichler, K., Poggioli, D., Pundir, S., Pureza, L., Qi, G. Y., Rosanoff, S., Saidi, R., Sawford, T., Shypitsyna, A., Turner, E., Volynkin, V., Wardell, T., Watkins, X., Watkins, Cowley, A., Figueira, L., Li, W. Z., McWilliam, H., Lopez, R., Xenarios, I., Bougueleret, L., Bridge, A., Poux, S., Redaschi, N., Aimo, L., Argoud-Puy, G., Auchincloss, A., Axelsen, K., Bansal, P., Baratin, D., Blatter, M. C., Boeckmann, B., Bolleman, J., Boutet, E.,

Bhaskara, R. M. & Srinivasan, N. (2011). Stability of domain structures in multidomain proteins. Scientific Reports, 1. Brisch, R., Saniotis, A., Wolf, R., Bielau, H., Bernstein, H., Steiner, J., Bogerts, B., Braun, K., Jankowski, Z., Kumaratilake, J., Henneberg, M., Gos, T. P., G. A. & Ringe, D. (2014). The role of dopamine in schizophrenia from a neurobiological and evolutionary perspective: old fashioned, but still in vogue. Frontiers in Psychiatry, 5, 11. Brose, K., Bland, K. S., Wang, K. H., Arnott, D., Henzel, W., Goodman, C. S., TessierLavigne, M. & Kidd, T. (1999). Slit proteins bind robe receptors and have an evolutionarily conserved role in repulsive axon guidance. Cell, 96(6), 795-806. Capriotti, E., Fariselli, P. & Casadio, R. (2005). I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Research, 33, W306-W310. Chen, V. B., Arendall, W. B., Headd, J. J., Keedy, D. A., Immormino, R. M., Kapral, G. J., Murray, L. W., Richardson, J. S. & Richardson, D. C. (2010). MolProbity: allatom structure validation for macromolecular crystallography. Acta Crystallographica Section D-Biological Crystallography, 66, 12-21. Chen, V. B., Davis, I. W. & Richardson, D. C. (2009). KiNG (Kinemage, Next Generation): A versatile interactive molecular and scientific visualization program. Protein Science, 18(11), 2403-2409. Dehouck, Y., Kwasigroch, J. M., Gilis, D. & Rooman, M. (2011). PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. Bmc Bioinformatics, 12.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Bibliography

Breuza, L., Casal-Casas, C., De Castro, E., Coudert, E., Cuche, B., Doche, M., Dornevil, D., Duvaud, S., Estreicher, A., Famiglietti, L., Feuermann, M., Gasteiger, E., Gehant, S., Gerritsen, V., Gos, A., Gruaz-Gumowski, N., Hinz, U., Hulo, C., Jungo, F., Keller, G., Lara, V., Lemercier, P., Lieberherr, D., Lombardot, T., Martin, X., Masson, P., Morgat, A., Neto, T., Nouspikel, N., Paesano, S., Pedruzzi, I., Pilbout, S., Pozzato, M., Pruess, M., et al. (2015). UniProt: a hub for protein information. Nucleic Acids Research, 43(D1), D204-D212.

Page

and stability (Gong et al., 2009). In contrast to p.N521T and p.D651H, p.D285A is highly destabilizing regardless the form (MD_iso, MD_seq) for stability measurement (Table 1). This may be due to its location on the Robo1 binding pocket in Slit2 D2 (Morlot et al., 2007b). Impact of p.D285A on whole protein stability, in fact, is significantly higher (1-way ANOVA: F(2, 3)=12.84, P=0.0338 using MD_seq dataset) (Fig. 2). p.D285A is most likely to be deleterious according to the disease prediction by iMutant3.0 and SDM (Table 1), in line with the previous evidence from physical property change analysis. There are no records from known disease databases, however, to support this observation. It is proposed that this residue can have important roles in ensuring proper attachment of Ig1/Ig2 of Robo1 to its respective binding site (Morlot et al., 2007b), therefore maintaining the balance of Slit-Robo regulatory network.

Fealey, M. E., Gauer, J. W., Kempka, S. C., Miller, K., Nayak, K., Sutton, R. B. & Hinderliter, A. (2012). Negative coupling as a mechanism for signal propagation between C2 domains of synaptotagmin I. Plos One, 7(10). Gong, S. S., Worth, C. L., Bickerton, G. R. J., Lee, S., Tanramluk, D. & Blundell, T. L. (2009). Structural and functional restraints in the evolution of protein families and superfamilies. Biochemical Society Transactions, 37, 727-733.

Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M. & Haussler, D. (2002). The human genome browser at UCSC. Genome Research, 12(6), 996-1006. Kepp, K. P. (2014). Computing stability effects of mutations in human superoxide dismutase 1. Journal of Physical Chemistry B, 118(7), 1799-1812. Khan, S. & Vihinen, M. (2010). Performance of protein stability predictors. Human Mutation, 31(6), 675-684. Kim, J. Y., Duan, X., Liu, C. Y., Jang, M. H., Guo, J. J. U., Pow-Anpongkul, N., Kang, E. C., Song, H. J. & Ming, G. L. (2009). DISC1 regulates new neuron development in the adult brain via modulation of AKT-mTOR signaling through KIAA1212. Neuron, 63(6), 761-773.

Gressens, P. (2005). Neuronal migration disorders. Journal of Child Neurology, 20(12), 968-971.

Kobe, B. & Kajava, A. V. (2001). The leucinerich repeat as a protein recognition motif. Current Opinion in Structural Biology, 11(6), 725-732.

Gulsuner, S., Walsh, T., Watts, A. C., Lee, M. K., Thornton, A. M., Casadei, S., Rippey, C., Shahin, H., Nimgaonkar, V. L., Go, R. C. P., Savage, R. M., Swerdlow, N. R., Gur, R. E., Braff, D. L., King, M. C., McClellan, J. M., Cogs & Grp, P. S. (2013). Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network. Cell, 154(3), 518-529.

Lechauve, C., Bouzhir-Sima, L., Yamashita, T., Marden, M. C., Vos, M. H., Lieb, U. & Kiger, L. (2009). Heme ligand binding properties and intradimer interactions in the full-length sensor protein Dos from Escherichia coli and its isolated heme domain. Journal of Biological Chemistry, 284(52), 36146-36159.

Henikoff, S. & Henikoff, J. G. (1992). Amino acid substitution matrices from protein blocks. Proceedings of the National Academy of Sciences of the United States of America, 89(22), 10915-10919. Howitt, J. A., Clout, N. J. & Hohenester, E. (2004). Binding site for Robo receptors revealed by dissection of the leucine-rich repeat region of Slit. Embo Journal, 23(22), 4406-4412. Hu, H. Y. (1999). Chemorepulsion of neuronal migration by Slit2 in the developing mammalian forebrain. Neuron, 23(4), 703711. Itoh, A., Miyabayashi, T., Ohno, M. & Sakano, S. (1998). Cloning and expressions of three mammalian homologues of Drosophila slit suggest possible roles for Slit in the

Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O'Donnell-Luria, A. H., Ware, J. S., Hill, A. J., Cummings, B. B., Tukiainen, T., Birnbaum, D. P., Kosmicki, J. A., Duncan, L. E., Estrada, K., Zhao, F. M., Zou, J., PierceHollman, E., Berghout, J., Cooper, D. N., Deflaux, N., DePristo, M., Do, R., Flannick, J., Fromer, M., Gauthier, L., Goldstein, J., Gupta, N., Howrigan, D., Kiezun, A., Kurki, M. I., Moonshine, A. L., Natarajan, P., Orozeo, L., Peloso, G. M., Poplin, R., Rivas, M. A., Ruano-Rubio, V., Rose, S. A., Ruderfer, D. M., Shakir, K., Stenson, P. D., Stevens, C., Thomas, B. P., Tiao, G., Tusie-Luna, M. T., Weisburd, B., Won, H. H., Yu, D. M., Altshuler, D. M., Ardissino, D., Boehnke, M., Danesh, J., Donnelly, S., Elosua, R., Florez, J. C., Gabriel, S. B., Getz, G., Glatt, S. J., Hultman, C. M., Kathiresan, S., Laakso, M.,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Dugan, J. P., Stratton, A., Riley, H. P., Farmer, W. T. & Mastick, G. S. (2011). Midbrain dopaminergic axons are guided longitudinally through the diencephalon by Slit/Robo signals. Molecular and Cellular Neuroscience, 46(1), 347-356.

formation and maintenance of the nervous system. Molecular Brain Research, 62(2), 175-186.

Page

Deller, M. C., Kong, L. & Rupp, B. (2016). Protein stability: a crystallographer's perspective. Acta Crystallographica Section F-Structural Biology Communications, 72, 72-95.

Morlot, C., Hemrika, W., Romijn, R. A., Gros, P., Cusack, S. & McCarthy, A. A. (2007a). Production of Slit2 LRR domains in mammalian cells for structural studies and the structure of human Slit2 domain 3. Acta Crystallographica Section D-Biological Crystallography, 63, 961-968. Morlot, C., Thielens, N. M., Ravelli, R. B. G., Hemrika, W., Romijn, R. A., Gros, P., Cusack, S. & McCarthy, A. A. (2007b). Structural insights into the Slit-Robo complex. Proceedings of the National Academy of Sciences of the United States of America, 104(38), 14923-14928. O'Neil, K. T. & Degrado, W. F. (1990). A thermodynamic scale for the helix-forming tendencies of the commonly occurring amino acids. Science, 250(4981), 646-651. Ode, H., Matsuyama, S., Hata, M., Neya, S., Kakizawa, J., Sugiura, W. & Hoshino, T. (2007). Computational characterization of structural role of the non-active site mutation M36I of human immunodeficiency virus type 1 protease. Journal of Molecular Biology, 370(3), 598-607. Petsko, G. A. & Ringe, D. (2004). Quarternary structure: Intermolecular Interface. In: Lawrence, E. & Robertson, M. (eds.) Protein structure and function. London: New Science Press Ltd. Porter, C. T., Bartlett, G. J. & Thornton, J. M. (2004). The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data. Nucleic Acids Research, 32, D129-D133. Purcell, S. M., Moran, J. L., Fromer, M., Ruderfer, D., Solovieff, N., Roussos, P., O'Dushlaine, C., Chambert, K., Bergen, S. E., Kahler, A., Duncan, L., Stahl, E., Genovese,

Rajasekaran, R., Doss, C. G. P., Sudandiradoss, C., Ramanathan, K., Purohit, R. & Sethumadhavan, R. (2008). Effect of deleterious nsSNP on HER2 receptor based on stability and binding affinity with herceptin: A computational approach. Comptes Rendus Biologies, 331(6), 409-417. Schlicker, A., Huthmacher, C., Ramirez, F., Lengauer, T. & Albrecht, M. (2007). Functional evaluation of domain-domain interactions and human protein interaction networks. Bioinformatics, 23(7), 859-865. Schoenfeld, T. J. & Cameron, H. A. (2015). Adult Neurogenesis and Mental Illness. Neuropsychopharmacology, 40(1), 113-128. Sherchan, P., Huang, L., Wang, Y. C., Akyol, O., Tang, J. P. & Zhang, J. H. (2016). Recombinant Slit2 attenuates neuroinflammation after surgical brain injury by inhibiting peripheral immune cell infiltration via Robo1-srGAP1 pathway in a rat model. Neurobiology of Disease, 85, 164173. Sherry, S. T., Ward, M. H., Kholodov, M., Baker, J., Phan, L., Smigielski, E. M. & Sirotkin, K. (2001). dbSNP: the NCBI database of genetic variation. Nucleic Acids Research, 29(1), 308-311. Shi, Y. Y., Zhao, X. Z., Yu, L., Tao, R., Tang, J. X., La, Y. J., Duan, Y., Gao, B., Gu, N. F., Xu, Y. F., Feng, G. Y., Zhu, S. M., Liu, H. J., Salter, H. & He, L. (2004). Genetic structure adds power to detect schizophrenia susceptibility at SLIT3 in the Chinese Han population. Genome Research, 14(7), 13451349. Tryka, K. A., Hao, L. N., Sturcke, A., Jin, Y. M., Wang, Z. Y., Ziyabari, L., Lee, M., Popova, N., Sharopova, N., Kimura, M. & Feolo, M. (2014). NCBI's Database of Genotypes and Phenotypes: dbGaP. Nucleic Acids Research, 42(D1), D975-D979. Velankar, S., van Ginkel, G., Alhroub, Y., Battle, G. M., Berrisford, J. M., Conroy, M. J.,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Lorch, M., Mason, J. M., Sessions, R. B. & Clarke, A. R. (2000). Effects of mutations on the thermodynamics of a protein folding reaction: Implications for the mechanism of formation of the intermediate and transition states. Biochemistry, 39(12), 3480-3485.

G., Fernandez, E., Collins, M. O., Komiyama, N. H., Choudhary, J. S., Magnusson, P. K. E., Banks, E., Shakir, K., Garimella, K., Fennell, T., DePristo, M., Grant, S. G. N., Haggarty, S. J., Gabriel, S., Scolnick, E. M., Lander, E. S., Hultman, C. M., Sullivan, P. F., McCarroll, S. A. & Sklar, P. (2014). A polygenic burden of rare disruptive mutations in schizophrenia. Nature, 506(7487), 185-+.

Page

NcCarroll, S., McCarthy, M. I., McGovern, D., McPherson, R., Neale, B. M., Palotie, A., Purcell, S. M., Saleheen, D., Scharf, J. M., Sklar, P., Sullivan, P. F., Tuomilehto, J., Tsuang, M. T., Watkins, H. C., Wilson, J. G., Daly, M. J., MacArthur, D. G. & Exome Aggregation, C. (2016). Analysis of proteincoding genetic variation in 60,706 humans. Nature, 536(7616), 285-+.

Dana, J. M., Gore, S. P., Gutmanas, A., Haslam, P., Hendrickx, P. M. S., Lagerstedt, I., Mir, S., Montecelo, M. A. F., Mukhopadhyay, A., Oldfield, T. J., Patwardhan, A., Sanz-Garcia, E., Sen, S., Slowley, R. A., Wainwright, M. E., Deshpande, M. S., Iudin, A., Sahni, G., Torres, J. S., Hirshberg, M., Mak, L., Nadzirin, N., Armstrong, D. R., Clark, A. R., Smart, O. S., Korir, P. K. & Kleywegt, G. J. (2016). PDBe: improved accessibility of macromolecular structure data from PDB and EMDB. Nucleic Acids Research, 44(D1), D385-D395. Vieux, E. F. & Barrick, D. (2011). Deletion of internal structured repeats increases the stability of a leucine-rich repeat protein, YopM. Biophysical Chemistry, 159(1), 152161.

Worth, C. L., Preissner, R. & Blundell, T. L. (2011). SDM-a server for predicting effects of mutations on protein stability and malfunction. Nucleic Acids Research, 39, W215-W222. Yamada, Y., Banno, Y., Yoshida, H., Kikuchi, R., Akao, Y., Murate, T. & Nozawa, Y. (2006). Catalytic inactivation of human phospholipase D2 by a naturally occurring Gly901Asp mutation. Archives of Medical Research, 37(6), 696-699. Yeh, M. L., Gonda, Y., Mommersteeg, M. T. M., Barber, M., Ypsilanti, A. R., Hanashima, C., Parnavelas, J. G. & Andrews, W. D. (2014). Robo1 modulates proliferation and neurogenesis in the developing neocortex. Journal of Neuroscience, 34(16), 5717-5731.

Page

Wang, J. H., Cao, Z. X., Zhao, L. L. & Li, S. Q. (2011). Novel strategies for drug discovery based on intrinsically disordered proteins (IDPs). International Journal of Molecular Sciences, 12(5), 3205-3219.

WHO. (2016). Schizophrenia [Online]. World Health Organization. Available: http://www.who.int/mediacentre/factsheets/f s397/en/ [Accessed 5 December 2016].

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Investigating the role of inflammation in wound repair and regeneration using Xenopus as a model system Maryam Khan (maryam.khan-3@student.manchester.ac.uk) Faculty of Biology, Medicine and Health, the University of Manchester, U.K.

Introduction It has long been known that many animal species, particularly in the early stages of life, have the ability to heal wounds and completely regenerate injured tissues and sometimes whole organs without scar formation. For most species where this is possible, this ability is restricted to the earliest stages of development, however in some, particularly amphibians, it is retained throughout the life cycle. The capability of certain species to regenerate tissues to their full capacity, as opposed to the generation of a nonfunctional scar lacking the appendages present in the pre-wound state, provides an opportunity to offset the many problems caused by scarring and impaired wound healing in human wound repair. Inflammation and the degree of the inflammatory response has

The ultimate aim of this research is therefore to identify the mechanisms by which scarless wound healing is possible, thus providing the opportunity to pave the way for potential improvements in wound healing in humans, for example following surgery, as well as the development of novel therapies in human wound repair and regeneration.

1. The process and mechanisms of wound healing The process of wound healing following an injury is comprised of 3 distinct, often overlapping phases following haemostasis; inflammation, proliferation or tissue formation, and scar maturation, or remodelling of the injured tissue (Gurtner et al., 2008). Wound healing is also mediated by several components, including cytokines, growth factors and inflammatory cells. Cells of the immune system, such as neutrophils,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Impaired wound healing, including both scarring and the formation of chronic wounds, is an area of major concern in modern medicine. Therefore, elucidating the mechanisms by which effective tissue regeneration occurs in other organisms may allow us to develop novel therapies for use in human patients, and to offset the problems caused by improper wound healing following injury or surgery.

been identified as a key factor responsible for the transition between wound healing without scars and healing that involves the formation of scars. For this reason, the mechanisms by which scarless wound healing takes place, and the influence of elements such as proinflammatory cytokines, growth factors and myeloid cells, has been widely studied in model organisms, most commonly in amphibians such as Xenopus.

Page

Abstract

Inflammation

Following the initial haemostasis phase, a local inflammatory response at the site of injury, involving recruitment of circulating inflammatory cells, takes place (Koh and DiPietro, 2013). This response is also stimulated by the hypoxic nature of wound site, which promotes cells such as macrophages to secrete pro-inflammatory mediators (Koh and DiPietro, 2013). Neutrophils are the primary cells to be recruited to the wound site (Walmsley et al., 2015) through the action of chemoattractants such as TGFÎ˛ and complement proteins, and remove bacteria and cellular and foreign debris to prevent infection (King et al., 2012). During this period, epithelial cells from the edges of the wound site begin to migrate and proliferate towards each other to begin to seal the wound (Enoch and Leaper, 2007). Circulating macrophages and monocytes arrive at the wound site around 48-96 hours following injury (Godwin et al., 2013), clearing excessive and apoptotic neutrophils and dead cells, as well as producing inflammatory factors such as TGF-Î˛, VEGF, EGF and FGF (Sun et al., 2014), which attract and activate fibroblasts, and stimulate the production of ECM (Walmsley et al., 2015). Later in the process, macrophages take on antiinflammatory properties to reduce the inflammatory response, indicating that macrophages are a key cellular regulator of tissue repair following wounding. These cells, as well as circulating monocytes, are also involved in the transition between inflammation and

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

In the normal process of wound repair, immediately following the injury, blood loss is reduced through vasoconstriction and the action of platelets, which, alongside the coagulation cascade, forms a clot to seal off the wound and prevent further blood loss and infection. The platelets then degranulate, releasing factors such as platelet-derived growth factor (PDGF), epidermal growth factor (EGF) and transforming growth factor (TGF-Î˛), which act as the major stimulus for inflammation and the normal wound healing response (Martin and Nunan, 2015), including stimulating cells such as keratinocytes and fibroblasts, involved in remodelling of the injured tissue (Ashcroft et al., 1999). These factors also act by attracting fibroblasts and macrophages and activating these cells, as well as activation of the complement and kinin cascades, clotting and plasmin generation (Enoch and Leaper, 2007).

Vasodilation then occurs, allowing protein such as fibronectin, fibrinogen and fibrin to form a fibrin plug through combination with the platelet clot (Williamson and Harding, 2004), which later acts as the matrix for tissue repair (Gurtner et al., 2008).

Page

macrophages and mast cells act to remove dead and damaged cells, and provide signals and secrete molecules such as growth factors, as well as modulating the extracellular matrix (ECM) environment to regulate the fibroblast response and formation of the scar (Godwin and Rosenthal, 2014). The process of wound repair must be carefully regulated in order to ensure that infection and blood loss is restricted and the injury is repaired as rapidly as possible, and in cases where elements of the wound repair process are either excessive or disrupted, an impaired wound healing response, such as a chronic wound, often results (Martin and Nunan, 2015). Furthermore, wound healing in scarless organisms, such as the axolotl, has been found to show a different profile in comparison to scarforming healing, for example, reduced haemostasis and lower levels of neutrophil infiltration (Seifert et al., 2012).

Proliferation

The proliferation stage of wound healing occurs between 48 hours and 10 days following injury (Walmsley et al., 2015). This involves the formation of the granulation tissue following fibroblast migration and proliferation and secretion of the ECM, composed of glycosaminoglycans, proteoglycans, elastin and collagen, by the fibroblasts, allowing re-epithelialisation to occur through the action of keratinocytes (Enoch and Leaper, 2007). The proportion of type I in comparison to type III collagen present has been shown to differ between scarred and non-scarred tissue (Walmsley et al., 2015), suggesting that the type of collagen present is involved in healing outcome. Angiogenesis also occurs during this phase, whereby the newly formed blood vessels invade the wound site. However, the robustness of angiogenesis, as well as levels of VEGF, have both been shown to influence scar formation, with scarforming wounds more vascular and higher in VEGF than non-scarring wounds, for example those occurring in human foetal tissue (Sun et al., 2014), with scarring regained in the foetus through the addition of exogenous VEGF.

Maturation

Following this phase, remodelling and maturation of the newly formed scar takes place, and can last for a year or more (Gurtner et al., 2008). ECM reorganisation is a constant process, accompanied by decreased vascularity of the tissue as collagen is continuously broken down and remodelled through

Adult wound repair involves rapid sealing of the injured tissue and a high level of inflammation, however this comes with the cost of scar formation. Conversely, in immature organisms, such as the human foetus, there is a much reduced level of inflammation, thus resulting in repair of the wound to a similar state to the original tissue, and without formation of an avascular scar. Furthermore, there has been found to be a clear link between inflammation and the inflammatory response to injury and the outcome and quality of healing of the wound (King et al., 2012), thus suggesting that it is the action of, for example, inflammatory factors and cells such as macrophages, that is ultimately responsible for the outcome of the healing process.

2. Scarring healing

wound

Wound healing in human adults is a process of reparative healing of the injury, as opposed to regeneration of a functional tissue (Walmsley et al., 2015) and often results in the production of a non-functional mass of fibrotic tissue, composed of fibroblasts and disorganised collagen (Gurtner et al., 2008), and lacking appendages such as hair follicles and sebaceous glands. This can often lead to a multitude of problems, including functional and psychological problems as

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

metalloproteinases (Walmsley et al., 2015). Wound contraction also occurs, involving fibroblast and ECM interactions (Enoch and Leaper, 2007), followed by maturation of scar whereby the collagen fibres thicken to increase strength of the scar, although the strength of the original tissue cannot be recovered (Yates et al., 2012), ultimately leading to the production of an avascular scar lacking appendages such as hair follicles and sebaceous glands.

Page

proliferation in the wound repair process. Mast cells appear in the wound site later and are responsible for the secretion of pro-inflammatory growth factors that result in fibroblast activation and scar formation (Sun et al., 2014).

It is known that factors such as age, tissue specificity and psychological stress affect the degree of scarring following injury (Ojeh et al., 2015). Furthermore, human wound healing may sometimes involve an excessive, pathological fibrotic response, with excessive collagen deposition, leading to the formation of raised hypertrophic scars (Enoch and Leaper, 2007) or keloid scars, scars which have grown beyond their original

Scar formation in response to injury is largely due to the ECM and fibroblasts (Gurtner et al., 2008), which is in turn affected by signals emitted by cells such as macrophages (Martin and Nunan, 2015). Scar forming wound repair in adults involves the rapid proliferation of fibroblasts in order to prevent infection occurring in the wound site, however this results in scar formation and prevention of complete recovery of tissue function (Hu et al., 2014a) as these two outcomes are commonly assumed to be exclusive of each other, suggesting that tissue fibrosis in response to injury is incompatible with tissue regeneration (Godwin and Rosenthal, 2014). Furthermore, the high levels of hyaluronic acid (HA) present in foetal tissues, which prevents fibroblast proliferation and thus inhibits scar formation, are not found in adult scarforming tissues (Walmsley et al., 2015), suggesting that tissue environment is also crucial for the outcome of healing. Macrophages have been shown to affect scar formation through the emission of signals that induce scarring, and the removal of these has been shown to result in incomplete repair (Godwin et al., 2013), whereas studies involving the removal of mast cells have led to the same outcome as normal wound healing. This therefore suggests that the role of mast cells in wound healing is likely to be more related to the fine-tuning of the repair process (Martin and Nunan, 2015), but macrophages play a more instrumental role in early wound healing

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Impaired wound healing has been shown to be linked with an out of control inflammatory response (Yates et al., 2012), for example, overexpression of IL5 in mice, a cytokine responsible for the regulation of eosinophils, results in prolonged inflammation and delayed and impaired wound healing (Leitch et al., 2009). However, it is possible to repair wounds to the original, functional tissue architecture without the formation of scars in some animals, including humans, particularly in the midgestational foetal stage, although in some cases bone regeneration and up to 70% of the liver mass is possible in adult humans (Stoick-Cooper et al., 2007). In other species, however, individuals retain the ability for tissue and even organ regeneration throughout life (Love et al., 2013a). As the mechanisms of wound healing are highly conserved at the cellular and molecular level, this provides the opportunity for study in those organisms that retain regenerative capacity through their lifetime, in order to determine the inflammatory and immune system changes responsible for the shift from regeneration to scarring.

boundaries, although there is likely a genetic component to keloid formation (Broughton et al., 2006). Both of these scar pathologies are unique to humans and are not found in other species, making study of the mechanisms underlying them more difficult (Ud-Din et al., 2014).

Page

well as aesthetic and medical, for example the formation of scar tissue following myocardial infarction can potentially lead to pathologies such as heart failure and arrhythmias (Gurtner et al., 2008), and places a large burden on healthcare systems around the world.

The outcome of the wound repair process has also been shown to be tissue specific. The oral mucosa is an example of the very few adult tissues that retain the ability for scar free healing in humans (Ud-Din et al., 2014). Healing in this tissue involves a faster resolution of inflammation and has been shown in pig studies to involve less wound contraction and lower numbers of inflammatory cells such as macrophages and mast cells than in tissues that heal through scar formation, such as skin (Sun et al., 2014; Turabelidze and DiPietro, 2012).

Scarless wound healing

Despite the problems associated with impaired wound healing in human adults, scarless wound repair and regeneration is possible, in both human foetuses (Hu et al., 2014a) and in other animals, including amphibians, reptiles and fish (Love et al., 2013a) throughout their lifetimes (Ud-Din et al., 2014). The

Studying the mechanisms and the exact reasons behind the switch from regeneration to fibrotic wound healing may therefore allow us to characterise the factors responsible for scarless healing. For example, it has been found that both regeneration and foetal wound healing involve a much lower degree of inflammatory response in comparison to adult wound healing (Ud-Din et al., 2014), as well as decreased numbers of neutrophils, macrophages, mast cells (see Figure 1) and pro-inflammatory cytokines such as TGFβ and interleukins such as IL-10 (Hu et al., 2014a), as opposed to scar forming wounds, which display much higher amounts of TGFβ in comparison (Walmsley et al, 2015). Mouse studies involving embryos lacking in IL-10 were found to result in scar formation (Godwin et al., 2013), and it is known that modulation of inflammation resulting in scarring from a non-scarring phenotype as a consequence of genetic deletion of IL-10 during development occurs in Xenopus. The immaturity of the foetal immune system and the resulting effects of a muted inflammatory response has therefore been hypothesised as a major reason for the ability to heal wounds without scars, therefore suggesting that the maturation of immune system elements such as platelets, required to secrete growth factors essential for the inflammatory response, is responsible for the transition

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Knocking down known factors involved in signalling in wound healing as well as cellular proliferation and differentiation, such as TGF-β, has also been shown to reduce scarring in mice studies (Martin and Nunan, 2015). Further experiments in mice involving the knocking down of Smad3, a protein involved in the mediation of signals from TGF-β, have also resulted in an increased rate and quality of wound healing, coupled with a reduced inflammatory response and lower numbers of fibroblasts in comparison to mice with non-disrupted Smad3 (Ashcroft et al., 1999). The lack of monocytes, which secrete TGF-β, present in null-mice resulted in a decreased scarring phenotype, consistent with previous findings regarding the role of TGF-β in wound healing and scarring (Ashcroft et al., 1999).

most widely used model organisms to study wound healing and regeneration in vivo are the axolotl salamander, with the ability to regenerate tissues and whole organs throughout life, and the Xenopus frog, in which regeneration is restricted to the pre-metamorphosis stage of life (Godwin and Rosenthal, 2014).

Page

and scar formation (He and Marneros, 2013).

A diminished inflammatory response and lower levels of pro-inflammatory cytokines such as IL-8 (Liechty et al., 1998) and IL-6 (Liechty et al., 2000), which mediate chemotaxis of immune cells including neutrophils, macrophages and keratinocytes to the wound site, have also been found to be characteristic of human foetal wound repair, again suggesting that lowered inflammation due to the lack of maturity of the immune system is key in scarless wound healing. In response to platelet-derived growth factor (PDGF), which is released during the wound healing process to increase production of IL-6 and IL-8, amongst others, a much dampened response is shown in the foetal compared to adult tissues (Liechty et al., 1998; 2000). Furthermore, adding exogenous cytokine, both IL-6 and IL-8, results in scar formation (Liechty at al., 2000). Likewise, in immunodeficient amphibians, scarless skin healing is possible through life, and these individuals display a higher ability for regeneration (Franchini and Bertolotti, 2014). The organisation of the collagen involved in the ECM of foetal wounds has also been found to differ from that in adult wounds, in that foetal ECM following healing resembles that of non-wounded skin (Ud-Din et al., 2014), with less

In addition, stem cells, particularly epidermal, such as those present in the hair follicle (Ojeh et al., 2015), mesenchymal, and foetal skin stem cells, have been indicated to play a role in scarless wound repair in the foetus, and has been implied to be a potential factor involved in the transition to scar-forming wound repair in late gestation. Although the stem cell profile of foetal skin tissue has not been fully characterised, the timing of the change from symmetrical to asymmetric stem cell division in epidermal cells has been found to temporally correlate with the transition to fibroproliferative healing involving scar formation (Hu et al., 2014b), indicating that stem cells may play a role in epidermal tissue regeneration.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Furthermore, studies in PU.1 mice, a genetically altered strain lacking leukocyte lineages but still able to heal wound with significantly less scarring than wild-type mice (Martin and Nunan, 2015) has again indicated that scar-free healing is associated with reduced inflammation.

crosslinking in collagen, whereas in adults collagen that is laid down following injury is far thicker and more disorganised (Hu et al., 2014a). However, it is not known precisely how molecular changes in fibroblasts induced by the inflammatory process leads to the disorganised deposition of collagen present in adult tissue scars (Martin and Nunan, 2015). Studies in African spiny mice, a species with the ability to fully regenerate tissue following dermal injury, found that in comparison to mice without this ability, the ECM that was developed following the injury was far more porous and dominated by collagen type III, as opposed to the dominance of collagen type I found in scars (Sun et al., 2014). Furthermore, it has been suggested that slow deposition of ECM and collagen in scarless healing, opposed to the rapid repair that results in scar formation, provides the opportunity for molecular communication in order to restore original tissue architecture and function (Sun et al., 2014).

Page

to a scar forming state (Bellayr et al., 2010).

In order to study the mechanisms of scarless wound healing and regeneration, as well as to identify changes occurring in the transition from scarless to scar forming healing, it is necessary to identify model systems in which these mechanisms can be determined. Two of the most commonly used model systems for this purpose are the Urodela salamander and the Xenopus frog. Both of these model systems have the capacity for regeneration and scarless wound healing, although only salamanders retain this ability, including the ability to regenerate organs such as the heart, tail and limbs (Godwin et al., 2013), throughout their life cycle, due to the high degree of cellular plasticity and potential for tissue renewal (Tseng and Levin, 2008), and potentially also due to the involvement of fibroblast regulation. However, it has been found that fibrotic healing pathways are retained in the axolotl, although they remain inactivated (Levesque et al., 2010). In Xenopus this ability is restricted to the premetamorphosis stages, with a loss of regenerative capacity as the immune

This transition that occurs during metamorphosis into the adult state closely reflect that of the development of scarring in the mammalian foetus during development, for example, similar ECM changes occur in both systems (Godwin and Rosenthal, 2014), therefore making Xenopus an ideal model system to study the transitional mechanisms between these two states in vivo. Xenopus embryos are also large and easily cultured, and analysing the effects of, for example, age on wound healing can be observed in multiple different aged organisms in tandem (Tseng and Levin, 2008). Wound healing in amphibians has many similarities to mammalian wound systems, at both the cellular and molecular level, and the fundamental aspects of the immune system, such as speed of onset and memory are retained in both (Godwin and Rosenthal, 2014), however the rapid laying down of fibrotic tissue in adult mammals results in an inability for regeneration (Gurtner et el., 2008). Despite this, the similarities between the molecular machinery in mammals and Xenopus makes it an ideal system in which to study the mechanisms of scarless wound healing and regeneration as well the factor involved in the transition from a scarless to a scarforming wound healing state. Other factors apart from inflammatory elements, have also been shown to play

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

a. Scarless wound healing in amphibians

system matures during development into the adult life cycle stages (Godwin and Rosenthal, 2014), as well as a delayed response and initiation of repair in adult frogs (Bertolotti et al., 2013).

Page

Mesenchymal stem cells have also been implied to play a role in enhanced wound closure and repair (Hu et al., 2014a). Studies involving injecting foetal skin stem cells into wounds on adult mice resulted in less scarring and faster resolution of wound healing, as well as increased re-epithelialisation (Hu et al., 2014b). It has also been suggested that depletion of skin stem cells play a role in the development of chronic non-healing wounds (Ojeh et al., 2015).

Figure 1: The process of wound healing following experimental wounding of Xenopus larvae. A shows the wounding of the lurp1:GFP transgenic larvae using a biopsy punch; B-D showing the closure of the wound from 5 minutes-14 days post-wounding and the migration of GFP-labelled myeloid cells towards the wound site; E-F showing the GFP-labelled cells in wound closure 2 hours and 7days post-wounding; G-H showing the capillary network surrounding the wound 2 hours and 7 days post wounding; I showing the wounding of mpeg1:GFP transgenic larvae using a biopsy punch; J-K showing the migration of macrophage-like cells towards the wound site. From Paredes et al. (2015), used with permission.

occurs in Xenopus as they age. The development of the thymus in Xenopus

b. Regeneration amphibians

Regeneration of appendages such as the tail and limb, including reformation of

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The shift from innate towards adaptive immunity has also been postulated to play a role in the decrease in scarless healing and regenerative capacity that

leads to range of altered responses following injury, including increased activity of lymphocytes such as T cells in comparison to inflammatory cells (Franchini and Bertolotti, 2014). Furthermore, nude mice display an ability for scarless skin wound healing, although a lack of T cells or thymus alone cannot confer this ability (Franchini and Bertolotti, 2014), suggesting that the balance between the innate response, including inflammation, and the adaptive response to injury, plays a role in the quality of wound healing.

Page

a role in scarless healing. For example, thyrotropin-releasing hormone (TRH), derived from adult Xenopus epithelial tissue, has been found to promote healing, wound closure and reepithelialisation in Xenopus skin wounds; this effect has been shown to be conserved in similar experiments involving human skin (Meier et al., 2013), again reinforcing the fact that both species retain similar fundamental mechanisms for wound repair.

Regeneration in amphibian species is also accompanied by an upregulation of genes, such as Sall4, which is temporally

Carbohydrate regulatory genes have also been found to show altered expression during tail regeneration in juvenile Xenopus (Love et al., 2013a). The alteration of the glucose metabolic pathway in this way provides an indication that the process of organ or appendage regeneration involves the modulation and usage or multiple pathways. Other factors such as nitrogen oxide (NO), (Franchini and Bertolotti, 2011) reactive oxygen species (ROS) and H₂O₂ (Love et al., 2013b) have also been suggested to provide essential stimulation necessary for regeneration by stimulating cell proliferation.

Conclusion The exact mechanisms involved in scarless wound healing occurring in both

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

It has been found in limb regeneration studies carried out in the axolotl salamander that early myeloid cell recruitment is a key feature in regeneration. Macrophages in particular, were found to be fundamentally essential in the regeneration of the limb and the lack of these has downstream effects such as a lack of TGF-β activation and ultimately failure to regenerate the limb (Godwin et al., 2013). However, the addition of anti-inflammatory agents, such as COX-2 inhibitors has been shown to allow the regaining of regenerative capacity in Xenopus larvae at stage 55, when this ability is ordinarily being lost (King et al., 2012).

expressed in Xenopus limbs only in the life cycle stages where regeneration is possible, Oct4, Klf4 and c-Myc, all of which are involved in cellular reprogramming (Godwin and Rosenthal, 2014), as well as the BMP, Notch, FGF, Wnt and TGFβ pathways, which are also involved in normal development of the tadpole tail (Ho and Whitman, 2008; Tseng and Levin, 2008; Love et al., 2011). Furthermore, as in wound healing, juvenile Xenopus regeneration involves less developed immune and inflammatory responses to appendage amputation than adults do, including lower levels of immune cell infiltration (Franchini and Bertolotti, 2011) again suggesting that lower efficiency and strength of inflammation is the primary factor responsible for regenerative capability. Scarless skin healing in Xenopus has also been shown to occur through a combination of repair in the dermis and regeneration in the epidermis (Bertolotti et al., 2013).

Page

major components such as spinal cord, muscles and blood vessels, involves the formation of an apical epithelial cap (AEC) from epithelial cells, which prevents fluid loss and infection (Bellayr et al., 2010). This is followed by the generation of a blastema, a ball of undifferentiated cells, potentially multipotent cells, which then gives rise through the process of epimorphic regeneration, and cellular dedifferentiation and reprogramming (King et al., 2012) to a newly formed, fully functional appendage or organ. The process of regeneration in both salamanders and Xenopus involves a concerted gene program, whereby the initial stages of regeneration resemble that of wound repair, followed by the formation of a regeneration bud, reprogramming of cellular identity and proliferation of these cell types and outgrowth and patterning of the appendage (Tseng and Levin, 2008).

humans and other vertebrates remain unclear, although many differences have observed between the processes of wound healing in organisms with and without the ability to heal wounds without scar formation. This therefore provides the opportunity for research into the various factors involved in the transition between forms of wound healing.

the complexities involved in scarless wound healing and regeneration and to identify factors involved that play a key role and may provide an opportunity for the development of novel therapeutics to aid in human wound healing and tissue repair.

Although wound healing in both scarless and scar-forming organisms is highly complex and involves interplay between many different molecular and cellular aspects and signalling, cells of the myeloid lineage, particularly macrophages, have consistently been shown to play a critical role in the outcome of wound healing, predominantly in the context of initiation and resolution of inflammation. Therefore further research into the molecular and genetic basis and mechanisms will allow us to develop a more complete picture of the mechanisms by which these cells, as well as other factors such as cytokines and growth factors, contribute to wound repair and the transition between functional tissue restoration and scar formation. Furthermore, it is necessary to develop a deeper understanding the roles of lineage specific cells in order to characterise the functional importance of these cells in wound repair.

Ashcroft G.S., Yang X., Glick A.B., Weinstein M., Letterio J.J., Mizel D.E., Anzano M., Greenwell-Wild T., Wahl S.M., Deng C., Roberts A.B. (1999) Mice lacking Smad3 show accelerated wound healing and an impaired local inflammatory response. Nature Cell Biology, 1: 260-266 Bellayr I.H., Walters T.J., Li Y. (2010) Scarless wound healing. Journal of the American College of Certified Wound Specialists, 2: 40-43 Bertolotti A., Malagoli D., Franchini A. (2013) Skin wound healing in different aged Xenopus laevis. Journal of Morphology, 274: 956-964 Broughon G., Janis J.E., Attinger C.E. (2006) Wound healing: an overview. Plastic and Reconstructive Surgery, 117: 7S Costa R.M.B., Soto X., Chen Y., Zorn A.M., Amaya E. (2008) spib is required for primitive myeloid development in Xenopus. Blood, 112: 2287-2296 Cowin A.J., Brosnan M.P., Holmes T.M., Ferguson M.J.W. (1998) Endogenous inflammatory response to dermal wound healing in the fetal and adult mouse. Developmental Dynamics, 212: 385-393 Eming S.A., Martin P., Tomic-Canic M. (2014) Wound repair and regeneration: Mechanisms, signalling, and translation. Sci Transl Med, 6: 265

Ferguson M.J.W., Oâ&#x20AC;&#x2122;Kane S. (2004) Scar-free healing: from embryonic mechanisms to

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Enoch S., Leaper D.J. (2007) Basic science of wound healing. Surgery, 26: 31-37

Page

By analysing the mechanisms by which successful scarless wound repair occurs in model organisms and the role of the immune system and inflammation in this, we can apply this to modern therapeutics to improve wound healing in humans, and provide the potential for non-fibrotic wound healing, for example, following surgery or injury. Therefore, more work is needed in order to clarify

Bibliography

adult therapeutic intervention. Phil Trans R Soc Lond B, 359: 839-850

scarless wound healing. Advances in Wound Care, 3: 304-314

Franchini A., Bertolotti E. (2011) Tail regenerative capacity and iNOS immunolocalization in Xenopus laevis tadpoles. Cell Tissue Res, 344: 261-269

King M.W., Neff A.W., Mescher A.L. (2012) The developing Xenopus limb as a model for studies on the balance between inflammation and regeneration. The Anatomical Record, 295: 1552-1561

Godwin J.W., Pinto A.R., Rosenthal N.A. (2013) Macrophages are required for adult salamander limb regeneration. PNAS, 110: 9415-9420 Godwin J.W., Rosenthal N. (2014) Scar-free wound healing and regeneration in amphibians: immunological influences on regenerative success. Differentiation, 87: 6675 Godwin J. (2014) The promise of perfect adult tissue repair and regeneration in mammals: learning from regenerative amphibians and fish. Bioessays, 36: 861-871 Gurtner G.C., Werner S., Barrandon Y., Longaker M.T. (2008) Wound repair and regeneration. Nature, 453: 314-321 He L., Marneros A.G. (2013) Macrophages are essential for the early wound healing response and the formation of a fibrovascular scar. The American Journal of Pathology, 182: 2407-2417 Ho D.M., Whitman M. (2008) TGF-Î˛ signalling is required for multiple processes during Xenopus tail regeneration. Developmental Biology, 315: 203-216 Hu M.S., Zhu T.N., Walmsley G.G., Longaker M.T., Lorenz H.P. (2014a) Advances in scarless wound healing. Journal of Clinical and Experimental Pathology, 4: 5 Hu M.S.M., Rennert R.C., McArdle A., Chung M.T., Walmsley G.G., Longaker M.T., Lorenz H.P. (2014b) The role of stem cells during

Leavitt T., Hu M.S., Marshall C.D., Barnes L.A., Lorenz H.P., Longaker M.T. (2016) Scarless wound healing: finding the right cells and signals. Cell Tissue Res, 365: 483493 Leichty K.W., Crombleholme T.M., Cass D.L., Martin B., Adzick N.S. (1998) Diminished interleukin-8 (IL-8) production in the fetal wound healing response. Journal of Surgical Research, 77: 80-84 Leichty K.W., Adzick N.S., Crombleholme T.M. (2000) Diminished interleukin-6 (IL-6) production during scarless human fetal wound repair. Cytokine, 12: 671-676 Leitch V.D., Strudwick X.L., Matthaei K.I., Dent L.A., Cowin A.J. (2009) IL-5overexpressing mice exhibit eosinophilia and altered wound healing through mechanisms involving prolonged inflammation. Immunology and Cell Biology, 87: 131-140 Levesque M., Villiard E., Roy S. (2010) Skin wound healing in axolotls: a scarless process. J Exp Zool B Mol Dev Evol, 314: 684â&#x20AC;&#x201C;697 Li J., Zhang S., Amaya E. (2016) The cellular and molecular mechanisms of tissue repair and regeneration as revealed by studies in Xenopus. Regeneration, 3: 198-208 Love N.R., Chen Y., Bonev B., Gilchrist M.J., Fairclough L., Lea R., Mohun T.J., Paredes R., Zeef L.A.H., Amaya E. (2011) Genomewide analysis of gene expression during Xenopus tropicalis tadpole tail regeneration. BMC Developmental Biology, 11:70

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Godwin J.W., Brockes J.P. (2006) Regeneration, tissue injury and the immune response. J. Anatomy, 209: 423-432

Koh T.J., DiPietro L.A. (2013) Inflammation and wound healing: the role of the macrophage. Expert Rev Mol Med, 13

Page

Franchini A., Berolotti E. (2014) The thymus and skin wound healing in Xenopus laevis adults. Acta Histochemica, 116: 1141-1147

Martin P., Leibovich S.J. (2005) Inflammatory cells during wound repair: the good, the bad and the ugly. Trends in Cell Biology, 15: 599-607 Martin P., Nunan R. (2015) Cellular and molecular mechanisms of repair in acute and chronic wound healing. British Journal of Dermatology, 173: 370-378 Meier N.T., Haslam I.S., Pattwell D.M., Zhang G.Y., Emelianov V., Paredes R., Debus S., Augustin M., Funk W., Amaya E., Kloepper J.E., Hardman M.J., Paus R. (2013) Thyrotropin-releasing hormone (TRH) promotes wound re-epithelialisation in frog and human skin. PLoS ONE, 8: 9 Mescher A.L., Neff A.W., King M.W. (2013) Changes in the inflammatory response to injury and its resolution during the loss of regenerative capacity in developing Xenopus limbs. PLoS ONE, 8: 11 Ojeh N., Pastar I., Tomic-Canic M., Stojadinovic O. (2015) Stem cells in skin regeneration, wound healing and their clinical applications. International Journal of Molecular Sciences, 16: 25476-25501 Oâ&#x20AC;&#x2122;Kane S., Ferguson M.J.W. (1997) Transforming Growth Factor Î˛s and wound healing. Int J Biochem Cell Biol, 29: 63-78 Paredes R., Ishibashi S., Borrill R., Robert J., Amaya E. (2015) Xenopus: an in vivo model for imaging the inflammatory response following injury and bacterial infection. Developmental Biology, 408: 213-228

Schultz G.S., Wysocki A. (2009) Interactions between extracellular matrix and growth factors in wound healing. Wound Repair and Regeneration, 17: 153-162 Seifert A.W., Monaghan J.R., Voss S.R., Maden M. (2012) Skin regeneration in adult axolotls: a blueprint for scar-free healing in vertebrates. PLoS ONE, 7: 4 Stoick-Cooper C.L., Moon R.T., Weindinger G. (2007) Advances in signalling in vertebrate regeneration as a prelude to regenerative medicine. Genes and Development, 21: 1292-1315 Sun G., Owens D.M., Mao J.J. (2014) Scarless skin regeneration- are we there yet? JSM Regenerative Medicine and Bioengineering, 2: 1007 Tseng A.S., Levin M. (2008) Tail regeneration in Xenopus laevis as a model for understanding tissue repair. J Dent Res, 89: 806-816 Turabelidze A., DiPietro L.A. (2012) Inflammation and wound healing. Endodontic Topics, 24: 26-38 Ud-Din S., Volk S.W., Bayat R. (2014) Regenerative healing, scar-free healing and scar formation across the species: current concepts and future perspectives. Experimental Dermatology, 23: 615-619 Walmsley G.G., Maan Z.N., Wong V.W., Duscher D., Hu M.S., Zielins E.R., Wearda T., Muhonen E., McArdle A., Tevlin R., Atashroo D.A., Senarath-Yapa K., Lorenz H.P., Gurtner G.C., Longaker M.T. (2015) Scarless wound healing: chasing the holy grail. Plastic and Reconstructive Surgery, 135: 907-917 Wilgus T.A., Ferreira A.M., Oberyszyn T.M., Bergdall V.K., DiPietro L.A. (2008) Regulation of scar formation by vascular endothelial growth factor, 88: 579-590

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Love N.R., Chen Y., Ishibashi S., Kritsiligkou P., Lea R., Koh Y., Gallop J.L., Dorey K., Amaya E. (2013b) Amputation-induced reactive oxygen species are required for successful Xenopus tadpole tail regeneration. Nature Cell Biology, 15: 222-229

Satoh A., Mitogawa K., Makanae A. (2015) Regeneration inducers in limb regeneration. Development, Growth and Differentiation, 57: 421-429

Page

Love N.R., Ziegler M., Chen Y., Amaya E. (2013a) Carbohydrate metabolism during vertebrate appendage regeneration: what is its role? How is it regulated?. Bioessays, 36: 27-33

during fetal wound healing. Dermatol, 132: 458-465

Invest

Wulff B.C., Parent A.E., Meleski M.A., DiPietro L.A., Schrementi M.E., Wilgus T.A. (2012) Mast cells contribute to scar formation

Yates C.C., Hebda P., Wells A. (2012) Skin wound healing and scarring: fetal wounds and regenerative restitution. Birth Defects Res C Embryo Today, 96: 325-333

Page

Williamson D., Harding K. (2004) Wound healing. Medicine, 32: 4-7

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The Methods and Ethics of Genetic Testing for Susceptibility to Alzheimer’s Disease Niamh Maguire (niamh.maguire@student.manchester.ac.uk)

Introduction

Alzheimer’s Disease (AD) affects over 35 million people worldwide. It is caused by a build-up of tau proteins causing neurofibrillary tangles, and a build-up of Amyloid-β proteins causing senile plaques, which together lead to memory loss and cognitive impairment. There are two main types of AD: Early Onset (EOAD) and Late Onset (LOAD). Genome Wide Association Studies (GWAS) has found susceptibility genes for both types; APP, PSEN1 and PSEN2 for EOAD, and APOE ε4 for LOAD. Overexpression of these genes increase the amount of Amyloid-β protein in the brain, causing senile plaques to develop. Genetic tests have been developed to detect the susceptibility genes for AD. The genetic tests are more reliable for EOAD genes as these genes are highly penetrant and autosomal dominant, but APOE ε4 for LOAD only confers up to an 8-fold risk, and therefore is not as predictive. Due to the relatively small risk presented by the overexpression of APOE ε4, ethical debate and controversy has surrounded implementation of genetic testing for AD. I will evaluate the risk presented by the susceptibility genes involved in AD development, and whether it is both informative and ethical to test an individual for their genetic risk for AD development.

Alzheimer’s Disease (AD) is the most common cause of dementia, affecting over 35 million people worldwide, including over 520,000 in the UK, mostly in the over 65 age category (Alzheimer's Society, 2014; Šerý et al., 2014). AD is a neurodegenerative disorder first described by Alzheimer in 1907 (Stelzmann et al., 1995), and is characterised by the development of neurofibrillary tangles containing tau protein in damaged nerve cells, followed by development of senile plaques containing Amyloid-β protein in the extracellular pockets of the CNS. These protein aggregations spread through the brain, leading to nerve cell and brain tissue destruction, and the most recognisable symptom of memory loss (Allen et al., 2014; Alzheimer’s Society, 2014; Braak, 2015). Stress induced changes in the endoplasmic reticulum and brain micro-haemorrhages have also been suggested to cause AD (Šerý et al., 2014). There are two main types of AD: early onset and late onset. Both diseases look alike, but differ in their age of onset and cause. Early Onset Alzheimer’s Disease (EOAD) is usually seen in patients under the age of 65, and accounts for about 1% of all Alzheimer’s cases (Sims and Williams, 2016). EOAD is often familial,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Page

Abstract

Faculty of Biology, Medicine and Health, The University of Manchester, U.K.

The issue of susceptibility to AD is prevalent in the public sphere. The media reports on new findings in the field, overly exaggerating the results to make a good story, and direct-to-consumer genetic testing companies advertise that they can conclusively tell an individual whether they will develop AD or not. This means that an increasing number of people with a family history of AD are seeking testing, putting extra pressure on physicians (Goldman et al., 2011). In order to provide effective testing, it is also necessary to provide pre- and posttesting genetic counselling to ensure that individuals are fully aware of the risks and benefits of genetic testing, and also to ensure that their psychological health is looked after. We can look to the implementation of genetic testing for Huntington’s Disease, another adultonset neurological disease, for guidelines as to how AD susceptibility testing could be implemented (Goldman et al., 2011). The Huntington’s Disease Society of America (2003), suggests that an individual should only be tested if an affected family member is known to have the susceptibility gene. The Society also suggests that genetic testing should only be carried out alongside comprehensive genetic counselling before, during and after the genetic test (Huntington’s Disease Society of America, 2003). However, at this time, while EOAD causative genes such as PSEN1 are good predictive markers, susceptibility genes for LOAD, particularly APOE, are unsuitable for testing due to the low risk conferred by the genes, and the fact that the genes are neither necessary nor sufficient for AD development. In the UK, testing is only currently offered to individuals thought to have a genetically linked AD through strong positive family

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

genetic variance means that genetically testing an individual for susceptibility to AD is currently unreliable.

Page

with a heritability value of 92-100%, and is mostly caused by three known genes: APP, PSEN1 and PSEN2 (Sims and Williams, 2016; Loy et al., 2014). The TREM2 gene has also been associated with EOAD, but this is a rare variant and so would be unsuitable for testing (Loy et al., 2014). Just over 500 families have been reported with such Mendelian forms of AD (Loy et al., 2014). Late Onset Alzheimer’s Disease (LOAD) is usually seen in patients over 65 years and accounts for up to 99% of all Alzheimer’s cases (Sims and Williams, 2016). The causative factors for LOAD are less well understood. Many cases of LOAD are sporadic and can be put down to environmental factors such as hypertension, hormone levels, smoking, stroke or heart disease, and the natural aging process (Ridge et al., 2013). Many families have been found where LOAD is present, but no linked gene mutations have been discovered. However, LOAD has been identified in some cases as a complex polygenic disease, with many small effect genes determining an individual’s susceptibility to and risk for LOAD. The International Genomics of Alzheimer’s Disease Project (IGAP and Schellenberg, 2012) is made up of four international research consortia, which since 2009 have uncovered ten novel LOAD susceptibility loci. The most significant of these loci is the AOPE ε4 allele, which can increase an individual’s risk of AD up to 8 fold (Loy et al., 2014) (See Table 1 for a summary of the main genes involved in AD development). However, it is estimated that we are only currently aware of 33% of the genetic variance of LOAD (Ridge et al., 2013). It has been suggested that epigenetic factors and non-coding RNA regulation may contribute to the remaining 67%, but this is as yet unproven (Šerý et al., 2014). The combination of low risk susceptibility genes and unknown

Alzheimer’s

Around 25% of the population aged over 55 have a family history of dementia (Loy et al., 2014). A third of AD patients have a first degree relative (sibling, parent or child) that also has suffered from AD, giving them a 2.5 fold risk of AD development (Bruni et al., 2014; Loy et al., 2014). This has prompted many researchers to investigate the underlying genetics involved in AD development. Many genetic techniques have been used to find these genes, but arguably the most successful has been Genome Wide Association Studies (GWAS). GWAS has been used to find genetic variants that are common to individuals with AD and their first degree relatives. GWAS has identified the pathways in which mutations occur that can lead to the development of AD including Amyloid-β protein production, Tau metabolism, immunity, inflammation, lipid metabolism, endocytosis and cell migration (Tosto and Reitz, 2013). GWAS has also helped to identify the specific gene variants that are causative, or provide susceptibility to AD (Tosto and Reitz, 2013). As mentioned before, EOAD affects those under the age of 65. It is also known as a Mendelian form of AD, due to the presence of autosomal dominant, high penetrance genes, and a strong family history of EOAD (Loy et al., 2014). There

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Genetics Disease

are three known causative genes: APP, PSEN1 and PSEN2, in which mutations account for 13% of EOAD cases (Combarros, 2014). The APP gene is located on chromosome 21 and encodes Amyloid Precursor Protein, a precursor to Amyloid-β protein, which is involved in forming the senile plaques seen in AD. Overexpression of APP leads to an increase in Amyloid-β protein and therefore an increased formation of plaques (Table 1). One example of APP overexpression leading to plaque formation is seen in the increased occurrence of AD in individuals with a trisomy of chromosome 21 and Down’s Syndrome (Thinakaran and Koo, 2007). A mutation that causes low expression of APP is a protective factor against AD (Loy et al., 2014). The PSEN1 gene on chromosome 14 and PSEN2 gene on chromosome 1 are similar genes that both encode forms of the Presenilin protein that make up γ-secretase, required to break down APP to Amyloidβ (Wakabayashi et al., 2007) (Table 1). Both PSEN1 and PSEN2 have a similar gene structure of ten exons, but only share 67% polypeptide similarity, with PSEN1 being a 43 kDa protein and PSEN2 being a 50 kDa protein (Wakabayashi et al., 2007). Interestingly, PSEN1 knock out mice are embryonic lethal, whereas PSEN2 knock out mice show no clear abnormalities (Wakabayashi et al., 2007). This suggests that the function of PSEN1 and PSEN2 proteins overlap (Wakabayashi et al., 2007). An increase in Presenilin expression would lead to increased levels of Amyloid-β and therefore increased formation of senile plaques. PSEN1 mutations are a more common cause of EOAD than PSEN2 and APP, although it is not yet known why (Wakabayashi et al., 2007).

Page

history, and their unaffected relatives, only after thorough genetic counselling (NICE, 2006). These restrictions mean genetic tests are only ever really carried out for EOAD in the UK at this time. This review will describe the role of genes in the development of both EOAD and LOAD, and evaluate whether or not susceptibility testing is suitable at this time.

The presence of APOE ε4 has also been shown to decrease the age of AD onset in individuals also carrying a PSEN1 or APP mutation (Bruni et al., 2014). Other genes identified by IGAP are involved in the AD development pathways of Amyloid-β protein production, Tau metabolism, immunity, inflammation, lipid metabolism, endocytosis and cell migration (Tosto and Reitz, 2013). According to Ridge et al. (2013), 33% of the total phenotypic variance seen in LOAD can be accounted for through genetics, the rest through environmental factors. Of this 33%, 6% is explained by APOE and 2% by the other known small effect genes found by GWAS. This means that 25% of the genetic variance is caused by unknown genetic factors. There are four main explanations for this unknown 25%: epigenetic effects, non-coding RNA regulation, low precision technology and gene-environment interactions. Epigenetic effects can be associated with the environment – cytosine methylation increases with age, stress and diet changes – and these changes can be passed on to offspring (Šerý et al., 2014). It is possible that these epigenetic changes can contribute to overexpression of genes encoding Amyloid Precursor

Page

LOAD affects those over the age of 65 and is also known as sporadic AD. The genetics of LOAD is more complicated than EOAD due to it being a complex polygenic disease interacting with environmental factors (Loy et al., 2014). There are no fully causative genes, just susceptibility genes. The International Genomics of Alzheimer’s Disease Project (IGAP) GWAS successfully identified ten genes that confer susceptibility to LOAD: APOE, ABCA7, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, MS4A4, and PICALM (IGAP and Schellenberg, 2012). While most of these only confer a small risk, 1.5 fold at the most (Combarros, 2014), the APOE gene has been found to be quite significant in the development of LOAD (Table 1). APOE is found on chromosome 19 and encodes Apolipoprotein E, thought to be involved in the aggregation of Amyloid-β protein in the formation of senile plaques (Namboori et al., 2011). There are four alleles of the APOE gene: ε1, ε2, ε3 and ε4, of which ε4 confers the highest risk, up to 8 fold depending on the number of alleles present (Loy et al., 2014; Namboori et al., 2011). APOE is likely to be only partially penetrant with semidominant inheritance (Combarros, 2014).

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

over the coming years that will allow us to uncover more novel variants. Finally, environmental interactions with genes are very likely to occur in a complex polygenic disease such as AD, but as of yet, any environment-gene interactions that occur are unclear.

Alzheimer’s Prediction

Disease

Risk

However, APOE ε4 risk association with AD can vary due to other factors such as age, ethnicity and gender (Devi et al., 1999). In a study conducted by Green et al. (2002), they found that the risk of Caucasian first degree relatives of AD patients developing AD by the age of 88 was 43.7%, compared to 26.9% in African-American first degree relatives

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Prediction of EOAD is relatively simple as the genes involved are highly penetrant and autosomal dominant. LOAD on the other hand is much more difficult to predict genetically due to its complex genetic nature. Most of the genes implicated in LOAD heritability have a very low risk factor (Combarros, 2014), so I will focus on risk conferred by APOE alleles. APOE risk is dependent on the genotype of the individual: ε2/ε3 genotype gives a 0.5 fold increase, ε3/ε4 a 3 fold increase, and ε4/ε4 an 8 fold increase (Loy et al., 2014). It is estimated that 20-25% of AD susceptibility is conferred by APOE (Ibrahim-Verbaas et al., 2016). It has also been shown that the presence of ε2 alleles can confer protection from AD (Sims and Williams, 2016). Family history is the most important factor in predicting an individual’s APOE genotype. In a study by Devi et al. (1999), 35% of individuals with a family history of LOAD were carriers of APOE ε4, compared to 27% of controls, and those with a family history of LOAD were more likely to be homozygous ε4/ε4.

Page

Protein and Tau, therefore increasing the protein levels (Šerý et al., 2014). However, this theory of epigenetic effect has not yet been proved to cause LOAD, as gaining evidence would require performing next generation sequencing on brain samples from affected individuals in order to determine the level of cytosine methylation on genes encoding Amyloid Precursor Protein and Tau (Šerý et al., 2014). This is obviously problematic as gaining samples would be traumatic to the patient. Non-coding RNA is already known to regulate gene expression in the brain. It is possible that non-coding RNAs also regulate pathways involved in long-term memory formation – the same pathways that are affected in AD (Šerý et al., 2014). GWAS have been crucial in the discovery of many AD susceptibility genes. However, GWAS are unable to detect associations that are not nearby a known SNP, or rare variants that have an allele frequency of less than 1% (Tosto and Reitz, 2013). It has also been suggested that APOE ε4 presence can block the detection of other loci in the same region during GWAS (IbrahimVerbaas et al., 2016). It is possible that there are undiscovered variants that cannot currently be detected by GWAS with great importance for understanding the development and heritability of AD. GWAS studies performed for other conditions using much larger sample sizes have been more successful in finding small effect genetic variants contributing to disease phenotypes (Klein et al., 2012). Next generation sequencing predicts that these undiscovered rare variants in individuals suffering from AD may have a major effect on the etiology of the disease, as next generation sequencing can be used to find further low frequency, large effect alleles (Ridge et al., 2013). As has been seen before in the field of genetics, it is likely that new technology will emerge

It is possible that polygenic risk scores may be useful in determining an individual’s risk to AD. Polygenic risk scores allows analysis of all the risk genes in an individual’s genome to calculate combined risk. Polygenic risk scores have already been successfully used in Parkinson’s disease and Schizophrenia (Escott-Price et al., 2015; Sims and Williams, 2016; Harris et al., 2014). However, Harris et al. (2014) showed that polygenic risk scores have no significant association with the development of AD.

According to Goldman (2012), there are four main issues that need to be taken into account when considering testing an individual for AD: whether the gene is causative, the clinical utility of the test, the effect the result could have on others and whether any discrimination could ensue. Each of these issues will be addressed in turn. As mentioned earlier, the three genes for EOAD are causative, and so are reliable markers for Alzheimer’s disease. However, genetic testing for LOAD is less reliable, and has sparked much debate. Out of the many genes that have been discovered to contribute towards LOAD development, APOE ε4 is the only loci that provide a high enough risk increase to be useful in predictive testing. But this risk is still relatively low, and due to the partial penetrance of the gene, even if an individual tests positive for the loci, they may never develop AD (Combarros, 2014). Similarly, testing negative does not rule out the possibility of developing

Risk and Benefits of Genetic Testing for Alzheimer’s Disease Susceptibility There are three reasons for carrying out a genetic test: diagnostic, prenatal and predictive. In the case of AD, there is no reason to carry out a diagnostic genetic test as other more reliable and less intrusive tests are available. Prenatal

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

testing is also not carried out as there would be no reason to abort the fetus. Predictive testing, on the other hand, is becoming more sought after to allow consenting individuals to know their risk of developing AD. There are many reasons why an individual may want to be tested for AD susceptibility. In a study by Gooding et al. (2006), individuals choosing to be tested for their APOE genotype reported their family history as the main reason for being tested. Also reported were financial and career worries, the possibility of new preventative measures or treatments being developed, and fear of becoming a burden on others. Whatever the reason, more and more patients are requesting genetic testing for AD susceptibility. What we must decide is whether the benefits of genotype knowledge outweigh the personal and psychological risks that come with genetic testing.

Page

of AD patients. Females were at a higher risk in both groups (Green et al., 2002). Slooter et al. (1998), showed in their study that APOE ε4 presence is associated with a younger onset of AD, and that the risk conferred by ε4 is likely to decrease with age. Tosto and Reitz (2013), reported that the ABCA7 locus has as strong as an effect as APOE ε4 in African Americans. Of course, these studies only show a correlation, and no molecular evidence is available to confirm the conclusions. With all of these outside influences, not to mention the addition of environmental influences, it is easy to see that predicting an individual’s risk of developing AD through their APOE genotype is complicated and unreliable. It is also important to keep in mind that the presence of APOE ε4 is neither sufficient nor necessary for an individual to develop AD.

Another concern when carrying out predictive testing is the possible impact on the psychology of the patient, particularly with a late-onset disease such as AD, potentially causing them to have unnecessary worry for their future.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

employers would be unlikely to discriminate against an individual positive for LOAD risk alleles, as they are not causative and it is likely to only affect the individual post-retirement. However, it is possible that employers would discriminate against an individual positive for EOAD causative genes. No cases of genetic discrimination involving AD susceptibility genes have been reported though to date. Insurance discrimination is more likely to occur than employment discrimination. Insurance discrimination is slightly less applicable in the UK, as we have free healthcare, but it is a problem in the US. Not all insurance policies will cover the cost of testing, and the insurers may make certain policies unavailable to those at risk of developing AD (Goldman, 2012). The withdrawal of insurance could be an issue for anyone planning to be tested for AD susceptibility, as many research subjects quote future care planning as a reason for being tested (Gooding et al., 2006). Zick et al. (2005) found that individuals testing positive for APOE ε4 are 5.76 times more likely to alter their life insurance and long-term care insurance to ensure they and their families are taken care of in the event of them developing AD. Potential genetic discrimination when purchasing insurance may also put individuals off taking part in important studies into the genetics of AD (Gooding et al., 2006; Zick et al., 2005). Fortunately, the British government have imposed a moratorium on the use of predictive genetic information by insurers until 2017 (HM Government and Association of British Insurers, 2011).

Page

AD. So, susceptibility genes for LOAD are not causative and testing for the presence of these genes should be treated with caution. In both EOAD and LOAD, testing is only recommended when a mutation has previously been identified in a family member (Goldman et al., 2011). Clinically, the testing for susceptibility is not particularly useful. While NICE recommends statins, hormone replacement, vitamin E supplements and anti-inflammatories for AD prevention (NICE, 2006), there are currently no significant preventive measures against AD, and current treatments are of low value (McConnell et al., 1998). It is also likely that some individuals that test positive for risk alleles will seek new, unproven preventions and treatments, without obtaining medical advice, which could have an adverse effect on their health (Goldman, 2012). The media often describe preventative measures that individuals can take, without explaining the mechanisms. In time, it is likely that effective treatments and preventative drugs will be developed. It is possible that genotype determination could help in deciding an individual’s optimum drug dosage and predict their level of reaction to a treatment (Šerý et al., 2014). Any genetic test does not just affect the individual undergoing the test, but also their family. If a mutation is found in an individual making them at a higher risk of developing Alzheimer’s disease, there is a 50% chance that the same mutation will also exist in their parents, siblings and children. It is important to involve family in the testing process, and further genetic counselling should be offered to family members of the individual being tested who could also be carriers of the mutation. Genetic discrimination can come in the form of employment discrimination and insurance discrimination. In the case of LOAD,

reduce the potential psychological harms of genetic testing. Obtaining informed consent can be difficult if a patient is already experiencing decreased cognitive activity, as they may not fully understand what the test involves and what effect the results may have, so it would be advised against testing these individuals (AGS Ethics Committee, 2001). Understanding can be greatly improved by proper genetic counselling before, during and after the test (Romero et al., 2005). Guidelines on how susceptibility testing for AD could be implemented should be based around the already successful Huntington’s Disease model (Goldman et al., 2011). A full family history for at least three generations should be taken from the individual seeking testing to check the likelihood of the AD being familial, and a mutation should have already been confirmed in an affected family member (Roberts and Uhlmann, 2013). The Huntington’s Disease Society of America (2003) recommends that the testing process involves neurological evaluation, genetic counselling, psychological assessment, a review of the potential impact on the individual, and that testing happens at a stable time in the individual’s life, with a companion to support them through the process.

As we have seen, the only genes that are viable for susceptibility testing are APP, PSEN1 and PSEN2 for EOAD, and AOPE ε4 for LOAD. While many other susceptibility loci have been found, their risk factors are far too negligible to be used as reliable prediction markers. The EOAD genes have high reliability as markers, as they are highly penetrant and autosomal dominant genes, so it is highly likely that a patient presenting with these genes will develop EOAD. The issues here are more with AOPE testing,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Conclusion

Page

This effect has been seen in patients with a confirmed presence of the gene for Huntington’s Disease. Approximately 1% of those testing positive for Huntington’s worldwide have suffered from severe psychological damage, and patients are reported to become increasingly distressed 7-10 years after the genetic test (Roberts and Uhlmann, 2013). In a study conducted by Gooding et al. (2006), individuals that tested positive for APOE ε4 reported feelings of relief after the test, but some also reported higher concern, and some described the result as “depressing”. Romero et al. (2005) reported similar results in their study, with the majority of subjects tested reported feeling less “depressed” after being given the results. However, over the 10 month follow up period, only a few subjects reported becoming increasingly worried (Romero et al., 2005). The majority of subjects were glad that they had been tested. One worry in susceptibility testing is that the results will be misinterpreted or not fully understood (Roberts and Uhlmann, 2013). Understanding of the mechanisms of genetics varies among the population; many older adults went to school before genetics became part of high school curriculum (AGS Ethics Committee, 2001). The media also portrays genetic tests as infallible, and direct-to-consumer genomics companies promise to conclusively determine disease risk, leaving people with a misunderstanding of the limitations of genetic tests when they begin to seek susceptibility testing (Kurt et al., 2011). Kurt et al. (2011) describes that individuals being tested for APOE ε4 view the test as a positive experience, but their concerns increase through the testing process, showing that their understanding of genetic testing prior to the test was limited. Understanding of and informed consent to the testing process are crucial to

In conclusion, at this current time genetic testing for susceptibility to Alzheimer’s disease should only be carried out clinically when the physician suspects EOAD from a strong positive family history of at least three generations, and when a mutation has already been detected in an affected family member. While there is no treatment or prevention, it seems unethical to perform a test for such a lifedestroying disease without being able to provide any further help after the results, except for life planning and counselling. Research into APOE ε4 testing and its reliability should continue to try and find a better way of predicting LOAD development from APOE genotype, if one exists. Hopefully, future technologies and discoveries will allow us to reliably test for AD susceptibility with a more definite result, and to be able to provide prevention and treatment therapies.

Bibliography AGS Ethics Committee. (2001). Genetic testing for late-onset Alzheimer's disease. Journal of the American Geriatrics Society, 49(2), 225. Allen, N., Robinson, A. C., Snowden, J., Davidson, Y. S. & Mann, D. M. A. (2014). Patterns of cerebral amyloid angiopathy define histopathological phenotypes in Alzheimer's disease. Neuropathology and Applied Neurobiology, 40(2), 136-148.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

It may be time for researchers to focus on preventions and treatments for the future rather than in finding further loci. It may also be interesting to look further into the concept of using genotype as a basis for personalised medicine in familial AD. We have seen that at this current time, GWAS has reached its peak

in AD research, and is therefore unlikely to find any more causative or risk genes that would be important for testing. In the future, new technologies and more powerful sequencing equipment will likely be developed that may uncover previously hidden causative and risk genes, and tell us more about the possible epigenetic and non-coding RNA interactions that may contribute to the development of AD. But until then, I think that we have saturated the amount of loci that we will find.

Page

as it confers such a relatively small risk of developing LOAD that it is debatable whether or not genetic testing for APOE ε4 holds much value – even if the test result is negative, the individual may still develop LOAD, and if it is positive, they still may never develop LOAD. This means that an individual could be put through the stress and worry of genetic testing, only to get a result that is relatively unreliable; this hardly seems fair on the patient. Admittedly, the media and direct-to-consumer genomics companies have had a role to play in procuring this stress by proclaiming the infallibility of genetic testing and the link between AD and genotype. It is therefore important to manage the expectations of patients throughout the process, and ensure that their psychological health is taken care of by a genetic counsellor. Individuals should only be tested clinically if they have a strong positive family history of AD (first degree relatives) and if a mutation has already been identified in an affected relative. However, other individuals that don’t meet these criteria but still want to be tested could be useful in research studies into AD genetics. Physicians that encounter such patients should encourage them to take part in trials to identify novel variants and new families carrying AD variants, as well as possible prevention therapies. Again, within a research environment, a high standard of patient care should be ensured, and the involvement of genetic counsellors at every stage of the research, and after the research has finished, is essential.

Alzheimer’s Society. (2014). Factsheet: What is Alzheimer's Disease [Online]. https://www.alzheimers.org.uk/site/scripts/d ownload_info.php?fileID=2415. [Accessed 12/02/2016].

B. (2006). Genetic susceptibility testing for Alzheimer disease: Motivation to obtain information and control as precursors to coping with increased risk. Patient Education and Counseling, 64(1), 259-267.

Braak, H. and Tredici, K. D. (2015). Neuroanatomy and pathology of sporadic Alzheimer's Disease: Springer, Cham, Switzerland. 162pp.

Green, R., Cupples, L., Benke, K., Edeki, T., Griffith, P., Williams, M., Hipps, Y., GraffRadford, N., Bachman, D. & Farrer, L. (2002). Risk of Dementia Among White and African American Relatives of Patients With Alzheimer Disease. Journal of the American Medical Association, 287(3), 329-336.

Devi, R., Ottman, R., Tang, R., Marder, R., Stern, R., Mayeux, R. & Tycko, R. (1999). Influence of APOE genotype on familial aggregation of AD in an urban population. Neurology, 53(4), 789-794. Escott-Price, V., Sims, R., Bannister, C., Harold, D., Vronskaya, M., Majounie, E., Badarinarayan, N., Morgan, K., Passmore, P., Holmes, C., Powell, J., Brayne, C., Gill, M., Mead, S., Goate, A., Cruchaga, C., Lambert, J.-C., van Duijn, C., Maier, W., Ramirez, A., Holmans, P., Jones, L., Hardy, J., Seshadri, S., Schellenberg, G. D., Amouyel, P. & Williams, J. (2015). Common polygenic variation enhances risk prediction for Alzheimer’s disease. Brain: A Journal of Neurology, 138(12), 3673-3684. Goldman, J. (2012). New Approaches to Genetic Counseling and Testing for Alzheimer’s Disease and Frontotemporal Degeneration. Curr Neurol Neurosci Rep, 12(5), 502-510. Goldman, J. S., Hahn, S. E., Williamson, J. C., Larusse-Eckert, S., Barber, M. B., Rumbaugh, M., Strecker, M. N., Roberts, J. S., Wylie, B., Richard, M. & Thomas, B. (2011). Genetic counseling and testing for Alzheimer disease: Joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors. Genetics in Medicine, 13(6), 597605. Gooding, H. C., Linnenbringer, E. L., Burack, J., Roberts, J. S., Green, R. C. & Biesecker, B.

HM Government and Association of British Insurers (2011). Concordat and Moratorium on Genetics and Insurance. [Online] https://www.gov.uk/government/uploads/syst em/uploads/attachment_data/file/216821/Co ncordat-and-Moratorium-on-Genetics-andInsurance-20111.pdf. [Accessed 20/02/2016]. Huntington’s Disease Society of America. (2003). Genetic Testing for Huntington's Disease: Its Relevance and Implications. [Online]. http://hdsa.org/wpcontent/uploads/2015/03/GeneticTesting-forHD.pdf [Accessed 14/02/2016] Ibrahim-Verbaas, C. A., Vronskaya, M., Lambert, J. C., Chung, J., Jun, G., Naj, A. C., Kunkle, B. W., Wang, L. S., Bis, J. C., Bellenguez, C., Harold, D., Lunetta, K. L., Destefano, A. L., Grenier-Boley, B., Sims, R., Beecham, G. W. & Smith, A. V. (2016). A novel Alzheimer disease locus located near the gene encoding tau protein. Molecular Psychiatry, 21(1), 108-117. IGAP & Schellenberg, G. D. (2012). International Genomics of Alzheimer's Disease Project (IGAP) genome-wide association study. Alzheimer’s and Dementia, 8(4), P101.

Klein, C., Lohmann, K. & Ziegler, A. (2012) The promise and limitations of genome-wide association studies. Journal of the American Medical Association, 308(18), 1867-1868.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Combarros, O. (2014). Genetic risk factors for Alzheimer's disease. In: Neurodegenerative Diseases: Clinical Aspects, Molecular Genetics and Biomarkers. Eds. Galimberti, D. & Scarpini, E. pp. 49-64. Springer, London.

Harris, S. E., Davies, G., Luciano, M., Payton, A., Fox, H. C., Haggarty, P., Ollier, W., Horan, M., Porteous, D. J., Starr, J. M., Whalley, L. J., Pendleton, N. & Deary, I. J. (2014). Polygenic risk for Alzheimer's disease is not associated with cognitive ability or cognitive aging in non-demented older people. Journal of Alzheimer’s Disease, 39(3), 565-574.

Page

Bruni, C. A., Conidi, E. M. & Bernardi, E. L. (2014). Genetics in Degenerative Dementia: Current Status and Applicability. Alzheimer Disease & Associated Disorders, 28(3), 199205.

Kurt, D. C., Roberts, J. S., Wendy, R. U. & Robert, C. G. (2011). Changes to perceptions of the pros and cons of genetic susceptibility testing after APOE genotyping for Alzheimer disease risk. Genetics in Medicine, 13(5), 409. Loy, C. T., Schofield, P. R., Turner, A. M. & Kwok, J. B. J. (2014). Genetics of dementia. The Lancet, 383(9919), 828-840. McConnell, L. M., Koenig, B. A., Greely, H. T. & Raffin, T. A. (1998). Genetic testing and Alzheimer disease: has the time come? Nature medicine, 4(7), 757-759. Namboori, P., Vineeth, K., Rohith, V., Hassan, I., Sekhar, L., Sekhar, A. & Nidheesh, M. (2011). The ApoE gene of Alzheimer's disease (AD). Funct Integr Genomics, 11(4), 519-522. NICE. (2006). NICE Pathway for Dementia [Online]. www.nice.org.uk/guidance/cg42/chapter/1Guidance#risk-factors-prevention-and-earlyidentification. [Accessed 31/01/2016]. Ridge, P. G., Mukherjee, S., Crane, P. K. & Kauwe, J. S. K. (2013). Alzheimer's disease: analyzing the missing heritability. PloS one, 8(11), e79771. Roberts, J. S. & Uhlmann, Genetic susceptibility neurodegenerative diseases: practice issues. Progress in 110, 89-101.

W. R. (2013). testing for Ethical and Neurobiology,

Romero, L., Garry, P., Schuyler, M., Bennahum, D., Qualls, C., Ballinger, L., Kelly, V., Schmitt, C., Skipper, B., Ortiz, I. & Rhyne, R. (2005). Emotional Responses to APO E Genotype Disclosure for Alzheimer’s Disease. J Genet Counsel, 14(2), 141-150.

Sims, R. & Williams, J. (2016). Defining the Genetic Architecture of Alzheimer's Disease: Where Next. Neurodegenerative Disease, 16(1-2), 6-11. Slooter, A. J., Cruts, M., Kalmijn, S., Hofman, A., Breteler, M. M., Van Broeckhoven, C. & van Duijn, C. M. (1998). Risk estimates of dementia by apolipoprotein E genotypes from a population-based incidence study: the Rotterdam Study. Archives of neurology, 55(7), 964-968. Stelzmann, R. A., Norman Schnitzlein, H. & Reed Murtagh, F. (1995). An English translation of Alzheimer's 1907 paper, “über eine eigenartige erkankung der hirnrinde”. Clinical Anatomy, 8(6), 429-431. Thinakaran, G. & Koo, E. H. (2007). APP biology, processing and function. In Alzheimer’s Disease Advances in Genetics, Molecular and Cellular Biology. Eds. Sisodia, S. S. and Tanzi, R. E.. pp. 17-34. Springer US, Boston. Tosto, G. & Reitz, C. (2013). Genome- wide Association Studies in Alzheimer’s Disease: A Review. Curr Neurol Neurosci Rep, 13(10), 17. Wakabayashi, T., Iwatsubo, T. and De Strooper, B. (2007). The biology of the Presenilin complexes. In Alzheimer’s Disease Advances in Genetics, Molecular and Cellular Biology. Eds. Sisodia, S. S. and Tanzi, R. E. pp. 17-34. Springer US, Boston. Zick, C., Mathews, C., Roberts, J. & CookDeegan, R. (2005). Genetic Testing For Alzheimer's Disease And Its Impact On Insurance Purchasing Behavior. Health Affairs, 24(2), 483-90.

Page

Šerý, O., Povová, J. & Balcar, V. J. (2014). Perspectives in genetic prediction of

Alzheimer's disease. Neuro endocrinology letters, 35(5), 359-366.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Healthy people with lethal mutations. What are the implications? Isla Black (isla.black@student.manchester.ac.uk) Faculty of Biology, Medicine and Health, The University of Manchester, U.K.

treatments

for

these

Introduction The study of genetic variation amongst humans has led to a deepening knowledge of the genetic contribution to disease. This is a very active area of research because once the interaction between the human genome and disease is fully understood, there is potential for huge improvements to human health, both in identifying causation, planning health and lifestyle choices based on genetic susceptibilities and in treatments of disease. As sequencing methods and technologies improved, work was completed on one of the first diseaseassociated genes discovered in 1983. This was the Huntingtin (HTT) gene and it was mapped onto human chromosome 4 (Gusella et al., 1983). To identify the nature of the mutation, the Huntington’s Disease Research Group worked to build a set of DNA probes corresponding to the specific region of the chromosome that they believed HTT was found (MacDonald et al., 1993). Sequencing of candidate genes using Sanger’s method (Sanger et al., 1977) led to identification of the specific trinucleotide repeat mutation that causes Huntington’s disease (MacDonald et al., 1993). Research projects such as the Human Genome Project worked to further understand the genomic basis of human disease (Green et al., 2011). Through projects such as these, more variations in

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Several studies analysing aggregations of human genome sequences have detected a small number of individuals carrying genetic variants classified as pathogenic and possibly lethal, yet the subjects are clinically healthy. With a focus on severe childhood Mendelian disorders, screening of thousands of genomes has detected specific mutations in people that have not manifested the associated disease phenotype. Cystic fibrosis and Smith-Lemli-Opitz syndrome are examples of the severe Mendelian childhood disease mutations that have been found in healthy individuals. Misclassification of gene variants in the past may be the cause of this. However, the links between genetic mutations and disease penetrance are not yet fully understood, for example the effects of epigenetic modifications. Therefore, this could also contribute to this unexplained phenomenon. Additionally, these individuals may be termed as “resilient” as it is possible they carry a genetic factor that acts as a protective mechanism against phenotypic manifestation of the disease. The implications of these findings may challenge the reliability of genetic testing including pre-implantation, pre-natal and predictive testing. However, identification of any protective genetic mechanism may result in novel drug targets and the development of

therapeutic disorders.

Page

Abstract

the Exome Aggregation Consortium (The Exome Aggregation Consortium, 2017.). Analysis of these data sets is hoped to lead to increased knowledge of interactions between the human genome and disease, particularly Mendelian, and eventually improve treatment options. However, the studies produced some interesting findings. It has been found there are people that carry what are thought to be pathogenic or lethal mutations yet they are clinically apparently healthy. The discovery of these individuals may lead to several implications in the human genetics, mainly in the fields of genetic testing and therapeutic development.

The public availability of genomic data is limited and several projects have worked to assemble an extensive collection of complete genome sequences for analysis and to aid in understanding variation between genomic sequences. The Exome Aggregation Consortium (ExAC) is a database of sequence data from over 60,000 people and was the most extensive collections ever collated at the time of its release (The Exome Aggregation Consortium, 2017). The exome data from ExAC was found to have a high proportion of data of European origin as well as several individuals from disease cohorts, therefore these are factors the researchers had to consider. The analysis of this large data set resulted in an informative catalogue of genetic variation in protein-coding regions (Lek et al., 2016). The team analysed 192 variants in alleles previously reported as pathogenic, and which had an allele frequency of over 1%, as this is deemed to be a higher than expected frequency for pathogenic variants. 183 were found to have insufficient supporting evidence for

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The discovery of healthy individuals carrying pathogenic mutations

Page

the genome have been identified and linked to phenotypic manifestations of human disease (Frazer et al., 2009). Mendelian disease has been a primary study focus to pinpoint gene variants behind phenotypes of severe or fatal disease (Chong et al., 2015). Approximately half of all known Mendelian disorders have one or more genetic variants associated with them which were mainly identified through methods such as linkage mapping followed by sequencing of candidate genes (Bamshad et al., 2011). However, it has been difficult to develop treatment options for many Mendelian disorders. Huntingtonâ&#x20AC;&#x2122;s disease currently has no available treatments to cure or slow disease progression, only symptomatic treatments are available (Lawrence, 2009). However, many research projects are working to progress in this area (Wild, 2016). The recent availability of rapid DNA sequencing technologies at a lower cost has allowed thousands of human exomes as well as whole genomes to be sequenced and analysed (Bamshad et al., 2011). Next-generation sequencing methods with extremely highthroughput, faster rates, and lower cost have enabled exome and whole-genome sequencing to become an everyday research tool (Hert et al., 2008). The development of consumer services such as 23andMe make genetic testing and genome sequencing more accessible than ever (23andMe UK, 2017). This accessibility has led to accumulation of extensive human sequence data, which is hugely informative for research into the genetic basis of human disease. Yet the various databases have been difficult to access in the past. The creation of various new projects that have worked to aggregate as much exome and genome sequencing information as possible are beginning to solve this issue, for example

This suggests that these mutations may not be pathogenic as previously thought, but may have varying effects or have no effect at all on the subject’s health. Several subsequent studies have reassessed previously recorded pathogenic gene variants. Once again, by using ExAC to compare sequencing data of over 7,000 cases of cardiomyopathy, it was found that 11.7% of individuals in the ExAC database presented hypertrophic cardiomyopathy variants which is higher than the recorded population incidence of 6.5%. The study suggests that previously reported gene variants of cardiomyopathy cases are not accurately clinically informative (Walsh et al., 2017). To address some of the challenges of ExAC, the recently released project the Genome Aggregation Database (gnomAD) has gathered a

Data classification interpretation

and

The way in which human genetic variation has been studied has changed and evolved due to huge advances in technology and the development of enhanced software. Since the first known sequencing determination of an Escherichia coli transfer RNA molecule in 1965 (Holley et al., 1965) using extremely slow and labour intensive experimental methods, to Sanger’s ‘dideoxy’ method (Sanger et al., 1977) and

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Figure 1. A graph showing the reassessment of variants with an allele frequency of over 1% globally. 192 variants were analysed and 163 of them were reclassified as not pathogenic by the American College of Medical Genetics in December 2015. The chart shows the proportions of variants that were reclassified due to insufficient evidence for pathogenicity or due to original classification error. The number of variants that were not reclassified but stayed as benign or disease associated are also shown (Lek et al., 2016).

greater set of both exome and full genome sequences from a more diverse population set (The Genome Aggregation Database, 2017). Another large study carried out screening and extensive analysis of over 500,000 genomes (Chen et al., 2016). The genes studied were restricted to those containing mutations categorised as fully penetrant only for a set of childhood Mendelian diseases. After screening panels to select individuals, the team identified 13 people carrying either homozygous for recessive disorders or heterozygous for dominant mutations for a childhood Mendelian disease, yet the subjects displayed no clinical disease phenotype (Chen et al., 2016). For example, two of the individuals were found to carry a homozygous mutation associated with Smith-Lemli-Opitz syndrome (SLOS) in the gene 7-dehydrocholesterol reductase (DHCR7). Homozygosity is rarely seen in SLOS, and in the few cases where it has been identified, individuals died shortly after birth and therefore manifested an extremely severe disease phenotype (Jira et al., 2001). These findings suggest that some individuals can survive with these expectedly lethal mutations and that seeking to detect these “resilient” individuals may initiate a way of studying Mendelian disease (Chen et al., 2016).

Page

pathogenicity and 163 of these were subsequently reclassified as benign by the American College of Medical Genetics (Richards et al., 2015). Figure 1 illustrates the results of the reassessment of the variants.

These studies also address the complexities behind genetic variation and disease. It is a possibility that these seemingly healthy individuals do carry the disease-causing mutation, yet there are other factors impacting the presentation of the disease. Penetrance is defined as the proportion of individuals that carry a pathogenic mutation who will display phenotypic symptoms of the associated disease (Cooper et al., 2013). For example, Huntington’s disease expresses varying degrees of penetrance depending on the number of trinucleotide repeats in the Huntingtin (HTT) gene. Individuals with between 36 and 39 repeats will display a reduced

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Causes of reduced penetrance in human disease

penetrance. Here, the onset of disease is usually late in life and the symptoms progress slowly. Individuals with over 40 trinucleotide repeats however will express full penetrance of Huntington’s and disease can occur at a young age with more rapid progression (Walker, 2007). Much is still unknown about the penetrance of human disease and there are thought to be countless factors that contribute to levels of penetrance. Therefore, it is important to consider that reduced penetrance may be the reason that these seemingly healthy individuals are carrying lethal mutations yet have extremely minor or undetectable phenotypic symptoms. Diseases that are genetically heterogeneous can display different levels of penetrance depending on the mutation that is present in the genome. An example of this can be seen in cystic fibrosis (CF). The phenylalanine deletion in the CFTR gene is the most common mutation detected in CF sufferers (Moskowitz et al., 2008), whereas a mutation found in the 3 seemingly healthy individuals in ‘The Resilience Project’ mentioned earlier (Chen et al., 2016) is a substitution of valine to phenylalanine in CFTR and may exhibit a reduced penetrance in carriers, therefore resulting in no clinical diagnosis of CF. Reduced penetrance of different mutations may be due to the location in the gene where the mutation arises. Partial penetrance has previously been shown in carriers of a splicing variant in intron 8 of the CFTR gene (Rave-Harel et al., 1997). The efficiency of the splicing mechanisms is thought to be impacted here resulting in a reduced clinical expression of CF. There may also be effects of modifier genes on penetrance of the disease. Expression of a genetic modifier can alter the expression of another gene (Nadeau, 2001). In the case of CF, many studies have focused on identification of a modifier gene to

Page

modern next generation sequencing methods in use today, genetic testing has dramatically changed. During this time, genetic variations have been detected and associated with certain disease phenotypes and subsequently extensive databases of this information have been developed and stored (Hutchison, 2007). Due to this shift in methods and the increased power of data analysis in human genetics, the interpretation of information and previous practice in human disease genetics is being challenged (Richards et al., 2015). As previously mentioned, the study by Lek et al. resulted in many previously thought to be pathogenic genetic variants being reclassified as benign (Figure 1) (Lek et al., 2016). The classification and interpretation of genetic variants is of great importance for clinical diagnostics and future research (Wang and Shen, 2014). Therefore, it is important to consider that classification of mutations associated with genetic diseases may not be fully reliable and further work may help to review the classification and pathogenicity of many of these.

The ExAC database was used by a study focusing on mutations in the NOTCH3 gene and the association with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). The frequency of a specific mutation due to the loss of a cysteine in an epidermal growth factor-like domain in the ExAC database was found to be much greater than the incidence of CADASIL in the global population (Rutten et al., 2016) The team suggested the explanation for this difference may be down to reduced penetrance in different population groups or that the late-onset form of CADASIL may be presenting which is

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Studies on reduced penetrance in human disease

more difficult to diagnose (Chabriat et al., 2009). Another study focused on mutations in the prion protein gene (PRNP), which are associated with several neurodegenerative conditions known as prion diseases. Using largescale data from ExAC and over 16,000 cases of prion disease, a research group looked into quantifying the penetrance levels of prion disease (Minikel et al., 2016). The results showed that when using the general population prevalence of prion disease, a maximum of 1.7 people in the ExAC data set would be expected to carry pathogenic variants in PRNP. However, variants for prion disease were found at a much higher rate as 52 individuals from ExAC carried a variant (Minikel et al., 2016). This suggests that penetrance of prion diseases is lower than previously thought. Additionally, the team accessed a collection of previously reported pathogenic alleles. Previous work on the variants was considered in assessment, including segregation of the variant in families and the variant causing spontaneous prion disease manifestation in mice. Four of the variants that had the most evidence for pathogenicity in the past (P102L, A117V, D178N and E200K) were not found at all in the ExAC aggregation but were found at a low frequency in another cohort used in the study. This low frequency was found to agree with the known prevalence of prion disease in the general population suggesting correct pathogenicity classification of the variants (Figure 2). Several variants were suggested as having reduced penetrance (V180I, V210I and M232R), as they presented allele frequencies in ExAC that were too high to be a fully penetrant disease variant, yet too low to agree with the population prevalence of prion disease (Figure 2). Some variants were thought to likely be benign (R208H, E196A) due to extremely high

Page

explain the disease variability seen between patients yet a definitive factor is yet to be found (Cutting, 2005). Another factor to be considered is the role of epigenetics in human disease. Epigenetic modifications include heritable changes that do not affect the primary DNA sequence. Post-translational modifications to histones and DNA methylation are examples, in addition to possible environmental and other factors (Wolffe and Matzke, 1999). Epigenetic modifications are thought to play an important role particularly in cardiac disorder penetrance, including in hypertrophic cardiomyopathy. The roles of long non-coding RNAs in epigenetic modification of cardiac disease are diverse and complex. For example, the modulation of transcription through interaction with chromatin-associated factors (Greco and Condorelli, 2015). There is a hugely complex interaction between epigenetic modifications such as these and gene expression, and much more work is required to understand the link between epigenetics and disease penetrance.

The implications of genetic testing in family planning Pre-implantation genetic diagnosis (PGD) involves the in-vitro testing of either oocytes or embryos that are created for use in assisted reproductive treatments. Most commonly, single blastomere cells are biopsied from the embryo and are then amplified using polymerase chain reaction (PCR) (Traeger-Synodinos, 2017). To diagnose monogenic diseases, linkage based testing is used whereby a set of markers are produced from a parental SNP microarray. The genotype of the known reference disease sequence is used to compare with the embryonic data to reach a diagnosis (Natesan et al., 2014). PGD is used to identify many single gene defects, including mutations associated

with cystic fibrosis and Huntingtonâ&#x20AC;&#x2122;s disease and the purpose is to evaluate the likelihood of whether implanted oocytes or embryos will result in a successful pregnancy and a healthy child. PGD was used to screen for cystic fibrosis for the first time in 1992 and resulted in a successful pregnancy and healthy child (Handyside et al., 1992). The number of PGD treatment cycles in the UK in 2013 was 578 according to the Human Fertilisation and Embryology Authority (Human Fertilisation and Embryology Authority, 2017). The implications of finding healthy individuals that appear to be carrying apparent disease-causing variants challenges the reliability of PGD results. It may be possible that detection of specific disease mutations in embryos undergoing PGD has resulted in the rejection and destruction of embryos that may actually have developed to be phenotypically healthy and show no sign of the disease. From this, undergoing expensive and sometimes risky IVF treatment to ensure healthy offspring from parents with a high risk of carrying disease mutations may be futile. This is because any offspring may never suffer from the disease even if they are carrying the mutation as previously assumed to be pathogenic. Additionally, carrier couples may make the decision not to have

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Page

frequencies detected in ExAC, and a low number of cases reported to prion surveillance centres (Figure 2) (Minikel et al., 2016). This may be due to past misclassification of pathogenic variants. That is an example of the benefits of using large-scale sequencing data as research into both misclassification and penetrance and the importance of varying penetrance in management of human disease.

Figure 2. A scatter graph showing the frequency of each variant in the ExAC collection and the number of cases reported to prion surveillance centres carrying that variant. The variants with segregation in families and causing spontaneous disease in mice are also shown (red triangles) (P102L, A117V, D178N and E200K). Taken from Minikel et al (2016).

children due to the chance of having a child carrying the disease. Pre-natal diagnosis (PND) is carried out on the foetus in the uterus in contrast to PGD. Pre-natal diagnosis can involve both invasive and non-invasive techniques for testing. Invasive tests involve sampling the amniotic fluid or placental tissue using aspiration needles. There is a small risk of damage to the foetus from invasive tests such as these that must be considered by patients before undergoing the procedure (Bauland et al., 2012). Non-invasive techniques include maternal blood tests to detect placental DNA (Han and Ryu, 2011). The implications of pre-natal genetic diagnosis are similar to PGD except that the pregnancy has progressed. Foetuses positively diagnosed as carrying a pathogenic mutation may be terminated assuming, perhaps incorrectly, that the offspring would suffer from the disease. As discussed, even if the foetus is found to carry a mutation, it may not go on to show full expression of the disorder. This questions the basis of prenatal genetic testing, or at least the sensitivity of these tests, and therefore introduces complex ethical challenges associated with these tests and their outcomes.

clinically accurate (Walsh et al., 2017). Predictive testing for cardiomyopathy is carried out on many young people thought to be at risk of developing the disease and a variety of preventative treatments are recommended for those given a positive diagnosis (Christiaans et al., 2008). Implantable CardioverterDefibrillators (ICDs) have been promoted as a preventative treatment for sudden death in those diagnosed with hypertrophic cardiomyopathy (Maron et al., 2007), and usually the presence of hypertrophic cardiomyopathy would be diagnosed clinically before this procedure was undertaken. However, due to the uncertainty of the variants associated with hypertrophic cardiomyopathy, there may be patients incorrectly diagnosed with the genetic predisposition to the disease who are then more likely to be treated with preventative options such as ICDs. Additionally, there are concerns around the psychological effects of positive diagnosis in predictive genetic tests on young people, and doubts around the accuracy of these tests suggests further moral and ethical implications (MacLeod et al., 2014).

The implications on predictive genetic testing and preventative treatments

The implications therapeutic development

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The Resilience Project suggests that it may be possible to study these healthy individuals with lethal mutations to develop new treatments or even cures for the childhood diseases that were studied (Chen et al., 2016). The main issue with the study was that confidentiality agreements were in place with the initial research subjects; the researchers were not allowed to re-contact the subjects, therefore further studies could not be carried out with these individuals (Chen et al., 2016). However, researchers were prompted into finding more of these resilient individuals to increase knowledge of disease. Currently,

Page

Due to the rapid advances in recent years, genomics has impacted medical practice in many ways, including in preventative treatment of disease (Bloss et al., 2011). Mendelian diseases such as Huntingtonâ&#x20AC;&#x2122;s are frequently diagnosed using predictive genetic testing in early life for individuals with a family history of the disorder (Baig et al., 2016). As previously mentioned, hypertrophic cardiomyopathy associated mutations were detected at a much higher prevalence in ExAC analysis than in the expected population suggesting the reported gene variants may not be

The aggregation and analysis of large human exome and genome sequencing data sets in these various studies has been extremely informative. The driving force behind research into population genome studies is to wholly understand the complex interactions between the

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Discussion

human genome and the presentation of disease, and these studies display just how much new information can be elucidated and investigated further (Bloss et al., 2011). The discovery of individuals harbouring specific mutations previously associated with several diseases, with a focus on childhood Mendelian disease, is one of the main findings from multiple genome aggregation studies, and it has been surprising for the human genetics field. There are several possible explanations for how these individuals are alive and seemingly healthy. Misclassification of genetic variants in previous studies may be a factor. Work by Lek et al. in 2016 resulted in reclassification of 163 gene variants from ‘pathogenic’ to ‘benign’. This work was down to the analysis of protein-coding regions of over 60,000 humans from ExAC (Lek et al., 2016) (The Exome Aggregation Consortium, 2017). Reduced or incomplete penetrance of disease is important. Recent work on prion disease, once again using large population data sets, suggested that penetrance is much lower than it was previously believed to be (Minikel et al., 2016). Reduced penetrance is complex and can be down to different mutation types, modifier genes or epigenetics (Shawky, 2014). Much more research is required to fully understand penetrance and the use of extensive genomic sequence data sets to study penetrance levels is a key way forward. Late onset of genetic disease is another element to be considered, for example the recent studies on CADASIL (Rutten et al., 2016). It is also a possibility that these individuals not only harbour the pathogenic mutation, but also carry another genetic factor that causes them to be “resilient”. This is a reasonably novel area of research and work by Chen et al. analysing over 500,000 human genomes could detect a group of 13

Page

research is being undertaken on an elderly man found to carry a mutation in a presenilin gene thought to be the main variant behind familial Alzheimer’s disease yet he does not suffer from Alzheimer’s. From this, Washington University set up a study to enrol and analyse volunteers to find more subjects who have not developed Alzheimer’s but carry the mutation. (Dominantly Inherited Alzheimer Network, 2017). This is hoped to give some insight into preventative treatments for those genetically destined to develop Alzheimer’s by studying those who are resilient. An example of using a protective genetic mechanism for developing therapeutics is the C-C chemokine receptor type 5 (CCR5) receptor in HIV protection. A small number of individuals were found to carry a rare mutation in the gene coding for the CCR5 receptor resulting in a 32 base pair deletion (Huang et al., 1996). This mutation altered the tertiary structure of the receptor and HIV is unable to enter and subsequently infect the cell. From this, CCR5 antagonists have been developed to specifically target and block the CCR5 receptor to prevent HIV from entering cells. CCR5 antagonists are used today as a treatment option to slow down the progression of HIV in affected patients (Cg, 2004). Therefore, further research into the molecular mechanisms of possible protective factors in Mendelian disease could result in the development of novel therapeutics for treatment.

genetic variants and associations with disease and it is rapidly growing (ClinVar, 2017). Using the sequences of unaffected individuals rather than just those affected is essential. The “All of Us Research Program’ is aiming to sequence and analyse the genomes of over one million volunteers in the US with a focus on developing precision medicine and preventative treatments (All of Us Research Program, 2017). Use of these extensive databases will be imperative in further understanding penetrance, resilience and the full extent of the interactions between human disease and the genome.

Bibliography 23andMe UK - DNA Genetic Testing & Analysis, (2017). [online] Available at:https://www.23andme.com/en-gb/ [accessed 22.03.17] All of Us Research Program - Nationlal Institute of Health, (2017) [online] Available at: https://www.nih.gov/researchtraining/allofus-research-program [accessed 22.03.17]. Baig, S.S., Strong, M., Rosser, E., Taverner, N.V., Glew, R., Miedzybrodzka, Z., Clarke, A., Craufurd, D., UK Huntington’s Disease Prediction Consortium, Quarrell, O.W. (2016). 22 Years of predictive testing for Huntington’s disease: the experience of the UK Huntington’s Prediction Consortium. European Journal of Human Genetics 24, 1396–1402.

Bauland, C.G., Smit, J.M., Scheffers, S.M., Bartels, R.H., van den Berg, P., Zeebregts, C.J., Spauwen, P.H. (2012). Similar risk for hemangiomas after amniocentesis and transabdominal chorionic villus sampling. Journal of Obstetrics & Gynaecolgy Research 38, 371–375.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Bamshad, M.J., Ng, S.B., Bigham, A.W., Tabor, H.K., Emond, M.J., Nickerson, D.A., Shendure, J. (2011). Exome sequencing as a tool for Mendelian disease gene discovery. Nature Reviews Genetics 12, 745–755.

Page

individuals that were seemingly resilient to various severe childhood Mendelian diseases (Chen et al., 2016). A new project is currently being run to collect volunteers to attempt to find more resilient individuals (The Resilience Project, 2017.). The future hopes of The Resilience Project are to study these people to develop new ways of disease prevention and treatment. The implications that come from the discovery of these individuals are farreaching. The reliability of genetic testing procedures, including preimplantation, prenatal and predictive, are challenged and there are potential ethical considerations. In the future, due to availability of commercial genome sequencing and genetic analysis services, the implications of these findings may be ever more apparent. Services such as 23andme pose difficulties by informing people of possible genetic risk factors and inherited conditions potentially without full medical and genetic advice when much more is still to be understood about the human genome and disease risk (23andMe UK, 2017).However, the future possibilities that have become available particularly for disease treatment options are exciting. Studies have already begun based on the detection of resilient individuals with the hope of new treatments, for example for Alzheimer’s disease (Dominantly Inherited Alzheimer Network, 2017). Finally, this review shows that data sharing in human genetics, particularly of human exome and genome sequences is greatly informative. The gnomAD browser is the improved genome database with a much greater diversity of data in terms of population and ancestry (Genome Aggregation Database, 2017). Resources such as this are extremely powerful in facilitating genomic research studies. ClinVar, for example, is a free online database providing recorded

Chabriat, H., Joutel, A., Dichgans, M., Tournier-Lasserve, E., Bousser, M.-G. (2009). CADASIL. The Lancet Neurology 8, 643–653. Chen, R., Shi, L., Hakenberg, J., Naughton, B., Sklar, P., Zhang, J., Zhou, H., Tian, L., Prakash, O., Lemire, M., Sleiman, P., Cheng, W., Chen, W., Shah, H., Shen, Y., Fromer, M., Omberg, L., Deardorff, M.A., Zackai, E., Bobe, J.R., Levin, E., Hudson, T.J., Groop, L., Wang, J., Hakonarson, H., Wojcicki, A., Diaz, G.A., Edelmann, L., Schadt, E.E., Friend, S.H. (2016). Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases. Nature Biotechnology 24, 531–538. Chong, J.X., Buckingham, K.J., Jhangiani, S.N., Boehm, C., Sobreira, N., Smith, J.D., Harrell, T.M., McMillin, M.J., Wiszniewski, W., Gambin, T., Coban Akdemir, Z.H., Doheny, K., Scott, A.F., Avramopoulos, D., Chakravarti, A., Hoover-Fong, J., Mathews, D., Witmer, P.D., Ling, H., Hetrick, K., Watkins, L., Patterson, K.E., Reinier, F., Blue, E., Muzny, D., Kircher, M., Bilguvar, K., López-Giráldez, F., Sutton, V.R., Tabor, H.K., Leal, S.M., Gunel, M., Mane, S., Gibbs, R.A., Boerwinkle, E., Hamosh, A., Shendure, J., Lupski, J.R., Lifton, R.P., Valle, D., Nickerson, D.A., Bamshad, M.J. (2015). The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities. The American Journal of Human Genetics 97, 199–215. Christiaans, I., Birnie, E., Bonsel, G.J., Wilde, A.A.M., van Langen, I.M. (2008). Uptake of genetic counselling and predictive DNA testing in hypertrophic cardiomyopathy. European Journal of Human Genetics 16, 1201–1207. ClinVar (2017) [online] Available https://www.ncbi.nlm.nih.gov/clinvar/ [accessed 21.03.17].

at:

Cutting, G. 2005. Modifier genetics: cystic fibrosis. Annual Review of Genomics and Human Genetics 6 1:237-60. Dominantly Inherited Alzheimer Network (DIAN) at Washington University, (2017) [online] Available at: http://www.dianinfo.org/ [accessed 11.03.17]. ExAC Browser, (2017) [online] Available at: http://exac.broadinstitute.org/ [accessed 11.03.17]. Frazer, K.A., Murray, S.S., Schork, N.J., Topol, E.J. (2009). Human genetic variation and its contribution to complex traits. Nature Reviews Genetics 10, 241–251. GnomAD browser, (2017) [online] Available at: http://gnomad.broadinstitute.org/about [accessed 18.03.17]. Greco, C.M., Condorelli, G. (2015). Epigenetic modifications and noncoding RNAs in cardiac hypertrophy and failure. Nature Reviews Cardiology 12, 488–497. Green, E.D., Guyer, M.S., Institute, N.H.G.R. (2011). Charting a course for genomic medicine from base pairs to bedside. Nature 470, 204–213. Gusella, J.F., Wexler, N.S., Conneally, P.M., Naylor, S.L., Anderson, M.A., Tanzi, R.E., Watkins, P.C., Ottina, K., Wallace, M.R., Sakaguchi, A.Y., Young, A.B., Shoulson, I., Bonilla, E., Martin, J.B. (1983). A polymorphic DNA marker genetically linked to Huntington’s disease. Nature 306, 234– 238. Handyside, A.H., Lesko, J.G., Tarín, J.J., Winston, R.M., Hughes, M.R. (1992). Birth of a normal girl after in vitro fertilization and preimplantation diagnostic testing for cystic fibrosis. The New England Journal of Medicine. 327, 905–909.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Cg, B. (2004). CCR5 antagonists for the treatment of HIV. Current Opinion In Investigational Drugs 5, 851–861.

Cooper, D.N., Krawczak, M., Polychronakos, C., Tyler-Smith, C., Kehrer-Sawatzki, H. (2013). Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease. Human Genetics 132, 1077–1130.

Page

Bloss, C.S., Jeste, D.V., Schork, N.J. (2011). Genomics for Disease Treatment and Prevention. Psychiatric Clinics of North America 34, 147–166.

Holley, R.W., Apgar, J., Everett, G.A., Madison, J.T., Marquisee, M., Merrill, S.H., Penswick, J.R., Zamir, A. (1965). Structure of a Ribonucleic Acid. Science 147, 1462–1465. Huang, Y., Paxton, W.A., Wolinsky, S.M., Neumann, A.U., Zhang, L., He, T., Kang, S., Ceradini, D., Jin, Z., Yazdanbakhsh, K., Kunstman, K., Erickson, D., Dragon, E., Landau, N.R., Phair, J., Ho, D.D., Koup, R.A. (1996). The role of a mutant CCR5 allele in HIV1 transmission and disease progression. Nature Medicine 2, 1240–1243. Human Fertilisation and Embryology Authority, (2017) [online] Available at: http://www.hfea.gov.uk/index.html [accessed 12.03.17]. Hutchison, C.A. (2007). DNA sequencing: bench to bedside and beyond. Nucleic Acids Research 35, 6227–6237. Jira, P.E., Wanders, R.J.A., Smeitink, J. a. M., Jong, J.D., Wevers, R.A., Oostheim, W., Tuerlings, J.H. a. M., Hennekam, R.C.M., Sengers, R.C.A., Waterham, H.R. (2001). Novel mutations in the 7-dehydrocholesterol reductase gene of 13 patients with Smith– Lemli–Opitz syndrome. Annals of Human Genetics 65, 229–236. Lawrence, D.M. (2009). Huntington’s Disease, 1 edition. pp. 94-95. ed. Chelsea House Publishers, New York. Lek, M., Karczewski, K.J., Minikel, E.V., Samocha, K.E., Banks, E., Fennell, T., O’Donnell-Luria, A.H., Ware, J.S., Hill, A.J., Cummings, B.B., Tukiainen, T., Birnbaum, D.P., Kosmicki, J.A., Duncan, L.E., Estrada, K., Zhao, F., Zou, J., Pierce-Hoffman, E., Berghout, J., Cooper, D.N., Deflaux, N., DePristo, M., Do, R., Flannick, J., Fromer, M., Gauthier, L., Goldstein, J., Gupta, N.,

MacDonald, M.E., Ambrose, C.M., Duyao, M.P., Myers, R.H., Lin, C., Srinidhi, L., Barnes, G., Taylor, S.A., James, M., Groot, N., MacFarlane, H., Jenkins, B., Anderson, M.A., Wexler, N.S., Gusella, J.F., Bates, G.P., Baxendale, S., Hummerich, H., Kirby, S., North, M., Youngman, S., Mott, R., Zehetner, G., Sedlacek, Z., Poustka, A., Frischauf, A.M., Lehrach, H., Buckler, A.J., Church, D., Doucette-Stamm, L., O’Donovan, M.C., RibaRamirez, L., Shah, M., Stanton, V.P., Strobel, S.A., Draths, K.M., Wales, J.L., Dervan, P., Housman, D.E., Altherr, M., Shiang, R., Thompson, L., Fielder, T., Wasmuth, J.J., Tagle, D., Valdes, J., Elmer, L., Allard, M., Castilla, L., Swaroop, M., Blanchard, K., Collins, F.S., Snell, R., Holloway, T., Gillespie, K., Datson, N., Shaw, D., Harper, P.S. (1993). A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington’s disease chromosomes. Cell 72, 971–983. MacLeod, R., Beach, A., Henriques, S., Knopp, J., Nelson, K., Kerzin-Storrar, L. (2014). Experiences of predictive testing in young people at risk of Huntington’s disease, familial cardiomyopathy or hereditary breast and ovarian cancer. European Journal of Human Genetics 22, 396–401. Maron, B.J., Spirito, P., Shen, W.-K., Haas, T.S., Formisano, F., Link, M.S., Epstein, A.E., Almquist, A.K., Daubert, J.P., Lawrenz,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Hert, D.G., Fredlake, C.P., Barron, A.E. (2008). Advantages and limitations of nextgeneration sequencing technologies: a comparison of electrophoresis and nonelectrophoresis methods. Electrophoresis 29, 4618–4626.

Howrigan, D., Kiezun, A., Kurki, M.I., Moonshine, A.L., Natarajan, P., Orozco, L., Peloso, G.M., Poplin, R., Rivas, M.A., RuanoRubio, V., Rose, S.A., Ruderfer, D.M., Shakir, K., Stenson, P.D., Stevens, C., Thomas, B.P., Tiao, G., Tusie-Luna, M.T., Weisburd, B., Won, H.-H., Yu, D., Altshuler, D.M., Ardissino, D., Boehnke, M., Danesh, J., Donnelly, S., Elosua, R., Florez, J.C., Gabriel, S.B., Getz, G., Glatt, S.J., Hultman, C.M., Kathiresan, S., Laakso, M., McCarroll, S., McCarthy, M.I., McGovern, D., McPherson, R., Neale, B.M., Palotie, A., Purcell, S.M., Saleheen, D., Scharf, J.M., Sklar, P., Sullivan, P.F., Tuomilehto, J., Tsuang, M.T., Watkins, H.C., Wilson, J.G., Daly, M.J., MacArthur, D.G., Exome Aggregation Consortium (2016). Analysis of proteincoding genetic variation in 60,706 humans. Nature 536, 285–291.

Page

Han, Y.J., Ryu, H.M. (2011). Prenatal Genetic Test. Journal of Genetic Medicine 8, 100–104.

Moskowitz, S.M., Chmiel, J.F., Sternen, D.L., Cheng, E., Gibson, R.L., Marshall, S.G., Cutting, G.R. (2008). Clinical practice and genetic counseling for cystic fibrosis and CFTR-related disorders. Genetics in Medicine 10, 851–868. Nadeau, J.H. (2001). Modifier genes in mice and humans. Nature Reviews Genetics 2, 165–174. Natesan, S.A., Bladon, A.J., Coskun, S., Qubbaj, W., Prates, R., Munne, S., Coonen, E., Dreesen, J.C.F.M., Stevens, S.J.C., Paulussen, A.D.C., Stock-Myer, S.E., Wilton, L.J., Jaroudi, S., Wells, D., Brown, A.P.C., Handyside, A.H. (2014). Genome-wide karyomapping accurately identifies the inheritance of single-gene defects in human

Rave-Harel, N., Kerem, E., Nissim-Rafinia, M., Madjar, I., Goshen, R., Augarten, A., Rahat, A., Hurwitz, A., Darvasi, A., Kerem, B. (1997). The molecular basis of partial penetrance of splicing mutations in cystic fibrosis. American Journal of Human Genetics 60, 87–94. Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W.W., Hegde, M., Lyon, E., Spector, E., Voelkerding, K., Rehm, H.L., ACMG Laboratory Quality Assurance Committee (2015). Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine 17, 405–424. Rutten, J.W., Dauwerse, H.G., Gravesteijn, G., van Belzen, M.J., van der Grond, J., Polke, J.M., Bernal‐Quiros, M., Lesnik Oberstein, S.A.J. (2016). Archetypal NOTCH3 mutations frequent in public exome: implications for CADASIL. Annals of Clinical and Translational Neurology 3, 844– 853. Sanger, F., Nicklen, S., Coulson, A.R. (1977). DNA sequencing with chain-terminating inhibitors. PNAS 8, 5463–5467. Shawky, R.M., (2014). Reduced penetrance in human inherited disease. Egyptian Journal of Medical Human Genetics 15, 103–111. The Resilience Project, (2017) [online] Available at: http://resilienceproject.com/ [accessed 21.03.17] Traeger-Synodinos, J. (2017). Preimplantation genetic diagnosis. Best Practice & Research Clinical Obstetrics & Gynaecology, Thalassaemia in Obstetric Practice 39, 74–88. Walker, F.O. (2007). Huntington’s disease. The Lancet 369, 218–228. Walsh, R., Thomson, K.L., Ware, J.S., Funke, B.H., Woodley, J., McGuire, K.J., Mazzarotto, F., Blair, E., Seller, A., Taylor, J.C., Minikel, E.V., Exome Aggregation Consortium,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Minikel, E.V., Vallabh, S.M., Lek, M., Estrada, K., Samocha, K.E., Sathirapongsasuti, J.F., McLean, C.Y., Tung, J.Y., Yu, L.P.C., Gambetti, P., Blevins, J., Zhang, S., Cohen, Y., Chen, W., Yamada, M., Hamaguchi, T., Sanjo, N., Mizusawa, H., Nakamura, Y., Kitamoto, T., Collins, S.J., Boyd, A., Will, R.G., Knight, R., Ponto, C., Zerr, I., Kraus, T.F.J., Eigenbrod, S., Giese, A., Calero, M., Pedro-Cuesta, J. de, Haïk, S., Laplanche, J.-L., Bouaziz-Amar, E., Brandel, J.-P., Capellari, S., Parchi, P., Poleggi, A., Ladogana, A., O’Donnell-Luria, A.H., Karczewski, K.J., Marshall, J.L., Boehnke, M., Laakso, M., Mohlke, K.L., Kähler, A., Chambert, K., McCarroll, S., Sullivan, P.F., Hultman, C.M., Purcell, S.M., Sklar, P., Lee, S.J. van der, Rozemuller, A., Jansen, C., Hofman, A., Kraaij, R., Rooij, J.G.J. van, Ikram, M.A., Uitterlinden, A.G., Duijn, C.M. van, (ExAC), E.A.C., Daly, M.J., MacArthur, D.G. (2016). Quantifying prion disease penetrance using large population control cohorts. Science Translational Medicine 8, 3229–3229.

preimplantation embryos in vitro. Genetics in Medicine 16, 838–845.

Page

T., Boriani, G., Estes, N.A.M., Favale, S., Piccininno, M., Winters, S.L., Santini, M., Betocchi, S., Arribas, F., Sherrid, M.V., Buja, G., Semsarian, C., Bruzzi, P. (2007). Implantable Cardioverter-Defibrillators and Prevention of Sudden Cardiac Death in Hypertrophic Cardiomyopathy. JAMA 298, 405–412.

MacArthur, D.G., Farrall, M., Cook, S.A., Watkins, H. (2017). Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples. Genetics in Medicine 19, 192–203.

Wolffe, A.P., Matzke, M.A. (1999). Epigenetics: regulation through repression. Science 286, 481–486.

Page

Wang, J., Shen, Y. (2014). When a “DiseaseCausing Mutation” Is Not a Pathogenic Variant. Clinical Chemistry 60, 711–713.

Wild, E.J. (2016). Huntington’s Disease: The Most Curable Incurable Brain Disorder? EBioMedicine 8, 3–4.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Expanding the Genetic Code: NonProteinogenic Amino Acids Owen Julianto Jonathan (owen.jonathan@student.manchester.ac.uk) Faculty of Biology, Medicine and Health, The University of Manchester, U.K.

Introduction Proteinogenic amino acids are incorporated into proteins during translation and it includes the standard twenty amino acids as well as selenocysteine and pyrrolysine. Each

Amino acids are incorporated into proteins during translation through a mechanism that involves an orthogonal aminoacyl-tRNA synthetase/isoacceptor tRNA (aaRS/iso-tRNA) pair that is specific for each different amino acid. Aminoacyl-tRNA synthetase is responsible for bringing together an isoacceptor tRNA with its correspondent amino acid (aminoacylation). On the other hand, the isoacceptor tRNA carries the amino acid to the ribosome where it recognizes a specific codon in the mRNA (Davis and Chin, 2012).

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Twenty amino acids are universally found in the genetic code of most known species. However, some organisms have evolved a way to incorporate an additional amino acid into their proteins during translation. Synthetic biologists have exploited this unique translation mechanism to allow the incorporation of other amino acids that are not naturally found in living cells. This review aims to describe the new and latest findings that are involved in the incorporation of nonproteinogenic amino acids and to discuss their possible future applications. The mechanism that involves the suppression of stop codons and engineering a new orthogonal aminoacyl-tRNA synthetase/isoacceptor tRNA (aaRS/isotRNA) pair was successfully implemented in Escherichia coli, opening an exciting area of research in expanding the genetic code. Incorporation of nonproteinogenic amino acids provides the tool to research protein interactions in a structural and molecular level and has other possible applications for biocontainment and design of therapeutic proteins.

standard amino acid is encoded by three base pairs known collectively as a codon, with some codons acting as ‘stop’ signals, known as stop codons (Clancy and Brown, 2008). While evolution has limited most organisms to these standard twenty amino acids, some methanogenic archaea were found to incorporate other natural amino acids – selenocysteine (Sec) and pyrrolysine (Pyl) – now referred to as the 21st and 22nd proteinogenic amino acid (Rother and Krzycki, 2010). These two amino acids are encoded through different mechanisms which similarly utilize codons that normally function as stop signals (Zhang et al., 2005). Aside from selenocysteine and pyrrolysine, there are other amino acids that can be found in nature that were not utilized by living organisms and many more that were chemically synthesized (Philip and Freeland, 2011).

Page

Abstract

The mechanism of incorporating selenocysteine also differs slightly between prokaryotes, eukaryotes and archaea. Firstly, a tRNA that is specific for selenocysteine (tRNAsec) is charged with serine (Ser) by seryl-tRNA synthetase, resulting in Ser-tRNAsec. In prokaryotes, tRNAsec with the serine residue is converted by selenocysteine synthase into Sec-tRNAsec in the presence of a selenium donor, selenophosphate. However, in eukaryotes and archaea, there is an additional enzymatic step involved; Ser-tRNAsec is first phosphorylated by a kinase before converted into the final product SectRNAsec by a different enzyme (Yuan et al., 2010). While all three domains of life have shown to incorporate selenocysteine, not all lineages within the three domains have this mechanism. The reason and advantage to use selenocysteine is still currently unknown. In a large proportion of prokaryotic proteins that contain selenocysteine, there exists a homologous protein with cysteine (Cys) at the respective position where selenocysteine is incorporated. In archaea, proteins that

Pyrrolysine Unlike Selenocysteine, proteins containing pyrrolysine was found only in methanogenic archaea, specifically in the family Methanosarcinaceae, and bacteria. Pyrrolysine is found in methylamine methyltransferase, proteins that are involved in the conversion of methyl groups into methane (Gaston et al., 2011). There are three classes of methylamine methyltransferases that contain pyrrolysine with each class being involved in the metabolism of different methyl groups. These proteins are monomethylamine methyltransferase (mtmB), dimethylamine methyltransferase (mtbB), and trimethylamine methyltransferase (mttB). All genes that are involved in encoding these proteins have UAG stop codons or ‘amber’ stop codons. Stop codons in these genes do not terminate translation but incorporates pyrrolysine instead. Currently, the existence of a eukaryotic methyltransferase that incorporates pyrrolysine has not been found and it is unknown whether there

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

All three domains of life – eukaryote, prokaryote, and archaea – have shown to produce selenoproteins that contain selenocysteine. Although there are slight differences, the overarching mechanism involves the UGA stop codon or ‘opal’ stop codon as the code for incorporation and the presence of a selenocysteine insertion sequence, known as the SECIS element (Rother and Krzycki, 2010). In eukaryotes and archaea, SECIS elements are in the 3’ untranslated regions (UTR) of the selenoprotein mRNA. While in prokaryotes, the SECIS elements are located immediately downstream of the UGA stop codon that encodes for selenocysteine (Su et al., 2005).

contain selenocysteine are restricted to methanogens and are involved in methanogenesis. However, not all methanogens utilize selenocysteine in their proteins and only two species, Methanococcales and Methanopyrales, were shown to incorporate selenocysteine in their metabolic processes (Rother and Krzycki, 2010). It is now thought that the incorporation of selenocysteine may have been an ancient evolutionary relic that is present in the last universal common ancestor before the three domains of life separated. The UGA stop codon may have originally been a sense codon for selenocysteine but due to different selective pressure during evolution, some species have lost this trait (Bock et al., 1991).

Page

Selenocysteine

It is still currently unknown why pyrrolysine is incorporated into methylamine methyltransferase proteins. While there are studies that demonstrate the importance of the amino acid in this protein, many of the proposed models are still largely untested (Rother and Krzycki, 2010).

Expanding the Genetic Code There has been previous success in adding unnatural amino acids into proteins through chemical and biosynthetic methods, allowing researchers to study protein structure and function in greater detail (Liu and Schultz, 2010). One such method involves the use of a wild-type aminoacyl-tRNA synthetase to add non-proteinogenic amino acids that are close structural analogs of the twenty standard amino acids (Link et al., 2003). However, this

To enhance this methodology, a general method has been developed to enable the incorporation of any non-proteinogenic amino acids for protein synthesis. This is done by exploiting the translational mechanism of organisms through the engineering of new aminoacyl-tRNA synthetase/isoacceptor tRNA (aaRS/isotRNA) pairs (Liu and Schultz, 2010). The method involves importing a heterologous aaRS/iso-tRNA pair from a different domain of life to ensure orthogonality and specificity. The anticodon loop of the tRNA is then mutated to correspond to a stop codon of choice (Liu and Schultz, 2010). In E. coli, the amber stop codon is the ideal codon for the incorporation of these new amino acids because it is the least used stop codon by the organism (Wals and Ovaa, 2014). However, there are several conditions that would have to be satisfied to successfully incorporate a new amino acid. First, the amino acid of choice must be able to be taken up by the host and be metabolically stable inside the host cell. In addition, it must be tolerated by critical components of the translational machinery, EF-Tu and the ribosome. Second, the unique codon must interact with the new tRNA only and not by any other tRNA. Third, the aaRS/iso-tRNA pair must be functional inside the host cell, specific to each other and specific to the amino acid of choice (Liu and Schultz, 2010). The first criterion is often easily achieved by most non-proteinogenic amino acids

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Pyrrolysine is incorporated into methylamine methyltransferase through a cluster of pyl genes, pylTSBCD. These five pyl genes are proved to be core genes for the biosynthesis and incorporation of pyrrolysine into proteins (Krzycki, 2010). The pylT gene encodes a tRNA that is specific for pyrrolysine which can recognize the amber codon, tRNAPyl while the pylS gene encodes pyrrolysl-tRNA synthetase which charges tRNAPyl directly with pyrrolysine (Gaston et al., 2011). A study has shown that these two genes are sufficient for the incorporation of pyrrolysine into proteins in E. coli only when exogenous pyrrolysine is supplemented (Blight et al., 2004). The enzymatic activity of the pylB, pylC, and pylD genes are still unknown in full detail but it is known that these genes are involved in the biosynthesis of pyrrolysine from two lysine residues (Gaston et al., 2011).

method is not site-specific and results in a whole replacement of the standard amino acid with the new amino acid in proteins. It is also limited to amino acids that are structurally similar to the standard twenty amino acids (Liu and Schultz, 2010).

Page

are other Pyl-containing proteins in existence (Zhang et al., 2005).

because of the highly promiscuous characteristic of EF-Tu and the ribosome (Liu and Schultz, 2010). In addition, the second criterion can be fulfilled through simple base-pairing rules and by designing a tRNA with an anticodon that corresponds to an unused stop codon. The challenge lies in the third criterion; ensuring that the aaRS/iso-tRNA pair are functionally specific to each other as well as specific to the amino acid. In order to solve this challenge, a method of selection is developed to ensure that the aaRS/iso-tRNA is specific to each other and able to incorporate the desired amino acid as well.

A similar two-step selection scheme is then used to alter the specificity of the aaRS/iso-tRNA pair to ensure specificity to the desired amino acid of choice. Firstly, a library of mutant aaRS is constructed and transformed into E. coli cells expressing the heterologous tRNA from the previous selection and are grown in a medium with the desired amino acid and an antibiotic, chloramphenicol. Similar to the previous positive selection process, an antibiotic resistant gene with an amber codon is involved to ensure that a functional aaRS is able to aminoacylate the tRNA mutant with an amino acid successfully.

Method of Selection

However, this does not ensure that the amino acid of choice is charged to the tRNA mutant. Thus, the surviving mutants go through a negative selection process and are transformed in E. coli cells that express an amber-coded barnase gene and the tRNA mutant. The cells are grown in a different medium in the absence of the desired amino acid to ensure that only aaRS/iso-tRNA pairs that are specific to the amino acid of choice survives. aaRS/iso-tRNA pairs that are not specific to the amino acid of choice will encode a natural amino acid and express the lethal toxin, thus killing the cells (Liu and Schultz, 2010).

Each amino acid has its own distinct chemical properties that allows it to express a wide range of properties. Thus, the incorporation of additional amino acids may provide new novel properties in proteins which can be used for a wide variety of applications. In protein research, the addition of nonproteinogenic amino acids have provided researchers the tools to study protein structure and function in a deeper level (Neumann-Staubitz and Naeumann, 2016).

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The tRNAs that survive are then transformed into E. coli cells that express the heterologous aaRS in a positive selection process which involves a Î˛lactamase gene with an amber codon. The Î˛-lactamase gene gives the bacteria resistance to ampicillin. In this selection process, the bacterial cells are grown under the presence of ampicillin, killing all cells that contain a nonfunctional tRNA and leaving cells that have a functional aaRS/iso-tRNA pair (Liu and Schultz, 2010).

Application

Page

While the method of selection differs slightly depending on the host cell, the method of selection in E. coli is used here as an example to show how the selection generally works. The first selection ensures that the aaRS/iso-tRNA pair are specific to each other. Firstly, a library of mutant tRNA based on the heterologous tRNA is transformed in E. coli cells that contain a lethal toxic gene, barnase, with an amber stop codon. This negative selection process is done in the absence of the heterologous aaRS, ensuring that if an endogenous E. coli aaRS interacts with the mutant tRNA, the lethal toxin will be expressed and kill the cell.

Certain other amino acids can act as cross-linkers which are activated by UV light (Neumann-Staubitz and Naeumann, 2016). An example of a crosslink amino acid is p-azidophenylalanine which can trap protein ligands when exposed to UV and provides researchers a tool to study protein interactions in living cells (Shao et al., 2015). Also, some amino acids such as phenylazophenylalanine can act as a photo-switch for regulating enzyme activity (Hoppmann et al., 2014). These types of amino acids have a side chain residue that can form side chain-to-side chain bridges with another amino acid on the same protein when exposed to light. These bridges cause conformation change

In another area, a synthetic E. coli strain that completely relies on nonproteinogenic amino acids was successfully created to demonstrate a potential solution in preventing the unintended proliferation of genetically modified organisms in the environment. The E. coli strain that was created by researchers at Yale University lacks all instances of the UAG stop codon along with RF1 (release factor), a protein that recognizes this stop codon and terminates translation. Instead, the stop codon is converted to a sense codon through the incorporation of an aaRS/isotRNA pair that recognizes this stop codon. By having the organism rely on non-proteinogenic amino acids to translate essential proteins, this E. coli strain may be a safe biocontainment mechanism for genetically modified organisms in the future (Mandell et al., 2015). Taking a similar approach, the reliance of non-proteinogenic amino acids in organisms can also be used in designing synthetic vaccines. These vaccines will depend on the amino acids to replicate within the host cell which ensures that an immune response would still be obtained without any detrimental effects (Jones, 2015). Bispecific antibodies which can simultaneously bind to two different antigens have also been synthesized using genetically encoded nonproteinogenic amino acids. This is demonstrated in a study where pacetylphenylalanine was incorporated at defined sites in each of the two antigenbinding fragment to create an anti-

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

In addition, amino acids with unique infrared (IR) and X-ray diffraction signatures have been used to study protein structure and dynamics. An example is p-cyanophenylalanine that contains a cyano group which absorbs in a clear spectral window at ~2200cm-1. This amino acid has been used to study metal ion and ligand binding in myoglobin (Liu and Schultz, 2010).

to the 3D structure of the enzyme and thus inhibiting its reactivity to bind to its substrate (Hoppman et al., 2011). The introduction of these amino acids may allow researchers to control biological processes in live cells for research purposes.

Page

Some non-proteinogenic amino acids are small and fluorescent which enable researchers to tag it into proteins without causing any major structural perturbation which is especially useful in a number of bioanalytical studies and applications. Currently, the traditional genetic fluorescent tags such as GFP are often limited due to their large size. This limits the resolution and precision of distance measurements in protein studies. Also, traditional genetic fluorescent tags are often insensitive to the local environment and can only be introduced at the C or N terminus of a protein. Thus, limiting investigations of changes in distance or polarity due to changes of the local environment (Summerer et al., 2006).

There are other researches that have taken a different route in expanding the genetic code. Ultimately, the goal would be to design a system or mechanism that would allow the incorporation of multiple non-proteinogenic amino acids efficiently. One solution would be to engineer synthetic tRNAs that recognize each of the three stop codons UAG, UGA, and UAA (Gubbens et al., 2010). However, there has been other research to reprogram the genetic code and translation machinery from recognizing triplet codons into quadruplet codons. With four base codons, there is an increased number of possible combinations that can be designated for each amino acid and through this system, multiple unnatural amino acids have been successfully incorporated (Wang et al., 2012). Another alternative approach was to create new unnatural base pairs, opening new possibilities of new codon sites that could be designated for these non-proteinogenic amino acids (Hirao and Kimoto, 2012). A different study took a different approach in expanding the genetic code by exploiting the complementary base pairing interaction between the tRNA and the ribosome. A new orthogonal ribosome-tRNA pair was evolved to specifically recognize an artificially programmed genetic code while also being able to function in parallel with a wild-type ribosome-tRNA pair, resulting in the production of two distinct peptides

Conclusion Evolution has directed most living organisms to utilize a standard set of twenty amino acids in their metabolism. Yet, a few have managed to use an additional amino acid for their own unique biological processes. With each amino acid having their own distinct chemical properties, the incorporation of non-proteinogenic amino acid in expanding the genetic code has enormous promise from its different possible applications in protein modification. However, this area of research is still in its infancy and significant challenges are still currently being addressed. The techniques are still continually being improved and new methods to increase efficiency of the system and yield of the protein are still being researched. Despite this, expanding the genetic code is certainly an exciting area of research within synthetic biology which may potentially have a great impact to the world in the future.

Bibliography Blight, S. K., Larue, R. C., Mahapatra, A., Longstaff, D. G., Chang, E., Zhao, G., Kang, P. T., Church-Church, K. B., Chan, M. K. & Krzycki, J. A. 2004. Direct charging of tRNA(CUA) with pyrrolysine in vitro and in vivo. Nature, 431, 333-335. Bock, A., Forchhammer, K., Heider, J., Leinfelder, W., Sawers, G., Veprek, B. & Zinoni, F. 1991. Selenocysteine - The 21ST Amino-acid. Molecular Microbiology, 5, 515520.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Other Associated Research

from a single mRNA strand in vitro (Terasaka et al., 2014). Although the goal would be to have these systems working in a living organisms, most of the research and studies mentioned have only been done successfully in vitro. However, there are challenges and constraints such as reduced translation efficiency that would have to be solved first before the next step can be taken.

Page

HER2/anti-CD3 bispecific antibody (Kim et al., 2012). The use of non-proteinogenic amino acids have advantages in the production of a single homogenous product which is difficult to obtain through chemical modifications of standard amino acids that often results in heterologous products (Wals and Ovaa, 2014).

England, P. M. 2004. Unnatural amino acid mutagenesis: A precise tool for probing protein structure and function. Biochemistry, 43, 11623-11629.

Link, A. J., Mock, M. L. & Tirrell, D. A. 2003. Non-canonical amino acids in protein engineering. Current Opinion in Biotechnology, 14, 603-609.

Gaston, M. A., Jiang, R. S. & Krzycki, J. A. 2011. Functional context, biosynthesis, and genetic encoding of pyrrolysine. Current Opinion in Microbiology, 14, 342-349.

Liu, C. C. & Schultz, P. G. 2010. Adding New Chemistries to the Genetic Code. In: Kornberg, R. D., Raetz, C. R. H., Rothman, J. E. & Thorner, J. W. (eds.) Annual Review of Biochemistry, Vol 79. Palo Alto: Annual Reviews.

Gubbens, J., Kim, S. J., Yang, Z. Y., Johnson, A. E. & Skach, W. R. 2010. In vitro incorporation of nonnatural amino acids into protein using tRNA(Cys)-derived opal, ochre, and amber suppressor tRNAs. Rna-a Publication of the Rna Society, 16, 1660-1672.

Mandell, D. J., Lajoie, M. J., Mee, M. T., Takeuchi, R., Kuznetsov, G., Norville, J. E., Gregg, C. J., Stoddard, B. L. & Church, G. M. 2015. Biocontainment of genetically modified organisms by synthetic protein design. Nature, 518, 55-+.

Hendrickson, T. L., De Crecy-Lagard, V. & Schimmel, P. 2004. Incorporation of nonnatural amino acids into proteins. Annual Review of Biochemistry, 73, 147-176.

Martin, G. W., Harney, J. W. & Berry, M. J. 1996. Selenocysteine incorporation in eukaryotes: Insights into mechanism and efficiency from sequence, structure, and spacing proximity studies of the type 1 deiodinase SECIS element. Rna-a Publication of the Rna Society, 2, 171-182.

Hirao, I. & Kimoto, M. 2012. Unnatural base pair systems toward the expansion of the genetic alphabet in the central dogma. Proceedings of the Japan Academy Series BPhysical and Biological Sciences, 88, 345367. Hoppmann, C., Lacey, V. K., Louie, G. V., Wei, J., Noel, J. P. & Wang, L. 2014. Genetically Encoding Photoswitchable Click Amino Acids in Escherichia coli and Mammalian Cells. Angewandte ChemieInternational Edition, 53, 3932-3936. Hoppmann, C., Schmieder, P., Heinrich, N. & Beyermann, M. 2011. Photoswitchable Click Amino Acids: Light Control of Conformation and Bioactivity. Chembiochem, 12, 25552559. Jones, L. H. 2015. Recent advances in the molecular design of synthetic vaccines. Nature Chemistry, 7, 952-960. Kim, C. H., Axup, J. Y., Dubrovska, A., Kazane, S. A., Hutchins, B. A., Wold, E. D., Smider, V. V. & Schultz, P. G. 2012. Synthesis of Bispecific Antibodies using Genetically Encoded Unnatural Amino Acids. Journal of the American Chemical Society, 134, 9918-9921.

Neumann-Staubitz, P. & Neumann, H. 2016. The use of unnatural amino acids to study and engineer protein function. Current Opinion in Structural Biology, 38, 119-128. Philip, G. K. & Freeland, S. J. 2011. Did Evolution Select a Nonrandom "Alphabet" of Amino Acids? Astrobiology, 11, 235-240. Rother, M. & Krzycki, J. A. 2010. Selenocysteine, Pyrrolysine, and the Unique Energy Metabolism of Methanogenic Archaea. Archaea-an International Microbiological Journal, 14. Shao, N., Singh, N. S., Slade, S. E., Jones, A. M. E. & Balasubramanian, M. K. 2015. Site Specific Genetic Incorporation of Azidophenylalanine in Schizosaccharomyces pombe. Scientific Reports, 5, 9. Su, D., Li, Y. H. & Gladyshev, V. N. 2005. Selenocysteine insertion directed by the 3'UTR SECIS element in Escherichia coli. Nucleic Acids Research, 33, 2486-2492. Summerer, D., Chen, S., Wu, N., Deiters, A., Chin, J. W. & Schultz, P. G. 2006. A genetically encoded fluorescent amino acid.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Davis, L. & Chin, J. W. 2012. Designer proteins: applications of genetic code expansion in cell biology. Nature Reviews Molecular Cell Biology, 13, 168-182.

Krzycki, J. A. 2010. Translation of UAG as Pyrrolysine. In: Atkins, J. F. & Gesteland, R. F. (eds.) Recoding: Expansion of Decoding Rules Enriches Gene Expression. Berlin: Springer-Verlag Berlin.

Page

Clancy, S. & Brown, W. Translation: DNA to mRNA to Protein. Nature Education 1(1):101.

Proceedings of the National Academy of Sciences of the United States of America, 103, 9785-9789. Terasaka, N., Hayashi, G., Katoh, T. & Suga, H. 2014. An orthogonal ribosome-tRNA pair via engineering of the peptidyl transferase center. Nature Chemical Biology, 10, 555557. Wals, K. & Ovaa, H. 2014. Unnatural amino acid incorporation in E. coli: current and future applications in the design of therapeutic proteins. Frontiers in Chemistry, 2, 12. Wan, W., Tharp, J. M. & Liu, W. R. 2014. Pyrrolysyl-tRNA synthetase: An ordinary enzyme but an outstanding genetic code expansion tool. Biochimica Et Biophysica Acta-Proteins and Proteomics, 1844, 10591070.

spontaneous protein double-labelling and FRET. Nature Chemistry, 6, 393-403. Wang, K. H., Schmied, W. H. & Chin, J. W. 2012. Reprogramming the Genetic Code: From Triplet to Quadruplet Codes. Angewandte Chemie-International Edition, 51, 2288-2297. Yuan, J., O'Donoghue, P., Ambrogelly, A., Gundllapalli, S., Sherrer, R. L., Palioura, S., Simonovic, M. & Soll, D. 2010. Distinct genetic code expansion strategies for selenocysteine and pyrrolysine are reflected in different aminoacyl-tRNA formation systems. Febs Letters, 584, 342-349. Zhang, Y., Baranov, P. V., Atkins, J. F. & Gladyshev, V. N. 2005. Pyrrolysine and selenocysteine use dissimilar decoding strategies. Journal of Biological Chemistry, 280, 20740-20751.

Page

Wang, K. H., Sachdeva, A., Cox, D. J., Wilf, N. W., Lang, K., Wallace, S., Mehl, R. A. & Chin, J. W. 2014. Optimized orthogonal translation of unnatural amino acids enables

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Long non-coding RNA and the Regulation of Gene Expression Kashmala Carys (kashmala.carys@student.manchester.ac.uk) Faculty of Biology, Medicine and Health, The University of Manchester, U.K.

The central scientific dogma states that deoxyribonucleic acid (DNA) is transcribed into ribonucleic acid (RNA) which is subsequently translated into proteins (Crick, 1958). Contemporary to the time, it was believed that genes only coded for proteins. The only proposed exceptions to this rule were transfer RNA (tRNA) and ribosomal RNA (rRNA), parts that did not code for a protein were termed intergenic DNA. Sharp and Roberts added further complexity in the late 1970s when they discovered that some genes were discontinuous and consisted of protein-coding regions, called exons, as well as non-proteincoding regions called introns (Berk and Sharp, 1977). During the 1990’s the Human Genome Project took place which resulted in a startling discovery that only 3% of the human genome codes for proteins, including their introns. This left vast amounts of intergenic DNA and intronic DNA deemed as ‘junk DNA’. However, this small percentage contrasts highly with the existing knowledge that between 70%-90% of our DNA is transcribed (Pennisi, 2012). In the past few decades, the focus has begun to shift to the exploration of the structure and possible functions of these transcribed non-coding RNA transcripts have. This has led to the discovery that these

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Exploration into non-coding regions of the genome has increased dramatically over recent decades. These regions were once thought to produce transcriptional noise. However, an emerging new understanding of these regions has led to the discovery of another level of regulatory molecules called non-coding RNAs. This report aims to look further into three specific long non-coding RNAs; X-inactivated specific transcript, Metastatic Associated Lung Adenocarcinoma Transcript 1 and Hox Antisense Intergenic RNA. The report will investigate their discovery and how they regulate both gene expression and themselves. This report also uncovers the dependency a variety of processes have on epigenetic regulation by long noncoding RNAs. It highlights non-coding RNAs as a crucial starting point in the regulation of protein-coding regions as well as whole chromosomes. It reveals a strong relationship between non-coding RNAs and proteins in order to coordinate and sustain chromatin modification. Due to conflicting data on the mechanisms of long non-coding RNAs, it can be concluded that how non-coding RNAs function is still very unclear and this pioneering field in molecular biology has only just begun.

Introduction: Including the Classification and Structure of Long non-coding RNAs

Page

Abstract

The structure of RNA consists of four nucleotides; adenine (A), uracil (U), cytosine (C) and guanine (G). LncRNAs, along with other RNAs, have been found to contain a multitude of base modifications resulting in a more dynamic molecule (Mercer and Mattick, 2013). One such modification in lncRNAs is N(6)-Methyladenosine which is a reversible post-transcriptional modification that adds a N⁶-methyl group

The ability for RNA to form a secondary structure stems from the formation of hydrogen bonding through Watson-Crick base pairing and Hoogsteen base pairing. This allows lncRNA to form a variety of secondary structures (Mercer and Mattick, 2013). One secondary structure observed in MALAT1 (metastasisassociated lung adenocarcinoma transcript 1), a lncRNA that is a regulator of alternative splicing, is a triple helix structure at its 3’ end. This structure prevents cleavage from exonucleases, allowing the RNA to mature (Wilusz et al., 2012). Another form of observed secondary structure in lncRNA is the hairpin. This secondary structure is also proposed to be present in MALAT1 and is stabilised by the addition of an N(6)-Methyladenosine modification (Zhou et al., 2016). Other secondary structures found in RNAs include bulges and pseudoknots (Mercer and Mattick, 2013). These secondary structures aid in the formation of larger tertiary structured lncRNAs, forming the finalised molecule ready to generate changes in gene expression. The structure of lncRNAs is still a

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The first ncRNA structure to be resolved was tRNA in 1965 by Holley et al. He characterised this by purifying the alanine tRNA from yeast and sequencing it through studying fragments from pancreatic ribonuclease digests. Since this initial finding, a better understanding of molecular mechanisms as well as a progression of genomic techniques and consortium-wide studies, such as ENCODE, have led to the uncovering of thousands of ‘RNA genes’ (Pennisi, 2012). This has resulted to the need for a classification system for RNA molecules. Small ncRNAs refer to ncRNAs with a transcript length of fewer than 200 nucleotides; examples include micro-RNAs and small inhibitory RNAs. Contrary, long non-coding RNAs (lncRNAs) refer to RNA molecules with a length greater than 200 nucleotides, which were first described during the sequencing of a mouse cDNA library (Rinn and Chang, 2012; Okazaki, et al., 2002).

to an adenosine base in a DRCH consensus motif. A consensus motif is a calculated probability that certain nucleotides will occur in a particular and unique order. In the DRCH consensus motif, D is equivalent to the following nucleotides A, G or U, R is equivalent to G or A, and H is either A, C or U (Zou et al., 2016). These post-transcriptional modifications are important as they can regulate lncRNA’s transport, processing and its ability to take part in gene expression. This is crucial to the function of lncRNAs, which will become more apparent in due course. It is also important due to a result in the change of the secondary structure of the long ncRNA that follows (Zhou et al., 2016).

Page

transcribed intergenic and intronic regions of DNA do not need to undergo translation and are another level of functional unit within the cell, called non-coding RNAs (ncRNAs). This has ultimately lead to a shift in paradigm of the central scientific dogma as increasing evidence highlights the invaluable importance of ncRNA’s diverse role in the molecular mechanisms of gene expression.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

LncRNAs have been observed to originate on anti-sense strands of DNA, meaning they will be transcribed in the

opposite orientation to other coding regions. They are also found in sense strands and have been located within protein-coding and intergenic regions of DNA (Kung et al., 2013). LncRNAs only found within intergenic parts of the DNA are categorised as lincRNAs, counter to lncRNAs which overlap into proteincoding regions. There are also divergent lncRNAs which are transcribed in opposition to the direction of the promoter (Sigova et al., 2013). In addition to this, many have been found close to protein-coding regions of DNA, in clusters (Mercer and Mattick, 2013). Supporting this statement, in a recent study by Herriges et al. (2014), it was noted that lncRNAs were identified near appropriate transcription factors required for gene expression in the lungs and endoderm. Further confirmation from a study by Spurlock et al. (2015) discovered that specific lncRNAs in Tcells were expressed along with proteincoding gene counterparts. Subsequently, it was reviewed that a cluster of lncRNAs including TH2-LCR lncRNA, originate next to the RAD50 locus and were expressed with genes encoding proteins such as, interleukin 4, 5 and 13. Interleukins play a number of crucial roles in the immune response and are differentially expressed by leukocytes. Due to this co-expression of the RAD50 locus with interleukin genes, it has been posited that the expression of this locus is important in controlling the differentiation between T-helper cells 1 and 2, which secrete different interleukins (Lee and Rao, 2004). This suggests the necessity of lncRNAs in the expression of protein-coding genes because the expression of certain lncRNAs only occurs in certain T-helper (TH) cells which express specific interleukins. Additionally, the TH2Locus Control Region transcript has been shown to overlap the genes coding for

Page

prematurely developed field within molecular biology. Currently, research suggests a lack of conservation between lncRNAs sequences which underpin their structure. This is converse to the array of evolutionary conservation found between protein-coding regions and therefore has presented a ‘non-conservation conundrum’. This conundrum implies that due to the lack of conservation between lncRNA sequences there should also be a lack of functionality too, as observed in proteins. However, this assumption is being shown to be incorrect as research already indicates that lncRNAs play an integral role in gene expression (Johnsson et al., 2013). A study in zebrafish conducted by Ulitsky et al. (2011) identified 550 long intervening non-coding RNAs (lincRNAs) through the use of RNA-Seq data, and poly-(A)-site mapping. In addition, they found that only 29 had similar sequences to mammalian orthologues, they determined this through phastCons scores. PhastCons is a program that compares sequences to identify conserved elements (Siepel et al., 2005), BLASTN was also used. However, just because there is a lack of conservation doesn’t mean these particular lncRNAs have any less of a function to the organism. Following on from this, data supplied by Kutter et al. (2012) explored the conservation of lncRNA between rodents. Their results depicted the enormity of the loss and gain of transcribed lncRNAs and suggested a rapid evolution of the transcriptome since the mouse and rat separated into different lineages, which also contrasts highly with the slower evolution of proteins. There is reason to suggest that perhaps lncRNA regions simply evolve at a faster rate than protein-coding regions.

The Dosage XIST

Compensator;

The first sign that lncRNA could be involved in gene expression was in the mechanism of X-chromosome inactivation. X-chromosome inactivation is an important mechanism in eutherian mammals. It allows for dosage compensation of the X-chromosome in a female’s somatic cells which balances the

XIST is a lncRNA that has a similar structure to mRNA as it is capped, polyadenylated and spliced. It has been found in a variety of isoforms, due to splicing (Plath et al., 2002). There are two prominent isoforms of XIST; the long form (L-form) and the short form (Sform), which are different at their 3’ ends. Memili et al. (2001) observed this phenomenon through hybridising the XIST transcript to specific probes lying upstream, in the middle of, and downstream of the proposed XIST transcript, in a Northern Blot. The two transcripts types were likely to have originated from the P2 promoter in XIST, not from the P1 promoter. This was confirmed by a study from Ma and Strauss (2005). It was also found that the S-type is polyadenylated after transcription, whereas the L-type is not. In their research, they observed that the L-type is predominately active during the early embryonic stages and most likely governs X-chromosome inactivation in embryos. However, both types are found active in the female somatic kidney cells.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Epigenetics is the ability of certain molecules to reversibly bind to DNA and modify chromatin structure. This results in a change of gene expression without affecting the genetic code itself (Spector, 2012). It has become more apparent that lncRNAs play a crucial role in a jig-sawlike puzzle of molecules which effect gene expression. It was discovered that lncRNAs have the ability to act either in a cis- or transmanner on DNA. If the RNA is cis- acting it will act on its surrounding genes, whereas if the RNA is trans-acting it will be able to affect genes throughout the DNA (Kung et al., 2013). Studies have shown that lncRNAs have the ability to interact with DNA in a variety of ways. One example is its capacity to recruit histone modifying proteins. For example, a lncRNA called ‘Air’ will recruit a methylating factor which will be able to silence paternal genes such as Slc22a2, which encodes a cation transporter protein (Nagano et al., 2008). Another way in which lncRNA can affect gene expression is through directly administering the methylation of DNA at CpG sites (Law and Jacobsen, 2010).

number of genes females (XX) and males (XY) (Lee, 2011). Through various studies predating the knowledge of lncRNAs, it was discovered that Xinactivation begins at a specific point along the X-chromosome. This is called the X-chromosome inactivation centre (Xic). During the early 1990s, it was observed that the inactivated Xchromosome uniquely expressed a RNA transcript at this centre (Brown et al., 1991). It was later discovered that an inability to transcribe this RNA gene meant that X-chromosome inactivation would not take place (Penny et al., 1996). This led to hypotheses that this lncRNA was the key to dosage compensation in mammals. The lncRNA involved in this process is a 17kb transcript named Xinactivated specific transcript (XIST) (Schaukowitch and Kim, 2014).

Page

interleukins. This further suggests that, the expression of lncRNAs leads to the regulation of associated protein-coding genes. The general observation that lncRNAs are often found a short distance away from protein-coding regions aids the phenomenon of the role lncRNA plays as an epigenetic regulator.

It has been revealed that there are two forms of X-Chromosome inactivation: imprinted X-chromosome inactivation and random X-chromosome inactivation (Lee, 2011). Recent studies have suggested that in females the paternal Xchromosome (Xp) is preferentially inactivated after fertilisation and during embryogenesis. In mice, Xp is imprinted through XIST coating the paternal Xchromosome in female embryos, this is called the initiation phase. This process will also happen at the start of random Xinactivation during the blastocyst stage in the inner cell mass (ICM) and through somatic cell generation (Cerase et al., 2015). XIST RNA has been shown to have a higher affinity for silent gene-coding regions on the X-chromosome. Therefore, it will bind to these regions and then spread to coat the active gene regions and the entire chromosome. This was illustrated through regions of low gene density loosing XIST when it is depleted in the nucleus. This mechanism of Xinactivation happens in a cis-acting manner; therefore the chromosome must carry the Xic. As XIST spreads distally from the Xic, it has been suggested that it alters the chromatin to increase its affinity for XIST and thus perpetuating the spread of XIST further (Leung and Panning, 2015). This is the maintenance phase of inactivation. This phase does not necessarily need the continued expression of XIST. As XIST has already been recruited, the inactive state is maintained by a large complex of proteins. One study conducted by Chu et al. (2015) identified around 81 proteins that interact with XIST. The functions of

The acquisition of PRC2 by XIST is still being debated today. One proposed model is the direct-interaction model, which requires the transcription of RepA. RepA is a conserved domain at the 5â&#x20AC;&#x2122;end of the XIST transcript which is 1.6kb in length. It has been posited that RepA has the ability to directly recruit the PCR2 (Zhao et al., 2008). This complex has an RNA binding domain called EHZ2, thus allowing it to interact with XIST (Betancur and Tomari, 2015). This interaction is important as PCR2 can modify chromatin in the X-chromosome at histone 3, lysine 27. It has been shown that a lack of PRC2 prevents the upregulation of XIST (Zhao et al., 2008). Additionally, a study by Simon et al. (2013) discovered that XIST location on the inactivated X-chromosome is linear to the location of PRC2. Despite this, the direct-interaction model has opposing evidence too, from a number of studies. For example, one study concluded that the paternal X chromosome in females is imprinted solely due to XIST, not due to regulation of chromatin (Okamoto et al., 2004). Moreover, recent research conducted by Cerase et al. (2014) mapped the genome and performed 3D structure illumination microscopy to observe that the targeting of PRC2 is not spatially coordinated well with silenced regions along the X-Chromosome where XIST works. This substantial conflict in data suggests that the mechanisms through which XIST maintains the regulation of inactivation are not clearly understood yet. What is known is that these proteins have the ability to orchestrate the maintenance XISTâ&#x20AC;&#x2122;s epigenetic

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

these proteins vary. For example, transcriptional repressor components of Sin3-HDAC1, allow histone deacetylases to be recruited. One of the most examined proteins to associate with XIST is the Polycomb Repressor Complex 2 (PRC2) (Engreitz et al., 2016).

Page

The difference in structure could help explain the stability of XIST in females from embryonic cell to somatic cell and the instability in males. Collectively, this data suggests regulation of the L and S isoforms evolve through differentiation of a female organism.

Figure 2: Genomic origin of MALAT-1 is transcribed to form the MALAT-1 precursor RNA, and then two cleavage events occur whereby Rnase P and Rnase Z cleave the tRNAlike structure from the precursor. This results in a complete MALAT-1 transcript with a 3’ helix formation and a mascRNA. Based on (Yoshimoto et al., 2016)

The Regulation of MALAT1: a Cancer Precursor Another lncRNA Associated Lung

is Metastasis Adenocarcinoma

The proposed structure of MALAT1 includes a 3’ triple helix, allowing it to escape exonucleases and mature (Wilusz et al., 2012). However, before this structure is reached, it must be spliced by RNase P and Z to remove a tRNA-like structure from the MALAT1 transcript. Afterwards, the transcript is left to be able to associate with a small cytoplasmic RNA (mascRNA), as shown in Figure 2 (Yoshimoto et al., 2016). In this state, the MALAT1 ncRNA is ready to perform its variable functions in the cell. Before MALAT1 can regulate gene expression, it needs to be upregulated itself. Recently, it was discovered that TAR-DNA binding protein (Tdp-43), a protein that can bind to DNA and RNA, has the ability to bind to MALAT1 in the brain. A decrease in the amount of Tdp43 reduced the expression of MALAT1, suggesting that it could be a key factor in promoting MALAT1’s expression (Polymenidou et al., 2011). This has also been linked to the potential of MALAT1’s

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

However, XIST itself needs to be regulated to ensure random Xinactivation to occur. For random Xinactivation to occur, paternal imprinting needs to be reversed in the ICM (Augui et al., 2011). This is important as it allows the eutherian mammal to be a mosaic organism (Ohhata and Wutz, 2013). Tsix, another lncRNA, has the capacity to do this. Tsix is the anti-sense transcript to Xist, and will be monoallelically expressed to repress the ability of XIST as an epigenetic regulator by directing the methylation promoter. This is done by recruiting Dnmt3a as a methyltransferase, which can methylate a cytosine in the XIST promoter. In female differentiated somatic cells, the active X-chromosome will express Tsix, and the inactive chromosome will express XIST (Ohhata et al., 2015). However, this complex mechanism is still not clearly understood.

Transcript 1 (MALAT1). MALAT1 is an essential lncRNA involved in many regulatory pathways in the cell. For example, regulating alternative splicing and cell cycle genes like p53. It is 8kb in length and unlike XIST; it displays a high level of conservation across mammals and lower invertebrates (Gutschner et al., 2013). It was originally discovered as a ‘prognostic parameter’ for patients who have lung adenocarcinoma or squamous cell carcinoma (Ji et al., 2003). However, after further research, it was recognised as one of the first lncRNAs directly linked to cancer progression. This widely expressed lncRNA provides insights into how lncRNA can be exploited by the cell during homeostasis as well as in cancerous conditions. Thus, MALAT1 reveals the power of long non-coding RNAs as regulators of gene expression.

Page

regulation by rearranging the chromatin.

The final lncRNA to be discussed is Hox Antisense Intergenic RNA (HOTAIR). HOTAIR was discovered in 2007 by Chang et al. It was one of the first lncRNAs to be shown to work in a transmanner. HOTAIR plays a pivotal role in the developmental pathway, like XIST. It is expressed in the HOXC locus between HOXc11 and HOXc12, and works on the HOXD region as well as translocating to chromosome 2. HOX genes are extremely important as their expression leads to the developmental patterning of an organism. As HOTAIR has been discovered, another layer to of this regulation of patterning has been added (Mallo and Alonso, 2013). Not only has it be linked to development but in more recent years it has been linked to certain types of cancer too, for example, breast cancer (Cai et al., 2014). This makes for a lncRNA which acts in a double-edged sword fashion; crucial as a developmental regulator and as a cancer precursor. HOTAIR contains two exons and is 2.2kb in length. Developmentally, its role as an epigenetic regulator is to repress the HOXD locus. Similar to XIST, HOTAIR recruits the PCR2 complex to trimethylate chromatin at histone 3, lysine 27. It was shown in a study by Rinn et al. (2007) that knocking down HOTAIR led to the expression of the HOXD cluster that would have otherwise been repressed. These clusters lacked the methylation they would normally receive in the presence of HOTAIR. However, a study by Schorderet and Duboule (2011) reported that when they knocked down HOTAIR from mice cells there was no effect observed on the regulation of chromatin in HoxD in the mice. This suggests a discrepancy between the role of HOTAIR in human and mice

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

MALAT1 is upregulated in a variety of ways unique to each origin of the tumour cell. During neuroblastoma formation, oxytocin will upregulate MALAT1 by the binding cyclicAMP response element binding transcription factor to MALAT1â&#x20AC;&#x2122;s promotor (Koshimizu et al., 2010). On the other hand, in tumour cells originating from the bladder, transforming growth factor beta (TGFbeta) has been shown to regulate MALAT1 expression. This was discovered through recording expression levels of MALAT1 and epithelialmesenchymal transition markers. Epithelial-mesenchymal transition is the process through which the bladder cells turn cancerous. Through assaying these markers and MALAT1, they discovered that over-expression of MALAT1 is correlated with poor patient survival. This could imply that MALAT1 plays a key role promoting the progression of carcinoma. However, this study included only 95 patients. A larger study would be able to provide a better insight into the role of MALAT1 in cancer progression and would be needed to confirm these findings by Fan et al. (2014). Lastly, in non-small cell lung cancer cells (NSCLCs), a higher expression of MALT1 was observed when compared to the standard lung tissue. The study also observed that knockdowns of MALAT1 lead to decreased cell movement and invasion. This suggests regulation of gene expression by MALAT1 is critical for metastasis in lung cancer cells (Guo et al., 2015).

The Pattern Coordinator, turn Cancer Regulator: HOTAIR

Page

involvement in neurodegenerative diseases too. This is because Tdp-43 can accumulate in clusters which are known to contribute to diseases like Amyotrophic Lateral Sclerosis (Arai et al., 2006). Despite this proposed form of regulation, MALAT1 is upregulated differently as cells differentiate into a tumour and turn metastatic.

Discussion Having focused on three different lncRNAs, a variety of themes have been

One of the themes that have been recognised is the capacity of lncRNA to act as an initiator of epigenetic regulation. All three lncRNAs discussed have the ability to start a cascade of chromatin modifications, which have then suggested to be maintained by chromatin modifying proteins. Both HOTAIR and XIST pursue this by enlisting the polycomb protein, PCR2. However, Yang et al. (2011) also observed the interaction of PCR2 with MALAT1. This suggests a fundamental relationship between lncRNAs and polycomb proteins. Conversely, as discussed previously, this relationship has a vast amount of conflicting data. This has been most well observed in PCR2’s interactions with XIST. Furthermore, conflicting data has been cited between PCR2 and HOTAIR as well. A study by Portoso et al. (2017) observes the ability of HOTAIR to repress areas of the chromatin without the need for PCR2. The disparity in the role of PCR2 suggests a lack of understanding as to how lncRNAs work to recruit proteins and modify histones. Even so, lncRNAs are described at initiators of chromatin modification and maintenance, and this has been observed to be up-held by a variety of chromatinmodifying protein interactions, not just PCR2, which leads to another over-riding theme of ‘molecular scaffolds’.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

HOTAIR is also classed as an oncogenic gene. The over-expression of HOTAIR has been linked to an array of cancers. One study by Xu et al. (2013) revealed, through real-time PCR of HOTAIR, that it was expressed more in gastric cancer tissue than it was in non-cancerous in patient’s body. However, this study took samples from only 83 patients, meaning other studies would need to be conducted to establish if there is a correlation between a greater expression of HOTAIR being found in tumour cells. Other findings show that it is able to prevent the expression of tumour suppressor genes like HOX10, as well as metastatic suppressors like JAM2. In one study by Gupta et al. (2010), HOTAIR was overexpressed in MDA-MB-231 cell line which led to repression of JAM2. Subsequently, HOTAIR was knocked out resulting in an enhanced JAM2 expression. This suggests that HOTAIR can epigenetically regulate a key metastatic component in the cell.

revealed throughout this report. Currently there are a vast number of lncRNAs that have been identified which have limited data. However, comparisons between well researched lncRNAs could suggest that the available data could be used as a model for those without data. However, major differences have also been displayed in this report. This suggests there must also be a large amount of diversity and adaptations present in each lncRNA for them to serve their function within the cell.

Page

development. Similarly to XIST, HOTAIR has the ability to interact with the EHZ2 domain in the PCR2 complex allowing it to target it to the HOXD site. However, HOTAIR can also target another complex called LSD1. LSD1 has the ability to de-methylate lysine 4. HOTAIR can recruit these two separate complexes as it is broadly separated into two subdomains. The 5’ subdomain can recruit PRC2, whereas the 3’ subdomain will recruit LSD1. Thus, it has been proposed that HOTAIR acts as a molecular scaffold to bring these complexes together to silence HOXD and regulate gene expression (Tsai et al., 2010).

All three lncRNAs have the ability to interact with different proteins to form complexes, due to diversity in their function. For example, unlike the other lncRNAs, MALAT1 has the ability to interact with splicing factors. This is due to one of its key roles as a regulator of pre-mRNA splicing (Zong et al., 2011). However, in most cases where lncRNAs act as a regulator of gene expression, without the lncRNA present as an initiator, the multitude of proteins which make up a complex would not be formed. This is why lncRNAs are often described as a molecular scaffold. Xist has been shown to interact with 81 proteins by Chu et al. (2015). However, HOTAIR has been observed to interact with two major histone modifying proteins; PCR2 and LSD1. This suggests a difference inability of certain lncRNAs to interact with proteins, probably due to certain conserved sites located in the lncRNA. For example, XIST has a highly conserved RepA region, allowing interactions with PCR2. HOTAIR has also been seen to interact with a protein called Suz-Twelve. This allows HOTAIR to regulate gene expression in transmanner (Tsai 2010). This is another topic that has been alluded to; cis and trans-acting lncRNAs.

lncRNAs. Supporting this is the observation that Xist is also regulated by Tsix, the antisense lncRNA transcript of XIST.

The ability for lncRNAs to act both cis and trans across the genome is another important aspect of the regulation of gene expression by lncRNAs. Both MALAT1 and XIST work in cis, whereas HOTAIR works in a trans-manner. This difference in ability is suggested to be mediated by proteins which interact with lncRNA. Another trans-acting lncRNA is Jpx, which is transcribed from an active chromosome to promote transcript of XIST in the alternative X-chromosome in females (Vance and Potting, 2014). This could also imply that lncRNAs donâ&#x20AC;&#x2122;t just interact with protein but are also upregulated and interact with other

Declaration of Interests

The range of functions for which lncRNAs have been accounted for already in gene expression makes this relatively new field particularly exciting. The plethora of interactions that lncRNAs can take part in and govern plays a crucial role in their ability to be able to regulate gene expression. Without these interactions, it is highly debatable whether lncRNAs could truly fulfil their new found role as the epigenetic regulators of the cell. There is still much to be explored in the regulatory mechanisms upheld by lncRNAs and with thousands of RNA genes described, the majority of their functions are still unknown. However, a better understanding of the nature of these molecules will undoubtedly add further dimensions to gene expression, disease regulation and homeostatic mechanisms that are critical to the cell.

Acknowledgements The author would like to thank Dr Matthew Ronshaugen for overseeing the project.

The author declares no conflict of interests.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Page

Arai, T., Hasegawa, M., Akiyama, H., Ikeda, K., Nonaka, T., Mori, H., Mann, D., Tsuchiya, K., Yoshida, M., Hashizume, Y. and Oda, T., (2006). TDP43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochemical and biophysical research communications 351(3), 602-

Bibliography

Betancur, J. and Tomari, Y., (2015). Cryptic RNA-binding by PRC2 components EZH2 and SUZ12. RNA biology 12(9), 959-965. Brown, C.J.,Ballabio, A., Rupert JL, Lafreniere RG, Grompe M, Tonlorenzi R, Willard HF.,(1991). A gene from the region of the human X inactivation centre is expressed exclusively from the inactive X chromosome. Nature 349 (6304), 38. Cai, B., Song, X.Q., Cai, J.P. and Zhang, S., (2013). HOTAIR: a cancer-related long non-coding RNA. Neoplasma 61(4), 379-391. Cerase, A., Pintacuda, G., Tattermusch, A. and Avner, P., (2015). Xist localization and function: new insights from multiple levels. Genome biology 16(1), 166. Cerase, A., Smeets, D., Tang, Y.A., Gdula, M., Kraus, F., Spivakov, M., Moindrot, B., Leleu, M., Tattermusch, A., Demmerle, J. and Nesterova, T.B., (2014). Spatial separation of Xist RNA and polycomb proteins revealed by superresolution microscopy. Proceedings of the National Academy of Sciences 111(6), 2235-2240. Chu, C., Zhang, Q.C., Da Rocha, S.T., Flynn, R.A., Bharadwaj, M., Calabrese, J.M., Magnuson, T., Heard, E. and Chang, H.Y., (2015). Systematic discovery of Xist RNA binding proteins. Cell 161(2), 404-416. Crick, F.H.C., (1958). On protein synthesis. Symp. Soc. Exp. Biol. XII, 138–163.

Fan, Y., Shen, B., Tan, M., Mu, X., Qin, Y., Zhang, F. and Liu, Y., (2014). TGF-β– Induced Upregulation of malat1 Promotes Bladder Cancer Metastasis by Associating with suz12. Clinical Cancer Research 20(6),1531-1541. Guo, F., Guo, L., Li, Y., Zhou, Q. and Li, Z., (2015). MALAT1 is an oncogenic long non-coding RNA associated with tumor invasion in non-small cell lung cancer regulated by DNA methylation. International journal of clinical and experimental pathology 8(12), 15903. Gupta, R.A., Shah, N., Wang, K.C., Kim, J., Horlings, H.M., Wong, D.J., Tsai, M.C., Hung, T., Argani, P., Rinn, J.L. and Wang, Y., (2010). Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature 464(7291), 10711076. Gutschner, T., Hämmerle, M., Eißmann, M., Hsu, J., Kim, Y., Hung, G., Revenko, A., Arun, G., Stentrup, M., Groß, M. and Zörnig, M., (2013). The noncoding RNA MALAT1 is a critical regulator of the metastasis phenotype of lung cancer cells. Cancer research 73(3),1180-1189. Herriges, M.J., Swarr, D.T., Morley, M.P., Rathi, K.S., Peng, T., Stewart, K.M. and Morrisey, E.E., (2014). Long noncoding RNAs are spatially correlated with transcription factors and regulate lung development. Genes & development 28(12),1363-1379. Holley, R.W., Everett, G.A., Madison, J.T. and Zamir, A., (1965). Nucleotide sequences in the yeast alanine transfer

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Augui, S., Nora, E.P. and Heard, E., (2011). Regulation of X-chromosome inactivation by the X-inactivation centre. Nature Reviews Genetics 12(6), 429-442.

Engreitz, J.M., Ollikainen, N. and Guttman, M., (2016). Long non-coding RNAs: spatial amplifiers that control nuclear structure and gene expression. Nature Reviews Molecular Cell Biology 17(12), 756–770.

Page

611.

noncoding RNA, and thymosin β4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene 22(39), 8031-8041. Johnsson, P., Lipovich, L., Grandér, D. and Morris, K.V., (2014). Evolutionary conservation of long non-coding RNAs; sequence, structure, function. Biochimica et Biophysica Acta (BBA)-General Subjects 1840(3), 1063-1071. Koshimizu, T.A., Fujiwara, Y., Sakai, N., Shibata, K. and Tsuchiya, H., (2010). Oxytocin stimulates expression of a noncoding RNA tumor marker in a human neuroblastoma cell line. Life sciences 86(11), 455-460. Kung, J.T., Colognori, D. and Lee, J.T., (2013). Long noncoding RNAs: past, present, and future. Genetics 193(3), 651-669. Kutter, C., Watt, S., Stefflova, K., Wilson, M.D., Goncalves, A., Ponting, C.P., Odom, D.T. and Marques, A.C., (2012). Rapid turnover of long noncoding RNAs and the evolution of gene expression. PLoS Genet 8(7), 1002841. Law, J.A. and Jacobsen, S.E., (2010). Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nature Reviews Genetics 11(3), 204-220. Lee, J.T., (2011). Gracefully ageing at 50, X-chromosome inactivation becomes a paradigm for RNA and chromatin control. Nature reviews Molecular cell biology 12(12), 815-826. Lee, D.U. and Rao, A., (2004). Molecular analysis of a locus control region in the T

Leung, K.N. and Panning, B., (2014). Xinactivation: Xist RNA uses chromosome contacts to coat the X. Current Biology 24(2), R80-R82. Ma, M. and Strauss, W.M., (2005). Analysis of the Xist RNA isoforms suggests two distinctly different forms of regulation. Mammalian genome 16(6), 391-404. Mallo, M. and Alonso, C.R., (2013). The regulation of Hox gene expression during animal development. Development 140(19), 3951-3963. Memili, E., Hong, Y.K., Kim, D.H., Ontiveros, S.D. and Strauss, W.M., (2001). Murine Xist RNA isoforms are different at their 3′ ends: a role for differential polyadenylation. 266(1), 131-137.

Gene

Mercer, T.R. and Mattick, J.S., (2013). Structure and function of long noncoding RNAs in epigenetic regulation. Nature structural & molecular biology 20(3), 300-307. Nagano, T., Mitchell, J.A., Sanz, L.A., Pauler, F.M., Ferguson-Smith, A.C., Feil, R. and Fraser, P., (2008). The Air noncoding RNA epigenetically silences transcription by targeting G9a to chromatin. Science, 322(5908),17171720. Ohhata, T., Matsumoto, M., Leeb, M., Shibata, S., Sakai, S., Kitagawa, K., Niida, H., Kitagawa, M. and Wutz, A., (2015). Histone H3 lysine 36 trimethylation is established over the Xist promoter by antisense Tsix transcription and contributes to repressing Xist expression. Molecular

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Ji, P., Diederichs, S., Wang, W., Böing, S., Metzger, R., Schneider, P.M., Tidow, N., Brandt, B., Buerger, H., Bulk, E. and Thomas, M., (2003). MALAT-1, a novel

helper 2 cytokine gene cluster: a target for STAT6 but not GATA3. Proceedings of the National Academy of Sciences of the United States of America 101(45), 16010-16015.

Page

ribonucleic acid. Journal of Biological Chemistry 240(5), 2122-2128.

Okamoto, I., Otte, A.P., Allis, C.D., Reinberg, D. and Heard, E., (2004). Epigenetic dynamics of imprinted X inactivation during early mouse development. Science 303(5658), 644649. Okazaki Y, Furuno M, Kasukawa T, Adachi J, Bono H, Kondo S, Nikaido I, Osato N, Saito R, Suzuki H, Yamanaka I, Kiyosawa H, Yagi K, Tomaru Y, Hasegawa Y, Nogami A, Schönbach C, Gojobori T, Baldarelli R, Hill DP, Bult C, Hume DA, Quackenbush J, Schriml LM, Kanapin A, Matsuda H, Batalov S, Beisel KW, Blake JA, Bradt D, Brusic V, Chothia C, Corbani LE, Cousins S, Dalla E, Dragani TA, Fletcher CF, Forrest A, Frazer KS, Gaasterland T, Gariboldi M, Gissi C, Godzik A, Gough J, Grimmond S, Gustincich S, Hirokawa N, Jackson IJ, Jarvis ED, Kanai A, Kawaji H, Kawasawa Y, Kedzierski RM, King BL, Konagaya A, Kurochkin IV, Lee Y, Lenhard B, Lyons PA, Maglott DR, Maltais L, Marchionni L, McKenzie L, Miki H, Nagashima T, Numata K, Okido T, Pavan WJ, Pertea G, Pesole G, Petrovsky N, Pillai R, Pontius JU, Qi D, Ramachandran S, Ravasi T, Reed JC, Reed DJ, Reid J, Ring BZ, Ringwald M, Sandelin A, Schneider C, Semple CA, Setou M, Shimada K, Sultana R, Takenaka Y, Taylor MS, Teasdale RD, Tomita M, Verardo R, Wagner L, Wahlestedt C, Wang Y, Watanabe Y, Wells C, Wilming LG, Wynshaw-Boris A, Yanagisawa M, Yang I, Yang L, Yuan Z, Zavolan M, Zhu Y, Zimmer A, Carninci P, Hayatsu N, Hirozane-Kishikawa T, Konno H, Nakamura M, Sakazume N, Sato K, Shiraki T, Waki K, Kawai J,

Pennisi, E., (2012). ENCODE project writes eulogy for junk DNA. Science 337 (6099),1159-1161. Penny, G.D., Kay, G.F., Sheardown, S.A., Rastan, S. and Brockdorff, N., (1996). Requirement for Xist in X chromosome inactivation. Nature 379(6561),131. Plath, K., Mlynarczyk-Evans, S., Nusinow, D.A. and Panning, B., (2002). Xist RNA and the mechanism of X chromosome inactivation. Annual review of genetics 36(1), 233-278. Polymenidou, M., Lagier-Tourenne, C., Hutt, K.R., Huelga, S.C., Moran, J., Liang, T.Y., Ling, S.C., Sun, E., Wancewicz, E., Mazur, C. and Kordasiewicz, H., (2011). Long premRNA depletion and RNA missplicing contribute to neuronal vulnerability from loss of TDP-43. Nature neuroscience 14(4), 459-468. Portoso, M., Ragazzini, R., Brenčič, Ž., Moiani, A., Michaud, A., Vassilev, I., Wassef, M., Servant, N., Sargueil, B. and Margueron, R., (2017). PRC2 is dispensable

for

HOTAIR‐mediated

transcriptional repression. The EMBO Journal, 201695335. Rinn, J.L. and Chang, H.Y., (2012). Genome regulation by long noncoding RNAs. Annual review of biochemistry 81,145-166. Rinn, J.L., Kertesz, M., Wang, J.K., Squazzo, S.L., Xu, X., Brugmann, S.A.,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Ohhata, T. and Wutz, A., (2013). Reactivation of the inactive X chromosome in development and reprogramming. Cellular and Molecular Life Sciences 70(14), 2443-2461.

Aizawa K, Arakawa T, Fukuda S, Hara A, Hashizume W, Imotani K, Ishii Y, Itoh M, Kagawa I, Miyazaki A, Sakai K, Sasaki D, Shibata K, Shinagawa A, Yasunishi A, Yoshino M, Waterston R, Lander ES, Rogers J, Birney E, Hayashizaki Y, (2002). Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature 420(6915), 563-573.

Page

and cellular biology, 35(22), 3909-3920.

Goodnough, L.H., Helms, J.A., Farnham, P.J., Segal, E. and Chang, H.Y., (2007). Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129(7), 1311-1323.

Tsai, M.C., Manor, O., Wan, Y., Mosammaparast, N., Wang, J.K., Lan, F., Shi, Y., Segal, E. and Chang, H.Y., (2010). Long noncoding RNA as modular scaffold of histone modification complexes. Science 329(5992), 689-693.

Schorderet, P. and Duboule, D., (2011). Structural and functional differences in the long non-coding RNA hotair in mouse and human. PLoS Genet 7(5), 1002071.

Ulitsky, I., Shkumatava, A., Jan, C.H., Sive, H. and Bartel, D.P., (2011). Conserved function of lincRNAs in vertebrate embryonic development despite rapid sequence evolution. Cell 147(7),1537-1550.

Simon, M.D., Pinter, S.F., Fang, R., Sarma, K., Rutenberg-Schoenberg, M., Bowman, S.K., Kesner, B.A., Maier, V.K., Kingston, R.E. and Lee, J.T., (2013). High-resolution Xist binding maps reveal two-step spreading during Xchromosome inactivation. Nature 504(7480), 465-469. Spector, T. (2012) Identically Different: why you can change your genes. Great Britain: Weidenfeld and Nicolson, 35. Spurlock III, C.F., Tossberg, J.T., Guo, Y., Collier, S.P., Crooke III, P.S. and Aune, T.M., (2015). Expression and functions of long noncoding RNAs during human T helper cell differentiation. Nature communications 6, 6932.

Wilusz, J.E., JnBaptiste, C.K., Lu, L.Y., Kuhn, C.D., Joshua-Tor, L. and Sharp, P.A., (2012). A triple helix stabilizes the 3â&#x20AC;˛ ends of long noncoding RNAs that lack poly (A) tails. Genes & development 26(21), 2392-2407. Xu, Z.Y., Yu, Q.M., Du, Y.A., Yang, L.T., Dong, R.Z., Huang, L., Yu, P.F. and Cheng, X.D., (2013). Knockdown of long non-coding RNA HOTAIR suppresses tumor invasion and reverses epithelialmesenchymal transition in gastric cancer. Int J Biol Sci, 9(6), 587-597. Yang, L., Lin, C., Liu, W., Zhang, J., Ohgi, K.A., Grinstein, J.D., Dorrestein, P.C. and Rosenfeld, M.G., (2011). ncRNAand Pc2 methylation-dependent gene relocation between nuclear structures mediates gene activation programs. Cell 147(4), 773-788. Yoshimoto, R., Mayeda, A., Yoshida, M. and Nakagawa, S., (2016). MALAT1 long non-coding RNA in cancer. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms 1859(1), 192-199. Zhou, K.I., Parisien, M., Dai, Q., Liu, N., Diatchenko, L., Sachleben, J.R. and Pan, T., (2016). N 6-methyladenosine

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Sigova, A.A., Mullen, A.C., Molinie, B., Gupta, S., Orlando, D.A., Guenther, M.G., Almada, A.E., Lin, C., Sharp, P.A., Giallourakis, C.C. and Young, R.A., (2013). Divergent transcription of long noncoding RNA/mRNA gene pairs in embryonic stem cells. Proceedings of the National Academy of Sciences 110(8), 2876-2881.

Vance, K.W. and Ponting, C.P., (2014). Transcriptional regulatory functions of nuclear long noncoding RNAs. Trends in Genetics 30(8), 348-355.

Page

Siepel, A., Bejerano, G., Pedersen, J.S., Hinrichs, A.S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L.W., Richards, S. and Weinstock, G.M., (2005). Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome research, 15(8), 10341050.

modification in a long noncoding RNA hairpin predisposes its conformation to protein binding. Journal of molecular biology 428(5), 822-833.

322(5902), 750-

Zong, X., Tripathi, V. and Prasanth, K.V., (2011). RNA splicing control: yet another gene regulatory role for long nuclear noncoding RNAs. RNA biology 8(6), 968977.

Page

Zhao, J., Sun, B.K., Erwin, J.A., Song, J.J. and Lee, J.T., (2008). Polycomb proteins targeted by a short repeat RNA to the mouse X

chromosome. Science 756.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Membrane Structures Involved in Adult Stem Cell Regulation Portia Hollyoak*, Prof. Hilary Ashe (*portia.hollyoak@student.manchester.ac.uk) Faculty of Biology, Medicine and Health, The University of Manchester, U.K.

Introduction Stem cells have a unique ability to selfrenew and have the potential to differentiate into different cell types. They play an important role in the creation of organs in the embryo as well as in the regeneration of tissues in the adult body (Lin, 2003; Watt & Hogan, 2000; Spradling et al., 2001; Weissman, 2000). This regenerative capability allows the development of in vitro disease models to understand disease processes as well as the creation of treatments for

Stem cells can be divided into two main types: embryonic and adult. Embryonic stem cells are derived from the inner cell mass of blastocysts and are pluripotent; they are able to give rise to all adult cell types (Chambers & Smith, 2004; Thomson et al., 1998). On the other hand, adult stem cells are found in most tissues in the adult body and are more restricted in terms of potential, only being able to give rise to cells of multiple lineages (multipotent) or even just cells of one lineage (unipotent) and are therefore often tissue-specific (Fuchs et al., 2001; Rossant, 2004; Weissman, 2000). Despite the existence of stem cells being known about for a long time, only a few stem cell types have been characterised to date. This is mostly as the complexity and vastness of mammalian tissues hinders identification. The search in invertebrate model systems, on the other hand, has been successful in identifying several stem cell niches in Drosophila and Caenorhabditis elegans (reviewed in Li & Xie, 2005), so these are often used to study stem cell biology. Adult stem cells reside in tissues and function to replace cells lost within their tissue due to natural cell death (apoptosis) or injury and thus are important for tissue homeostasis and regeneration in the body (Li & Xie, 2005).

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The exchange of information between cells in the form of signals, over both long and short distances, is critical for multicellular life. Numerous developmental processes depend on cellcell signalling as well as the maintenance and function of adult tissues. Stem cells are the key players in the maintenance of tissues in the adult body and their behaviour can be regulated by signalling from their niche. Such stem cell-niche communication requires specificity and recent evidence suggests that this can be achieved via the extension of cellular membrane protrusions such as Cytonemes, Tunelling Nanotubes (TNTs), Primary Cilia and Microtubule (MT)-Nanotubes. Here, we review the contexts where cellular protrusions play a role in regulation of adult stem cell behaviour.

a wide range of diseases and injuries, including the construction of replacement organs.

Page

Abstract

However, in some cases, a combination of signals cannot entirely account for the specificity of cell-cell signalling. Therefore, there must be other ways by which it is achieved. Recently, membrane structures have been implicated as a one such route of highly specific signalling between cells (Buszczak et al., 2016). As signalling is critical for stem cell regulation, the following membrane structures have been associated with stem cell-niche signalling: Cytonemes, Tunnelling Nanotubes (TNTs), Primary Cilia, and Microtubule (MT)-Nanotubes. These structures differ in size, components, and the signals, which they transmit, but all allow selective transmission of signalling pathways. This review aims to present current knowledge of the role that these membrane structures play in stem cell regulation by reviewing published research.

Cytonemes Cytonemes were first identified in the Drosophila wing disc by Ramirez-Weber, F.A., and Kornberg, T.B. (1999), where they extended from wing disc cells and orientated uniformly toward the disc midline where decapentaplegic (Dpp) protein, a BMP signalling ligand, is expressed. This suggested that Dpp signalling may occur by a direct contact model instead of by simple diffusion, where Dpp-expressing cells secrete Dpp at the site of cytoneme contact and dispersion takes place in or on cytonemes. Thus, cytonemes were thought to mediate specific morphogen signalling and to make up for inadequate

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Signalling is defined as the ability of cells to communicate with each other and is carried out via countless mechanisms, which can be split into two broad categories: cell-cell contact dependent signalling and cell signalling via secreted molecules. Cell-cell contact-dependent signalling occurs mostly by membranebound signalling molecules and receptors but can also occur by other methods such as gap junctions. However, the majority of signalling occurs via secreted molecules over either short distance (paracrine) or long distance (endocrine). Regarding the signalling involved in stem cell regulation, it mostly involves membrane-bound signalling molecules and paracrine signalling. Each niche has a unique combination of signalling pathways, which are coordinated to regulate stem cell renewal, proliferation, and differentiation, although there are several signalling pathways which appear frequently in stem cell niches across species. The major signalling pathways are: the Janus kinase-signal transducers and activators of transcription (JAK-STAT), Wnt, Hedgehog (Hh), Bone Morphogenetic Protein (BMP) and Notch signalling pathways (Bausek, 2013; Stine & Matunis, 2013; Nusse, 2008; Petrova & Joyner, 2014; Shivdasani & Ingham,

2003). The majority of these signalling pathways function in a contextdependent manner, with the results of pathway activation varying from stem cell maintenance, to proliferation, to promotion of stem cell differentiation depending on the niche.

Page

This homeostatic function is maintained by a delicate balance between selfrenewal, proliferation and differentiation, which are regulated by a complicated network of intrinsic genetic programs modulated by extrinsic cues from their ‘niche’ (Spradling et al., 2001). The concept of a stem cell ‘niche’ was first proposed by Schofield almost 40 years ago (Schofield, 1978), and can be defined as the stem cells’ local microenvironment which is composed of surrounding cells, external signals and the extracellular matrix, and varies from niche to niche (Morrison et al., 2008; Li & Xie, 2005).

Interestingly, each subtype seems to be dedicated to transducing a single distinct morphogen pathway, such as Hh and BMP, by presenting only the receptors for a particular pathway on their membranes (Bilioni et al., 2013; Callejo et al., 2011; Roy & Kornberg, 2011; Bischoff et al., 2013; Roy et al., 2014; Kornberg & Roy, 2014a; b). Cytonemes may also prove to be a potential solution to how signalling pathways containing

Most research on cytonemes has focussed on their function within development in transducing morphogens. However, as morphogens are also found to influence adult stem cell niches, recent research has started to uncover the role of cytonemes in stem cell regulation. In the Drosophila ovary stem cell niche, there are 2-3 GSCs supported by three types of somatic niche cells: terminal filament cells (TFCs), cap cells (CpCs), and escort cells (ECs; Morrison et al., 2008). Several signalling pathways have been shown to be at play between these cells including Notch, JAK/Stat and BMP signalling, the latter of which is an important regulator within the niche and functions to promote self-renewal and repress differentiation of GSCs. It is therefore

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Figure 1: Cytonemes in cell-cell signalling. Cytonemes are long, actinbased extensions of the cell membrane, which present receptors, or ligands for a specific signalling pathway on their surface and in this way transduce cell-cell signalling.

insoluble proteins, such as Wnt, are transduced between cells (Port & Basler, 2010). Although, it is not fully understood how cytonemes select their targets, they have been observed extending towards a basic fibroblast growth factor (bFGF) gradient within in vitro Drosophila cell cultures which suggests a chemo-tactical guidance system (Ramírez-Weber & Kornberg, 1999). Another characteristic of cytonemes is their fragility; Cytonemes have proven difficult to detect for a long time due to their sensitivity to fixation, where they become stunted and misshapen in the process. Nowadays, there are several ways by which cytonemes can be reliably detected, such as labelling with cytoplasmic or membrane-bound GFP or with fluorescently labelled signalling receptors and cytoneme components, such as actin. Despite this, cytoneme detection is still hindered by problems such as fluorescence quenching, phototoxicity, compression of cytonemes during tissue preparation and the fact that most cytonemes do not lie in a single focal plane (Kornberg & Roy, 2014b).

Page

diffusion of ligands (Ramírez-Weber & Kornberg, 1999). Several types of cytonemes have now been identified in Drosophila such as in the wing, leg, eye imaginal discs and the ovary (reviewed in Kornberg & Roy, 2014b); they differ in shape and composition depending on their location but share many distinctive characteristics. In general, cytonemes are long cytoplasmic extensions that contact the membrane of a target cell without making a cytoplasmic connection (Sherer & Mothes, 2008). They are composed of tight bundles of actin filaments associated with other cytoskeletal proteins and have typical diameters of 0.2μm and lengths of up to 700μm (Ramírez-Weber & Kornberg, 1999). They extend from both the apical and basal surfaces of polarized cells (Hsiung et al., 2005), make synaptic contacts with target cells, and through these contacts, transduce morphogen signalling (Fig. 1).

As cytonemes are known to facilitate cellcell signalling, their long lengths suggest that a transport mechanism is required. Indeed, Snyder et al. (2015) showed that the carrier molecule Myosin X (MyoX) can travel along Lgr5-induced cytonemes. Furthermore, they also showed that GPCR signalling adaptor protein β-arrestin-2 (βarr2) translocated within cytonemes and interacted with MyoX. Overall, their data provides evidence for Lgr4 and Lgr5 being drivers of cytoneme formation and a mechanism whereby mammalian stem cells could be regulated by directional and compartmentalised signalling by cytonemes (Snyder et al., 2015). Despite these studies, however, little is known about the role of cytonemes in stem cell regulation and an effort should be made to expand exploration into in vivo mammalian tissues.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

The majority of cytoneme studies have been carried out using invertebrate cells whilst only a few have been carried out using those of vertebrates. One such study of the latter investigated the involvement of a subfamily of leucinerich G-protein-coupled receptor (Lgrs) in the formation of cytonemes from Human Embryonic Kidney (HEK) cells (Snyder et al., 2015). The particular subfamily of

Lgrs they investigated contains Lgrs4-6; Lgr5 is a Wnt pathway-associated Lgr that is a stem cell marker within many tissues whilst Lgr4 and Lgr6 are markers of stem and progenitor cell lineages (Hsu et al., 2000, 1998; Snyder et al., 2015). Snyder et al. (2015) showed that overexpression of Lgr4 and Lgr5 at the plasma membrane of HEK cells induced the formation of cell protrusions, which were often found directed towards the basolateral surface and branched when in contact with the substratum. These cell protrusions were determined to be cytonemes as they formed by a filopodial formation mechanism, exceeded lengths of 80μm, and contained actin and typical actin modified proteins (Hsiung et al., 2005; Ramírez-Weber & Kornberg, 1999; Snyder et al., 2015). Interestingly, the number and length of the cytonemes were dependent on the expression level of Lgr4 and Lgr5 at the plasma membrane.

Page

assumed to be under tight regulation. Indeed, Rojas-Ríos et al. (2012) revealed that the Hh signalling pathway, itself mediated by short cytonemes, regulates BMP signalling in the Drosophila ovarian GSC niche. They discovered that CpCs extend cytonemes adorned with Hh protein towards ECs, which register the signal and respond by expressing and secreting Drosophila BMP homologues and essential stem cell factors, Dpp and glass bottom boat (gbb). These factors are then detected by the stem cells, and promote self-renewal and repress differentiation. Disruption of actin polymerisation within CpCs resulted in a loss of these cytonemes and produced a significant decrease in the number of GSCs per niche. Furthermore, under conditions of low Hh signalling within the niche, CpCs extend up to 6-fold longer Hh-decorated cytonemes towards the signalling-deficient area of the niche in order to increase the range of Hh ligand spreading. Therefore, these results indicate cytonemes are important for transduction of the Hh signalling pathway and stem cell regulation within the female Drosophila GSC niche (RojasRíos et al., 2012). In contrast, the female GSC niche in the Earwig is structurally simple and differs from that of Drosophila. Cytonemes are seen to extend from ECs to the most posterior TF cell, but the function of these cytonemes and whether they are involved in GSC regulation is unknown (Tworzydlo et al., 2009).

Studies have established that TNTs provide intercellular transport of cellular components over long distances (Fig. 2; Gerdes et al., 2007), for example: organelles, such as mitochondria (Naphade et al., 2015; Onfelt et al., 2006; Wang & Gerdes, 2015; Islam et al., 2012; Vallabhaneni et al., 2012; Liu et al., 2014; Pasquier et al., 2013; Plotnikov et al., 2010; Ahmad et al., 2014), proteins, ions and small molecules (Guescini et al., 2012; Lou et al., 2012; Mi et al., 2011; Rolf et al., 2012; Thayanithy et al., 2014). Such trafficking of cargo within TNTs has been noted to occur unidirectionally and bidirectionally, which implies different mechanisms exist to control trafficking within TNTs in different cell, types (Sisakhtnezhad & Khosravi, 2015). Importantly, their conduit ability makes it an obvious mechanism for a broad spectrum of cell-cell communications. For

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

TNTs were first discovered extending from cultured rat pheochromocytoma PC12 cells (Rustom et al., 2004) and represent another type of cell protrusion involved in cell-cell signalling. In contrast to cytonemes, TNTs are thin, tubular membrane bridges that form between cells and create continuity between the cells’ cytoplasms, therefore providing a conduit for the transfer of surface membrane material as well as cytoplasmic components. They are not limited to forming between pairs of cells but often form large networks of interconnecting cells (Rustom et al., 2004; Watkins & Salter, 2005; Gerdes & Rustom, 2006). These specific types of cellular extension have since been found to be present in a variety of cell types in vitro (Rustom et al., 2004; Onfelt et al., 2006) and in vivo (Caneparo et al., 2011; Pyrgaki et al., 2010; Naphade et al., 2015; Chinnery et al., 2008) and differ widely in their properties but can be roughly classified into two types: ‘thin TNTs’ which have a diameter less than 0.7μm and are mostly composed of Factin, and ‘thick TNTs’ which have a diameter greater than 0.7μm and are composed of both F-actin and microtubules (Onfelt et al., 2006). Interestingly, different types of TNTs exist within the same cell type and are interconvertible depending on the physiological context (Wang & Gerdes, 2015). In addition, their lengths vary widely and can reach up to several cell diameters (Rustom et al., 2004), in the majority of cases appearing as unbranched straight lines (Rustom et al., 2004; Onfelt et al., 2006; Koyanagi et al., 2005). Moreover, TNTs are transient structures and their lifetimes alter depending on the cell type, ranging from a few minutes to a few hours (Bukoreshtliev et al., 2009; Gurke et al., 2008). Like cytonemes, TNT structure

shows a sensitivity to prolonged light exposure, mechanical stress and chemical fixation (Rustom et al., 2004). The formation of TNTs between cells takes only several minutes but can occur by two distinct actin-polymerisation based mechanisms. The first studies on TNTs in PC12 cells illustrated that they formed by an outgrowth of filopodia-like protrusions towards a neighbouring cell. When one protrusion made contact, this resulted in TNT formation and remodifying along with degeneration of other protrusions. The directed growth of TNTs to target cells suggested a chemotactical guidance system, which is supported by evidence of gradientdirected growth in cytonemes (Rustom et al., 2004; Ramírez-Weber & Kornberg, 1999). The second mechanism observed is the formation of TNTs by the divergence of attached cells which retain the membrane channel and elongate it in the process of migration (Ramírez-Weber & Kornberg, 1999).

Page

Tunelling Nanotubes (TNTs)

Only a few studies, however, have explored their involvement in adult stem cell regulation. Gillette et al. (2009) investigated the interactions between Haematopoietic stem-progenitor cells (HSPCs) and osteoblasts in the bone marrow niche. It was already previously known that osteoblasts provide HSPCs with signals for their proliferation and maintenance, however the mechanisms by which these signals were targeted to HSPCs were unclear. They revealed that TNTs form between osteoblasts and HSPCs and mediate the transfer of signalling endosomes into osteoblasts causing an increase in secretion of

Primary Cilia Cilia and flagella are highly conserved, eukaryotic, microtubule-based organelles that extend from the cell surface (Singla & Reiter, 2006). The Primary Cilium is an immotile, sensory cilia subtype, which is present on the majority of mammalian cell types during the growth arrest stage of the cell cycle (Wheatley, 1995). They consist of a microtubule-based skeleton (axoneme) that extends from the cell basal body surrounded by a membrane, which is continuous with the plasma

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

example, TNTs have been implicated in tumour development and metastasis (He et al., 2011; Lou et al., 2012; Thayanithy et al., 2014), the progression of neurodegenerative diseases and the transfer of pathogens (Gousset et al., 2009; Sowinski et al., 2008; Dubey & Ben-Yehuda, 2011; Roberts et al., 2015). Additionally, TNTs have been shown to play an important role in signalling during embryogenic development (Caneparo et al., 2011), the cellular stress response (Wang et al., 2011; Wang & Gerdes, 2015), and cellular differentiation and reprogramming (Koyanagi et al., 2005; Rolf et al., 2012; Takahashi et al., 2013).

Page

Figure 2: Tunnelling Nanotubes (TNTs) in cell-cell signalling. TNTs are thin, freely hovering channels between cells, which are continuous with the cytoplasm and provide intercellular transport of cellular components such as organelles, ions and vesicles as well as membrane components.

stromal-derived factor (SDF-1), a chemokine responsible for HSC trafficking to the bone marrow (Gillette et al., 2009). Transport of other membranous components also took place across TNTs such as CD133, a stem cell marker with unknown function (Fargeas et al., 2006). This interaction via TNTs therefore may provide a channel for signalling which indirectly influences the trafficking, proliferation and maintenance of HSPCs (Gillette et al., 2009). Following from this discovery, a recent study has found that human HSPCs and leukemic cells form TNTs when cultured on primary mesenchymal stromal cells or specific extracellularmatrix-based substrata, and that cell migration is the primary driver for TNT formation. Like the previous study, it was noted that a stem cell marker, CD133, is transferred between the cells by selective transport within TNTs using motor proteins (Reichert et al., 2016). As CD133 is a marker for cells with stem cell-like properties and the fact that membrane â&#x20AC;&#x2DC;raftsâ&#x20AC;&#x2122; are important in signal transduction, it could be hypothesised that membrane rafts containing CD133 and other stem cell-specific signalling pathways could be exchanged between cells bridged by TNTs (Fargeas et al., 2006), potentially conferring stem-cell like properties to the receiving cell.

In addition, mutations in cilia proteins have been shown to cause rare, recessive human disorders known as ciliopathies, which are characterised by

Due to their ability to transduce signals from the external cellular environment, they are an obvious potential mechanism for stem cell regulation. Indeed, research has implicated the primary cilium in the regulation of the Hh (Huangfu et al., 2003; Liu et al., 2005; May et al., 2005; Huangfu & Anderson, 2005; Haycraft et al., 2005) and Wnt signalling pathway (Simons et al., 2005; Ross et al., 2005), which are known to be involved in stem cell function (Ahn et al., 2005; Lai et al., 2002; Karhadkar et al., 2004), proliferation and differentiation (Logan & Nusse, 2004; Clevers, 2006). However, the majority of the research published has focussed on stem cell regulation within development (Awan et al., 2009; Kiprilov et al., 2008; Han et al., 2008; Han & Alvarez-Buylla, 2010). Nonetheless, several studies have investigated primary cilia in the regulation of adult stem cells. In mouse postnatal epidermal tissues, loss of primary cilia by conditional knockout of the genes IFT88 and Kif3a, which are required for proper cilia structure and function, resulted in disruption of normal skin homeostasis due to activation of Shh signalling. Several phenotypes were observed such as tissue hyperplasia, abnormal proliferation and a reduction in the number of cells retaining the BrdU label, suggesting a disruption of stem cell maintenance. Overall, the data indicates that primary cilia on epidermal cells are involved in the epidermal stress response and normal tissue homeostasis (Croyle et al., 2011). Other studies performed using IFT88 siRNA-mediated knockdown have determined that primary cilia are necessary for the chemically induced differentiation of human mesenchymal

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Figure 3. Primary Cilia in cell-cell signalling. Primary cilia are composed of a microtubule skeleton (axoneme) surrounded by a membrane which is continuous with the cell membrane. Primary cilia display receptors, ion channels and effector proteins that are specific to the tissue and function to transduce mechanical and biochemical signals from the surrounding cellular environment by the transport of signalling pathway components along the cilium.

developmental abnormalities (Tobin & Beales, 2009; Baker & Beales, 2009; Badano et al., 2006; Gerdes et al., 2009).

Page

membrane of the cell. Primary cilia are usually observed using an electron microscope, or by labelling with fluorescent Îą-tubulin antibodies, and on average have a diameter of 0.2Îźm and a length of 0.5Îźm (Wheatley, 1995; Wheatley et al., 1996). The intraflagellar transport (IFT) machinery, a system of motor proteins and adaptors carries out assembly and maintenance of primary cilia (Rosenbaum & Witman, 2002). The IFT machinery also carries out the bidirectional transport of signalling pathway components along the cilium (reviewed in Goetz & Anderson, 2010), as the function of primary cilia is to transduce mechanical and biochemical signals from the surrounding cellular environment to control a wide variety of cellular processes during development and tissue homeostasis (Davenport & Yoder, 2005; Pazour & Witman, 2003). Evidence for this particular function has been provided by numerous reports of cilia displaying receptors, ion channels and effector proteins specific to the functions of the tissue in which their cells are situated (Fig. 3; Christensen et al., 2007).

The final type of cell protrusion in this review, MT-nanotubes, functions solely to mediate selective signalling towards GSCs. So far only a single publication has uncovered them, in the Drosophila testis where GSCs give rise to sperm. In the testis, around nine GSCs are connected to a cluster of somatic cells, called â&#x20AC;&#x2DC;the hubâ&#x20AC;&#x2122;, which secretes several ligands that promote GSC self-renewal: the cytokinelike ligand Unpaired (Upd), and BMP signalling ligands Dpp and Gbb (Tulina & Matunis, 2001; Kiger et al., 2001; Shivdasani & Ingham, 2003; Kawase et al., 2004). GSCs usually divide

As they are MT-based and cell-cycle dependent, it was a possibility that they could be primary cilia. However, this was not the case as the MT-nanotubes were not necessarily associated with the basal body, lacked acetylated microtubules and were sensitive to fixation (Inaba et al., 2015); This sensitivity is a feature that is shared with tunnelling nanotubes (Davis & Sowinski, 2008) and cytonemes (RamĂrez-Weber & Kornberg, 1999), probably explaining why MT-nanotubes have escaped previous detection. MTnanotubes were found to contain components found in primary cilia and cytonemes such as IFT-B complex proteins which are required for assembly and transport (Goetz & Anderson, 2010), Dlic, a dynein intermediate chain required for retrograde transport (Perrone et al., 2003) and klp10A, a MTdepolymerizing kinesin which suppresses cilia formation (Kobayashi et al., 2011). RNAi-mediated knockdown of the former two proteins resulted in fewer and shorter MT-nanotubes, and knockdown of the latter significantly increased the thickness of MTnanotubes. Thus, these results show that primary cilia proteins localize to MTnanotubes and regulate their formation (Inaba et al., 2015).

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Microtubule (MT)-Nanotubes

asymmetrically, giving one daughter cell which remains attached to the hub and retains its stem cell identity, and another daughter cell which is displaced from the hub and starts to differentiate (Yamashita et al., 2003). MT-based structures, which were subsequentlynamed MT-Nanotubes, were seen extending from GSCs and orientating uniformly towards the hub. These protrusions were seen in all stages of the cell cycle, except for mitosis and were not just found singularly; around half of GSCs displayed multiple MTnanotubes per cell (Inaba et al., 2015).

Page

stem cells (hMSCs) along with the transduction of mechanical signalling (Tummala et al., 2010; Hoey et al., 2012). The involvement of primary cilia in driving differentiation is also conserved in human adipose-derived stem cells (hASCs), where three of the key components of primary cilia are critical for hASC osteogenic lineage specification. In particular, it was found that IFT88 protein knockdown (KD) increased hASC proliferation, which suggests that removal of the cilium may allow the hASCs to remain in a more proliferative state (Bodle et al., 2013). Most recently, McMurray et al. (2013) investigated the effect of cilia length and Wnt signalling on hMSC differentiation. They found that cultivating MSCs on grooves produced longer cilia and down regulated their response to Wnt, supressing proliferation; however, disrupting cilia formation by siRNAmediated KD of Ift88 restored proliferation in MSCs even when cultured on the grooves. Therefore, these findings establish that regulation of cilia structure and function adjusts the cellular response to Wnt and in turn, stem cell differentiation or proliferation (McMurray et al., 2013).

In other species, such as the milkweed bug (Oncopeltus fasciatus), GSCs have also been documented extending

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

explain GSC maintenance, other studies have revealed that certain extracellular matrix proteins also function to maintain GSCs by restricting Upd diffusion and sequestering Dpp in the niche (Harrison et al., 1998; Guo & Wang, 2009; Hayashi et al., 2009; Zheng et al., 2011). Future studies will be required to determine whether MT-nanotube and ECM proteins act independently or collaboratively to maintain GSCs. Despite having similar reproductive functions, there are striking similarities and differences between the male and female Drosophila GSC niches in terms of composition and signalling pathways (Spradling et al., 2001). As previously explained, the female ovarian GSC niche contains five to seven nondividing somatic CpCs that anchor two or three GSCs and stimulate their reception of Dpp, a GSC maintenance signal (Song et al., 2002; Xie et al., 1998). Upon division of a GSC, one daughter remains associated with the CpCs, retaining the stem cell fate whilst the other is displaced away from the niche and as a result, starts to differentiate. Interestingly, unpublished research from the Ashe lab has hinted at the presence of MT-nanotubes in the female Drosophila GSC niche. Using YGP tagged Tkv, puncta were observed to be located within the CpC regions, even though Tkv was under a GSC-specific driver. Expression of GFP tagged tubulin under a GSC-specific driver further confirmed the presence of these MTnanotubes by permitting their visualisation. Further work will need to be undertaken to confirm if these MTnanotubes are analogous to those in the testis, if similar genes are required for their formation, and how these nanotubes interact with their environment.

Page

Inaba et al. (2015) then tried to determine the function of these MTnanotubes. As they extended from GSCs to the hub, they hypothesised that MTnanotubeswere involved in GSC-niche communication via the BMP signalling pathway. Indeed, they found that the BMP receptor Thickveins (Tkv) localised within the MT-nanotubes as puncta and seemed to be transported along the MTnanotubes in the direction of the hub. Furthermore, they confirmed that Tkv receptors that localised on MT-nanotubes were ligand-bound, implying that activation of BMP signalling occurs on and also could be transduced by MTnanotubes. This hypothesis was further supported by the following evidence: fewer Tkv puncta in the hub area were seen along with a decrease in Dpp pathway activity in GSCs when MTnanotubes were shortened whilst conversely, the number of puncta and the responsiveness of GSCs to Dpp increased when the width of MT-nanotubes was enlarged. In addition, and most interestingly, it was revealed that BMP proteins and their receptor were necessary and sufficient for the formation of MT-nanotubes. Therefore, a model can be created in which MTnanotubes are required for the transport of Tkv to the hub to bind secreted Dpp to activate BMP signalling in GSCs, yet rather paradoxically, BMPs are required for MT-nanotube formation. Overall, these results indicate that MT-nanotubes extend from GSCs into the hub to mediate BMP signalling and promote GSC self-renewal (Fig. 4). In this way, the self-renewal signals secreted by the Hub can be selectively received by GSCs whilst the differentiating daughter cells (typically lacking MT-nanotubules) can be prevented from picking up the required signal threshold for selfrenewal due to distance (Inaba et al., 2015). Despite this elegant model to

Adult stem cells function to replace cells in tissues lost by apoptosis and injury (Li & Xie, 2005). This regenerative ability is maintained by a delicate balance between self-renewal and differentiation, which are regulated by intrinsic cues from the cell’s genetics and extrinsic cues from their niche (Spradling et al., 2001). These extrinsic cues often take the form of signalling proteins presented or secreted from surrounding cells and despite much research on their function, little is known about how they are specifically targeted to stem cells. Research has revealed that membrane structures can be used as a route of highly specific signalling between stem cells and their niche (Buszczak et al., 2016), and this review has aimed to present the role that several types play in stem cell regulation. Cytonemes are long, actin-based, cell membrane extensions, which transduce specific morphogens by presenting receptors specific for a particular signalling pathway on their surface (Roy et al., 2011). These structures have been shown to be involved in regulating stem cell maintenance in the Drosophila ovarian GSC niche (Rojas-Ríos et al., 2012) and in transporting signalling pathway components in HEK cells (Snyder et al., 2015). TNTs, on the other hand, are thin channels, which bridge the cytoplasms of two connecting cells allowing the transfer of cytoplasmic components such as organelles and vesicles (Sherer & Mothes, 2008). They have been detected bridging HSPCs and osteoblasts and could potentially provide a channel for signalling that influences the trafficking, proliferation and maintenance of HSPCs (Gillette et al., 2009). In addition, TNTs have also been found between HSPCs and leukemic cells, possibly allowing the transfer of

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Figure 4: MT-Nanotubes mediate GSC-niche signalling. In the Drosophila testis, GSCs are connected to a cluster of somatic cells called ‘the hub’, which produces Dpp, a signal received by the GSCs and promotes self-renewal. However, Dpp signalling is not activated in the differentiating daughter cell, the gonioblast. Inaba et al. (2015) report that this selective signalling is achieved by the use of MT-nanotubes which extend from GSCs, present the Dpp receptor Tkv and thus mediate Dpp signalling exclusively between the GSC and hub cells. The gonioblasts do not extend MT-nanotubes and due to distance, they do not receive the required signal threshold to promote self-renewal.

Conclusion

Page

projections towards their niche, a cluster of apical cells, their equivalent to the hub cells in Drosophila (Schmidt & Dorn, 2004). These projections vary in their diameter but are generally thicker than typical filopodia and have unique formation dynamics. The authors proposed that these projections, like MTnanotubes, may function to mediate signal transduction between the GSCs and their niche (Schmidt & Dorn, 2004). However, this has yet to be confirmed. In a more distantly related species, Caenorhabditis elegans, the mesenchymal distal tip cell (DTC) provides the niche for GSCs and it has been observed extending multiple cellular process, which intercalate between germ cells (Byrd et al., 2014). The function of these processes remain unknown but several hypotheses have been put forward, such as delivering Notch signalling to GSCs or anchoring the GSCs to the distal tip. Further work needs to be undertaken to clarify the functions of both these types of protrusions, determine their components, and identify whether they are functionally or morphologically similar to MT-nanotubes.

References Ahmad, T., Mukherjee, S., Pattnaik, B., Kumar, M., Singh, S., Rehman, R., Tiwari, B.K., Jha, K.A., Barhanpurkar, A.P., Wani, M.R., Roy, S.S., Mabalirajan, U., Ghosh, B. & Agrawal, A. (2014) Miro1 regulates intercellular mitochondrial transport & enhances mesenchymal stem cell rescue efficacy. EMBO Journal, 33: 994–1010. Ahn, S., Joyner, A.L., Nakada, D., Pineda, A., Burgess, R.J., Vue, T.Y., Johnson, J.E., Morrison, S.J., Ahn, S., Joyner, A., Arnold, K., Sarkar, A., Yram, M., Polo, J., Bronson, R., Sengupta, S., Seandel, M., Geijsen, N., Hochedlinger, K. et al. (2005) In vivo analysis of quiescent adult neural stem cells responding to Sonic hedgehog. Nature, 437: 894–897. Awan, A., Oliveri, R.S., Jensen, P.L., Christensen, S.T. & Andersen, C.Y. (2009) Immunoflourescence and mRNA Analysis of Human Embryonic Stem Cells (hESCs) Grown Under Feeder-Free Conditions. In 195–210. Badano, J.L., Mitsuma, N., Beales, P.L. & Katsanis, N. (2006) The ciliopathies: an emerging class of human genetic disorders. Annu Rev Genomics Hum Genet, 7: 125–148. Baker, K. & Beales, P.L. (2009) Making sense of cilia in disease: The human ciliopathies. American Journal of Medical Genetics, Part C: Seminars in Medical Genetics, 151: 281– 295. Bausek, N. (2013) JAK-STAT signaling in stem cells and their niches in Drosophila. JAK-STAT, 2: e25686. Bilioni, A., Sánchez-Hernández, D., Callejo, A., Gradilla, A.-C., Ibáñez, C., Mollica, E., Carmen Rodríguez-Navas, M., Simon, E. & Guerrero, I. (2013) Balancing Hedgehog, a retention and release equilibrium given by Dally, Ihog, Boi and shifted/DmWif. Developmental Biology, 376: 198–212.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

It is evident that this review raises numerous remaining unanswered questions, which require additional research to be undertaken to clarify the role membrane structures play in adult stem cell regulation. Future work should aim to elucidate the molecular cargo of each membrane structure, their formation dynamics, guidance systems, mechanisms of cell-cell signalling, and how they interact with the extracellular matrix, among others. In particular, an effort should be made to investigate the presence and function of membrane structures within stem cell niches in vivo, in order to confirm that these structures naturally form and carry out a function. The field would also benefit if specific definitions, criteria and terminology of each membrane structure could be established as often morphological and cytoskeletal characteristics are shared between structures. However, this may suggest that membrane structures are not distinct and are interconvertible (Wang & Gerdes, 2015). Additional work is required to compare structures under different conditions and to determine if recategorisation is needed. As knowledge

of stem cell regulation by membrane structures advances, it will permit development of stem cell applications and therapies, which have the potential to treat countless injuries and diseases including cancer, and thus will have a major impact on worldwide health.

Page

components, which confer stem-cell like properties (Reichert et al., 2016). Another membrane structure, primary cilia, are immotile, sensory cilia which transduce mechanical and biochemical signals from the external cellular environment (Satir et al., 2010). Research has implicated primary cilia in the homeostasis of the epidermis (Croyle et al., 2011), in differentiation of hASCs and hMSCs (Bodle et al., 2013; Tummala et al., 2010; Hoey et al., 2012; McMurray et al., 2013). Finally, MT-nanotubes, mediate Dpp signalling exclusively between GSCs and hub cells in the Drosophila testis (Inaba et al., 2015), although similar structures have been uncovered in other niches (Schmidt & Dorn, 2004; Byrd et al., 2014).

Bukoreshtliev, N. V., Wang, X., Hodneland, E., Gurke, S., Barroso, J.F. V & Gerdes, H.H. (2009) Selective block of tunneling nanotube (TNT) formation inhibits intercellular organelle transfer between PC12 cells. FEBS Letters, 583: 1481–1488. Buszczak, M., Inaba, M. & Yamashita, Y.M. (2016) Signaling by Cellular Protrusions: Keeping the Conversation Private. Trends in Cell Biology, 26: 526–534. Byrd, D.T., Knobel, K., Affeldt, K., Crittenden, S.L., Kimble, J., Lander, A., Kimble, J., Clevers, H., Fuchs, E., Montarras, D., Jones, D., Wagers, A., Oatley, J., Brinster, R., Lehmann, R., Morrison, S., Spradling, A., Kimble, J., White, J. et al. (2014) A DTC Niche Plexus Surrounds the Germline Stem Cell Pool in Caenorhabditis elegans Ed. D. J. Reiner. PLoS ONE, 9: e88372. Callejo, A., Bilioni, A., Mollica, E., Gorfinkiel, N., Andrés, G., Ibáñez, C., Torroja, C., Doglio, L., Sierra, J. & Guerrero, I. (2011) Dispatched mediates Hedgehog basolateral release to form the long-range morphogenetic gradient in the Drosophila wing disk epithelium. Proceedings of the National Academy of Sciences of the United States of America, 108: 12591–8. Caneparo, L., Pantazis, P., Dempsey, W. & Fraser, S.E. (2011) Intercellular bridges in vertebrate gastrulation. PLoS ONE, 6: e20230. Chambers, I. & Smith, A. (2004) Self-renewal of teratocarcinoma and embryonic stem cells. Oncogene, 23: 7150–7160. Chinnery, H.R., Pearlman, E. & McMenamin, P.G. (2008) Cutting Edge: Membrane Nanotubes In Vivo: A Feature of MHC Class II+ Cells in the Mouse Cornea. Journal of Immunology, 180: 5779–5783.

Clevers, H. (2006) Wnt/beta-Catenin Signaling in Development and Disease. Cell, 127: 469–480. Croyle, M.J., Lehman, J.M., O’Connor, A.K., Wong, S.Y., Malarkey, E.B., Iribarne, D., Dowdle, W.E., Schoeb, T.R., Verney, Z.M., Athar, M., Michaud, E.J., Reiter, J.F. & Yoder, B.K. (2011) Role of epidermal primary cilia in the homeostasis of skin and hair follicles. Development, 138: 1675–1685. Davenport, J.R. & Yoder, B.K. (2005) An incredible decade for the primary cilium: a look at a once-forgotten organelle. American journal of physiology. Renal physiology, 289: 1159–1169. Davis, D.M. & Sowinski, S. (2008) Membrane nanotubes: dynamic long-distance connections between animal cells. Nature Reviews Molecular Cell Biology, 9: 431–436. Dubey, G.P. & Ben-Yehuda, S. (2011) Intercellular nanotubes mediate bacterial communication. Cell, 144: 590–600. Fargeas, C.A., Fonseca, A. V, Huttner, W.B. & Corbeil, D. (2006) Prominin-1 (CD133): from progenitor cells to human diseases. Future Lipidology, 1: 213–225. Fuchs, E., Merrill, B.J., Jamora, C. & Dasgupta, R. (2001) At the Roots of a NeverEnding Cycle. Developmental Cell, 1: 13–25. Gerdes, H.-H. & Rustom, A. (2006) Tunneling Nanotubes. In Cell-Cell Channels. Springer, New York, 200–207. Gerdes, H.H., Bukoreshtliev, N. V. & Barroso, J.F. V (2007) Tunneling nanotubes: A new route for the exchange of components between animal cells. FEBS Letters, 581: 2194–2201. Gerdes, J.M., Davis, E.E., Katsanis, N., Abdelkhalek, H.B., Beckers, A., SchusterGossler, K., Pavlova, M.N., Burkhardt, H., Lickert, H., Rossant, J., Reinhardt, R., Schalkwyk, L.C., Müller, I., al., et, Adler, P.N., Zhu, C., Stone, D., Afzelius, B.A., Arts, H.H. et al. (2009) The Vertebrate Primary Cilium in Development, Homeostasis, and Disease. Cell, 137: 32–45. Gillette, J.M., Larochelle, A., Dunbar, C.E. & Lippincott-Schwartz, J. (2009) Intercellular

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Bodle, J.C., Rubenstein, C.D., Phillips, M.E., Bernacki, S.H., Qi, J., Banes, A.J. & Loboa, E.G. (2013) Primary Cilia: The Chemical Antenna Regulating Human AdiposeDerived Stem Cell Osteogenesis Ed. A. Asakura. PLoS ONE, 8: e62554.

Christensen, S.T., Pedersen, L.B., Schneider, L. & Satir, P. (2007) Sensory Cilia and integration of signal transduction in human health and disease. Traffic, 8: 97–109.

Page

Bischoff, M., Gradilla, A.-C., Seijo, I., Andrés, G., Rodríguez-Navas, C., González-Méndez, L. & Guerrero, I. (2013) Cytonemes are required for the establishment of a normal Hedgehog morphogen gradient in Drosophila epithelia. Nature Cell Biology, 15: 1269– 1281.

Gousset, K., Schiff, E., Langevin, C., Marijanovic, Z., Caputo, A., Browman, D.T., Chenouard, N., de Chaumont, F., Martino, A., Enninga, J., Olivo-Marin, J.-C., Männel, D. & Zurzolo, C. (2009) Prions hijack tunnelling nanotubes for intercellular spread. Nature Cell Biology, 11: 328–336. Guescini, M., Leo, G., Genedani, S., Carone, C., Pederzoli, F., Ciruela, F., Guidolin, D., Stocchi, V., Mantuano, M., Borroto-Escuela, D.O., Fuxe, K. & Agnati, L.F. (2012) Microvesicle and tunneling nanotube mediated intercellular transfer of g-protein coupled receptors in cell cultures. Experimental Cell Research, 318: 603–613. Guo, Z. & Wang, Z. (2009) The glypican Dally is required in the niche for the maintenance of germline stem cells and short-range BMP signaling in the Drosophila ovary. Development (Cambridge, England), 136: 3627–3635. Gurke, S., Barroso, J.F. V. & Gerdes, H.-H. (2008) The art of cellular communication: tunneling nanotubes bridge the divide. Histochemistry and Cell Biology, 129: 539– 550. Han, Y.-G. & Alvarez-Buylla, A. (2010) Role of primary cilia in brain development and cancer. Current opinion in neurobiology, 20: 58–67. Han, Y.-G., Spassky, N., Romaguera-Ros, M., Garcia-Verdugo, J.-M., Aguilar, A., Schneider-Maunoury, S. & Alvarez-Buylla, A. (2008) Hedgehog signaling and primary cilia are required for the formation of adult neural stem cells. Nature Neuroscience, 11: 277–284. Harrison, D.A., McCoon, P.E., Binari, R., Gilman, M. & Perrimon, N. (1998) Drosophila unpaired encodes a secreted protein that activates the JAK signaling pathway. Genes & Development, 12: 3252–3263. Hayashi, Y., Kobayashi, S. & Nakato, H. (2009) Drosophila glypicans regulate the germline stem cell niche. The Journal of cell biology, 187: 473–80.

He, K., Shi, X., Zhang, X., Dang, S., Ma, X., Liu, F., Xu, M., Lv, Z., Han, D., Fang, X. & Zhang, Y. (2011) Long-distance intercellular connectivity between cardiomyocytes and cardiofibroblasts mediated by membrane nanotubes. Cardiovascular Research, 92: 39– 47. Hoey, D.A., Tormey, S., Ramcharan, S., O’Brien, F.J. & Jacobs, C.R. (2012) Primary cilia-mediated mechanotransduction in human mesenchymal stem cells. Stem Cells, 30: 2561–2570. Hsiung, F., Ramírez-Weber, F.-A., Iwaki, D.D. & Kornberg, T.B. (2005) Dependence of Drosophila wing imaginal disc cytonemes on Decapentaplegic. Nature, 437: 560–563. Hsu, S.Y., Kudo, M., Chen, T., Nakabayashi, K., Bhalla, A., van der Spek, P.J., van Duin, M. & Hsueh, A.J.W. (2000) The Three Subfamilies of Leucine-Rich RepeatContaining G Protein-Coupled Receptors (LGR): Identification of LGR6 and LGR7 and the Signaling Mechanism for LGR7. Molecular Endocrinology, 14: 1257–1271. Hsu, S.Y., Liang, S.-G. & Hsueh, A.J.W. (1998) Characterization of Two LGR Genes Homologous to Gonadotropin and Thyrotropin Receptors with Extracellular Leucine-Rich Repeats and a G ProteinCoupled, Seven-Transmembrane Region. Molecular Endocrinology, 12: 1830–1845. Huangfu, D. & Anderson, K. V (2005) Cilia and Hedgehog responsiveness in the mouse. Proceedings of the National Academy of Sciences of the United States of America, 102: 11325–11330. Huangfu, D., Liu, A., Rakeman, A.S., Murcia, N.S., Niswander, L. & Anderson, K. V. (2003) Hedgehog signalling in the mouse requires intraflagellar transport proteins. Nature, 426: 83–87. Inaba, M., Buszczak, M. & Yamashita, Y.M. (2015) Nanotubes mediate niche-stem-cell signalling in the Drosophila testis. Nature, 523: 329–332. Islam, M.N., Das, S.R., Emin, M.T., Wei, M., Sun, L., Westphalen, K., Rowlands, D.J.,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Goetz, S.C. & Anderson, K. V. (2010) The primary cilium: a signalling centre during vertebrate development. Nature Reviews Genetics, 11: 331–344.

Haycraft, C.J., Banizs, B., Aydin-Son, Y., Zhang, Q., Michaud, E.J. & Yoder, B.K. (2005) Gli2 and Gli3 localize to cilia and require the intraflagellar transport protein polaris for processing and function. PLoS genetics, 1: e53.

Page

transfer to signalling endosomes regulates an ex vivo bone marrow niche. Nature Cell Biology, 11: 303–311.

Li, L. & Xie, T. (2005) Stem cell niche: structure and function. Annual Review of Cell and Developmental Biology, 21: 605– 631. Lin, H. (2003) Stem cells: To be and not to be. Nature, 425: 353–355.

Karhadkar, S.S., Steven Bova, G., Abdallah, N., Dhara, S., Gardner, D., Maitra, A., Isaacs, J.T., Berman, D.M. & Beachy, P.A. (2004) Hedgehog signalling in prostate regeneration, neoplasia and metastasis. Nature, 431: 707–712.

Liu, A., Wang, B. & Niswander, L.A. (2005) Mouse intraflagellar transport proteins regulate both the activator and repressor functions of Gli transcription factors. Development, 132: 3103–3111.

Kawase, E., Wong, M.D., Ding, B.C. & Xie, T. (2004) Gbb/Bmp signaling is essential for maintaining germline stem cells and for repressing bam transcription in the Drosophila testis. Development, 131: 1365– 1375.

Liu, K., Ji, K., Guo, L., Wu, W., Lu, H., Shan, P. & Yan, C. (2014) Mesenchymal stem cells rescue injured endothelial cells in an in vitro ischemia-reperfusion model via tunneling nanotube like structure-mediated mitochondrial transfer. Microvascular Research, 92: 10–18.

Kiger, A.A., Jones, D.L., Schulz, C., Rogers, M.B. & Fuller, M.T. (2001) Stem cell selfrenewal specified by JAK-STAT activation in response to a support cell cue. Science, 294: 2542–2545.

Logan, C.Y. & Nusse, R. (2004) The Wnt Signalling Pathway in Development and Disease. Annual Review of Cell and Developmental Biology, 20: 781–810.

Kobayashi, T., Tsang, W.Y., Li, J., Lane, W. & Dynlacht, B.D. (2011) Centriolar Kinesin Kif24 Interacts with CP110 to Remodel Microtubules and Regulate Ciliogenesis. Cell, 145: 914–925. Kornberg, T.B. & Roy, S. (2014a) Communicating by touch - neurons are not alone. Trends in Cell Biology, 24: 370–376. Kornberg, T.B. & Roy, S. (2014b) Cytonemes as specialized signaling filopodia. Development, 141: 729–736. Koyanagi, M., Brandes, R.P., Haendeler, J., Zeiher, A.M. & Dimmeler, S. (2005) Cell-tocell connection of endothelial progenitor cells with cardiac myocytes by nanotubes: a novel mechanism for cell fate changes? Circulation Research, 96: 1039–1041. Lai, K., Kaspar, B.K., Gage, F.H. & Schaffer, D. V. (2002) Sonic hedgehog regulates adult neural progenitor proliferation in vitro and in vivo. Nature Neuroscience, 6: 21–27.

Lou, E., Fujisawa, S., Morozov, A., Barlas, A., Romin, Y., Dogan, Y., Gholami, S., Moreira, A.L., Manova-Todorova, K. & Moore, M.A.S. (2012) Tunneling nanotubes provide a unique conduit for intercellular transfer of cellular contents in human malignant pleural mesothelioma Ed. P.-C. Yang. PLoS ONE, 7: e33093. May, S.R., Ashique, A.M., Karlen, M., Wang, B., Shen, Y., Zarbalis, K., Reiter, J., Ericson, J. & Peterson, A.S. (2005) Loss of the retrograde motor for IFT disrupts localization of Smo to cilia and prevents the expression of both activator and repressor functions of Gli. Developmental Biology, 287: 378–389. McMurray, R.J., Wann, A.K.T., Thompson, C.L., Connelly, J.T., Knight, M.M., Kim, S., Schneider, L., Zhu, D., Shi, S., Wang, H., Liao, K., Ezratty, E.J., Caspary, T., Larkins, C.E., Anderson, K. V., Lancaster, M.A., Schroth, J., Gleeson, J.G., Neugebauer, J.M. et al. (2013) Surface topography regulates wnt signaling through control of primary cilia structure in mesenchymal stem cells. Scientific Reports, 3: 351–60. Mi, L., Xiong, R., Zhang, Y., Yang, W., Chen, J.-Y. & Wang, P.-N. (2011) Microscopic observation of the intercellular transport of CdTe quantum dot aggregates through tunneling-nanotubes. Journal of

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Kiprilov, E.N., Awan, A., Desprat, R., Velho, M., Clement, C.A., Byskov, A.G., Andersen, C.Y., Satir, P., Bouhassira, E.E., Christensen, S.T. & Hirsch, R.E. (2008) Human embryonic stem cells in culture possess primary cilia with hedgehog signaling machinery. The Journal of Cell Biology, 180: 897–904.

Page

Quadri, S.K., Bhattacharya, S. & Bhattacharya, J. (2012) Mitochondrial transfer from bone-marrow–derived stromal cells to pulmonary alveoli protects against acute lung injury. Nature Medicine, 18: 759– 765.

Naphade, S., Sharma, J., Gaide Chevronnay, H.P., Shook, M.A., Yeagy, B.A., Rocca, C.J., Ur, S.N., Lau, A.J., Courtoy, P.J. & Cherqui, S. (2015) Brief reports: Lysosomal crosscorrection by hematopoietic stem cell-derived macrophages via tunneling nanotubes. Stem Cells, 33: 301–309. Nusse, R. (2008) Wnt signaling and stem cell control. Cell Research, 18: 523–527. Onfelt, B., Nedvetzki, S., Benninger, R.K.P., Purbhoo, M.A., Sowinski, S., Hume, A.N., Seabra, M.C., Neil, M.A.A., French, P.M.W. & Davis, D.M. (2006) Structurally Distinct Membrane Nanotubes between Human Macrophages Support Long-Distance Vesicular Traffic or Surfing of Bacteria. The Journal of Immunology, 177: 8476–8483. Pasquier, J., Guerrouahen, B.S., Al Thawadi, H., Ghiabi, P., Maleki, M., Abu-Kaoud, N., Jacob, A., Mirshahi, M., Galas, L., Rafii, S., Le Foll, F. & Rafii, A. (2013) Preferential transfer of mitochondria from endothelial to cancer cells through tunneling nanotubes modulates chemoresistance. Journal of Translational Medicine, 11: 94. Pazour, G.J. & Witman, G.B. (2003) The vertebrate primary cilium is a sensory organelle. Current Opinion in Cell Biology, 15: 105–110. Perrone, C.A., Tritschler, D., Taulman, P., Bower, R., Yoder, B.K. & Porter, M.E. (2003) A novel dynein light intermediate chain colocalizes with the retrograde motor for intraflagellar transport at sites of axoneme assembly in Chlamydomonas and mammalian cells. Molecular Biology of the Cell, 14: 2041–2056. Petrova, R. & Joyner, A.L. (2014) Roles for Hedgehog signaling in adult organ homeostasis and repair. Development, 141: 3445–3457.

Port, F. & Basler, K. (2010) Wnt Trafficking: New Insights into Wnt Maturation, Secretion and Spreading. Traffic, 11: 1265–1271. Pyrgaki, C., Trainor, P., Hadjantonakis, A.K. & Niswander, L. (2010) Dynamic imaging of mammalian neural tube closure. Developmental Biology, 344: 941–947. Ramírez-Weber, F.A. & Kornberg, T.B. (1999) Cytonemes: Cellular processes that project to the principal signaling center in Drosophila imaginal discs. Cell, 97: 599–607. Reichert, D., Scheinpflug, J., Karbanova, J., Freund, D., Bornhauser, M. & Corbeil, D. (2016) Tunneling nanotubes mediate the transfer of stem cell marker CD133 between hematopoietic progenitor cells. Experimental hematology, 44: 1092–1112. Roberts, K.L., Manicassamy, B. & Lamb, R.A. (2015) Influenza A virus uses intercellular connections to spread to neighboring cells. Journal of Virology, 89: 1537–1549. Rojas-Ríos, P., Guerrero, I., González-Reyes, A., Morrison, S.J., Spradling, A.C., Scadden, D.T., Traiffort, E., Angot, E., Ruat, M., Brabletz, S., Schmalhofer, O., Brabletz, T., Mandal, L., Martinez-Agosto, J.A., Evans, C.J., Hartenstein, V., Banerjee, U., Krzemien, J., Dubois, L. et al. (2012) Cytoneme-Mediated Delivery of Hedgehog Regulates the Expression of Bone Morphogenetic Proteins to Maintain Germline Stem Cells in Drosophila Ed. T. Kornberg. PLoS Biology, 10: e1001298. Rolf, H.J., Niebert, S., Niebert, M., Gaus, L., Schliephake, H. & Wiese, K.G. (2012) Intercellular transport of Oct4 in mammalian cells: A basic principle to expand a stem cell niche? PLoS ONE, 7: e32287. Rosenbaum, J.L. & Witman, G.B. (2002) Intraflagellar transport. Nature Reviews Molecular Cell Biology, 3: 813–825. Ross, A.J., May-Simera, H., Eichers, E.R., Kai, M., Hill, J., Jagger, D.J., Leitch, C.C., Chapple, J.P., Munro, P.M., Fisher, S., Tan, P.L., Phillips, H.M., Leroux, M.R., Henderson, D.J., Murdoch, J.N., Copp, A.J., Eliot, M.-M., Lupski, J.R., Kemp, D.T. et al.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Morrison, S.J., Spradling, A.C., Adams, G.B., Scadden, D.T., Chabner, K.T., Alley, I.R., Olson, D.P., Szczepiorkowski, Z.M., Poznansky, M.C., Kos, C.H., Pollak, M.R., Brown, E.M., Ahn, S., Joyner, A.L., Arai, F., Hirao, A., Ohmura, M., Sato, H., Matsuoka, S. et al. (2008) Stem cells and niches: mechanisms that promote stem cell maintenance throughout life. Cell, 132: 598– 611.

Plotnikov, E.Y., Khryapenkova, T.G., Galkina, S.I., Sukhikh, G.T. & Zorov, D.B. (2010) Cytoplasm and organelle transfer between mesenchymal multipotent stromal cells and renal tubular cells in co-culture. Experimental Cell Research, 316: 2447–2455.

Page

Biomaterials and Nanobiotechnology, 2: 172– 179.

Roy, S., Hsiung, F. & Kornberg, T.B. (2011) Specificity of Drosophila cytonemes for distinct signaling pathways. Science, 332: 354–358. Roy, S., Huang, H., Liu, S. & Kornberg, T.B. (2014) Cytoneme-Mediated ContactDependent Transport of the Drosophila Decapentaplegic Signaling Protein. Science, 343: 1244624. Roy, S. & Kornberg, T.B. (2011) Direct Delivery Mechanisms of Morphogen Dispersion. Science Signaling, 4: pt8. Rustom, A., Saffrich, R., Markovic, I., Walther, P. & Gerdes, H.-H. (2004) Nanotubular highways for intercellular organelle transport. Science, 303: 1007–1010. Satir, P., Pedersen, L.B. & Christensen, S.T. (2010) The Primary Cilium at a glance. Journal of Cell Science, 123: 499–503. Schmidt, E.D. & Dorn, A. (2004) Structural polarity and dynamics of male germline stem cells in the milkweed bug (Oncopeltus fasciatus). Cell and Tissue Research, 318: 383–394. Schofield, R. (1978) The relationship between the spleen colony-forming cell and the haemopoietic stem cell. Blood cells, 4: 7–25. Sherer, N.M. & Mothes, W. (2008) Cytonemes and tunneling nanotubules in cell–cell communication and viral pathogenesis. Trends in Cell Biology, 18: 414–420. Shivdasani, A.A. & Ingham, P.W. (2003) Regulation of stem cell maintenance and transit amplifying cell proliferation by tgfbeta signaling in Drosophila spermatogenesis. Current Biology, 13: 2065– 2072. Simons, M., Gloy, J., Ganner, A., Bullerkotte, A., Bashkurov, M., Krönig, C., Schermer, B., Benzing, T., Cabello, O.A., Jenny, A., Mlodzik, M., Polok, B., Driever, W., Obara, T. & Walz, G. (2005) Inversin, the gene product mutated in nephronophthisis type II, functions as a molecular switch between Wnt

Singla, V. & Reiter, J.F. (2006) The Primary Cilium as the Cell’s Antenna: Signaling at a Sensory Organelle. Science, 313: 629–633. Sisakhtnezhad, S. & Khosravi, L. (2015) Emerging physiological and pathological implications of tunneling nanotubes formation between cells. European Journal of Cell Biology, 94: 429–443. Snyder, J.C., Rochelle, L.K., Marion, S., Lyerly, H.K., Barak, L.S. & Caron, M.G. (2015) Lgr4 and Lgr5 drive the formation of long actin-rich cytoneme-like membrane protrusions. Journal of Cell Science, 128: 1230–1240. Song, X., Zhu, C.-H., Doan, C. & Xie, T. (2002) Germline Stem Cells Anchored by Adherens Junctions in the Drosophila Ovary Niches. Science, 296:. Sowinski, S., Jolly, C., Berninghausen, O., Purbhoo, M.A., Chauveau, A., Köhler, K., Oddos, S., Eissmann, P., Brodsky, F.M., Hopkins, C., Önfelt, B., Sattentau, Q. & Davis, D.M. (2008) Membrane nanotubes physically connect T cells over long distances presenting a novel route for HIV-1 transmission. Nature Cell Biology, 10: 211– 219. Spradling, A., Drummond-Barbosa, D. & Kai, T. (2001) Stem cells find their niche. Nature, 414: 98–104. Stine, R.R. & Matunis, E.L. (2013) JAKSTAT signaling in stem cells. Advances in experimental medicine and biology, 786: 247– 267. Takahashi, A., Kukita, A., Li, Y., Zhang, J., Nomiyama, H., Yamaza, T., Ayukawa, Y., Koyano, K. & Kukita, T. (2013) Tunneling nanotube formation is essential for the regulation of osteoclastogenesis. Journal of Cellular Biochemistry, 114: 1238–1247. Thayanithy, V., Dickson, E.L., Steer, C., Subramanian, S. & Lou, E. (2014) Tumorstromal cross talk: Direct cell-to-cell transfer of oncogenic microRNAs via tunneling nanotubes. Translational Research, 164: 359–365. Thomson, J.A., Itskovitz-Eldor, J., Shapiro, S.S., Waknitz, M.A., Swiergiel, J.J., Marshall, V.S. & Jones, J.M. (1998) Embryonic Stem Cell Lines Derived from Human Blastocysts. Science, 282: 1827.

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Rossant, J. (2004) Embryonic Stem Cells in Perspective. Handbook of Stem Cells xxi– xxiii.

signaling pathways. Nature Genetics, 37: 537–543.

Page

(2005) Disruption of Bardet-Biedl syndrome ciliary proteins perturbs planar cell polarity in vertebrates. Nature Genetics, 37: 1135– 1140.

Tobin, J.L. & Beales, P.L. (2009) The nonmotile ciliopathies. Genetics in Medicine, 11: 386–402. Tulina, N. & Matunis, E. (2001) Control of stem cell self-renewal in Drosophila spermatogenesis by JAK-STAT signaling. Science, 294: 2546–2549. Tummala, P., Arnsdorf, E.J. & Jacobs, C.R. (2010) The Role of Primary Cilia in Mesenchymal Stem Cell Differentiation: A Pivotal Switch in Guiding Lineage Commitment. Cellular and Molecular Bioengineering, 3: 207–212. Tworzydlo, W., Kloc, M. & Bilinski, S.M. (2009) Female germline stem cell niches of earwigs are structurally simple and different from those of Drosophila melanogaster. Journal of Morphology, 271: 634–640.

J., Dickinson, L.., Lehmann, R., Brand, A.., Perrimon, N., Brook, W.., Cohen, S.., Brummel, T. et al. (1998) decapentaplegic is essential for the maintenance and division of germline stem cells in the Drosophila ovary. Cell, 94: 251–260. Yamashita, Y.M., Jones, D.L. & Fuller, M.T. (2003) Orientation of asymmetric stem cell division by the APC tumor suppressor and centrosome. Science, 301: 1547–1550. Zheng, Q., Wang, Y., Vargas, E. & DiNardo, S. (2011) magu is required for germline stem cell self-renewal through BMP signaling in the Drosophila testis. Developmental Biology, 357: 202–210.

Vallabhaneni, K.C., Haller, H. & Dumler, I. (2012) Vascular Smooth Muscle Cells Initiate Proliferation of Mesenchymal Stem Cells by Mitochondrial Transfer via Tunneling Nanotubes. Stem Cells and Development, 21: 3104–3113. Wang, X. & Gerdes, H.-H. (2015) Transfer of mitochondria via tunneling nanotubes rescues apoptotic PC12 cells. Cell Death and Differentiation, 22: 1181–1191. Wang, Y., Cui, J., Sun, X. & Zhang, Y. (2011) Tunneling-nanotube development in astrocytes depends on p53 activation. Cell Death and Differentiation, 18: 732–742. Watkins, S.C. & Salter, R.D. (2005) Functional connectivity between immune cells mediated by tunneling nanotubules. Immunity, 23: 309–318. Watt, F.M. & Hogan, B.L. (2000) Out of Eden: stem cells and their niches. Science, 287: 1427–1430. Weissman, I.L. (2000) Stem Cells: Units of Development, Units of Regeneration, and Units in Evolution. Cell, 100: 157–168.

Xie, T., Spradling, A.C., Arora, K., Dai, H., Kazuko, S.., Jamal, J., O’Connor, M.., Letsou, A., Warrior, R., Baker, D., Wang, C., Morre,

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017

Page

Wheatley, D.N., Wang, a M. & Strugnell, G.E. (1996) Expression of primary cilia in mammalian cells. Cell biology International, 20: 73–81.

Wheatley, D.N. (1995) Primary Cilia in Normal and Pathological Tissues. Pathobiology, 63: 222–238.

88 Page

Manchester Undergraduate Journal of Biological Sciences | vol. 1, July 2017