CONTENTS International Microbiology (2016) 19:133-182 ISSN (print): 1139-6709. e-ISSN: 1618-1095 www.im.microbios.org
Volume 19, Number 3, September 2016
RESEARCH REVIEW
Jiménez J, Bru S, Ribeiro MPC, Clotet J Phosphate: from stardust to eukaryotic cell cycle control
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RESEARCH ARTICLES
Yaish MW, Al-Harrasi I, Alansari AS, Al-Yahyai R, Glick BR The use of high throughput DNA sequence analysis to assess the endophytic microbiome of date palm roots grown under different levels of salt stress Mora FX, Avilés-Reyes RX, Guerrero-Latorre L, Fernández-Moreira E Atypical enteropathogenic Escherichia coli (aEPEC) in children under five years old with diarrhea in Quito (Ecuador) Fernández-Martínez MA, Pointing SB, Pérez-Ortega S, Arróniz-Crespo M, Green TGA, Rozzi R, Sancho LG, de los Ríos A Functional ecology of soil microbial communities along a glacier forefield in Tierra del Fuego (Chile) Chan YS, Khoo KS, Sit NW Investigation of twenty selected medicinal plants from Malaysia for anti-Chikungunya virus activity PIONEERS IN MICROBIOLOGY: Paulina Beregoff (1902–1989), Colombia
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Journal Citations Reports 5-year Impact Factor of International Microbiology is 2,17. The journal is covered in several leading abstracting and indexing databases, including the following ones: Agricultural & Environmental Biotechnology Abstracts; ASFA/Aquatic Sciences & Fisheries Abstracts; BIOSIS; CAB Abstracts; Chemical Abstracts; SCOPUS; Current Contents/Agriculture, Biology & Environmental Sciences; EBSCO; EMBASE/Elsevier Bibliographic Databases; Food Science & Technology Abstracts; ICYT/CINDOC; IBECS/ BNCS; ISI Alerting Services; MEDLINE/Index Medicus; Latindex; MedBioWorld; PubMed; SciELO-Spain; Science Citation Index Expanded; SciSearch.
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Front cover legends Upper left. Papillomavirus, the causal agent of several human diseases, some of them developing as cancers. Several Spanish groups perform outstanding research on this virus and on the illnesses that it causes. The definitive link between the presence of the papillomavirus and cervix cancer in women was established by Colombian physician and researcher Nubia Muñoz, in Lyon, France. (Magnification, 600,000×)
Center. View of the Pia Glacier. The glacier is located at the southern slope of Cordillera Darwin in Tierra del Fuego (Chile) and has an impressive icefront—of more than 100 m high—falling directly into the waters of Pia Bay, inside the Alberto de Agostini National Park. Its forefield is a good place to study the chronosequence of plant colonization and soil evolution due to the climatic characteristics of geographical region. (Photo: www.australis.com)
Lower right. Macrophotograph of a growing colony of the mold Aspergillus sp. The colony is growing in a Petri dish. Note the whitish, button -like structure formed by a drop of liquid secreted by the sector on the left. Photo by Rubén Duro, Center for Microbiological Research (CIM), Barcelona. (Magnification, 1.4×)
Upper right. Dark field micrograph of the cyanobacterium Chroococcus sp., isolated from a freshwater pond. Note the envelope surrounding the paired cells. Photo by Rubén Duro, Center for Microbiological Research (CIM), Barcelona. (Magnification, 1500×) Lower left. Dark field micrograph of the predator ciliate Pseudoprorodon sp., isolated from a freshwater lake. Note the pieces of food inside the large digestive vacuoles and the small ciliate being engulfed near the cytostome of the cell on the left. Photo by Rubén Duro, Center for Microbiological Research (CIM), Barcelona. (Magni fication, 3000×)
Back cover: Pioneers in Microbiology Paulina Beregoff (1902–1989), Colombia Paulina Beregoff was the first woman to obtain a degree in medicine in Colombia. She was born in 1902 in Kiev—by then a city of the Russian Empire—, in an aristocratic family of Jewish descent. Due to the political situation in her country, she was educated in the United States, where, in 1921, she graduated in Bacteriology and Parasitology and Pharmacy and Chemistry at the University of Pennsylvania. She started working at the laboratory of Pathology of that university and became a member of the Rivas Bacteriological Society of the University of Pennsylvania. In 1922, the Dean of the School of Medicine of the University of Cartagena, Colombia, asked the University of Pennsylvania for an expert in tropical diseases, including yellow fever. This disease was a great concern in Cartagena due to the high mortality rates it caused and because of the implications on the image of the city, which was a major commercial and harbor center. The University needed a qualified advisor that could also train local physicians, and the University of Pennsylvania chose Beregoff for that task. Once in Cartagena, she had to identify an epidemic outbreak that had been causing many fatalities, mostly among indigenous peoples living in the Magdalena River shores. Colombian phys icians were not familiar with symptoms and causal agents of diseases such as yellow fever, typhoid fever and malaria, but thought that the epidemic outbreak could be due to one of them. Beregoff sent samples of cultures
from corpses of people killed by the disease to be analyzed at the University of Pennsylvania. The disease turned out to be fiebre tifomalárica and not simply malaria, as they first had considered. Beregoff thought that the infection depended mostly on the deficiencies or resistance of the immune system and proposed that physicians should work to prevent the disease. Once she had achieved her task, she intended to go back to Philadelphia to study medicine at Temple University, but she was asked to remain in Cartagena, where she could also study medicine. In 1922 she enrolled at the University of Cartagena under special conditions. Due to her previous studies and qualification, she could be waived the first two years of the studies of medicine. She set up the first laboratories of bacteriology and parasitology in Cartagena, with microscopes and other equipment donated by the University of Pennsylvania. Her thesis director recognized her great contribution, she having been able to differentiate the various species of Laveran’s haematozoa, to observe the treponema causing yaws, to find the Piroplasma Donovani, the parasite of KalaAzar (visceral leishmaniasis) in the blood, and having been the first to isolate the “typhoid bacillus”, confirming thus the presence of typhoid fever in town. She could also to properly perform the Wassermann technique on syphilis. The fact that she was a foreign woman and the she had had some privileges in her medicine studies was criticized by some people. In 1933 she married bacteriologist Arthur Stanley Gillow and they moved to Canada. Since then she signed her publications as Pauline Beregoff-Gillow. After her husband’s death, in 1964, she returned to Colombia and dedicated his husband’s legacy to set up a foundation under his name that should work on preventive medicine. She died on September 20, 1989 and left her fortune to the foundation.
Front cover and back cover design by MBerlanga & RGuerrero
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RESEARCH REVIEW International Microbiology 19(3):133-141 (2016) doi:10.2436/20.1501.01.271. ISSN (print): 1139-6709. e-ISSN: 1618-1095
www.im.microbios.org
Phosphate: from stardust to eukaryotic cell cycle control Javier Jiménez, Samuel Bru, Mariana P.C. Ribeiro, Josep Clotet* Department of Basic Sciences, School of Medicine and Health Sciences, Universitat Internacional de Catalunya, Barcelona, Spain Received 30 July 2016 · Accepted 15 August 2016
Summary. Phosphorus is a pivotal element in all biochemical systems: it serves to store metabolic energy as ATP, it forms the backbone of genetic material such as RNA and DNA, and it separates cells from the environment as phospholipids. In addition to this “big hits”, phosphorus has recently been shown to play an important role in other important processes such as cell cycle regulation. In the present review, we briefly summarize the biological processes in which phosphorus is involved in the yeast Saccharomyces cerevisiae before discussing our latest findings on the role of this element in the regulation of DNA replication in this eukaryotic model organism. We describe both the role of phosphorus in the regulation of G1 progression by means of the Cyclin Dependent Kinase (CDK) Pho85 and the stabilization of the cyclin Cln3, as well as the role of other molecule composed of phosphorus–the polyphosphate–in cell cycle progression, dNTP synthesis, and genome stability. Given the eminent role played by phosphorus in life, we outline the future of phosphorus in the context of one of the main challenges in human health: cancer treatment. [Int Microbiol 19(3):133-141 (2016)] Keywords: Saccharomyces cerevisiae · Pho85 · cyclin · polyphosphate · cell cycle
Introduction Cosmic material brought to the Earth by meteorites, often referred to as stardust, forms the basis of one of the hypotheses used to explain how phosphorus became biologically available on the early Earth. Phosphorus’ career, so to speak, has thus continued at meteoric speed, making it a biological star: its major tasks include storing metabolic energy in the form of ATP, providing the backbone of genetic material, and separating cells from the environment as phospholipids. In addition, it is involved in the post-translational modifica-
Corresponding author: J. Clotet E-mail: jclotet@uic.cat *
tion of proteins, it plays a role in enzymatic cofactors, and it takes part in cell signalling, among other processes. Phosphorus is a mineral element that presents poor solubility, absence of a volatile phase, and low reactivity, factors that make it difficult to understand how phosphorylated molecules (ancestors of the plethora of organic molecules containing phosphorus) first started to form and become an important element in the prebiotic world [32]. The phosphorus that formed the first phosphorylated biomolecules had to have come from a mineral source, primordial molecules which evolved to produce the large variety of phosphomolecules present in modern Earth [24,32]. How did phosphorus enter into biomolecules? A hypothesis to answer this question involves a meteoritic phosphide source—the mineral schreibersite—[9,44,45]. Recent findings have shown that
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phorus needed for nucleotides or phospholipids to exist, or for proteins to be phosphorylated, it brings about, in essence, the regulation of basically all biochemical reactions that allow cells to work and to be. Once phosphorus is biologically available in the form of phosphate (orthophosphate, to be precise), it can be interiorised, utilised and stored by cells, from archaea to eukaryotes. Cells have developed intricate systems for phosphate intake from the environment, using systems that range from transport by transmembrane channels to scavenging by degrading molecules from the medium in which phosphate is found, or even sourcing internal reservoirs (see below). As for the other nutrients, signalling pathways are in charge of keeping the intracellular homeostasis of phosphate by impinging on intake and storage systems. All these mechanisms have been very well elucidated in the yeast S. cerevisiae (see [54] for an excellent review on phosphate metabolism).
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schreibersite could have influenced phosphorus chemistry on early Earth because it is capable of spontaneously phosphorylate organic compounds [46]. Certainly, there are other findings supporting less poetic hypotheses for the bioavailability of phosphorus, namely the “warm little pond” intuitively predicted by Charles Darwin in which a simple evaporitic environment rich in urea could promote thermodynamically favoured phosphorus solubility [10], or other environmental situations that may have been plausible on ancient Earth [18]. It should be mentioned that this review takes some literary licence with the stardust hypothesis, and not a firm position, within the context of the very interesting field of the prebiotic chemistry, field which is absolutely alien to the authors. Whatever the case, phosphorus travelled to become biologically available and took the throne in a kingdom dominated by carbon, hydrogen, and nitrogen. Not only is phos-
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Fig. 1. The phosphate sensing and response–or Pho–pathway. The Pho pathway is led by the Cyclin Dependent Kinase (CDK) Pho85. Pho85 associates with its cyclin Pho80 and the CDK inhibitor (CDKI) Pho81, which is active when phosphate is limited, inactivating the CDK. The transcription factor Pho4 is therefore dephosphorylated and accumulates in the nucleus, inducing the gene transcription response to phosphate scarcity. Phosphate can be transported into the cell by means of 2 transporter systems: a high affinity system (Pho84-Pho89) and a low affinity system (Pho90-Pho87). Phosphate is stored in the vacuole as polyphosphate molecules by means of the Vtc2-Vtc3-Vtc4 system. The phosphate sensor involved has not yet been identified, however, a low phosphate signal is known to be transmitted via certain inositol polyphosphate species (4,6PPIP5) synthesized by Vip1, activating Pho81 and thus inhibiting Pho85.
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Table 1. polyP functions Function
Organism
Reference
A variety of biochemical reactions due to high energy bonds (analogous to those in ATP) and its properties as a polyanion
All
[34]
Buffer against alkalis
Dunalliela salina algae
[48]
Storage unit for Ca2+ and bacterial transformation
Bacteria
[11]
Detoxifier acting as a versatile metal-chelating agent
Bacteria
[31]
Antioxidative protection
Bacteria
[22]
Signalling and regulatory processes
Saccharomyces cerevisiae
[5]
Cell viability and proliferation
Shigella and Salmonella spp
[33]
Pathogen virulence
Trypanosoma cruzi
[39]
Production of poly-3-hydroxybutyrate
Ralstonia eutropha
[58]
Modulator of the microbial stress response
Pseudomonas aeruginosa
Structural component and chemical chaperone
E. coli
[23]
Cell cycle progression
Saccharomyces cerevisiae
[8]
Sensing, responding, and storing phosphate Phosphate, like glucose or nitrogen, is an essential nutrient for all living organisms. Depletion of any of these molecules forces cells to enter in the quiescent G0 state [55]. Cells have thus very wisely evolved to produce sophisticated systems that monitor, control, and respond to phosphate concentration. In the yeast S. cerevisiae, intracellular phosphate concentration is monitored and homeostatically controlled by the Pho pathway (Fig. 1), a pathway that has been extensively studied and elucidated, mainly by the O’Shea group [36]. Using the Pho signal, transduction pathway cells are able to sense and respond to variations in environmental phosphate. This process is led by the cyclin-dependent kinase (CDK) Pho85 which, like other CDKs, must interact with a cyclin (a protein showing a cyclic expression profile) to be active. Pho85 can bind with 10 different cyclins for its many functions in the biology of S. cerevisiae (for reviews see [28,29]). In the case of phosphate homeostasis, the cyclin associated with Pho85 is Pho80. Pho85-Pho80 kinase activity is regulated in response to phosphate levels by the CDK inhibitor (CDKI) Pho81, which is constitutively bound to the CDKcyclin complex, forming a ternary CDK-cyclin-CDKI complex [50]. When phosphate is limiting, the kinase activity of Pho85-Pho80 is faded by Pho81, permitting the dephosphorylation and activation of the transcription factor Pho4 and causing the transcription of genes involved in the survival response to phosphate starvation. Among these genes are those
[14,23]
codifying for the high-affinity phosphate transporters Pho84 and Pho89 [42,47,51] responsible for external phosphate intake and the acid phosphatases Pho5 (external), Pho3 (in the periplasmic space), and Pho11 and Pho12 located in the cell wall [47], which scavenge for all the available forms of phosphate. Yeast also contains a set of proteins that function as low-affinity transporters (Pho87 and Pho90) and are present in the plasma membrane when phosphate in the medium is abundant [67]. Homologues to the yeast Pho pathway have been described, namely, the Pho regulon in bacteria [64] and pef1+ in S. pombe [56]. Although a proportion of intracellular phosphate is driven to the mitochondria to enter into the energy cycle by means of the transporter Pho1 [59], the bulk of phosphate is used in the cytoplasm for several anabolic processes, such as phospholipid or ribonucleotide synthesis. However, for osmotic and biochemical reasons, the remaining phosphate cannot remain in the cytoplasm; in fact, cytoplasmic phosphate concentration in yeast is kept constant at around 20 mM [3,49,60]. To keep phosphate concentration constant, apart from using transportation, cells are able to store phosphate in the form of a molecule called polyphosphate (polyP). This function has been described in some bacterial species [17] and extrapolated to all species and cell types, and is generally accepted by the scientific community. Polyphosphate is a linear molecule made up of anywhere between a few and several hundred—or even thousands—of phosphate molecules linked by phosphoanhydride covalent bonds [34], which are present in all cell types, from archaeal to mammalian. In yeast, polyP is synthe-
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sized by the Vacuole Transport Complex (VTC) comprising Vtc1, Vtc2, Vtc3, Vtc4, and Vtc5 proteins [51,16,27]. The VTC complex is located in the vacuole membrane and its main function is to fetch excess phosphate from the cytoplasm and bring it to the vacuole while includes it in the polyP polymer. In the mobilization of polyP to produce phosphate, 2 polyphosphatases have been described in yeast: Ppn1 (endo- or exo-polyphosphatase, depending on environmental conditions [2]) and Ppx1 (exo-polyphosphatase), and it is very likely that other proteins with polyphosphatase activity await discovery. In addition to its role in storage function, polyP has been involved in many other processes, including virulence, stress response, survival, detoxification, and Ca2+ storage (see Table 1). The paper by Albi et al. recently provided an excellent review of polyP functions [1]. Polyphosphate plays decisive roles in mammalian cells, participating in processes such as blood clotting [40], bone mineralization [43], neurotransmission [26] and Alzheimer disease [12]. Despite the presence of polyP in mammalian cells, however, no polyP polymerase activity has been found to date [4]. With regard to polyP degradation activity, some candidates have been proposed (e.g., H-prune) [43], although the definitive main actor has not yet been identified. Intracellular phosphate concentrations must be kept constant, regardless of demand from the different cellular processes. When phosphate is suddenly taken from the cytoplasm pool, the mobilization of stored polyP may occur as a quick-response homeostatic mechanism; if the perturbation persists, however, Pho pathway activation must take place to adapt to the new environment.
Cell cycle regulation by phosphate It is well known that nutrients control cell cycle progression, specifically through the passage of the Start point (restriction point in mammalian cells) at the end of the G1 phase, a checkpoint that, once passed, forces cells to proceed through a new and complete round of the cell cycle [13]. Nutrients impinge on cell cycle control by activating several signalling pathways, including those of protein kinase A and Snf1, which positively regulate cell proliferation in response to glucose availability [21], and the TORC1 pathway, which controls the cell cycle according to nitrogen levels [37]. Consequently, inactivation of any of these 3 major pathways, even when other
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nutrients are plentiful, results in a cell cycle blockade and the production of the typical phenotypes of the G0-like growth arrest program [15]. Establishing and maintaining proper arrest in G1 is an important cellular response to nutrient deprivation; cells that fail to arrest the cell cycle at G1 during nutrient scarcity and proceed through S-phase show DNA replication stress and decreased viability [65]. Given that the cyclin Cln3 is the most upstream control point in the cell cycle and is directly responsible for driving cells pass Start, it seems logical that it should be a sort of a hub for signals alerting to nutrient scarcity. Indeed, it has been shown that Cln3 is less stable during nitrogen deprivation [19]. Some light has recently been shed on this molecular mechanism [57]. In terms of the involvement of phosphate in cell cycle control, the Clotet group showed that the before mentioned putative master regulator Cln3 is phosphorylated by Pho85-Pho80, a phosphorylation that is essential for stabilizing Cln3, thus permitting cell cycle progression. Correspondingly, the Cln3 phosphomimetic mutant maintains high levels of Cln3 regardless of Pho85-Pho80 activity, and therefore it does not properly arrest in G1 in the absence of phosphate, dying prematurely [38,30]. Pho85 is thus a key factor in stabilizing Cln3 in rich media, allowing cell cycle progression through Start. Mechanistically speaking, it is know that Cln3 amounts are controlled by the phosphorylation state of its destruction box, the PEST region. The responsible kinase is Cdk1, and this process determines Cln3 degradation by the proteasome [35]. When phosphate is present, Pho85-Pho80 phosphorylates 2 residues that precisely frame the PEST region, suggesting that this phosphorylation manipulates ubiquitination and subsequent destruction by proteasome. In the case of the regulation by nitrogen, Pho85 (here, bonded to the cyclins Clg1 or Pcl2) is also involved. When nitrogen is present Pho85-Pcl2 or Pho85-Clg1 cannot phosphorylate the chaperone Ssa1, event that also protects Cln3 from early destruction [57] (Fig. 2). Cells without cln3 are viable and show only a modest delay in G1 progression, suggesting that the regulation of Cln3 may be superfluous in ideal lab conditions (i.e., grown in YPD at 30Âş and agitated at 200 rpm). However, the destabilization of Cln3 appears to be a key factor in achieving correct cell arrest during nitrogen or phosphate starvation; cells that do not arrest properly are prone to entry into S-phase, rapidly losing viability [65]. Moreover, a cell that cannot sense correctly the presence of these nutrients after refeeding will have
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Fig. 2. The regulation of Cln3 by nutrient availability. Nitrogen scarcity activates Pho85 through an unknown mechanism, determining the phosphorylation of the chaperone Ssa1 and the degradation of Cln3. Phosphate availability activates the PHO pathway, producing direct phosphorylation and stabilization of Cln3. In both cases, nitrogen or phosphate scarcities block cell cycle progression through G1 by Cln3 destruction.
delayed Cln3 appearance and therefore delayed restart of the cell cycle, and thus be at a competitive disadvantage (our unpublished results). Yeast in natural environments should thrive under constantly changing nutrient conditions, and in this scenario Pho85 must be fundamental in controlling the constant cell cycle stalls and restarts that a yeast cell is subjected to.
Polyphosphate involvement in the cell cycle Polyphosphate is the other form in which phosphate is present in cells, appearing to play a role in the storage of phosphate. However, a number of recent reports, especially on prokaryotic cells, have suggested that the amount of polyP is related in some way with the cell cycle stage. In the bacteria Caulobacter crescentus, the biogenesis and localization of polyP is controlled as a function of the cell cycle, ensuring regular partitioning of polyP granules between mother and daughter cells [25]. When polyP production is impaired, cells improperly initiate chromosome replication [7]. In the cyanobacteria Synechococcus elongatus the average size of polyP bod-
ies increases gradually during the dark period, without a significant change in number or distribution. However, during the light period, the number of polyP bodies increases while the size of each polyP body decreases, with cells elongating until the end of this light period, when most cells divide. The regular coordinated changes of polyP bodies and DNA shape during the cell division cycle, together with an intimate physical interaction, suggest that polyP bodies play a role in supplying material for DNA [53]. Other findings that support the correlation of the cell cycle and polyP have been reported in Chlamydomonas reinhardtii [66]: polyP amounts peak during late cytokinesis and a slight fluctuation of polyP occurs during the cell cycle. The overexpression of an exopolyphosphatase in Pseudomonas sp. produces decreased levels of polyP, among other phenotypes, bringing about a cellular division malfunction [61]. In Synechococcus sp. from microbial mats, the levels of enzymes involved in the metabolism of polyP are differentially accumulated during the diel cycle; the levels of polyphosphate kinase peak at night, while polyP levels are highest during the early morning hours [20]. Finally, polyP and cell cycle have also been reported to correlate in mammalian cells. The proliferation of normal human fibroblast cells is enhanced by the addition
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Fig. 3. The many roles played by polyP. In S. cerevisiae, the polyphosphatases Ppx1 and Ppn1 degrade polyP chains previously synthesised by Vtc4 and stored in the vacuole. The resultant inorganic phosphate (Pi) could be used for steady synthesis of RNA and phospholipids, and for the dNTPs synthesis that takes place every time a cell passes through G1 and S phases.
of inorganic polyP into culture media [52], suggesting that polyP plays a role in promoting the cell cycle, although it might be mediated through the interaction with cell-membrane receptors. In yeast, polyP amount is cyclically regulated [8,41]: polyP content is reduced when cells enter into the S-phase and recover before mitosis. Interestingly, despite of the reduction in polyP amount in these phases of the cell cycle, cytoplasmic phosphate concentration remains constant [8]. This finding brings about 2 fundamental and somewhat related questions: i) what is the purpose of polyP cyclical reduction? and ii) is there a homeostatic system in place to address the cyclical variation in the demand of intracellular phosphate? In terms of the implication of polyP in the cell cycle, the supporting evidence in the different systems and models described above that point to polyP playing a role in cell cycle progression compelled us to further analyse this possibility. Our strategy [8] was to study cell cycle progression in yeast mutants that are deficient in polyP, either because cells are unable to produce it (vtc4∆) or unable to mobilize it (ppn1, ppx1∆). In both cases, cell cycle progression was found to
be impaired and was restored when external phosphate was added. The effect on the cell cycle appears to be more remarkable when cells grow in phosphate-limiting conditions, a situation that occurs normally when yeast cells are in a natural, fluctuating environment. On this basis, the high concentration of phosphate in the lab-growth media may be the main reason why some polyP functions in yeast, like those discussed here, have been so recalcitrant and escaped the scrutiny of the dedicated scientific community for so long. Phosphate is steadily consumed in the production of essential molecules, mainly RNA and phospholipids [68]. To our understanding, RNA and phospholipids are steadily synthesized, and consequently phosphate demand resulting from this synthesis throughout the cell cycle has not been described, nor is it thought to happen. Because polyP reduction occurs concomitantly with DNA synthesis, we speculated about the role of polyP in providing phosphate for the swift production of nucleotides (dNTPs), the basic building blocks for DNA synthesis, at the end of the G1-phase. To this end, we measured the dNTPs content of yeast cells deficient in polyP and found that their ability to produce them is impaired. This evidence supports the hypothesis that polyP
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consumed at the end of G1 and during the S-phase provides the phosphate necessary for DNA duplication (Fig. 3). This hypothesis is coherent with phosphate numbers. The phosphate amount included in a yeast genome can be easily calculated (7.5×107 molecules) and, according to our quantification, the reduced polyP amount in a cell accounts for approximately 4.5×108 phosphate molecules, a sufficient amount to meet the demand produced by the duplication of a genome. This work puts forth evidence to support what was suggested by others [7,53], revealing a new role for polyP as a phosphate supplier for the synthesis of dNTPs and, in turn, DNA duplication. DNA replication under conditions with limited amounts of dNTPs results in genomic instability [6,62]. Accordingly, polyP mutants, which have reduced amounts of dNTPs, show increased genomic instability, shown by the ability to lose plasmids and the presence of recombination events [8]. polyP is therefore relevant in cell physiology in terms of this new role in sustaining DNA replication. Considering the data derived from our work on polyP, we suggest that polyP plays a homeostatic role in managing short-term variations in the internal concentration of phosphate, eventualities that can arise as a consequence of discrete phenomena such as DNA replication or DNA damage repair.
Concluding remarks Phosphate has the ability to impact cell cycle progression to benefit the fate of a cell. Cells need phosphate, together with the mechanisms involved in its regulation, to proliferate in an orderly fashion. Following this line of argument, it is evident that phosphate homeostasis could be a target to treat cells that proliferate uncontrollably. In fact, insertion and expression of the yeast polyphosphatase gene PPX1 in MCF-7 mammary cancer cells has been reported to produce a markedly deficient response to mitogens [63]. Preliminary experiments are being carried out in our lab to identify conditions in which the absence of polyP in cancer cells works together with chemotherapeutic treatment, potentially allowing for a reduction in dosage and toxic effects. This dazing meteoric story of phosphorus, and the understanding of microbial phosphate metabolism, has allowed us to envisage its future involvement in cancer treatment, one of the most relevant problems faced by modern medicine.
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Acknowledgements. We especially thank J. Ariño and D. Canadell for valuable discussion on polyP and S. Kron and A. Truman for discussion on Cln3 nutrients involvement. We thank the rest of components of our group for their constant support. This work was funded by the Spanish Ministerio de Economía y Competitividad MINECO grant ref: BFU 2013-44189-P to JC. SB was recipient of a grant from the UIC. Competing interests. None declared.
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RESEARCH ARTICLE International Microbiology 19(3):143-155 (2016) doi:10.2436/20.1501.01.272. ISSN (print): 1139-6709. e-ISSN: 1618-1095
www.im.microbios.org
The use of high throughput DNA sequence analysis to assess the endophytic microbiome of date palm roots grown under different levels of salt stress Mahmoud W. Yaish,1* Ibtisam Al-Harrasi,1 Aliya S. Alansari,1 Rashid Al-Yahyai,2 Bernard R. Glick3 Department of Biology, College of Science, Sultan Qaboos University, Muscat, Oman. 2Department of Crop Sciences, College of Agricultural and Marine Sciences, Sultan Qaboos University, Muscat, Oman. 3 Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
1
Received 30 August 2016 · Accepted 30 September 2016
Summary. Date palms are able to grow under diverse abiotic stress conditions including in saline soils, where microbial communities may be help in the plant’s salinity tolerance. These communities able to produce specific growth promoting substances can enhance date palm growth in a saline environment. However, these communities are poorly defined. In the work reported here, the date palm endophytic bacterial and fungal communities were identified using the pyrosequencing method, and the microbial differential abundance in the root upon exposure to salinity stress was estimated. Approximately 150,061 reads were produced from the analysis of six ribosomal DNA libraries, which were prepared from endophytic microorganisms colonizing date palm root tissues. DNA sequence analysis of these libraries predicted the presence of a variety of bacterial and fungal endophytic species, some known and others unknown. The microbial community compositions of 30% and 8% of the bacterial and fungal species, respectively, were significantly (p ≤ 0.05) altered in response to salinity stress. Differential enrichment analysis showed that microbe diversity indicated by the Chao, Shannon and Simpson indices were slightly reduced, however, the overall microbial community structures were not significantly affected as a consequence of salinity. This may reflect a buffering effect by the host plant on the internal environments that these communities are colonizing. Some of the endophytes identified in this study were strains that were previously isolated from saline and marine environments. This suggests possible interactions with the plant that are favorable to salinity tolerance in date palm. [Int Microbiol 19(3):143-155 (2016)] Keywords: Phoenix dactylifera · endophytes · salt stress
Introduction Soil contains a very large number of different microorganisms. Moreover, one gram of soil may contain as many as one
* Corresponding author: M.W. Yaish E-mail: myaish@squ.edu.om
billion (1,000,000,000) of both cultivable and uncultivable microbe cells [42]. Plant growth and development is directly affected by soil components including the wide variety of microbes. Amongst the many soil microbes are numerous endophytes, organisms that internally colonize plant tissues without causing any damage or disease to the host plants. The diversity and abundance of each class within the microbial community is determined based on the complex relationship
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between the host and environmental conditions [27]. While the detailed functioning of these microbes is not totally understood, numerous endophytic microbes isolated from various plant species have been characterized as plant growth-promoting bacteria (PGPB) [33]. These organisms may facilitate plant growth in a variety of ways including improving the availability of some nutrients such as nitrogen, phosphorus, potassium, iron and calcium [36] or modulating plant hormone levels, either by providing plants with phytohormones such as auxin, cytokinin or gibberellin or by lowering plant ethylene levels through the action of the enzyme 1-aminocyclopropane-1-carboxylate (ACC) deaminase to interfere with stress ethylene formation [13]. The availability of these hormonal and nutritional factors is important to help plants to tolerate stressful conditions. Therefore, the presence of endophytic microbes has a positive effect on plants that are growing under salinity [3]. Inoculation of plants with endophytic bacteria promotes salinity tolerance and increases the productivity of various plant species including rice [37] and tomato [3]. Similarly, endophytic fungi have been shown to have a positive effect on soybean seed germination and plant growth [31]. A similar effect was observed when abscisic acid-deficient tomato plants were inoculated with an endophytic fungus and grown under salinity stress [19]. Date palm (Phoenix dactylifera L.) is a primary woody plant in arid and semiarid regions. Despite the fact that date palm is a relatively salt tolerant plant, it nevertheless suffers from high levels of salt in soil [48]. In a previous study, numerous endophytic bacterial species, which were cultured from date palm roots, had a positive effect on plants that were growing under saline [46] and drought conditions [11]. However, as many endophytic microbes are uncultivatable, a large number of endophytic microbial species are still unknown. Using the high throughput technique of next generation sequencing gives a more robust microbial characterization technique compared to conventional culturing methods. Such characterization of the indigenous microbial community is crucial to understand the contribution of the entire microbial community to salinity stress tolerance mechanisms in date palm, as well as in other plants. Thus, characterizing the microbial endophytic community by DNA barcoding, as a way to identify species, is a key step in the description of these individual microbes and in their functional characterization for possible use in subsequent applied research. The identification and quantification of endophytes in plants grown under
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distinct environmental conditions may facilitate an understanding of their role in plants. Root-associated bacterial (rhizosphere) communities in date palm have previously been studied under saline conditions [12]. In this report, several strain belong to Enterobacter, Flavobacterium, Mycobacterium, Pseudomonas, Rhizobium and Streptomyces genera were cultured and tested for their potential plant growth promoting capacity. This study concluded that the date palm bacterial community structures have been significantly affected by environmental factors such as drought and salinity however these factors did not affect the growth promoting features of these bacteria. Despite this knowledge about rhizosphere bacteria, very little is known regarding the nature and composition of the endophytic communities in date palm roots. Therefore, the present study was directed specifically toward characterizing the endophytic bacterial and fungal communities in date palm roots, and to studying the changes to these communities that occur when the host plant is exposed to salinity stress. In this study, only root system were examined since nearly all endophytes may be found in roots while only a limited fraction of endophytes are found in other plant tissues [35]. In addition, as root tissues are in direct contact with the soil ecosystem, salinity should reveal a significant impact on the microbial community composition.
Materials and methods Plant growth conditions and soil analysis. Date palm, Phoenix dactylifera L. (variety Khalas; the most common commercial variety) seeds were washed thoroughly with sterilized distilled water and then with 75% ethanol, followed by a 3% commercial bleach solution. After washing thoroughly with sterilized distilled sterilized water three times, the seeds were soaked in water overnight at 30°C. They were then germinated in sterilized vermiculite for 10 days at the same temperature. Subsequently, the germinated seeds were placed in 2-liter pots containing soils that had been collected from the rhizospheres of date palm trees planted at the Sultan Qaboos University date palm vineyard located at the coordinates 23°35'22.2" N 58°09'56.1" E, Muscat, Oman. The plants were incubated in a growth chamber under controlled environmental conditions as previously described [45,49]. Briefly, the plants were incubated under a 16/8h light/dark cycle with the 350 μE m–2 s–1 light intensity, 35º/30ºC day/night temperature, with 60% humidity. Seedlings were irrigated weekly to field capacity either with autoclaved distilled water (control treatment) or with a NaCl solution of concentrations gradually ascended on a weekly basis from 50 mM to 300 mM. Finally, the plants were watered for the last two weeks of growth with the 300 mM NaCl solution (salinity treatment). The chemical and physical properties of the soil were analyzed based on the previously published protocols [9] by the Ministry of Agriculture and Fisheries’ soil analysis laboratories in Jumah, Oman. The levels of soil salin-
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ity were measured as electrical conductivity (E.C.) of the saturated soil paste extracts using an ELE international E.C. meter (UK). The salinity level of the soil was measured in both sets of pots (control and treatment) before and after the treatment. The tacit assumption behind this work is that changes in soil salinity will differentially affect the proliferation and hence the abundance of soil microorganisms including those organisms that will specifically be taken up by plant roots and subsequently be scored as root endophytes. DNA extraction and barcoding. After removal of the remaining bacteria from the surface of seeds, the roots of 12 control and 12 treated seedlings (each biological triplicate was composed of four roots excised from four different seedlings) were surface disinfected as described [47]. Roots were thoroughly rinsed with sterile water and then washed with a 5.25 % solution of commercial bleach solution for 3 minutes followed by a 3% hydrogen peroxide solution for 3 minutes. Finally, the seeds were rinsed once with sterile water containing 10 % Tween-20 and then four times with sterile water. Subsequently, the root tissues were flash frozen and ground in liquid nitrogen using a mortar and pestle. The total DNA contained in each biological replicate was extracted from a pool of root tissues from four different plants using the Qiagen DNeasy Plant Mini Kit, following the manufacturer’s instructions. The DNA was quantified using a NanoDrop 2000c spectrophotometer (Thermo Scientific). The bacterial communities were barcoded and identified based on ribosomal DNA (16S rRNA) sequencing, using the next generation 454-pyrosequencing method available at the sequencing facilities of the Macrogen Inc. Company, Korea. Then, V3-V4 16S rRNA genes were amplified by fused PCR [15] and library quantitation was carried out using the GS FLX+ Series — XL+ manual instructions (Roche). Members within the fungal communities were barcoded and identified based on the internal transcribed spacer (ITS) DNA sequences using the same approach. The ITS3-ITS4 sequence regions were used for DNA barcoding. The primers that were used for barcoding are listed in Table 1. The PCR products were cleaned-up using AMPure9 beads and quantified using a Picogreen assay [2]. The amplicons were sequenced using a Roche Genome Sequencer FLX Plus. DNA sequencing was carried out using the GS FLX 454 (Roche); the CD-HIT-OTU (version 454-0.0.2) was used to de novo assemble the raw data. Data analysis. GS FLX data processing was performed using Roche GS FLX software (v 3.0). Raw data were demultiplexed using barcode se-
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quences, which are a combination of specific index sequences and primer sequences, without allowing mismatch (by Macrogen’s in-house software). Short reads were removed and tails that were too long were trimmed. Duplicates and chimeric reads were removed and filtered reads were clustered at 100% identity using CD-HIT-DUP software [17]. The remaining representative reads from the non-chimeric clusters were clustered using a greedy algorithm [52] into Operational Taxonomic Units (OTUs) at a 98% cut-off identity at the species level. Prior to further sequence analysis, the mitochondria- and the plastid-related OTUs were removed from the data. Raw data were sorted according to the barcode sequences of each sample. Each read was compared (local and global alignment) to the SILVA database [30] to find the best matching information for the taxonomic assignment using a basic local alignment search tool (BLAST). Furthermore, the similarity between the read sequences was tested to determine the OTUs and perform the statistical analysis on the diversity and evenness of the sample species. The Shannon and Simpson index was used to study the biodiversity based on the richness of the species. Furthermore, the Chao1 index was used as an abundance-based richness estimator. The similarity criteria were: species 98%, genus 94%, family 90%, order 85%, class 80% and phylum 75%. The Maximum likelihood phylogenetic tree was constructed using Mega software [21] with the default settings. QIIME 1.8.0 software [7] was used to generate the OTU count, Shannon, Simpson, and Chao1 indices and to statistically compare and validate the OTU frequencies across samples of the two groups. Each group was composed of three biological replicates based on the p ≤ 0.05. For the differential rRNA gene enrichment analysis among the control and salinity treated samples, the Mann-Whitney U test, as a version of bootstrap equal to 2000 times, was used. The p-value was corrected by the Bonferroni procedure for multiple comparisons [16]. Nonmetric multidimensional scale (NMDS) was used to illustrate the effect of the salinity treatments on the microbial community composition using the Past 3 software package [14] and the Bray–Curtis similarity index. Tests of the null hypotheses of no differences among the microbial communities compositions were examined using permutation multivariate analysis of variance (PERMANOVA) [26], and presented in ordinations using the NMDS. The p-value was recalculated based on the Bonferroni significance. The 16S rRNA gene sequences obtained in this project were deposited in GenBank under the accession numbers KU579200 to KU579246 and the internal transcribed spacer (ITS) DNA sequences were deposited under the accession numbers KU593585 to KU593608.
Table 1. Primers used in rRNA gene amplification and barcoding. *M is a standard ambiguity codes for A or C nucleotides. Target
Forward MID (5′–3′)
Forward Primer (5′–3′)
Reverse MID (5′–3′)
Reverse Primer (5′–3′)
Bacteria (16S, V1V4)
AGCACTGTAG
GAGTTTGATCMTGGCTCAG*
AGCACTGTAG
TACCAGGGTATCTAATCC
Fungi (ITS3-ITS 4)
ATCAGACACG
ATCAGACACG
ATATCGCGAG
ATATCGCGAG
ACGAGTGCGT
GCATCGATGAAGAACGCAGC
ACGAGTGCGT
ACGCTCGACA
ACGCTCGACA
AGACGCACTC
AGACGCACTC
TCTCTATGCG
TCTCTATGCG
TCCTCCGCTTATTGATATGC
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Results Salinity treatment retards seedling growth. At the end of the treatment, the plants have approached the end of the first leaf growth stage. The results showed that the initial average electrical conductivity (E.C.) level of soil was 1.3 (±0.2 S.D.) deciSiemens per metre (dS/m). After treatment, the average E.C. in the control pots was 0.9 (±0.21 S.D.) dS/m, while the average E.C. in the salt treated pots was 17.2 (±0.48 S.D.) dS/m. As a consequence of the salt treatment, the plants showed a severe reduction in growth compared to those that were grown under normal conditions. In addition, salinity caused necrosis of the leaf tips and leaf deformation (Fig. 1). Soil analysis showed that it is mainly composed of fine sand particles and the levels of nitrogen (N), phosphorus (P), potassium (K) and total organic carbon (TOC) was significantly reduced in soils treated with saline solutions (Table 2). rRNA gene library sequencing reveals the presence of a divergent endophytic community. When the total DNA was extracted from the root tissues and used for barcoding, pyrosequencing products of the six bacterial 16S rRNA gene libraries were assembled into 159,372 reads, 95% of which were coded for sorted barcode sequences with an average length of ~606 bp. After the removal of the mitochondrial and plastid related sequences, a total of 10,092 assembled sequences were assigned to bacterial species including 7249 and 2843 reads obtained from the control and the treatment libraries, respectively.
Fig. 1. The effect of the gradual salinity treatment on the growth of the date palm seedlings.
After removal of the plant-related sequences, the six fungal ITS gene libraries generated a total of 139,969 reads, 96% were sorted into reads of an average length of ~295 bp including 67,491 and 72,478 reads sequenced from the control and the NaCl-treated root libraries, respectively. The BLAST analysis revealed that about 96% of the sequenced 16S bacteria rRNA genes were assigned to the Proteobacteria phylum and the rest (4%) were assigned to Actinobacteria, Bacteroidetes, Cyanobacteria or Firmicutes phyla. The Proteobacteria phylum alone included 17 bacteria families. The most abundant were Enterobacteriaceae (54%), Rhodocyclaceae (20%), Rhizobiaceae (7%), Xanthomonadaceae (7%), Pseudomonadaceae (3%), and Saccharospirillaceae (3%) while the rest of the phyla contained six families including Flammeovirgaceae, Flavobacteriaceae and Sapros-
Table 2. The chemical and physical properties of the soil used in this experiment. Significant differences (p ≤ 0.05) are indicated by an asterisk of a certain component were calculated based on three experimental replicates. Soil chemical and physical properties
Control
NaCl-treatment
N (%)
0.33
0.29*
P (ppm)
263
210*
K (ppm)
740
600*
Coarse sand %
0.1
0.1
Total organic carbon (TOC) %
6.6
5.8
Fine sand %
90
90
Silt %
2.5
2.5
Clay %
4.2
4.2
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Table 3. Bacteria OTUs identified from date palm roots based 16S ribosomal DNA sequences and their mean abundance in the libraries prepared from the control and salinity treated plants. Significant enrichment (p ≤ 0.05) of a certain strain was calculated based on three biological replicates. The strains are ordered based on the descending p-value. OTUs
Abundance
OTUs
p-value
Control
NaCl
1.4
0
0.03
Saccharospirillum sp.
0
13.7
Enterobacter cloacae
1014.4
0
Reichenbachiella sp.
0
Fulvivirga kasyanovii Flavobacterium anhuiense Saccharospirillum sp. Thalassospira xianhensis
Abundance
p-value
Control
NaCl
Caulobacter segnis
2.7
0
0.18
0.03
Flavobacterium hauense
1.4
0
0.52
0.03
Unclassified Saprospiraceae
0
1.4
0.52
25.4
0.04
Thalassospira sp.
0
1.4
0.53
0
43.7
0.04
Alcanivorax dieselolei
0
3.4
0.53
19
0
0.04
Hoeflea suaedae
0
3.4
0.53
0
74.4
0.04
Delftia tsuruhatensis
11
0
0.53
0
630
0.04
Methylophaga thiooxydans
0
2.4
0.53
153.7
0
0.04
Flavobacterium beibuense
0
1.4
0.53
Pseudomonas stutzeri
15
0
0.04
Zoogloea oryzae
3.4
0
0.54
Stenotrophomonas maltophilia
228
0
0.04
Pseudacidovorax intermedius
5
0
0.54
Acidovorax wautersii
7.7
0
0.04
Novosphingobium mathurense
2
0
0.54
Enterobacter sp.
725
0
0.04
Streptomyces scabiei
3.4
0
0.54
Pseudoxanthomonas sp.
6.7
0
0.05
Rhizobium tropici
2.4
0
0.54
Rhizobium rosettiformans
5.7
0.4
0.06
Streptomyces coeruleofuscus
0
19.4
0.54
Incertae sp
3
0
0.16
Rhizobium azibense
18
0
0.54
Uliginosibacterium sp.
24
0
0.16
Chryseobacterium nakagawai
1.4
0
0.55
Sphingopyxis sp.
0
37
0.16
Unclassified Rhodocyclaceae
1.4
0
0.55
Rhizobium huautlense
0
1.7
0.16
Novispirillum itersonii
0
3.4
0.55
Labrenzia aggregata
0
11.7
0.17
Vibrio furnissii
0
6.7
0.55
Saccharospirillum sp.
0
2.7
0.17
Pseudomonas aeruginosa
88
0
0.55
Ensifer adhaerens
0
39.7
0.17
Mycobacterium porcinum
0
1.4
0.55
Denitromonas sp.
0
4
0.17
Sulfurospirillum deleyianum
65.4
0
0.56
Marinobacter algicola
0
10
0.18
Rhizobium daejeonense
Agrobacterium tumefaciens
piraceae (Bacteroidetes); Mycobacteriaceae and Streptomycetaceae (Actinobacteria), and Lachnospiraceae (Firmicutes). The analysis also revealed the presence of a total of 49 OTUs, representing 35 unique genera, where Enterobacter, Flavobacterium, Pseudomonas, Rhizobium, Saccharospirillum, Streptomyces and Thalassospira spp were represented more than once (Table 3). In addition to the bacterial endophytes, the taxonomy abundance ratio of fungal endophytes was calculated based on the ITS gene analysis. This showed that about 91% of the sequences were assigned to Ascomycota, 0.3% to Basidiomycota and 0.05% to Zygomycota phyla. In addition, 8.4% were unassigned. The Ascomycota phylum included Botryosphaeriaceae, Incertae sedis, Trichocomaceae, Debaryomycetaceae,
Nectriaceae, Chaetomiaceae families, while the Basidiomycota phylum included only the Ceratobasidiaceae family. Furthermore, the Zygomycota phylum included only the Mortierellaceae family. The sequence analysis revealed the presence of a total of 24 OTUs, of which there were 19 OTUs representing 13 unique genera, where Fusarium, Humicola, Rhizopycnis, Sordariomycetes spp. and the Sordariales order were represented more than once (Table 4). Diversity and composition of microbial communities in date palm roots upon exposure to salinity stress. The rRNA library gene sequencing revealed the presence of a low-divergence endophytic community. The biodiversity of the bacterial and fungal endophytic
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Table 4. Fungal OTUs identified from date palm roots based ITS DNA sequences and their mean abundance in the libraries prepared from the control and salinity treated plants. Significant enrichment (p ≤ 0.05) of a certain strain was calculated based on three biological replicates. The strains were ordered based on the descending p-value. Taxon name
Abundance
p-value
Fusarium oxysporum
55
0
0.54
0.05
Mortierella sp.
26
0
0.54
640.4
0.12
Ceratobasidium sp.
143.4
1.4
0.55
40.4
0
0.17
Rhizopycnis vagum
10,290.4
16,236.4
0.62
Humicola sp.
0
33.7
0.19
Fusarium sp.
18
18.7
0.62
Fusarium solani
42
23.4
0.31
Rhizopycnis vagum
1
30
0.78
35.4
736.4
0.32
Unclassified Sordariales
37.4
0.4
0.79
Unclassified Gnomoniaceae
68
0
0.51
Unclassified Pleosporales
200
0.4
0.80
Unclassified Sordariomycetes
0
60.4
0.52
Rhizopycnis vagum
4
25.7
0.80
Unclassified Sordariales
73
0
0.53
Haematonectria haematococca
24.7
8
0.81
Aspergillus ochraceopetaliformis
154
0
0.53
Fusarium solani
6952
2983.7
0.92
Fusarium longipes
45.7
0
0.54
Fusarium sp.
331.4
124.7
0.93
Preussia sp. Unclassified Sordariomycetes
Meyerozyma caribbica
0
2043.7
0.04
1733.4
112
15
p-value
NaCl
Aspergillus niger
NaCl
Abundance Control
Humicola fuscoatra
Control
Taxon name
communities that were growing in date palm roots were studied based on the OTUs, Shannon, Simpson and Chao1 indices. The analysis resulted in low index values, indicating lowdivergence bacterial and fungal communities. The diversity, as well as the abundance-based richness of the bacterial and fungal communities, was reduced even further in the plants that were exposed to salinity stress, compared to those that were grown under normal conditions. However, this decrease was not significant on the basis of p ≤ 0.05 (Fig. 2). A Mann-Whitney U test statistical analysis based on the three biological replicates of each group and the p ≤ 0.05 showed that, out of 47 OTUs identified from the bacterial community living in the roots, 14 OTUs were differentially enriched when the plants were exposed to salinity stress (Table 3). The Thalassospira, Saccharospirillum, Fulvivirga, Reichenbachiella and Saccharospirillum spp. were enriched in the root tissue pools of plants that were grown under salinity stress. However, Rhizobium daejeonense, Enterobacter, Flavobacterium, Pseudoxanthomonas, Agrobacterium, Stenotrophomonas, Pseudomonas, Acidovorax and Pseudoxanthomonas spp. were enriched in the root tissue pools of the plants that were grown under normal conditions (Table 3). The phylogenetic analysis, which was based on the 16S rRNA gene sequences, revealed the presence of four major
bacterial clades. Three of these clades harbored strains whose abundance within the community was significantly altered by the salinity treatment (Fig. 3). The other clade within the phylogenetic tree included Mycobacterium porcinum and Streptomyces species was not affected under the same treatment. Unlike the results observed for the endophytic bacteria, the fungal communities showed that, out of the 24 OTUs that were identified in this study, only Humicola fuscoatra and Aspergillus niger were significantly (p ≤ 0.05) enriched in roots when the plants were exposed to salinity stress and to normal conditions, respectively (Table 4). Aspergillus niger abundance decreased in the presence of salt while Humicola fuscoatra abundance increased in the presence of salt. According to the phylogenetic tree analysis, these two species were clustered within the same clade (Fig. 4). The total bacterial and fungal community variations based on the abundance as determined by the rRNA and ITS DNA sequencing data were investigated using the NMDS ordination-based analysis. The NMDS gave a satisfactory representation of the data (stress = 0.1063, Bray-Curtis distance index), however, by using PERMANOVA, microbial community composition did not differ significantly between treatments (p < 0.096) (Fig. 5).
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Discussion Prolonged salinity stress treatment showed a negative effect on date palm seedling phenotype/growth (Fig. 1). A similar phenotype was previously observed when an artificial soil was used where the leaf length and the primary root length were significantly reduced by an average of 63% and 34%, respectively [45]. The change in the plant phenotype may reflect the impact of the added salt on both the plants themselves and the composition of their endophytic microbial communities [1]. The rhizosphere is the major source of the endophytes, therefore, a microbial community change in the rhizosphere is likely to have a direct impact on the endophytic community composition. In comparison with the endophytic bacteria, Ferjani el al. [12] found that the date palm free living rhizosphere bacteria community structures have been significantly affected by macroecological factors such as salinity, however, functional analysis showed that these communities have maintained their role in helping plants when grown under stress. The study also showed the isolation of some bacterial genera such as Enterobacter, Flavobacterium, Mycobacterium, Pseudomonas, Rhizobium and Streptomyces that are
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Fig. 2. The biodiversity coefficient changes in the bacterial (A) and the fungal (B) endophytic communities in response to salinity stress. The one-way analysis of the variance (ANOVA) test did not show a significant (p â&#x2030;¤ 0.05) change in the biodiversity in response to the salinity treatment. Values are means Âą standard error (n = 3).
also present in the endophytic communities of the current report. In fact, a previous study concluded that salinity is an important selective factor for date palm rhizosphere microbiomes [12]. Date palms retain a significant amount of salt in the root tissues when they are exposed to salinity stress [41,48]. Therefore, there is a direct relationship between soil and root salinity levels that may significantly impact endophytic microbial community structures. Regardless the read number of each OTU, Rhizobium species were the only shared bacterial OTUs identified in microbial communities isolated from the control and the treated plants (Table 3), however, there were 13 out of 24 fungal OTUs commonly available in both communities (Table 4). Therefore these shared microbial species can be considered to be the core endophyte microbiota of date palm. Despite the fact that the biodiversity indices based on the analyzed 16S and ITS barcodes were relatively low (Fig. 2), a wide range of different endophytic bacterial and fungal species were identified from date palm roots growing under normal and saline conditions. However, evidence for totally different endophytic microbial communities present due to salinity treatment was not feasible based on the enrichment data analysis pre-
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Fig. 3. Maximum likelihood phylogenetic tree based on 16S rRNA gene sequences, showing the relationships between the bacterial taxa identified in this study. The bootstrap values â&#x2030;Ľ50 % (based on 1000 replications) are shown at branching points. Differentially abundance strains (p â&#x2030;¤ 0.05) in the salinitytreated and control roots are shown in red and blue, respectively.
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Fig. 4. Maximum likelihood phylogenetic tree based on ITS gene sequences, showing the relationships between fungal taxa identified in this study. The bootstrap values â&#x2030;Ľ50 % (based on 1000 replications) are shown at branching points. Differentially abundance strains (p â&#x2030;¤ 0.05) in the salinity-treated and control roots are shown in red and blue, respectively.
sented in this work. The low biodiversity indices are probably due to the fact that specific types of microbial species can penetrate and internally colonize root tissues regardless of the species that can inhabit the rhizosphere. Thus, a previous molecular analysis revealed that plant immunity systems can restrict microbial populations inside plants [35]. In addition, some endophytic microbes may have been present in the seeds and inherited from the mother plants and could have out-competed newcomer strains. For example, a microbiome analysis revealed that different types of soils had a lesser effect on the structure of the observed endophytic bacterial communities than different maize genotypes [18]. This was attributed to the inheritance of some microbes, a common phenomenon in seeds that are able to maintain the original microbial communities. Previous studies have shown that sa-
line stress affects the community structure of bacterial [23], as well as the fungal endophytes [24]. This is consistent with the results that were obtained in this study, in which the biodiversity index values tended to decline (although not statistically significantly) when the plants were grown under salinity stress. In fact, high soil salinity levels negatively affect not only the endophytic microbial community diversity but also the soil microbial communities per se and hence reduce the decomposition and the mineral fixation activities in the soil[34]. This situation usually leads to changes in the soil nutrient contents [38]. This notion is consistent with the results obtained from the analysis of the salinity treated soils in this study (Table 2). In this study, the identified endophytic bacterial species included some species that were previously isolated from oth-
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Fig. 5. Nonmetric multidimensional scale (NMDS) ordination illustrates the changes in the microbial community composition due to salinity treatments. The PREMANOVA test among the two groups (salinity vs. control) showed insignificant (p = 0.096) differences among the bacterial and fungal endophytic communities identified from treated (T1-3) and control (C1-3) soils.
er plant species, such as Enterobacter, Mycobacterium, Rhizobium, Stenotrophomonas, Streptomyces genera [35], and from date palm such as Enterobacter, Chryseobacterium and Stenotrophomonas spp. [47]. However, the rest of the OTUs found in this study have not previously been observed in date palm tissues (Table 3). Some previously isolated bacteria species from date palm root tissues such as Enterobacter and Stenotrophomonas spp showed an ability to promote canola (Brassica napus) growth when inoculated under saline conditions [47]. This is because those strains were selected for the ability to produce growthpromoting IAA and/or ACC-deaminase. However, in this project, both Enterobacter and Stenotrophomonas spp. were significantly (p â&#x2030;¤ 0.05) inhibited in the roots in response to the salinity treatment when detected in date palm roots. These findings enforce the notion that the endophytic microbial behavior basically depends on both host plant species and the environmental conditions. Among the bacterial community, some OTUs were highly abundant in roots in response to the salinity treatment. Previ-
ous work showed that all of these OTUs were isolated from saline environments but none of them were previously isolated from plant tissues. For example, Saccharospirillum spp. were previously isolated from hypersaline lakes and salty mines [10], grown in high saline ranges, and utilized chitin as a source of carbon [40]. Similarly, Reichenbachiella spp. were previously isolated from a tidal flat of the Yellow Sea [8] and from a freshwater marsh, and were among the most common genera of the active wood-chip-sediment boundary layer inhabitants in the deep Mediterranean sea [5]. Fulvivirga kasyanovii and Fulvivirga sp. were previously isolated from sea water [39]. Furthermore, Thalassospira xianhensis was isolated from oil-polluted saline soil and shown to degrade organic materials [53]. The bacterial community included other species that tend to insignificantly accumulate (p â&#x2030;¤ 0.05) in roots in response to salinity (Table 3). For example, Marinobacter algicola is a marine bacterium [4] and was among the dominant species that was identified from saline desert microbiota [29]. The presence of these salinity tolerant bacteria suggests that these species are able to colonize date palm
ENDOPHYTIC MICROBIOME OF DATE PALM
roots and could help plants when grown under saline conditions. However, at this stage, clear supportive evidence for this statement is not yet available. Endophytic Humicola sp. was differentially accumulated in date palm roots when the plants were treated with salinity stress (Table 4). Previous reports have shown that this is a nonpathogenic fungus [43] that could be isolated from seaweeds such as the brown algal species Fucus serratus and Padina tetrastromatica [32], as well as from different plants growing in Mediterranean salt marshes [25] and from wild ginger (Amomum siamense) [6]. Furthermore, Aspergillus niger is differentially accumulated in date palm roots when the plants are grown in the absence of salt. This species is a common systemic phytopathogen. However, some Aspergillus niger strains have been used to solubilize and immobilize inorganic phosphate in the soil [22]. Previous studies have also isolated endophytic Aspergillus species from different plant species. For example, Aspergillus sp. CY725 was isolated from Cynodon dactylon, a marine-derived mangrove endophytic fungi [54]. The rest of the identified fungal species have previously been isolated from other plant species. For example, endophytic Fusarium species were isolated from bamboo [20] and mangrove plants [28]; Fusarium solani was isolated from Ficus carica [51] and Rheum palmatum L. [50]; and Fusarium oxysporum was isolated from Cinnamomum kanehirae [44]. Salinity can cause a wide range of physiological stresses on plants. These stresses are triggered by the internal and external salt stimuli. The amount of the accumulated salt in the plant depends on the ability of the root system to exclude Na+ ions. Previous studies have shown that date palm cvs. Medjool and Barhi [41] and Khalas, which was used in the present study (unpublished data), retain a high level of Na+ in roots but are able to maintain a relatively low level of salt in leaves when the plant grows in saline conditions. However, it is not known whether salts and endophytes are concentrated within the same compartment in the plant tissues. Regardless of the site of accumulation, salt stress clearly alters the plant-microbe relationship. Therefore, it is not surprising that the differential microbial community enrichment phenomenon described here was affected by soil salinity. The information garnered in this study provides a baseline of information on the composition of endophytic microbial communities in date palm roots and their potential role in salinity tolerance. In addition, this information could provide a starting point for future investigations directed towards devel-
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oping a better understanding of the role of each member within these microbial communities. Acknowledgements. This work was supported by a generous grant from the College of Science, Sultan Qaboos University number IG/Sci/ Biol/13/01 and the TRC grant number 151 to MWY. We thank the laboratory of soil analysis, Ministry of Agriculture and Fisheries’ in Jumah, Oman for the soil samples analyses.
Competing interests. None declared.
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RESEARCH ARTICLE International Microbiology 19(3):157-160 (2016) doi:10.2436/20.1501.01.273. ISSN (print): 1139-6709. e-ISSN: 1618-1095
www.im.microbios.org
Atypical enteropathogenic Escherichia coli (aEPEC) in children under five years old with diarrhea in Quito (Ecuador) Francisco X. Mora,1 Rolando X. Avilés-Reyes,2 Laura Guerrero-Latorre,1 Esteban Fernández-Moreira1* Facultad de Medicina, Universidad de las Américas, Quito, Ecuador. 2Pharmaceutical Science Division, University of Wisconsin, Madison, WI, USA
1
Received 5 August 2016 · Accepted 15 September 2016
Summary. Enteropathogenic Escherichia coli (EPEC) remain one the most important pathogens infecting children and they are one of the main causes of persistent diarrhea worldwide. In this study, we have isolated EPEC from 94 stool samples of children under five years old with diarrheal illness in the area of Quito (Ecuador), and we have determined the occurrence of the two subtypes of EPEC, typical EPEC (tEPEC) and atypical (aEPEC), by PCR amplification of the genes eae (attaching and effacing) and bfp (bundle- forming pilus). Typical EPEC is positive for eae and bfp genes while aEPEC is positive only for eae. Our results suggest that aEPEC is the most prevalent subtype in Quito (89.36 %), while subtype tEPEC is less prevalent (10.64 %). [Int Microbiol 19(3):157-160 (2016)] Keywords: Escherichia coli · atypical EPEC · genes eae and bfp · diarrhea in children · Quito (Ecuador)
Introduction Diseases that affect the gastrointestinal system are one of the main causes of child morbidity and mortality in developing countries. The diarrhea produced by Escherichia coli agents have high incidence in those countries [12]. The diarrheagenic E. coli are subdivided into six pathotypes [8]. The most prevalent pathotype worldwide is EPEC (enteropathogenic E. coli),
Corresponding author: E. Fernández-Moreira E-mail: esteban.fernandez@udla.edu.ec *
which cause 79,000 children deaths under 5-year-old around the world per year [10]. Since 1995, it is documented that EPEC presents two subtypes: the typical (tEPEC) and atypical (aEPEC). Typical EPEC is characterized by the plasmid gene bfp (bundle- forming pilus) and the chromosomal gene eae (attaching and effacing), and a single human reservoir. Only aEPEC has eae gene and infects humans and cattle. The typical subtype is positive for genes eae and bfp and atypical subtype only to eae gene [11]. To identify EPEC it is necessary first identify the presence of eae gene. The eae gene is present in all EPEC and absent in normal microbiota of E. coli [13]. To our knowledge, only two studies of EPEC prevalence in Ecuadorian population [14,15] have been published. How-
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ever, in those studies, only the presence of bfp gene (only present in subtype tEPEC) was determined and in consequence, aEPEC prevalence was underestimated. In this manuscript we attempted to quantify the prevalence of atypical and typical EPEC in children <5 by PCR amplification of genes eae and bfp in the Quito area.
Materials and methods Bacterial strains. Fecal samples of children under five years old with diarrhea illness were collected during February and June 2013 by clinical laboratories (Netlab; Zurita & Zurita; Pazmiño & Narváez) in Quito. Samples were screened for Escherichia coli pathotypes determination by multiplex PCR [2]. The samples included in the study were those with EPEC gene amplification (eae gene). DNA extraction. To purify and quantify the DNA of the EPEC strains, they were grown in LB medium (BBL, Sparks, MD, USA) to avoid the reagents present in the selective medium MacConkey, which interfere in the process of DNA extraction and quantification. DNA was extracted using the Wizard genomic DNA purification Kit (Promega, Madison, WI, USA). DNA concentration and purity was measured using a Nanodrop 2000/2000c® (Thermo Scientific,Wilmington, DE, USA) according to the manufacturer's protocol . EPEC typification. The 94 EPEC strains identified by pathotype determination were analyzed for eae and bfp genes by duplex PCR (Table 1). The reaction contained 12,5 μl of GoTaq® Green Master Mix 2x (Promega, Madison, WI, USA), 0,3 μM of each forward and reverse primer, 2 ng Template DNA and PCR-grade water up to a total reaction volume of 25 μl. DNA amplification was carried out in a PCR Thermal Cycler Multigene Optimax (Labnet, Edison, NJ, USA). The Thermal Cycling protocol was as follow: initial denaturation for 5 min at 94°C followed by 30 cycles of 45 s at 94°C, 45 s at 57°C and 45 s at 72°C and a final extension of 10 min at 74°C [7,15]. Detection of PCR products was by electrophoresis in 1% ultrapure agarose gel (Invitrogen, Waltham, MA, USA) for 60 min at 90V and 120 mAmp. DNA was stained with Green® (Sigma Aldrich) and visualized under UV
light and the lanes was compared with 100 bp DNA ladder (Promega, Madison, WI, USA). To quality control the EPEC strains positive for eae and bfp genes were provided by James Nataro (Virginia University) and Roberto Vidal (University of Chile) (Table 1). Limit detection. We have determined the detection limit of PCR amplification used. DNA concentration was determined with bacterial culture adjusted to 0.5 McFarland with a nephelometer (Hanna Industries, WoonSocket, RI, USA) approximately 1.5x108 CFU/ml and diluted 1/10. Dilutions were analyzed by Nanodrop 2000/2000c to determinate the DNA concentration and used to amplify eae gene. GenPro Software (Media Cybernetics Inc., Rockville, MD) was used for calculation of the Relative Optical Density of PCR amplification products on agarose gels. Statistical analysis. We Graph Pad Software (GraphPad Software Inc., San Diego, CA, USA) was used to analyze the results. The ANOVA one way and Student-Newman-Keuls post-test was used to determine the statistical significance.
Results and Discussion During the period from February to June 2013, a total of 94 fecal samples were determined for EPEC from children aged <5 years old with diarrhea in Quito. They were positive for eae gene and negative for the genes: vt1; vt2; aggR; eltB; estA; daaC and ipaH. It was determined that 2 ng is the minimum amount of DNA to detect those genes. This amount of DNA corresponds to 103 CFU/ml (Fig. 1). The two subtypes of EPEC, tEPEC and aEPEC, were determined by duplex PCR amplification of the genes eae and bfp. The DNA concentration of the samples studied was comprised in a range between 45 and 80 ng/µl. The 94 samples were positive for the eae gene, and 10 samples were also positive for the bfp gene. Therefore, the relative frequency of subtype aEPEC in
Table 1. Primers used to amplify EPEC genes by real-time PCR Category
Target
Localiz.
eae
Chromosome
bfp
Plasmid
EPEC
Orient.
Primer seq. (5'-3')
F
5'-GTAAGTCTCAAACGCAAGCAACCAC-3'
R
5'-AACCTTGTTGTCAATTTTCAGTTCATCA-3'
F
5'-AATGGTGCTTGCGCTTGCTGC-3'
R
5'-GCCGCTTTATCCAACCTGGTA-3'
*Reference sequence Escherichia coli chromosome (CP017444.1) and plasmid (NC_010862.1).
Amplicon size
Position*
167
122313-122479
268
2725-3008
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ATYPICAL EPEC
Fig 1. Detection limit of EPEC (eae gene). Lanes 2 to 11, dilutions from 108 to 101 CFU/ml, respectively; lane 11, negative control. Lanes 1 and 12 DNA ladder (100 bp). The 198 bp products correlate with the eae gene.
the amplified bfp gene was present in the tEPEC subtype. As it has been observed in the present work, tEPEC only accounts for the 10% of all EPECs isolated from clinical samples in Quito. For that reason, the percentages of total EPEC presented in previous works were underestimated. It has been suggested that pathogens evolve through gene loss [1]. The basic genetic differences between the two subgroups of EPEC are the absences of plasmid pEAF and the plasmidic bfp gene [9] in the aEPEC subtype. In addition, the aEPEC subtype has several reservoirs described [7], this fact suggest that this subtype is already more adapted to circulate
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Quito is 89.36 % and tEPEC subtype is 10.64% (Fig. 2). The eae and bfp genes were amplified at least three times. The relative optical density image analysis of the bands showed no significant differences greater than 25% between them (P < 0.01). Our study shown that the prevalence of 90% aEPEC and 10% tEPEC in Quito properly correlated with the prevalence of aEPEC in the region: Peru with 76.8 % [3], Argentina with 93.1 % [5] and Venezuela with 88.9 % [6]. Previous studies conducted in Ecuador [14,15] underestimated the prevalence of Escherichia coli EPEC pathotypes. In those studies, only
Fig 2. Duplex PCR amplification of the eae (198 bp) and bfp (255 bp) genes. Escherichia coli EPEC samples are specified from 1 to 94. The controls are verified E. coli strains. Lane C+ tEPEC E. coli strain (James Nataro, U. of Virginia) and lane C- aEPEC E. coli strain (Roberto Vidal, U. of Chile). The 94 samples were positive for the eae gene and samples 37, 48, 50, 55, 70, 73, 76, 84, 90 and 93 were also positive for the bfp gene.
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among population with low-sanitation standards. Moreover, some studies have suggested that food animals may be potential reservoirs for aEPEC strains [3]. Most of the samples in our study come from the area of Quito. In the future there should be a study taking into account representative samples of the four geographical areas of Ecuador (coast, highlands, jungle and Galapagos Islands) to have a real picture of EPEC burden in the whole country.
Acknowledgements. This study was supported by the Pontificia Universidad Católica del Ecuador grant J13126. Competing interests. None declared.
References 1. Bliven KA, Maurelli AT (2012) Antivirulence genes: Insights into pathogen evolution through gene loss. Infect Immun 80:4061-4070 2. Chandra M, Cheng P, Rondeau G, Porwollik S, McClelland M (2013) A single step multiplex PCR for identification of six diarrheagenic E. coli pathotypes and Salmonella. Int J Med Microbiol 303:210-216 3. Comery R, Thanabalasuriar A, Garneau P, Portt A, Boerlin P, ReidSmith RJ, et al. (2013) Identification of potentially diarrheagenic atypical enteropathogenic Escherichia coli strains present in Canadian food animals at slaughter and in retail meats. Appl Environ Microbiol 79:3892-3896 4. Contreras CA, Ochoa TJ, Lacher DW, DebRoy C, Navarro A, Talledo M, et al. (2010) Allelic variability of critical virulence genes (eae, bfpA and perA) in typical and atypical enteropathogenic Escherichia coli in Peruvian children. J Med Microbiol 59:25-31
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5. Gabriel MM, Esquivel P, Lifschitz V, Lucrecia Medina M, Silvina Lösch L, Antonio Merino L (2010) Detection of diarrheagenic Escherichia coli in children from poor neighborhoods in Corrientes, Argentina. Rev Cubana Med Trop 62:42-47 6. Hannaoui E, Villalobos L, Martínez R, Maldonado A, Hagel I, Bastardo J (2010) Diarrheagenic Escherichia coli associated with acute diarrhea in children of Cumaná, Venezuela. Invest Clin 51:489-500 7. Hernandes RT, Elias WP, Vieira MAM, Gomes TAT (2009) An overview of atypical enteropathogenic Escherichia coli. FEMS Microbiol Lett 297:137-149 8. Hu J, Torres AG (2015) Enteropathogenic Escherichia coli: foe or innocent bystander? Clin Microbiol Infect 21:729-734 9. Kaper JB. (1996) Defining EPEC. Rev Microbiol 12:130-133 10. Lanata CF, Fischer-Walker CL, Olascoaga AC, Torres CX, Aryee MJ, Black RE (2013) Global causes of diarrheal disease mortality in children <5 years of age: A systematic review. PLoS One 8:e72788 11. Nataro JP, Kaper JB (1998) Diarrheagenic Escherichia coli. Clin Microbiol Rev 11:142-201 12. Qadri F, Svennerholm A-M, Faruque ASG, Sack RB (2005) Enterotoxigenic Escherichia coli in developing countries: epidemiology, microbiology, clinical features, treatment, and prevention. Clin Microbiol Rev 18:4654-4683 13. Trabulsi LR, Keller R, Tardelli Gomes TA (2002) Typical and atypical enteropathogenic Escherichia coli. Emerg Infect Dis 8:508-513 14. Vasco G, Trueba G, Atherton R, Calvopiña M, Cevallos W, Andrade T, et al. (2014) Identifying etiological agents causing diarrhea in low income Ecuadorian communities. Am J Trop Med Hyg 91:563-569 15. Vieira N, Bates SJ, Solberg OD, Ponce K, Howsmon R, Cevallos W, et al. (2007) High prevalence of enteroinvasive Escherichia coli isolated in a remote region of northern coastal Ecuador. Am J Trop Med Hyg 76:528-533
RESEARCH ARTICLE International Microbiology 19(3):161-173 (2016) doi:10.2436/20.1501.01.274. ISSN (print): 1139-6709. e-ISSN: 1618-1095
www.im.microbios.org
Functional ecology of soil microbial communities along a glacier forefield in Tierra del Fuego (Chile) Miguel A. Fernández-Martínez,1 Stephen B. Pointing,2 Sergio Pérez-Ortega,1,3 María Arróniz-Crespo,4,5 T. G. Allan Green,5 Ricardo Rozzi,6 Leopoldo G. Sancho,5 Asunción de los Ríos1* Department of Biochemistry and Microbial Ecology, Museo Nacional de Ciencias Naturales, CSIC. Madrid, Spain. 2Institute for Applied Ecology, Auckland University of Technology, Auckland, New Zealand. 3Real Jardín Botánico, CSIC, Madrid, Spain. 4 Department of Chemistry and Tecnology of Food, Universidad Politécnica de Madrid, Madrid, Spain. 5 Department of Plant Biology II. Universidad Complutense de Madrid, Madrid, Spain. 6 Institute of Ecology and Biodiversity, University of Magallanes, Puerto Williams, Chile 1
Received 25 August 2016 · Accepted 25 September 2016 Summary. A previously established chronosequence from Pia Glacier forefield in Tierra del Fuego (Chile) containing soils of different ages (from bare soils to forest ones) is analyzed. We used this chronosequence as framework to postulate that microbial successional development would be accompanied by changes in functionality. To test this, the GeoChip functional microarray was used to identify diversity of genes involved in microbial carbon and nitrogen metabolism, as well as other genes related to microbial stress response and biotic interactions. Changes in putative functionality generally reflected succession-related taxonomic composition of soil microbiota. Major shifts in carbon fixation and catabolism were observed, as well as major changes in nitrogen metabolism. At initial microbial dominated succession stages, microorganisms could be mainly involved in pathways that help to increase nutrient availability, while more complex microbial transformations such as denitrification and methanogenesis, and later degradation of complex organic substrates, could be more prevalent at vegetated successional states. Shifts in virus populations broadly reflected changes in microbial diversity. Conversely, stress response pathways appeared relatively well conserved for communities along the entire chronosequence. We conclude that nutrient utilization is likely the major driver of microbial succession in these soils. [Int Microbiol 19(3):161-173 (2016)] Keywords: Functional genes · antibiotic resistance · GeoChip microarray · primary succession · chronosequence
Introduction Microorganisms play a fundamental role in the initial colonization of exposed soils after glacial retreat [9,29,31,43,65]. Pioneer microorganisms are responsible for most biological transformations and drive the development of stable and la* Corresponding author: A. de los Ríos E-mail: arios@mncn.csic.es
Supplementary information (SI) [http://hdl.handle.net/10261/147168] contains additional Figures and Tables.
bile pools of nutrients [5,33] that facilitate further microbial colonization, and, subsequently establishment of lichens, bryophytes and vascular plants [9,13,51]. Numerous studies have investigated the changes in microbial community composition along chronosequences in glacier forelands [9,39,59, 65]. However, the associated changes in functional community structure and their role in the succession are still poorly understood. Soil microbial communities underpin carbon (C) and nitrogen (N) transformation processes (e.g., photosynthesis, N2 fixation, substrate decomposition, nutrient mineralization),
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edaphic factors [34,53] . The progressive changes in soil pH, moisture and nutrient availability that follow glacial retreat shape the community structure along the primary succession [37,50,52]. While some microorganisms can acclimate to shifts in abiotic factors, other taxa do not, and are consequently replaced [17,37]. Microbial succession also involves biotic interactions, inducing complicated network structures [11]. The competition for nutrient resources and space among different microbial groups can be regulated by synthesis of antibiotics along the succession [24,52] and, therefore, the antibiotic resistance genes are involved in interspecific microbial interactions [12,57]. Viruses (particularly phage) can be considered as another potential biotic driver in primary succession, as they can exert a bottom-up control on microbial communities [32,57]. The Pia Glacier forefield is located at the southern slope of Cordillera Darwin (Tierra del Fuego, Chile). Cordillera Darwin presents circa 80% of the surface covered by an ice cap, although most of the glaciers located at the mountain range have been receding constantly since the Little Ice Age (circa between AD 1750 and 1850) [36]. The area has a cool maritime climate with an average 5°C of temperature with little seasonal variations [45]. The southern slopes of Cordillera Darwin receive heavy rainfall of c. 1600 mm/year [28,35,45]. This forefield presents a clear sequence of moraine bands and rapid rates of vegetation growth and soil development, with Nothofagus tree-dominated stages present after only 34 years of soil surface exposure (Fig.1) [1,44]. The vegetation pattern along the chronosequence is characterized by pioneer
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which are essential for soil development and nutrient cycling in soils [19,47,58,65]. In newly exposed glacier forefield soils, organic carbon levels are low, limiting the microbial growth [47]. In these soils, microbial carbon input is primarily mediated by photosynthetic carbon fixation [20,39,65], but autochthonous or allochthonous organic matter breakdown can be also an important source of nutrients [3,21,26]. Microbial communities are also involved in other important carbon transformations along glacier forefield soils such as methanogenesis and methane oxidation [2,27,38]. Nitrogen has been identified as the main limiting nutrient in high latitude ecosystems, and also possibly a key factor in the regulation of forefield ecosystem functional dynamics [6,54,64]. At initial stages of soil development the main microbial contribution is atmospheric N2 fixation, either by free-living or symbiotic diazotrophs [1,6,42]. Nitrogen can also be released from ancient autochthonous or allochthonous nitrogen-rich organic matter (i.e., chitinolysis and proteolysis), by heterotrophic or mixotrophic microbial degradation [8,16,46,47]. During successional development of vegetation, the contribution of microorganisms to nitrogen cycling becomes more related to the transformation of nitrogenized compounds from freshly deposited organic matter [41]. Microbially mediated ammonification and nitrification lead to increases in bioavailable nitrogen [14,22,31]. Nitrogen may also be lost from the soil system, due to nitrogen volatilization, via microbial denitrification, as well as leaching of mobile nitrates to deeper soil layers [8,41,47]. Soil microbial communities are heavily influenced by
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Fig. 1. Schematic illustration of studied Pia Glacier chronosequence.
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Table 1. Site vegetation description and environmental attributes measures along the chronosequence of Pia Glacier forefield. Only mean values obtained for the three sampled transects are represented. Data were obtained from a previous study (1). Succeion stages (years being ice-free)
Vegetation
pH
NH4+
NO2-
NO3-
Inorganic N
total N
total C
1 yr
Bare soil
6.81±0.34
0
0
1.82±0.63
1.82±0.63
0
0.25±0.03
4 yrs
Pioneer lichens (Sterocaulon sp.) and mosses (Ditrichium cylindricarpum, Acroschisma wilsonii)
6.72±0.14
1.04±0
0
12.38±5.07
13.42±4.4
0
0.24±0.025
7 yrs
Lichens (Sterocaulon sp.) and pioneer herbs (Gunnera magellanica)
5.72±0.18
5.27±2.29
0
10.12±0
15.39±2.65
0.02±0.01
0.78±0.27
10 yrs
Herbs (Gunnera magellanica, Uncinia tenuis, Gaultheria mucronata, Empetrum rubrum and young Nothofagus spp.)
5.17±0.2
30.22±10
0
4.62±1.43
34.84±9.88
0.03±0.01
1.7±0.34
Herbs and bushes (Uncinia tenuis, Gaultheria mucronata, Empetrum rubrum, young Nothofagus antarctica and N. betuloides
5.04±0.46
37.7±9.9
0.15±0
1.65±0.05
39.5±10.72
0.22±0.11
6.61±2.81
Forest (Nothofagus antarctica, N. betuloides)
4.55±0.02
88.5±1.3
0.13±0
46.46±31.5
135.09±30.21
1.51±0.09
39.03±1.34
19 yrs
34 yrs
Content of NH4+, NO2-, NO3- and Inorganic N are expressed in mg/kg of soil and total soil N and C as percentage.
lichens (Placopsis spp. and Sterocaulum sp.) and mosses (e.g., Ditrichum cylindricarpum) settled in soils ice-free for 4 to 7 years, along with herbs (Gunnera magellanica, Uncinia tenuis) and, subsequently, bushes (Gaultheria mucronata, Empetrum rubrum) and young Nothofagus antarctica and N. betuloides at soils ice-free for 10 to 19 years and the development of Nothofagus forest at soils ice-free for more than 34 years (Table 1). We hypothesized that the rapid succession in Pia Glacier must be due, at least in part, to microbial efficient conditioning nutrient cycling in soil via carbon and nitrogen transformations, and that succession likely involves overcoming significant abiotic and biotic stressors. To test this hypothesis, we analyzed the functional gene profile of microbial communities using the GeoChip 4.0 micro-array in order to target key gene markers for major metabolic, stress response pathways and interactions [12,23,55,62,63]. This study improves our understanding on microbial functional ecology in glacier forelands through a qualitative insight into what functional attributes may underpin differences in microbial diversity along a well-defined soil chronosequence.
Materials and methods The study was conducted along a chronosequence established in soils from the Pia Glacier forefield (54º 46’ S 69º 40’ W) of ice-free times ranging from 1 to 34 years, attributed using aerial photographs, dendrochronology and lichenometry [1,44]. Soils located close to the glacier front (from 1 to 7 years being ice-free) are characterized by high pH, very low or undetectable total C and N contents, and low concentration of extractable NH4+- N, but relatively high concentration of NO3–- N (around 10 mg kg–1 after 4 and 7 years being ice-free, Table 1). After 10 years of soil exposure, significant accumulation of N, C and NH4+- N were detected and soil development progresses rapidly to an organic soil within the forest, which presents high contents of C and N (over 39% TC and 1.5% TN), NH4+- N (88.5 mg kg–1), NO3–- N (46.5 mg kg–1) and low pH (4.5) (Table 1). More detailed soil chemical properties along the chronosequence have been described in previous study [1]. Soil samples from different succession stages were collected during the austral summer of 2009 at sites that have been ice-free for 1, 4, 7, 10, 19 and 34 years (Fig. 1). At each succession stage, 3 sampling points were selected at 3 parallel transects established along the glacier forefield, from the glacier terminus towards the oldest dated moraines. At each sampling point, three surface soil samples (circa 0–5 cm depth) each 1m apart were aseptically recovered and pooled to yield a 200g composite sampling point sample. Samples were directly frozen and stored at –20°C until processed. Genomic DNA was extracted using the PowerMax Soil DNA Isolation Kit (MO BIO Laboratories, Inc.). DNA concentrations were determined us-
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ing a NanoDrop ND 1000 spectrophotometer (Thermo Fisher Scientific™). DNA samples from the same succession stage (three sampling points) were pooled in equimolar concentrations for further analysis. Pooled DNA samples were then concentrated using a SpeedVac concentrator (Savant Inc.) and purified using QiaEX II DNA Purification Kit (Qiagen Laboratories INC.). Functional diversity was assessed using the GeoChip 4.0 microarray. This comprises 84,000 50-mer oligonucleotide probes covering 141,995 gene variants from 410 distinct functional gene families involved in microbial carbon, nitrogen, sulphur, and phosphorus cycling, energy metabolism, antibiotic resistance, metal resistance/reduction, organic remediation, stress responses, bacteriophage and virulence, major biogeochemical, ecological and other metabolic processes [55]. The GeoChip hybridization was carried out as previously described [55]. Signal intensities were scanned and used as a proxy for gene abundance. Hierarchical cluster of the successional stages, based in gene abundance, was performed using Euclidean distances and the average linkage (between groups) clustering algorithm in SPSS v.23.0, in order to find similarity patterns. The normalized hybridization output data were reorganized on the basis of functional categories (in this study C- and N-cycling, stress responses, viral diversity and antibiotic resistance gene signatures) as previously described [12,56]. Pathway-specific GeoChip oligonucleotides are presented in a very large number in the analysis, creating a level of redundancy that allows a high degree of confidence in signal recovery, inferring occurrence of any given pathway [23]. Contributions of different taxa to each metabolic pathway (C- and N- cycling and stress responses were depicted using a heat map, where signal intensity was used as a proxy for relative abundance. Probes that returned positive signals from all of the sampling points were defined as ‘common’ genes while those with positive signals at only one sampling point were defined as ‘unique’ genes according to [60]. Hybridization of DNA from sampling points along the chronosequence was achieved with 94.56% of the probes on average, over a total 83,992 probes. The GeoChip dataset reported in this paper is publicly available at http://ieg.ou. edu/4download/. The linkages between functional community structure and soil attributes were evaluated by Mantel tests and redundancy analysis (RDA) performed in R v. 3.3.1 using the vegan package (v. 2.2-1) [40]. Bray-Curtis similarities for functional genes among different samples were calculated on normalized data (following [12,56]) and visualised using non-metric multidimensional scaling (NMDS) with R package vegan v. 2.2–1 [40]. This was applied to all pathways except anammox, which was excluded from this analysis due to their occurrence in a single phylum (Planctomycetes).
Results Functional community structure. Functional community structure. Among the 79,419 probes returning positive signals, 13,000 were derived from genes involved in carbon (C) cycling, 3428 from nitrogen (N) cycling, and 12,471 from stress responses genes, while 907 corresponded to viral signatures and 260 to antibiotic resistance genes. The microarray analysis revealed that communities from all the succession stages supported potential for autotrophic, heterotrophic, diazotrophic and stress response pathways (Figs. 2 and 5). Unique (present only in one succession stage) and common (present in all successional stages) genes accounted for 22.19% and 36.16% of total detected genes, respectively. The average of unique genes abundance from all functional path-
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ways was lower than that of non-unique genes. Bacteria displayed the highest proportion of unique (19.23%) and common (32.73%) genes (Table 2A). C- and N-cycling and stress response pathways showed similar proportion of unique and common genes (Table 2B). The proportion of unique genes, for all major taxa and metabolic pathways, was greater in soils ice-free for 4 years and markedly greater in soils ice-free for 7 years, than in the other successional stages (Table 2A–B). In fact, α-diversity indices (richness and Shannon index) for functional genes in soils being ice-free for 4years and 7 years were higher than in any other successional stages for the three pathways analyzed [SI Table S1]. However, due to the lowest ratios between the average of unique gene abundance and average non-unique gene abundance (AUA/ANUA) were found at soils ice-free for 4 and 7 years, these unique genes tended to be rare genes that were typically low in abundance. A hierarchical cluster analysis, based on all functional gene abundance (C-cycling, N-cycling and stress response pathways) from the different successional stages revealed that these genes clustered in two groups, with soils being ice-free for 4 years and 7 years forming a separate group from the rest [SI Figs. S6, S8]. Carbon metabolism. Autotrophy, acetogenesis, methanogenesis, methane oxidation and organic compound degradation genes were detected for microbial communities across all succession stages (Fig. 2, [SI Figs. S1, S2]). The potential for carbon fixation (photoautotrophy and chemoautotrophy) was indicated among 34 taxa among archaea, bacteria and algae (Fig. 2). Potential for acetogenesis was found in the Euryarcheota and 20 bacterial taxa with strongest signals for Deltaproteobacteria, Epsilomproteobacteria and Sphirochaetes (Fig. 2). The potential for methanogenesis was found in 4 archaeal and 15 bacterial taxa, with stronger signals for bacterial taxa (Fig. 2). We identified 6 bacterial taxa with capacity for methane oxidation. The strongest signal was for Proteobacteria (especially for Betaproteobacteria) and these were evenly distributed along the chronosequence. Verrucomicrobia methane oxidation genes were detected only in soils that were ice-free for 34 years (Fig. 2). The ability to carry out degradation of different organic compounds (e.g., starch, chitin, cellulose, lignin, pectin) was identified in 74 taxa among all the major domains (Fig. 2) with stronger signals for fungal taxa at different succession stages. Some of the major pathways involved in C-cycling were associated to specific succession stages along the glacier chronosequence (Fig. 3A). Degradative pathways for different organic polymers (starch, pectin, lignin and chitin) were associ-
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Table 2. Distribution of common (C, present in all the sampling points) and unique (U, present only in one sampling point) genes, for the entire chronosequence (total) and the different succession stages, among taxa (A) and different metabolic pathways (B). Values are expressed as percentages of the total genes detected. A TAXA
C (total) %
U (total) %
U (1yr) %
U (4yr) %
U (7yr) %
U (10yr) %
U (19yr) %
U (34yr) %
Archaea
0.97
0.97
0.97
0.97
0.97
0.97
0.97
0.97
Bacteria
32.73
19.23
2.47
3.87
7.62
1.97
1.65
1.64
Fungi
1.99
1.81
0.25
0.35
0.67
0.20
0.18
0.17
Others
0.47
0.29
0.06
0.05
0.10
0.03
0.02
0.03
METABOLIC CATEGORY
C (total)
U (total) %
U (1yr) %
U (4yr) %
U (7yr) %
U (10yr) %
U (19yr) %
U (34yr) %
C cycling
36.84
21.78
2.91
4.36
8.30
2.30
1.97
1.94
N cycling
34.10
22.05
2.95
4.43
8.69
2.28
1.95
1.75
Stress resp.
36.02
26.67
2.87
4.55
9.14
2.31
1.86
1.94
B
ated to microbial communities from soils being ice-free for 1 year. Meanwhile, the potential for cellulose degradation was associated to soils being ice-free for 1 year but also closely positioned to soils being ice-free for 34 years. Glyoxylate cycle and different degradative pathways (e.g., degradation of terpenes, cutine and hemicellulose) were associated to soils being ice-free for 19 years and aromatic compounds transformation to soils being ice-free for 34 years. The distribution of C-1 pathways genes (CH4 cycle) was not homogeneous: while potential for methanogenesis was associated to microbial communities from soils being ice-free for 7 years, bacterial methane oxidation was situated close to the subsequent succession stage, soils being ice-free for 10 years. Links between environmental attributes and functional diversity of gene involved in C-cycling could not be proven by Mantel test. Nitrogen metabolism. The potential for the major activities involved in N-cycling was detected for communities across all succession stages (Fig. 2, [SI Fig. S3]). N2 fixation genes were detected among 23 taxa, with the highest signals for Acidobacteria, Epsilonproteobacteria and Thermodesulfobacteria from different succession stages (Fig. 2). The potential for nitrification was found in 2 archaeal and 8 bacterial taxa, with the highest signal for Epsilonproteobacteria. We found 24 taxa among archaeal, bacterial and fungal domains capable to remove soil nitrate via denitrification, with the highest signals for different taxonomic groups (Verrucomicrobia, Deltaproteobacteria and Chloroflexi) at different succession stages. The ability to ammonification was found in a total
18 taxa among archaea, bacteria and fungi with highest signals for bacterial taxa. Genes for assimilatory nitrate reduction were found in Euryarchaeota and 12 bacterial taxa, showing the highest signals in Planctomycetes, Deltaproteobacteria and Deinococcus-Thermus. The potential for dissimilatory nitrate reduction was found in Euryarchaeota and 15 bacterial taxa, the highest signal were detected for Euryarchaeota, Deinococus-Thermus and Planctonomycetes genes. The ability to ammonia assimilation was found in a total 27 taxa among archaea, bacteria, fungi, algae and protozoa with highest signals for different taxonomic groups at different succession stages. The potential for annamox pathway was recognized only for Planctomycetes (Fig. 2) but with strong signal at every succession stage. Nitrogen-cycling pathways differed markedly along the chronosequence (Fig. 3B). Most genes were associated to non-forest succession stages. N fixation gene (nifH) was plotted close to soils being ice-free for 1 and 4 years indicating that these potential are mainly associated to initial succession stages. Denitrification genes were situated at the center of the ordination indicating that this activity is no clearly associated to any specific succession stage. The genes involved in nitrification were sited close to soils being ice-free for 1 year, dissimilatory nitrate reduction genes close to soils being icefree for 7 years, asssimilatory nitrate reduction genes close to soils being ice-free for 10 years and ammonia assimilation close to soils being ice-free for 19 years. Ammonification genes were ordinated near of soils being ice-free for 1 year and 10 years.
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Fig. 2. Distribution heatmap of carbon- and nitrogen-cycling genes among microbial taxa and succession stages. Blue color indicates non-detected signal, while intensity of positive signals are indicated from yellow (lower signal intensities) to red color (higher signal intensities).
Correlation between abundance of N-cycling genes and soil attributes was detected. Mantel test showed that NH4+ soil content was significantly correlated (r = 0.69, P < 0.05) with functional community structure related to nitrogen metabolism, suggesting that it is very important for explaining the variations between the functional genes from different successional stages. Other environmental variables such as pH, NO3- and total N and the time being ice-free showed also high correlation although the significance was lower (P < 0.1). Consistently, the results of RDA showed that NH4+,
NO3- and Total N based on their direction and magnitude were the most important factors influencing nitrogen metabolism functional community structure, when only significant environmental variables were included in the RDA biplot (Fig. 4). In the RDA ordination biplot, axis 1 and axis 2 explained 88.6% and 5.66%, respectively, of the variance in the relationship between the selected environmental variables and the N-cycling functional gene abundance, and showed the opposite direction of pH vector with respect to all the other factors. Notably, soils with lower NO3– content
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Fig. 4. Biplot of redundancy analysis (RDA) of N-cycling genes abundance and soil environmental variable significantly related to nitrogen metabolism functional community structure variations (pH, NH4+, NO3â&#x20AC;&#x201C; and Total N) in the Pia Glacier chronosequence.
Fig. 3. Two dimensional non-metric multidimensional scaling (NMDS) ordination plots of sampling points (Bray-Curtis similarities) showing the distribution of the different (A) C-cycling (stress = 0.096) and (B) N-cycling (stress = 0.074) pathways along the glacier chronosequence. Genes were grouped into different categories, which are shown in red.
(soils being ice-free for 1, 10 and 19 years) clustered together and soils with higher N-cycling gene abundance and diversity (soils being ice-free for 4 and 7 years being icefree) were segregated from the rest along the axis 1. Stress responses. Archaeal, bacterial and fungal stress response genes to cold and heat shocks, desiccation,
osmotic and oxidative stresses and glucose, oxygen, nitrogen and phosphate limitation were widespread along the chronosequence (Fig. 5). The highest signals were found for the genes less taxonomically widely distributed, such as genes for cold shock proteins found in a few groups of bacteria, for drought tolerance found in Euryarchaeota and some fungal groups, and for glucose limitation detected for Euryarchaeota and a few groups of bacteria. The signals were slightly more pronounced at soils that have been ice-free for 1 year, 4 years and 7 years for the most of the stress response genes (Fig. 5). Links between environmental attributes and abundance of gene involved in stress responses could not be proven. Virus signatures and antibiotic resistance. Virus signatures and antibiotic resistance. Genes from a total of 12 viral taxa were detected along the chronosequence, eight corresponding to viruses with eukaryotic hosts and four infecting prokaryotes. The eukaryotic-infecting viral signatures included two families of ssRNA (Alphaflexiviridae and Narnaviridae) and four of dsRNA fungal viruses (Chrysoviridae, Hypoviridae, Partitiviridae and Totiviridae). One family of ssDNA (Bacillariodnavirus) and one of dsDNA algal vi-
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Fig. 5. Distribution heatmap of stress response genes among microbial taxa and succession stages. Blue color indicates non-detected signal, while intensity of positive signals are indicated from yellow (lower signal intensities) to red color (higher signal intensities).
ruses (Phycodnaviridae) were also detected. On its behalf, within the four bacteriophage families identified, two corresponded to dsDNA (Caudovirales and Corticoviridae), one to ssDNA (Microviridae) and one to ssRNA (Leviviridae) viruses. Every viral family was detected at every succession stage, except for two bacteriophage families, Microviridae, only present at soils being ice-free for 1 and 4 years, and Corticoviridae, only detected at soils being ice-free for 4 years (Fig. 6). Alphaflexiviridae (with fungi and plants as natural host) genes increase in abundance along the succession (Fig. 6). Diverse categories of fungal, bacterial and archaeal antibiotic resistance genes encoding for isopencillin, phenazine-1-carboxilic acid, bacitracin, erythromycin, lincomy-
cin, p-aminobenzoic acid, 2,4-diacetylphloroglucinol, aminopyrrolnitrin, subtilin and streptomycin were detected at every sampling point (Table 3). The majority of them were of bacterial origin.
Discussion Soil microbial communities from Pia Glacier forefield differed in their putative functionality along the studied chronosequence, especially in carbon and nitrogen metabolism. Carbon and nitrogen fixation were associated primarily with initial succession stages. Our data indicates chemoautotrophic
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lectively they may be important in oligotrophic soils [3,8,46]. Strong phylum-specific role for microbial taxa in nitrogen- cycling was indicated and occurrence was closely related to soil characteristics. Younger nitrogen-poor soils supported high levels of nitrogen fixing and ammonification pathways, but also evidence of pathways for net loss of nitrogen from the soil via denitrification. In soils ice-free for 1 and 4 years, oxygen penetration could be facilitated by the lack of soils crust structure, which might favor the process of nitrification [7,30]. Nitrification processes have not been previously associated to initial succession stages of soil crusts development [8], but the fast colonization rates observed in these soils exposed after the Pia Glacier retreat (Fernández-Martínez et al., 2017) could facilitate a faster microbial colonization of N fixers and ammonifiers. The lack of nitrate plant assimilation processes can also contribute to the observed nitrate accumulation at soils being ice-free for 4 and 7 years. Dissimilatory nitrate reduction (associated to soils being ice-free for 7 years), assimilatory nitrate reduction (associated to soils being ice-free for 10 years) and denitrification (associated mainly to soils being ice-free for 7 and 10 years) could be facilitated by the accumulation of nitrates in previous succession stages. The bacterial ammonia assimilation associated to soils being icefree for 19 years could be facilitated by the previous production of ammonia through bacterial assimilatory and dissimilatory nitrate reduction. Previous studies have reported that soil
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pathways also operate in the forefield soil, thus expanding the microbial capacity to incorporate C to these soils beyond photoautotrophy, a feature also observed in other soils from extreme environments [12,18,56]. Pathways for nitrogen fixation were more commonly encountered for non-photosynthetic taxa. This highlights the importance of Proteobacteria and other taxa in nitrogen fixation, similarly to observations made for Antarctic soils [12]. Free-living Cyanobacteria, might have a lower contribution to the carbon and nitrogen fixation process in soils than previously assumed [39,61]. We detected genes involved in pathways of organic polymer degradation attributed to a wide range of different taxonomic groups along the chronosequence, although an interesting pattern emerged in that early successional stages were dominated by bacterial pathways whereas in later vegetated successional stages fungal pathways were more diverse. Higher abundance of bacterial taxa with high capacity of decomposing organic matter, including recalcitrant polymers, such as Actinobacteria has been found at the earliest successional stage than at later successional stages (Fernández-Martínez et al., 2017). Organic C inputs could have started via glacial runoff, wind-blown detritus or mammal and bird droppings [6,47,65], as well as ancient organic matter stored beneath the ice glacier [3]. Our data suggest strong potential for microbial turnover of these carbon reservoirs, including C-1 pathways (methanogenesis and methane oxidation), and col-
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Fig. 6. Relative abundance of viral families along the glacier chronosequence. Viral families were identified as eight microeukaryotic-infecting viruses (six fungal viruses: Alphaflexiviridae, Narnaviridae, Chrysoviridae, Hypoviridae, Partitiviridae and Totiviridae; two algal viruses: Bacillariodnavirus and Phycodnaviridae) and four prokaryote-infecting viruses (Caudovirales, Corticoviridae, Microviridae and Leviviridae).
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Table 3. Relative signal intensity of antibiotic resistance genes recovered from the GeoChip.Genes pcbC (isopencillin N synthase) and phzF (phenazine-1-carboxilic acid) were found in both eukaryotes and prokaryotes. Antibiotic resistance genes for prokaryotes were: bacA (bacitracin), igrD (erythromycin), lmbA (lincomycin), pabA (p-aminobenzoic acid), phlD (2,4-diacetylphloroglucinol), phzA (phenazine-1-carboxilic acid), prnD (aminopyrrolnitrin), spaR (subtilin) and strR (5â&#x20AC;˛-hydroxystreptomycin).
Eukaryotic
Prokaryotic
Gene
1 yr
4 yrs
7 yrs
10 yrs
19 yrs
34 yrs
pcbC
0.046
0.040
0.044
0.049
0.051
0.055
phzF
0.010
0.013
0.013
0.000
0.005
0.006
Archaea
phzF
0.005
0.005
0.005
0.000
0.000
0.000
Bacteria
bacA
0.013
0.014
0.014
0.015
0.019
0.015
igrD
0.022
0.020
0.022
0.023
0.022
0.026
lmbA
0.018
0.015
0.016
0.019
0.018
0.018
pabA
0.032
0.036
0.042
0.033
0.032
0.032
Fungi
pcbC
0.234
0.230
0.217
0.216
0.233
0.227
phlD
0.012
0.009
0.020
0.019
0.012
0.013
phzA
0.103
0.102
0.086
0.112
0.110
0.105
phzF
0.463
0.4890
0.490
0.476
0.457
0.458
prnD
0.017
0.013
0.013
0.012
0.018
0.012
spaR
0.011
0.012
0.006
0.012
0.011
0.006
strR
0.013
0.014
0.017
0.014
0.013
0.026
properties play a key role in structuring soil microbial communities [15,34,53]. N-cycling functional structure may be, therefore, closely linked to the successional soil development. The efficient use of available soil nutrients could be the main driver of the observed successional functional changes at Pia Glacier forefield. At initial succession stages, microorganisms are mainly involved in anabolic and catabolic pathways that help to increase nutrient availability. The subsequent colonization by lichen, mosses and pioneer vascular plants is accompanied by more complex microbial transformations such as denitrification and methanogenesis. This phenomenon of nutrient microorganism-plant competence has been reported in different glacier forefields over the world [10,25,29,54]. In addition, the vegetation cover formed by lichen, mosses and pioneer herbs could facilitate the early colonization of soils by taxonomic microbial groups with specific environmental requirements, through their contribution to the formation of diverse microenvironments [1,13]. Indeed, for soils ice-free for 7 years, where lichens, mosses and pioneer plants coexist, the proportion of unique genes is higher, which suggests a higher diversity of microhabitats with favorable conditions for specific microbial activities. Anaerobic conditions could be favored by the water holding capacity of terricolous lichens [13] and soil crusts [4] thus facilitating the
activity of denitrifying bacteria, and reducing nitrification processes [7,30] and inducing methanogenesis processes [27], in soils being ice-free for 7 years. The establishment of a consistent plant cover and the forest development, and the consequent higher availability of nutrients in soils, could result in dominance of catabolic microbial activities. In fact, organic soils from Nothofagus forest in the studied areas has been considered the major substrate for heterotrophic soil microbial communities [54]. The root exudation of carbohydrates or presence of plant litter in vegetated succession stages from the Pia Glacier forefield chronosequence can promote mobilization of both C and N from this organic matter because microbial communities have the potentials to degrade different organic compounds [6,62,63]. Gene signatures encoding enzymes that can degrade complex organic substrates (starch, linin, chitin and pectin) were associated primarily to pioneer communities of bacteria and fungi, but these genes were also detected at succession stages with presence of Nothofagus trees although with dominance of degradative fungal genes. Indeed, terpenes or hemicellulose degradation potentials were primarily associated to soils being ice-free for 19 years, and the degradation of aromatic compounds (activities also involved in lignin degradation pathway) to soils being ice-free for 34 years. The higher accumulation of plant litter at forest
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soils could induce the presence of microorganisms with capacity of degrading a broader range of organic compounds. Metabolic activities involved in the degradation of complex organic compounds have been previously associated to highly vegetated soils from other glacier forefields located at the Northern Hemisphere [3,22]. The lack of remarkable differences in stress response gene profiles along the studied chronosequence indicated that this is a generalized feature for microorganisms colonizing Pia Glacier forefield. These results do not suggest the existence of a strong abiotic control at this level along the chronosequence. The higher stress response gene diversity detected in microbial communities from younger soils could be related to the colonization by pioneer microorganisms with a wider range of stress tolerance strategies than colonizers of older soils [50,52]. Distribution of the relevant frequency of viral signals along the forefield appeared intimately related to the presence of their potential hosts along the succession, suggesting that virus could play a role in control on microbial populations along this succession process. In fact, the viral activity could suppose a ‘bottom-up’ trophic regulatory mechanism on their hosts along the studied chronosequence, similarly to the mechanism described for Antarctic endolithic microbial communities [57]. This strategy would explain the higher proportion of microeukaryote-infecting virus at respect to prokaryote-infecting ones found in soils being ice-free for 10 and 19 years, where extensive plant colonization facilitates the colonization by mycorrhizal and saprophytic fungi (FernándezMartínez et al., 2017). The restricted occurrence of the bacteriophage families Microviridae and Corticoviridae could be associated to the increase of soil water retention associated to lichen and moss colonization [13,42], or intermittent local flooding, due to these families have been described associated to specific hosts from moisture-sufficient soils [57]. The identification of antibiotic resistance genes along Pia Glacier forefield permit to suggest another potential biotic regulation of microbial community structure along primary succession, although marked successional patterns have not been found. The antibiotic resistance pathways could be involved not only in the defense against pathogens [12,24,32], but also in rapid microbial competitive response induced by low availability of nutrients [49,52]. This control could be characteristic of soil microbial communities because antibiotic resistance genes were not previously found in ice from Chile and Antarctica glaciers and attributed to the isolation of these areas [48]. Successional replacement of putative metabolic pathways associated to changes in community structure and soil attri-
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butes has been evident along Pia Glacier forefield succession. These results confirmed our expectations that functional community structure changes parallel to primary succession. In turn, microbial communities exhibited functional attributes that could modify the soil properties along the succession favouring the successional microbial taxa replacement and the fast establishment of plant communities. We suggest nutrient availability is a key driver for microbial functionality in soils.
Acknowledgements. We thank F. Massardo (Universidad de Magallanes) and David Palacios (UCM) for organising and supervising the field work and for logistic support. Captain Mansilla and the crew of ‘Don Pelegrín’ are thanked for their excellent navigation skills and hospitality on board. The development of the GeoChip 4.0 and associated computational pipelines used in this study was supported by Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA) through the US Department of Energy (DEAC02-05CH11231). This work was supported by grants CTM2012-38222-C02-01/02 and CTM2015-64728-C2-2-R from the Spanish Ministry of Economy and Competitiveness and the Institute for the Applied Ecology New Zealand. SPO was supported by the grants CTM201238222-C02-02 and RYC-2014-16784 from the Spanish Ministry of Economy and Competitiveness. Thanks are due to Spanish Education and Culture Ministry, for making possible discussion of some of the results through PRX15/00478 Salvador Madariaga grant to AdR. We are also very obliged to Laura Barrios (Unidad Estadística. Área de Informática Científica. SGAI, CSIC) for her statistical advice. Competing interests. None declared.
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RESEARCH ARTICLE International Microbiology 19(3):175-182 (2016) doi:10.2436/20.1501.01.275. ISSN (print): 1139-6709. e-ISSN: 1618-1095
www.im.microbios.org
Investigation of twenty selected medicinal plants from Malaysia for anti-Chikungunya virus activity Yik Sin Chan,1 Kong Soo Khoo,2 Nam Weng Sit1* Department of Biomedical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar, Perak, Malaysia. 2 Department of Chemical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar, Perak, Malaysia
1
Received 27 August 2016 · Accepted 30 September 2016
Summary. Chikungunya virus is a reemerging arbovirus transmitted mainly by Aedes mosquitoes. As there are no specific treatments available, Chikungunya virus infection is a significant public health problem. This study investigated 120 extracts from selected medicinal plants for anti-Chikungunya virus activity. The plant materials were subjected to sequential solvent extraction to obtain six different extracts for each plant. The cytotoxicity and antiviral activity of each extract were examined using African monkey kidney epithelial (Vero) cells. The ethanol, methanol and chloroform extracts of Tradescantia spathacea (Commelinaceae) leaves showed the strongest cytopathic effect inhibition on Vero cells, resulting in cell viabilities of 92.6% ± 1.0% (512 µg/ml), 91.5% ± 1.7% (512 µg/ml) and 88.8% ± 2.4% (80 µg/ml) respectively. However, quantitative RT-PCR analysis revealed that the chloroform extract of Rhapis excelsa (Arecaceae) leaves resulted in the highest percentage of reduction of viral load (98.1%), followed by the ethyl acetate extract of Vernonia amygdalina (Compositae) leaves (95.5%). The corresponding 50% effective concentrations (EC50) and selectivity indices for these two extracts were 29.9 ± 0.9 and 32.4 ± 1.3 µg/ml, and 5.4 and 5.1 respectively. Rhapis excelsa and Vernonia amygdalina could be sources of anti-Chikungunya virus agents. [Int Microbiol 19(3):175-182 (2016)] Keywords: Chikungunya virus · antivirals · cytotoxicity · sequential extraction · medicinal plants
Introduction The Chikungunya virus is a reemerging mosquito-borne virus that belongs to the family Togaviridae, genus Alphavirus and causes Chikungunya fever in humans. The virus was first isolated in 1952-1953, after an outbreak on the Makonde Plateau, Tanzania [25]. The virus reemerged from the coastal ar-
Corresponding author: Nam Weng Sit E-mail: sitnw@utar.edu.my *
eas of Kenya in 2004 with 5000 cases reported, and spread throughout the Indian Ocean islands (~270,000 cases in La Reunion island in 2005-2006), to India and Sri Langka (~1.4– 6.5 million cases in 2006-2007), Italy and France via imported cases in 2007, Caribbean and Central and South America (~440,000 cases in 2014) and North America (>10,000 cases in 2013–2015), causing high morbidity in over 50 countries or territories [25,28]. The virus is transmitted to humans mainly by Aedes aegypti and Aedes albopictus mosquitoes. The symptoms of Chikungunya fever, which include high fever, headaches, severe back and joint pain, and rash, appear after 4–7 days. Al-
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though the symptoms are self-limiting, arthralgia or arthritis may persist for months or even years [15]. The name “Chikungunya” is derived from a Makonde word that means “that which contorts or bends up” describing the distinctive severity of joint pains [31]. The medical treatment of Chikungunya virus infection relies on symptomatic relief as no specific treatment is available. Most of the deaths occur in neonates, adults with underlying medical conditions and the elderly. The Chikungunya virus mortality rate has been estimated to be 1:1000 [31]. Thus there is an urgent need to discover new antiviral compounds from natural resources especially medicinal plants [32]. Virtually all cultures have relied, and continue to rely on medicinal plants for primary health care. Plants are rich source of phytochemicals which have been proven to have antimicrobial, antihypertensive, antidiabetic, antioxidative, hepatoprotective, cardioprotective and other therapeutic activities. Around 50% of currently available drugs are derived from natural sources, using either natural substances or a synthesized analogue of the natural product [17]. Reviews highlighting the potential and discovery of new drugs from medicinal plants against viral infections have been published recently [6,12]. This study was performed to investigate extracts of 20 selected medicinal plants from Malaysia for anti-Chikungunya virus activity.
Materials and methods Plant materials. The aerial parts of Alternanthera sessilis, Asystasia gangetica, Ipomoea aquatica, Persicaria odorata and Talinum fruticosum, the rhizome hairs of Cibotium barometz, the stem of Cissus quadrangularis, and the leaves of the other thirteen plants were used in the study. Cibotium barometz and Physalis minima were obtained from Cameron Highlands, Pahang; Ficus deltoidea and Tradescantia spathacea were harvested from Batu Pahat, Johor; Pereskia bleo was obtained from Lukut, Negeri Sembilan; and the remaining plants were obtained from different towns in the state of Perak in Malaysia. The identity of these plants was confirmed by Professor Hean Chooi Ong, an ethnobotanist at the Institute of Biological Sciences, Faculty of Science, University of Malaya, Malaysia, and the scientific names were further confirmed using the database “The Plant List” [www.theplantlist.org]. Specimen vouchers were prepared and deposited at the herbarium of Faculty of Science, Universiti Tunku Abdul Rahman (Kampar campus) and the reference numbers assigned are listed in Table 1, which shows also the traditional uses of these plants (Table 1). Preparation of plant extracts.
Fresh plant materials were washed thoroughly with tap water. The plant samples were then blended and extracted sequentially with hexane, chloroform, ethyl acetate, ethanol, methanol and distilled water at room temperature with agitation (100 rpm) using an orbital shaker (IKA-Werke KS 501, Germany). The maceration was carried out for three cycles (one day per cycle). The filtrates were evaporated at 40°C using a rotary evaporator (Buchi Rota-vapor R205, Switzerland), ex-
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cept for the water extracts which were lyophilized using a freeze-dryer (Martin Christ Alpha, UK). The dried extracts were reconstituted in a dimethyl sulfoxide-ethanol mixture (60:40, v/v) to achieve a stock concentration of 256 mg/ml. The extracts were then sterilized using 0.45 μm syringe filters and stored at −20°C prior to use.
Cell culture and virus propagation.
African monkey kidney epithelial (Vero) cell line (CCL-81) was purchased from American Type Culture Collection. The cell line was used for propagation of Chikungunya virus, cytotoxicity testing of plant extracts and cytopathic effect inhibition assay. The cell line was maintained in Dulbecco’s modified Eagle medium (DMEM) (Sigma-Aldrich, St Louis, USA) supplemented with 5% of fetal bovine serum (Gibco, New York, USA), 1% of penicillin-streptomycin (Gibco, New York, USA) solution and sodium bicarbonate (Merck, Kenilworth, USA). Cultured Vero cells were incubated at 37°C in a humidified atmosphere with 5% of carbon dioxide [9]. The medium was changed twice a week. The Chikungunya virus (accession number EU703761) used belonged to the Bagan Panchor strain (Asian genotype) and was provided by Professor Shamala Devi of Faculty of Medicine, University of Malaya, Malaysia. The virus was propagated in the Vero cells and harvested after cytopathic effect had developed and stored at –80°C prior to bioassay.
Cytotoxicity assay.
The cytotoxicity assay was carried out by seeding 4 × 104 Vero cells in each well of 96-well microtiter plates and incubated for 24 h at 37°C in a humidified incubator with 5% CO2. Fresh DMEM medium (supplemented with 1% of fetal bovine serum) containing eight twofold serially diluted concentrations of extracts (640 to 5 µg/ml, 100 µl each) was added after 24 h of cell seeding while control wells contained cells without the test sample. The microtiter plates were then incubated at 37°C in a humidified incubator with 5% CO2 for 72 h. The cell viability was determined by the neutral red uptake assay [22]. The assay was conducted in three independent experiments with duplicates for each experiment.
Cytopathic effect inhibition assay.
Non-toxic concentrations of the extracts with cell viability ≥ 90%, as determined from the cytotoxicity assay, were used in the cytopathic effect inhibition assay. Vero cells (4 × 104 cells/well) were seeded in 96-well microtiter plates and incubated at 37°C and 5% CO2 for 24 h. Extracts of six concentrations, obtained by twofold serial dilution in DMEM (supplemented with 1% of fetal bovine serum) were then added together with Chikungunya virus at multiplicity of infection of 1. The virus titer was determined using the Reed and Muench method [21]. Medium (DMEM only), virus (cells with virus only) and cell (cells with medium only) controls were included in each microtiter plate. Chloroquine (MP Biomedicals, Illkirch, France; purity > 99.9%) with a concentration range of 0.39 to 12.4 µM was used as the positive control. The microtiter plates were then incubated at 37°C and 5% CO2 for 72 h. Determination of cell viability was carried out by the neutral red uptake assay [22]. The assay was performed in three independent experiments with duplicates for each experiment.
Quantitative RT-PCR. Quantitative RT-PCR was performed to determine the effects of selected active extracts (cell viability ≥ 70% in the cytopathic effect inhibition assay) on the Chikungunya virus replication by quantifying the viral genomic RNA copies based on the one-step SYBR Green based quantitative RT-PCR assay of Ali et al. [2]. The oligonucleotides were designed from the E1 region of Chikungunya virus and the sequence for the forward primer and reverse primer was 5′- CTCATACCGCATCCGCATCAG-3′ and 5′-ACATTGGCCCCACAATGAATTTG-3′ respectively. Tenfold serial dilutions of a virus stock with a known copy number (1010 to 100) were used to generate a standard curve in which the Chikungunya virus RNA
Mistletoe fig, “mas cotek” Jiaogulan, five-leaf ginseng Water spinach, water morning glory Malabar melastome Shiny bush or silver bush Rose cactus, leaf cactus Vietnamese mint, “Laksa leaf”
Ground cherry, wild cape gooseberry Broadleaf lady palm, bamboo palm Star goose berry, sweet leaf
Waterleaf Boatlily, oyster plant, Moses-in-theCradle White buttercup Bitter leaf
Moraceae
Cucurbitaceae
Convolvulaceae
Melastomataceae
Piperaceaea
Cactaceae
Polygonaceae
Solanaceae
Arecaceae
Phyllanthaceae
Talinaceae
Commelinaceae
Passifloraceae
Compositae
Ficus deltoidea Jack
Gynostemma pentaphyllum (Thunb.) Makino
Ipomoea aquatica Forssk.
Melastoma malabathricum L.
Peperomia pellucida (L.) Kunth
Pereskia bleo (Kunth) DC.
Persicaria odorata (Lour.) Soják
Physalis minima L.
Rhapis excelsa (Thunb.) Henry
Sauropus androgynus (L.) Merr.
Talinum fruticosum (L.) Juss.
Tradescantia spathacea Sw.
Turnera subulata Sm.
Vernonia amygdalina Delile
Antiinflammatory, anodyne [33]
Golden chicken fern, woolly fern “Edible stemmed vine”
Cibotiaceae
Vitaceae
Mountain pomegranate, false guava, thorny bone-apple
Rubiaceae
Catunaregam spinosa (Thunb.) Tirveng.
Cibotium barometz (L.) J.Sm.
Chinese violet
Acanthaceae
Asystasia gangetica (L.) T.Anderson
Cissus quadrangularis L.
Paralysis, leprosy, cough [5]
Bird’s nest fern
Aspleniaceae
Asplenium nidus L.
Leaf
Leaf
Leaf
Aerial part
Leaf
Leaf
Leaf
Aerial part
Leaf
Leaf
Leaf
Aerial part
Leaf
Leaf
Stem
Rhizome hairs
Leaf
Aerial part
Leaf
Aerial part
Part used
UTAR/FSC/12/004
UTAR/FSC/12/002
UTAR/FSC/13/006
UTAR/FSC/13/002
UTAR/FSC/11/010
UTAR/FSC/12/008
UTAR/FSC/14/003
UTAR/FSC/11/009
UTAR/FSC/11/011
UTAR/FSC/14/002
UTAR/FSC/13/007
UTAR/FSC/13/010
UTAR/FSC/12/010
UTAR/FSC/10/021
UTAR/FSC/11/007
UTAR/FSC/12/009
UTAR/FSC/13/003
UTAR/FSC/12/001
UTAR/FSC/11/008
UTAR/FSC/13/009
Specimen voucher number
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Nausea, bacterial infection, malaria, diabetes [34]
Coughs, bronchitis [1]
Fever, cough, bronchitis [26]
Polyuria, internal heat, measles, gastrointestinal disorders [27]
Increase lactation, cough, hypertension, diabetes, nose ulceration, eye ailments, earache [20]
Hemostatic, antidysenteric [11]
Diuretic, purgative, anthelmintic, fevers, dropsy [10]
Fever, swellings, nausea, acne, hair and skin conditions, digestion, stomach complaints [24]
Cancer, hypertension, diabetes, gastric pain, ulcer [35]
Bone aches, headache, fever, eczema, abdominal pains [19]
Toothache, wounds, diarrhea, anti-infection, scar prevention [13]
High blood pressure, diabetes and possess cooling effect [3]
Heat clearing, detoxification, relieving cough [16]
Diabetes, disorders of menstrual cycle [8]
Skin infections, gastritis, asthma, constipations, eye diseases, piles, anemia, burns, wounds, fracture healing [23]
Rheumatism, swelling, diabetes, asthma [29]
Hypertension, kill lice, contraceptive [7]
Cuts and wound, gives cooling effect to body, relieves neuritis [30]
Sessile joyweed, dwarf copperleaf
Amaranthaceae
Alternanthera sessilis (L.) R.Br. ex DC.
Traditional use
Common name
Family
Plant species
Table 1. The family, common name and traditional uses of 20 selected medicinal plants from Malaysia
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standard was obtained by in vitro synthesis of RNA transcripts from DNA templates using MAXIscript in vitro kit (Ambion, Texas, USA). Sample RNAs were harvested from the extract-treated, virus-infected Vero cells and extracted using Invisorb spin virus RNA Mini Kit (Invitek, Berlin, Germany). The RT-PCR was conducted using the iScript One-Step RT-PCR kit (Biorad, Hercules, California, USA). The samples were assayed in a 25 µl reaction containing 2 µM of each forward and reverse primer, 5 µl of extracted RNA, 0.25 µl of reverse transcriptase, and 12.5 µl of SYBR Green Premix 2X. The amplifications were performed using Rotar Gene Q (Qiagen, Valencia, USA) with thermal cycling consisting of a reverse transcription step at 50°C for 30 min, initial denaturation at 95°C for 15 min, followed by 40 cycles of amplification step and a final extension at 72°C for 10 min. The Chikungunya virus RNA copy number present in the extract-treated, virusinfected cells was then quantified using the generated standard curve based on the cycle threshold (Ct) values against serially diluted Chikungunya virus stock. All samples were assayed in triplicates.
Data analysis. The percentages of cell viability at different extract concentrations were analyzed by one-way analysis of variance using IBM SPSS Statistics (Version 20) software. The significance level was set at P < 0.05. Post hoc test, either with Tukey’s (equal variance assumed) or Dunnett’s (equal variance not assumed) test was further conducted to determine which concentration of an extract that produced significant result.
Results As a wide polarity range of solvents were used in the extraction, hexane and chloroform extracts can be grouped as nonpolar extracts, ethyl acetate extract as intermediate polar extract, and ethanol, methanol and water extracts as polar extracts. For the cytotoxicity study, nonpolar and intermediate polar extracts were generally more toxic to the Vero cells than polar extracts (data not shown) which prevented the evaluation of their potential antiviral effects at higher concentrations. Non-toxic concentrations (cell viability ≥ 90%) of an extract were then screened for cytopathic effect inhibitory activity. We classified the cytopathic effect inhibitory activity as strong (cell viability ≥ 70%), moderate (cell viability from 31% to 69%), and weak (cell viability ≤ 30%). Based on this classification, out of 120 extracts, only 9 showed strong inhibitory activity (Table 2) while 24 of the extracts showed moderate inhibitory activity. They were Alternanthera sessilis (chloroform), Asystasia gangetica (ethyl acetate and ethanol), Catunaregam spinosa (ethyl acetate, ethanol and methanol), Ficus deltoidea (ethanol and methanol), Ipomoea aquatica (ethanol and methanol), Melastoma malabathricum (chloroform, ethyl acetate, ethanol, methanol and water), Peperomia pellucida (chloroform), Persicaria odorata (methanol), Physalis minima (ethanol and methanol), Rhapis excelsa (hexane, ethyl acetate, ethanol and methanol), and Vernonia
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amygdalina (chloroform). The rest of the extracts possessed weak inhibitory activity. Nine extracts which showed strong cytopathic effect inhibitory activity were derived from five medicinal plants (Fig. 1). The ethanol and methanol extracts of T. spathacea showed the strongest cytopathic effect inhibition, with cell viabilities of 92.6% ± 1.0% and 91.5% ± 1.7% (mean ± s.d., n = 3) respectively at 512 µg/ml. This was followed by the chloroform extract of T. spathacea (88.8% ± 2.4% at 80 µg/ml), ethyl acetate extract of I. aquatica (87.2% ± 3.8% at 320 µg/ml) and methanol extract of V. amygdalina (81.9% ± 5.0% at 320 µg/ml). The 50% effective concentrations (EC50), as determined from the plot of percentages of cell viability against extract concentrations, and selectivity indices for these extracts are shown in Table 2. The chloroform extract of R. excelsa and the ethyl acetate extract of V. amygdalina had the lowest EC50 value and resulted in the highest selectivity indices (Table 2). The selectivity indices for the ethanol and methanol extracts of T. spathacea could not be calculated as there was no significant cytotoxicity recorded for these two extracts even at the highest concentration tested (640 µg/ml). Extracts which exhibited strong inhibitory activity were selected for Chikungunya viral load quantification by using quantitative RT-PCR and the results are shown in Table 3. The percentage of reduction in viral load of an active extract was compared with the virus control, in which the mean RNA copy number was 1.36 x 109 copies/µl after 72 h post infection without any extract treatment. The chloroform extract of R. excelsa produced the highest percentage of reduction of viral load with 98.1%, followed by the ethyl acetate extract of V. amygdalina at 95.5% and the ethanol extract of P. odorata at 89.9%. In contrast, the ethanol and methanol extracts of T. spathacea were only able to reduce the viral load by 52.7% and 46.3% respectively (Table 3).
Discussion A total of 120 extracts obtained from 20 medicinal plants belonging to 20 different families were investigated for the cytotoxic and anti-Chikungunya virus activities. A Vero cell line was used as it is one of the most common and well established mammalian cell lines used to assess the effects of chemicals, toxins and other substances at the molecular level [4]. The cell line is also known to be susceptible to many viruses, including Chikungunya virus [25], and displayed cytopathic effect upon infection. The cytopathic effect inhibitory activity of an extract de-
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Fig. 1. Viability of African monkey kidney epithelial (Vero) cells co-incubated with the Chikungunya virus and the plant extracts at 37ยบC and 5% CO2 for 72 h. (A) Ipomoea aquatica, (B) Persicaria odorata, (C) Rhapis excelsa, (D) Tradescantia spathacea and (E) Vernonia amygdalina. The cell viability was determined by the neutral red uptake assay. The asterisk mark indicates significant difference (P < 0.05) when analyzed with one-way ANOVA test. The x-axis is displayed in log scale.
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Table 2. Fifty percent cytotoxic concentration (CC50) and fifty percent effective concentration (EC50) of the medicinal plant extracts which have strong cytopathic effect inhibitory activity against the Chikungunya virus on African monkey kidney epithelial (Vero) cells Plant
Extract
CC50a (µg/ml)
EC50a (µg/ml)
Selectivity indexb
Ipomoea aquatica
Ethyl acetate
> 640
227.0 ± 7.2
> 2.8
Persicaria odorata
Ethanol
454.9 ± 6.9
132.7 ± 2.7
3.4
Rhapis excelsa
Chloroform
161.5 ± 19.2
29.9 ± 0.9
5.4
Tradescantia spathacea
Chloroform Ethanol Methanol
238.5 ± 3.1 NA NA
60.2 ± 0.6 202.2 ± 2.1 179.0 ± 9.7
4.0 NA NA
Vernonia amygdalina
Ethyl acetate Ethanol Methanol
165.5 ± 9.2 272.4 ± 6.6 485.5 ± 2.8
32.4 ± 1.3 67.3 ± 1.2 199.9 ± 13.7
5.1 4.0 2.4
Results are presented as mean ± standard deviation, n = 3. bSelectivity index is calculated as CC50/EC50. NA denotes could not be determined as there was no significant cytotoxicity at the highest concentration (640 µg/ml) used.
a
pends on the plant species, type of solvent used for extraction, and extract concentration used in the assay. The extracts that possessed strong inhibitory activity against the Chikungunya virus were extracted mostly using chloroform, ethyl acetate, ethanol and methanol (Fig. 1). Although the ethanol and methanol extracts of Tradescantia spathacea exerted the strongest cytopathic effect inhibitory activity, the chloroform extract of Rhapis excelsa and ethyl acetate extract of Vernonia amygdalina had the highest percentage of reduction in the viral load compared to the virus control. This can be explained by the different targets of active extracts in inhibiting the virus. To control viral infection, various aspects of viruses, such as their structure, strategies for multiplication and propaga-
tion, and viral entry and release in the host cells could serve as potential targets for antiviral therapy [6]. The results from the viral load study suggest that the chloroform extract of R. excelsa and ethyl acetate extract of V. amygdalina might have direct virucidal effect on the Chikungunya virus. While active extracts of T. spathacea, in addition to the virucidal effect, might also inhibit the release of mature virus from the infected cells and prevent the spread of the virus to other cells. Phytochemical analysis of the leaf of T. spathacea reveals the presence of secondary metabolites such as alkaloids, flavonoids, glycosides, saponins and tannins [18]. The leaves of V. amygdalina contain alkaloids, anthraquinone, coumarins, glycosides, polyphenolics, reducing sugar, saponins, steroids,
Table 3. Quantitative RT-PCR analysis of viral load in the African monkey kidney epithelial (Vero) cells co-incubated with the Chikungunya virus and selected medicinal plant extracts Plant
Extract
Concentration (µg/ml)
RNA copy numbera (copies/µl)
Percentage of reductionb (%)
Ipomoea aquatica
Ethyl acetate
320
4.78 x 108 ± 0.43x 108
64.9
Persicaria odorata
Ethanol
160
1.37 x 108 ± 0.32 x 108
89.9
Rhapis excelsa
Chloroform
40
0.26 x 108 ± 0.07 x108
98.1
Tradescantia spathacea
Chloroform Ethanol Methanol
80 512 512
2.22 x 108 ± 0.71 x 108 6.44 x 108 ± 0.96 x 108 7.30 x 108 ± 0.44 x 108
83.7 52.7 46.3
Vernonia amygdalina
Ethyl acetate Ethanol Methanol
80 160 320
0.61 x 108 ± 0.17 x 108 2.26 x 108 ± 2.86 x 108 2.35 x 108 ± 0.15 x 108
95.5 83.4 82.7
Results are presented as mean ± standard deviation, n = 3. bThe percentage of reduction of the chikungunya virus RNA copy number is compared with the virus control (1.36 x 109 copies/μl) after 72 h post infection.
a
ANTI-CHIKUNGUNYA VIRUS ACTIVITY
and terpenoids [34]. Very little is known about secondary metabolites of R. excelsa. Hassanein et al. [11] reported the isolation of four flavonoids, i.e., apigenin-8-C-glucoside (vitexin), apigenin-6,8-di-C-β-glucopyranoside (vicenin-2), luteolin6-C-glucoside (isoorientin) and luteolin-8-C-glucoside (orientin) from the leaves of R. excelsa. Some phytochemicals in these plants may account for the antiviral activity observed in this study. The flavonoid silymarin was recently identified to possess significant anti-Chikungunya virus activity at the post-entry stages [14]. Andrographolide, a bicyclic diterpenoid lactone from the plant Andrographis paniculata is effective in inhibiting Chikungunya virus replication [32]. Treatment with the leaf extracts of Rhapis excelsa and Vernonia amygdalina resulted in the highest percentage of reduction in the viral load and could be a potential source of novel anti-Chikungunya virus compounds. Thus further efforts are needed to isolate and characterize the active compounds, and to investigate the mechanism of their action. Acknowledgements. The authors thank Kuok Foundation for the financial support provided to the project (Vote: 4393/000) and Ministry of Higher Education, Malaysia for the MyMaster scholarship granted to Yik Sin Chan for her Master of Science candidature. Competing interests. None declared.
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