Pennscience Vol 12 Issue 2 Sleep

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Contents Features 05 Sleep:

An Introduction

Sleep Research Aids 08 in Understanding of Neurodegenerative Diseases

10 Suspended Animation

and Sleep: A Complicated Relationship Memory and Sleep 12

15 How Drugs Affect Sleep

Research of Dermal Papilla Cell Origin in Hair 17 Analysis Follicle Neogenesis after Wounding Antimicrobial, Cytotoxic, and Antiproliferative Properties of Native and Invasive Orchids in the Dominican Ethnobotany

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Signatures of Rats Resilient or Vulnerable to Social 29 miRNA Defeat Stress

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Editorial Staff Coby Basal Nicholas Lim Karanbir Pahil Donald Zhang

Sarah Murray Vihang Nakhate

DESIGN EDITORS Courtney Connolly Carolyn Lye

WRITING MANAGERS Natalie Neale Donald Zhang

EDITING MANAGERS Maria Lee Vivek Nimgaonkar

BUSINESS MANAGER Claudia Cheung

COPY EDITING

WRITING

EDITORS-IN-CHIEF

EDITING

Carolyn Lye Mike Zhai

WEBSITE

Terry Sun Adel Qalieh

Ishmam Ahmed Yixuan Geng Megan Hayes Mufadal Maloo Karanbir Pahil Vishal Patel Ivan Ye Edward Zhao

DESIGN

Ryan Bliss

ASSISTANT BUSINESS MANAGERS Luke Chen Yixuan Geng

FACULTY ADVISORS

Dr. M. Krimo Bokreta Dr. Jorge Santiago-Aviles

About PennScience PennScience is a peer-reviewed journal of undergraduate research published by the Science and Technology Wing at the University of Pennsylvania. PennScience is an undergraduate journal that is advised by a board of faculty members. PennScience presents relevant science features, interviews, and research articles from many disciplines including biological sciences, chemistry, physics, mathematics, geological sciences, and computer sciences. PennScience is a SAC funded organization. For additional information about the journal including submission guidelines, visit www.pennscience.org or email us at pennscience@gmail.com.

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Letter from the Editors Dear Readers, We are thrilled to present our second issue of the 9th volume of PennScience. The theme for this issue, sleep, was inspired by some fascinating recent advances in elucidating the molecular basis of this familiar and rather elusive phenomenon. For instance, research published in Science last fall suggests that sleep may be crucial for the removal of toxic metabolites from the interstitial space in brain tissue1. Our features aim to explore the mysteries of sleep in the context of recent findings and also to shed some light on its role in health and disease as we understand it today. We are incredibly grateful to all our staff writers who contributed to this issue. Natalie Neale opens with an introduction to sleep, explaining some of the hormonal factors behind sleep, the impacts of the circadian rhythm, and the different stages of sleep. Nicholas Lim steps into ongoing research on the relationship between sleep disturbances and neurodegenerative diseases like Huntington's and Parkinson's. Donald Zhang discusses the relationship between hibernation and sleep and the potential for suspended animation in the future. Karanbir Pahil explores a subject a bit closer to home for students: does sleep improve memory? Finally, Coby Basal provides a practical overview of sleep aids available today and their potential consequences. As always, this PennScience issue also showcases excellent undergraduate research papers. Laura Doherty investigates the role of dermal papilla cells in hair follicle regeneration. Matthew Bond explores the medicinal properties of invasive orchids in Dominican Republic. Finally, Benjamin Nicholas investigates how the regulation of micro RNAs may underlie resilience or susceptibility to social stress. We have greatly enjoyed our time leading PennScience, and we would like to welcome Vivek Nimgaonkar and Donald Zhang as our new Co-Editors-in-Chief. As we leave, we would like to thank the groups and individuals who have made PennScience possible. First, we would like to thank our incredible journal staff for their relentless hard work, dedication, and enthusiasm for the journal. We owe our funding to the Student Activities Council and the Science and Technology Wing, without which we could not publish a high quality journal. We would also like to thank our faculty advisors, Dr. Bokreta and Dr. Santiago-Aviles, for their unwavering support and guidance. Finally, we would like to thank the Penn faculty who took the time to meet with us and share their insights. Thank you for reading PennScience and we hope you enjoy our latest issue! Sincerely, Sarah Murray and Vihang Nakhate Co-Editors-in-Chief 1

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Xie, L., et al. (2013) Sleep drives metabolite clearance from the adult brain. Science 18, 373-377.

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SLEEP:

An Introduction

By Natalie Neale

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t is well known that sleep is a behavioral phenomenon necessary to our survival. While it is related to other phenomena such as coma and hibernation, sleep is distinct from these. Sleep is characterized by several key aspects, including behavioral quiescence, stereotypical posture, increased arousal threshold, and an increase in activity following deprivation. Sleep and chronobiology research over the years has provided insight into the neurobiological mechanisms of sleep, and this research continues to progress. Nonetheless, relatively little is known about why sleep is important on a biological level. Current research aims to uncover this and other mysteries surrounding sleep, as well as how to optimize health and activity around sleeping behavior. Central to understanding sleep is the concept of the circadian rhythm of human sleep-wake cycles. In adult humans, the average period for the sleep-wake cycle is 24.18 hours (1). Sleep onset and offset can be influenced by zeitgebers, which are environmental stimuli that can cause phase shifts in our biological clocks. The dominant zeitgeber is light, but other factors such as caffeine and exercise can also influence sleepiness and wakefulness. Zeitgebers, particularly light, entrain the human sleep-wake cycle to the Earth’s photoperiod, and in the absence of them, a phenomenon called “free-running” will occur, in which the human sleep-wake cycle will oscillate at its internal rhythm of 24.18 hours, slightly longer than the 24 hour day of Earth. Humans do not free-run under normal conditions because the human brain is sensitive to the 24-hour photoperiod established by Earth’s rotation, as the pineal gland releases the hormone melatonin periodically to promote sleep onset (2). This process begins with retinal ganglion cells that contain a photopigment called melanopsin and are sensitive to light (3). These cells relay signals to the brain via the retinohypothalamic tract, a neural pathway that is separate from the main visual pathway (4). This tract projects to the suprachiasmatic nucleus (SCN) in

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the midbrain and is considered the biological clock of the brain (4). The SCN serves as a pacemaker and promotes a circadian rhythm in all tissues of the body, as well as circadian release of particular hormones. The biological clock mechanism in the SCN operates based on negative feedback: gene transcription is stimulated periodically, and as the protein products accumulate, they eventually suppress their own transcription (Figure 1). The positive factors in the feedback loop are transcription factors named BMAL1 and CLOCK, which promote transcription of genes encoding proteins CRY1, CRY2, PER1, PER2 and PER3 (5). As CRY and PER proteins accumulate, they inhibit the ability of BMAL1 and CLOCK to promote their own transcription, resulting in a negative feedback loop that oscillates according to time of day. The SCN regulates melatonin, which signals the brain to go to sleep (levels are highest in the early evening). Cortisol, considered the “wake” hormone, does the opposite, but it is also regulated by the SCN (5). This sleep-wake cycle is crucial, and irregularities in it may even serve as a predictor for neurodegenerative disease. In addition to circadian rhythm control of sleep through hormonal regulation, sleepiness and wakefulness are also affected by homeostatic factors — regardless of time of day, sleepiness increases with sleep deprivation. Alertness is also influenced by endogenous factors, like stress and exogenous factors, such as caffeine and exercise. In addition to the discovery of circadian and homeostatic drives for sleep, the stages of the sleep cycle have been discovered as well. Stages of sleep are split into five stages (Figure 2) (6). Stage 1 is light sleep and involves high amplitude theta waves seen in EEG recordings. In stage 2, sleep spindles appear, body temperature drops and heart rate slows. In stage 3, sleep becomes deeper and delta waves occur. Stage 4 is known as delta sleep because of the increasing number of delta waves. Stage 5 is rapid eye movement (REM) sleep, when dreaming occurs and voluntary muscles become paralyzed. After stage 4, stage 3 and stage 2 can follow before entering REM sleep, and after REM, humans usually return to stage 2. This cycle occurs 4 or 5 times throughout the night. People usually enter their first REM phase 90 minutes into sleep, and REM stages get longer throughout the night. The amount of REM and nonREM sleep are under circadian control, further emphasizing the importance of the human pacemaker on not just sleep onset, but on brain activity during sleep. Given the developments in the understanding of sleep and chronobiology, there is now growing concern and research surrounding the health implications of overnight shifts, jet lag, and technologies that keep the world bright and operating throughout the night. These activities put humans out of sync with their endogenous biological rhythms, resulting in sleep deprivation and disorders such as delayed sleep syndrome and night shift disorder. It is widely known that sleep deprivation is harmful, compromising our health as well as cognitive performance (7). Decreased cognitive performance due to sleep deprivation can even lead to tragedies such as car and airplane crashes. There are over 100,000 drowsy driving crashes per year in 6

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the United States (9). Given what we know about circadian rhythm and homeostatic sleep drive, scientists are investigating ways to potentially manipulate the sleep-wake cycle using zeitgebers to promote wakefulness at the appropriate times. In addition to cognitive performance, understanding the circadian rhythm also has medical implications. Since the circadian clock, which regulates sleep wake cycles, also regulates oscillations in various hormone levels throughout the day, scientists hope to apply this knowledge to proper treatment regimens for a variety of diseases. Sleep and chronobiology are even relevant to cancer, as tumor growth may increase when circadian rhythms are out of sync. There has been research suggesting a link between night shift work and breast cancer (10). Not only is sleep important to cognitive function and general health, but research is also exploring the crucial role it may serve in memory consolidation. Clearly, sleep is an important phenomenon that serves a vital role in many aspects of our lives. There has been profound progress in understanding the structure and mechanisms of sleep, and research is starting to elucidate why animals require sleep. This research will have profound implications across various aspects of public health and society.

Resources 1. C. A. Czeisler, et al., Stability, Precision, and Near-24Hour Period of the Human Circadian Pacemaker. Science. 284, 2177-2181 (1999).. 2. J. Arendt, Melatonin and the pineal gland: influence on mammalian seasonal and circadian physiology. Reproduction. 3, 13-22 (1998). 3. S. Hattar, et. al, Melanopsin-Containing Retinal Ganglion Cells: Architecture, Projections, and Intrinsic Photosensitivity. Science. 295, 1065-1070 (2002). 4. A. A. Sadun, J. Schaechter, L. Smith, A retinohypothalamic pathway in man: Light mediation of circadian rhythms. Brain Research. 302, 371-377 (1984). 5. E. F. Pace-Schott, A. Hobson, The Neurobiology of Sleep: Genetics, cellular physiology and subcortical networks. Nature. 3, 591-605 (2002). 6. A. A. Borbely, et. al, Sleep deprivation: Effect on sleep stages and EEG power density in man. Electroencephalography and Clinical Neurophysiology. 51, 483-493 (1981). 7. M. Corsi-Cabrera, et. al, Amplitude reduction in visual event-related potentials as a function of sleep deprivation. Europe PubMed Central. 22, 181-189 (1999). 8. H. P. A. Van Dongan, et. al, The Cumulative Cost of Additional Wakefulness: Dose-Response Effects on Neurobehavioral Functions and Sleep Physiology From Chronic Sleep Restriction and Total Sleep Deprivation. Sleep. 26,117-126 (2003). 9. National Highway Traffic Safety Administration, Research on Drowsy Driving. Retrieved from http:// www.dot.gov.


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Call for Submissions Looking for a chance to publish your research? PennScience is accepting submissions for our upcoming Fall 2014 issue! Submit your independent study projects, senior Design projects, reviews, and other original research articles to share your work with fellow undergraduates at Penn and beyond. Email submissions and any questions to pennscience@gmail.com.

Research in any scientific field will be considered, including but not limited to:Â

Biochemistry | Biological Sciences | Biotechnology | Chemistry | Computer Science | Engineering | Geology | Mathematics | Medicine | Physics | Psychology

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SLEEP RESEARCH AIDS IN UNDERSTANDING OF

NEURODEGENERATIVE DISEASES

By Nicholas Lim

Understanding sleep disturbances

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any people who suffer from neurodegenerative diseases like Alzheimer’s disease (AD) and Parkinson’s disease (PD) often experience changes in their sleep patterns. It is still unclear why this happens. However, the growing body of work in sleep science is beginning to decode the cause of these disturbances in the sleep-wake cycle and circadian rhythm. Additionally, it is known that sleep disturbances may precede other symptoms of neurodegeneration and cognitive decline. This raises the tantalizing possibility of using sleeping patterns as a diagnostic marker to identify patients at-risk for neurodegenerative diseases before they present cognitive or motor symptoms.

Alzheimer’s disease preceded by sleep irregularities Scientists have found that irregularities in the sleep-wake cycle can foreshadow a person’s clinical development of Alzheimer’s disease. AD is characterized by the loss of neurons in the cerebral cortex and other subcortical regions, and it is the leading cause of dementia worldwide (1). One of the hallmarks of AD is the accumulation of the protein amyloid-β (Aβ) into aggregates called plaques. The initiation of AD pathogenesis seems to occur when normal, soluble Aβ undergoes a conformational change into malformed complexes of oligomers, protofibrils, and fibrils. The accumulation of these Aß plaques is concentration-dependent and confers toxicity to neurons (2). Understanding the factors that regulate soluble Aβ levels is critically important to elucidating the pathogenesis of AD. David Holtzman’s lab at Washington University in St. Louis observed that soluble levels of Aβ in mice brains seem to peak during waking hours and fell as mice slept (3). Furthermore, they discovered that depriving the mice of sleep led to a dramatic rise in Aβ concentration

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FEATURES (4). Holtzman’s findings suggested that sleep disturbances could precipitate amyloid plaque formation. If sleep cycle irregularities increase the concentration of soluble Aβ, then sleep disturbances earlier in life may predispose people to Alzheimer’s. In 2012, Holtzman further showed that the natural cycle of waking and sleeping breaks down in mice following plaque formation, but is restored again when antibodies are used to eliminate the plaques (5). The aggregation of amyloid-β in the brain occurs many years before the clinical onset of AD. The data suggests that Aβ aggregation disrupts the sleep-wake cycle and diurnal fluctuation of Aβ. If scientists are able to track minute changes in sleep-wake behavior of elderly patients, they may be able to accurately diagnose AD prior to symptom onset. This would be a huge step for the field and may lead to the possibility for early intervention to help slow down or prevent the otherwise inevitable cognitive decline.

Parallels in Parkinson’s disease Similar results have been observed in Parkinson’s disease patients. PD is the progressive degeneration of midbrain neurons that produce dopamine — a neurotransmitter involved in the control of movement, reward-motivated behavior, and the sleep-wake cycle. By the time motor symptoms have arisen — including the hallmark resting tremors, the Parkinsonian gait, and postural instability — nearly 60 percent of dopaminergic neurons have already been lost (6). It is unlikely that any potential neuroprotective therapy will be able to halt degeneration at such an advanced stage of disease progression. Therefore, the identification of patients at pre-motor phase of the disease is essential to the development of any successful neurointervention therapy. It is well known that an overwhelming majority of PD patients report some level of sleep disturbance variably manifested by excessive daytime napping, nocturnal insomnia or REM sleep behavior disorder (RBD) (7). The pathology, while not fully understood, most likely reflects cellular change found early in PD pathology, particularly involving the pedunculopontine nucleus, a multifunctional area in the brainstem and the hypothalamus (8). Furthermore, as in AD, sleep disturbances may precede the development of motor and cognitive dysfunction in PD patients. A study by Eduard Tolosa’s group in Barcelona found that 45 percent of patients with RBD would go on to develop a neurodegenerative disease, most commonly PD, typically about 11 years after their initial RBD diagnosis (9). These trends suggest that sleep disturbances may be caused by the early degeneration of midbrain neurons in pre-motor PD patients. There is hope in the scientific community that characterizing these sleep disturbances before the onset of more debilitating symptoms might permit earlier intervention of potential PD therapies.

Future direction It’s becoming increasingly clear that disrupted sleep can

predispose people to neurodegenerative diseases. However, groups are beginning to investigate if the reverse is true as well. Perhaps healthy sleeping patterns could have a neuroprotective effect from these debilitating diseases. Early data seems to support that hypothesis. One study, by Tandberg et al. in Norway, found that about half of the subjects in a PD group reported a “sleep benefit (SB)”(10). According to the study, SB is characterized by a restoration of motor function upon awakening from sleep, prior to the intake of medication. Out of 250 patients with PD, 40 percent performed significantly better on simple motor tasks after adequate sleep. Whether sleep therapy can be a viable treatment for neurodegenerative diseases like AD and PD remains to be seen. However, it is undeniable that sleep patterns are intimately linked to neurodegeneration. As scientists work to understand the biological mechanisms behind this connection, we may be in a better position to detect these debilitating neurological diseases earlier and ultimately stop their progression before greater symptoms develop.

Resources 1. M. Hashimoto, E. Rockenstein, L. Crews, E. Masliah, Role of protein aggregation in mitochondrial dysfunction and neurodegeneration in Alzheimer’s and Parkinson’s diseases. Neuromolecular Medicine. 4, 21-36 (2003). 2. G. S. Bloom, Amyloid-β and Tau: The Trigger and Bullet in Alzheimer Disease Pathogenesis. JAMA neurology. 71, 505-508 (2014). 3. J. E. Kang, et al., Amyloid-beta dynamics are regulated by orexin and the sleep-wake cycle. Science. 326,10051007 (2009). 4. M. Costandi, Neurodegeneration: amyloid awakenings. Nature. 497, S19-20 (2013). 5. J. H. Roh, et al., Disruption of the sleep-wake cycle and diurnal fluctuation of β-amyloid in mice with Alzheimer’s disease pathology. Science translational medicine. 4, 150ra122-150ra122 (2012). 6. G. Becker, et al., Early diagnosis of Parkinson’s disease. Journal of neurology. 249, iii40-iii48 (2002). 7. K. R. Chaudhuri, et al., The Parkinson’s disease sleep scale: a new instrument for assessing sleep and nocturnal disability in Parkinson’s disease. Journal of Neurology, Neurosurgery and Psychiatry. 73, 629-635 (2002). 8. C. H. Hawkes, J. Deeb, Predicting Parkinson’s disease: worthwhile but are we there yet? Practical Neurology. 6, 272-277 (2006). 9. A. Iranzo, et al., Rapid-eye-movement sleep behaviour disorder as an early marker for a neurodegenerative disorder: a descriptive study. Lancet Neurology. 5, 572-577 (2006). 10. E. Tandberg, J. P. Larsen, K. Karlsen, Excessive daytime sleepiness and sleep benefit in Parkinson’s disease: a community-based study. Movement Disorders. 14, 922-927 (1999).

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SUSPENDED ANIMATION AND

SLEEP A Complicated Relationship By Donald Zhang

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uspense can kill, but in the future it may save lives. Suspended animation, the extreme slowing down of the biochemical and physiological processes of life, could solve many medical problems if achieved in humans. For example, patients in need of organ transplant could be induced into a dormant state, buying them time as they wait for a donor (1). There is also research being done into the use of suspended animation for long-range human space travels. Advantages include decreasing psychological stress on the travelers and reducing the amount of room needed on the spacecraft for food storage and living space (2). The idea of suspended animation seems simple enough: it is conceptually similar to a long sleep. Sleep is a very familiar concept as humans spend a third of their lives asleep (3, 4). But what is sleep? The answer is not so straightforward. Perhaps a simple, basic definition of sleep is a “state of unconsciousness.” However, does that mean that states such as coma or

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hibernation are also forms of sleep? It turns out that there are important physiological differences between sleep and other forms of unconsciousness, much of which has yet to be fully explained. Understanding these distinctions will be key to any possibility of controlling human consciousness and developing suspended animation.

Anesthesia and Coma Anesthesia is a useful point of comparison to investigate this issue. Patients undergoing surgery usually receive general anesthesia, or in more common terms, they are “put to sleep.” Is general anesthesia actually “sleep?” One way to find out is by using electroencephalography (EEG), which measures electrical activity in the brain over time. This allows for the observation of voltage fluctuations during brain cell communications. The resulting graph typically consists of oscillating curves. Parameters such as the amplitude and


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frequency of oscillation, as well as motifs and patterns such as “K-complexes” or “sleep spindles”, are diagnostics of certain brain activities (3). There are several distinct types of anesthesia with varying levels of deepness, much like how sleep is divided into rapid eye movement (REM) sleep and four stages of non-rapid eye movement (NREM) sleep. The anesthesiologist chooses the appropriate level of anesthesia for the particular procedure being done. For the level of anesthesia typically used in surgery, the EEG patterns are high amplitude, low frequency and do not resemble the patterns found in any of the sleep phases. Instead, the patterns resemble those of a coma. Besides EEG patterns, there are other physiological similarities between coma and anesthesia that differ from sleep, including unresponsiveness to painful stimuli. For practical purposes, general anesthesia is actually an artificial coma that can be controlled by doctors (4). Thus, while coma is normally a consequence of severe brain damage, the induction of a coma-like state can be used as a tool for healing. However, in the quest for suspended animation, it turns out that hibernation, rather than coma, may be the better option.

Hibernation Hibernation is another form of unconsciousness practiced by some mammals marked by dramatically decreased body temperature and metabolic rate. This extreme adaptation can last from days to months and is designed to conserve energy during times when food is scarce (5). Like anesthesia and coma, hibernation is a distinct state from sleep, as shown by studies done on ground squirrels and more recently, the fattailed dwarf lemur. The fat-tailed dwarf lemur is the only known hibernating primate, hibernating in tree holes for seven months at a time. During dormancy the lemur’s body temperature and metabolic rate fluctuate greatly with changes in the ambient temperature (6). Researchers from Duke University studied both sleeping and hibernating lemurs using EEG and correlated the results with measurements of body temperature and metabolic rate. At low temperatures, the EEG patterns during hibernation were monotonous and of very low voltage, inconsistent with sleep EEG patterns but consistent with those of other, nonprimate hibernators. At high temperatures, patterns consistent with REM sleep were observed. Interestingly, NREM sleep patterns were practically absent (5). The potential implications are very important: The fact that the lemurs were able to go without NREM sleep for months at a time with no apparent detrimental effects provides evidence that NREM sleep may not be necessary at low metabolic rates. The researchers hypothesized that the low temperature and metabolic rate during hibernation lead to decreased brain

activity, explaining the relatively flat EEG patterns. As these lemurs are the closest human relatives known to hibernate, this new information and further study may prove useful in attempts at inducing a hibernation-like state in people.

Conclusion How close are we to achieving suspended animation? There’s a lot of work to be done before it can be attempted on humans, but promising results have been seen in animal models. Researchers at the Fred Hutchinson Cancer Research Center used gaseous hydrogen sulfide to induce a “suspended animation-like state” in mice (7). Mice do not naturally hibernate, but after inhaling the hydrogen sulfide, they underwent extremely large decreases in body temperature and metabolic rate. Most importantly, they were brought back without adverse effects. Other experiments involving replacement of blood with cold saline solution in dogs and pigs showed success as well (8, 9). However, as the lemur study shows, there is an intricate relationship between hibernation and sleep that is still unclear. For translation of hibernation to humans to be successful, more attention needs to be focused on this link to sleep physiology. While it may be a completely different phenomenon, sleep may provide us with the answers we need for suspended animation.

Resources 1. H. Aslami, N. P. Juffermans, Induction of a hypometabolic state during critical illness - a new concept in the ICU? Neth. J. Med. 68, 190–8 (2010). 2. J. E. Bradford, D. Talk, Torpor inducing transfer habitat for human stasis to Mars. Presented at the 2014 NASA Symposium, Atlanta, GA, February, 2014. 3. H. Colten, B. Altevogt, Eds. Sleep disorders and sleep deprivation: an unmet public health problem (National Academy of Sciences, Washington, DC, 2006). 4. E. N. Brown, R. Lydic, N. D. Schiff, General Anesthesia, Sleep, and Coma. N. Engl. J. Med. 363, 2638–2650 (2010). 5. A. D. Krystal et al., The relationship of sleep with temperature and metabolic rate in a hibernating primate. PLoS One 8, e69914 (2013). 6. M. B. Silvarolla, P. Mazzafera, L. C. Fazuoli, Hibernation in a tropical primate. Nature 429, 825–826 (2004). 7. E. Blackstone, M. Morrison, M. Roth, H2S induces a suspended animation–like state in mice. Science 308, 518 (2005). 8. A. Nozari et al., Suspended Animation Can Allow Survival without Brain Damage after Traumatic Exsanguination Cardiac Arrest of 60 Minutes in Dogs. J. Trauma Inj. Infect. Crit. Care 57, 1266–1275 (2004). 9. H. B. Alam et al., Does the rate of rewarming from profound hypothermic arrest influence the outcome in a swine model of lethal hemorrhage? J. Trauma 60, 134–46 (2006).

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MEMORY& SLEEP By Karanbir Singh Pahil

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e’ve all fallen asleep while studying for an exam or working on a homework problem, only to wake up knowing the answer or understanding the material as if by magic. We’ve all been told that the best way to study is by rereading notes right before sleeping. Studies have shown that sleep can cause overnight epiphanies regarding numeric problem-solving tasks (1). But why does this happen? Does sleep help with learning, and if so, how? It turns out that sleep plays a large role in memory formation and learning. Memory formation occurs in stages known as encoding (the initial engagement with an idea), consolidation (a process that allows memories to become stronger and more resilient over time in the absence of practicing), recall (the act of accessing an old memory for use), integration (linking new memories to old ideas), and reorganization (changing ‘where’ a memory is located in the brain). Sleep plays an important role in each of these memory stages. We’ve known about sleep’s role in memory encoding

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FEATURES for over 50 years (2). A recent study has shown that an individual’s memory of faces is severely impaired if he or she is deprived of sleep for over 36 hours (3), and that sleep deprivation can cause a 40 percent reduction in new memory formation. These negative effects are nuanced and dependent on the types of memories being formed. The formation of emotionally negative memories is less affected by sleep deprivation than the formation of emotionally positive memories (4). This effect has also been observed in animals, especially regarding tasks dependent on the hippocampus (an area of the brain that plays a large role in memory consolidation and spatial tasks) (5). Early PET studies revealed that the metabolism of glucose in the prefrontal cortex (PFC) slows after a night of sleep deprivation. Since the prefrontal cortex is very important in memory encoding, this caused many to believe decreased PFC activity caused the negative effects of sleep deprivation on memories (6). However, it should be noted that PET imaging is much less adept at quickly measuring changing levels of brain activation for long term tasks than fMRI, and in fact, fMRI studies on the topic have shown that sleep deprivation is actually correlated with increased PFC activity, as well as increased parietal lobe activity and decreased medial temporal lobe activity (7). This suggests that regions of the brain that are normally not involved in memory encoding are recruited to help compensate for the decreased activity of the brain regions that are normally involved in memory encoding. After sleep deprivation, the brain realizes that the regions involved in encoding are impaired and tries to compensate by offloading these tasks to other, less adapted regions of the brain (8). Memory consolidation is a multistage “process whereby a memory, through the simple passage of time, becomes increasingly resistant to interference from competing or disrupting factors in the absence of further practice” (9). In other words, consolidation is the stabilization and enhancement of memory by the passage of time. It allows memories to be retained for a period of days or years. Interestingly, not all memories can undergo consolidation (10). The stages of consolidation occur during different portions of the sleep-wake cycle (11). Much of memory stabilization occurs while one is awake, while significant memory enhancement occurs while sleeping (11). Examples of memory enhancement that occur during sleep include the restoration of lost memories and the promotion of additional learning (12-13). Sleep has an important role in the consolidation of declarative memories (factual knowledge). For example the amount of posttraining REM sleep (one of the stages of sleep characterized by rapid eye movements) correlates with success in the learning of a foreign language (14). This is because access to weak associations and the ability to creatively process new information (15-16) are both enhanced by REM sleep. Similarly, increased intensity of language lessons correlates with an increased amount of REM sleep, indicating a possible homeostatic link between REM sleep and consolidation. Interestingly, word-pair association

task performance regarding related words improves with increased quantity of slow-wave sleep (deep sleep) because it helps strengthen the ‘tagging’ of pre-formed associations for subsequent recall. In other words, sleep has a larger effect on the ability to recall relatively intuitive word-pairs (e.g. dog and bone) than on the ability to recall unintuitive and novel wordpairs (e.g. dog and leaf). Sleep is better at strengthening preexisting associations than creating completely new associations (17). All of this does not mean that sleep is a magical elixir that will invariably improve academic performance. The correlation between sleep and performance on memory-related tasks depends on task difficulty (18). For example, sleep is not helpful in making simple emotionless memories. Sleep is only helpful for consolidation of complex memories, emotionally compelling memories, or memories that are related to previously existing memories (4). Sleep also plays an important role in the consolidation of procedural memories, including motor learning (learning of physical processes such as typing), visual learning, and auditory learning. For example, sleep increases performance in sequential finger-tapping tasks that are similar to playing songs on the piano (19). Similar results have been noted regarding tasks involving various other motor skills (4). Increased performance is especially notable on the first night after lessons, as inadequate sleep compromises the hippocampus (20). When learning a long sequence of steps, people tend to break the sequence into ‘chunks’. Unsurprisingly, people tend to initially have ‘problem points’, which are chunks of the sequence that they are relatively poor at recalling. After sleep, subjects tend to have much greater improvement in their ‘problem points’ than they have in the rest of a task (1). Similarly, both REM and short-wave sleep have aided memory consolidation in studies involving visual and auditory learning (22). In one study, differences in quantity of REM and short-wave sleep accounted for 80 percent of the intersubject learning differences (21). All of the studies discussed so far involved the positive effects of a full night’s sleep. Some studies have shown that even naps can help with motor-skills and visual learning (23-24). Surprisingly,

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FEATURES those who took 30 to 90 minute naps showed reduced sleeprelated learning benefits from a full night of sleep. There may therefore be a ceiling to the learning benefits provided by sleep. The same studies also showed that over-repetition of a task over the course of a day without taking a nap can reduce retention. When something new is learned, the information is ‘fresh’ in the mind and the memories associated with said information are unstable in that they are prone to be easily altered (strengthened, weakened, erased or changed). Memory recall (the act of accessing an old memory for use) can have a destabilizing effect on memories by returning said memories into a state similar to that of newly learned memories. In other words, recall returns a memory into a state in which it is prone to being altered, strengthened or forgotten. Therefore memories often need to undergo reconsolidation after being accessed (25). Sleep may have a role in both destabilizing and reconsolidating memories (4). In order for a concept to be fully understood, it must often be integrated with other knowledge. The locations of different memories in the brain are often also reorganized. Both integration and reorganization can occur without re-exposing oneself to the relevant material, and sleep may have a role in both of these processes (15). Given all of this, the impulse to sacrifice sleep for an extra few hours of pre-exam studying is misplaced. If anything, students should sacrifice a bit of study time to ensure they always get a full night of sleep. Learning can be maximized by reading notes before going to sleep. Midday naps can also help with the learning process. Overdoing homework problems may end up being counterproductive and decrease retention. All in all, a little bit of laziness, if it means an afternoon siesta or a few more hours of rest at night, may actually help improve school performance.

Resources 1. M. P. Walker, and R. Stickgold, Sleep-dependent learning and memory consolidation. Neuron. 44, 121-133 (2004). 2. G. O. Morris, H. L. Williams, A. Lubin, MISPERCEPTION AND DISORIENTATION DURING SLEEPDEPRIVATION. Archives of General Psychiatry. 2, 247-254 (1960). 3. Y. Harrison, J. A. Horne, Sleep loss and temporal memory, Quarterly Journal of Experimental Psychology Section a-Human Experimental PsychologyI. 53, 271-279 (2000). 4. M. P. Walker, R. Stickgold, Sleep, memory, and plasticity. Annual Review of Psychology. 57, 139-166 (2006). 5. Z. W. Guan, X. W. Peng, J. D. Fang, Sleep deprivation impairs spatial memory and decreases extracellular signalregulated kinase phosphorylation in the hippocampus. Brain Research. 1018, 38-47 (2004). 6. M. Thomas, et al., Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity. Journal of sleep research. 9, 335-352 (2000). 7. S. P. A. Drummond, et al., Altered brain response to verbal learning following sleep deprivation, Nature. 403, 655-657 (2000). 14 PENNSCIENCE JOURNAL | SPRING 2014

8. S. P. A. Drummond, G. G. Brown, The effects of total sleep deprivation on cerebral responses to cognitive performance. Neuropsychopharmacology. 25, S68-S73 (2001). 9. J. L. McGaugh, Memory--a Century of Consolidation, Science. 287, 248-251 (2000). 10. K. M. Goedert, D. B. Willingham, Patterns of interference in sequence learning and prism adaptation inconsistent with the consolidation hypothesis. Learn. Mem. 9, 279-292 (2002). 11. M. P. Walker, T. Brakefield, J. A. Hobson, R. Stickgold, Dissociable stages of human memory consolidation and reconsolidation. Nature. 425. 616-620 (2003). 12. K. M. Fenn, H. C. Nusbaum, D. Margoliash, Consolidation during sleep of perceptual learning of spoken language. Nature. 425. 614-616 (2003). 13. R. Stickgold, L. James, J. A. Hobson, Visual discrimination learning requires sleep after training, Nature Neuroscience. 3, 1237-1238 (2000). 14. J. Dekoninck, D. Lorrain, G. Christ, G. Proulx, D. Coulombe, INTENSIVE LANGUAGE-LEARNING AND INCREASES IN RAPID EYE-MOVEMENT SLEEP - EVIDENCE OF A PERFORMANCE-FACTOR. International Journal of Psychophysiology. 8, 43-47 (1989). 15. R. Stickgold, L. Scott, C. Rittenhouse, J. A. Hobson, Sleepinduced changes in associative memory, Journal of Cognitive Neuroscience. 11, 182-193 (1999). 16. M. P. Walker, C. Liston, J. A. Hobson, R. Stickgold, Cognitive flexibility across the sleep-wake cycle: REM-sleep enhancement of anagram problem solving. Cognitive Brain Research. 14, 317-324 (2002). 17. S. Gais, J. Born, Low acetylcholine during slow-wave sleep is critical for declarative memory consolidation. Proceedings of the National Academy of Sciences of the United States of America. 101, 2140-2144 (2004). 18. A. J. Tilley, J. A. C. Empson, REM-SLEEP AND MEMORY CONSOLIDATION. Biological Psychology. 6, 293-300 (1978). 19. M. P. Walker, T. Brakefield, A. Morgan, J. A. Hobson, R. Stickgold, Practice with sleep makes perfect: Sleepdependent motor skill learning. Neuron. 35, 205-211 (2002). 20. S. Fischer, M. Hallschmid, A. L. Elsner, J. Born, Sleep forms memory for finger skills. Proceedings of the National Academy of Sciences of the United States of America. 99, 11987-11991 (2002). 21. S. Gais, W. Plihal, U. Wagner, J. Born, Early sleep triggers memory for early visual discrimination skills. Nature Neuroscience. 3, 1335-1339 (2000). 22. N. Gaab, M. Paetzold, M. Becker, M. P. Walker, G. Schlaug, The influence of sleep on auditory learning: a behavioral study. Neuroreport. 15, 731-734 (2004). 23. M. P. Walker, R. Stickgold, It’s practice, with sleep, that makes perfect: Implications of sleep-dependent learning and plasticity for skill performance. Clinics in Sports Medicine. 24, 301-317 (2005). 24. S. Mednick, K. Nakayama, R. Stickgold, Sleep-dependent learning: a nap is as good as a night. Nature Neuroscience. 6, 697-698 (2003). 25. K. Nader, Memory traces unbound. Trends in Neurosciences. 26, 65-72 (2003).


FEATURES

HOW DRUGS AFFECT

SLEEP

By Coby Basal

T

ens of millions of Americans currently suffer from sleep disorders (1). Insomniacs sometimes resort to sleep medications to treat their symptoms. Medication utilization generally increases with age, with people over 80 consuming the highest percentage of sleep medications (6). Some of the most common drugs that are prescribed include Ambien, Sonata, and Lunesta and are classified as hypnotics. This class of drugs is very closely related to sedatives. While sedatives often treat anxiety disorders by calming people, hypnotics go a step further by inducing sleep. Ambien, Sonata, and Lunesta each induce a calming effect on the brain, acting on the GABAA neuroreceptors in the brain to help people fall asleep faster (3-4). They are generally meant for short term use. Therefore, doctors often recommend patients with insomnia to have a plan on how and when they will stop taking the prescribed medication. These medications should not be overused since studies have found that one in

six people who are treated with hypnotics for up to a month have adverse side effects (5). In fact, it has been found that the adverse effects of hypnotics in people over 60 often outweigh the benefits (5). One of the major problems caused by hypnotics pertains to withdrawal symptoms. Such symptoms can include anxiety, unusual dreams, nausea, and vomiting (7). Hypnotics can also be problematic since they have the potential to interact with other medications that the user is taking. An additional problem is the reduced effectiveness of some hypnotics over time. This may lead to the reliance on higher and higher dosages, which can in turn lead to further and further dependence. Another major category of drugs that is used for treating sleep disorders is the class of antiParkinsonian drugs. These drugs are prescribed less frequently than hypnotics. They often treat conditions that cause sleep disruption such as

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FEATURES restless leg syndrome, a condition that is characterized by an urge to move one’s leg (8). The anti-Parkinsonian drugs regulate dopamine, which plays an important role in sleep regulation and the body’s circadian rhythm (9). In this way, through dopamine regulation, this class of drugs can lead to improved sleep.

prescribed than other treatments. Further testing on those drugs, whose effects are disputed, is ongoing, and many new medications, whose effects are unknown, are being tested in clinical trials.

A third type of drug (or rather dietary supplement) that can help treat insomnia is melatonin (10). Melatonin is a hormone that plays a large role in circadian rhythm regulation. Taking melatonin supplements can help one who has sleep onset latency, meaning that melatonin can reduce the amount of time it takes for someone to initiate sleep (11). Melatonin is also often taken to treat jet lag since it can refresh the circadian rhythm.

1. J. L. Hossain, C. M. Shapiro, “The prevalence, cost implications, and management of sleep disorders: an overview.” Sleep and Breathing. 6, 85-102 (2002). 2. E. Sanna, et al., “Comparison of the effects of zaleplon, zolpidem, and triazolam at various GABA< sub> A</sub> receptor subtypes.” European journal of pharmacology, 451, 103-110 (2002). 3. F. Jia, P. A. Goldstein, N. L. Harrison, “The modulation of synaptic GABAA receptors in the thalamus by eszopiclone and zolpidem.” Journal of Pharmacology and Experimental Therapeutics. 328, 1000-1006 (2009). 4. J. Glass, et al., Sedative hypnotics in older people with insomnia: meta-analysis of risks and benefits. BMJ. 331, 1169 (2005). 5. Y. Chong, et al., Prescription Sleep Aid Use Among Adults: United States, 2005-2010. NCHS Data Brief. No. 127, 1-8 (2013). 6. Mayo Clinic, Prescription sleeping pills: What’s right for you? (2011). Retrieved from www.mayoclinic.org 7. C. J. Earley, R. P. Allen, “Pergolide and carbidopa/ levodopa treatment of the restless legs syndrome and periodic leg movements in sleep in a consecutive series of patients.” Sleep. 19, 801-810 (1996). 8. S. González, et al., Circadian-related heteromerization of adrenergic and dopamine D4 receptors modulates melatonin synthesis and release in the pineal gland. PLoS biology. 10, e1001347 (2012). 9. Buscemi, Nina, et al. Melatonin for Treatment of Sleep Disorders. Evid Rep Technol Assess (Summ). 108, 1-7 (2004). 10. L. Panagiotou, K. Mystakidou, Non-analgesic effects of opioids: opioids’ effects on sleep (including sleep apnea). Current Pharmaceutical Design. 18, 60256033 (2012). 11. K. Ramakrishnan, D. C. Scheid, Treatment Options for Insomnia. AJOL. 49, 36-41 (2007). 12. Anticonvulsant Screening Program. National Institute of Neurological Disorders and Stroke. Web. www.ninds.nih.gov 13. C. W. Brazil, Nocturnal seizures and the effects of anticonvulsants on sleep. Current Neurology and Neuroscience Reports. 8, 149-154 (2008). 14. M. K. Erman, Therapeutic options in the treatment of insomnia. Journal of Clinical Psychiatry. 66, 18-23 (2004). 15. M. H. Kryger, et al. Anticonvulsants: Gabapentin and Pregabalin. In Principles and Practice of Sleep Medicine (Saunders, Philadelphia, ed. 5, 2010). 16. J. K. Walsh, et al., Dose-Response Effects of Tiagabine on the Sleep of Older Adults. Sleep. 28, 673-676 (2005).

Opiates constitute a fourth type of drug that is prescribed to treat sleep disorders. Opiates are derived from the opium poppy plant, Papaver somniferum, which in Latin translates to “sleep inducing poppy.” Scientific literature disagrees about whether opiates are helpful in treating sleep disorders. People often report sleep disturbances and changes in sleep quantity and quality as a result of opiate usage (10). However, trials have also found greatly improved sleep quantity with fewer sleep disturbances in people taking opiates (10). Some scientists argue that opiates are useful for treating insomnia that is associated with pain (11). But these same scientists say that opiates fragment sleep and reduce sleep time in certain stages of the sleep cycle. What can make opiates particularly useful for treating insomnia is their ability to produce an analgesic effect along with sedation (11). Thus, it appears that opiates should not be prescribed to typical insomnia patients, but rather only to patients that have pain associated with their insomnia. A fifth type of drug that can serve as a treatment for insomnia is the drug class of anticonvulsants. Such drugs commonly treat epileptic seizures, and so epilepsy patients prone to sleep disruption, may experience improved sleep with anticonvulsants (13). However, anticonvulsants are not considered an optimal treatment option for most people since they can have severe side effects (14). Nevertheless, in spite of side effects such as dizziness, dry mouth, cognitive impairment, and increased appetite, one study argues that anticonvulsants such as pregabalin could have valuable sleep-inducing effects in not only patients with epilepsy, but also those with pain and even those without additional symptoms (15). The anticonvulsant drug tiagabine has also been used to treat sleep disorders. Tiagabine has demonstrated the capability to increase total sleep time and sleep continuity while reducing the amount of time it takes one to fall asleep and ultimately get out of bed after awakening (16). As might be expected given the prevalence of sleep disorders, many drugs currently exist that treat such disorders. Some drugs such as hypnotics and some dietary supplements such as melatonin are more often 16 PENNSCIENCE JOURNAL | SPRING 2014

Resources


RESEARCH

Analysis of dermal papilla cell origin in hair follicle neogenesis after wounding Laura M Doherty1, Denise Gay2, Ying Zheng2 and George Cotsarelis2 Kimberly Gallagher3 School of Arts and Sciences, University of Pennsylvania, Philadelphia PA 19104, USA. Department of Dermatology, Kligman Laboratories, Perelman School of Medicine at the University of Pennsylvania, Philadelphia PA 19104, USA. 3 Department of Biology, University of Pennsylvania, Philadelphia PA 19104, USA. December 2013 1

2

The process in which hair follicles form and grow is complicated and requires signaling between different components of the follicle in both the dermis and the epidermis. The dermal papilla cells, which are found at the very base of the follicle bulb and show some stem cell-like characteristics, are crucial to the development and cycling of hair follicles. It is unclear how the new dermal papilla cells develop in the wound-induced hair neogenesis model. Using lineage analysis, Cre-mediated excision, and a fluorescent marker, we have tracked dermal papilla cells to see if they migrate into the wound area to begin hair follicle development in healing skin. Dermal papilla cells were marked during CD133 expression to fluoresce red. We then checked hair follicles in healed skin to see if they were derivative of the marked dermal papilla. We originally hypothesized that wound induced hair neogenesis necessitates movement of existing dermal papilla cells into the wound area in order to allow new hair follicles to form. This was based on a variety of factors, including the static nature of dermal papilla cell populations. However, the data has provisionally shown that dermal papilla cell migration is an unlikely explanation for hair follicle neogenesis post-wounding. This research will contribute directly to new approaches for promoting hair growth in patients with hair loss. Understanding the mechanisms for regeneration of hair follicles presents new opportunities for developing treatments for hair loss and other skin disorders in humans, including alopecia and male pattern baldness.

Introduction: The Hair Follicle

The hair follicle (HF) is an important skin organ that is responsible for producing hair, and includes components from both the dermal and epidermal layers of the skin. All HFs share the same basic structure and method of development1. Both an inner and outer root sheath surround the HF’s central hair shaft, which extends from the epidermis into the dermis. A basement membrane acts as a barrier between the epidermal and dermal regions. A sebaceous gland, secreting oily matter, and a bulge region, housing stem cells, are found around midway down the shaft in the dermal region. The bulb at the bottom of the HF includes a dermal sheath and, at the very base, dermal papilla (DP) cells1,2. Hair growth and development are regulated through a variety of complicated pathways in which the dermal and epidermal components of the HF must communicate3. These signaling events occur for the first time in fetal development, where DP cells induce HF formation through interaction with the epidermis4. Signaling continues perpetually throughout the life of the HF as the hair cycles between the three phases of anagen, catogen, and telogen. Each cycle of hair growth requires another phase of signaling involving the DP cells1. The dermal cells are considered inducers of HF development, while the above epidermal components are mainly referred to as responders in this orchestrated HF formation. DP cells are widely suggested to be essential for hair follicle morphogenesis and growth to occur2,5.

Figure 1. The structure of a hair follicle2.The dermal papilla region is found at the base of the HF, enclosed in the dermal sheath. During the telogen phase of cycling, it is possible that the DP is found slightly beneath the HF structure, while during anagen, the DP is enclosed within the dermal sheath.

The WIHN Model

HFs have been shown to develop de novo following wounding in genetically normal adult mice. These newly generated HFs cycle through all of the normal cycling phases and express the same molecular markers of follicular differentiation. HFs are thought to form only during development and loss of HFs is often deemed permanent, leaving questions as to how new HFs form in a wound area6. This wound-induced hair neogenesis (WIHN) model suggests that wounding induces an embryonic phenotype in the skin

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RESEARCH that allows new HFs to form and develop. Signaling between the dermis and epidermis induces HF growth, so both of these components must be present in the WIHN model. In the wounding procedure, a square of full-thickness skin is removed from the backs of adult mice and the area is allowed to heal and regrow both the dermis and epidermis. 14-19 days following wounding, epidermal down-growths resembling developing hair follicles appear, displaying normal morphology7.

Dermal Papilla Cells

DP cells play a critical role in the formation of HFs, both in normal development and following wounding. Together with components from the epithelium, DP cells induce development of HFs5,6. Dermal fibroblasts, through signaling, initiate proliferation of cells in the epidermis and the growth of a hair germ; the fibroblasts mature into DP cells, which are engulfed by the hair shaft (Fig. 2)8. Research indicates that HFs cannot develop unless DP cells in the underlying dermis aggregate and allow the forming shaft to grow downwards and envelop the mesenchymal (dermal) cluster3,4. However, the number of DP cells in an organism is thought to be fairly static and there is little to no proliferation of DP cells9,10. While DP cell populations grow in number during the anagen phase of the hair cycle, their numbers fall again in the catogen phase. This is local intrafollicular papilla cell proliferation, and DP cells do not divide in order to form new HFs post-development in normal skin11. Each new phase of hair cycling mimics the original morphogenesis of HFs, requiring more molecular signaling between dermal and epidermal cells12. This shows the DP cells are playing an active role in HF regulation and upkeep. It is unclear whether wound induced hair neogenesis relies on a generation of new DP cells, similar to an embryonic development state, or if there is another source of these cells that initiates signaling to begin HF formation.

Fig. 2. DP cells likely arise from maturation of dermal papilla fibroblasts. Molecular signaling between the dermis and epidermis initiates HF growth. The DP cells are engulfed by the hair peg down growth, a primitive hair shaft. The inner root sheath is formed right above the DP region8. 18 PENNSCIENCE JOURNAL | SPRING 2014

Prominin 1, or CD133, is a trans-membrane glycoprotein and surface marker expressed in a variety of developing tissues and stem cells13,14. It has also been shown to be a useful marker for differentiated cell types, and its expression is not limited to stem cells15. DP cells are not true stem cells, as they are found at the base of the HF bulb and not in the bulge region (Fig. 1) of the HF16. CD133 has been proven as a marker for DP cells in mice during the late embryonic state and the few days following birth. CD133 is expressed only during a very small window of growth, and previous studies have shown that CD133 expression is generally gone by P710,17.

Experimental Design and Procedure After wounding, new HFs form in the healed skin. DP cells must be present in order for HFs to develop and maintain growth and cycling, but their origin is not clear. To track possible mobility of already existing DP cells in mice after wounding, we have designed an experiment that labels CD133 expressing populations before expression disappears. In order to permanently mark these populations, lineage analysis and the use of a reporter gene were needed. This lineage analysis allows us to differentiate between pre-existing DP cells and DP cells that may form de novo after wounding. Using a reporter such as GFP would not allow for this distinction. The mice in this experiment contain a ‘knock-in’ creERT2 fusion protein and an internal ribosome entry site (IRES)-β-galactosidase (lacZ), which replaces the first ATG codon of CD133 expression (Fig. 2). The creERT2 enzyme is a Cre recombinase fused to a mutated form of the estrogen receptor, which can be activated by tamoxifen, an agonist of the estrogen receptor. After proper tamoxifen induction, creERT2 can gain access to the nucleus of the cells expressing CD133. The activation of this Cre enzyme renders the gene inactive; homozygotes for this engineered CD133 construct experience unfavorable phenotype effects, including blindness, but are still useful for the purpose of this research as CD133 is dispensable for development14. These CD133 mice are bred with ROSA26r-Tomato reporter mice. Tomato is a fluorescent reporter found downstream of ROSA26r. ROSA26r is a gene present in all embryonic and adult mice18. There is a stop codon between ROSA26r and Tomato that is flanked by loxP sites. Cre proteins in the nucleus (made available through CD133 expression and subsequent induction by tamoxifen) will excise the stop codon by splicing at the loxP sites, and transcription will continue past ROSA26r to the Tomato gene, activating red fluorescence19. Therefore, mice treated with tamoxifen during the small window of Prominin expression, and that are positive for both the genetically engineered CD133 and Tomato genes, will experience red fluorescence in cells that were at one time CD133 (+). Properly induced DP cells will permanently fluoresce, even after CD133 expression is turned off, since ROSA26r expression will continue.


RESEARCH ATG Start Sequence

Normal Prominin 1 (CD133) Gene Vs. Engineered CD133 Gene

CD133 Sequence

CD133 cont.

CD133 Sequence

CD133 cont. Cre protein

creERT2

IRES - nlacZ Tamoxifen

Fig 3. Prominin 1 (CD133)-creERT2 construct. In the engineered mouse, the ATG start sequence has been replaced with the ‘knock in’ CreERT2 and the internal ribosome entry site (IRES). Tamoxifen induction allows for a Cre protein to enter the nucleus. The Cre enzyme is unable to enter the nucleus unless the mouse is positive for the engineered CD133 gene and there is proper induction. loxP ROSA26r

loxP STOP

Tomato

Cre protein

ROSA26r

Tomato

Fig. 4. ROSA26r-Tomato construct. In mice positive for CD133, the Cre protein enters the nucleus to act on this genetic construct. With the STOP codon in place, Tomato cannot be expressed. The enzyme excises the STOP codon between ROSA26r and the Tomato reporter gene, allowing Tomato fluorescence to be expressed. Mice positive for both Tomato and the engineered Prominin 1 genes will express fluorescence in CD133 expressing populations. We were first interested in marking existing DP cells with fluorescence within the correct time period of induction. When pups were born (P0), we treated the back-skins with 4 μL of 15 mg/mL tamoxifen dissolved in ethanol. This was repeated for 7 days so that proper induction occurred before the cutoff of P717. When the mice were 5-6 weeks of age, they were wounded; their back-skins were pinned and fixed to analyze levels of successful tamoxifen induction (Fig. 5-7). The mice were left to heal. We were then interested in seeing whether or not DPs in HFs formed after wounding were derivative of the DP cells we had marked. When healing was completed (about 4 weeks post-wounding) and hair had grown back over the wound, these mice were euthanized and the healed back-skins were taken and analyzed for any indication of fluorescence (Fig. 8-9). All skins were also mounted into frozen blocks for sectioning and analysis. The mice were genotyped with PCR. Analyzing sections of the healed wound skin will give

answers as to whether or not DP cells migrate from already established DP populations into the wound area, or if there is another mechanism of DP generation. Any DPs that fluoresce red in the healed wound skin must have come from already available DP cells, indicating mobility and migration. No newly generated DP cells will express the Tomato gene since tamoxifen induction of CD133 was not utilized during this later time period. If the healed wound skin shows no red fluorescence in any of the DP cells, then these cells likely were formed in the time period after wounding through an unknown mechanism.

Materials and Methods Wounding

Prom1-creERT2-lacZ mice were crossed with ROSA26r-Tomato mice, both from Jackson Laboratories. These mice were wounded after they grew large enough to be weaned, at an age range of 4 weeks to 6 weeks. Under anesthesia, a full thickness skin excision of 1.25cm2 was made on the backside of these mice and the wound was left to heal for a period of 4 weeks to 6 weeks, or until evidence of new hair follicles being formed was seen. Wounded mice were checked daily for seven days postwounding. The Institutional Animal Care and Use Committee approved all animal protocols.

Genotyping

Tissue for genotyping was collected from a portion of the back skin when euthanizing the animals after wound healing. DNA was purified using a DNeasy Blood & Tissue Kit from Qiagen ©. The reaction mixture for each PCR sample consisted of 12.5μL GoTaq Green Master Mix, 1μL of each construct-specific primer, 1μL of purified DNA, and RNase-free water bring the total volume of the mixture to 25μL. Each DNA sample was tested for both the Prominin 1 and Tomato genes. PCR products were generated with a standard program in a thermal cycler. Samples were electrophoresed in 1.2% agarose gel stained with ethidium bromide.

Induction

Tamoxifen free-base was dissolved in 200 proof ethanol at a concentration of 15 mg/mL. This form of tamoxifen has proved the most successful, as other forms were not as soluble in our carrier, ethanol. The solution was stored in the dark at 4°C to maintain stability and to prevent photolysis products. For wounding experiments, 4μL of the solution were applied to the backs of pups from P0P7. The back skin taken during wounding the animals was analyzed for levels of successful induction. Previous experimentation has shown that this dose is ideal, as larger doses may be toxic to the pups, and smaller doses do not allow for significant induction.

Immunohistochemistry

The same method of immunohistochemistry was used for all sets of skin analyzed in the experiments. The tissues were embedded in Tissue-Tek O.C.T and frozen

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RESEARCH on dry ice. These blocks were stored at -80°C, and later cut into sections 10μm thick using a cryostat. Sections were fixed for ten minutes with 4% paraformaldehyde and washed in PBS. They were then stained for one hour with a 1:50 dilution of Integrin α6/CD49f-FITC antibody, which targets cell surface glycoproteins. After a final wash in PBS, the slides were mounted and stained with DAPI, targeting cellular nuclei, and viewed under fluorescence with a Leica DFC420 microscope.

F

G

Fig. 7. Histology of HFs that have been successfully induced

Results with tamoxifen. These structures are mature, parallel HFs from Tamoxifen induction successfully marked DP cells unwounded skin. Staining of these slides successfully outlines before wounding important components of the HF, including the bulb, shaft, and CD133 is an effective marker of most DP cells when mice are positive for both the CD133 and Tomato genes. After tamoxifen induction from P0-P7, mice were allowed to develop for approximately 4 to 6 weeks after birth, and were then wounded. We genotyped these mice and analyzed the back-skins that were taken during wounding, focusing on those that were positive for both of the target genes. A sample of these double positive skins is found in photographs below.

A

B

both inner and outer dermal sheaths. The dotted outlines in figure G show the regions of the HF bulb where DP cells congregate, within the epidermal basement membrane. Stained with DAPI (blue) to target all nuclei and Integrin α6/CD49f-FITC antibody (green), which is expressed in a variety of epidermal cells. Tomato fluorescence is shown in red. Pictures are overlaid to show all staining.

DP cells in HFs that formed de novo after wounding did not fluoresce

After new HFs had formed after wounding, these skins were analyzed under a microscope to check for red fluorescence. No fluorescence of DP cells was observed in any of the post-wounding skins. This indicates that DP cells may not migrate into the wound area, but this is not a definitive answer.

H

I

C

Fig. 5. Back-skin whole mounts show that tamoxifen induction of DP cells before wounding was successful. The Tomato reporter (shown in purple for A and B, orange for C) is clearly labeling the DP cells at the base of the HF (refer to Fig 1). The close-up in B shows the short-range mobility of the DP during cycling through anagen, catogen, and telogen.

D

E

Fig. 6. Tamoxifen induction before wounding was successful in all experimental groups. A back-skin wholemount (D), shown under fluorescence in E. These are the same pictures under different lighting. This skin was taken during wounding, 4 weeks after tamoxifen induction. The red Tomato marker can be seen at the base of many HFs.

20 PENNSCIENCE JOURNAL | SPRING 2014

Fig. 8. No fluorescence was seen in HFs formed after wounding. The above whole-mounts are from the same mouse as Fig. 5, postwounding. These are the same picture taken under different lighting conditions. Photo H is under normal light to show presence of HFs in the wound center 5 weeks after wounding. The hair follicles show normal morphology. Photo I is the same photo under a fluorescent filter. No fluorescence is seen at the base of any of the hair follicles where the DP cells are located. These DP are not derivative of the previously marked DP, seen in Fig. 5.


RESEARCH Fig. 9. Histology of post-wounding back skin further solidified that there was no fluorescence seen in HFs after wounding. Stained with DAPI (blue) to target all nuclei and Integrin α6/CD49f-FITC antibody (green), which is expressed in a variety of epidermal cells. Tomato fluorescence is shown in red. Pictures are overlaid to show all staining. Erratic growth of new HFs in the wound are made it difficult to show parallel structures.

Discussion

The DP region is a dense and rounded group of cells found enclosed within the dermal sheath in the bulb of the HF. The pictures in Fig. 5 show groups of cells in the HF bulb expressing Tomato fluorescence, and the fluorescent region is exactly the location and shape of expected DP cells (shown in Fig. 1-2). These cells have been successfully induced with tamoxifen. Based on the morphology, we reason that CD133 is a cell surface marker that does in fact target the DP. No Tomato fluorescence was seen in the HFs in the healed skin (the red spots in Fig. 8I & 9 are, based on shape and location, blood vessels). These data suggest that DP cells in HF neogenesis after wounding are not derivative of DP cells that have migrated from the surrounding unwounded area. However, there is evidence of incomplete and scattered induction, which leads to the possibility of insufficient induction of Tomato expression, or that CD133 only targets a specific subpopulation of DP cells. Therefore, the hypothesis that DP cells from surrounding HFs contribute to neogenic HF DPs still cannot be ruled out and further experimentation is needed. Fluorescence was not seen at the base of all hair follicles in mice with successful induction (Fig. 5-7). The Cre-lox recombination method used has been shown to be only partially effective20. There may also be issues with the method of induction, including concentration of tamoxifen or type of solvent used, as well as the method of application on pups. The skin barrier in mice is formed two to three days prior to birth21. Tamoxifen is able to enter through the barrier, as evidenced by successful induction (Fig. 5-7). Since the skin barrier is already present at P0, the amount of tamoxifen penetrating through the barrier should not change significantly between P0 and P7. This should not be contributing to the patchy induction. A larger concentration of tamoxifen may have been necessary to completely induce the DP cells of all hair follicles. This presents other issues, as tamoxifen is known to have a variety of unwanted side effects22. For these experiments, 4μL of tamoxifen solution (15 mg/mL in 200 proof ethanol) was used. We have found through previous experiments that a larger concentration (4μL at 20 mg / mL) of tamoxifen sometimes kills pups within the first day of application, and leaves surviving pups very small and unable to wound. Smaller amounts of tamoxifen (4μL at 5 mg/mL) have sometimes shown no induction at all. The pups treated with tamoxifen (4μL at 15mg/mL, or .06mg total) did not develop normally alongside pups that had no exposure to tamoxifen. Normal weaning age for mice is at 21 days old, while the pups that had been treated with tamoxifen were not large enough to wean until at least four or five weeks old. Some litters never developed properly and did not survive to become a weight that would be healthy for weaning and wounding. The tamoxifen also posed a threat to the fertility of the female mice. Once pups were treated with tamoxifen in the same cage as an adult female, the female was often unable to give birth to any more litters even after a significant amount of time. In one case a female did give birth to a second litter. Tamoxifen is a

known estrogen agonist and can contribute to this loss of female mouse fertility23. This has made experimentation difficult, as new litters of pups are rarely born. A larger concentration of tamoxifen would most likely prompt more infertility. We have reasoned that the 15mg/mL concentration and amount of 4μL is sufficient for this research, but it is still not perfect. The solvent for the tamoxifen (200 proof ethanol) could have contributed to the slow development seen in pups. Ethanol was originally used because of its ability to dissolve the tamoxifen and its volatility. Tamoxifen is insoluble in water, and the use of water as the solvent would have led to unreliable dosing. However, ethanol has been shown to damage mice in the neonatal stage, and exposure to ethanol at P0-P7 could harbor similar detrimental effects24. Although the application of 4μL is small, it is comparatively large for the bodyweight of a newborn pup. For future experiments, a less harmful solvent such as DMSO could be used for application of tamoxifen onto the pups. This may result is less developmental defects and toxicity. It is also possible that tamoxifen affects the process of hair growth. Although new HFs are formed in the wound area, tamoxifen may have contributed to the small number of new hairs seen growing in the wound area. It may also have affected the visibility of the fluorescent marker in some way. The marker may be time-dependent and could even fade over time, but these possibilities are still unclear. With more research, a better combination of tamoxifen concentration and solvent choice could lead to more tamoxifen being administered safely, giving more complete induction and conclusive results. Fig. 5-7 show that even in successfully induced DP region, only a subpopulation of the DP cells are marked for fluorescence. The morphology of Picture G shows that only 2-3 DP cells in each HF are actually marked. While CD133 should be expressed in all DP cells CD133 may only be expressed in a subpopulation of DP cells during the time of tamoxifen induction from P0-P717. The other DP cells seem to remain unaffected. Since such a small percentage of the DP cells in this example are marked with fluorescence, there is a chance that there exist mobile DP cells that are unmarked by the CD133 / Tomato construct. These cells may be responsible for new HF formation. To test this, a different marker would have to be compared with CD133. Research shows that the Sox2 gene is a marker for all DP cells between E16.5 and E18.5, and a specific subset of HFs post-E18.5. Although CD133 should be a more universal marker for different kinds of HFs, the use of both markers together could be helpful to this experiment25. The Corin gene locus has also been shown to target DP cells, but its activity is delayed until P3 and is gone by P79. Cre activity at this locus will express YFP (yellow fluorescence) in targeted cells; however, other dermal cells are sometimes affected, meaning Corin-cre mice are not restricted to only DP cells26. By using a Sox2 or Corin inducible mouse model, perhaps more DP cells would be marked and the results of this experiment could be more conclusive. The timing and method of tamoxifen induction could be improved. While application from P0-P7 has worked for our experiments, embryonic induction may be much more effective. CD133 expression is strongest at E16.5 and Sox2 expression is strongest between E14.5 and E18.517,25. If tamoxifen was injected or applied on mice during the embryonic stages, it may be able to act more effectively and give more complete induction. The risk involved lies in tamoxifen’s effects on female mouse fertility. Tamoxifen exposure to a pregnant mouse may cause a chemically induced

SPRING 2014 | PENNSCIENCE JOURNAL 21


RESEARCH abortion, as tamoxifen affects estrogen receptors in mice. Tamoxifen administered prenatally has caused lesions and reproductive tract abnormalities in female mice27. The tamoxifen may be overly toxic for embryonic mice, killing them at even low doses and concentrations. For embryonic induction, we should use an even lower concentration than we use at P0-P7 to avoid this effect of toxicity. Tamoxifen induction through food for adult mice has been successful. Induction times vary between different target genes, where some LoxP insertion sites are affected within days and others take up to four weeks28. More information about tamoxifen’s speed of induction on CD133 /Tomato would be needed to use this method for inducing embryonic mice, as the gestation period for a mouse is 20 days on average. Feeding pregnant mice pellets with tamoxifen also poses the risk of a chemically induced abortion or other negative side effects, similar to embryonic injections. In the future, besides more conclusive research on the above experiments, we should consider other possibilities besides DP cell mobility. If DP cells do not migrate into the wound area to form new HFs, then they must be generated from another mechanism or from other cell types. Wounding could induce an embryonic phenotype in the skin; this may be the cause of de novo generation of DP cells and HFs7,9. Other studies have shown that the connective tissue sheath may be a source for new DP cells but this may not hold true for the WIHN model9,11. The exact mechanisms and pathways behind DP cells and their origins in HF neogenesis remain unclear. Understanding DP cell regulation is essential in order to manage hair disorders, including male-pattern baldness and alopecia.

Author Contributions

Project manuscript was prepared by L.M.D., with contributions from K.G., Y.Z., and G.C. Project concept and experimental design planned by L.M.D. and D.G. L.M.D. conducted all mouse handling and breeding, tamoxifen application on pups, postwounding observations, genotyping, cryosectioning, and immunofluorescence. Mouse wounding performed by A.N. Microscopy analyses and photography were performed by L.M.D. with help from D.G. and Y.Z.

References 1. 2. 3. 4. 5.

6. 7.

8.

Paus R. & Cotsarelis G. The biology of hair follicles. N Engl J Med. 342(7):491-497 (1999). Yang C. & Cotsarelis G. Review of hair follicle dermal cells. J Dermatol Sci. 57(1):2-11 (2010). Millar S.E. Molecular mechanisms regulating hair follicle development. J Invest Dermatol. 118(2):216-25 (2002). Hardy M.H. The secret life of the hair follicle. Trends Genet. 8(2):55-61 (1992). Jahoda C.A., Reynolds A.J. & Oliver R.F. Induction of hair growth in ear wounds by cultured dermal papilla cells. J Invest Dermatol. 101(4):584-590 (1993). Schmidt-Ullrich R. & Paus R. Molecular principles of hair follicle induction and morphogenesis. Bioessays. 27:247–261 (2005). Ito M., Yang Z., Andl T., Cui C., Kim N., Millar S. & Cotsarelis G. Wntdependent de novo hair follicle regeneration in adult mouse skin after wounding. Nature. 447:316-321 (2007) Philpott M. & Paus R. Principles of hair follicle morphogenesis. Molecular basis of epithelial appendage morphogenesis (ed. C.M. Chuong) 75-110. Austin, Texas: RG Landes Company (1998).

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Chi W., Enshell-Seijffers D. & Morgan B.A. De novo production of dermal papilla cells during the anagen phase of the hair cycle. J Invest Dermatol. 130(11):2664-2666 (2010). Driskell R.R., Clavel C., Rendl M., & Watt F.M. Hair follicle dermal papilla cells at a glance. J Cell Sci. 124:1179-1182 (2011). Tobin D.J., Gunin A., Magerl M., Handijski B. & Paus R. Plasticity and cytokinetic dynamics of the hair follicle mesenchyme: Implications for hair growth control. J Invest Dermatol. 120:895-904 (2003). Oliver R.F. & Jahoda C.A. Dermal-epidermal interactions. Clin Dermatol. 6:74-82 (1988). Mizrak D., Brittan M. & Alison M.R. CD133: molecule of the moment. J Pathol. 214:3-9 (2008). Zhu L., Gibson P., Currie D.S., Tong Y., Richardson R.J., Bayazitov I.T., Poppleton H., Zakharenko S., Ellison D.W. & Gilbertson R.J. Prominin 1 marks intestinal stem cells that are susceptible to neoplastic transformation. Nature. 457(7229):603-607 (2009). Shmelkov S.V., Butler J.M., Hooper A.T., Hormigo A., Kushner J., Milde T., St. Clair R., Baljevic M., White I., Jin D.K., Chadburn A., Murphy A.J., Valenzuela D.M., Gale N.W., Thurston G., Yancopoulos G.D., D’Angelica M., Kemeny N., Lyden D. & Rafii, S. CD133 expression is not restricted to stem cells, and both CD133+ and CD133- metastatic colon cancer cells initiate tumors. J Clin Invest. 118(6):2111-2120 (2008). Cotsarelis G., Sun T. & Lavker R.M. Label-retaining cells reside in the bulge area of pilosebaceous unit: Implications for follicular stem cells, hair cycle, and skin carcinogenesis. Cell. 61(7):1329-1337 (1990). Ito Y., Hamazaki T.S., Ohnuma K., Tamaki K., Asashima M. & Okochi H. Isolation of Murine Hair-Inducing Cells Using the Cell Surface Marker Prominin-1/CD133. J Invest Dermatol. 127:1052-1060 (2007). Mao X., Fujiwara Y. & Orkin S.H. Improved reporter strain for monitoring Cre recombinase-mediated DNA excisions in mice. Proc Natl Acad Sci. 96:5037–5042 (1999). Muzumdar M.D., Tasic B., Miyamichi K., Li L. & Luo L. A global doublefluorescent Cre reporter mouse. Genesis. 45(9):593-605 (2007). Mao X., Fujiwara Y., Chapdelaine A., Yang H. & Orkin S.H. Activation of eGFP expression by Cre-mediated excision in a new ROSA26 reporter mouse strain. Blood. 97(1):324-326 (2001). Aszterbaum M., Menon G.K., Feingold K.R. & Williams M.L. Ontogeny of the epidermal barrier to water loss in the rat: correlation of function with stratum corneum structure and lipid content. Pediatr Res. 4(1):308-317 (1992). Mujumdar S.K., Valdellon J.A. & Brown K.A. In vitro investigations on the toxicity and cell death induced by tamoxifen on two non-breast cancer cell types. J Biomed Biotechnol. 1(3):99-107 (2001). Jordan C.V. Designer estrogens. Scien Amer. 279:60–67 (1998). Furumiya J. & Hashimoto Y. Effects of ethanol exposure on spatial learning in mice during synaptogenesis. Japanese Journal of Alcohol Studies and Drug Dependence. 46(2):250-259 (2011). Driskell R.R., Giangreco A., Jensen K.B., Mulder K.W. & Watt F.M. Sox2 positive dermal papilla cells specify hair follicle type in mammalian epidermis. Development 136(16):2815-23 (2009). Enshell-Seijffers D., Lindon C., Kashiwagi M. & Morgan B.A. beta-catenin activity in the dermal papilla regulates morphogenesis and regeneration of hair. Dev Cell. 18(4):633-642 (2010). Diwan B.A., Anderson L.M. & Ward J.M. Proliferative lesions of oviduct and uterus in CD-1 mice exposed prenatally to tamoxifen. Carcinogenesis. 18(10):2009-2014 (1997). Kiermayer C., Conrad M., Schneider M., Schmidt J. & Breilmeier M. Optimization of spatiotemporal gene inactivation in mouse heart by oral application of tamoxifen citrate. Genesis. 45(1):11-16 (2007).


RESEARCH

Antimicrobial, Cytotoxic, and Antiproliferative Properties of Native and Invasive Orchids in the Dominican Ethnobotany Matthew O. Bond, Manuel A. Aregullin, and Maria T. Laux Cornell University, Ithaca, N.Y. Although the discovery of natural product candidates for initial drug screening is often guided by the use of ethnobotany, ecological factors can also point to likely candidates for investigation. One such ecological characteristic, invasiveness, can be linked with the production of novel chemical compounds. Therefore, invasive plant species may be more likely to contain biologically active chemistry that is useful for biochemical research and the development of new medicines. In order to test this theory, five species of the Orchidaceae family used in the ethnobotany of the Dominican Republic were collected. Crude extracts were prepared from the plant material, and used to perform in vitro bioassays that measured antibacterial, antifungal, cytotoxic, and antimitotic activity. Results showed that the strongly invasive species tested was more biologically active than 3 of the other native and minimally invasive species, supporting the hypothesis.

Introduction: This research seeks to explore the potential of ethnomedicine, the practice of using plants in traditional medicine. Western biomedicine faces problems including high costs, unpleasant side effects, increased microbial resistance, and inadequacy of treatments for many chronic conditions, such as cardiovascular disease, cancer, Alzheimer’s, and diabetes. Exploration of plants used for traditional healing may yield alternative treatments without these drawbacks. Approximately 80% of the world’s population already relies primarily on natural products as sources of medicine. This occurs even in areas where western medicine is available, due to easier access, cultural preference, and lower cost1. Natural medicines may have been used by humans for over 60,000 years. Today, an estimated 60% of pharmaceuticals are derived directly or indirectly from natural products, 80% of which were already being used for similar purposes in ethnobotany2,3.

Dominican Ethnobotany:

The Dominican Republic is an ideal location for working with herbal medicine, because of its rich cultural heritage. The blend of Taino (an extinct indigenous group), Spanish, French, and African influences has created a very robust collection of natural healing traditions4. Hispaniola Island has a naturally high biodiversity, which enriched over time by the introduction of new species. Many of these plants only survive in cultivation, but some of them have become naturalized and invasive. Strongly invasive species often produce novel chemical compounds which can allow the introduced plants to outcompete native species, and therefore show great potential as sources of new phytomedicines5. For this study, five species from the Orchidaceae family that are used in traditional medicine have been analyzed in a series of bioassays for active chemistry that may possess medicinal properties. Three of these species tested are indigenous to the Dominican Republic, one species is introduced, and one species is invasive.

Medicinal Orchids:

Orchidaceae is the second largest flowering plant family. Orchids have been used medicinally throughout the world for millennia, and are referenced in the Chinese Materia Medica (Shen Nung Pen-tsao Ching), one of the oldest pharmacopeias in existence6. Members of the orchid family have been shown to possess diuretic, anti-rheumatic, antiinflammatory, anticarcinogenic, hypoglycemic, antimicrobial, anticonvulsive, relaxative, neuroprotective, and antiviral activity7. They contain a wide diversity of chemical classes, including phenanthropyans, alkaloids, flavonoids, triterpenoids, stilbenoids, anthocyanins, quinones, glucosides, bibenzyls, and phenanthrenes5.

Plant Description:

Cyrtopodium punctatum is an epiphytic orchid endemic to the Dominican Republic. The pseudobulb is used by Dominicans to treat broken bones, coughs, and kidney disease9,10. In Cuba, the roots are used to treat pneumonia and venereal diseases11. The Charote Indians of Argentina use the pseudobulbs to prepare a decoction used as an emetic and blood pressure regulator12. The most commercially important orchid genus is Vanilla. The seedpods of several species in this genus are used to produce the well-known extract. The primary chemical component of this extract is vanillin, which has antimicrobial, antioxidant, anticarcinogenic, antisicklic, anti-hypolipidemic, anti-aggregant, anti-hepatotoxic, anti-inflammatory, antiviral, analgesic, anesthetic, antiseptic, antimutagenic, antinvasive, antimetastatic, antinocioceptive, and antidepressant properties13,14. Vanilla extract also contains tannins, polyphenols, free amino acids, resins, acids, ethers, alcohols, acetals, heterocyclics, phenolics, hydrocarbons, esters and carbonyls14. Vanilla dilloniana is an endemic species in the Dominican Republic. The climbing stems are used to stimulate appetite and aid digestion10. The pseudobulbs of Broughtonia domingensis, an epiphytic orchid endemic to the Dominican Republic, are often used for infections and kidney problems10. No other medicinal in-

SPRING 2014 | PENNSCIENCE JOURNAL 23


RESEARCH formation about this genus or species could be found in the literature. Oeceoclades maculata is a terrestrial orchid. It is native to the tropics of Africa, but is invasive, and is now found throughout the neotropics15. In the Dominican Republic, the roots and pseudobulb are used to make a tea for stomach problems10. No other information about this genus or species could be found in the literature. The genus Dendrobium is native to southeast Asia and Oceania. Many ornamental hybrids of Dendrobium have been developed and introduced around the world, but the genus only Orchid

Ecological Status in Dominican Republic

displays invasive behavior in Hawaii and the Seychelles16. At least a dozen different Dendrobium species are used in traditional medicine throughout southeast Asia6,7,8. Dendrobium species contain phenanthrenes; stilbenoids; lectins; alkaloids; the enzymes chalcone synthase, sucrose synthase, and cytokinin oxidase; and polysaccharides. These compounds have shown immunomodulatory, hepatoprotective, antioxidant, anticancer, and neuroprotective activities6,17. The species used in this research, Dendrobium x hybrida section Phalaenanthes, is commonly grown epiphytically or terrestrially as an ornamental plant. The roots were used for extraction.

Ecological Status in the World

Use in Dominican Republic

Plant part tested

Cyrtopodium punctatum

Endemic

Non-invasive

Broken bones, coughs9, and kidney disease10

Roots

Vanilla dilloniana

Endemic

Non-invasive

Stimulate appetite and aid digestion10

Stems

Broughtonia domingensis

Endemic

Non-invasive

Infections and kidney disorders10

Pseudobulb

Oeceoclades maculata

Introduced

Invasive through neotropics

Stomach problems10

Roots and pseudobulb

Dendrobium x hybrida section Phalaenanthes

Introduced, non-invasive

Genus invasive in Hawaii and the Seychelles

None — other Dendrobium spp. used throughout Asia7

Roots

Table 1: Summary table of plant information: origin ecological behavior, ethnobotanical use, and part tested.

Materials and Methods: Plant material from Dominican medicinal species was collected in the Punta Cana area, and tested in the lab at the Punta Cana Ecological Foundation. The plant part used in traditional preparations was isolated from the collected plant material and laid flat on a laboratory bench top and allowed to air dry for a period of days. After approximately four days, the dried plant material was ground in a blender to yield small particulates. Unless otherwise noted, 1 gram of ground plant material from each species was transferred to a scintillation vial and 7.5 ml of an organic solvent were added and allowed to stand for 48 hours before they were used in bioassays. Two extracts were prepared for each plant species, one with isopropyl alcohol [(CH 3)2CHOH] and one with methanol (CH 3OH). Due to limited availability of plant material, 0.3 grams of Dendrobium particulate were extracted with 5 ml of organic solvent. In order to cover the large volume of Cyrtopodium particulate, 15ml of organic solvent were used.

Disc Diffusion Antimicrobial Assays:

Filter discs of extracts were prepared for Kirby-Bauer

24 PENNSCIENCE JOURNAL | SPRING 2014

disc diffusion by submerging 5 discs twice in each methanol or the isopropanol crude extract. Saturated filter discs were left out at room temperature for 30 minutes in order for the solvent to evaporate and leave behind only the crude plant extract. Five nutrient agar plates prepared using 23 g of Nutrient Agar [Difco BD cat# 213000) in 1 L of water. One plate was inoculated with each of the following microbes: Pseudomonas aeruginosa, Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, and Saccharomyces cerevisiae. After inoculation, dried filter discs were placed on agar surface. Plates were incubated at 37°C for 24 hours before inhibition area were analyzed.

Artemia salina Cytotoxicity Assay:

This assay was used to determine the lethality of the plant extracts to brine shrimp (Artemia salina) nauplii, an in vitro assay which correlates strongly with results from antitumor activity in human cancer cell lines 18. A 24 well plate (6x4) with a capacity of 3 mL per well was used for the brine shrimp assay. The plate was set up for testing as follows: a 1 mL aliquot of brine shrimp from a hatchery was transferred to the first well in column #1 using a pipette followed by the addition of 2 mL of brine


RESEARCH from a glass cup. 0.5 mL from well #1 was transferred into each of the remaining 5 wells in the first row (#2-#6). 2 mL of brine were then added to each well to make a total of 2.5mL in each well. This was repeated for each row of wells. After all wells in the plate were set up for testing, each row was designated for a single extract at four different concentrations. 1 drop (25 μL) of each extract was added to the first well of its designated row; 2 (50 μL), 3 (75 μL), and 4 drops (100 μL) of each extract were added to the rest of the wells in the row. Eight control wells were also prepared using isopropyl alcohol and methanol at each of the four concentrations. After 12 hours the wells were observed under a dissecting microscope and the number of brine shrimp actively swimming was counted to determine percent mortality relative to the controls. The assay was repeated twice and results were averaged.

bition of division at the one cell stage. A positive result indicates that the compounds from the plant alter or inhibit DNA synthesis19,20. Arbacia punctata urchins were gathered from the Punta Cana Resort and Hotel pier and placed on ice to prevent premature spawning. Gametes were obtained by injecting approximately 1 mL of 0.1M KCl through the soft tissue of the oral surface into the body cavity. Approximately 5 mL of eggs were collected inside of a beaker and were fertilized with 200 μL of sperm. One drop of fertilized egg solution and 1mL of seawater was placed into each well of a 24 well plate. Extracts and solvent controls were placed at concentrations of either 1 or 4 drops into wells. Anti-mitotic activity of extracts was determined 4 hours after fertilization using a compound microscope to observe whether or not cell division post-fertilization had occurred. Three sample counts were taken in each well. The percent of mitotic activity for all counts in a well was averaged, and analyzed with standard error bars.

Sea Urchin Embryo Antiproliferative Assay:

This assay was conducted to test the extracts for inhi-

Results: Disc Diffusion Antimicrobial Assays:

effective, and produced the only inhibitory results out of all isopropanol fractions. The Dendrobium extract exhibited no antimicrobial activity. In general, the methanol extracts contained more deterrent chemistry.

As seen in table 1, the overall microbial inhibition of the extracts was weak. The Vanilla extract was the most

Antimicrobial Assays Solvent

Isopropanol

Plant

Cyrtopodium punctatum

Methanol

Vanilla dilloniana

Broughtonia domingensis

Oeceoclades maculata

Dendrobium x hybrida

Cyrtopodium punctatum

Vanilla dilloniana

Broughtonia domingensis

Oeceoclades maculata

Dendrobium x hybrida

Gram negative bacteria Escherichia coli

0

0

0

0

0

+

0

+

0

0

Pseudomonas aeruginosa

0

+

0

0

0

+

+

0

+

0

Listeria 0 monocytogenes

0

0

0

0

+

0

+

0

0

Staphylococcus aureus

0

+

0

0

0

+

0

0

0

0

0

+

0

0

0

+

0

0

+

0

Gram positive bacteria

Fungus Saccharomyces cerevisiae

Table 2: Result o f microbial inhibition tests. Key: 0= no inhibition, + = weakly active. The isopropanol extract of V. dilloniana and the methanol extract of C. punctatum contain chemistry that could provide a source of antimicrobial treatments.

Artemia salina Cytotoxicity Assay:

As seen in figures 1 and 2, the controls showed equivalent inhibition to most extracts, and increasing concentrations of ex-

tract did not produce a clear pattern. Vanilla and Oeceoclades extracts showed the strongest cytotoxicity and sharpest results. The lethal concentration (LC50) could not be determined for any of the extracts at the concentrations tested.

SPRING 2014 | PENNSCIENCE JOURNAL 25


RESEARCH Antiproliferative Assay

100 90

25 μL

80

50 μL

70

Cyrtopodium Vanilla Broughtonia Oeceoclades Dendrobium punctatum dilloniana domingensis maculata x hybrida

Methanol extracts

Control

100 μL

Figure 1: Lethality of m ethanol extracts to brine shrimp. Data is average of two trials. The strong, dose-­‐dependent response of V. dilloniana indicates that it contains chemical compounds that could kill rapidly dividing cells.

% of live shrimp

100 25 μL

80

50 μL

70

75 μL

60 50

100 μL

Cyrtopodium Vanilla Broughtonia Oeceoclades Dendrobium punctatum dilloniana domingensis maculata x hybrida

Isopropanol extracts

Control

Figure 2: Lethality of isopropanol extracts to brine shrimp. Data is average of two trials. The strong, dose-­‐dependent response of O. maculata indicates that it contains chemical compounds that could kill rapidly dividing cells.

Sea Urchin Embryo Antiproliferative Assay: As seen in figure 3, all 25 µL methanol extracts showed significant inhibition of mitosis, compared to the control. As seen in figure 4, the 25 µL isopropanol extracts also showed significantly lower proliferative activity than the control, except for Vanilla. The 100 µL dose of isopropanol Cyrtopodium and Broughtonia extracts also showed significantly lower proliferative activity than the control.

% Cell Division

Antiproliferative Assay 50 40 30 20

25 μL

100 μL

10 0

Cyrtopodium punctatum

Vanilla dilloniana

Broughtonia domingensis

Oeceoclades Dendrobium x maculata hybrida

Methanol Extracts

Control

Figure 3: Mitotic inhibition of sea urchin embryos by methanol extracts. n=3. All orchid species may contain anti-­‐cancer compounds.

26 PENNSCIENCE JOURNAL | SPRING 2014

40 30 20

25 μL

100 μL

10 Cyrtopodium punctatum

Vanilla dilloniana

Broughtonia domingensis

Oeceoclades Dendrobium x maculata hybrida

Isopropanol Extracts

Control

Figure 4: Mitotic inhibition of sea urchin embryos by isopropanol extracts. n=3. The dose-­‐ dependent response of D. x hybrida and B. domingensis indicates that they contain potential anti-­‐cancer compounds. C. punctatum and O. maculata may also contain anti-­‐cancer compounds.

Discussion:

Cytotoxicity Assay

90

50

0

75 μL

60 50

% Cell Division

% of live shrimp

Cytotoxicity Assay

As seen in Table 3 (right), all orchid species tested displayed some form of biological activity, supporting their use in traditional medicine and confirming the value of ethnobotany as a tool in drug discovery. However, no claims can be made regarding the efficacy of specific treatments using these plants. The results of this exploration indicate that several of these plants, particularly Vanilla dilloniana and Oeceoclades maculata, may merit future pharmacological study. The antibacterial and antifungal activity exhibited by Cyrtopodium punctatum may explain its traditional role in the treatment of cough, pneumonia, kidney disorders, and venereal disease. It also showed antiproliferative properties. Broughtonia domingensis also exhibited antiproliferative properties, but showed only mild antibacterial activity. The most active plant tested was Vanilla dilloniana, particularly the methanol fraction, indicating that the active chemistry is mildly lipophilic. The primary compound in vanilla bean extract is vanillin, which is easily extracted in methanol or isopropanol. Vanillin has shown antimicrobial activity against Escherichia coli, Listeria monocytogenes, and fungi 4. Although the methanol extract of V. dilloniana did not inhibit either of these bacteria, it did show activity against other bacteria, as well as the yeast Saccharomyces cerevisiae inhibited by the isopropanol extract. The methanol extract also showed antiproliferative activity. Vanillin has shown anti-aggregant, antimutagenic, antinvasive, and antimetastatic properties 13,14. Thus, vanillin may be the active compound responsible for the bioactivity observed in the V. dilloniana extract. However, there are many other chemical classes in vanilla bean extract that have biological activity, listed previously, which may also have influenced the results of the bioassays14. Oeceoclades maculata, produced the second most active extract. Most of the positive bioassay results were from the isopropanol fraction, indicating that the active chemistry is highly lipophilic. It showed antibacterial, antifungal, cytotoxic, and antiproliferative


RESEARCH

Cyrtopodium punctatum

Vanilla dilloniana Broughtonia domingensis

Oeceoclades maculata

Dendrobium x hybrida

Fraction:

Methanol

Isopropanol

Methanol

Isopropanol

Methanol

Isopropanol

Methanol

Isopropanol

Methanol

Isopropanol

Antibacterial

X

X

X

X

X

Antifungal

X

X

X

Cytotoxic

X

X

Antiproliferative

X

X

X

X

X

X

X

X

X

Extract:

Table 3: Summary of bioassay results, showing V. dilloniana to be m ost active and D. x hybrida to be least active.

activity. This validates the Dominican use in the treatment of infections. The least active orchid tested was Dendrobium x hybrida section Phalaenanthes. It only showed activity in the antiproliferative assay. This supports prior studies that have shown other Dendrobium spp. to have chemical compounds with anticancer properties17. Orchids are known to require associations with fungi in order to germinate and grow successfully. This symbiosis requires the orchid to be able to keep the fungi outside of the cells in order to prevent complete infection by the fungus. It is hypothesized that antifungal agents are produced by orchids in order to maintain a balanced relationship with the fungus7. However, only 3 of the 10 fractions tested produced a positive result in the antifungal activity. This may be because Saccharomyces cerevisiae is a yeast in the phylum Ascomycota, which does participate in symbioses with plants. Most soil-borne fungi that have interactions with orchids are in the phylum Basidiomycota, so orchids may preferentially produce antifungal agents specific to this phylum 21.

Limitations: In the antimicrobial assays, all inhibition was extremely weak, producing results that were hard to quantify. The cytotoxicity assay had to be repeated 4 times, due to low egg viability. Accurate counts were often difficult due to the high amount of movement of live shrimp. The first successful test still had a very low number of shrimp in each well (~8), so it was repeated until a second successful test was completed with ~20 shrimp in each well. These data were averaged to create more representative results. Another factor that may have affected the results was the misidentification of two orchids. Cyrtopodium punctatum was initially identified as belonging to a genus whose roots are used medicinally. Thus, only the roots were prepared for extract, instead of the traditional C. punctatum preparation that includes both

the pseudobulbs and the roots9, 10, 11, 12. Dendrobium x hybrida section Phalaenanthes was initially identified as belonging to a genus whose roots are used medicinally. Thus, the roots were prepared for extract, while ethnobotanical preparations of other Dendrobium spp., primarily use leaves, not roots7. Because the roots of Dendrobium x hybrida were collected from a cultivated plant in a nursery pot, they may have been contaminated with chemicals commonly used in commercial cultivation, such as pesticides, fungicides, and fertilizers. Although the roots were thoroughly washed, they may still have contained trace amounts of materials which could have affected the results.

Conclusions: Many factors help determine how and why certain plants display invasive behavior. Two of these, defenses against herbivory and enhanced competitive ability, are chemically mediated. Thus, invasive species may be more likely to contain unique photochemistry that has biological activity5. Oeceoclades maculata, an orchid endemic to tropical Africa, has rapidly invaded the entire neotropical region. As one of the most successful invasive species on the planet, it provides a good candidate for bioactivity comparison with orchids that are endemic to the Dominican Republic15. Out of five species of orchid that were studied, O. maculata had the second highest level of biological activity. It was more active than two of the three native species tested, and was considerably more active than Dendrobium x hybrida section Phalaenanthes, which is in a genus that only displays weakly invasive behavior. This supports the hypothesis that highly invasive species are more likely to produce biologically active chemistry, which is a new source of therapeutic drugs.

Acknowledgements: I wish to specially thank the following individuals and organizations for their financial and intellectual

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RESEARCH support: Cornell University MHIRT Program (Dr. Manuel Aregullin, Dr. Maria Laux, 2013 Participants), National Institute of Health, Cornell University Department of Plant Biology, Dextra Undergraduate Research Endowment Fund, Punta Cana Ecological Foundation, Dr. Kevin Nixon, Dr. Jackeline Salazar, Rolando Sano, Dr. John Berry, and Dr. Marcus McFerren.

Literature Cited: 1. Tam, T. W., Liu, R., Arnason, J. T., Krantis, A., Staines, W. A., Haddad, P. S., and Foster, B. C. 2009. Actions of ethnobotanically selected Cree anti-diabetic plants on human cytochrome P450 isoforms and flavin-containing monooxygenase 3. J. Ethnopharmacology 126(1): 119-126. 2. Ji, H.F., Li, X.J., and Zhang, H.Y. 2009. Natural products and drug discovery. Can thousands of years of ancient medical knowledge lead us to new and powerful drug combinations in the fight against cancer and dementia? EMBO Reports 10:194–200. 3. Fabricant, D. S. and Farnsworth, N. R. 2001. The Value of Plants Used in Traditional Medicine for Drug Discovery. Env. Health Perspectives. 109(1): 69-75. 4. Brown, I. Z. 1999. Culture and Customs of the Dominican Republic. Greenwood Press, Westwood, CT, USA: 16-69. 5. Cappuccino, N, and Arnason, J. T. 2006. Novel Chemistry of Invasive Exotic Plants. Biol. Lett. 2(2): 189-903. 6.

Kong, J. M., Goh, N-K., Chia, L-S., and Chia, T-F. 2003. Recent advances in traditional plant drugs and orchids. Acta Pharmacologica Sinica 24(1): 7-21.

7.

Gutierrez, R. M. P. 2010. Orchids: A review of uses in traditional medicine, its phytochemistry and pharmacology. J. Med. Plants Research 4(8): 592-638.

8. Singh, A., and Duggal, S. 2009. Medicinal Orchids: An Overview. Ethnobotanical Leaflets 13: 351-63. 9. Salazar, Jackeline. 2013. Cornell University MHIRT Program. Personal Communication. 10. Sano, Rolando. 2013. Cornell University MHIRT Program. Personal Communication. 11. Cano, J. H., and Volpato, G. 2004. Herbal Micture in the Traditional Medicine of Eastern Cuba. J. 28 PENNSCIENCE JOURNAL | SPRING 2014

Ethnopharmacology 9(2-3): 293-316. 12. Scarpa, G. F. 2009. Medical ethnobotany of Chorote indians and comparison with the one of Criollos of Semiarid Chaco, Argentina. Darwiniana 47(1): 92. 13. Shoeb, A., Chowta, M., Pallempati, G., Rai, A., and Singh, A. 2013. Evaluation of antidepressant activity of vanillin in mice. Indian J. of Pharmacology 45(2): 141. 14. Sinha, A. K., Sharma, U. K., and Sharma, N. 2008. A comprehensive review on vanilla flavor: Extraction, isolation and quantification of vanillin and others constituents. Int. J. Food Sci. and Nutrition 5 s9(4): 299-326. 15. Cohen, I. M., and Ackerman, J. D. 2009. Oeceoclades maculata, an alien tropical orchid in a Caribbean rainforest. Annals of Botany 104(3): 557563. 16. Emonocot 2013. “Dendrobium Sw.” Kew Royal Botanic Garden. Website, accessed 7/22/13: http://emonocot.org/taxon/urn:kew.org:wcs:taxon:56967 17. Ng, T. B., Wong, J. H., Ye, X., Wing Sze, C. W., Tong, Y., and Zhang, K. Y. 2012. Review of research on Dendrobium, a prized folk medicine. Applied Microbiology and Biotechnology 93(5): 1795-1803. 18. McLaughlin, J. L, Chang, C., and Smith, D. L. 1993. Simple Bench-Top Bioassays (Brine Shrimp and Potato Discs) for the Discovery of Plant Antitumor Compounds. In: Human Medicinal Agents from Plants. Kinghorn, A, et al. ACS Symposium Series; American Chemical Society: Washington, DC.: 112-137. 19. Ikegami, S., and Kawada, K.; Kimura, Y., and Suzuki, A. 1979. A Rapid and Convenient Procedure for the Detection of Inhibitors of DNA Synthesis Using Starfish Oocytes and Sea Urchin Embryos. Agric. Biol. Chem. 43(1): 161-166 20. Semenova, M. N., Kiselyov, A., and Semenov, V. V. 2006. Sea urchin embryo as a model organism for the rapid functional screening of tubulin modulators. BioTechniques 40: 765-774. 21. Garriga, R., Saladini, C., Timossini, C., Viera, N., and Bayman, Pl. 2009. "Mycorrhizal specificity of the invasive orchid Oeceoclades maculata in Puerto Rico". Río Piedras Campus: External Scientific Advisory Committe (ESAC). http://repositorio. upr.edu:8080/jspui/handle/10586 /202


RESEARCH

miRNA Signatures of Rats Resilient or Vulnerable to Social Defeat Stress Benjamin Nicholas, Abhishek Sengupta, Willem Heydendael, Seema Bhatnagar University of Pennsylvania, Philadelphia PA 19104, USA The biological mechanisms underlying resilience and susceptibility to social stress, a major risk factor in several psychiatric disorders, remain to be elucidated. However, regulation of gene expression by microRNAs (miRNAs) has received more attention recently as a potential molecular mechanism underpinning some elements of psychiatric disorders. miRNAs are small RNA molecules about 20 to 24 nucleotides in length which can suppress expression of a given gene by binding to the 3’ UTR of the corresponding mRNA transcript. Though a growing body of knowledge now exists connecting the regulatory effects of miRNAs in the brain to psychiatric disorders, the question of the relevance of miRNA regulation to stress resilience and susceptibility remains unanswered. To assess the potential role of miRNA regulation underlying stress resilience and susceptibility, rats were subjected to social defeat stress and segregated into short latency (SL) and long latency (LL) groups based on latency to defeat. Microarrray and RT-PCR analysis of the miRNA expression in peripheral blood of each group of rats revealed a panel of differentially expressed miRNAs between SL and LL which could potentially serve as blood-based biomarkers of stress susceptibility or resilience in humans. A similar analysis of miRNA expression in the prefrontal cortex (PFC) of these rats revealed another panel of differentially expressed miRNAs between SL and LL. Analysis of gene expression (via custom RT-PCR array) in the PFC of such rats as well as target prediction analysis for differentially expressed miRNAs in the PFC identified Vascular Endothelial Growth Factor A (VEGF-A) as a potential gene target of miRNAs up-regulated in the PFC of SL rats.

Introduction Stress is a major risk factor for a plethora of psychological pathologies such as Major Depressive Disorder (MDD)1. Such stress-related disorders place an alarming amount of disease burden on society, as there is a 16.2% chance that someone will suffer from MDD alone sometime in his or her lifetime2. Though stress is a prevalent component of everyday life, it precipitates psychopathology in some while others are left unscathed3. Thus, the ability to predict and explain phenotypes which are either resilient or susceptible to stress is a necessary step for combating stress-related psychiatric disorders. The hypothalamic-pituitary-adrenal (HPA) axis has been relatively well characterized with respect to its mediation of the stress response and its role in determining susceptibility and resilience to social stress has recently been studied4,5. Another brain region which is gaining traction as a critical component of the stress response is the prefrontal cortex (PFC)6. As the most evolved brain region, the PFC regulates thoughts, actions, and emotions through widespread projections to the amygdala, hypothalamus, brainstem, monoamine systems, hippocampus, and reward circuits. This connectivity alone places the PFC in a position to modulate the stress response7.Indeed, lesions of various subregions of the rodent PFC can result in a strengthening of the HPA axis stress response, implying that a role of the PFC in stress modulation may involve inhibition of HPA axis activity8-10. The rodent PFC has also been shown to be highly sensitive to activation via stress and also undergo structural modifications in response

to such stress. Chronic stress in particular appears to be associated with architectural changes in the PFC which hinder its ability to inhibit the HPA axis stress response7. Thus the literature so far suggests that the PFC plays a crucial role in determining whether an individual is susceptible or resilient to stress, but the cellular mechanism by which resilience or susceptibility is reflected in the structure of the PFC remains to be elucidated. Attention has also recently been directed towards microRNAs (miRNAs) as potential mediators of the processes underlying psychiatric disorders. miRNAs are small RNA molecules about 20 to 24 nucleotides in length which can suppress expression of a given gene by binding to the 3’ UTR of the corresponding mRNA transcript11. In the context of neurons, miRNAs are known to regulate gene networks in a manner such that they can assist the brain in adapting to new situations and also mediate neuronal plasticity12. As several psychological disorders involve deficits in these processes, the level of miRNA regulation has become an active area of research for discovering the mechanisms of psychopathology13.For instance, a characteristic miRNA signature has been identified in the PFCs of depressed patients who committed suicide14. However, the question of the relevance of miRNA regulation to stress resilience and susceptibility remains unanswered15. Studying the miRNA and gene expression of rats resilient and susceptible to social stress could potentially illuminate how stress leads to the structural changes in the PFC. Furthermore, since miRNA expression has been shown to be more reproducible than gene expression, identification of a panel of differen-

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tially expressed miRNAs between susceptible and resilient individuals in peripheral blood could serve as a useful clinical tool16. Such blood-based signatures have already been identified for Alzheimer’s disease and schizophrenia in humans, and in the latter case, the identified signature was found capable of diagnosing its corresponding disorder with about 80% accuracy in a test cohort of human patients16, 17. The aim of this study was to determine the differences between a susceptible and resilient rat on the level of miRNA regulation. The social defeat paradigm (modified by Wood et. al. from Miczek) has proven a useful tool for identifying rats that are resilient or susceptible to social stress5. Analyzing the miRNA expression in the blood of rats identified by this method as either resilient or susceptible to social stress could yield a panel of biomarkers indicative of resilience or susceptibility, while a similar analysis in the PFC of such rats could offer an explanation for how resilience or susceptibility to stress is determined by the cellular processes underlying the cytoarchitecture of the PFC.

Methods Social Defeat Paradigm The social defeat paradigm used to segregate rats that are resilient or susceptible to stress was carried out as described by Wood5. Male Sprague Dawley rats were used as intruder or control rats, while male LongEvans rats who had been previously screened for high levels of aggression served as residents (Charles River, Wilmington, MA). Sprague-Dawley rats were assigned randomly to a social defeat group or a control group for 7 consecutive days. Each day, each rat assigned to the social defeat group (the “intruder”) was placed in the home cage of an unfamiliar resident for thirty minutes. Each episode typically involved an antagonistic encounter between the two rats and usually ended with 30 PENNSCIENCE JOURNAL | SPRING 2014

subordination or defeat of the intruder. Defeat was signaled by the intruder assuming a supine position for about 3 seconds. Following defeat, a wire mesh partition was positioned in the cage to prevent further physical contact between intruder and resident. However, visual, auditory, and olfactory contact continued for the rest of the 30 minute session. Latency to assume the submissive supine posture characteristic of social defeat was recorded and averaged over seven consecutive days of defeat exposure. If an intruder managed to resist defeat by the resident for 15 minutes, the wire mesh enclosure was positioned between the two rats for the rest of the session. Control rats were placed behind the wire mesh enclosure in a novel cage for a 30 minute session each day for seven consecutive days. After each session, rats were returned to their home cages. Tissue Collection Following completion of the 7 day defeat paradigm, all intruder and control rats were sacrificed. Peripheral blood and whole brains were extracted from each and frozen at -80°C. In preparation for tissue analysis for miRNA expression, the blood samples were later thawed and centrifuged so that the plasma could be removed, leaving only the cellular components behind in the pellet. The brains were also thawed and punched at the PFC. PCR Analysis of Tissue Total RNA was extracted from both blood pellets and PFC punches and analyzed via Affymetrix MicroRNA 2.0 Microarray. Gene expression was also analyzed in PFC punches via custom RT-PCR array. Validation of significant miRNAs identified by microarray in both blood and PFC was performed by RT-PCR. 20-μL RT-PCR reactions were prepared according to the manufacturer’s instructions using the QuantiTect


RESEARCH SYBR Green PCR kit, cDNA samples of concentration 1.5 ng/μL, and the appropriate universal and miRNAspecific primers (Qiagen). miRNA Target Prediction To further study the functional consequences of such differential miRNA regulation on the PFC, lists of putative gene targets of the miRNAs significantly up-regulated in the PFC of SL rats as compared to LL rats (SL>LL) were compiled by querying three online miRNA target prediction algorithms – miRDB (http://mirdb.org/miRDB/), TargetScan (http://www. targetscan.org/), and miRanda (http://www.microrna. org/microrna/home.do). The results from these three databases were combined to form a union of putative gene targets of SL>LL miRNAs in the PFC. Figure 1 shows the general scheme of how this union was generated. The union was then filtered to identify high quality predictions. A predicted gene target of a SL>LL miRNA in the PFC was identified as a “high quality prediction” if it (1) was predicted by all three algorithms to be targeted by at least one miRNA and (2) was also predicted by any of the databases to be targeted by at least five miRNAs. These conditions were used to filter the lists of predicted targets of SL>LL miRNA in the PFC so that only high quality predictions remained. SL-LL differences Various manipulations were used to identify differences between rats which exhibited a short average latency to defeat (SL) and rats which exhibited a long average latency to defeat (LL). An arbitrary latency cutoff was selected based on the distribution to differentiate SL rats from LL rats. All significant differences in expression of miRNAs and genes in the blood and PFC between SL and LL rats were identified via Student’s t-test (P < 0.05). miRNA expression was also correlated with target gene expression as well as defeat latency using R2 and p-values (respectively) as indicators of the strength of the correlation (R2 > 0.2, P < 0.05). Pathway analysis To assess the functional consequences of miRNA regulation of these predicted gene targets, each list of high quality predictions was used to query the Kyoto Encyclopedia of Genes and Genomes (KEGG) via WebGestalt (http://bioinfo.vanderbilt.edu/webgestalt/) and Ingenuity Pathway Analysis (IPA; http://www.ingenuity.com/products/pathways_analysis.html). KEGG is an online database that contains lists of genes which constitute certain biological pathways while WebGestalt is an online system which can query such databases with a given list of genes and then provide the user with a list of biological pathways which are most highly implicated by the inputted list of genes according to certain statistical parameters. The following parameters were used: Organism: rnorvegicus, ID Type: gene_symbol, Ref Set: entrezgene, Significance Level:

p < 0.05, Statistics Test: Hypergeometric, MTC: BH, Minimum: 2. IPA was used to generate novel gene networks based on input lists of genes. Those gene targets in the PFC which had expression levels consistent with SL>LL miRNA regulation (as measured in the custom RT-PCR array), were predicted to be targeted by SL>LL miRNAs, and also appeared in the pathways provided by this analysis were selected for further study. Using only miRNAs which correlated or trended with defeat latency, correlation plots between target mRNA levels and regulator miRNA levels were created to determine if the negative correlation expected of miRNA regulation could be detected for each gene of interest. Western blot for VEGF-A Validation of differential expression of Vascular Endothelial Growth Factor A (VEGF-A) between PFCs of SL and LL rats was carried out via western blot. PFC samples were used from a separate cohort of rats which had undergone the same seven day defeat paradigm. Primary antibodies used included goat anti-VEGF primary antibodies (Santa Cruz Technologies; 1:100) as well as mouse anti-β-actin primary antibodies (Sigma; 1:5000). The following secondary antibodies were used as well: mouse anti-goat (Odyssey; 1:15000) and donkey anti-mouse (Odyssey; 1:15000). VEGF-A expression was calculated as a percentage of β-actin expression. Any significant differences in differential expression of VEGF were calculated via Student’s t-test (P < 0.05).

Results The average defeat latencies of intruder rats were found to fall into a bimodal distribution (see figure 2). On the basis of this distribution, a cutoff of 300 seconds was selected to differentiate SL rats from LL rats

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32 PENNSCIENCE JOURNAL | SPRING 2014


RESEARCH (where defeat latencies shorter than 300 seconds indicate SL and latencies longer than 300 seconds indicate LL). Microarray analysis identified panels of miRNAs differentially expressed to a significant degree between SL and LL rats in both blood and PFC (P < 0.05). The expression of some of these miRNAs correlated with defeat latency across subjects (P < 0.05). Table 1 displays all miRNAs expressed to a significantly different degree between SL and LL rats in blood and PFC as well as the p-values of their defeat latency correlations. Additionally, the custom RT-PCR array revealed that VEGF-A is significantly down-regulated in SL rats as compared to LL rats (P < 0.05; see figure 3A).Significantly higher expression of miR-20b-5p in blood of SL rats as compared to LL was confirmed via RT-PCR (P < 0.05; figure 3B). Similarly, significantly higher expression of miR-16 and miR-22 in the PFC of SL rats as compared to LL rats was also confirmed via RT-PCR (P < 0.05; figures 3C and 3D). Querying the KEGG database via Webgestalt with the high quality gene target predictions of SL>LL miRNAs identified in the PFC yielded a list of the biological pathways most heavily targeted by this particular group of miRNAs in PFC. Figure 4 displays one of these pathways, with predicted gene targets indicated by red font. Querying IPA with the high quality gene target predictions of SL>LL miRNAs identified in the PFC yielded two large overlapping gene target networks which also included other genes added by IPA which have been shown to have experimentallyverified interactions with the gene targets. Overlaying data from the custom RT-PCR array onto this amalgamated gene target network allowed for visualization of differences in gene expression between SL and LL rats on the landscape of miRNA regulation. VEGF-A is the only gene indicated in this network by custom RTPCR array data as a gene target which is differentially expressed to a significant degree between SL and LL rats in the PFC. Further validation of VEGF-A expression in SL and LL rats via western blot confirmed that this gene is indeed significantly down-regulated in SL PFCs as compared to LL PFCs by Student’s t-test (P < 0.05; see figure 5). The expression of several predicted SL>LL miRNA regulators of VEGF-A was found to correlate negatively with VEGF-A expression (see figure 6).

Discussion The first major goal of this study was to identify miRNAs in the blood with patterns of expression which could differentiate an individual susceptible to social stress from a resilient individual. While this study did identify a panel of miRNAs significantly upregulated in the blood of SL rats as compared to LL rats as well as a panel of miRNAs significantly up-regulated in the blood of LL rats as compared to SL rats, a smaller

number of these miRNAs were found to correlate with the corresponding behavioral phenotype (resilience or susceptibility). Nonetheless, miR-20b-5p did arise as a SL>LL miRNA in the blood which has not only been validated by RT-PCR as a significantly up-regulated in SL as compared to LL but also correlates with defeat latency. Though a practical blood-based miRNA signature indicative of susceptibility to stress should ideally include an entire panel of biomarkers which correlate with the correct behavioral phenotype, miR-20b-5p offers a good starting point for further research to develop such a biomarker signature. The other major goal of this study was to illuminate how differential expression of miRNAs in the PFC may give rise to a resilient or susceptible phenotype on the cellular level. The beginning of the answer to this question entails appraisal of the fact that a much larger degree of up-regulation of miRNA expression in SL rats was observed as compared to that of LL rats in both blood and PFC (see table 1). More up-regulated miRNAs implies more gene suppression (as suggested by the fact that the original, unfiltered union of predicted gene targets is over three times greater for SL>LL miRNAs than one which had been generated for LL>SL miRNAs) which in turn implies more differences from baseline in the SL phenotype as compared to the LL

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RESEARCH phenotype. Furthermore, this greater number of predicted gene targets for SL>LL miRNAs as opposed to LL>SL miRNAs was found to offer more enrichment of pathways serving cellular functions than afforded by those of LL>SL miRNAs. Since the predicted gene regulation of SL>LL miRNAs thus resulted in more discernible and readily interpretable results, most of the analysis of the functional consequences of miRNA regulation in this study pertains to the SL phenotype. Figure 4 highlights one of the pathways targeted by SL>LL miRNAs which has been identified by WebGestalt via KEGG. Genes which are predicted targets of SL>LL miRNAs are highlighted in red font and the cellular processes which the pathway mediates are shown on the right side of each image. This pathway as well as others identified by the KEGG analysis demonstrates that SL>LL miRNAs are predicted to suppress the expression of several genes needed for pathways which support cellular functions such as migration, proliferation, differentiation, axonal outgrowth, and plasticity. The results of this analysis are consistent with the notion that structural changes induced by stress in the PFC and the resulting deficits in PFC function may underlie a phenotype of stress susceptibility potentially due to lack of inhibition of the HPA axis response6. Of particular interest, however, is VEGF-A and its signaling pathway which mediates cell proliferation, migration, and survival. VEGF-A was the first discovered member of the VEGF family. Thus, VEGF-A is synonymous with its historical name “VEGF.�18 VEGFA is an important growth factor which influences vascular permeability and angiogenesis19. Though the VEGF family consists of six isoforms which primarily act on blood vessels, increasing evidence has indicated that VEGF-A, VEGF-B, and VEGF-C also act on neurons18. Of particular interest, inadequate levels of VEGF-A may be linked to the degeneration of motor neurons observed in amyotrophic lateral sclerosis (ALS)19. VEGF-A was identified in this study as the one gene highlighted by custom RT-PCR array data (and confirmed by western blot) to undergo significant changes in expression between SL and LL rats within the context of regulation exerted by SL>LL miRNAs in the PFC (Figure 5). Both of these techniques demonstrate that VEGF-A is down-regulated in the PFC of SL rats as compared to that of LL rats. Up-regulation of miR497, 27a, 195, 22, and 16 has also been identified in the PFC of SL rats as compared to that of LL rats via microarray (as well as RT-PCR in the case of 22 and 16). VEGF-A is a high quality gene target prediction for all of these miRNAs. Inhibition of VEGF-A by these SL>LL miRNAs is further suggested by the negative expression correlations some of these miRNAs have with VEGF-A expression, as negative correlations between regulator miRNA expression and gene target expression are consistent with the notion of miRNA-mediated regulation (see Figure 6). These results suggest 34 PENNSCIENCE JOURNAL | SPRING 2014

that the potential inhibition of VEGF-A expression by miRNAs up-regulated in the SL phenotype may suppress a cell survival pathway and therefore contribute to a disruption of PFC function which underlies the susceptible phenotype. Again, Figure 5 depicts a network of gene targets of SL>LL miRNAs in the PFC with custom RT-PCR data overlaid. It is interesting to note that, beyond the significant down-regulation of VEGF-A, general down-regulation is also observable for many glutamate receptors. Though this down-regulation is not statistically significant, it may be worth noting since downregulation of other types of glutamate receptors in the rodent PFC due to repeated stress has been identified in a previous study. This study also found an association between cognitive deficits and loss of glutamate receptors in the PFC due to repeated stress20. The general down-regulation of glutamate receptors found in the PFC of SL rats may therefore reflect cognitive deficits which contribute to a phenotype of stress susceptibility. This study has demonstrated that differential expression of miRNAs can not only be used to potentially develop a panel of blood-based biomarkers which can identify an individual who is susceptible to social stress but can also serve to explain how a phenotype of stress susceptibility might develop through potential miRNA-mediated changes to the structure of the PFC. However, more research is needed to further develop biomarkers of stress susceptibility or resilience as well as to experimentally verify whether or not the SL>LL miRNAs identified in this study do in fact exert a direct regulatory effect on their predicted targets which causally results in downstream modifications of PFC cytoarchitecture. Furthermore, it would be enlightening to repeat this study with the added step of taking blood samples from rats before any stress exposure in addition to taking blood samples after completion of the paradigm. This would allow for the disentanglement of the effects of defeat and the effects of underlying genetic predispositions on the biological signatures accompanying stress susceptibility. Such research may help complete the inchoate picture of the role of miRNAs and the PFC in the stress response as well as lead to novel diagnostic and therapeutic approaches to stress-induced psychopathologies.

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3. Yehuda, R., Flory, J. D., Southwick, S., and Charney, D. S. (2006). Developing an agenda for translational studies of resilience and vulnerability following trauma exposure. Annals of the New York Academy of Sciences, 1071, 379-96.

14. Smalheiser, N. R., Lugli, G., Rizavi, H. S., Torvik, V. I., Turecki, G., and Dwivedi, Y. (2012). MicroRNA expression is down-regulated and reorganized in prefrontal cortex of depressed suicide subjects. PLoS ONE, 7(3), e33201. doi: 10.1371/journal. pone.0033201.

4. Bear, M. F., Connors, B. W., and Paradiso, M. A. (2007). Neuroscience: Exploring the Brain, 3rd ed. Philadelphia: Lippincott Williams & Wilkins. 5. Wood, S. K., Walker, H. E., Valentino, R. J., and Bhatnagar, S. (2010). Individual Differences in Reactivity to Social Stress Predict Susceptibility and Resilience to a Depressive Phenotype: Role of Corticotropin-Releasing Factor. Neuroendocrinology, 151(4), 1795-1805 6. Holmes, A. and Wellman, C. L. (2009). Stress-induced prefrontal reorganization and executive dysfunction in rodents. Neuroscience and Biobehavioral Reviews, 33, 773-783. 7. Arnsten, A. F. T. Stress signaling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience, 10, 410-22. 8. Brake, W. G. Flores, G., Francis, D., Meaney, M. J., Srivastava, L. K., and Gratton, A. (2000). Enhanced nucleus accumbens dopamine and plasma corticosterone stress responses in adult rats with neonatal excitotoxic lesions to the medial prefrontal cortex. Neuroscience, 96(4), 687-95. 9. Diorio, D., Viau, V., and Meaney, M. J. (1993). The role of medial prefrontal cortex (cingulate gyrus) in the regulation of hypothalamic-pituitary adrenal responses to stress. The Journal of Neuroscience, 13(9), 3839-47. 10. Figueiredo, H. F., Bruestle, A., Bodie, B., Dolgas, C. M., and Herman, J. P. (2003). The medial prefrontal cortex differentially regulated stress-induced cfos expression in the forebrain depending on type of stressor. European Journal of Neuroscience, 18, 2357-64. 11. Ebert, M. S. and Sharp, P. A. (2012). Roles for MicroRNAs in Conferring Robustness to Biological Processes. Cell, 149, 515-521. 12. McNeill, E. and Van Vactor, D. (2012). MicroRNAs shape the neuronal landscape. Neuron, 75, 363-79. 13. Hunsberger, J. G., Austin, D. R., Chen, G., and Manji, H. K. (2009). MicroRNAs in mental health:

15. Mouillet-Richard, S., Baudry, A., Launay, J., and Kellermann, O. (2012). MicroRNAs and depression. Neurobiology of Disease. doi: 10.1016/j. nbd.2011.12.035. 16. Lai, C-Y, Yu, S-L, Hsieh, M. H., Chen, C-H, Chen, H-Y, Wen, C-C, ‌ Chen, W. J. (2011). MicroRNA Expression Aberration as Potential Peripheral Blood Biomarkers for Schizophrenia. PLoS ONE, 6(4). doi: 10.1371/journal.pone.0021635. 17. Schipper, H. M., Maes, O. C., Chertkow, H. M., and Wang, E. (2007). MicroRNA expression in Alzheimer blood mononuclear cells. Gene Regulation and Systems Biology, 1, 263-74. 18. Raab, S. and Plate, K. (2007). Different networks, common growth factors: Shared growth factors and receptors of the vascular and the nervous system. Acta Neuropathologica, 113, 607-26. 19. Sathasivam, S. (2008). VEGF and ALS. Neuroscience Research, 62, 71-7. 20. Yuen, E. Y., Wei, J., Liu, W., Zhong, P., Li, X., and Yan, Z. (2012). Repeated stress causes cognitive impairment by suppressing glutamate receptor expression and function in prefrontal cortex. Neuron, 73, 962-77.

Acknowledgements Dr. Seema Bhatnagar served as the research sponsor for this study and her advice and guidance throughout the research process has been greatly appreciated. Abhishek Sengupta was instrumental in providing advice and guidance as well as providing instruction on how to perform basic laboratory techniques (from handling a pipet to carrying out RT-PCR). Sandra Luz assisted this study by generously providing punches of the PFCs of rats who had undergone a 7 day defeat paradigm (identical to the one described in the methods section) for western blot analysis. Geralyn Kelly offered some greatly appreciated instruction and assistance in performing western blot experiments. Dr. Willem Heydendael also provided advice and guidance throughout the process. This study was funded with the following grant: DARPA 58077 LSDRP to SB.

SPRING 2014 | PENNSCIENCE JOURNAL 35


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