2019 CCIB Annual Retreat

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Thursday, December 12, 2019
9:00 a.m. – 5:00 p.m.
JOINT HEALTH SCIENCE CENTER

(201 S. Broadway, Camden, NJ 08103)

5:30 P.M. – 9:30 P.M.
Dinner & After Hours Event
Spirit of Philadelphia Cruise “Freedom Elite”

2019 CCIB RETREAT – ITINERARY

9:00am	Breakfast

9:30am	Welcome
	Chancellor, Rutgers-Camden – Dr. Phoebe Haddon
	Dean of the Faculty of Arts and Sciences–Camden, Dr. Howard Marchitello
	Director, CCIB – Dr. Nir Yakoby
(Abstracts for all speakers can be found below)
10:00am	Keynote Speaker: Dr. Michael Lawrence Klein Dean, College of Science & Technology and Laura H. Carnell Professor of Science, Temple University Title: Nature’s Exquisite Sensing Machines: Unveiling the Molecular Mechanism of Pain Sensation

11:00am	BREAK

11:15am	Speaker: Dr. Xingyun Qi, Assistant Professor, Department of Biology, Rutgers-Camden Title: “How much salt water should I drink?” Reading the minds of plants

11:45am	Speaker: Dr. Guillaume Lamoureux, Associate Professor, Department of Chemistry, Rutgers-Camden Title: End-to-end learning of biomolecular interactions

12:15pm	Poster Session & Lunch provided by CCIB

1:45pm	Speaker: Dr. Joseph V. Martin, Professor, Department of Biology, Rutgers-Camden Title: Thyronamines, Novel Thyroid Hormone Derivatives in Rodent Adrenal Gland and Brain

2:15pm	Speaker: Dr. Jean-Pierre Issa, MD, Chief Executive Officer, Coriell Institute for Medical Research Title: Epigenetic Stem Cell Aging and Cancer Susceptibility

2:45pm	Speaker: Dr. Robert Margolskee, Director and President, Monell Chemical Senses Center, Philadelphia Title: Multiple sweet taste signaling pathways in taste cells

3:15pm	BREAK

3:30pm	Speaker: CCIB Best Student Paper 2018 – Nathaniel Merrill Title: Linear-in-flux-expressions modeling of Tuberculosis Metabolic Networks.

3:45pm	Speaker: Dr. Nathan Fried, Assistant Professor, Department of Biology Title: “The Behavioral Ethology of Sleep & Pain.”

4:15pm	Speaker: Dr. Tom Joseph, Assistant Professor of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania Title: Anesthetic binding to ryanodine receptor 1

4:45pm	Closing Remarks & Annual Retreat Group Photo

5:30pm	Dinner & After Hours Social Event aboard the Freedom Elite

2019 CCIB RETREAT – SPEAKER ABSTRACTS

KEYNOTE SPEAKER – Dr. Michael Lawrence Klein, Dean, College of Science & Technology and Laura H. Carnell Professor of Science, Temple University

Title: Nature’s Exquisite Sensing Machines: Unveiling the Molecular Mechanism of Pain Sensation

Abstract: Everyday experience tells us that water will not “wet” an oily surface. For example, when rain falls on a car that has been recently cleaned and waxed, the rainwater forms droplets and does not wet the surface as a continuous film. This talk will explore the microscopic manifestations of this phenomenon as it applies to naturally occurring and engineered surfaces, comprised of molecules. Of particular interest are so-called ion channels that are Nature’s way of allowing communication between the inside and outside of the cell. Ion channels live in the lipid bilayer membrane that is the main constituent of the cell wall. Typically, ion channels consist of a bundle of a few proteins organized around a central pore, through which ions such as sodium and potassium, either enter or leave the cell.

Membrane-bound ion channels often have a common structural motif, consisting of the central pore, plus so-called peripheral sensor domains that control opening and/or closing (gating) of the pore to allow passage of ions into or out of the cell. The latter, in turn, provide the control mechanisms for many physiological functions.

The overall architecture of sodium and potassium ion channels, is shared with other ion channels, such as the so-called transient receptor potential (TRP) family of sensory channels. Structural studies on ion channels over the past few years have yielded clues into the possible operational mechanisms of Nature’s nanomachines, including members of the TRP family.

After a general discussion on the phenomenon of wetting and dewetting, this presentation will focus on one specific ion channel, the so-called capsaicin or vanilloid receptor, TRPV1, which promotes the passage of ions across cellular membranes in response to stimuli such as acidity and hotness.

Importantly, the molecular underpinnings of TRPV1 gating, in particular the mechanism, is still unclear. Here, large-scale molecular dynamics simulations have been employed in an attempt to shed light on the closed to open gating transition of TRPV1. Seemingly, gating relies on the motion of a single, evolutionarily conserved, amino acid in the region of the pore domain. A model for TRPV1 gating is proposed, based on the molecular simulations.

Dr. Xingyun Qi – CCIB, Department of Biology, Rutgers-Camden

Title: “How much salt water should I drink?” Reading the minds of plants

Abstract: Salinity is one of the major environmental threats that endangers crop productivity worldwide. Its toxicity originates from the uptake and fast distribution of NaCl in plant bodies. Stomata, micro-pores on plant aerial surfaces, play critical roles in transpiration and thus in NaCl delivery from roots to the whole plant body. However, the exact mechanism of how salinity regulates stomatal development remains elusive. Our results indicate that the number of stomata on leaf surface is greatly reduced upon salinity stress. We thus hypothesize that regulation on stomatal formation is one strategy plants employ to tolerate and survive salinity. Focusing on the core pathway of stomatal formation in the model plant Arabidopsis thaliana, we investigate the mechanisms of how salinity signal impinges on gene regulatory networks during stomatal development. In parallel, we will compare the salinity-tolerant model plant Thellungiella salsuginea with Arabidopsis thaliana to explore new molecular players involved in salinity regulation on stomatal formation. Understanding the contribution of stomata in plant salinity tolerance will provide insight into sustainable agriculture in marginal land to feed the increasing world population.

Dr. Guillaume Lamoureux – CCIB, Department of Chemistry, Rutgers-Camden

Title: End-to-end learning of biomolecular interactions

Abstract: To understand the molecular details of any biological process, one inevitably has to know the three-dimensional structure of a large number of protein-ligand and protein-protein complexes. Experimental approaches to this problem are unlikely to scale up, and there is a constant need for innovation in computational methods.

In this talk, I will present our recent efforts at developing unified “sequence-to-structure-to-function” models based on deep neural networks. Following an end-to-end learning approach, the models aim to discover the molecular representations most useful for the combined tasks of predicting function from structure and structure from sequence. While our current interests are in the prediction of protein structure and of protein-protein interactions, the models rely on raw atomic densities and are therefore generalizable to any biomolecule.

Dr. Joseph V. Martin – CCIB, Department of Biology, Rutgers-Camden

Title: Thyronamines, Novel Thyroid Hormone Derivatives in Rodent Adrenal Gland and Brain

Abstract: Thyroid hormones are examples of aromatic amino acids. As first emphasized by our collaborator Mary Dratman, all other aromatic amino acids (e.g., tyrosine and tryptophan) are decarboxylated as part of synthetic pathways for neurotransmitters such as dopamine and serotonin. Our collaboration is engaged in the investigation of a family of decarboxylated thyroid hormone metabolites, the thyronamines (TAMs). Previously, two TAMs, 3 iodothyronamine (3T1AM) and the less potent, fully deiodinated, thyronamine (T0AM), have been isolated from brain and studied over the past ten years. In contrast to the signs of hyperthyroidism, administration of these compounds to rats causes decreases in body temperature and heart rate.

However, our new studies using QTOF mass spectrometry have now identified 13 novel TAMs (along with 3T1AM and T0AM) in adrenal medulla. Furthermore, classical preparations of nerve terminals (synaptosomes) from rat brain also contain the new compounds. Additionally, the TAMs are released by depolarization of synaptosomes with isotonic solutions containing high levels of potassium ions, in the same way as neurotransmitters are. The novel TAMs were synthesized by our collaborator David Augeri and effects on body temperature and heart rate measured. Several of the compounds caused rapid effects on body temperature and heart rate. These results contribute importantly to characterization of TAMs as neurotransmitters.

Dr. Jean-Pierre Issa, MD, PhD – President and Chief Executive Officer, Coriell Institute for Medical Research

Title: Epigenetic Stem Cell Aging and Cancer Susceptibility

Abstract: DNA methylation affects gene expression and genome stability in complex ways depending on the location of the CpG site in question. In humans, methylation patterns are highly regulated and generally conserved between different individuals with R²>0.98 when comparing promoter DNA methylation genome wide among unrelated individuals of similar age. Despite this high degree of regulation, there are quantitative differences in methylation between individuals as well as evidence of methylation drift (increase at some loci, decrease at other loci) associated with aging in mammals. There is also a large degree of methylation drift in cancer cells (compared to normal tissues in the same individual) and a smaller but significant drift in other diseases such as atherosclerosis and neuro-degeneration.

Genome wide methylation drift is associated with age in multiple species (humans, mice, monkeys) and correlates with a given species’ maximal lifespan. Within a species, epigenetic drift is tissue specific and affects up to a quarter of the methylome. The potential consequences of drift are twofold. First, it can induce epigenetic diversity within a tissue, and this can serve as fodder for Darwinian selection to promote the development of proliferative diseases such as cancer and atherosclerosis. Second, given that some genes are affected more prominently due to genomic structural features, enough cells are affected in older tissues to potentially change gene expression and tissue function.

The causes and determinants of age-related methylation drift remain incompletely understood. There are diverse observations suggesting that the rate of drift can be modified by diet, chronic inflammation and exposures. Some of the outstanding questions in the field include the possibilities that methylation drift is modified by germline polymorphisms that influence DNA methylation genome wide, by prenatal exposures including diet and environmental toxins, and by lifestyle factors (including diet, exposures and exercise) that affect low level inflammation systemically. More broadly, epigenetic drift appears to be a stem cell phenomenon, may cause age-associated stem cell dysfunction, and is consistent with aging hypotheses that postulate that stem cell exhaustion is a major factor in physiologic and pathologic age. Causally, there are strong data that DNA methylation drift is strictly linked to stem cell proliferation, suggesting that it is largely a case of replication errors in methylation maintenance. Finally, the model whereby methylation drift enables Darwinian selection at the tissue level implies the possibility of preventing age-related development of pre-neoplasia and treating established neoplasia through interventions targeting epigenetic processes.

Dr. Robert Margolskee – Director and President, Monell Chemical Senses Center, Philadelphia

Title: Multiple sweet taste signaling pathways in taste cells

Abstract: Sweet taste cells express two signalling pathways for sweet compounds. The primary sweet sensor for sugars and non-caloric sweeteners is the combination of type 1 taste receptors 2 and 3 (T1R2+T1R3). This heteromeric receptor has multiple ligand binding sites enabling it to respond to many different types of sweet compounds. Activation of T1R2+T1R3 by a sugar or a non-caloric sweetener initiates a signal transduction cascade involving gustducin, phospholipase C beta-2, Ca²⁺ release and Ca²⁺-activation of the TrpM5 ion channel, ultimately leading to depolarization of the cell. However, in the absence of T1R2+T1R3 (e.g., in TAS1R3 knockout mice), animals still respond to sugars, demonstrating the presence of a T1R-independent pathway. This second pathway uses glucose transporters and sodium glucose cotransporter-1 along with the ATP-gated K⁺ channel (a metabolic sensor). This T1R-independent sugar-specific sweet pathway functions similarly to how the pancreas detects and responds to glucose based on its ability to generate ATP. We have found also that sweet taste cells express multiple disaccharide-hydrolyzing enzymes previously known to occur only in the intestine’s “brush border.” This enables sweet-responding taste cells to detect disaccharide sugars by the second (“metabolic”) pathway. Together with salivary amylase, these taste cell-expressed enzymes may locally break down dietary disaccharides and starch hydrolysis products into monosaccharides that could serve as substrates for the T1R-independent sugar sensing pathway. An important implication is that sugars can activate both sweet pathways, while non-caloric sweeteners can only activate the T1R2+T1R3 pathway. This may explain difficulties in using non-caloric sweeteners to replicate the sensory properties of sugars. Key open questions are if the two pathways encode different information, whether there is cross-talk between them, and how each pathway affects physiological responses.

Mr. Nathaniel Merrill – CCIB Ph.D. Student, Rutgers-Camden

Recipient of the 2018 CCIB Best Paper Award

Title: Linear-in-flux-expressions modeling of Tuberculosis Metabolic Networks.

Abstract: The Mycobacterium tuberculosis (briefly MTB) has infected thirty percent of the world’s population according to the World Health Organization(WHO). In 1993 the WHO declared tuberculosis (brifely TB) a global emergency. The bacterium is known to endure hostile environments within the host organism through two main factors 1. a genetically diverse sub-populations and 2. a sophisticated gene regulatory network that effectively switches the state of its metabolism. In this approach, we extend systems biology tools such as Linear-in-flux-expressions to design advanced models for drug action on complex networks. Using MTB gene microarray data as well as pathway information from the KEGG database we develop a metabolic model to detail the synergistic and antagonistic effects of different drug combinations.

Dr. Nathan Fried – Department of Biology, Rutgers-Camden

Title: “The Behavioral Ethology of Sleep & Pain.”

Abstract: Rodents are the main model systems for pain research, but determining their pain state is challenging. To develop an objective method to assess pain sensation in mice, we adopt high-speed videography to capture sub-second behavioral features following hind paw stimulation with both noxious and innocuous stimuli and identify several differentiating parameters indicating the affective and reflexive aspects of nociception. Using statistical modeling and machine learning, we integrate these parameters into a single index and create a “mouse pain scale,” which allows us to assess pain sensation in a graded manner for each withdrawal. We demonstrate the utility of this method by determining sensations triggered by three different von Frey hairs and optogenetic activation of two different nociceptor populations. We extend this methodology to drosophila to explore the effects of sleep deprivation on pain sensation. Our behavior-based “pain scale” approach will help improve the rigor and reproducibility of using withdrawal reflex assays to assess pain sensation in mice.

Dr. Thomas T. Joseph, MD, Ph.D. – Assistant Professor of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania

Title: Anesthetic binding to ryanodine receptor 1

Abstract: Ryanodine receptor 1 (RyR1) is a calcium channel whose dysfunction is implicated in malignant hyperthermia, a hypermetabolic disease state afflicting patients under anesthesia. It is posited that triggering anesthetic agents bind to mutant RyR1 or its binding partners, biasing the channel to the open state, causing uncontrolled calcium release from the sarcoplasmic reticulum and a resultant overwhelming metabolic load. Using molecular dynamics studies in collaboration with experimentalists, we identify anesthetic binding sites on this protein. Ligand binding affinities are predicted using alchemical free energy perturbation.

2019 CCIB RETREAT – POSTER ABSTRACTS

Zheming An

Title: Developing a Systems Approach to Forensic DNA Validation

Abstract: Statistical evidence and probabilistic reasoning play an important and increasing role in criminal investigations, prosecutions, and trials. Our work aims to develop an integrated “systems-level” approach to help assess the probative value of DNA evidence and standardize the validation process of forensic evidence. We collectively study the previous protocols reported by the forensic laboratory and propose a pipeline with relevant equipment and software. We perform a set of experiments and simulate the validation processes. Then we implement the statistical methods to improve the efficacy and reliability of the procedure. Our findings help to improve routine criminal investigations and prosecutions.

Kaitlin Bassi

Title: The Protein Blobulator

Abstract: Intrinsically Disordered Regions (IDRs) of proteins lack a fixed structure, and it is challenging to predict their ensemble and functional effects when amino acid substitutions occur. Many of these substitutions in IDRs are associated with neurodegenerative diseases such as Alzheimer’s and Parkinson’s Disease. Substitutions can have effects on net charge and hydropathy and influence long-range interactions that affect tertiary structure, especially in stretches of four hydrophobic residues or more. An interactive web tool was developed to provide a Blobulation of any given protein sequence. This Blobulation approach provides a framework for demonstrating how different subdomains of IDRs have distinct physical properties from each other, and how these distinctions can have a functional effect.

Heather Ciallella

Title: Deep Learning Modeling of the Estrogen Receptor Adverse Outcome Pathway

Abstract: Traditional computational models for chemical toxicity evaluations often perform as “black boxes,” which provide toxicity predictions without clear mechanistic interpretations. In this study, we use a well-studied set of EPA Toxicity Forecaster (ToxCast) in vitro bioassays for estrogen receptor agonist activity to explore the potential for biologically interpretable neural networks based on the concept of the adverse outcome pathway. It is expected that the resulting neural networks will take advantage of their inherent hierarchical structure to mimic the nature of complex biological systems and the combined effects of in vitro assays testing for events at increasing levels of biological organization on the resulting in vivo adverse outcomes.

Katrina Dewitt

Title: Community Assembly and Trait Distribution Across Spatial Scales

Abstract: Functional trait variation among individuals in a community has become a fundamental component to understand how ecological communities are structured and function. Functional traits are morphological, biochemical, phenological, physiological and behavioral characteristics measured at an individual level, which play fundamental roles in an organism’s performance. These traits respond to varying environmental conditions and also determine the influence that organisms have on ecosystem function. Among these functional traits, the elemental composition of living organisms (i.e., carbon, nitrogen, and phosphorus) relates and responds to its environment, playing fundamental roles in shaping community structure and biogeochemical processes. Despite these main ecological roles, organismal stoichiometry has rarely been analyzed from a functional trait approach. The aim of this study is to assess the stoichiometric trait distribution and diversity of aquatic macroinvertebrates across spatial scales, from local to regional. To do this, we will use the aquatic communities inhabiting pitcher plants (Sarracenia purpurea), which are widely distributed across North America, and represent an ideal model to study community structure across spatial gradients. Here we will assess variation in stoichiometric traits across two hierarchical ecological scales: (i) local: between pitcher plants within a bog; and (ii) regional: among bogs within a region (NJ). Specifically, we will address the following two questions: (1) what is the range of trait variation across spatial scales and (2) to what extent does the functional trait structure of different communities change along with environmental conditions? This study can help understand how organismal traits and the assembly of communities may respond to environmental changes and affect the structure and functioning of ecological communities.

Nick Gattone

Title: The role of tRNA-derived fragments (tRFs) in patterning epithelial cells

Abstract: Many species of non-coding RNAs act as regulators of tissue development through post-transcriptional modification of mRNA. tRNA-derived fragments (tRFs) are a recently discovered group of small non-coding RNAs that seem to perform this function. We hypothesize tRFs have a role in the development of animal tissues. CRISPR/Cas9 was used to delete the tRNA gene Val-CAC-1-1, which encodes for a tRF computationally predicted to target sprouty (sty), a crucial regulator of the EGFR pathway. Increased sty would result in reduced EGFR signaling. If this is the case, our model system, the Drosophila eggshell should display morphological changes. Although eggs do have different morphologies, subsequent qPCR analysis revealed this is not a result of the EGFR pathway, but of the tRF’s modulation of Icarus, a gene involved in the JNK signaling pathway. RNA-seq data was also obtained to see transcriptome-wide effects of the tRF deletion.

Lingyu Guan

Title: Targeting modes of tRNA fragments loaded to Argonaute

Abstract: Transfer RNA fragments (tRFs) are a class of small RNA molecules derived from mature or precursor tRNAs. Although characterized very recently, tRFs have been gradually attracting more attention. They are found across a wide range of organisms and tissues in cytoplasmic compartments or loaded to RISC complexes, often in numbers comparable to microRNAs. We analyzed sequences of chimeras formed in vivo between Argonaute-loaded tRFs and their targets, corresponding to various gene types, in addition to protein-coding transcripts. In the latter, 3′ UTRs were the likely primary target regions, although we observed interactions of tRFs with coding sequences and 5′ UTRs. We also report a novel phenomenon – a large number of putative interactions between tRFs and introns, compatible with the role of Argonaute in the nucleus. We clustered tRF binding patterns and identified enriched motifs that may be responsible for tRF-target interactions. Such interaction sites appear to be primarily located on the 5’ end of a tRF, often involving additional binding of the 3’ nucleotides of guide tRFs, similar to microRNAs. Strikingly, our results match interaction sites detected in a recent experimental screen, confirming the validity of our approach to predict the sites and mechanisms of tRF/target interactions computationally.

James Kelley

Title: Interactive VCF parser for graphical display of structural variants

Abstract: A massive amount of whole genome sequencing (WGS) data exists due to next generation sequencing (NGS) with dramatically increased speed and low cost compared to classical Sanger sequencing. WGS data is typically analyzed to find variants and predict their effects. This process can be automated for single nucleotide variants (SNVs) and short indels. However, detection of copy number variants (CNVs) and structural variants (SVs) is difficult, and visual representation is helpful so that decisions on variant calls and variant classifications can be supported by manual inspection. Streamlining the process of such inspection is thus important.

Variant Call Format, or VCF (1), is a standard format for storing called variants. It is a human-readable format but a sheer volume of variants and somewhat cryptic evidence representation make variant inspection inconvenient and tedious. Here we present an interactive VCF parser (IVP) for graphical display of structural variants. IVP processes a file for an entire genome and produces data for GenomeNavigator (GN), a next-generation visualization tool for all variants. Data processing takes only a few hours and generates a few GB of data. Production of such data manually for visualization in Integrative Genomics Viewer (IGV) (2), the most popular software for visualization of variants, would be tedious work. Data for each variant can be rapidly accessed from a data table. Data can be filtered to only display variants that affect exons, or specific types of variants. GN separates reads into categories of that support a variant call, reads that do not, and reads with mates on different chromosomes, and can visualize SV-relevant offscreen mates of visible reads in separate windows. The speed and ease of data processing by IVP and convenient novel features of GN make these tools a good choice for visual inspection of structural variants in a genome.

Ravi Kumar

Title: Machine Learning Approach for Identification of True Variants

Abstract: Next-generation sequencing (NGS) technology produces massive amount of sequencing data. Many algorithms are developed for identification of each type of genome variants such as single nucleotide variant (SNVs), indels, structural variants (SVs), and copy number variants (CNVs). However, existing tools are often inaccurate and give high false positive’s rate. We present Genome Rearrangement OmniMapper (GROM) with machine learning approach applied, for identification of true variants. GROM is up to 72 times faster than commercially available tools for the same purpose, but outputs variants at billions of locations. Here, we propose a machine learning model (Random Forest Classifier) to filter true variants from GROM output.

Dheenadhayalan Kumarasamy

Title:

Abstract:

Anna Liang

Title: Thyronamine Analogues of Catecholamines in Adrenal Gland

Abstract: Thyroid hormones (THs) are compounds produced by the thyroid gland and are essential to the growth and development of organisms. Abnormalities in hormone levels can alter the body’s physiology, which can lead to diseases and disorders (e.g. hyperthyroidism and hypothyroidism). There are two active forms of THs, triiodothyronine (T3) and thyroxine (T4), and one inactive form, 3,3’,5-triiodothyronine (rT3). THs are amino acids which can be decarboxylated into metabolites known as thyronamines. Thyronamines are still relatively new compounds and not much is known yet about their roles in the body. So far, only two thyronamines, 3-iodothyronamine (3T1AM) and thyronamine (T0AM), have been studied and isolated from rodent brains. Previous work done by Dr. Mary B. Dratman has confirmed the localization of T3 in nerve terminals (synaptosomes). Since THs and catecholamines are derived from tyrosine and thyronamines are derived from thyroid hormones, it is feasible to propose that thyronamines may act like catecholamines. This can help explain some of the neurological effects associated with hyperthyroidism. The current study aims to: 1) to identify epinephrine and norepinephrine analogue thyronamines in the adrenal glands and synaptosomes, and 2) to observe the physiological effects (body temperature and motor activity) of thyronamines to find a compound that can induce a hyperthyroid-like state. Preliminary studies done by the Martin lab have identified additional seven dopamine-analogues thyronamines in the adrenal medulla and synaptosomes of Sprague Dawley rats using liquid chromatography-quandrupole time-of-flight mass spectrometry (LC-QTOF-MS) and Bruker Daltonics Data Analysis 4.3 software. We were not only able to identify the seven new thyronamines, T0AM, T1AM, T3 and T4, but we were able to identify three new norepinephrine-like thyronamines that were not previously known to be present: T2AM-N, T3AM-N and T4AM-N. In the physiological study, adult male mice (C57BL/10J) had a telemetry device (Mini Mitter E-Mitter) implanted to record core body temperature and motor activity using the Vital View program. Mice received intraperitoneal injections (IP) of a vehicle solution (0.9% NaCl + 0.001 N HCl) or a similar solution containing dissolved thyronamines. The results were normalized using Excel and then analyzed using GraphPad Prism. Most of the compounds caused hypothermia. However, we were able to identify a compound, 3’-T1AM-E, an epinephrine-like derivative that can induce a hyperthyroid-like state. Therefore, the thyronamines are novel compounds localized in adrenal glands and synaptosomes, with multiple physiological actions.

Stacy Love

Title: Understanding the morphological and thermal properties of cellulose-silk biocomposites with coagulant, hydrogen peroxide, as a function of ionic liquid type

Abstract: Ionic liquids are ideal solvents for the fabrication of a cellulose-silk blended polymer and may be classified as manufactured molten salts that can be designed to be environmentally benign. These useful solvents are liquids composed of ions that are fluid around or below 100 °C. Research of ionic liquids is booming due to their reusability and versatility in their dissolution capabilities, as well as their diversity in ionic combinations. The possibility for different binary ionic liquid types is on the order of at least 10^6, which creates various dissolution parameters, and thus suites the unique dissolution properties of large organic compounds such as cellulose and silk. Both cellulose and silk contain relatively strong intermolecular forces, such as hydrogen bonds, which hold their three-dimensional structures close together. Ionic liquids not only can break these intermolecular forces but can also maintain the molecular weights of the respective molecules. The characterization and analyzation of the physiochemical properties in a blended cellulose-silk polymer film as a function of solvent type are shown on this poster. Solvent types, 1-ethyl-3-methylimidazolium acetate (EMIMAc) and 1-ethyl-3-methylimidazolium chloride (EMIMCl) were used at 90% total mass volume in a blended 90% cellulose-10% silk system. The interpretation of these results conclude that by changing the solvent type in the fabrication process, a change in the thermal degradation and morphological properties of a blended biopolymer material will occur; further allowing for a fine-tuning of the physiochemical properties of a cellulose-silk blended material, and thus promoting different functionalities for unique applications within fields ranging from biomaterials, bio-electrics, tissue engineering and more.

Shannon Lynch

Title: City ant, Desert ant: Investigating the changing dynamics of ant-tree cholla mutualisms along an urbanization gradient in Albuquerque, NM

Abstract: Globally, habitats are becoming more stressful and less predictable. We have a poor understanding of how these changes in environmental conditions are influencing organisms living in modern ecosystems. Among different global change drivers, urbanization is perhaps the most multifaceted; organisms living in cities must simultaneously cope with fragmentation, urban heat islands, changing water dynamics, and pollution. The objective of this survey was to provide new insights of urban desert selective pressures and their effect on the ant-pant mutualism between Cylindropuntia imbricate, their ant-defenders and herbivorous arthropods. To examine this, last summer we performed a plant and arthropod survey along an urbanized gradient from Albuquerque (New Mexico) to the Sevilleta National Wildlife Refuge (New Mexico). We are still working on sorting field samples so all results presented here are preliminary. I found along this urbanization gradient that urban sites had higher variability of C. imbricata size in comparison to suburban and desert sites. Deserts had the highest average ant occurrence, with suburban and open space sites having similar averages. Narnia is one of the most common herbivorous arthropod we encountered. The average occurrence of Narnia was highest in the desert, with open space and suburban sites having similar averages. When taking all of this into consideration, it is likely urbanization if altering this mutualism. Understanding the interplay of urbanization, changes in vegetation, and herbivores is crucial for insights in land management and responsible future city planning and development. This is becoming ever more important due to increased urbanization throughout the world.

Sung Won Oh

Title: DNA-Mediated Proximity Assembly Circuit for Regulating Biochemical Reactions

Abstract: Smart nanodevices that integrate the molecular recognition and signal production hold great promise for the point-of-care diagnosis (POC) applications. Here, we developed nanodevice capable of sensing various bio-targets and reporting signals on an easy-to-read platform. The nanodevice combines the mechanisms of dynamic DNA nanostructures (sensing unit) with the proximity assembly of enzyme/cofactor system (assembly unit). Our effort centers on methods to control the conformational switch of nanodevices for recognizing targets and to trigger the subsequent assembly of enzyme/cofactor structures for producing and amplifying signals. Nanodevices have been demonstrated to detect various targets of nucleic acids and small-molecule metabolites with colorimetric or fluorescence signals. The DNA-mediated proximity assembly circuit can potentially be applied to engineer smart nanodevices for molecular diagnosis and be transferred to a paper-based POC tests.

Megan Rhone

Title: Responses of arthropod communities to an influx of woody debris in the NJ Pine Barrens

Abstract: Climate change is modifying weather patterns, including the frequency and intensity of storms. The ecological consequences of these storms have been studied but have been primarily related to warm weather storms such as hurricanes. During the winter of 2017-18, New Jersey experienced an increase in snow storms. These storms caused significant tree damage, mostly consisting of broken branches and limbs. For the NJ Pinelands, this produced an atypical environment. The increased fine woody debris (FWD) altered the forest floor, increasing its habitat complexity. I tested the hypothesis that a forest floor with increased FWD would result in increased ground dwelling arthropod abundance and diversity, with potential shifts in composition. I conducted a field experiment in the NJ Pinelands with plots that were treated with the addition or removal of FWD. Carnivore abundance was significantly influenced by the addition of FWD with a 62% increase. Carnivores also showed shifts in composition when FWD was added. Ant diversity increased 56% in addition plots and ant composition was significantly different in addition plots than in either control or removal plots. Changes in arthropod communities in the NJ Pinelands could lead to altered ecosystem services they provide in the NJ Pinelands including soil turnover, decomposition and seed dispersal. The results found in this study broadly implicates the effect of climate change on the NJ Pinelands Reserve.

Karleena Rybacki

Title: Intermolecular Interactions of Keratin/Cellulose Biocomposites Fabricated Using Ionic Liquids

Abstract: A biocomposite scaffold is a thin, sheet-like film made up of a protein and a polysaccharide. The biomaterials chosen, Keratin Azure and Avicel Cellulose, are biodegradable and innocuous to other biological entities. Keratin Azure is a fibrous, structural protein that has a flexible secondary structure that has tunable properties. The crystallinity of Avicel Cellulose can be tuned by the different formations of alpha helices and beta sheets within the protein structure. The biomaterials studied are insoluble in water and the use of an ionic liquid with a strong anion and cation group as the solvent, effectively breaks apart the hydrogen bonds which in turn effectively dissolves the biomaterials for regeneration. The regeneration of biocomposite scaffolds is a growing topic of interest in the science community; however, the intermolecular interactions are not completely understood. Understanding these interactions in relation to the physical, mechanical, morphological and thermal properties can lead to new and effective materials for the production of biocomposite scaffolds. The characterization tests used were: Fourier Transform Infrared Spectroscopy (FTIR), Thermal Gravimetric Analysis (TGA), and Scanning Electron Microscopy (SEM). By changing the fabrication method, understanding how the crystallinity of cellulose can be affected by the formation of alpha helices/beta sheets, and looking into the different hydrophobic and hydrophilic interactions in a biocomposite film can lead to advances in the medical research field including: tissue engineering, advances in natural based electrolyte batteries, and filtration of heavy metals in the environment.

Swati Sharma

Title: Predictive modeling for chemical developmental toxicity assessments

Abstract: Developmental toxicity is a critical health hazard that needs to be addressed in chemical risk assessments. Traditional animal testing for developmental toxicity evaluations is expensive and time consuming, and requires a large number of animals. Therefore, as an alternative method to animal models, computational modeling is a promising approach to quickly evaluate chemical toxicity. In this project, a large database consisting of 1365 chemicals with their developmental toxicity potentials was collected from various sources. The quantitative structure-activity relationship (QSAR) model was first developed and was evaluated by a five-fold cross validation of the training set and an external validation of a new test set. The predictivity of the resulting model was moderate and needs further improvement. To this goal, a large amount of bioassay data were collected from public domain and some assays were found to be useful to distinguish the compounds that were predicted incorrectly in the QSAR model. This extra biological data profile indicates a promising potential to construct an enhanced predictive model for development toxicity.

Liam Sharp

Title: Nicotinic acetylcholine receptors lipid preferences within complex quasi-native membranes

Abstract: The nicotinic acetylcholine receptor (nAChR) is a highly lipid-sensitive neurotransmitter receptor and pentameric ligand-gated ion channel. We previously used coarse-grained molecular dynamics (CG-MD) simulations to investigate boundary lipids of a single nAChR in model domain-forming membranes, with neutral head groups and symmetric leaflets. We observed that nAChRs partition into a liquid-disordered domain if such a domain exists, and also quantified specific boundary interactions with both cholesterol and polyunsaturated fatty acids. The simulated systems were distinct from native membranes in several critical ways: they did not include charged head-groups, asymmetric leaflets, multiple proteins, or the heteroacidic lipids that reduce domain formation. The current research focuses on overcoming these limitations by introducing multiple proteins into quasi-native membranes, including membranes based on rat synapses. We characterize the effects of increased membrane complexity on boundary lipid diversity, the role of leaflet asymmetry in determining boundary lipid asymmetry, and the role of head-group charge vs. chain unsaturation in determining affinity for the nAChR TMD. We find that the presence of domains reduces the concentration of nAChRs required for dimerization, but that formation of dimers and higher-order oligomers does not require domain formation. Finally, we investigate the effects of oligomerization on deformations of the surrounding membrane and associated lipid sorting.

Nidhi Sheth

Title: Developing Forensically Relevant Single-Cell Pipelines for Human Identification

Abstract: Assessing the degree of consistency between genetic profiles from suspects and profiles obtained from items of evidence is undertaken by probabilistic models that consider all possible genotype combinations making forensic interpretation an arduous task. The application of single-cell techniques, however, has the potential to fill the gap left by a traditional laboratory pipelines by de-convolving the cells at the front-end of processing. Though single-cell profiling could be a substantial boon to forensic identity testing it comes with its own challenges which must be overcome. For example, in order to develop reasonable models, distributions of allele drop-out, which can be described as the Pr( or the probability that the signal intensity, , is below the lower signal boundary, i.e. AT or analytical threshold, given DNA was extracted from at least one cell, must be characterized for each laboratory process.

The forensic analytical pipeline consists of, in general, extraction, amplification of forensically relevant microsatellites and electrophoresis to distinguish the fragments. Though a sensitive pipeline, it relies heavily on the efficient extraction and purification of DNA from the cell’s matrix. Thus, early work focused on examining the performance of four direct-to-PCR extraction methods: i) forensicGEM®(MicroGEM); ii) DEPArray™ LysePrep Kit (Menarini Biosystems); iii) Direct PCR Lysis Solution (Thermo Scientific); and iv) PicoPure^TM (Thermo Scientific). Specifically, 408 cells (i.e., 102 cells per extraction method) were vacuum-pipetted into 96-well microtiter plates and the DNA was extracted using said methods as per manufacture’s recommendations. The DNA was amplified for 30 cycles using the GlobalFiler® PCR Amplification kit (Thermo Scientific). Fragment separation and peak-detection were accomplished with a 3500 Genetic Analyzer (Life Technologies Corporation) (25-sec injection) and GeneMapper IDX v 1.4, respectively. Early analysis suggested the extraction chemistry did not impact downstream signal detection; thus, we implemented the direct-to-PCR PicoPure^TMmethodology for subsequent tests due to its compatibility with current pipelines.

Once the full laboratory process was finalized, an additional 556 single cells were analyzed to test if drop-out was cell-independent. We compared the experimental distributions of drop-out rates for each single-cell profile to the expected rates modeled with a binomial distribution with parameters N_Het, the number of expected heterozygote alleles and, Pr(D), the probability of drop-out across all samples. Early analysis demonstrates allele drop-out is cell dependent, suggesting full forensically relevant evaluations of single-cell profiles will require models that address this unique feature.

Christopher Sottolano

Title: Drosophila speciation through the evolution of TGF-alpha like ligand Gurken

Abstract: Normal animal development depends on combinations of interacting signaling pathways, which spatiotemporally regulate gene expression in specific domains of cells, leading to tissue differentiation. The Epidermal growth factor receptor (EGFR) is one such pathway necessary for determining cell fate. Drosophila oogenesis provides an excellent system to probe how activation of this pathway, by TGFα-like ligand Gurken (GRK), leads to morphological structures on the resulting eggshell. During this process, the oocyte is enveloped in a monolayer of follicular epithelial cells. EGFR signaling determines the anterior-posterior and dorsal-ventral axes of the developing oocyte, patterning the follicle cells, and leading to the formation of structures such as respiratory dorsal appendages, and in certain species, a lumen-like ridge along the dorsal side. Studies in the Yakoby lab have shown that GRK from species such as D. guttifera, a member of the Drosophila subgenus, is not capable of sufficiently activating the EGFR pathway when placed in D. melanogaster (D. mel), a member of the Sophophora subgenus. Conversely, other species such as D. willistoni and D. nebulosa can activate the receptor. Gurken from species known to activate EGFR in D. mel, was found to be correlated to the presence of a histidine-rich domain which is not present in the GRK of the Drosophila subgenus. Trans-genre genetic perturbation experiments and computational analysis were used to support the idea of incompatibility of Drosophila GRK with Sophophora EGFR, and examine whether activation of EGFR in the Sophophora is dependent on this His-rich domain. Replacement of GRK in D. mel with that of D. virilis, a member of the Drosophila subgenus, resulted in insufficient activation of EGFR. These results imply evolution of GRK across Drosophila subgenre, which would suggest adaptation of other proteins, such as EGFR, to accommodate for the change in the ligand.

Gabriele Stankeviciute

Title: Characterization of The Bacterial Sphingolipid Biosynthesis Pathway

Abstract: The gram-negative aquatic bacterium Caulobacter crescentus responds to phosphate limitation by synthesizing a novel hexosyl-hexuronosyl-ceramide glycosphingolipid (GSL-2). While ceramide-based GSLs are ubiquitous in eukaryotes, in bacteria they had been observed previously mainly in the Sphingomonadaceae family, where they act as a surrogate for the lack of outer-membrane lipopolysaccharides (LPS). Identifying how prevalent sphingolipids are in bacteria is challenging since the eukaryotic synthesis pathway appears to lack clear enzymatic homologues and these likely arose out of convergent evolution. Even though lipidomes of various bugs have been characterized, the lipid fingerprint of bacteria vary wildly when accounting for nutrient deprivation and other environmental stresses. So far we have identified four genes that are involved in ceramide synthesis and have developed a genome-scale screening method which could identify the prokaryotic ceramide synthase and desaturase genes.

Cody Stevens

Title: Evolution in cis-regulation of a posterior fate determinant.

Abstract: Understanding cis-regulatory modules (CRMs) and the transcriptional networks they act within is important for providing an insight into spatiotemporal genetic regulation. Moreover, characterization of these CRMs gives a window into the evolution of species diversity. The Drosophila gene midline (MID) has been shown to dictate a posterior fate in the developing oocyte. While functional activation and regulation of MID has previously been studied, the CRMs that control midline are less understood. Furthermore, Drosophila species that exhibit a morphological novelty on their eggshells, the dorsal ridge, the expression pattern of
MID is dynamical different than species lacking this structure. Here, we examine two midline CRMs in Drosophila melanogaster and two previously unknown CRMs in Drosophila nebulosa, a species which has a dorsal ridge. Using a sliding window approach of enhancer bashing, we propose regulatory sequences within the Drosophila melanogaster CRMs that govern spatiotemporal patterning of MID through development. Interestingly, in Drosophila nebulosa these similar genome geographical regions yield expression patterns reminiscent of the future dorsal ridge. We suggest the evolution of MID CRMs happened in cis, resulting in the generation of a morphological novelty. Comparative sequence analysis between species can be a useful approach to better understanding the evolution of organismal diversity.

Kristen Woods

Title: Untangling Direct and Domain-Mediated Interactions Between Nicotinic Acetylcholine Receptors in DHA-Rich Membranes

Abstract: At the neuromuscular junction (NMJ), the nicotinic acetylcholine receptor (nAChR) self-associates to give rise to rapid muscle movement. While lipid domains have maintained nAChR aggregates in vitro, their specific roles in nAChR clustering are currently unknown. In the present study, we carried out coarse-grained molecular dynamics simulations (CG-MD) of 1-4 nAChR molecules in two membrane environments: one mixture containing domain-forming, homoacidic lipids, and a second mixture consisting of heteroacidic lipids. Spontaneous dimerization of nAChRs was up to ten times more likely in domain-forming membranes; however, the effect was not significant in four-protein systems, suggesting that lipid domains are less critical to nAChR oligomerization when protein concentration is higher. With regard to lipid preferences, nAChRs consistently partitioned into liquid-disordered domains occupied by the omega-3 ([Formula: see text]-3) fatty acid, docosahexaenoic acid (DHA); enrichment of DHA boundary lipids increased with protein concentration, particularly in homoacidic membranes. This result suggests dimer formation blocks access of saturated chains and cholesterol, but not polyunsaturated chains, to boundary lipid sites.

Linlin Zhao

Title: Interpretable hybrid read-across for hepatotoxicity using in vitro assay and gene expression data

Abstract: Big data offer a novel alternative approach to evaluate hepatotoxicity potential for new and existing chemicals. In this study, we explored an in-house hepatotoxicity database by searching it against the big data pool and extracted various information including in vitro assays (PubChem), and NIH LINCS Program landmark gene expression signature data (L1000FWD). Hybrid read-across models were developed for predicting chemical hepatotoxicity by incorporating in vitro assays and gene expression signature data. The hybrid read-across models developed in this study were compared with the traditional read-across models. The in vitro assays and genes that are used to build the hybrid read-across models were investigated for revealing the mechanisms of hepatotoxic compounds. The results indicated that the integration of gene expression data and in vitro bioassay data strengthened the power of the traditional read-across model for hepatotoxicity prediction. This hybrid read-across strategy can be further applied to study other complicated chemical toxicity prediction.