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2018 CCIB Annual Retreat

Thursday, December 13, 2018
9:00 a.m. – 5:00 p.m.
Camden Nursing and Science Building

(530 Federal Street, Camden, NJ 08103)

5:00 p.m. – 6:00 p.m.
6 p.m. – 7 p.m.
The Amazing Escape Room

(2050 Springdale Rd Suite 200, Cherry Hill, New Jersey 08003)








Provost, Rutgers-Camden – Dr. Michael Palis


Associate Dean for Research, Rutgers-Camden, Dr. Howard Marchitello


Director, CCIB – Dr. Nir Yakoby

 (Abstracts for all speakers can be found below)


Speaker: Dr. Benedetto Piccoli

Title: Networks and measures to model biological systems



Speaker:  Lingyu Guan

Title: What can we learn from odd-shaped bacteria?







Keynote Speaker:  Dr. Monica Driscoll

Distinguished Professor of Molecular Biology & Biochemistry, School of Arts & Sciences, Rutgers, The State University of New Jersey

Title: Addressing the Complexities of Neurodegeneration and Aging, One Worm at a Time.



Poster Session & Lunch provided by CCIB



Speaker:  CCIB – Dr. David Salas de la Cruz

Title:  Understanding the ionic liquid and coagulant role in the formation of cellulose-silk biocomposites for battery and medical applications



Speaker:  CCIB Student – Sung Won Oh

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


Speaker:  CCIB – Dr. Julianne Griepenburg

Title:    Wavelength-specific, plasmonic nanoparticle mediated rupture of polymersomes using ultrafast, single-pulse irradiation






Speaker:  CCIB Best Student Paper 2017 – Ruchi Lohia

Title:   Conformational effects of a disease-associated hydrophobic-to-hydrophobic substitution and histidine protonation state located at the midpoint of the intrinsically disordered region of proBDNF



Speaker: CCIB – Dr. Sudha Moorthy

Title:    Dissecting Signaling Events during UPEC Pathogenesis



Speaker:  CCIB Student – Cody Stevens

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



Closing Remarks & Annual Retreat Group Photo


Dinner provided by CCIB



Leave for the CCIB Social Event – Amazing Escape Room


KEYNOTE SPEAKER – DR. MONICA DRISCOLL, Distinguished Professor of Molecular Biology and Biochemistry, School of Arts and Sciences, Rutgers, The State University of New Jersey

Title:  Addressing the Complexities of Neurodegeneration and Aging, One Worm at a Time 

Abstract:  Aging is an inescapable component of human biology. Age-associated decline in functionality and the striking rise in risk for diseases such as diabetes, cancer and Alzheimer’s disease that accompanies age, couple to create one of the most pressing medical, social and economic challenges of our time.

My lab uses a simple animal, the 959-celled transparent nematode C. elegans, to decipher molecular mechanisms of fundamental processes such as the biology of aging and longevity. A major focus of our work is on defining the conserved factors that promote healthy aging, conferring a long “healthspan”. I will discuss work that provided insight into: 1) how we should think about the aging problem, 2) genes and environmental factors that keep neurons and muscles healthier for extended periods of time; 3) how our work on aging led us to send aging-associated experiments to the International Space Station this week. I will attempt to give an overview of rationale for these approaches to aging biology and to summarize outcomes and their potential significance.


DR. BENEDETTO PICCOLI – CCIB Ph.D. Student, Rutgers-Camden

Title:   Networks and measures to model biological systems

Abstract:  We show how dynamical systems on graphs is a valuable tool to model large networks, such as metabolic ones. Then we turn the attention to measures: a mathematical tool generalizing functions, which is particularly fit to model multi-scale dynamics.


MS. LINGYU GUAN – CCIB Ph.D. Student, Rutgers-Camden

Title: Analysis of rRNA-derived fragments in human HEK293 cells

Abstract:  The development of the next-generation sequencing technologies allows the identification of previously escaped small RNAs (sRNAs). microRNAs (miRNAs) are the most well-studied sRNAs which have been reported to play essential post-transcriptional regulatory roles. Recent studies have expanded the spectrum of sRNAs with the discovery of fragments generated from longer RNA molecules such as transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs). In this study, we focused on rRNA-derived fragments (rRFs) which have been observed in different species, whereas rRFs in human is little known. Aiming to infer the potential biogenesis and functionality of rRFs, we analyzed the CLASH (Crosslinking, Ligation and Sequencing of Hybrids) dataset. This dataset provides the sequences of in vivo formed hybrids between sRNAs and their putative targets in HEK293 cells. We showed that rRFs were cleaved from rRNA molecules under specific mechanisms and they were not random by-products. Using algorithms including sliding 7-mer windows, motif findings and clustering, we found that typical miRNA-like 7-mer “seed” was absent for rRFs, suggesting a different mechanism from miRNAs that rRFs used to recognize and bind to their targets. Additionally, only a small portion of targets in the hybrids shared common motif sequences for rRFs to bind to. Instead we speculate that the overall nucleotide composition might affect the binding patterns of rRFs from the observation that Guanines were enriched in the base-paired regions of rRFs. Last, we related the origins of rRFs to the rRNAs evolution. We found significant depletion of rRFs in the large rRNA expansion segments particularly ES7 and ES27. We hypothesize that the biogenesis of rRFs might be an ancient mechanism in the evolutionary history.


DR. DAVID SALAS de la CRUZ – Department of Chemistry, Rutgers-Camden

Title:   Understanding the ionic liquid and coagulant role in the formation of cellulose-silk biocomposites for battery and medical applications

Abstract:  The study of protein-polysaccharide interactions in biocomposite materials carries implications for fields ranging from medicine to environmental science and materials science. These materials are extremely versatile as shown from a variety of biocomposites used by nature. However, to facilitate deployment of new biocomposite materials in modern technology, the development of new methodologies is required to tune the properties of these materials to suit specific technological demands. For examples, silk-based composites are currently being researched in the areas of bone marrow structures and water filtration. However, the morphological reasons of such success are not readily explained. Silk is a biomaterial showing potential in these areas but is a weak structural material. Cellulose, which is the most abundant biomaterial, can add structural support to silk enhancing the versatility of these materials. In this study, we combined experimental and theoretical modelling to analyze structural, mechanical, electrical and thermal properties of cellulose-silk biocomposites using various characterization equipment such as FT-IR, X-ray Scattering, TGA, DSC, EIS, AFM, and SEM. The main objective was to understand the material physicochemical properties as a function of three polar coagulation agents: water (H2O), ethanol (EtOH), and hydrogen peroxide (H2O2). The results showed that the solubility of the pure substance in the chosen ionic liquid can be used to modulate the amount of crystallinity of the biopolymer blend. This has profound effect on the material mechanical, electrical and thermal properties.


MS. SUNG WON OH – CCIB Ph.D. Student, Rutgers-Camden

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

Abstract:  Smart nanodevices that integrate molecular recognition and signal production hold great promise for the point-of-care (POC) diagnostic applications. Herein, the development of a DNA-mediated proximity assembly of biochemical reactions, which was capable of sensing various bio-targets and reporting easy-to-read signals is reported. The circuit was composed of a DNA hairpin-locked catalytic cofactor with inhibited activity. Specific molecular inputs can trigger a conformational switch of the DNA locks through the mechanisms of toehold displacement and aptamer switching, exposing an active cofactor. The subsequent assembly of an enzyme/cofactor pair actuated a reaction to produce colorimetric or fluorescence signals for detecting target molecules. The developed system could be potentially applied to smart biosensing in molecular diagnostics and POC tests.


DR. JULIANNE GRIEPENBURG – Department of Physics, Rutgers-Camden

Title:   Wavelength-specific, plasmonic nanoparticle mediated rupture of polymersomes using ultrafast, single-pulse irradiation

Abstract:   Polymersomes are robust vesicles that are self-assembled from amphiphilic diblock copolymers. They are of tremendous interest in the field of drug delivery due to their ability to stably encapsulate molecules within both the hydrophobic membrane and hydrophilic lumen of the vesicle. In this study, light-stimulated release of hydrophilic encapsulants has been achieved through the incorporation of plasmonic nanoparticles, facilitating disruption of the membrane upon ultrafast, single-pulse irradiation. Cargo release can be controlled ranging from complete vesicle rupture and instantaneous release, to membrane pore formation and effusion. Initial studies were performed on the micron-scale to facilitate single vesicle imaging, however, methods are currently underway to optimize the system in the nano regime for future applications in drug delivery.


MS. RUCHI LOHIA – CCIB Ph.D. Student, Rutgers-Camden

Recipient of the 2017 CCIB Best Paper Award

Title:   Conformational effects of a disease-associated hydrophobic-to-hydrophobic substitution and histidine protonation state located at the midpoint of the intrinsically disordered region of proBDNF

Abstract:   Val66Met substitution at the midpoint of the prodomain of precursor brain-derived neurotrophic factor (proBDNF) has been widely studied for its association with increased susceptibility to neuropsychiatric disorders including schizophrenia and unipolar depression. Previously, NMR studies demonstrated that the prodomain is disordered with different secondary structure preferences for V66 and M66 (Anastasia et al. 2013).

We carried out 128μs of molecular dynamics (MD) simulations with temperature replica exchange (64replicas, 2μs per replica) of the 90-residues BDNF prodomain with and without Val66Met substitution to investigate its conformational effects. We observe that Val66Met increases the formation of long helices and decreases the formation of long beta sheets structure around residue 66. Secondary structure coupling is found in V66 at residue 66 and 92. Differential secondary structure in V66 and M66 leads to different pairs of dominating salt bridges which introduces slight differences in radius of gyration of the two forms.

HIS65 is located in a negatively charged region of the prodomain sequence and can exist in protonated form. We further probe the effects of protonated HIS65 on the conformational ensemble of V66 and M66 with MD simulations (128μs). Consistent with the previous simulations we find that Val66Met increases the formation of long helices. Additionally, protonated histidine increases the formation of long helices and eliminates the beta structure tendency around residue 66 in both V66 and M66 forms.

These results indicate that the neutral substitution may exert its effects by critically adjusting the entropic cost of local secondary-structure elements, which, in turn, affects the conformational ensemble via differential salt bridging patterns. Additionally, histidine protonation acts as a conformational switch between helix and beta sheet structures for M66 forms.


DR. SUDHA MOORTHY – Department of Biology, Rutgers-Camden 

Title:   Dissecting Signaling Events during UPEC Pathogenesis

Abstract:  Pathogenesis involves a continuous interplay between the host and microbes and between microbes themselves. The first (and in fact, the most important!) step of a successful infection by invasive as well as non-invasive bacteria is adhesion to the host. This triggers off a cascade of gene expression in the bacteria and the host which will determine the outcome of the infective process. The bacteria engage a plethora of virulence and fitness factors (like toxins and iron acquisition proteins) to enable colonization; the host in turn engages its defences (immune system) to counteract the bacteria. Study of these signaling pathways helps understand the progression of pathogenesis as well as identify novel therapies. 

Urinary tract infections (UTIs) are some of the most common bacterial infections worldwide. UTIs can be caused by a variety of microbes but almost 75-95% of all urinary tract infections are caused by Uropathogenic Escherichia coli (UPEC). The risk of recurrence and the rise in multidrug resistant UPEC has made the study of host pathogen interactions during UPEC pathogenesis critical.

Upon adhesion to the host bladder cell surface, UPEC are internalized by the cell. Following entry, most UPEC cells face one of three fates: (i) they can be quickly returned back to the extracellular environment (ii) they can enter into a nonreplicating quiescent state, or (iii) they can multiply, forming large intracellular bacterial communities (IBCs). In this work, using the established cell culture based infection assay for UPEC, we have elucidated key steps in the signaling cascade that determines formation of IBCs vs reservoirs. Further, we show that mechanical properties of the environment such as the elasticity of the supporting matrix influence the fate of the internalized bacteria. 



MR. CODY STEVENS – CCIB Ph.D. Student, Rutgers-Camden

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.



Ms. Gabriele Stankeviciute – CCIB, Rutgers-Camden           

Title:  Stalk elongation in Caulobacter crescentus yields distinct peptidoglycan domains

Abstract:  The diversity of cell shapes across the bacterial kingdom reflects evolutionary pressures that have produced physiologically important morphologies. While efforts have been made to understand the regulation of some prototypical cell morphologies such as that of rod-shaped Escherichia coli, little is known about most cell shapes. For Caulobacter crescentus, polar stalk synthesis is tied to its dimorphic life cycle, and stalk elongation is regulated by phosphate availability. Based on the previous observation that C. crescentusstalks are lysozyme-resistant, we compared the composition of the peptidoglycan cell wall of stalks and cell bodies and identified key differences in peptidoglycan crosslinking. Cell-body peptidoglycan contained primarily DD-crosslinks between meso-diaminopimelic acid and D-alanine residues, whereas stalk peptidoglycan had more LD-transpeptidation (meso-diaminopimelic acid-meso-diaminopimelic acid), mediated by LdtD. We determined that ldtDis dispensable for stalk elongation; rather, stalk LD-transpeptidation reflects an aging process associated with low peptidoglycan turnover in the stalk. We also found that lysozyme resistance is a structural consequence of LD-crosslinking. Despite no obvious selection pressure for LD-crosslinking or lysozyme resistance in C. crescentus, the correlation between these two properties was maintained in other organisms, suggesting that DAP-DAP crosslinking may be a general mechanism for regulating bacterial sensitivity to lysozyme.


Ms. Kristen Woods – CCIB, Rutgers-Camden           


Abstract:   The nicotinic acetylcholine receptor (nAChR) is an excitatory neurotransmitter receptor that mediates muscle functioning by forming nAChR-associated, lattice networks. At the neuromuscular junction (NMJ), synaptic and intracellular proteins, notably Agrin, MusK, and rapsyn, ultimately stabilize these highly dense networks. Experimental evidence suggests that cholesterol-rich domains, known as lipid rafts, facilitate signaling among Agrin-Musk and rapsyn, and their presence is essential for healthy nAChR clustering. In spite of their importance, the structural and functional mechanisms of lipid domains are currently unknown. Alongside cholesterol, Docosahexaenoic acid omega-3 fatty acids (DHA-PUFAs) are prevalent at the NMJ, correlate with domain formation, and strongly promote neuronal health. In the present study, we computationally explored the role of DHA-PUFAs on nAChR clustering in the presence and absence of lipid domains. Within coarse-grained (CG) model membranes, nAChRs consistently partitioned into flexible, liquid-disordered domains; boundary lipids were rich in DHA-PUFAs regardless of the number of nAChR molecules, but preventing domain formation also reduced the likelihood of these acyl chains aggregating around nAChR. Taken together, our findings suggest that by inducing domain formation in membranes, DHA plays a critical role in the early stages of nAChR oligomerization.


Mr. Sean McQuade – CCIB, Rutgers-Camden           

Title:  Stability of Metabolic Networks via Linear-In-Flux-Expressions

Abstract:   This work addresses two main problems: 1. for fixed metabolite levels, find all fluxes for which the metabolite
levels are an equilibrium, and 2. for fixed fluxes, find all metabolite levels which are equilibria for the system.  We show that there is a structure of the graph necessary for the existence of equilibria. We use theory from various areas of mathematics, such as compartmental systems and Markov chains to analyze LIFE systems.


Mr. Christopher Sottolano – CCIB, Rutgers-Camden           

Title:   Drosophila nebulosa: a new system for genetic manipulations

Abstract:   Drosophila melanogaster (D. mel) has been groomed for over a century as a leading system to study a wide range of developmental processes through genetic perturbations.  At the same time, there are 1000s of other Drosophila species with fascinating differences in patterns and morphologies. However, these flies lack genetic tools to study the origin of evolutionary processes that caused the dramatic differences among closely related species. The recent development of the targeted genome editing technology by CRISPR/Cas9 system, is an opportunity to apply this tool to other species. We previously identified D. nebulosa (D. neb) as an attractive system to study the evolution of eggshell structures. In particular, its eggshell contains the lumen-like structure dorsal ridge, which is absent from D. mel eggshells. A correlation between the activation pattern of the epidermal growth factor receptor (EGFR) and dorsal ridge formation was found. This fly was also observed to have changes in bone morphogenetic protein signaling as well. Hence, we aim to establish the CRISPR/Cas9 tool in D. neb. A basic requirement for transgenics in D. mel is white-eyed flies that can be complemented and allow to screen for transgenic selectable markers, including red eyes. Using qPCR, we determined that, like in D. mel, the white gene resides on the X chromosome in D. neb. Using different combinations of guide RNAs and Cas9, we aimed to mutate the white gene in D. neb and insert the Cas9 into it. We successfully generated a white-eyed D. neb, which demonstrates that the CRISPR/Cas9 system is useful in this species. The genomes of the transgenic flies are currently analyzed for the mutation in the white gene and the insertion of Cas9. This fly will be used to study the process of dorsal ridge formation through perturbations in EGFR signaling.   


Ms. Sung Won Oh – CCIB, Rutgers-Camden           

Title: DNA-Mediated Proximity Assembly Circuit for Biochemical Sensing

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 a 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. The 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 be potentially applied to  engineer smart nanodevices for molecular diagnosis and be transferred to a paper-based POC tests.


Ms. Abby Robinson – CCIB, Rutgers-Camden           

Title:  Nanoparticle mediated release from polymersomes under single pulsed femtosecond irradiation

Abstract:   The self-assembly of amphiphilic diblock copolymers into polymeric vesicles, commonly known as polymersomes, is an area of high interest in research due to potential applications in the field of drug delivery. Polymersomes are fully synthetic robust vesicles, comprised of a hydrophobic membrane and a hydrophilic core, providing the ability for stable dual-encapsulation of a variety of molecules. Methods have been developed for triggered encapsulant release using ultrafast, single-pulse irradiation with visible and near infrared light to initiate spatial and temporal control of cargo release. We have shown that the incorporation of gold nanoparticles (AuNP) within the vesicle membrane provides wavelength specific vesicle rupture in response to 532 nm; the encapsulation of gold nanorods provides the ability to shift the polymersome response wavelength to the near-infrared. Initial studies were performed on micron size polymersomes to facilitate single vesicle imaging. However, this system must be scaled down the nanometer size regime for biomedical applications. Vesicles with diameters ranging from 80-200 nm have been deemed optimal for in-vivo drug delivery with prolonged blood circulation. We are concurrently working towards the development of  the nanoscale system, and in this process have discovered interesting properties pertaining to vesicle stability.


Mr. James Kelley – CCIB, Rutgers-Camden           

Title: Comparative Analysis of Variants Detected by GROM in Polar Bear and Brown Bear Genomes

Abstract:  Polar bears are one of many species facing the possibility of extinction in the near future;  however, their relatives, the brown bears, are thriving. We conducted a genomic comparison  using our GROM (3) algorithm to identify variants that could relate to the differences that  allow bears to survive in their respective environments. We detected 27 fixed structural  variants (SV) and roughly 250 indels that affect exonic regions of genes. Some of these  genes are related to phenotypic differences between the two types of bear such as fur color,  bone and facial structure, body size and weight, and circulating cholesterol level. Many  indels were found to be deleterious, while some occurred as pairs in the same gene,  restoring the reading frame. Our findings expand on the 2014 study (2) that only considered  the effects of single nucleotide polymorphisms (SNP).


Mr. Daniel Russo – CCIB, Rutgers-Camden           

Title: Extensive data-driven modeling of food-derived bioactive peptides that inhibit the angiotensin I-converting enzyme

Abstract:   Approximately a third of all adults over the age of 20 have high blood pressure, a precursor to a variety of heart and kidney diseases and a risk factor for heart attacks and strokes. In humans, blood pressure is regulated by the renin-angiotensin hormone system. The angiotensin I-converting enzyme (ACE), as a key component of this system, catalyzes the conversion of angiotensin I to angiotensin II which acts a signaling molecule to narrow blood vessels resulting in blood pressure increase. Compounds that inhibit ACE activity have successfully been developed as treatments for controlling blood pressure and rank among the most widely prescribed drugs on the market. Furthermore, small peptides from a variety of food origins such as milk, soy, or fish, have been delineated as ACE inhibitors. These food-originating ACE-inhibiting peptides have gained remarkable interest over the years due to their therapeutic potential, safe toxicity profile and little side effects. Unlike small molecules, there are no curated bioactivity data repositories for peptides, hindering further modeling studies. In this work, we present the results of a data-driven modeling study to investigate the ACE inhibition of small peptides. First, a large database of peptides with ACE inhibitions was compiled from a variety of sources. This database consisted of 4,529 peptide sequences with IC50 data for ACE inhibition and various lengths ranging from 2-50 amino acids. To our knowledge, this is the largest database characterization for ACE inhibiting peptides to date. These peptides were grouped by the number of residues and used as the basis for several quantitative structure-activity relationship model developments using a variety of machine learning algorithms combined with a variety of descriptors. Several models showed good correlation with the experimentally-derived activities through cross-validation (r2 > 0.5). Additionally, predictions of peptides, which were not included in the current database, showed cleared evidence for amino acid preference to strongly increase/decrease ACE-inhibitions, which varies based on peptide length. In summary, we show how data-driven informatics modeling studies can be an applicable method to perform peptide virtual screening to select new ACE-inhibiting peptides which have potentially therapeutic effects. 


Mr. Liam Sharp – CCIB, Rutgers-Camden           

Title: Boundary Lipids of the Nicotinic Acetylcholine Receptor in Quasi-Native Membranes

Abstract:   The nicotinic acetylcholine receptor (nAChR) is a neurotransmitter receptor and pentameric ligand gated ion channel (pLGIC) critical for signaling across synapses, including the neuromuscular junction. In reconstituted membranes, the nAChR function depends heavily on cholesterol, leading to the hypothesis that nAChR will partition into cholesterol-enriched liquid-ordered domains (“rafts”). Native nAChR membranes are rich in lipids with saturated fatty acid (like palmitic acid) or polyunsaturated fatty acid (PUFA) acyl chains (like docosahexaenoic acid (DHA)). Using coarse-grained molecular dynamics simulations (CG-MD) we characterized preferential lipid interactions and partitioning behavior of nAChR in binary membranes (cholesterol and lipids with two palmitic acid acyl chains) ternary membranes (cholesterol, a lipid with two palmitic acid acyl chains, and lipids with either two chains composed of the long-chain omega-3 PUFA docosahexaenoic acid (DHA) or of the omega-6 PUFA linoleic acid).

We quantify occupation of non-annular and annular regions by cholesterol and saturated and polyunsaturated lipids.  In the absence of PUFAs, cholesterol is enriched in the nAChR annulus in a concentration-dependent manner.  Cholesterol is also distributed throughout the non-annular (embedded) sites, while palmatic acyl chains persistently occupy only one interface between the beta and alpha subunits. When lipids containing long-chain PUFA acyl chains are introduced, they displace cholesterol from two additional interfaces. Contrary to expectations, in domain-forming membranes containing PUFAs, the nAChR is observed to consistently partition into PUFA-rich, cholesterol-poor domains. Saturated lipids with either phosphatidylcholine (PC) and phosphatidylethanolamine (PE) head groups are significantly depleted in such systems, although the extent of depletion is reduced for PE. While nAChR consistently partitions into the cholesterol poor domain, the alpha-gamma and delta-beta faces interact more than other faces with the cholesterol-rich domains. We extend this approach to more complex membranes of interest, including more realistic synaptic membranes and the Xenopus oocyte membranes used for electrophysiology.


Mr. Mark Nessel – CCIB, Rutgers-Camden           

Title:  Global body size scaling of elemental content in invertebrates and vertebrates

Abstract:   One of the primary determinants of organismal demands for energy and matter is body size. Ecological Stoichiometry Theory (EST) focuses on the balance of elements (i.e., matter) in living organisms and their environment, and attempts to understand the causes and consequences of stoichiometric variation among organisms and their environment. The growth rate hypothesis, central to EST, predicts that P and N content in small invertebrates should scale inversely with body size. In contrast, as vertebrates get larger they are required to invest more P into skeletons. Understanding how tissues rich in certain elements like lipids (Carbon rich), proteins (Nitrogen rich) and bones and scales (Phosphorus rich) scale with body size can also help us understand these trends. These universal elemental-body size relationships have been difficult to infer and remain contentious. Here we take a macroecological approach and ask if global-scale variation in organismal stoichiometry (C, N, P) of invertebrates and vertebrates is consistent with scaling relationships predicted from EST principles. Using a global database on animal elemental stoichiometry we ask: (i) Does nutrient content scale with body size as predicted by tissue scaling and EST principles? (ii) What is the role of phylogenetic relatedness on body size scaling relationships?


Ms. Heather Ciallella – CCIB, Rutgers-Camden           

Title:  Predictive Multitask Deep Learning Modeling of Estrogen Receptor Activities

Abstract:   Endocrine disruption is an important toxicity mechanism for many chemicals, especially those of environmental interest, such as pesticides. Traditional experimental testing, both in vitro and in vivo, to identify toxicants that can induce endocrine disruptions are expensive and time-consuming. Computational modelling is a promising alternative method for chemical toxicity evaluations. The rapid generation of data obtained from high-throughput screening (HTS) assays and computational power increase advanced the computational modelling into a big data era. New modelling approaches, such as deep learning, are being used for model development. This work features an extensive modeling study using classic machine learning algorithms, normal deep neural networks, and multitask deep neural networks for 18 ToxCast estrogen receptor (ER) binding assays. A random selection of 20% of all the compounds was used as a test set, with the remaining 80% compounds for model development. Chemical descriptors consisted of two binary fingerprints (FCFP6 and MACCS keys). Each descriptor set was combined with six traditional machine learning algorithms (AdaBoost Decision Tree, Bernoulli Naïve Bayes, k-Nearest Neighbors, Naïve Bayes, Random Forest, and Support Vector Machines), two deep learning approaches (normal deep neural networks and multitask deep neural networks) to develop models for all 18 ER endpoints. The resulting model performance was evaluated using the correct classification ratio (CCR), sensitivity, and specificity for the prediction of the test set. A consensus model was obtained by averaging predictions from all individual models. The results showed that individual models have predictivity accuracy (CCR) ranging from 0.5000 to 0.7716 and the consensus model has similar performance compared to the best individual model (multitask deep neural network) with an accuracy of 0.7565. We concluded that multitask deep neural network is a better algorithm to deal with large databases with mechanism-related toxicity endpoints (i.e., ER bindings). It is expected that this modelling strategy can be used for other computational toxicology modelling studies, especially for toxicity pathway modelling.


Mr. Zheming An – CCIB, Rutgers-Camden           

Title:  Stability of Human Circadian Rhythm

Abstract:   Circadian rhythms are widely found in living organisms including human beings. Circadian rhythm is an endogenously generated biological rhythm with a period about 24 hours. Organisms synchronize their circadian clock to the external signals such as the sunlight and temperature during the entrainment process. The two key characteristics of the typical circadian clock are its free-running period and phase of entrainment. Plenty of previous studies aimed at the relationship between the period and phase. A “simple rule” describes that an organism with a short period results a phase advance while an organism with a long period results a phase delay. Our model intended to explain a wider range of results beyond the rule. Also, we provided an analytical solution of the ordinary differential equation system which further described the range of entrainment. We investigated the stability of circadian rhythms across different timescales. The results can be applied to sleep disorders diagnostics as well as jet lag recovery.


Ms. Stacy Love – CCIB, Rutgers-Camden           

Title:  The effects of hydrogen peroxide on cellulose crystallinity

Abstract:   The study of protein-polysaccharide interactions in biocomposite materials carries implications for fields ranging from medicine to environmental science and materials science. These materials are extremely versatile as shown from a variety of biocomposites used by nature. However, to facilitate the deployment of new biocomposite materials in modern technology, the development of new methodologies is required to tune the properties of these materials to suit specific technological demands. For example, such protein-polysaccharide composites are currently being researched in the area of tissue scaffold engineering; however, the morphological bases of successful outcomes are not readily explained. Cellulose, which is the most abundant biomaterial worldwide, can add structural support to a protein, such as silk, enhancing the versatility of such materials. Given our past preliminary data, we suspected that hydrogen peroxide, as a coagulation agent, crystallizes the molecular structure of our biomaterial compared to both water and EtOH, creating a means for fine-tuning at the molecular level and thus adding more or less structural support. This poster presents data to further corroborate this claim, as well as to show hydrogen peroxide concentration effects on thermal and topological properties as well as to the secondary structures of the silk’s amide I and II region in a blended cellulose-silk based biomaterial. The main objective was to support the claim that hydrogen peroxide crystallizes the molecular structure of the biocomposite material and to determine if the effect was mainly on the cellulose compared to the silk composite of the material.


Mr. Joshua Waters – CCIB, Rutgers-Camden           

Title:  Fungal adaptation of carbon utilization through transcriptional rewiring

Abstract:   Structural changes in transcription factors, along with structural changes in cis-regulatory elements, can lead to novel gene expression patterns for transcription factors, or their target genes. These types of changes in gene regulation, known as transcriptional rewiring, can allow organisms to adapt to new environments. Genetic plasticity, has therefore allowed for the colonization of almost every environment on Earth, including nutrient poor environments. Understanding how gene regulatory networks evolve at the molecular level has therefore come to the forefront of evolutionary biology. Carbon metabolism, especially, has become a preferred system for studying transcriptional rewiring, due to the metabolic diversity observed in nature, and the importance of metabolic plasticity in adaptation to niche environments.

            The Xylan degradation regulator, xlr-1, is a conserved transcriptional regulator in Ascomycete fungi involved in secondary metabolism, regulating metabolism of plant cell walls. Though its presence is conserved in Ascomycetes, its role varies greatly across genera of fungi. In many fungal genera, xlr-1 orthologs work in concert with a cellulose degradation regulator to control both cellulose and hemicellulose metabolism; however, there are genera in which it solely governs the hemicellulose response, such as is observed in Neurospora crassa, or it acts as the main regulator of both cellulose and hemicellulose metabolism, as observed in Trichoderma reesei. These differences may be explained by transcriptional rewiring. Therefore, we aim to investigate transcriptional rewiring of the xylan degradation regulon in filamentous ascomycete fungi at the species and intra-species level. We will use a multi-Omics approach, combined with reciprocal allele-swaps to characterize transcriptional rewiring of the xylan degradation regulon at the species and intra-species level.


Mrs. Nicole Revaitis – CCIB, Rutgers-Camden           

Title:   Modeling the spatiotemporal dynamics of EGFR activation in the follicular epithelium

Abstract:   Organogenesis requires the coordination among multiple cell signaling pathways to develop tissues into functional organs. While the overall impact of ligands and their associated signaling pathways has been extensively studied, the mechanisms behind the distribution of ligands remains widely unknown.  Here, we develop a mathematical model to understand the variables that shape the distribution of the TGF-α like ligand, Gurken (GRK), during Drosophila oogenesis.  The GRK molecule binds to the epidermal growth factor receptor (EGFR) and subsequently activates the signaling pathway in the overlying follicle cells.  By monitoring EGFR activation through diphospho-ERK (dpERK), we can determine how genetic perturbations impact signaling and the consequent changes on the Drosophila eggshell. Our model focuses on the dynamic distributions of GRK and dpERK during mid-oogenesis. To develop our model, we use defined parameters and extrapolated values from literature and experimental measurements.  These values are integrated into 2-D simulations and tested using quantitative data from genetic perturbations to fine tune the parameters.  After successfully establishing a wild type model, we look at the mechanics that take place within the egg chamber, the precursor to the mature egg, throughout oogenesis.  These mechanics include the dynamic position of the oocyte nucleus (where GRK is localized before secretion), the movement of the follicle cells, and the overall growth of the egg chamber.  Here we show simulations that predict the contribution of each of the mechanics on the overall distribution of the ligand.  Furthermore, we use this model to predict patterns of EGFR activation in genetic perturbations.  Our comprehensive model allows a systematic approach for determining the contribution of individual parameters’ impact on EGFR activation and their underlying effects on morphogenesis. 


Mr. Kevin DeYoung – Biology, Rutgers-Camden           

Title:  Metabolic regulation of stalk synthesis in Caulobacter



Mr. Nathaniel Merrill – CCIB, Rutgers-Camden

Title:  Stability using Linear-In-Flux-Expressions

Abstract:  The Linear-in-Flux-Expressions (LIFE) methodology was developed for analyzing metabolic systems, particularly in simulating variability in patient populations. With LIFE, the relationships between parameters are used to reduce the overall complexity of the system.  When LIFE methodology is used, simulated system perturbations more closely match empirical data. These systems can also be associated to generalized graphs, and the graph properties provide insight into the dynamics of the metabolic system. This work addresses two main problems: 1. for fixed metabolite levels, find all fluxes for which the system is at equilibrium, and 2. for fixed fluxes, find all metabolite levels which are equilibria for the system. General results relating stability of systems to the structure of the associated graph are shown. It is also shown that a certain structure of the graph necessary for stable dynamics. 


2017 CCIB Annual Retreat

2016 CCIB Annual Retreat

2015 CCIB Annual Retreat