2017 CCIB Annual Retreat
Thursday, December 14, 2017
9 a.m. – 5:00 p.m.
Camden Nursing and Science Building
Room 201
2017 CCIB RETREAT – ITINERARY
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9:00 am |
Breakfast |
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9:30 am |
Welcome |
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Dr. Michael Palis – Provost, Rutgers-Camden |
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Dr. Kris Lindenmeyer – Dean of the Faculty of Arts and Sciences & the Graduate School, Rutgers-Camden |
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Dr. Nir Yakoby – Director, CCIB |
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(Abstracts for all speakers can be found below) |
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10:00 am |
Dr. Grace Brannigan – CCIB Title: Physics-based Pharmacology of the Central Nervous System |
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10:30 am |
Mr. Daniel Russo – CCIB PhD Candidate Title: Developing mechanism-based toxicity models from big data. |
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10:45 am |
Break |
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11:10 am |
Dr. Jinglin Fu – CCIB Title: DNA-based Proximity Assembly Circuit for Actuating Biochemical Reactions
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11:45 am |
Mr. Sean McQuade – CCIB PhD Candidate Title: Advancing early phase drug discovery toward robust in silico testing. |
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(Abstracts for all posters can be found below) |
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12:00 pm |
Poster Session & Lunch |
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2:00 pm |
Keynote Speaker: Dr. Sarah Tishkoff David and Lyn Silfen University Professor, Departments of Genetics and Biology at the Perelman School of Medicine and School of Arts and Sciences at the University of Pennsylvania Title: Evolution and Adaptation in Africa: Implications for Health and Disease |
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3:00 pm |
Break |
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3:15 pm |
Dr. Catherine Grgicak – CCIB Title: Production of High-Fidelity Electropherograms Results in Improved and Consistent Match-Statistics: Standardizing Forensic Validation |
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3:45 pm |
Ms. Nicole Revaitis – CCIB PhD Candidate Title: Modelling the dynamics of the Drosophila eggshell |
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4:00 pm |
Ms. Catherine Guay – CCIB PhD Candidate Title: Uncovering regulatory DNA at genome-scale |
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4:15 pm |
Dr. Sean O’Malley – CCIB Title: Dynamics of High Frequency Brain Activity. |
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4:45 pm |
Closing Remarks – Dr. Nir Yakoby Annual CCIB Retreat Group Photo |
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CCIB AFTER HOURS SOCIAL EVENTS |
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5:00 pm |
Dinner |
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6:30 pm |
Amazing Escape Room |
2017 CCIB Retreat Itinerary download
2017 CCIB RETREAT – SPEAKER ABSTRACTS
Dr. Grace Brannigan – Department of Physics, Rutgers-Camden
Title: Physics-based Pharmacology of the Central Nervous System
Abstract: Coming Soon
Mr. Daniel Russo – CCIB PhD Student, Rutgers-Camden
Title: Developing mechanism-based toxicity models from big data.
Abstract: Accurate predictive computational models for complex toxicity endpoints, e.g. oral acute toxicity and hepatotoxicity, have remained elusive. The difficulties in model development for these endpoints can be attributed to the complex mechanisms relevant to the toxicity phenomena. Recent work has shown that incorporating biological data into model development has resulted in better predictivity and allowed for intuition on mechanisms of action for toxicants. However, in the current ‘big data’ era, finding and characterizing relevant biological data to evaluate chemical toxicity is a major challenge. In this work, a new approach for creating predictive toxicity models based on the available bioassay data for chemicals of interest is presented. Briefly, all available biological data for the target compounds are automatically extracted. Chemical features relevant to each bioassay testing are identified by using Fisher’s Exact Test (p < 0.05) to rank chemical fragments existing in the target compounds of each bioassay dataset. The available bioassays can be clustered by the chemical fragment features that contribute to their activation. In this study, PubChem bioassays were prioritized and clustered based upon the chemical-in vitro relationships described above for rat oral acute toxicity. Several clusters of PubChem bioassays not only are able to predict acute toxicity for new compounds but also show toxicity mechanisms for toxicants containing the relevant chemical features. This approach can be easily applied to generate predictive models for other animal toxicity endpoints.
Dr. Jinglin Fu – Department of Chemistry, Rutgers-Camden
Title: DNA-based Proximity Assembly Circuit for Actuating Biochemical Reactions
Abstract: We combine dynamic DNA nanostructures with the catalytic swinging arms to develop biochemical sensing circuits capable of detecting various targets. A DNA logic-gated structure is used to lock a cofactor (e.g. NAD+) within a hairpin which makes the cofactor unable to interact with an enzyme partner. Specific molecular inputs, such as nucleic acids, small molecules or proteins, can trigger the conformational switch of the DNA hairpin to release a locked cofactor arm by mechanisms of toehold displacement and aptamer switches. Then, the proximity co-assembly of an enzyme and a cofactor is triggered for actuating a nanoreactor to catalyze the production of detectable signals. To increase the sensitivity of circuit, we investigated strategies of using catalyzed hairpin assembly to actuate multiple enzyme/cofactor pairs. The DNA-based reaction circuit will produce easy-to-read colorimetric or fluorescence signals for detection.
Mr. Sean McQuade – CCIB PhD Student, Rutgers-Camden
Title: Advancing early phase drug discovery toward robust in silico testing.
Abstract: The pharmaceutical industry is embracing in silico early phase drug discovery with benefits to monetary costs, and development time. Quantitative Systems Pharmacology models simulate an individual’s response to treatment with a Virtual Patient(VP). A VP’s usefulness in describing a clinical patient lies in the details of constructing this simulated metabolic network. The metabolic network should respond to chemical perturbations within biological limitations. Linear-In-Flux-Expressions(LIFE) provide us a way to equilibrate VPs. This is a natural, biologically-justifiable way to generate VPs, yielding responses to treatment that are more similar to clinical patients than previous methods.
KEYNOTE SPEAKER – Dr. Sarah Tishkoff – University of Pennsylvania
Title: Evolution and Adaptation in Africa: Implications for Health and Disease
Abstract: Africa is thought to be the ancestral homeland of all modern human populations. It is also a region of tremendous cultural, linguistic, climatic, and genetic diversity. Despite the important role that African populations have played in human history, they remain one of the most underrepresented groups in human genomics studies. A comprehensive knowledge of patterns of variation in African genomes is critical for a deeper understanding of human genomic diversity, the identification of functionally important genetic variation, the genetic basis of adaptation to diverse environments and diets, and the origins of modern humans. Furthermore, a deeper understanding of African genomic variation will provide the necessary foundation for powerful and efficient genome-wide association and systems biology studies to identify coding and regulatory variants that play a role in phenotypic variation including disease susceptibility. We have used whole genome SNP genotyping, high coverage genomic and transcriptomic sequencing analyses to characterize patterns of genomic variation, ancestry, and local adaptation across ethnically and geographically diverse African populations. We have identified candidate loci that play a role in adaptation to infectious disease, diet and high altitude, as well as the short stature trait in African Pygmies. Additionally, our studies shed light on human evolutionary history and African population history.
Dr. Catherine Grgicak – Department of Chemistry, Rutgers-Camden
Title: Production of High-Fidelity Electropherograms Results in Improved and Consistent Match-Statistics: Standardizing Forensic Validation
Abstract: Samples containing low-copy or complex DNA mixtures are routinely encountered in operations. The signal acquired from these sample types are difficult to interpret as they do not always contain all of the genotypic information from each contributor, where the loss of genetic information is associated with sampling and detection effects. The present work focuses on developing a validation scheme to aid in mitigating the effects of the latter to produce high-fidelity electopherograms (EPGs) that can be effectively interpreted by all probabilistic genotyping systems.
To this end, we have devised a computational system, named RESOLVIt (Resolving Evidentiary Signal for Objective Laboratory Validation), that generates synthetic EPGs in a laboratory-specific manner. As an input to the system, a large number of single source profiles of known genotype are provided by the laboratory. From these data, the distribution of the peak heights at noise positions is modeled as a function of the starting template amount using a log-normal distribution. The electrophoresis sensitivity, which is used to generate the DNA height distribution, is also acquired from the single source experimental data procured from the laboratory. Other pertinent laboratory conditions, such as the number of PCR cycles, injection time, starting template mass, etc. are input parameters and are easily modified by the user.
Since RESOLVIt utilizes a simulation approach, which is based upon experimental data acquired from the laboratory, multifarious scenarios may be explored by each laboratory in a cost-effective manner. Metrics such as signal1copy-to-noise resolution, false positive and false negative signal detection rates are used to select tenable laboratory conditions that result in high-fidelity signal in the single-copy regime. We demonstrate that the metrics acquired from simulation are consistent with experimental data obtained from two capillary electrophoresis platforms and various injection parameters. Once good resolution is obtained, analytical thresholds can be determined using detection error tradeoff analysis, if necessary.
Decreasing the limit of detection of the forensic process to one copy of DNA is a powerful mechanism by which to increase the information content on alleles from minor components of a mixture, which is particularly important for probabilistic system inference. By utilizing another fully continuous probabilistic system, CEESIt (Computational Evaluation of Evidentiary Signal), we demonstrate that if the forensic pipeline is engineered to produce high-fidelity EPG signal then the likelihood ratio (LR) of a true contributor increases and the probability that the LR of a randomly chosen person is greater than one decreases. CEESIt has been developed to not only compute the LR but also the probability that the LR is greater than one for millions of randomly chosen contributors, making it a powerful validation tool. This systematic, in-silico, laboratory-specific, computational-based approach to improve allele information content is, potentially, the first step towards standardization of the bio-analytical pipeline and DNA validation process across operational laboratories.
Ms. Nicole Revaitis – CCIB PhD Student, Rutgers-Camden
Title: Determination of parameters for modeling the dynamics of EGFR signaling during Drosophila oogenesis
Abstract: Organogenesis requires the coordination among multiple cell signaling pathways to develop tissues into functional organs. While many have studied the overall impact of ligands and their associated signaling pathways, 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-? 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. The parameters used were extrapolated from literature or quantified using analyses on genetic perturbations. However, we are still left with three unknown variables: the rate of internalization of the ligand-receptor complex (Kec), the diffusion of GRK in the perivitelline space (D), and the quantity of receptor (R0). Using CRISPR-Cas9, we developed a stable fly line that has an endogenously GFP labeled EGFR. We used this fly to follow the localization of the ligand and the dynamic interactions with the EGFR. We detect changes in the distribution of the receptor in the presence of high levels of EGFR signaling. The interplay between quantitative data and modeling aids to establish a model to study the dynamics and diversity of EGFR signaling during eggshell formation.
Ms. Catherine Guay – CCIB PhD Student, Rutgers-Camden
Title: Uncovering gene regulatory information at genome-scale
Abstract: Cis-regulatory modules (CRMs) integrate transcription factor inputs to causally affect gene expression. CRMs are thus an essential component of gene regulatory networks (GRNs) and are useful for deciphering gene regulatory information. We functionally identified ~45,000 CRMs out of ~12,000,000 human genomic test fragments in HepG2 liver carcinoma cells using our novel genome-scale reporter assay method. To exploit the abundant regulatory information contained within these CRMs, we performed motif enrichment analysis. Such analysis reveals DNA binding site motifs for transcription factors (TFs) that are either over- or under- represented within a set of CRMs. Traditionally, enrichment is determined against a null model of random sequences, and TFs for motifs that are enriched in CRMs are predicted to be direct regulators of CRM activity. Innovatively, we utilized a set of our functionally defined inactive genomic fragments rather than random sequences to detect relative motif enrichment in CRMs. We computed the relative enrichment of motifs and the proportion of putative targets for 601 TFs. Two motifs, Pitx2 and IKZF1, were highly enriched and present on ~60% of CRMs. Interestingly, neither of the corresponding TFs for these motifs is expressed in HepG2 cells. We hypothesized two alternative models for these non-expressed TFs of highly enriched motifs: either as positive or negative regulators of HepG2-CRMs in other cell-types. To test these hypotheses, we ectopically expressed pitx2 or izkf1 in HepG2 cells and measured their effects on the HepG2-CRMs. We observed that pitx2 down-regulates the majority of CRMs, whereas ikzf11 had only a minor effect on CRM activities in HepG2 cells. Our results highlight the utility of a large number of functionally identified CRMs as well as inactive DNA fragments to formulate and test hypotheses on novel regulatory interactions. The results also emphasize the potential that CRMs from one cell type can predict GRNs in other cell types.
Dr. Sean O’Malley – Department of Physics, Rutgers-Camden
Title: Dynamics of High Frequency Brain Activity
Abstract: Evidence suggests that electroencephalographic (EEG) activity extends far beyond the traditional frequency range. Much of the prior study of >120 Hz EEG is in epileptic brains. In the current work, we measured EEG activity in the range of 200 to 2000 Hz, in the brains of healthy, spontaneously behaving rats. Both arrhythmic (1/f-type) and rhythmic (band) activities were identified and their properties shown to depend on EEG-defined stage of sleep/wakefulness. The inverse power law exponent of 1/f-type noise is shown to decrease from 3.08 in REM and 2.58 in NonREM to a value of 1.99 in the Waking state. Such a trend represents a transition from long- to short-term memory processes when examined in terms of the corresponding Hurst index. In addition, treating the 1/f type activity as baseline noise reveals the presence of two, newly identified, high frequency EEG bands. The first band (?) is centered between 260–280 Hz; the second, and stronger, band is a broad peak in the 400–500 Hz range (termed ?). Both of these peaks display log-normal distributions. The functional significance of these frequency bands is supported by the variation in the strength of the peaks with EEG-defined sleep/wakefulness.
2017 CCIB RETREAT – POSTER ABSTRACTS
Zheming An, CCIB PhD Student with Dr. Piccoli
Title: Mathematical Analyses Relating Circadian Period and Phase of Entrainment
Abstract: Circadian rhythms are observed in most organisms, from cyanobacteria to human, and it’s driven by a circadian clock which is synchronized with solar time. A typical circadian clock has several characteristics, such as it is a self-sustaining endogenous, entrainable oscillator exhibit temperature compensation. In the past few decades, how to clearly address entrained phase and period interaction has become a key problem for chronobiologists. In this study, we decided to test the entrained phase and period relationship by using a mathematical model composed of three differential equations. The simulation results could give us a more comprehensive view and it explains more available data.
Lingyu Guan, CCIB PhD Student with Dr. Grigoriev
Title: Analysis of rRNA-derived Fragments in Human
Abstract: Ribosomal RNAs (rRNAs) are the most abundant RNAs in human cells however rRNA-derived fragments (rRFs) were were usually cleaned as contamination in the traditional RNA-seq analysis. Recent studies reported small RNA (sRNA) originated from non-coding rRNA including tRNA, snoRNAs as well as rRNAs in multiple organism. Nevertheless the biogenesis and functions of rRFs in human cells remain unclear. CLASH technique allowed the discovery of Argonaute(AGO)-associated RNA-RNA interactions. Here we reanalyzed the first human CLASH sequencing dataset to investigate the mechanism of human rRFs and rRNAs integrated with other sRNAs. We are also developing a database of human rRNAs and rRFs to facilitate future research as current rRNA-related databases are supporting microbiome studies.
Spyros Karaiskos, CCIB PhD Student with Dr. Grigoriev
Title: Analyzing the mode of action of tRNA derived fragments
Abstract: Transfer RNA fragments (tRFs) are a class of small RNA molecules derived from mature or precursor tRNAs. Although tRFs have been characterized very recently, gradually they have been attracting more attention. Similar to microRNAs, there is evidence that tRFs are found across a wide range of organisms and tissues in cytoplasmic compartments or loaded to RISC complexes, often in numbers comparable to microRNAs. Despite clear differences between tRFs and microRNAs, there is accumulating evidence that tRFs may play a vital role in post-transcriptional gene regulation and RNA silencing.
Here we describe potential interactions of human tRF with their putative target RNAs associated with human Argonaute complexes as elucidated from CLASH (Crosslinking, Ligation, And Sequencing of Hybrids) sequencing results. We found that Argonaute-loaded tRFs target a wide range of transcripts corresponding to various gene types, from rRNA to lincRNA to protein-coding transcripts. In the latter, 3′ UTR regions are the likely primary target of tRFs, although there is a significant number of interactions of tRFs with coding and 5′ UTR regions. Furthermore, we observed a novel phenomenon – a large number of putative interactions between tRFs and intronic sequences. We provide ample evidence supporting the notion that tRF “seed” sequences can be located on either end of a tRF molecule in agreement with experimentally validated results from earlier studies.
We performed extensive computational analysis, including k-mer search in the UTR regions conserved across multiple species and testing for motif enrichment in tRF-targeted sequences derived from the CLASH experiments. Contrary to the traditional view of microRNAs “seed” sequences, located on the 5′ end of the microRNAs molecule, we found that tRF “seeds” can be located both on the 5′ and 3′ end of the tRF molecule as well as in the middle of the fragment. Last, we performed clustering analysis for tRF/RNA hybrids aiming to shed light into the base pairing patterns between tRFs and their targets. Our results show that tRFs may operate in a very similar manner to miRNAs when loaded to Argonaute proteins, supporting the notion that tRFs are an active component of the post-transcriptional machinery.
Joseph Kawash, CCIB PhD Student with Dr. Grigoriev
Title: Comparative genome analysis provides insight to adaptation in woolly mammoth
Abstract: The woolly mammoth (Mammuthus primigenius) is an ancient species of megafauna that inhabited the upper Arctic regions of the globe until the demise of the most recent population about 3500 years ago. Though the woolly mammoth did not persist, its sister species, the Asian elephant, has successfully carried on to the present date. Despite being studied extensively anatomically, little is known about the genetic divergence and evolution between woolly mammoth and Asian elephant. Until recently, whole genome sequence availability of woolly mammoth specimens has been sparse and typically of low quality, a common challenge for ancient genomes; therefore few comparative genetic studies have been performed. These studies have been limited in sample size as well as breadth of mutation type. We expand upon current findings through the systematic identification of single nucleotide, as well as, indel, and structural variant fixed mutations for woolly mammoth. Our sample included individuals spanning a wide geographical (encompassing the range or 2 separate clades) and chronological (60,000 – 4,000 years ago) range. Woolly mammoth unique changes were identified affecting exon regions of several genes associated with metabolism, circadian rhythms, immunity, cold adaptation, and anatomy. Through the analysis of 4 woolly mammoth and 4 Asian elephant samples, we identified variation affecting large portions of the genome not previously reported, suggesting signs of evolutionary adaptation to the Arctic environment.
James Kelley, CCIB MS Student with Dr. Lun
Title: A Comprehensive Summary of the Uses of Genome Scale Metabolic Networks (GEMs)
Abstract: A genome-scale metabolic network (GEM) is a collection of known reactions, metabolites, and genes in an organism. GEMs can be used to make quantitative predictions of cellular metabolism using techniques such as flux balance analysis (FBA). GEMs can be used to predict strategies to metabolically engineer organisms such as bacteria, yeast, fungi, and plants to produce greater yields of chemicals important to industry or create conditions where organisms produce greater yields of these chemicals. Chemicals produced include biofuels, fuel additives and precursors, antibiotics, enzymes, vitamins, flavorings, healthy food supplements, animal feeds, pharmaceuticals and cosmetics. GEMs can be used to identify drug targets in disease causing organisms and parasites and assist in development of antibiotics, and vaccines to combat these organisms. GEMs can be used to study processes such as photosynthesis and nitrogen fixation. Software such as MOST (Metabolic Optimization and Simulation Tool) can use GEMs to make predictions by running analyses such as FBA on these GEMs.
Dr. Bala Koritala, Post Doc with Dr. Lee
Title: Uncoupled Circadian Clock Enhances Reproductive Fitness
Abstract: The circadian clock has been attributed as a fitness trait in multiple organisms from cyanobacteria to humans. However, the mechanism of habitat specific circadian clock variation and its influence on fitness is not well understood. In the current study, we show the strength of clock regulation of asexual development is shaped by local habitat and plays a role in organismal fitness. We found that habitat-specific-clock-variation is involved in local adaptation in N. discreta, a species that is adapted to two different habitats, under or above tree bark. African N. discreta strains, whose habitat is above the tree bark, have higher fitness under a light/dark cycling condition relative to a constant ambient light condition. North American strains, whose habitat is under the tree bark, gained reproductive fitness in comparison to that of African strains, regardless of light/dark cycle, but lost their clock regulation of asexual development. Furthermore, we identified ‘adaptive genes’ responsible for habitat-specific-clock variation using QTL and RNA-seq analyses. Our data provide new insights into a mechanism by which local adaptation of circadian regulation influences its reproductive fitness.
Dr. Kwangwon Lee, Department of Biology
Title: Experimental and Mathematical Analyses Relating Circadian Period and Phase of Entrainment in Neurospora crassa
Abstract: Circadian rhythms are observed in most organisms on earth and known to play a major role in successful adaptation to the 24 h cycling environment. Circadian phenotypes are characterized by a free running period that is observed in constant conditions and an entrained phase that is observed in cyclic conditions. Thus, the relationship between the free running period and phase of entrainment is of interest. A popular simple rule has been that the entrained phase is the expression of the period in a cycling environment, i.e., that a short period causes an advanced phase, and a long period causes a delayed phase. However, there are experimental data that are not explained by this simple relationship, and no systematic study has been done to explore all possible period-phase relationships. Here we show the existence of stable period-phase relationships that are exceptions to this rule. First, we analyzed period-phase relationships using populations with different degrees of genome complexity. Second, we generated isogenic F1 populations by crossing 14 classical period mutants to the same female, and analyzed two populations with a short period/delayed phase and a long period/advanced phase. Third, we generated a mathematical model to account for such variable relationships between period and phase. Our analyses support the view that the circadian period of an organism is not the only predictor of the entrained phase.
Nathaniel Merrill, CCIB PhD Student with Dr. Piccoli
Title: Ancient Food Web Analysis
Abstract: From its creation, food web theory has played a crucial role in ecology. Food webs depict the interactions between species. Most often, this network describes feeding relationships. Despite the use of food webs in current ecology, there has been little analysis of ancient feeding network. Understanding ancient networks could help to reconstruct past climate conditions and potentially provide information of how ecological communities responded to changes to climate conditions. This information would be instrumental in projecting how current communities may react to changing climates. To evaluate how realistic a reconstruction network may be, they are compared to modern living networks. The reconstructed networks are shown to differ from modern living in having more links per species. The reconstructed networks also are shown to have a time bias in favor of recent species.
Steven Moffett, CCIB PhD Student with Dr. Martin
Title: Effect of thyroid hormone on Torpedo nicotinic acetylcholine receptors expressed in Xenopus oocytes
Abstract: In the past, thyroid hormones were thought to have exclusively genomic actions in adults, with no short-term signaling effects, but recent evidence contradicts this. Clinical effects of thyroid hormone deficiency or surplus are sleep and psychological disorders. The thyroid hormone 3, 3’,5-triiodothyronine (T3) has been shown to localize in noradrenergic centers and noradrenergic projection sites in adult rat brains. Recently, T3 has been shown to have an effect on sleep after microinjection into the sleep-active median preoptic nucleus of adult male rats. It has also been demonstrated to have neurotransmitter-like, inhibitory effects on the GABAA receptor, a pentameric, ligand-gated ion channel and prevalent mediator of inhibitory synaptic activity in the brain.
The nicotinic acetylcholine receptor (nAChR) is a pentameric ligand-gated ion channel crucial in synaptic transmission between neurons and at the neuromuscular junction. The high density of nAChRs in the sea ray Torpedo’s electric organ allow for extraction of large amounts of intact nAChRs. After solubilizing and reconstituting extracted receptors in enriched lipids or detergents, Torpedo nAChRs can be used to establish a crystal structure, to perform binding/imaging studies, or to perform functional tests.
Within hours of injecting reconstituted nAChRs into the oocyte of the African claw-toed frog (Xenopus laevis), receptors incorporate into the oocyte cell membrane and the oocytes can be used for electrophysiological testing using two-electrode voltage clamping (TEVC). We extracted nAChRs from the electric organ of Torpedo californica and reconstituted functional channels in asolectin (soybean) lipids. We injected resuspended nAChRs in Xenopus oocytes and performed pharmacological tests on T3, as well as on its derivative, 3,3’,5-triiodothyroacetic acid (Triac). We show neurotransmitter-like effects of T3 and Triac on the nicotinic acetylcholine receptor.
Sreelekha Revur, CCIB PhD Student with Dr. Klein
Title: Identification of a novel regulator of stalk synthesis in Caulobacter crescentus
Abstract: Prokaryotes exist in diverse morphologies in nature. The shape of the cell offers the cell it the ability to adapt to the selective pressures of its environment. Bacterial shape is a function of its cell wall composition. Our current knowledge of bacterial cell wall synthesis is generally limited to rod shaped cells. To address the question of how special morphological features, aid different bacterial cells in survival, we use Caulobacter crescentus as a model organism. Caulobacter crescentus has a polar cellular extension called a stalk that elongates dramatically in response to phosphate starvation. Stalk synthesis is a highly regulated process of unidirectional extension of the cell envelope. The stalk also serves as a cell polarity marker during the asymmetric cell division in Caulobacter crescentus. The phenomenon of stalk localization is governed by a polar localization complex; however, the mechanism of stalk synthesis remains unknown. The current work aims at characterizing a novel penicillin binding protein (PBP), CC_2105 that may have a function in the regulation of stalk synthesis.
Abby Robinson, Chemistry Graduate Student with Dr. O’Malley & Dr. Griepenburg
Title: Wavelength specific nanoparticle mediated release of polymersomes using ultrafast single pulse irradiation
Abstract: The self-assembly of amphiphilic di-block copolymers into polymeric vesicles, commonly known as polymersomes, is an area of high interest in research due to the potential applications in the field of drug delivery. Polymersomes are fully synthetic robust vesicles composed 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 provide a non-invasive method of achieving spatial and temporal control. We have shown that the incorporation of gold nanoparticles (AuNP) within the vesicle membrane provides wavelength specific vesicle rupture at 532 nm. The wavelength dependence of our polymersome system can be shifted by altering the plasmonic mode of the nanoparticles by way of shape and composition.
Catherine Rosenberg, CCIB PhD Student with Dr. Lun
Title: Comparison of Modified and Traditional Circumferential to Water Displacement Volume Measurement of the Upper Extremity
Abstract: There is a fundamental gap in evaluating the efficacy of lymphedema interventions because of inconsistent limb volume measurement methods across standards of care and facilities. The gold standard of limb volume measurement (water displacement; WD) is time-consuming, contraindicated for those with infection or open wounds and is limited to upper (UE) and lower extremities. The purpose of this pre-pilot study is to develop a prototype formula equivalent to WD by using a modified truncated cone (MTC) method.
Methods: We use a prospective, cross-sectional design to compare two computational measurement methods to WD: (1) our novel MTC using circumferential measures starting at the wrist including the palm and fingers progressing up the UE in 4cm increments to the anterior axillary skinfold with a standard midpoint at the elbow; (2) truncated cone (TC) using the same method as MTC but excluding fingers while assuming 4cm increments on the palm.
Results: To date, we have recruited 26 healthy participants for a total of 52 UEs (our unit of analysis) – 100% is female, 92.3% are right handed and have an average 27.67 years old (s.d. 13.49 ), BMI of 24.62 (s.d. 3.88 ). The mean volume percent difference between MTC and WD is 0.40 % (s.d. = ± 2.40) whereas the difference between WD and TC is -4.99% (s.d. = ± 2.61). The percent difference between MTC and WD was significantly less than the percent difference between TC and WD (p<0.0001).
Conclusions: These pre-pilot data suggest that the MTC method may hold promise as an accurate measurement technique comparable to WD. Our data show that for this sample TC underestimates volume found with WD by 4.99 % – a difference which might pose a clinical barrier to evaluating the efficacy of lymphedema management. This study is ongoing and our next step is to test our novel MTC in those with lymphedema of the UE.
Liam Sharp, CCIB PhD Student with Dr. Brannigan
Title: Nicotinic Acetylcholine Receptors Partitioning Preference in Quasi-Native Membranes Containing Polyunsaturated Fatty Acids
Abstract: Nicotinic acetylcholine receptors (nAChR) are pentameric ligand gated ion channels, critical to signaling across synapses and the neuro-muscular junction. While sensitive to boundary lipids, nAChR have been shown to be functionally dependent on cholesterol. This dependence on cholesterol has led to the hypothesis that nAChR resides within the cholesterol rich liquid ordered domains. Using the MARTINI force field, coarse-grained molecular dynamic simulations were preformed, with nAChRs in quasi-native ternary membranes. Native nAChR membrane composition has an abundance of polyunsaturated fatty acids (PUFAs), saturated fatty acids, and cholesterol. The two PUFAs chosen for these simulations were Docosahexaenoic acid and Linoleic acid.
These simulations display nAChR consistently residing in the PUFA enriched disordered domain, remaining nearby the liquid ordered domain. Analysis of boundary lipid composition confirms nAChR boundary lipids are enriched in PUFAs. Further analysis of nAChR subunit-domain interaction show alpha subunits preference for cholesterol rich domains, while beta subunits show preference for PUFAs. Lastly, analysis shows PUFAs and cholesterol binding non-annularly nAChR.
This study is being expanded to compare complex quasi-native synaptic and oocyte membranes. The oocyte membrane, in particular, is an optimal model for studying lipid-protein interactions, because it has a lower abundance of n-3 PUFAs compared to the neuron. From our simulations, we find that differences in membrane composition are especially noticeable around nAChRs. Given that nAChRs no longer exhibit partitioning preferences in oocyte membranes, our initial simulations suggest that oocytes do not provide a sufficiently native-like environment for nAChR
Gabriele Stankeviciute, CCIB PhD Student with Dr. Klein
Title: Unique peptidoglycan synthesized solely in bacterial appendage
Abstract: Cell shape diversity among prokaryotes is most studied in rod-shaped bacteria such as Bacillus subtilis and Escherichia coli, but unusual shape characterization and its physiological regulation of its coordinated synthesis is lacking. Caulobacter crescentus serves as a model organism when studying odd-shaped bacteria as its cellular protrusion, the stalk and overall morphology is directly coupled to its life cycle. Additionally, the stalk elongates dramatically when growing in phosphate-limiting conditions and thus the cell wall and both inner and outer membrane must keep up with the continuation in extending the cell layers surrounding the stalk. From various microscopy and HPLC analyses of the muropeptides that comprise the peptidoglycan, PG layer, it is evident that the PG incorporated into the stalk is somehow chemically distinct than what is in the cell body. This project focuses on figuring out the chemical composition of the stalk appendage as well as the genetic mechanisms that control these changes.
Cody Stevens, CCIB PhD Student with Dr. Yakoby
Title: Pointed is necessary and sufficient for establishing the posterior end of the follicular epithelium
Abstract: The anterior-posterior axis during Drosophila oogenesis is regulated by a small number of cell signaling pathways. The Janus-kinase/Signal Transducers and Activators of Transcription (JAK/STAT) is activated in both posterior and anterior ends of the follicular epithelium. Previously shown, JAK/STAT activation is required for the expression of decapentaplegic (dpp), the bone morphogenetic protein (BMP) signaling ligand, which consequently activates this pathway in the anterior follicular epithelium. In the posterior, JAK/STAT works in concert with the epidermal growth factor receptor (EGFR) to express the ETS-transcription factor pointed (pnt). Pnt was shown to control the dorsal midline width, which sets the distance between the two dorsolateral domains of the respiratory dorsal appendages primordia. Here we show that Pnt is necessary for determining the posterior fate of the follicular epithelium. In addition, our results indicate that Pnt is sufficient to repress anterior fate formation, as seen by the loss of BMP signaling. This complex signaling and transcriptional network provide insight into the establishment of the anterior-posterior axis of the fly.
David Verrill, Chemistry Graduate Student with Dr. Salas
Title: Thermal and Structural Analysis of Metastable Biocomposites
Abstract: The field of regenerative medicine is currently investigating the utilization of biomaterials grafts in the area of wound treatment. A current material that is being studied is the medical grade tilapia skins which are being investigated for their collagen type 1 and 3 protein structures as a new kind of burn wound treatment. The material showed promising results and fast healing. Utilizing biomaterials such as bombyx mori silk, a protein, along with cellulose, a polysaccharide, will provide the necessary structural and physicochemical properties to aid in the healing process. For examples, silk-based composites are currently being researched in the areas of bone marrow structures. However, the morphological reasons of such success was not readily explained. Silk is a biomaterial showing potential in this area 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, the objective was to analyze structural and thermal properties of silk-based biocomposites using various characterization equipment such as SEM, TGA, and DSC. The main objective was to regenerate the samples using ionic liquids and to understand the effect of three polar coagulation agents: water (H2O), ethanol (EtOH), and hydrogen peroxide (H2O2).
Sung Won Oh, CCIB PhD Student with Dr. Fu
Title: Biochemical Sensing Circuits Based on DNA-Scaffolded Proximity Assembly
Abstract: In biochemical pathways, many enzyme functions are regulated by inhibition byproducts, or product feedback inhibition. In this project, artificial sensing circuits are designed to channel the transfer of intermediates in multi-enzyme reactions. Swinging arms play important role in multi-step, catalytic transformations in multienzyme complexes. Proximity assembly circuits will be implemented to swinging arms to control the release and activation of swinging arms to control the transport of intermediates in enzyme reactions. Proximity assembly circuits are composed of single-stranded DNA molecules to regulate the pathway activities and specificities. In order to regulate the multienzyme pathway, which will be implemented on DNA nanostructures for controlling and switching pathway activities to produce different final products depending on specific inputs. Proximity assembly circuits for controlling swinging arms has been created with toehold design for DNA strand displacement, resulting in releasing of swinging arm. Currently, to increase the signal production for more sensitivity, we are utilizing the hairpin assembly circuit to amplify the assembled enzyme/cofactor nanostructures. Eventually, the proximity assembly circuits will be applied to detecting biotargets with signal amplification in a small test tube and visible color change.
Wenyi Wang, CCIB PhD Student with Dr. Zhu
Title: Virtual Gold Nanoparticle Library: Simulation, Modeling and Experimental Validation
Abstract: Experimentally testing nanomaterials for their complex bioactivities (e.g. toxicity) is expensive and time-consuming. Computational modeling methods are demanded to predict toxicities of nanomaterials before chemical synthesis. However, the current computational nanotoxicity modeling studies still rely on certain few experimental parameters (e.g., nanoparticle size) and are not applicable for predicting new nanomaterials. We designed and constructed a novel computational approach that can quantify the nanostructure diversity to various new nano-descriptors and use the resulting descriptors to develop predictive models for nanotoxicity. Firstly, we experimentally synthesized 34 gold nanoparticles, which have different sizes and surface ligands, and tested them against multiple toxicity relevant assays as the training set. Then we virtually built the gold nanoparticle libraries for this dataset. Based on the surface chemistry simulations, we calculated 86 new nano-descriptors and used them to develop predictive models for hydrophilicity, induction of HO-1 level in A549 cell line, and cellular uptake in A549 and HEK293 cell line. These four models were then experimentally validated by predicting 7 newly synthesized GNPs with a high prediction performance of R2 as 0.918, 0.919, 0.768 and 0.930 respectively. The high external predictivity of the resulting models shown its capability for virtual screening of new GNPs for their toxicity potentials. This study and the resulting computational approaches pave the path to the design of new safe nanomaterials by providing biocompatible virtual nanoparticles.
John Whittaker, CCIB PhD Student with Dr. Larini
Title: Evaluating Force Fields and Implicit Solvents in the Study of Intrinsically Disordered Proteins
Abstract: Intrinsically disordered proteins (IDPs) represent a class of understudied but functionally important proteins that lack definite secondary and tertiary structure. The diversity of an IDP’s conformational ensemble over time makes them notoriously difficult to characterize experimentally. Thus, molecular dynamics (MD) simulations have been employed in order to gain a unique, atomistic glimpse into the equilibrium characteristics of these proteins. Unfortunately, though, many of the available MD force fields and solvent models that dictate these properties have been developed and validated with the study of structured biomolecules in mind. Here, we examine a number of disordered peptide systems with respect to numerous popular force fields and implicit solvent models in order to determine which combination of parameters delivers the most accurate representation of experimental data. Doing so delivers valuable information for groups who wish to undertake an MD investigation into the properties of these IDP systems with hopes to better understand them.
Kristin Woods, CCIB PhD Student with Dr. Brannigan
Title: Oligomerization of nicotinic acetylcholine receptors in domain-forming membranes
Abstract: The nicotinic acetylcholine receptor (nAChR) is an excitatory pentameric ligand gated ion channel found throughout the central and peripheral nervous system. At the neuromuscular junction, nAChRs cluster at a high density, in order to rapidly activate the skeletal muscle. Recent research indicates that lipid microdomains, referred to as lipid rafts, mediate the clustering of nAChRs at the neuromuscular junction; however, due to methodological limitations, it is unclear whether lipid rafts contribute structurally and/or functionally to nAChR cluster formation.
In the present study, we use coarse-grained molecular dynamics simulations to investigate the oligomerization of nAChRs in membranes with and without lipid domains. In domain-forming membranes, nAChRs exhibit a strong a?nity for the domain interface and even dimerizing along well-defined interfaces. Oligomerization is not observed in membranes lacking domains. Boundary lipids are rich in polyunsaturated acyl chains regardless of the number of nAChR molecules, but preventing domain formation also reduces the likelihood of these acyl chains aggregating around nAChR. These results imply that nAChR organization, oligomerization, and local environment is highly sensitive to membrane organization, with long-tailed PUFAs playing a critical role in both phase separation and protein clustering in neuronal membranes.
Linlin Zhao, CCIB PhD Student with Dr. Zhu
Title: Mechanism-Driven Computational Modeling of Hepatotoxicity Based on Chemical Information, Biological Data and Toxicity Pathways
Abstract: Hepatotoxicity is a leading cause of attrition in drug development and has resulted in a considerable number of drug withdrawals from the market. Traditional preclinical and clinical studies to evaluate drug hepatotoxicity are expensive and time-consuming. With the advent of critical advancements in in vitro testing approaches, in particular High Throughput Screening (HTS), there has been a rapid accumulation of chemical toxicity data and a critical need to capitalize on publicly available datasets. Together, big data offer a novel alternative approach to evaluate hepatotoxicity potential for new and existing chemicals. To this end, we curated and merged all available in vivo hepatotoxicity data obtained from the literature and public database resources, which yielded a comprehensive dataset of ~4,000 unique compounds that could be categorized as hepatotoxic or non-hepatotoxic in human. For compounds in this datasets, ToxPrint Chemotypes from ChemoTyper® were used to generate potential structural toxicophores. Next, biological responses were profiled using in-house automatic data mining tool to search against the PubChem® database. Then, PubChem biological data were clustered based on chemical-in vitro relationships. Using the clustered bioprofiles of the training set containing over 2,500 compounds, multiple read-across models were developed that showed acceptable predictivity in the cross validation procedure (positive predictive values: 0.50 to 0.82). By integrating toxicophore information to develop chemical-in vitro-in vivo relationships, the predictivity was further improved by 12.8% to 68.0% for 14 models (positive predictive values: 0.72 to 0.96). These selected models were used to predict the hepatotoxicity potential of over 1,200 external new compounds and achieved similar performance (positive predictive values: 0.64 to 1.00). The chemical-in vitro-in vivo relationships obtained from these top ranked models can be integrated into several adverse outcome pathways (AOPs). This study developed new computational read-across models based on substantial publicly available data that can be used to predict the hepatotoxicity of new compounds and elucidate novel mechanisms of injury by integrating chemical and biological data into toxicity pathways.