Life Sciences Commons^™

Neutralizing Antibodies Against Ebv Gp42 Show Potent In Vivo Protection And Define Novel Epitopes, Qian Wu, Ling Zhong, Dongmei Wei, Wanlin Zhang, Junping Hong, Yinfeng Kang, Kaiyun Chen, Yang Huang, Qingbing Zheng, Miao Xu, Mu-Sheng Zeng, Yi-Xin Zeng, Ningshao Xia, Qinjian Zhao, Claude Krummenacher, Yixin Chen, Xiao Zhang

Faculty Scholarship for the College of Science & Mathematics

Epstein-Barr virus (EBV) is the first reported human oncogenic virus and infects more than 95% of the human population worldwide. EBV latent infection in B lymphocytes is essential for viral persistence. Glycoprotein gp42 is an indispensable member of the triggering complex for EBV entry into B cells. The C-type lectin domain (CTLD) of gp42 plays a key role in receptor binding and is the major target of neutralizing antibodies. Here, we isolated two rabbit antibodies, 1A7 and 6G7, targeting gp42 CTLD with potent neutralizing activity against B cell infection. Antibody 6G7 efficiently protects humanized mice from lethal EBV challenge and …

Trehalose Enhances Mitochondria Deficits In Human Npc1 Mutant Fibroblasts But Disrupts Mouse Purkinje Cell Dendritic Growth Ex Vivo., Collin M Macleod, Fawad A K Yousufzai, Liam T Spencer, Sarah Kim, Lucianne A Rivera-Rosario, Zerian D Barrera, Lindsay Walsh, Claude Krummenacher, Benjamin Carone, Ileana Soto

Faculty Scholarship for the College of Science & Mathematics

Lysosomes play important roles in catabolism, nutrient sensing, metabolic signaling, and homeostasis. NPC1 deficiency disrupts lysosomal function by inducing cholesterol accumulation that leads to early neurodegeneration in Niemann-Pick type C (NPC) disease. Mitochondria pathology and deficits in NPC1 deficient cells are associated with impaired lysosomal proteolysis and metabolic signaling. It is thought that activation of the transcription factor TFEB, an inducer of lysosome biogenesis, restores lysosomal-autophagy activity in lysosomal storage disorders. Here, we investigated the effect of trehalose, a TFEB activator, in the mitochondria pathology of NPC1 mutant fibroblasts in vitro and in mouse developmental Purkinje cells ex vivo. We …

Sctiger: A Deep-Learning Method For Inferring Gene Regulatory Networks From Case Versus Control Scrna-Seq Datasets., Madison Dautle, Shaoqiang Zhang, Yong Chen

Faculty Scholarship for the College of Science & Mathematics

Inferring gene regulatory networks (GRNs) from single-cell RNA-seq (scRNA-seq) data is an important computational question to find regulatory mechanisms involved in fundamental cellular processes. Although many computational methods have been designed to predict GRNs from scRNA-seq data, they usually have high false positive rates and none infer GRNs by directly using the paired datasets of case-versus-control experiments. Here we present a novel deep-learning-based method, named scTIGER, for GRN detection by using the co-differential relationships of gene expression profiles in paired scRNA-seq datasets. scTIGER employs cell-type-based pseudotiming, an attention-based convolutional neural network method and permutation-based significance testing for inferring GRNs among …

Ultrasound-Assisted Air-Jet Spinning Of Silk Fibroin-Soy Protein Nanofiber Composite Biomaterials., Futian Yang, Fang Wang, Janine Mazahreh, Xiao Hu

Faculty Scholarship for the College of Science & Mathematics

Ultrasound utilizes a non-radiation technology that can meet modern standards to gain access to cheap, reliable and sustainable modern energy. Ultrasound technology can be implemented in the field of biomaterials for its exceptional potential in controlling the shape of nanomaterials. This study presents the first example of the production of soy and silk fibroin protein composite nanofibers in various ratios via combining ultrasonic technology with air-spray spinning. Characterization of ultrasonic spun nanofibers was performed by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), differential scanning calorimetry (DSC), thermogravimetric (TG) analysis, water contact angle, water retention, enzymatic …

Kif6 Trp719arg Genetic Variant Increases Risk For Thoracic Aortic Dissection, Juan J Velasco, Yupeng Li, Bulat A Ziganshin, Mohammad A Zafar, John A Rizzo, Deqiong Ma, Hui Zang, Asanish Kalyanasundaram, John A Elefteriades

Faculty Scholarship for the College of Science & Mathematics

Background: KIF6 (kinesin family member 6), a protein coded by the KIF6 gene, serves an important intracellular function to transport organelles along microtubules. In a pilot study, we found that a common KIF6 Trp719Arg variant increased the propensity of thoracic aortic aneurysms (TAA) to suffer dissection (AD). The present study aims for a definite investigation of the predictive ability of KIF6 719Arg vis à vis AD. Confirmatory findings would enhance natural history prediction in TAA. Methods: 1108 subjects (899 aneurysm and 209 dissection patients) had KIF6 719Arg variant status determined. Results: The 719Arg variant in the KIF6 gene correlated strongly …

Discovering New Potential Inhibitors To Sars-Cov-2 Rna Dependent Rna Polymerase (Rdrp) Using High Throughput Virtual Screening And Molecular Dynamics Simulations., Dylan Brunt, Phillip M Lakernick, Chun Wu

Faculty Scholarship for the College of Science & Mathematics

RNA dependent RNA polymerase (RdRp), is an essential in the RNA replication within the life cycle of the severely acute respiratory coronavirus-2 (SARS-CoV-2), causing the deadly respiratory induced sickness COVID-19. Remdesivir is a prodrug that has seen some success in inhibiting this enzyme, however there is still the pressing need for effective alternatives. In this study, we present the discovery of four non-nucleoside small molecules that bind favorably to SARS-CoV-2 RdRp over the active form of the popular drug remdesivir (RTP) and adenosine triphosphate (ATP) by utilizing high-throughput virtual screening (HTVS) against the vast ZINC compound database coupled with extensive …

Deciphering Hierarchical Organization Of Topologically Associated Domains Through Change-Point Testing., Haipeng Xing, Yingru Wu, Michael Q Zhang, Yong Chen

Faculty Scholarship for the College of Science & Mathematics

BACKGROUND: The nucleus of eukaryotic cells spatially packages chromosomes into a hierarchical and distinct segregation that plays critical roles in maintaining transcription regulation. High-throughput methods of chromosome conformation capture, such as Hi-C, have revealed topologically associating domains (TADs) that are defined by biased chromatin interactions within them.

RESULTS: We introduce a novel method, HiCKey, to decipher hierarchical TAD structures in Hi-C data and compare them across samples. We first derive a generalized likelihood-ratio (GLR) test for detecting change-points in an interaction matrix that follows a negative binomial distribution or general mixture distribution. We then employ several optimal search strategies to …

Bone-Loading Physical Activity And Alcohol Intake But Not Bmi Affect Areal Bone Mineral Density In Young College-Aged Korean Women: A Cross-Sectional Study., Dong Jun Sung, Harshvardhan Singh, Seung-Bum Oh, Sojung Kim

Faculty Scholarship for the College of Science & Mathematics

The purpose of this cross-sectional study was to determine the differences in areal bone mineral density (aBMD) based on alcohol consumption behaviors, bone-loading history as assessed by a bone-specific physical activity questionnaire (BPAQ), and the body mass index (BMI). College-aged female students (N = 112) were recruited from the universities in Seoul and Gyeonggi province, South Korea. The aBMD of the lumbar spine and non-dominant side of the proximal femur (total hip, TH; femoral neck, FN; femoral trochanter, FT) were measured using dual energy X-ray absorptiometry (DXA). Alcohol consumption was determined by the frequency and amount of alcohol intake during …

Fishermp: Fully Parallel Algorithm For Detecting Combinatorial Motifs From Large Chip-Seq Datasets., Shaoqiang Zhang, Ying Liang, Xiangyun Wang, Zhengchang Su, Yong Chen

Faculty Scholarship for the College of Science & Mathematics

Detecting binding motifs of combinatorial transcription factors (TFs) from chromatin immunoprecipitation sequencing (ChIP-seq) experiments is an important and challenging computational problem for understanding gene regulations. Although a number of motif-finding algorithms have been presented, most are either time consuming or have sub-optimal accuracy for processing large-scale datasets. In this article, we present a fully parallelized algorithm for detecting combinatorial motifs from ChIP-seq datasets by using Fisher combined method and OpenMP parallel design. Large scale validations on both synthetic data and 350 ChIP-seq datasets from the ENCODE database showed that FisherMP has not only super speeds on large datasets, but also …

Transcranial Direct Current Stimulation Of Motor Cortex Enhances Running Performance., Seung-Bo Park, Dong Jun Sung, Bokyung Kim, Sojung Kim, Joung-Kyue Han

Faculty Scholarship for the College of Science & Mathematics

Transcranial direct current stimulation (tDCS) is a technique used to modulate neuronal excitability through non-invasive brain stimulation that can enhance exercise performance. We hypothesize that tDCS would improve submaximal running time to exhaustion (TTE) and delay the increase in the rating of perceived exertion (RPE) over time. We also hypothesize that tDCS would not lead to difference in cardiorespiratory responses. We employed a randomized, single-blinded, and counterbalanced design in which 10 trained men participated. After receiving either 20 min of 1.98 mA anodal tDCS applied over the primary motor cortex (M1) or sham-operated control on separate days, participants completed a …

Association Between Bone-Specific Physical Activity Scores And Pqct-Derived Measures Of Bone Strength And Geometry In Healthy Young And Middle-Aged Premenopausal Women., Sojung Kim, Breanne S Baker, Pragya Sharma-Ghimire, Debra A Bemben, Michael G Bemben

Faculty Scholarship for the College of Science & Mathematics

The aim of this study was to determine if bone-specific physical activity questionnaire (BPAQ) scores were positively related to bone health in healthy young and middle-aged premenopausal women. The total BPAQ was a stronger predictor of bone strength and bone mineral density of hip in young women as compared to middle-aged premenopausal women.

PURPOSE: The purpose of this study was to determine whether the BPAQ scores were predictive indices of volumetric BMD (vBMD), bone strength, and bone geometry in young and middle-aged premenopausal women.

METHODS: Healthy young (n = 60) and middle-aged premenopausal women (n = 54) between the ages …

In Situ Capture Of Chromatin Interactions By Biotinylated Dcas9., Xin Liu, Yuannyu Zhang, Yong Chen, Mushan Li, Feng Zhou, Kailong Li, Hui Cao, Min Ni, Yuxuan Liu, Zhimin Gu, Kathryn E Dickerson, Shiqi Xie, Gary C Hon, Zhenyu Xuan, Michael Q Zhang, Zhen Shao, Jian Xu

Faculty Scholarship for the College of Science & Mathematics

Cis-regulatory elements (CREs) are commonly recognized by correlative chromatin features, yet the molecular composition of the vast majority of CREs in chromatin remains unknown. Here, we describe a CRISPR affinity purification in situ of regulatory elements (CAPTURE) approach to unbiasedly identify locus-specific chromatin-regulating protein complexes and long-range DNA interactions. Using an in vivo biotinylated nuclease-deficient Cas9 protein and sequence-specific guide RNAs, we show high-resolution and selective isolation of chromatin interactions at a single-copy genomic locus. Purification of human telomeres using CAPTURE identifies known and new telomeric factors. In situ capture of individual constituents of the enhancer cluster controlling human β-globin …

A Cationic Amphiphilic Random Copolymer With Ph-Responsive Activity Against Methicillin-Resistant Staphylococcus Aureus., Sungyoup Hong, Haruko Takahashi, Enrico T Nadres, Hamid Mortazavian, Gregory Caputo, John G Younger, Kenichi Kuroda

Faculty Scholarship for the College of Science & Mathematics

In this report, we demonstrate the pH-dependent, in vitro antimicrobial activity of a cationic, amphiphilic random copolymer against clinical isolates of drug-resistant Staphylococcus aureus. The polymer was developed toward a long-term goal of potential utility in the treatment of skin infections. The proposed mechanism of action of the polymer is through selectively binding to bacterial membranes and subsequent disruption of the membrane structure/integrity, ultimately resulting in bacterial cell death. The polymer showed bactericidal activity against clinical isolates of methicillin-resistant or vancomycin-intermediate S. aureus. The polymer was effective in killing S. aureus at neutral pH, but inactive under acidic conditions (pH …

Relationship Between Bone-Specific Physical Activity Scores And Measures For Body Composition And Bone Mineral Density In Healthy Young College Women., Sojung Kim, Wi-Young So, Jooyoung Kim, Dong Jun Sung

Faculty Scholarship for the College of Science & Mathematics

OBJECTIVE: The purpose of this cross-sectional study was to investigate the relationship between bone-specific physical activity (BPAQ) scores, body composition, and bone mineral density (BMD) in healthy young college women.

METHODS: Seventy-three college women (21.7 ± 1.8 years; 162.1 ± 4.6 cm; 53.9 ± 5.8 kg) between the ages of 19 and 26 years were recruited from the universities in Seoul and Gyeonggi province, South Korea. We used dual energy X-ray absorptiometry to measure the lumbar spine (L2-L4) and proximal femur BMD (left side; total hip, femoral neck). The BPAQ scores (past, pBPAQ; current, cBPAQ; total, tBPAQ) were used to …

De Novo Deciphering Three-Dimensional Chromatin Interaction And Topological Domains By Wavelet Transformation Of Epigenetic Profiles., Yong Chen, Yunfei Wang, Zhenyu Xuan, Min Chen, Michael Q Zhang

Faculty Scholarship for the College of Science & Mathematics

Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experimental complexity and costs. Here we describe a novel computational method, called CITD, for de novo prediction of the chromatin interaction map by integrating histone modification data. We used the public epigenomic data from human fibroblast IMR90 cell and embryonic stem cell (H1) to develop and test CITD, which can not only successfully reconstruct the chromatin interaction frequencies discovered by …

Integrated Transcriptome Analysis Reveals Mirna-Mrna Crosstalk In Laryngeal Squamous Cell Carcinoma., Yang Zhang, Yong Chen, Jinhai Yu, Guiming Liu, Zhigang Huang

Faculty Scholarship for the College of Science & Mathematics

Next generation sequencing (NGS) has proven to be a powerful tool in delineating myriads of molecular subtypes of cancer, as well as in revealing accumulation of genomic mutations throughout cancer progression. Whole genome microRNA (miRNA) and mRNA expression profiles were obtained from patients with laryngeal squamous cell carcinoma (LSCC) using deep sequencing technology, and were analyzed by utilizing integrative computational approaches. A large number of protein-coding and non-coding genes were detected to be differentially expressed, indicating a functional switch in LSCC cells. A total of 127 mutated genes were detected to be significantly associated with ectoderm and epidermis development. Eleven …

Prioritizing Protein Complexes Implicated In Human Diseases By Network Optimization., Yong Chen, Thibault Jacquemin, Shuyan Zhang, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

BACKGROUND: The detection of associations between protein complexes and human inherited diseases is of great importance in understanding mechanisms of diseases. Dysfunctions of a protein complex are usually defined by its member disturbance and consequently result in certain diseases. Although individual disease proteins have been widely predicted, computational methods are still absent for systematically investigating disease-related protein complexes.

RESULTS: We propose a method, MAXCOM, for the prioritization of candidate protein complexes. MAXCOM performs a maximum information flow algorithm to optimize relationships between a query disease and candidate protein complexes through a heterogeneous network that is constructed by combining protein-protein interactions …

Integrating Human Omics Data To Prioritize Candidate Genes., Yong Chen, Xuebing Wu, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

BACKGROUND: The identification of genes involved in human complex diseases remains a great challenge in computational systems biology. Although methods have been developed to use disease phenotypic similarities with a protein-protein interaction network for the prioritization of candidate genes, other valuable omics data sources have been largely overlooked in these methods.

METHODS: With this understanding, we proposed a method called BRIDGE to prioritize candidate genes by integrating disease phenotypic similarities with such omics data as protein-protein interactions, gene sequence similarities, gene expression patterns, gene ontology annotations, and gene pathway memberships. BRIDGE utilizes a multiple regression model with lasso penalty to …

Identifying Potential Cancer Driver Genes By Genomic Data Integration., Yong Chen, Jingjing Hao, Wei Jiang, Tong He, Xuegong Zhang, Tao Jiang, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

Cancer is a genomic disease associated with a plethora of gene mutations resulting in a loss of control over vital cellular functions. Among these mutated genes, driver genes are defined as being causally linked to oncogenesis, while passenger genes are thought to be irrelevant for cancer development. With increasing numbers of large-scale genomic datasets available, integrating these genomic data to identify driver genes from aberration regions of cancer genomes becomes an important goal of cancer genome analysis and investigations into mechanisms responsible for cancer development. A computational method, MAXDRIVER, is proposed here to identify potential driver genes on the basis …

Detection And Quantification Of Methylation In Dna Using Solid-State Nanopores., Jiwook Shim, Gwendolyn I Humphreys, Bala Murali Venkatesan, Jan Marie Munz, Xueqing Zou, Chaitanya Sathe, Klaus Schulten, Farhad Kosari, Ann M Nardulli, George Vasmatzis, Rashid Bashir

Faculty Scholarship for the College of Science & Mathematics

Epigenetic modifications in eukaryotic genomes occur primarily in the form of 5-methylcytosine (5 mC). These modifications are heavily involved in transcriptional repression, gene regulation, development and the progression of diseases including cancer. We report a new single-molecule assay for the detection of DNA methylation using solid-state nanopores. Methylation is detected by selectively labeling methylation sites with MBD1 (MBD-1x) proteins, the complex inducing a 3 fold increase in ionic blockage current relative to unmethylated DNA. Furthermore, the discrimination of methylated and unmethylated DNA is demonstrated in the presence of only a single bound protein, thereby giving a resolution of a single …

The Proteomics Of Lipid Droplets: Structure, Dynamics, And Functions Of The Organelle Conserved From Bacteria To Humans., Li Yang, Yunfeng Ding, Yong Chen, Shuyan Zhang, Chaoxing Huo, Yang Wang, Jinhai Yu, Peng Zhang, Huimin Na, Huina Zhang, Yanbin Ma, Pingsheng Liu

Faculty Scholarship for the College of Science & Mathematics

Lipid droplets are cellular organelles that consists of a neutral lipid core covered by a monolayer of phospholipids and many proteins. They are thought to function in the storage, transport, and metabolism of lipids, in signaling, and as a specialized microenvironment for metabolism in most types of cells from prokaryotic to eukaryotic organisms. Lipid droplets have received a lot of attention in the last 10 years as they are linked to the progression of many metabolic diseases and hold great potential for the development of neutral lipid-derived products, such as biofuels, food supplements, hormones, and medicines. Proteomic analysis of lipid …

Uncover Disease Genes By Maximizing Information Flow In The Phenome-Interactome Network., Yong Chen, Tao Jiang, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

MOTIVATION: Pinpointing genes that underlie human inherited diseases among candidate genes in susceptibility genetic regions is the primary step towards the understanding of pathogenesis of diseases. Although several probabilistic models have been proposed to prioritize candidate genes using phenotype similarities and protein-protein interactions, no combinatorial approaches have been proposed in the literature.

RESULTS: We propose the first combinatorial approach for prioritizing candidate genes. We first construct a phenome-interactome network by integrating the given phenotype similarity profile, protein-protein interaction network and associations between diseases and genes. Then, we introduce a computational method called MAXIF to maximize the information flow in this …

Domainrbf: A Bayesian Regression Approach To The Prioritization Of Candidate Domains For Complex Diseases., Wangshu Zhang, Yong Chen, Fengzhu Sun, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

BACKGROUND: Domains are basic units of proteins, and thus exploring associations between protein domains and human inherited diseases will greatly improve our understanding of the pathogenesis of human complex diseases and further benefit the medical prevention, diagnosis and treatment of these diseases. Within a given domain-domain interaction network, we make the assumption that similarities of disease phenotypes can be explained using proximities of domains associated with such diseases. Based on this assumption, we propose a Bayesian regression approach named "domainRBF" (domain Rank with Bayes Factor) to prioritize candidate domains for human complex diseases.

RESULTS: Using a compiled dataset containing 1,614 …