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The Trnaval Half: A Strong Endogenous Toll-Like Receptor 7 Ligand With A 5′-Terminal Universal Sequence Signature, Kamlesh Ganesh Pawar, Takuya Kawamura, Yohei Kirino

Computational Medicine Center Faculty Papers

Toll-like receptors (TLRs) are crucial components of the innate immune system. Endosomal TLR7 recognizes single-stranded RNAs, yet its endogenous ssRNA ligands are not fully understood. We previously showed that extracellular (ex-) 5'-half molecules of tRNA^HisGUG (the 5'-tRNA^HisGUG half) in extracellular vesicles (EVs) of human macrophages activate TLR7 when delivered into endosomes of recipient macrophages. Here, we fully explored immunostimulatory ex-5'-tRNA half molecules and identified the 5'-tRNA^ValCAC/AAC half, the most abundant tRNA-derived RNA in macrophage EVs, as another 5'-tRNA half molecule with strong TLR7 activation capacity. Levels of the ex-5'-tRNA^ValCAC/AAC half were highly up-regulated in macrophage EVs …

Integrated Transcriptomics And Histopathology Approach Identifies A Subset Of Rejected Donor Livers With Potential Suitability For Transplantation, Ankita Srivastava, Alexandra Manchel, John Waters, Manju Ambelil, Benjamin K. Barnhart, Jan B. Hoek, Ashesh P. Shah, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

BACKGROUND: Liver transplantation is an effective treatment for liver failure. There is a large unmet demand, even as not all donated livers are transplanted. The clinical selection criteria for donor livers based on histopathological evaluation and liver function tests are variable. We integrated transcriptomics and histopathology to characterize donor liver biopsies obtained at the time of organ recovery. We performed RNA sequencing as well as manual and artificial intelligence-based histopathology (10 accepted and 21 rejected for transplantation).

RESULTS: We identified two transcriptomically distinct rejected subsets (termed rejected-1 and rejected-2), where rejected-2 exhibited a near-complete transcriptomic overlap with the accepted livers, …

The Typical Trna Co-Expresses Multiple 5' Trna Halves Whose Sequences And Abundances Depend On Isodecoder And Isoacceptor And Change With Tissue Type, Cell Type, And Disease, Robert Akins, Kayleigh Ostberg, Tess Cherlin, Nikolas Tsiouplis, Phillipe Loher, Isidore Rigoutsos

Computational Medicine Center Faculty Papers

Transfer RNA-derived fragments (tRFs) are noncoding RNAs that arise from either mature transfer RNAs (tRNAs) or their precursors. One important category of tRFs comprises the tRNA halves, which are generated through cleavage at the anticodon. A given tRNA typically gives rise to several co-expressed 5'-tRNA halves (5'-tRHs) that differ in the location of their 3' ends. These 5'-tRHs, even though distinct, have traditionally been treated as indistinguishable from one another due to their near-identical sequences and lengths. We focused on co-expressed 5'-tRHs that arise from the same tRNA and systematically examined their exact sequences and abundances across 10 different human …

Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone

Complex Biosystems PhD Program: Dissertations

The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …

The Role Of Non-Coding Rnas In Myelodysplastic Neoplasms, Vasileios Georgoulis, Epameinondas Koumpis, Eleftheria Hatzimichael

Computational Medicine Center Faculty Papers

Myelodysplastic syndromes or neoplasms (MDS) are a heterogeneous group of myeloid clonal disorders characterized by peripheral blood cytopenias, blood and marrow cell dysplasia, and increased risk of evolution to acute myeloid leukemia (AML). Non-coding RNAs, especially microRNAs and long non-coding RNAs, serve as regulators of normal and malignant hematopoiesis and have been implicated in carcinogenesis. This review presents a comprehensive summary of the biology and role of non-coding RNAs, including the less studied circRNA, siRNA, piRNA, and snoRNA as potential prognostic and/or predictive biomarkers or therapeutic targets in MDS.

Exploring The Interactions Between Sars-Cov-2 And Host Proteins., Sojan Shrestha

School of Biological Sciences: Dissertations, Theses, and Student Research

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current pandemic, Coronavirus Disease 2019 (COVID-19). SARS-CoV-2 is considered to be of zoonotic origin; it originated in non-human animals and was transmitted to humans. Since the early stage of the pandemic, however, the evidence of transmissions from humans to animals (reverse zoonoses) has been found in multiple animal species including mink, white-tailed deer, and pet and zoo animals. Furthermore, secondary zoonotic events of SARS-CoV-2, transmissions from animals to humans, have been also reported. It is suggested that non-human hosts can act as SARS-CoV-2 reservoirs where accumulated …

Soil Microbial Community Composition Of White Oak Mountain, Tennessee, Matthew Gano, Timothy D. Trott

Research in Biology

Abstract - Soil microbial communities are responsible for nutrient cycling in terrestrial ecosystems and have symbiotic and parasitic relationships with the plant community. However, little is known about the factors that determine the soil microbial community composition. In this study we examined how spring wildflower diversity and geographical factors influence the soil microbial community composition of the second growth oak hickory forests of White Oak Mountain in Southeast Tennessee. The characterization of the soil microbial community was completed with 16S/18S/ITS rDNA amplicon sequencing of total DNA extracted from soil samples that were normalized for each sample plot. Here we characterize …

Prediction Of Kinase-Substrate Associations Using The Functional Landscape Of Kinases And Phosphorylation Sites, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark R. Chance, Mehmet Koyutürk

Faculty Scholarship

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships …

A Single-Cell Atlas Of Bovine Skeletal Muscle Reveals Mechanisms Regulating Intramuscular Adipogenesis And Fibrogenesis, Leshan Wang, Peidong Gao, Chaoyang Li, Qianglin Liu, Zeyang Yao, Yuxia Li, Xujia Zhang, Jiangwen Sun, Constantine Simintiras, Matthew Welborn, Kenneth Mcmillin, Stephanie Oprescu, Shihuan Kuang, Xing Fu

Computer Science Faculty Publications

Background

Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis.

Methods

Skeletal muscle single-cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell-cell communication analysis, were performed to elucidate …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Dfhic: A Dilated Full Convolution Model To Enhance The Resolution Of Hi-C Data, Bin Wang, Kun Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Hi-C technology has been the most widely used chromosome conformation capture(3C) experiment that measures the frequency of all paired interactions in the entire genome, which is a powerful tool for studying the 3D structure of the genome. The fineness of the constructed genome structure depends on the resolution of Hi-C data. However, due to the fact that high-resolution Hi-C data require deep sequencing and thus high experimental cost, most available Hi-C data are in low-resolution. Hence, it is essential to enhance the quality of Hi-C data by developing the effective computational methods.

Results: In this work, we propose …

Intergenic Transcription In In Vivo Developed Bovine Oocytes And Pre-Implantation Embryos, Saurav Ranjitkar, Mohammad Shiri, Jiangwen Sun, Xiuchun Tian

Computer Science Faculty Publications

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and …

Cellbrf: A Feature Selection Method For Single-Cell Clustering Using Cell Balance And Random Forest, Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang

Computer Science Faculty Publications

Motivation

Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. Results

We develop CellBRF, a feature selection method that considers genes’ relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating …

Adjusting For Gene-Specific Covariates To Improve Rna-Seq Analysis, Hyeongseon Jeon, Kyu-Sang Lim, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

Summary

This paper suggests a novel positive false discovery rate (pFDR) controlling method for testing gene-specific hypotheses using a gene-specific covariate variable, such as gene length. We suppose the null probability depends on the covariate variable. In this context, we propose a rejection rule that accounts for heterogeneity among tests by employing two distinct types of null probabilities. We establish a pFDR estimator for a given rejection rule by following Storey's q-value framework. A condition on a type 1 error posterior probability is provided that equivalently characterizes our rejection rule. We also present a suitable procedure for selecting a tuning …

A Computational Analysis Of Hybrid Genome Assembly Strategies, Joseph Walewski

Computer Science Honors Papers

The central dogma of molecular biology states that DNA is transcribed to RNA and then translated into proteins. Since DNA is the starting material for many of biology’s macromolecules, it has been referred to as “nature’s instruction book.” The sum of all DNA in a cell is referred to as the genome, and genome sequencing is how we interpret the DNA.

Due to limitations on currently available technology, it is not possible to retrieve the entire genome in one contiguous set of data. Therefore, genome sequencing is a computer science problem as sequencing “reads” must be stitched together to obtain …

Deciphering The Genetic Architecture Of Key Female Floral Traits For Hybrid Wheat Seed Production, Juan Jimenez

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Wheat (Triticum aestivum L.) is a staple cereal that provides 20% of the calories and proteins in human intake (Ray et al., 2013). Global population is projected to increase to 9.7 billion by 2050. Food production must increase by 70% to feed this future population. Wheat production is in crisis due to political and environmental challenges and is projected to decline by 0.8% in 2022 (FAO, 2022). To ensure food security yield genetic gain must increase by around 1.4% annually. Taking advantage of heterosis, hybrid wheat has the potential to boost grain yield. However, hybrid wheat seed production systems …

Sequence-Based Bioinformatics Approaches To Predict Virus-Host Relationships In Archaea And Eukaryotes, Yingshan Li

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Viral metagenomics is independent of lab culturing and capable of investigating viromes of virtually any given environmental niches. While numerous sequences of viral genomes have been assembled from metagenomic studies over the past years, the natural hosts for the majority of these viral contigs have not been determined. Different computational approaches have been developed to predict hosts of bacteria phages. Nevertheless, little progress has been made in the virus-host prediction, especially for viruses that infect eukaryotes and archaea. In this study, by analyzing all documented viruses with known eukaryotic and archaeal hosts, we assessed the predictive power of four computational …

Radiation Exposure Determination In A Secure, Cloud-Based Online Environment, Ben C. Shirley, Eliseos J. Mucaki, Peter Rogan

Biochemistry Publications

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI …

Tree To Tree: Phylogenetics Of Diverse Anura Using Portable Lab Equipment: Primer Optimization, Bioinformatic Pipeline, And Phylogenetic Analyses Reveal Potential New Species And Ability To Identify Evolutionary Relationships In A Hyper Diverse Anura Clade Using Nanopore Sequencing, Elinor Sterner

Independent Study Project (ISP) Collection

The Corredor Llanganates-Sangay is an extremely significant region for conservation, coined a “gift to the earth” by the World Wildlife Fund. Understanding amphibians species and populations is key due to their roles as hyper sensitive bioindicators. In recent years, portable sequencing equipment (Mini PCR thermocyclers, Oxford Nanopore Technology’s MinION sequencer, etc) make genetic data collection in remote areas possible, greatly increasing potential for conservation genetics and genomics. This study uses portable equipment to sequence two mitochondrial loci in 104 Anuran samples collected in four sites in the Corridor and presents phylogenies of each gene as well as a concatenated phylogeny. …

Patient-Specific Genome-Scale Metabolic Models For Individualized Predictions Of Liver Disease, Alexandra Manchel, Jan B. Hoek, Ramon Bataller, Radhakrishnan Mahadevan, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

The prevalence of liver disease is steadily increasing, coupled with the limited availability of therapeutic treatments. Recent literature points to metabolic reprogramming as a key feature of liver failure. Hence, we sought to uncover the metabolic pathways and mechanisms associated with liver disease and acute liver failure. We generated patient-specific genome scale metabolic models by integrating RNA-seq data from patient liver samples with a generalized human metabolic model. Flux balance analysis simulations showed a distinct separation of non-alcohol associated and alcohol-associated disease states. Our analysis suggests that the alcohol associated liver has an increased flux through nucleotide and glycerophospholipid metabolic …

Statistical Genetic Discoveries Using Restricted Maximum Likelihood Method, Erika Wu

2022 REYES Proceedings

In statistical genetics, genetic association and genomic prediction become more successful with a highly heritable trait. Identifying highly heritable components of a complex disease can thus advance scientific understanding of the disease and potentially lead to effective prevention and treatments. Using Matlab and existing large-scale genome datasets, we evaluate a restricted maximum likelihood approach to identify highly heritable components of a complex disease as a function of multiple clinical variables.

Insights To Protein Pathogenicity From The Lens Of Protein Evolution, Janelle Nunez-Castilla

FIU Electronic Theses and Dissertations

As protein sequences evolve, differences in selective constraints may lead to outcomes ranging from sequence conservation to structural and functional divergence. Evolutionary protein family analysis can illuminate which protein regions are likely to diverge or remain conserved in sequence, structure, and function. Moreover, nonsynonymous mutations in pathogens may result in the emergence of protein regions that affect the behavior of pathogenic proteins within a host and host response. I aimed to gain insight on pathogenic proteins from cancer and viruses using an evolutionary perspective. First, I examined p53, a conformationally flexible, multifunctional protein mutated in ~50% of human cancers. Multifunctional …

In Silico Characterization Of Protein-Protein Interactions Mediated By Short Linear Motifs, Heidy Elkhaligy

FIU Electronic Theses and Dissertations

Short linear motifs (SLiMs), often found in intrinsically disordered regions (IDPs), can initiate protein-protein interactions in eukaryotes. Although pathogens tend to have less disorder than eukaryotes, their proteins alter host cellular function through molecular mimicry of SLiMs. The first objective was to study sequence-based structure properties of viral SLiMs in the ELM database and the conservation of selected viral motifs involved in the virus life cycle. The second objective was to compare the structural features for SliMs in pathogens and eukaryotes in the ELM database. Our analysis showed that many viral SliMs are not found in IDPs, particularly glycosylation motifs. …

Alterations Of The Gut Mycobiome In Patients With Ms - A Bioinformatic Approach, Saumya Shah

Honors Scholar Theses

The mycobiome is the fungal component of the gut microbiome and is implicated in several autoimmune diseases. However, its role in multiple sclerosis (MS) has not been studied. We performed descriptive and formal statistical tests using the R language to characterize the gut mycobiome in people with MS (pwMS) and healthy controls. We found that the microbiome composition of multiple sclerosis patients is different from healthy people. The mycobiome had significantly higher alpha diversity and inter-subject variation in pwMS than controls. Additionally, Saccharomyces and Aspergillus were over-represented in pwMS. Different mycobiome profiles, defined as mycotypes, were associated with different bacterial …

Comparative Analyses Of De Novo Transcriptome Assembly Pipelines For Diploid Wheat, Natasha Pavlovikj

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Gene expression and transcriptome analysis are currently one of the main focuses of research for a great number of scientists. However, the assembly of raw sequence data to obtain a draft transcriptome of an organism is a complex multi-stage process usually composed of pre-processing, assembling, and post-processing. Each of these stages includes multiple steps such as data cleaning, error correction and assembly validation. Different combinations of steps, as well as different computational methods for the same step, generate transcriptome assemblies with different accuracy. Thus, using a combination that generates more accurate assemblies is crucial for any novel biological discoveries. Implementing …

Genomic Analysis Of Metabolic Differences Found In Clostridium Perfringens That Cause Necrotic Enteritis In Poultry, Connor Aylor

School of Veterinary and Biomedical Sciences: Dissertations, Theses, and Student Research

Clostridium perfringens is a common member of gut microbiota in healthy animals, but can also be an important pathogen in human and veterinary medicine. It produces several protein toxins that contribute to both histotoxic and enteric diseases in animals. Necrotic enteritis in poultry has been associated with the NetB toxin of C. perfringens; however, this toxin alone is insufficient to cause disease in infected chickens. While considerable research has focused on the presence of toxins and virulence factors, little has been done to assess the function of metabolic factors on the ability of the bacteria to cause disease. In …

Using Machine Learning To Recognize Chronic Rhinosinusitis, Irene Liu '23

Student Publications & Research

Chronic Rhinosinusitis (CRS) is a nasal disease characterized by the inflammation of the mucosa and paranasal sinuses with a duration of at least 12 consecutive weeks. So, to diagnose CRS, one needs to keep a record of their symptoms for ~12 weeks before they are recommended to get a tomography which will allow physicians to classify them as a patient with CRS or without. This is a timely and costly process; thus, machine learning should be used to speed the process up. Since patients with CRS have more obstructed noses, the sound produced should be different than an individual without …

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

The Low Abundance Of Cpg In The Sars-Cov-2 Genome Is Not An Evolutionarily Signature Of Zap, Ali Afrasiabi, Hamid Alinejad-Rokny, Azad Khosh, Mostafa Rahnama, Nigel Lovell, Zhenming Xu, Diako Ebrahimi

Plant Pathology Faculty Publications

The zinc finger antiviral protein (ZAP) is known to restrict viral replication by binding to the CpG rich regions of viral RNA, and subsequently inducing viral RNA degradation. This enzyme has recently been shown to be capable of restricting SARS-CoV-2. These data have led to the hypothesis that the low abundance of CpG in the SARS-CoV-2 genome is due to an evolutionary pressure exerted by the host ZAP. To investigate this hypothesis, we performed a detailed analysis of many coronavirus sequences and ZAP RNA binding preference data. Our analyses showed neither evidence for an evolutionary pressure acting specifically on CpG …

Completing Single-Cell Dna Methylome Profiles Via Transfer Learning Together With Kl-Divergence, Sanjeeva Dodlapati, Zongliang Jiang, Jiangwen Sun

Computer Science Faculty Publications

The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with …