Systems Biology Commons^™

Systems Network Analysis Of Protein Interaction Network (Pin) For Deducing Molecular Mechanistic Action Of Bap Induced Carcinogenesis, Anukriti ., Anupam Dhasmana, Uma Bhardwaj

Research Symposium

Background: Benzo[a]pyrene (BaP), a polycyclic aromatic hydrocarbon, has been placed in group 1 by IARC which indicates that it is a potential carcinogen to human beings. It has shown tumorigenic properties in approximately all animal model systems. In the current study, we have tried to identify the most probable biomolecular targets of BaP using systems biology approach.

Method: All the proteins that interact with BaP were extracted from T3DB. STRING-db was used to generate the Protein- protein interaction network (PPIN). Various apps of cytoscape software were used for network analysis, modulation and GO enrichment analysis. By developing biokinetic …

Leveraging Mass Spectrometry-Based Proteomics And Post-Translational Modifications For System-Wide Understanding Of Bioenergy Plants And Their Environment, Him K. Shrestha

Doctoral Dissertations

Bioenergy research focuses on utilizing renewable biomass feedstocks to produce biofuels and bioproducts to address growing concerns about energy security and climate change. To better understand the details of bioenergy crop production and conversion to bioproducts, it is essential to characterize bioenergy plants and their environments at a molecular systems level. Mass spectrometry has emerged as a promising technique for detailed proteomic information, including post-translational modifications (PTMs), of molecular processes and cellular functions of biological systems. In this dissertation, proteomic approaches have been optimized and implemented to deepen our understanding of the interaction of plants and their environment in a …

Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha

LSU Doctoral Dissertations

Schrenkiella parvula is an extremophyte model closely related to Arabidopsis thaliana and Brassica crops. Its natural habitat includes shores of saline lakes in the Irano-Turanian region. It has adapted to grow in soils rich in multiple salts including Na⁺ and K⁺. I have investigated the genetic basis for high K⁺ tolerance in plants using S. parvula as a stress tolerant model compared to the premier plant model, Arabidopsis thaliana which is highly sensitive to salt stresses using physiological, ionomic, transcriptomic, and metabolomic approaches. Under high K⁺ stress, root system architecture changes significantly compared to control …

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations & Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …

A Context-Forward In Vivo Functional Genomics Platform For Target Discovery And Establishing Vulnerability Context In Pancreatic Cancer, Johnathon Rose, Johnathon Lynn Rose

Dissertations & Theses (Open Access)

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a very poor patient prognosis (5-year survival of ≤ 7%). While transcriptional profiling has aided in the classification of this disease into at least two broader subtypes, this alone has so far been insufficient to inform on more nuanced patterns of oncogenic dependency. We hypothesized that a more comprehensive and granular characterization of PDAC disease diversity is required to establish relevant context for targeted therapy. To this end, we sought to establish an integrated platform to: i) more comprehensively characterize differential oncogenic signaling across our tumor models, and ii) establish …

Metabolic Network Analysis Of Filamentous Cyanobacteria, Daniel Alexis Norena-Caro

LSU Doctoral Dissertations

Cyanobacteria were the first organisms to use oxygenic photosynthesis, converting CO₂ into useful organic chemicals. However, the chemical industry has historically relied on fossil raw materials to produce organic precursors, which has contributed to global warming. Thus, cyanobacteria have emerged as sustainable stakeholders for biotechnological production. The filamentous cyanobacterium Anabaena sp. UTEX 2576 can metabolize multiple sources of Nitrogen and was studied as a platform for biotechnological production of high-value chemicals (i.e., pigments, antioxidants, vitamins and secondary metabolites). From a Chemical engineering perspective, the biomass generation in this organism was thoroughly studied by interpreting the cell as a microbial …

Metabolic Modeling Of Multispecies Microbial Biofilms, Poonam Phalak

Doctoral Dissertations

Biofilms are ubiquitous in medical, environmental, and engineered microbial systems. The majority of naturally occurring microbes grow as mixed species biofilms. These complicated biofilm consortia are comprised of many cell phenotypes with complex interactions and self-organized into three-dimensional structures. Approximately 2% of the US population suffers from non-healing chronic wounds infected by a combination of commensal and pathogenic bacteria whereas about 500,000 cases of Clostridium difficile infections (CDI) are reported annually. These polymicrobial infections are often resilient to antibiotic treatment due to the nutrient-rich environments and species interactions that promote community stability and robustness. This thesis focusses on developing metabolic …

Micom: Metagenome-Scale Modeling To Infer Metabolic Interactions In The Gut Microbiota., Christian Diener, Sean M Gibbons, Osbaldo Resendis-Antonio

Articles, Abstracts, and Reports

Compositional changes in the gut microbiota have been associated with a variety of medical conditions such as obesity, Crohn's disease, and diabetes. However, connecting microbial community composition to ecosystem function remains a challenge. Here, we introduce MICOM, a customizable metabolic model of the human gut microbiome. By using a heuristic optimization approach based on L2 regularization, we were able to obtain a unique set of realistic growth rates that corresponded well with observed replication rates. We integrated adjustable dietary and taxon abundance constraints to generate personalized metabolic models for individual metagenomic samples. We applied MICOM to a balanced cohort of …

Deciphering The Role Of Human Arylamine N-Acetyltransferase 1 (Nat1) In Breast Cancer Cell Metabolism Using A Systems Biology Approach., Samantha Marie Carlisle

Electronic Theses and Dissertations

Background: Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. NAT1 can additionally hydrolyze acetyl-coenzyme A (acetyl-CoA) in the absence of an arylamine substrate. NAT1 expression varies inter-individually and is elevated in several cancers including estrogen receptor positive (ER+) breast cancers. Additionally, multiple studies have shown the knockdown of NAT1, by both small molecule inhibition and siRNA methods, in breast cancer cells leads to decreased invasive ability and proliferation and decreased anchorage-independent colony formation. However, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear. Additionally, consequences …

Studying Egfr Signaling Through Single Molecule Imaging And Computational Modeling, Emanuel Salazar Cavazos

Biomedical Sciences ETDs

Signaling through the Epidermal Growth Factor Receptor (EGFR) plays an important role in both physiological and cancer-related processes. In this work, single-molecule microscopy measurements and computational modeling were closely integrated to better understand the mechanisms that regulate EGFR signaling. Technical improvements were made over the previously described Single-Molecule Pull-down (SiMPull) assay to facilitate direct detection of the phosphorylation state of thousands of individual receptors, and thereby estimate both the fraction of receptors phosphorylated at specific tyrosine residues and the frequency of multisite phosphorylation. These improvements enabled the first direct detection of multisite phosphorylation on full-length Epidermal Growth Factor Receptor (EGFR), …

Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande

KGI Theses and Dissertations

Huntington’s disease (HD) is a debilitating neurodegenerative disorder with a complex pathophysiology. Despite extensive studies to study the disease, the sequence of events through which mutant Huntingtin (mHtt) protein executes its action still remains elusive. The phenotype of HD is an outcome of numerous processes initiated by the mHtt protein along with other proteins that act as either suppressors or enhancers of the effects of mHtt protein and PolyQ aggregates. Utilizing an integrative systems biology approach, I construct and analyze a Huntington’s disease integrome using human orthologs of protein interactors of wild type and mHtt protein. Analysis of this integrome …

Systems Biology Approach To Late-Onset Alzheimer's Disease Genome-Wide Association Study Identifies Novel Candidate Genes Validated Using Brain Expression Data And Caenorhabditis Elegans Experiments, Shubhabrata Mukherjee, Joshua C. Russell, Daniel T. Carr, Jeremy D. Burgess, Mariet Allen, Daniel J. Serie, Kevin L. Boehme, John S. K. Kauwe, Adam C. Naj, David W. Fardo, Dennis W. Dickson, Thomas J. Montine, Nilufer Ertekin-Taner, Matt R. Kaeberlein, Paul K. Crane

Biostatistics Faculty Publications

Introduction—We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci.

Methods—We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions.

Results—We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ …

Acclimation, Adaptation, Traits And Trade-Offs In Plankton Functional Type Models: Reconciling Terminology For Biology And Modelling, Kevin J. Flynn, Michael St. John, John A. Raven, David O. F. Skibinski, J. Icarus Allen, Aditee Mitra, Eileen E. Hofmann

CCPO Publications

We propose definitions in terminology to enhance ongoing collaborations between biologists and modellers on plankton ecology. Organism "functional type" should refer to commonality in ecology not biogeochemistry; the latter is largely an emergent property of the former, while alignment with ecology is also consistent with usage in terrestrial science. Adaptation should be confined, as in genetics, to consideration of species inter-generational change; most so-called "adaptive" plankton models are thus acclimative, modifying vital rates in response to stimuli. Trait trade-off approaches should ideally only be considered for describing intra-generational interactions; in applications between generations, and certainly between unrelated species, such concepts …

Identification Of Yeast Cell Cycle Regulated Genes Based On Genomic Features, Chao Cheng, Yao Fu, Linsheng Shen, Mark Gerstein

Dartmouth Scholarship

Background: Time-course microarray experiments have been widely used to identify cell cycle regulated genes. However, the method is not effective for lowly expressed genes and is sensitive to experimental conditions. To complement microarray experiments, we propose a computational method to predict cell cycle regulated genes based on their genomic features – transcription factor binding and motif profiles.

Results: Through integrating gene-expression data with ChIP-chip binding and putative binding sites of transcription factors, our method shows high accuracy in discriminating yeast cell cycle regulated genes from non-cell cycle regulated ones. We predict 211 novel cell cycle regulated genes. Our model rediscovers …

Systems Biology Approaches To Probe Gene Regulation In Bacteria, Diogo F. Troggian Veiga

Dissertations & Theses (Open Access)

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb).

First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses …

Determining The Genotype-Phenotype Connection In Synthetic Inducible Gene Expression Systems, Rhys M. Adams

Dissertations & Theses (Open Access)

Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise.

Methods I created probabilistic …

Correlation Network Analysis For Data Integration And Biomarker Selection, Aram Adourian, Ezra Jennings, Raji Balasubramanian, Wade M. Hines, Doris Damian, Tom N. Plasterer, Clary B. Clish, Paul Stroobant, Robert N. Mcburney, Elwin R. Verheij, Ivana I. Bobeldijk, J Van Der Greef, J Lindberg, K Kenne, U Andersson, H Hellmold, K Nilsson, H Salter, I Schuppe-Koistinen

Raji Balasubramanian

This work demonstrates the application of correlation networks to a systems-based investigation of drug-induced hepatotoxicity and the identification of specific and relevant biomarkers in this context.

The Hyperthermophilic Archaeon Sulfolobus: From Exploration To Exploitation, Stan J.J. Brouns, Thijs J.G. Ettema, Kenneth M. Stedman, Jasper Walther, Hauke Smith, Ambrosius P.L. Snijders, Mark Young, Rolf Bernander, Phillip C. Wright, Betina Siebers, John Van Der Oost

Biology Faculty Publications and Presentations

In the early 1970s, Sulfolobus was first isolated by Thomas Brock and co-workers from sulfur-rich acidic hot springs in Yellowstone National Park. Sulfolobus became one of the model organisms of Archaea in general, and of Crenarchaea in particular. Many of its unusual physiological characteristics have been investigated, and several of its thermostable enzymes have been studied in considerable detail. For fundamental reasons, and because of its potential for industrial applications, Sulfolobus has been selected for a genome sequence project. The recent completion of the Sulfolobus solfataricus genome has set the stage for a series of postgenome research lines that will …