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Item Microbial adaptation to cultivation stress using storage compounds(Montana State University - Bozeman, College of Agriculture, 2022) Arnold, Adrienne Dale; Chairperson, Graduate Committee: Ross Carlson; This is a manuscript style paper that includes co-authored chapters.Methanotrophs and green algae are microorganisms that grow on single carbon substrates. Methanotrophs are bacteria that use methane as their carbon source, and green algae are eukaryotic phototrophs that grow on CO 2. They are of interest both as primary producers in the environment and as biological catalysts for the conversion of greenhouse gases into value-added compounds. Understanding how methanotrophs and green algae adapt to cultivation stresses is key to understanding carbon cycling in the environment and in industrial settings. This work uses stoichiometric metabolic modeling to investigate the role of carbon storage compounds in the metabolism of C1-utilizing organisms. Storage compounds are accumulated as intracellular reserves of polysaccharides or lipids, which can be catabolized under stress conditions to provide carbon and energy to the cell. Catabolism of carbon storage compounds often results in the excretion of multi-carbon organic compounds that can be utilized as carbon substrates by other members of the microbial community. In silico metabolic models were developed for methanotroph and algal systems and used to examine the breakdown of storage compounds in response to common cultivation stresses. For the aerobic methanotrophs, predictions focused on the use of polyhydroxybutyrate and glycogen in adaptation to O 2 limitation. For the green algae, starch and triacylglycerol reserves are analyzed as sources for compatible solutes, which are produced by cells in response to high salinity conditions. Metabolic modeling of storage compound utilization by methanotrophs and algae helps elucidate the role of these organisms as primary producers and presents an opportunity for industrial production of multi-carbon compounds from single carbon substrates.Item An omics-based interrogation of disparate microbial systems: multi-omics analysis of a bio-mining archaeon and the effects of arsenic on the E. coli Lipidome(Montana State University - Bozeman, College of Letters & Science, 2023) Fausset, Hunter Lee; Chairperson, Graduate Committee: Brian Bothner; This is a manuscript style paper that includes co-authored chapters.Systems biology represents the next frontier in the elucidation of biochemical mechanisms, disease states, and microorganisms. Rather than approaching individual parts of an organism, such as a specific protein, molecule, or mRNA, a systems biology or "omics" investigation seeks to characterize all proteins, molecules, or RNA simultaneously. This is crucial, because all macromolecules in a lifeform exist in dynamic equilibria with those around them; no one biological process occurs in a vacuum. Omics investigations have ballooned in usage over the last decades due to scientists realizing their power in characterizing complex biological phenomena. This has also been spurred on by advances in technologies enabling the robust elucidation of thousands of molecules at once, particularly benefitting from the modernization of mass spectrometry. This technique can be used to study any number of biological problems including those presented here; a multi-omics investigation into a mineral- eating methanogen and a lipidomic characterization of arsenic exposure in a key member of the gut microbiome, E.coli. Methanosarcina barkeri, a widespread methanogen found in marine sediments, is able to reductively dissolve minerals such as pyrite (FeS2) to satisfy their iron and sulfur requirements. Presented here are two investigations containing transcriptomic, proteomic, metabolomic, and lipidomic analyses, performed in parallel on the same biomass. Together, these experiments suggest that the organism undergoes a significant phenotypic shift in response to changes in just two elements, Fe and S. Overall inferences are echoed in the small molecule analyses; the metabolomes and lipidome of the organism change similarly in to the proteome. Key sulfur equilibria are implied in the process, as are specific lipids, choline, and dethiobiotin. A similar approach was applied to E.coli treated with arsenic, as a proxy for understanding the detoxifcation that takes place in the gut microbiome after ingestion. Marked lipidomic changes were observed in E.coli resulting from treatment, which were dependent both on species of arsenic as well as presence of the Ars operon. As a foundational study, this work answered some and generated many more hypotheses on the biochemical fate of As in microorganisms in the gut microbiome.Item The relationship between physiological stress response and variation in omics data(Montana State University - Bozeman, College of Letters & Science, 2021) Steward, Katherine Fay; Chairperson, Graduate Committee: Brian Bothner; This is a manuscript style paper that includes co-authored chapters.Omics analysis is the cornerstone of systems biology. It offers comprehensive assessments of stress, interaction networks and connections to phenotype. Defining a stressed phenotype can be challenging, however, as stress response mechanisms can arise from a range of environmental conditions and experimental perturbations. Previous work from our lab noted the possibility of a relationship between stress in omics data and the variation of that data. This connection has yet to be clearly defined, and the cellular mechanisms responsible for the canalization of omics data remain a mystery. In this work I have taken advantage of the sensitivity of metabolomics and proteomics to detect cellular stress and characterize its relationship to variation. By utilizing coefficient of variation (CV) as a statistic of merit, the depth of the relationship between stress and variation can be uncovered. Once the model was clearly defined, a proteomics dataset with a large proportion of protein coverage was utilized to investigate what pathways might be responsible for the metabolite and protein canalization.Item Analysis of complex samples by mass spectrometry leads to insights into system dynamics(Montana State University - Bozeman, College of Letters & Science, 2021) Peach, Jesse Thomas; Chairperson, Graduate Committee: Brian Bothner; James Larson, Sutton Kanta, Eric Boltinghouse, Rebecca Mueller, Ganesh Balasubramanian, Mohammed Refai, Brent Peyton and Brian Bothner were co-authors of the article, 'Optimization of thermal small molecule and protein mass spectrometry analysis' submitted to the journal 'Analytical biochemistry' which is contained within this dissertation.; Rebecca Mueller, Dana Skorupa, Margaux Mesle, Sutton Kanta, Eric Boltinghouse, Bailey Sharon, Valerie Copie, Brian Bothner and Brent Peyton were co-authors of the article, 'Longitudinal meta-analysis of the Five Sisters Hot Springs in Yellowstone National Park reveals a dynamic thermoalkaline environment' submitted to the journal 'Environmental microbiology' which is contained within this dissertation.; Stephanie M. Wilson, Logan D. Gunderson, Lizzi Frothingham, Tan Tran, Seth T. Walk, Carl J. Yeoman, Brian Bothner and Mary P. Miles were co-authors of the article, 'Temporal metabolic response yields a dynamic biosignature of inflammation' submitted to the journal 'iScience' which is contained within this dissertation.Systems biology offers a holistic approach to biological science. In its most complete form, systems biology requires comprehensive data encompassing all of the parts or molecules across a set of hierarchical networks. To obtain and analyze the comprehensive and large datasets required for systems biology analysis, biologists have taken advantage of new technology and computational tools. Over the last few decades, advances in computational modeling and analysis technology has dramatically increased the efficacy of systems biology and the understanding of the natural world. However, systems biology is still an emerging discipline. The overwhelming scale of potential biological data that has yet to be described, coupled with interpretation and application obstacles, leaves much work to be accomplished. One aspect of systems biology that needs development is the interpretation and analysis of temporal biological data. Temporal data reveals more about biological phenomena than static data as biology is inherently dynamic. This dissertation explores the benefits of temporal profiling of complex samples to make time-resolved conclusions about complicated biological questions. Three research projects are the backbone of this document, with a chapter being devoted to each. Chapter 2 describes the development of a comprehensive method for extraction and mass spectrometry analysis of several different fractions from hot spring sediment. Chapter 3 delves into a multi-omics analysis tracking changes over the course of three years in a thermoalkaline spring system in Yellowstone National Park. It defines how specific extracellular small molecules correlate with microbial fitness. Specifically, how unique nitrogen and sulfur containing molecules in the sediment drive archaeal abundance and diversity. The final chapter introduces the concept of a 'dynamic biosignature', a set of metabolites that have similar responses to known biomarkers, in this case pro-inflammatory cytokines. A cohort of metabolites was identified that provided mechanistic insight into the inflammatory response. Overall, this dissertation provides examples of systems biology analysis and provides evidence that static, single time-point datasets fail to capture that which is the essence of biology - change.Item The stoichiometry of nutrient and energy transfer: from organelles to organisms(Montana State University - Bozeman, College of Engineering, 2016) Hunt, Kristopher Allen; Chairperson, Graduate Committee: Ross Carlson; James P. Folsom, Reed L. Taffs and Ross P. Carlson were co-authors of the article, 'Complete enumeration of elementary flux modes through scalable, demand-based subnetwork definition' in the journal 'Bioinformatics' which is contained within this thesis.; Ashley E. Beck was an author and Hans C. Bernstein and Ross P. Carlson were co-authors of the article, 'Interpreting and designing microbial communities for bioprocess applications, from components to interactions to emergent properties' in the journal 'Biotechnology for biofuel production and optimization' which is contained within this thesis.; Ryan deM. Jennings, William P. Inskeep and Ross P. Carlson were co-authors of the article, 'Stoichiometric modeling of assimilatory and dissimilatory biomass utilization in a microbial community' in the journal 'Environmental microbiology' which is contained within this thesis.; Ryan deM. Jennings, William P. Inskeep and Ross P. Carlson were co-authors of the article, 'Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community' submitted to the journal 'The International Society for Microbial Ecology journal' which is contained within this thesis.; Natasha D. Mallette, Brent M. Peyton and Ross P. Carlson were co-authors of the article, 'Theoretical and practical limitations of hydrocarbon production for a cellulolytic, endophytic filamentous fungus' submitted to the journal 'Metabolic engineering' which is contained within this thesis.All life requires the acquisition and transformation of nutrients and energy, driving processes from cellular nutrient flow to planetary biogeochemical cycling. However, the organisms and communities responsible for these processes are often uncultivable and too complex to observe directly and understand. Stoichiometric modeling, a systems biology approach, analyzes the reactions in an organism and incorporates data from multiple sources to extract biologically meaningful parameters, such as theoretical limits of conversion and yields of a metabolism. These limits and yields quantify relationships between organisms to establish governing principles, from resource requirements to community productivity as a function of population composition. The presented work expanded the stoichiometric modeling algorithm and identified fundamental principles that govern nutrient and energy transfer associated with heterotrophy, community composition, and intracellular compartmentalization. A scalable routine capable of analyzing complex metabolic networks by dividing them into tractable subnetworks was demonstrated for a eukaryotic diatom. The metabolic model contained approximately two billion routes through the network and established an international benchmark for elementary flux mode analysis. Additionally, a heterotrophic archaeon was examined for the resource requirements while consuming 29 different forms of biomass derived dissolved organic carbon. These resource requirements and limitations establish a basis to analyze heterotrophy with regard to the limiting nutrient in a variety of systems. The resulting resource requirements of heterotrophy were incorporated into a community where an iron oxidizing autotroph was hypothesized to be the primary source of carbon and energy. Analysis of the community model and in situ measurements of iron and oxygen utilization indicated additional electron donors were required to account for the observed acquisition of nutrients in some communities. Finally, limits and resource requirements for fungal production of hydrocarbons were identified as a function of carbon and energy partitioning using simulated genetic modifications, providing context regarding endophytic production of bioactive molecules for host resistance as well as endophyte capacity as a petroleum producing alternative.Item Development of a protein-based sensor assay for rapid classification of complex biological samples(Montana State University - Bozeman, College of Letters & Science, 2016) Hamerly, Timothy Kyle; Chairperson, Graduate Committee: Brian Bothner; Joshua Heinemann, Monika Tokmina-Lukaszewska, Elizabeth R. Lusczek, Kristine E. Mulier, Greg J. Beilman and Brian Bothner were co-authors of the article, 'Bovine serum albumin as a molecular sensor for the discrimmination of complex metabolite samples' in the journal 'Analytica chemica acta' which is contained within this dissertation.; Brian Bothner was a co-author of the article, 'Adding metrics to the aging of whiskey using a protein sensor assay' which is contained within this dissertation.; Brian Bothner was a co-author of the article, 'Analysis of wine using the protein sensor assay' which is contained within this dissertation.; Brian Bothner was a co-author of the article, 'Investigations into the use of a protein sensor assay for metabolite analysis' in the journal 'Applied biochemistry and biotechnology' which is contained within this dissertation.Metabolomics, one of the core 'omics' fields within the umbrella of systems biology, is the study of the small molecules which can be used to characterize the state of an organism. Metabolites are constantly being transformed inside a cell in direct response to stimuli around them. This makes the metabolome the most dynamic of all the omics fields and is considered to be a direct readout of the cells state at any given time. Although highly informative, the metabolome is inherently difficult to study, with thousands of known metabolites, any of which could be important for classifying a cell into a healthy or diseased state. Techniques such as mass spectrometry are well suited to study the metabolome and have been used to successfully classify cells by identify markers for a given disease state. However, current methods require lengthy analysis times due in part to the complexity of the metabolome. The research presented in this dissertation highlights a new and promising methodology which improves classification and speeds marker discovery. Making use of a protein found in animals which has evolved to selectively bind metabolites, an assay was developed which better classified samples compared to current methods used in the field of metabolomics. This improved classification was achieved with an overall decrease in analysis time. The implementation of this method in the study of complex biological systems would have an immediate impact in academic and medical research.Item Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective(Montana State University - Bozeman, College of Letters & Science, 2014) Heinemann, Joshua Vance; Chairperson, Graduate Committee: Brian Bothner; Walid S. Maaty, George Gauss, Narahari Akkaladevi, Susan K. Brumfield, Vamseedhar Rayaprolu, Mark Young, C. Martin Lawrence and Brian Bothner were co-authors of the article, 'Fossil record of an HK-97-like provirus' in the journal 'Virology' which is contained within this thesis.; Timothy Hamerly, Walid S. Maaty, Navid Movahed, Joseph D. Steffens, Benjamin D. Reeves, Jonathan K. Hilmer, Jesse Therien, Paul A. Grieco, John W. Peters and Brian Bothner were co-authors of the article, 'Expanding the paradigm of thiol redox in the thermophilic root of life' in the journal 'Biochimica et biophysica acta' which is contained within this thesis.; Aurélien Mazurie, Monika Tokmina-Lukaszewska, Greg J. Beilman and Brian Bothner were co-authors of the article, 'Application of support vector machines to metabolomics experiments with limited replicates' in the journal 'Metabolomics' which is contained within this thesis.; Brigit Noon, Mohammad J. Mohigmi, Aurélien Mazurie, David L. Dickensheets and Brian Bothner were co-authors of the article, 'Real-time digitization of metabolomic patterns from a living system using mass spectrometry' submitted to the journal 'Journal of the American Chemical Society' which is contained within this thesis.One of the goals of systems biology is to develop a model which encapsulates the molecular, structural and temporal complexity of a living organism. While modern omics experiments can deliver a high resolution view of an organism's molecular complexity, methods for correlating the information from multiple biomolecular systems (i.e. genes, proteins and metabolites) and their changes over time remain greatly underdeveloped. Presented in this research are: (1) methods for understanding the inter-relation of multiple biomolecular systems correlating genomics, proteomics and metabolomics experiments; (2) techniques for machine learning based metabolic biomarker selection; (3) robotics technology for real-time measurement of changes in metabolism. The methods for correlating information from multiple biomolecular systems have provided a new perspective of biomolecular adaptation and evolutionary relationships in the thermophilic archaea. The techniques for biomarker selection have provided a method to assess the reliability of biomarkers in experiments where limited samples are available. The new technology has provided an engineered system for automated analysis of metabolic patterns and how they change over time. Together, these results have created a framework for future improvement of our understanding of biology through the use of molecular biology, machine learning and robotics.Item Toward resolving the human neocortex epileptic proteome(Montana State University - Bozeman, College of Letters & Science, 2013) Keren-Aviram, Gal; Chairperson, Graduate Committee: Edward DratzEpilepsy is a common and often devastating neurological disorder, which is not well understood at the molecular level. Exactly why some brain regions produce epileptic discharges and others do not is not known. Patients who fail to respond to antiseizure medication can benefit from surgical removal of brain regions that produce epileptic activities. The tissue removed in these surgeries offers an invaluable resource to uncover the molecular and cellular basis of human epilepsy. Here, we report a proteomic study, as part of a Systems Biology of Epilepsy Project, which utilizes in vivo electrophysiologically-characterized human brain samples from the neocortex of 6 patients with refractory epilepsy, to determine whether there are common proteomic patterns in human brain regions that produce epileptic discharges. This study is unique in that comparison of protein expression was made within same patient, between nearby epileptic and non-epileptic (or less epileptic) brain regions, as defined by their interictal (between seizure) spike frequencies. Protein spots were resolved from three subcellular fractions, using two-dimensional differential-in-gel-electrophoresis, revealing 31 spots that changed significantly and were identified by liquid-chromatography tandem mass-spectrometry. Interestingly, glial fibrillary acidic protein was found to be consistently down regulated in high spiking brain tissue and glial fibrillary acidic protein levels showed strong negative correlation with spiking frequency. We next developed a two-step analysis method to select for frequently changing spots among the patients and identified 397 of those proteins. Spots of interest were clustered by protein expression patterns across all samples. This analysis predicted proteomic changes due to both histological differences and molecular pathways by examination of gene ontology clusters. Our experimental design and proteomic data analysis predicts novel glial and vascular changes and changes in cytoskeleton and neuronal projections that provide new insights into the structural and functional basis of neocortical epilepsy.Item Proteomic and systems biology analysis of the response of monocytes to infection by Coxiella burnetii and exposure to innate immune adjuvants(Montana State University - Bozeman, College of Letters & Science, 2010) Shipman, Matthew Richard; Chairperson, Graduate Committee: Edward Dratz.Coxiella burnetii is an obligate intracellular pathogen that infects human monocytes, specifically inhabiting the phagolysosome. C. burnetii is a potential bioterror agent and is classified by the National Institute for Allergies and Infectious Diseases (NIAID) as a category B pathogen. This bacterium is remarkably infectious, requiring as little as one bacterium to cause infection. We used phase II C. burnetii, an avirulent laboratory strain that acts as a model for wild type phase I strains. Our research was directed towards a deeper understanding of the monocyte proteome in response to a) infection by phase II C. burnetii, and b) exposure to immune adjuvants known to increase monocyte resistance to infection by C. burnetii. Monomac I cells were infected with phase II C. burnetii and aliquots were taken at 24, 48, and 96 hours postinfection. Experiments with immune adjuvants that increase monocyte killing of C. burnetii, involved Monomac I cells treated with Securinine, E. coli lipopolysaccharide (LPS), and monophosphoryl lipid A (MPL). Securinine is a GABA A receptor antagonist that is being developed at Montana State University for biodefense purposes, and triggers an innate immune response that differs from classic Toll-like receptor (TLR) stimulation of innate immunity represented by LPS and MPL. We employed multiplex 2D gel electrophoresis (m2DE) using ZDyes, a new generation of covalent fluorescent protein dyes being developed at Montana State University, coupled with MS/MS analysis and bioinformatics to determine the proteome changes in Monomac I cells in response to the conditions described above, and to develop a preliminary mechanistic model using a systems biology approach to account for the observed changes and propose multiple testable hypotheses to focus downstream research efforts. We also tested the effects on Monomac I cells infected with phase II C. burnetii +/- Securinine. We observed a high proportion of cell death in the + Securinine samples, using a dosage of Securinine higher than the optimal effective dosage. The information derived from this experiment will be useful in monitoring the tendency towards cell death in Securinine treated samples both from C. burnetii infected monocytes and other cell types (e.g. neurons) that contain GABA A receptors.