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Item Investigating the metalloproteome of bacteria and archaea(Montana State University - Bozeman, College of Letters & Science, 2024) Larson, James Daniel; Chairperson, Graduate Committee: Brian Bothner; This is a manuscript style paper that includes co-authored chapters.Metalloproteins are proteins that rely on a bound metal for activity and comprise 30-50% of all proteins which are responsible for catalyzing imperative biological functions. Understanding the interplay between essential and toxic metals in the environment and the metalloproteins from an organism (metalloproteome) is important for a fundamental understanding of biology. A challenge in studying the metalloproteome is that standard proteomic methods disrupt protein-metal interactions, therefore losing information about protein- metal bonds required for metalloprotein function. One of the focuses of my work has been to develop a non-denaturing chromatographic technique that maintains these non-covalent interactions. My approach for investigating the native metalloproteome together with leading- edge mass spectrometry methods was used to characterize microbial responses to evolutionarily relevant environmental perturbations. Arsenic is a pervasive environmental carcinogen in which microorganisms have naturally evolved detoxification mechanisms. Using Escherichia coli strains containing or lacking the arsRBC arsenic detoxification locus, my research demonstrated that exposure to arsenic causes dramatic changes to the distribution of iron, copper, and magnesium. In addition, the native arsRBC operon regulates metal distribution beyond arsenic. Two specific stress responses are described. The first relies on ArsR and leads to differential regulation of TCA-cycle metalloenzymes. The second response is triggered independently of ArsR and increases expression of molybdenum cofactor and ISC [Fe-S] cluster biosynthetic enzymes. This work provides new insights into the metalloprotein response to arsenic and the regulatory role of ArsR and challenges the current understanding of [Fe-S] cluster biosynthesis during stress. Iron is an essential and plentiful metal, yet the most abundant iron mineral on Earth, pyrite (FeS2), was thought to be unavailable to anaerobic microorganisms. It has recently been shown that methanogenic archaea can meet their iron (and sulfur) demands solely from FeS2. This dissertation shows that Methanosarcina barkeri employs different metabolic strategies when grown under FeS2 or Fe(II) and HS- as the sole source of iron and sulfur which changes the native metalloproteome, metalloprotein complex stoichiometry, and [Fe-S] cluster and cysteine biosynthesis strategies. This work advances our understanding of primordial biology and the different mechanisms of iron and sulfur acquisition dictated by environmental sources of iron and sulfur.Item Characterization of osteoarthritis metabolism: a mass spectrometry based-approach(Montana State University - Bozeman, College of Letters & Science, 2024) Welhaven, Hope Diane Aloha; Co-chairs, Graduate Committee: Brian Bothner and Ronald K. June II; This is a manuscript style paper that includes co-authored chapters.Osteoarthritis (OA) effects 7% of the global population, equating to more than 500 million people worldwide, and is the leading cause of disability. Its multifaceted etiology includes risk factors ranging from genetics, to aging, obesity, sex, race, and joint injury. OA manifests differently across the patient population where symptom severity, rate of progression, response to treatment, pain perception, as well as others vary person to person posing significant challenges for effective management and prevention. At the cellular level, imbalanced matrix catabolism and anabolism contribute to the breakdown of cartilage, underlying bone, and other tissues affected by OA. Leveraging mass spectrometry-based techniques, particularly metabolomics, offers a promising avenue to dissect OA metabolism across musculoskeletal tissues, while considering individual patient-specific risk factors. Therefore, the goals of this research were to: (1) comprehensively characterize OA phenotypes and endotypes and (2) explore OA pathogenesis within the context of disease-associated risk factors. The first area of research focuses on profiling OA phenotypes and endotypes across disease development. These results provide clear evidence of OA-induced metabolic perturbations in OA cartilage and bone and elucidate mechanisms that shift as disease progresses. Several metabolites and pathways associated with lipid, amino acid, matrix, and vitamin metabolism were differentially regulated between healthy and OA tissues and within OA endotypes. The second area of research focuses on the impact of OA risk factors -- sex, injury, obesity, loading -- on the metabolism of circulatory fluids (i.e., serum, synovial fluid) and chondrocytes. Identification of metabolic indicators of disease, such as cervonyl carnitine, and metabolic pathways associated with these risk factors holds potential for improving screening, monitoring disease progression, and guiding preventative strategies. Overall, this work contributes to our current understanding of OA, its diverse metabolic landscape, risk factors and their interactions. Moreover, it lays the groundwork for personalized medicine by providing detailed insights into individualized phenotypic profiles, thereby advancing the prospect of tailored treatment strategies for OA individuals.Item Development and analysis of lipidomics procedures for the causal investigation of Alzheimer's disease(Montana State University - Bozeman, College of Letters & Science, 2022) Koch, Max Richard; Chairperson, Graduate Committee: Edward Dratz; This is a manuscript style paper that includes co-authored chapters.Uncovering sets of molecular features which cause a healthy metabolic state to transition to one of disease, requires extensive experimentation and often presents a difficult analysis. In the case of neurodegenerative diseases, such as Alzheimer's Disease, simply obtaining suitable samples can be a challenging endeavor. Many current 'Omics' techniques excel at profiling a vast array of molecules, such as water-soluble metabolites, lipids, and proteins, in order to compare groups of samples from healthy and diseased organisms. Such approaches primarily use various associations between molecules and disease to identify biomarkers. However, these 'omics' experiments frequently result in intriguing biological hypotheses, but to date have rarely provided mechanistic explanations. How then, can mechanistic explanations be recovered from metabolite or lipid profile data? In our work, we applied these methods to 6 Alzheimer's diseased brain samples and 6 age matched controls. When analyzed via mass spectrometry, lipids which differed significantly between control and disease were identified, but this information was not able to'provide mechanistic insight. The beginning of any 'omics' based experiment starts with the extraction of the desired molecules. In order to assess the efficiency of three different lipid extraction methods, a lipid standard was extracted from a matrix composed of rat liver tissue and analyzed by mass spectrometry. The classic Folch extraction was found to be best at reproducibly extracting a wide range of lipids. Several of the lipids identified from human brains showed oxidative damage. Lastly, 5 statistical measures of dependence and 3 network algorithms were investigated for their ability to reconstruct mechanistic relationships in a dynamic model of arachidonic acid metabolism. Many of the metabolites of arachidonic acid are oxidation products. Under conditions of high noise and relatively few samples, standard measures of correlation, such as Pearson's correlation, Spearman's correlation and Kendall's Tau were found to perform the best. Metrics which incorporate nonlinear metabolic relations and network algorithms were found to be applicable, when sample size is large and the signal to noise ratio is close to l.Item Investigating the role of allostery through changes in protein stability and dynamics(Montana State University - Bozeman, College of Letters & Science, 2021) Patterson, Angela Jean; Chairperson, Graduate Committee: Brian Bothner; Faiz Ahmad and Jaigeeth Deveryshetty were authors and Jenna R. Mattice, Nilisha Pokhrel, Brian Bothner and Edwin Antony were co-authors of the article, 'Hydrogen-deuterium exchange reveals a dynamic DNA-binding map of replication protein A' in the journal 'Nucleic Acids Research' which is contained within this dissertation.; Zhongchao Zhao, Elizabeth Waymire, Adam Zlotnick, and Brian Bothner were co-authors of the article, 'Dynamics of hepatitis B virus capsid protein dimer regulates assembly through an allosteric network' in the journal 'ACS chemical biology' which is contained within this dissertation.; Paul B.G. van Erp was an author and Ravi Kant, Luke Berry, Sarah M. Golden, Brittney L. Forsman, Joshua Carter, Ryan N. Jackson, Brian Bothner and Blake Wiedenheft were co-authors of the article, 'Conformational dynamics of DNA binding and Cas 3 recruitment by the CRISPR RNA-guide cascade complex' in the journal 'ACS chemical biology' which is contained within this dissertation.; Aidan White, Elizabeth Waymire, Sophie Fleck, Sarah Golden, Royce Wilkinson, Blake Wiedenheft and Brian Bothner were co-authors of the article, 'Thermodynamics of CRISPR-anti-CRISPR interactions provides mechanistic insight into inhibition' which is contained within this dissertation.Allostery is the presence of a communication network that links functional sites of a protein that are distal from one another. The existence of an allosteric network can be observed through conformational change or a change in protein dynamics. These networks can be used to provide insight into the mechanistic function of proteins or protein complexes. In this thesis, four protein complexes were studied (RPA, HBV, Cascade, and Csy) and allosteric networks within the complexes were observed by monitoring the changes in protein dynamics upon an energy perturbation. To measure the changes in protein dynamics, hydrogen deuterium exchange mass spectrometry was used. This technique allows for the determination of how often the hydrogen bonding within a protein structure is broken. By tracking the longevity of the hydrogen bonding network that comprises the studied protein's structure, the dynamics of the protein can be studied. In this work, each of the proteins had changes in protein dynamics that were distal from the site of the energy perturbation that had functional impacts on each of the protein complexes. The combined presence of the distal changes in dynamics with an effect on protein function fits the definition of allostery. If allostery is present in these four diverse systems, is it possible that allostery is present in all proteins?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 Relating protein structure to function: how protein dynamics maximizes energy gained by electron transfer in an anaerobic energy conservation mechanism(Montana State University - Bozeman, College of Letters & Science, 2019) Berry, Luke Montgomery; Chairperson, Graduate Committee: Brian Bothner; Angela Patterson, Natasha Pence, John Peters and Brian Bothner were co-authors of the article, 'Hydrogen deuterium exchange mass spectrometry of oxygen sensitive proteins' in the journal 'Bio-protocols' which is contained within this dissertation.; Saroj Poudel, Monika Tokmina-Lukaszewska, Daniel R. Colman, Diep M.N. Nguyen, Gerrit J. Schut, Micheal W.W. Adams, John W. Peters, Eric S. Boyd and Brian Bothner were co-authors of the article, 'H/D exchange mass spectrometry and statistical coupling analysis reveal a role for allostery in a ferredoxin-dependent bifurcating transhydrogenase catalytic cycle' in the journal 'Biochimica et biophysica acta (BBA) - general subjects' which is contained within this dissertation.; Monika Tokmina-Lukaszewska, Derek F. Harris, Oleg A. Zadvornyy, Simone Raugei, John W. Peters, Lance C. Seefeldt and Brian Bothner were co-authors of the article, 'Combining in-solution and computational methods to characterize the structure-function relationship of the nitrogengase systems' which is contained within this dissertation.; Hayden Kallas, Derek F. Harris, Monika Tokmina-Lukaszewska, Simone Raugei, Lance C. Seefeldt and Brian Bothner were co-authors of the article, 'Iron protein docking effects on MOFE protein dynamics: function of negative cooperativity and the regulation of electron trasfer' which is contained within this dissertation.Reduced ferredoxin (Fd) plays a critical role in anaerobic metabolism by acting as an alternative source of energy to adenosine triphosphate (ATP). The reduction potential of Fd is low (-450 mV) making it difficult to reduce individually. However, it has recently been discovered that a unique mechanism known as electron bifurcation allows anaerobic organisms to reduce Fd without suffering a loss of energy. Electron bifurcation was originally discovered in complex III of the electron transport chain, and increased the efficiency of the proton motive force without an overall change in the electron flow, minimizing energy loss. EB accomplishes this is by coupling a favorable (exergonic) and unfavorable (endergonic) reduction reaction. The exergonic reaction produces a singly reduced cofactor with a sufficiently negative reduction potential to allow the endergonic process to proceed. This allows anaerobic organisms to couple the formation of NADH, with the reduction of Fd. A detail of interest in the bifurcating mechanism is how these enzymes regulate the flow of electrons down the exergonic and endergonic branches to prevent multiple electrons from traveling down the exergonic branch. It is hypothesized that changes in the protein conformation alter the distance between cofactors altering the rate of electron transfer. To fully understand how changes in a protein's conformation regulates electron transfer in electron bifurcation we used a suite of in-solution techniques, such as H/D exchange and chemical cross-linking coupled to mass spectrometry to characterize the structure and dynamics of the model bifurcating enzyme, NADH-dependent ferredoxin-NADP+ oxidoreductase (Nfn), during the different steps of electron bifurcation. Additionally we also set out to use these techniques to characterize the structure and dynamics of the nitrogenase systems in order to obtain biophysical evidence of negative cooperativity in the various nitrogenase systems.Item Characterization of metabolic changes in osteoarthritis using global metabolomic profiling(Montana State University - Bozeman, College of Agriculture, 2018) Carlson, Alyssa Kay; Chairperson, Graduate Committee: Ronald K. June II; Rachel A. Rawle, Erik Adams, Mark C. Greenwood, Brian Bothner and Ronald K. June were co-authors of the article, 'Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers' in the journal 'Biochemical and biophysical research communications' which is contained within this thesis.; Rachel A. Rawle, Cameron W. Wallace, Erik Adams, Mark C. Greenwood, Brian Bothner and Ronald K. June were co-authors of the article, 'Global metabolomic profiling of human synovial fluid for rheumatoid arthritis biomarkers' in the journal 'Clinical and experimental rheumatology' which is contained within this thesis.; Rachel A. Rawle, Cameron Wallace, Ellen Brooks, Erik Adams, Mark C. Greenwood, Merissa Olmer, Martin K. Lotz, Brian Bothner and Ronald K. June were co-authors of the article, 'Characterization of osteoarthritis phenotypes in human synovial fluid using global metabolomic profiling' submitted to the journal 'Arthritis and rheumatology' which is contained within this thesis.; Rachel A. Rawle, Erica Barboza, Albert Batushansky, Timothy M. Griffin, Brian Bothner and Ronald K. June were co-authors of the article, 'In vivio mechanotransduction: effect of acute exercise on the metabolomic profiles of mouse synovial fluid' submitted to the journal 'Journal of biomechanics' which is contained within this thesis.; Rachel A. Rawle, Erin Hutchison, Joanna Hudson, Brian Bothner, Timothy M. Griffin and Ronald K. June were co-authors of the article, 'The effect of long-term voluntary exercise on the metabolomic profiles of synovial fluid from high-fat diet-induced obese mice' submitted to the journal 'Arthritis and rheumatology' which is contained within this thesis.; Dissertation includes one article of which Alyssa Kay Carlson is not the main author.Osteoarthritis affects over 250 million individuals worldwide. It is a disease of the whole joint, exhibiting heterogenous pathology, and a multifactorial etiology consisting of obesity and joint trauma as important risk factors. This heterogenous nature contributes to the disparity in symptom presentation and response to treatments, presenting challenges for diagnosis and the development of targeted therapies for osteoarthritis phenotypes. Therefore, the goals of this work were to (1) enhance our understanding of osteoarthritis as a heterogenous disease for improved early diagnosis and (2) evaluate the interaction between osteoarthritis risk factors and therapeutic interventions. Because osteoarthritis and its risk factors are associated with aberrant metabolism, liquid chromatography-mass spectrometry-based global metabolomic profiling was employed to investigate changes in small molecules in response to osteoarthritis, risk factors, and therapeutic interventions. The first area of research focused on osteoarthritis diagnosis. The results show that global metabolomic profiling of human osteoarthritic synovial fluid is capable of identifying candidate biomarkers of osteoarthritis and classifying donors into subgroups representative of metabolic phenotypes. Metabolic phenotypes include structural deterioration, oxidative stress, and/or inflammation. The second area of research focused on osteoarthritis risk factors and therapeutic interventions. We investigated the effects of acute exercise in mouse synovial fluid to provide insight into exercise as a nonpharmacologic mechanobiology-based intervention prescribed for osteoarthritis. We found that acute exercise may have beneficial effects in maintaining overall joint health. We expanded on exercise as a nonpharmacologic treatment by investigating the effects of long-term exercise in an obesity-associated osteoarthritis mouse model. Long-term exercise did not exacerbate osteoarthritis in the knee joints of obese mice but did abrogate some obesity-induced metabolic perturbations in the synovial fluid. In addition, a pharmacologic intervention was investigated in posttraumatic osteoarthritis. Inhibition of early response genes by a Cdk9 inhibitor immediately after joint trauma was also capable of reversing a portion of injury-induced metabolic perturbations in whole joints of injured mice. Overall, this work demonstrates that global metabolomic profiling has potential for biomarker discovery and classifying patients into metabolic phenotypes. It also demonstrates the potential for exercise and inhibition of early response genes as therapeutic interventions for obesity-associated and post-traumatic osteoarthritis.Item The application of mass spectrometry in environmental chemistry: investigating biological cycling of arsenic, mercury and glycine betaine in aquatic ecosystems(Montana State University - Bozeman, College of Letters & Science, 2019) Alowaifeer, Abdullah Mohammed; Chairperson, Graduate Committee: Timothy R. McDermott; Brian Bothner (co-chair); Masafumi Yoshinaga, Patricia E. Bigelow, Brian Bothner and Timothy R. McDermott were co-authors of the article, 'Biological cycling of arsenic and mercury in Yellowstone Lake' which is contained within this thesis.; Qian Wang, Brian Bothner and Timothy R. McDermott were co-authors of the article, 'Examining the role of photoautotrophs contributing to glycine betaine, methylated amines and methane in oxic waters' which is contained within this thesis.Elemental cycling is a complex process that occurs abiotically and biotically. While abiotic cycling is well defined, biological cycling is more complex as it involves different microbes, animals and enzymes that govern its form and fate. In my project, I investigated the biological cycling of two of the most toxic elements known, arsenic and mercury. I examine their bioavailability, bioaccumulation and biomagnification in freshwater aquatic systems using Yellowstone Lake as a study model. In addtion, the sources and sinks of glycine betaine, an important aquatic metabolite that contributes to the carbon and nitrogen cycle, is investigated in Yellowstone Lake and three rivers located around the state of Montana. This research presented in this dissertation offers new insight on how arsenic and mercury cycle in aquatic systems and introduces a new hypothesis of the possible source of glycine betaine in freshwater ecosystem. Additionally, this project highlights a new and promising methodology to detect and quatify methylated amines in water samples.Item Computational investigation on protein sequencing and genome rearrangement problems(Montana State University - Bozeman, College of Engineering, 2018) Qingge, Letu; Chairperson, Graduate Committee: Binhai ZhuDe novo protein sequencing and genome rearrangement problems are the classical problems in bioinformatics. De novo protein sequencing problem try to determine the whole sequence of amino acids based on the mass spectrometry data without using the database search. Genome rearrangement problems try to recognize the evolutionary process between two species. In this dissertation, first, we describe the process of constructing target protein sequences by utilizing mass spectrometry based data from both top-down and bottom-up tandem mass spectra. In addition to using data from mass spectrometry analysis, we also utilize techniques for de novo protein sequencing using a homologous protein sequence as a reference to attempt to fill in any remaining gaps in the constructed protein scaffold. Initial results for analysis on real datasets yield over 96-100% coverage and 73-91% accuracy with the target protein sequence. Second, we use different genome rearrangement operations to transform one genome to another such that the similarity between two genomes is maximized. We explore these problems in terms of theoretical and experimental analysis. For sorting unsigned genome problem by double cut and join (DCJ) operation, we design a randomized fixed parameter tractable (FPT) approximation algorithm for computing the DCJ distance with an approximation factor 4/3 + Epsilon, and the running time O*(2 d*), where d* represents the optimal DCJ distance. For one-sided exemplar adjacency number problem, we reformulate the problem as maximum independent set in a colored interval graph and hence reduce the appearance of each gene at most twice. Moreover, we design a factor-2 approximation and also show that the approximation factor can not be improved less than 2 by some local search technique. At last, we apply integer linear programming to solve the reduced instance exactly. For the minimum copy number generation problem, we analyze the complexity of different variations of this problem and show a practical algorithm for the general case based on greedy method.Item Fungal production of biofuel and flavor compounds in liquid and solid state(Montana State University - Bozeman, College of Engineering, 2017) Schoen, Heidi Renee; Chairperson, Graduate Committee: Brent M. Peyton; Kristopher A. Hunt, Gary A. Strobel, Brent M. Peyton and Ross A. Carlson were co-authors of the article, 'Carbon chain length of biofuel- and flavor-relevant volatile organic compounds produced by lignocellulolytic fungal endophytes changes with culture temperature' submitted to the journal 'Mycoscience' which is contained within this thesis.; Brent M. Peyton and W. Berk Knighton were co-authors of the article, 'Rapid total volatile organic carbon quantification from microbial fermentation using a platinum catalyst and proton transfer reaction-mass spectrometry' in the journal 'AMB express' which is contained within this thesis.; W. Berk Knighton and Brent M. Peyton were co-authors of the article, 'Volatile organic compound production at varying oxygen conditions in a solid state fungal reactor' submitted to the journal 'Bioresource Technology' which is contained within this thesis.; W. Berk Knighton and Brent M. Peyton were co-authors of the article, 'Production of volatile organic compounds under varying nitrogen conditions by ascocoryne sarcoides' submitted to the journal 'Biotechnology and Bioengineering' which is contained within this thesis.Oil reserves are limited, so new sources of fuels and petroleum byproducts must be found. Some endophytic, filamentous fungi produce fuel and flavor relevant compounds from minimally pretreated cellulosic materials. Additionally, fungal volatile organic compounds can act synergistically as mycofumigants to inhibit bacteria, insects, and fungi. This dissertation identifies and quantifies fungal volatile organic compounds. A new method was created to quantify the total volatile organic carbon in the gas phase. A platinum catalyst was used to completely oxidize organic compounds to carbon dioxide, which was then measured with a carbon dioxide detector. This method agreed to within 94% of volatile organic carbon measurements taken with proton transfer reaction-mass spectrometry. Additionally, fungal production of fuel and flavor relevant volatile organic compounds was measured with varying pH and temperature in liquid cultures from Nodulisporium isolates EC, CO and TI. Production was also measured for TI when grown in solid state on the agricultural byproduct beet pulp at varying oxygen conditions. Finally, the model volatile organic compound producing organism Ascocoryne sarcoides was grown in liquid state with varying nitrogen sources, including amino acids. The three Nodulisporium isolates produced longer carbon number compounds at lower temperatures, which are better biofuels and are more likely to be bioactive. This trend was especially strong among volatile organic compounds associated with fatty acid metabolism. The fungi produced fewer compounds at lower pH. In solid state, TI had the highest total production of ethanol and carbon number four and higher compounds under anoxic conditions, but the highest production rates under microaerophilic conditions. Additionally, ethanol appeared to be the only major anoxic fermentation byproduct. Finally, A. sarcoides produced the most ethanol and carbon number four and higher compounds in the gas phase with ammonium chloride as the nitrogen source. Nitrogen sources that are reactants for volatile organic compounds, like leucine and phenylalanine, had lower gas phase concentrations of volatile organic compounds.