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Witte, Brian HurinTaming the Wild RubisCO: Explorations in Functional Metagenomics
Doctor of Philosophy, The Ohio State University, 2012, Microbiology
Ribulose bisphosphate carboxylase/oxygenase (E.C. 4.1.1.39) (RubisCO) is the most abundant protein on Earth and the mechanism by which the vast majority of carbon enters the planet’s biosphere. Despite decades of study, many significant questions about this enzyme remain unanswered. As anthropogenic CO2 levels continue to rise, understanding this key component of the carbon cycle is crucial to forecasting feedback circuits, as well as to engineering food and fuel crops to produce more biomass with few inputs of increasingly scarce resources. This study demonstrates three means of investigating the natural diversity of RubisCO. Chapter 1 builds on existing DNA sequence-based techniques of gene discovery and shows that RubisCO from uncultured organisms can be used to complement growth in a RubisCO-deletion strain of autotrophic bacteria. In a few short steps, the time-consuming work of bringing an autotrophic organism in to pure culture can be circumvented. Chapter 2 details a means of entirely bypassing the bias inherent in sequence-based gene discovery by using selection of RubisCO genes from a metagenomic library. Chapter 3 provides a more in-depth study of the RubisCO from the methanogenic archaeon Methanococcoides burtonii. Mc. burtonii RubisCO (MBR) is unique in being intermediate between two previously-recognized families of RubisCO, as well as having an unprecedented C-terminal loop structure. Deletion of all or part of the loop appears to improve the oxygen tolerance of MBR, while simultaneously disrupting ability of the protein to form a decameric holoenzyme. This is the first report of a structural feature in RubisCO that can prevent the association of RubisCO dimers into higher-order structures without eliminating the catalytic activity of the enzyme.

Committee:

F. R. Tabita (Committee Chair); Joe Krzycki (Committee Member); Birgit E. Alber (Committee Member); Paul Fuerst (Committee Member)

Subjects:

Biochemistry; Biological Oceanography; Biology; Microbiology

Keywords:

RubisCO; ribulose 1-5-bisphosphate carboxylase/oxygenase; metagenomics; enzymolygy; functional metagenomics

Robitaille, NicolasMETAGENOMIC ANALYSIS OF THE DEVELOPING PERI-IMPLANT SULCUS
Master of Science, The Ohio State University, 2015, Dentistry
Background: Dental endosseous implants are nowadays an increasingly popular option of treatment, when it comes to replacing missing teeth. Until recently, very little was known about the composition of the complex microbiome present in the peri-implant sulcus, and the scientific evidence concerning a sequence of implant microbial colonization is virtually nonexistent. Methods: 5 adult partially edentulous nonsmokers receiving a two-staged single implant were selected. Patients were excluded if they had less than 20 teeth, were medicated with immunosuppressants or bisphosphonates, presented with active periodontal or peri-implant disease, uncontrolled systemic disease, pregnancy, or had received antibiotic therapy in the last 3 months. Samples were harvested from the peri-implant sulcus, as well as gingival sulci of adjoining and contralateral teeth immediately after uncovery and at 1, 7, 21, 42 and 84 days following uncovery. Genomic DNA was isolated, sheared; size selected and sequenced using the Illumina 150 bp paired-end chemistry. Sequences were filtered, and functionally annotated using the MG-RAST pipeline. Functional profiles were compared between groups and over time using paired t-test and repeated-measures ANOVA with Tukey HSD analysis. A threshold of 20% of all functions was set in order to establish a significant difference between groups examined. Results: Statistical analysis revealed no significant differences in functional diversity and abundance between teeth located in close promity to the implant fixture and teeth located in the contralateral quadrant (388 functional genes out of 7256 (5.4%) were significantly different between these groups). When all teeth were taken as a group and compared with fixtures however, 1987 functional genes out of 7256 (27.4%) were significantly different between groups. Colonization patterns the periodontal sulcus followed a different path when compared to implants. The periodontal sulcus was stably colonized by a community within 24 hours and this did not change significantly over 84 days. However, in the peri-implant microbiome the greatest functional changes were observed after the baseline visit. The microbiome remained stable until after 42 days when significant changes were observed again. Conclusion : Distinct functional genes were detected around implants and teeth at any given time point. While the periodontal microbiome is colonized within 24 hours and stays relatively stable over 84 days, the peri-implant microbiome is still under development over this period of time. Therefore, the results of this study suggest that, in a given patient, the bacterial ecosystem surrounding a tooth or an implant fixture may differ significantly in development and colonization.

Committee:

Purnima Kumar, PhD (Advisor); John Walters, PhD (Committee Member); Daniel Reed, DDS (Committee Member)

Subjects:

Dental Care; Dentistry; Genetics; Microbiology

Keywords:

Dental implants, Bacterial colonization, peri-implantitis, peri-mucositis, Metagenomics

Lamendella, ReginaComparative Metagenomic Approaches to Reveal Swine-specific Populations Useful for Fecal Source Identification
PhD, University of Cincinnati, 2009, Engineering : Environmental Science

Despite current efforts to reduce fecal loads into aquatic environments, the problem persists, partially due to the inability to reliably identify the origin of fecal pollution. The swine industry has come under increasing environmental scrutiny due to augmented production and concentration of farming operations, resulting in large amounts of more concentrated waste products. Swine waste often harbors several human pathogens and thus presents a great risk to human health. Recently, methods targeting host-specific microbial populations have been proposed to identify specific sources and loads of fecal pollution entering environmental waters. Currently, there are a limited number of swine-specific markers available for source tracking studies. This is in part explained by our limited understanding of phylogenetic and functional diversity present within the swine gut microbiome. Several selective pressures imposed at the host and microbe level are predicted to result in unique microbial populations within the swine gastrointestinal system, which could serve as useful targets for swine fecal source tracking purposes.

Two popular targets utilized for fecal source tracking are Bifidobacterium and Bacteroidales 16S rRNA genes. In this study, the 16S rRNA gene sequence diversity of these two bacterial groups was examined to determine identity and distribution of swine-specific populations. The occurrence and abundance of these fecal bacterial populations were studied using samples from several geographically diverse host fecal types and impacted environmental samples. This molecular ecology approach revealed the diversity patterns of these popular fecal source tracking targets and unveiled previously unknown swine fecal source-specific populations relevant to environmental swine fecal pollution.

Since 16S rRNA gene approaches underestimate functional diversity, the swine fecal microbiome was analyzed using metagenomics-based (i.e., collective fecal microbial genomes) approaches to reveal the identity and functionality of the uncultivable majority within the swine distal gut. Function-specific genes represent another potential pool of swine-specific genetic targets. The use of this in silico comparative metagenomic approach facilitated the discovery of several genetic targets harbored exclusively in the swine gut. Coupling the detection of these function-specific targets to the 16S rRNA-based assays will help further validate if a swine fecal source is present within a given environmental sample. Using the approaches herein described has lead to the design of more comprehensive swine fecal source-specific assays, which will ultimately facilitate the accurate identification and relative contribution of swine fecal pollution in environmental waters.

Chapter one of this dissertation will discuss the detrimental impacts of swine fecal pollution, microbial source tracking methods, and how comparative metagenomics can be utilized for uncovering source-specific targets. Chapter two focuses on analyzing bifidobacterial diversity within different mammalian and avian fecal sources with the purpose of testing this bacterial group as a potential fecal source tracking target. Chapter three evaluates the currently available swine-specific fecal source tracking PCR-based assays within surface and groundwater surrounding swine farms. Chapter four examines Bacteroidales host distribution and presence within fecally contaminated environmental samples with the purpose of revealing populations both specific to swine fecal sources that can also be detected in environmental monitoring scenarios. Chapter five discusses the application of comparative metagenomics as an approach to expose bacterial populations and functional attributes unique to the swine distal gut. Chapter six discusses future directions of the field of microbial source tracking.

Committee:

Daniel Oerther, PhD (Committee Chair); Makram Suidan, PhD (Committee Member); Alison Weiss, PhD (Committee Member); Alice Layton, PHD (Committee Member)

Subjects:

Environmental Engineering

Keywords:

Bacteroidales;fecal pollution;16S rRNA;metagenomics;molecular diversity;ecology

Zimmerman, Brian DHuman Mitochondrial DNA and Endogenous Bacterial Surrogates for Risk Assessment of Graywater Reuse
MS, University of Cincinnati, 2014, Engineering and Applied Science: Environmental Science
Groundwater aquifers and surface waters currently used as drinking water and irrigation sources are in danger of over exploitation, leading to potable water scarcity in many regions of the world. On-site treatment and reuse of recycled wastewaters such as graywater for non-potable purposes has the ability to enhance water sustainability by alleviating demands on potable water supplies, which is particularly valuable in arid regions or in times of severe draught. However, given the inevitable downstream human contact, graywater represents a waterborne pathogen transmission and amplification pathway if human exposure to reused water is practiced without adequate treatment. Enteric pathogens are currently thought to be one of the most significant public health risks to water reuse. (1) Thus, previous studies sought to predict enteric pathogen presence in graywater through the use of fecal indicator bacteria (FIB) to indicate human fecal contamination and possible pathogen presence. However, FIB are known to grow in stored graywater, (2) do not correlate well with pathogens, (3) and may not accurately predict risks from pathogens transmitted via respiratory/oral and dermal pathways. (4) Therefore, new metrics to measure and predict microbial risk in graywater recycling systems is necessary for advancement of these systems. Due to potential pathogen presence, it is recommended that graywater undergo biological treatment and disinfection prior to reuse if downstream human contact is expected. U.S. graywater guidelines (2012) suggest using fecal coliforms of 0/100mL as the most conservative disinfection surrogate for reuse. (5) However, their quantities at different stages of treatment may vary due to re-growth, (6) causing inaccurate readings of the microbial log removal. Therefore, there is also a need for better microbial surrogates that can be used during graywater treatment to indicate process performance and pathogen reduction. Technologies such as high throughput DNA sequencing and quantitative polymerase chain reaction (qPCR) can assist with identifying novel surrogates potentially suited to evaluate pathogen removal in these systems. In this investigation, we utilize high throughput pyrosequencing and qPCR to identify and quantify select bacterial and human surrogates and pathogens in industrial laundry graywater sourced from the University of Cincinnati’s athletic facility. Pyrosequencing and qPCR revealed that laundry water microbiota was dominated by the skin-associated bacteria Staphylococcus, Corynebacterium, and Propionibacterium (6.5, 5.7, 5.4 log10 copies/100mL respectively). While human mitochondrial DNA (HmtDNA) was less abundant (2.8 log10 copies/100mL) it showed strong positive correlations with these three genera (r = 0.45, P = 0.002) as well as the opportunistic pathogen Staphylococcus aureus (r = 0.54, P = 3.2 x 10^-4). Further, HmtDNA closely followed a first order exponential decay model (R&sup2 = 0.98), remaining detectable in stored laundry graywater for up to six days at 20&degC. Based on consistency, abundance, and persistence in graywater, this research identifies HmtDNA and skin-associated bacteria such as total Staphylococcus as potential molecular surrogates for measuring microbial log removal in future graywater treatment evaluations.

Committee:

David Wendell, Ph.D. (Committee Chair); Jay L Garland, Ph.D. (Committee Member); Nicholas Ashbolt, Ph.D. (Committee Member); Drew McAvoy, Ph.D. (Committee Member); George Sorial, Ph.D. (Committee Member)

Subjects:

Environmental Engineering

Keywords:

Human mitochondrial DNA;graywater;risk assessment;metagenomics;bacterial pyrosequencing;qPCR

Moller, Abraham GhoreishiMapping ecologically important virus-host interactions in geographically diverse solar salterns with metagenomics
Master of Science, Miami University, 2016, Cell, Molecular and Structural Biology (CMSB)
Viruses that infect microbes are critical players in the world’s ecosystems. By lysing microbes, viruses turn over nutrients, regulate microbial populations, and maintain global biogeochemical cycles. Despite this ecological importance, determining viral-microbial interactions - especially interactions with lytic viruses, which do not integrate into their host’s genome - remains a major challenge. In this work, we determine viral interactions with microbes in salt-collecting ponds (salterns), where viruses are the dominant predator of the microbial community. Low microbial diversity, environmental stability, and high viral density also make solar salterns excellent model ecosystems for studying viral-archaeal interactions. By using a suite of bioinformatics tools to analyze saltern metagenomes, we mapped virus-host interactions across geographically diverse salterns and related them to carbon cycling. Our studies suggest viruses are critical players in saltern carbon cycling, and the loss of CRISPRs in archaea hosts may play an important role in regulating virus-mediated nutrient cycling in these environments.

Committee:

Chun Liang, PhD (Advisor); Michael Crowder, PhD (Committee Chair); Gary Lorigan, PhD (Committee Member)

Subjects:

Bioinformatics; Ecology; Microbiology

Keywords:

metagenomics, bioinformatics, CRISPR, virus-host interactions, hypersaline ecosystems, solar salterns, environmental microbiology

Tuttle, Taylor ACharacterization of the Persistent Cyanobacterial Bloom, Planktothrix, in Sandusky Bay, Lake Erie
Master of Science (MS), Bowling Green State University, 2015, Biological Sciences
Planktothrix sp. is less studied than other bloom-forming cyanobacteria. The aim of this study was to determine characteristics of the Planktothrix bloom in Sandusky Bay. Using the 2013 Sandusky Bay metagenome and 2014 summer samples, it was found that the bloom in Sandusky Bay has limited diversity and is continuously dominated by Planktothrix. Nutrient profiles of the Bay suggest nitrogen limitation throughout the bloom season. Physical parameters recorded in Sandusky Bay are suboptimal for many known bloom-forming cyanobacteria. Given this information, it is not yet understood how Planktothrix survives and dominates Sandusky Bay. Future work will look further at community members playing a role in the nitrogen cycle in the Bay. Additionally, the succession of genotypes will be determined over time as the environmental parameters will be monitored over a longer period of time to determine how survival of Planktothrix is supported.

Committee:

George Bullerjahn (Advisor); Robert McKay (Committee Member); Raymond Larsen (Committee Member)

Subjects:

Bioinformatics; Microbiology; Molecular Biology

Keywords:

Lake Erie; Planktothrix; phylogenetic analysis; metagenomics; cyanobacteria; Sandusky Bay

Bellinger, Christina GCommercial Soils as a Potential Vehicle for Antibiotic Resistance Transmission
Master of Science, The Ohio State University, 2017, Food Science and Technology
There is growing concern as to the continued ability of antibiotics in clinical settings to be effective due to increases in antibiotic resistance in pathogens. This increase is a major threat to human health, with approximately 23,000 annually killed by untreatable bacteria in the United States alone. The environment is a potential reservoir for antibiotic resistance genes and soil is high in bacterial diversity. This study aims to analyze augmented soils, especially a pilot study on their resistome, to assess the potential risk of commercial soil in disseminating antibiotic resistant bacteria to humans and the environment. A study of fifteen commercial soils was conducted using culture-dependent and metagenomic methods, with six noncommercial garden and general environmental soils used for comparison. Serially diluted soil samples were plated on plate count agar (PCA) and individual colonies were picked and transferred to antibiotic-supplemented agar using the following types and concentrations: ampicillin (16g/L), tetracycline (100g/L), erythromycin (100g/L), and lincomycin (16mg/L). DNA was extracted from soil samples, pooled and sequenced by high throughput sequencing. Primers were designed for three resistance genes in relative high abundance, aac(3)-Id, catB6, and MacB. PCR amplification to detect these genes in individual samples was conducted. All samples studied lacked response to at least one antibiotic using culturing methods, on average 66% to ampicillin, 77% to lincomycin, 15% to erythromycin, and 9% to tetracycline. A total of 59 total phyla were represented in the pooled soil sample, representing 2118 different genera, with the vast majority of bacteria present belonging to the phylum Proteobacteria. aminoglycoside resistance genes presented at elevated levels. Aac(3)-Id was detected in five commercial and one noncommercial soil. catB6 was detected in one soil. The ratio of antibiotic resistance gene hits to total 16S rRNA was 0.023, consistent with previous studies of residential soil and much lower than animal manures, which can range from 0.75-3ARG/16S rRNA. In summary, pilot results suggest commercial soils may not represent a major pool of antibiotic resistance genes but more analysis is needed to fully understand their place in the antibiotic resistance ecology.

Committee:

Hua Wang, Dr. (Advisor)

Subjects:

Food Science; Microbiology

Keywords:

antibiotic resistance; soils; potting soils; metagenomics; soil antibiotic resistance

Gerst, Michelle MarieImproving methods to isolate bacteria producing antibacterial compounds followed by identification and characterization of select antimicrobials
Doctor of Philosophy, The Ohio State University, 2017, Microbiology
Novel antimicrobials are needed in the medical and food industries to combat antibiotic and/or preservative resistant microorganisms. Several approaches are used to screen for novel antimicrobial compounds produced by bacteria including genome mining and culture based techniques. Genome mining techniques are limited by the challenge to test for antimicrobial activity of products from discovered sequences. Culture based techniques are time consuming and often lead to re-discovery of known compounds. A review of commonly used methods revealed that development of a high-throughput technique for antimicrobial detection combined with mass spectrometry and whole genome sequencing would further the field of antimicrobials discovery in bacteria. For one drug to be approved for use, approximately 10,000 compounds failed. Therefore, many compounds are needed to fill this pipeline for one antimicrobial to be approved for use to treat human disease. A high-throughput culture-based screening assay was developed to identify bacteria producing anti-Listeria and/or anti-Escherichia coli compounds, particularly the spore-forming producers. Whole genome sequencing and mass spectrometry were useful tools to identify and assess the novelty of compounds produced by the screened antimicrobial producing bacteria. Additionally, the advantages and limitations of metagenomic DNA and PCR in discovery of antimicrobial producing isolates were explored. Using soil samples from different sources, 46 Bacillus isolates were identified to produce antimicrobial compounds using the newly-developed high-throughput culture assay. Two isolates, Bacillus velezensis OSY-S3 (traditional culture techniques) and Bacillus velezensis GF610 (high-throughput microassay), and their antimicrobial products were further explored in depth. B. velezensis OSY-S3 produced LCI antimicrobial compound, surfactin, and fengycin, and removed Staphylococcus aureus biofilms. B. velezensis GF610 produced amyloliquecidin GF610, a two-component lantibiotic effective against pathogenic and spoilage Gram-positive microorganisms. In conclusion, the high-throughput culture based assay was effective in identifying many isolates producing antimicrobial compound(s). The detection limit of degenerate primers in metagenomic DNA made this technique less useful than the high-throughput microassay for discovery of novel compounds. Whole genome sequencing and mass spectrometry helped to more rapidly unravel the identity of the antimicrobial compounds produced by the isolates than traditional isolation techniques. The combination of high-throughput microassay, mass spectrometry, and whole genome sequencing is a useful approach to rapidly identify antimicrobial compounds produced by bacteria.

Committee:

Ahmed Yousef, Ph.D. (Advisor); Charles Daniels, Ph.D. (Committee Member); Stephanie Seveau, Ph.D. (Committee Member); Daniel Wozniak, Ph.D. (Committee Member)

Subjects:

Bioinformatics; Microbiology

Keywords:

antimicrobial peptide, method development, Bacillus velezensis, metagenomics, PCR, mass spectrometry

Solden, Lindsey MUncovering New Players and New Roles in Microbial Anoxic Carbon Transformations
Doctor of Philosophy, The Ohio State University, 2018, Microbiology
Organic carbon in anoxic ecosystems flows in a cascade from complex plant material to more labile sugars, and ultimately to short-chain fatty acids (SCFA) and gasses like carbon dioxide and methane. Microbial communities, groups of microorganisms that interact with one another, facilitate this process. Microbial anaerobic carbon degradation is exemplified in ruminants. These animals harness energy from plant material using the power of interacting microorganisms, which break down plant carbon into SCFA under largely anoxic conditions in the rumen. Because microbial SCFA can provide up to 80% of the animal’s energy, understanding microbial carbon degradation mechanisms in the rumen is important for many agricultural industries including the production of meat, milk, leather, and wool. Beyond domesticated ruminants, there are over 75 million wild ruminants that are fundamental members in ecosystems from Alaska to Australia. Furthermore, the microbial enzymes that break down plant material in the rumen have industrial applications for modifying enzymatic cocktails in biofuel production. The research presented here uses cultivation-independent and laboratory approaches to assign carbon degradation capabilities to specific members of the microbial community in the moose rumen. Moose, animals that naturally forage on woody biomass, were selected to provide access to natural rumen microbial communities that are especially adapted to a high lignocellulose diet. We sampled rumen fluid from moose in the spring, summer, and winter, along a seasonal gradient in lignocellulose. Rumen fluid was sampled via the rumen cannula, offering access into the active microbial interactions mediating complex carbon degradation. From these rumen fluid samples, we performed high-throughput shotgun metagenomics and metaproteomics, coupled to multiple methods for metabolite quantification (1H NMR, sequential fiber analyses, and carbohydrate microarray polymer profiling (CoMPP)). We binned hundreds of genomes, resulting in 77 unique (~>80% complete) genomes. A majority of these genomes (71%) belong to novel genera, families, and orders. Five of these genomes belong to an uncultivated, Bacteroidetes family, the BS11, which represent the first ever genomic representatives from this family. A newly resolved genus in this family was the most enriched member on a high lignocellulose diet and was found to ferment hemicellulose sugars. To uncover interactions between these microorganisms and determine their functional role, we mapped metaproteomics data to the unique genome data. This revealed most of the carbon degradation enzymes were encoded within polysaccharide utilization loci from uncultivated Bacteroidetes genomes. We then characterized the carbon metabolite chemistry focusing primarily on carbohydrate polymers and sugars of using CoMPP and 1H NMR. Linking our proteomes to metabolomics, we discovered that proteins from only seven Bacteroidetes genomes were processing all plant polymers detected, suggesting that a few generalist microorganisms are responsible for most of the carbon degradation in the rumen. One of these highly active Bacteroidetes genomes contained protospacer linkages to viral genomes, indicating that immunity against viral predation that may be required for some organisms to sustain carbon degradation in the rumen. Finally, winter rumen fluid with elevated condensed tannins was used to enrich for tannin-degrading microorganisms. From these reactors, we isolated a Streptococcus sp. that can degrade Sorghum condensed tannins (CT) in the presence of glucose. Label-free proteomics was performed to evaluate the dynamic proteome when the isolate was grown in the presence or absence of CT. CT lead to the enrichment of many proteins annotated as tannase enzyme, transcriptional regulators for phenolic metabolism, putative enzymes involved in phenolic metabolism, stress response proteins, and proteins originating from prophage. Cumulatively, this dissertation research examines the rumen on multiple scales, to identify microbial community and viral interactions, microorganism physiology, and the putative enzymes that facilitate how carbon flows through the rumen.

Committee:

Kelly Wrighton, Ph.D. (Advisor); Venkat Gopalan, Ph.D. (Committee Member); Jeffrey Firkins, Ph.D. (Committee Member); Daniel Wozniak, Ph.D. (Committee Member)

Subjects:

Microbiology

Keywords:

Bacteroidetes; carbon degradation; polysaccharide utilization loci; genome resolved metagenomics; metaproteomics; condensed tannin; rumen microbiome

Plis, Kevin A.The Effects of Novel Feature Vectors on Metagenomic Classification
Master of Science (MS), Ohio University, 2014, Computer Science (Engineering and Technology)
Metagenomics plays a crucial role in our understanding of the world around us. Machine learning and bioinformatics methods have struggled to accurately identify the organisms present in metagenomic samples. By using improved feature vectors, higher classification accuracy can be found when using the machine learning classification approach to identify the organisms present in a metagenomic sample. This research is a pilot study that explores novel feature vectors and their effect on metagenomic classification. A synthetic data set was created using the genomes of 32 organisms from the Archaea and Bacteria domains, with 450 fragments of varying length per organism used to train the classification models. By using a novel feature vector one tenth of the size of the currently used feature vectors, a 6.34%, 21.91%, and 15.07% improvement was found over the species level accuracy on 100, 300, and 500 bp fragments, respectively, for this data set. The results of this study also show that using more features does not always translate to a higher classification accuracy, and that higher classification accuracy can be achieved through feature selection.

Committee:

Lonnie Welch, PhD (Advisor)

Subjects:

Artificial Intelligence; Bioinformatics; Computer Science

Keywords:

Metagenomics; Classification; Machine Learning; SVM; Support Vector Machine; Feature Vector; Feature Selection; Bioinformatics

Hariharan, JananiPredictive Functional Profiling of Soil Microbes under Different Tillages and Crop Rotations in Ohio
Master of Science, The Ohio State University, 2015, Environmental Science
Food production and security is dependent on maintaining soil health and quality. Thus, the emphasis on sustainable and healthy soil function is a top priority for scientists and land managers. One of the most important factors that influences soil function is the microbial community. Recent advances have allowed us to quantify more accurately the composition of such communities, but there is still a knowledge gap with regard to the contribution of microorganisms to various processes occurring in the soil. Understanding this will facilitate the development of healthier agroecosystems. In this thesis, a predictive functional approach is used to elucidate bacterial species–function relationships. Bacterial community profiles were compared across two tillage systems and two crop rotations in Northern Ohio (Wooster and Hoytville). 16S rRNA gene-targeted sequencing was performed and the raw data obtained were filtered, denoised and processed using QIIME. Open-reference OTU picking and taxonomic assignment was performed using the Greengenes database. I then used a computational approach called PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) to predict metagenomes and the most likely functions performed by individual species of bacteria. Sequence analysis reveals a large number of unidentified OTUs, which is consistent with our expectations of the soil ecosystem. Comparison of sequencing data from different platforms indicates that the dataset generated using Illumina sequencing provided better hits with the reference database than pyrosequencing, and was associated with a greater number of putative soil bacterial functions. PICRUSt allows an estimation of the level of involvement each OTU has with a specific gene function, which enables comparisons to be made across bacterial species and treatment conditions. Predicted functions of the bacterial community revealed a large number of proteins connected with metabolism and maintenance of natural organic molecules in soil as well as enzymes related to degradation of xenobiotics. Using this approach, I was also able to map specific OTUs to their functional potential. Bacterial enzymes implicated in the cycling of nitrogen, sulfur, carbon and methane through the soil were examined, as were enzymes that catalyzed the oxidative degradation of hydrocarbon compounds that are considered soil pollutants. Specialized groups of bacteria were linked to functions like nitrogen fixation and degradation of compounds like atrazine and chlorohydrocarbons. A broader range of OTUs was found to contain genes for carbon utilization and sulfur metabolism. These predictions are supported by previous ecological studies. There were other OTU-function relationships predicted in these studies that are novel and could be valuable in identifying commercially important microorganisms. These leads will require experimental validation. A clear difference was seen between the no-till and plow-till treatments, with no-till being functionally enriched for most major nutrient cycles. No such differences were observed between the different crop rotations. Proteobacteria, Actinobacteria and Acidobacteria were some of the most abundant phyla found in these soil samples, along with Nitrospirae, and Bacteroidetes. I concluded that long-term and continuous application of different tillage systems, and to a lesser extent crop rotation, result in unique bacterial communities that affect the overall functioning of the soil.

Committee:

Warren Dick (Advisor); Parwinder Grewal (Advisor); Margaret Staton (Committee Member)

Subjects:

Agriculture; Biogeochemistry; Bioinformatics; Ecology; Environmental Science; Microbiology; Soil Sciences

Keywords:

PICRUSt; soil metagenomics; soil bacteria; soil function; nutrient cycling

Abu Doleh, AnasHigh Performance and Scalable Matching and Assembly of Biological Sequences
Doctor of Philosophy, The Ohio State University, 2016, Electrical and Computer Engineering
Next Generation Sequencing (NGS), the massive parallel and low-cost sequencing technology, is able to generate an enormous size of sequencing data. This facilitates the discovery of new genomic sequences and expands the biological and medical research. However, these big advancements in this technology also bring big computational challenges. In almost all NGS analysis pipelines, the most crucial and computationally intensive tasks are sequence similarity searching and de novo genome assembly. Thus, in this work, we introduced novel and efficient techniques to utilize the advancements in the High Performance Computing hardware and data computing platforms in order to accelerate these tasks while producing high quality results. For the sequence similarity search, we have studied utilizing the massively multithreaded architectures, such as Graphical Processing Unit (GPU), in accelerating and solving two important problems: reads mapping and maximal exact matching. Firstly, we introduced a new mapping tool, Masher, which processes long~(and short) reads efficiently and accurately. Masher employs a novel indexing technique that produces an index for huge genome, such as the human genome, with a small memory footprint such that it could be stored and efficiently accessed in a restricted-memory device such as a GPU. The results show that Masher is faster than state-of-the-art tools and obtains a good accuracy and sensitivity on sequencing data with various characteristics. Secondly, maximal exact matching problem has been studied because of its importance in detection and evaluating the similarity between sequences. We introduced a novel tool, GPUMEM, which efficiently utilizes GPU in building a lightweight indexing and finding maximal exact matches inside two genome sequences. The index construction is so fast that even by including its time, GPUMEM is faster in practice than state-of-the-art tools that use a pre-built index. De novo genome assembly is a crucial step in NGS analysis because of the novelty of discovered sequences. Firstly, we have studied parallelizing the de Bruijn graph based de novo genome assembly on distributed memory systems using Spark framework and GraphX API. We proposed a new tool, Spaler, which assembles short reads efficiently and accurately. Spaler starts with the de Bruijn graph construction. Then, it applies an iterative graph reduction and simplification techniques to generate contigs. After that, Spaler uses the reads mapping information to produce scaffolds. Spaler employs smart parallelism level tuning technique to improve the performance in each of these steps independently. The experiments show promising results in term of scalability, execution time and quality. Secondly, we addressed the problem of de novo metagenomics assembly. Spaler may not properly assemble the sequenced data extracted from environmental samples. This is because of the complexity and diversity of the living microbial communities. Thus, we introduced meta-Spaler, an extension of Spaler, to handle metagenomics dataset. meta-Spaler partitions the reads based on their expected coverage and applies an iterative assembly. The results show an improving in the assembly quality of meta-Spaler in comparison to the assembly of Spaler.

Committee:

Umit Catalyurek (Advisor); Kun Huang (Committee Member); Fusun Ozguner (Committee Member)

Subjects:

Bioinformatics; Computer Engineering

Keywords:

bioinformatics;sequence similarity;indexing;graphical processing unit;Apache Spark;de Bruijn graph;de novo assembly;metagenomics

Yadav, PoojaQuantitative Analysis of Microbial Species in a Metagenome Based on Their Signature Sequences
Master of Science (MS), Bowling Green State University, 2017, Biological Sciences
ABSTRACT Xu, Zhaohui, Advisor McKay, Robert Roy, Sankardas Shotgun metagenomics has provided a relatively new and powerful approach to study the environmental samples to characterize the microbial communities in contrast to pure cultures by conventional techniques. To determine the microbial diversity and to understand the role of microbes in the ecosystem, quantitative studies are important whose values are comparable across different studies and samples. We have developed a statistical approach to microbial profiling which encompasses quantitative characterization and comparison of relative abundance of the microbes in a metagenome sample based on their signature sequences (unique k-mers). We demonstrated the utility of this approach by characterizing and quantifying the relative abundance of the microbes in 4 different simulated metagenome samples (Comp_25, Comp_50, Comp_75, and Comp_100). The suffix of simulated metagenome name represents the gene content percentage of reporter species in the simulated metagenomes. The analysis of simulated metagenomes for data volume 6e9 and 6e10 furnish the information about the abundance of species by identifying the unique k-mers (signature sequences) of the six reporter species B. licheniformis, L. brevis, L. fermentum, L. plantarum, P. ananatis, and P. vagans. Our developed approach has efficiently identified the abundance of 4 reporter species i.e. B. licheniformis, L. brevis, L. fermentum, P. ananatis whereas 2 species L. plantarum and P. vagans were overestimated in the simulated metagenomes. So, application of advanced statistics, refinement of the algorithm, and an increase in data volume would be our next steps to improve the accuracy of our approach to estimate the ratio of species of a metagenome.

Committee:

Zhaohui Xu (Advisor); Robert McKay (Committee Member); Sankardas Roy (Committee Member)

Subjects:

Biology

Keywords:

Metagenomics; Genomic signature sequences; Quantitative analysis

Allen, Monet AliciaAnalysis of a Bacterial Nitrification Community in Lake Superior Enrichment Cultures
Master of Science (MS), Bowling Green State University, 2014, Biological Sciences
Lake Superior is the largest of these Laurentian Great Lakes and comprises about 10% of the surficial liquid freshwater on Earths surface. Over the last century, there has been a five-fold increase in the nitrate level in Lake Superior from ~5µM to ~26 µM (Sterner et al., 2007). Nitrification is a major process in the nitrogen cycle carried out mainly by the nitrifying microbial community. Isotopic assays, have shown that most of the nitrate is coming from in-lake nitrification processes. This buildup of nitrate results from a lack of dissimilatory processes removing nitrate from the water column. Primary production is also limited in this oligotrophic environment, constrained by iron and phosphorus resulting in low organic carbon availability. This study focused on understanding the community structure of a bacterial nitrifying community derived from Lake Superior water. A phylogenetic analysis of the bacterial 16S rRNA genes was accomplished by comparing the composition of the cultures to known bacteria present in the lake through the iTag 16S Lake Superior database available in our laboratory. Through metagenomic studies the of identification of genes involved in utilization of dominant nitrogen species as well as alternative phosphorus sources in this P-limited system was completed.

Committee:

George Bullerjahn, Dr. (Advisor); Robert McKay, Dr. (Committee Member); Raymond Larsen, Dr. (Committee Member)

Subjects:

Biogeochemistry; Bioinformatics; Biology

Keywords:

Bacterial Nitrification; Lake Superior; Metagenomics