Dissertations / Theses: 'Microbial bioinformatics'

1

Hooper, Sean. "Dynamics of Microbial Genome Evolution." Doctoral thesis, Uppsala University, Molecular Evolution, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3283.

Full text

Abstract:

The success of microbial life on Earth can be attributed not only to environmental factors, but also to the surprising hardiness, adaptability and flexibility of the microbes themselves. They are able to quickly adapt to new niches or circumstances through gene evolution and also by sheer strength of numbers, where statistics favor otherwise rare events.An integral part of adaptation is the plasticity of the genome; losing and acquiring genes depending on whether they are needed or not. Genomes can also be the birthplace of new gene functions, by duplicating and modifying existing genes. Genes can also be acquired from outside, transcending species boundaries. In this work, the focus is set primarily on duplication, deletion and import (lateral transfer) of genes – three factors contributing to the versatility and success of microbial life throughout the biosphere. We have developed a compositional method of identifying genes that have been imported into a genome, and the rate of import/deletion turnover has been appreciated in a number of organisms. Furthermore, we propose a model of genome evolution by duplication, where through the principle of gene amplification, novel gene functions are discovered within genes with weak- or secondary protein functions. Subsequently, the novel function is maintained by selection and eventually optimized. Finally, we discuss a possible synergic link between lateral transfer and duplicative processes in gene innovation.

APA, Harvard, Vancouver, ISO, and other styles

2

Meng, Da. "Bioinformatics tools for evaluating microbial relationships." Pullman, Wash. : Washington State University, 2009. http://www.dissertations.wsu.edu/Dissertations/Spring2009/d_meng_042209.pdf.

Full text

Abstract:

Thesis (Ph. D.)--Washington State University, May 2009. Title from PDF title page (viewed on June 8, 2009). "School of Electrical Engineering and Computer Science." Includes bibliographical references.

APA, Harvard, Vancouver, ISO, and other styles

3

Atkinson, Samantha Nicole. "Bioinformatic assessment of disrupted microbial communities." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6696.

Full text

Abstract:

Bioinformatics is a unique field in that it incorporates many different disciplines, including biology, computer science, and statistics, to study biological data. There is a vast array of techniques that utilize bioinformatics, including pangenomics, RNASeq, whole genome metagenomics, and 16S sequencing. To study bacterial interactions, we used a model system of species interactions, Myxococcus xanthus. M. xanthus is a soil bacterium that is a known predator of other bacteria. It has one of the largest repertoires of two component systems (TCS) to respond to external stresses. TCS are a pair of proteins, one that senses environmental stress (histidine kinase, HK) and another that usually acts as a transcriptional regulator (response regulators, RR). We studied a class of RRs, NtrC-like, reliant on an alternative sigma factor, sigma54. The oligomerization of NtrC-like RRs is regulated to modulate activation of the protein, which would change the bacterium’s ability to respond to its environment. We studied HsfA, a NtrC-like RR that regulates specialized metabolites. Specialized metabolites are used in bacterial interactions. In predation interactions they are used to kill prey. Our goal was to find genes that might be involved in specialized metabolite production that would aid in predation. We used prediction tools to find putative binding sites of HsfA to find potentially new metabolites. We used two motifs to attempt to predict if the oligomerization of these response regulators is positively or negatively regulated. We found that the presence of a motif in the receiver domain to be associated with negative regulation of oligomerization, but further studies are needed to experimentally confirm this finding. One environment in which bacterial interactions occur is in the gut. The gut microbiome is the consortium of organisms and their genomic content in the gastrointestinal tract. The gut microbiome is sensitive to aspects of a person’s lifestyle, such as diet and medication. Here we studied the effect of two different diets and two drugs on the gut microbiome. Risperidone, an antipsychotic used to treat schizophrenia and bipolar disorder, has been shown to cause obesity and diabetes. We studied the effect of diet and risperidone usage on weight gain and the microbiome using a C57Bl/6J female mouse model. Our results show that diet has a strong impact on the microbial composition of the gut in response to risperidone. As many mental health patients stop and restart their medication, we examined the effect of stopping and restarting risperidone on the microbiome. When risperidone is stopped the microbiome reverts to a state similar to the control group but diverges into a different microbial composition upon restarting treatment. Interestingly, mice did not gain significantly more weight than their control group upon the second risperidone treatment. Further studies are needed to examine the functional changes occurring with the stop and restart of risperidone to determine the mechanism of mice resisting weight gain during the second round of treatment. Captopril is used to treat hypertension, a very common disease in the United States. Here we studied the effect of captopril on weight gain, metabolic phenotypes, and the gut microbiome. Our results showed that captopril caused an increase in resting metabolic rate (RMR) in mice. This occurred through an increase in energy expenditure. This increase in RMR had the effect of captopril-treated mice being resistant to weight gain. Our group has previously shown that the gut microbiome can directly affect RMR. Therefore, we studied the gut microbiome of captopril-treated mice. We observed a shift in their gut microbiome to organisms Akkermansia muciniphila and Lactobacillus, associated with lean body mass. Captopril therefore has the potential to be a better medication to treat patients with both hypertension and obesity. Further studies are needed to determine the effect of captopril on the microbiome in a hypertension mouse model.

APA, Harvard, Vancouver, ISO, and other styles

4

Jones, Katy June. "Bioinformatic analysis of biotechnologically important microbial communities." Thesis, University of Exeter, 2018. http://hdl.handle.net/10871/34543.

Full text

Abstract:

Difficulties associated with the study of microbial communities, such as low proportions of cultivable species, have been addressed in recent years with the advent of a range of sequencing technologies and bioinformatic tools. This is enabling previously unexplored communities to be characterised and utilised in a range of biotechnology applications. In this thesis bioinformatic methods were applied to two datasets of biotechnological interest: microbial communities found living with the oil-producing alga Botryococcus braunii and microbial communities in acid mine drainage (AMD). B. braunii is of high interest to the biofuel industry due to its ability to produce high amounts of oils, in the form of hydrocarbons. However, a number of factors, including low growth rates, have prevented its cultivation on an industrial scale. Studies show B. braunii lives in a consortium with numerous bacteria which may influence its growth. This thesis reports both whole genome analysis and 16S rRNA gene sequence analysis to gain a greater understanding of the B. braunii bacterial consortium. Bacteria have been identified, some of which had not previously been documented as living with B. braunii, and evidence is presented for ways in which they may influence growth of the alga, including B-vitamin synthesis and secretion systems. AMD is a worldwide problem, polluting the environment and negatively impacting on human health. This by-product of the mining industry is a problem in the South West of England, where disused metalliferous mines are now a source of AMD. Bioremediation of AMD is an active area of research; sulphur-reducing bacteria and other bacteria which can remove toxic metals from AMD can be utilised for this purpose. Identifying bacteria and archaea that are able to thrive in AMD and which also have these bioremediation properties is therefore of great importance. Metagenomic sequencing has been carried out on the microbial community living in AMD sediment at the Wheal Maid tailings lagoon near Penryn in Cornwall. From these data have been identified a diverse range of bacteria and archaea present at both the sediment surface level and at depth, including microorganisms closely related to taxa reported from metalliferous mines on other continents. Evidence has been found of sulphur-reducing bacteria and of pathways for various other bioremediation-linked processes.

APA, Harvard, Vancouver, ISO, and other styles

5

Brown, Shawn Paul. "Rules and patterns of microbial community assembly." Diss., Kansas State University, 2014. http://hdl.handle.net/2097/18324.

Full text

Abstract:

Doctor of Philosophy Division of Biology Ari M. Jumpponen Microorganisms are critically important for establishing and maintaining ecosystem properties and processes that fuel and sustain higher-trophic levels. Despite the universal importance of microbes, we know relatively little about the rules and processes that dictate how microbial communities establish and assemble. Largely, we rely on assumptions that microbial community establishment follow similar trajectories as plants, but on a smaller scale. However, these assumptions have been rarely validated and when validation has been attempted, the plant-based theoretical models apply poorly to microbial communities. Here, I utilized genomics-inspired tools to interrogate microbial communities at levels near community saturation to elucidate the rules and patterns of microbial community assembly. I relied on a community filtering model as a framework: potential members of the microbial community are filtered through environmental and/or biotic filters that control which taxa can establish, persist, and coexist. Additionally, I addressed whether two different microbial groups (fungi and bacteria) share similar assembly patterns. Similar dispersal capabilities and mechanisms are thought to result in similar community assembly rules for fungi and bacteria. I queried fungal and bacterial communities along a deglaciated primary successional chronosequence to determine microbial successional dynamics and to determine if fungal and bacterial assemblies are similar or follow trajectories similar to plants. These experiments demonstrate that not only do microbial community assembly dynamics not follow plant-based models of succession, but also that fungal and bacterial community assembly dynamics are distinct. We can no longer assume that because fungi and bacteria share small propagule sizes they follow similar trends. Further, additional studies targeting biotic filters (here, snow algae) suggest strong controls during community assembly, possibly because of fungal predation of the algae or because of fungal utilization of algal exudates. Finally, I examined various technical aspects of sequence-based ecological investigations. These studies aimed to improve microbial community data reliability and analyses.

APA, Harvard, Vancouver, ISO, and other styles

6

Montana, Aldrin. "Algorithms for Library-based Microbial Source Tracking." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/959.

Full text

Abstract:

Pyroprinting is a novel, library-based microbial source tracking method developed by the Biology department at Cal Poly, San Luis Obispo. This method consists of two parts: (1) a collection of bacterial fingerprints, called pyroprints, from known host species, and (2) a method for pyroprint comparison. Currently, Cal Poly Library of Pyroprints (CPLOP), a web-based database application, provides storage and analysis of over $10000$ pyroprints. This number is quickly growing as students and researchers continue to use pyroprinting for research. Biologists conducting research using pyroprinting rely on methods for partitioning collected bacterial isolates into bacterial strains. Clustering algorithms are commonly used for bacterial strain analysis of organisms in computational biology. Unfortunately, agglomerative hierarchical clustering, a commonly used clustering algorithm, is inadequate given the nature of data collection for pyroprinting. While the clusters produced by agglomerative hierarchical clustering are acceptable, pyroprinting requires a method of analysis that is scalable and incorporates useful metadata into the clustering process. We propose ontology-based hierarchical clustering (OHClust!), a modification of agglomerative hierarchical clustering that expresses metadata-based relationships as an ontology to direct the order in which hierarchical clustering algorithms analyze the data. In this thesis, the strengths and weaknesses of OHClust! are discussed, and its performance is analyzed in comparison to agglomerative hierarchical clustering.

APA, Harvard, Vancouver, ISO, and other styles

7

Shankar, Vijay. "Extension of Multivariate Analyses to the Field of Microbial Ecology." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464358122.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Sanchez, Rhea I. "Annotation consistency tool : the assessment of JCVI microbial genome annotations /." Online version of thesis, 2009. http://hdl.handle.net/1850/10653.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Colby, Graham. "Microbial Responses to Environmental Change in Canada’s High Arctic." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39254.

Full text

Abstract:

The Arctic is undergoing a rapid environmental shift with increasing temperatures and precipitations expected to continue over the next century. Yet, little is known about how microbial communities and their underlying metabolic processes will respond to ongoing climatic changes. To address this question, we focused on Lake Hazen, NU, Canada. As the largest High Arctic lake by volume, it is a unique site to investigate microbial responses to environmental changes. Over the past decade, glacial coverage of the lake has declined. Increasing glacial runoff and sedimentation rates in the lake has resulted in differential influx of nutrients through spatial gradients. I used these spatial gradients to study how environmental changes might affect microbial community structure and functional capacity in Arctic lakes. I performed a metagenomic analysis of microbial communities from hydrological regimes representing high, low, and negligible influence of glacial runoff and compared the observed structure and function to the natural geochemical gradients. Genes and reconstructed genomes found in different abundances across these sites suggest that high-runoff regimes alter geochemical gradients, homogenise the microbial structure, and reduce genetic diversity. This work shows how a genome-centric metagenomics approach can be used to predict future microbial responses to a changing climate.

APA, Harvard, Vancouver, ISO, and other styles

10

He, Lian. "Development of Steady-State and Dynamic Flux Models for Broad-Scope Microbial Metabolism Analysis." Thesis, Washington University in St. Louis, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10103229.

Full text

Abstract:

Flux analysis techniques, including flux balance analysis (FBA) and 13C-metabolic flux analysis (MFA), can characterize carbon and energy flows through a cell’s metabolic network. By employing both 13C-labeling experiments and nonlinear programming, 13C-MFA provides a rigorous way of examining cell flux distributions in the central metabolism. FBA, on the other hand, gives a holistic review of optimal fluxomes on the genome scale. In this dissertation, flux analysis techniques were constructed to investigate the microbial metabolisms. First, an open-source and programming-free platform of 13C-MFA (WUFlux) with a user-friendly interface in MATLAB was developed, which allowed both mass isotopomer distribution (MID) analysis and metabolic flux calculations. Several bacterial templates with diverse substrate utilizations were included in this platform to facilitate 13C-MFA model construction. The corrected MID data and flux profiles resulting from our platform have been validated by other available 13C-MFA software. Second, 13C-MFA was applied to investigate the variations of bacterial metabolism in response to genetic manipulations or changing growth conditions. Specifically, we investigated the central metabolic responses to overproduction of fatty acids in Escherichia coli and the carbon flow distributions of Synechocystis sp. PCC 6803 under both photomixotrophic and photoheterotrophic conditions. By employing the software of isotopomer network compartmental analysis, we performed isotopically non-stationary MFA on Synechococcus elongatus UTEX 2973. The 13C-based analysis was also conducted for other non-model species, such as Chloroflexus aurantiacus. The resulting flux distributions detail how cells manage the trade-off between carbon and energy metabolisms to survive under stressed conditions, support high productions of biofuel, or organize the metabolic routes for sustaining biomass growth. Third, conventional FBA is suitable for only steady-state conditions. To describe the environmental heterogeneity in bioreactors and temporal changes of cell metabolism, we integrated genome-scale FBA with growth kinetics (time-dependent information) and cell hydrodynamic movements (space-dependent information). A case study was subsequently carried out for wild-type and engineered cyanobacteria, in which a heterogeneous light distribution in photobioreactors was considered in the model. The resulting integrated genome-scale model can offer insights into both intracellular and extracellular domains and facilitate the analysis of bacterial performance in large-scale fermentation systems. Both steady-state and dynamic flux analysis models can offer insights into metabolic responses to environmental fluctuations and genetic modifications. They are also useful tools to provide rational strategies of constructing microbial cell factories for industrial applications.

APA, Harvard, Vancouver, ISO, and other styles

11

Hu, Yue. "Microbial DNA Sequencing in Environmental Studies." Doctoral thesis, KTH, Skolan för bioteknologi (BIO), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204897.

Full text

Abstract:

The field of microbial ecology has just entered a new era of rapid technological development and generation of big data. The high-throughput sequencing techniques presently available provide an opportunity to extensively inventorize the blueprints of life. Now, millions of microbes of natural microbial communities can be studied simultaneously without prior cultivation. New species and new functions (genes) can be discovered just by mining sequencing data. However, there is still a tremendous number of microorganisms not yet examined, nor are the ecosystem functions these carry out. The modern genomic technologies can contribute to solve environmental problems and help us understand ecosystems, but to most efficiently do so, methods need to be continuously optimised. During my Ph. D. studies, I developed a method to survey eukaryotic microbial diversity with a higher accuracy, and applied various sequencing-based approaches in an attempt to answer questions of importance in environmental research and ecology. In PAPER-I, we developed a set of 18S rRNA gene PCR primers with high taxonomic coverage, meeting the requirements of currently popular sequencing technologies and matching the richness of 18S rRNA reference sequences accumulated so far. In PAPER-II, we conducted the first sequencing-based spatial survey on the combined eukaryotic and bacterial planktonic community in the Baltic Sea to uncover the relationship of microbial diversity and environmental conditions. Here, the 18S primers designed in PAPER-I and a pair of broad-coverage 16S primers were employed to target the rRNA genes of protists and bacterioplankton for amplicon sequencing. In PAPER-III, we integrated metagenomic, metabarcoding, and metatranscriptomic data in an effort to scrutinise the protein synthesis potential (i.e., activity) of microbes in the sediment at a depth of 460 m in the Baltic Sea and, thus, disclosing microbial diversity and their possible ecological functions within such an extreme environment. Lastly, in PAPER-IV, we compared the performance of E. coli culturing, high-throughput sequencing, and portable real-time sequencing in tracking wastewater contamination in an urban stormwater system. From the aspects of cost, mobility and accuracy, we evaluated the usage of sequencing-based approaches in civil engineering, and for the first time, validated the real-time sequencing device in use within water quality monitoring. In summary, these studies demonstrate how DNA sequencing of microbial communities can be applied in environmental monitoring and ecological research. Yue Hu was supported by a scholarship from the China Scholarship Council (CSC #201206950024)Yue Hu has been publishing papers under the name "Yue O. O. Hu".QC 20170403

APA, Harvard, Vancouver, ISO, and other styles

12

Mabrouk, Nabil. "Analyzing individual-based models of microbial systems." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2010. http://tel.archives-ouvertes.fr/tel-00712153.

Full text

Abstract:

Cette thèse s'inscrit dans le cadre du débat en écologie théorique entre ceux qui favorisent les modèles mathématiques agrégés contenant un nombre relativement faible d'équations exprimant quelques principes généraux et ceux qui préfèrent les modèles individus-centré (multi-agents) qui sont structurellement plus réalistes et comprennent une représentation détaillées des processus et interactions à l'échelle de l'individu. Dans cette thèse nous proposons d'établir un lien entre ces deux approches en dérivant des modèles déterministes basés sur les moments spatiaux et approximant la dynamique des modèles individus-centrés de systèmes microbiens. Nous illustrons cette approche sur l'exemple de croissance d'un bio lm formé par des bactéries mobiles ou immobiles. Nous montrons que les modèles des moments peuvent rendre compte des principales propriétés des structures spatiales obtenues par simulation individus-centrée. En n nous explorons les limites des modèles des moments notamment à rendre compte de l'e et des uctuations locales de l'environnement des individus lorsque celles ci a ectent la dynamique du système microbien simulé par le modèle individus-centré.

APA, Harvard, Vancouver, ISO, and other styles

13

Suen, Garret. "Understanding prokaryotic diversity in the post-genomics era." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available, full text:, 2008. http://wwwlib.umi.com/cr/syr/main.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Eckstrom, Korin. "Evaluating The Resistome And Microbial Composition During Food Waste Feeding And Composting On A Vermont Poultry Farm." ScholarWorks @ UVM, 2018. https://scholarworks.uvm.edu/graddis/886.

Full text

Abstract:

While commonly thought of as a waste product, food scraps and residuals represent an important opportunity for energy and nutrient recapture within the food system. As demands on production continue to increase, conservation of these valuable resources has become a priority area. In the wake of new legislation in Vermont, Act 148, the Universal Recycling Law, the fate of microbial species in food waste, scraps and residuals is increasingly important. The presence of antimicrobial resistance genes in all types of foods calls for an increased need to estimate risk of antibiotic resistance transfer and maintenance across all segments of food production and distribution systems, from farm to fork. Specifically, the fate of antibiotic resistance genes (ARGs) in these co-mingled food wastes has not been sufficiently characterized; as legislative programs increase in popularity, surveillance of these materials is pressing and should be documented to assess the risk and potential measures for mitigation and management as we approach commercial scales of implementation Previous studies have relied on a combination of targeted techniques, such as 16S rRNA sequencing and qPCR on a specific subset of ARGs; however, these may not cover the full extent of resistance or microorganisms of concern in any given sample. As sequencing technologies improve and costs continue to drop, more comprehensive tools, such as shotgun metagenomic sequencing, can be applied to these problems for both surveillance and novel gene discovery. In this study, we leveraged the increased screening power of the Illumina HiSeq and shotgun metagenomic sequencing to identify and characterize ARGs, microbial communities, and associated virulence factors of food scraps, on-farm composts, and several consumer products. Isolates were also screened for antibiotic resistance to demonstrate the functionality of ARGs identified. The resistome, microbiome, and virulence genes were characterized in all samples. Fifty unique ARGs were identified that spanned 8 major drug classes. Most frequently found were genes related to aminoglycoside, macrolide, and tetracycline resistance. Additionally, 54 distinct virulence factors and 495 bacterial species were identified. Virulence factors were present across the farm setting and mainly included gene transfer mechanisms, while bacteria clustered distinctly into site and farm, as well as separate on farm niches. The relationship between these categories was also assessed by both Pearson correlation and co-inertia analysis, with the most significant relationship being between ARGs and virulence factors (P = 0.05, RV = 0.67). While limited in this study, these patterns reinforce the finding that spread of antibiotic resistance genes may be dependent on the virulence factors present enabling transfer, rather than total microbial community composition.

APA, Harvard, Vancouver, ISO, and other styles

15

Kalantar, Katrina. "Combined Host and Microbial Metagenomic Next-Generation Sequencing| Applying Integrated Analysis Approaches for a Comprehensive Evaluation of Infectious Disease Response to Inform Diagnosis, Surveillance, and Treatment." Thesis, University of California, San Francisco, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13428465.

Full text

Abstract:

Infectious diseases are a leading cause of morbidity and mortality worldwide. Despite significant advancement in our understanding of infectious disease biology, existing microbiologic diagnostic tests often fail to identify etiologic pathogens in cases of suspected infection. Metagenomic next-generation sequencing (mNGS) offers the potential for a universal pathogen detection method, but analysis and interpretation of findings are challenging. This is especially true for lower respiratory tract infections (LRTIs) where mNGS data interpretation is complicated by the existence of a respiratory microbiome composed of pathobionts present in both health and disease. To address the need for improved LRTI diagnostics, we first compared two fluid types commonly used for diagnosis of LRTI, showing that despite moderate microbiome differences, both mini-bronchioalveolar lavage (mBAL) and tracheal aspirate (TA) samples are suitable for identification of pathogens in the context of an infection. Then, we evaluated the utility of mNGS as a diagnostic for LRTI in a cohort of 92 TA samples from adults with acute respiratory failure. We developed methods for sifting putative pathogens from commensal microbiota as well as pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. We applied the models developed for evaluation of LRTI status to several other cohorts and disease contexts to show their broad applicability. The low sensitivity of existing clinical diagnostics results in an imperfect gold standard, complicating the development of mNGS-based biomarkers. We explored the impact of label noise on host gene expression classifiers and methods for circumventing the issue. First, we tested whether label-noise robust logistic regression approaches could improve classifier performance by enabling the use of a larger training set. Then, we tested whether variational autoencoders, an unsupervised dimensionality reduction approach, could generate novel insight from combined host and microbial mNGS data. Altogether, this work suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for diagnosis of infections and contextualization of patient response.

APA, Harvard, Vancouver, ISO, and other styles

16

Kioroglou, Dimitrios. "Analysis of microbial populations in wines through NGS methodologies." Doctoral thesis, Universitat Rovira i Virgili, 2020. http://hdl.handle.net/10803/670208.

Full text

Abstract:

La vinificación es un proceso complejo que involucra varias etapas hasta el embotellado y comercialización del vino. Durante este proceso, la cantidad limitada de nutrientes provoca la competencia microbiana, que resulta en la producción de metabolitos que modulan el producto final del vino. Esta actividad microbiana puede conferir características organolépticas beneficiosas o indeseables a la calidad del vino. En los últimos años, el enfoque principal se ha centrado en la detección y el seguimiento de microorganismos determinados, que supuestamente estropean el vino, y la aplicación de metodologías empíricas para la prevención del crecimiento microbiano indeseable. Sin embargo, los hallazgos de las investigaciones han mostrado una base multifactorial del deterioro del vino, y han subrayado la necesidad de una estrategia innovadora que permita el estudio de la diversidad microbiana en su totalidad. La secuenciación de última generación parece un enfoque adecuado y prometedor para este propósito, ya que parece capaz de superar las limitaciones de las metodologías convencionales evaluación de los resultados derivados en función de su alineación con hallazgos anteriores y su capacidad para proporcionar nuevos conocimientos. En general, el trabajo actual ha logrado corroborar estudios previos, sugerir mejoras sobre las implementaciones relacionadas con la bioinformática y la estadística y ampliar nuestro conocimiento sobre varios factores que influyen en la vinificación. Winemaking is a intricate process, involving various stages until the wine bottling and commercialization. During this process, the limited amount of nutrients leads to microbial competition, which in turn results in the production of metabolites that modulate the final wine product. This microbial activity may confer beneficial or undesirable organoleptic characteristics to the wine quality. The past years, the main focus has been given to the detection and monitoring of specific putative wine-spoiling microorganisms and the application of empirical methodologies for the prevention of unwanted microbial growth. Nevertheless, research findings have shown a multifactorial basis of the wine spoilage and underlined the need for an innovative strategy that will allow the study of the microbial diversity in its entirety. Next-generation-sequencing appears a suitable and promising approach for this purpose, as it seems able to overcome the limitations of conventional methodologies. In this work, various aspects associated to the NGS-based metataxonomic analysis have been studied, in relation to the performance of the NGS technology against conventional applications, and the establishment of a bioinformatic and statistical framework for the analysis of metataxonomic data.

APA, Harvard, Vancouver, ISO, and other styles

17

Donnelly, Chase P. "Microbial Ecology of South Florida Surface Waters: Examining the Potential for Anthropogenic Influences." Thesis, NSUWorks, 2018. https://nsuworks.nova.edu/occ_stuetd/485.

Full text

Abstract:

South Florida contains one of the largest subtropical wetlands in the world, and yet not much is known about the microbes that live in these surface waters. These microbes play an important role in chemical cycling and maintaining good water quality for both human and ecosystem health. The hydrology of Florida’s surface waters is tightly regulated with the use of canal and levee systems run by the US Army Corps of Engineers and The South Florida Water Management District. These canals run through the Everglades, agriculture, and urban environments to control water levels in Lake Okeechobee, the Water Conservation Areas, and the surrounding farm lands. I hypothesized that there would be noticeable shifts in the microbial communities (also known as “microbiomes”) at the agriculture and urban sites due to anthropogenic influences such as agricultural and sewage runoff. It is also hypothesized that the diversity and stability of these sites will differ from the natural environment Grassy Waters Preserve (GWP), which we studied as a control. The northern section of GWP is a rain-fed Everglades ecosystem with little influence from manmade canal systems, so GWP can represent wetlands before human influences. High-throughput 16s rRNA sequencing was conducted on 112 GWP, canal, and agricultural water samples taken over a one-year period from September 2016 to November 2017. Data were processed in Qiime2 using DADA2 and resulted in 67732 unique taxa. Nineteen metadata factors were measured for 87 of the sampling points to investigate environmental effects. These factors explained 25% (r2=0.25, p=0.002) of the variation between sample locations. Conductivity was found to have the highest effect on microbial diversity (r2=0.078, p=0.002) while latitude and month also significantly influenced the microbial makeup. Urban and agricultural sites were found to have higher stability with lower variation in microbiomes over the course of study. The GWP site was found to have a high seasonality, probably due to its dependence on rain. The most abundant taxa for all sites (urban, agriculture, and control) were; family Spirochaetaceae, phylum Actinobacteria, and family Burkholderiaceae, respectively. Contamination of GWP and canal sites was also investigated using SourceTracker code. Intracoastal waters that receive canal water were found to be heavily influenced in the peak wet season when there is high flow through from the canals. GWP had little influence from farm lands compared to a high influence of agriculture on the urban sites.

APA, Harvard, Vancouver, ISO, and other styles

18

Ye, Lin, and 叶林. "Exploring microbial community structures and functions of activated sludge by high-throughput sequencing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48079649.

Full text

Abstract:

To investigate the diversities and abundances of nitrifiers and to apply the highthroughput sequencing technologies to analyze the overall microbial community structures and functions in the wastewater treatment bioreactors were the major objectives of this study. Specifically, this study was conducted: (1) to investigate the diversities and abundances of AOA, AOB and NOB in bioreactors, (2) to explore the bacterial communities in bioreactors using 454 pyrosequencing, and (3) to analyze the metagenomes of activated sludge using Illumina sequencing. A lab-scale nitrification bioreactor was operated for 342 days under low DO (0.15~0.5 mg/L) and high nitrogen loading (0.26~0.52 kg-N/(m3d)). T-RFLP and cloning analysis showed there were only one dominant AOA, AOB and NOB species in the bioreactor, respectively. The amoA gene of the dominant AOA had a similarity of 89.3% with the isolated AOA species Nitrosopumilus maritimus SCM1. The AOB species detected in the bioreactor belonged to Nitrosomonas genus. The abundance of AOB was more than 40 times larger than that of AOA. The percentage of NOB in total bacteria increased from not detectable to 30% when DO changed from 0.15 to 0.5 mg/L. Compared with traditional methods, pyrosequencing analysis of the bacteria in this bioreactor provided unprecedented information. 494 bacterial OTUs was obtained at 3% distance cutoff. Furthermore, 454 pyrosequencing was applied to investigate the bacterial communities of activated sludge samples from 14 WWTPs of Asia (mainland China, Hong Kong, and Singapore) and North America (Canada and the United States). The results revealed huge amounts of OTUs in activated sludge, i.e. 1183~3567 OTUs in one sludge sample at 3% distance cutoff. Clear geographical differences among these samples were observed. The AOB amoA genes in different WWTPs were found quite diverse while the 16S rRNA genes were relatively conserved. To explore microbial community structures and functions in the abovementioned labscale bioreactor and a full-scale bioreactor, over six gigabases of metagenomic sequence data and 150,000 paired-end reads of PCR amplicons were generated from the activated sludge in the two bioreactors on Illumina HiSeq2000 platform. Three kinds of sequences (16S rRNA amplicons, 16S rRNA gene tags and predicted genes) were used to conduct taxonomic assignment and their applicabilities and reliabilities were compared. Specially, based on 16S rRNA and amoA gene sequences, AOB were found more abundant than AOA in the two bioreactors. Furthermore, the analysis of the metabolic profiles and pathways indicated that the overall pathways in the two bioreactors were quite similar. However, the abundances of some specific genes in the two bioreactors were different. In addition, 454 pyrosequencing was also used to detect potentially pathogenic bacteria in environmental samples. It was found most abundant potentially pathogenic bacteria in the WWTPs were affiliated with Aeromonas and Clostridium. Aeromonas veronii, Aeromonas hydrophila and Clostridium perfringens were species most similar to the potentially pathogenic bacteria found in this study. Overall, the percentage of the sequences closely related to known pathogenic bacteria sequences was about 0.16% of the total sequences. Additionally, a Java application (BAND) was developed for graphical visualization of microbial abundance data. published_or_final_version Civil Engineering Doctoral Doctor of Philosophy

APA, Harvard, Vancouver, ISO, and other styles

19

Rozmarynowycz, Mark Jeremy. "Spatio-Temporal Distribution Of Microbial Communities In TheLaurentian Great Lakes." Bowling Green State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1416427796.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Lemos, Leandro Nascimento. "Reconstrução e análise de genomas de bactérias de compostagem a partir de dados metagenômicos." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-07012016-094306/.

Full text

Abstract:

Na última década tem sido possível reconstruir o genoma de bactérias e arquéias presentes em comunidades microbianas de ambientes naturais a partir de dados metagenômicos. Isso tem revolucionado nosso entendimento sobre a topologia da árvore da vida e a descoberta de novas capacidades metabólicas, bem como auxiliado na identificação mais acurada de genes de interesse industrial, visto que os dados estão mais completos e menos fragmentados. Com base neste contexto, o objetivo geral deste projeto foi reconstruir o genoma de bactérias ligadas a degradação de biomassa vegetal em comunidades microbianas da compostagem, focando em análises de diversidade de enzimas de Glicosil Hidrolases (GHs), a partir de dados de sequências metagenômicas gerados no projeto temático processo 11/50870-6. Para alcançar os nossos objetivos, foram desenvolvidos pipelines computacionais com softwares já disponíveis na literatura e foram utilizados dois conjuntos principais de dados de sequenciamento massivo (um conjunto de dados seriados que engloba inúmeros estágios do processamento da compostagem e um conjunto de dados do metagenoma de um consórcio microbiano celulolítico e termofílico construído a partir de amostras da compostagem). Foram reconstruídos 13 genomas (sete genomas em amostras dos dados seriados e seis genomas na amostra do consórcio microbiano), sendo identificado no mínimo quatro novas espécies. As análises baseadas em filogenômica indicam a presença de pelo menos uma nova classe dentro do filo Firmicutes, uma nova espécie da família Paenibacillaceae e a reconstrução pela primeira vez do genoma da espécie Bacillus thermozeamaize. Também foram identificadas 33 lacunas/ilhas metagenômicas (IMs). Essas regiões apresentaram genes diretamente ligados a biossíntese de polissacarídeos do envelope celular, pseudogenes e proteínas hipotéticas. Algumas dessas proteínas estão diretamente ligadas ao reconhecimento de bacteríofagos durante a fase de infecção viral. A presença de IMs também indica uma divergência entre as populações microbianas presentes na compostagem com a espécie de referência. Quanto ao potencial de degradação de biomassa vegetal, todos os microrganismos apresentam genes com potencial para degradação de material lignocelulolítico durante o processamento de diferentes estágios da compostagem, indicando a importância do papel funcional dessas bactérias na compostagem. In the last decade it has been possible to reconstruct Bacteria and Archaea genomes that are in natural microbial communities from metagenomic samples. This has revolutionized our understanding of the topology of the tree of life and the discovery of new metabolic functions, as well as aided in more accurate identification of industrial bioprospecting genes, since the genomic data are more complete and less fragmented. Based on this background, the aim of this project was to reconstruct the bacterial genomes linked to plant biomass degradation in composting communities, focusing on diversity analysis of Glycosyl Hydrolases (GHs) from metagenomic sequence data generated in the Thematic Project (Process 11/50870-6). To achieve our objectives, computational pipelines have been developed (this pipelines were based on software already available in the literature) and we use these pipelines in two massive data sets generated by high-throughput sequencing (one data set of time series compost sample which includes several stages of the composting process and other data set from a cellu- lolytic and thermophilic microbial consortium). Thirteen genomes were reconstructed (seven genomes from time series metagenomic data and six genomes from microbial consortium). At least four new species have been identified, and the analyzes based on phylogenomic inferences indicate the presence of at least one new class of Firmicutes phylum, and a new Paenibacillaceae family and the reconstruction for the first time the Bacillus thermozeamaize genome. They also identified 33 gaps/metagenomic Islands (IMs). These gaps had genes directly linked to polysaccharide biosynthesis of the cell envelope, pseudogenes and hypothetical proteins. Some of these proteins are directly linked to the bacteriophage during the recognition phase of viral infection. The presence of gaps also indicates a divergence between microbial populations present in the compost with the reference genome. All microbial genomes reconstructed in this studyhave genes linked to lignocellulolytic potential degradation during the different stages of composting process, indicating the functional role this bactéria in this environment.

APA, Harvard, Vancouver, ISO, and other styles

21

Kremer, Frederico Schmitt. "Genix: desenvolvimento de uma nova pipeline automatizada para anotação de genomas microbianos." Universidade Federal de Pelotas, 2016. http://repositorio.ufpel.edu.br:8080/handle/prefix/3732.

Full text

Abstract:

Submitted by Maria Beatriz Vieira (mbeatriz.vieira@gmail.com) on 2017-10-18T12:09:03Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_frederico_schmitt_kremer.pdf: 1606431 bytes, checksum: 192db9fb559b24dfd0b3038659fdd5b7 (MD5) Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-10-23T11:10:01Z (GMT) No. of bitstreams: 2 dissertacao_frederico_schmitt_kremer.pdf: 1606431 bytes, checksum: 192db9fb559b24dfd0b3038659fdd5b7 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-10-23T11:11:40Z (GMT) No. of bitstreams: 2 dissertacao_frederico_schmitt_kremer.pdf: 1606431 bytes, checksum: 192db9fb559b24dfd0b3038659fdd5b7 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Made available in DSpace on 2017-10-23T11:11:52Z (GMT). No. of bitstreams: 2 dissertacao_frederico_schmitt_kremer.pdf: 1606431 bytes, checksum: 192db9fb559b24dfd0b3038659fdd5b7 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-02-17 Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq O advento do sequenciamento de DNA de nova geração (NGS) reduziu significativamente o custo dos projetos de sequenciamento de genomas. Quanto mais fácil é de obter novos dados genômicos, mais acuradas deve ser a etapa de anotação, de forma a se reduzir a perda de informações relevantes e efetuar o acúmulo de erros que possam afetar a acurácia das análises posteriores. No caso dos genomas bacterianos, um grande número de programas para anotação já foi desenvolvido, entretanto, muitos destes softwares não incorporaram etapas para otimizar os seus resultados, como filtragem de proteínas falso-positivas/spurious e a anotação mais completa de RNA não-codificantes. O presente trabalho descreve o desenvolvimento do Genix, uma nova pipeline automatizada que combina a funcionalidade de diferentes softwares, incluindo Prodigal, tRNAscan-SE, RNAmmer, Aragorn, INFERNAL, NCBI-BLAST+, CD-HIT, Rfam e Uniprot, com a intenção de aumentar a afetividade dos resultados de anotação. Para avaliar a acurácia da presente ferramenta, foram usados como modelo de estudo os genomas de referência de Escherichia coli K-12, Leptospira interrogans cepa Fiocruz L1-130, Listeria monocytogenese EGD-e e Mycobacterium tuberculosis H37Rv. Os resultados obtidos pelo Genix foram comparados às anotações originais e as obtidas pelas ferramentas de anotação RAST e BASys, considerando genes novos, faltantes e exclusivos, informações de anotação funcional e predições de ORFs spurious. De forma a se quantificar o grau de acurácia, uma nova métrica, denominada discrepância de anotação foi também proposta. Na análise comparativa o Genix apresentou para todos os genomas o menor valor de discrepância, variando entre 0,96 e 5,71%, sendo o maior valor observado no genoma de L. interrogans, para o qual RAST e BASys apresentaram valores superiores a 14,0%. Além disso, foram identificadas proteínas spurious nas anotações geradas pelos demais programas, e, em menor número, nas anotações de referência, indicando que a utilização do Antifam permite um melhor controle do número de genes falso positivos. A partir dos testes realizados, foi possível demonstrar que o Genix é capaz de gerar anotação com boa acurácia (baixo discrepância), menor perda de genes relevantes (funcionais) e menor número de genes falso positivos. The advent of next-generation sequencing (NGS) significantly reduced the cost of genome sequencing projects. The easier it is to generate genomic data, the more accurate the annotation steps must to be to avoid both the loss of information and the accumulation of erroneous features that may affect the accuracy of further analysis. In the case of bacteria genomes, a range of web annotation software has been developed; however, many applications have not incorporated the steps required to improve the output (eg: false-positive/spurious ORF filtering and a more complete non-coding RNA annotation). The present work describes the implementation of Genix, a new bacteria genome annotation pipeline that combines the functionality of the programs Prodigal, tRNAscan-SE, RNAmmer, Aragorn, INFERNAL, NCBI-BLAST+, CD-HIT, Rfam and UniProt, with the intention of increasing the effectiveness of the annotation results. To evaluate the accuracy of Genix, we used as models of study the reference genomes of Escherichia coli K-12, Leptospira interrogans strain Fiocruz L1-130, Listeria monocytogenes EGD-e and Mycobacterium tuberculosis H37Rv. the results obtained by Genix were compared to the original annotation and to those from the annotation pipelines RAST and BASys considering new, missing and exclusive genes, functional annotation information and the prediction of spurious ORFs. To quantify the annotation accuracy, a new metric, called “annotation discrepancy” was developed. In a comparative analysis, Genix showed the smallest discrepancy for the four genomes, ranging for 0.96 to 5.71%, the highest discrepancy was bserved in the L. interrogans genome, for which RAST and BASys resulted in discrepancies greater than 14.0%. Additionally, several spurious proteins were identified in the annotations generated by RAST and BASys, and, in smaller number, in the reference annotations, indicating that the use of the Antifam database allows a better control of the number of false-positive genes. Based on the evaluations, it was possible to show that Genix is able to generate annotations with good accuracy (low discrepancy), low omission of relevant (functional) genes and a small number of false-positive genes.

APA, Harvard, Vancouver, ISO, and other styles

22

Driscoll, Timothy. "Host-Microbe Relations: A Phylogenomics-Driven Bioinformatic Approach to the Characterization of Microbial DNA from Heterogeneous Sequence Data." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/50921.

Full text

Abstract:

Plants and animals are characterized by intimate, enduring, often indispensable, and always complex associations with microbes. Therefore, it should come as no surprise that when the genome of a eukaryote is sequenced, a medley of bacterial sequences are produced as well. These sequences can be highly informative about the interactions between the eukaryote and its bacterial cohorts; unfortunately, they often comprise a vanishingly small constituent within a heterogeneous mixture of microbial and host sequences. Genomic analyses typically avoid the bacterial sequences in order to obtain a genome sequence for the host. Metagenomic analysis typically avoid the host sequences in order to analyze community composition and functional diversity of the bacterial component. This dissertation describes the development of a novel approach at the intersection of genomics and metagenomics, aimed at the extraction and characterization of bacterial sequences from heterogeneous sequence data using phylogenomic and bioinformatic tools. To achieve this objective, three interoperable workflows were constructed as modular computational pipelines, with built-in checkpoints for periodic interpretation and refinement. The MetaMiner workflow uses 16S small subunit rDNA analysis to enable the systematic discovery and classification of bacteria associated with a host genome sequencing project. Using this information, the ReadMiner workflow comprehensively extracts, assembles, and characterizes sequences that belong to a target microbe. Finally, AssemblySifter examines the genes and scaffolds of the eukaryotic genome for sequences associated with the target microbe. The combined information from these three workflows is used to systemically characterize a bacterial target of interest, including robust estimation of its phylogeny, assessment of its signature profile, and determination of its relationship to the associated eukaryote. This dissertation presents the development of the described methodology and its application to three eukaryotic genome projects. In the first study, the genomic sequences of a single, known endosymbiont was extracted from the genome sequencing data of its host. In the second study, a highly divergent endosymbiont was characterized from the assembled genome of its host. In the third study, genome sequences from a novel bacterium were extracted from both the raw sequencing data and assembled genome of a eukaryote that contained significant amounts of sequence from multiple competing bacteria. Taken together, these results demonstrate the usefulness of the described approach in singularly disparate situations, and strongly argue for a sophisticated, multifaceted, supervised approach to the characterization of host-associated microbes and their interactions. Ph. D.

APA, Harvard, Vancouver, ISO, and other styles

23

Li, Wei. "INFLUENCE OF ENVIRONMENTAL DRIVERS AND INTERACTIONS ON THE MICROBIAL COMMUNITY STRUCTURE IN PERMANENTLY STRATIFIED MEROMICTIC ANTARCTIC LAKES." Miami University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=miami1469757316.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Zhong, Xiao. "A study of several statistical methods for classification with application to microbial source tracking." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0430104-155106/.

Full text

Abstract:

Thesis (M.S.)--Worcester Polytechnic Institute. Keywords: classification; k-nearest-neighbor (k-n-n); neural networks; linear discriminant analysis (LDA); support vector machines; microbial source tracking (MST); quadratic discriminant analysis (QDA); logistic regression. Includes bibliographical references (p. 59-61).

APA, Harvard, Vancouver, ISO, and other styles

25

Gregory, Jill Christine. "Transmission of Atherosclerosis and Thrombosis Susceptibility with Gut Microbial Transplantation." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1437067679.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Wei, Yulong. "Microbes Carry Distinct Genomic Signatures in Adaptation to Their Translation Machinery and Host Environments." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42422.

Full text

Abstract:

How do bacteria grow and replicate rapidly? How do viruses and phages adapt to their host environments? Bacteria require efficient translation to grow and replicate rapidly, and translation is often rate-limited by initiation. A feature that is conserved across bacterial lineages is the Shine-Dalgarno (SD) sequence at the mRNA 5’ UTR, which pairs with the anti-SD sequence located at the 3’ end of mature 16S rRNA. Nonetheless, much about this interaction remains unclear. Chapter 2 reveals evolutionary differences between Cyanobacteria and chloroplast translation initiation using a new model (DtoStart) that better define optimal SD sequence and an RNA-Seq-based approach that reliably characterize the 3’ end of mature 16S rRNAs. Efficacy of translation elongation depends much on tRNA-mediated codon adaptation. In Escherichia coli, selection favours major codons because they are rapidly decoded by abundantly available cognate tRNAs. Nonetheless, the degree codon bias correlates with tRNA availability is unclear in many bacterial species because tRNA abundance is often inadequately approximated by gene copy numbers. To better understand tRNA-mediated codon bias, Chapter 3 describes an RNA-Seq-based approach to robustly quantify tRNA abundance. Finally, Chapter 4 evaluates the degree optimal translation initiation and elongation signals affect ribosome dynamics. The emergence of COVID-19 pandemic poses a serious global health emergency. To establish infection during cell entry, the coronavirus Spike protein binds to the host ACE2 receptor, and a high binding potential between these two players is key to infectivity. While SARS-CoV-2 transmits efficiently in humans, it is less clear which other mammals are at risk of being infected. Chapter 5 investigates the host range of SARS-CoV-2 through comparative sequence analyses at the ACE2 receptors and the Spike proteins. As obligate parasites, coronaviruses regularly infect host tissues that express antiviral proteins (AVPs) in abundance and must evade or adapt to the host cellular environments post-entry. Two AVPs that shape viral genomes are ZAP that binds to CpG dinucleotides to facilitate viral transcript degradation, and APOBEC3 which deaminates C into U leading to dysfunctional transcripts. Chapter 6 shows that coronavirus genomes are CpG deficient to evade ZAP and are subjected to constant C to U deamination by APOBEC3. This thesis examines two key concepts of microbial genome evolution: 1) coevolution between gene features and the translation machinery in bacteria, and 2) adaptation of viruses to the hosts they infect. Chapters 2, 3, and 4 are aimed at improving our understanding in bacterial gene expression in the applications of transgenic biosynthesis and phage therapy. Chapters 5 and 6 are aimed at improving our understanding in the origin and evolution of SARS-CoV-2 and our ability to control the spread of infection.

APA, Harvard, Vancouver, ISO, and other styles

27

Hathaway, Nicholas J. "A suite of computational tools to interrogate sequence data with local haplotype analysis within complex Plasmodium infections and other microbial mixtures." eScholarship@UMMS, 2018. https://escholarship.umassmed.edu/gsbs_diss/970.

Full text

Abstract:

The rapid development of DNA sequencing technologies has opened up new avenues of research, including the investigation of population structure within infectious diseases (both within patient and between populations). In order to take advantage of these advances in technologies and the generation of new types of data, novel bioinformatics tools are needed that won’t succumb to artifacts introduced by the data generation, and thus provide accurate and precise results. To achieve this goal I have create several tools. First, SeekDeep, a pipeline for analyzing targeted amplicon sequencing datasets from various technologies, is able to achieve 1-base resolution even at low frequencies and read depths allowing for accurate comparison between samples and the detection of important SNPs. Next, PathWeaver, a local haplotype assembler designed for complex infections and highly variable genomic regions with poor reference mapping. PathWeaver is able to create highly accurate haplotypes without generating chimeric assemblies. PathWeaver was used on the key protein in pregnancy-associated malaria Plasmodium falciparum VAR2CSA which revealed population sub-structuring within the key binding domain of the protein observed to be present globally along with confirming copy number variation. Finally, the program Carmen is able to utilize PathWeaver to augment the results from targeted amplicon approaches by reporting where and when local haplotypes have been found previously. These rigorously tested tools allow the analysis of local haplotype data from various technologies and approaches to provide accurate, precise and easily accessible results.

APA, Harvard, Vancouver, ISO, and other styles

28

Mahato, Joyanto. "Comparative study of three Fe (III)-ion reducing bacteria gives insights into bioelectricity generation in the MFC technique." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-18598.

Full text

Abstract:

Microbial fuel cell (MFC) technology is a renewable energy source that employs microorganisms as biocatalysts to degrade substrates into electrons and protons, and then transfer the electrons to the anode electrode. Electron transfer rates by microorganisms depend on many factors as well as on their diverse electron transfer mechanisms. The present study compared cytochromes, flavoproteins, electron transfer complexes, redoxins and other extracellular membrane proteins that have direct involvement in electron transfer mechanisms in Escherichia coli str. K-12 MG1655, Rhodopseudomonas pulastris DX-1 and Shewanella oneidensis MR-1. Escherichia coli str. The results showed that K-12 MG1655 had a more diverse range of extracellular proteins for electron transfer mechanisms compared to Rhodopseudomonas pulastris DX-1 and Shewanella oneidensis MR-1. Escherichia coli str. K-12 MG1655 expressed more flavoproteins, redoxin and electron transfer complex related proteins that had direct involvement in electron transfer mechanisms compared to two other bacterial species indicating that it may be able to transfer more electrons when employed in MFC technique. Escherichia coli str. K-12 MG1655 expressed 16 cytochromes, 9 flavoproteins, 6 redoxins, 6 electron transport complexes, 1 hypothetical and 1 oxidoreductase proteins. On the other hand, Rhodopseudomonas pulastris DX-1 and Shewanella oneidensis MR-1 expressed 26 and 35 cytochromes proteins. But these two bacterial species expressed less flavoproteins and redoxin related proteins and they didn’t express any electron transport complexes or hypothetical and oxidoreductase related proteins for electron transfer. STRING and SMART results suggested that the identified proteins transferred electrons either by connecting with other types of identified proteins in the constructed gene network or independently by taking part in oxidation-reduction reaction, metal ion reduction reaction or by their FMN binding activities.

APA, Harvard, Vancouver, ISO, and other styles

29

Karns, Rachael Cassandra. "Microbial Community Richness Distinguishes Shark Species Microbiomes in South Florida." NSUWorks, 2017. http://nsuworks.nova.edu/occ_stuetd/453.

Full text

Abstract:

The microbiome (microbial community) of individuals is crucial when characterizing and understanding processes that are required for organism function and survival. Microbial organisms, which make up an individual’s microbiome, can be linked to disease or function of the host organism. In humans, individuals differ substantially in their microbiome compositions in various areas of the body. The cause of much of the composition diversity is yet unexplained, however, it is speculated that habitat, diet, and early exposure to microbes could be altering the microbiomes of individuals (Human Microbiome Project Consortium, 2012b, 2012a). To date, only one study has reported on microbiome characterization in a shark (Doane et al., 2017; skin microbiome of the common thresher shark). A comparative characterization of microbiomes sampled from different shark species and anatomical locations will allow an understanding of the differences in microbiomes that may be explained by variance in shark habitat and diet. Florida leads as shark bite capitol of the world, with 778 unprovoked bites recorded since 1837, or 4-5 average bites per year. With only a few bites a year, there is not a lot of opportunities to study these bites. What can be studied, however, is how the microbial environment in shark’s teeth is composed. To understand overall microbiome composition, and if microbiomes are distinct from the environment, or specific by species or anatomical location (henceforth location), we characterized microbiomes from the teeth, gill, skin, and cloacal microbiomes of 8 shark species in south Florida (nurse, lemon, sandbar, Caribbean reef, Atlantic sharpnose, blacktip, bull, and tiger) using high throughput DNA sequencing of the 16S rRNA gene V4 region. There was a significant difference in microbial community richness among species, sample location, but not the interaction between species and location. Microbial diversity by location was significantly different for both the Shannon index and Inverse Simpson index. Samples examined by species had no significant difference in microbial community diversity overall for both Shannon and Inverse Simpson indexes. Microbial community diversity of samples by location and species combined significantly differed when submitted to an analysis of variance with the Shannon index, but not the Inverse Simpson index. Teeth microbial communities showed the most diversity based on both Shannon and Inverse Simpson indices. Teeth microbiomes are distinct but also share taxa with the water they inhabit, including potentially pathogenic genera such as Streptococcus (8.0% ± 9.0%) and Haemophilus (2.9% ± 3.3%) in the Caribbean reef shark. The lemon shark teeth hosted Vibrio (10.8% ± 26.0%) and the Corynebacterium genus (1.6%±5.1%). The Vibrio genus (2.8% ± 6.34%), Salmonella enterica (2.6% ± 6.4%), and the genus Kordia (3.1% ± 6.0%) are found in the nurse shark teeth microbial community. Strikingly, the Vibrio genus was represented in the sandbar shark (54.0% ± 46.0%) and tiger shark (5.8% ±12.3%) teeth microbiomes. One OTU related to traditionally non-pathogenic family Phyllobacteriaceae appear to be driving up to 32% of variance in teeth microbiome diversity. We conclude that south Florida sharks host distinct microbiomes from the surrounding environment and vary among species due to differences in microbial community richness. Future work should focus on bacteria found in shark teeth to determine if those present are pathogenic and could provide insights to bite treatment.

APA, Harvard, Vancouver, ISO, and other styles

30

Patel, Jignasa. "Meta-Transcriptome Profiles of the Marine Sponge, Axinella corrugata and its Microbial Consortia: A Pyrosequencing Approach." NSUWorks, 2012. http://nsuworks.nova.edu/occ_stuetd/174.

Full text

Abstract:

Marine micro-organisms are important components of various biogeochemical cycles, complex food webs and ecological niches. Metagenomic sequencing can provide rapid profile of metabolic activities within the sponge and resident microbes. However, the study of metatranscriptomes from sponges using high throughput sequencing technology has only recently begun. Through this study we isolated, characterized and compared metatranscriptome profiles of Axinella corrugata host and sponge-specific microbial communities using 454 pyrosequencing technology. Four cDNA libraries (two eukaryotic and two prokaryotic) were generated from Axinella corrugata sponge samples collected in December 2009 and May 2010, and were characterized to a) reveal which metabolic genes were actively expressed and b) reveal possible interactions between the sponge and its microbial symbionts. The techniques used for isolation of mRNA and cDNA normalization also helped in optimization of whole-transcriptome amplification. More than 130,000 ESTs were generated for the two seasonal sponge samples and the metagenomic data sets were analyzed using bioinformatics tool, MG-RAST. Several stress-related transcripts were found which can increase our understanding of sensitivity of the sponge to changes in physical parameters in nature. The involvement of the sponge and its microbial consortia is depicted through actively expressed nitrogen and sulfur metabolism genes. Novel genes involved in several functional pathways may be discovered upon further studying hypothetical genes found across all four metagenomic data sets. Metatranscriptomic data sheds light on the functional role of microbes within the sponges and the extent of their involvement in sponge metabolism. 16S rRNA analysis was also carried out using genomic DNA of the same samples, to better elucidate the bacterial taxa abundance in the sponge. This study provides a profile of active mRNA trancripts in Axinella corrugata which include eukaryotic as well as prokaryotic sequences. The data analysis of this research provides new information at the cross-disciplinary interface between molecular biology and computational science.

APA, Harvard, Vancouver, ISO, and other styles

31

Damaso, Natalie. "Biogeographical Patterns of Soil Microbial Communities: Ecological, Structural, and Functional Diversity and their Application to Soil Provenance." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/3006.

Full text

Abstract:

The current ecological hypothesis states that the soil type (e.g., chemical and physical properties) determines which microbes occupy a particular soil and provides the foundation for soil provenance studies. As human profiles are used to determine a match between evidence from a crime scene and a suspect, a soil microbial profile can be used to determine a match between soil found on the suspect’s shoes or clothing to the soil at a crime scene. However, for a robust tool to be applied in forensic application, an understanding of the uncertainty associated with any comparisons and the parameters that can significantly influence variability in profiles needs to be determined. This study attempted to address some of the most obvious uncertainties of soil provenance applications such as spatial variability, temporal variability, and marker selection (i.e., taxa discrimination). Pattern analysis was used to validate the ecological theories driving the soil microbial biogeography. Elucidating soil microbial communities’ spatial and temporal variability is critical to improve our understanding of the factors regulating their structure and function. Microbial profiling and bioinformatics analyses of the soil community provided a rapid method for soil provenance that can be informative, easier to perform, and more cost effective than approaches using traditional physico-chemical data. This study also showed that stable profiles may allow comparison between evidence and a possible crime scene despite the time lapse (4 years) between sample collections, however, this is dependent on the analysis method, site, vegetation, and level of disturbance. Marker selection was also an important consideration for profiling. Even though Fungi look promising for single taxon soil discrimination, the additional markers can help discriminate between a wide variety of soil types. As in human identification, the more DNA markers queried the greater the discrimination power. Lastly, this study illustrated a novel method to query the iron relating genes and ability to design a novel marker that can easily be used to profile the functional diversity of a soil community to enhance soil classification. Overall this research demonstrated the potential and effectiveness of using microbial DNA from soil, not just for comparison, but also for intelligence gathering to pinpoint the geographic origin of the soil.

APA, Harvard, Vancouver, ISO, and other styles

32

Fernández, Guerra Antonio. "Ecology and evolution of microbial nitrifiers / Ecología y evolución de los microorganismos nitrificantes." Doctoral thesis, Universitat de Barcelona, 2013. http://hdl.handle.net/10803/108001.

Full text

Abstract:

Ammonia oxidation, the first and the rate-limiting step in nitrification, is one of the cornerstones of the cycle. Members from the bacterial and archaeal domains are key players in ammonia oxidation in many different environ- ments. Usually these organisms are found coexisting but the most recent studies suggests that archaeal ammonia oxidizers show an incredible ability to adapt and oxidize ammonia under different environmental conditions and have displaced their bacterial counterparts in terms of importance in the global biogeochemical cycle, providing an avalanche of AOA molecular data (16S rDNA and amoA gene sequences) from very diverse environments worldwide. As far as we don’t have enough genomic data to perform an holistic approach using population genomics and reverse ecology to unveil the ecological and evolutionary mechanisms driving the adaptation; we focused our experiments on the amoA gene sequence. Because ammonia monooxygenase is supposed to be the key enzyme in the ammonia oxidation, we applied a combination of community ecology and molecular evolution methods to understand the mechanisms of the diversification patterns observed in the amoA gene. Another unsolved question in the archaeal ammonia oxidation is the unusual biochemistry found in the genome sequences from cultured archaeal ammonia oxidizers. In archaea, all the elements of the bacterial ammonia oxidizing pathway are missing but the genes coding for the presumptive AMO. To unveil missing pathways in this process, we have developed a powerful approach based on graphical models to capture all the functional associations present in metagenomes based in their ecological co-ocurrence. The results of the analyses revealed for the first time a global picture of the phylogenetic community structure of ammonia- oxidizing assemblages. Our study unveiled larger phylogenetic richness in AOA with more dissimilar communities and clear monophyletic groups for the different habitats. The rates of diversification in AOA were higher than in AOB and the archaeal diversification dynamics showed an unusual feature, with an initial diversification process followed by a long period of stasis and a final burst of diversification. The variations observed between AOB and AOA in terms of community structure, phylogenetic diversity, diversification patterns, and habitat dispersion were unexpected just a very few years ago, and the community phylogenetics approach has nicely captured these differences. Understand the diversification processes observed in AOA and their successful performance under a myriad of different environmental conditions such as low pH, different ammonia concentrations, high hydrostatic pressures, high light exposure, low oxygen availability among others, needs however of a deeper insight adding the evolutionary processes. Individual changes at the level of nucleotides were translated to the global diversification patterns of archaeal ammonia oxidizers. Thus, this resulted in a step further from the results obtained after applying community phylogenetics methods providing precise evolutionary information behind the phylogenetic patterns observed within an ecological context. We will gain the full picture once the results can be integrated in a comparative genomics framework. After applying methods of reverse engineering of regulatory the associations between the known and the unknown fraction were reconstructed offering a pioneering fresh view for microbial ecology. One especially relevant result obtained from this approach on AOA was the reconstruction of the association network of the different AMO subunits to the other proteins previously reported in the marine AOA Nitrosopumilus. The information recovered from metagenomics combined with available genomes fuels hypothesis for the particular and yet unknown biochemistry of ammonia oxidation in Archaea. La oxidación del amonio es una de las piezas clave del ciclo del Nitrógeno. Tanto las bacterias como las arqueas oxidadoras del amonio se pueden encontrar coexistiendo a lo largo de diferentes ambientes. Pero cuando la primera arquea oxidadora del amonio fue aislada, se puso en relevancia la importancia de estas en comparación con las bacterias en los ciclos biogeoquímicos globales. Desde entonces hemos sido inundados por una avalancha de secuencias génicas de estas arqueas, mostrando una gran capacidad de diversificación y adaptación a ambientes diferentes. Al no disponer de suficientes datos para realizar una aproximación holistica utilizando genómica de poblaciones y de ecología inversa para poder discernir los mecanismos ecológicos y evolutivos relacionados con la adaptación; nos hemos centrado en estudiar la secuencia del amoA. La amonio monooxigenasa es la enzima responsable de la oxidación del amonio, para su estudio hemos aplicado una combinación de técnicas de ecología de comunidades y de evolución molecular con el objetivo de entender los mecanismos de los patrones de diversificación observados. Por otra banda, otro de los misterios asociados a la oxidación del amonio por parte de las arqueas, es su inusual bioquímica para realizar la oxidación del amonio. En arqueas faltan todos los elementos necesarios para llevar a cabo la oxidación del amonio a excepción del AMO. Para poder aportar algo de luz a este misterio hemos desarrollado un potente método basado en modelos gráficos para capturar todas las asociaciones funcionales presentes en los metagenomas basado en sus co-ocurrencias ecológicas.

APA, Harvard, Vancouver, ISO, and other styles

33

Blank, Carrine E., Hong Cui, Lisa R. Moore, and Ramona L. Walls. "MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions." BIOMED CENTRAL LTD, 2016. http://hdl.handle.net/10150/614758.

Full text

Abstract:

Background: MicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The ontology was built to support the ongoing development of a natural language processing algorithm, MicroPIE (or, Microbial Phenomics Information Extractor). During the MicroPIE design process, we realized there was a need for a prokaryotic ontology which would capture the evolutionary diversity of phenotypes and metabolic processes across the tree of life, capture the diversity of synonyms and information contained in the taxonomic literature, and relate microbiological entities and processes to terms in a large number of other ontologies, most particularly the Gene Ontology (GO), the Phenotypic Quality Ontology (PATO), and the Chemical Entities of Biological Interest (ChEBI). We thus constructed MicrO to be rich in logical axioms and synonyms gathered from the taxonomic literature. Results: MicrO currently has similar to 14550 classes (similar to 2550 of which are new, the remainder being microbiologically-relevant classes imported from other ontologies), connected by similar to 24,130 logical axioms (5,446 of which are new), and is available at (http://purl.obolibrary.org/obo/MicrO.owl) and on the project website at https://github.com/carrineblank/MicrO. MicrO has been integrated into the OBO Foundry Library (http://www.obofoundry.org/ontology/micro.html), so that other ontologies can borrow and re-use classes. Term requests and user feedback can be made using MicrO's Issue Tracker in GitHub. We designed MicrO such that it can support the ongoing and future development of algorithms that can leverage the controlled vocabulary and logical inference power provided by the ontology. Conclusions: By connecting microbial classes with large numbers of chemical entities, material entities, biological processes, molecular functions, and qualities using a dense array of logical axioms, we intend MicrO to be a powerful new tool to increase the computing power of bioinformatics tools such as the automated text mining of prokaryotic taxonomic descriptions using natural language processing. We also intend MicrO to support the development of new bioinformatics tools that aim to develop new connections between microbial phenotypes and genotypes (i.e., the gene content in genomes). Future ontology development will include incorporation of pathogenic phenotypes and prokaryotic habitats.

APA, Harvard, Vancouver, ISO, and other styles

34

Schneider, Barbara Schaedler Fidelis. "ANÁLISE METAGENÔMICA DE BACTÉRIAS DIAZOTRÓFICAS DE SOLOS ORGÂNICOS DO ESTADO DO PARANÁ." UNIVERSIDADE ESTADUAL DE PONTA GROSSA, 2016. http://tede2.uepg.br/jspui/handle/prefix/140.

Full text

Abstract:

Made available in DSpace on 2017-07-21T14:19:29Z (GMT). No. of bitstreams: 1 BARBARA S F.pdf: 4456843 bytes, checksum: 3391dc9c3b4a16b452d346cd9b46e209 (MD5) Previous issue date: 2016-09-09 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior The organic soils from High-Elevation Grasslands of the Parana State are characterized by being large water tanks which fix carbon, have low pH and are poor in nutrients. Though are essential to the Atlantic Forest, there is little information on the microorganisms involved in its maintenance. In this work, microbiological data of organic soils in three different regions, during the dry and rainy seasons were analyzed. Using bioinformatics and statistic tools, nifH gene pirosequences were analyzed to determine the structure of diazotrophic communities and to identify the environmental factors that affect their diversity. The sequences of the nifH gene showed the prevalence of Proteobacteria (35.25%) followed by Spirochaetes (1.27%), Firmicutes (0.80%), Cyanobacteria (0.76%), Chlorobi (0.41%) Actinobacteria (0.10%) and Bacteriodetes (0.04%). Bradyrhizobium was the most abundant genus in the six libraries analyzed, presenting a positive correlation with the increase in the soil pH. Most of nifH gene OTUs showed to be cosmopolitan and the endemism was related to rare species. The OTUs classified as Proteobacteria, Calothrix, Spirochaeta, Halorhodospira, Rhizobiales, Alphaproteobacteria and Bradyrhizobium presented a significant correlation with the rainfall indexes. Os solos orgânicos dos Campos de Altitude paranaense caracterizam-se por serem grandes reservatórios de água, fixarem carbono, terem baixo pH e serem pobres em nutrientes. Embora sejam essenciais para a Mata Atlântica, há pouca informação sobre os microrganismos envolvidos na sua manutenção. Nesse trabalho, foram analisados dados microbiológicos de solos orgânicos de três regiões distintas, durante as estações de seca e chuva. Utilizando ferramentas de bioinformática e estatística foram analisadas pirossequencias do gene nifH para determinar a estrutura das comunidades diazotróficas e para identificar os fatores ambientais que afetam a sua diversidade. As sequências do gene nifH mostraram a prevalência de Proteobactéria (35,25%) seguida por Spirochaetes (1,27%), Firmicutes (0,80%), Cyanobacteria (0,76%), Chlorobi (0,41%), Actinobacteria (0,10%) e Bacteriodetes (0,04%). Bradyrhizobium foi o gênero mais abundante nas seis bibliotecas analisadas, apresentando correlação positiva com o aumento do pH dos solos. A maioria das OTU do gene nifH foram cosmopolitas e o endemismo está relacionado às espécies raras. As OTU classificadas como Proteobacteria, Calothrix, Spirochaeta, Halorhodospira, Rhizobiales, Alfaproteobacteria e Bradyrhizobium apresentaram significativa correlação com os índices pluviométricos.

APA, Harvard, Vancouver, ISO, and other styles

35

Pan, Juan. "Ether Bridge Formation and Chemical Diversification in Loline Alkaloid Biosynthesis." UKnowledge, 2014. http://uknowledge.uky.edu/plantpath_etds/14.

Full text

Abstract:

Loline alkaloids, found in many grass-Epichloë symbiota, are toxic or feeding deterrent to invertebrates. The loline alkaloids all share a saturated pyrrolizidine ring with a 1-amine group and an ether bridge linking C2 and C7. The steps in biosynthesis of loline alkaloids are catalyzed by enzymes encoded by a gene cluster, designated LOL, in the Epichloë genome. This dissertation addresses the enzymatic, genetic and evolutionary basis for diversification of these alkaloids, focusing on ether bridge formation and the subsequent modifications of the 1-amine to form different loline alkaloids. Through gene complementation of a natural lolO mutant and comparison of LOL clusters in strains with different loline alkaloid profiles, I found that lolO, predicted to encode a 2-oxoglutarate-dependent nonheme iron (2OG/Fe) dioxygenase, is required in formation of the ether bridge. Through application of isotopically labeled compound to Epichloë uncinata culture, I established that exo-1-acetamidopyrrolizidine (AcAP) and N-acetylnorloline (NANL) are true pathway intermediates. Application of AcAP to yeast expressing lolO resulted in production of NANL, establishing that LolO is sufficient to catalyze this unusual oxygenation reaction. After ether formation, modifications on the 1-amino group give loline, N-methylloline (NML), N-formylloline (NFL) and N-acetylloline (NAL). A double knockout of lolN, predicted to encode an acetamidase, and lolM, predicted to encode a methyltransferase, produced only NANL. Complementation of the double knockout with wild-type lolN and lolM restored the loline alkaloid profile. These results indicate that LolN is involved in deacetylating NANL to produce norloline, which is then modified to form the other lolines. Crude protein extract of a yeast transformant expressing LolM converted norloline to loline and NML, and loline to NML, supporting the hypothesis that LolM functions as a methyltransferase in the loline-alkaloid biosynthesis pathway. The alkaloid NAL was observed in some but not all plants symbiotic with Epichloë siegelii, and when provided with exogenous loline, asymbiotic meadow fescue (Lolium pratense) plants produced N-acetylloline (NAL), indicating that a plant acetyltransferase converts loline to NAL. I further analyzed the basis for loline alkaloid diversity by comparing the LOL clusters in the Epichloë and Atkinsonella species with different loline alkaloid profiles, and found that LOL clusters changed position, orientation and gene content over their evolutionary history. Frequent, independent losses of some or all late pathway genes, lolO, lolN, lolM and lolP, resulted in diverse loline alkaloid profiles. In addition, phylogenetic analyses demonstrated transspecies polymorphism of the LOL clusters. Based on my findings, I established that in Epichloë and Atkinsonella species the ether bridge is formed on acetamidopyrrolizidine. My study of the loline alkaloid profile of Adenocarpus decorticans (Fabaceae) suggests that these plants probably use a similar strategy at least with respect to ether-bridge formation. Further diversification steps of loline alkaloids in grass-Clavicipitaceae symbiota are carried out by enzymes of both Epichloë species and the host plant. Finally, I present evidence that LOL clusters have evolved by balancing selection for chemical diversity.

APA, Harvard, Vancouver, ISO, and other styles

36

Janky, Rekin's. "Etude bioinformatique de l'évolution de la régulation transcriptionnelle chez les bactéries." Doctoral thesis, Universite Libre de Bruxelles, 2007. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210603.

Full text

Abstract:

L'objet de cette thèse de bioinformatique est de mieux comprendre l’ensemble des systèmes de régulation génique chez les bactéries. La disponibilité de centaines de génomes complets chez les bactéries ouvre la voie aux approches de génomique comparative et donc à l’étude de l’évolution des réseaux transcriptionnels bactériens. Dans un premier temps, nous avons implémenté et validé plusieurs méthodes de prédiction d’opérons sur base des génomes bactériens séquencés. Suite à cette étude, nous avons décidé d’utiliser un algorithme qui se base simplement sur un seuil sur la distance intergénique, à savoir la distance en paires de bases entre deux gènes adjacents. Notre évaluation sur base d’opérons annotés chez Escherichia coli et Bacillus subtilis nous permet de définir un seuil optimal de 55pb pour lequel nous obtenons respectivement 78 et 79% de précision. Deuxièmement, l’identification des motifs de régulation transcriptionnelle, tels les sites de liaison des facteurs de transcription, donne des indications de l’organisation de la régulation. Nous avons développé une méthode de recherche d’empreintes phylogénétiques qui consiste à découvrir des paires de mots espacés (dyades) statistiquement sur-représentées en amont de gènes orthologues bactériens. Notre méthode est particulièrement adaptée à la recherche de motifs chez les bactéries puisqu’elle profite d’une part des centaines de génomes bactériens séquencés et d’autre part les facteurs de transcription bactériens présentent des domaines Hélice-Tour-Hélice qui reconnaissent spécifiquement des dyades. Une évaluation systématique sur 368 gènes de E.coli a permis d’évaluer les performances de notre méthode et de tester l’influence de plus de 40 combinaisons de paramètres concernant le niveau taxonomique, l’inférence d’opérons, le filtrage des dyades spécifiques de E.coli, le choix des modèles de fond pour le calcul du score de significativité, et enfin un seuil sur ce score. L’analyse détaillée pour un cas d’étude, l’autorégulation du facteur de transcription LexA, a montré que notre approche permet d’étudier l’évolution des sites d’auto-régulation dans plusieurs branches taxonomiques des bactéries. Nous avons ensuite appliqué la détection d’empreintes phylogénétiques à chaque gène de E.coli, et utilisé les motifs détectés comme significatifs afin de prédire les gènes co-régulés. Au centre de cette dernière stratégie, est définie une matrice de scores de significativité pour chaque mot détecté par gène chez l’organisme de référence. Plusieurs métriques ont été définies pour la comparaison de paires de profils de scores de sorte que des paires de gènes ayant des motifs détectés significativement en commun peuvent être regroupées. Ainsi, l’ensemble des nos méthodes nous permet de reconstruire des réseaux de co-régulation uniquement à partir de séquences génomiques, et nous ouvre la voie à l’étude de l’organisation et de l’évolution de la régulation transcriptionnelle pour des génomes dont on ne connaît rien.The purpose of my thesis is to study the evolution of regulation within bacterial genomes by using a cross-genomic comparative approach. Nowadays, numerous genomes have been sequenced facilitating in silico analysis in order to detect groups of functionally related genes and to predict the mechanism of their relative regulation. In this project, we combined prediction of operons and regulons in order to reconstruct the transcriptional regulatory network for a bacterial genome. We have implemented three methods in order to predict operons from a bacterial genome and evaluated them on hundreds of annotated operons of Escherichia coli and Bacillus subtilis. It turns out that a simple distance-based threshold method gives good results with about 80% of accuracy. The principle of this method is to classify pairs of adjacent genes as “within operon” or “transcription unit border”, respectively, by using a threshold on their intergenic distance: two adjacent genes are predicted to be within an operon if their intergenic distance is smaller than 55bp. In the second part of my thesis, I evaluated the performances of a phylogenetic footprinting approach based on the detection of over-represented spaced motifs. This method is particularly suitable for (but not restricted to) Bacteria, since such motifs are typically bound by factors containing a Helix-Turn-Helix domain. We evaluated footprint discovery in 368 E.coli K12 genes with annotated sites, under 40 different combinations of parameters (taxonomical level, background model, organism-specific filtering, operon inference, significance threshold). Motifs are assessed both at the level of correctness and significance. The footprint discovery method proposed here shows excellent results with E. coli and can readily be extended to predict cis-acting regulatory signals and propose testable hypotheses in bacterial genomes for which nothing is known about regulation. Moreover, the predictive power of the strategy, and its capability to track the evolutionary divergence of cis-regulatory motifs was illustrated with the example of LexA auto-regulation, for which our predictions are remarkably consistent with the binding sites characterized in different taxonomical groups. A next challenge was to identify groups of co-regulated genes (regulons), by regrouping genes with similar motifs, in order to address the challenging domain of the evolution of transcriptional regulatory networks. We tested different metrics to detect putative pairs of co-regulated genes. The comparison between predicted and annotated co-regulation networks shows a high positive predictive value, since a good fraction of the predicted associations correspond to annotated co-regulations, and a low sensitivity, which may be due to the consequence of highly connected transcription factors (global regulator). A regulon-per-regulon analysis indeed shows that the sensitivity is very weak for these transcription factors, but can be quite good for specific transcription factors. The originality of this global strategy is to be able to infer a potential network from the sole analysis of genome sequences, and without any prior knowledge about the regulation in the considered organism. Doctorat en Sciences info:eu-repo/semantics/nonPublished

APA, Harvard, Vancouver, ISO, and other styles

37

Ahmad, Sarah. "Identification of pathogen-specific protein-encoding genes from microbial pathogens based on bioinformatic analysis." Thesis, University of Exeter, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425246.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Gordon, Skyler A. "An Assessment of Potential False Positive E.coli Pyroprints in the CPLOP Database." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1730.

Full text

Abstract:

The genetic information found in each species of organism is unique, and can be used as a tool to differentiate at the molecular level. This has caused rapid genotyping methods to become the cornerstone of a new area of research dependent on reading the genome as a form of identification. One of these specific identification methods, known as pyroprinting, relies on the small variation of DNA sequences within the same species to develop a unique, reproducible fingerprint. By simultaneously pyrosequencing multiple polymorphic loci within the ribosomal operons known as the intergenic transcribed spacers, a reproducible output is obtained, known as a pyroprint, which can be used like a fingerprint to identify that organism. This section of the genome not only differs between species but also between isolated bacteria within that species, allowing for the differentiation of species subtypes, referred to as strains. While this is a viable method for generating reproducible fingerprints from individual strains it may be possible to obtain identical fingerprints from non-identical organisms. The following report uses direct sequence comparison and in silico pyrosequencing of E. coli isolates housed in the Center for Applications in Biotechnology at California Polytechnic State University, San Luis Obispo that have matching pyroprints to show that it is possible to receive near identical pyroprints from non-identical sequences of intergenic transcribed spacers. Although the exact likelihood and cause of this false positive result remains undetermined due to limitations in the sequencing method, its existence questions the accuracy of using pyroprints of the ITS regions as a method of strain classification.

APA, Harvard, Vancouver, ISO, and other styles

39

Wheeler, Gregory Lawrence. "Plant Carnivory and the Evolution of Novelty in Sarracenia alata." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531948732481904.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Choudhury, Anika Nawar. "Utilizing bacteriophage to evolve antibiotic susceptibility in multidrug-resistant Pseudomonas aeruginosa." Bowling Green State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1626570706534933.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Wehking, Jörn [Verfasser]. "Bioinformatic analyses of biogenic aerosol particles by classical and high-throughput sequencing : diversity, seasonal dynamics, and characterization of airborne microbial communities / Jörn Wehking." Mainz : Universitätsbibliothek Mainz, 2018. http://d-nb.info/117135861X/34.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Zayed, Ahmed Abdelfattah. "Microbe-Environment Interactions in Arctic and Subarctic Systems." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1562494472055278.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Tomazetto, Geizecler 1979. "Diversidade e prospecção de metagenoma microbiano em fermentadores de biogás produzindo H2." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/317324.

Full text

Abstract:

Orientador: Valeria Maia Merzel Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia Made available in DSpace on 2018-08-22T20:30:53Z (GMT). No. of bitstreams: 1 Tomazetto_Geizecler_D.pdf: 2728814 bytes, checksum: 5ca8845e4db01805f12ccff354b0a0b0 (MD5) Previous issue date: 2013 Resumo: O hidrogênio é apontado como o candidato mais promissor para substituição do combustível fóssil devido a sua maior eficiência na conversão de energia útil e ausência de emissão de substâncias tóxicas. A produção de hidrogênio a partir de resíduos orgânicos é realizada por meio de digestão anaeróbica, tornando-se uma alternativa ecologicamente correta para atender à futura demanda por hidrogênio. No entanto, os micro-organismos e os processos metabólicos envolvidos estão longe de serem exaustivamente caracterizados. Nesse trabalho, amostras de uma planta de tratamento de esgoto doméstico foram analisadas em dois estudos complementares visando à caracterização de sua diversidade filogenética e a descrição de novas hidrogenases. O primeiro trabalho combinou a análise dos genes de RNAr 16S e FeFehidrogenase (hydA) com ferramentas estatísticas para estimar a riqueza e diversidade da comunidade procariótica em nível filogenético e funcional. As análises filogenéticas e de diversidade das bibliotecas gênicas demonstraram que todas as sequências de arquéias foram afiliadas a Euryarchaeota não cultivadas e, com relação ao Dominio Bactéria, Proteobacteria foi grupo filogenético predominante apresentando os maiores índices de diversidade e riqueza. As sequências putativas de hydA foram identificadas como sequências de genes de FeFehidrogenases ainda não descritas. Na segunda abordagem, a biblioteca metagenômica de fosmideo construída nesse estudo foi analisada empregando a tecnologia de pirosequenciamento 454 e resultou em aproximadamente 218 Mb de dados. Os três diferentes classificadores aplicados permitiram uma visão geral dos grupos taxonômicos mais abundantes devido ao enorme número de sequências metagenômicas não classificadas. Contudo, análises taxonômicas revelaram Gammaproteobacteria e Deltaproteobacteria, respectivamente, como as classes taxonômicas predominantes, enquanto que as espécies do gênero Methanospirillum foram dominantes entre as arquéias metanogênicas. A análise do metabolismo da comunidade microbiana através das bases de dados COG e Carma revelou que a degradação da biomassa depende de diferentes grupos filogenéticos, como por exemplo, Bacteroidia e Gammaproteobacteria, os quais foram indicados como envolvidos na degradação de carboidratos e proteínas, respectivamente. Além disso, as análises sugerem Clostridia e Methanomicrobiales e Methanosarcinales como principais micro-organismos produtores de hidrogênio e metano, respectivamente. As análises das seis sequências codificantes de FeFehidrogenase identificadas no conjunto de dados metagenômicos revelaram que essas representam novas sequências do gene alvo. Contudo, quatro dessas sequências foram identificadas na biblioteca de fosmídeo pela triagem gênica baseada no uso de PCR. O conjunto de resultados obtido nesse estudo permitiu elucidar a composição e o potencial metabólico dos micro-organismos residentes na planta de tratamento de esgoto analisada e sugere esse ambiente como um reservatório potencial de novos genes de hidrogenases para a exploração biotecnológica Abstract: Hydrogen appears to be the most promising candidate for the replacement of fossil fuel due to its potentially higher efficiency of conversion to usable power and no toxic emission production. The production of hydrogen from organic wastes is performed through the anaerobic digestion, making it an environmentally friendly alternative for satisfying future hydrogen demands. Nonetheless, the microorganisms and metabolic processes involved are far from being exhaustively characterized. In this work, samples of a domestic sewage treatment plant were analyzed in two complementary studies aiming at the characterization of its phylogenetic diversity and the description of new hydrogenases. The first one, combined the analysis of 16S rRNA and [FeFe]-hydrogenase (hydA) genes with statistical tools to estimate richness and diversity of the prokaryotic community at the phylogenetic and functional levels. Phylogenetic analysis showed that all archaeal sequences were affiliated with yet uncultured Euryarchaeota and that Proteobacteria were the most predominant and diversified phylogenetic group within the bacterial library. The putative hydA sequences were identified as hitherto undetected [Fe-Fe]- hydrogenase gene sequences. Diversity statistical analysis confirmed a great richness and diversity of bacterial and hydA sequences retrieved from the sewage sludge sample. In the second approach, a fosmid metagenomic library was constructed and analyzed employing 454- pyrosequencing technology, resulting in approximately 218 Mb of data. Three different classifiers applied allowed a broad overview of the most abundant taxonomic groups due to a huge number of metagenome reads remained unidentified. However, taxonomic analysis revealed Gammaproteobacteria and Deltaproteobacteria, respectively, as the most abundant classes, whereas species of the genus Methanospirillum were dominant among methanogenic Archaea. The analyzes of the microbial community metabolism by means of COG and Carma databases revealed that the degradation of biomass depends on different phylogenetic groups, for instance, Bacteroidia and Gammaproteobacteria were indicated as involved into the degradation of carbohydrate and proteins. Furthermore, the analysis suggested Clostridia and Methanomicrobiales and Methanosarcinales as the main microorganisms producing hydrogen and methane, respectively. Analysis of the six coding sequences of FeFe-hydrogenases identified into the dataset revealed that they represented novel target gene sequences. However, only four of these coding sequences could be detected into the fosmid library by PCR screening. The combined results obtained in this study allowed us to have an insight of the composition and potential metabolism of the microbes residing in the analyzed domestic sewage treatment plant and suggested such environment as a potential reservoir for new hydrogenase genes to biotechnological exploration Doutorado Genetica de Microorganismos Doutora em Genética e Biologia Molecular

APA, Harvard, Vancouver, ISO, and other styles

44

Amgarten, Deyvid Emanuel. "Análise computacional da diversidade viral presente na comunidade microbiana do processo de compostagem do Zoológico de São Paulo." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-14072017-161226/.

Full text

Abstract:

O estudo da diversidade viral em amostras ambientais tem se tornado cada vez mais importante devido a funções-chave desempenhadas por esses organismos. Estudos recentes têm fornecido evidências de que vírus de bactérias (bacteriófagos) podem ser os principais determinantes em ciclos biogeoquímicos de grandes ecossistemas, além de atuarem no fluxo de genes entre comunidades ambientais e na plasticidade funcional das mesmas frente a estresses ambientais. Neste trabalho, propomos a investigação e caracterização da diversidade viral presente em amostras de compostagem através de abordagens não dependentes e dependentes de cultivo. Na primeira abordagem, coletamos amostras seriadas de uma unidade de compostagem do zoológico de São Paulo para realização de sequenciamento metagenômico. O conjunto de sequências gerado foi extensivamente minerado (data-mining) para a produção de resultados de diversidade e abundância de táxons virais ao longo do processo de compostagem. Adicionalmente, procedemos com a montagem e recuperação de sequências virais candidatas a genomas completos e/ou parciais de novos vírus ambientais. Os dois protocolos computacionais utilizados para a mineração de dados encontram-se definidos e automatizados, podendo ser aplicados em quaisquer conjuntos de dados de sequenciamento metagenômico ou metatranscritômico obtidos através da plataforma Illumina. A segunda abordagem correspondeu ao isolamento e caracterização de novos fagos de Pseudomonas obtidos de amostras de compostagem. Três novos fagos foram identificados e tiveram os seus genomas sequenciados. A caracterização genômica desses fagos revelou genomas com alto grau de novidade, insights sobre a evolução de Caudovirales e a presença de genes de tRNA, cuja função pode estar relacionada com um mecanismo dos fagos para contornar o viés traducional apresentado pela bactéria hospedeira. A caracterização experimental dos novos fagos isolados demonstrou grande potencial para lise e dissolução de biofilme da cepa Pseudomonas aeruginosa PA14, conhecida como agente causador de infecções hospitalares em pacientes imunodeprimidos. Em suma, os dados reunidos nesta dissertação caracterizam a diversidade presente no viroma da compostagem e contribuem para o entendimento dos perfis taxonômico, funcional e ecológico do processo. The study of the viral diversity in environmental samples has become increasingly important due to key-roles that are performed by these organisms in our ecosystems. Recent publications provide evidence that viruses of bacteria (bacteriophages) may be key-players in biogeochemical cycles of large ecosystems, as oceans and forests. Besides, they may also be determinant in the genes flux among populations and in the plasticity of the communities face to environmental stresses. In this work, we propose the investigation and characterization of the viral diversity in composting samples through non-culturable and culturable-dependent approaches. In the first approach, we sampled a composting unit from the Sao Paulo Zoo Park in different time points and proceeded with metagenomic sequencing. The dataset generated was extensively mined to provide results of diversity and abundance of viral taxa through the composting process. Additionally, we proceeded with the assembly and retrieval of candidate sequences to partial or/and complete viral genomes. The two computational protocols were automatized as pipelines and can be applied to any metagenomic dataset of illumina reads. The second approach refers to the isolation and characterization of new Pseudomonas phages obtained from composting samples. Three new phages were identified and their genomes were sequenced. A detailed characterization of these genomes revealed high degree of novelty, insights about evolution of tailed-phages and the presence of tRNA genes, which may be related to a mechanism to bypass host translational bias. The experimental characterization of the new phages demonstrated great potential to lyse bacterial cells and to degrade Pseudomonas aeruginosa PA14 biofilms. In short, the data presented in this dissertation shed light to the composting virome diversity, as well as to the functional and ecological profiles of viruses in the composting environment.

APA, Harvard, Vancouver, ISO, and other styles

45

Pacheco, Alan Roberto. "Environmental modulation of microbial ecosystems." Thesis, 2021. https://hdl.handle.net/2144/42638.

Full text

Abstract:

Natural microbiota are essential to the health of living systems - from the human gut to coral reefs. Although advances in DNA sequencing have allowed us to catalogue many of the different organisms that make up these microbial communities, significant challenges remain in understanding the complex networks of interspecies metabolic interactions they exhibit. These interactions are crucial to community stability and function, and are highly context-dependent: the availability of different nutrients can determine whether a set of microbes will interact cooperatively or competitively, which can drastically change a community’s structure. Disentangling the environmental factors that determine these behaviors will not only fundamentally enhance our knowledge of their ecological properties, but will also bring us closer to the rational engineering of synthetic microbiomes with novel functions. Here, I integrate modeling and experimental approaches to quantify the dependence of microbial communities on environmental composition. I then show how this relationship can be leveraged to facilitate the design of synthetic consortia. The first chapter of this dissertation is a review article that introduces a framework for cataloguing interaction mechanisms, which enables quantitative comparisons and predictive models of these complex phenomena. The second chapter is a computational study that explores one such attribute – metabolic cost – in high detail. It demonstrates how a large variety of molecules can be secreted without imposing a fitness cost on microbial organisms, allowing for the emergence of beneficial interspecies interactions. The third chapter is an experimental study that determines how the number of unique environmental nutrients affects microbial community growth and taxonomic diversity. The integration of stoichiometric and consumer resource models enabled the discovery of basic ecological principles that govern this environment-phenotype relationship. The fourth chapter applies these principles to the design of engineered communities via a search algorithm that identifies environmental compositions that yield specific ecosystem properties. This dissertation then concludes with extensions of the modeling methods used throughout this work to additional model systems. Future work could further quantify how microbial community phenotypes depend on each of the individual factors explored in this thesis, while also leveraging emerging knowledge on interaction mechanisms to design synthetic consortia.

APA, Harvard, Vancouver, ISO, and other styles

46

Plata, Caviedes German. "Probabilistic Reconstruction and Comparative Systems Biology of Microbial Metabolism." Thesis, 2013. https://doi.org/10.7916/D80C534R.

Full text

Abstract:

With the number of sequenced microbial species soon to be in the tens of thousands, we are in a unique position to investigate microbial function, ecology, and evolution on a large scale. In this dissertation I first describe the use of hundreds of in silico models of bacterial metabolic networks to study the long-term the evolution of growth and gene-essentiality phenotypes. The results show that, over billions of years of evolution, the conservation of bacterial phenotypic properties drops by a similar fraction per unit time following an exponential decay. The analysis provides a framework to generate and test hypotheses related to the phenotypic evolution of different microbial groups and for comparative analyses based on phenotypic properties of species. Mapping of genome sequences to phenotypic predictions -such as used in the analysis just described- critically relies on accurate functional annotations. In this context, I next describe GLOBUS, a probabilistic method for genome-wide biochemical annotations. GLOBUS uses Gibbs sampling to calculate probabilities for each possible assignment of genes to metabolic functions based on sequence information and both local and global genomic context data. Several important functional predictions made by GLOBUS were experimentally validated in Bacillus subtilis and hundreds more were obtained across other species. Complementary to the automated annotation method, I also describe the manual reconstruction and constraints-based analysis of the metabolic network of the malaria parasite Plasmodium falciparum. After careful reconciliation of the model with available biochemical and phenotypic data, the high-quality reconstruction allowed the prediction and in vivo validation of a novel potential antimalarial target. The model was also used to contextualize different types of genome-scale data such as gene expression and metabolomics measurements. Finally, I present two projects related to population genetics aspects of sequence and genome evolution. The first project addresses the question of why highly expressed proteins evolve slowly, showing that, at least for Escherichia coli, this is more likely to be a consequence of selection for translational efficiency than selection to avoid misfolded protein toxicity. The second project investigates genetic robustness mediated by gene duplicates in the context of large natural microbial populations. The analysis shows that, under these conditions, the ability of duplicated yeast genes to effectively compensate for the loss of their paralogs is not a monotonic function of their sequence divergence.

APA, Harvard, Vancouver, ISO, and other styles

47

Sinclair, Lucas. "Molecular methods for microbial ecology : Developments, applications and results." Doctoral thesis, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297613.

Full text

Abstract:

Recent developments in DNA sequencing technology allow the study of microbial ecology at unmatched detail. To fully embrace this revolution, an important avenue of research is the development of bioinformatic tools that enable scientists to leverage and manipulate the exceedingly large amounts of data produced. In this thesis, several bioinformatic tools were developed in order to process and analyze metagenomic sequence data. Subsequently, the tools were applied to the study of microbial biogeography and microbial systems biology. A targeted metagenomics pipeline automating quality filtering, joining and taxonomic annotation was developed to assess the diversity of bacteria, archaea and eukaryotes permitting the study of biogeographic patterns in great detail. Next, a second software package which provides annotation based on environmental ontology terms was coded aiming to exploit the cornucopia of information available in public databases. It was applied to resource tracking, paleontology, and biogeography. Indeed, both these tools have already found broad applications in extending our understanding of microbial diversity in inland waters and have contributed to the development of conceptual frameworks for microbial biogeography in lotic systems. The programs were used for analyzing samples from several environments such as alkaline soda lakes and ancient sediment cores. These studies corroborated the view that the dispersal limitations of microbes are more or less non-existant as environmental properties dictating their distribution and that dormant microbes allow the reconstruction of the origin and history of the sampled community. Furthermore, a shotgun metagenomics analysis pipeline for the characterization of total DNA extraction from the environment was put in place. The pipeline included all essential steps from raw sequence processing to functional annotation and reconstruction of prokaryotic genomes. By applying this tool, we were able to reconstruct the biochemical processes in a selection of systems representative of the tens of millions of lakes and ponds of the boreal landscape. This revealed the genomic content of abundant and so far undescribed prokaryotes harboring important functions in these ecosystems. We could show the presence of organisms with the capacity for photoferrotrophy and anaerobic methanotrophy encoded in their genomes, traits not previously detected in these systems. In another study, we showed that microbes respond to alkaline conditions by adjusting their energy acquisition and carbon fixation strategies. To conclude, we demonstrated that the "reverse ecology" approach in which the role of microbes in elemental cycles is assessed by genomic tools is very powerful as we can identify novel pathways and obtain the partitioning of metabolic processes in natural environments.

APA, Harvard, Vancouver, ISO, and other styles

48

"Revealing Microbial Responses to Environmental Dynamics: Developing Methods for Analysis and Visualization of Complex Sequence Datasets." Doctoral diss., 2017. http://hdl.handle.net/2286/R.I.46177.

Full text

Abstract:

abstract: The greatest barrier to understanding how life interacts with its environment is the complexity in which biology operates. In this work, I present experimental designs, analysis methods, and visualization techniques to overcome the challenges of deciphering complex biological datasets. First, I examine an iron limitation transcriptome of Synechocystis sp. PCC 6803 using a new methodology. Until now, iron limitation in experiments of Synechocystis sp. PCC 6803 gene expression has been achieved through media chelation. Notably, chelation also reduces the bioavailability of other metals, whereas naturally occurring low iron settings likely result from a lack of iron influx and not as a result of chelation. The overall metabolic trends of previous studies are well-characterized but within those trends is significant variability in single gene expression responses. I compare previous transcriptomics analyses with our protocol that limits the addition of bioavailable iron to growth media to identify consistent gene expression signals resulting from iron limitation. Second, I describe a novel method of improving the reliability of centroid-linkage clustering results. The size and complexity of modern sequencing datasets often prohibit constructing distance matrices, which prevents the use of many common clustering algorithms. Centroid-linkage circumvents the need for a distance matrix, but has the adverse effect of producing input-order dependent results. In this chapter, I describe a method of cluster edge counting across iterated centroid-linkage results and reconstructing aggregate clusters from a ranked edge list without a distance matrix and input-order dependence. Finally, I introduce dendritic heat maps, a new figure type that visualizes heat map responses through expanding and contracting sequence clustering specificities. Heat maps are useful for comparing data across a range of possible states. However, data binning is sensitive to clustering cutoffs which are often arbitrarily introduced by researchers and can substantially change the heat map response of any single data point. With an understanding of how the architectural elements of dendrograms and heat maps affect data visualization, I have integrated their salient features to create a figure type aimed at viewing multiple levels of clustering cutoffs, allowing researchers to better understand the effects of environment on metabolism or phylogenetic lineages. Dissertation/Thesis Chapter 2 Excel file of transcriptome responses Chapter 2 Perl scripts Chapter 3 Cluster Aggregation Perl script Chapter 4 Example of the top-down clustering method used to construct dendritic heat maps Chapter 4Perl scripts and dendritic heat map images Chapter 4 Perl scripts and dendritic heat map images Doctoral Dissertation Geological Sciences 2017

APA, Harvard, Vancouver, ISO, and other styles

49

Sheth, Ravi Uday. "New Tools for Understanding and Engineering Complex Microbial Communities." Thesis, 2019. https://doi.org/10.7916/d8-1ctx-5t13.

Full text

Abstract:

Microbes exist in unfathomably diverse, dynamic and intricately structured ecosystems. However, we lack the tools to fully capture the complexity of these microbiomes, which in turn limits our ability to understand their ecology and function. Here, I address these shortcomings by developing new high-throughput measurement tools to characterize microbiomes across functionally distinct axes. First, from a synthetic biology perspective, I leverage the bacterial CRISPR-Cas immune system to enable a new class of population-wide passive recording devices in cells for capture temporally varying signals and horizontally transferred DNA sequences. Second, in the microbiome arena, I develop a new suite of tools (experimental and theoretical) to capture and analyze the spatiotemporal dynamics of microbiomes at macroscopic and microscopic length scales. Taken together, these measurements provide deep insights into the ecology of complex microbiomes, and constitute a suite of powerful new tools to study microbes in their native context.

APA, Harvard, Vancouver, ISO, and other styles

50

Joseph, Tyler. "Methods for modeling the dynamics of microbial communities." Thesis, 2021. https://doi.org/10.7916/d8-ratn-pw39.

Full text

Abstract:

Advances in DNA sequencing of microbial communities have revealed a complex relationship between the human microbiome and our health. Community dynamics, host-microbe interactions, and changing environmental pressures create a dynamic ecosystem that is just beginning to be understood. In this work, we develop methods for investigating the dynamics of the microbiome. First, we develop a model for describing community dynamics. We show that the proposed approaches accurately describes community trajectories over time. Next, we develop a method for modeling and eliminating technical noise from longitudinal data. We demonstrate that the method can accurately reconstruct microbial trajectories from noisy data. Finally, we develop a method for estimating bacterial growth rates from metagenomic sequencing. Using a case-control cohort of individuals with irritable bowel disease, we show how growth rates can be associated with disease status, community states, and metabolites. Altogether, these models can be used to help uncover the relationship between microbial dynamics, human health, and disease.

APA, Harvard, Vancouver, ISO, and other styles

Dissertations / Theses on the topic 'Microbial bioinformatics'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles