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A study of microbial diversity using comparative genomics and comparative metagenomics methods.

机译:使用比较基因组学和比较宏基因组学方法研究微生物多样性。

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摘要

Development of sequencing technologies makes it possible to access the microbial diversity on the molecular level. Through sequencing of microbial genomes and metagenomes, insights are gained into the metabolic roles played by the microbes and the formation of complex microbial communities. In order to obtain comprehensive understanding of the microbial diversity, it is essential to know what makes the microbes different from each other, what shapes the microbes and microbiomes to adapt to diverse environments, and how to access the microbial world where a majority of the microbes are yet novel. Despite of successes in literature that identified structural or metabolic differences between various microbes and microbiomes, the description and interpretation of microbial diversity is yet controversial and often dependent on the level of detail one may want to conclude. For example, microbiome structures can be resolved on various taxonomic levels, and microbiome dynamics can be explained with biological processes, pathways or various molecular functions. Consequently, thorough study of microbial diversity is essential and the methods used are supposed to be adaptable to varying demands.;This dissertation aims to improve our current understanding towards microbial diversity in varying microbes and microbiomes, by methods that are generally adaptable in comparative genomics and comparative metagenomics. As the fundamental prerequisite for studying microbial diversity, genomic comparisons are performed. Methods are developed to predict novel 16S rRNA genes and to benchmark alternative marker genes for enhanced inference of phylogenetic relationship between microbes. A genomic comparison database is also constructed to provide public access to comparing all prokaryotic complete genomes. Furthermore, feature selection methods are introduced to identify microbial signatures that are responsible for varying environmental factors in comparative genomics or metagenomics studies. By implementing feature selection, this dissertation proves the possibility to identify protein signatures in human gut microbiomes that are relevant to age, and to identify pathway signatures differentially expressed in a fungal organism that help explain how the organism reacts to alternative nutrient. As a method adaptable for various data types, feature selection can be widely used to explain the microbial diversity in microbes or microbiomes under varying circumstances. Finally, the dissertation aims to provide access to the novel members of microbiome, which represent a more diverse microbial world than in our current knowledgebase. Using a pipeline with comparative genomics and metagenomic approaches combined, a novel microbial genome enriched in a soil microbiome is found and putatively recovered in comparison with its close relatives. With developed understanding of microbial genomes, microbial signatures shaping the environment and access to the novel microbes in microbiomes, the interpretation of microbial diversity is greatly improved.
机译:测序技术的发展使得有可能在分子水平上获得微生物多样性。通过对微生物基因组和元基因组进行测序,可以深入了解微生物的代谢作用以及复杂微生物群落的形成。为了获得对微生物多样性的全面了解,必须了解使微生物彼此不同的原因,使微生物和微生物群落变形的形状以适应各种环境,以及如何进入大多数微生物的微生物世界还很新颖。尽管在文献中已经成功地确定了各种微生物和微生物群落之间的结构或代谢差异,但微生物多样性的描述和解释仍存在争议,并且通常取决于人们可能要得出的结论。例如,微生物组结构可以在各种分类学水平上解析,微生物组动力学可以用生物学过程,途径或各种分子功能来解释。因此,对微生物多样性的深入研究是必不可少的,并且所采用的方法应该能够适应各种不同的需求。本论文旨在通过普遍适用于比较基因组学和方法的方法,提高我们对各种微生物和微生物群落中微生物多样性的当前理解。比较宏基因组学。作为研究微生物多样性的基本前提,进行基因组比较。已开发出方法来预测新的16S rRNA基因并基准化替代标记基因,以增强推断微生物之间的系统发生关系。还建立了基因组比较数据库,以提供公众访问以比较所有原核完整基因组。此外,在比较基因组学或宏基因组学研究中,引入了特征选择方法来识别导致不同环境因素的微生物特征。通过实施特征选择,本论文证明了鉴定与年龄有关的人类肠道微生物组中蛋白质特征的可能性,并鉴定了在真菌生物体中差异表达的途径特征的可能性,这有助于解释该生物体对替代营养物的反应。作为适用于各种数据类型的方法,特征选择可以广泛用于解释在不同情况下微生物或微生物群落中的微生物多样性。最后,本文旨在为微生物组的新成员提供访问途径,这些微生物组代表了比我们当前知识库中更多样化的微生物世界。使用比较基因组学和宏基因组学方法相结合的方法,发现了一种富含土壤微生物组的新型微生物基因组,并与近亲相比,推测其得到了恢复。通过对微生物基因组的深入了解,塑造环境的微生物特征以及进入微生物群中新型微生物的途径,对微生物多样性的解释得到了极大的改善。

著录项

  • 作者

    Lan, Yemin.;

  • 作者单位

    Drexel University.;

  • 授予单位 Drexel University.;
  • 学科 Bioinformatics.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 106 p.
  • 总页数 106
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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