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Uncovering hidden microbial metabolism using 2D NMR- and LC-MS-based comparative metabolomics.

机译:使用基于2D NMR和LC-MS的比较代谢组学发现隐藏的微生物代谢。

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Recent advances in genomic sequencing technology have facilitated relatively inexpensive, high-fidelity sequencing of microbial genomes. Increased genome sequencing capacity has been accompanied by developments in bioinformatics, which enable rapid homology searching to predict gene products, such as enzymes involved in the production of small-molecules. The recent surge in genomic information revealed that only a small percentage of genes involved in small-molecule biosynthesis had previously been characterized. In fact, it appears that we have only scratched the surface in understanding the full biosynthetic potential of microorganisms. The current void in small-molecule discovery is in part because of the particular challenges associated with identifying new compounds and in part because of the nature of microbial small-molecule production.;Perhaps the largest obstacle in the path to characterizing new small-molecules is the absence of a templated structure. For instance, in genomics, the number of building blocks is extremely limited, just four different bases, which fit together predictably through phosphodiester bonds. Moving up in complexity to proteomics, the number of building blocks increases to roughly twenty amino acids, however still assembled in a predictable manner, through peptide bonds. Additionally, protein primary sequence can be derived directly from the corresponding genetic sequence, which coupled with homology searching enables quick judgments as to whether or not a detailed characterization is warranted. The situation in metabolomics is starkly more complicated as the number of building blocks increases to over one-hundred chemical entities that can be assembled in virtually any imaginable way that obeys the laws of chemistry. Moreover, small-molecule structural insights simply cannot be attained from the genetic sequence alone, meaning every compound must be individually characterized.;In addition to the challenges of small-molecule characterization, the very nature of microbial biosynthesis has significantly hindered more thorough annotation of the metabolome. Expression of genes encoding biosynthetic enzymes is tightly regulated and responsive to various natural environments. Simple laboratory culturing conditions usually fail to reproduce the necessary cues to promote small-molecule production. While media screening methods or so called fermentation optimization is an option to overcome this barrier, the power of genetic engineering offers a far more straightforward solution and has the added benefit of precision. The production of small-molecules can be turned on or eliminated in a controlled manner by creating over-expression or knock-out mutant microbial strains. Comparison of mutant and wild-type strains using differential analysis by 2D-NMR spectroscopy (DANS) and LC-MS-based comparative metabolomics enables a systems biology prospective of metabolic changes resulting from genetic engineering.;Described herein is the utilization of DANS and LC-MS-based comparative metabolomics to discover novel metabolites from orphan microbial biosynthetic gene clusters. Applied to the has gene cluster in Aspergillus fumigatus DANS revealed the biosynthesis of a novel iron(III)-complex, which was shown to increase A. fumigatus' virulence. Results from the has study led to an investigation of diketopiperazine formation in the notorious gliotoxin biosynthetic pathway. Gliotoxin biosynthesis was shown to be dependent on a cluster-encoded cyclization domain, which ultimately functioned to cyclize a modified dipeptide into the diketopiperazine core of the gliotoxin structure. In another A. fumigatus gene cluster, called fsq, DANS and LC-MS-based comparative metabolomics revealed the elusive fungal isoquinoline formation pathway, which despite having been described in plants more than twenty years ago, remained unknown in fungi until now. The fungal isoquinoline pathway was shown to be conserved through the characterization of another isoquinoline producing gene cluster in the plant pathogenic fungus A. flavus. Lastly, the identification and characterization of an additional set of fsq-dependent metabolites, called the fumizinones, is described. The fumizinones derive from an alternative biosynthetic mechanism, resulting in pyrazinone formation, rather than isoquinoline formation, as observed for the main products of the fsq pathway.
机译:基因组测序技术的最新进展促进了微生物基因组的相对廉价,高保真测序。基因组测序能力的提高伴随着生物信息学的发展,生物信息学的发展使得能够进行快速同源性搜索来预测基因产物,例如参与小分子生产的酶。最近的基因组信息激增表明,以前只鉴定了参与小分子生物合成的基因的一小部分。实际上,似乎我们只是在了解微生物的全部生物合成潜能上才涉足表面。小分子发现中当前的空白部分是由于与鉴定新化合物有关的特殊挑战,部分是由于微生物小分子生产的本质。也许表征新小分子的道路上最大的障碍是没有模板结构。例如,在基因组学中,构件的数量极为有限,只有四个不同的碱基,可以通过磷酸二酯键将它们预测地结合在一起。随着蛋白质组学的复杂性提高,构件的数量增加到大约20个氨基酸,但是仍然可以通过肽键以可预测的方式组装。另外,蛋白质一级序列可以直接从相应的遗传序列中获得,结合同源性搜索可以快速判断是否需要进行详细的鉴定。代谢组学的情况更加复杂,因为构建基团的数量增加到一百多种,可以用几乎任何可以想象得到的服从化学定律的方式进行组装的化学实体。而且,仅凭基因序列就无法获得小分子的结构见解,这意味着必须对每种化合物进行单独表征。除了小分子表征的挑战外,微生物生物合成的本质也大大阻碍了对分子的更彻底注释。代谢组。编码生物合成酶的基因的表达受到严格调节,并对各种自然环境有反应。简单的实验室培养条件通常无法复制促进小分子生产的必要线索。尽管可以采用培养基筛选方法或所谓的发酵优化方法来克服这一障碍,但是基因工程的力量提供了一种更为直接的解决方案,并具有更高的精度优势。小分子的产生可以通过产生过表达或敲除突变的微生物菌株以受控方式开启或消除。使用2D-NMR光谱分析(DANS)和基于LC-MS的比较代谢组学进行差异分析比较突变株和野生型菌株,使系统生物学有望预测基因工程导致的代谢变化。;本文所述是利用DANS和LC -MS为基础的比较代谢组学,从孤儿微生物生物合成基因簇中发现新的代谢物。应用于烟曲霉中的has基因簇DANS揭示了新型铁(III)配合物的生物合成,该复合物显示出可提高烟曲霉的毒力。该研究的结果导致对臭名昭著的胶体毒素生物合成途径中二酮哌嗪形成的研究。胶质毒素的生物合成显示依赖于簇编码的环化结构域,其最终起到将修饰的二肽环化成胶质毒素结构的二酮哌嗪核心的作用。在另一个称为fsq的烟曲霉基因簇中,基于DANS和LC-MS的比较代谢组学揭示了难以捉摸的真菌异喹啉形成途径,尽管在二十多年前已在植物中进行了描述,但迄今为止在真菌中仍然未知。通过表征植物病原性真菌黄曲霉中另一个产生异喹啉的基因簇,表明真菌异喹啉途径是保守的。最后,描述了称为fumizinones的另一组依赖fsq的代谢物的鉴定和表征。烟熏气酮源自另一种生物合成机制,导致吡嗪酮的形成,而不是异喹啉的形成,正如对fsq途径的主要产物所观察到的那样。

著录项

  • 作者

    Baccile, Joshua Andrew.;

  • 作者单位

    Cornell University.;

  • 授予单位 Cornell University.;
  • 学科 Biochemistry.;Analytical chemistry.;Molecular chemistry.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 339 p.
  • 总页数 339
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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