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用于分析复杂细菌群落的高通量技术。

High-throughput techniques for analyzing complex bacterial communities.

作者信息

Stahl David A

机构信息

University of Washington, Seattle, WA 98195, USA.

出版信息

Adv Exp Med Biol. 2004;547:5-17. doi: 10.1007/978-1-4419-8861-4_2.

Abstract

A more complete understanding of microbial diversity and the environmental processes they control will require much more than a biotic inventory. It will require a deeper understanding of the basic features of systems organization and inter-population interactions. Communities, not total biomass, control net process rates driving the biogeochemical cycles sustaining the biosphere. Although the general patterns of macroorganismal diversity are relatively well known, spatial and temporal patterns of microorganismal diversity are essentially unknown. Having tools capable of resolving these patterns is a prerequisite to developing an understanding of the relationship between community structure and function. This talk discusses conceptual and technical developments that now provide the framework for systematically resolving temporal and spatial patterns of microorganisms and relating those patterns to processes at local and system levels. Of particular emphasis will be ongoing studies using highly parallel analyses with DNA microarrays for intensive monitoring of microbial populations in environmental systems. Although microarray technology is reasonably well established for studies of model organisms in well-defined laboratory settings, the application of this technology to environmental systems of uncharacterized diversity imposes additional demands on implementation; in particular, the requirement for optimized discrimination between target and non-target nucleic acids in complex, and undefined, mixtures. To increase the resolving power (information content) of our DNA microarray format, we are investigating the use of thermal dissociation of hybrids immobilized on individual array elements to resolve target and non-target sequences that differ by a single nucleotide. These studies, combined with specialized algorithms for optimizing the readout of the microarray should serve for informed environmental application. Initial studies have validated the general approach for analyses of sediment systems.

摘要

要更全面地理解微生物多样性及其所控制的环境过程,所需的远不止一份生物清单。这需要更深入地了解系统组织的基本特征以及种群间的相互作用。驱动维持生物圈的生物地球化学循环的净过程速率是由群落而非总生物量控制的。尽管大型生物多样性的一般模式相对为人所知,但微生物多样性的时空模式基本上还不清楚。拥有能够解析这些模式的工具是理解群落结构与功能之间关系的先决条件。本次演讲将讨论概念和技术的发展,这些发展现在为系统地解析微生物的时空模式以及将这些模式与局部和系统层面的过程联系起来提供了框架。将特别强调正在进行的研究,这些研究使用DNA微阵列进行高度并行分析,以密集监测环境系统中的微生物种群。尽管微阵列技术在明确界定的实验室环境中对模式生物的研究已经相当成熟,但将该技术应用于多样性未知的环境系统对实施提出了额外要求;特别是在复杂且未定义的混合物中对目标核酸和非目标核酸进行优化区分的要求。为了提高我们DNA微阵列形式的分辨能力(信息含量),我们正在研究利用固定在单个阵列元件上的杂交体的热解离来解析相差单个核苷酸的目标序列和非目标序列。这些研究与用于优化微阵列读数的专门算法相结合,应有助于明智地应用于环境领域。初步研究已经验证了分析沉积物系统的一般方法。

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