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基于聚合酶链式反应的微生物群落中特定分类群丰度的定量分析:定量及避免常见陷阱

PCR-based quantification of taxa-specific abundances in microbial communities: Quantifying and avoiding common pitfalls.

作者信息

Bonk Fabian, Popp Denny, Harms Hauke, Centler Florian

机构信息

Department of Environmental Microbiology, UFZ - Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany.

Department of Environmental Microbiology, UFZ - Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany.

出版信息

J Microbiol Methods. 2018 Oct;153:139-147. doi: 10.1016/j.mimet.2018.09.015. Epub 2018 Sep 26.

Abstract

The quantification of relative and absolute taxa-specific abundances in complex microbial communities is crucial for understanding and modeling natural and engineered ecosystems. Many errors inherent to this quantification are, though well-known, still insufficiently addressed and can potentially lead to a completely different interpretation of experimental results. This review provides a critical assessment of next generation sequencing (NGS) of amplicons and quantitative real-time PCR for the quantification of relative and absolute taxa-specific genome abundances. Starting from DNA extraction, the following error sources were considered: DNA extraction efficiency, PCR-associated bias, variance of strain-specific 16S rRNA operon copy number per genome, and analysis of quantitative real-time PCR and NGS data. Tools and methods for estimating and minimizing these errors are presented and demonstrated on published data. In conclusion, amplicon sequencing and qPCR of 16S rRNA genes are valuable tools to determine relative and absolute taxa-specific genome abundances, but results can deviate by several orders of magnitudes from the true values if the reviewed error sources are ignored. Many of these errors can be minimized in a cost-efficient manner and large errors can be easily identified by plausibility checks as shown in this review. Finally, the accurate conversion of genome abundances to cell numbers and microbial biomasses was pointed out as an important future research topic for the integration of PCR-based abundances into mathematical models.

摘要

对复杂微生物群落中相对和绝对的特定分类群丰度进行量化,对于理解和模拟自然及工程生态系统至关重要。尽管这种量化中存在的许多固有误差广为人知,但仍未得到充分解决,并且可能导致对实验结果的完全不同解释。本综述对用于量化相对和绝对特定分类群基因组丰度的扩增子下一代测序(NGS)和定量实时PCR进行了批判性评估。从DNA提取开始,考虑了以下误差来源:DNA提取效率、PCR相关偏差、每个基因组中菌株特异性16S rRNA操纵子拷贝数的差异,以及定量实时PCR和NGS数据的分析。本文介绍了估计和最小化这些误差的工具和方法,并在已发表的数据上进行了演示。总之,16S rRNA基因的扩增子测序和qPCR是确定相对和绝对特定分类群基因组丰度的有价值工具,但如果忽略本文所述的误差来源,结果可能会与真实值相差几个数量级。其中许多误差可以以经济高效的方式最小化,并且通过本文所示的合理性检查可以轻松识别大的误差。最后,指出将基因组丰度准确转换为细胞数量和微生物生物量是将基于PCR的丰度整合到数学模型中的一个重要未来研究课题。

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