Department of Internal Medicine, National Taiwan University Hospital Bei-Hu Branch, Taipei, Taiwan; Institute of Food Science and Technology, National Taiwan University, Taipei, Taiwan.
Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
J Formos Med Assoc. 2019 Feb;118(2):545-555. doi: 10.1016/j.jfma.2018.02.005. Epub 2018 Mar 2.
Although great interest has been displayed by researchers in the contribution of gut microbiota to human health, there is still no standard protocol with consensus to guarantee the sample quality of metagenomic analysis. Here we reviewed existing methodology studies and present suggestions for optimizing research pipeline from fecal sample collection to DNA extraction. First, we discuss strategies of clinical metadata collection as common confounders for microbiome research. Second, we propose general principles for freshly collected fecal sample and its storage and share a DIY stool collection kit protocol based on the manual procedure of Human Microbiome Project (HMP). Third, we provide a useful information of collection kit with DNA stabilization buffers and compare their pros and cons for multi-omic study. Fourth, we offer technical strategies as well as information of novel tools for sample aliquoting before long-term storage. Fifth, we discuss the substantial impact of different DNA extraction protocols on technical variations of metagenomic analysis. And lastly, we point out the limitation of current methods and the unmet needs for better quality control of metagenomic analysis. We hope the information provided here will help investigators in this exciting field to advance their studies while avoiding experimental artifacts.
尽管研究人员对肠道微生物群对人类健康的贡献表现出了极大的兴趣，但仍没有达成共识的标准方案来保证宏基因组分析的样本质量。在这里，我们回顾了现有的方法学研究，并提出了从粪便样本采集到 DNA 提取的优化研究方案的建议。首先，我们讨论了临床元数据收集策略，因为这些策略是微生物组研究的常见混杂因素。其次，我们提出了新鲜采集的粪便样本及其储存的一般原则，并根据人类微生物组计划（HMP）的手动程序分享了 DIY 粪便收集试剂盒方案。第三，我们提供了收集试剂盒中 DNA 稳定剂的有用信息，并比较了它们在多组学研究中的优缺点。第四，我们提供了用于长期储存前样本等分的技术策略以及新型工具的信息。第五，我们讨论了不同 DNA 提取方案对宏基因组分析技术差异的重大影响。最后，我们指出了当前方法的局限性和对宏基因组分析更好质量控制的未满足需求。我们希望这里提供的信息将帮助该领域的研究人员在避免实验假象的同时推进他们的研究。
