Fricker Alena M, Podlesny Daniel, Fricke W Florian
Dept. of Microbiome Research and Applied Bioinformatics, Institute for Nutritional Sciences, University of Hohenheim, Stuttgart, Germany.
Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
J Adv Res. 2019 Mar 23;19:105-112. doi: 10.1016/j.jare.2019.03.006. eCollection 2019 Sep.
Microbiome research has transformed the scientific landscape, as reflected by the exponential increase in microbiome-related publications from many different disciplines. Host-associated microbial communities play a role for almost all aspects of human, animal and plant biology and health. Consequently, there are tremendous expectations for the development of new clinical, agricultural and biotechnological applications of microbiome research. However, the field continues to be largely shaped by descriptive studies, the mechanistic understanding of microbiome functions for their hosts remains fragmentary, and direct applications of microbiome research are lacking. The aim of this review is therefore to provide a general introduction to the technical opportunities and challenges of microbiome research, as well as to make experimental and bioinformatic recommendations, i.e. (i) to avoid, reduce and assess the confounding effects of sample storage, nucleic acid isolation and microbial contamination; (ii) to minimize non-microbial contributions in host-associated microbiome samples; (iii) to sharpen the focus on physiologically relevant microbiome features by distinguishing signals from metabolically active and inactive or dead microbes and by adopting quantitative methods; and (iv) to enforce open data and protocol policies in order increase the transparency, reproducibility and credibility of the field.
微生物组研究已经改变了科学格局,这从许多不同学科中与微生物组相关的出版物呈指数级增长就可以看出。与宿主相关的微生物群落几乎在人类、动物和植物生物学及健康的各个方面都发挥着作用。因此,人们对微生物组研究在新的临床、农业和生物技术应用方面的发展寄予厚望。然而,该领域在很大程度上仍然由描述性研究主导,对微生物组对其宿主功能的机制理解仍然支离破碎,并且缺乏微生物组研究的直接应用。因此,本综述的目的是对微生物组研究的技术机遇和挑战进行总体介绍,并提出实验和生物信息学方面的建议,即:(i)避免、减少和评估样本储存、核酸分离和微生物污染的混杂效应;(ii)尽量减少宿主相关微生物组样本中的非微生物贡献;(iii)通过区分来自代谢活跃和不活跃或死亡微生物的信号并采用定量方法,更加关注生理相关的微生物组特征;(iv)实施开放数据和协议政策,以提高该领域的透明度、可重复性和可信度。