Colorado State University, Fort Collins, CO, USA.
Duke University, Durham, NC, USA.
Nat Microbiol. 2018 Sep;3(9):977-982. doi: 10.1038/s41564-018-0201-z. Epub 2018 Aug 24.
Translating the ever-increasing wealth of information on microbiomes (environment, host or built environment) to advance our understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes that they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field. We propose that research focused on how microbiomes influence the systems they inhabit should work within a common framework and target known microbial processes that contribute to the system-level processes of interest. Here, we identify three distinct categories of microbiome characteristics (microbial processes, microbial community properties and microbial membership) and propose a framework to empirically link each of these categories to each other and the broader system-level processes that they affect. We posit that it is particularly important to distinguish microbial community properties that can be predicted using constituent taxa (community-aggregated traits) from those properties that cannot currently be predicted using constituent taxa (emergent properties). Existing methods in microbial ecology can be applied to more explicitly elucidate properties within each of these three categories of microbial characteristics and connect them with each other. We view this proposed framework, gleaned from a breadth of research on environmental microbiomes and ecosystem processes, as a promising pathway with the potential to advance discovery and understanding across a broad range of microbiome science.
将越来越多的微生物组（环境、宿主或建筑环境）信息转化为对系统水平过程的深入理解，这被证明是一项极具挑战性的研究任务。造成这一挑战的原因之一是，微生物组的特征与其影响的系统水平过程之间的关系通常是在缺乏稳健的概念框架的情况下进行评估的，而且在报告时并没有阐明潜在的因果机制。对相关性方法的依赖限制了将单一关系的推断扩展到其他系统并推进该领域的潜力。我们提出，专注于微生物组如何影响其所处系统的研究应该在一个共同的框架内进行，并针对有助于研究人员感兴趣的系统水平过程的已知微生物过程进行研究。在这里，我们确定了微生物组特征的三个不同类别（微生物过程、微生物群落属性和微生物成员），并提出了一个框架，以经验性地将这些类别中的每一个与彼此以及它们所影响的更广泛的系统水平过程联系起来。我们认为，特别重要的是要区分那些可以使用组成分类群（群落聚集特征）来预测的微生物群落属性和那些目前不能使用组成分类群来预测的属性（新兴属性）。现有的微生物生态学方法可以应用于更明确地阐明这三个微生物特征类别中的每一个类别的属性，并将它们相互联系起来。我们认为，从广泛的环境微生物组和生态系统过程研究中得出的这个框架是一个很有前途的途径，有可能在广泛的微生物组科学领域中推进发现和理解。
