Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, CO, USA ; Department of Ecology and Evolutionary Biology, University of Colorado Boulder, CO, USA.
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, CO, USA.
Front Microbiol. 2014 Nov 12;5:614. doi: 10.3389/fmicb.2014.00614. eCollection 2014.
Most environments harbor large numbers of microbial taxa with ecologies that remain poorly described and characterizing the functional capabilities of whole communities remains a key challenge in microbial ecology. Shotgun metagenomic analyses are increasingly recognized as a powerful tool to understand community-level attributes. However, much of this data is under-utilized due, in part, to a lack of conceptual strategies for linking the metagenomic data to the most relevant community-level characteristics. Microbial ecologists could benefit by borrowing the concept of community-aggregated traits (CATs) from plant ecologists to glean more insight from the ever-increasing amount of metagenomic data being generated. CATs can be used to quantify the mean and variance of functional traits found in a given community. A CAT-based strategy will often yield far more useful information for predicting the functional attributes of diverse microbial communities and changes in those attributes than the more commonly used analytical strategies. A more careful consideration of what CATs to measure and how they can be quantified from metagenomic data, will help build a more integrated understanding of complex microbial communities.
大多数环境中都存在大量具有生态特征的微生物类群，这些特征仍未得到充分描述，而描述整个群落的功能能力仍然是微生物生态学的一个关键挑战。鸟枪法宏基因组分析越来越被认为是理解群落水平特征的有力工具。然而，由于缺乏将宏基因组数据与最相关的群落水平特征联系起来的概念策略，其中大部分数据未得到充分利用。微生物生态学家可以借鉴植物生态学家的群落聚合特征 (CAT) 概念，从不断增加的宏基因组数据中获得更多的洞察力。CAT 可用于量化给定群落中功能特征的均值和方差。与更常用的分析策略相比，基于 CAT 的策略通常可以为预测不同微生物群落的功能属性及其属性变化提供更有用的信息。更仔细地考虑要测量的 CAT 以及如何从宏基因组数据中对其进行量化，将有助于更全面地理解复杂的微生物群落。
