Cordero Otto X, Datta Manoshi S
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computational and Systems Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Computational and Systems Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Curr Opin Microbiol. 2016 Jun;31:227-234. doi: 10.1016/j.mib.2016.03.015. Epub 2016 May 25.
In most environments, microbial interactions take place within microscale cell aggregates. At the scale of these aggregates (∼100μm), interactions are likely to be the dominant driver of population structure and dynamics. In particular, organisms that exploit interspecific interactions to increase ecological performance often co-aggregate. Conversely, organisms that antagonize each other will tend to spatially segregate, creating distinct micro-communities and increased diversity at larger length scales. We argue that, in order to understand the role that biological interactions play in microbial community function, it is necessary to study microscale spatial organization with enough throughput to measure statistical associations between taxa and possible alternative community states. We conclude by proposing strategies to tackle this challenge.
在大多数环境中，微生物相互作用发生在微观尺度的细胞聚集体内。在这些聚集体的尺度（约100μm）上，相互作用很可能是种群结构和动态的主要驱动因素。特别是，利用种间相互作用来提高生态性能的生物通常会共同聚集。相反，相互拮抗的生物往往会在空间上分离，从而在更大的长度尺度上形成不同的微型群落并增加多样性。我们认为，为了理解生物相互作用在微生物群落功能中所起的作用，有必要以足够的通量研究微观尺度的空间组织，以测量分类群与可能的替代群落状态之间的统计关联。我们最后提出应对这一挑战的策略。
