Tan Justin, Zuniga Cristal, Zengler Karsten
Department of Bioengineering, University of California, San Diego, CA, 92093, USA.
J Microbiol. 2015 May;53(5):295-305. doi: 10.1007/s12275-015-5060-1. Epub 2015 May 3.
Microorganisms do not exist in isolation in the environment. Instead, they form complex communities among themselves as well as with their hosts. Different forms of interactions not only shape the composition of these communities but also define how these communities are established and maintained. The kinds of interaction a bacterium can employ are largely encoded in its genome. This allows us to deploy a genomescale modeling approach to understand, and ultimately predict, the complex and intertwined relationships in which microorganisms engage. So far, most studies on microbial communities have been focused on synthetic co-cultures and simple communities. However, recent advances in molecular and computational biology now enable bottom up methods to be deployed for complex microbial communities from the environment to provide insight into the intricate and dynamic interactions in which microorganisms are engaged. These methods will be applicable for a wide range of microbial communities involved in industrial processes, as well as understanding, preserving and reconditioning natural microbial communities present in soil, water, and the human microbiome.
微生物在环境中并非孤立存在。相反，它们在自身之间以及与宿主之间形成复杂的群落。不同形式的相互作用不仅塑造了这些群落的组成，还决定了这些群落如何建立和维持。细菌能够采用的相互作用类型在很大程度上由其基因组编码。这使我们能够采用基因组规模建模方法来理解并最终预测微生物所参与的复杂且相互交织的关系。到目前为止，大多数关于微生物群落的研究都集中在合成共培养物和简单群落上。然而，分子生物学和计算生物学的最新进展现在使我们能够从环境中复杂的微生物群落开始采用自下而上的方法，以深入了解微生物所参与的复杂且动态的相互作用。这些方法将适用于涉及工业过程的广泛微生物群落，以及理解、保护和修复土壤、水和人类微生物组中存在的自然微生物群落。
