Meroz Nittay, Livny Tal, Friedman Jonathan
Institute of Environmental Sciences, Hebrew University, Rehovot.
Institute of Environmental Sciences, Hebrew University, Rehovot; Department of Immunology and Regenerative Biology, Weizmann Institute, Rehovot.
Curr Opin Microbiol. 2024 Aug;80:102511. doi: 10.1016/j.mib.2024.102511. Epub 2024 Jul 13.
Microbial communities are fundamental to every ecosystem on Earth and hold great potential for biotechnological applications. However, their complex nature hampers our ability to study and understand them. A common strategy to tackle this complexity is to abstract the community into a network of interactions between its members - a phenomenological description that captures the overall effects of various chemical and physical mechanisms that underpin these relationships. This approach has proven useful for numerous applications in microbial ecology, including predicting community dynamics and stability and understanding community assembly and evolution. However, care is required in quantifying and interpreting interactions. Here, we clarify the concept of an interaction and discuss when interaction measurements are useful despite their context-dependent nature. Furthermore, we categorize different approaches for quantifying interactions, highlighting the research objectives each approach is best suited for.
微生物群落是地球上每个生态系统的基础,在生物技术应用方面具有巨大潜力。然而,它们的复杂性质阻碍了我们研究和理解它们的能力。解决这种复杂性的一个常见策略是将群落抽象为其成员之间的相互作用网络——这是一种现象学描述,它捕捉了支撑这些关系的各种化学和物理机制的总体影响。这种方法已被证明在微生物生态学的众多应用中很有用,包括预测群落动态和稳定性以及理解群落组装和进化。然而,在量化和解释相互作用时需要谨慎。在这里,我们阐明了相互作用的概念,并讨论了尽管相互作用测量具有上下文依赖性,但在何时它们仍然有用。此外,我们对量化相互作用的不同方法进行了分类,突出了每种方法最适合的研究目标。