Network-free approach for microbial networks

Human-associated and environmental microbial communities play important roles in their ecosystems. These communities consist of trillions of micro-organisms of typically hundreds of different taxa, which interact with each other and with their environment, represented as tangled ecological networks. Understanding these networks is key to understanding their dynamics and developing control strategies. However, reliable reconstruction of such large networks is a very challenging task, especially where the available data is limited. In my talk, I will review recent studies where we developed and applied a top-down approach to studying microbial networks, such as the `universality’ of their dynamics [1], their `effective connectivity' and its relation to May's stability criterion [2], detection of keystones [3], and if time permits, I will briefly present new results on the analysis of single-time-point microbial samples.

1) Universality of human microbial dynamics, Bashan A. et al, Nature (2016).
2) Complexity–stability trade-off in empirical microbial ecosystems, Yonatan Y. et al, Nature Ecology & Evolution (2022).

3) Top-down identification of keystone species in the microbiome, Amit G. and Bashan A., bioRxiv