Unlocking the potential of metagenomics to understand microbial communities in complex aquatic environments

How individual microbial populations assemble in communities based on the dynamic interaction between available seed taxa and local environmental drivers is still poorly understood. Historically, this is due to the inability to grow many bacterial and archaeal species in the laboratory to simulate competition and environmental selection, drastically limiting our estimates of the functional potential of natural microbial ecosystems.

One way to circumvent the culturability issue is to sequence the genomes of microorganisms by direct extraction of DNA from their natural environment (a.k.a. metagenomics). The resulting sequence data can then be analyzed using ecosystem-wide network models and global simulations of community dynamics.

Here I will review how this integration of metagenomic data within the larger framework of the physico-chemical metadata has been successfully employed to generate ecologically relevant insights into microbially driven ecosystems from Antarctica, the deep-sea and the urban waterways in Singapore.

The heuristic value of in-silico simulations will be discussed in relation to: (1) understanding the effects of environmental perturbations on the dynamics of microbial systems, (2) describing the advective transport of members of the community by ocean currents (3) modelling the predator-prey interactions between viral and bacterial populations.