Understanding interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete. Within this seminar, we will illustrate recent and complementary computational modelings that aim to overcome these points in different manners, promoting the recent field called systems ecology.
First, we will present a network analysis that focus on the biological carbon pump in the global ocean. The biological carbon pump is the process by which photosynthesis transforms CO2 to organic carbon sinking to the deep-ocean as particles where it is sequestered. While the intensity of the pump correlate to plankton community composition, the underlying ecosystem structure and interactions driving this process remain largely uncharacterized. We will show that the abundances of just a few bacterial and viral genes elucidate ecosystem behaviors and present a case study for scaling biological modelings from genes-to-ecosystems.
Second, we will emphasize the functional role of bacteria within a natural community by proposing a graph-based modeling combined with a combinatorial optimization technique. Such an approach depicts from genome-scale knowledge, the respective role of microbial strains to catalyze environmental processes.
Finally, we will show preliminary results on a probabilistic modeling that predicts microbial community structure across observed physicochemical data, from a putative network and partial quantitative knowledge. This modeling shows that, despite distinct quantitative environmental perturbations, the constraints on a community structure could remain stable.
Related references:
Guidi, L., Chaffron, S., Bittner, L., Eveillard, D., Larhlimi, A., Roux, S., et al. (2016). Plankton networks driving carbon export in the oligotrophic ocean. Nature, 532, 465–470.
Bordron, P., Latorre, M., Cortés, M.P., González, M., Thiele, S., Siegel, A., et al. (2016). Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach. Microbiologyopen, 5, 106–117.
Bourdon, J., Eveillard, D. & Siegel, A. (2011). Integrating quantitative knowledge into a qualitative gene regulatory network. PLoS Comput Biol, 7, e1002157.
