Lecturer: Dr. Yonatan Friedman
Affiliation: Department of Physics,
Massachusetts Institute of Technology [MIT]
Abstract:
Ecosystems are arguably the most complex but
least understood level of biological
organization. Microbial communities,
composed of numerous interacting species,
are of particular importance due to the recent
realization that they play key roles in shaping
natural ecosystems and determining human
health and wellbeing. Although much progress
has been made in characterizing these
complex communities, the lack of tractable
model systems has made it challenging to
identify unifying principles governing
community assembly and function. In this talk I
describe my recent experimental efforts to
develop a predictive understanding of
microbial community structure. I first
proposed a simple, qualitative assembly rule
that predicts community structure from the
outcomes of pairwise competitions. To
evaluate the rule’s accuracy, I quantified the
network of pairwise competitive outcomes
among species within a model microbial
community. The assembly rule was surprisingly
successful in predicting the outcome of three-
species competition, indicating that higher-
order interactions among species can often be
neglected. However, when trio competitions
resulted in unexpected outcomes, it was
necessary to incorporate this information to
predict the outcome of competitions between
more diverse species collections. These results
illustrate how a bottom-up approach of
characterizing individual interactions can
explain the emergent behavior within complex
multi-species communities.