Project summary
Microbial communities within the human gut broadly and significantly affect host health. Engineering the
dynamics of microbial communities is therefore a promising direction for new therapeutics. However, microbes
within a community affect one another’s growth through a wide variety of mechanisms whose relative importance
remain unclear, hindering the predictive capability of existing models for community dynamics. To address this
knowledge gap, I propose experimental and mathematical modeling methods to disentangle and measure
the strengths of the various interaction mechanisms.
Key to my proposal is our lab’s powerful set of communities and microbial isolates derived from mice stool
that have similar compositions in laboratory cultures as in the gut of gnotobiotic mice. They enable me to
assemble and perturb the communities in lab cultures while mimicking behaviors relevant to host health. Guided
by mathematical models that represent microbes as consumers and producers of environmental resources, as
well as agents of other potential interaction mechanisms, I will assemble different combinations of the isolates
and measure their growth properties to quantify their interaction mechanisms. For example, the amount of growth
of one species in the medium spent by the growth of another species reflects the amount of overlap in the
resources consumed by these two species. I will infer interaction mechanisms from two additional perspectives
by quantifying environmental metabolites during growth of the communities, and investigating the statistics of
fluctuations in species abundances over time in vivo. These three approaches will integrate high throughput
experiments with mathematical modeling to systematically measure the importance of various interaction
mechanisms, and generate a framework to do so for any microbial community. Together, the outcomes will
ground species interactions mechanistically, empowering the engineering of microbial communities.
My interdisciplinary proposal leverages my PhD training in physics, particularly statistical physics and the
modeling of complex systems, and bacterial physiology. It will also train me in high-throughput phenotyping
(next-generation sequencing and mass spectrometry metabolomics) of microbial communities, which will help
me achieve my career goal to lead a laboratory that engineer microbial communities to benefit society. My
sponsoring scientist Dr. Kerwyn Casey Huang in the Stanford Department of Bioengineering is an excellent
mentor for the plan. His interdisciplinary lab bridges phenomena from single molecules to the multi-species scale
using physical and biological techniques, and collaborates intimately with leading labs in microbiota research at
Stanford. Thus, it is the ideal environment to pursue the ideas in my proposal. I will also actively engage
undergraduate and graduate students in my proposed projects.