# Understanding Robustness of a Cooperative Microbial Community during Evolution

> **NIH NIH R01** · FRED HUTCHINSON CANCER RESEARCH CENTER · 2020 · $324,607

## Abstract

Multi-species microbial communities can outperform single species in producing pharmaceuticals and fighting
infections. However, for a community to be useful, it must be “robust” in the sense that it must retain member
species and survive internal and external perturbations. Community robustness arises from interactions
between community members and can thus change rapidly as community members evolve. To date, we
understand very little about various forms of robustness and how they change during evolution. Theoretical
work is often based on unrealistic assumptions, while empirical work is largely observational or correlational.
To understand community robustness and how they might change as community members evolve, we have
created a cooperative yeast community. It consists of two mutually-dependent yeast strains exchanging
essential metabolites. The two strains are reproductively isolated, and can thus be regarded as two species.
Due to mutual dependence, the two strains coexist over a long term and can thus be further engineered to
carry out “division of labor” in complex tasks such as degrading a mixture of waste products. However, such a
community can still go extinct upon population reduction. Here, we will examine community robustness against
two commonly-encountered external perturbations: extreme population reduction such as during the
colonization of a new host, or gradual population reduction such as during periodic purge from the gut. We aim
to understand these two forms of robustness so that we can manipulate them. We also want to understand
how robustness might change as community members evolve and diversify.
We have passaged multiple communities for over 150 generations. All communities became more robust in
surviving severe population reductions. Strikingly, robustness against gradual population reduction increased
in some communities, but it decreased in other communities. To understand community robustness and how
they change during evolution, we have developed high-throughput assays to measure phenotypes of cells from
the two strains. Mathematical models based on these measurements successfully predicted for example
robustness against severe population reduction in the ancestral community. We will use these mathematical
models to predict how we might effectively alter robustness. We will also predict which subset of evolved
community members are important in altering community robustness. We will experimentally test model
predictions. Model-experiment discrepancies will motivate us to uncover missing elements that are important to
community robustness, such as evolved new interactions and rare evolved genotypes with extreme
phenotypes. Our work will provide an experimental and mathematical approach to understanding communities
harboring evolutionary complexity.

## Key facts

- **NIH application ID:** 9967044
- **Project number:** 5R01GM124128-04
- **Recipient organization:** FRED HUTCHINSON CANCER RESEARCH CENTER
- **Principal Investigator:** LI XIE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $324,607
- **Award type:** 5
- **Project period:** 2017-09-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9967044

## Citation

> US National Institutes of Health, RePORTER application 9967044, Understanding Robustness of a Cooperative Microbial Community during Evolution (5R01GM124128-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9967044. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*