NSF Award
2448203
Microbial communities and microbiomes occur everywhere and impact soil health, environmental processes, human health, and many other process that impact climate resilience and the bioeconomy. To date, is has been difficult to predict how the addition of new microbial species into a community impacts microbiome function, and as such, it has been difficult to design microbiomes with desired functions. The prediction of microbiome functions from the genotypes of constituent species remains a longstanding, unsolved problem in microbiome science and engineering. The long-term goal of this project is to develop and apply an integrated experimental and computational approach to uncover the design principles at the molecular and cellular level that govern microbiome function. These models would be able to then be used in a variety of applications to solve problems related to climate resilience, human health, and the bioeconomy. In addition, the investigators will increase the inclusion and public participation in STEM by partnering with a well-established informal science education program at the Morgridge Institute for Research, serving thousands of youths per year. <br/><br/>This project will integrate advanced machine learning techniques with high-throughput microbial community construction and metabolomics in order to elucidate design principles of molecular networks involving any cellular process (e.g. metabolism, stress, signaling) that govern microbiome functions. Notably, the proposed framework will enable the prediction of new and uncharacterized species on microbiome functions, which has not been previously demonstrated using a data-driven model. The investigators will apply this multi-scale modeling framework to study the effects of diverse bacteria on community composition and anaerobic metabolic states. While this proposal focuses on the genotype-function mapping of microbial communities, the data-driven framework will provide a foundation for the prediction of microbiome functions from omics data including transcriptional profiling data, proteomics and beyond. The novel systems biology framework could be applied more broadly to any microbiome or microbiome function. Deciphering the molecular-level design principles of microbiomes would provide a deeper insight into the organizational principles of these energetically efficient and resilient systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
