How does spatial differentiation of ecotypes enhance microbial mutualism?

This project will investigate how cooperation among microbial species become more stable and productive over time. Microbes are major drivers of ecosystem function, recycling carbon, nitrogen, and minerals including rare earth metals. This project will investigate a central but poorly understood mechanism through which members of the same species specialize to perform specific tasks, divide labor, and improve productivity of the entire community. Decoding the rules that govern this specialization will transform the ability to rationally engineer microbial communities for biotechnology, materials science, and energy production. Specifically, outcomes of this research will provide a blueprint for engineering stable, productive synthetic communities that can be deployed across the bioeconomy—from the production of renewable biogas and agricultural bio-stimulants to industrial waste upcycling and critical mineral recovery. Notably, the project will train six high school student interns, three teachers, and 300 student ambassadors drawn from across all 50 states through on-site and on-line internships and the established Systems Thinkers in STEM Ambassadorship (STiSA). Participants will develop a next generation science standards (NGSS)-aligned curriculum module that connects microbial ecology, systems thinking, and computational modeling to real-world challenges. The cross-disciplinary training of students in systems biology, artificial intelligence (AI), and biotechnology, will help generate a workforce required for tackling the most pressing challenges of the future. Using a model synthetic community (SynCom) of a sulfate-reducing bacterium (Desulfovibrio vulgaris, Dv) and a methanogenic archaeon (Methanococcus maripaludis, Mm), researchers will test the hypothesis that microbial mutualism improves through the interplay of spatially and physiologically differentiated ecotypes within the same habitat. Prior work demonstrated that few mutations selected over a short evolutionary timescale (<1,000 generations) generated ecotypes that segregated across particle-attached and free-floating (planktonic) communities. Genome-scale modeling revealed metabolic specialization across ecotypes, boosting methane productivity of the entire community. The project pursues three research aims. In Aim 1, long-read genome sequencing of individual sediment particles and planktonic biomass will be used to resolve the biogeography of ecotypes within replicate bioreactors. Aim 2 develops SynPRIME—a novel five-compartment in silico model integrating gene regulatory networks with metabolic flux balance analysis—to uncover how transcriptional reprogramming drives the physiological interplay between spatially segregated ecotypes. In Aim 3, a library of genetically characterized ecotypes will be assembled into new SynComs through high-throughput pairwise screening and hypothesis-driven combinatorial assembly, enabling bottom-up testing of partner selection principles and direct validation of SynPRIME predictions. Together, these aims will reveal principles of ecotype specialization and community assembly, producing a generalizable systems biology framework to rationally design novel SynComs for biotechnology applications. In addition to training a graduate student and a postdoctoral researcher, this project will engage six high school student interns and three teachers in project-related science activities. The team will develop a Next Generation Science Standards-aligned high school curriculum module on how process partitioning by microbial communities drives nutrient cycles across ecosystems (e.g., soil, oceans, and root). Finally, the curriculum module will be disseminated to schools across the US and >100 countries, while measuring key performance indicators, including numbers of students and teachers impacted, student learning, and STEM identity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation NSF Award ID: 2622322 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Nitin Baliga | Institution: Institute for Systems Biology, SEATTLE, WA | Award Amount: $1,585,262 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2622322 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2622322.html