The m-CAFEs SFA, led by Lawrence Berkeley National Laboratory (LBNL), is developing and deploying unique laboratory capabilities that capture key aspects of grass rhizosphere communities in the field and identify the causal mechanisms that govern microbial interactions within the rhizosphere. Computational modeling is used to predict interactions and responses that are then tested experimentally and refined until they accurately predict field processes. [Courtesy LBNL]
The Microbial Community Analysis and Functional Evaluation in Soils (m-CAFEs) project is a multi-institutional Science Focus Area (SFA) aimed at understanding the interactions, localization, and dynamics of grass rhizosphere communities at the molecular level (i.e., genes, proteins, metabolites). Gaining this understanding will enable prediction of community responses to perturbations and insights into the persistence and fate of engineered genes and microbes for secure biosystems design. To achieve this understanding, advanced fabricated ecosystems (called EcoFABs) are used in combination with gene-editing technologies such as CRISPR-Cas and bacterial-virus approaches (i.e., phage-based methods) to interrogate gene and microbial functions in situ—addressing key challenges highlighted in recent U.S. Department of Energy reports. This work is integrated with the development of predictive computational models that are iteratively refined through simulation and experimentation. Simplified microbial consortia assembled in the laboratory are used in combination with studies of partially reduced, native soil-derived microbial communities to gain critical insights into engineered genes and microbes within soil microbiomes and the biology and ecology of uncultivated microbes. This SFA is currently piloting meter-scale contained and controlled ecosystems (called EcoPODs) that enable the extension of m-CAFEs science into more complex environments. The research on microbial communities leverages the team’s extensive expertise in CRISPR-Cas systems, phage biology, genome-resolved metagenomics, high-throughput bacterial and fungal genetics, and systems biology, as well as plant mutant collections and phenotyping capabilities. Together, these efforts lay a critical foundation for developing secure biosystems design strategies, harnessing beneficial microbiomes to support sustainable bioenergy, and improving the understanding of nutrient cycling in the rhizosphere. The knowledge gained and approaches pioneered by m-CAFEs can be extended to other ecosystems and will advance microbiome research toward a more predictive and causative science.