ENIGMA Environmental Atlas: An Integrated Approach to Linking Microbial Genotype to Phenotype in a Dynamic Subsurface Ecosystem
Romy Chakraborty1* (email@example.com), Adam M. Deutschbauer2, Brandon C. Enalls1, Jennifer V. Kuehl2, Markus de Raad2, Bradley W. Biggs2, Hira Lesea2, Lauren M. Lui2, Valentine V. Trotter2, John-Marc Chandonia2, Torben Nielsen2, Hans K. Carlson2, Mingfei Chen1, Peter J. Walian1, Trent R. Northen2, Adam P. Arkin2, and Paul D. Adams1
1Lawrence Berkeley National Laboratory (LBNL); and 2University of California–Berkeley
The goal of the Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA) Science Focus Area (SFA) is to develop theoretical, technological, and scientific approaches to gain a predictive and mechanistic understanding of the biotic and abiotic factors that constrain microbial communities’ assembly and activity in dynamic environments. To link genetic, ecological, and environmental factors to the structure and function of microbial communities, ENIGMA uses a systems biology approach to integrate and develop laboratory, field, and computational methods.
Despite decades of research, there are still significant gaps in fundamental understanding of microbes, their interactions to form communities, and their relationships with the environment. Towards this, this project is constructing an ‘ENIGMA Environmental Atlas,’ a valuable resource that enables mapping genotype to phenotype for a significant number of diverse subsurface microbes at the research field site, the Oak Ridge Reservation Field Research Center. This Atlas includes a growing collection of over 2200 microbial isolates representing 36 orders and 895 unique strains from the site. Genome sequencing of 750 isolates to date has revealed both macro and microdiversity. High-resolution electron microscopy images reveal unique morphotypes and features. Researchers have established genetic toolkits and genome-wide mutant libraries in 25 diverse isolates to date and are using these resources to annotate genes of unknown function and interrogate physiological responses to environmental stressors.
The team has combined several statistical analyses using field environmental and sequencing-based metadata to identify high-priority targets for deeper isolation and characterization effort based on abundance, community correlation, and other metrics. The team is developing diverse assays to investigate the physiology of these ‘most wanted’ microbes including high throughput carbon utilization, metal toxicity thresholds, biofilm formation, and exometabolomic profiling. Exometabolomic profiling of 135 isolates confirmed that substrate use is phylogenetically conserved. Together, these measurements enable understanding the interaction of microbes with each other and determining if field measurements of co-occurrence coincide with positive interactions among isolates, helping to progress the ability to predict community function from metagenomic and amplicon sequence variant data.
The team presents progress thus far on the development of this unique community-usable platform and highlights several instances where the Atlas can be used to better understand the complexities that govern microbial community structure and function in the environment.
This material by ENIGMA SFA Program at Lawrence Berkeley National Laboratory is based upon work supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research (BER) Program under contract number DE-AC02-05CH11231.