Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2024 Abstracts

Applying Metabolic Models to Mechanistically Understand and Predict Interactions Between Anaerobic Methanotrophic Archaea and Sulfate-Reducing Bacteria Strains in Geochemical Cycling Processes


Filipe Liu1* ([email protected]), Andrew P. Freiburger1, José P. Faria1, Nidhi Gupta1, Janaka Edirisinghe1, Ranjani Murali2, Grayson Chadwick2, Victoria Orphan2, Christopher S. Henry1


1Argonne National Laboratory; 2California Institute of Technology


Investigate metabolic syntropy between anaerobic methane oxidation (AOM) archaea with sulfate-reducing bacteria (SRB). Design a coupled methane (archaea)/sulfate electron transport chain (ETC) model. Evaluate the interaction between diverse strains of AOM archaea and SRB.


Microbial communities of methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) annually prevent the release of gigatons of methane into the environment and are therefore critical agents in climate regulation and geochemical cycling. The “reverse methanogenesis” of methane oxidation in ANME, which requires electron transfer to a syntrophic partner, is the proposed syntrophic mechanism that drives sulfate-coupled anaerobic oxidation of methane in these communities; however, their physiology, interactions, and ecology remain opaque.

To model this metabolic system and resolve mechanistic details, we improved our reconstruction pipeline for all archaea and bacteria to construct genome-scale metabolic models: the ModelSEED2. Our new archaea pipeline now captures unique pathways and reaction intermediates to archaea. We concurrently developed a suite of community modeling tools to mechanistically simulate syntrophic interactions within this community under native conditions, which is essential to contextualize the ecological roles of ANME and SRB. These community modeling tools permit the parameterization of omics data that represent metabolic phenotypes. Our method allows us to better recapitulate community dynamics with thermodynamic and uptake constraints. Further, we additionally developed new tools to leverage pangenome information from phylogenetically close strains to improve model reconstruction for metagenome-assembled- genomes (MAGs), which are often incomplete when analyzed on their own. These tools are critical for modeling ANME strains because they cannot be isolated in the laboratory and are thus all MAGs. Due to the limited biomass available in these systems, ANME MAGs are also often incomplete. To overcome this challenge, we applied a pangenome-based approach to enhance our ANME MAG models to include all core genes from the pangenome, boosting the size of our ANME models by hundreds of conserved reactions while still preserving the distinctive metabolic features that distinguish each ANME clade. We construct metabolic models of several ANME and SRB MAGs that were assembled and binned from metagenomic data from previous studies (Chadwick et al. 2022; Murali et al. 2023). We implemented an energy metabolism pathway that couples anaerobic methane oxidation with the sulfate reduction pathway.

The improved annotation accuracy of these models will empower community simulations towards resolving the “reverse methanogenesis” hypothesis, which may explain the natural stability and selectivity of these communities and would ultimately clarify anthropogenic influences on these keystone communities and biogeochemical cycles in marine environments. We perform a detailed accounting for the flow of nutrients and energy within our community model to mechanistically explain low yields and slow growth in these systems.


Murali, R., et al. 2023. “Physiological Potential and Evolutionary Trajectories of Syntrophic Sulfate-Reducing Bacterial Partners of Anaerobic Methanotrophic Archaea,” PLoS Biology, 21(9). DOI:10.1371/journal.pbio.3002292.

Chadwick, G. L., et al. 2022. “Comparative Genomics Reveals Electron Transfer and Syntrophic Mechanisms Differentiating Methanotrophic and Methanogenic Archaea. PLOS Biology 20(1), e3001508. DOI:10.1371/journal.pbio.3001508.

Funding Information

This work is supported as part of the BER DE-FOA-0002602. At Argonne National Laboratory, DE-FOA-0002602 is funded by the U.S. DOE, Office of Science, BER program under Award Number DE-AC02-06CH11357.