Synergistic epistasis enhances cooperativity of mutualistic interspecies interactions
Abstract
Frequent fluctuations in sulfate availability rendered syntrophic interactions between the sulfate reducing bacterium Desulfovibrio vulgaris (Dv) and the methanogenic archaeon Methanococcus maripaludis (Mm) unsustainable. By contrast, prolonged laboratory evolution in obligate syntrophy conditions improved the productivity of this community but at the expense of erosion of sulfate respiration (SR). Hence, we sought to understand the evolutionary trajectories that could both increase the productivity of syntrophic interactions and sustain SR. We combined a temporal and combinatorial survey of mutations accumulated over 1000 generations of 9 independently-evolved communities with analysis of the genotypic structure for one community down to the single-cell level. We discovered a high level of parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance of a rare SR+ Dv lineage within many evolution lines. An in-depth investigation revealed that synergistic epistasis across Dv and Mm genotypes had enhanced cooperativity within SR- and SR+ assemblages, allowing their co-existence as r- and K-strategists, respectively.
Additional Information
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. This material by ENIGMA-Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Science Focus Area Program at Lawrence Berkeley National Laboratory is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research under contract number DE-AC02-05CH11231. In addition, sequencing of ancestral cocultures and early generation samples was supported by the National Science Foundation under Grant No. DEB-1453205 and DEB-1257525 to KLH. The pipeline for sequencing data analysis was developed using funds from the National Institute of Health under grant number R01AI141953 to NSB. We would like to thank Nicholas Elliott for his help with growth analysis, Joseph Hellerstein, and Adrian Lopez Garcia de Lomana for discussion on data analysis. Author Contributions: Conceptualization and Methodology, S.T., N.S., N.S.B., D.A.S. and K.L.H; Investigation, S.T., N.S., A.W.T., C.E.A., J.J.V., J.W., K.A.H., J.H., Y.F., L.W., and Y.M.S.; Formal Analysis, S.T., N.S., and N.S.B.; Data Curation, S.T., N.S., K.L.H., K.A.H., and N.S.B; Writing – Original Draft, S.T., N.S.B., K.L.H., and D.A.S.; Visualization, S.T., N.S.B.; Supervision, N.S.B., K.L.H., and D.A.S.; Resources and Funding Acquisition, J.Z., N.S.B., K.L.H., and D.A.S. The authors have declared no competing interest. Data and Code Availability: Bulk and Single cell sequencing data used in this study and associated biosample meta-data information can be obtained through the NCBI Bioproject database (https://www.ncbi.nlm.nih.gov/bioproject) with accession number PRJNA248017. Custom R and Python codes used for sequence analysis, variant calling, data analysis and figure preparations are available on GitHub (https://github.com/sturkarslan/evolution-of-syntrophy). Annotated mutations within the context of other functional and regulatory genome information can be explored through Syntrophy Portal (http://networks.systemsbiology.net/syntrophy/).Attached Files
Submitted - 2020.06.22.160184v2.full.pdf
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Additional details
- Eprint ID
- 104077
- Resolver ID
- CaltechAUTHORS:20200626-103612993
- Department of Energy (DOE)
- DE-AC02-05CH11231
- NSF
- DEB-1453205
- NSF
- DEB-1257525
- NIH
- R01AI141953
- Created
-
2020-06-26Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field