Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Serdar Turkarslan, Nejc Stopnisek, Anne W. Thompson, Christina E. Arens, Jacob J. Valenzuela, James Wilson, Kristopher A. Hunt, Jessica Hardwicke, Adrián López García de Lomana, Sujung Lim, Yee Mey Seah, Ying Fu, Liyou Wu, Jizhong Zhou, Kristina L. Hillesland, David A. Stahl, Nitin S. Baliga*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR− and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.

Original languageEnglish
Pages (from-to)2233-2247
Number of pages15
JournalISME Journal
Volume15
Issue number8
DOIs
Publication statusPublished - 21 Feb 2021

Bibliographical note

Funding Information:
Acknowledgements This material by Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA) (http:// enigma.lbl.gov), a Science Focus Area Program at Lawrence Berkeley National Laboratory is based upon work supported by the US Department of Energy, Office of Science, Office of Biological, and Environmental Research under contract number DE-AC02-05CH11231. Sequencing of ancestral and early generation cocultures was supported by the National Science Foundation grant no. DEB-1453205 and DEB-1257525 to KLH. Development of the sequencing analysis pipeline was funded by the National Institute of Health under grant number R01AI141953 to NSB. Authors thank to Nicholas Elliott for his help with growth analysis, and Joseph Hellerstein for discussion on data analysis.

Publisher Copyright:
© 2021, The Author(s).

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