Abstract
ABSTRACT Microbes adopt a diversity of strategies to successfully compete with coexisting strains for space and resources. One common strategy is the production of toxic compounds to inhibit competitors, but the strength and direction of selection for this strategy varies depending on the environment. In particular, existing theoretical and experimental evidence suggests growth in spatially-structured environments makes toxin production more beneficial because competitive interactions are localized. Because higher growth rates increase the localization of resource competition in a structured environment, theory predicts that toxin production should be especially beneficial under these conditions. We tested this hypothesis by developing a genome-scale metabolic modeling approach and complementing it with comparative genomics to investigate the impact of growth rate on selection for costly toxin production. Our modeling approach expands the current abilities of the dynamic flux balance analysis platform COMETS to incorporate signaling and toxin production. Using this capability, we find that our modeling framework predicts that the strength of selection for toxin production increases as growth rate increases. This finding is supported by comparative genomics analyses that include diverse microbial species. Our work emphasizes that toxin production is more likely to be maintained in rapidly-growing, spatially-structured communities, thus improving our ability to manage critical microbial communities and informing natural product discovery.
Full text
1,696 characters
· extracted from
oa-doi-fallback
· click to expand
ABSTRACT
Microbes adopt a diversity of strategies to successfully compete with coexisting strains for space and resources. One common strategy is the production of toxic compounds to inhibit competitors, but the strength and direction of selection for this strategy varies depending on the environment. In particular, existing theoretical and experimental evidence suggests growth in spatially-structured environments makes toxin production more beneficial because competitive interactions are localized. Because higher growth rates increase the localization of resource competition in a structured environment, theory predicts that toxin production should be especially beneficial under these conditions. We tested this hypothesis by developing a genome-scale metabolic modeling approach and complementing it with comparative genomics to investigate the impact of growth rate on selection for costly toxin production. Our modeling approach expands the current abilities of the dynamic flux balance analysis platform COMETS to incorporate signaling and toxin production. Using this capability, we find that our modeling framework predicts that the strength of selection for toxin production increases as growth rate increases. This finding is supported by comparative genomics analyses that include diverse microbial species. Our work emphasizes that toxin production is more likely to be maintained in rapidly-growing, spatially-structured communities, thus improving our ability to manage critical microbial communities and informing natural product discovery.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Study Funding Information: NSF 1935458 to WRH
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.