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An Economic Framework of Microbial Trade.

Tasoff J, Mee MT, Wang HH - PLoS ONE (2015)

Bottom Line: Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities.Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum.This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

View Article: PubMed Central - PubMed

Affiliation: Department of Economics, Claremont Graduate University, Claremont, California, United States of America.

ABSTRACT
A large fraction of microbial life on earth exists in complex communities where metabolic exchange is vital. Microbes trade essential resources to promote their own growth in an analogous way to countries that exchange goods in modern economic markets. Inspired by these similarities, we developed a framework based on general equilibrium theory (GET) from economics to predict the population dynamics of trading microbial communities. Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities. We find that the economic concept of comparative advantage is a necessary condition for mutualistic trade. Our model suggests that microbial communities can grow faster when species are unable to produce essential resources that are obtained through trade, thereby promoting metabolic specialization and increased intercellular exchange. Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum. We experimentally tested this tradeoff using a synthetic consortium of Escherichia coli cells and found the results match the predictions of the model. This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

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(a)-(c) Stable contribution-space of three populations with decreasing comparative advantage.Horizontal and vertical axes are contribution rates of species-1 and species-2 respectively. Productivity parameters are , ,  for (a), , ,  for (b), and , ,  for (c). Color contours are the population ratio of species-2 versus species-1 in the form of log(N2 / N1). The stable contribution-space shrinks as comparative advantage decreases. (d) Dotted line cross-section from plot (b) showing population ratio as a function of species-1 contribution  for a fixed species-2 contribution of . (e) Populations growth rate of plot (b) with darker contours representing increased growth rate. (f) Dotted line cross-section from plot (e) showing growth rate as a function of species-1 contribution  for a fixed species-2 contribution of .
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pone.0132907.g005: (a)-(c) Stable contribution-space of three populations with decreasing comparative advantage.Horizontal and vertical axes are contribution rates of species-1 and species-2 respectively. Productivity parameters are , , for (a), , , for (b), and , , for (c). Color contours are the population ratio of species-2 versus species-1 in the form of log(N2 / N1). The stable contribution-space shrinks as comparative advantage decreases. (d) Dotted line cross-section from plot (b) showing population ratio as a function of species-1 contribution for a fixed species-2 contribution of . (e) Populations growth rate of plot (b) with darker contours representing increased growth rate. (f) Dotted line cross-section from plot (e) showing growth rate as a function of species-1 contribution for a fixed species-2 contribution of .

Mentions: It remains an open question whether comparative advantage is necessary for two populations to live together in SSS. We consider a community of two trading species where the productivity ratios of the two species are reciprocals of each other, that is . This means that, for example, a species-1 cell may produce four molecules of metabolite-1 and two of metabolite-2 for every glucose molecule consumed, and a species-2 cell may produce two of metabolite-1 and four of metabolite-2 for every glucose molecule consumed. By definition, as this productivity ratio increases so does the comparative advantage. For simplicity, we assume that the growth requirements for each metabolite for both species is one (i.e. ). Thus for populations with different magnitudes of comparative advantage, there exists different sets of SSS (Fig 5A–5C). An increase in the metabolite contribution rate by a species will move the SSS along the surface where the contours indicate the population ratio log(N2 / N1). Here, we refer to the contribution-space that produces SSS as the “stable contribution-space”. When there is no comparative advantage (i.e. ), the stable contribution-space is empty. An increase in comparative advantage leads to a larger stable contribution-space (Fig 5A–5C). The analysis indicates that for this setup, comparative advantage is necessary for SSS. Further discussions on the shape and intuition regarding the stable contribution-space can be found in the Supporting InformationS1 Appendix.


An Economic Framework of Microbial Trade.

Tasoff J, Mee MT, Wang HH - PLoS ONE (2015)

(a)-(c) Stable contribution-space of three populations with decreasing comparative advantage.Horizontal and vertical axes are contribution rates of species-1 and species-2 respectively. Productivity parameters are , ,  for (a), , ,  for (b), and , ,  for (c). Color contours are the population ratio of species-2 versus species-1 in the form of log(N2 / N1). The stable contribution-space shrinks as comparative advantage decreases. (d) Dotted line cross-section from plot (b) showing population ratio as a function of species-1 contribution  for a fixed species-2 contribution of . (e) Populations growth rate of plot (b) with darker contours representing increased growth rate. (f) Dotted line cross-section from plot (e) showing growth rate as a function of species-1 contribution  for a fixed species-2 contribution of .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4519184&req=5

pone.0132907.g005: (a)-(c) Stable contribution-space of three populations with decreasing comparative advantage.Horizontal and vertical axes are contribution rates of species-1 and species-2 respectively. Productivity parameters are , , for (a), , , for (b), and , , for (c). Color contours are the population ratio of species-2 versus species-1 in the form of log(N2 / N1). The stable contribution-space shrinks as comparative advantage decreases. (d) Dotted line cross-section from plot (b) showing population ratio as a function of species-1 contribution for a fixed species-2 contribution of . (e) Populations growth rate of plot (b) with darker contours representing increased growth rate. (f) Dotted line cross-section from plot (e) showing growth rate as a function of species-1 contribution for a fixed species-2 contribution of .
Mentions: It remains an open question whether comparative advantage is necessary for two populations to live together in SSS. We consider a community of two trading species where the productivity ratios of the two species are reciprocals of each other, that is . This means that, for example, a species-1 cell may produce four molecules of metabolite-1 and two of metabolite-2 for every glucose molecule consumed, and a species-2 cell may produce two of metabolite-1 and four of metabolite-2 for every glucose molecule consumed. By definition, as this productivity ratio increases so does the comparative advantage. For simplicity, we assume that the growth requirements for each metabolite for both species is one (i.e. ). Thus for populations with different magnitudes of comparative advantage, there exists different sets of SSS (Fig 5A–5C). An increase in the metabolite contribution rate by a species will move the SSS along the surface where the contours indicate the population ratio log(N2 / N1). Here, we refer to the contribution-space that produces SSS as the “stable contribution-space”. When there is no comparative advantage (i.e. ), the stable contribution-space is empty. An increase in comparative advantage leads to a larger stable contribution-space (Fig 5A–5C). The analysis indicates that for this setup, comparative advantage is necessary for SSS. Further discussions on the shape and intuition regarding the stable contribution-space can be found in the Supporting InformationS1 Appendix.

Bottom Line: Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities.Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum.This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

View Article: PubMed Central - PubMed

Affiliation: Department of Economics, Claremont Graduate University, Claremont, California, United States of America.

ABSTRACT
A large fraction of microbial life on earth exists in complex communities where metabolic exchange is vital. Microbes trade essential resources to promote their own growth in an analogous way to countries that exchange goods in modern economic markets. Inspired by these similarities, we developed a framework based on general equilibrium theory (GET) from economics to predict the population dynamics of trading microbial communities. Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities. We find that the economic concept of comparative advantage is a necessary condition for mutualistic trade. Our model suggests that microbial communities can grow faster when species are unable to produce essential resources that are obtained through trade, thereby promoting metabolic specialization and increased intercellular exchange. Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum. We experimentally tested this tradeoff using a synthetic consortium of Escherichia coli cells and found the results match the predictions of the model. This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

No MeSH data available.


Related in: MedlinePlus