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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.

No MeSH data available.


Related in: MedlinePlus

Biotic Equilibrium in the 2x2 Model.Cell 1 takes glucose  and uses it to produce the orange metabolite-1, and the red metabolite-2, A fraction , of metabolite-1 production is exported and a fraction of the export is then re-imported. The cell also imports red metabolite-2 from cell 2. The imports plus the production for each metabolite equals the consumption of each metabolite  and , facilitating growth u1.
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pone.0132907.g002: Biotic Equilibrium in the 2x2 Model.Cell 1 takes glucose and uses it to produce the orange metabolite-1, and the red metabolite-2, A fraction , of metabolite-1 production is exported and a fraction of the export is then re-imported. The cell also imports red metabolite-2 from cell 2. The imports plus the production for each metabolite equals the consumption of each metabolite and , facilitating growth u1.

Mentions: Consider a community of microbes in a well-mixed environment, which contains nutrients that each microbe can use to grow and produce various metabolites. Some of these metabolites are released back into the environment where they are taken up by other microbes for utilization. For simplicity, let us consider a community containing two distinct species, each able to convert one primary resource abundantly available in the medium (e.g. sugars) into two additional metabolites (e.g. amino acids) that then can be readily exchanged through membrane transporters. Both species need the two produced metabolites for growth, and both possess the metabolic pathways necessary to generate them. Biotic general equilibrium theory (BGET) takes the growth needs, metabolic capabilities, and intercellular transport rates of each species and determines the production and allocation of metabolites, and instantaneous growth rate of each species (Fig 1). To determine the population dynamics over time, BGET is then iterated over a discrete-time framework. We refer to “variables” as outputs of the model and “parameters” as inputs. In the main text of this paper, we describe the basic intuition of the model using a 2-member community as an example and focus on stable steady-state population dynamics. A formalized description of the 2-member model is presented in the Materials and Methods section. A list of parameters and variables and a diagram that depicts their relations is presented in Fig 2. The general BGET model that allows for an arbitrary collection of species, metabolites, and metabolic interactions is also detailed in the Materials and Methods section.


An Economic Framework of Microbial Trade.

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

Biotic Equilibrium in the 2x2 Model.Cell 1 takes glucose  and uses it to produce the orange metabolite-1, and the red metabolite-2, A fraction , of metabolite-1 production is exported and a fraction of the export is then re-imported. The cell also imports red metabolite-2 from cell 2. The imports plus the production for each metabolite equals the consumption of each metabolite  and , facilitating growth u1.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0132907.g002: Biotic Equilibrium in the 2x2 Model.Cell 1 takes glucose and uses it to produce the orange metabolite-1, and the red metabolite-2, A fraction , of metabolite-1 production is exported and a fraction of the export is then re-imported. The cell also imports red metabolite-2 from cell 2. The imports plus the production for each metabolite equals the consumption of each metabolite and , facilitating growth u1.
Mentions: Consider a community of microbes in a well-mixed environment, which contains nutrients that each microbe can use to grow and produce various metabolites. Some of these metabolites are released back into the environment where they are taken up by other microbes for utilization. For simplicity, let us consider a community containing two distinct species, each able to convert one primary resource abundantly available in the medium (e.g. sugars) into two additional metabolites (e.g. amino acids) that then can be readily exchanged through membrane transporters. Both species need the two produced metabolites for growth, and both possess the metabolic pathways necessary to generate them. Biotic general equilibrium theory (BGET) takes the growth needs, metabolic capabilities, and intercellular transport rates of each species and determines the production and allocation of metabolites, and instantaneous growth rate of each species (Fig 1). To determine the population dynamics over time, BGET is then iterated over a discrete-time framework. We refer to “variables” as outputs of the model and “parameters” as inputs. In the main text of this paper, we describe the basic intuition of the model using a 2-member community as an example and focus on stable steady-state population dynamics. A formalized description of the 2-member model is presented in the Materials and Methods section. A list of parameters and variables and a diagram that depicts their relations is presented in Fig 2. The general BGET model that allows for an arbitrary collection of species, metabolites, and metabolic interactions is also detailed in the Materials and Methods section.

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