A microbial model of economic trading and comparative advantage

Economic microbiology: exploring microbes as agents in economic systems

Microbial communities exhibit striking parallels with economic markets, resembling intricate ecosystems where microorganisms engage in resource exchange akin to human market transactions. This dynamic network of resource swapping mirrors economic trade in human markets, with microbes specializing in metabolic functions much like businesses specializing in goods and services. Cooperation and competition are central dynamics in microbial communities, with alliances forming for mutual benefit and species vying for dominance, similar to businesses seeking market share. The human microbiome, comprising trillions of microorganisms within and on our bodies, is not only a marker of socioeconomic status but also a critical factor contributing to persistent health inequalities. Social and economic factors shape the composition of the gut microbiota, impacting healthcare access and quality of life. Moreover, these microbes exert indirect influence over human decisions by affecting neurotransmitter production, influencing mood, behavior, and choices related to diet and emotions. Human activities significantly impact microbial communities, from dietary choices and antibiotic use to environmental changes, disrupting these ecosystems. Beyond their natural roles, humans harness microbial communities for various applications, manipulating their interactions and resource exchanges to achieve specific goals in fields like medicine, agriculture, and environmental science. In conclusion, the concept of microbial communities as biological markets offers valuable insights into their intricate functioning and adaptability. It underscores the profound interplay between microbial ecosystems and human health and behavior, with far-reaching implications for multiple disciplines. To paraphrase Alfred Marshall, "the Mecca of the economist lies in economic microbiology."

Bottom-up synthetic ecology study of microbial consortia to enhance lignocellulose bioconversion

Lignocellulose is the most abundant organic carbon polymer on the earth. Its decomposition and conversion greatly impact the global carbon cycle. Furthermore, it provides feedstock for sustainable fuel and other value-added products. However, it continues to be underutilized, due to its highly recalcitrant and heterogeneric structure. Microorganisms, which have evolved versatile pathways to convert lignocellulose, undoubtedly are at the heart of lignocellulose conversion. Numerous studies that have reported successful metabolic engineering of individual strains to improve biological lignin valorization. Meanwhile, the bottleneck of single strain modification is becoming increasingly urgent in the conversion of complex substrates. Alternatively, increased attention has been paid to microbial consortia, as they show advantages over pure cultures, e.g., high efficiency and robustness. Here, we first review recent developments in microbial communities for lignocellulose bioconversion. Furthermore, the emerging area of synthetic ecology, which is an integration of synthetic biology, ecology, and computational biology, provides an opportunity for the bottom-up construction of microbial consortia. Then, we review different modes of microbial interaction and their molecular mechanisms, and discuss considerations of how to employ these interactions to construct synthetic consortia via synthetic ecology, as well as highlight emerging trends in engineering microbial communities for lignocellulose bioconversion.

It's the Economy, Stupid: Applying (Micro)economic Principles to Microbiome Science

A key challenge in microbiome science is the scale mismatch problem, which arises when the scale at which microbial communities are sampled, interrogated, and averaged is different from the scale at which individual microorganisms within those communities interact with each other and with their environment. Profiling the microbial communities in a teaspoon of soil, from a scoop of fecal matter, or along a plant leaf surface represents a scale mismatch of multiple orders of magnitude, which may limit our ability to interpret or predict species interactions and community assembly within such samples. In this Perspective, we explore how economists, who are historically and topically split along the lines of micro- and macroeconomics, deal with the scale mismatch problem, and how taking clues from (micro)economists could benefit the field of microbiomics.

A piece of the pie: engineering microbiomes by exploiting division of labor in complex polysaccharide consumption

Although microbes competing for simple substrates are well-known to obey the ecological competitive exclusion principle, little is known regarding how complex substrates influence the ecology of microbial communities. The vast structural diversity of polysaccharides makes them ideal substrates for cooperative microbial degradation. Potential mechanisms for division of metabolic labor in microbial communities consuming polysaccharides are 1) complementary differences in gene content, 2) alternate regulation of polysaccharide degradation genes, 3) subtle differences in hydrolytic enzyme functionality, and 4) specialization in transport and consumption of hydrolysis products. Engineering division of labor in polysaccharide degradation using these mechanisms as control points may improve our ability to engineer microbiomes for improved productivity and stability in diverse environments.

Mathematical Modelling of Auxin Transport in Plant Tissues: Flux Meets Signalling and Growth

Plant hormone auxin has critical roles in plant growth, dependent on its heterogeneous distribution in plant tissues. Exactly how auxin transport and developmental processes such as growth coordinate to achieve the precise patterns of auxin observed experimentally is not well understood. Here we use mathematical modelling to examine the interplay between auxin dynamics and growth and their contribution to formation of patterns in auxin distribution in plant tissues. Mathematical models describing the auxin-related signalling pathway, PIN and AUX1 dynamics, auxin transport, and cell growth in plant tissues are derived. A key assumption of our models is the regulation of PIN proteins by the auxin-responsive ARF-Aux/IAA signalling pathway, with upregulation of PIN biosynthesis by ARFs. Models are analysed and solved numerically to examine the long-time behaviour and auxin distribution. Changes in auxin-related signalling processes are shown to be able to trigger transition between passage- and spot-type patterns in auxin distribution. The model was also shown to be able to generate isolated cells with oscillatory dynamics in levels of components of the auxin signalling pathway which could explain oscillations in levels of ARF targets that have been observed experimentally. Cell growth was shown to have influence on PIN polarisation and determination of auxin distribution patterns. Numerical simulation results indicate that auxin-related signalling processes can explain the different patterns in auxin distributions observed in plant tissues, whereas the interplay between auxin transport and growth can explain the ‘reverse-fountain’ pattern in auxin distribution observed at plant root tips.

Paradoxes in leaky microbial trade

Microbes produce metabolic resources that are important for cell growth yet leak into the environment. Other microbes can use these resources, adjust their own metabolic production accordingly, and alter the resources available for others. We analyze a model in which metabolite concentrations, production regulation, and population frequencies coevolve in the simple case of two cell types producing two metabolites. We identify three paradoxes where changes that should intuitively benefit a cell type actually harm it. For example, a cell type can become more efficient at producing a metabolite and its relative frequency can decrease-or alternatively the total population growth rate can decrease. Another paradox occurs when a cell type manipulates its counterpart's production so as to maximize its own instantaneous growth rate, only to achieve a lower final growth rate than had it not manipulated. These paradoxes highlight the complex and counterintuitive dynamics that emerge in simple microbial economies.

Maintenance of Microbial Cooperation Mediated by Public Goods in Single- and Multiple-Trait Scenarios

Microbes often form densely populated communities, which favor competitive and cooperative interactions. Cooperation among bacteria often occurs through the production of metabolically costly molecules produced by certain individuals that become available to other neighboring individuals; such molecules are called public goods. This type of cooperation is susceptible to exploitation, since nonproducers of a public good can benefit from it while saving the cost of its production (cheating), gaining a fitness advantage over producers (cooperators). Thus, in mixed cultures, cheaters can increase in frequency in the population, relative to cooperators. Sometimes, and as predicted by simple game-theoretic arguments, such increases in the frequency of cheaters cause loss of the cooperative traits by exhaustion of the public goods, eventually leading to a collapse of the entire population. In other cases, however, both cooperators and cheaters remain in coexistence. This raises the question of how cooperation is maintained in microbial populations. Several strategies to prevent cheating have been studied in the context of a single trait and a unique environmental constraint. In this review, we describe current knowledge on the evolutionary stability of microbial cooperation and discuss recent discoveries describing the mechanisms operating in multiple-trait and multiple-constraint settings. We conclude with a consideration of the consequences of these complex interactions, and we briefly discuss the potential role of social interactions involving multiple traits and multiple environmental constraints in the evolution of specialization and division of labor in microbes.

Principles for designing synthetic microbial communities

Advances in synthetic biology to build microbes with defined and controllable properties are enabling new approaches to design and program multispecies communities. This emerging field of synthetic ecology will be important for many areas of biotechnology, bioenergy and bioremediation. This endeavor draws upon knowledge from synthetic biology, systems biology, microbial ecology and evolution. Fully realizing the potential of this discipline requires the development of new strategies to control the intercellular interactions, spatiotemporal coordination, robustness, stability and biocontainment of synthetic microbial communities. Here, we review recent experimental, analytical and computational advances to study and build multi-species microbial communities with defined functions and behavior for various applications. We also highlight outstanding challenges and future directions to advance this field.

An Economic Framework of Microbial Trade

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.