Spatial self-organization favors heterotypic cooperation over cheating

Synthetic Ecosystems: From the Test Tube to the Biosphere

The study of ecosystems, both natural and artificial, has historically been mediated by population dynamics theories. In this framework, quantifying population numbers and related variables (associated with metabolism or biological-environmental interactions) plays a central role in measuring and predicting system-level properties. As we move toward advanced technological engineering of cells and organisms, the possibility of bioengineering ecosystems (from the gut microbiome to wildlands) opens several questions that will require quantitative models to find answers. Here, we present a comprehensive survey of quantitative modeling approaches for managing three kinds of synthetic ecosystems, sharing the presence of engineered strains. These include test tube examples of ecosystems hosting a relatively low number of interacting species, mesoscale closed ecosystems (or ecospheres), and macro-scale, engineered ecosystems. The potential outcomes of synthetic ecosystem designs and their limits will be relevant to different disciplines, including biomedical engineering, astrobiology, space exploration and fighting climate change impacts on endangered ecosystems. We propose a space of possible ecosystems that captures this broad range of scenarios and a tentative roadmap for open problems and further exploration.

A simple model and rules for the evolution of microbial mutualistic symbiosis with positive fitness feedbacks

The evolution of microbe-microbe mutualistic symbiosis is considered to be promoted by repeated exchanges of fitness benefits, which can generate positive fitness feedbacks ('partner fidelity feedback') between species. However, previous evolutionary models for mutualism have not captured feedback dynamics or coupling of fitness between species. Here, a simple population model is developed to understand the evolution of mutualistic symbiosis in which two microbial species (host and symbiont) continuously grow and exchange fitness benefits to generate feedback dynamics but do not strictly control each other. The assumption that individual microbes provide constant amounts of resources, which are equally divided among interacting partner individual, enables us to reveal a simple rule for the evolution of costly mutualism with positive fitness feedbacks: the product of the benefit-to-cost ratios for each species exceeds one. When this condition holds, high cooperative investment levels are favored in both species regardless of the amount invested by each partner. The model is then extended to examine how symbiont mutation, immigration, or switching affects the spread of selfish or cooperative symbionts, which decrease and increase their investment levels, respectively. In particular, when a host associates with numerous symbionts without enforcement, neither mutation nor immigration but rather random switching would allow the spread of cooperative symbionts. Examples using symbiont switching for evolution would include large ciliates hosting numerous intracellular endosymbionts. The simple model and rules would provide a basis for understanding the evolution of microbe-microbe mutualistic symbiosis with positive fitness feedbacks and without enforcement mechanisms.

Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities

The gut microbiome plays a major role in human health; however, little is known about the structural arrangement of microbes and factors governing their distribution. In this work, we present an in silico agent-based model (ABM) to conceptually simulate the dynamics of gut mucosal bacterial communities. We explored how various types of metabolic interactions, including competition, neutralism, commensalism, and mutualism, affect community structure, through nutrient consumption and metabolite exchange. Results showed that, across scenarios with different initial species abundances, cross-feeding promotes species coexistence. Morphologically, competition and neutralism resulted in segregation, while mutualism and commensalism fostered high intermixing. In addition, cooperative relations resulted in community properties with little sensitivity to the selective uptake of metabolites produced by the host. Moreover, metabolic interactions strongly influenced colonization success following the invasion of newcomer species. These results provide important insights into the utility of ABM in deciphering complex microbiome patterns.

Metabolic interactions control the transfer and spread of plasmid-encoded antibiotic resistance during surface-associated microbial growth

Surface-associated microbial systems are hotspots for the spread of plasmid-encoded antibiotic resistance, but how surface association affects plasmid transfer and proliferation remains unclear. Surface association enables prolonged spatial proximities between different populations, which promotes plasmid transfer between them. However, surface association also fosters strong metabolic interactions between different populations, which can direct their spatial self-organization with consequences for plasmid transfer and proliferation. Here, we hypothesize that metabolic interactions direct the spatial self-organization of different populations and, in turn, regulate the spread of plasmid-encoded antibiotic resistance. We show that resource competition causes populations to spatially segregate, which represses plasmid transfer. In contrast, resource cross-feeding causes populations to spatially intermix, which promotes plasmid transfer. We further show that the spatial positionings that emerge from metabolic interactions determine the proliferation of plasmid recipients. Our results demonstrate that metabolic interactions are important regulators of both the transfer and proliferation of plasmid-encoded antibiotic resistance.

Spontaneous symmetry breaking of cooperation between species

In mutualistic associations, two species cooperate by exchanging goods or services with members of another species for their mutual benefit. At the same time, competition for reproduction primarily continues with members of their own species. In intra-species interactions, the prisoner's dilemma is the leading mathematical metaphor to study the evolution of cooperation. Here we consider inter-species interactions in the spatial prisoner's dilemma, where members of each species reside on one lattice layer. Cooperators provide benefits to neighbouring members of the other species at a cost to themselves. Hence, interactions occur across layers but competition remains within layers. We show that rich and complex dynamics unfold when varying the cost-to-benefit ratio of cooperation, r. Four distinct dynamical domains emerge that are separated by critical phase transitions, each characterized by diverging fluctuations in the frequency of cooperation: (i) for large r cooperation is too costly and defection dominates; (ii) for lower r cooperators survive at equal frequencies in both species; (iii) lowering r further results in an intriguing, spontaneous symmetry breaking of cooperation between species with increasing asymmetry for decreasing r; (iv) finally, for small r, bursts of mutual defection appear that increase in size with decreasing r and eventually drive the populations into absorbing states. Typically, one species is cooperating and the other defecting and hence establish perfect asymmetry. Intriguingly and despite the symmetrical model set-up, natural selection can nevertheless favour the spontaneous emergence of asymmetric evolutionary outcomes where, on average, one species exploits the other in a dynamical equilibrium.

Enhanced metabolic entanglement emerges during the evolution of an interkingdom microbial community

While different stages of mutualism can be observed in natural communities, the dynamics and mechanisms underlying the gradual erosion of independence of the initially autonomous organisms are not yet fully understood. In this study, by conducting the laboratory evolution on an engineered microbial community, we reproduce and molecularly track the stepwise progression towards enhanced partner entanglement. We observe that the evolution of the community both strengthens the existing metabolic interactions and leads to the emergence of de novo interdependence between partners for nitrogen metabolism, which is a common feature of natural symbiotic interactions. Selection for enhanced metabolic entanglement during the community evolution repeatedly occurred indirectly, via pleiotropies and trade-offs within cellular regulatory networks, and with no evidence of group selection. The indirect positive selection of metabolic dependencies between microbial community members, which results from the direct selection of other coupled traits in the same regulatory network, may therefore be a common but underappreciated driving force guiding the evolution of natural mutualistic communities.

Strategies to enhance production of metabolites in microbial co-culture systems

Increasing evidence shows that microbial synthesis plays an important role in producing high value-added products. However, microbial monoculture generally hampers metabolites production and limits scalability due to the increased metabolic burden on the host strain. In contrast, co-culture is a more flexible approach to improve the environmental adaptability and reduce the overall metabolic burden. The well-defined co-culturing microbial consortia can tap their metabolic potential to obtain yet-to-be discovered and pre-existing metabolites. This review focuses on the use of a co-culture strategy and its underlying mechanisms to enhance the production of products. Notably, the significance of comprehending the microbial interactions, diverse communication modes, genetic information, and modular co-culture involved in co-culture systems were highlighted. Furthermore, it addresses the current challenges and outlines potential future directions for microbial co-culture. This review provides better understanding the diversity and complexity of the interesting interaction and communication to advance the development of co-culture techniques.

The collapse of cooperation during range expansion of Pseudomonas aeruginosa

Cooperation is commonly believed to be favourable in spatially structured environments, as these systems promote genetic relatedness that reduces the likelihood of exploitation by cheaters. Here we show that a Pseudomonas aeruginosa population that exhibited cooperative swarming was invaded by cheaters when subjected to experimental evolution through cycles of range expansion on solid media, but not in well-mixed liquid cultures. Our results suggest that cooperation is disfavoured in a more structured environment, which is the opposite of the prevailing view. We show that spatial expansion of the population prolongs cooperative swarming, which was vulnerable to cheating. Our findings reveal a mechanism by which spatial structures can suppress cooperation through modulation of the quantitative traits of cooperation, a process that leads to population divergence towards distinct colonization strategies.

Mutualism at the leading edge: insights into the eco-evolutionary dynamics of host-symbiont communities during range expansion

The evolution of mutualism between host and symbiont communities plays an essential role in maintaining ecosystem function and should therefore have a profound effect on their range expansion dynamics. In particular, the presence of mutualistic symbionts at the leading edge of a host-symbiont community should enhance its propagation in space. We develop a theoretical framework that captures the eco-evolutionary dynamics of host-symbiont communities, to investigate how the evolution of resource exchange may shape community structure during range expansion. We consider a community with symbionts that are mutualistic or parasitic to various degrees, where parasitic symbionts receive the same amount of resource from the host as mutualistic symbionts, but at a lower cost. The selective advantage of parasitic symbionts over mutualistic ones is increased with resource availability (i.e. with host density), promoting mutualism at the range edges, where host density is low, and parasitism at the population core, where host density is higher. This spatial selection also influences the speed of spread. We find that the host growth rate (which depends on the average benefit provided by the symbionts) is maximal at the range edges, where symbionts are more mutualistic, and that host-symbiont communities with high symbiont density at their core (e.g. resulting from more mutualistic hosts) spread faster into new territories. These results indicate that the expansion of host-symbiont communities is pulled by the hosts but pushed by the symbionts, in a unique push-pull dynamic where both the host and symbionts are active and tightly-linked players.

Siderophore-mediated iron partition promotes dynamical coexistence between cooperators and cheaters

Microbes shape their habitats by consuming resources and producing a diverse array of chemicals that can serve as public goods. Despite the risk of exploitation by cheaters, genes encoding sharable molecules like siderophores are widely found in nature, prompting investigations into the mechanisms that allow producers to resist invasion by cheaters. In this work, we presented the chemostat-typed "resource partition model" to demonstrate that dividing the iron resource between private and public siderophores can promote stable or dynamic coexistence between producers and cheaters in a well-mixed environment. Moreover, our analysis shows that when microbes not only consume but also produce resources, chemical innovation leads to stability criteria that differ from those of classical consumer resource models, resulting in more complex dynamics. Our work sheds light on the role of chemical innovations in microbial communities and the potential for resource partition to facilitate dynamical coexistence between cooperative and cheating organisms.

Initial type and abundance of cyanobacteria determine morphotype development of phototrophic ecosystems

Phototrophic aggregates containing filamentous cyanobacteria occur naturally, for example, as cryoconite on glaciers and microbialites in fresh or marine waters, but their formation is not fully understood. Laboratory models are now available to reproduce aggregation, that is, the formation of different morphotypes like hemispheroids, microbial mats or sphere-like aggregates we call photogranules. In the model, activated sludge as starting matrix is transformed into aggregates enclosed by a phototrophic layer of growing cyanobacteria. These cyanobacteria were either enriched from the matrix or we added them intentionally. We hypothesize that the resulting morphotype depends on the type and concentration of the added cyanobacteria. When cyanobacteria from mature photogranules were added to activated sludge, photogranulation was not observed, but microbial mats were formed. Photogranulation of sludge could be promoted when adding sufficient quantities of cyanobacterial strains that form clumps when grown as isolates. The cyanobacteria putatively responsible for photogranulation were undetectable or only present in low abundance in the final communities of photogranules, which were always dominated by mat-forming cyanobacteria. We suggest that, in a temporal succession, the ecosystem engineer initiating photogranulation eventually disappears, leaving behind its structural legacy. We conclude that understanding phototrophic aggregate formation requires considering the initial succession stages of the ecosystem development.

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure.

Impact of direct physical association and motility on fitness of a synthetic interkingdom microbial community

Mutualistic exchange of metabolites can play an important role in microbial communities. Under natural environmental conditions, such exchange may be compromised by the dispersal of metabolites and by the presence of non-cooperating microorganisms. Spatial proximity between members during sessile growth on solid surfaces has been shown to promote stabilization of cross-feeding communities against these challenges. Nonetheless, many natural cross-feeding communities are not sessile but rather pelagic and exist in turbulent aquatic environments, where partner proximity is often achieved via direct cell-cell adhesion, and cooperation occurs between physically associated cells. Partner association in aquatic environments could be further enhanced by motility of individual planktonic microorganisms. In this work, we establish a model bipartite cross-feeding community between bacteria and yeast auxotrophs to investigate the impact of direct adhesion between prokaryotic and eukaryotic partners and of bacterial motility in a stirred mutualistic co-culture. We demonstrate that adhesion can provide fitness benefit to the bacterial partner, likely by enabling local metabolite exchange within co-aggregates, and that it counteracts invasion of the community by a non-cooperating cheater strain. In a turbulent environment and at low cell densities, fitness of the bacterial partner and its competitiveness against a non-cooperating strain are further increased by motility that likely facilitates partner encounters and adhesion. These results suggest that, despite their potential fitness costs, direct adhesion between partners and its enhancement by motility may play key roles as stabilization factors for metabolic communities in turbulent aquatic environments.

Spatial self-organization of metabolism in microbial systems: A matter of enzymes and chemicals

Most bacteria live in dense, spatially structured communities such as biofilms. The high density allows cells to alter the local microenvironment, whereas the limited mobility can cause species to become spatially organized. Together, these factors can spatially organize metabolic processes within microbial communities so that cells in different locations perform different metabolic reactions. The overall metabolic activity of a community depends both on how metabolic reactions are arranged in space and on how they are coupled, i.e., how cells in different regions exchange metabolites. Here, we review mechanisms that lead to the spatial organization of metabolic processes in microbial systems. We discuss factors that determine the length scales over which metabolic activities are arranged in space and highlight how the spatial organization of metabolic processes affects the ecology and evolution of microbial communities. Finally, we define key open questions that we believe should be the main focus of future research.

Breakdown of clonal cooperative architecture in multispecies biofilms and the spatial ecology of predation

Biofilm formation, including adherence to surfaces and secretion of extracellular matrix, is common in the microbial world, but we often do not know how interaction at the cellular spatial scale translates to higher-order biofilm community ecology. Here we explore an especially understudied element of biofilm ecology, namely predation by the bacterium Bdellovibrio bacteriovorus. This predator can kill and consume many different Gram-negative bacteria, including Vibrio cholerae and Escherichia coli. V. cholerae can protect itself from predation within densely packed biofilm structures that it creates, whereas E. coli biofilms are highly susceptible to B. bacteriovorus. We explore how predator-prey dynamics change when V. cholerae and E. coli are growing in biofilms together. We find that in dual-species prey biofilms, E. coli survival under B. bacteriovorus predation increases, whereas V. cholerae survival decreases. E. coli benefits from predator protection when it becomes embedded within expanding groups of highly packed V. cholerae. But we also find that the ordered, highly packed, and clonal biofilm structure of V. cholerae can be disrupted if V. cholerae cells are directly adjacent to E. coli cells at the start of biofilm growth. When this occurs, the two species become intermixed, and the resulting disordered cell groups do not block predator entry. Because biofilm cell group structure depends on initial cell distributions at the start of prey biofilm growth, the surface colonization dynamics have a dramatic impact on the eventual multispecies biofilm architecture, which in turn determines to what extent both species survive exposure to B. bacteriovorus.

Environmental and ecological controls of the spatial distribution of microbial populations in aggregates

In microbial communities, the ecological interactions between species of different populations are responsible for the spatial distributions observed in aggregates (granules, biofilms or flocs). To explore the underlying mechanisms that control these processes, we have developed a mathematical modelling framework able to describe, label and quantify defined spatial structures that arise from microbial and environmental interactions in communities. An artificial system of three populations collaborating or competing in an aggregate is simulated using individual-based modelling under different environmental conditions. In this study, neutralism, competition, commensalism and concurrence of commensalism and competition have been considered. We were able to identify interspecific segregation of communities that appears in competitive environments (columned stratification), and a layered distribution of populations that emerges in commensal (layered stratification). When different ecological interactions were considered in the same aggregate, the resultant spatial distribution was identified as the one controlled by the most limiting substrate. A theoretical modulus was defined, with which we were able to quantify the effect of environmental conditions and ecological interactions to predict the most probable spatial distribution. The specific microbial patterns observed in our results allowed us to identify the optimal spatial organizations for bacteria to thrive when building a microbial community and how this permitted co-existence of populations at different growth rates. Our model reveals that although ecological relationships between different species dictate the distribution of bacteria, the environment controls the final spatial distribution of the community.

Guided by the principles of microbiome engineering: Accomplishments and perspectives for environmental use

Although the accomplishments of microbiome engineering highlight its significance for the targeted manipulation of microbial communities, knowledge and technical gaps still limit the applications of microbiome engineering in biotechnology, especially for environmental use. Addressing the environmental challenges of refractory pollutants and fluctuating environmental conditions requires an adequate understanding of the theoretical achievements and practical applications of microbiome engineering. Here, we review recent cutting-edge studies on microbiome engineering strategies and their classical applications in bioremediation. Moreover, a framework is summarized for combining both top-down and bottom-up approaches in microbiome engineering toward improved applications. A strategy to engineer microbiomes for environmental use, which avoids the build-up of toxic intermediates that pose a risk to human health, is suggested. We anticipate that the highlighted framework and strategy will be beneficial for engineering microbiomes to address difficult environmental challenges such as degrading multiple refractory pollutants and sustain the performance of engineered microbiomes in situ with indigenous microorganisms under fluctuating conditions.

Even allocation of benefits stabilizes microbial community engaged in metabolic division of labor

Microbial communities execute metabolic pathways to drive global nutrient cycles. Within a community, functionally specialized strains can perform different yet complementary steps within a linear pathway, a phenomenon termed metabolic division of labor (MDOL). However, little is known about how such metabolic behaviors shape microbial communities. Here, we derive a theoretical framework to define the assembly of a community that degrades an organic compound through MDOL. The framework indicates that to ensure community stability, the strains performing the initial steps should hold a growth advantage (m) over the "private benefit" (n) of the strain performing the last step. The steady-state frequency of the last strain is then determined by the quotient of n and m. Our experiments show that the framework accurately predicts the assembly of our synthetic consortia that degrade naphthalene through MDOL. Our results provide insights for designing and managing stable microbial systems for metabolic pathway optimization.

Growth instabilities shape morphology and genetic diversity of microbial colonies

Cellular populations assume an incredible variety of shapes ranging from circular molds to irregular tumors. While we understand many of the mechanisms responsible for these spatial patterns, little is known about how the shape of a population influences its ecology and evolution. Here, we investigate this relationship in the context of microbial colonies grown on hard agar plates. This a well-studied system that exhibits a transition from smooth circular disks to more irregular and rugged shapes as either the nutrient concentration or cellular motility is decreased. Starting from a mechanistic model of colony growth, we identify two dimensionless quantities that determine how morphology and genetic diversity of the population depend on the model parameters. Our simulations further reveal that population dynamics cannot be accurately described by the commonly-used surface growth models. Instead, one has to explicitly account for the emergent growth instabilities and demographic fluctuations. Overall, our work links together environmental conditions, colony morphology, and evolution. This link is essential for a rational design of concrete, biophysical perturbations to steer evolution in the desired direction.

Ecological modelling approaches for predicting emergent properties in microbial communities

Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties-patterns or functions that cannot be deduced linearly from the properties of the constituent parts-underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.

Substrate availability and toxicity shape the structure of microbial communities engaged in metabolic division of labor

Metabolic division of labor (MDOL) represents a widespread natural phenomenon, whereby a complex metabolic pathway is shared between different strains within a community in a mutually beneficial manner. However, little is known about how the composition of such a microbial community is regulated. We hypothesized that when degradation of an organic compound is carried out via MDOL, the concentration and toxicity of the substrate modulate the benefit allocation between the two microbial populations, thus affecting the structure of this community. We tested this hypothesis by combining modeling with experiments using a synthetic consortium. Our modeling analysis suggests that the proportion of the population executing the first metabolic step can be simply estimated by Monod-like formulas governed by substrate concentration and toxicity. Our model and the proposed formula were able to quantitatively predict the structure of our synthetic consortium. Further analysis demonstrates that our rule is also applicable in estimating community structures in spatially structured environments. Together, our work clearly demonstrates that the structure of MDOL communities can be quantitatively predicted using available information on environmental factors, thus providing novel insights into how to manage artificial microbial systems for the wide application of the bioindustry.

Dynamic proteome allocation regulates the profile of interaction of auxotrophic bacterial consortia

Microbial ecosystems are composed of multiple species in constant metabolic exchange. A pervasive interaction in microbial communities is metabolic cross-feeding and occurs when the metabolic burden of producing costly metabolites is distributed between community members, in some cases for the benefit of all interacting partners. In particular, amino acid auxotrophies generate obligate metabolic inter-dependencies in mixed populations and have been shown to produce a dynamic profile of interaction that depends upon nutrient availability. However, identifying the key components that determine the pair-wise interaction profile remains a challenging problem, partly because metabolic exchange has consequences on multiple levels, from allocating proteomic resources at a cellular level to modulating the structure, function and stability of microbial communities. To evaluate how ppGpp-mediated resource allocation drives the population-level profile of interaction, here we postulate a multi-scale mathematical model that incorporates dynamics of proteome partition into a population dynamics model. We compare our computational results with experimental data obtained from co-cultures of auxotrophic Escherichia coli K12 strains under a range of amino acid concentrations and population structures. We conclude by arguing that the stringent response promotes cooperation by inhibiting the growth of fast-growing strains and promoting the synthesis of metabolites essential for other community members.

Global dynamics of microbial communities emerge from local interaction rules

Most microbes live in spatially structured communities (e.g., biofilms) in which they interact with their neighbors through the local exchange of diffusible molecules. To understand the functioning of these communities, it is essential to uncover how these local interactions shape community-level properties, such as the community composition, spatial arrangement, and growth rate. Here, we present a mathematical framework to derive community-level properties from the molecular mechanisms underlying the cell-cell interactions for systems consisting of two cell types. Our framework consists of two parts: a biophysical model to derive the local interaction rules (i.e. interaction range and strength) from the molecular parameters underlying the cell-cell interactions and a graph based model to derive the equilibrium properties of the community (i.e. composition, spatial arrangement, and growth rate) from these local interaction rules. Our framework shows that key molecular parameters underlying the cell-cell interactions (e.g., the uptake and leakage rates of molecules) determine community-level properties. We apply our model to mutualistic cross-feeding communities and show that spatial structure can be detrimental for these communities. Moreover, our model can qualitatively recapitulate the properties of an experimental microbial community. Our framework can be extended to a variety of systems of two interacting cell types, within and beyond the microbial world, and contributes to our understanding of how community-level properties emerge from microscopic interactions between cells.

Microorganisms perform essential processes on our planet. Many of these processes result from interactions between different species growing in spatially structured communities. A central goal is to understand how community processes emerge from such interactions between cells. Here we develop a mathematical framework to derive community-level properties, such as the community composition, growth rate, and spatial organization, from the molecular mechanisms underlying these cell-cell interactions. We focus on mutualistic communities consisting of two cell types that need to interact with each other in order to grow. We derive equations that describe how changes in the molecular parameters of cellular interactions affect individuals’ and community properties. We find that spatial structure has a negative impact on these mutualistic communities: as cells become surrounded by their own type, they have less access to the other cell type with which they need to interact to grow well. We show that our framework can also be applied to other types of microbial communities and potentially to non-microbial systems such as tissues. More generally, this work advances our understanding of how scales are connected in biological systems, both in the microbial world and beyond.

Type IV Pilus Shapes a 'Bubble-Burst' Pattern Opposing Spatial Intermixing of Two Interacting Bacterial Populations

Microbes are social organisms that commonly live in sessile biofilms. Spatial patterns of populations within biofilms can be important determinants of community-level properties. Spatial intermixing emerging from microbial interaction is one of the best-studied characteristics of spatial patterns. The specific levels of spatial intermixing critically contribute to how the dynamics and functioning of such communities are governed. However, the precise factors that determine spatial patterns and intermixing remain unclear. Here, we investigated the spatial patterning and intermixing of an engineered synthetic consortium composed of two mutualistic Pseudomonas stutzeri strains that degrade salicylate via metabolic cross-feeding. We found that the consortium self-organizes across space to form a previously unreported spatial pattern (here referred to as a ‘bubble-burst’ pattern) that exhibits a low level of intermixing. Interestingly, when the genes encoding type IV pili were deleted from both strains, a highly intermixed spatial pattern developed and increased the productivity of the entire community. The intermixed pattern was maintained in a robust manner across a wide range of initial ratios between the two strains. Our findings show that the type IV pilus plays a role in mitigating spatial intermixing of different populations in surface-attached microbial communities, with consequences for governing community-level properties. These insights provide tangible clues for the engineering of synthetic microbial systems that perform highly in spatially structured environments.

IMPORTANCE When growing on surfaces, multispecies microbial communities form biofilms that exhibit intriguing spatial patterns. These patterns can significantly affect the overall properties of the community, enabling otherwise impermissible metabolic functions to occur as well as driving the evolutionary and ecological processes acting on communities. The development of these patterns is affected by several drivers, including cell-cell interactions, nutrient levels, density of founding cells, and surface properties. The type IV pilus is commonly found to mediate surface-associated behaviors of microorganisms, but its role on pattern formation within microbial communities is unclear. Here, we report that in a cross-feeding consortium, the type IV pilus affects the spatial intermixing of interacting populations involved in pattern formation and ultimately influences overall community productivity and robustness. This novel insight assists our understanding of the ecological processes of surface-attached microbial communities and suggests a potential strategy for engineering high-performance synthetic microbial communities.

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.

McComedy: A user-friendly tool for next-generation individual-based modeling of microbial consumer-resource systems

Individual-based modeling is widely applied to investigate the ecological mechanisms driving microbial community dynamics. In such models, the population or community dynamics emerge from the behavior and interplay of individual entities, which are simulated according to a predefined set of rules. If the rules that govern the behavior of individuals are based on generic and mechanistically sound principles, the models are referred to as next-generation individual-based models. These models perform particularly well in recapitulating actual ecological dynamics. However, implementation of such models is time-consuming and requires proficiency in programming or in using specific software, which likely hinders a broader application of this powerful method. Here we present McComedy, a modeling tool designed to facilitate the development of next-generation individual-based models of microbial consumer-resource systems. This tool allows flexibly combining pre-implemented building blocks that represent physical and biological processes. The ability of McComedy to capture the essential dynamics of microbial consumer-resource systems is demonstrated by reproducing and furthermore adding to the results of two distinct studies from the literature. With this article, we provide a versatile tool for developing next-generation individual-based models that can foster understanding of microbial ecology in both research and education.

Microorganisms such as bacteria and fungi can be found in virtually any natural environment. To better understand the ecology of these microorganisms–which is important for several research fields including medicine, biotechnology, and conservation biology–researchers often use computer models to simulate and predict the behavior of microbial communities. Commonly, a particular technique called individual-based modeling is used to generate structurally realistic models of these communities by explicitly simulating each individual microorganism. Here we developed a tool called McComedy that helps researchers applying individual-based modeling efficiently without having to program low-level processes, thus allowing them to focus on their actual research questions. To test whether McComedy is not only convenient to use but also generates meaningful models, we used it to reproduce previously reported findings of two other research groups. Given that our results could well recapitulate and furthermore extend the original findings, we are confident that McComedy is a powerful and versatile tool that can help to address fundamental questions in microbial ecology.

Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities

Microbial communities often perform important functions that depend on inter-species interactions. To improve community function via artificial selection, one can repeatedly grow many communities to allow mutations to arise, and "reproduce" the highest-functioning communities by partitioning each into multiple offspring communities for the next cycle. Since improvement is often unimpressive in experiments, we study how to design effective selection strategies in silico. Specifically, we simulate community selection to improve a function that requires two species. With a "community function landscape", we visualize how community function depends on species and genotype compositions. Due to ecological interactions that promote species coexistence, the evolutionary trajectory of communities is restricted to a path on the landscape. This restriction can generate counter-intuitive evolutionary dynamics, prevent the attainment of maximal function, and importantly, hinder selection by trapping communities in locations of low community function heritability. We devise experimentally-implementable manipulations to shift the path to higher heritability, which speeds up community function improvement even when landscapes are high dimensional or unknown. Video walkthroughs: https://go.nature.com/3GWwS6j ; https://online.kitp.ucsb.edu/online/ecoevo21/shou2/ .

Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress

Antibiotic resistance in microbial communities reflects a combination of processes operating at different scales. In this work, we investigate the spatiotemporal dynamics of bacterial colonies comprised of drug-resistant and drug-sensitive cells undergoing range expansion under antibiotic stress. Using the opportunistic pathogen Enterococcus faecalis with plasmid-encoded β-lactamase, we track colony expansion dynamics and visualize spatial patterns in fluorescently labeled populations exposed to antibiotics. We find that the radial expansion rate of mixed communities is approximately constant over a wide range of drug concentrations and initial population compositions. Imaging of the final populations shows that resistance to ampicillin is cooperative, with sensitive cells surviving in the presence of resistant cells at otherwise lethal concentrations. The populations exhibit a diverse range of spatial segregation patterns that depend on drug concentration and initial conditions. Mathematical models indicate that the observed dynamics are consistent with global cooperation, despite the fact that β-lactamase remains cell-associated. Experiments confirm that resistant colonies provide a protective effect to sensitive cells on length scales multiple times the size of a single colony, and populations seeded with (on average) no more than a single resistant cell can produce mixed communities in the presence of the drug. While biophysical models of drug degradation suggest that individual resistant cells offer only short-range protection to neighboring cells, we show that long-range protection may arise from synergistic effects of multiple resistant cells, providing surprisingly large protection zones even at small population fractions.

Optogenetic Tools for Control of Public Goods in Saccharomyces cerevisiae

Microorganisms live in dense and diverse communities, with interactions between cells guiding community development and phenotype. The ability to perturb specific intercellular interactions in space and time provides a powerful route to determining the critical interactions and design rules for microbial communities. Approaches using optogenetic tools to modulate these interactions offer promise, as light can be exquisitely controlled in space and time. We report new plasmids for rapid integration of an optogenetic system into Saccharomyces cerevisiae to engineer light control of expression of a gene of interest. In a proof-of-principle study, we demonstrate the ability to control a model cooperative interaction, namely, the expression of the enzyme invertase (SUC2) which allows S. cerevisiae to hydrolyze sucrose and utilize it as a carbon source. We demonstrate that the strength of this cooperative interaction can be tuned in space and time by modulating light intensity and through spatial control of illumination. Spatial control of light allows cooperators and cheaters to be spatially segregated, and we show that the interplay between cooperative and inhibitory interactions in space can lead to pattern formation. Our strategy can be applied to achieve spatiotemporal control of expression of a gene of interest in S. cerevisiae to perturb both intercellular and interspecies interactions.

IMPORTANCE Recent advances in microbial ecology have highlighted the importance of intercellular interactions in controlling the development, composition, and resilience of microbial communities. In order to better understand the role of these interactions in governing community development, it is critical to be able to alter them in a controlled manner. Optogenetically controlled interactions offer advantages over static perturbations or chemically controlled interactions, as light can be manipulated in space and time and does not require the addition of nutrients or antibiotics. Here, we report a system for rapidly achieving light control of a gene of interest in the important model organism Saccharomyces cerevisiae and demonstrate that by controlling expression of the enzyme invertase, we can control cooperative interactions. This approach will be useful for understanding intercellular and interspecies interactions in natural and synthetic microbial consortia containing S. cerevisiae and serves as a proof of principle for implementing this approach in other consortia.

Adaptive laboratory evolution of microbial co-cultures for improved metabolite secretion

Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness-costly metabolites through natural selection. In this strategy, metabolic cross-feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co-evolved wild-type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B-group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.

Causes and consequences of pattern diversification in a spatially self-organizing microbial community

Surface-attached microbial communities constitute a vast amount of life on our planet. They contribute to all major biogeochemical cycles, provide essential services to our society and environment, and have important effects on human health and disease. They typically consist of different interacting genotypes that arrange themselves non-randomly across space (referred to hereafter as spatial self-organization). While spatial self-organization is important for the functioning, ecology, and evolution of these communities, the underlying determinants of spatial self-organization remain unclear. Here, we performed a combination of experiments, statistical modeling, and mathematical simulations with a synthetic cross-feeding microbial community consisting of two isogenic strains. We found that two different patterns of spatial self-organization emerged at the same length and time scales, thus demonstrating pattern diversification. This pattern diversification was not caused by initial environmental heterogeneity or by genetic heterogeneity within populations. Instead, it was caused by nongenetic heterogeneity within populations, and we provide evidence that the source of this nongenetic heterogeneity is local differences in the initial spatial positionings of individuals. We further demonstrate that the different patterns exhibit different community-level properties; namely, they have different expansion speeds. Together, our results demonstrate that pattern diversification can emerge in the absence of initial environmental heterogeneity or genetic heterogeneity within populations and can affect community-level properties, thus providing novel insights into the causes and consequences of microbial spatial self-organization.

The spatial organization of microbial communities during range expansion

Microbes in nature often live in dense and diverse communities exhibiting a variety of spatial structures. Microbial range expansion is a universal ecological process that enables populations to form spatial patterns. It can be driven by both passive and active processes, for example, mechanical forces from cell growth and bacterial motility. In this review, we provide a taste of recent creative and sophisticated efforts being made to address basic questions in spatial ecology and pattern formation during range expansion. We especially highlight the role of motility to shape community structures, and discuss the research challenges and future directions.

Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities

The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood.

Microbial communities play a key role in biogeochemical cycles, bioremediation, and human health. In crowded microbial systems such as biofilms and cellular aggregates, the close proximity between individual cells reduces the free space for the nutrients diffusion. To model the heterogeneous nature of these microbial systems, we developed CROMICS, a framework that integrates the information about the metabolic capabilities of each individual cell as well as the size and location of cells and macromolecules in the medium. The interactions among the individuals arise naturally through competition for or the exchange of metabolites. We show how the presence of mutants and a reduced diffusion in crowded environments can perturb the local availability of nutrients and therefore modify the dynamics of a microbial community. The discovered mechanisms underlying the microbial interactions in crowded systems together with the developed framework represent a valuable starting point for future studies of the interplay of human microbiome and host metabolism, the pathogen invasion, and the evaluation of antibiotic effectiveness.

Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism

Microbial communities are of considerable significance for biogeochemical processes, for the health of both animals and plants, and for biotechnological purposes. A key feature of microbial interactions is the exchange of nutrients between cells. Isotope labelling followed by analysis with secondary ion mass spectrometry (SIMS) can identify nutrient fluxes and heterogeneity of substrate utilisation on a single cell level. Here we present a novel approach that combines SIMS experiments with mechanistic modelling to reveal otherwise inaccessible nutrient kinetics. The method is applied to study the onset of a synthetic mutualistic partnership between a vitamin B₁₂-dependent mutant of the alga Chlamydomonas reinhardtii and the B₁₂-producing, heterotrophic bacterium Mesorhizobium japonicum, which is supported by algal photosynthesis. Results suggest that an initial pool of fixed carbon delays the onset of mutualistic cross-feeding; significantly, our approach allows the first quantification of this expected delay. Our method is widely applicable to other microbial systems, and will contribute to furthering a mechanistic understanding of microbial interactions.

Selfishness driving reductive evolution shapes interdependent patterns in spatially structured microbial communities

Microbes release a wide variety of metabolites to the environment that benefit the whole population, called public goods. Public goods sharing drives adaptive function loss, and allows the rise of metabolic cross-feeding. However, how public goods sharing governs the succession of communities over evolutionary time scales remains unclear. To resolve this issue, we constructed an individual-based model, where an autonomous population that possessed functions to produce three essential public goods, was allowed to randomly lose functions. Simulations revealed that function loss genotypes could evolve from the autonomous ancestor, driven by the selfish public production trade-off at the individual level. These genotypes could then automatically develop to three possible types of interdependent patterns: complete functional division, one-way dependency, and asymmetric functional complementation, which were influenced by function cost and function redundancy. In addition, we found random evolutionary events, i.e., the priority and the relative spatial positioning of genotype emergence, are also important in governing community assembly. Moreover, communities occupied by interdependent patterns exhibited better resistance to environmental perturbation, suggesting such patterns are selectively favored. Our work integrates ecological interactions with evolution dynamics, providing a new perspective to explain how reductive evolution shapes microbial interdependencies and governs the succession of communities.

Harnessing pluripotent stem cells as models to decipher human evolution

The study of human evolution, long constrained by a lack of experimental model systems, has been transformed by the emergence of the induced pluripotent stem cell (iPSC) field. iPSCs can be readily established from noninvasive tissue sources, from both humans and other primates; they can be maintained in the laboratory indefinitely, and they can be differentiated into other tissue types. These qualities mean that iPSCs are rapidly becoming established as viable and powerful model systems with which it is possible to address questions in human evolution that were until now logistically and ethically intractable, especially in the quest to understand humans' place among the great apes, and the genetic basis of human uniqueness. In this review, we discuss the key lessons and takeaways of this nascent field; from the types of research, iPSCs make possible to lingering challenges and likely future directions. We provide a comprehensive overview of how the seemingly unlikely combination of iPSCs and explicit evolutionary frameworks is transforming what is possible in our understanding of humanity's past and present.

Nutrient complexity triggers transitions between solitary and colonial growth in bacterial populations

Microbial populations often experience fluctuations in nutrient complexity in their natural environment such as between high molecular weight polysaccharides and simple monosaccharides. However, it is unclear if cells can adopt growth behaviors that allow individuals to optimally respond to differences in nutrient complexity. Here, we directly control nutrient complexity and use quantitative single-cell analysis to study the growth dynamics of individuals within populations of the aquatic bacterium Caulobacter crescentus. We show that cells form clonal microcolonies when growing on the polysaccharide xylan, which is abundant in nature and degraded using extracellular cell-linked enzymes; and disperse to solitary growth modes when the corresponding monosaccharide xylose becomes available or nutrients are exhausted. We find that the cellular density required to achieve maximal growth rates is four-fold higher on xylan than on xylose, indicating that aggregating is advantageous on polysaccharides. When collectives on xylan are transitioned to xylose, cells start dispersing, indicating that colony formation is no longer beneficial and solitary behaviors might serve to reduce intercellular competition. Our study demonstrates that cells can dynamically tune their behaviors when nutrient complexity fluctuates, elucidates the quantitative advantages of distinct growth behaviors for individual cells and indicates why collective growth modes are prevalent in microbial populations.

Extracellular Metabolism Sets the Table for Microbial Cross-Feeding

The transfer of nutrients between cells, or cross-feeding, is a ubiquitous feature of microbial communities with emergent properties that influence our health and orchestrate global biogeochemical cycles. Cross-feeding inevitably involves the externalization of molecules. Some of these molecules directly serve as cross-fed nutrients, while others can facilitate cross-feeding. Altogether, externalized molecules that promote cross-feeding are diverse in structure, ranging from small molecules to macromolecules. The functions of these molecules are equally diverse, encompassing waste products, enzymes, toxins, signaling molecules, biofilm components, and nutrients of high value to most microbes, including the producer cell. As diverse as the externalized and transferred molecules are the cross-feeding relationships that can be derived from them. Many cross-feeding relationships can be summarized as cooperative but are also subject to exploitation. Even those relationships that appear to be cooperative exhibit some level of competition between partners. In this review, we summarize the major types of actively secreted, passively excreted, and directly transferred molecules that either form the basis of cross-feeding relationships or facilitate them. Drawing on examples from both natural and synthetic communities, we explore how the interplay between microbial physiology, environmental parameters, and the diverse functional attributes of extracellular molecules can influence cross-feeding dynamics. Though microbial cross-feeding interactions represent a burgeoning field of interest, we may have only begun to scratch the surface.

Cooperation of partially-transformed clones: an invisible force behind the early stages of carcinogenesis

1Most tumours exhibit significant heterogeneity and are best described as communities of cellular populations competing for resources. Growing experimental evidence also suggests, however, that cooperation between cancer clones is important as well for the maintenance of tumour heterogeneity and tumour progression. However, a role for cell communication during the earliest steps in oncogenesis is not well characterised despite its vital importance in normal tissue and clinically manifest tumours. Here, we present a simple analytical model and stochastic lattice-based simulations to study how the interaction between the mutational process and cell-to-cell communication in three-dimensional tissue architecture might contribute to shape early oncogenesis. We show that non-cell-autonomous mechanisms of carcinogenesis could support and accelerate pre-cancerous clonal expansion through the cooperation of different, non- or partially- transformed mutants. We predict the existence of a 'cell-autonomous time-horizon', a time before which cooperation between cell-to-cell communication and DNA mutations might be one of the most fundamental forces shaping the early stages of oncogenesis. The understanding of this process could shed new light on the mechanisms leading to clinically manifest cancers.

Droplet printing reveals the importance of micron-scale structure for bacterial ecology

Bacteria often live in diverse communities where the spatial arrangement of strains and species is considered critical for their ecology. However, a test of this hypothesis requires manipulation at the fine scales at which spatial structure naturally occurs. Here we develop a droplet-based printing method to arrange bacterial genotypes across a sub-millimetre array. We print strains of the gut bacterium Escherichia coli that naturally compete with one another using protein toxins. Our experiments reveal that toxin-producing strains largely eliminate susceptible non-producers when genotypes are well-mixed. However, printing strains side-by-side creates an ecological refuge where susceptible strains can persist in large numbers. Moving to competitions between toxin producers reveals that spatial structure can make the difference between one strain winning and mutual destruction. Finally, we print different potential barriers between competing strains to understand how ecological refuges form, which shows that cells closest to a toxin producer mop up the toxin and protect their clonemates. Our work provides a method to generate customised bacterial communities with defined spatial distributions, and reveals that micron-scale changes in these distributions can drive major shifts in ecology.

The spatial arrangement of bacterial strains and species within microbial communities is considered crucial for their ecology. Here, Krishna Kumar et al. use a droplet-based printing method to arrange different bacterial genotypes across a sub-millimetre array, and show that micron-scale changes in spatial distributions can drive major shifts in ecology.

Pleiotropic mutations can rapidly evolve to directly benefit self and cooperative partner despite unfavorable conditions

Cooperation, paying a cost to benefit others, is widespread. Cooperation can be promoted by pleiotropic ‘win-win’ mutations which directly benefit self (self-serving) and partner (partner-serving). Previously, we showed that partner-serving should be defined as increased benefit supply rate per intake benefit. Here, we report that win-win mutations can rapidly evolve even under conditions unfavorable for cooperation. Specifically, in a well-mixed environment we evolved engineered yeast cooperative communities where two strains exchanged costly metabolites, lysine and hypoxanthine. Among cells that consumed lysine and released hypoxanthine, ecm21 mutations repeatedly arose. ecm21 is self-serving, improving self’s growth rate in limiting lysine. ecm21 is also partner-serving, increasing hypoxanthine release rate per lysine consumption and the steady state growth rate of partner and of community. ecm21 also arose in monocultures evolving in lysine-limited chemostats. Thus, even without any history of cooperation or pressure to maintain cooperation, pleiotropic win-win mutations may readily evolve to promote cooperation.

Accumulation of dead cells from contact killing facilitates coexistence in bacterial biofilms

Bacterial communities are governed by a wide variety of social interactions, some of which are antagonistic with potential significance for bacterial warfare. Several antagonistic mechanisms, such as killing via the type VI secretion system (T6SS), require killer cells to directly contact target cells. The T6SS is hypothesized to be a highly potent weapon, capable of facilitating the invasion and defence of bacterial populations. However, we find that the efficacy of contact killing is severely limited by the material consequences of cell death. Through experiments with Vibrio cholerae strains that kill via the T6SS, we show that dead cell debris quickly accumulates at the interface that forms between competing strains, preventing physical contact and thus preventing killing. While previous experiments have shown that T6SS killing can reduce a population of target cells by as much as 106-fold, we find that, as a result of the formation of dead cell debris barriers, the impact of contact killing depends sensitively on the initial concentration of killer cells. Killer cells are incapable of invading or eliminating competitors on a community level. Instead, bacterial warfare itself can facilitate coexistence between nominally antagonistic strains. While a variety of defensive strategies against microbial warfare exist, the material consequences of cell death provide target cells with their first line of defence.

Computation in bacterial communities

Bacteria across many scales are involved in a dynamic process of information exchange to coordinate activity and community structure within large and diverse populations. The molecular components bacteria use to communicate have been discovered and characterized, and recent efforts have begun to understand the potential for bacterial signal exchange to gather information from the environment and coordinate collective behaviors. Such computations made by bacteria to coordinate the action of a population of cells in response to information gathered by a multitude of inputs is a form of collective intelligence. These computations must be robust to fluctuations in both biological, chemical, and physical parameters as well as to operate with energetic efficiency. Given these constraints, what are the limits of computation by bacterial populations and what strategies have evolved to ensure bacterial communities efficiently work together? Here the current understanding of information exchange and collective decision making that occur in microbial populations will be reviewed. Looking toward the future, we consider how a deeper understanding of bacterial computation will inform future direction in microbiology, biotechnology, and biophysics.

Reciprocal Fitness Feedbacks Promote the Evolution of Mutualistic Cooperation

Mutually beneficial interactions are ubiquitous in nature and have played a pivotal role for the evolution of life on earth. However, the factors facilitating their emergence remain poorly understood. Here, we address this issue both experimentally and by mathematical modeling using cocultures of auxotrophic strains of Escherichia coli, whose growth depends on a reciprocal exchange of amino acids. Coevolving auxotrophic pairs in a spatially heterogeneous environment for less than 150 generations transformed the initial interaction that was merely based on an exchange of metabolic byproducts into a costly metabolic cooperation, in which both partners increased the amounts of metabolites they produced to benefit their corresponding partner. The observed changes were afforded by the formation of multicellular clusters, within which increased cooperative investments were favored by positive fitness feedbacks among interacting genotypes. Under these conditions, non-cooperative individuals were less fit than cooperative mutants. Together, our results highlight the ease with which mutualistic cooperation can evolve, suggesting similar mechanisms likely operate in natural communities. VIDEO ABSTRACT.

Aspects of Multicellularity in Saccharomyces cerevisiae Yeast: A Review of Evolutionary and Physiological Mechanisms

The evolutionary transition from single-celled to multicellular growth is a classic and intriguing problem in biology. Saccharomyces cerevisiae is a useful model to study questions regarding cell aggregation, heterogeneity and cooperation. In this review, we discuss scenarios of group formation and how this promotes facultative multicellularity in S. cerevisiae. We first describe proximate mechanisms leading to aggregation. These mechanisms include staying together and coming together, and can lead to group heterogeneity. Heterogeneity is promoted by nutrient limitation, structured environments and aging. We then characterize the evolutionary benefits and costs of facultative multicellularity in yeast. We summarize current knowledge and focus on the newest state-of-the-art discoveries that will fuel future research programmes aiming to understand facultative microbial multicellularity.

Expansion, Exploitation and Extinction: Niche Construction in Ephemeral Landscapes

We aim to understand general consequences of niche construction on metapopulation dynamics in ephemeral landscapes. To this effect, a contact process-like stochastic spatial model is introduced where local populations colonize and go extinct on a dynamic landscape of habitable and destroyed patches. In contrast to previous models, where the extinction threshold is a consequence of available niche rendered by global rates of patch destruction/renewal, here we investigate how the metapopulation persists when they are the sole generators of their own niche. Niche construction is full-filled by localized populations through the transformation of destroyed patches in their neighborhood to viable habitat for future colonization. With this theoretical framework we are able to address the dual nature of niche construction by investigating the ephemerality of the landscape (destruction rate) and the continuum of population level strategies, where construction comes at a cost to colonization. Using mean field theory and Monte Carlo simulations of the model, we are able to quantify optimal population level strategies in a wide range of ephemeral landscapes. Interestingly, we observe qualitative differences at the extinction threshold between analytic and numeric results. Investigating this discrepancy further, we find that increasing niche construction neighborhood in the spatial model leads to two interrelated effects i) an increased rate in range expansion ii) a loss in resiliency and return of the discontinuous transition at the extinction threshold. Furthermore, in the discontinuous regime of the model, spatial clustering prior to a critical transition disappears. This is a significant finding as spatial clustering has been considered to be an early warning signal before ecosystems reach their 'tipping point'. In addition to maintaining stability, we find local niche construction strategies have an advantage when in scramble competition with an exploiter strategy because of their ability to monopolize the constructed niche due to spatial adjacency. As the niche construction neighborhood expands this advantage disappears and the exploiter strategy out-competes the niche constructor. In some cases the exploiter pushes the niche constructor to extinction, thus a tragedy of the commons ensues leading to 'ecological suicide' and a collapse of the niche.

ROS-associated immune response and metabolism: a mechanistic approach with implication of various diseases

The immune system plays a pivotal role in maintaining the defense mechanism against external agents and also internal danger signals. Metabolic programming of immune cells is required for functioning of different subsets of immune cells under different physiological conditions. The field of immunometabolism has gained ground because of its immense importance in coordination and balance of immune responses. Metabolism is very much related with production of energy and certain by-products. Reactive oxygen species (ROS) are generated as one of the by-products of various metabolic pathways. The amount, localization of ROS and redox status determine transcription of genes, and also influences the metabolism of immune cells. This review discusses ROS, metabolism of immune cells at different cellular conditions and sheds some light on how ROS might regulate immunometabolism.

Cheaters shape the evolution of phenotypic heterogeneity in Bacillus subtilis biofilms

Biofilms are closely packed cells held and shielded by extracellular matrix composed of structural proteins and exopolysaccharides (EPS). As matrix components are costly to produce and shared within the population, EPS-deficient cells can act as cheaters by gaining benefits from the cooperative nature of EPS producers. Remarkably, genetically programmed EPS producers can also exhibit phenotypic heterogeneity at single-cell level. Previous studies have shown that spatial structure of biofilms limits the spread of cheaters, but the long-term influence of cheating on biofilm evolution is not well understood. Here, we examine the influence of EPS nonproducers on evolution of matrix production within the populations of EPS producers in a model biofilm-forming bacterium, Bacillus subtilis. We discovered that general adaptation to biofilm lifestyle leads to an increase in phenotypical heterogeneity of eps expression. However, prolonged exposure to EPS-deficient cheaters may result in different adaptive strategy, where eps expression increases uniformly within the population. We propose a molecular mechanism behind such adaptive strategy and demonstrate how it can benefit the EPS producers in the presence of cheaters. This study provides additional insights on how biofilms adapt and respond to stress caused by exploitation in long-term scenario.

Interaction-dependent effects of surface structure on microbial spatial self-organization

Surface-attached microbial communities consist of different cell types that, at least to some degree, organize themselves non-randomly across space (referred to as spatial self-organization). While spatial self-organization can have important effects on the functioning, ecology and evolution of communities, the underlying determinants of spatial self-organization remain unclear. Here, we hypothesize that the presence of physical objects across a surface can have important effects on spatial self-organization. Using pairs of isogenic strains of Pseudomonas stutzeri, we performed range expansion experiments in the absence or presence of physical objects and quantified the effects on spatial self-organization. We demonstrate that physical objects create local deformities along the expansion frontier, and these deformities increase in magnitude during range expansion. The deformities affect the densities of interspecific boundaries and diversity along the expansion frontier, and thus affect spatial self-organization, but the effects are interaction-dependent. For competitive interactions that promote sectorized patterns of spatial self-organization, physical objects increase the density of interspecific boundaries and diversity. By contrast, for cross-feeding interactions that promote dendritic patterns, they decrease the density of interspecific boundaries and diversity. These qualitatively different outcomes are probably caused by fundamental differences in the orientations of the interspecific boundaries. Thus, in order to predict the effects of physical objects on spatial self-organization, information is needed regarding the interactions present within a community and the general geometric shapes of spatial self-organization that emerge from those interactions. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.