Bottom-Up Approaches to Synthetic Cooperation in Microbial Communities

Dispersal shapes compositional and functional diversity in aquatic microbial communities

Segregation and mixing shape the structure and functioning of aquatic microbial communities, but their respective roles are challenging to disentangle in field studies. We explored the hypothesis that functional differences and beta diversity among stochastically assembled communities would increase in the absence of dispersal. Contrariwise, we expected biotic selection during homogenizing dispersal to reduce beta and gamma diversity as well as functional variability. This was experimentally addressed by examining the compositional and functional changes of 20 freshwater bacterial assemblages maintained at identical conditions over seven growth cycles for 34 days and subjected to two consecutive dispersal regimes. Initial dispersal limitation generated high beta diversity and led to the repeated emergence of community types that were dominated by particular taxa. Compositional stability and evenness of the community types varied over successive growth cycles, reflecting differences in functional properties. Carbon use efficiency increased during cultivation, with some communities of unique composition outperforming the replicate community types. Homogenizing dispersal led to high compositional similarity and reduced gamma diversity. While a neutral and a competition-based (Elo-rating) model together largely explained community assembly, a pseudomonad disproportionally dominated across communities, possibly due to interaction-related genomic traits. In conclusion, microbial assemblages stochastically generated by dispersal limitation can be gradually "refined" into distinct community types by subsequent deterministic processes. Segregation of communities represented an insurance mechanism for highly productive but competitively weak microbial taxa that were excluded during community coalescence.

IMPORTANCE

We experimentally assessed the compositional and functional responses of freshwater bacterial assemblages exposed to two consecutive dispersal-related events (dispersal limitation and homogenizing dispersal) under identical growth conditions. While segregation led to a decreased local diversity, high beta diversity sustained regional diversity and functional variability. In contrast, homogenizing dispersal reduced the species pool and functional variability of the metacommunity. Our findings highlight the role of dispersal in regulating both diversity and functional variability of aquatic microbial metacommunities, thereby providing crucial insight to predict changes in ecosystem functioning.

Deciphering and designing microbial communities by genome-scale metabolic modelling

Microbial communities are shaped by the complex interactions among organisms and the environment. Genome-scale metabolic models (GEMs) can provide deeper insights into the complexity and ecological properties of various microbial communities, revealing their intricate interactions. Many researchers have modified GEMs for the microbial communities based on specific needs. Thus, GEMs need to be comprehensively summarized to better understand the trends in their development. In this review, we summarized the key developments in deciphering and designing microbial communities using different GEMs. A timeline of selected highlights in GEMs indicated that this area is evolving from the single-strain level to the microbial community level. Then, we outlined a framework for constructing GEMs of microbial communities. We also summarized the models and resources of static and dynamic community-level GEMs. We focused on the role of external environmental and intracellular resources in shaping the assembly of microbial communities. Finally, we discussed the key challenges and future directions of GEMs, focusing on the integration of GEMs with quorum sensing mechanisms, microbial ecology interactions, machine learning algorithms, and automatic modeling, all of which contribute to consortia-based applications in different fields.

Re-vitalizing wastewater: Nutrient recovery and carbon capture through microbe-algae synergy using omics-biology

Increasing amounts of wastewater is the most pervasive and challenging environmental problem globally. Conventional treatment methods are costly and entail huge energy, carbon consumption and greenhouse gas emissions. Owing to their unique ability of carbon capturing and resource recovery, microalgae-microbiome based treatment is a potential approach and is widely used for carbon-neutral wastewater treatment. Microalgae-bacteria synergy (i.e., the functionally beneficial microbial synthetic communities) performs better and enhances carbon-sequestration and nutrient recovery from wastewater treatment plants. This review presents a comprehensive information regarding the potential of microalgae-microbiome as a sustainable agent for wastewater and discusses synergistic approaches for effective nutrient removal. Moreover, this review discusses, the role of omics-biology and Insilco approaches in unravelling and understanding the algae-microbe synergism and their response toward wastewater treatment. Finally, it discusses various microbiome engineering approaches for developing the effective microalgae-bacteria partners for carbon sequestration and nutrient recovery from wastewater, and summarizes future research perspectives on microalgae-microbiome based bioremediation.

Inferring bacterial interspecific interactions from microcolony growth expansion

Bacterial species interactions significantly shape growth and behavior in communities, determining the emergence of community functions. Typically, these interactions are studied through bulk population measurements, overlooking the role of cell-to-cell variability and spatial context. This study uses real-time surface growth measurements of thousands of sparsely positioned microcolonies to investigate interactions and kinetic variations in monocultures and cocultures of Pseudomonas putida and P. veronii under substrate competition (succinate) or substrate independence (d-mannitol and putrescine). In monoculture, microcolonies exhibited expected substrate-dependent expansion rates, but individual colony sizes were affected by founder cell density, spatial positioning, growth rates, and lag times. In coculture, substrate competition favored P. putida, but unexpectedly, reduced the maximum growth rates of both species. In contrast, 10% of P. veronii microcolonies under competition grew larger than expected, likely due to founder cell phenotypic variation and stochastic spatial positioning. These effects were alleviated under substrate independence. A linear relationship between founder cell ratios and final colony area ratios in local neighborhoods (6.5-65 µm radius) was observed in coculture, with its slope reflecting interaction type and strength. Measured slopes in the P. putida to P. veronii biomass ratio under competition were one-third reduced compared to kinetic predictions using a cell-agent growth model, which exometabolite analysis and simulations suggested may be due to metabolite cross-feeding or inhibitory compound production. This indicates additional factors beyond inherent monoculture growth kinetics driving spatial interactions. Overall, the study demonstrates how microcolony growth experiments offer valuable insights into bacterial interactions, from local to community-level dynamics.

Synthetic microbial communities: A gateway to understanding resistance, resilience, and functionality in spontaneously fermented food microbiomes

This review delves into the intricate traits of microbial communities encountered in spontaneously fermented foods (SFF), contributing to resistance, resilience, and functionality drivers. Traits of SFF microbiomes comprise of fluctuations in community composition, genetic stability, and condition-specific phenotypes. Synthetic microbial communities (SMCs) serve as a portal for mechanistic insights and strategic re-programming of microbial communities. Current literature underscores the pivotal role of microbiomes in SFF in shaping quality attributes and preserving the cultural heritage of their origin. In contrast to starter driven fermentations that tend to be more controlled but lacking the capacity to maintain or reproduce the complex flavors and intricacies found in SFF. SMCs, therefore, become indispensable tools, providing a nuanced understanding and control over fermented food microbiomes. They empower the prediction and engineering of microbial interactions and metabolic pathways with the aim of optimizing outcomes in food processing. Summarizing the current application of SMCs in fermented foods, there is still space for improvement. Challenges in achieving stability and reproducibility in SMCs are identified, stemming from non-standardized approaches. The future direction should involve embracing standardized protocols, advanced monitoring tools, and synthetic biology applications. A holistic, multi-disciplinary approach is paramount to unleashing the full potential of SMCs and fostering sustainable and innovative applications in fermented food systems.

Exploring di (2-ethylhexyl) phthalate degradation by a synthetic marine bacterial consortium: Genomic insights, pathway and interaction prediction, and application in sediment microcosms

Di (2-ethylhexyl) phthalate (DEHP), a toxic phthalate ester (PAE) plasticizer, is often detected in marine sediment and biota. Our understanding of DEHP-degrading marine bacteria and the associated genetic mechanisms is limited. This study established a synthetic bacterial consortium (A02) consisting of three marine bacteria (OR05, OR16, and OR21). Consortium A02 outperformed the individual strains in DEHP degradation. Investigations into the degradation of DEHP intermediates revealed that OR05 and OR16 likely contributed to enhanced DEHP degradation by Consortium A02 via the utilization of DEHP intermediates, such as protocatechuic acid and mono (ethylhexyl) phthalate, with OR21 as the key DEHP degrader. A pathway of DEHP degradation by Consortium A02 was predicted based on genome analysis and experimental degradation. Bioaugmentation with Consortium A02 led to 80% DEHP degradation in 26 days in saline sediment (100 mg/kg), surpassing the 53% degradation by indigenous microbes, indicating the potential of A02 for treating DEHP-contaminated sediments. Meanwhile, bioaugmentation notably changed the bacterial community, with the exclusive presence of certain bacterial genera in the A02 bioaugmented microcosms, and was predicted to result in a more dynamic and active sediment bacterial community. This study contributes to the limited literature on DEHP degradation by marine bacteria and their associated genes.

Microbial community interactions determine the mineralization of soil organic phosphorus in subtropical forest ecosystems

In subtropical forest ecosystems with few phosphorus (P) inputs, P availability and forest productivity depend on soil organic P (Po) mineralization. However, the mechanisms by which the microbial community determines the status and fate of soil Po mineralization remain unclear. In the present study, soils were collected from three typical forest types: secondary natural forest (SNF), mixed planting, and monoculture forest of Chinese fir. The P fractions, Po-mineralization ability, and microbial community in the soils of different forest types were characterized. In addition, we defined Po-mineralizing taxa with the potential to interact with the soil microbial community to regulate Po mineralization. We found that a higher labile P content persisted in SNF and was positively associated with the Po-mineralization capacity of the soil microbial community. In vitro cultures of soil suspensions revealed that soil Po mineralization of three forest types was distinguished by differences in the composition of fungal communities. We further identified broad phylogenetic lineages of Po-mineralizing fungi with a high intensity of positive interactions with the soil microbial community, implying that the facilitation of Po-mineralizing taxa is crucial for soil P availability. Our dilution experiments to weaken microbial interactions revealed that in SNF soil, which had the highest interaction intensity of Po-mineralizing taxa with the community, Po-mineralization capacity was irreversibly lost after dilution, highlighting the importance of microbial diversity protection in forest soils. In summary, this study demonstrates that the interactions of Po-mineralizing microorganisms with the soil microbial community are critical for P availability in subtropical forests.IMPORTANCEIn subtropical forest ecosystems with few phosphorus inputs, phosphorus availability and forest productivity depend on soil organic phosphorus mineralization. However, the mechanisms by which the microbial community interactions determine the mineralization of soil organic phosphorus remain unclear. In the present study, soils were collected from three typical forest types: secondary natural forest, mixed planting, and monoculture forest of Chinese fir. We found that a higher soil labile phosphorus content was positively associated with the organic phosphorus mineralization capacity of the soil microbial community. Soil organic phosphorus mineralization of three forest types was distinguished by the differences in the composition of fungal communities. The positive interactions between organic phosphorus-mineralizing fungi and the rest of the soil microbial community facilitated organic phosphorus mineralization. This study highlights the importance of microbial diversity protection in forest soils and reveals the microbial mechanism of phosphorus availability maintenance in subtropical forest ecosystems.

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.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Plant Growth-Promoting Bacteria of Soil: Designing of Consortia Beneficial for Crop Production

Plant growth-promoting bacteria are commonly used in agriculture, particularly for seed inoculation. Multispecies consortia are believed to be the most promising form of these bacteria. However, designing and modeling bacterial consortia to achieve desired phenotypic outcomes in plants is challenging. This review aims to address this challenge by exploring key antimicrobial interactions. Special attention is given to approaches for developing soil plant growth-promoting bacteria consortia. Additionally, advanced omics-based methods are analyzed that allow soil microbiomes to be characterized, providing an understanding of the molecular and functional aspects of these microbial communities. A comprehensive discussion explores the utilization of bacterial preparations in biofertilizers for agricultural applications, focusing on the intricate design of synthetic bacterial consortia with these preparations. Overall, the review provides valuable insights and strategies for intentionally designing bacterial consortia to enhance plant growth and development.

Environmental microbiome engineering for the mitigation of climate change

Environmental microbiome engineering is emerging as a potential avenue for climate change mitigation. In this process, microbial inocula are introduced to natural microbial communities to tune activities that regulate the long-term stabilization of carbon in ecosystems. In this review, we outline the process of environmental engineering and synthesize key considerations about ecosystem functions to target, means of sourcing microorganisms, strategies for designing microbial inocula, methods to deliver inocula, and the factors that enable inocula to establish within a resident community and modify an ecosystem function target. Recent work, enabled by high-throughput technologies and modeling approaches, indicate that microbial inocula designed from the top-down, particularly through directed evolution, may generally have a higher chance of establishing within existing microbial communities than other historical approaches to microbiome engineering. We address outstanding questions about the determinants of inocula establishment and provide suggestions for further research about the possibilities and challenges of environmental microbiome engineering as a tool to combat climate change.

Electrogenetic signaling and information propagation for controlling microbial consortia via programmed lysis

To probe signal propagation and genetic actuation in microbial consortia, we have coopted the components of both redox and quorum sensing (QS) signaling into a communication network for guiding composition by "programming" cell lysis. Here, we use an electrode to generate hydrogen peroxide as a redox cue that determines consortia composition. The oxidative stress regulon of Escherichia coli, OxyR, is employed to receive and transform this signal into a QS signal that coordinates the lysis of a subpopulation of cells. We examine a suite of information transfer modalities including "monoculture" and "transmitter-receiver" models, as well as a series of genetic circuits that introduce time-delays for altering information relay, thereby expanding design space. A simple mathematical model aids in developing communication schemes that accommodate the transient nature of redox signals and the "collective" attributes of QS signals. We suggest this platform methodology will be useful in understanding and controlling synthetic microbial consortia for a variety of applications, including biomanufacturing and biocontainment.

Low-abundance populations distinguish microbiome performance in plant cell wall deconstruction

BACKGROUND

Plant cell walls are interwoven structures recalcitrant to degradation. Native and adapted microbiomes can be particularly effective at plant cell wall deconstruction. Although most understanding of biological cell wall deconstruction has been obtained from isolates, cultivated microbiomes that break down cell walls have emerged as new sources for biotechnologically relevant microbes and enzymes. These microbiomes provide a unique resource to identify key interacting functional microbial groups and to guide the design of specialized synthetic microbial communities.

RESULTS

To establish a system assessing comparative microbiome performance, parallel microbiomes were cultivated on sorghum (Sorghum bicolor L. Moench) from compost inocula. Biomass loss and biochemical assays indicated that these microbiomes diverged in their ability to deconstruct biomass. Network reconstructions from gene expression dynamics identified key groups and potential interactions within the adapted sorghum-degrading communities, including Actinotalea, Filomicrobium, and Gemmatimonadetes populations. Functional analysis demonstrated that the microbiomes proceeded through successive stages that are linked to enzymes that deconstruct plant cell wall polymers. The combination of network and functional analysis highlighted the importance of cellulose-degrading Actinobacteria in differentiating the performance of these microbiomes.

CONCLUSIONS

The two-tier cultivation of compost-derived microbiomes on sorghum led to the establishment of microbiomes for which community structure and performance could be assessed. The work reinforces the observation that subtle differences in community composition and the genomic content of strains may lead to significant differences in community performance. Video Abstract.

Reconciling concepts of black queen and tragedy of the commons in simulated bulk soil and rhizosphere prokaryote communities

The Black Queen hypothesis describes the evolutionary strategy to lose costly functions in favour of improving growth efficiency. This results in mutants (cheaters) becoming obligately dependent upon a provider (black queen) to produce a necessary resource. Previous analyses demonstrate black queens and cheaters reach a state of equilibrium in pair-wise systems. However, in complex communities, accumulation of cheaters likely poses a serious burden on shared resources. This should result in a Tragedy of the Commons (ToC), whereby over-utilisation of public resources risks making them growth-limiting. With a collection of differential equations, microbial communities composed of twenty prokaryote ‘species’ either from rhizosphere, characterised by abundant carbon and energy sources, or bulk soil, with limited carbon and energy supply, were simulated. Functional trait groups differed based on combinations of cellulase and amino acid production, growth and resource uptake. Randomly generated communities were thus composed of species that acted as cellulolytic prototrophic black queens, groups that were either cellulolytic or prototrophic, or non-cellulolytic auxotrophic cheaters. Groups could evolve to lose functions over time. Biomass production and biodiversity were tracked in 8,000 Monte Carlo simulations over 500 generations. Bulk soil favoured oligotrophic co-operative communities where biodiversity was positively associated with growth. Rhizosphere favoured copiotrophic cheaters. The most successful functional group across both environments was neither black queens nor cheaters, but those that balanced providing an essential growth-limiting function at a relatively low maintenance cost. Accumulation of loss of function mutants in bulk soil risked resulting in loss of cumulative growth by ToC, while cumulative growth increased in the rhizosphere. In the bulk soil, oligotrophic adaptations assisted species in avoiding extinction. This demonstrated that loss of function by mutation is a successful evolutionary strategy in host-associated and/or resource-rich environments, but poses a risk to communities that must co-operate with each other for mutual co-existence. It was concluded that microbial communities must follow different evolutionary and community assembly strategies in bulk soil versus rhizosphere, with bulk soil communities more dependent on traits that promote co-operative interactions between microbial species.

Combating biotic stresses in plants by synthetic microbial communities: Principles, applications, and challenges

Presently, agriculture worldwide is facing the major challenge of feeding the increasing population sustainably. The conventional practices have not only failed to meet the projected needs, but also led to tremendous environmental consequences. Hence, to ensure a food-secure and environmentally sound future, the major thrust is on sustainable alternatives. Due to challenges associated with conventional means of application of biocontrol agents in the management of biotic stresses in agro-ecosystems, significant transformations in this context is needed. The crucial role played by soil microbiomes in efficiently and sustainably managing the agricultural production has unfolded a newer approach of rhizospheric engineering that shows immense promise in mitigating biotic stresses in an eco-friendly manner. The strategy of generating synthetic microbial communities (SynCom), by integrating omics approaches with traditional techniques of enumeration and in-depth analysis of plant-microbe interactions, is encouraging. The review discusses the significance of the rhizospheric microbiome in plant's fitness, and its manipulation for enhancing plant attributes. The focus of the review is to critically analyze the potential tools for the design and utilization of SynCom as a sustainable approach for rhizospheric engineering to ameliorate biotic stresses in plants. Further, based on the synthesis of reports in the area, we have put forth possible solutions to some of the critical issues that impair the large-scale application of SynComs in agriculture.

Ecological firewalls for synthetic biology

It has been recently suggested that engineered microbial strains could be used to protect ecosystems from undesirable tipping points and biodiversity loss. A major concern in this context is the potential unintended consequences, which are usually addressed in terms of designed genetic constructs aimed at controlling overproliferation. Here we present and discuss an alternative view grounded in the nonlinear attractor dynamics of some ecological network motifs. These ecological firewalls are designed to perform novel functionalities (such as plastic removal) while containment is achieved within the resident community. That could help provide a self-regulating biocontainment. In this way, engineered organisms have a limited spread while-when required-preventing their extinction. The basic synthetic designs and their dynamical behavior are presented, each one inspired in a given ecological class of interaction. Their possible applications are discussed and the broader connection with invasion ecology outlined.

Glutamic acid reshapes the plant microbiota to protect plants against pathogens

BACKGROUND

Plants in nature interact with other species, among which are mutualistic microorganisms that affect plant health. The co-existence of microbial symbionts with the host contributes to host fitness in a natural context. In turn, the composition of the plant microbiota responds to the environment and the state of the host, raising the possibility that it can be engineered to benefit the plant. However, technology for engineering the structure of the plant microbiome is not yet available.

RESULTS

The loss of diversity and reduction in population density of Streptomyces globisporus SP6C4, a core microbe, was observed coincident with the aging of strawberry plants. Here, we show that glutamic acid reshapes the plant microbial community and enriches populations of Streptomyces, a functional core microbe in the strawberry anthosphere. Similarly, in the tomato rhizosphere, treatment with glutamic acid increased the population sizes of Streptomyces as well as those of Bacillaceae and Burkholderiaceae. At the same time, diseases caused by species of Botrytis and Fusarium were significantly reduced in both habitats. We suggest that glutamic acid directly modulates the composition of the microbiome community.

CONCLUSIONS

Much is known about the structure of plant-associated microbial communities, but less is understood about how the community composition and complexity are controlled. Our results demonstrate that the intrinsic level of glutamic acid in planta is associated with the composition of the microbiota, which can be modulated by an external supply of a biostimulant. Video Abstract.

Microbial Systems Ecology to Understand Cross-Feeding in Microbiomes

Understanding how microorganism-microorganism interactions shape microbial assemblages is a key to deciphering the evolution of dependencies and co-existence in complex microbiomes. Metabolic dependencies in cross-feeding exist in microbial communities and can at least partially determine microbial community composition. To parry the complexity and experimental limitations caused by the large number of possible interactions, new concepts from systems biology aim to decipher how the components of a system interact with each other. The idea that cross-feeding does impact microbiome assemblages has developed both theoretically and empirically, following a systems biology framework applied to microbial communities, formalized as microbial systems ecology (MSE) and relying on integrated-omics data. This framework merges cellular and community scales and offers new avenues to untangle microbial coexistence primarily by metabolic modeling, one of the main approaches used for mechanistic studies. In this mini-review, we first give a concise explanation of microbial cross-feeding. We then discuss how MSE can enable progress in microbial research. Finally, we provide an overview of a MSE framework mostly based on genome-scale metabolic-network reconstruction that combines top-down and bottom-up approaches to assess the molecular mechanisms of deterministic processes of microbial community assembly that is particularly suitable for use in synthetic biology and microbiome engineering.

Would that it were so simple: Interactions between multiple traits undermine classical single-trait-based predictions of microbial community function and evolution

Understanding how microbial traits affect the evolution and functioning of microbial communities is fundamental for improving the management of harmful microorganisms, while promoting those that are beneficial. Decades of evolutionary ecology research has focused on examining microbial cooperation, diversity, productivity and virulence but with one crucial limitation. The traits under consideration, such as public good production and resistance to antibiotics or predation, are often assumed to act in isolation. Yet, in reality, multiple traits frequently interact, which can lead to unexpected and undesired outcomes for the health of macroorganisms and ecosystem functioning. This is because many predictions generated in a single-trait context aimed at promoting diversity, reducing virulence or controlling antibiotic resistance can fail for systems where multiple traits interact. Here, we provide a much needed discussion and synthesis of the most recent research to reveal the widespread and diverse nature of multi-trait interactions and their consequences for predicting and controlling microbial community dynamics. Importantly, we argue that synthetic microbial communities and multi-trait mathematical models are powerful tools for managing the beneficial and detrimental impacts of microbial communities, such that past mistakes, like those made regarding the stewardship of antimicrobials, are not repeated.

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.

Interspecies bacterial competition regulates community assembly in the C. elegans intestine

From insects to mammals, a large variety of animals hold in their intestines complex bacterial communities that play an important role in health and disease. To further our understanding of how intestinal bacterial communities assemble and function, we study the C. elegans microbiota with a bottom-up approach by feeding this nematode with bacterial monocultures as well as mixtures of two to eight bacterial species. We find that bacteria colonizing well in monoculture do not always do well in co-cultures due to interspecies bacterial interactions. Moreover, as community diversity increases, the ability to colonize the worm gut in monoculture becomes less important than interspecies interactions for determining community assembly. To explore the role of host-microbe adaptation, we compare bacteria isolated from C. elegans intestines and non-native isolates, and we find that the success of colonization is determined more by a species' taxonomy than by the isolation source. Lastly, by comparing the assembled microbiotas in two C. elegans mutants, we find that innate immunity via the p38 MAPK pathway decreases bacterial abundances yet has little influence on microbiota composition. These results highlight that bacterial interspecies interactions, more so than host-microbe adaptation or gut environmental filtering, play a dominant role in the assembly of the C. elegans microbiota.

Multi-Replicated Enrichment Communities as a Model System in Microbial Ecology

Recent advances in robotics and affordable genomic sequencing technologies have made it possible to establish and quantitatively track the assembly of enrichment communities in high-throughput. By conducting community assembly experiments in up to thousands of synthetic habitats, where the extrinsic sources of variation among replicates can be controlled, we can now study the reproducibility and predictability of microbial community assembly at different levels of organization, and its relationship with nutrient composition and other ecological drivers. Through a dialog with mathematical models, high-throughput enrichment communities are bringing us closer to the goal of developing a quantitative predictive theory of microbial community assembly. In this short review, we present an overview of recent research on this growing field, highlighting the connection between theory and experiments and suggesting directions for future work.

Formation, characterization and modeling of emergent synthetic microbial communities

Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions.

Rethinking Crop Nutrition in Times of Modern Microbiology: Innovative Biofertilizer Technologies

Global population growth poses a threat to food security in an era of increased ecosystem degradation, climate change, soil erosion, and biodiversity loss. In this context, harnessing naturally-occurring processes such as those provided by soil and plant-associated microorganisms presents a promising strategy to reduce dependency on agrochemicals. Biofertilizers are living microbes that enhance plant nutrition by either by mobilizing or increasing nutrient availability in soils. Various microbial taxa including beneficial bacteria and fungi are currently used as biofertilizers, as they successfully colonize the rhizosphere, rhizoplane or root interior. Despite their great potential to improve soil fertility, biofertilizers have yet to replace conventional chemical fertilizers in commercial agriculture. In the last 10 years, multi-omics studies have made a significant step forward in understanding the drivers, roles, processes, and mechanisms in the plant microbiome. However, translating this knowledge on microbiome functions in order to capitalize on plant nutrition in agroecosystems still remains a challenge. Here, we address the key factors limiting successful field applications of biofertilizers and suggest potential solutions based on emerging strategies for product development. Finally, we discuss the importance of biosafety guidelines and propose new avenues of research for biofertilizer development.

Metabolic modelling approaches for describing and engineering microbial communities

Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to growing awareness of their influence on a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications involving microorganisms, both in vivo and in silico, have been developed in the context of isolated microbes. In vivo microbial consortia development is extremely difficult and costly because it implies replicating suitable environments in the wet-lab. Computational approaches are thus a good, cost-effective alternative to study microbial communities, mainly via descriptive modelling, but also via engineering modelling. In this review we provide a detailed compilation of examples of engineered microbial communities and a comprehensive, historical revision of available computational metabolic modelling methods to better understand, and rationally engineer wild and synthetic microbial communities.

Development and Analysis of a Stable, Reduced Complexity Model Soil Microbiome

The soil microbiome is central to the cycling of carbon and other nutrients and to the promotion of plant growth. Despite its importance, analysis of the soil microbiome is difficult due to its sheer complexity, with thousands of interacting species. Here, we reduced this complexity by developing model soil microbial consortia that are simpler and more amenable to experimental analysis but still represent important microbial functions of the native soil ecosystem. Samples were collected from an arid grassland soil and microbial communities (consisting mainly of bacterial species) were enriched on agar plates containing chitin as the main carbon source. Chitin was chosen because it is an abundant carbon and nitrogen polymer in soil that often requires the coordinated action of several microorganisms for complete metabolic degradation. Several soil consortia were derived that had tractable richness (30–50 OTUs) with diverse phyla representative of the native soil, including Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Verrucomicrobia. The resulting consortia could be stored as glycerol or lyophilized stocks at −80°C and revived while retaining community composition, greatly increasing their use as tools for the research community at large. One of the consortia that was particularly stable was chosen as a model soil consortium (MSC-1) for further analysis. MSC-1 species interactions were studied using both pairwise co-cultivation in liquid media and during growth in soil under several perturbations. Co-abundance analyses highlighted interspecies interactions and helped to define keystone species, including Mycobacterium, Rhodococcus, and Rhizobiales taxa. These experiments demonstrate the success of an approach based on naturally enriching a community of interacting species that can be stored, revived, and shared. The knowledge gained from querying these communities and their interactions will enable better understanding of the soil microbiome and the roles these interactions play in this environment.

Understanding the Mechanisms of Positive Microbial Interactions That Benefit Lactic Acid Bacteria Co-cultures

Microorganisms grow in concert, both in natural communities and in artificial or synthetic co-cultures. Positive interactions between associated microbes are paramount to achieve improved substrate conversion and process performance in biotransformation and fermented food production. The mechanisms underlying such positive interactions have been the focus of numerous studies in recent decades and are now starting to be well characterized. Lactic acid bacteria (LAB) contribute to the final organoleptic, nutritional, and health properties of fermented food products. However, interactions in LAB co-cultures have been little studied, apart from the well-characterized LAB co-culture used for yogurt manufacture. LAB are, however, multifunctional microorganisms that display considerable potential to create positive interactions between them. This review describes why LAB co-cultures are of such interest, particularly in foods, and how their extensive nutritional requirements can be used to favor positive interactions. In that respect, our review highlights the benefits of co-cultures in different areas of application, details the mechanisms underlying positive interactions and aims to show how mechanisms based on nutritional interactions can be exploited to create efficient LAB co-cultures.

Microbial Species Coexistence Depends on the Host Environment

Organisms and their resident microbial communities form a complex and mostly stable ecosystem. It is known that the specific composition and abundance of certain bacterial species affect host health and fitness, but the processes that lead to these microbial patterns are unknown. We investigate this by deconstructing the simple microbiome of the freshwater polyp Hydra We contrast the performance of its two main bacterial associates, Curvibacter and Duganella, on germfree hosts with two in vitro environments over time. We show that interactions within the microbiome but also the host environment lead to the observed species frequencies and abundances. More specifically, we find that both microbial species can only stably coexist in the host environment, whereas Duganella outcompetes Curvibacter in both in vitro environments irrespective of initial starting frequencies. While Duganella seems to benefit through secretions of Curvibacter, its competitive effect on Curvibacter depends upon direct contact. The competition might potentially be mitigated through the spatial distribution of the two microbial species on the host, which would explain why both species stably coexist on the host. Interestingly, the relative abundances of both species on the host do not match the relative abundances reported previously nor the overall microbiome carrying capacity as reported in this study. Both observations indicate that rare microbial community members might be relevant for achieving the native community composition and carrying capacity. Our study highlights that for dissecting microbial interactions the specific environmental conditions need to be replicated, a goal difficult to achieve with in vitro systems.IMPORTANCE This work studies microbial interactions within the microbiome of the simple cnidarian Hydra and investigates whether microbial species coexistence and community stability depend on the host environment. We find that the outcome of the interaction between the two most dominant bacterial species in Hydra's microbiome differs depending on the environment and results in a stable coexistence only in the host context. The interactive ecology between the host and the two most dominant microbes, but also the less abundant members of the microbiome, is critically important for achieving the native community composition. This indicates that the metaorganism environment needs to be taken into account when studying microbial interactions.

Fitness and Productivity Increase with Ecotypic Diversity among Escherichia coli Strains That Coevolved in a Simple, Constant Environment

The productivity of a biological community often correlates with its diversity. In the microbial world this phenomenon can sometimes be explained by positive, density-dependent interactions such as cross-feeding and syntrophy. These metabolic interactions help account for the astonishing variety of microbial life and drive many of the biogeochemical cycles without which life as we know it could not exist. While it is difficult to recapitulate experimentally how these interactions evolved among multiple taxa, we can explore in the laboratory how they arise within one. These experiments provide insight into how different bacterial ecotypes evolve and from these, possibly new "species." We have previously shown that in a simple, constant environment a single clone of Escherichia coli can give rise to a consortium of genetically and phenotypically differentiated strains, in effect, a set of ecotypes, that coexist by cross-feeding. We marked these different ecotypes and their shared ancestor by integrating fluorescent protein into their genomes and then used flow cytometry to show that each evolved strain is more fit than the shared ancestor, that pairs of evolved strains are fitter still, and that the entire consortium is the fittest of all. We further demonstrate that the rank order of fitness values agrees with estimates of yield, indicating that an experimentally evolved consortium more efficiently converts primary and secondary resources to offspring than its ancestor or any member acting in isolation.IMPORTANCE Polymicrobial consortia occur in both environmental and clinical settings. In many cases, diversity and productivity correlate in these consortia, especially when sustained by positive, density-dependent interactions. However, the evolutionary history of such entities is typically obscure, making it difficult to establish the relative fitness of consortium partners and to use those data to illuminate the diversity-productivity relationship. Here, we dissect an Escherichia coli consortium that evolved under continuous glucose limitation in the laboratory from a single common ancestor. We show that a partnership consisting of cross-feeding ecotypes is better able to secure primary and secondary resources and to convert those resources to offspring than the ancestral clone. Such interactions may be a prelude to a special form of syntrophy and are likely determinants of microbial community structure in nature, including those having clinical significance such as chronic infections.

Synthetic Biology for Terraformation Lessons from Mars, Earth, and the Microbiome

What is the potential for synthetic biology as a way of engineering, on a large scale, complex ecosystems? Can it be used to change endangered ecological communities and rescue them to prevent their collapse? What are the best strategies for such ecological engineering paths to succeed? Is it possible to create stable, diverse synthetic ecosystems capable of persisting in closed environments? Can synthetic communities be created to thrive on planets different from ours? These and other questions pervade major future developments within synthetic biology. The goal of engineering ecosystems is plagued with all kinds of technological, scientific and ethic problems. In this paper, we consider the requirements for terraformation, i.e., for changing a given environment to make it hospitable to some given class of life forms. Although the standard use of this term involved strategies for planetary terraformation, it has been recently suggested that this approach could be applied to a very different context: ecological communities within our own planet. As discussed here, this includes multiple scales, from the gut microbiome to the entire biosphere.

Modeling population heterogeneity from microbial communities to immune response in cells

Heterogeneity is universally observed in all natural systems and across multiple scales. Understanding population heterogeneity is an intriguing and attractive topic of research in different disciplines, including microbiology and immunology. Microbes and mammalian immune cells present obviously rather different system-specific biological features. Nevertheless, as typically occurs in science, similar methods can be used to study both types of cells. This is particularly true for mathematical modeling, in which key features of a system are translated into algorithms to challenge our mechanistic understanding of the underlying biology. In this review, we first present a broad overview of the experimental developments that allowed observing heterogeneity at the single cell level. We then highlight how this "data revolution" requires the parallel advancement of algorithms and computing infrastructure for data processing and analysis, and finally present representative examples of computational models of population heterogeneity, from microbial communities to immune response in cells.

An evolutionary quantitative genetics model for phenotypic (co)variances under limited dispersal, with an application to socially synergistic traits

Darwinian evolution consists of the gradual transformation of heritable traits due to natural selection and the input of random variation by mutation. Here, we use a quantitative genetics approach to investigate the coevolution of multiple quantitative traits under selection, mutation, and limited dispersal. We track the dynamics of trait means and of variance-covariances between traits that experience frequency-dependent selection. Assuming a multivariate-normal trait distribution, we recover classical dynamics of quantitative genetics, as well as stability and evolutionary branching conditions of invasion analyses, except that due to limited dispersal, selection depends on indirect fitness effects and relatedness. In particular, correlational selection that associates different traits within-individuals depends on the fitness effects of such associations between-individuals. We find that these kin selection effects can be as relevant as pleiotropy for the evolution of correlation between traits. We illustrate this with an example of the coevolution of two social traits whose association within-individuals is costly but synergistically beneficial between-individuals. As dispersal becomes limited and relatedness increases, associations between-traits between-individuals become increasingly targeted by correlational selection. Consequently, the trait distribution goes from being bimodal with a negative correlation under panmixia to unimodal with a positive correlation under limited dispersal.