Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities

Nutrient Exchange of Carbon and Nitrogen Promotes the Formation of Stable Mutualisms Between Chlorella sorokiniana and Saccharomyces cerevisiae Under Engineered Synthetic Growth Conditions

Microbial biotechnological processes can be based on single species pure cultures or on multi-species assemblages. While these assemblages can be advantageous by offering more functionalities and more resilience to changing environmental conditions, they can be unpredictable and difficult to control under synthetically engineered growth conditions. To overcome the unpredictable nature of these microbial assemblages, the generation of stable mutualistic systems through synthetic ecology approaches may provide novel solutions for understanding microbial interactions in these environments. Here we establish a stable association between two evolutionarily unrelated, but biotechnologically complementary species isolated from winery wastewater; a strain of the yeast Saccharomyces cerevisiae and microalga, Chlorella sorokiniana. Yeast and microalgae were able to form obligate (interdependent) and non-obligate (facultative) mutualisms under engineered batch co-culture growth conditions. Obligate mutualism was maintained through the reciprocal exchange of carbon and nitrogen where the yeast ferments mannose to produce carbon dioxide for use by the microalga; and the microalga provides the yeast with nitrogen by metabolizing nitrite to ammonium. The effect of temperature and pH on the establishment of these mutualisms was evaluated and pH was found to be a key determinant for mutualism formation under obligatory conditions. Moreover, the combinations of the two species under non-obligatory growth conditions led to improvement in growth rate and biomass production when compared to single species cultures grown under the same conditions. Such engineered mutualisms are the first step in developing stable multi-species assemblages, while providing a system to generate novel insight into the evolution of mutualistic interactions between phylogenetically distant microorganisms.

Dispersal homogenizes communities via immigration even at low rates in a simplified synthetic bacterial metacommunity

Selection and dispersal are ecological processes that have contrasting roles in the assembly of communities. Variable selection diversifies and strong dispersal homogenizes them. However, we do not know whether dispersal homogenizes communities directly via immigration or indirectly via weakening selection across habitats due to physical transfer of material, e.g., water mixing in aquatic ecosystems. Here we examine how dispersal homogenizes a simplified synthetic bacterial metacommunity, using a sequencing-independent approach based on flow cytometry and mathematical modeling. We show that dispersal homogenizes the metacommunity via immigration, not via weakening selection, and even when immigration is four times slower than growth. This finding challenges the current view that dispersal homogenizes communities only at high rates and explains why communities are homogeneous at small spatial scales. It also offers a benchmark for sequence-based studies in natural microbial communities where immigration rates can be inferred solely by using neutral models.

The Use of Defined Microbial Communities To Model Host-Microbe Interactions in the Human Gut

The human intestinal ecosystem is characterized by a complex interplay between different microorganisms and the host. The high variation within the human population further complicates the quest toward an adequate understanding of this complex system that is so relevant to human health and well-being. To study host-microbe interactions, defined synthetic bacterial communities have been introduced in gnotobiotic animals or in sophisticated in vitro cell models. This review reinforces that our limited understanding has often hampered the appropriate design of defined communities that represent the human gut microbiota. On top of this, some communities have been applied to in vivo models that differ appreciably from the human host. In this review, the advantages and disadvantages of using defined microbial communities are outlined, and suggestions for future improvement of host-microbe interaction models are provided. With respect to the host, technological advances, such as the development of a gut-on-a-chip system and intestinal organoids, may contribute to more-accurate in vitro models of the human host. With respect to the microbiota, due to the increasing availability of representative cultured isolates and their genomic sequences, our understanding and controllability of the human gut "core microbiota" are likely to increase. Taken together, these advancements could further unravel the molecular mechanisms underlying the human gut microbiota superorganism. Such a gain of insight would provide a solid basis for the improvement of pre-, pro-, and synbiotics as well as the development of new therapeutic microbes.

Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior

The manipulation and engineering of microbiomes could lead to improved human health, environmental sustainability, and agricultural productivity. However, microbiomes have proven difficult to alter in predictable ways, and their emergent properties are poorly understood. The history of biology has demonstrated the power of model systems to understand complex problems such as gene expression or development. Therefore, a defined and genetically tractable model community would be useful to dissect microbiome assembly, maintenance, and processes. We have developed a tractable model rhizosphere microbiome, designated THOR, containing Pseudomonas koreensis, Flavobacterium johnsoniae, and Bacillus cereus, which represent three dominant phyla in the rhizosphere, as well as in soil and the mammalian gut. The model community demonstrates emergent properties, and the members are amenable to genetic dissection. We propose that THOR will be a useful model for investigations of community-level interactions.

The quest to manipulate microbiomes has intensified, but many microbial communities have proven to be recalcitrant to sustained change. Developing model communities amenable to genetic dissection will underpin successful strategies for shaping microbiomes by advancing an understanding of community interactions. We developed a model community with representatives from three dominant rhizosphere taxa, the Firmicutes, Proteobacteria, and Bacteroidetes. We chose Bacillus cereus as a model rhizosphere firmicute and characterized 20 other candidates, including “hitchhikers” that coisolated with B. cereus from the rhizosphere. Pairwise analysis produced a hierarchical interstrain-competition network. We chose two hitchhikers, Pseudomonas koreensis from the top tier of the competition network and Flavobacterium johnsoniae from the bottom of the network, to represent the Proteobacteria and Bacteroidetes, respectively. The model community has several emergent properties, induction of dendritic expansion of B. cereus colonies by either of the other members, and production of more robust biofilms by the three members together than individually. Moreover, P. koreensis produces a novel family of alkaloid antibiotics that inhibit growth of F. johnsoniae, and production is inhibited by B. cereus. We designate this community THOR, because the members are the hitchhikers of the rhizosphere. The genetic, genomic, and biochemical tools available for dissection of THOR provide the means to achieve a new level of understanding of microbial community behavior.

The rate of environmental fluctuations shapes ecological dynamics in a two-species microbial system

Species interactions change when the external conditions change. How these changes affect microbial community properties is an open question. We address this question using a two-species consortium in which species interactions change from exploitation to competition depending on the carbon source provided. We built a mathematical model and calibrated it using single-species growth measurements. This model predicted that low frequencies of change between carbon sources lead to species loss, while intermediate and high frequencies of change maintained both species. We experimentally confirmed these predictions by growing co-cultures in fluctuating environments. These findings complement more established concepts of a diversity peak at intermediate disturbance frequencies. They also provide a mechanistic understanding for how the dynamics at the community level emerges from single-species behaviours and interspecific interactions. Our findings suggest that changes in species interactions can profoundly impact the ecological dynamics and properties of microbial systems.

Deterministic Assembly and Diversity Gradient Altered the Biofilm Community Performances of Bioreactors

Community assembly process (determinism vs stochasticity) determines the composition and diversity of a microbial community, and then shapes its functions. Understanding this complex process and its relationship to the community functions becomes a very important task for the applications of microbial biotechnology. In this study, we applied microbial electrolysis cells (MECs) with moderate species numbers and easily tractable functions as a model ecosystem, and constructed a series of biofilm communities with gradient biodiversity to examine the roles of community assembly in determining microbial community structure and functions. After stable biofilms formed, the best MEC reactor performances (e.g., gas productivity, total energy efficiency) were achieved in the group in which biofilms had the second highest α-diversity, and biofilms with even lower diversity showed declining performance. Null model analyses indicated that both deterministic and stochastic assembly played roles in the formation of biofilm communities. When deterministic assembly dominates this formation, the higher diversity of the biofilm community would generally show better reactor performance. However, when the stochasticity dominates the assembly process, the bioreactor performance would decline. This study provides novel evidence that the assembly mechanism could be one of the key processes to shift the functions, and proposes an important guidance for selecting the most efficient microorganisms for environmental biotechnologies.

Simple organizing principles in microbial communities

There is a great deal of interest in discovering the principles that organize microbial communities, to better understand the structure and diversity of these communities in the natural world. Recent conceptual and technical advances have shown how simple organizing principles can give rise to surprising diversity and complex patterns in these consortia. Understanding competition, cooperation, and communication among microbes has provided novel insights into the structure and behavior of microbial collectives, and the use of simple animal models has advanced our understanding of microbial ecology in the host. These multidisciplinary efforts to understand and predict the properties of microbial communities will be critical in the development of microbial ecology as an applied science.

Effect of mixed soil microbiomes on pyrene removal and the response of the soil microorganisms

Mixed soil microbiomes were established by introducing aliquots of a paddy soil into a red soil. The new mixed microbiomes effectively metabolized high-molecular-weight polycyclic aromatic hydrocarbons (PAHs, pyrene) in the soil mixtures. The pyrene removal efficiencies were 19% and 98%, respectively, in the original red soil and the paddy soil. The pyrene removal effectiveness by the mixed microbial community was enhanced by increasing the amount of paddy soil inoculant and the pyrene removal rates were 93%, 58% and 27% in paddy soil/red soil mixtures of 1:1, 3:7 and 1:9 (w/w), respectively. Supplementation with sterile paddy soil and nutrients changed the soil environment but the pyrene removal efficiency was not enhanced, indicating that the microbial composition largely determined the extent of pyrene removal. Moreover, the pyrene removal rate was positively related to the pyrene dioxygenase gene (nidA) abundance. The greater the percentage of the paddy soil in the soil mixture the greater the similarity of the mixed microbiome to that of the original paddy soil itself. The community of the inoculated sterile paddy soil was similar to that of the red soil and the community diverged from those of the red soil and the paddy soil with increasing culture time. After culture for 42 days, some enriched genera were responsible for PAH degradation, notably Nevskia, Ralstonia, Gemmatimonas and Lysobacter, while some genera have no clear classification information or category name at the genus level, such as f__Acidobacteriaceae and o__JG30-KF-AS9. This study is very important in recognizing the role of natural soil in the formation of a mixed microbiome to stimulate the degradation of PAHs in a soil with low intrinsic PAH degradation capability.

Experimental evaluation of the importance of colonization history in early-life gut microbiota assembly

The factors that govern assembly of the gut microbiota are insufficiently understood. Here, we test the hypothesis that inter-individual microbiota variation can arise solely from differences in the order and timing by which the gut is colonized early in life. Experiments in which mice were inoculated in sequence either with two complex seed communities or a cocktail of four bacterial strains and a seed community revealed that colonization order influenced both the outcome of community assembly and the ecological success of individual colonizers. Historical contingency and priority effects also occurred in Rag1^-/- mice, suggesting that the adaptive immune system is not a major contributor to these processes. In conclusion, this study established a measurable effect of colonization history on gut microbiota assembly in a model in which host and environmental factors were strictly controlled, illuminating a potential cause for the high levels of unexplained individuality in host-associated microbial communities.

The microbial community living in the gastrointestinal tract of humans, also known as the gut microbiome, is essential for health. Disturbances of this community can lead to chronic diseases. Each person has a unique and stable community of gut microbes that is as personal as a ‘fingerprint’. Studies have shown that an individual’s genetics, diet, environment, lifestyle, and physiological state all make small contributions to the variation of the gut microbiome among individuals. However, less than 30% of this variation can be explained, and even identical twins, who share the same genetics and often diets and lifestyle, have distinct gut microbiomes. This suggests that other unknown factors likely shape these microbial communities too.

The microbial communities and the gut make up an ecosystem that is likely subject to many of the same ecological rules that govern ecosystems like rainforests or coral reefs. Yet many studies have overlooked the role of ecology in shaping the gut microbiota. For example, it is well known that the order in which organisms arrive in a community may influence how they interact and assemble into communities. It is possible that the order bacteria are introduced into the gastrointestinal tract of babies early in life may also change the make up of their gut microbiome, and thus introduce the variation that is currently unaccounted for.

Now, Martínez et al. show that the first types of bacteria to colonize the gut of mice have a lasting impact on their microbiome. In the experiments, genetically identical mice were housed under exactly the same conditions in airtight plastic bubbles. This allowed the scientists to control when the young mice first encountered specific microbes and microbe communities. Distinct microbial communities collected from different adult mice were introduced into the gastrointestinal tract of the young mice in sequence. Martínez et al. found that the microbes they introduced into the young mice first had the strongest influence on their gut microbiome at the end of the experiments.

When the experiments were repeated with a cocktail of four different bacteria the results were similar – the earlier arrivals showed enhanced colonization and had the biggest influence on the microbe community. This suggests that the timing of bacterial arrival in the gut is very important to shape the gut microbiome. Since it is highly random and unpredictable in real-life, and likely to differ even among twins, it could explain why the gut microbiome can be so unique. More studies are needed to understand how antibiotics, formula feeding, or cesarean sections affect gut microbiota early in life, and consequently health. This may help scientists develop better ways to influence the microbiota to improve health, for example, by introducing beneficial microbes early in life.

Ecology of Contaminant Biotransformation in the Mycosphere: Role of Transport Processes

Fungi and bacteria often share common microhabitats. Their co-occurrence and coevolution give rise to manifold ecological interactions in the mycosphere, here defined as the microhabitats surrounding and affected by hyphae and mycelia. The extensive structure of mycelia provides ideal "logistic networks" for transport of bacteria and matter in structurally and chemically heterogeneous soil ecosystems. We describe the characteristics of the mycosphere as a unique and highly dynamic bacterial habitat and a hot spot for contaminant biotransformation. In particular, we emphasize the role of the mycosphere for (i) bacterial dispersal and colonization of subsurface interfaces and new habitats, (ii) matter transport processes and contaminant bioaccessibility, and (iii) the functional stability of microbial ecosystems when exposed to environmental fluctuations such as stress or disturbances. Adopting concepts from ecological theory, the chapter disentangles bacterial-fungal impacts on contaminant biotransformation in a systemic approach that interlinks empirical data from microbial ecosystems with simulation data from computational models. This approach provides generic information on key factors, processes, and ecological principles that drive microbial contaminant biotransformation in soil. We highlight that the transport processes create favorable habitat conditions for efficient bacterial contaminant degradation in the mycosphere. In-depth observation, understanding, and prediction of the role of mycosphere transport processes will support the use of bacterial-fungal interactions in nature-based solutions for contaminant biotransformation in natural and man-made ecosystems, respectively.

Taking the technical microbiome into the next decade

The 'microbiome' has become a buzzword. Multiple new technologies allow to gather information about microbial communities as they evolve under stable and variable environmental conditions. The challenge of the next decade will be to develop strategies to compose and manage microbiomes. Here, key aspects are considered that will be of crucial importance for future microbial technological developments. First, the need to deal not only with genotypes but also particularly with phenotypes is addressed. Microbial technologies are often highly dependent on specific core organisms to obtain the desired process outcome. Hence, it is essential to combine omics data with phenotypic information to invoke and control specific phenotypes in the microbiome. Second, the development and application of synthetic microbiomes is evaluated. The central importance of the core species is a no-brainer, but the implementation of proper satellite species is an important route to explore. Overall, for the next decade, microbiome research should no longer almost exclusively focus on its capacity to degrade and dissipate but rather on its remarkable capability to capture disordered components and upgrade them into high-value microbial products. These products can become valuable commodities in the cyclic economy, as reflected in the case of 'reversed sanitation', which is introduced here.

Boosting mediated electron transfer in bioelectrochemical systems with tailored defined microbial cocultures

Bioelectrochemical systems (BES) hold great promise for sustainable energy generation via a microbial catalyst from organic matter, for example, from wastewater. To improve current generation in BES, understanding the underlying microbiology of the electrode community is essential. Electron mediator producing microorganism like Pseudomonas aeruginosa play an essential role in efficient electricity generation in BES. These microbes enable even nonelectroactive microorganism like Enterobacter aerogenes to contribute to current production. Together they form a synergistic coculture, where both contribute to community welfare. To use microbial co-operation in BES, the physical and chemical environments provided in the natural habitats of the coculture play a crucial role. Here, we show that synergistic effects in defined cocultures of P. aeruginosa and E. aerogenes can be strongly enhanced toward high current production by adapting process parameters, like pH, temperature, oxygen demand, and substrate requirements. Especially, oxygen was identified as a major factor influencing coculture behavior and optimization of its supply could enhance electric current production over 400%. Furthermore, operating the coculture in fed-batch mode enabled us to obtain very high current densities and to harvest electrical energy for 1 month. In this optimized condition, the coulombic efficiency of the process was boosted to 20%, which is outstanding for mediator-based electron transfer. This study lays the foundation for a rationally designed utilization of cocultures in BES for bioenergy generation from specific wastewaters or for bioprocess sensing and for benefiting from their synergistic effects under controlled bioprocess condition.

Dynamic microbial succession of Shanxi aged vinegar and its correlation with flavor metabolites during different stages of acetic acid fermentation

Shanxi aged vinegar (SAV), one of the famous Chinese vinegars, is produced by multispecies solid-state fermentation in which the acetic acid fermentation stage (AAF) is especially important. However, how bacterial succession and their metabolites change along with the different stages of AAF is still poorly understood. In this study, we investigated the dynamic bacterial succession and flavor formation in three batches of SAV using high-throughput sequencing and metabolomics approaches. It is interesting to find that AAF can be divided into three stages based on its bacterial community succession (early stage, days 0–4; medium stage, days 5–21; and later stage, days 22–26). Pantoea, Pediococcus, Lactococcus and Rhizobium played an important role in the early stage; Lactobacillus was dominant in the medium stage (67.72%); and Acetobacter, Komagataeibacter and Kroppenstedtia were the key bacteria in the later stage. A total of seven organic acids and 42 volatile constituents (esters, alcohol, ketones and aldehydes) were detected during the AAF. Spearman correlation analysis showed a significant correlation between the bacterial community and these flavor metabolites during the AAF of the SAV. This is the first report to explore the relationships between volatile flavor metabolites and bacterial community succession by a three-staged method and provide theoretical support for a flavor formation mechanism in traditional SAV.

Modelling upper respiratory tract diseases: getting grips on host-microbe interactions in chronic rhinosinusitis using in vitro technologies

Chronic rhinosinusitis (CRS) is a chronic inflammation of the mucosa of the nose and paranasal sinuses affecting approximately 11% of the adult population in Europe. Inadequate immune responses, as well as a dysbiosis of the sinonasal microbiota, have been put forward as aetiological factors of the disease. However, despite the prevalence of this disease, there is no consensus on the aetiology and mechanisms of pathogenesis of CRS. Further research requires in vitro models mimicking the healthy and diseased host environment along with the sinonasal microbiota. This review aims to provide an overview of CRS model systems and proposes in vitro modelling strategies to conduct mechanistic research in an ecological framework on the sinonasal microbiota and its interactions with the host in health and CRS.

HOMEs for plants and microbes - a phenotyping approach with quantitative control of signaling between organisms and their individual environments

We describe a simple, scalable, modular, and frugal approach to create model ecosystems as millifluidic networks of interconnected habitats (hosting microbes or plants), which offers (i) quantitative and dynamic control over the exchange of chemicals between habitats, and (ii) independent control over their environment. Oscillatory laminar flows produce regions of vortex mixing around obstacles. When these overlap, rapid mass transport by dispersion occurs, which is quantitatively describable as diffusion, but is directional and tunable in rate over 3 orders of magnitude. This acceleration in the rate of diffusion is equivalent to reducing the distance between the habitats, and therefore, the organisms, down to the length scales characteristic of signaling in soil (<2 mm).

Bacterial Microbiota of Rice Roots: 16S-Based Taxonomic Profiling of Endophytic and Rhizospheric Diversity, Endophytes Isolation and Simplified Endophytic Community

Rice is currently the most important food crop in the world and we are only just beginning to study the bacterial associated microbiome. It is of importance to perform screenings of the core rice microbiota and also to develop new plant-microbe models and simplified communities for increasing our understanding about the formation and function of its microbiome. In order to begin to address this aspect, we have performed a 16S rDNA taxonomic bacterial profiling of the rhizosphere and endorhizosphere of two high-yield rice cultivars—Pionero 2010 FL and DANAC SD20A—extensively grown in Venezuela in 2014. Fifteen putative bacterial endophytes were then isolated from surface-sterilized roots and further studied in vitro and in planta. We have then performed inoculation of rice seedlings with a simplified community composed by 10 of the isolates and we have tracked them in the course of 30 days in greenhouse cultivation. The results obtained suggest that a set was able to significantly colonize together the rice endorhizospheres, indicating possible cooperation and the ability to form a stable multispecies community. This approach can be useful in the development of microbial solutions for a more sustainable rice production.

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.

Synthetic microbial ecology and the dynamic interplay between microbial genotypes

Assemblages of microbial genotypes growing together can display surprisingly complex and unexpected dynamics and result in community-level functions and behaviors that are not readily expected from analyzing each genotype in isolation. This complexity has, at least in part, inspired a discipline of synthetic microbial ecology. Synthetic microbial ecology focuses on designing, building and analyzing the dynamic behavior of ‘ecological circuits’ (i.e. a set of interacting microbial genotypes) and understanding how community-level properties emerge as a consequence of those interactions. In this review, we discuss typical objectives of synthetic microbial ecology and the main advantages and rationales of using synthetic microbial assemblages. We then summarize recent findings of current synthetic microbial ecology investigations. In particular, we focus on the causes and consequences of the interplay between different microbial genotypes and illustrate how simple interactions can create complex dynamics and promote unexpected community-level properties. We finally propose that distinguishing between active and passive interactions and accounting for the pervasiveness of competition can improve existing frameworks for designing and predicting the dynamics of microbial assemblages.

Initial evenness determines diversity and cell density dynamics in synthetic microbial ecosystems

The effect of initial evenness on the temporal trajectory of synthetic communities in comprehensive, low-volume microcosm studies remains unknown. We used flow cytometric fingerprinting and 16S rRNA gene amplicon sequencing to assess the impact of time on community structure in one hundred synthetic ecosystems of fixed richness but varying initial evenness. Both methodologies uncovered a similar reduction in diversity within synthetic communities of medium and high initial evenness classes. However, the results of amplicon sequencing showed that there were no significant differences between and within the communities in all evenness groups at the end of the experiment. Nevertheless, initial evenness significantly impacted the cell density of the community after five medium transfers. Highly even communities retained the highest cell densities at the end of the experiment. The relative abundances of individual species could be associated to particular evenness groups, suggesting that their presence was dependent on the initial evenness of the synthetic community. Our results reveal that using synthetic communities for testing ecological hypotheses requires prior assessment of initial evenness, as it impacts temporal dynamics.

Investigation of different nitrogen reduction routes and their key microbial players in wood chip-driven denitrification beds

Field denitrification beds containing polymeric plant material are increasingly used to eliminate nitrate from agricultural drainage water. They mirror a number of anoxic ecosystems. However, knowledge of the microbial composition, the interaction of microbial species, and the carbon degradation processes within these denitrification systems is sparse. This study revealed several new aspects of the carbon and nitrogen cycle, and these findings can be correlated with the dynamics of the microbial community composition and the activity of key species. Members of the order Pseudomonadales seem to be important players in denitrification at low nitrate concentrations, while a switch to higher nitrate concentrations seems to select for members of the orders Rhodocyclales and Rhizobiales. We observed that high nitrate loading rates lead to an unpredictable transition of the community's activity from denitrification to dissimilatory reduction of nitrate to ammonium (DNRA). This transition is mirrored by an increase in transcripts of the nitrite reductase gene nrfAH and the increase correlates with the activity of members of the order Ignavibacteriales. Denitrification reactors sustained the development of an archaeal community consisting of members of the Bathyarchaeota and methanogens belonging to the Euryarchaeota. Unexpectedly, the activity of the methanogens positively correlated with the nitrate loading rates.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

A Synthetic Community System for Probing Microbial Interactions Driven by Exometabolites

Understanding microbial interactions is a fundamental objective in microbiology and ecology. The synthetic community system described here can set into motion a range of research to investigate how the diversity of a microbiome and interactions among its members impact its function, where function can be measured as exometabolites. The system allows for community exometabolite profiling to be coupled with genome mining, transcript analysis, and measurements of member productivity and population size. It can also facilitate discovery of natural products that are only produced within microbial consortia. Thus, this synthetic community system has utility to address fundamental questions about a diversity of possible microbial interactions that occur in both natural and engineered ecosystems.

Though most microorganisms live within a community, we have modest knowledge about microbial interactions and their implications for community properties and ecosystem functions. To advance understanding of microbial interactions, we describe a straightforward synthetic community system that can be used to interrogate exometabolite interactions among microorganisms. The filter plate system (also known as the Transwell system) physically separates microbial populations, but allows for chemical interactions via a shared medium reservoir. Exometabolites, including small molecules, extracellular enzymes, and antibiotics, are assayed from the reservoir using sensitive mass spectrometry. Community member outcomes, such as growth, productivity, and gene regulation, can be determined using flow cytometry, biomass measurements, and transcript analyses, respectively. The synthetic community design allows for determination of the consequences of microbiome diversity for emergent community properties and for functional changes over time or after perturbation. Because it is versatile, scalable, and accessible, this synthetic community system has the potential to practically advance knowledge of microbial interactions that occur within both natural and artificial communities.

IMPORTANCE Understanding microbial interactions is a fundamental objective in microbiology and ecology. The synthetic community system described here can set into motion a range of research to investigate how the diversity of a microbiome and interactions among its members impact its function, where function can be measured as exometabolites. The system allows for community exometabolite profiling to be coupled with genome mining, transcript analysis, and measurements of member productivity and population size. It can also facilitate discovery of natural products that are only produced within microbial consortia. Thus, this synthetic community system has utility to address fundamental questions about a diversity of possible microbial interactions that occur in both natural and engineered ecosystems.

Author Video: An author video summary of this article is available.

The Impact of Saccharomyces cerevisiae on a Wine Yeast Consortium in Natural and Inoculated Fermentations

Natural, also referred to as spontaneous wine fermentations, are carried out by the native microbiota of the grape juice, without inoculation of selected, industrially produced yeast or bacterial strains. Such fermentations are commonly initiated by non-Saccharomyces yeast species that numerically dominate the must. Community composition and numerical dominance of species vary significantly between individual musts, but Saccharomyces cerevisiae will in most cases dominate the late stages of the fermentation and complete the process. Nevertheless, non-Saccharomyces species contribute significantly, positively or negatively, to the character and quality of the final product. The contribution is species and strain dependent and will depend on each species or strain's absolute and relative contribution to total metabolically active biomass, and will therefore, be a function of its relative fitness within the microbial ecosystem. However, the population dynamics of multispecies fermentations are not well understood. Consequently, the oenological potential of the microbiome in any given grape must, can currently not be evaluated or predicted. To better characterize the rules that govern the complex wine microbial ecosystem, a model yeast consortium comprising eight species commonly encountered in South African grape musts and an ARISA based method to monitor their dynamics were developed and validated. The dynamics of these species were evaluated in synthetic must in the presence or absence of S. cerevisiae using direct viable counts and ARISA. The data show that S. cerevisiae specifically suppresses certain species while appearing to favor the persistence of other species. Growth dynamics in Chenin blanc grape must fermentation was monitored only through viable counts. The interactions observed in the synthetic must, were upheld in the natural must fermentations, suggesting the broad applicability of the observed ecosystem dynamics. Importantly, the presence of indigenous yeast populations did not appear to affect the broad interaction patterns between the consortium species. The data show that the wine ecosystem is characterized by both mutually supportive and inhibitory species. The current study presents a first step in the development of a model to predict the oenological potential of any given wine mycobiome.

Yeast Creates a Niche for Symbiotic Lactic Acid Bacteria through Nitrogen Overflow

Many microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, cross-feeding in a readily established community. In nitrogen-rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis. Quantity of the available nitrogen sources and the status of nitrogen catabolite repression pathways jointly modulate this niche creation. We demonstrate how nitrogen overflow by yeast benefits L. plantarum in grape juice, and contributes to emergence of mutualism with L. lactis in a medium with lactose. Our results illustrate how metabolic decisions of an individual species can benefit others.

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Yeast overflows amino acids that enable survival of lactic acid bacteria (LAB)

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Overflow is in proportion to nitrogen excess and regulated via TORC1 pathway

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Phenotype supporting LAB growth is conserved across diverse yeast isolates

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Yeast-LAB mutualism readily emerges when lactose is the main C-source

Assigning ecological roles to the populations belonging to a phenanthrene-degrading bacterial consortium using omic approaches

The present study describes the behavior of a natural phenanthrene-degrading consortium (CON), a synthetic consortium (constructed with isolated strains from CON) and an isolated strain form CON (Sphingobium sp. AM) in phenanthrene cultures to understand the interactions among the microorganisms present in the natural consortium during phenanthrene degradation as a sole carbon and energy source in liquid cultures. In the contaminant degradation assay, the defined consortium not only achieved a major phenanthrene degradation percentage (> 95%) but also showed a more efficient elimination of the intermediate metabolite. The opposite behavior occurred in the CON culture where the lowest phenanthrene degradation and the highest HNA accumulation were observed, which suggests the presence of positive and also negative interaction in CON. To consider the uncultured bacteria present in CON, a metagenomic library was constructed with total CON DNA. One of the resulting scaffolds (S1P3) was affiliated with the Betaproteobacteria class and resulted in a significant similarity with a genome fragment from Burkholderia sp. HB1 chromosome 1. A complete gene cluster, which is related to one of the lower pathways (meta-cleavage of catechol) involved in PAH degradation (ORF 31-43), mobile genetic elements and associated proteins, was found. These results suggest the presence of at least one other microorganism in CON besides Sphingobium sp. AM, which is capable of degrading PAH through the meta-cleavage pathway. Burkholderiales order was further found, along with Sphingomonadales order, by a metaproteomic approach, which indicated that both orders were metabolically active in CON. Our results show the presence of negative interactions between bacterial populations found in a natural consortium selected by enrichment techniques; moreover, the synthetic syntrophic processing chain with only one microorganism with the capability of degrading phenanthrene was more efficient in contaminant and intermediate metabolite degradation than a generalist strain (Sphingobium sp. AM).

Electroactive Biofilms for Sensing: Reflections and Perspectives

Microbial electrochemistry has from the onset been recognized for its sensing potential due to the microbial ability to enhance signals through metabolic cascades, its relative selectivity toward substrates, and the higher stability conferred by the microbial ability to self-replicate. The greatest challenge has been to achieve stable and efficient transduction between a microorganism and an electrode surface. Over the past decades, a new kind of microbial architecture has been observed to spontaneously develop on polarized electrodes: the electroactive biofilm (EAB). The EAB conducts electrons over long distances and performs quasi-reversible electron transfer on conventional electrode surfaces. It also possesses self-regenerative properties. In only a few years, EABs have inspired considerable research interest for use as biosensors for environmental or bioprocess monitoring. Multiple challenges still need to be overcome before implementation at larger scale of this new kind of biosensors can be realized. This perspective first introduces the specific characteristics of the EAB with respect to other electrochemical biosensors. It summarizes the sensing applications currently proposed for EABs, stresses their limitations, and suggests strategies toward potential solutions. Conceptual prospects to engineer EABs for sensing purposes are also discussed.

Unraveling the correlation between microbiota succession and metabolite changes in traditional Shanxi aged vinegar

Shanxi aged vinegar (SAV) is a well-known vinegar produced by traditional solid-state fermentation and has been used in China for thousands of years. However, how microorganisms and their metabolites change along with fermentation is unclear. Here, 454 high-throughput sequencing and denaturing gradient gel electrophoresis were used to investigate the composition of microbial community. Metabolites were further analyzed by gas chromatography–mass spectrometry and high–performance liquid chromatography. Results showed that the composition of bacterial community changed dramatically at different stages of fermentation. The bacterial genera (relative abundance > 0.1%) decreased from 17 in daqu (starter used in starch saccharification) to 2 at the 12th day of alcohol fernemtation (AF). 15 bacterial genera at the 1st day of acetic acid fermentation (AAF) decreased to 4 genera, involving Acetobacter (50.9%), Lactobacillus (47.9%), Komagataeibacter (formerly Gluconacetobacter, 0.7%) and Propionibacterium (0.1%) at the 7th day of AAF. The structure of fungal community was more homogeneous. Saccharomyces and Saccharomycopsis were predominant in AF and AAF. A total of 87 kinds of nonvolatile metabolites were detected. Canonical correspondence analysis showed a significant correlation between the microbiota succession and the formation of metabolites during the fermentation of SAV. This study provides detailed information for the fermentation mechanism of traditional SAV.

A stabilized microbial ecosystem of self-limiting bacteria using synthetic quorum-regulated lysis

Microbial ecologists are increasingly turning to small, synthesized ecosystems1-5 as a reductionist tool to probe the complexity of native microbiomes6,7. Concurrently, synthetic biologists have gone from single-cell gene circuits8-11 to controlling whole populations using intercellular signalling12-16. The intersection of these fields is giving rise to new approaches in waste recycling17, industrial fermentation18, bioremediation19 and human health16,20. These applications share a common challenge7 well-known in classical ecology21,22-stability of an ecosystem cannot arise without mechanisms that prohibit the faster-growing species from eliminating the slower. Here, we combine orthogonal quorum-sensing systems and a population control circuit with diverse self-limiting growth dynamics to engineer two 'ortholysis' circuits capable of maintaining a stable co-culture of metabolically competitive Salmonella typhimurium strains in microfluidic devices. Although no successful co-cultures are observed in a two-strain ecology without synthetic population control, the 'ortholysis' design dramatically increases the co-culture rate from 0% to approximately 80%. Agent-based and deterministic modelling reveal that our system can be adjusted to yield different dynamics, including phase-shifted, antiphase or synchronized oscillations, as well as stable steady-state population densities. The 'ortholysis' approach establishes a paradigm for constructing synthetic ecologies by developing stable communities of competitive microorganisms without the need for engineered co-dependency.

Effects of Growth Surface Topography on Bacterial Signaling in Coculture Biofilms

Bacteria form interface-associated communities called biofilms, often comprising multiple species. Biofilms can be detrimental or beneficial in medical, industrial, and technological settings, and their stability and function are determined by interspecies communication via specific chemical signaling or metabolite exchange. The deterministic control of biofilm development, behavior, and properties remains an unmet challenge, limiting our ability to inhibit the formation of detrimental biofilms in biomedical settings and promote the growth of beneficial biofilms in biotechnology applications. Here, we describe the development of growth surfaces that promote the growth of commensal Escherichia coli instead of the opportunistic pathogen Pseudomonas aeruginosa. Periodically patterned growth surfaces induced robust morphological changes in surface-associated E. coli biofilms and influenced the antibiotic susceptibilities of E. coli and P. aeruginosa biofilms. Changes in the biofilm architecture resulted in the accumulation of a metabolite, indole, which controls the competition dynamics between the two species. Our results show that the surface on which a biofilm grows has important implications for species colonization, growth, and persistence when exposed to antibiotics.

Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities

Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities. We created so-called in silico communities, which allow us to explore the possibilities of bacterial flow cytometry data using supervised machine learning techniques. We can identify single cells with an accuracy >90% for more than half of the communities consisting out of two bacterial populations. In order to assess to what extent an in silico community is representative for its synthetic counterpart, we created so-called abundance gradients, a combination of synthetic (i.e., in vitro) communities containing two bacterial populations in varying abundances. By showing that we are able to retrieve an abundance gradient using a combination of in silico communities and supervised machine learning techniques, we argue that in silico communities form a viable representation for synthetic bacterial communities, opening up new opportunities for the analysis of synthetic communities and bacterial flow cytometry data in general.

Probiotic Diversity Enhances Rhizosphere Microbiome Function and Plant Disease Suppression

Bacterial communities associated with plant roots play an important role in the suppression of soil-borne pathogens, and multispecies probiotic consortia may enhance disease suppression efficacy. Here we introduced defined Pseudomonas species consortia into naturally complex microbial communities and measured the importance of Pseudomonas community diversity for their survival and the suppression of the bacterial plant pathogen Ralstonia solanacearum in the tomato rhizosphere microbiome. The survival of introduced Pseudomonas consortia increased with increasing diversity. Further, high Pseudomonas diversity reduced pathogen density in the rhizosphere and decreased the disease incidence due to both intensified resource competition and interference with the pathogen. These results provide novel mechanistic insights into elevated pathogen suppression by diverse probiotic consortia in naturally diverse plant rhizospheres. Ecologically based community assembly rules could thus play a key role in engineering functionally reliable microbiome applications.

The increasing demand for food supply requires more-efficient control of plant diseases. The use of probiotics, i.e., naturally occurring bacterial antagonists and competitors that suppress pathogens, has recently reemerged as a promising alternative to agrochemical use. It is, however, still unclear how many and which strains we should choose for constructing effective probiotic consortia. Here we present a general ecological framework for assembling effective probiotic communities based on in vitro characterization of community functioning. Specifically, we show that increasing the diversity of probiotic consortia enhances community survival in the naturally diverse rhizosphere microbiome, leading to increased pathogen suppression via intensified resource competition and interference with the pathogen. We propose that these ecological guidelines can be put to the test in microbiome engineering more widely in the future.

Microbiome Selection Could Spur Next-Generation Plant Breeding Strategies

“No plant is an island too…”

Plants, though sessile, have developed a unique strategy to counter biotic and abiotic stresses by symbiotically co-evolving with microorganisms and tapping into their genome for this purpose. Soil is the bank of microbial diversity from which a plant selectively sources its microbiome to suit its needs. Besides soil, seeds, which carry the genetic blueprint of plants during trans-generational propagation, are home to diverse microbiota that acts as the principal source of microbial inoculum in crop cultivation. Overall, a plant is ensconced both on the outside and inside with a diverse assemblage of microbiota. Together, the plant genome and the genes of the microbiota that the plant harbors in different plant tissues, i.e., the ‘plant microbiome,’ form the holobiome which is now considered as unit of selection: ‘the holobiont.’ The ‘plant microbiome’ not only helps plants to remain fit but also offers critical genetic variability, hitherto, not employed in the breeding strategy by plant breeders, who traditionally have exploited the genetic variability of the host for developing high yielding or disease tolerant or drought resistant varieties. This fresh knowledge of the microbiome, particularly of the rhizosphere, offering genetic variability to plants, opens up new horizons for breeding that could usher in cultivation of next-generation crops depending less on inorganic inputs, resistant to insect pest and diseases and resilient to climatic perturbations. We surmise, from ever increasing evidences, that plants and their microbial symbionts need to be co-propagated as life-long partners in future strategies for plant breeding. In this perspective, we propose bottom–up approach to co-propagate the co-evolved, the plant along with the target microbiome, through – (i) reciprocal soil transplantation method, or (ii) artificial ecosystem selection method of synthetic microbiome inocula, or (iii) by exploration of microRNA transfer method – for realizing this next-generation plant breeding approach. Our aim, thus, is to bring closer the information accrued through the advanced nucleotide sequencing and bioinformatics in conjunction with conventional culture-dependent isolation method for practical application in plant breeding and overall agriculture.

Synthetic biology platform technologies for antimicrobial applications

The growing prevalence of antibiotic resistance calls for new approaches in the development of antimicrobial therapeutics. Likewise, improved diagnostic measures are essential in guiding the application of targeted therapies and preventing the evolution of therapeutic resistance. Discovery platforms are also needed to form new treatment strategies and identify novel antimicrobial agents. By applying engineering principles to molecular biology, synthetic biologists have developed platforms that improve upon, supplement, and will perhaps supplant traditional broad-spectrum antibiotics. Efforts in engineering bacteriophages and synthetic probiotics demonstrate targeted antimicrobial approaches that can be fine-tuned using synthetic biology-derived principles. Further, the development of paper-based, cell-free expression systems holds promise in promoting the clinical translation of molecular biology tools for diagnostic purposes. In this review, we highlight emerging synthetic biology platform technologies that are geared toward the generation of new antimicrobial therapies, diagnostics, and discovery channels.

Quorum Sensing Communication Modules for Microbial Consortia

The power of a single engineered organism is limited by its capacity for genetic modification. To circumvent the constraints of any singular microbe, a new frontier in synthetic biology is emerging: synthetic ecology, or the engineering of microbial consortia. Here we develop communication systems for such consortia in an effort to allow for complex social behavior across different members of a community. We posit that such communities will outpace monocultures in their ability to perform complicated tasks if communication among and between members of the community is well regulated. Quorum sensing was identified as the most promising candidate for precise control of engineered microbial ecosystems, due to its large diversity and established utility in synthetic biology. Through promoter and protein modification, we engineered two quorum sensing systems (rpa and tra) to add to the extensively used lux and las systems. By testing the cross-talk between all systems, we thoroughly characterized many new inducible systems for versatile control of engineered communities. Furthermore, we've identified several system pairs that exhibit useful types of orthogonality. Most notably, the tra and rpa systems were shown to have neither signal crosstalk nor promoter crosstalk for each other, making them completely orthogonal in operation. Overall, by characterizing the interactions between all four systems and their components, these circuits should lend themselves to higher-level genetic circuitry for use in microbial consortia.

Specialized Microbiome of a Halophyte and its Role in Helping Non-Host Plants to Withstand Salinity

Root microbiota is a crucial determinant of plant productivity and stress tolerance. Here, we hypothesize that the superior halo-tolerance of seepweed Suaeda salsa is tightly linked to a specialized belowground microbiome. To test this hypothesis, we performed a phylogenetic trait-based framework analysis based on bacterial 16S rRNA gene and fungal nuclear rRNA internal transcribed spacer profiling. Data showed that the dominant α-proteobacteria and γ-proteobacteria communities in bulk soil and root endosphere tend to be phylogenetically clustered and at the same time exhibit phylogenetic over-dispersion in rhizosphere. Likewise, the dominant fungal genera occurred at high phylogenetic redundancy. Interestingly, we found the genomes of rhizospheric and endophytic bacteria associated with S. salsa to be enriched in genes contributing to salt stress acclimatization, nutrient solubilization and competitive root colonization. A wide diversity of rhizobacteria with similarity to known halotolerant taxa further supported this interpretation. These findings suggest that an ecological patterned root-microbial interaction strategy has been adopted in S. salsa system to confront soil salinity. We also demonstrated that the potential core microbiome members improve non-host plants growth and salt tolerance. This work provides a platform to improve plant fitness with halophytes-microbial associates and novel insights into the functions of plant microbiome under salinity.

Microbially Mediated Plant Salt Tolerance and Microbiome-based Solutions for Saline Agriculture

Soil salinization adversely affects plant growth and has become one of the major limiting factors for crop productivity worldwide. The conventional approach, breeding salt-tolerant plant cultivars, has often failed to efficiently alleviate the situation. In contrast, the use of a diverse array of microorganisms harbored by plants has attracted increasing attention because of the remarkable beneficial effects of microorganisms on plants. Multiple advanced '-omics' technologies have enabled us to gain insights into the structure and function of plant-associated microbes. In this review, we first focus on microbe-mediated plant salt tolerance, in particular on the physiological and molecular mechanisms underlying root-microbe symbiosis. Unfortunately, when introducing such microbes as single strains to soils, they are often ineffective in improving plant growth and stress tolerance, largely due to competition with native soil microbial communities and limited colonization efficiency. Rapid progress in rhizosphere microbiome research has revived the belief that plants may benefit more from association with interacting, diverse microbial communities (microbiome) than from individual members in a community. Understanding how a microbiome assembles in the continuous compartments (endosphere, rhizoplane, and rhizosphere) will assist in predicting a subset of core or minimal microbiome and thus facilitate synthetic re-construction of microbial communities and their functional complementarity and synergistic effects. These developments will open a new avenue for capitalizing on the cultivable microbiome to strengthen plant salt tolerance and thus to refine agricultural practices and production under saline conditions.

Biotic Interactions in Microbial Communities as Modulators of Biogeochemical Processes: Methanotrophy as a Model System

Microbial interaction is an integral component of microbial ecology studies, yet the role, extent, and relevance of microbial interaction in community functioning remains unclear, particularly in the context of global biogeochemical cycles. While many studies have shed light on the physico-chemical cues affecting specific processes, (micro)biotic controls and interactions potentially steering microbial communities leading to altered functioning are less known. Yet, recent accumulating evidence suggests that the concerted actions of a community can be significantly different from the combined effects of individual microorganisms, giving rise to emergent properties. Here, we exemplify the importance of microbial interaction for ecosystem processes by analysis of a reasonably well-understood microbial guild, namely, aerobic methane-oxidizing bacteria (MOB). We reviewed the literature which provided compelling evidence for the relevance of microbial interaction in modulating methane oxidation. Support for microbial associations within methane-fed communities is sought by a re-analysis of literature data derived from stable isotope probing studies of various complex environmental settings. Putative positive interactions between active MOB and other microbes were assessed by a correlation network-based analysis with datasets covering diverse environments where closely interacting members of a consortium can potentially alter the methane oxidation activity. Although, methanotrophy is used as a model system, the fundamentals of our postulations may be applicable to other microbial guilds mediating other biogeochemical processes.

Synthetic transitions: towards a new synthesis

The evolution of life in our biosphere has been marked by several major innovations. Such major complexity shifts include the origin of cells, genetic codes or multicellularity to the emergence of non-genetic information, language or even consciousness. Understanding the nature and conditions for their rise and success is a major challenge for evolutionary biology. Along with data analysis, phylogenetic studies and dedicated experimental work, theoretical and computational studies are an essential part of this exploration. With the rise of synthetic biology, evolutionary robotics, artificial life and advanced simulations, novel perspectives to these problems have led to a rather interesting scenario, where not only the major transitions can be studied or even reproduced, but even new ones might be potentially identified. In both cases, transitions can be understood in terms of phase transitions, as defined in physics. Such mapping (if correct) would help in defining a general framework to establish a theory of major transitions, both natural and artificial. Here, we review some advances made at the crossroads between statistical physics, artificial life, synthetic biology and evolutionary robotics.This article is part of the themed issue 'The major synthetic evolutionary transitions'.