Top-down and bottom-up cohesiveness in microbial community coalescence

Evidence of sewage discharge on the coalescence mechanism of aquatic microbial communities during high amplitude hydrological periods

Microbial community coalescence is a ubiquitous ecological process in various ecosystems. However, limited research has addressed the effects of the coalescence on microbial ecological processes and network structure, particularly in the context of sewage discharge during high amplitude hydrological periods. Employing 16S rRNA sequencing and species source tracking analysis, we investigated the coalescence pattern of bacterioplankton in the Chishui river and sewage across various hydrological periods. The results demonstrated that the downstream bacterioplankton mainly originated from the upstream water body, and the sewage discharge from the wastewater treatment plants (WWTPs) had less impact on the downstream bacterioplankton. In the low-water period, the bacterioplankton community showed significant coalescence, and the specialist species and functional taxa gathered in the downstream. Bacterioplankton displayed distinct ecological succession patterns after community coalescence, with notable variations in the abundance of dominant group. Bacterioplankton community assembly was dominated by stochastic processes in river and the sewage over different hydrological periods. The ecological networks exhibited the highest complexity in the high-water period, whereas their stability was most pronounced in the low-water period. Species diversity, as opposed to functional and phylogenetic diversity, might be a more accurate indicator to predict changes in microbial network structure. Our findings will provide new perspectives on the mechanisms of aquatic microbial community coalescence in natural environments.

Metagenomics-resolved genomics provide novel ecological insights into resistome community coalescence of wastewater in river environment

The discharge of wastewater into rivers can lead to resistome coalescence, thereby enhancing the spread risk of antibiotic resistance genes (ARGs) through mixing of exogenous wastewater resistome communities with indigenous riverine communities. At present, the understanding on the role of resistome community coalescence in the dissemination of ARGs is still very limited, and little is known about the process and its ecological implications. To bridge the gap, this study has conducted field-based surveys and microcosm experiments to deeply dissect the coalescence of resistome community in wastewater within river environment, utilizing genome-centric metagenomic analysis approach. The field investigation suggests resistome coalescence enhances the abundance and diversity of ARGs in the receiving river. Furthermore, the microcosm experiments reveal the effect of mixing ratio on resistome coalescence in the water-sediment system and decipher the temporal attenuation dynamics of the coalesced resistome in the environment. The results show the higher proportion of wastewater has a greater impact on ARGs in the water, whereas the effect of mixing ratio is lesser in the sediments. Temporally, the source-specific ARGs originating from wastewater exhibit decreasing trends over the experimental duration, and relatively, the attenuation in the water is more pronounced than that in the sediments. Interestingly, natural light not only facilitates the attenuation of ARGs in the water but may also induce their deposition at the water-sediment interface. Variance partitioning analyses suggest the microbiome, mobilome, and abiotic factors collectively shape the coalescence of the resistome communities in the environment. The study provides empirical evidence on resistome coalescence in river systems, which is instrumental in gaining a better understanding of the spread mechanism of ARGs in the environment.

Activated sludge microbial community assembly: the role of influent microbial community immigration

Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater. However, the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilized controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analyzed by harvesting wastewater biomass solids from three different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 14% of the sequencing reads in the AS. By modeling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principles for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs.IMPORTANCEIn biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. This study developed a reproducible protocol to investigate the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls, allowing intrinsic definitions of core and immigrant populations to be established. The method developed herein will allow sequential manipulative experiments to be performed to test specific hypothesis and optimize wastewater treatment processes to meet new treatment goals.

Starting with screening strains to construct synthetic microbial communities (SynComs) for traditional food fermentation

With the elucidation of community structures and assembly mechanisms in various fermented foods, core communities that significantly influence or guide fermentation have been pinpointed and used for exogenous restructuring into synthetic microbial communities (SynComs). These SynComs simulate ecological systems or function as adjuncts or substitutes in starters, and their efficacy has been widely verified. However, screening and assembly are still the main limiting factors for implementing theoretic SynComs, as desired strains cannot be effectively obtained and integrated. To expand strain screening methods suitable for SynComs in food fermentation, this review summarizes the recent research trends in using SynComs to study community evolution or interaction and improve the quality of food fermentation, as well as the specific process of constructing synthetic communities. The potential for novel screening modalities based on genes, enzymes and metabolites in food microbial screening is discussed, along with the emphasis on strategies to optimize assembly for facilitating the development of synthetic communities.

Practical applications of soil microbiota to improve ecosystem restoration: current knowledge and future directions

Soil microbiota are important components of healthy ecosystems. Greater consideration of soil microbiota in the restoration of biodiverse, functional, and resilient ecosystems is required to address the twin global crises of biodiversity decline and climate change. In this review, we discuss available and emerging practical applications of soil microbiota into (i) restoration planning, (ii) direct interventions for shaping soil biodiversity, and (iii) strategies for monitoring and predicting restoration trajectories. We show how better planning of restoration activities to account for soil microbiota can help improve progress towards restoration targets. We show how planning to embed soil microbiota experiments into restoration projects will permit a more rigorous assessment of the effectiveness of different restoration methods, especially when complemented by statistical modelling approaches that capitalise on existing data sets to improve causal understandings and prioritise research strategies where appropriate. In addition to recovering belowground microbiota, restoration strategies that include soil microbiota can improve the resilience of whole ecosystems. Fundamentally, restoration planning should identify appropriate reference target ecosystem attributes and - from the perspective of soil microbiota - comprehensibly consider potential physical, chemical and biological influences on recovery. We identify that inoculating ecologically appropriate soil microbiota into degraded environments can support a range of restoration interventions (e.g. targeted, broad-spectrum and cultured inoculations) with promising results. Such inoculations however are currently underutilised and knowledge gaps persist surrounding successful establishment in light of community dynamics, including priority effects and community coalescence. We show how the ecological trajectories of restoration sites can be assessed by characterising microbial diversity, composition, and functions in the soil. Ultimately, we highlight practical ways to apply the soil microbiota toolbox across the planning, intervention, and monitoring stages of ecosystem restoration and address persistent open questions at each stage. With continued collaborations between researchers and practitioners to address knowledge gaps, these approaches can improve current restoration practices and ecological outcomes.

Microeukaryote community coalescence strengthens community stability and elevates diversity

Mixing of entire microbial communities represents a frequent, yet understudied phenomenon. Here, we mimicked estuarine condition in a microcosm experiment by mixing a freshwater river community with a brackish sea community and assessed the effects of both environmental and community coalescences induced by varying mixing processes on microeukaryotic communities. Signs of shifted community composition of coalesced communities towards the sea parent community suggest asymmetrical community coalescence outcome, which, in addition, was generally less impacted by environmental coalescence. Community stability, inferred from community cohesion, differed among river and sea parent communities, and increased following coalescence treatments. Generally, community coalescence increased alpha diversity and promoted competition from the introduction (or emergence) of additional (or rare) species. These competitive interactions in turn had community stabilizing effect as evidenced by the increased proportion of negative cohesion. The fate of microeukaryotes was influenced by mixing ratios and frequencies (i.e. one-time versus repeated coalescence). Namely, diatoms were negatively impacted by coalescence, while fungi, ciliates, and cercozoans were promoted to varying extents, depending on the mixing ratios of the parent communities. Our study suggests that the predictability of coalescence outcomes was greater when the sea parent community dominated the final community, and this predictability was further enhanced when communities collided repeatedly.

Global epistasis and the emergence of function in microbial consortia

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

Relative dispersion ratios following fecal microbiota transplant elucidate principles governing microbial migration dynamics

Microorganisms frequently migrate from one ecosystem to another. Yet, despite the potential importance of this process in modulating the environment and the microbial ecosystem, our understanding of the fundamental forces that govern microbial dispersion is still lacking. Moreover, while theoretical models and in-vitro experiments have highlighted the contribution of species interactions to community assembly, identifying such interactions in vivo, specifically in communities as complex as the human gut, remains challenging. To address this gap, here we introduce a robust and rigorous computational framework, termed Relative Dispersion Ratio (RDR) analysis, and leverage data from well-characterized fecal microbiota transplant trials, to rigorously pinpoint dependencies between taxa during the colonization of human gastrointestinal tract. Our analysis identifies numerous pairwise dependencies between co-colonizing microbes during migration between gastrointestinal environments. We further demonstrate that identified dependencies agree with previously reported findings from in-vitro experiments and population-wide distribution patterns. Finally, we explore metabolic dependencies between these taxa and characterize the functional properties that facilitate effective dispersion. Collectively, our findings provide insights into the principles and determinants of community dynamics following ecological translocation, informing potential opportunities for precise community design.

High immigration rates critical for establishing emigration-driven diversity in microbial communities

Unraveling the mechanisms governing the diversity of ecological communities is a central goal in ecology. Although microbial dispersal constitutes an important ecological process, the effect of dispersal on microbial diversity is poorly understood. Here, we sought to fill this gap by combining a generalized Lotka-Volterra model with experimental investigations. Our model showed that emigration increases the diversity of the community when the immigration rate crosses a defined threshold, which we identified as Ineutral. We also found that at high immigration rates, emigration weakens the relative abundance of fast-growing species and thus enhances the mass effect and increases the diversity. We experimentally confirmed this finding using co-cultures of 20 bacterial strains isolated from the soil. Our model further showed that Ineutral decreases with the increase of species pool size, growth rate, and interspecies interaction. Our work deepens the understanding of the effects of dispersal on the diversity of natural communities.

Les Houches Lectures on Community Ecology: From Niche Theory to Statistical Mechanics

Ecosystems are among the most interesting and well-studied examples of self-organized complex systems. Community ecology, the study of how species interact with each other and the environment, has a rich tradition. Over the last few years, there has been a growing theoretical and experimental interest in these problems from the physics and quantitative biology communities. Here, we give an overview of community ecology, highlighting the deep connections between ecology and statistical physics. We start by introducing the two classes of mathematical models that have served as the workhorses of community ecology: Consumer Resource Models (CRM) and the generalized Lotka-Volterra models (GLV). We place a special emphasis on graphical methods and general principles. We then review recent works showing a deep and surprising connection between ecological dynamics and constrained optimization. We then shift our focus by analyzing these same models in "high-dimensions" (i.e. in the limit where the number of species and resources in the ecosystem becomes large) and discuss how such complex ecosystems can be analyzed using methods from the statistical physics of disordered systems such as the cavity method and Random Matrix Theory.

Toward an integrative framework for microbial community coalescence

Community coalescence is defined as the mixing of intact ecological communities. From river confluences to fecal microbiota transplantation, community coalescence constitutes a common ecological occurrence affecting natural and engineered microbial systems. In this opinion article, we propose an integrative framework for microbial community coalescence to guide advances in our understanding of this important - yet underexplored - ecological phenomenon. We start by aligning community coalescence with the unified framework of biological invasion and enumerate commonalities and idiosyncrasies between these two analogous processes. Then, we discuss how organismal interactions and cohesive establishment affect coalescence outcomes with direct implications for community functioning. Last, we propose the use of ecological null modeling to study the interplay of ecological processes structuring community reassembly following coalescence.

Metagenomics-assembled analysis revealed the characteristics of antibiotic resistome and community coalescence in the soils irrigated with different irrigation materials

Antibiotic resistance has received widespread attention in recent years. Soil irrigation and fertilization are routine agricultural practices, but also lead to the spread of antibiotic resistance genes (ARGs) in soil-crop system such as via resistome coalescence. Despite community coalescence being ubiquitous and important in natural ecosystems, little research has been done to investigate resistome coalescence during soil irrigation activities. In this study, the characteristics of antibiotic resistome and community coalescence in the soils irrigated with different irrigation materials (wastewater, wastewater-river water, and wastewater-manure) have been revealed by utilizing microcosm experiments and high-throughput sequencing-based metagenomic assembly approaches. Results showed irrigation and coalescence changed soil quality and resistome. Totally, 789 unique ARGs were identified in the irrigation system, including some emerging ARGs. The abundance and diversity of ARGs increased in the coalesced soils, mainly due to the newly imported ARGs from irrigation materials. Relatively, the soils irrigated with wastewater and manure showed higher level of ARGs. Irrigation with the mixtures containing river water caused greater loss of indigenous taxa, while the community structure of mixing treatment with manure changed more dramatically. Interestingly, the succession of community in coalesced soils was influenced by transient competition for resources and ecological niche width, and the highest abundance and diversity of microorganisms and ARGs were found in the initial phase of coalescence, followed by a gradual succession towards the original community. With increasement of wastewater in the irrigation materials, the soil community showed a stepwise change rather than linear change. Notably, natural deposit of irrigation materials reduced their impacts on the ARGs in the coalesced soils. Findings provide new insights into the resistome coalescence during agricultural practices for reducing the spread risks of ARGs.

Drivers and consequences of microbial community coalescence

Microbial communities are undergoing unprecedented dispersion and amalgamation across diverse ecosystems, thereby exerting profound and pervasive influences on microbial assemblages and ecosystem dynamics. This review delves into the phenomenon of community coalescence, offering an ecological overview that outlines its four-step process and elucidates the intrinsic interconnections in the context of community assembly. We examine pivotal mechanisms driving community coalescence, with a particular emphasis on elucidating the fates of both source and resident microbial communities and the consequential impacts on the ecosystem. Finally, we proffer recommendations to guide researchers in this rapidly evolving domain, facilitating deeper insights into the ecological ramifications of microbial community coalescence.

Metaphors as design tools for microbial consortia: An analysis of recent peer-reviewed literature

Single engineered microbial species cannot always conduct complex transformations, while complex, incompletely defined microbial consortia have heretofore been suited to a limited range of tasks. As biodesigners bridge this gap with intentionally designed microbial communities, they will, intentionally or otherwise, build communities that embody particular ideas about what microbial communities can and should be. Here, we suggest that metaphors-ideas about what microbial communities are like-are therefore important tools for designing synthetic consortia-based bioreactors. We identify a range of metaphors currently employed in peer-reviewed microbiome research articles, characterizing each through its potential structural implications and distinctive imagery. We present this metaphor catalogue in the interest of, first, making metaphors visible as design choices, second, enabling deliberate experimentation with them towards expanding the potential design space of the field, and third, encouraging reflection on the goals and values they embed.

Predicting bacterial interaction outcomes from monoculture growth and supernatant assays

How to derive principles of community dynamics and stability is a central question in microbial ecology. Bottom-up experiments, in which a small number of bacterial species are mixed, have become popular to address it. However, experimental setups are typically limited because co-culture experiments are labor-intensive and species are difficult to distinguish. Here, we use a four-species bacterial community to show that information from monoculture growth and inhibitory effects induced by secreted compounds can be combined to predict the competitive rank order in the community. Specifically, integrative monoculture growth parameters allow building a preliminary competitive rank order, which is then adjusted using inhibitory effects from supernatant assays. While our procedure worked for two different media, we observed differences in species rank orders between media. We then parameterized computer simulations with our empirical data to show that higher order species interactions largely follow the dynamics predicted from pairwise interactions with one important exception. The impact of inhibitory compounds was reduced in higher order communities because their negative effects were spread across multiple target species. Altogether, we formulated three simple rules of how monoculture growth and supernatant assay data can be combined to establish a competitive species rank order in an experimental four-species community.

Re-considering and designing microbiomes for future waste biorefinery

It is an increasingly promising research direction using microbiomes to produce various chemicals in order to support people's growing need for sustainability. Currently, bottom-up constructed defined microbiomes and top-down constructed undefined microbiomes play an essential role in the fields of synthetic biology and environmental engineering, respectively. However, if we are goal-oriented and want to align scientific principles with technology and engineering in future waste biorefinery, we need to reconsider and design microbiomes interdisciplinarily. In this editorial, we briefly review the latest applications of two approaches to microbiome design (bottom-up and top-down) and the dilemmas faced in using complex waste. Consequently, we introduce the concept of 'sustainable synthetic microbiomics' to apply combined bottom-up and top-down constructed microbiomes to provide products for human needs from low-value waste. Furthermore, we outline the relatively comprehensive research contents and expected prospects based on the pressing problems. Finally, burning questions on key research contents are proposed for specific cases, hoping to provide valuable views for future microbiome biorefinery.

Biodiversity and Constrained Information Dynamics in Ecosystems: A Framework for Living Systems

The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex post adaptation, typically associated with natural selection, and its proactive counterpart, ex ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified ecosystem stability, (ii) identified correlations between some biodiversity indexes and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, it was suggested that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories-fluctuations, rapid environmental responses, and long-term changes-converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems.

Risk characteristics of resistome coalescence in irrigated soils and effect of natural storage of irrigation materials on risk mitigation

Irrigation and fertilization are the routinely agricultural practices but also cause resistome coalescence, by which the entire microbiomes from irrigation materials invade soil microbial community, to transfer antibiotic resistance genes (ARGs) in the coalesced soils. Although studies have reported the effect of irrigation or fertilization on the prevalence and spread of ARGs in soils, risk characteristics of resistome coalescence in irrigation system remain to be demonstrated and few has shown whether natural storage of irrigation materials will reduce resistance risks. To fill the gaps, two microscopic experiments were conducted for deeply exploring resistance risks in the soils irrigated with wastewater and manure fertilizer from a perspective of community coalescence by metagenomic analysis, and to reveal the effect of natural storage of irrigation materials on the reduction of resistance risks in the coalesced soils. Results showed irrigation and coalescence significantly increased the abundance and diversity of ARGs in the soils, and introduced some emerging resistance genes into the coalesced community, including mcr-type, tetX, qacB, and an array of genes conferring resistance to carbapenem. Procrustes analysis demonstrated microbial community was significantly correlated with the ARGs in coalesced soils, and variance partitioning analysis quantified its dominant role on shaping resistome profile in the environment. Besides ARGs, abundant and diverse mobile genetic elements (MGEs) were also identified in the coalesced soils and co-existed on the ARG-carrying contigs, implying potential transfer risk of ARGs in the irrigation system. Further, the analysis of metagenome-assembled genomes (MAGs) confirmed the risk by recovering 358 ARGs-carrying MAGs and identifying the resistant bacteria that co-carried multiple ARGs and MGEs. As expected, the natural storage of irrigation water and manure fertilizer reduced about 27%-54% of ARGs, MGEs and virulence factors in the coalesced soils, thus caused the soils to move towards lower resistance risks to a certain extent.

Microcosm experiments revealed resistome coalescence of sewage treatment plant effluents in river environment

Sewage treatment plant (STP) effluents are important contributors of antibiotic resistance (AR) pollution in rivers. Effluent discharging into rivers causes resistome coalescence. However, their mechanisms and dynamic processes are poorly understood, especially for the effects of dilution, diffusion, and sunlight-induced attenuation on coalescence. In this study, we have constructed microcosmic experiments based on in-situ investigation to explore these issues. The first batch experiment revealed the effects of dilution and diffusion. The coverage of water coalesced resistomes ranged 66.26∼152.18 × /Gb and was positively correlated with effluent volume (Mann-Kendall test, p < 0.01). Principal coordinate analysis (PCoA) and source tracking analysis demonstrated that dilution and diffusion stepwise reduced AR pollution. The second batch experiment explored the temporal dynamics and sunlight attenuation on coalesced resistomes. Under natural light, the coverage and diversity of water resistomes posed decreasing trends, primarily attributed to drastic erasure of effluent traces. The proportion of effluent-specific ARGs in coalesced resistomes significantly declined over time (Spearman's r = -0.83 and -0.94 in coverage and richness). While under dark condition, the coverage and diversity increased. Sunlight radiation intensified the interactions between water and sediment resistomes, as evidenced by more shared ARGs and less dissimilarities across niches. Network analysis, metagenome-assembled genome (MAG) analysis and variation partitioning analysis (VPA) showed that microbiome controlled resistome coalescence, explaining 56.5% and 58.4% of resistomes in water and sediment, respectively. Biotic and abiotic factors synergistically explained 40% of water resistomes. This study offers a comprehensive understanding of AR transmission and provides theoretical bases for grasping AR pollution and developing effective suppression strategies.

Statistically learning the functional landscape of microbial communities

Microbial consortia exhibit complex functional properties in contexts ranging from soils to bioreactors to human hosts. Understanding how community composition determines function is a major goal of microbial ecology. Here we address this challenge using the concept of community-function landscapes-analogues to fitness landscapes-that capture how changes in community composition alter collective function. Using datasets that represent a broad set of community functions, from production/degradation of specific compounds to biomass generation, we show that statistically inferred landscapes quantitatively predict community functions from knowledge of species presence or absence. Crucially, community-function landscapes allow prediction without explicit knowledge of abundance dynamics or interactions between species and can be accurately trained using measurements from a small subset of all possible community compositions. The success of our approach arises from the fact that empirical community-function landscapes appear to be not rugged, meaning that they largely lack high-order epistatic contributions that would be difficult to fit with limited data. Finally, we show that this observation holds across a wide class of ecological models, suggesting community-function landscapes can be efficiently inferred across a broad range of ecological regimes. Our results open the door to the rational design of consortia without detailed knowledge of abundance dynamics or interactions.

Influence of metabolic guilds on a temporal scale in an experimental fermented food derived microbial community

The influence of community diversity, which can be measured at the level of metabolic guilds, on community function is a central question in ecology. Particularly, the long-term temporal dynamic between a community's function and its diversity remains unclear. We investigated the influence of metabolic guild diversity on associated community function by propagating natural microbial communities from a traditionally fermented milk beverage diluted to various levels. Specifically, we assessed the influence of less abundant microbial types, such as yeast, on community functionality and bacterial community compositions over repeated propagation cycles amounting to ∼100 generations. The starting richness of metabolic guilds had a repeatable effect on bacterial community compositions, metabolic profiles, and acidity. The influence of a single metabolic guild, yeast in our study, played a dramatic role on function, but interestingly not on long-term species sorting trajectories of the remaining bacterial community. Our results together suggest an unexpected niche division between yeast and bacterial communities and evidence ecological selection on the microbial communities in our system.

Emergent cooperative behavior in transient compartments

We introduce a minimal model of multilevel selection on structured populations, considering the interplay between game theory and population dynamics. Through a bottleneck process, finite groups are formed with cooperators and defectors sampled from an infinite pool. After the fragmentation, these transient compartments grow until the maximal number of individuals per compartment is attained. Eventually, all compartments are merged and well mixed, and the whole process is repeated. We show that cooperators, even if interacting only through mean-field intragroup interactions that favor defectors, may perform well because of the intergroup competition and the size diversity among the compartments. These cycles of isolation and coalescence may therefore be important in maintaining diversity among different species or strategies and may help to understand the underlying mechanisms of the scaffolding processes in the transition to multicellularity.

The ecology of scale: impact of volume on coalescence and function in methanogenic communities

Engineered ecosystems span multiple volume scales, from a nano-scale to thousands of cubic metres. Even the largest industrial systems are tested in pilot scale facilities. But does scale affect outcomes? Here we look at comparing different size laboratory anaerobic fermentors to see if and how the volume of the community affects the outcome of community coalescence (combining multiple communities) on community composition and function. Our results show that there is an effect of scale on biogas production. Furthermore, we see a link between community evenness and volume, with smaller scale communities having higher evenness. Despite those differences, the overall patterns of community coalescence are very similar at all scales, with coalescence leading to levels of biogas production comparable with that of the best-performing component community. The increase in biogas with increasing volume plateaus, suggesting there is a volume where productivity stays stable over large volumes. Our findings are reassuring for ecologists studying large ecosystems and industries operating pilot scale facilities, as they support the validity of pilot scale studies in this field.

Antibiotic resistance in bacterial communities

Bacteria are single-celled organisms, but the survival of microbial communities relies on complex dynamics at the molecular, cellular, and ecosystem scales. Antibiotic resistance, in particular, is not just a property of individual bacteria or even single-strain populations, but depends heavily on the community context. Collective community dynamics can lead to counterintuitive eco-evolutionary effects like survival of less resistant bacterial populations, slowing of resistance evolution, or population collapse, yet these surprising behaviors are often captured by simple mathematical models. In this review, we highlight recent progress - in many cases, advances driven by elegant combinations of quantitative experiments and theoretical models - in understanding how interactions between bacteria and with the environment affect antibiotic resistance, from single-species populations to multispecies communities embedded in an ecosystem.

Emergent coexistence in multispecies microbial communities

Understanding the mechanisms that maintain microbial biodiversity is a critical aspiration in ecology. Past work on microbial coexistence has largely focused on species pairs, but it is unclear whether pairwise coexistence in isolation is required for coexistence in a multispecies community. To address this question, we conducted hundreds of pairwise competition experiments among the stably coexisting members of 12 different enrichment communities in vitro. To determine the outcomes of these experiments, we developed an automated image analysis pipeline to quantify species abundances. We found that competitive exclusion was the most common outcome, and it was strongly hierarchical and transitive. Because many species that coexist within a stable multispecies community fail to coexist in pairwise co-culture under identical conditions, we concluded that multispecies coexistence is an emergent phenomenon. This work highlights the importance of community context for understanding the origins of coexistence in complex ecosystems.

Prokaryotic community interchange between distinct microhabitats causes community pressure on anammox biofilm development

Biofilms are an efficient way to underpin the biological process of wastewater treatment. However, little is known about the driving forces of biofilm formation and development in industrial settings. Long-term observation of anammox biofilms indicated the interplay between different microhabitats (biofilm, aggregate, plankton) was important in sustaining biofilm formation. SourceTracker analysis showed that 88.77 ± 2.26% of initial biofilm originated from the aggregate, however, independent evolution was led by anammox species in the later stage (182d and 245d). Noticeably, the source proportion of aggregate and plankton increased when temperature varied, suggesting an interchange of species between different microhabitats could be helpful to biofilm recovery. The microbial interaction pattern and community variation displayed similar trends, but the unknown source proportion of interaction was very high during the entire incubation (7-245d), thereby the same species may develop different relationships within the distinct microhabitats. The core phyla, Proteobacteria and Bacteroidota, accounted for ∼80% of interactions in all lifestyles, which is consistent with the fact that Bacteroidota played important role in the early stage of biofilm assembly. Although anammox species evolved few links with other OTUs, Candidatus Brocadiaceae still outcompeted the NS9 marine group to dominate the homogeneous selection process in the later stage (56-245d) of biofilm assembly, implying that the functional species may be decoupled from the core species in the microbial network. The conclusions will shed a light on the understanding of biofilm development in large-scale biosystems of wastewater treatment.

Non-gene-editing microbiome engineering of spontaneous food fermentation microbiota-Limitation control, design control, and integration

Non-gene-editing microbiome engineering (NgeME) is the rational design and control of natural microbial consortia to perform desired functions. Traditional NgeME approaches use selected environmental variables to force natural microbial consortia to perform the desired functions. Spontaneous food fermentation, the oldest kind of traditional NgeME, transforms foods into various fermented products using natural microbial networks. In traditional NgeME, spontaneous food fermentation microbiotas (SFFMs) are typically formed and controlled manually by the establishment of limiting factors in small batches with little mechanization. However, limitation control generally leads to trade-offs between efficiency and the quality of fermentation. Modern NgeME approaches based on synthetic microbial ecology have been developed using designed microbial communities to explore assembly mechanisms and target functional enhancement of SFFMs. This has greatly improved our understanding of microbiota control, but such approaches still have shortcomings compared to traditional NgeME. Here, we comprehensively describe research on mechanisms and control strategies for SFFMs based on traditional and modern NgeME. We discuss the ecological and engineering principles of the two approaches to enhance the understanding of how best to control SFFM. We also review recent applied and theoretical research on modern NgeME and propose an integrated in vitro synthetic microbiota model to bridge gaps between limitation control and design control for SFFM.

Maximal ecological diversity exceeds evolutionary diversity in model ecosystems

Understanding community saturation is fundamental to ecological theory. While investigations of the diversity of evolutionary stable states (ESSs) are widespread, the diversity of communities that have yet to reach an evolutionary endpoint is poorly understood. We use Lotka-Volterra dynamics and trait-based competition to compare the diversity of randomly assembled communities to the diversity of the ESS. We show that, with a large enough founding diversity (whether assembled at once or through sequential invasions), the number of long-time surviving species exceeds that of the ESS. However, the excessive founding diversity required to assemble a saturated community increases rapidly with the dimension of phenotype space. Additionally, traits present in communities resulting from random assembly are more clustered in phenotype space compared to random, although still markedly less ordered than the ESS. By combining theories of random assembly and ESSs we bring a new viewpoint to both the saturation and random assembly literature.

Ecological Drivers of Community Cohesion

From protocellular to societal, networks of living systems are complex and multiscale. Discerning the factors that facilitate assembly of these intricate interdependencies using pairwise interactions can be nearly impossible. To facilitate a greater understanding, we developed a mathematical and computational model based on a synthetic four-strain Saccharomyces cerevisiae interdependent system. Specifically, we aimed to provide a greater understanding of how ecological factors influence community dynamics. By leveraging transiently structured ecologies, we were able to drive community cohesion. We show how ecological interventions could reverse or slow the extinction rate of a cohesive community. An interconnected system first needs to persist long enough to be a subject of natural selection. Our emulation of Darwin's "warm little ponds" with an ecology governed by transient compartmentalization provided the necessary persistence. Our results reveal utility across scales of organization, stressing the importance of cyclic processes in major evolutionary transitions, engineering of synthetic microbial consortia, and conservation biology. IMPORTANCE We are facing unprecedented disruption and collapse of ecosystems across the globe. To have any hope of mitigating this phenomenon, a much greater understanding of ecosystem dynamics is required. However, ecosystems are typically composed of highly dynamic networks of individual species. These interactions are further modulated by abiotic and biotic factors that vary temporally and spatially. Thus, ecological dynamics are obfuscated by this complexity. Here, we developed a theoretical model, informed by a synthetic experimental system, of Darwin's "warm little ponds." This cycling four-species system seeks to elucidate the ecological factors that drive or inhibit interaction. We show that these factors could provide an essential tool for avoiding the accelerating ecological collapse. Our study also provides a starting point to develop a more encompassing model to inform conservation efforts.

Enhancing plant growth promoting rhizobacterial activities through consortium exposure: A review

Plant Growth Promoting Rhizobacteria (PGPR) has gained immense importance in the last decade due to its in-depth study and the role of the rhizosphere as an ecological unit in the biosphere. A putative PGPR is considered PGPR only when it may have a positive impact on the plant after inoculation. From the various pieces of literature, it has been found that these bacteria improve the growth of plants and their products through their plant growth-promoting activities. A microbial consortium has a positive effect on plant growth-promoting (PGP) activities evident by the literature. In the natural ecosystem, rhizobacteria interact synergistically and antagonistically with each other in the form of a consortium, but in a natural consortium, there are various oscillating environmental conditions that affect the potential mechanism of the consortium. For the sustainable development of our ecological environment, it is our utmost necessity to maintain the stability of the rhizobacterial consortium in fluctuating environmental conditions. In the last decade, various studies have been conducted to design synthetic rhizobacterial consortium that helps to integrate cross-feeding over microbial strains and reveal their social interactions. In this review, the authors have emphasized covering all the studies on designing synthetic rhizobacterial consortiums, their strategies, mechanism, and their application in the field of environmental ecology and biotechnology.

Self-consistent dispersal puts tight constraints on the spatiotemporal organization of species-rich metacommunities

Biodiversity is often attributed to a dynamic equilibrium between the immigration and extinction of species. This equilibrium forms a common basis for studying ecosystem assembly from a static reservoir of migrants-the mainland. Yet, natural ecosystems often consist of many coupled communities (i.e., metacommunities), and migration occurs between these communities. The pool of migrants then depends on what is sustained in the ecosystem, which, in turn, depends on the dynamic migrant pool. This chicken-and-egg problem of survival and dispersal is poorly understood in communities of many competing species, except for the neutral case-the "unified neutral theory of biodiversity." Employing spatiotemporal simulations and mean-field analyses, we show that self-consistent dispersal puts rather tight constraints on the dynamic migration-extinction equilibrium. When the number of species is large, species are pushed to the edge of their global extinction, even when competition is weak. As a consequence, the overall diversity is highly sensitive to perturbations in demographic parameters, including growth and dispersal rates. When dispersal is short range, the resulting spatiotemporal abundance patterns follow broad scale-free distributions that correspond to a directed percolation phase transition. The qualitative agreement of our results for short-range and long-range dispersal suggests that this self-organization process is a general property of species-rich metacommunities. Our study shows that self-sustaining metacommunities are highly sensitive to environmental change and provides insights into how biodiversity can be rescued and maintained.