Context-dependent dynamics lead to the assembly of functionally distinct microbial communities

Complex interplay between the microalgae and their microbiome in production raceways

Algae-associated microbiomes are underexplored, limiting our understanding of their influence on the large-scale microalgae reactors. Over two 8-month periods, microbial dynamics were monitored three times per week in two microalgae raceways inoculated with Desmodesmus armatus. One reactor received wastewater, while the other used clean water and fertilizers. The sampled culture volume was filtered into pico and nano size fractions before DNA extraction. Metabarcoding of the 18S and 16S rRNA genes revealed a high microbial diversity across the two time series and a complex eukaryotic and prokaryotic community growing alongside the microalga. Chlorophyta and Fungi were the dominant eukaryotic groups, while Alphaproteobacteria, Gammaproteobacteria, Actinobacteria, and Bacteroidia dominated the prokaryotic communities. Contrasting Amplicon Sequence Variants (ASVs) were found between healthy (D. armatus abundance > 70 %) and unhealthy (D. armatus abundance 10-20 %) conditions across reactors and time series. Network analysis identified up to 10 potential ecological interactions among D. armatus and its microbiome, predominantly positive. Specific ASVs associated with a healthy condition were positively correlated with D. armatus, while other ASVs linked to an unhealthy condition were negatively correlated. Potentially pathogenic bacteria included Mycobacterium and Flavobacterium, whereas potentially beneficial taxa included Geminocystis, Thiocapsa, Ahniella, and Bosea. Several fungal ASVs showed context-specific associations, whereas specific fungi such as Paraphelidium tribonemae, Aphelidium parallelum, Aphelidium desmodesmi, Aphelidiomycota sp., Rozellomycota sp., and Rhizophidium sp, were identified as potentially harmful. This study reveals the striking diversity and complexity of microalgae-associated microbiomes within raceways, providing valuable insights for optimizing industrial production processes, particularly for wastewater treatment and sustainable green biomass generation.

Macroecological patterns in experimental microbial communities

Ecology has historically benefited from the characterization of statistical patterns of biodiversity within and across communities, an approach known as macroecology. Within microbial ecology, macroecological approaches have identified universal patterns of diversity and abundance that can be captured by effective models. Experimentation has simultaneously played a crucial role, as the advent of high-replication community time-series has allowed researchers to investigate underlying ecological forces. However, there remains a gap between experiments performed in the laboratory and macroecological patterns documented in natural systems, as we do not know whether these patterns can be recapitulated in the lab and whether experimental manipulations produce macroecological effects. This work aims at bridging the gap between experimental ecology and macroecology. Using high-replication time-series, we demonstrate that microbial macroecological patterns observed in nature exist in a laboratory setting, despite controlled conditions, and can be unified under the Stochastic Logistic Model of growth (SLM). We found that demographic manipulations (e.g., migration) impact observed macroecological patterns. By modifying the SLM to incorporate said manipulations alongside experimental details (e.g., sampling), we obtain predictions that are consistent with macroecological outcomes. By combining high-replication experiments with ecological models, microbial macroecology can be viewed as a predictive discipline.

Urbanization leads to asynchronous homogenization of soil microbial communities across biomes

Soil bacterial and fungal communities play fundamental roles in biogeochemical cycles and ecosystem stability. Urbanization alters soil properties and microbial habitats, driving shifts in community composition, yet the divergent responses of bacteria and fungi and their ecological consequences remain inadequately understood. To elucidate these differential responses, we investigated soil bacterial and fungal communities along an urbanization gradient, ranging from undisturbed reference forests to urban parks, across three distinct climatic regions. To capture different disturbance intensities, urban parks were classified by tree age into old parks (>60-year-old trees) and young parks (10-20-year-old trees). Climate had a strong influence on soil microbiota, yet urbanization still significantly altered both bacterial and fungal communities in all regions. Urban disturbances homogenized soil microbial communities: average similarity among bacterial communities increased from ∼79 % in forests to ∼85 % in young urban parks, indicating substantial homogenization, whereas fungal communities showed little homogenization. Urbanization also homogenized microbial functional traits, with a greater reduction in trait dissimilarity for bacteria than for fungi. Bacterial communities exhibited high adjustability to urban conditions, dominated by generalist taxa (∼90 %), whereas fungal communities consisted mostly of specialists (∼83 %). Despite these asynchronous responses-bacteria adjusting and homogenizing more than fungi-overlapping functional traits between bacteria and fungi help maintain functional resilience in urban ecosystems.

Paradox of the Sub-Plankton: Plausible Mechanisms and Open Problems Underlying Strain-Level Diversity in Microbial Communities

Microbial communities are often complex and highly diverse, typically with dozens of species sharing spatially-restricted environments. Within these species, genetic and ecological variation often exists at a much finer scale, with closely related strains coexisting and competing. While the coexistence of strains in communities has been heavily explored over the past two decades, we have no self-consistent theory of how this diversity is maintained. This question challenges our conventional understanding of ecological coexistence, typically framed around species with clear phenotypic and ecological differences. In this review, we synthesise plausible mechanisms underlying strain-level diversity (termed microdiversity), focusing on niche-based mechanisms such as nutrient competition, neutral mechanisms such as migration, and evolutionary mechanisms such as horizontal gene transfer. We critically assess the strengths and caveats of these mechanisms, acknowledging key gaps that persist in linking genetic similarity to ecological divergence. Finally, we highlight how the origin and maintenance of microdiversity could pose a major challenge to conventional ecological thinking. We articulate a call-to-arms for a dialogue between well-designed experiments and new theoretical frameworks to address this grand conceptual challenge in understanding microbial biodiversity.

The invisible architects: microbial communities and their transformative role in soil health and global climate changes

During the last decades, substantial advancements have been made in identifying soil characteristics that impact the composition of the soil microbiome. However, the impacts of microorganisms on their respective soil habitats have received less attention, with the majority of prior research focusing on the contributions of microbes to the dynamics of soil carbon and nitrogen. Soil microbiome plays a critical role in soil habitats by influencing soil fertility, crop yields, and biotic and abiotic stress tolerance. In addition to their roles in nutrient cycling and organic matter transformations, soil microorganisms affect the soil environment via many biochemical and biophysical mechanisms. For instance, the soil microbiome plays an essential role in soil mechanical stability and pore connectivity and regulates the flow of nutrients, oxygen, and water. Similarly, soil microbiomes perform various critical functions in an ecosystem, which leads to carbon stabilization for a long time and could serve as microbiome engineering targets for global climate change mitigation. In this review, considering soil structure, hydrology, and chemistry, we outline how microorganisms alter the soil ecosystem. Further, this study investigates the mechanisms by which feedback loops can be generated between microorganisms and soil. Moreover, we analyze the potential of microbially mediated modifications of soil properties as a viable strategy to address soil threats and global climate challenges. In addition, the current study propose a deep learning-based approach to develop a synthetic microbial consortium to improve soil health and mitigate climate change.

Caenorhabditis nematodes influence microbiome and metabolome characteristics of their natural apple substrates over time

The microbiomes of host organisms and their direct source environments are closely linked and key for shaping microbial community dynamics. The relationship between these linked dynamics is largely unexplored because source substrates are usually unavailable. To address this current knowledge gap, we employed bacteriovorous Caenorhabditis nematodes as a unique model system, for which source substrates like rotting apples can be easily collected. We compared single host microbiomes with their corresponding apple source substrates, as well as nematode-free substrates, over a 2-year sampling period in the botanical garden in Kiel, Germany. We found that single worms have unique microbiomes, which overlap most strongly with nematodes from the same source apple. A comparison to previous, related work revealed that variation in microbiome composition of natural Caenorhabditis isolates is significantly influenced by the substrate type, from which worms were obtained (e.g., fruits or compost). Our current sampling further showed that microbiome assembly is mostly driven by dispersal limitation. Importantly, two independent analysis approaches consistently suggest that worm microbiomes significantly influence characteristics of the apple microbiomes, possibly indicating niche construction by nematodes. Moreover, combining apple microbiome and metabolome data, we identified individual microbes and specific compounds indicative of fruit ripening that are significantly associated with nematode presence. In conclusion, our study elucidates the complex relationship between host microbiomes and their directly connected substrate microbiomes. Our analyses underscore the significant influence of nematode microbiomes on shaping the apple microbiome and, consequently, the fruit's metabolic capacity, thereby enhancing our general understanding of host-microbiome interactions in their natural habitat.IMPORTANCEAlmost all complex organisms are host to a microbial community, the microbiome. This microbiome can influence diverse host functions, such as food processing, protection against parasites, or development. The relationship between host and microbiome critically depends on the assembly of the microbial community, which may be shaped by microbes in the directly linked environment, the source microbiome. This assembly process is often not well understood because of the unavailability of source substrates. Here, we used Caenorhabditis nematodes as a model system that facilitates a direct comparison of host and source microbiomes. Based on a 2-year sampling period, we identified (i) a clear link between assembly dynamics of host and source microbiomes, (ii) a significant influence of nematode microbiomes on apple microbiomes, and (iii) specific microbes and compounds that are associated with the presence of nematodes in the sampled substrates. Overall, our study enhances our understanding of microbiome assembly dynamics and resulting functions.

Small molecule metabolites drive plant rhizosphere microbial community assembly patterns

The assembly of rhizosphere microbial communities is essential for maintaining plant health, yet it is influenced by a wide range of biotic and abiotic factors. The key drivers shaping the composition of these communities, however, remain poorly understood. In this study, we analyzed 108 plant samples and evaluated root traits, plant growth characteristics, soil enzyme activities, rhizosphere metabolites, and soil chemical properties to identify the primary determinants of rhizosphere community assembly. Across 36 soil samples, we obtained 969,634 high-quality sequences, clustering into 6,284 ASVs predominantly classified into Proteobacteria (57.99%), Actinobacteria (30%), and Bacteroidetes (5.13%). Our findings revealed that rhizosphere metabolites accounted for more variance in microbial community composition compared to chemical properties (ANOVA, F = 1.53, p = 0.04), enzyme activities, or root traits (ANOVA, F = 1.04, p = 0.001). Seven small molecule metabolites, including glycerol, sorbitol, phytol, and alpha-ketoglutaric acid, were significantly correlated with βNTI, underscoring their role as critical drivers of microbial community assembly. The genus Rhizobium, significantly associated with βNTI (R = 0.25, p = 0.009), emerged as a keystone taxon shaping community structure. Soil culture experiments further validated that small molecule metabolites can modulate microbial community assembly. The ST treatment, enriched with these metabolites, produced 1,032,205 high-quality sequences and exhibited significant shifts in community composition (Adonis, p = 0.001, R = 0.463), with Rhizobium showing higher abundance compared to the control (CK). Variable selection (βNTI >2) drove phylogenetic turnover in ST, while stochastic processes (|βNTI| < 2) dominated in CK. This study provides quantitative insights into the role of rhizosphere metabolites in shaping microbial community assembly and highlights their potential for targeted modulation of rhizosphere microbiomes.

Functional microbiome assembly in food environments: addressing sustainable development challenges

The global food system faces numerous challenges, creating an urgent need for sustainable reform. Functional microbiome assemblies offer transformative potential by endowing microbial foods with diverse, beneficial characteristics. These assemblies can dynamically influence specific food systems, positioning them as a promising approach for reshaping food production. However, the current applications and types of microbiome assemblies in foods remain limited, with a lack of effective screening and regulatory methods. This review introduces the functions and practical approaches for implementing microbiome assemblies in food systems alongside future directions for enhancing their applications. Several ecological studies evaluated how to regulate functional output and revealed that environmental conditions, which shape the niche for species survival, significantly influenced the functional output of microbiomes. Building on this theoretical foundation, this review presents a model for functional output comprising niche conditions, functional gene codes, and corresponding functional outputs. This model is illustrated with examples to explore sustainable applications and regulatory mechanisms for functional microbiome assemblies. By highlighting the roles of functional outputs in food systems and examining the potential for food environments to induce and modulate microbiome functions, this review provides a roadmap to address emerging challenges in food sustainability.

Bacterial community function increases leaf growth in a pitcher plant experimental system

Across diverse ecosystems, bacteria and their hosts engage in complex relationships having negative, neutral, or positive interactions. However, the specific effects of leaf-associated bacterial community functions on plant growth are poorly understood. Although microbes can promote plant growth through various biochemical mechanisms, investigating the community's functional contributions to plant growth remains to be explored. To address this gap, we characterized the relationships between bacterial community function and host plant growth in the purple pitcher plant (Sarracenia purpurea). The main aim of our research was to investigate how different bacterial community functions affect the growth and nutrient content in the plant. Previous research has suggested that microbial communities aid in prey decomposition and subsequent nutrient acquisition in carnivorous plants, including S. purpurea. However, the specific functional roles of bacterial communities in plant growth and nutrient uptake are not well known. In this study, sterile, freshly opened pitchers were inoculated with three functionally distinct, pre-assembled bacterial communities. Bacterial community composition and function were measured over 8 weeks using physiological assays, metagenomics, and metatranscriptomics. Distinct community functions affected plant traits; a bacterial community enriched in decomposition was associated with larger leaves with almost double the biomass of control pitchers. Physiological differences in bacterial communities were supported by metatranscriptomics; for example, the bacterial community with the highest chitinase activity had greater expression of transcripts associated with chitinase enzymes. The relationship between bacterial community function and plant growth observed here indicates potential mechanisms, such as chitinase activity, for host-associated bacterial functions to support pitcher plant growth.

IMPORTANCE

This study addresses a gap in understanding the relationships between bacterial community function and plant growth. We inoculated sterile, freshly opened pitcher plant leaves with three functionally distinct bacterial communities to uncover potential mechanisms through which bacterial functions support plant health and growth. Our findings demonstrate that distinct community functions significantly influence plant traits, with some bacterial communities supporting more plant growth than in control pitchers. These results highlight the ecological roles of microbial communities in plants and thus ecosystems and suggest that nutrient cycling is an important pathway through which microbes support host plant health. This research provides valuable insights into plant-microbe interactions and the effects of diverse microbial community functions.

Characterizing a stable five-species microbial community for use in experimental evolution and ecology

Model microbial communities are regularly used to test ecological and evolutionary theory as they are easy to manipulate and have fast generation times, allowing for large-scale, high-throughput experiments. A key assumption for most model microbial communities is that they stably coexist, but this is rarely tested experimentally. Here we report the (dis)assembly of a five-species microbial community from a metacommunity of soil microbes that can be used for future experiments. Using reciprocal invasion-from-rare experiments we show that all species can coexist and we demonstrate that the community is stable for a long time (~600 generations). Crucially for future work, we show that each species can be identified by their plate morphologies, even after >1 year in co-culture. We characterise pairwise species interactions and produce high-quality reference genomes for each species. This stable five-species community can be used to test key questions in microbial ecology and evolution.

Metabolic complexity drives divergence in microbial communities

Microbial communities are shaped by environmental metabolites, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. Here we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but they diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively simpler ones that then participate in cross-feeding between community members, is necessary and sufficient to recapitulate our experimental observations. In addition to helping understand the role of the environment in community assembly, the divergence-complexity effect can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions towards microbiome engineering applications.

Bacteria face trade-offs in the decomposition of complex biopolymers

Although depolymerization of complex carbohydrates is a growth-limiting bottleneck for microbial decomposers, we still lack understanding about how the production of different types of extracellular enzymes affect individual microbes and in turn the performance of whole decomposer communities. In this work we use a theoretical model to evaluate the potential trade-offs faced by microorganisms in biopolymer decomposition which arise due to the varied biochemistry of different depolymerizing enzyme classes. We specifically consider two broad classes of depolymerizing extracellular enzymes, which are widespread across microbial taxa: exo-enzymes that cleave small units from the ends of polymer chains and endo-enzymes that act at random positions generating degradation products of varied sizes. Our results demonstrate a fundamental trade-off in the production of these enzymes, which is independent of system's complexity and which appears solely from the intrinsically different temporal depolymerization dynamics. As a consequence, specialists that produce either exo- or only endo-enzymes limit their growth to high or low substrate conditions, respectively. Conversely, generalists that produce both enzymes in an optimal ratio expand their niche and benefit from the synergy between the two enzymes. Finally, our results show that, in spatially-explicit environments, consortia composed of endo- and exo-specialists can only exist under oligotrophic conditions. In summary, our analysis demonstrates that the (evolutionary or ecological) selection of a depolymerization pathway will affect microbial fitness under low or high substrate conditions, with impacts on the ecological dynamics of microbial communities. It provides a possible explanation why many polysaccharide degraders in nature show the genetic potential to produce both of these enzyme classes.

Association of microbial community structure with gill disease in marine-stage farmed Atlantic salmon (Salmo salar); a yearlong study

BACKGROUND

Understanding the relationship between resident microbiota and disease in cultured fish represents an important and emerging area of study. Marine gill disorders in particular are considered an important challenge to Atlantic salmon (Salmo salar) aquaculture, however relatively little is known regarding the role resident gill microbiota might play in providing protection from or potentiating different gill diseases. Here, 16S rRNA sequencing was used to examine the gill microbiome alongside fish health screening in farmed Atlantic salmon. Results were used to explore the relationship between microbial communities and gill disease.

RESULTS

Microbial community restructuring was observed throughout the sampling period and linked to varied drivers of change, including environmental conditions and severity of gill pathology. Taxa with significantly greater relative abundance on healthier gills included isolates within genus Shewanella, and taxa within family Procabacteriaceae. In contrast, altered abundance of Candidatus Branchiomonas and Rubritalea spp. were associated with damaged gills. Interestingly, more general changes in community richness and diversity were not associated with altered gill health, and thus not apparently deleterious to fish. Gross and histological gill scoring demonstrated seasonal shifts in gill pathology, with increased severity of gill damage in autumn. Specific infectious causes that contributed to observed pathology within the population included the gill disorder amoebic gill disease (AGD), however due to the uncontrolled nature of this study and likely mixed contribution of various causes of gill disease to observed pathology results do not strongly support an association between the microbial community and specific infectious or non-infectious drivers of gill pathology.

CONCLUSIONS

Results suggest that the microbial community of farmed Atlantic salmon gills undergo continual restructuring in the marine environment, with mixed influences upon this change including environmental, host, and pathogenic factors. A significant association of specific taxa with different gill health states suggests these taxa might make meaningful indicators of gill health. Further research with more frequent sampling and deliberate manipulation of gills would provide important advancement of knowledge in this area. Overall, although much is still to be learnt regarding what constitutes a healthy or maladapted gill microbial community, the results of this study provide clear advancement of the field, providing new insight into the microbial community structure of gills during an annual production cycle of marine-stage farmed Atlantic salmon.

Higher-order interactions and emergent properties of microbial communities: The power of synthetic ecology

Humans have long relied on microbial communities to create products, produce energy, and treat waste. The microbiota residing within our bodies directly impacts our health, while the soil and rhizosphere microbiomes influence the productivity of our crops. However, the complexity and diversity of microbial communities make them challenging to study and difficult to develop into applications, as they often exhibit the emergence of unpredictable higher-order phenomena. Synthetic ecology aims at simplifying complexity by constituting synthetic or semi-natural microbial communities with reduced diversity that become easier to study and analyze. This strategy combines methodologies that simplify existing complex systems (top-down approach) or build the system from its constituent components (bottom-up approach). Simplified communities are studied to understand how interactions among populations shape the behavior of the community and to model and predict their response to external stimuli. By harnessing the potential of synthetic microbial communities through a multidisciplinary approach, we can advance knowledge of ecological concepts and address critical public health, agricultural, and environmental issues more effectively.

Connecting microbial community assembly and function

Microbial ecology is moving away from purely descriptive analyses to experiments that can determine the underlying mechanisms driving changes in community assembly and function. More species-rich microbial communities generally have higher functional capabilities depending on if there is positive selection of certain species or complementarity among different species. When building synthetic communities or laboratory enrichment cultures, there are specific choices that can increase the number of species able to coexist. Higher resource complexity or the addition of physical niches are two of the many factors leading to greater biodiversity and associated increases in functional capabilities. We can use principles from community ecology and knowledge of microbial physiology to generate improved microbiomes for use in medicine, agriculture, or environmental management.

Analysis of the northern pitcher plant (Sarracenia purpurea L.) phytotelm bacteriome throughout a temperate region growing season

The insectivorous Northern Pitcher Plant, Sarracenia purpurea, recruits a dynamic biotic community in the rainwater collected by its pitcher-shaped leaves. Insect capture and degradation within the pitcher fluid (phytotelma) has been well documented as a mechanism for supplementing the plant's nitrogen, phosphorous, and micronutrient requirements. Metagenomic studies have shown a diverse microbiome in this phytotelm environment, including taxa that contribute metabolically to prey digestion. In this investigation, we used high-throughput 16S rDNA sequencing and bioinformatics to analyze the S. purpurea phytotelm bacteriome as it changes through the growing season (May-September) in plants from the north-central region of the species' native range. Additionally, we used molecular techniques to detect and quantify bacterial nitrogenase genes (nifH) in all phytotelm samples to explore the hypothesis that diazotrophy is an additional mechanism of supplying biologically available nitrogen to S. purpurea. The results of this study indicate that while prokaryote diversity remains relatively stable in plants at different locations within our region, diversity changes significantly as the growing season progresses. Furthermore, nifH genes were detected at biologically significant concentrations in one hundred percent of samples, suggesting that nitrogen fixation may be an important contributor to the S. purpurea nutrient budget.

Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure

Climate changes significantly impact greenhouse gas emissions from wetland soil. Specifically, wetland soil may be exposed to oxygen (O2) during droughts, or to sulfate (SO42-) as a result of sea level rise. How these stressors - separately and together - impact microbial food webs driving carbon cycling in the wetlands is still not understood. To investigate this, we integrated geochemical analysis, proteogenomics, and stoichiometric modeling to characterize the impact of elevated SO42- and O2 levels on microbial methane (CH4) and carbon dioxide (CO2) emissions. The results uncovered the adaptive responses of this community to changes in SO42- and O2 availability and identified altered microbial guilds and metabolic processes driving CH4 and CO2 emissions. Elevated SO42- reduced CH4 emissions, with hydrogenotrophic methanogenesis more suppressed than acetoclastic. Elevated O2 shifted the greenhouse gas emissions from CH4 to CO2. The metabolic effects of combined SO42- and O2 exposures on CH4 and CO2 emissions were similar to those of O2 exposure alone. The reduction in CH4 emission by increased SO42- and O2 was much greater than the concomitant increase in CO2 emission. Thus, greater SO42- and O2 exposure in wetlands is expected to reduce the aggregate warming effect of CH4 and CO2. Metaproteomics and stoichiometric modeling revealed a unique subnetwork involving carbon metabolism that converts lactate and SO42- to produce acetate, H2S, and CO2 when SO42- is elevated under oxic conditions. This study provides greater quantitative resolution of key metabolic processes necessary for the prediction of CH4 and CO2 emissions from wetlands under future climate scenarios.

Intestinal colonization resistance in the context of environmental, host, and microbial determinants

Microbial communities that colonize the human gastrointestinal (GI) tract defend against pathogens through a mechanism known as colonization resistance (CR). Advances in technologies such as next-generation sequencing, gnotobiotic mouse models, and bacterial cultivation have enhanced our understanding of the underlying mechanisms and the intricate microbial interactions involved in CR. Rather than being attributed to specific microbial clades, CR is now understood to arise from a dynamic interplay between microbes and the host and is shaped by metabolic, immune, and environmental factors. This evolving perspective underscores the significance of contextual factors, encompassing microbiome composition and host conditions, in determining CR. This review highlights recent research that has shifted its focus toward elucidating how these factors interact to either promote or impede enteric infections. It further discusses future research directions to unravel the complex relationship between host, microbiota, and environmental determinants in safeguarding against GI infections to promote human health.

Revealing the comprehensive impact of organic compounds on the partial nitrification-anammox system during incineration leachate treatment: metabolic hierarchy and adaptation

Organics, as widespread pollutants in high-strength ammonia wastewater, typically exert adverse effects on the performance of partial nitrification-anammox (PNA) systems. However, the in-depth knowledge on how microbial consortia respond to these disturbances remains limited. In this study, we unveiled the evolution of complex organic matter flow and its impact on the metabolic hierarchy and adaptation of microbial consortia, employing multi-omics approaches, i.e., 16S amplicon sequencing, metagenomics, and metabolomics. In a two-stage PNA system sequentially treating synthetic wastewater and incineration leachate over 230 days, partial nitrification stayed stable (nitrite accumulation > 97%) while anammox efficiency dropped (nitrogen removal decreased from 86% to 78%). The phenomenon was revealed to be correlated with the evolution of dissolved organic matter (DOM) and xenobiotic organic compounds (XOCs). In the PN stage, ammonia-oxidizing bacteria (AOB) exhibited excellent adaptability through active metabolic regulation after treating leachate. Numerous heterotrophs proliferated to utilize DOM and XOCs, triggering a "boom" state evident in the glycerophospholipid metabolism. However, in the anammox stage, the competition between carbon fixation and central carbon metabolism within autotrophs and heterotrophs became evident. Increased biosynthesis costs inhibited the central metabolism (specific anammox activity decreased by 66%) and the Wood-Ljungdahl pathway of anammox bacteria (AnAOB) in the presence of recalcitrant organics. Additionally, the degradation of organics was limited, exhibiting a "bust" state. This study revealed the metabolic adaption and susceptibility of AOB and AnAOB in response to organics from the leachate, demonstrating the applicability of the two-stage configuration for treating high-strength wastewater containing abundant and diverse organics.

High-throughput characterization of the effect of sodium chloride and potassium chloride on 31 lactic acid bacteria and their co-cultures

Salt (NaCl) is associated with a risk of hypertension and the development of coronary heart disease, so its consumption should be limited. However, salt plays a key role in the quality and safety of food by controlling undesirable microorganisms. Since studies have focused primarily on the effect of salts on the overall counts of the lactic acid bacteria (LAB) group, we have not yet understood how salt stress individually affects the strains and the interactions between them. In this study, we characterized the effect of sodium chloride (NaCl) and potassium chloride (KCl) on the growth and acidification of 31 LAB strains. In addition, we evaluated the effect of salts on a total of 93 random pairwise strain combinations. Strains and co-cultures were tested at 3% NaCl, 5% NaCl, and 3% KCl on solid medium using an automated approach and image analysis. The results showed that the growth of LAB was significantly reduced by up to 68% at 5% NaCl (p < 0.0001). For the co-cultures, a reduction of up to 57% was observed at 5% NaCl (p < 0.0001). However, acidification was less affected by salt stress, whether for monocultures or co-cultures. Furthermore, KCl had a lesser impact on both growth and acidification compared to NaCl. Indeed, some strains showed a significant increase in growth at 3% KCl, such as Lactococcus lactis subsp. lactis 74310 (23%, p = 0.01). More importantly, co-cultures appeared to be more resilient and had more varied responses to salt stress than the monocultures, as several cases of suppression of the significant effect of salts on acidification and growth were detected. Our results highlight that while salts can modulate microbial interactions, these latter can also attenuate the effect of salts on LAB.

Impact of timing on the invasion of synthetic bacterial communities

Microbial communities regularly experience ecological invasions that can lead to changes in composition and function. Factors thought to impact susceptibility to invasions, such as diversity and resource use, vary over the course of community assembly. We used synthetic bacterial communities to evaluate the success and impact of invasions occurring at different times during the community assembly process. Fifteen distinct communities were subjected to each of three bacterial invaders at the initial assembly of the community ("initial invasion"), 24 h into community assembly ("early invasion"), when the community was still undergoing transient dynamics, and 7 days into community assembly ("late invasion"), once the community had settled into its final composition. Communities were passaged daily and characterized through sequencing after reaching a stable composition. Invasions often failed to persist over time, particularly in higher richness communities. However, invasions had their largest effect on composition when they occurred before a community had settled into a stable composition. We found instances where an invader was ultimately excluded yet had profound and long-lasting effects on invaded communities. Invasion outcome was positively associated with lower community richness and resource use efficiency by the community, which varied throughout assembly. Our results demonstrate that microbial communities experiencing transient community dynamics are more affected by, and in some instances prone to, invasion, a finding relevant to efforts to modify the composition of microbial communities.

Reciprocal inhibition and competitive hierarchy cause negative biodiversity-ecosystem function relationships

The relationship between biodiversity and ecosystem function (BEF) captivates ecologists, but the factors responsible for the direction of this relationship remain unclear. While higher ecosystem functioning at higher biodiversity levels ('positive BEF') is not universal in nature, negative BEF relationships seem puzzlingly rare. Here, we develop a dynamical consumer-resource model inspired by microbial decomposer communities in pitcher plant leaves to investigate BEF. We manipulate microbial diversity via controlled colonization and measure their function as total ammonia production. We test how niche partitioning among bacteria and other ecological processes influence BEF in the leaves. We find that a negative BEF can emerge from reciprocal interspecific inhibition in ammonia production causing a negative complementarity effect, or from competitive hierarchies causing a negative selection effect. Absent these factors, a positive BEF was the typical outcome. Our findings provide a potential explanation for the rarity of negative BEF in empirical data.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

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

Bridging theory and experiments of priority effects

Priority effects play a key role in structuring natural communities, but considerable confusion remains about how they affect different ecological systems. Synthesizing previous studies, we show that this confusion arises because the mechanisms driving priority and the temporal scale at which they operate differ among studies, leading to divergent outcomes in species interactions and biodiversity patterns. We suggest grouping priority effects into two functional categories based on their mechanisms: frequency-dependent priority effects that arise from positive frequency dependence, and trait-dependent priority effects that arise from time-dependent changes in interacting traits. Through easy quantification of these categories from experiments, we can construct community models representing diverse biological mechanisms and interactions with priority effects, therefore better predicting their consequences across ecosystems.

Combinatorial fluorescent labeling of live anaerobic bacteria via the incorporation of azide-modified sugars into newly synthesized macromolecules

The human gut microbiome modulates physiological functions and pathologies; however, a mechanistic understanding of microbe-host and microbe-microbe interactions remains elusive owing to a lack of suitable approaches to monitor obligate anaerobic bacterial populations. Common genetically encoded fluorescent protein reporters, derived from the green fluorescent protein, require an oxidation step for fluorescent light emission and therefore are not suitable for use in anaerobic microbes residing in the intestine. Fluorescence in situ hybridization is a useful alternative to visualize bacterial communities in their natural niche; however, it requires tissue fixation. We therefore developed an approach for the real-time detection and monitoring of live communities of anaerobic gut commensals in their natural environment. We leverage the bacterial cells' reliance on sugars for macromolecule synthesis in combinatorial click chemistry labeling, where the addition of azide-modified sugars to the culturing media enables the fluorescence labeling of newly synthesized molecules via the addition of combinations of exogenous fluorophores conjugated to cyclooctynes. This process is suitable for labeling communities of live anaerobic gut bacteria with combinations of fluorophores that do not require oxygen to mature and fluoresce, and that can be detected over time in their natural environments. The labeling procedure requires 4-9 d, depending on the varying growth rates of different bacterial strains, and an additional 1-2 d for the detection and monitoring steps. The protocol can be completed by users with basic expertise in bacterial culturing.

Tidal flat microbial communities between the Huaihe estuary and Yangtze River estuary

Tidal flats have important ecological functions and offer great economic value. Using field sampling, numerical simulation, and high-throughput sequencing, the ecological state of typical tidal flats along the eastern coast of China was investigated. The findings demonstrated that the area may be separated into subregions with notable differences in the features of microbial communities due to the variations in water quality and total pollutant discharge of seagoing rivers. With a ratio of 62%, the development of the microbial community revealed that homogenous selection predominated. In general, the formation of microbial communities follows deterministic processes, especially those of environmental selection. The wetland microbial communities are impacted by pollutants discharged into the sea from the Huaihe River and the Yangtze River. The Yangtze River's nitrogen pollutants affected the wetland zone, and denitrification dominated. The study established ecological patterns between the river and the sea and we offer suggestions for managing watersheds and safeguarding the ecology of coastal tidal flats.

Different gut microbial types were found in captive striped hamsters

Background

Typing analysis has become a popular approach to categorize individual differences in studies of animal gut microbial communities. However, previous definitions of gut microbial types were more understood as a passive reaction process to different external interferences, as most studies involve diverse environmental variables. We wondered whether distinct gut microbial types can also occur in animals under the same external environment. Moreover, the role of host sex in shaping gut microbiota has been widely reported; thus, the current study preliminarily explores the effects of sex on potential different microbial types.

Methods

Here, adult striped hamsters Cricetulus barabensis of different sexes were housed under the same controlled laboratory conditions, and their fecal samples were collected after two months to assess the gut microbiota by 16S rRNA sequencing.

Results

The gut microbiota of captive striped hamsters naturally separated into two types at the amplicon sequence variant (ASV) level. There was a significant difference in the Shannon index among these two types. A receiver operating characteristic (ROC) curve showed that the top 30 ASVs could effectively distinguish each type. Linear discriminant analysis of effect size (LEfSe) showed enrichment of the genera Lactobacillus, Treponema and Pygmaiobacter in one gut microbial type and enrichment of the genera Turicibacter and Ruminiclostridium in the other. The former type had higher carbohydrate metabolism ability, while the latter harbored a more complex co-occurrence network and higher amino acid metabolism ability. The gut microbial types were not associated with sex; however, we did find sex differences in the relative abundances of certain bacterial taxa, including some type-specific sex variations.

Conclusions

Although captive animals live in a unified environment, their gut bacteria can still differentiate into distinct types, but the sex of the hosts may not play an important role in the typing process of small-scale captive animal communities. The relevant driving factors as well as other potential types need to be further investigated to better understand host-microbe interactions.

Metabolic similarity and the predictability of microbial community assembly

When microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia.

Selection of initial microbial community for the alcoholic fermentation of sesame flavor-type baijiu

The initial microbial community is critical for the production of volatile metabolites during traditional food fermentations. Selection of the initial community plays an important role in improving the quality of fermented foods. Here, we used high-throughput amplicon sequencing combined with multivariate statistical methods to explore the microbial succession in stacking and alcoholic fermentation stages in sesame flavor-type baijiu making. We proposed a selection strategy for the initial microbial community in the alcoholic fermentation stage, which determined the quality of baijiu. Results suggested that the microbial composition statistically differed between stacking and alcoholic fermentation stages (ANOSIM, Bacteria: R = 0.60, P = 0.001; Fungi: R = 0.53, P = 0.001). Microbial succession drove metabolic succession (Bacteria: r = 0.87, P < 0.05; Fungi: r = 0.56, P < 0.05) in alcoholic fermentation. The fermentation time of stacking fermentation determined the initial community for alcoholic fermentation, and it can be used as a criterion for selection of the initial microbial community for alcoholic fermentation. The succession distance of the microbial community was varied and reached the highest (Bacteria: 0.048, Fungi: 0.064) at 30 h in stacking fermentation. When we selected 30 h as stacking fermentation time, the concentration (4.58 mg/kg) and diversity (0.61) of volatile metabolites were highest at the end of alcoholic fermentation. This work developed a succession distance-guided approach to select the initial microbial community for the alcoholic fermentation of sesame flavor-type baijiu. This approach can be used to improve the quality of baijiu.

Stage-mediated priority effects and season lengths shape long-term competition dynamics

The relative arrival time of species can affect their interactions and thus determine which species persist in a community. Although this phenomenon, called priority effect, is widespread in natural communities, it is unclear how it depends on the length of growing season. Using a seasonal stage-structured model, we show that differences in stages of interacting species could generate priority effects by altering the strength of stabilizing and equalizing coexistence mechanisms, changing outcomes between exclusion, coexistence and positive frequency dependence. However, these priority effects are strongest in systems with just one or a few generations per season and diminish in systems where many overlapping generations per season dilute the importance of stage-specific interactions. Our model reveals a novel link between the number of generations in a season and the consequences of priority effects, suggesting that consequences of phenological shifts driven by climate change should depend on specific life histories of organisms.

Multidimensional specialization and generalization are pervasive in soil prokaryotes

Habitat specialization underpins biological processes from species distributions to speciation. However, organisms are often described as specialists or generalists based on a single niche axis, despite facing complex, multidimensional environments. Here, we analysed 236 environmental soil microbiomes across the United States and demonstrate that 90% of >1,200 prokaryotes followed one of two trajectories: specialization on all niche axes (multidimensional specialization) or generalization on all axes (multidimensional generalization). We then documented that this pervasive multidimensional specialization/generalization had many ecological and evolutionary consequences. First, multidimensional specialization and generalization are highly conserved with very few transitions between these two trajectories. Second, multidimensional generalists dominated communities because they were 73 times more abundant than specialists. Lastly, multidimensional specialists played important roles in community structure with ~220% more connections in microbiome networks. These results indicate that multidimensional generalization and specialization are evolutionarily stable with multidimensional generalists supporting larger populations and multidimensional specialists playing important roles within communities, probably stemming from their overrepresentation among pollutant detoxifiers and nutrient cyclers. Taken together, we demonstrate that the vast majority of soil prokaryotes are restricted to one of two multidimensional niche trajectories, multidimensional specialization or multidimensional generalization, which then has far-reaching consequences for evolutionary transitions, microbial dominance and community roles.

Metabolic complexity drives divergence in microbial communities

Microbial communities are shaped by the metabolites available in their environment, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. To this end, we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the diverse assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively smaller ones, is necessary and sufficient to recapitulate all of our experimental observations. In addition to pointing to a fundamental principle of community assembly, the divergence-complexity effect has important implications for microbiome engineering applications, as it can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions.

Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding

When bacterial species with the same resource preferences share the same growth environment, it is commonly believed that direct competition will arise. A large variety of competition and more general 'interaction' models have been formulated, but what is currently lacking are models that link monoculture growth kinetics and community growth under inclusion of emerging biological interactions, such as metabolite cross-feeding. In order to understand and mathematically describe the nature of potential cross-feeding interactions, we design experiments where two bacterial species Pseudomonas putida and Pseudomonas veronii grow in liquid medium either in mono- or as co-culture in a resource-limited environment. We measure population growth under single substrate competition or with double species-specific substrates (substrate 'indifference'), and starting from varying cell ratios of either species. Using experimental data as input, we first consider a mean-field model of resource-based competition, which captures well the empirically observed growth rates for monocultures, but fails to correctly predict growth rates in co-culture mixtures, in particular for skewed starting species ratios. Based on this, we extend the model by cross-feeding interactions where the consumption of substrate by one consumer produces metabolites that in turn are resources for the other consumer, thus leading to positive feedback in the species system. Two different cross-feeding options were considered, which either lead to constant metabolite cross-feeding, or to a regulated form, where metabolite utilization is activated with rates according to either a threshold or a Hill function, dependent on metabolite concentration. Both mathematical proof and experimental data indicate regulated cross-feeding to be the preferred model to constant metabolite utilization, with best co-culture growth predictions in case of high Hill coefficients, close to binary (on/off) activation states. This suggests that species use the appearing metabolite concentrations only when they are becoming high enough; possibly as a consequence of their lower energetic content than the primary substrate. Metabolite sharing was particularly relevant at unbalanced starting cell ratios, causing the minority partner to proliferate more than expected from the competitive substrate because of metabolite release from the majority partner. This effect thus likely quells immediate substrate competition and may be important in natural communities with typical very skewed relative taxa abundances and slower-growing taxa. In conclusion, the regulated bacterial interaction network correctly describes species substrate growth reactions in mixtures with few kinetic parameters that can be obtained from monoculture growth experiments.

Cooperative microbial interactions drive spatial segregation in porous environments

The role of microbial interactions and the underlying mechanisms that shape complex biofilm communities are poorly understood. Here we employ a microfluidic chip to represent porous subsurface environments and show that cooperative microbial interactions between free-living and biofilm-forming bacteria trigger active spatial segregation to promote their respective dominance in segregated microhabitats. During initial colonization, free-living and biofilm-forming microbes are segregated from the mixed planktonic inoculum to occupy the ambient fluid and grain surface. Contrary to spatial exclusion through competition, the active spatial segregation is induced by cooperative interactions which improves the fitness of both biofilm and planktonic populations. We further show that free-living Arthrobacter induces the surface colonization by scavenging the biofilm inhibitor, D-amino acids and receives benefits from the public goods secreted by the biofilm-forming strains. Collectively, our results reveal how cooperative microbial interactions may contribute to microbial coexistence in segregated microhabitats and drive subsurface biofilm community succession.

Metabolic interaction models recapitulate leaf microbiota ecology

Resource allocation affects the structure of microbiomes, including those associated with living hosts. Understanding the degree to which this dependency determines interspecies interactions may advance efforts to control host-microbiome relationships. We combined synthetic community experiments with computational models to predict interaction outcomes between plant-associated bacteria. We mapped the metabolic capabilities of 224 leaf isolates from Arabidopsis thaliana by assessing the growth of each strain on 45 environmentally relevant carbon sources in vitro. We used these data to build curated genome-scale metabolic models for all strains, which we combined to simulate >17,500 interactions. The models recapitulated outcomes observed in planta with >89% accuracy, highlighting the role of carbon utilization and the contributions of niche partitioning and cross-feeding in the assembly of leaf microbiomes.

Top-down identification of keystone taxa in the microbiome

Keystone taxa in ecological communities are native taxa that play an especially important role in the stability of their ecosystem. However, we still lack an effective framework for identifying these taxa from the available high-throughput sequencing without the notoriously difficult step of reconstructing the detailed network of inter-specific interactions. In addition, while most microbial interaction models assume pair-wise relationships, it is yet unclear whether pair-wise interactions dominate the system, or whether higher-order interactions are relevant. Here we propose a top-down identification framework, which detects keystones by their total influence on the rest of the taxa. Our method does not assume a priori knowledge of pairwise interactions or any specific underlying dynamics and is appropriate to both perturbation experiments and metagenomic cross-sectional surveys. When applied to real high-throughput sequencing of the human gastrointestinal microbiome, we detect a set of candidate keystones and find that they are often part of a keystone module - multiple candidate keystone species with correlated occurrence. The keystone analysis of single-time-point cross-sectional data is also later verified by the evaluation of two-time-points longitudinal sampling. Our framework represents a necessary advancement towards the reliable identification of these key players of complex, real-world microbial communities.

Fucosylated Human Milk Oligosaccharides Drive Structure-Specific Syntrophy between Bifidobacterium infantis and Eubacterium hallii within a Modeled Infant Gut Microbiome

SCOPE

Fucosylated human milk oligosaccharides (fHMOs) are metabolized by Bifidobacterium infantis and promote syntrophic interactions between microbiota that colonize the infant gut. The role of fHMO structure on syntrophic interactions and net microbiome function is not yet fully understood.

METHODS AND RESULTS

Metabolite production and microbial populations are tracked during mono- and co-culture fermentations of 2'fucosyllactose (2'FL) and difucosyllactose (DFL) by two B. infantis strains and Eubacterium hallii. This is also conducted in an in vitro modeled microbiome supplemented by B. infantis and/or E. hallii. Metabolites are quantified by high performance liquid chromatography. Total B. infantis and E. hallii populations are quantified through qRT-PCR and community composition through 16S amplicon sequencing. Differential metabolism of 2'FL and DFL by B. infantis strains gives rise to strain- and fHMO structure-specific syntrophy with E. hallii. Within the modeled microbial community, fHMO structure does not strongly alter metabolite production in aggregate, potentially due to functional redundancy within the modeled community. In contrast, community composition is dependent on fHMO structure.

CONCLUSION

Whereas short chain fatty acid production is not significantly altered by the specific fHMO structure introduced to the modeled community, specific fHMO structure influences the composition of the gut microbiome.

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for control of natural and engineered systems. Discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28 d microcosm incubations to examine microbial community compositional and functional stability during plant-litter decomposition. Using DOC abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a "low DOC" phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as 1 solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. Importance Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

Multispecies biofilms on reverse osmosis membrane dictate the function and characteristics of the bacterial communities rather than their structure

The main reason for the deterioration of membrane operation during water purification processes is biofouling, which has therefore been extensively studied. Biofouling was shown to reduce membrane performance reflected by permeate flux decline, reduced selectivity, membrane biodegradation, and consequently, an increase in energy consumption. Studies of biofouling focused on the identification of the assembled microbial communities, the excretion of extracellular polymeric substances (EPS), and their combined role in reduced membrane performance and lifetime. However, the link between the structure and function of biofouling communities has not been elucidated to date. Here, we provide a novel insight, suggesting that bacterial functions rather than composition control biofouling traits on reverse osmosis (RO) membranes. We studied the potential activity of RO biofilms at metatranscriptome resolution, accompanied by the morphology and function of the biofouling layer over time, including microscopy and EPS composition, adhesion, and viscoelastic properties. To that end, we cultivated natural multispecies biofilms in RO membranes under treated wastewater flow and extracted RNA to study their taxonomies and gene expression profiles. Concomitantly, the biofilm structure was visualized using both scanning electron microscopy and laser scanning confocal microscopy. We also used quartz crystal microbalance with dissipation to characterize the affinity of EPS to membrane-mimetic sensors and evaluated the viscoelasticity of the Ex-Situ EPS layer formed on the sensor. Our results showed that different active bacterial taxa across five taxonomic classes were assembled on the RO membrane, while the composition shifted between 48 and 96 h. However, regardless of the composition, the maturation of the biofilm resulted in the expression of similar gene families tightly associated with the temporal kinetics of the EPS composition, adhesion, and viscoelasticity. Our findings highlight the temporal selection of specific microbial functions rather than composition, featuring the adhesion kinetics and viscoelastic properties of the RO biofilm.

Niche Modification by Sulfate-Reducing Bacteria Drives Microbial Community Assembly in Anoxic Marine Sediments

Sulfate-reducing bacteria (SRB) are essential functional microbial taxa for degrading organic matter (OM) in anoxic marine environments. However, there are little experimental data regarding how SRB regulates microbial communities. Here, we applied a top-down microbial community management approach by inhibiting SRB to elucidate their contributions to the microbial community during OM degradation. Based on the highly replicated microcosms (n = 20) of five different incubation stages, we found that many microbial community properties were influenced after inhibiting SRB, including the composition, structure, network, and community assembly processes. We also found a strong coexistence pattern between SRB and other abundant phylogenetic lineages via positive frequency-dependent selection. The relative abundances of the families Synergistaceae, Peptostreptococcaceae, Dethiosulfatibacteraceae, Prolixibacteraceae, Marinilabiliaceae, and Marinifilaceae were simultaneously suppressed after inhibiting SRB during OM degradation. A close association between SRB and the order Marinilabiliales among coexisting taxa was most prominent. They contributed to preserved modules during network successions, were keystone nodes mediating the networked community, and contributed to homogeneous ecological selection. The molybdate tolerance test of the isolated strains of Marinilabiliales showed that inhibited SRB (not the inhibitor of SRB itself) triggered a decrease in the relative abundance of Marinilabiliales. We also found that inhibiting SRB resulted in reduced pH, which is unsuitable for the growth of most Marinilabiliales strains, while the addition of pH buffer (HEPES) in SRB-inhibited treatment microcosms restored the pH and the relative abundances of these bacteria. These data supported that SRB could modify niches to affect species coexistence. IMPORTANCE Our model offers insight into the ecological properties of SRB and identifies a previously undocumented dimension of OM degradation. This targeted inhibition approach could provide a novel framework for illustrating how functional microbial taxa associate the composition and structure of the microbial community, molecular ecological network, and community assembly processes. These findings emphasize the importance of SRB during OM degradation. Our results proved the feasibility of the proposed study framework, inhibiting functional taxa at the community level, for illustrating when and to what extent functional taxa can contribute to ecosystem services.

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

IMPORTANCE

Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

The community-function landscape of microbial consortia

Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

Investigating the eco-evolutionary tunnels for establishing cooperative communities

Diversity is abundant among microbial communities. Understanding the assembly of diverse microbial communities is a significant challenge. One of the recent plausible explanations for the assembly involves eco-evolutionary tunnels, where species interact in the same timescale with the mutational rate. Analysis of data generated by agent-based models was used to understand these tunnels. However, modeling the interactions explicitly by dynamic models is lacking. Here, we present the modeling and characterization of eco-evolutionary tunnels that give rise to cooperative evolutionary stable communities (ESC). We find that higher order, but common interactions are sufficient for eco-evolutionary tunnels. We identify three distinct scenarios: evolution of costly cooperation, mutationally inaccessible assembly, and bistability. Biological interpretations of the models are shedding light on the evolution of cooperation. One of the important findings is that if species maximize their benefit by preying on the other strain when dominant and cooperating at intermediate abundances, the assembly process needs eco-evolutionary tunneling. In addition, we characterize the importance of genetic drift with respect to eco-evolutionary tunnels, intermittently stable communities, and the effect of high population limits on the tunnels.

Ecological landscapes guide the assembly of optimal microbial communities

Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Assembling microbial communities: a genomic analysis of a natural experiment in neotropical bamboo internodes

Microbes participate in ecological communities, much like multicellular organisms. However, microbial communities lack the centuries of observation and theory describing and predicting ecological processes available for multicellular organisms. Here, we examine early bacterial community assembly in the water-filled internodes of Amazonian bamboos from the genus Guadua. Bamboo stands form distinct habitat patches within the lowland Amazonian rainforest and provide habitat for a suite of vertebrate and invertebrate species. Guadua bamboos develop sealed, water-filled internodes as they grow. Internodes are presumed sterile or near sterile while closed, but most are eventually opened to the environment by animals, after which they are colonized by microbes. We find that microbial community diversity increases sharply over the first few days of environmental exposure, and taxonomic identity of the microbes changes through this time period as is predicted for early community assembly in macroscopic communities. Microbial community taxonomic turnover is consistent at the bacteria phylum level, but at the level of Operational Taxonomic Units (OTUs), internode communities become increasingly differentiated through time. We argue that these tropical bamboos form an ideal study system for microbial community ecology due to their near-sterile condition prior to opening, relatively consistent environment after opening, and functionally limitless possibilities for replicates. Given the possible importance of opened internode habitats as locations of transmission for both pathogenic and beneficial microbes among animals, understanding the microbial dynamics of the internode habitat is a key conservation concern for the insect and amphibian species that use this microhabitat.

The Stochastic Assembly of Nitrobacter winogradskyi-Selected Microbiomes with Heterotrophs from Sewage Sludge or Grassland Soil

Chemolitho-autotrophic microorganisms like the nitrite-oxidizing Nitrobacter winogradskyi create an environment for heterotrophic microorganisms that profit from the production of organic compounds. It was hypothesized that the assembly of a community of heterotrophic microorganisms around N. winogradskyi depends on the ecosystem from which the heterotrophs are picked. To test this hypothesis, pure cultures of N. winogradskyi were grown in continuously nitrite-fed bioreactors in a mineral medium free of added organic carbon that had been inoculated with diluted sewage sludge or with a suspension from a grassland soil. Samples for chemical and 16S rRNA gene amplicon analyses were taken after each volume change in the bioreactor. At the end of the enrichment runs, samples for shotgun metagenomics were also collected. Already after two volume changes, the transformations in community structure became less dynamic. The enrichment of heterotrophs from both sewage and soil was highly stochastic and yielded different dominant genera in most of the enrichment runs that were independent of the origin of the inoculum. Hence, the hypothesis had to be refuted. Notwithstanding the large variation in taxonomic community structure among the enrichments, the functional compositions of the communities were statistically not different between soil- and sludge-based enrichments. IMPORTANCE In the process of aerobic nitrification, nitrite-oxidizing bacteria together with ammonia-oxidizing microorganisms convert mineral nitrogen from its most reduced appearance, i.e., ammonium, into its most oxidized form, i.e., nitrate. Because the form of mineral nitrogen has large environmental implications, nitrite-oxidizing bacteria such as Nitrobacter winogradskyi play a central role in the global biogeochemical nitrogen cycle. In addition to this central role, the autotrophic nitrite-oxidizing bacteria also play a fundamental role in the global carbon cycle. They form the basis of heterotrophic food webs, in which the assimilated carbon is recycled. Little is known about the heterotrophic microorganisms that participate in these food webs, let alone their assembly in different ecosystems. This study showed that the assembly of microbial food webs by N. winogradskyi was a highly stochastic process and independent of the origin of the heterotrophic microorganisms, but the functional characteristics of the different food webs were similar.

A ridge-to-reef ecosystem microbial census reveals environmental reservoirs for animal and plant microbiomes

Because microbiome research generally focuses on a single host or habitat, we know comparatively little about the diversity and distribution of microbiomes at a landscape scale. Our study demonstrates that most of the microbial diversity present within a watershed is maintained within environmental substrates like soil or stream water, and microbiomes of organisms are generally subsets of those that are lower on the food chain. This result challenges the notion that sources of microbial inoculum are likeliest derived from close relatives. By identifying sources of shared microbial diversity within the landscape, we can better understand the origins and assembly processes of symbiotic microbes and how this might abet global conservation, restoration, or bio-engineering goals, such as preserving biodiversity and ecosystem services.

Microbes are found in nearly every habitat and organism on the planet, where they are critical to host health, fitness, and metabolism. In most organisms, few microbes are inherited at birth; instead, acquiring microbiomes generally involves complicated interactions between the environment, hosts, and symbionts. Despite the criticality of microbiome acquisition, we know little about where hosts’ microbes reside when not in or on hosts of interest. Because microbes span a continuum ranging from generalists associating with multiple hosts and habitats to specialists with narrower host ranges, identifying potential sources of microbial diversity that can contribute to the microbiomes of unrelated hosts is a gap in our understanding of microbiome assembly. Microbial dispersal attenuates with distance, so identifying sources and sinks requires data from microbiomes that are contemporary and near enough for potential microbial transmission. Here, we characterize microbiomes across adjacent terrestrial and aquatic hosts and habitats throughout an entire watershed, showing that the most species-poor microbiomes are partial subsets of the most species-rich and that microbiomes of plants and animals are nested within those of their environments. Furthermore, we show that the host and habitat range of a microbe within a single ecosystem predicts its global distribution, a relationship with implications for global microbial assembly processes. Thus, the tendency for microbes to occupy multiple habitats and unrelated hosts enables persistent microbiomes, even when host populations are disjunct. Our whole-watershed census demonstrates how a nested distribution of microbes, following the trophic hierarchies of hosts, can shape microbial acquisition.