Toxicity drives facilitation between 4 bacterial species

Response of microbial communities in aquifers with multiple organic solvent contamination: Implications for MNA remedy

The application of Monitored Natural Attenuation (MNA) technology has been widespread, while there is a paucity of data on groundwater with multiple co-contaminants. This study focused on high permeability, low hydraulic gradient groundwater with co-contamination of benzene, toluene, ethylbenzene, and xylenes (BTEX), chlorinated aliphatic hydrocarbons (CAHs), and chlorinated aromatic hydrocarbons (CPs). The objective was to investigate the responses of microbial communities during natural attenuation processes. Results revealed greater horizontal variation in groundwater microbial community composition compared to vertical variation. The variation was strongly correlated with the total contaminant quantity (r = 0.722, p < 0.001) rather than individual contaminants. BTEX exerted a more significant influence on community diversity than other contaminants. The assembly of groundwater microbial communities was primarily governed by deterministic processes (βNTI < -2) in high contaminant concentration zones, while stochastic processes (|βNTI| < 2) dominated in low-concentration zones. Moreover, the microbial interactions shifted at different depths indicating the degradation rate variation in the vertical. This study makes fundamental contribution to the understanding for the effects of groundwater flow and material fields on indigenous microbial communities, which will provide a scientific basis for more precise adoption of microbial stimulation/augmentation to accelerate the rate of contaminant removal.

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

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

Community interactions among microbes give rise to host-microbiome mutualisms in an aquatic plant

Microbiomes often benefit plants, conferring resistance to pathogens, improving stress tolerance, or promoting plant growth. As potential plant mutualists, however, microbiomes are not a single organism but a community of species with complex interactions among microbial taxa and between microbes and their shared host. The nature of ecological interactions among microbes in the microbiome can have important consequences for the net effects of microbiomes on hosts. Here, we compared the effects of individual microbial strains and 10-strain synthetic communities on microbial productivity and host growth using the common duckweed Lemna minor and a synthetic, simplified version of its native microbiome. Except for Pseudomonas protegens, which was a mutualist when tested alone, all of the single strains we tested were commensals on hosts, benefiting from plant presence but not increasing host growth relative to uninoculated controls. However, 10-strain synthetic microbial communities increased both microbial productivity and duckweed growth more than the average single-strain inoculation and uninoculated controls, meaning that host-microbiome mutualisms can emerge from community interactions among microbes on hosts. The effects of community inoculation were sub-additive, suggesting at least some competition among microbes in the duckweed microbiome. We also investigated the relationship between L. minor fitness and that of its microbes, providing some of the first empirical estimates of broad fitness alignment between plants and members of their microbiomes; hosts grew faster with more productive microbes or microbiomes.

IMPORTANCE

There is currently substantial interest in engineering synthetic microbiomes for health or agricultural applications. One key question is how multi-strain microbial communities differ from single microbial strains in their productivity and effects on hosts. We tested 20 single bacterial strains and 2 distinct 10-strain synthetic communities on plant hosts and found that 10-strain communities led to faster host growth and greater microbial productivity than the average, but not the best, single strain. Furthermore, the microbial strains or communities that achieved the greatest cell densities were also the most beneficial to their hosts, showing that both specific single strains and multi-strain synthetic communities can engage in high-quality mutualisms with their hosts. Our results suggest that ~5% of single strains, as well as multi-strain synthetic communities comprised largely of commensal microbes, can benefit hosts and result in effective host-microbe mutualisms.

Cadmium contamination decreased bacterial network complexity and stability in coastal reclamation areas

Cadmium(Cd) contamination can exert significantly adverse effects on soil microbiota in reclaimed areas, however, its effects on bacterial network structure are still limitedly understood. Here we collected soil samples from typical reclaimed wetlands (RW) and ditch wetlands (DW) in coastal reclamation areas and examined the effects of Cd contamination on the bacterial network complexity and stability. The results showed that the bacterial networks were destabilized by the Cd contamination, while bacteria in DW soils showed robust invulnerability characterized by higher node constancy and compositional stability compared with RW soils. Soil bacteria resisted Cd stress by forming a network with intensive connections in the module but sparser connections among the modules. Especially, network modularity was higher in DW soils than in RW soils, but made it more vulnerable to nodes removal. In addition, Cd contamination promoted bacterial positive cohesion but decreased negative cohesion in RW soils. Flavobacteriaceae, Xanthomonadaceae, and Alcaligenaceae were identified as core phylotypes, which played pivotal roles in regulating interspecies interactions due to higher contributions to cohesion and significant correlations with soil nutrients. The findings of this work indicate the changes of bacterial network structure and the indispensable role of core phylotypes in regulating interactions and maintaining network sustainability under Cd contamination.

Exploring bacterial community assembly in vadose and saturated zone soil for tailored bioremediation of a long-term hydrocarbon-contaminated site

Indigenous soil microbial communities play a pivotal role in the in situ bioremediation of contaminated sites. However, research on the distribution characteristics of microbial communities at various soil depths remains limited. In particular, there is little information on the assembly of microbial communities, especially those with degradation potential, in the vadose and saturated zones of hydrocarbon-contaminated sites. In this study, 18 soil samples were collected from the vadose zone and saturated zone at a long-term hydrocarbon-contaminated site. The diversity, composition, and driving factors of assembly of the soil bacterial community were determined by high-throughput sequencing analysis. Species richness and diversity were significantly higher in the vadose zone soils than in the saturated zone soils. Significant differences in abundance at both the phylum and genus levels were observed between the two zones. Soil bacterial community assembly was driven by the combination of pollution stress and nutrients in the vadose zone but by nutrient limitations in the saturated zone. The abundance of dechlorinating bacteria was greater in the saturated zone soils than in the vadose zone soils. Compared with contaminant concentrations, nutrient levels had a more pronounced impact on the abundance of dechlorinating bacteria. In addition, the interactions among dechlorinating bacterial populations were stronger in the saturated zone soils than in the vadose zone soils. These findings underscore the importance of comprehensively understanding indigenous microbial communities, especially those with degradation potential, across different soil layers to devise specific, effective in situ bioremediation strategies for contaminated sites.

Fungal identity mediates the impacts of multiple stressors on freshwater ecosystems

Predicting how multiple anthropogenic stressors affect natural ecosystems is a major challenge in ecology. Freshwater ecosystems are threatened worldwide by multiple co-occurring stressors, which can affect aquatic biodiversity, ecosystem functioning and human wellbeing. In stream ecosystems, aquatic fungi play a crucial role in global biogeochemical cycles and food web dynamics, therefore, assessing the functional consequences of fungal biodiversity loss under multiple stressors is crucial. Here, a microcosm approach was used to investigate the effects of multiple stressors (increased temperature and nutrients, drying, and biodiversity loss) on three ecosystem processes: organic matter decomposition, fungal reproduction, and fungal biomass accrual. Net effects of stressors were antagonistic for organic matter decomposition, but additive for fungal reproduction and biomass accrual. Net effects of biodiversity were mainly positive for all processes, even under stress, demonstrating that diversity assures the maintenance of ecosystem processes. Fungal species displayed distinct contributions to each ecosystem process. Furthermore, species with negligible contributions under control conditions changed their role under stress, either enhancing or impairing the communities' performance, emphasizing the importance of fungal species identity. Our study highlights that distinct fungal species have different sensitivities to environmental variability and have different influence on the overall performance of the community. Therefore, preserving high fungal diversity is crucial to maintain fungal species with key ecosystem functions within aquatic communities in face of environmental change.

Pneumococcus and the stress-gradient hypothesis: A trade-off links R0 and susceptibility to co-colonization across countries

Modern molecular technologies have revolutionized our understanding of bacterial epidemiology, but reported data across studies and different geographic endemic settings remain under-integrated in common theoretical frameworks. Pneumococcus serotype co-colonization, caused by the polymorphic bacteria Streptococcus pneumoniae, has been increasingly investigated and reported in recent years. While the global genomic diversity and serotype distribution of S. pneumoniae have been well-characterized, there is limited information on how co-colonization patterns vary globally, critical for understanding the evolution and transmission dynamics of the bacteria. Gathering a rich dataset of cross-sectional pneumococcal colonization studies in the literature, we quantified patterns of transmission intensity and co-colonization prevalence variation in children populations across 17 geographic locations. Linking these data to an SIS model with cocolonization under the assumption of quasi-neutrality among multiple interacting strains, our analysis reveals strong patterns of negative co-variation between transmission intensity (R0) and susceptibility to co-colonization (k). In line with expectations from the stress-gradient-hypothesis in ecology (SGH), pneumococcus serotypes appear to compete more in co-colonization in high-transmission settings and compete less in low-transmission settings, a trade-off which ultimately leads to a conserved ratio of single to co-colonization μ=1/(R0-1)k. From the mathematical model's behavior, such conservation suggests preservation of 'stability-diversity-complexity' regimes in coexistence of similar co-colonizing strains. We find no major differences in serotype compositions across studies, pointing to adaptation of the same set of serotypes across variable environments as an explanation for their differential interaction in different transmission settings. Our work highlights that the understanding of transmission patterns of Streptococcus pneumoniae from global scale epidemiological data can benefit from simple analytical approaches that account for quasi-neutrality among strains, co-colonization, as well as variable environmental adaptation.

The impact of phage and phage resistance on microbial community dynamics

Where there are bacteria, there will be bacteriophages. These viruses are known to be important players in shaping the wider microbial community in which they are embedded, with potential implications for human health. On the other hand, bacteria possess a range of distinct immune mechanisms that provide protection against bacteriophages, including the mutation or complete loss of the phage receptor, and CRISPR-Cas adaptive immunity. While our previous work showed how a microbial community may impact phage resistance evolution, little is known about the inverse, namely how interactions between phages and these different phage resistance mechanisms affect the wider microbial community in which they are embedded. Here, we conducted a 10-day, fully factorial evolution experiment to examine how phage impact the structure and dynamics of an artificial four-species bacterial community that includes either Pseudomonas aeruginosa wild-type or an isogenic mutant unable to evolve phage resistance through CRISPR-Cas. Additionally, we used mathematical modelling to explore the ecological interactions underlying full community behaviour, as well as to identify general principles governing the impacts of phage on community dynamics. Our results show that the microbial community structure is drastically altered by the addition of phage, with Acinetobacter baumannii becoming the dominant species and P. aeruginosa being driven nearly extinct, whereas P. aeruginosa outcompetes the other species in the absence of phage. Moreover, we find that a P. aeruginosa strain with the ability to evolve CRISPR-based resistance generally does better when in the presence of A. baumannii, but that this benefit is largely lost over time as phage is driven extinct. Finally, we show that pairwise data alone is insufficient when modelling our microbial community, both with and without phage, highlighting the importance of higher order interactions in governing multispecies dynamics in complex communities. Combined, our data clearly illustrate how phage targeting a dominant species allows for the competitive release of the strongest competitor while also contributing to community diversity maintenance and potentially preventing the reinvasion of the target species, and underline the importance of mapping community composition before therapeutically applying phage.

High synthetic cost-amino acids reduce member interactions of acetate-degrading methanogenic microbial community

Introduction

The cooperation among members of microbial communities based on the exchange of public goods such as 20 protein amino acids (AAs) has attracted widespread attention. However, little is known about how AAs availability affects interactions among members of complex microbial communities and the structure and function of a community.

Methods

To investigate this question, trace amounts of AAs combinations with different synthetic costs (low-cost, medium-cost, high-cost, and all 20 AAs) were supplemented separately to acetate-degrading thermophilic methanogenic reactors, and the differences in microbial community structure and co-occurring networks of main members were compared to a control reactor without AA supplementation.

Results

The structure of the microbial community and the interaction of community members were influenced by AAs supplementation and the AAs with different synthetic costs had different impacts. The number of nodes, links, positive links, and the average degree of nodes in the co-occurrence network of the microbial communities with AAs supplementation was significantly lower than that of the control without AAs supplementation, especially for all 20 AAs supplementation followed by the medium- and high-cost AAs supplementation. The average proportion of positive interactions of microbial members in the systems supplemented with low-cost, medium-cost, high-cost, all AAs, and the control group were 0.42, 0.38, 0.15, 0.4, and 0.45, respectively. In addition, the ecological functions of community members possibly changed with the supplementation of different cost AAs.

Discussion

These findings highlight the effects of AAs availability on the interactions among members of complex microbial communities, as well as on community function.

Niche availability and competitive loss by facilitation control proliferation of bacterial strains intended for soil microbiome interventions

Microbiome engineering - the targeted manipulation of microbial communities - is considered a promising strategy to restore ecosystems, but experimental support and mechanistic understanding are required. Here, we show that bacterial inoculants for soil microbiome engineering may fail to establish because they inadvertently facilitate growth of native resident microbiomes. By generating soil microcosms in presence or absence of standardized soil resident communities, we show how different nutrient availabilities limit outgrowth of focal bacterial inoculants (three Pseudomonads), and how this might be improved by adding an artificial, inoculant-selective nutrient niche. Through random paired interaction assays in agarose micro-beads, we demonstrate that, in addition to direct competition, inoculants lose competitiveness by facilitating growth of resident soil bacteria. Metatranscriptomics experiments with toluene as selective nutrient niche for the inoculant Pseudomonas veronii indicate that this facilitation is due to loss and uptake of excreted metabolites by resident taxa. Generation of selective nutrient niches for inoculants may help to favor their proliferation for the duration of their intended action while limiting their competitive loss.

Competition quenching strategies reduce antibiotic tolerance in polymicrobial biofilms

Bacteria typically live in dense communities where they are surrounded by other species and compete for a limited amount of resources. These competitive interactions can induce defensive responses that also protect against antimicrobials, potentially complicating the antimicrobial treatment of pathogens residing in polymicrobial consortia. Therefore, we evaluate the potential of alternative antivirulence strategies that quench this response to competition. We test three competition quenching approaches: (i) interference with the attack mechanism of surrounding competitors, (ii) inhibition of the stress response systems that detect competition, and (iii) reduction of the overall level of competition in the community by lowering the population density. We show that either strategy can prevent the induction of antimicrobial tolerance of Salmonella Typhimurium in response to competitors. Competition quenching strategies can thus reduce tolerance of pathogens residing in polymicrobial communities and could contribute to the improved eradication of these pathogens via traditional methods.

Cadmium levels and soil pH drive structure and function differentiation of endophytic bacterial communities in Sedum plumbizincicola: A field study

Sedum plumbizincicola is a promising hyperaccumulator for heavy metal phytoremediation. It grows in heavy metal polluted soil and stores specific endophyte resources with heavy metal tolerance or growth promotion characteristics. In this study, the endophyte communities of S. plumbizincicola, growing naturally in the field (two former mining locations and one natural location) were investigated, and their structure and function were comparatively studied. The bioaccumulation and translocation characteristics of cadmium (Cd) and selenium (Se) in S. plumbizincicola were also evaluated. The results showed that the heavy metal pollution reduced the richness and diversity of endophyte communities. Soil pH and Cd concentration could be the key factors affecting the composition of the endophyte community. Co-occurrence network analysis identified that 22 keystone taxa belonging to Actinobacteriota, Firmicutes, Myxococcota and Proteobacteria were positively correlated with Cd bioaccumulation and translocation. The predicted endophyte metabolic pathways were enriched in physiological metabolism, immune system, and genetic Information processing. These findings may help to understand how endophytes assist host plants to enhance their adaptability to harsh environments, and provide a basis for further exploration of plant-endophyte interactions and improvement in phytoremediation efficiency.

Oxidative stress changes interactions between 2 bacterial species from competitive to facilitative

Knowing how species interact within microbial communities is crucial to predicting and controlling community dynamics, but interactions can depend on environmental conditions. The stress-gradient hypothesis (SGH) predicts that species are more likely to facilitate each other in harsher environments. Even if the SGH gives some intuition, quantitative modeling of the context-dependency of interactions requires understanding the mechanisms behind the SGH. In this study, we show with both experiments and a theoretical analysis that varying the concentration of a single compound, linoleic acid (LA), modifies the interaction between 2 bacterial species, Agrobacterium tumefaciens and Comamonas testosteroni, from competitive at a low concentration, to facilitative at higher concentrations where LA becomes toxic for one of the 2 species. We demonstrate that the mechanism behind facilitation is that one species is able to reduce reactive oxygen species (ROS) that are produced spontaneously at higher concentrations of LA, allowing for short-term rescue of the species that is sensitive to ROS and longer coexistence in serial transfers. In our system, competition and facilitation between species can occur simultaneously, and changing the concentration of a single compound can alter the balance between the two.

How antibiotic exposure affect predator-prey interactions by population dynamics in ciliates?

Biodiversity loss resulting from environmental pollution is a global concern. While interspecific interactions are central to ecology, the impact of environmental pollution on predator-prey interactions and its ecological consequences, such as extinction and biodiversity loss, remain unclear. To investigate the effects of antibiotic exposure on predation strength and the resulting ecological consequence, the Didinium-Paramecium was utilized as a predator-prey model and exposed to nitrofurazone or erythromycin, two common pollutants, respectively. Initially, we determined prey population growth dynamics, body size, and predator numerical-functional responses. Subsequently, these above parameters were integrated into a mathematical model of predator-prey predation. Then both the long time-series data and phase portraits obtained through model simulation were used to estimate interaction strength and to predict the outcome of predator-prey coexistence. Our results revealed that exposure to either antibiotic significantly reduced prey population growth parameters (e.g., μmax and K) while increasing individual body size. The combined effects of antibiotic exposure and predation pressure on population growth inhibition or body size promotion were variable, mostly additive, with a few cases of synergy and extremely rare antagonism, depending on antibiotic exposure concentration. As antibiotic exposure concentration increased, the predator rmax generally declined, while functional responses varied depending on specific parameters, implying a decrease in predator-prey interaction strength. Analyses of phase portrait features showed that the population oscillation amplitude decreased with increasing antibiotic exposure concentrations, the cycle length of adjacent peaks increased, and prey extinction occurred earlier. In conclusion, antibiotic exposure reduced both predator and prey fitness, underlying the reason antibiotics reduces the strength of predator-prey interaction. Despite the indirect benefits of prey gain from this, the presence of predators can expedite the process of prey extinction caused by antibiotic exposure.

Ecological dependencies and the illusion of cooperation in microbial communities

Ecological dependencies - where organisms rely on other organisms for survival - are a ubiquitous feature of life on earth. Multicellular hosts rely on symbionts to provide essential vitamins and amino acids. Legume plants similarly rely on nitrogen-fixing rhizobia to convert atmospheric nitrogen to ammonia. In some cases, dependencies can arise via loss-of-function mutations that allow one partner to benefit from the actions of another. It is common in microbiology to label ecological dependencies between species as cooperation - making it necessary to invoke cooperation-specific frameworks to explain the phenomenon. However, in many cases, such traits are not (at least initially) cooperative, because they are not selected for because of the benefits they confer on a partner species. In contrast, dependencies in microbial communities may originate from fitness benefits gained from genomic-streamlining (i.e. Black Queen Dynamics). Here, we outline how the Black Queen Hypothesis predicts the formation of metabolic dependencies via loss-of-function mutations in microbial communities, without needing to invoke any cooperation-specific explanations. Furthermore we outline how the Black Queen Hypothesis can act as a blueprint for true cooperation as well as discuss key outstanding questions in the field. The nature of interactions in microbial communities can predict the ability of natural communities to withstand and recover from disturbances. Hence, it is vital to gain a deeper understanding of the factors driving these dynamic interactions over evolutionary time.

Artificial selection of microbial communities: what have we learnt and how can we improve?

Microbial communities are capable of performing diverse functions with important bioindustrial and medical applications. One approach to improving community function is to breed new communities by artificially selecting for those displaying high community function ('community selection'). Importantly, community selection can improve the function of interest without needing to understand how the function arises, just like in classical artificial selection of individuals. However, experimental studies of community selection have had varied and largely limited success. Here, we review a conceptual framework to help foster an understanding of community selection and its associated challenges, and provide broad insights for designing effective selection strategies.

Elevated CO2 and nitrogen addition enhance the symbiosis and functions of rhizosphere microorganisms under cadmium exposure

Soil microbes are fundamental to ecosystem health and productivity. How soil microbial communities are influenced by elevated atmospheric carbon dioxide (eCO2) concentration and nitrogen (N) deposition under heavy metal pollution remains uncertain, despite global exposure of terrestrial ecosystems to eCO2, high N deposition and heavy metal stress. Here, we conducted a four year's open-top chamber experiment to assess the effects of soil cadmium (Cd) treatment (10 kg hm-2 year-1) alone and combined treatments of Cd with eCO2 concentration (700 ppm) and/or N addition (100 kg hm-2 year-1) on tree growth and rhizosphere microbial community. Relative to Cd treatment alone, eCO2 concentration in Cd contaminated soil increased the complexity of microbial networks, including the number links, average degree and positive/negative ratios. The combined effect of eCO2 and N addition in Cd contaminated soil not only increased the complexity of microbial networks, but also enhanced the abundance of microbial urealysis related UreC and nitrifying related amoA1 and amoA2, and the richness of arbuscular mycorrhiza fungi (AMF), thereby improving the symbiotic functions between microorganisms and plants. Results from correlation analysis and structural equation model (SEM) further demonstrated that eCO2 concentration and N addition acted on functions and networks differently. Elevated CO2 positively regulated microbial networks and functions through phosphorus (P) and Cd concentration in roots, while N addition affected microbial functions through soil available N and soil organic carbon (SOC) concentration and microbial network through soil Cd concentration. Overall, our findings highlight that eCO2 concentration and N addition make microbial communities towards ecosystem health that may mitigate Cd stress, and provide new insights into the microbiology supporting phytoremediation for Cd contaminated sites in current and future global change scenarios.

Facilitation and competition deconstructed: a mechanistic modelling approach to the stress gradient hypothesis applied to drylands

Facilitative interactions among species are key in plant communities. While experimental tests support the Stress Gradient Hypothesis (SGH) as an association between facilitation and stress, whether the shape of net effects along stress gradients can be predicted is controversial, with no available mathematical modelling approaches. We proposed a novel test, using a modification of the R* model to study how negative and positive partial effects of plant interactions in drylands combine along two common stress gradients. We modelled different interactions: competition for water and light, amelioration of soil infiltration and/or grazing protection, obtaining that intensity and importance of facilitation did not generally increase along stress gradients, being dependent on the interaction type. While along the water stress gradient net interactions became more positive, reaching a maximum and then waning again, various outcomes were observed along the grazing gradient. Shape variety was mainly driven by the various shapes of the partial positive effects. Under resource stress, additive interaction effects can be expected, whereas when including grazing, the effects were non-additive. In the context of the SGH, deconstructing the effect of positive and negative interaction in a pairwise mechanistic models of drylands does not show a unique shape along stress gradients.

Interspecific competition prevents the proliferation of social cheaters in an unstructured environment

Bacterial communities are intricate ecosystems in which various members interact, compete for resources, and influence each other's growth. Antibiotics intensify this complexity, posing challenges in maintaining biodiversity. In this study, we delved into the behavior of kin bacterial communities when subjected to antibiotic perturbations, with a particular focus on how interspecific interactions shape these responses. We hypothesized that social cheating-where resistant strains shield both themselves and neighboring cheaters-obstructed coexistence, especially when kin bacteria exhibited varied growth rates and antibiotic sensitivities. To explore potential pathways to coexistence, we incorporated a third bacterial member, anticipating a shift in the dynamics of community coexistence. Simulations and experimental bacterial communities confirmed our predictions, emphasizing the pivotal role of interspecific competition in promoting coexistence under antibiotic interference. These insights are crucial for understanding bacterial ecosystem stability, interpreting drug-microbiome interactions, and predicting bacterial community adaptations to environmental changes.

Soil organic carbon loss decreases biodiversity but stimulates multitrophic interactions that promote belowground metabolism

Soil organic carbon (SOC) plays an essential role in mediating community structure and metabolic activities of belowground biota. Unraveling the evolution of belowground communities and their feedback mechanisms on SOC dynamics helps embed the ecology of soil microbiome into carbon cycling, which serves to improve biodiversity conservation and carbon management strategy under global change. Here, croplands with a SOC gradient were used to understand how belowground metabolisms and SOC decomposition were linked to the diversity, composition, and co-occurrence networks of belowground communities encompassing archaea, bacteria, fungi, protists, and invertebrates. As SOC decreased, the diversity of prokaryotes and eukaryotes also decreased, but their network complexity showed contrasting patterns: prokaryotes increased due to intensified niche overlap, while that of eukaryotes decreased possibly because of greater dispersal limitation owing to the breakdown of macroaggregates. Despite the decrease in biodiversity and SOC stocks, the belowground metabolic capacity was enhanced as indicated by increased enzyme activity and decreased enzymatic stoichiometric imbalance. This could, in turn, expedite carbon loss through respiration, particularly in the slow-cycling pool. The enhanced belowground metabolic capacity was dominantly driven by greater multitrophic network complexity and particularly negative (competitive and predator-prey) associations, which fostered the stability of the belowground metacommunity. Interestingly, soil abiotic conditions including pH, aeration, and nutrient stocks, exhibited a less significant role. Overall, this study reveals a greater need for soil C resources across multitrophic levels to maintain metabolic functionality as declining SOC results in biodiversity loss. Our researchers highlight the importance of integrating belowground biological processes into models of SOC turnover, to improve agroecosystem functioning and carbon management in face of intensifying anthropogenic land-use and climate change.

Root-associated bacterial microbiome shaped by root selective effects benefits phytostabilization by Athyrium wardii (Hook.)

The root-associated microbiome assembly substantially promotes (hyper)accumulator plant growth and metal accumulation and is influenced by multiple factors, especially host species and environmental stress. Athyrium wardii (Hook.) is a phytostabilizer that grows in lead (Pb)-zinc (Zn) mine tailings and shows high root Pb accumulation. However, there remains little information on the assembly of the root-associated microbiome of A. wardii and its role in phytostabilization. A field study investigated the structural and functional variation in the root-associated bacterial microbiome of Athyrium wardii (Hook.) exposed to different levels of contamination in Pb-Zn mine tailings. The root compartment dominated the variation in the root-associated bacterial microbiome but the levels of contaminants showed less impact. Bacterial co-occurrence was enhanced in the rhizosphere soil and rhizoplane but tended to be much simpler in the endosphere in terms of network complexity and connectivity. This indicates that the microbial community assembly of A. wardii was non-random and shaped by root selective effects. Proteobacteria, Chloroflexi, Actinobacteria, Cyanobacteria, and Acidobacteriota were generally the dominant bacterial phyla. The genera Crossiella and Bradyrhizobium were enriched in the rhizosphere and cyanobacterial genera were enriched in the endosphere, demonstrating substantial advantages to plant survival and adaptation in the harsh mine environment. Functional categories involved in amino acid and carbohydrate metabolism were abundant in the rhizosphere soil, thus contributing to metal solubility and bioavailability in the rhizosphere. Membrane transporters, especially ATP-binding cassette transporters, were enriched in the endosphere, indicating a potential role in metal tolerance and transportation in A. wardii. The study shows substantial variation in the structure and function of microbiomes colonizing different compartments, with the rhizosphere and endophytic microbiota potentially involved in plant metal tolerance and accumulation during phytostabilization.

Metabolic interactions affect the biomass of synthetic bacterial biofilm communities

IMPORTANCE

Co-occurrence network analysis is an effective tool for predicting complex networks of microbial interactions in the natural environment. Using isolates from a rhizosphere, we constructed multi-species biofilm communities and investigated co-occurrence patterns between microbial species in genome-scale metabolic models and in vitro experiments. According to our results, metabolic exchanges and resource competition may partially explain the co-occurrence network analysis results found in synthetic bacterial biofilm communities.

From microbiome composition to functional engineering, one step at a time

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.

Master regulators of biological systems in higher dimensions

A longstanding goal of biology is to identify the key genes and species that critically impact evolution, ecology, and health. Network analysis has revealed keystone species that regulate ecosystems and master regulators that regulate cellular genetic networks. Yet these studies have focused on pairwise biological interactions, which can be affected by the context of genetic background and other species present, generating higher-order interactions. The important regulators of higher-order interactions are unstudied. To address this, we applied a high-dimensional geometry approach that quantifies epistasis in a fitness landscape to ask how individual genes and species influence the interactions in the rest of the biological network. We then generated and also reanalyzed 5-dimensional datasets (two genetic, two microbiome). We identified key genes (e.g., the rbs locus and pykF) and species (e.g., Lactobacilli) that control the interactions of many other genes and species. These higher-order master regulators can induce or suppress evolutionary and ecological diversification by controlling the topography of the fitness landscape. Thus, we provide a method and mathematical justification for exploration of biological networks in higher dimensions.

Moderate anthropogenic disturbance stimulates versatile microbial taxa contributing to denitrification and aromatic compound degradation

Wastewater treatment plants (WWTPs) effluent often contains a significant amount of residual organic pollutants and nutrients, causing disturbance to the coastal effluent receiving areas (ERA). Microbial communities in coastal ERA sediments may benefit from the coexistence of organic pollutants and nutrients, promoting the emergence of versatile taxa that are capable of eliminating these substances simultaneously. However, the identification and exploration of versatile taxa in natural environments under anthropogenic disturbances remain largely uncharted territory. In this study, we specifically focused on the versatile taxa coupled by the degradation of aromatic compounds (ACs) and denitrification, using Hangzhou Bay in China as our study area. We explored how WWTPs effluent disturbance would affect the versatile taxa, and particularly examined the role of disturbance intensity in shaping their composition. Intriguingly, we found that versatile taxa were mainly derived from denitrifiers like Pseudomonas, suggesting the fulfilled potential of denitrifiers regarding ACs degradation. We also discovered that moderate disturbance stimulated the diversity of versatile taxa, resulting in strengthened functional redundancy. Through correlation network analysis, we further demonstrated that moderate disturbance enhanced the community-level cooperation. Thus, moderate disturbance serves as a catalyst for versatile taxa to maintain community function, making them more resilient to effluent disturbances. Additionally, we identified COD and NO3--N concentrations as significant environmental factors influencing the versatile taxa. Overall, our findings reveal the role of effluent disturbances in the promotion of versatile taxa, and highlight moderate disturbance can foster more robust versatile taxa that are better equipped to handle effluent disturbances.

Metabolic exchanges are ubiquitous in natural microbial communities

Microbial communities drive global biogeochemical cycles and shape the health of plants and animals-including humans. Their structure and function are determined by ecological and environmental interactions that govern the assembly, stability and evolution of microbial communities. A widely held view is that antagonistic interactions such as competition predominate in microbial communities and are ecologically more important than synergistic interactions-for example, mutualism or commensalism. Over the past decade, however, a more nuanced picture has emerged, wherein bacteria, archaea and fungi exist within interactive networks in which they exchange essential and non-essential metabolites. These metabolic interactions profoundly impact not only the physiology, ecology and evolution of the strains involved, but are also central to the functioning of many, if not all, microbiomes. Therefore, we advocate for a balanced view of microbiome ecology that encompasses both synergistic and antagonistic interactions as key forces driving the structure and dynamics within microbial communities.

On the De Novo Emergence of Ecological Interactions during Evolutionary Diversification: A Conceptual Framework and Experimental Test

AbstractEcological interactions are crucial to the structure and function of biological communities, but we lack a causal understanding of the forces shaping their emergence during evolutionary diversification. Here we provide a conceptual framework linking different modes of diversification (e.g., ecological diversification), which depend on environmental characteristics, to the evolution of different forms of ecological interactions (e.g., resource partitioning) in asexual lineages. We tested the framework by examining the net interactions in communities of Pseudomonas aeruginosa produced via experimental evolution in nutritionally simple (SIM) or complex (COM) environments by contrasting the productivity and competitive fitness of whole evolved communities relative to their component isolates. As expected, we found that nutritional complexity drove the evolution of communities with net positive interactions whereas SIM communities had similar performance as their component isolates. A follow-up experiment revealed that high fitness in two COM communities was driven by rare variants (frequency <0.1%) that antagonized PA14, the ancestral strain and common competitor used in fitness assays. Our study suggests that the evolution of de novo ecological interactions in asexual lineages is predictable at a broad scale from environmental conditions. Further, our work demonstrates that rare variants can disproportionately impact the function of relatively simple microbial communities.

Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes

Microbiome engineering offers the potential to leverage microbial communities to improve outcomes in human health, agriculture, and climate. To translate this potential into reality, it is crucial to reliably predict community composition and function. But a brute force approach to cataloging community function is hindered by the combinatorial explosion in the number of ways we can combine microbial species. An alternative is to parameterize microbial community outcomes using simplified, mechanistic models, and then extrapolate these models beyond where we have sampled. But these approaches remain data-hungry, as well as requiring an a priori specification of what kinds of mechanisms are included and which are omitted. Here, we resolve both issues by introducing a mechanism-agnostic approach to predicting microbial community compositions and functions using limited data. The critical step is the identification of a sparse representation of the community landscape. We then leverage this sparsity to predict community compositions and functions, drawing from techniques in compressive sensing. We validate this approach on in silico community data, generated from a theoretical model. By sampling just [Formula: see text]1% of all possible communities, we accurately predict community compositions out of sample. We then demonstrate the real-world application of our approach by applying it to four experimental datasets and showing that we can recover interpretable, accurate predictions on composition and community function from highly limited data.

Global patterns in gene content of soil microbiomes emerge from microbial interactions

Microbial metabolism sustains life on Earth. Sequencing surveys of communities in hosts, oceans, and soils have revealed ubiquitous patterns linking the microbes present, the genes they possess, and local environmental conditions. One prominent explanation for these patterns is environmental filtering: local conditions select strains with particular traits. However, filtering assumes ecological interactions do not influence patterns, despite the fact that interactions can and do play an important role in structuring communities. Here, we demonstrate the insufficiency of the environmental filtering hypothesis for explaining global patterns in topsoil microbiomes. Using denitrification as a model system, we find that the abundances of two characteristic genotypes trade-off with pH; nar gene abundances increase while nap abundances decrease with declining pH. Contradicting the filtering hypothesis, we show that strains possessing the Nar genotype are enriched in low pH conditions but fail to grow alone. Instead, the dominance of Nar genotypes at low pH arises from an ecological interaction with Nap genotypes that alleviates nitrite toxicity. Our study provides a roadmap for dissecting how global associations between environmental variables and gene abundances arise from environmentally modulated community interactions.

Salinity-triggered homogeneous selection constrains the microbial function and stability in lakes

Climate change and anthropogenic exploitation have led to the gradual salinization of inland waters worldwide. However, the impacts of this process on the prokaryotic plankton communities and their role in biogeochemical cycles in the inland lake are poorly known. Here, we take a space-for-time substitution approach, using 16S rRNA gene amplicon sequencing and metagenomic sequencing. We analyzed the prokaryotic plankton communities of 11 lakes in northwest China, with average water salinities ranging from 0.002 to 14.370%. The results demonstrated that, among the various environmental parameters, salinity was the most important driver of prokaryotic plankton β-diversity (Mantel test, r = 0.53, P < 0.001). (1) Under low salinity, prokaryotic planktons were assembled by stochastic processes and employed diverse halotolerant strategies, including the synthesis and uptake of compatible solutes and extrusion of Na+ or Li+ in exchange for H+. Under elevated salinity pressure, strong homogeneous selection meant that only planktonic prokaryotes showing an energetically favorable halotolerant strategy employing an Mnh-type Na+/H+ antiporter remained. (2) The decreasing taxonomic diversity caused by intense environmental filtering in high-salinity lakes impaired functional diversity related to substance metabolism. The prokaryotes enhanced the TCA cycle, carbon fixation, and low-energy-consumption amino acid biosynthesis in high-salinity lakes. (3) Elevated salinity pressure decreased the negative:positive cohesion and the modularity of the molecular ecology networks for the planktonic prokaryotes, indicating a precarious microbial network. Our findings provide new insights into plankton ecology and are helpful for the protecting of the biodiversity and function of inland lakes against the background of salinization. KEY POINTS: • Increased salinity enhances homogeneous selection in the microbial assembly. • Elevated salinity decreases the microbial co-occurrence networks stability. • High salinity damages the microbial function diversity.

Interspecies interactions determine growth dynamics of biopolymer-degrading populations in microbial communities

Microbial communities perform essential ecosystem functions such as the remineralization of organic carbon that exists as biopolymers. The first step in mineralization is performed by biopolymer degraders, which harbor enzymes that can break down polymers into constituent oligo- or monomeric forms. The released nutrients not only allow degraders to grow, but also promote growth of cells that either consume the degradation products, i.e., exploiters, or consume metabolites released by the degraders or exploiters, i.e., scavengers. It is currently not clear how such remineralizing communities assemble at the microscale-how interactions between the different guilds influence their growth and spatial distribution, and hence the development and dynamics of the community. Here, we address this knowledge gap by studying marine microbial communities that grow on the abundant marine biopolymer alginate. We used batch growth assays and microfluidics coupled to time-lapse microscopy to quantitatively investigate growth and spatial distribution of single cells. We found that the presence of exploiters or scavengers alters the spatial distribution of degrader cells. In general, exploiters and scavengers-which we collectively refer to as cross-feeder cells-slowed down the growth of degrader cells. In addition, coexistence with cross-feeders altered the production of the extracellular enzymes that break down polymers by degrader cells. Our findings reveal that ecological interactions by nondegrading community members have a profound impact on the functions of microbial communities that remineralize carbon biopolymers in nature.

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.

Unraveling the complexities of Cd-aniline composite pollution: Insights from standalone and joint toxicity assessments in a bacterial community

Cadmium (Cd) and aniline frequently co-occur in industrial settings but have rarely been addressed as composite toxicants in terms of the overall toxicity despite extensive knowledge of the environmental impact of each individual pollutant. In this study, we attempt to assess the relation of individual and combined toxic effects of Cd and aniline using a bacterial consortium cultured from soils as a model system. Results showed that the consortial bacteria exhibited drastically stronger tolerance to stand-alone Cd and aniline in comparison to literature data acquired from single species studies. When occurring simultaneously, the joint toxicity displayed a concentration-dependent behavior that wasn't anticipated based on individual chemical tests. Specifically, additive effects manifested with Cd and aniline at their IC10s, but changed to synergistic when the concentrations increased to IC20, and finally transitioned into antagonistic at IC30s and beyond. In addition, co-occurring aniline appeared to have retarded the cellular accumulation of Cd while increasing the enzymatic activities of superoxide dismutase and catalase relative to that in Cd-alone treatments. Finally, the bacterial community experienced distinct compositional changes under solo and combined toxicities with several genera exhibiting inconsistent behavior between treatments of single and composite toxicants. Findings from this study highlight the complexity of bacterial response to composite pollutions and point to the need for more comprehensive references in risk and toxicology assessment at multi-chemical contamination sites.

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.

The impact of phage and phage resistance on microbial community dynamics

Where there are bacteria, there will be bacteriophages. These viruses are known to be important players in shaping the wider microbial community in which they are embedded, with potential implications for human health. On the other hand, bacteria possess a range of distinct immune mechanisms that provide protection against bacteriophages, including the mutation or complete loss of the phage receptor, and CRISPR-Cas adaptive immunity. Yet little is known about how interactions between phages and these different phage resistance mechanisms affect the wider microbial community in which they are embedded. Here, we conducted a 10-day, fully factorial evolution experiment to examine how phage impact the structure and dynamics of an artificial four-species bacterial community that includes either Pseudomonas aeruginosa wild type or an isogenic mutant unable to evolve phage resistance through CRISPR-Cas. Our results show that the microbial community structure is drastically altered by the addition of phage, with Acinetobacter baumannii becoming the dominant species and P. aeruginosa being driven nearly extinct, whereas P. aeruginosa outcompetes the other species in the absence of phage. Moreover, we find that a P. aeruginosa strain with the ability to evolve CRISPR-based resistance generally does better when in the presence of A. baumannii, but that this benefit is largely lost over time as phage is driven extinct. Combined, our data highlight how phage-targeting a dominant species allows for the competitive release of the strongest competitor whilst also contributing to community diversity maintenance and potentially preventing the reinvasion of the target species, and underline the importance of mapping community composition before therapeutically applying phage.

A spatially structured mathematical model of the gut microbiome reveals factors that increase community stability

Given the importance of gut microbial communities for human health, we may want to ensure their stability in terms of species composition and function. Here, we built a mathematical model of a simplified gut composed of two connected patches where species and metabolites can flow from an upstream patch, allowing upstream species to affect downstream species' growth. First, we found that communities in our model are more stable if they assemble through species invasion over time compared to combining a set of species from the start. Second, downstream communities are more stable when species invade the downstream patch less frequently than the upstream patch. Finally, upstream species that have positive effects on downstream species can further increase downstream community stability. Despite it being quite abstract, our model may inform future research on designing more stable microbial communities or increasing the stability of existing ones.

Inter-bacterial mutualism promoted by public goods in a system characterized by deterministic temperature variation

Mutualism is commonly observed in nature but not often reported for bacterial communities. Although abiotic stress is thought to promote microbial mutualism, there is a paucity of research in this area. Here, we monitor microbial communities in a quasi-natural composting system, where temperature variation (20 °C-70 °C) is the main abiotic stress. Genomic analyses and culturing experiments provide evidence that temperature selects for slow-growing and stress-tolerant strains (i.e., Thermobifida fusca and Saccharomonospora viridis), and mutualistic interactions emerge between them and the remaining strains through the sharing of cobalamin. Comparison of 3000 bacterial pairings reveals that mutualism is common (~39.1%) and competition is rare (~13.9%) in pairs involving T. fusca and S. viridis. Overall, our work provides insights into how high temperature can favour mutualism and reduce competition at both the community and species levels.

Strong succession in prokaryotic association networks and community assembly mechanisms in an acid mine drainage-impacted riverine ecosystem

Acid mine drainage (AMD) serves as an ideal model system for investigating microbial ecology, interaction, and assembly mechanism in natural environments. While previous studies have explored the structure and function of microbial communities in AMD, the succession patterns of microbial association networks and underlying assembly mechanisms during natural attenuation processes remain elusive. Here, we investigated prokaryotic microbial diversity and community assembly along an AMD-impacted river, from the extremely acidic, heavily polluted headwaters to the nearly neutral downstream sites. Microbial diversity was increased along the river, and microbial community composition shifted from acidophile-dominated to freshwater taxa-dominated communities. The complexity and relative modularity of the microbial networks were also increased, indicating greater network stability during succession. Deterministic processes, including abiotic selection of pH and high contents of sulfur and iron, governed community assembly in the headwaters. Although the stochasticity ratio was increased downstream, manganese content, microbial negative cohesion, and relative modularity played important roles in shaping microbial community structure. Overall, this study provides valuable insights into the ecological processes that govern microbial community succession in AMD-impacted riverine ecosystems. These findings have important implications for in-situ remediation of AMD contamination.

Resource competition can explain simplicity in microbial community assembly

Predicting the composition and diversity of communities is a central goal in ecology. While community assembly is considered hard to predict, laboratory microcosms often follow a simple assembly rule based on the outcome of pairwise competitions. This assembly rule predicts that a species that is excluded by another species in pairwise competition cannot survive in a multispecies community with that species. Despite the empirical success of this bottom-up prediction, its mechanistic origin has remained elusive. In this study, we elucidate how this simple pattern in community assembly can emerge from resource competition. Our geometric analysis of a consumer-resource model shows that trio community assembly is always predictable from pairwise outcomes when one species grows faster than another species on every resource. We also identify all possible trio assembly outcomes under three resources and find that only two outcomes violate the assembly rule. Simulations demonstrate that pairwise competitions accurately predict trio assembly with up to 100 resources and the assembly of larger communities containing up to twelve species. We then further demonstrate accurate quantitative prediction of community composition using the harmonic mean of pairwise fractions. Finally, we show that cross-feeding between species does not decrease assembly rule prediction accuracy. Our findings highlight that simple community assembly can emerge even in ecosystems with complex underlying dynamics.

Exploring the Frequency and Distribution of Ecological Non-monotonicity in Associations among Ecosystem Constituents

Complex links between biotic and abiotic constituents are fundamental for the functioning of ecosystems. Although non-monotonic interactions and associations are known to increase the stability, diversity, and productivity of ecosystems, they are frequently ignored by community-level standard statistical approaches. Using the copula-based dependence measure qad, capable of quantifying the directed and asymmetric dependence between variables for all forms of (functional) relationships, we determined the proportion of non-monotonic associations between different constituents of an ecosystem (plants, bacteria, fungi, and environmental parameters). Here, we show that up to 59% of all statistically significant associations are non-monotonic. Further, we show that pairwise associations between plants, bacteria, fungi, and environmental parameters are specifically characterized by their strength and degree of monotonicity, for example, microbe-microbe associations are on average stronger than and differ in degree of non-monotonicity from plant-microbe associations. Considering directed and non-monotonic associations, we extended the concept of ecosystem coupling providing more complete insights into the internal order of ecosystems. Our results emphasize the importance of ecological non-monotonicity in characterizing and understanding ecosystem patterns and processes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10021-023-00867-9.

A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia

Harnessing the power of microbial consortia is integral to a diverse range of sectors, from healthcare to biotechnology to environmental remediation. To fully realize this potential, it is critical to understand the mechanisms behind the interactions that structure microbial consortia and determine their functions. Constraint-based reconstruction and analysis (COBRA) approaches, employing genome-scale metabolic models (GEMs), have emerged as the state-of-the-art tool to simulate the behavior of microbial communities from their constituent genomes. In the last decade, many tools have been developed that use COBRA approaches to simulate multi-species consortia, under either steady-state, dynamic, or spatiotemporally varying scenarios. Yet, these tools have not been systematically evaluated regarding their software quality, most suitable application, and predictive power. Hence, it is uncertain which tools users should apply to their system and what are the most urgent directions that developers should take in the future to improve existing capacities. This study conducted a systematic evaluation of COBRA-based tools for microbial communities using datasets from two-member communities as test cases. First, we performed a qualitative assessment in which we evaluated 24 published tools based on a list of FAIR (Findability, Accessibility, Interoperability, and Reusability) features essential for software quality. Next, we quantitatively tested the predictions in a subset of 14 of these tools against experimental data from three different case studies: a) syngas fermentation by C. autoethanogenum and C. kluyveri for the static tools, b) glucose/xylose fermentation with engineered E. coli and S. cerevisiae for the dynamic tools, and c) a Petri dish of E. coli and S. enterica for tools incorporating spatiotemporal variation. Our results show varying performance levels of the best qualitatively assessed tools when examining the different categories of tools. The differences in the mathematical formulation of the approaches and their relation to the results were also discussed. Ultimately, we provide recommendations for refining future GEM microbial modeling tools.

Combined effect of simulated microgravity and low-dose ionizing radiation on structure and antibiotic resistance of a synthetic community model of bacteria isolated from spacecraft assembly room

Understanding the structural and antibiotic resistance changes of microbial communities in space environments is critical for identifying potential pathogens that may pose health risks to astronauts and for preventing and controlling microbial contamination. The research to date on microbes under simulated space factors has primarily been carried out on single bacterial species under the individual effects of microgravity or low-dose radiation. However, microgravity (MG) and low-dose ionizing radiation (LDIR) coexist in the actual spacecraft environment, and microorganisms coexist as communities in the spacecraft environment. Thus, the microbial response to the real changes present during space habitation has not been adequately explored. To address this knowledge gap, we compared the dynamics of community composition and antibiotic resistance of synthetic bacterial communities under simulated microgravit, low-dose ionizing radiation, and the conditions combined, as it occurs in spacecraft. To ensure representative bacteria were selected, we co-cultured of 12 bacterial strains isolated from spacecraft cleanrooms. We found that the weakened competition between communities increased the possibility of species coexistence, community diversity, and homogeneity. The number of Bacilli increased significantly, while different species under the combined conditions showed various changes in abundance compared to those under the individual conditions. The resistance of the synthetic community to penicillins increased significantly under low doses of ionizing radiation but did not change significantly under simulated microgravity or the combined conditions. The results of functional predictions revealed that antibiotic biosynthesis and resistance increased dramatically in the community under space environmental stress, which confirmed the results of the drug sensitivity assays. Our results show that combined space environmental factors exert different effects on the microbial community structure and antibiotic resistance, which provides new insights into our understanding of the mechanisms of evolution of microorganisms in spacecraft, and is relevant to effective microbial pollution prevention and control strategies.

Depth and contaminant-shaped bacterial community structure and assembly at an aged chlorinated aliphatic hydrocarbon-contaminated site

Chlorinated aliphatic hydrocarbons (CAHs) are potentially toxic substances that have been detected in various contaminated environments. Biological elimination is the main technique of detoxifying CAHs in the contaminated sites, but the soil bacterial community at CAH-contaminated sites have been little investigated. Here, high-throughput sequencing analysis of soil samples from different depths (to 6 m depth) at an aged CAH-contaminated site has been conducted to investigate the community composition, function, and assembly of soil bacteria. The alpha diversity of the bacterial community significantly increased with increasing depth and bacterial community also became more convergent with increasing depth. Organohalide-respiring bacteria (OHRB) is considered keystone taxa to reduce the environmental stress of CAHs by reductive dechlorinate CAHs into nontoxic products, increases the alpha diversity of bacterial community and improves the stability of bacterial co-occurrence network. The high concentration of CAHs in deep soil and the stable anaerobic environment make deterministic processes dominate bacterial community assembly, while the topsoil is dominated by dispersal limitation. In general, CAHs at contaminated sites have a great impact on bacterial community, but the CAHs metabolic community acclimated in deep soil can reduce the environmental stress of CAHs, which provides foundation for the monitored natural attenuation technology in CAHs-contaminated sites.

Deciphering Interactions Within a 4-Strain Riverine Bacterial Community

The dynamics of a community of four planktonic bacterial strains isolated from river water was followed in R2 broth for 72 h in batch experiments. These strains were identified as Janthinobacterium sp., Brevundimonas sp., Flavobacterium sp. and Variovorax sp. 16S rRNA gene sequencing and flow cytometry analyses were combined to monitor the change in abundance of each individual strain in bi-cultures and quadri-culture. Two interaction networks were constructed that summarize the impact of the strains on each other's growth rate in exponential phase and carrying capacity in stationary phase. The networks agree on the absence of positive interactions but also show differences, implying that ecological interactions can be specific to particular growth phases. Janthinobacterium sp. was the fastest growing strain and dominated the co-cultures. However, its growth rate was negatively affected by the presence of other strains 10 to 100 times less abundant than Janthinobacterium sp. In general, we saw a positive correlation between growth rate and carrying capacity in this system. In addition, growth rate in monoculture was predictive of carrying capacity in co-culture. Taken together, our results highlight the necessity to take growth phases into account when measuring interactions within a microbial community. In addition, evidence that a minor strain can greatly influence the dynamics of a dominant one underlines the necessity to choose population models that do not assume a linear dependency of interaction strength to abundance of other species for accurate parameterization from such empirical data.

A three-species synthetic community model whose rapid response to antagonism allows the study of higher-order dynamics and emergent properties in minutes

Microbial communities can be considered complex adaptive systems. Understanding how these systems arise from different components and how the dynamics of microbial interactions allow for species coexistence are fundamental questions in ecology. To address these questions, we built a three-species synthetic community, called BARS (Bacillota A + S + R). Each species in this community exhibits one of three ecological roles: Antagonistic, Sensitive, or Resistant, assigned in the context of a sediment community. We show that the BARS community reproduces features of complex communities and exhibits higher-order interaction (HOI) dynamics. In paired interactions, the majority of the S species (Sutcliffiella horikoshii 20a) population dies within 5 min when paired with the A species (Bacillus pumilus 145). However, an emergent property appears upon adding the third interactor, as antagonism of species A over S is not observed in the presence of the R species (Bacillus cereus 111). For the paired interaction, within the first 5 min, the surviving population of the S species acquires tolerance to species A, and species A ceases antagonism. This qualitative change reflects endogenous dynamics leading to the expression for tolerance to an antagonistic substance. The stability reached in the triple interaction exhibits a nonlinear response, highly sensitive to the density of the R species. In summary, our HOI model allows the study of the assembly dynamics of a three-species community and evaluating the immediate outcome within a 30 min frame. The BARS has features of a complex system where the paired interactions do not predict the community dynamics. The model is amenable to mechanistic dissection and to modeling how the parts integrate to achieve collective properties.

Stress-induced metabolic exchanges between complementary bacterial types underly a dynamic mechanism of inter-species stress resistance

Metabolic cross-feeding plays vital roles in promoting ecological diversity. While some microbes depend on exchanges of essential nutrients for growth, the forces driving the extensive cross-feeding needed to support the coexistence of free-living microbes are poorly understood. Here we characterize bacterial physiology under self-acidification and establish that extensive excretion of key metabolites following growth arrest provides a collaborative, inter-species mechanism of stress resistance. This collaboration occurs not only between species isolated from the same community, but also between unrelated species with complementary (glycolytic vs. gluconeogenic) modes of metabolism. Cultures of such communities progress through distinct phases of growth-dilution cycles, comprising of exponential growth, acidification-triggered growth arrest, collaborative deacidification, and growth recovery, with each phase involving different combinations of physiological states of individual species. Our findings challenge the steady-state view of ecosystems commonly portrayed in ecological models, offering an alternative dynamical view based on growth advantages of complementary species in different phases.

The characteristics and metabolic potentials of the soil bacterial community of two typical military demolition ranges in China

The response mechanism of soil microbiota in military polluted sites can effectively indicate the biotoxicity of ammunition. In this study, two military demolition ranges polluted soils of grenades and bullet were collected. According to high-throughput sequencing, after grenade explosion, the dominant bacteria in Site 1 (S1) are Proteobacteria (97.29 %) and Actinobacteria (1.05 %). The dominant bacterium in Site 2 (S2) is Proteobacteria (32.95 %), followed by Actinobacteria (31.17 %). After the military exercise, the soil bacterial diversity index declined significantly, and the bacterial communities interacted more closely. The indigenous bacteria in S1 were influenced more compared to those in S2. According to the environmental factor analysis, the bacteria composition can easily be influenced by heavy metals and organic pollutants, including Cu, Pb, Cr and Trinitrotoluene (TNT). About 269 metabolic pathways annotated in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were detected in bacterial communities, including nutrition metabolism (C, 4.09 %; N, 1.14 %; S, 0.82 %), external pollutant metabolism (2.52 %) and heavy metal detoxication (2.12 %), respectively. The explosion of ammunition changes the basic metabolism of indigenous bacteria, and heavy metal stress inhibits the TNT degradation ability of bacterial communities. The pollution degree and community structure influence the metal detoxication strategy at the contaminated sites together. Heavy metal ions in S1 are mainly discharged through membrane transporters, while heavy metal ions in S2 are mainly degraded through lipid metabolism and biosynthesis of secondary metabolites. The results obtained in this study can provide deep insight into the response mechanism of the soil bacterial community in military demolition ranges with composite pollutions of heavy metals and organic substances. CAPSULE: Heavy metal stress changed the composition, interaction and metabolism of indigenous communities in military demolition ranges, especially the TNT degradation process.

Phylogenetic distance affects the artificial microbial consortia's effectiveness and colonization during the bioremediation of polluted soil with Cr(VI) and atrazine

Soils co-contaminated with heavy metals and organic pollutants are common and threaten the natural environment and human health. Although artificial microbial consortia have advantages over single strains, the mechanism affecting their effectiveness and colonization in polluted soils still requires determination. Here, we constructed two kinds of artificial microbial consortia from the same or different phylogenetic groups and inoculated them into soil co-contaminated with Cr(VI) and atrazine to study the effects of phylogenetic distance on consortia effectiveness and colonization. The residual concentrations of pollutants demonstrated that the artificial microbial consortium from different phylogenetic groups achieved the highest removal rates of Cr(VI) and atrazine. The removal rate of 400 mg/kg atrazine was 100%, while that of 40 mg/kg Cr(VI) was 57.7%. High-throughput sequence analysis showed that the soil bacterial negative correlations, core genera, and potential metabolic interactions differed among treatments. Furthermore, artificial microbial consortia from different phylogenetic groups had better colonization and a more significant effect on the abundance of native core bacteria than consortia from the same phylogenetic group. Our study highlights the importance of phylogenetic distance on consortium effectiveness and colonization and offers insight into the bioremediation of combined pollutants.

Dosage concentration and pulsing frequency affect the degradation efficiency in simulated bacterial polycyclic aromatic hydrocarbon-degrading cultures

A major source of anthropogenic polycyclic aromatic hydrocarbon (PAH) inputs into marine environments are diffuse emissions which result in low PAH concentrations in the ocean water, posing a potential threat for the affected ecosystems. However, the remediation of low-dosage PAH contaminations through microbial processes remains largely unknown. Here, we developed a process-based numerical model to simulate batch cultures receiving repeated low-dosage naphthalene pulses compared to the conventionally used one-time high-dosage. Pulsing frequency as well as dosage concentration had a large impact on the degradation efficiency. After 10 days, 99.7%, 97.2%, 86.6%, or 83.5% of the 145 mg L^-1 naphthalene was degraded when given as a one-time high-dosage or in 2, 5, or 10 repeated low-concentration dosages equally spaced throughout the experiment, respectively. If the simulation was altered, giving the system that received 10 pulses time to recover to 99.7%, pulsing patterns affected the degradation of naphthalene. When pulsing 10 days at once per day, naphthalene accumulated following each pulse and if the degradation was allowed to continue until the recovered state was reached, the incubation time was prolonged to 17 days with a generation time of 3.81 days. If a full recovery was conditional before the next pulse was added, the scenario elongated to 55 days and generation time increased to 14.15 days. This indicates that dissolution kinetics dominate biodegradation kinetics, and the biomass concentration of PAH-degrading bacteria alone is not a sufficient indicator for quantifying active biodegradation. Applying those findings to the environment, a one-time input of a high dosage is potentially degraded faster than repeated low-dosage PAH pollution and repeated low-dosage input could lead to PAH accumulation in vulnerable pristine environments. Further research on the overlooked field of chronic low-dosage PAH contamination is necessary.