A meta-analysis of changes in bacterial and archaeal communities with time

Deciphering microbial metabolic interactions and their implications for community dynamics in acid mine drainage sediments

The microbially-mediated reduction processes have potential for the bioremediation of acid mine drainage (AMD), which represents a worldwide environment problem. However, we know little about the microbial interactions in anaerobic AMD sediments. Here we utilized genome-resolved metagenomics to uncover the nature of cooperative and competitive metabolic interactions in 90 AMD sediments across Southern China. Our analyses recovered well-represented prokaryotic communities through the reconstruction of 2625 population genomes. Functional analyses of these genomes revealed extensive metabolic handoffs which occurred more frequently in nitrogen metabolism than in sulfur metabolism, as well as stable functional redundancy across sediments resulting from populations with low genomic relatedness. Genome-scale metabolic modeling showed that metabolic competition promoted microbial co-occurrence relationships, suggesting that community assembly was dominated by habitat filtering in sediments. Notably, communities colonizing more extreme conditions tended to be highly competitive, which was typically accompanied with increased network complexity but decreased stability of the microbiome. Finally, our results demonstrated that heterotrophic Thermoplasmatota associated with ferric iron and sulfate reduction contributed most to the elevated levels of competition. Our study shed light on the cooperative and competitive metabolisms of microbiome in the hazardous AMD sediments, which may provide preliminary clues for the AMD bioremediation in the future.

Microbial acidification by N, S, Fe and Mn oxidation as a key mechanism for deterioration of subsea tunnel sprayed concrete

The deterioration of fibre-reinforced sprayed concrete was studied in the Oslofjord subsea tunnel (Norway). At sites with intrusion of saline groundwater resulting in biofilm growth, the concrete exhibited significant concrete deterioration and steel fibre corrosion. Using amplicon sequencing and shotgun metagenomics, the microbial taxa and surveyed potential microbial mechanisms of concrete degradation at two sites over five years were identified. The concrete beneath the biofilm was investigated with polarised light microscopy, scanning electron microscopy and X-ray diffraction. The oxic environment in the tunnel favoured aerobic oxidation processes in nitrogen, sulfur and metal biogeochemical cycling as evidenced by large abundances of metagenome-assembled genomes (MAGs) with potential for oxidation of nitrogen, sulfur, manganese and iron, observed mild acidification of the concrete, and the presence of manganese- and iron oxides. These results suggest that autotrophic microbial populations involved in the cycling of several elements contributed to the corrosion of steel fibres and acidification causing concrete deterioration.

Stochastic processes drive the dynamic assembly of bacterial communities in Salix matsudana afforested soils

Introduction

This study investigates the dynamic shifts in soil bacterial communities within a Salix matsudana afforested ecosystem transitioning from agricultural land. Understanding the temporal variability in bacterial diversity and community structures is crucial for informing forest management and conservation strategies, particularly in regions undergoing afforestation.

Methods

We employed high-throughput sequencing across three distinct months (August, September, and October) to analyze the temporal variability in bacterial community composition and diversity. Network analysis was utilized to identify keystone species and assess community stability under varying environmental conditions, including fluctuations in temperature and precipitation.

Results

We uncover significant temporal variability in bacterial diversity and community structures, which are closely tied to fluctuations in temperature and precipitation. Our findings reveal the abundance of the dominant bacterial phyla, such as Actinobacteria and Proteobacteria, which did not change overall, highlighting the stability and resilience of the microbial community across seasonal transitions. Notably, the increasing similarity in community composition from August to October indicates a reduction in species turnover, likely driven by more homogeneous environmental conditions. Through comprehensive network analysis, we identify the pivotal role of keystone species, particularly the human pathogen Nocardia, in maintaining community stability under reduced soil moisture. The observed variations in community connectivity underscore the microbial community's resilience and adaptability to seasonal shifts, with higher stability in August and October contrasting with the instability observed in September.

Discussion

These results underscore the complex interplay between stochastic and deterministic processes in bacterial community assembly, significantly shaped by prevailing environmental conditions. The insights gained from this research have far-reaching implications for forestry management and conservation strategies, particularly in regions undergoing similar afforestation efforts.

Enhancing soil petrochemical contaminant remediation through nutrient addition and exogenous bacterial introduction

Biostimulation (providing favorable environmental conditions for microbial growth) and bioaugmentation (introducing exogenous microorganisms) are effective approaches in the bioremediation of petroleum-contaminated soil. However, uncertainty remains in the effectiveness of these two approaches in practical application. In this study, we constructed mesocosms using petroleum hydrocarbon-contaminated soil. We compared the effects of adding nutrients, introducing exogenous bacterial degraders, and their combination on remediating petroleum contamination in the soil. Adding nutrients more effectively accelerated total petroleum hydrocarbon (TPH) degradation than other treatments in the initial 60 days' incubation. Despite both approaches stimulating bacterial richness, the community turnover caused by nutrient addition was gentler than bacterial degrader introduction. As TPH concentrations decreased, we observed a succession in microbial communities characterized by a decline in copiotrophic, fast-growing bacterial r-strategists with high rRNA operon (rrn) copy numbers. Ecological network analysis indicated that both nutrient addition and bacterial degrader introduction enhanced the complexity and stability of bacterial networks. Compared to the other treatment, the bacterial network with nutrient addition had more keystone species and a higher proportion of negative associations, factors that may enhance microbial community stability. Our study demonstrated that nutrient addition effectively regulates community succession and ecological interaction to accelerate the soil TPH degradation.

Genomic fingerprints of the world's soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes-more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.IMPORTANCEWe address a critical gap in our understanding of soil microorganisms and their functions, which have a profound impact on our environment. We analyzed 1,512 global soils with advanced analytics to create detailed genetic profiles (fingerprints) of soil microbiomes. Our work reveals novel patterns in how microorganisms are distributed across different soil environments. For instance, we discovered shifts in microbial potential to acquire nutrients in relation to soil acidity, as well as changes in stress responses and potential greenhouse gas emissions linked to soil structure. We also identified soils with putative high activity that had unique genomic characteristics surrounding resource acquisition, plant-microbe interactions, and fungal activity. Finally, we observed that closely related microorganisms tend to respond in similar ways to changes in their surroundings. Our work is a significant step toward comprehending the intricate world of soil microorganisms and its role in the global climate.

Synthesis of recovery patterns in microbial communities across environments

BACKGROUND

Disturbances alter the diversity and composition of microbial communities. Yet a generalized empirical assessment of microbiome responses to disturbance across different environments is needed to understand the factors driving microbiome recovery, and the role of the environment in driving these patterns.

RESULTS

To this end, we combined null models with Bayesian generalized linear models to examine 86 time series of disturbed mammalian, aquatic, and soil microbiomes up to 50 days following disturbance. Overall, disturbances had the strongest effect on mammalian microbiomes, which lost taxa and later recovered their richness, but not their composition. In contrast, following disturbance, aquatic microbiomes tended away from their pre-disturbance composition over time. Surprisingly, across all environments, we found no evidence of increased compositional dispersion (i.e., variance) following disturbance, in contrast to the expectations of the Anna Karenina Principle.

CONCLUSIONS

This is the first study to systematically compare secondary successional dynamics across disturbed microbiomes, using a consistent temporal scale and modeling approach. Our findings show that the recovery of microbiomes is environment-specific, and helps to reconcile existing, environment-specific research into a unified perspective. Video Abstract.

Resource diversity disturbs marine Vibrio diversity and community stability, but loss of Vibrio diversity enhances community stability

Vibrio is a salt-tolerant heterotrophic bacterium that occupies an important ecological niche in marine environments. However, little is known about the contribution of resource diversity to the marine Vibrio diversity and community stability. In this study, we investigated the association among resource diversity, taxonomic diversity, phylogenetic diversity, and community stability of marine Vibrio in the Beibu Gulf. V. campbellii and V. hangzhouensis were the dominant groups in seawater and sediments, respectively, in the Beibu Gulf. Higher alpha diversity was observed in the sediments than in the seawater. Marine Vibrio community assembly was dominated by deterministic processes. Pearson's correlation analysis showed that nitrite (NO 2 - -N), dissolved inorganic nitrogen (DIN), ammonium (NH 4 + -N), and pH were the main factors affecting marine Vibrio community stability in the surface, middle, and bottom layers of seawater and sediment, respectively. Partial least-squares path models (PLS-PM) demonstrated that resource diversity, water properties, nutrients, and geographical distance had important impacts on phylogenetic and taxonomic diversity. Regression analysis revealed that the impact of resource diversity on marine Vibrio diversity and community stability varied across different habitats, but loss of Vibrio diversity increases community stability. Overall, this study provided insights into the mechanisms underlying the maintenance of Vibrio diversity and community stability in marine environments.

Inoculation with adapted bacterial communities promotes development of full scale slow sand filters for drinking water production

Gravity-driven filtration through slow sand filters (SSFs) is one of the oldest methods for producing drinking water. As water passes through a sand bed, undesired microorganisms and chemicals are removed by interactions with SSF biofilm and its resident microbes. Despite their importance, the processes through which these microbial communities form are largely unknown, as are the factors affecting these processes. In this study, two SSFs constructed using different sand sources were compared to an established filter and observed throughout their maturation process. One SSF was inoculated through addition of sand scraped from established filters, while the other was not inoculated. The operational and developing microbial communities of SSFs, as well as their influents and effluents, were studied by sequencing of 16S ribosomal rRNA genes. A functional microbial community resembling that of the established SSF was achieved in the inoculated SSF, but not in the non-inoculated SSF. Notably, the non-inoculated SSF had significantly (p < 0.01) higher abundances of classes Armatimonadia, Elusimicrobia, Fimbriimonadia, OM190 (phylum Planctomycetota), Parcubacteria, Vampirivibrionia and Verrucomicrobiae. Conversely, it had lower abundances of classes Anaerolineae, Bacilli, bacteriap25 (phylum Myxococcota), Blastocatellia, Entotheonellia, Gemmatimonadetes, lineage 11b (phylum Elusimicrobiota), Nitrospiria, Phycisphaerae, subgroup 22 (phylum Acidobacteriota) and subgroup 11 (phylum Acidobacteriota). Poor performance of neutral models showed that the assembly and dispersal of SSF microbial communities was mainly driven by selection. The temporal turnover of microbial species, as estimated through the scaling exponent of the species-time relationship, was twice as high in the non-inoculated filter (0.946 ± 0.164) compared to the inoculated filter (0.422 ± 0.0431). This study shows that the addition of an inoculum changed the assembly processes within SSFs. Specifically, the rate at which new microorganisms were observed in the biofilm was reduced. The reduced temporal turnover may be driven by inoculating taxa inhibiting growth, potentially via secondary metabolite production. This in turn would allow the inoculation community to persist and contribute to SSF function.

Ecological patterns and processes of temporal turnover within lung infection microbiota

BACKGROUND

Chronic infection and consequent airway inflammation are the leading causes of morbidity and early mortality for people living with cystic fibrosis (CF). However, lower airway infections across a range of chronic respiratory diseases, including in CF, do not follow classical 'one microbe, one disease' concepts of infection pathogenesis. Instead, they are comprised of diverse and temporally dynamic lung infection microbiota. Consequently, temporal dynamics need to be considered when attempting to associate lung microbiota with changes in disease status. Set within an island biogeography framework, we aimed to determine the ecological patterns and processes of temporal turnover within the lung microbiota of 30 paediatric and adult CF patients prospectively sampled over a 3-year period. Moreover, we aimed to ascertain the contributions of constituent chronic and intermittent colonizers on turnover within the wider microbiota.

RESULTS

The lung microbiota within individual patients was partitioned into constituent chronic and intermittent colonizing groups using the Leeds criteria and visualised with persistence-abundance relationships. This revealed bacteria chronically infecting a patient were both persistent and common through time, whereas intermittently infecting taxa were infrequent and rare; respectively representing the resident and transient portions of the wider microbiota. It also indicated that the extent of chronic colonization was far greater than could be appreciated with microbiological culture alone. Using species-time relationships to measure temporal turnover and Vellend's rationalized ecological processes demonstrated turnover in the resident chronic infecting groups was conserved and underpinned principally by the deterministic process of homogenizing dispersal. Conversely, intermittent colonizing groups, representing newly arrived immigrants and transient species, drove turnover in the wider microbiota and were predominately underpinned by the stochastic process of drift. For adult patients, homogenizing dispersal and drift were found to be significantly associated with lung function. Where a greater frequency of homogenizing dispersal was observed with worsening lung function and conversely drift increased with better lung function.

CONCLUSIONS

Our work provides a novel ecological framework for understanding the temporal dynamics of polymicrobial infection in CF that has translational potential to guide and improve therapeutic targeting of lung microbiota in CF and across a range of chronic airway diseases. Video Abstract.

Oxygen-dependent biofilm dynamics in leaf decay: an in vitro analysis

Biofilms are important in the natural process of plant tissue degradation. However, fundamental knowledge of biofilm community structure and succession on decaying leaves under different oxygen conditions is limited. Here, we used 16S rRNA and ITS gene amplicon sequencing to investigate the composition, temporal dynamics, and community assembly processes of bacterial and fungal biofilms on decaying leaves in vitro. Leaves harvested from three plant species were immersed in lake water under aerobic and anaerobic conditions in vitro for three weeks. Biofilm-covered leaf samples were collected weekly and investigated by scanning electron microscopy. The results showed that community composition differed significantly between biofilm samples under aerobic and anaerobic conditions, though not among plant species. Over three weeks, a clear compositional shift of the bacterial and fungal biofilm communities was observed. The alpha diversity of prokaryotes increased over time in aerobic assays and decreased under anaerobic conditions. Oxygen availability and incubation time were found to be primary factors influencing the microbial diversity of biofilms on different decaying plant species in vitro. Null models suggest that stochastic processes governed the assembly of biofilm communities of decaying leaves in vitro in the early stages of biofilm formation and were further shaped by niche-associated factors.

Temporal profiling of sediment microbial communities in the Three Gorges Reservoir Area discovered time-dissimilarity patterns and multiple stable states

Microbial communities play vital roles in cycling nutrients and maintaining water quality in aquatic ecosystems. To better understand the dynamics of microbial communities and to pave way to effective ecological remediation, it's essential to reveal the temporal patterns of the communities and to identify their states. However, research exploring the dynamic changes of microbial communities needs a large amount of time-series data, which could be an extravagant requirement for a single study. In this research, we overcame this challenge by conducting a meta-analysis of years of accumulations of 16S rRNA high-throughput sequencing data from the Three Gorges Reservoir Area (TGRA), an ecological and environmental hotspot. For better understanding the microbial communities time-dissimilarity dynamics, three microbial communities time-dissimilarity patterns were hypothesized, and the linear pattern in the TGRA was validated. In addition, to explore the stability of microbial communities in the TGRA, two alternative stable states were revealed, and their differences in community richness, alpha diversity indices, community composition, ecological network topological properties, and metabolic functions were demonstrated. In short, two states of microbial communities showed distinct richness and alpha diversity indices, and the communities in one state were more dominated by Halomonas and Nitrosopumilaceae genera, facilitating nitrogen cycling metabolic processes; whilst the main genera of the other state were Bathyarchaeia and Methanosaeta, which favored methane-related metabolism. Moreover, different studies and environmental differences between mainstream and tributaries were attributed as the potential inducing factors of the state division. Our study provides a comprehensive insight into the dynamics and stability of microbial communities in the TGRA, and a reference for future studies on microbial community dynamics.

Temporal assembly patterns of microbial communities in three parallel bioreactors treating low-concentration coking wastewater with differing carbon source concentrations

Carbon source is an important factor of biological treatment systems, the effects of which on their temporal community assembly patterns are not sufficiently understood currently. In this study, the temporal dynamics and driving mechanisms of the communities in three parallel bioreactors for low-concentration coking wastewater (CWW) treatment with differing carbon source concentrations (S0 with no glucose addition, S1 with 200 mg/L glucose addition and S2 with 400 mg/L glucose addition) were comprehensively studied. High-throughput sequencing and bioinformatics analyses including network analysis and Infer Community Assembly Mechanisms by Phylogenetic bin-based null model (iCAMP) were used. The communities of three systems showed turnover rates of 0.0029∼0.0034 every 15 days. Network analysis results showed that the S0 network showed higher positive correlation proportion (71.43%) and clustering coefficient (0.33), suggesting that carbon source shortage in S0 promoted interactions and cooperation of microbes. The neutral community model analysis showed that the immigration rate increased from 0.5247 in S0 to 0.6478 in S2. The iCAMP analysis results showed that drift (45.89%) and homogeneous selection (31.68%) dominated in driving the assembly of all the investigated microbial communities. The contribution of homogeneous selection increased with the increase of carbon source concentrations, from 27.92% in S0 to 36.08% in S2. The OTUs participating in aerobic respiration and tricarboxylic acid (TCA) cycle were abundant among the bins mainly affected by deterministic processes, while those related to the metabolism of refractory organic pollutants in CWW such as alkanes, benzenes and phenols were abundant in the bins dominated by stochastic processes.

Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure

Understanding the assembly of multispecies microbial communities represents a significant challenge in ecology and has wide applications in agriculture, wastewater treatment, and human healthcare domains. Traditionally, studies on the microbial community assembly focused on analyzing pairwise relationships among species; however, neglecting higher-order interactions, i.e., the change of pairwise relationships in the community context, may lead to substantial deviation from reality. Herein, we have proposed a simple framework that incorporates higher-order interactions into a bottom-up prediction of the microbial community assembly and examined its accuracy using a seven-member synthetic bacterial community on a host plant, duckweed. Although the synthetic community exhibited emergent properties that cannot be predicted from pairwise coculturing results, our results demonstrated that incorporating information from three-member combinations allows the acceptable prediction of the community structure and actual interaction forces within it. This reflects that the occurrence of higher-order effects follows consistent patterns, which can be predicted even from trio combinations, the smallest unit of higher-order interactions. These results highlight the possibility of predicting, explaining, and understanding the microbial community structure from the bottom-up by learning interspecies interactions from simple beyond-pairwise combinations.

Mass-immigration shapes the antibiotic resistome of wastewater treatment plants

Wastewater treatment plants (WWTPs) are the hotspots for the spread of antibiotic resistance genes (ARGs) into the environment. Nevertheless, a comprehensive assessment of the city-level and short-term daily (inter-day) variations of ARG profiles in the whole process (influent-INF, activated sludge-AS and effluent-EF) of WWTPs is still lacking. Here, 285 ARGs and ten mobile gene elements were monitored in seven WWTPs in Xiamen for seven days via high-throughput qPCR. The average daily load of ARGs to WWTPs was about 1.32 × 1020 copies/d, and a total of 1.56 × 1018 copies/d was discharged to the environment across the entire city. Stochastic processes were the main force determining the assembly of ARG communities during sampling campaign, with their relative importance ranked in the order of INF > EFF > AS. There're little daily variations in ARG richness, abundance, β-diversity composition as well as assembly mechanisms. The results of SourceTracker, variation partitioning analysis, and hierarchical partitioning analysis indicated that bacteria and ARGs from upstream treatment processes played an increasingly dominant role in shaping ARG communities in AS and EFF, respectively, suggesting the importance of mass-immigration of bacteria and ARGs from the source on ARG transport in wastewater treatment processes. This emphasizes the need to revise the way we mitigate ARG contamination but focus on the source of ARGs in urban wastewater.

Core taxa underpin soil microbial community turnover during secondary succession

Understanding the processes that underpin the community assembly of bacteria is a key challenge in microbial ecology. We studied soil bacterial communities across a large-scale successional gradient of managed and abandoned grasslands paired with mature forest sites to disentangle drivers of community turnover and assembly. Diversity partitioning and phylogenetic null-modelling showed that bacterial communities in grasslands remain compositionally stable following abandonment and secondary succession but they differ markedly from fully afforested sites. Zeta diversity analyses revealed the persistence of core microbial taxa that both reflected and differed from whole-scale community turnover patterns. Differences in soil pH and C:N were the main drivers of community turnover between paired grassland and forest sites and the variability of pH within successional stages was a key factor related to the relative dominance of deterministic assembly processes. Our results indicate that grassland microbiomes could be compositionally resilient to abandonment and secondary succession and that the major changes in microbial communities between grasslands and forests occur fairly late in the succession when trees have established as the dominant vegetation. We also show that core taxa may show contrasting responses to management and abandonment in grasslands.

Resistance of aerobic granular sludge microbiomes to periodic loss of biomass

Granular sludge is a biofilm process used for wastewater treatment which is currently being implemented worldwide. It is important to understand how disturbances affect the microbial community and performance of reactors. Here, two acetate-fed replicate reactors were inoculated with acclimatized sludge and the reactor performance, and the granular sludge microbial community succession were studied for 149 days. During this time, the microbial community was challenged by periodically removing half of the reactor biomass, subsequently increasing the food-to-microorganism (F/M) ratio. Diversity analysis together with null models show that overall, the microbial communities were resistant to the disturbances, observing some minor effects on polyphosphate-accumulating and denitrifying microbial communities and their associated reactor functions. Community turnover was driven by drift and random granule loss, and stochasticity was the governing ecological process for community assembly. These results evidence the aerobic granular sludge process as a robust system for wastewater treatment.

Exploring the Entropy Complex Networks with Latent Interaction

In the present work, we study the introduction of a latent interaction index, examining its impact on the formation and development of complex networks. This index takes into account both observed and unobserved heterogeneity per node in order to overcome the limitations of traditional compositional similarity indices, particularly when dealing with large networks comprising numerous nodes. In this way, it effectively captures specific information about participating nodes while mitigating estimation problems based on network structures. Furthermore, we develop a Shannon-type entropy function to characterize the density of networks and establish optimal bounds for this estimation by leveraging the network topology. Additionally, we demonstrate some asymptotic properties of pointwise estimation using this function. Through this approach, we analyze the compositional structural dynamics, providing valuable insights into the complex interactions within the network. Our proposed method offers a promising tool for studying and understanding the intricate relationships within complex networks and their implications under parameter specification. We perform simulations and comparisons with the formation of Erdös-Rényi and Barabási-Alber-type networks and Erdös-Rényi and Shannon-type entropy. Finally, we apply our models to the detection of microbial communities.

Effects of deterministic assembly of communities caused by global warming on coexistence patterns and ecosystem functions

Seasonal rhythms in biological and ecological dynamics are fundamental in regulating the structuring of microbial communities. Evaluating the seasonal rhythms of microorganisms in response to climate change could provide information on their variability and stability over longer timescales (>20-year). However, information on temporal variability in microorganism responses to medium- and long-term global warming is limited. In this study, we aimed to elucidate the temporal dynamics of microbial communities in response to global warming; to this end, we integrated data on the maintenance of species diversity, community composition, temporal turnover rates (v), and community assembly process in two typical ecosystems (meadows and shrub habitat) on the Qinghai-Tibet Plateau. Our results showed that 21 years of global warming would increase the importance of the deterministic process for microorganisms in both ecosystems across all seasons (R2 of grassland (GL) control: 0.524, R2 of GL warming: 0.467; R2 of shrubland (SL) control: 0.556, R2 of SL warming: 0.543), reducing species diversity and altering community composition. Due to environmental filtration pressure from 21 years of warming, the low turnover rate (v of warming: -3.13/-2.00, v of control: -2.44/-1.48) of soil microorganisms reduces the resistance and resilience of ecological communities, which could lead to higher community similarity and more clustered taxonomic assemblages occurring across years. Changes to temperature might increase selection pressure on specialist taxa, which directly causes dominant species (v of warming: -1.63, v of control: -2.49) primarily comprising these taxa to be more strongly impacted by changing temperature than conditionally (v of warming: -1.47, v of control: -1.75) or always rare taxa (v of warming: -0.57, v of control: -1.33). Evaluation of the seasonal rhythms of microorganisms in response to global warming revealed that the variability and stability of different microbial communities in different habitats had dissimilar biological and ecological performances when challenged with an external disturbance. The balance of competition and cooperation, because of environmental selection, also influenced ecosystem function in complex terrestrial ecosystems. Overall, our study enriches the limited information on the temporal variability in microorganism responses to 21 years of global warming, and provides a scientific basis for evaluating the impact of climate warming on the temporal stability of soil ecosystems.

Evidence of the cooperative response of Blattella germanica gut microbiota to antibiotic treatment

Gut microbiota plays a key role in host health under normal conditions. However, bacterial composition can be altered by external factors such as antibiotic (AB) intake. While there are many descriptive publications about the effects of AB on gut microbiota composition after treatment, the dynamics and interactions among the bacterial taxa are still poorly understood. In this work, we performed a longitudinal study of gut microbiome dynamics in B. germanica treated with kanamycin. The AB was supplied in three separate periods, giving the microbiota time to recover between each antibiotic intake. We applied two new statistical models, not focusing on pair-wise interactions, to more realistically study the interactions between groups of bacterial taxa and how some groups affect a single taxon. The first model provides information on the importance of a given genus, and the rest of the community, to define the abundance of that genus. The second model, on the other hand, provides details about the relationship between groups of bacteria, focusing on which community groups affect the taxa. These models help us to identify which bacteria are community-dependent in stress conditions, which taxa might be better adapted than the rest of the community, and which bacteria might be working together within the community to overcome the antibiotic. In addition, these models enable us to identify different bacterial groups that were separated in control conditions but were found together in treated conditions, suggesting that when the environment is more hostile (as it is under antibiotic treatment), the whole community tends to work together.

Unraveling the roles of coastal bacterial consortia in degradation of various lignocellulosic substrates

Lignocellulose, as the most abundant natural organic carbon on earth, plays a key role in regulating the global carbon cycle, but there have been only few studies in marine ecosystems. Little information is available about the extant lignin-degrading bacteria in coastal wetlands, limiting our understanding of their ecological roles and traits in lignocellulose degradation. We utilized in situ lignocellulose enrichment experiments coupled with 16S rRNA amplicon and shotgun metagenomics sequencing to identify and characterize bacterial consortia attributed to different lignin/lignocellulosic substrates in the southern-east intertidal zone of East China Sea. We found the consortia enriched on woody lignocellulose showed higher diversity than those on herbaceous substrate. This also revealed substrate-dependent taxonomic groups. A time-dissimilarity pattern with increased alpha diversity over time was observed. Additionally, this study identified a comprehensive set of genes associated with lignin degradation potential, containing 23 gene families involved in lignin depolymerization, and 371 gene families involved in aerobic/anaerobic lignin-derived aromatic compound pathways, challenging the traditional view of lignin recalcitrance within marine ecosystems. In contrast to similar cellulase genes among the lignocellulose substrates, significantly different ligninolytic gene groups were observed between consortia under woody and herbaceous substrates. Importantly, we not only observed synergistic degradation of lignin and hemi-/cellulose, but also pinpointed the potential biological actors at the levels of taxa and functional genes, which indicated that the alternation of aerobic and anaerobic catabolism could facilitate lignocellulose degradation. Our study advances the understanding of coastal bacterial community assembly and metabolic potential for lignocellulose substrates. IMPORTANCE It is essential for the global carbon cycle that microorganisms drive lignocellulose transformation, due to its high abundance. Previous studies were primarily constrained to terrestrial ecosystems, with limited information about the role of microbes in marine ecosystems. Through in situ lignocellulose enrichment experiment coupled with high-throughput sequencing, this study demonstrated different impacts that substrates and exposure times had on long-term bacterial community assembly and pinpointed comprehensive, yet versatile, potential decomposers at the levels of taxa and functional genes in response to different lignocellulose substrates. Moreover, the links between ligninolytic functional traits and taxonomic groups of substrate-specific populations were revealed. It showed that the synergistic effect of lignin and hemi-/cellulose degradation could enhance lignocellulose degradation under alternation of aerobic and anaerobic conditions. This study provides valuable taxonomic and genomic insights into coastal bacterial consortia for lignocellulose degradation.

Stability of human gut microbiome: Comparison of ecological modelling and observational approaches

The gut microbiome plays a pivotal role in the human body, and perturbations in its composition have been linked to various disorders. Stability is an essential property of a healthy human gut microbiome, which allows it to maintain its functional richness under the external influences. This property has been explored through two distinct methodologies - mathematical modelling based on ecological principles and statistical analysis drawn from observations in interventional studies. Here we conducted a meta-analysis aimed to compare the two approaches utilising the data from 9 interventional and time series studies encompassing 3512 gut microbiome profiles obtained via 16S rRNA gene sequencing. By employing the previously published compositional Lotka-Volterra method, we modelled the dynamics of the microbial community and evaluated ecological stability measures. These measures were compared to those based on observed microbiome changes. There was a substantial correlation between the outcomes of the two approaches. Particularly, local stability assessed within the ecological paradigm was positively correlated with observational stability measures accounting for the compositional nature of microbiome data. Additionally, we were able to reproduce the previously reported inverse relationship between the community's robustness to microorganism loss and local stability, attributed to the distinct impacts of coefficient characterising the network decomposition on these two stability assessments. Our findings demonstrate harmonisation between the ecological and observational approaches to microbiome analysis, advancing the understanding of healthy gut microbiome concept. This paves the way to develop efficient microbiome-targeting interventions for disease prevention and treatment.

Soil bacterial community composition is more stable in kiwifruit orchards relative to phyllosphere communities over time

BACKGROUND

Soil and phyllosphere (leaves and fruit) microbes play critical roles in the productivity and health of crops. However, microbial community dynamics are currently understudied in orchards, with a limited number incorporating temporal monitoring. We used 16S rRNA gene amplicon sequencing to investigate bacterial community temporal dynamics and community assembly processes on the leaves and fruit, and in the soil of 12 kiwifruit orchards across a cropping season in New Zealand.

RESULTS

Community composition significantly differed (P < 0.001) among the three sample types. However, the communities in the phyllosphere substrates more closely resembled each other, relative to the communities in the soil. There was more temporal stability in the soil bacterial community composition, relative to the communities residing on the leaves and fruit, and low similarity between the belowground and aboveground communities. Bacteria in the soil were more influenced by deterministic processes, while stochastic processes were more important for community assembly in the phyllosphere.

CONCLUSIONS

The higher temporal variability and the stochastic nature of the community assembly processes observed in the phyllosphere communities highlights why predicting the responsiveness of phyllosphere communities to environmental change, or the likelihood of pathogen invasion, can be challenging. The relative temporal stability and the influence of deterministic selection on soil microbial communities suggests a greater potential for their prediction and reliable manipulation.

The aeromicrobiome: the selective and dynamic outer-layer of the Earth's microbiome

The atmosphere is an integral component of the Earth's microbiome. Abundance, viability, and diversity of microorganisms circulating in the air are determined by various factors including environmental physical variables and intrinsic and biological properties of microbes, all ranging over large scales. The aeromicrobiome is thus poorly understood and difficult to predict due to the high heterogeneity of the airborne microorganisms and their properties, spatially and temporally. The atmosphere acts as a highly selective dispersion means on large scales for microbial cells, exposing them to a multitude of physical and chemical atmospheric processes. We provide here a brief critical review of the current knowledge and propose future research directions aiming at improving our comprehension of the atmosphere as a biome.

Abundant bacterial subcommunity is structured by a stochastic process in an agricultural system with P fertilizer inputs

Soil microorganisms play an important role in agroecosystems and are related to ecosystem functioning. Nevertheless, little is understood about their community assembly and the major factors regulating stochastic and deterministic processes, particularly with respect to the comparison of abundant and rare bacterial subcommunities in agricultural systems. Here, we investigated the assembly of abundant and rare bacterial subcommunities in fields with different crops (maize and wheat) and phosphorus (P) fertilizer input at three different growth stages on the Loess Plateau. The high-throughput sequencing dataset was assessed using null and neutral community models. We found that abundant bacteria was governed by the stochastic process of homogenizing dispersal, but rare bacterial subcommunity was predominant by deterministic processes in maize and wheat fields due to broader niche breadths of abundant species. Soil nitrogen (N) and P also determined the assembly of abundant and rare soil subcommunities. The relative abundance and composition of the abundant and rare bacterial subcommunities were also influenced by soil nutrients (soil available P (AP) and NO₃^--N) and agricultural practices (P fertilization and crop cultivation). In addition, the abundant bacterial community was more susceptible to P fertilizer input than that of the rare bacteria, and a higher relative abundance of abundant bacteria was observed in the P70 treatment both in maize and wheat soils. The microbial co-occurrence network analysis indicated that the maize field and low nutrient treatment exhibited stronger associations and that the abundant bacteria showed fewer interconnections. This study provides new insights toward understanding the mechanisms for the assembly of abundant and rare bacterial taxa in dryland cropping systems, enhancing our understanding of ecosystem diversity theory in microbial ecology.

Phylogenetic group-based assembly and co-occurrence pattern of the microbial community in full-scale wastewater treatment plants during the Chinese spring festival

The quality and quantity of domestic sewage discharge vary significantly during the Chinese Spring Festival due to the huge population shift. The dynamics of microbial community traits during the Spring Festival, particularly the phylogenetic group-based assembly and co-occurrence patterns, are however little understood. Here, influent and activated sludge samples from 2 full-scale wastewater treatment plants were collected bi-daily throughout a 20-day Spring Festival period and subjected to high-throughput Illumina-MiSeq sequencing. The findings revealed that the microbial communities in the activated sludge displayed a comparatively stable pattern, and that the influent communities experienced significant temporal fluctuations in terms of diversity and composition. The characterization by "Infer Community Assembly Mechanisms by Phylogenetic-bin based null model" demonstrated that for Competibacter glycogen-accumulating organisms, the assembly mechanism shifted from deterministic process (HoS = 69.5%) before the Spring Festival to stochastic process (DR = 65.9%) after the Spring Festival. The network analysis revealed that the network structure of sludge communities was more stable before the Spring Festival than that after the Spring Festival. Additionally, sludge communities had no keystone species in common with the influent before the Spring Festival, while the sludge and influent communities shared two keystone taxa after the Spring Festival (Sebaldella and Candidatus Competibacter). This study would deepen our understanding of the microbial ecology in biological wastewater treatment systems, which also aids in managing wastewater treatment plants.

Microbial dynamics and bioreactor performance are interlinked with organic matter removal from wastewater treatment plant effluent

Optimizing bioreactor performance for organic matter removal can achieve sustainable and energy-efficient micropollutant removal in subsequent tertiary treatment. Bioreactor performance heavily depends on its resident microbial community; hence, a deeper understanding of community dynamics is essential. The microbial communities of three different bioreactors (biological activated carbon, moving bed biofilm reactor, sand filter), used for organic matter removal from wastewater treatment effluent, were characterized by 16S rRNA gene amplicon sequence analysis. An interdependency between bioreactor performance and microbial community profile was observed. Overall, Proteobacteria was the most predominant phylum, and Comamonadaceae was the most predominant family in all bioreactors. The relative abundance of the genus Roseococcus was positively correlated with organic matter removal. A generalized Lotka-Volterra (gLV) model was established to understand the interactions in the microbial community. By identifying microbial dynamics and their role in bioreactors, a strategy can be developed to improve bioreactor performance.

Microbiome assembly and maintenance across the lifespan of bumble bee workers

How a host's microbiome changes over its lifespan can influence development and ageing. As these temporal patterns have only been described in detail for a handful of hosts, an important next step is to compare microbiome succession more broadly and investigate why it varies. Here we characterize the temporal dynamics and stability of the bumble bee worker gut microbiome. Bumble bees have simple and host-specific gut microbiomes, and their microbial dynamics may influence health and pollination services. We used 16S rRNA gene sequencing, quantitative PCR and metagenomics to characterize gut microbiomes over the lifespan of Bombus impatiens workers. We also sequenced gut transcriptomes to examine host factors that may control the microbiome. At the community level, microbiome assembly is highly predictable and similar to patterns of primary succession observed in the human gut. However, at the strain level, partitioning of bacterial variants among colonies suggests stochastic colonization events similar to those observed in flies and nematodes. We also find strong differences in temporal dynamics among symbiont species, suggesting ecological differences among microbiome members in colonization and persistence. Finally, we show that both the gut microbiome and host transcriptome-including expression of key immunity genes-stabilize, as opposed to senesce, with age. We suggest that in highly social groups such as bumble bees, maintenance of both microbiomes and immunity contribute to inclusive fitness, and thus remain under selection even in old age. Our findings provide a foundation for exploring the mechanisms and functional outcomes of bee microbiome succession.

Bacterial communities in a subarctic stream network: Spatial and seasonal patterns of benthic biofilm and bacterioplankton

Water-column bacterial communities are assembled by different mechanisms at different stream network positions, with headwater communities being controlled by mass effects (advection of bacteria from terrestrial soils) while downstream communities are mainly driven by environmental sorting. Conversely, benthic biofilms are colonized largely by the same set of taxa across the entire network. However, direct comparisons of biofilm and bacterioplankton communities along whole stream networks are rare. We used 16S rRNA gene amplicon sequencing to explore the spatiotemporal variability of benthic biofilm (2 weeks old vs. mature biofilm) and water-column communities at different network positions of a subarctic stream from early summer to late autumn. Amplicon sequence variant (ASV) richness of mature biofilm was about 2.5 times higher than that of early biofilm, yet the pattern of seasonality was the same, with the highest richness in midsummer. Biofilm bacterial richness was unrelated to network position whereas bacterioplankton diversity was negatively related to water residence time and distance from the source. This pattern of decreasing diversity along the network was strongest around midsummer and diminished greatly as water level increased towards autumn. Biofilm communities were phylogenetically clustered at all network positions while bacterioplankton assemblages were phylogenetically clustered only at the most downstream site. Both early and mature biofilm communities already differed significantly between upstream (1st order) and midstream (2nd order) sections. Network position was also related to variation in bacterioplankton communities, with upstream sites harbouring substantially more unique taxa (44% of all upstream taxa) than midstream (20%) or downstream (8%) sites. Some of the taxa that were dominant in downstream sections were already present in the upmost headwaters, and even in riparian soils, where they were very rare (relative abundance <0.01%). These patterns in species diversity and taxonomic and phylogenetic community composition of the riverine bacterial metacommunity were particularly strong for water-column communities, whereas both early and mature biofilm exhibited weaker spatial patterns. Our study demonstrated the benefits of studying bacterioplankton and biofilm communities simultaneously to allow testing of ecological hypotheses about biodiversity patterns in freshwater bacteria.

The microbial environment modulates non-genetic maternal effects on egg immunity

Background

In a diverse microbial world immune function of animals is essential. Diverse microbial environments may contribute to extensive variation in immunological phenotypes of vertebrates, among and within species and individuals. As maternal effects benefit offspring development and survival, whether females use cues about their microbial environment to prime offspring immune function is unclear. To provide microbial environmental context to maternal effects, we asked if the bacterial diversity of the living environment of female zebra finches Taeniopygia guttata shapes maternal effects on egg immune function. We manipulated environmental bacterial diversity of birds and tested if females increased immunological investment in eggs in an environment with high bacterial diversity (untreated soil) versus low (gamma-sterilized soil). We quantified lysozyme and ovotransferrin in egg albumen and IgY in egg yolk and in female blood, and we used 16S rRNA gene sequencing to profile maternal cloacal and eggshell microbiotas.

Results

We found a maternal effect on egg IgY concentration that reflected environmental microbial diversity: females who experienced high diversity deposited more IgY in their eggs, but only if maternal plasma IgY levels were relatively high. We found no effects on lysozyme and ovotransferrin concentrations in albumen. Moreover, we uncovered that variation in egg immune traits could be significantly attributed to differences among females: for IgY concentration in yolk repeatability R = 0.80; for lysozyme concentration in albumen R = 0.27. Furthermore, a partial least squares path model (PLS-PM) linking immune parameters of females and eggs, which included maternal and eggshell microbiota structures and female body condition, recapitulated the treatment-dependent yolk IgY response. The PLS-PM additionally suggested that the microbiota and physical condition of females contributed to shaping maternal effects on egg immune function, and that (non-specific) innate egg immunity was prioritized in the environment with low bacterial diversity.

Conclusions

The microbial environment of birds can shape maternal effects on egg immune function. Since immunological priming of eggs benefits offspring, we highlight that non-genetic maternal effects on yolk IgY levels based on cues from the parental microbial environment may prove important for offspring to thrive in the microbial environment that they are expected to face.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-022-00195-8.

Analysis of Postmortem Intestinal Microbiota Successional Patterns with Application in Postmortem Interval Estimation

Microorganisms play a vital role in the decomposition of vertebrate remains in natural nutrient cycling, and the postmortem microbial succession patterns during decomposition remain unclear. The present study used hierarchical clustering based on Manhattan distances to analyze the similarities and differences among postmortem intestinal microbial succession patterns based on microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns were obtained. Generally, the normal intestinal flora in the cecum was gradually decreased with changes in the living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied upon oxygen consumption. Furthermore, a random forest regression model was developed to predict the postmortem interval based on the microbial succession trend dataset. The model demonstrated a mean absolute error of 20.01 h and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and the Lachnospiraceae NK4A136 group were considered significant biomarkers for this model according to the ranked list. The present study explored microbial succession patterns in terms of relative abundances and variety, aiding in the prediction of postmortem intervals and offering some information on microbial behaviors in decomposition ecology.

Effect of nitrous oxide (N2O) on the structure and function of nitrogen-oxide reducing microbial communities

Nitrous oxide (N₂O) is a potent greenhouse gas that can be produced by nitrifying and denitrifying bacteria. Yet the effects of N₂O on microbial communities is not well understood. We used batch tests to explore the effects of N₂O on mixed denitrifying communities. Batch tests were carried out with acetate as the electron donor and with the following electron acceptors: nitrate (NO₃^-), nitrite (NO₂^-), N₂O, NO₃^- + N₂O, and NO₂^- + N₂O. Activated sludge from a municipal wastewater treatment plant was used as the inoculum. The bacteria grew readily with N₂O as the sole acceptor. When N₂O was provided along with NO₃^- or NO₂^-, it was used concurrently and resulted in higher growth rates than the same acceptors without added N₂O. The microbial communities resulting from N₂O addition were significantly different at the genus level from those with just NO₃^- or NO₂^-. Tests with N₂O as the sole added acceptor revealed a reduced diversity. Analysis of inferred gene content using PICRUSt2 indicated a greater abundance of genera with a complete denitrification pathway when growing on N₂O or NO₂^-, relative to all other tests. This suggests that specific N₂O reduction rates are high, and that N₂O alone selects for a low-diversity, fully denitrifying community. When N₂O is present with NO₂^- or NO₃^-, the microbial communities were more diverse and did not select exclusively for full denitrifiers. N₂O alone appears to select for a "generalist" community with full denitrification pathways and lower diversity. In terms of denitrification genes, the combination of acceptors with N₂O appeared to increase the number of microbes carrying nirK, while fully denitrifying bacteria appear more likely to carry nirS. Lastly, all the taxa in NO₂^- and N₂O samples were predicted to harbor nosZ. This suggests the potential for reduced N₂O emissions in denitrifying systems.

Differential colonization and functioning of microbial community in response to phosphate levels

Microbes play a major role in phosphate cycling and regulate its availability in various environments. The metagenomic study highlights the microbial community divergence and interplay of phosphate metabolism functional genes in response to phosphate rich (100 mgL^-1), limiting (25 mgL^-1), and stressed (5 mgL^-1) conditions at lab-scale bioreactor. Total five core phyla were found responsive toward different phosphate (Pi) levels. However, major variations were observed in Proteobacteria and Actinobacteria with 33-81% and 5-56% relative abundance, respectively. Canonical correspondence analysis reflects the colonization of Sinorhizobium (0.8-4%), Mesorhizobium (1-4%), Rhizobium (0.5-3%) in rich condition whereas, Pseudomonas (1-2%), Rhodococcus (0.2-2%), Flavobacterium (0.2-1%) and Streptomyces (0.3-4%) colonized in limiting and stress condition. The functional profiling demonstrates that Pi limiting and stress condition subjected biomass were characterized by abundant PQQ-Glucose dehydrogenase, alkaline phosphatase, 5'-nucleotidase, and phospholipases C genes. The finding implies that the major abundant genera belonging to phosphate solubilization enriched in limiting/stressed conditions decide the functional turnover by modulating the metabolic flexibility for Pi cycling. The study gives a better insight into intrinsic ecological responsiveness mediated by microbial communities in different Pi conditions that would help to design the microbiome according to the soil phosphate condition. Furthermore, this information assists in sustainably maintaining the ecological balance by omitting excessive chemical fertilizers and eutrophication.

First Steps into Ruminal Microbiota Robustness

Despite its central role in ruminant nutrition, little is known about ruminal microbiota robustness, which is understood as the ability of the microbiota to cope with disturbances. The aim of the present review is to offer a comprehensive description of microbial robustness, as well as its potential drivers, with special focus on ruminal microbiota. First, we provide a briefing on the current knowledge about ruminal microbiota. Second, we define the concept of disturbance (any discrete event that disrupts the structure of a community and changes either the resource availability or the physical environment). Third, we discuss community resistance (the ability to remain unchanged in the face of a disturbance), resilience (the ability to return to the initial structure following a disturbance) and functional redundancy (the ability to maintain or recover initial function despite compositional changes), all of which are considered to be key properties of robust microbial communities. Then, we provide an overview of the currently available methodologies to assess community robustness, as well as its drivers (microbial diversity and network complexity) and its potential modulation through diet. Finally, we propose future lines of research on ruminal microbiota robustness.

Ruminal Bacterial Community Successions in Response to Monensin Supplementation in Goats

Simple Summary

Monensin has been successfully used in the ruminants’ diets to manipulate ruminal fermentation and improve feed efficiency, but its use is facing decreased levels of social acceptance due to the potential impacts on public health. Understanding the ruminal bacterial community successions in response to monensin supplementation would help the search for alternatives. We found that the ruminal ecosystem was reshaped through a series of succession processes during the adaption to monensin rather than following a clear dichotomy between Gram-positive and Gram-negative cell types, and the carbohydrate-degrading bacteria presented a higher adaptability. Therefore, a potential alternative for monensin as a rumen modifier could be one with similar patterns of ruminal microbial community successions.

Abstract

Previous studies have demonstrated that the effects of monensin on methanogenesis and ruminal fermentation in ruminants were time-dependent. To elucidate the underlying mechanism, we investigated the ruminal bacterial community successions during the adaptation to monensin supplementation and subsequent withdrawal in goats. The experiment included a baseline period of 20 days followed by a treatment period of 55 days with 32 mg monensin/d and a washout period of 15 days. Monensin supplementation reduced the α diversity and changed the structure of ruminal microflora. The α diversity was gradually restored during adaption, but the structure was still reshaped. The temporal dynamics of 261 treatment- and/or time-associated ruminal bacteria displayed six patterns, with two as monensin-sensitive and four as monensin-resistant. The monensin sensitivity and resistance of microbes do not follow a clear dichotomy between Gram-positive and Gram-negative cell types. Moreover, the temporal dynamic patterns of different bacterial species within the same genus or family also displayed variation. Of note, the relative abundance of the total ruminal cellulolytic bacteria gradually increased following monensin treatment, and that of the total amylolytic bacteria were increased by monensin, independent of the duration. In conclusion, under the pressure of monensin, the ruminal ecosystem was reshaped through a series of succession processes, and the carbohydrate-degrading bacteria presented a higher level of adaptability.

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.

Distinct and Temporally Stable Assembly Mechanisms Shape Bacterial and Fungal Communities in Vineyard Soils

Microbial communities in agricultural soils are fundamental for plant growth and in vineyard ecosystems contribute to defining regional wine quality. Managing soil microbes towards beneficial outcomes requires knowledge of how community assembly processes vary across taxonomic groups, spatial scales, and through time. However, our understanding of microbial assembly remains limited. To quantify the contributions of stochastic and deterministic processes to bacterial and fungal assembly across spatial scales and through time, we used 16 s rRNA gene and ITS sequencing in the soil of an emblematic wine-growing region of Italy.Combining null- and neutral-modelling, we found that assembly processes were consistent through time, but bacteria and fungi were governed by different processes. At the within-vineyard scale, deterministic selection and homogenising dispersal dominated bacterial assembly, while neither selection nor dispersal had clear influence over fungal assembly. At the among-vineyard scale, the influence of dispersal limitation increased for both taxonomic groups, but its contribution was much larger for fungal communities. These null-model-based inferences were supported by neutral modelling, which estimated a dispersal rate almost two orders-of-magnitude lower for fungi than bacteria.This indicates that while stochastic processes are important for fungal assembly, bacteria were more influenced by deterministic selection imposed by the biotic and/or abiotic environment. Managing microbes in vineyard soils could thus benefit from strategies that account for dispersal limitation of fungi and the importance of environmental conditions for bacteria. Our results are consistent with theoretical expectations whereby larger individual size and smaller populations can lead to higher levels of stochasticity.

Synchronous Seasonality in the Gut Microbiota of Wild Mouse Populations

The gut microbiome performs many important functions in mammalian hosts, with community composition shaping its functional role. However, the factors that drive individual microbiota variation in wild animals and to what extent these are predictable or idiosyncratic across populations remains poorly understood. Here, we use a multi-population dataset from a common rodent species (the wood mouse, Apodemus sylvaticus), to test whether a consistent “core” gut microbiota is identifiable in this species, and to what extent the predictors of microbiota variation are consistent across populations. Between 2014 and 2018 we used capture-mark-recapture and 16S rRNA profiling to intensively monitor two wild wood mouse populations and their gut microbiota, as well as characterising the microbiota from a laboratory-housed colony of the same species. Although the microbiota was broadly similar at high taxonomic levels, the two wild populations did not share a single bacterial amplicon sequence variant (ASV), despite being only 50km apart. Meanwhile, the laboratory-housed colony shared many ASVs with one of the wild populations from which it is thought to have been founded decades ago. Despite not sharing any ASVs, the two wild populations shared a phylogenetically more similar microbiota than either did with the colony, and the factors predicting compositional variation in each wild population were remarkably similar. We identified a strong and consistent pattern of seasonal microbiota restructuring that occurred at both sites, in all years, and within individual mice. While the microbiota was highly individualised, some seasonal convergence occurred in late winter/early spring. These findings reveal highly repeatable seasonal gut microbiota dynamics in multiple populations of this species, despite different taxa being involved. This provides a platform for future work to understand the drivers and functional implications of such predictable seasonal microbiome restructuring, including whether it might provide the host with adaptive seasonal phenotypic plasticity.

Emergent Diversity and Persistent Turnover in Evolving Microbial Cross-Feeding Networks

A distinguishing feature of many ecological networks in the microbial realm is the diversity of substrates that could potentially serve as energy sources for microbial consumers. The microorganisms are themselves the agents of compound diversification via metabolite excretion or overflow metabolism. It has been suggested that the emerging richness of different substrates is an important condition for the immense biological diversity in microbial ecosystems. In this work, we study how complex cross-feeding networks (CFN) of microbial species may develop from a simple initial community given some elemental evolutionary mechanisms of resource-dependent speciation and extinctions using a network flow model. We report results of several numerical experiments and report an in-depth analysis of the evolutionary dynamics. We find that even in stable environments, the system is subject to persisting turnover, indicating an ongoing co-evolution. Further, we compare the impact of different parameters, such as the ratio of mineralization, as well as the metabolic versatility and variability on the evolving community structure. The results imply that high microbial and molecular diversity is an emergent property of evolution in cross-feeding networks, which affects transformation and accumulation of substrates in natural systems, such as soils and oceans, with potential relevance to biotechnological applications.

ARZIMM: A Novel Analytic Platform for the Inference of Microbial Interactions and Community Stability from Longitudinal Microbiome Study

Dynamic changes of microbiome communities may play important roles in human health and diseases. The recent rise in longitudinal microbiome studies calls for statistical methods that can model the temporal dynamic patterns and simultaneously quantify the microbial interactions and community stability. Here, we propose a novel autoregressive zero-inflated mixed-effects model (ARZIMM) to capture the sparse microbial interactions and estimate the community stability. ARZIMM employs a zero-inflated Poisson autoregressive model to model the excessive zero abundances and the non-zero abundances separately, a random effect to investigate the underlining dynamic pattern shared within the group, and a Lasso-type penalty to capture and estimate the sparse microbial interactions. Based on the estimated microbial interaction matrix, we further derive the estimate of community stability, and identify the core dynamic patterns through network inference. Through extensive simulation studies and real data analyses we evaluate ARZIMM in comparison with the other methods.

Fine-Scale Adaptations to Environmental Variation and Growth Strategies Drive Phyllosphere Methylobacterium Diversity

Methylobacterium is a prevalent bacterial genus of the phyllosphere. Despite its ubiquity, little is known about the extent to which its diversity reflects neutral processes like migration and drift, versus environmental filtering of life history strategies and adaptations. In two temperate forests, we investigated how phylogenetic diversity within Methylobacterium is structured by biogeography, seasonality, and growth strategies. Using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches, we uncovered a considerable diversity of Methylobacterium in the phyllosphere. We cultured different subsets of Methylobacterium lineages depending upon the temperature of isolation and growth (20°C or 30°C), suggesting long-term adaptation to temperature. To a lesser extent than temperature adaptation, Methylobacterium diversity was also structured across large (>100 km; between forests) and small (<1.2 km; within forests) geographical scales, among host tree species, and was dynamic over seasons. By measuring the growth of 79 isolates during different temperature treatments, we observed contrasting growth performances, with strong lineage- and season-dependent variations in growth strategies. Finally, we documented a progressive replacement of lineages with a high-yield growth strategy typical of cooperative, structured communities in favor of those characterized by rapid growth, resulting in convergence and homogenization of community structure at the end of the growing season. Together, our results show how Methylobacterium is phylogenetically structured into lineages with distinct growth strategies, which helps explain their differential abundance across regions, host tree species, and time. This work paves the way for further investigation of adaptive strategies and traits within a ubiquitous phyllosphere genus. IMPORTANCE Methylobacterium is a bacterial group tied to plants. Despite the ubiquity of methylobacteria and the importance to their hosts, little is known about the processes driving Methylobacterium community dynamics. By combining traditional culture-dependent and -independent (metabarcoding) approaches, we monitored Methylobacterium diversity in two temperate forests over a growing season. On the surface of tree leaves, we discovered remarkably diverse and dynamic Methylobacterium communities over short temporal (from June to October) and spatial (within 1.2 km) scales. Because we cultured different subsets of Methylobacterium diversity depending on the temperature of incubation, we suspected that these dynamics partly reflected climatic adaptation. By culturing strains under laboratory conditions mimicking seasonal variations, we found that diversity and environmental variations were indeed good predictors of Methylobacterium growth performances. Our findings suggest that Methylobacterium community dynamics at the surface of tree leaves results from the succession of strains with contrasting growth strategies in response to environmental variations.

Vertical and temporal variations of soil bacterial and archaeal communities in wheat-soybean rotation agroecosystem

Soil microbes are an essential component of terrestrial ecosystems and drive many biogeochemical processes throughout the soil profile. Prior field studies mainly focused on the vertical patterns of soil microbial communities, meaning their temporal dynamics have been largely neglected. In the present study, we investigated the vertical and temporal patterns of soil bacterial and archaeal communities in a wheat-soybean rotation agroecosystem at a depth of millions of sequences per sample. Our results revealed different vertical bacterial and archaeal richness patterns: bacterial richness was lowest in the deep soil layer and peaked in the surface or middle soil layer. In contrast, archaeal richness did not differ among soil layers. PERMANOVA analysis indicated that both bacterial and archaeal community compositions were significantly impacted by soil depth but unaffected by sampling time. Notably, the proportion of rare bacteria gradually decreased along with the soil profile. The rare bacterial community composition was the most important indicator for soil nutrient fertility index, as determined by random forest analysis. The soil prokaryotic co-occurrence networks of the surface and middle soil layers are more connected and harbored fewer negative links than that of the deep soil layer. Overall, our results highlighted soil depth as a more important determinant than temporal variation in shaping the soil prokaryotic community and interspecific interactions and revealed a potential role of rare taxa in soil biogeochemical function.

Diversity of Microbial Communities of Pinus sylvestris var. mongolica at Spatial Scale

Soil microorganisms play an indispensable role in the forest ecosystem. It is necessary to study the soil microorganisms in Pinus sylvestris var. mongolica, which is one of the afforestation species widely planted in the northern sandy region of China. We collected soil samples of P. sylvestris at large spatial scales and analyzed bacterial and fungal community composition differences using high-throughput sequencing techniques. The results showed that: (1) the richness index of different sandy lands was significantly different. The α-diversity of bacteria was the highest in Mu Us Sandy Land, and the α-diversity of fungi was the highest in Horqin Sandy Land. (2) The dominant phyla of bacteria were Actinobacteria, Proteobacteria, Chloroflexi and Acidobacteria, while the dominant phyla of fungi were Ascomycota and Basidiomycota. The relative abundance of dominant phyla was different. (3) Temperature and precipitation were the main driving factors of bacterial and fungal community change at large spatial scale. In addition, bacteria were also affected by total nitrogen, soil organic carbon and pH content; fungal community was affected by pH. The microorganisms showed obvious differences in geographical distribution, which could provide ideas for promoting sustainable management of P. sylvestris stand.

Temporal variability in quantitative human gut microbiome profiles and implications for clinical research

While clinical gut microbiota research is ever-expanding, extending reference knowledge of healthy between- and within-subject gut microbiota variation and its drivers remains essential; in particular, temporal variability is under-explored, and a comparison with cross-sectional variation is missing. Here, we perform daily quantitative microbiome profiling on 713 fecal samples from 20 Belgian women over six weeks, combined with extensive anthropometric measurements, blood panels, dietary data, and stool characteristics. We show substantial temporal variation for most major gut genera; we find that for 78% of microbial genera, day-to-day absolute abundance variation is substantially larger within than between individuals, with up to 100-fold shifts over the study period. Diversity, and especially evenness indicators also fluctuate substantially. Relative abundance profiles show similar but less pronounced temporal variation. Stool moisture, and to a lesser extent diet, are the only significant host covariates of temporal microbiota variation, while menstrual cycle parameters did not show significant effects. We find that the dysbiotic Bact2 enterotype shows increased between- and within-subject compositional variability. Our results suggest that to increase diagnostic as well as target discovery power, studies could adopt a repeated measurement design and/or focus analysis on community-wide microbiome descriptors and indices.

Multivariate statistical monitoring system for microbial population dynamics

Microbiomes in their natural environments vary dynamically with changing environmental conditions. The detection of these dynamic changes in microbial populations is critical for understanding the impact of environmental changes on the microbial community. Here, we propose a novel method to detect time-series changes in the microbiome, based on multivariate statistical process control. By focusing on the interspecies structures, this approach enables the robust detection of time-series changes in a microbiome composed of a large number of microbial species. Applying this approach to empirical human gut microbiome data, we accurately traced time-series changes in microbiota composition induced by a dietary intervention trial. This method was also excellent for tracking the recovery process after the intervention. Our approach can be useful for monitoring dynamic changes in complex microbial communities.

Seasonal dynamics of soil microbial diversity and functions along elevations across the treeline

Although microbial diversity patterns along elevations have been extensively studied, little is known about whether the patterns are influenced by seasonality. To test the seasonal and elevational effects on microbial communities and functions, we collected soil samples across a mountain gradient above and below the treeline in three seasons (spring, summer and autumn). Microbial diversity based on the sequencing of 16S rRNA, 18S rRNA and nifH genes was measured, and microbial functions represented by soil basal respiration and microbial biomass were analyzed. As expected, we found significant seasonal and elevational effects on microbial α- and β-diversity and functions, and the effects of elevations were greater than seasonal effects. Elevational patterns of microbial β-diversity and functions were not influenced by seasonality. However, the elevational α-diversity patterns showed by specific groups (bacteria, protist and metazoa) changed among seasons. Further, we identified key soil properties (i.e. moisture, total carbon, total nitrogen and nitrate) which had higher seasonal and elevational variations, mainly contributing to the spatiotemporal variations of microbial diversity and functions. The findings of higher soil nutrients, archaeal and metazoan richness, and microbial functions at the treeline elevation, imply a strong edge effect of treeline on microbial diversity and functions. Together, our study highlights that seasonality influences the elevational patterns of soil microbial α-diversity, rather than that of β-diversity and functions, thus provides new insights into the seasonal and elevational effects on microbial communities and functions.

Terrestrial connectivity, upstream aquatic history and seasonality shape bacterial community assembly within a large boreal aquatic network

During transit from soils to the ocean, microbial communities are modified and re-assembled, generating complex patterns of ecological succession. The potential effect of upstream assembly on downstream microbial community composition is seldom considered within aquatic networks. Here, we reconstructed the microbial succession along a land-freshwater-estuary continuum within La Romaine river watershed in Northeastern Canada. We captured hydrological seasonality and differentiated the total and reactive community by sequencing both 16 S rRNA genes and transcripts. By examining how DNA- and RNA-based assemblages diverge and converge along the continuum, we inferred temporal shifts in the relative importance of assembly processes, with mass effects dominant in spring, and species selection becoming stronger in summer. The location of strongest selection within the network differed between seasons, suggesting that selection hotspots shift depending on hydrological conditions. The unreactive fraction (no/minor RNA contribution) was composed of taxa with diverse potential origins along the whole aquatic network, while the majority of the reactive pool (major RNA contribution) could be traced to soil/soilwater-derived taxa, which were distributed along the entire rank-abundance curve. Overall, our findings highlight the importance of considering upstream history, hydrological seasonality and the reactive microbial fraction to fully understand microbial community assembly on a network scale.

Prospects for multi-omics in the microbial ecology of water engineering

Advances in high-throughput sequencing technologies and bioinformatics approaches over almost the last three decades have substantially increased our ability to explore microorganisms and their functions - including those that have yet to be cultivated in pure isolation. Genome-resolved metagenomic approaches have enabled linking powerful functional predictions to specific taxonomical groups with increasing fidelity. Additionally, related developments in both whole community gene expression surveys and metabolite profiling have permitted for direct surveys of community-scale functions in specific environmental settings. These advances have allowed for a shift in microbiome science away from descriptive studies and towards mechanistic and predictive frameworks for designing and harnessing microbial communities for desired beneficial outcomes. Water engineers, microbiologists, and microbial ecologists studying activated sludge, anaerobic digestion, and drinking water distribution systems have applied various (meta)omics techniques for connecting microbial community dynamics and physiologies to overall process parameters and system performance. However, the rapid pace at which new omics-based approaches are developed can appear daunting to those looking to apply these state-of-the-art practices for the first time. Here, we review how modern genome-resolved metagenomic approaches have been applied to a variety of water engineering applications from lab-scale bioreactors to full-scale systems. We describe integrated omics analysis across engineered water systems and the foundations for pairing these insights with modeling approaches. Lastly, we summarize emerging omics-based technologies that we believe will be powerful tools for water engineering applications. Overall, we provide a framework for microbial ecologists specializing in water engineering to apply cutting-edge omics approaches to their research questions to achieve novel functional insights. Successful adoption of predictive frameworks in engineered water systems could enable more economically and environmentally sustainable bioprocesses as demand for water and energy resources increases.

Temporal turnover of the soil microbiome composition is guild-specific

Although spatial and temporal variation are both important components structuring microbial communities, the exact quantification of temporal turnover rates of fungi and bacteria has not been performed to date. In this study, we utilised repeated resampling of bacterial and fungal communities at specific locations across multiple years to describe their patterns and rates of temporal turnover. Our results show that microbial communities undergo temporal change at a rate of 0.010-0.025 per year (in units of Sorensen similarity), and the change in soil is slightly faster in fungi than in bacteria, with bacterial communities changing more rapidly in litter than soil. Importantly, temporal development differs across fungal guilds and bacterial phyla with different ecologies. While some microbial guilds show consistent responses across regional locations, others show site-specific development with weak general patterns. These results indicate that guild-level resolution is important for understanding microbial community assembly, dynamics and responses to environmental factors.