Microbial Ecosystem Functioning Research Articles

Lipid biochemical diversity and dynamics reveal phytoplankton nutrient-stress responses and carbon export mechanisms in mesoscale eddies in the North Pacific Subtropical Gyre

Mesoscale eddies cause deviations from the background physical and biogeochemical states of the oligotrophic oceans, but how these perturbations manifest in microbial ecosystem functioning, such as community macromolecular composition or carbon export, remains poorly characterized. We present comparative lipidomes from communities entrained in two eddies of opposite polarities (cyclone–anticyclone) in the North Pacific Subtropical Gyre (NPSG). A previous work on this two-eddy system has shown differences in particulate inorganic carbon (PIC) and biogenic silica sinking fluxes between the two eddies despite comparable total organic carbon fluxes. We measured the striking differences between the lipidomes of suspended and sinking particles that indicate taxon-specific responses to mesoscale perturbations. Specifically, cyanobacteria did not appear to respond to increased concentrations of phosphorus in the subsurface of the cyclonic eddy, while eukaryotic microbes exhibit P-stress relief as reflected in their lipid signatures. Furthermore, we found that two classes of lipids drive differences between suspended and sinking material: sinking particles are comparatively enriched in phosphatidylcholine (PC, a membrane-associated lipid) and triacylglycerol (TAG, an energy storage lipid). We observed significantly greater export of TAGs from the cyclonic eddy as compared to the anticyclone and found that this flux is strongly correlated with the concentration of ballast minerals (PIC and biogenic silica). This increased export of TAGs from the cyclone, but not the anticyclone, suggests that cyclonic eddy perturbations may be a mechanism for the delivery of energy-rich organic material below the euphotic zone.

Microbial community structure in a constructed wetland based on a recirculating aquaculture system: Exploring spatio-temporal variations and assembly mechanisms

The diversity, composition and performance of microbial communities within constructed wetlands (CW) were markedly influenced by spatio-temporal variations. A pilot-scale integrated vertical-flow constructed wetland (IVCW) as the biological purification unit within a recirculating aquaculture system (RAS) was established and monitored in this study. The investigation aimed to elucidate the responses of community structure, co-occurrence networks, and assembly mechanisms of the microbial community to spatial and temporal changes. Spatially, all a-diversity indices and microbial networks complexity were significantly higher in the upstream pool of the IVCW than in the downstream pool. Temporally, the richness increased over time, while the evenness showed a decreasing trend. The number of nodes and edges of microbial networks increased over time. Notably, the stable pollutant removal efficiencies were observed during IVCW operations, despite a-diversity and bacterial community networks exhibited significant variations across time. Functional redundancy emerged as a likely mechanism contributing to the stability of microbial ecosystem functions. Null model and neutral model analyses revealed the dominance of deterministic processes shaping microbial communities over time, with deterministic influences being more pronounced at lower a-diversity levels. DO and inorganic nitrogen emerged as the principal environmental factor influencing microbial community dynamics. This study provides a theoretical foundation for the regulation of microbial communities and environmental factors within the context of IVCW.

Microbial community composition predicts bacterial production across ocean ecosystems.

Microbial ecological functions are an emergent property of community composition. For some ecological functions, this link is strong enough that community composition can be used to estimate the quantity of an ecological function. Here, we apply random forest regression models to compare the predictive performance of community composition and environmental data for bacterial production (BP). Using data from two independent long-term ecological research sites-Palmer LTER in Antarctica and Station SPOT in California-we found that community composition was a strong predictor of BP. The top performing model achieved an R2 of 0.84 and RMSE of 20.2pmolL-1hr-1 on independent validation data, outperforming a model based solely on environmental data (R2 = 0.32, RMSE = 51.4pmolL-1hr-1). We then operationalized our top performing model, estimating BP for 346 Antarctic samples from 2015 to 2020 for which only community composition data were available. Our predictions resolved spatial trends in BP with significance in the Antarctic (P value = 1 × 10-4) and highlighted important taxa for BP across ocean basins. Our results demonstrate a strong link between microbial community composition and microbial ecosystem function and begin to leverage long-term datasets to construct models of BP based on microbial community composition.

Depth effects on bacterial community altitudinal patterns and assembly processes in the warm-temperate montane forests of China

Soil bacterial communities are essential for ecosystem function, yet their response along altitudinal gradients in different soil strata remains unclear. Understanding bacterial community co-occurrence networks and assembly patterns in mountain ecosystems is crucial for comprehending microbial ecosystem functions. We utilized Illumina MiSeq sequencing to study bacterial diversity and assembly patterns of surface and subsurface soils across a range of elevations (700 to 2100 m) on Dongling Mountain. Our results showed significant altitudinal distribution patterns concerning bacterial diversity and structure in the surface soil. The bacterial diversity exhibited a consistent decrease, while specific taxa demonstrated unique patterns along the altitudinal gradient. However, no altitudinal dependence was observed for bacterial diversity and community structure in the subsurface soil. Additionally, a shift in bacterial ecological groups is evident with changing soil depth. Copiotrophic taxa thrive in surface soils characterized by higher carbon and nutrient content, while oligotrophic taxa dominate in subsurface soils with more limited resources. Bacterial community characteristics exhibited strong correlations with soil organic carbon in both soil layers, followed by pH in the surface soil and soil moisture in the subsurface soil. With increasing depth, there is an observable increase in taxa-taxa interaction complexity and network structure within bacterial communities. The surface soil exhibits greater sensitivity to environmental perturbations, leading to increased modularity and an abundance of positive relationships in its community networks compared to the subsurface soil. Furthermore, the bacterial community at different depths was influenced by combining deterministic and stochastic processes, with stochasticity (homogenizing dispersal and undominated) decreasing and determinism (heterogeneous selection) increasing with soil depth.

Four functional profiles for fibre and mucin metabolism in the human gut microbiome

BackgroundWith the emergence of metagenomic data, multiple links between the gut microbiome and the host health have been shown. Deciphering these complex interactions require evolved analysis methods focusing on the microbial ecosystem functions. Despite the fact that host or diet-derived fibres are the most abundant nutrients available in the gut, the presence of distinct functional traits regarding fibre and mucin hydrolysis, fermentation and hydrogenotrophic processes has never been investigated.ResultsAfter manually selecting 91 KEGG orthologies and 33 glycoside hydrolases further aggregated in 101 functional descriptors representative of fibre and mucin degradation pathways in the gut microbiome, we used nonnegative matrix factorization to mine metagenomic datasets. Four distinct metabolic profiles were further identified on a training set of 1153 samples, thoroughly validated on a large database of 2571 unseen samples from 5 external metagenomic cohorts and confirmed with metatranscriptomic data. Profiles 1 and 2 are the main contributors to the fibre-degradation-related metagenome: they present contrasted involvement in fibre degradation and sugar metabolism and are differentially linked to dysbiosis, metabolic disease and inflammation. Profile 1 takes over Profile 2 in healthy samples, and unbalance of these profiles characterize dysbiotic samples. Furthermore, high fibre diet favours a healthy balance between profiles 1 and profile 2. Profile 3 takes over profile 2 during Crohn’s disease, inducing functional reorientations towards unusual metabolism such as fucose and H2S degradation or propionate, acetone and butanediol production. Profile 4 gathers under-represented functions, like methanogenesis. Two taxonomic makes up of the profiles were investigated, using either the covariation of 203 prevalent genomes or metagenomic species, both providing consistent results in line with their functional characteristics. This taxonomic characterization showed that profiles 1 and 2 were respectively mainly composed of bacteria from the phyla Bacteroidetes and Firmicutes while profile 3 is representative of Proteobacteria and profile 4 of methanogens.ConclusionsIntegrating anaerobic microbiology knowledge with statistical learning can narrow down the metagenomic analysis to investigate functional profiles. Applying this approach to fibre degradation in the gut ended with 4 distinct functional profiles that can be easily monitored as markers of diet, dysbiosis, inflammation and disease.6PP5aGzbMER7d2AAtHiJDfVideo

Geochemical constraints on bacteriophage infectivity in terrestrial environments

Lytic phages can be potent and selective inhibitors of microbial growth and can have profound impacts on microbiome composition and function. However, there is uncertainty about the biogeochemical conditions under which phage predation modulates microbial ecosystem function, particularly in terrestrial systems. Ionic strength is critical for infection of bacteria by many phages, but quantitative data is limited on the ion thresholds for phage infection that can be compared with environmental ion concentrations. Similarly, while carbon composition varies in the environment, we do not know how this variability influences the impact of phage predation on microbiome function. Here, we measured the half-maximal effective concentrations (EC50) of 80 different inorganic ions for the infection of E. coli with two canonical dsDNA and ssRNA phages, T4 and MS2, respectively. Many alkaline earth metals and alkali metals enabled lytic infection but the ionic strength thresholds varied for different ions between phages. Additionally, using a freshwater nitrate-reducing microbiome, we found that the ability of lytic phages to influence nitrate reduction end-products depended upon the carbon source as well as ionic strength. For all phage:host pairs, the ion EC50s for phage infection exceeded the ion concentrations found in many terrestrial freshwater systems. Thus, our findings support a model where phages most influence terrestrial microbial functional ecology in hot spots and hot moments such as metazoan guts, drought influenced soils, or biofilms where ion concentration is locally or transiently elevated and nutrients are available to support the growth of specific phage hosts.

Food web structure and energy flux dynamics, but not taxonomic richness, influence microbial ecosystem functions in a Sphagnum-dominated peatland

Soil microbial communities are vital for multiple ecosystem processes and services. In particular, soil microbial food webs are key determinants of soil biodiversity, functioning and stability. Unclear, however, is how structural features of food webs, such as species richness and turnover, biomass and energy transfer across trophic levels, influence the provisioning and stability of ecosystem functioning. Here, we explore the relationships between different facets of microbial food web structure (e.g. species richness, connectance, biomass and energy fluxes across trophic levels) and ecosystem functions (i.e. decomposition and microbial enzyme activity) across different habitats and depths in a peatland. We show that no aspect of taxonomic richness directly explained variation in ecosystem functions. Instead, we find that trophic interactions between basal species and primary consumers, and especially increasing connectance, biomass and energy flux transiting from decomposers and phototrophs to algivores, bacterivores and fungivores, enhance ecosystem functions in the peatland. These findings demonstrate that focusing on taxonomic diversity without explicit inclusion of food web structure and energy flows therein gives an incomplete and uninformative comprehension of relationships between biodiversity and ecosystem functioning, at least in peatlands. Our findings further suggest that the inclusion of soil microbial food webs in large-scale biogeochemical models is of fundamental importance to provide the necessary guidance for managing and mitigating the effects of environmental change.

Assembly Processes and Biogeographical Characteristics of Soil Bacterial Sub-communities of Different Habitats in Urban Green Spaces.

The process of urbanization is one of the most important human-driven activities that reshape the natural distribution of soil microorganisms. However, it is still unclear about the effects of urbanization on the different taxonomic soil bacterial community dynamics. In this study, we collected soil samples from highly urbanized the regions of Yangtze River Delta, Beijing-Tianjin-Hebei in China, to explore the bio-geographic patterns, assembly processes, and symbiotic patterns of abundant, moderate, and rare bacterial communities. We found that the number of moderate and rare taxa species were lower than that of abundant taxa, but their α-diversity index was higher than abundant taxa. Proteobacteria, Acidobacteria, Actinobacteria, Bacterioidetes, and Chloroflexi were the dominant phylum across all three sub-communities. And the β-diversity value of rare taxa was significantly higher than those of moderate and abundant taxa. Abundant, moderate, and rare sub-communities showed a weak distance-decay relationship, and the moderate taxa had the highest turnover rate of microbial geography in the context of urbanization. Diffusion limitation was the dominant process of soil bacterial community assembly. The co-occurrence networks of abundant, moderate, and rare taxa were dominated by positive correlations. The network of moderate taxa had the highest modularity, followed by abundant taxa. The main functions of the abundant, moderate, and rare taxa were related to Chemoheterotrophy and N transformations. Redundancy analysis showed that the dispersal limitation, climate, and soil properties were the main factors dominating bio-geographic differences in soil bacterial community diversity. We conclude that human-dominated urbanization processes have generated more uncertain survival pressures on soil bacteria, which resulted in a stronger linkage but weak bio-geographic variation for soil bacteria. In the future urban planning process, we suggest that such maintenance of native vegetation and soil types should be considered to maintain the long-term stability of local microbial ecosystem functions.

Specialist species of fungi and bacteria are more important than the intermediate and generalist species in near-urban agricultural soils

Near-urban farmland is an important component of agricultural soils in China. Understanding the distribution and functional patterns of soil microbial communities is essential for accurate fertilization and disease control in this area. By considering the generalists, intermediates, and specialists of soil microbiota, we studied the soil microbial community assembly process and functional transformations characteristics in near-urban farmlands. We found that the intermediate group has the highest relative abundance with 66.24 % and 50.33 % for fungi and bacteria, respectively. A steeper geographic distance decay relationship (DDR) was found for the specialist bacteria than the generalist and intermediate taxa in the near-urban farmlands. However, the generalist species of fungi showed a steeper DDR than the intermediate and specialist. Both bacterial and fungal generalists have the widest niche, followed by the intermediate and specialists, respectively. The null model indicated that the deterministic processes dominate the community assembly process for bacteria (56%) and fungi (54 %). Variation partitioning analysis (VPA) showed that both the specialists and intermediate groups were more susceptible to geospatial distance than the generalists. Soil water content, C and N nutrients were the main factors driving the changes in the community structure of dominant generalist, intermediate and specialist species. The main functional groups of the generalists and specialist bacteria were chemoheterotrophy. Moreover, specialist bacteria have much more functions related to nitrogen transformation and organic matter degradation than generalist species. For fungi, the specialist species mainly are responsible for saprophytic, pathotrophic_saprotrophic and symbiotrophic nutritional types. Interestingly, the specialist fungi also consisted of a higher number of saprophytic, pathotrophic and symbiotic trophic functions. Thus, fungal and bacterial specialist species, rather than the intermediate or generalist groups support the soil microbial ecosystem functions in the near-urban farmland.

MetaPhage: an Automated Pipeline for Analyzing, Annotating, and Classifying Bacteriophages in Metagenomics Sequencing Data.

ABSTRACTPhages are the most abundant biological entities on the planet, and they play an important role in controlling density, diversity, and network interactions among bacterial communities through predation and gene transfer. To date, a variety of bacteriophage identification tools have been developed that differ in the phage mining strategies used, input files requested, and results produced. However, new users attempting bacteriophage analysis can struggle to select the best methods and interpret the variety of results produced. Here, we present MetaPhage, a comprehensive reads-to-report pipeline that streamlines the use of multiple phage miners and generates an exhaustive report. The report both summarizes and visualizes the key findings and enables further exploration of key results via interactive filterable tables. The pipeline is implemented in Nextflow, a widely adopted workflow manager that enables an optimized parallelization of tasks in different locations, from local server to the cloud; this ensures reproducible results from containerized packages. MetaPhage is designed to enable scalability and reproducibility; also, it can be easily expanded to include new miners and methods as they are developed in this continuously growing field. MetaPhage is freely available under a GPL-3.0 license at https://github.com/MattiaPandolfoVR/MetaPhage.IMPORTANCE Bacteriophages (viruses that infect bacteria) are the most abundant biological entities on earth and are increasingly studied as members of the resident microbiota community in many environments, from oceans to soils and the human gut. Their identification is of great importance to better understand complex bacterial dynamics and microbial ecosystem function. A variety of metagenome bacteriophage identification tools have been developed that differ in the phage mining strategies used, input files requested, and results produced. To facilitate the management and the execution of such a complex workflow, we developed MetaPhage (MP), a comprehensive reads-to-report pipeline that streamlines the use of multiple phage miners and generates an exhaustive report. The pipeline is implemented in Nextflow, a widely adopted workflow manager that enables an optimized parallelization of tasks. MetaPhage is designed to enable scalability and reproducibility and offers an installation-free, dependency-free, and conflict-free workflow execution.

Microbial response of distinct soil types to land-use intensification at a South-Indian rural-urban interface

AimsRural-urban dynamics are leading to agricultural intensification practices, which affect microbial ecosystem functions in a soil-specific way. This study aimed to investigate what effects agricultural intensification has on soil microbial communities.MethodsThe effects of N fertilization level (low and high) and crop type (maize and finger millet) on microbial communities were investigated, using a two-factorial split-plot design, at two fields (irrigated and rainfed) on typical soil types (Nitisol and Acrisol) mimicking an intensification gradient in the rural-urban interface of the Indian Megacity Bangalore.ResultsThe Nitisol had higher pH and clay content than the Acrisol. In combination with irrigation, this led to higher aboveground plant biomass (APB), soil organic carbon (SOC), microbial biomass (MB), fungal ergosterol and microbial necromass. High APB resulted in low total P content, due to P export in APB and high soil C/P and MB-C/P ratios in the Nitisol. Crop type and N fertilization level did not affect microbial parameters in the irrigated Nitisol, whereas crop type affected ergosterol and MBP and N fertilization level affected basal respiration in the rainfed Acrisol. Particulate organic matter (POM) was a major explanatory factor for most microbial parameters in both soils. In the Acrisol, drought reduced metabolic demand, which counteracted negative effects of low pH and clay on the MB. This was indicated by similar metabolic quotients and MBC/SOC ratios in both soils.ConclusionsThese results indicate the current need for water and high-quality fresh plant inputs to improve the microbial contribution to soil fertility at Bangalore.

Geochemical, Biological, and Clumped Isotopologue Evidence for Substantial Microbial Methane Production Under Carbon Limitation in Serpentinites of the Samail Ophiolite, Oman

AbstractIn hyperalkaline () fluids that have participated in low‐temperature (<150) serpentinization reactions, the dominant form of C is often methane (), but the origin of this is uncertain. To assess origin in serpentinite aquifers within the Samail Ophiolite, Oman, we determined fluid chemical compositions, analyzed taxonomic profiles of fluid‐hosted microbial communities, and measured isotopic compositions of hydrocarbon gases. We found that 16S rRNA gene sequences affiliated with methanogens were widespread in the aquifer. We measured clumped isotopologue (D and ) relative abundances less than equilibrium, consistent with substantial microbial production. Furthermore, we observed an inverse relationship between dissolved inorganic C concentrations and across fluids bearing microbiological evidence of methanogenic activity, suggesting that the apparent C isotope effect of microbial methanogenesis is modulated by C availability. An additional source of is evidenced by the presence of ‐bearing fluid inclusions in the Samail Ophiolite and our measurement of high values of ethane and propane, which are similar to those reported in studies of ‐rich inclusions in rocks from the oceanic lithosphere. In addition, we observed 16S rRNA gene sequences affiliated with aerobic methanotrophs and, in lower abundance, anaerobic methanotrophs, indicating that microbial consumption of in the ophiolite may further enrich in 13C. We conclude that substantial microbial is produced under varying degrees of C limitation and mixes with abiotic released from fluid inclusions. This study lends insight into the functioning of microbial ecosystems supported by water/rock reactions.

Dynamic carbon flux network of a diverse marine microbial community

The functioning of microbial ecosystems has important consequences from global climate to human health, but quantitative mechanistic understanding remains elusive. The components of microbial ecosystems can now be observed at high resolution, but interactions still have to be inferred e.g., a time-series may show a bloom of bacteria X followed by virus Y suggesting they interact. Existing inference approaches are mostly empirical, like correlation networks, which are not mechanistically constrained and do not provide quantitative mass fluxes, and thus have limited utility. We developed an inference method, where a mechanistic model with hundreds of species and thousands of parameters is calibrated to time series data. The large scale, nonlinearity and feedbacks pose a challenging optimization problem, which is overcome using a novel procedure that mimics natural speciation or diversification e.g., stepwise increase of bacteria species. The method allows for curation using species-level information from e.g., physiological experiments or genome sequences. The product is a mass-balancing, mechanistically-constrained, quantitative representation of the ecosystem. We apply the method to characterize phytoplankton—heterotrophic bacteria interactions via dissolved organic matter in a marine system. The resulting model predicts quantitative fluxes for each interaction and time point (e.g., 0.16 µmolC/L/d of chrysolaminarin to Polaribacter on April 16, 2009). At the system level, the flux network shows a strong correlation between the abundance of bacteria species and their carbon flux during blooms, with copiotrophs being relatively more important than oligotrophs. However, oligotrophs, like SAR11, are unexpectedly high carbon processors for weeks into blooms, due to their higher biomass. The fraction of exudates (vs. grazing/death products) in the DOM pool decreases during blooms, and they are preferentially consumed by oligotrophs. In addition, functional similarity of phytoplankton i.e., what they produce, decouples their association with heterotrophs. The methodology is applicable to other microbial ecosystems, like human microbiome or wastewater treatment plants.

Recurrent microbial community types driven by nearshore and seasonal processes in coastal Southern California.

A multitude of concurrent biological and physical processes contribute to microbial community turnover, especially in highly dynamic coastal environments. Characterizing what factors contribute most to shifts in microbial community structure and the specific organisms that correlate with changes in the products of photosynthesis improves our understanding of nearshore microbial ecosystem functions. We conducted high frequency sampling in nearshore Southern California in order to capture sub-weekly microbial community dynamics. Microbial communities were characterized by flow cytometry and 16S rRNA gene sequencing, and placed in the context of physicochemical parameters. Within our time-series, season and nutrient availability corresponded to changes in dominant microbial community members. Concurrent aseasonal drivers with overlapping scales of variability were also apparent when we used network analysis to assess the microbial community as subsets of the whole. Our analyses revealed the microbial community as a mosaic, with overlapping groups of taxa that varied on different timescales and correlated with unique abiotic and biotic factors. Specifically, a subnetwork associated with chlorophyll a exhibited rapid turnover, indicating that ecologically important subsets of the microbial community can change on timescales different than and in response to factors other than those that govern turnover of most members of the assemblage.

How trophic cascades and photic zone nutrient content interact to generate basin-scale differences in the microbial food web

Abstract In linear food chains, resource and predator control produce positive and negative correlations, respectively, between biomass at adjacent trophic levels. These simple relationships become more complex in food webs that contain alternative food chains of unequal lengths. We have used a “minimum” model for the microbial part of the pelagic food web that has three such food chains connecting free mineral nutrients to copepods: via diatoms, autotrophic flagellates, and heterotrophic bacteria. Trophic cascades from copepods strongly modulates the balance between the three pathways and, therefore, the functionality of the microbial food web in services such as food production for higher trophic levels, DOM degradation, and ocean carbon sequestration. The result is a theoretical framework able to explain, not only apparent conflicts in Arctic mesocosm experiments, but also biogeochemical features of the Mediterranean. Here, the fundamental difference between Arctic and Mediterranean microbial food webs is the way they are predator driven by seasonal migration of large copepods in the Arctic, but resource driven due to the anti-estuarine circulation in the Mediterranean. In this framework, global change effects on microbial ecosystem functions are more like to come indirectly through changes in these drivers than through direct temperature effects on the microbes.

Theoretical and Simulation-Based Investigation of the Relationship between Sequencing Effort, Microbial Community Richness, and Diversity in Binning Metagenome-Assembled Genomes.

We applied theoretical and simulation-based approaches to characterize how microbial community structure influences the amount of sequencing effort to reconstruct metagenomes that are assembled from short-read sequences. First, a coupon collector equation was proposed as an analytical model for predicting sequencing effort as a function of microbial community structure. Characterization was performed by varying community structure properties such as richness, evenness, and genome size. Simulations demonstrated that while community richness and evenness influenced the sequencing effort required to sequence a community metagenome to exhaustion, the effort necessary to sequence an individual genome to a target fraction of exhaustion depended only on the relative abundance of the genome and its genome size. A second analysis evaluated the quantity, completion, and contamination of metagenome-assembled genomes (MAGs) as a function of sequencing effort on four preexisting sequence read data sets from different environments. These data sets were subsampled to various degrees of completeness to simulate the effect of sequencing effort on MAG retrieval. Modeling suggested that sequencing efforts beyond what is typical in published experiments (1 to 10 Gbp) would generate diminishing returns in terms of MAG binning. A software tool, Genome Relative Abundance to Sequencing Effort (GRASE), was created to assist investigators to further explore this relationship. Reevaluation of the relationship between sequencing effort and binning success in the context of genome relative abundance, as opposed to base pairs, provides a constraint on sequencing experiments based on the relative abundance of microbes in an environment rather than arbitrary levels of sequencing effort.IMPORTANCE Short-read sequencing with Illumina sequencing technology provides an accurate, high-throughput method for characterizing the metabolic potential of microbial communities. Short-read sequences can be assembled and binned into metagenome-assembled genomes, thus shedding light on the function of microbial ecosystems that are important for health, agriculture, and Earth system processes. The work presented here provides an analytical framework for selecting sequencing effort as a function of genome relative abundance. As such, experimental goals in metagenome-assembled genome creation projects can select sequencing effort based on the rarest target genome as a constrained threshold. We hope that the results presented here, as well as GRASE, will be valuable to researchers planning sequencing experiments.

Disturbance Size Can Be Compensated for by Spatial Fragmentation in Soil Microbial Ecosystems

One major interest in soil systems ecology is to maintain ecosystem functions. As soil is exposed to disturbances of different spatial configurations, identifying disturbance characteristics that still allow for maintaining functions is crucial. In macro-ecology, the influence of fragmentation on ecosystems is continuously debated, especially in terms of extinction thresholds on the landscape scale. Whether this influence is positive or negative depends on the considered type of fragmentation: habitat fragmentation often promotes population extinction, whereas spatially fragmented disturbances reduce extinction probability in many cases. In this study, we make use of these concepts to analyze how spatial disturbance characteristics determine functional resilience on the microscale. We used the numerical model eColony considering bacterial growth, substrate consumption and dispersal for analyzing the dynamic response of biodegradation as an exemplary important microbial ecosystem function to disturbance events. We systematically varied the frequency of the disturbance events, and the size and fragmentation of the disturbed area. We found that the influence of the disturbance size on functional recovery depends on the spatial fragmentation of the disturbance, indicating that to some extent disturbance size can be compensated for by the spatial configuration of the disturbed area. In general, biodegradation performance decreases as the disturbed area increases in size and becomes more contiguous. However, if a disturbance is highly fragmented, an increase in disturbance size has no influence on biodegradation performance unless the disturbance is critically large. In this case, the functional performance decreases dramatically. Under recurrent disturbances, this critical disturbance size is shifted towards lower values depending on the disturbance frequency. Our results indicate the importance of spatial disturbance characteristics for functional resilience of soil microbial ecosystems. Critical values for disturbance size and degree of fragmentation emerge from an interplay between both characteristics. Consequently, these characteristics which are widely discussed on the landscape scale need to be equally considered on smaller scales when assessing functional resilience of soil ecosystems.

Spatiotemporal disturbance characteristics determine functional stability and collapse risk of simulated microbial ecosystems

Terrestrial microbial ecosystems are exposed to many types of disturbances varying in their spatial and temporal characteristics. The ability to cope with these disturbances is crucial for maintaining microbial ecosystem functions, especially if disturbances recur regularly. Thus, understanding microbial ecosystem dynamics under recurrent disturbances and identifying drivers of functional stability and thresholds for functional collapse is important. Using a spatially explicit ecological model of bacterial growth, dispersal, and substrate consumption, we simulated spatially heterogeneous recurrent disturbances and investigated the dynamic response of pollutant biodegradation – exemplarily for an important ecosystem function. We found that thresholds for functional collapse are controlled by the combination of disturbance frequency and spatial configuration (spatiotemporal disturbance regime). For rare disturbances, the occurrence of functional collapse is promoted by low spatial disturbance fragmentation. For frequent disturbances, functional collapse is almost inevitable. Moreover, the relevance of bacterial growth and dispersal for functional stability also depends on the spatiotemporal disturbance regime. Under disturbance regimes with moderate severity, microbial properties can strongly affect functional stability and shift the threshold for functional collapse. Similarly, networks facilitating bacterial dispersal can delay functional collapse. Consequently, measures to enhance or sustain bacterial growth/dispersal are promising strategies to prevent functional collapses under moderate disturbance regimes.

Prediction of functional metagenomic composition using archived 16S rDNA sequence data from the gut microbiota of livestock

The volume of microbial genetic terabases in public repositories is getting infamous, yet much of this data has been used only once. On top of this global concern, there is still much to be done to fully understand the nature and function of microbial ecosystems, for example the gastrointestinal (GI) tract. Here we used archived 16S rDNA sequence data to predict the metabolic profile of the GI microbiota from livestock using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). Study 1 (cows’ study) comprised samples of both tissues and contents of rumen, jejunum, ileum, cecum, and colon. There was no difference in any predicted metagenomic feature between tissues and contents but interesting patterns were observed among the different sections of the gut (e.g. genes involved in protein digestion and absorption were lower in the ileum and the jejunum). Study 2 (lambs’ study) comprised samples of rumen, duodenum, jejunum, ileum, colon and feces. The results revealed that the GI microbiota in efficient and inefficient lambs (as determined by Residual Feed Intake) did not display a distinctive metabolic profile for any anatomical region; however, over 200 features were significantly different (adjusted P < 0.05) among different locations of the digestive tract, thus strongly supporting the well-known notion of distinctive metabolic profiles of the microbiota depending on the location where they inhabit. These results were confirmed using another tool to predict metagenomic content (Piphillin). It is our hope that this study encourages others to visualize the potential of using public archived DNA data for the benefit of livestock science. Moreover, this study adds valuable information for understanding the impact of the gut microbiota on livestock health and performance.

Using null models to infer microbial co-occurrence networks

Although microbial communities are ubiquitous in nature, relatively little is known about the structural and functional roles of their constituent organisms’ underlying interactions. A common approach to study such questions begins with extracting a network of statistically significant pairwise co-occurrences from a matrix of observed operational taxonomic unit (OTU) abundances across sites. The structure of this network is assumed to encode information about ecological interactions and processes, resistance to perturbation, and the identity of keystone species. However, common methods for identifying these pairwise interactions can contaminate the network with spurious patterns that obscure true ecological signals. Here, we describe this problem in detail and develop a solution that incorporates null models to distinguish ecological signals from statistical noise. We apply these methods to the initial OTU abundance matrix and to the extracted network. We demonstrate this approach by applying it to a large soil microbiome data set and show that many previously reported patterns for these data are statistical artifacts. In contrast, we find the frequency of three-way interactions among microbial OTUs to be highly statistically significant. These results demonstrate the importance of using appropriate null models when studying observational microbiome data, and suggest that extracting and characterizing three-way interactions among OTUs is a promising direction for unraveling the structure and function of microbial ecosystems.