A communal catalogue reveals Earth's multiscale microbial diversity

Microbial diversity and oil biodegradation potential of northern Barents Sea sediments

The Arctic, an essential ecosystem on Earth, is subject to pronounced anthropogenic pressures, most notable being the climate change and risks of crude oil pollution. As crucial elements of Arctic environments, benthic microbiomes are involved in climate-relevant biogeochemical cycles and hold the potential to remediate upcoming contamination. Yet, the Arctic benthic microbiomes are among the least explored biomes on the planet. Here we combined geochemical analyses, incubation experiments, and microbial community profiling to detail the biogeography and biodegradation potential of Arctic sedimentary microbiomes in the northern Barents Sea. The results revealed a predominance of bacterial and archaea phyla typically found in the deep marine biosphere, such as Chloroflexi, Atribacteria, and Bathyarcheaota. The topmost benthic communities were spatially structured by sedimentary organic carbon, lacking a clear distinction among geographic regions. With increasing sediment depth, the community structure exhibited stratigraphic variability that could be correlated to redox geochemistry of sediments. The benthic microbiomes harbored multiple taxa capable of oxidizing hydrocarbons using aerobic and anaerobic pathways. Incubation of surface sediments with crude oil led to proliferation of several genera from the so-called rare biosphere. These include Alkalimarinus and Halioglobus, previously unrecognized as hydrocarbon-degrading genera, both harboring the full genetic potential for aerobic alkane oxidation. These findings increase our understanding of the taxonomic inventory and functional potential of unstudied benthic microbiomes in the Arctic.

Metagenomic approaches and opportunities in arid soil research

Arid soils present unique challenges and opportunities for studying microbial diversity and bioactive potential due to the extreme environmental conditions they bear. This review article investigates soil metagenomics as an emerging tool to explore complex microbial dynamics and unexplored bioactive potential in harsh environments. Utilizing advanced metagenomic techniques, diverse microbial populations that grow under extreme conditions such as high temperatures, salinity, high pH levels, and exposure to metals and radiation can be studied. The use of extremophiles to discover novel natural products and biocatalysts emphasizes the role of functional metagenomics in identifying enzymes and secondary metabolites for industrial and pharmaceutical purposes. Metagenomic sequencing uncovers a complex network of microbial diversity, offering significant potential for discovering new bioactive compounds. Functional metagenomics, connecting taxonomic diversity to genetic capabilities, provides a pathway to identify microbes' mechanisms to synthesize valuable secondary metabolites and other bioactive substances. Contrary to the common perception of desert soil as barren land, the metagenomic analysis reveals a rich diversity of life forms adept at extreme survival. It provides valuable findings into their resilience and potential applications in biotechnology. Moreover, the challenges associated with metagenomics in arid soils, such as low microbial biomass, high DNA degradation rates, and DNA extraction inhibitors and strategies to overcome these issues, outline the latest advancements in extraction methods, high-throughput sequencing, and bioinformatics. The importance of metagenomics for investigating diverse environments opens the way for future research to develop sustainable solutions in agriculture, industry, and medicine. Extensive studies are necessary to utilize the full potential of these powerful microbial communities. This research will significantly improve our understanding of microbial ecology and biotechnology in arid environments.

Longitudinal bacterial community dynamics and sodium hypochlorite intervention in a newly built university building

Urbanisation and building advancements have increased microbial growth in indoor environments, altering human interactions with these microorganisms. Restrooms and their sinks harbour diverse bacterial communities, that differ from those found in natural environments, that could have negative implications for human health. Over two and a half years, this study examined the diversity, temporal dynamics, and resilience of bacterial communities in restroom sink P-traps in a newly built university building. Structured into two phases, the first phase consisted of continuous monitoring of bacterial community dynamics for two years (n = 352), while the second phase involved an intervention with sodium hypochlorite (bleach) and subsequent sampling (n = 132). In the first phase, we show that sink communities converge, becoming more compositionally similar to other sinks within the building. Bacterial families such as Rhodocyclaceae and Flavobacteriaceae dominated across the sinks, and others such as Comamonadaceae, Moraxellaceae and Enterbacteriaceae were highly prevalent. When comparing bacterial structure and composition to other sinks located on the university campus, the mean bacterial dissimilarity decreased over time, indicating compositional similarity, particularly with the newer buildings on campus. The second phase demonstrated resilience by the bacterial sink communities. Following bleach treatments, a distinct increase in Acinetobacter was observed. However, by the fourth week after bleach invention, bacterial communities had re-established to levels observed prior to treatment. This study had the unique opportunity to sample a newly built building before occupancy and for the subsequent two and a half years. The findings provide crucial insights into the development and resilience of sink P-trap bacterial communities in restrooms, laying the groundwork for more targeted approaches to disinfection strategies.

MICROBIOME AND INFLAMMASOME ALTERATIONS FOUND DURING RADIATION DOSE FINDING IN A SINCLAIR MINIPIG MODEL OF GASTROINTESTINAL ACUTE RADIATION SYNDROME

ABSTRACT

Both abdominal radiotherapy and a nuclear event can result in gastrointestinal symptoms, including acute radiation syndrome (GI-ARS). GI-ARS is characterized by compromised intestinal barrier integrity increasing the risk for infectious complications. Physiologically relevant animal models are crucial for elucidating host responses and therapeutic targets. We aimed to determine the radiation dose requirements for creating GI-ARS in the Sinclair minipig. Male, sexually mature swine were randomly divided into sham (n = 6) and three lower hemibody radiation dosage groups of 8, 10, and 12 Gy (n = 5/group) delivered using linear accelerator-derived x-rays (1.9 Gy/min). Animals were monitored for GI-ARS symptoms for 14 days with rectal swab and blood collection at days 0-3, 7, 10, and 14 followed by necropsy for western blotting and histology. Dose-dependent increases in weight loss, diarrhea severity, and mortality (log-rank test, P = 0.041) were seen. Villi length was significantly reduced in all irradiated animals compared to controls ( P < 0.001). Serum citrulline decreased and bacterial translocation increased after irradiation compared to controls. Increased NLRP3 levels in post-mortem jejunum were seen ( P = 0.0043) as well as increased IL-1β levels in the 12 Gy group ( P = 0.041). Radiation dose and survival were associated with significant gut microbial community shifts in beta diversity. Moreover, decedents had increased Porphyromonas, Campylobacter, Bacteroides , Parvimonas , and decreased Fusobacterium and decreased Aerococcus, Lactobacillus, Prevotella, and Streptococcus . Our novel Sinclair minipig model showed dose-dependent clinical symptoms of GI-ARS. These findings provide invaluable insights into the intricate interplay between GI-ARS, intestinal inflammation, and gut microbiota alterations offering potential targets for therapeutic and diagnostic interventions after radiation exposure.

Biological S0 reduction at neutral and acidic conditions: Performance and microbial community shifts in a H2/CO2-fed bioreactor

Sulfidogenesis is a promising technology for the selective recovery of chalcophile bulk metals (e.g. Cu, Zn, and Co) from metal-contaminated waters such as acid mine drainage (AMD) and metallurgy waste streams. The use of elemental sulfur (S0) instead of sulfate (SO42-) as electron acceptor reduces electron donor requirements four-fold, lowering process costs, and expanding the range of operating conditions to a more acidic pH. We previously reported autotrophic S0 reduction using an industrial mesophilic granular sludge as inoculum under thermoacidophilic conditions. Here, we examined the effect of pH on the S0 reduction performance of the same inoculum, in a gas-lift reactor run at 30°C under neutral (pH 6.9) and acidic (pH 3.8) conditions, continuously fed with mineral media and H2 and CO2. Steady-state volumetric sulfide production rates (VSPR) dropped 2.5-fold upon transition to acidic pH, from 1.79 ± 0.18 g S2-·L-1·d-1 to 0.71 ± 0.07 g S2-·L-1·d-1. Microbial community composition was analyzed using 16S rRNA gene amplicon sequencing. At neutral pH (6.9), the high relative abundance of the S0-reducing genus Sulfurospirillum, previously known only for heterotrophic members, combined with the presence of Acetobacterium and detection of acetate, suggests an important role for heterotrophic S0 reduction facilitated by acetogenesis. Conversely, at acidic pH (3.9), S0 reduction appeared autotrophic, as indicated by the high relative abundance of Desulfurella.

Social behaviour mediates the microbiome response to antibiotic treatment in a wild mammal

High levels of social connectivity among group-living animals have been hypothesized to benefit individuals by creating opportunities to rapidly reseed the microbiome and maintain stability against disruption. We tested this hypothesis by perturbing the microbiome of a wild population of Grant's gazelles with an antibiotic and asking whether microbiome recovery differs between individuals with high versus low levels of social connectivity. We found that after treatment, individuals with high social connectivity experienced a faster increase in microbiome richness than less socially connected individuals. Unexpectedly, the rapid increase in microbiome richness of highly connected individuals that received treatment led to their microbiomes becoming more distinct relative to the background population. Our results suggest that the microbiome of individuals with high social connectivity can be rapidly recolonized after a perturbation event, but this leads to a microbiome that is more distinct from, rather than more similar to the unperturbed state. This work provides new insight into the role of social interactions in shaping the microbiome.

A global microbiome analysis reveals the ecological feature of Tistrella and its production of the bioactive didemnins in the marine ecosystem

Marine microorganisms like Tistrella are essential for producing bioactive compounds, including didemnins with antitumor and antiviral properties. However, our understanding of Tistrella's ecological features and didemnin production in natural environments is limited. In this study, we used genomics and metagenomics to show that Tistrella is widely distributed across natural habitats, especially in marine environments from the surface to 5000 m deep, with distinct non-random distribution patterns revealed by co-occurrence analysis. Importantly, transcriptional profiling of didemnin biosynthetic gene clusters indicates active in situ production of this compound within marine ecosystems. These findings enhance our understanding of Tistrella's ecology and secondary metabolite production in natural environments. Further research is needed to explore the ecological dynamics and functional impacts of Tistrella in these ecosystems.

Don't let valuable microbiome data go to waste: combined usage of merging and direct-joining of sequencing reads for low-quality paired-end amplicon data

The pernicious nature of low-quality sequencing data warrants improvement in the bioinformatics workflow for profiling microbial diversity. The conventional merging approach, which drops a copious amount of sequencing reads when processing low-quality amplicon data, requires alternative methods. In this study, a computational workflow, a combination of merging and direct-joining where the paired-end reads lacking overlaps are concatenated and pooled with the merged sequences, is proposed to handle the low-quality amplicon data. The proposed computational strategy was compared with two workflows; the merging approach where the paired-end reads are merged, and the direct-joining approach where the reads are concatenated. The results showed that the merging approach generates a significantly low number of amplicon sequences, limits the microbiome inference, and obscures some microbial associations. In comparison to other workflows, the combination of merging and direct-joining strategy reduces the loss of amplicon data, improves the taxonomy classification, and importantly, abates the misleading results associated with the merging approach when analysing the low-quality amplicon data. The mock community analysis also supports the findings. In summary, the researchers are suggested to follow the merging and direct-joining workflow to avoid problems associated with low-quality data while profiling the microbial community structure.

IL-22 resolves MASLD via enterocyte STAT3 restoration of diet-perturbed intestinal homeostasis

The exponential rise in metabolic dysfunction-associated steatotic liver disease (MASLD) parallels the ever-increasing consumption of energy-dense diets, underscoring the need for effective MASLD-resolving drugs. MASLD pathogenesis is linked to obesity, diabetes, "gut-liver axis" alterations, and defective interleukin-22 (IL-22) signaling. Although barrier-protective IL-22 blunts diet-induced metabolic alterations, inhibits lipid intake, and reverses microbial dysbiosis, obesogenic diets rapidly suppress its production by small intestine-localized innate lymphocytes. This results in STAT3 inhibition in intestinal epithelial cells (IECs) and expansion of the absorptive enterocyte compartment. These MASLD-sustaining aberrations were reversed by administration of recombinant IL-22, which resolved hepatosteatosis, inflammation, fibrosis, and insulin resistance. Exogenous IL-22 exerted its therapeutic effects through its IEC receptor, rather than hepatocytes, activating STAT3 and inhibiting WNT-β-catenin signaling to shrink the absorptive enterocyte compartment. By reversing diet-reinforced macronutrient absorption, the main source of liver lipids, IL-22 signaling restoration represents a potentially effective interception of dietary obesity and MASLD.

Pre-challenge gut microbial signature predicts RhCMV/SIV vaccine efficacy in rhesus macaques

Rhesus cytomegalovirus expressing simian immunodeficiency virus (RhCMV/SIV) vaccines protect ~59% of vaccinated rhesus macaques against repeated limiting-dose intra-rectal exposure with highly pathogenic SIVmac239M, but the exact mechanism responsible for the vaccine efficacy is unknown. It is becoming evident that complex interactions exist between gut microbiota and the host immune system. Here, we aimed to investigate if the rhesus gut microbiome impacts RhCMV/SIV vaccine-induced protection. Three groups of 15 rhesus macaques naturally pre-exposed to RhCMV were vaccinated with RhCMV/SIV vaccines. Rectal swabs were collected longitudinally both before SIV challenge (after vaccination) and post-challenge and were profiled using 16S rRNA based microbiome analysis. We identified ~2,400 16S rRNA amplicon sequence variants (ASVs), representing potential bacterial species/strains. Global gut microbial profiles were strongly associated with each of the three vaccination groups, and all animals tended to maintain consistent profiles throughout the pre-challenge phase. Despite vaccination group differences, by using newly developed compositional data analysis techniques, we identified a common gut microbial signature predictive of vaccine protection outcome across the three vaccination groups. Part of this microbial signature persisted even after SIV challenge. We also observed a strong correlation between this microbial signature and an early signature derived from whole blood transcriptomes in the same animals. Our findings indicate that changes in gut microbiomes are associated with RhCMV/SIV vaccine-induced protection and early host response to vaccination in rhesus macaques.IMPORTANCEThe human immunodeficiency virus (HIV) has infected millions of people worldwide. Unfortunately, still there is no vaccine that can prevent or treat HIV infection. A promising pre-clinical HIV vaccine based on rhesus cytomegalovirus (RhCMV) expressing simian immunodeficiency virus (SIV) antigens (RhCMV/SIV) provides sustained, durable protection against SIV challenge in ~59% of vaccinated rhesus macaques. There is an urgent need to understand the cause of this protection vs non-protection outcome. In this study, we profiled the gut microbiomes of 45 RhCMV/SIV vaccinated rhesus macaques and identified gut microbial signatures that were predictive of RhCMV/SIV vaccination groups and vaccine protection outcomes. These vaccine protection-associated microbial features were significantly correlated with early vaccine-induced host immune signatures in whole blood from the same animals. These findings show that the gut microbiome may be involved in RhCMV/SIV vaccine-induced protection, warranting further research into the impact of the gut microbiome in human vaccine trials.

MBCN: A novel reference database for Effcient Metagenomic analysis of human gut microbiome

Metagenomic shotgun sequencing data can identify microbes and their proportions. But metagenomic shotgun data profiling results obtained from multiple projects using different reference databases are difficult to compare and apply meta-analysis. Our work aims to create a novel collection of human gut prokaryotic genomes, named Microbiome Collection Navigator (MBCN). 2379 human gut metagenomic samples are screened, and 16,785 metagenome-assembled genomes (MAGs) are assembled using a standardized pipeline. In addition, MAGs are combined with the representative genomes from public prokaryotic genomes collections to cluster, and pan-genomes for each cluster's genomes are constructed to build Kraken2 and Bracken databases. The databases built by MBCN are more comprehensive and accurate for profiling metagenomic reads comparing with other collections on simulated reads and virtual bio-projects. We profile 1082 human gut metagenomic samples with MBCN database and organize profiles and metadata on the web program. Meanwhile, using MBCN as a reference database, we also develop a unified, standardized, and systematic metagenomic analysis pipeline and platform, named MicrobiotaCN (http://www.microbiota.cn) and common statistical and visualization tools for microbiome research are integrated into the web program. Taken together, MBCN and MicrobiotaCN can be a valuable resource and a powerful tool that allows researchers to perform metagenomic analysis by a unified pipeline efficiently.

Comparative evaluation of soil DNA extraction kits for long read metagenomic sequencing

Metagenomics has been transformative in our understanding of the diversity and function of soil microbial communities. Applying long read sequencing to whole genome shotgun metagenomics has the potential to revolutionise soil microbial ecology through improved taxonomic classification, functional characterisation and metagenome assembly. However, optimisation of robust methods for long read metagenomics of environmental samples remains undeveloped. In this study, Oxford Nanopore sequencing using samples from five commercially available soil DNA extraction kits was compared across four soil types, in order to optimise read length and reproducibility for comparative long read soil metagenomics. Average extracted DNA lengths varied considerably between kits, but longer DNA fragments did not translate consistently into read lengths. Highly variable decreases in the length of resulting reads from some kits were associated with poor classification rate and low reproducibility in microbial communities identified between technical repeats. Replicate samples from other kits showed more consistent conversion of extracted DNA fragment size into read length and resulted in more congruous microbial community representation. Furthermore, extraction kits showed significant differences in the community representation and structure they identified across all soil types. Overall, the QIAGEN DNeasy PowerSoil Pro Kit displayed the best suitability for reproducible long-read WGS metagenomic sequencing, although further optimisation of DNA purification and library preparation may enable translation of higher molecular weight DNA from other kits into longer read lengths. These findings provide a novel insight into the importance of optimising DNA extraction for achieving replicable results from long read metagenomic sequencing of environmental samples.

Distinctive patterns of bacterial community succession in the riverine micro-plastisphere in view of biofilm development and ecological niches

Exploring plastic bacterial community succession is a crucial step in analyzing and predicting the ecological assembly processes of the plastisphere and its associated environmental impacts. However, microbial biofilm development and niche differentiation during plastic bacterial community succession have rarely scarcely considered. Here, we assessed the differences between three microplastics (MPs) and two natural polymers in terms of biofilm development and niche properties during bacterial community succession, and identified a genus of MPs-degrading bacteria with strong competitive potential in the plastisphere. MPs biofilm development exhibits secondary succession characteristics, whereas natural polymer biofilms persist during the primary succession stage. During succession in plastic bacterial communities, the relationship between nutrient resources and microbial competition was reflected in a positive correlation between species competition and niche breadth, which contradicted the common belief that increased nutrient availability leads to reduced competition. Furthermore, the co-occurrence network revealed that specialists were species with greater competitive potential within the plastisphere. Additionally, the MPs-degrading Exiguobacterium genus represented a key taxon in the plastisphere. Our study provides a reliable pathway for revealing the specificity of plastic bacterial community succession from multiple perspectives and enhances the understanding of ecological assembly processes in the plastisphere.

Genomic convergence in terrestrial root plants through tandem duplication in response to soil microbial pressures

Despite increasing reports of convergent adaptation, evidence for genomic convergence across diverse species worldwide is lacking. Here, our study of 205 Archaeplastida genomes reveals evidence of genomic convergence through tandem duplication (TD) across different lineages of root plants despite their genomic diversity. TD-derived genes, notably prevalent in trees with developed root systems embedded in soil, are enriched in enzymatic catalysis and biotic stress responses, suggesting adaptations to environmental pressures. Correlation analyses suggest that many factors, particularly those related to soil microbial pressures, are significantly associated with TD dynamics. Conversely, flora transitioned to aquatic, parasitic, halophytic, or carnivorous lifestyles-reducing their interaction with soil microbes-exhibit a consistent decline in TD frequency. This trend is further corroborated in mangroves that independently adapted to hypersaline intertidal soils, characterized by diminished microbial activity. Our findings propose TD-driven genomic convergence as a widespread adaptation to soil microbial pressures among terrestrial root plants.

Microbial community storm dynamics signal sources of "old" stream water

Accurate characterization of the movement of water through catchments, particularly during precipitation event response, is critical for hydrological efforts such as contaminant transport modeling or prediction of extreme flows. Abiotic hydrogeochemical tracers are commonly used to track sources and ages of surface waters but provide limited details about transit pathways or the spatial dynamics of water storage and release. Alternatively, biotic material in streams is derived from thousands of taxa originating from a variety of environments within watersheds, including groundwater, sediment, and upslope terrestrial environments, and this material can be characterized with genetic sequencing and bioinformatics. We analyzed the stable water isotopes (δ18O and δ2H) and microbiome composition (16S rRNA gene amplicon sequencing) of the Marys River of western Oregon, USA during an early season storm to describe the processes, storage, and flowpaths that shape surface water hydrology. Stable water isotopes (δ18O and δ2H) typified an event response in which stream water is composed largely of 'old' water introduced to the catchment before the storm, a common though not well understood phenomenon. In contrast, microbial biodiversity spiked during the storm, consisting of early- and late-event communities clearly distinguishable from pre-event communities. We applied concentration-discharge (cQ) analysis to individual microbial taxa and found that most Alphaproteobacteria sequences were positively correlated (i.e., were mobilized) with discharge, whereas most sequences from phyla Gammaproteobacteria and Bacteroidota were negatively correlated with discharge (i.e., were diluted). Source predictions using the prokaryote habitat preference database ProkAtlas found that freshwater-associated microbes composed a smaller fraction of the microbial community during the stream rise and a larger fraction during the recession, while soil and biofilm-associated microbes increased during the storm and remained high during recession. This suggests that the "old" water discharged during the storm was likely stored and released from, or passed through, soil- and biofilm-rich environments, demonstrating that this approach adds new, biologically derived tracer information about the hydrologic pathways active during and after this event. Overall, this study demonstrates an approach for integrating information-rich DNA into water resource investigations, incorporating tools from both hydrology and microbiology to demonstrate that microbial DNA is useful not only as an indicator of biodiversity but also functions as an innovative hydrologic tracer.

Profiling the fecal microbiome and its modulators across the lifespan in the Netherlands

Defining what constitutes a healthy microbiome throughout our lives remains an ongoing challenge. Understanding to what extent host and environmental factors can influence it has been the primary motivation for large population studies worldwide. Here, we describe the fecal microbiome of 3,746 individuals (0-87 years of age) in a nationwide study in the Netherlands, in association with extensive questionnaires. We validate previous findings, such as infant-adult trajectories, and explore the collective impact of our variables, which explain over 40% of the variation in microbiome composition. We identify associations with less explored factors, particularly those ethnic related, which show the largest impact on the adult microbiome composition, diversity, metabolic profiles, and CAZy (carbohydrate-active enzyme) repertoires. Understanding the sources of microbiome variability is crucial, given its potential as a modifiable target with therapeutic possibilities. With this work, we aim to serve as a foundational element for the design of health interventions and fundamental research.

Vegetable phylloplane microbiomes harbour class 1 integrons in novel bacterial hosts and drive the spread of chlorite resistance

Bacterial hosts in vegetable phylloplanes carry mobile genetic elements, such as plasmids and transposons that are associated with integrons. These mobile genetic elements and their cargo genes can enter human microbiomes via consumption of fresh agricultural produce, including uncooked vegetables. This presents a risk of acquiring antimicrobial resistance genes from uncooked vegetables. To better understand horizontal gene transfer of class 1 integrons in these compartments, we applied epicPCR, a single-cell fusion-PCR surveillance technique, to link the class 1 integron integrase (intI1) gene with phylogenetic markers of their bacterial hosts. Ready-to-eat salads carried class 1 integrons from the phyla Bacteroidota and Pseudomonadota, including four novel genera that were previously not known to be associated with intI1. We whole-genome sequenced Pseudomonas and Erwinia hosts of pre-clinical class 1 integrons that are embedded in Tn402-like transposons. The proximal gene cassette in these integrons was identified as a chlorite dismutase gene cassette, which we showed experimentally to confer chlorite resistance. Chlorine-derived compounds such as acidified sodium chlorite and chloride dioxide are used to disinfectant raw vegetables in food processing facilities, suggesting selection for chlorite resistance in phylloplane integrons. The spread of integrons conferring chlorite resistance has the potential to exacerbate integron-mediated antimicrobial resistance (AMR) via co-selection of chlorite resistance and AMR, thus highlighting the importance of monitoring chlorite residues in agricultural produce. These results demonstrate the strength of combining epicPCR and culture-based isolation approaches for identifying hosts and dissecting the molecular ecology of class 1 integrons.

Potential applications of microbial genomics in nuclear non-proliferation

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as "characteristic communities of microorganisms" found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

Unraveling the distribution pattern and driving forces of soil microorganisms under geographic barriers

The Altai Mountains (ALE) and the Greater Khingan Mountains (GKM) in northern China are forest regions dominated by coniferous trees. These geographically isolated regions provide an ideal setting for studying microbial biogeographic patterns. In this study, we employed high-throughput techniques to obtain DNA sequences of soil myxomycetes, bacteria, and fungi and explored the mechanisms underlying the assembly of both local and cross-regional microbial communities in relation to environmental factors. Our investigation revealed that the environmental heterogeneity in ALE and GKM significantly affected the succession and assembly of soil bacterial communities at cross-regional scales. Specifically, the optimal environmental factors affecting bacterial Bray-Curtis similarity were elevation and temperature seasonality. The spatial factors and climate change impact on bacterial communities under the geographical barriers surpassed that of local soil microenvironments. The assembly pattern of bacterial communities transitions from local drift to cross-regional heterogeneous selection. Environmental factors had a relatively weak influence on myxomycetes and fungi. Both soil myxomycetes and fungi faced considerable dispersal limitation at local and cross-regional scales, ultimately leading to weak geographical distribution patterns.IMPORTANCEThe impact of environmental selection and dispersal on the soil microbial spatial distribution is a key concern in microbial biogeography, particularly in large-scale geographical patterns. However, our current understanding remains limited. Our study found that soil bacteria displayed a distinct cross-regional geographical distribution pattern, primarily influenced by environmental selection. Conversely, the cross-regional geographical distribution patterns of soil myxomycetes and fungi were relatively weak. Their composition exhibited a weak association with the environment at local and cross-regional scales, with assembly primarily driven by dispersal limitation.

Diverse non-canonical electron bifurcating [FeFe]-hydrogenases of separate evolutionary origins in Hydrogenedentota

Hydrogenedentota, a globally distributed bacterial phylum-level lineage, is poorly understood. Here, we established a comprehensive genomic catalog of Hydrogenedentota, including a total of seven clades (or families) with 179 genomes, and explored the metabolic potential and evolutionary history of these organisms. We show that a single genome, especially those belonging to Clade 6, often encodes multiple hydrogenases with genomes in Clade 2, which rarely encode hydrogenases being the exception. Notably, most members of Hydrogenedentota contain a group A3 [FeFe]-hydrogenase (BfuABC) with a non-canonical electron bifurcation mechanism, in addition to substrate-level phosphorylation and electron transport-linked phosphorylation pathways, in energy conservation. Furthermore, we show that BfuABC from Hydrogenedentota fall into five sub-types. Phylogenetic analysis reveals five independent routes for the evolution of BfuABC homologs in Hydrogenedentota. We speculate that the five sub-types of BfuABC might be acquired from Bacillota (synonym Firmicutes) through separate horizontal gene transfer events. These data shed light on the diversity and evolution of bifurcating [FeFe]-hydrogenases and provide insight into the strategy of Hydrogenedentota to adapt to survival in various habitats.

IMPORTANCE

The phylum Hydrogenedentota is widely distributed in various environments. However, their physiology, ecology, and evolutionary history remain unknown, primarily due to the limited availability of the genomes and the lack of cultured representatives of the phylum. Our results have increased the knowledge of the genetic and metabolic diversity of these organisms and shed light on their diverse energy conservation strategies, especially those involving electron bifurcation with a non-canonical mechanism, which are likely responsible for their wide distribution. Besides, the organization and phylogenetic relationships of gene clusters coding for BfuABC in Hydrogenedentota provide valuable clues to the evolutionary history of group A3 electron bifurcating [FeFe]-hydrogenases.

Methane-oxidizing bacterial community dynamics in sub-alpine forest soil

Microbial activities in sub-alpine forest soil influence global cycling of the potent greenhouse gas methane. Understanding the dynamics of methane-oxidizing bacterial communities, particularly the roles of potentially active versus total microbial populations, is necessary for reducing uncertainty in global methane budget estimates. However, our understanding of the factors influencing methane cycling in forest soils is limited by our lack of knowledge about the biology of the microbes involved and how these communities are shaped by their environment. Here, we compared the composition and potential activity of microbial communities using 16S rRNA gene amplicon sequencing of total genomic DNA (gDNA) and potentially active complementary DNA (cDNA) from shallow soil in Red Butte Canyon (Salt Lake City, Utah, USA). We compared riparian and upland soils at two time points in the growing season and found distinct differences in both the community composition of the gDNA and cDNA libraries and the potential drivers of these community structures. Aerobic methane-oxidizing bacteria (methanotrophs) were detected in all samples, with cDNA libraries containing a higher average relative abundance and diversity of methanotrophs compared to gDNA libraries. Methane flux at the sample sites did not significantly correlate to the relative abundance (gDNA) or potential activity (cDNA) of methanotrophs. In the cDNA libraries, there were significant positive correlations between the abundance of Methylococcaceae family methanotrophs and several non-methanotrophic methylotrophs previously found to be associated with methane-oxidizing bacterial communities. These findings suggest a complex relationship between methane-cycling bacterial communities and methane flux and highlight the need for further in situ studies to understand the environmental and ecological influences of these microbial consortia.

IMPORTANCE

Methane-oxidizing bacteria are found in diverse soil and sediment environments and play an important role in mitigating flux of this potent greenhouse gas into the atmosphere. However, it is unclear how these bacteria and their associated communities are structured in the environment and how their activity ultimately influences methane flux. In this work, we examine the composition and structure of methane-oxidizing bacterial communities in sub-alpine forest soil and find soil- and time-specific differences between the stable and potentially active populations. We also find that the potentially active populations of certain methanotrophs and non-methanotrophs are positively correlated. This work provides a step toward refining our understanding of microbially mediated biogeochemical cycles.

Refining microbial community metabolic models derived from metagenomics using reference-based taxonomic profiling

Characterization of microbial community metabolic output is crucial to understanding their functions. Construction of genome-scale metabolic models from metagenome-assembled genomes (MAG) has enabled prediction of metabolite production by microbial communities, yet little is known about their accuracy. Here, we examined the performance of two approaches for metabolite prediction from metagenomes, one that is MAG-guided and another that is taxonomic reference-guided. We applied both on shotgun metagenomics data from human and environmental samples, and validated findings in the human samples using untargeted metabolomics. We found that in human samples, where taxonomic profiling is optimized and reference genomes are readily available, when number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach. The two approaches showed significant overlap but each identified metabolites not predicted in the other. Pathway enrichment analyses identified significant differences in inferences derived from data based on the approach, highlighting the need for caution in interpretation. In environmental samples, when the number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach for total metabolites in both sample types and non-redundant metabolites in seawater samples. Nonetheless, as was observed for the human samples, the approaches overlapped substantially but also predicted metabolites not observed in the other. Our findings report on utility of a complementary input to genome-scale metabolic model construction that is less computationally intensive forgoing MAG assembly and refinement, and that can be applied on shallow shotgun sequencing where MAGs cannot be generated.IMPORTANCELittle is known about the accuracy of genome-scale metabolic models (GEMs) of microbial communities despite their influence on inferring community metabolic outputs and culture conditions. The performance of GEMs for metabolite prediction from metagenomes was assessed by applying two approaches on shotgun metagenomics data from human and environmental samples, and validating findings in the human samples using untargeted metabolomics. The performance of the approach was found to be dependent on sample type, but collectively, the reference-guided approach predicted more metabolites than the MAG-guided approach. Despite the differences, the predictions from the approaches overlapped substantially but each identified metabolites not predicted in the other. We found significant differences in biological inferences based on the approach, with some examples of uniquely enriched pathways in one group being invalidated when using the alternative approach, highlighting the need for caution in interpretation of GEMs.

Unveiling the deterministic dynamics of microbial meta-metabolism: a multi-omics investigation of anaerobic biodegradation

BACKGROUND

Microbial anaerobic metabolism is a key driver of biogeochemical cycles, influencing ecosystem function and health of both natural and engineered environments. However, the temporal dynamics of the intricate interactions between microorganisms and the organic metabolites are still poorly understood. Leveraging metagenomic and metabolomic approaches, we unveiled the principles governing microbial metabolism during a 96-day anaerobic bioreactor experiment.

RESULTS

During the turnover and assembly of metabolites, homogeneous selection was predominant, peaking at 84.05% on day 12. Consistent dynamic coordination between microbes and metabolites was observed regarding their composition and assembly processes. Our findings suggested that microbes drove deterministic metabolite turnover, leading to consistent molecular conversions across parallel reactors. Moreover, due to the more favorable thermodynamics of N-containing organic biotransformations, microbes preferentially carried out sequential degradations from N-containing to S-containing compounds. Similarly, the metabolic strategy of C18 lipid-like molecules could switch from synthesis to degradation due to nutrient exhaustion and thermodynamical disadvantage. This indicated that community biotransformation thermodynamics emerged as a key regulator of both catabolic and synthetic metabolisms, shaping metabolic strategy shifts at the community level. Furthermore, the co-occurrence network of microbes-metabolites was structured around microbial metabolic functions centered on methanogenesis, with CH4 as a network hub, connecting with 62.15% of total nodes as 1st and 2nd neighbors. Microbes aggregate molecules with different molecular traits and are modularized depending on their metabolic abilities. They established increasingly positive relationships with high-molecular-weight molecules, facilitating resource acquisition and energy utilization. This metabolic complementarity and substance exchange further underscored the cooperative nature of microbial interactions.

CONCLUSIONS

All results revealed three key rules governing microbial anaerobic degradation. These rules indicate that microbes adapt to environmental conditions according to their community-level metabolic trade-offs and synergistic metabolic functions, further driving the deterministic dynamics of molecular composition. This research offers valuable insights for enhancing the prediction and regulation of microbial activities and carbon flow in anaerobic environments. Video Abstract.

Acidic proteomes are linked to microbial alkaline preference in African lakes

Microbial amino acid composition (AA) reflects adaptive strategies of cellular and molecular regulations such as a high proportion of acidic AAs, including glutamic and aspartic acids in alkaliphiles. It remains understudied how microbial AA content is linked to their pH adaptation especially in natural environments. Here we examined prokaryotic communities and their AA composition of genes with metagenomics for 39 water and sediments of East African lakes along a gradient of pH spanning from 7.2 to 10.1. We found that Shannon diversity declined with the increasing pH and that species abundance were either positively or negatively associated with pH, indicating their distinct habitat preference in lakes. Microbial communities showed higher acidic proteomes in alkaline than neutral lakes. Species acidic proteomes were also positively correlated with their pH preference, which was consistent across major bacterial lineages. These results suggest selective pressure associated with high pH likely shape microbial amino acid composition both at the species and community levels. Comparative genome analyses further revealed that alkaliphilic microbes contained more functional genes with higher acidic AAs when compared to those in neutral conditions. These traits included genes encoding diverse classes of cation transmembrane transporters, antiporters, and compatible solute transporters, which are involved in cytoplasmic pH homeostasis and osmotic stress defense under high pH conditions. Our results provide the field evidence for the strong relationship between prokaryotic AA composition and their habitat preference and highlight amino acid optimization as strategies for environmental adaptation.

Integrating functional metagenomics to decipher microbiome-immune interactions

Microbial metabolites can be viewed as the cytokines of the microbiome, transmitting information about the microbial and metabolic environment of the gut to orchestrate and modulate local and systemic immune responses. Still, many immunology studies focus solely on the taxonomy and community structure of the gut microbiota rather than its functions. Early sequencing-based microbiota profiling approaches relied on PCR amplification of small regions of bacterial and fungal genomes to facilitate identification of the microbes present. However, recent microbiome analysis methods, particularly shotgun metagenomic sequencing, now enable culture-independent profiling of microbiome functions and metabolites in addition to taxonomic characterization. In this review, we showcase recent advances in functional metagenomics methods and applications and discuss the current limitations and potential avenues for future development. Importantly, we highlight a few examples of key areas of opportunity in immunology research where integrating functional metagenomic analyses of the microbiome can substantially enhance a mechanistic understanding of microbiome-immune interactions and their contributions to health and disease states.

Effect of long-term liquid dairy manure application on activity and structure of bacteria and archaea in no-till soils depends on plant in development

This study aimed to evaluate the impact of long-term liquid dairy manure (LDM) application on the activity and structure of soil bacterial and archaea communities in two cropping seasons over 1 year of a no-till crop rotation system. The experiment was run in a sandy clay loam texture Oxisol, in Brazil, including LDM doses of 60, 120, and 180 m3 ha-1 year-1, installed in 2005. Soil sampling was conducted during spring 2018 and autumn 2019 at 0-10-cm depth. Microbial biomass carbon and nitrogen, 16S rRNA gene sequencing, microbial respiration and quotient were performed. Over the 14-year period, LDM application increased soil microbial community activity. Analysis of 16S rRNA gene sequencing revealed dominance by Proteobacteria, Acidobacteria, and Actinobacteria phyla (67% in spring and 70% in autumn). Genera Pirulla and Nitrososphaera showed enrichment at LDM doses of 120 and 180 m3 ha-1 year-1 doses, respectively. During spring, following black oat cropping, shifts in the relative abundance of Bacteroidetes, Proteobacteria, Firmicutes, Gemmatimonadetes, Verrucomicrobia, Chloroflexi, Actinobacteria, and AD3 phyla were observed due to LDM application, correlating with soil chemical indicators such as pH, K, Ca, Mn, and Zn. Our findings indicate that plant development strongly influences microbial community composition, potentially outweighing the impact of LDM. Our findings indicate that the application of liquid dairy manure alters the soil bacterial activity and community; however, this effect depends on the developing plant.

RiboSnake - a user-friendly, robust, reproducible, multipurpose and documentation-extensive pipeline for 16S rRNA gene microbiome analysis

Background

Next-generation sequencing for microbial communities has become a standard technique. However, the computational analysis remains resource-intensive. With declining costs and growing adoption of sequencing-based methods in many fields, validated, fully automated, reproducible and flexible pipelines are increasingly essential in various scientific fields.

Results

We present RiboSnake, a validated, automated, reproducible QIIME2-based pipeline implemented in Snakemake for analysing 16S rRNA gene amplicon sequencing data. RiboSnake includes pre-packaged validated parameter sets optimized for different sample types, from environmental samples to patient data. The configuration packages can be easily adapted and shared, requiring minimal user input.

Conclusion

RiboSnake is a new alternative for researchers employing 16S rRNA gene amplicon sequencing and looking for a customizable and user-friendly pipeline for microbiome analyses with in vitro validated settings. By automating the analysis with validated parameters for diverse sample types, RiboSnake enhances existing methods significantly. The workflow repository can be found on GitHub (https://github.com/IKIM-Essen/RiboSnake).

Community structure and assembly of myxomycetes in northern Chinese forests under geographic barriers

The study of myxomycete biogeography has a long-standing history and has consistently drawn scholarly interest. Nevertheless, studies focusing specifically on the spatial and temporal distribution patterns of myxomycete diversity are relatively limited, with even fewer investigating the mechanisms driving the generation and maintenance of myxomycete diversity. Therefore, this study selected two geographically distant sampling sites within northern Chinese forests to investigate myxomycete species composition, community structure, environmental drivers, and assembly patterns under geographic barriers. We established plots in the Altai Mountains (ALE) and the Greater Khingan Mountains (GKM), gathered bark and litter, and conducted 80-day moist chamber cultures of myxomycetes. Additionally, myxomycete specimens were collected in the field simultaneously to supplement the data set. This study collected 541 myxomycete specimens belonging to 73 species from 28 genera, spanning 12 families and eight orders. The ALE and the GKM had 20 identical species, accounting for 27% of the total species. Myxomycetes from both regions exhibited abundant occurrence 18 days after cultivation, with the quantity on bark substrates notably higher than on litter. Arcyria pomiformis and Comatricha elegans were the most common species in moist chamber cultures. Mantel test outcomes revealed that environmental factors had no significant impact on myxomycete community similarity between the two areas, aligning with findings from the neutral community model analysis, indicating a predominant influence of stochastic processes on myxomycete community structure in moist chamber cultures. This study represents the first application of a quantitative framework to analyze myxomycete community assembly cultivated in moist chambers.

Spatial analysis of murine microbiota and bile acid metabolism during amoxicillin treatment

Antibiotics cause collateral damage to resident microbes that is associated with various health risks. To date, studies have largely focused on the impacts of antibiotics on large intestinal and fecal microbiota. Here, we employ a gastrointestinal (GI) tract-wide integrated multiomic approach to show that amoxicillin (AMX) treatment reduces bacterial abundance, bile salt hydrolase activity, and unconjugated bile acids in the small intestine (SI). Losses of fatty acids (FAs) and increases in acylcarnitines in the large intestine (LI) correspond with spatially distinct expansions of Proteobacteria. Parasutterella excrementihominis engage in FA biosynthesis in the SI, while multiple Klebsiella species employ FA oxidation during expansion in the LI. We subsequently demonstrate that restoration of unconjugated bile acids can mitigate losses of commensals in the LI while also inhibiting the expansion of Proteobacteria during AMX treatment. These results suggest that the depletion of bile acids and lipids may contribute to AMX-induced dysbiosis in the lower GI tract.

Impact of methane mitigation strategies on the native ruminant microbiome: A protocol for a systematic review and meta-analysis

Recently, research has investigated the role of the ruminant native microbiome, and the role microbes play in methane (CH4) production and mitigation. However, the variation across microbiome studies makes implementing impactful strategies difficult. The first objective of this study is to identify, summarize, compile, and discuss the current literature on CH4 mitigation strategies and how they interact with the native ruminant microbiome. The second objective is to perform a meta-analysis on the identified16S rRNA sequencing data. A literature search using Web of Science, Scopus, AGRIS, and Google Scholar will be implemented. Eligible criteria will be defined using PICO (population, intervention, comparator, and outcomes) elements. Two independent reviewers will be utilized for both the literature search and data compilation. Risk of bias will be assessed using the Cochrane Risk Bias 2.0 tool. Publicly available 16S rRNA amplicon gene sequencing data will be downloaded from NCBI Sequence Read Archive, European Nucleotide Archive or similar database using appropriate extraction methods. Data processing will be performed using QIIME2 following a standardized protocol. Meta-analyses will be performed on both alpha and beta diversity as well as taxonomic analyses. Alpha diversity metrics will be tested using a Kruskal-Wallis test with a Benjamini-Hochberg multiple testing correction. Beta diversity will be statistically tested using PERMANOVA testing with multiple test corrections. Hedge's g standardized mean difference statistic will be used to calculate fixed and random effects model estimates using a 95% confidence interval. Heterogeneity between studies will be assessed using the I2 statistic. Potential publication bias will be further assessed using Begg's correlation test and Egger's regression test. The GRADE approach will be used to assess the certainty of evidence. The following protocol will be used to guide future research and meta-analyses for investigating CH4 mitigation strategies and ruminant microbial ecology. The future work could be used to enhance livestock management techniques for GHG control. This protocol is registered in Open Science Framework (https://osf.io/vt56c) and available in the Systematic Reviews for Animals and Food (https://www.syreaf.org/contact).

Soil properties predict below-ground community structure, but not nematode microbiome patterns in semi-arid habitats

Microbial and microeukaryotic communities are extremely abundant and diverse in soil habitats where they play critical roles in ecosystem functioning and services that are essential to soil health. Soil biodiversity is influenced by above-ground (vegetation) and below-ground factors (soil properties), which together create habitat-specific conditions. However, the compound effects of vegetation and soil properties on soil communities are less studied or often focused on one component of the soil biota. Here, we integrate metabarcoding (16S and 18S rRNA genes) and nematode morphology to assess the effects of habitat and soil properties shaping microbial and microeukaryotic communities as well as nematode-associated microbiomes. We show that both vegetation and soil properties (soil bulk density) were major factors structuring microbial and microeukaryotic communities in semi-arid soil habitats. Despite having lower nutrients and lower pH, denser soils displayed significantly higher alpha diversity than less dense soils across datasets. Nematode-associated microbiomes have lower microbial diversity, strongly differ from soil microbes and are more likely to respond to microscale variations among samples than to vegetation or soil bulk density. Consequently, different nematode lineages and trophic groups are likely to display similar associated microbiomes when sharing the same microhabitat. Different microbiome taxa were enriched within specific nematode lineages (e.g. Mycobacterium, Candidatus Cardinium) highlighting potentially new species-specific associations that may confer benefits to their soil nematode hosts. Our findings highlight the importance of exploring above- and below-ground effects to assess community structure in terrestrial habitats, and how fine-scale analyses are critical for understanding patterns of host-associated microbiomes.

A potential CO2 carrier to improve the utilization of HCO3- by plant-soil ecosystem for carbon sink enhancement

INTRODUCTION

Improving the rhizospheric HCO3- utilization of plant-soil ecosystem could increase the carbon sink effect of terrestrial ecosystem. However, to avoid its physiological stress on the crop growth, the dosage of HCO3- allowed to add into the rhizosphere soil was always low (i.e., <5-20 mol/m3).

OBJECTIVES

To facilitate the utilization of relatively high concentrations of HCO3- by plants in the pursuit of achieving terrestrial carbon sink enhancement.

METHODS

In this study, the feasibility of directly supplementing a high concentration HCO3- carried by the biogas slurry to the plant rhizosphere was investigated using the tomato as a model plant.

RESULTS

The CO2-rich biogas slurry was verified as a potential CO2 carrier to increase the rhizospheric HCO3- concentration to 36 mol/m3 without causing a physiological stress. About 88.3 % of HCO3- carried by biogas slurry was successfully fixed by tomato-soil ecosystem, in which 43.8 % of HCO3- was assimilated by tomato roots for the metabolism, 0.5 ‰ of HCO3- was used by microorganisms for substances synthesis of cell structure through dark fixation, and 44.4 % of HCO3- was retained in the soil. The rest of HCO3- (∼11.7 %) might escape into the atmosphere through the reaction with H+. Correspondingly, the carbon fixation of tomato-soil ecosystem increased by 150.1 g-CO2/m2-soil during a tomato growth cycle. As for the global countries that would adopt the strategy proposed in this study to cultivate the tomato, an extra carbon sink of soil with about 1031.1 kt-C per year (i.e., an additional 0.21 tons of carbon per hectare soil) could be obtained.

CONCLUSION

This would be consistent with the goal of soil carbon sink enhancement launched at COP21. Furthermore, the regions with low GDP per capita may easily achieve a high reduction potential of CO2 emissions from the agricultural land after adopting the irrigation of CO2-rich biogas slurry.

Prokaryote communities along a source-to-estuary river continuum in the Brazilian Atlantic Forest

The activities of microbiomes in river sediments play an important role in sustaining ecosystem functions by driving many biogeochemical cycles. However, river ecosystems are frequently affected by anthropogenic activities, which may lead to microbial biodiversity loss and/or changes in ecosystem functions and related services. While parts of the Atlantic Forest biome stretching along much of the eastern coast of South America are protected by governmental conservation efforts, an estimated 89% of these areas in Brazil are under threat. This adds urgency to the characterization of prokaryotic communities in this vast and highly diverse biome. Here, we present prokaryotic sediment communities in the tropical Juliana River system at three sites, an upstream site near the river source in the mountains (Source) to a site in the middle reaches (Valley) and an estuarine site near the urban center of Ituberá (Mangrove). The diversity and composition of the communities were compared at these sites, along with environmental conditions, the former by using qualitative and quantitative analyses of 16S rRNA gene amplicons. While the communities included distinct populations at each site, a suite of core taxa accounted for the majority of the populations at all sites. Prokaryote diversity was highest in the sediments of the Mangrove site and lowest at the Valley site. The highest number of genera exclusive to a given site was found at the Source site, followed by the Mangrove site, which contained some archaeal genera not present at the freshwater sites. Copper (Cu) concentrations were related to differences in communities among sites, but none of the other environmental factors we determined was found to have a significant influence. This may be partly due to an urban imprint on the Mangrove site by providing organic carbon and nutrients via domestic effluents.

16S amplicon-based microbiome biomapping of a commercial broiler hatchery

Hatcheries, where eggs from multiple breeder farms are incubated and hatched before being sent to different broiler farms, represent a nexus point in the commercial production of broilers in the United States. Considering all downstream microbial quality and safety aspects of broiler production (live production, processing, consumer use) can be potentially affected by the hatchery, a better understanding of microbial ecology within commercial hatcheries is essential. Therefore, a commercial broiler hatchery was biomapped using 16S rRNA amplicon-based microbiome analyses of four sample type categories (Air, Egg, Water, Facility) across five different places in the pre-hatch, hatch, and post-hatch areas. While distinct microbiota were found for each sample type category and hatchery area, microbial community analyses revealed that Egg microbiota trended towards clustering with the facility-related samples when moving from the prehatch to post-hatch areas, highlighting the potential effect of the hatchery environment in shaping the pre-harvest broiler-related microbiota. Prevalence analyses revealed 20 ASVs (Core20) present in the core microbiota of all sample types and areas, with each ASV possessing a unique distribution throughout the hatchery. Interestingly, three Enterobacteriaceae ASVs were in the Core20, including Salmonella. Subsequent analyses showed that Salmonella, while a minor prehatch and hatch Core20ASV, dominated the Enterobacteriaceae niche and total microbiota in the chick pad feces in the post-hatch area of the hatchery, and the presence of this Salmonella ASV in the post-hatch feces was associated with swabs of breakroom tables. These findings highlight the complexity of commercial hatchery microbiota, including identifying chick pad feces and breakroom tables as potentially important sampling or disinfection targets for hatchery managers to focus their Salmonella mitigation efforts to reduce loads entering live production farms.

MICROPHERRET: MICRObial PHEnotypic tRait ClassifieR using Machine lEarning Techniques

BACKGROUND

In recent years, there has been a rapid increase in the number of microbial genomes reconstructed through shotgun sequencing, and obtained by newly developed approaches including metagenomic binning and single-cell sequencing. However, our ability to functionally characterize these genomes by experimental assays is orders of magnitude less efficient. Consequently, there is a pressing need for the development of swift and automated strategies for the functional classification of microbial genomes.

RESULTS

The present work leverages a suite of supervised machine learning algorithms to establish a range of 86 metabolic and other ecological functions, such as methanotrophy and plastic degradation, starting from widely obtainable microbial genome annotations. Tests performed on independent datasets demonstrated robust performance across complete, fragmented, and incomplete genomes above a 70% completeness level for most of the considered functions. Application of the algorithms to the Biogas Microbiome database yielded predictions broadly consistent with current biological knowledge and correctly detecting functionally-related nuances of archaeal genomes. Finally, a case study focused on acetoclastic methanogenesis demonstrated how the developed machine learning models can be refined or expanded with models describing novel functions of interest.

CONCLUSIONS

The resulting tool, MICROPHERRET, incorporates a total of 86 models, one for each tested functional class, and can be applied to high-quality microbial genomes as well as to low-quality genomes derived from metagenomics and single-cell sequencing. MICROPHERRET can thus aid in understanding the functional role of newly generated genomes within their micro-ecological context.

The impact of management on the fecal microbiome of endangered greater sage-grouse (Centrocercus urophasianus) in a zoo-based conservation program

Greater sage-grouse (Centrocercus urophasianus) are a critically endangered species in Canada with fewer than 140 individuals remaining on native habitats in southern Alberta and Saskatchewan. In 2014, the Wilder Institute/Calgary Zoo initiated North America's only zoo-based conservation breeding program for this species to bolster declining wild populations through conservation reintroductions. Within the managed population of sage-grouse, morbidity and mortality have primarily been associated with intestinal bacterial infections. As a preliminary study to assess the gastrointestinal health of this species in managed care, the fecal bacterial microbiome of adult and juvenile captive sage-grouse was characterized with 16S rRNA sequencing. The composition of the microbiome at the phylum level in greater sage-grouse is consistent with previous studies of the avian microbiome, with Bacillota as the most abundant phyla, and Actinomycetota, Bacteroidota and Pseudomonadota also being highly abundant. Antibiotic use and sex did not have a significant impact on the diversity or composition of the microbiome, but the management of juvenile sage-grouse did influence the development of the microbiome. Juveniles that were raised outdoors under maternal care developed a microbiome much more similar to adults when compared to chicks that were incubated and hand-raised. The local environment and parental care appear to be important factors influencing the diversity and composition of the gastrointestinal microbiome in this species.

PM-profiler: a high-resolution and fast tool for taxonomy annotation of amplicon-based microbiome

Amplicon sequencing stands as a cornerstone in microbiome profiling, yet concerns persist regarding its resolution and accuracy. The enhancement of reference databases and annotations marks a new era for 16S rRNA-based profiling. Capitalizing on this potential, we introduce PM-profiler, a novel tool for profiling amplicon short reads. PM-profiler is implemented by C++-based advanced algorithms, such as pre-allocated hash for reference construction, hybrid and dynamic short-read matching, big-data-guided dual-mode hierarchical taxonomy annotation strategy, and full-procedure parallel computing. This tool delivers species-level resolution and ultrafast speed for large-scale microbiomes, surpassing alignment-based approaches and the Naïve-Bayesian model. Furthermore, recognizing the global uneven distribution of microbes, we delineate optimal annotation strategies for each sampling habitat based on microbial patterns over 270,000 microbiomes. Integrated with the established workflow of Parallel-Meta Suite and the latest curated reference databases, this endeavor offers a swift and dependable solution for high-precision microbiome surveys.IMPORTANCEOur study introduces PM-profiler, a new tool that deciphers the complexity of microbial communities. With advanced algorithms, flexible annotation strategies, and well-organized big-data, PM-profiler provides a faster and more accurate way to study on microbiomes, paving the way for discoveries that could improve our understanding of microbiomes and their impact on the world.

Effects of high dose aspartame-based sweetener on the gut microbiota and bone strength in young and aged mice

In a recent study examining the effects of manipulating the gut microbiome on bone, a control group of mice in which the microbiome was altered using a non-caloric, aspartame-based sweetener resulted in whole bone strength being 40% greater than expected from geometry alone, implicating enhanced bone tissue strength. However, the study was not designed to detect changes in bone in this control group and was limited to young male mice. Here we report a replication study examining how changes in the gut microbiome caused by aspartame-based sweetener influence bone. Male and female C57Bl/6 J mice were untreated or treated with a high dose of sweetener (10 g/L) in their drinking water from either 1 to 4 mo of age (young cohort; n = 80) or 1 to 22 mo of age (aged cohort; n = 52). Sweetener did not replicate the modifications to the gut microbiome observed in the initial study and did not result in an increase in bone tissue strength in either sex at either age. Aged male mice dosed with sweetener had larger bones (+17% femur section modulus, p<.001) and greater whole bone strength (+22%, p=.006) but the increased whole bone strength was explained by the associated increase in body mass (+9%, p<.001). No differences in body mass, whole bone strength, or femoral geometry were associated with sweetener dosing in males from the young cohort or females at either age. As we were unable to replicate the gut microbiota observed in the initial experiment, it remains unclear if changes in the gut microbiome can enhance bone tissue strength. Although prior work studying gut microbiome-induced changes in bone with oral antibiotics has been highly repeatable, the current study highlights the variability of nutritional manipulations of the gut microbiota in mice.

Methyl-reducing methanogenesis by a thermophilic culture of Korarchaeia

Methanogenesis mediated by archaea is the main source of methane, a strong greenhouse gas, and thus is critical for understanding Earth's climate dynamics. Recently, genes encoding diverse methanogenesis pathways have been discovered in metagenome-assembled genomes affiliated with several archaeal phyla1-7. However, all experimental studies on methanogens are at present restricted to cultured representatives of the Euryarchaeota. Here we show methanogenic growth by a member of the lineage Korarchaeia within the phylum Thermoproteota (TACK superphylum)5-7. Following enrichment cultivation of 'Candidatus Methanodesulfokora washburnenis' strain LCB3, we used measurements of metabolic activity and isotope tracer conversion to demonstrate methanol reduction to methane using hydrogen as an electron donor. Analysis of the archaeon's circular genome and transcriptome revealed unique modifications in the energy conservation pathways linked to methanogenesis, including enzyme complexes involved in hydrogen and sulfur metabolism. The cultivation and characterization of this new group of archaea is critical for a deeper evaluation of the diversity, physiology and biochemistry of methanogens.

Metabolic complexity drives divergence in microbial communities

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

Multi-scale beta-diversity patterns in testate amoeba communities: species turnover and nestedness along a latitudinal gradient

The relationship between species diversity and spatial scale is a central topic in spatial community ecology. Latitudinal gradient is among the core mechanisms driving biodiversity distribution on most scales. Patterns of β-diversity along latitudinal gradient have been well studied for aboveground terrestrial and marine communities, whereas soil organisms remain poorly investigated in this regard. The West Siberian Plain is a good model to address diversity scale-dependence since the latitudinal gradient does not overlap with other possible factors such as elevational or maritime. Here, we collected 111 samples following hierarchical sampling (sub-zones, ecosystem types, microhabitat and replicate samples) and performed multi-scale partitioning of β-diversity of testate amoeba assemblages as a model of study. We found that among-ecosystem β-diversity is a leading scale in testate amoeba assemblages variation. Rare species determine β-diversity at all scale levels especially in the northern regions, where rare taxa almost exclusively accounted for the diversity at the ecosystem level. β-Diversity is generally dominated by the turnover component at all scales in lower latitudes, whereas nestedness prevailed at among-ecosystem scale in higher latitudes. These findings indicate that microbial assemblages in northern latitudes are spatially homogeneous and constrained by historical drivers at larger scales, whereas in southern regions, it is dominated by the turnover component both at the microhabitat and ecosystem scales and therefore determined by recent vegetation and environmental heterogeneity. Overall, we have provided the evidence for the existence of negative latitudinal gradient for among-ecosystem β-diversity but not for among-microhabitat and among-sample β-diversity for terrestrial testate amoeba communities.

The polymicrobial nature of the oral cavity and claws of cats diagnosed by mass spectrometry and next-generation sequencing

Close contact between cats and humans increases the risk of transmission of zoonotic pathogens, through bites and scratches due to the complexity of microorganisms in the oral and nail microbiotas of felines. This study investigated the presence of bacteria and fungi in the oral cavity and claws of 100 apparently healthy cats using conventional and selective microbiological culture media, and next-generation sequencing (NGS) and mass spectrometry (MALDI-TOF MS). Furthermore, antimicrobial susceptibility testing of bacteria isolates was performed by disc diffusion method. In total, 671 bacteria and 33 yeasts were identified by MALDI-TOF MS. Neisseria animaloris (10.8 %), Staphylococcus felis (8.5 %), and Pasteurella multocida (7 %) were the most prevalent bacteria in oral cavity samples (n = 343), while the most common yeast (n = 19) was Candida albicans (68.4 %). Staphylococcus pettenkoferi (13.4 %), Staphylococcus felis (6.4 %), and Staphylococcus simulans (5.8 %) were the prevalent bacteria identified in the claw samples (n = 328), while Rhodotorula mucilaginosa (57.2 %) was the most common yeast (n = 14). NGS predominantly identified the genera Moraxella, Neisseria, Pasteurella, and Fusobacterium in oral cavity samples, whereas enterobacteria and staphylococci were prevalent in nail bed samples. In addition, the genera Capnocytophaga and Bartonella were identified, which have been described in serious human infections secondary to feline aggressions. Levofloxacin, marbofloxacin, and amoxicillin/clavulanic acid were the most effective drugs against the main groups of bacteria identified. Multidrug resistance was observed in 17 % of the bacterial isolates. Furthermore, three staphylococci harboring the methicillin resistance gene mecA were identified. We highlight the complexity of microorganisms inhabiting the oral/claw microbiotas of cats, the high resistance rate of the isolates to conventional antimicrobial agents, and the zoonotic risk of aggressions caused by bites and scratches from domestic cats.

Domestication and evolutionary histories of specialized gut symbionts across cephalotine ants

The evolution of animals and their gut symbionts is a complex phenomenon, obscured by lability and diversity. In social organisms, transmission of symbionts among relatives may yield systems with more stable associations. Here, we study the history of a social insect symbiosis involving cephalotine ants and their extracellular gut bacteria, which come predominantly from host-specialized lineages. We perform multi-locus phylogenetics for symbionts from nine bacterial orders, and map prior amplicon sequence data to lineage-assigned symbiont genomes, studying distributions of rigorously defined symbionts across 20 host species. Based on monophyly and additional hypothesis testing, we estimate that these specialized gut bacteria belong to 18 distinct lineages, of which 15 have been successfully isolated and cultured. Several symbiont lineages showed evidence for domestication events that occurred later in cephalotine evolutionary history, and only one lineage was ubiquitously detected in all 20 host species and 48 colonies sampled with amplicon 16S rRNA sequencing. We found evidence for phylogenetically constrained distributions in four symbionts, suggesting historical or genetic impacts on community composition. Two lineages showed evidence for frequent intra-lineage co-infections, highlighting the potential for niche divergence after initial domestication. Nearly all symbionts showed evidence for occasional host switching, but four may, more often, co-diversify with their hosts. Through our further assessment of symbiont localization and genomic functional profiles, we demonstrate distinct niches for symbionts with shared evolutionary histories, prompting further questions on the forces underlying the evolution of hosts and their gut microbiomes.

Microbial Metagenomics Revealed the Diversity and Distribution Characteristics of Groundwater Microorganisms in the Middle and Lower Reaches of the Yangtze River Basin

Groundwater is one of the important freshwater resources on Earth and is closely related to human activities. As a good biological vector, a more diverse repertory of antibiotic resistance genes in the water environment would have a profound impact on human medical health. Therefore, this study conducted a metagenomic sequencing analysis of water samples from groundwater monitoring points in the middle and lower reaches of the Yangtze River to characterize microbial community composition and antibiotic resistance in the groundwater environment. Our results show that different microbial communities and community composition were the driving factors in the groundwater environment, and a diversity of antibiotic resistance genes in the groundwater environment was detected. The main source of antibiotic resistance gene host was determined by correlation tests and analyses. In this study, metagenomics was used for the first time to comprehensively analyze microbial communities in groundwater systems in the middle and lower reaches of the Yangtze River basin. The data obtained from this study serve as an invaluable resource and represent the basic metagenomic characteristics of groundwater microbial communities in the middle and lower reaches of the Yangtze River basin. These findings will be useful tools and provide a basis for future research on water microbial community and quality, greatly expanding the depth and breadth of our understanding of groundwater.

Gut microbiome diversity and biogeography for Chinese bumblebee Bombus pyrosoma

Gut microbiota of the bumblebee is critical as it modulates the health and fitness of the host. However, the mechanisms underlying the formation and maintenance of the diversity of bumblebee gut bacteria over a long period of evolution have yet to be elucidated. In particular, the gut bacterial diversity and community assembly processes of Bombus pyrosoma across the Chinese border remain unclear. In this study, we systematically carried out unprecedented sampling of 513 workers of the species Bombus pyrosoma across the Chinese landscape and used full-length 16S rRNA gene sequencing to examine their gut microbiota diversity and biogeography. The gut microbiota composition and community structure of Bombus pyrosoma from different geographical locations were diverse. On the whole, the gut bacteria Gilliamella and Snodgrassella are dominant in bumblebees, but opportunistic pathogens Serratia and Pseudomonas are dominant in some sampling sites such as Hb15, Gs1, Gs45, Qhs15, and Ssx35. All or part of environmental factors such as latitude, annual mean temperature, elevation, human footprint, population density, and annual precipitation can affect the alpha diversity and community structure of gut bacteria. Further analysis showed that the assembly and shift of bumblebee gut bacterial communities under geographical variation were mainly driven by the stochastic drift of the neutral process rather than by variable selection of niche differentiation. In conclusion, our unprecedented sampling uncovers bumblebee gut microbiome diversity and shifts over evolutionary time.

IMPORTANCE

The microbiotas associated with organisms facilitates host health and fitness, and the homeostasis status of gut microbiota also reflects the habitat security faced by the host. In addition, managing gut microbiota is important to improve bumblebee health by understanding the ecological process of the gut microbiome. Thus, we first carried out an runprecedented sampling of 513 workers of the species Bombus pyrosoma across the Chinese landscape and used full-length 16S rRNA gene sequencing to uncover their gut microbiota diversity and biogeography. Our study provides new insights into the understanding of gut microbiome diversity and shifts for Chinese Bumblebee over evolutionary time.

Unassigning bacterial species for microbiome studies

The method of 16S rRNA marker gene sequencing has fueled microbiome research and continues to be relevant. A perceived weakness of the method is that taxonomic assignments are not possible to make at the rank of species. We show that by working to rule out bacterial or archaeal species membership, we can provide an answer that is more accurate and useful. The Unassigner software operates on 16S rRNA marker gene data and computes a rule-out probability for species membership using a beta-binomial distribution. We demonstrate that our approach is accurate based on full-genome comparisons. Our method is consistent with existing approaches and dramatically improves on them based on the percentage of reads it can associate with a species in a sample. The software is available at https://github.com/PennChopMicrobiomeProgram/unassigner.IMPORTANCEWhile existing methods do not provide reliable species-level assignments for 16S rRNA marker gene data, the Unassigner software solves this problem by ruling out species membership, allowing researchers to reason at the species level.

SENSE-PPI reconstructs interactomes within, across, and between species at the genome scale

Ab initio computational reconstructions of protein-protein interaction (PPI) networks will provide invaluable insights into cellular systems, enabling the discovery of novel molecular interactions and elucidating biological mechanisms within and between organisms. Leveraging the latest generation protein language models and recurrent neural networks, we present SENSE-PPI, a sequence-based deep learning model that efficiently reconstructs ab initio PPIs, distinguishing partners among tens of thousands of proteins and identifying specific interactions within functionally similar proteins. SENSE-PPI demonstrates high accuracy, limited training requirements, and versatility in cross-species predictions, even with non-model organisms and human-virus interactions. Its performance decreases for phylogenetically more distant model and non-model organisms, but signal alteration is very slow. In this regard, it demonstrates the important role of parameters in protein language models. SENSE-PPI is very fast and can test 10,000 proteins against themselves in a matter of hours, enabling the reconstruction of genome-wide proteomes.

Dietary Acculturation Is Associated With Altered Gut Microbiome, Circulating Metabolites, and Cardiovascular Disease Risk in US Hispanics and Latinos: Results From HCHS/SOL

BACKGROUND

Dietary acculturation, or adoption of dominant culture diet by migrant groups, influences human health. We aimed to examine dietary acculturation and its relationships with cardiovascular disease (CVD), gut microbiota, and blood metabolites among US Hispanic and Latino adults.

METHODS

In the HCHS/SOL (Hispanic Community Health Study/Study of Latinos), US exposure was defined by years in the United States (50 states and Washington, DC) and US nativity. A dietary acculturation pattern was derived from 14 172 participants with two 24-hour dietary recalls at baseline (2008-2011) using least absolute shrinkage and selection operator regression, with food groups as predictors of US exposure. We evaluated associations of dietary acculturation with incident CVD across ≈7 years of follow-up (n=211/14 172 cases/total) and gut microbiota (n=2349; visit 2, 2014 to 2017). Serum metabolites associated with both dietary acculturation-related gut microbiota (n=694) and incident CVD (n=108/5256 cases/total) were used as proxy measures to assess the association of diet-related gut microbiome with incident CVD.

RESULTS

We identified an empirical US-oriented dietary acculturation score that increased with US exposure. Higher dietary acculturation score was associated with higher risk of incident CVD (hazard ratio per SD, 1.33 [95% CI, 1.13-1.57]), adjusted for sociodemographic, lifestyle, and clinical factors. Sixty-nine microbial species (17 enriched from diverse species, 52 depleted mainly from fiber-utilizing Clostridia and Prevotella species) were associated with dietary acculturation, driven by lower intakes of whole grains, beans, and fruits and higher intakes of refined grains. Twenty-five metabolites, involved predominantly in fatty acid and glycerophospholipid metabolism (eg, branched-chain 14:0 dicarboxylic acid** and glycerophosphoethanolamine), were associated with both diet acculturation-related gut microbiota and incident CVD. Proxy association analysis based on these metabolites suggested a positive relationship between diet acculturation-related microbiome and risk of CVD (r=0.70, P<0.001).

CONCLUSIONS

Among US Hispanic and Latino adults, greater dietary acculturation was associated with elevated CVD risk, possibly through alterations in gut microbiota and related metabolites. Diet and microbiota-targeted interventions may offer opportunities to mitigate CVD burdens of dietary acculturation.

Comparative evaluation of 16S rRNA primer pairs in identifying nitrifying guilds in soils under long-term organic fertilization and water management

Compared with 454 sequencing technology, short-read sequencing (e.g., Illumina) technology generates sequences of high accuracy, but limited length (<500 bp). Such a limitation can prove that studying a target gene using a large amplicon (>500 bp) is challenging. The ammonia monooxygenase subunit A (amoA) gene of ammonia-oxidizing archaea (AOA), which plays a crucial part in the nitrification process, is such a gene. By providing a full overview of the community of a functional microbial guild, 16S ribosomal ribonucleic acid (rRNA) gene sequencing could overcome this problem. However, it remains unclear how 16S rRNA primer selection influences the quantification of relative abundance and the identification of community composition of nitrifiers, especially AOA. In the present study, a comparison was made between the performance of primer pairs 338F-806R, 515F-806R, and 515F-907R to a shotgun metagenome approach. The structure of nitrifier communities subjected to different long-term organic matter amendment and water management protocols was assessed. Overall, we observed higher Chao1 richness diversity of soil total bacteria by using 515F-806R compared to 338F-806R and 515F-907R, while higher Pielou's evenness diversity was observed by using 515F-806R and 515F-907R compared to 338F-806R. The studied primer pairs revealed different performances on the relative abundance of Thaumarchaeota, AOB, and NOB. The Thaumarchaeota 16S rRNA sequence was rarely detected using 338F-806R, while the relative abundances of Thaumarchaeota detected using 515F-806R were higher than those detected by using 515F-907R. AOB showed higher proportions in the 338F-806R and 515F-907R data, than in 515F-806R data. Different primers pairs showed significant change in relative proportion of NOB. Nonetheless, we found consistent patterns of the phylotype distribution of nitrifiers in different treatments. Nitrosopumilales (NP) and Nitrososphaerales (NS) clades were the dominant members of the AOA community in soils subject to controlled irrigation, whereas Ca. Nitrosotaleales (NT) and NS clades dominated the AOA community in soils subject to flooding irrigation. Nitrospira lineage II was the dominant NOB phylotype in all samples. Overall, ideal 16S rRNA primer pairs were identified for the analysis of nitrifier communities. Moreover, NP and NT clades of AOA might have distinct environmental adaptation strategies under different irrigation treatments.

Quantifying compositional variability in microbial communities with FAVA

Microbial communities vary across space, time, and individual hosts, presenting new challenges for the development of statistics measuring the variability of community composition. To understand differences across microbiome samples from different host individuals, sampling times, spatial locations, or experimental replicates, we present FAVA, a new normalized measure for characterizing compositional variability across multiple microbiome samples. FAVA quantifies variability across many samples of taxonomic or functional relative abundances in a single index ranging between 0 and 1, equaling 0 when all samples are identical and equaling 1 when each sample is entirely comprised of a single taxon. Its definition relies on the population-genetic statisticF S T , with samples playing the role of "populations" and taxa playing the role of "alleles." Its convenient mathematical properties allow users to compare disparate data sets. For example, FAVA values are commensurable across different numbers of taxonomic categories and different numbers of samples considered. We introduce extensions that incorporate phylogenetic similarity among taxa and spatial or temporal distances between samples. We illustrate how FAVA can be used to describe across-individual taxonomic variability in ruminant microbiomes at different regions along the gastrointestinal tract. In a second example, a longitudinal analysis of gut microbiomes of healthy human adults taking an antibiotic, we use FAVA to quantify the increase in temporal variability of microbiomes following the antibiotic course and to measure the duration of the antibiotic's influence on microbial variability. We have implemented this tool in an R package, FAVA, which can fit easily into existing pipelines for the analysis of microbial relative abundances.