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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

Nepali oral microbiomes reflect a gradient of lifestyles from traditional to industrialized

Background

Lifestyle plays an important role in shaping the gut microbiome. However, its contributions to the oral microbiome remains less clear, due to the confounding effects of geography and methodology in investigations of populations studied to date. Furthermore, while the oral microbiome seems to differ between foraging and industrialized populations, we lack insight into whether transitions to and away from agrarian lifestyles shape the oral microbiota. Given the growing interest in so-called 'vanishing microbiomes' potentially being a risk factor for increased disease prevalence in industrialized populations, it is important that we distinguish lifestyle from geography in the study of microbiomes across populations.

Results

Here, we investigate salivary microbiomes of 63 Nepali individuals representing a spectrum of lifestyles: foraging, subsistence farming (individuals that transitioned from foraging to farming within the last 50 years), agriculturalists (individuals that have transitioned to farming for at least 300 years), and industrialists (expatriates that immigrated to the United States within the last 20 years). We characterize the role of lifestyle in microbial diversity, identify microbes that differ between lifestyles, and pinpoint specific lifestyle factors that may be contributing to differences in the microbiomes across populations. Contrary to prevailing views, when geography is controlled for, oral microbiome alpha diversity does not differ significantly across lifestyles. Microbiome composition, however, follows the gradient of lifestyles from foraging through agrarianism to industrialism, supporting the notion that lifestyle indeed plays a role in the oral microbiome. Relative abundances of several individual taxa, including Streptobacillus and an unclassified Porphyromonadaceae genus, also mirror lifestyle. Finally, we identify specific lifestyle factors associated with microbiome composition across the gradient of lifestyles, including smoking and grain source.

Conclusion

Our findings demonstrate that by controlling for geography, we can isolate an important role for lifestyle in determining oral microbiome composition. In doing so, we highlight the potential contributions of several lifestyle factors, underlining the importance of carefully examining the oral microbiome across lifestyles to improve our understanding of global microbiomes.

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.

Quantifying functional redundancy in polysaccharide-degrading prokaryotic communities

BACKGROUND

Functional redundancy (FR) is widely present, but there is no consensus on its formation process and influencing factors. Taxonomically distinct microorganisms possessing genes for the same function in a community lead to within-community FR, and distinct assemblies of microorganisms in different communities playing the same functional roles are termed between-community FR. We proposed two formulas to respectively quantify the degree of functional redundancy within and between communities and analyzed the FR degrees of carbohydrate degradation functions in global environment samples using the genetic information of glycoside hydrolases (GHs) encoded by prokaryotes.

RESULTS

Our results revealed that GHs are each encoded by multiple taxonomically distinct prokaryotes within a community, and the enzyme-encoding prokaryotes are further distinct between almost any community pairs. The within- and between-FR degrees are primarily affected by the alpha and beta community diversities, respectively, and are also affected by environmental factors (e.g., pH, temperature, and salinity). The FR degree of the prokaryotic community is determined by deterministic factors.

CONCLUSIONS

We conclude that the functional redundancy of GHs is a stabilized community characteristic. This study helps to determine the FR formation process and influencing factors and provides new insights into the relationships between prokaryotic community biodiversity and ecosystem functions. Video Abstract.

Diversity and structure of the deep-sea sponge microbiome in the equatorial Atlantic Ocean

Sponges (phylum Porifera) harbour specific microbial communities that drive the ecology and evolution of the host. Understanding the structure and dynamics of these communities is emerging as a primary focus in marine microbial ecology research. Much of the work to date has focused on sponges from warm and shallow coastal waters, while sponges from the deep ocean remain less well studied. Here, we present a metataxonomic analysis of the microbial consortia associated with 23 individual deep-sea sponges. We identify a high abundance of archaea relative to bacteria across these communities, with certain sponge microbiomes comprising more than 90 % archaea. Specifically, the archaeal family Nitrosopumilaceae is prolific, comprising over 99 % of all archaeal reads. Our analysis revealed that sponge microbial communities reflect the host sponge phylogeny, indicating a key role for host taxonomy in defining microbiome composition. Our work confirms the contribution of both evolutionary and environmental processes to the composition of microbial communities in deep-sea sponges.

A systematic comparison of natural product potential, with an emphasis on RiPPs, by mining of bacteria of three large ecosystems

The implementation of several global microbiome studies has yielded extensive insights into the biosynthetic potential of natural microbial communities. However, studies on the distribution of several classes of ribosomally synthesized and post-translationally modified peptides (RiPPs), non-ribosomal peptides (NRPs) and polyketides (PKs) in different large microbial ecosystems have been very limited. Here, we collected a large set of metagenome-assembled bacterial genomes from marine, freshwater and terrestrial ecosystems to investigate the biosynthetic potential of these bacteria. We demonstrate the utility of public dataset collections for revealing the different secondary metabolite biosynthetic potentials among these different living environments. We show that there is a higher occurrence of RiPPs in terrestrial systems, while in marine systems, we found relatively more terpene-, NRP-, and PK encoding gene clusters. Among the many new biosynthetic gene clusters (BGCs) identified, we analyzed various Nif-11-like and nitrile hydratase leader peptide (NHLP) containing gene clusters that would merit further study, including promising products, such as mersacidin-, LAP- and proteusin analogs. This research highlights the significance of public datasets in elucidating the biosynthetic potential of microbes in different living environments and underscores the wide bioengineering opportunities within the RiPP family.

Primary to post-depositional microbial controls on the stable and clumped isotope record of shoreline sediments at Fayetteville Green Lake

Lacustrine carbonates are a powerful archive of paleoenvironmental information but are susceptible to post-depositional alteration. Microbial metabolisms can drive such alteration by changing carbonate saturation in situ, thereby driving dissolution or precipitation. The net impact these microbial processes have on the primary δ18O, δ13C, and Δ47 values of lacustrine carbonate is not fully known. We studied the evolution of microbial community structure and the porewater and sediment geochemistry in the upper ~30 cm of sediment from two shoreline sites at Green Lake, Fayetteville, NY over 2 years of seasonal sampling. We linked seasonal and depth-based changes of porewater carbonate chemistry to microbial community composition, in situ carbon cycling (using δ13C values of carbonate, dissolved inorganic carbon (DIC), and organic matter), and dominant allochems and facies. We interpret that microbial processes are a dominant control on carbon cycling within the sediment, affecting porewater DIC, aqueous carbon chemistry, and carbonate carbon and clumped isotope geochemistry. Across all seasons and sites, microbial organic matter remineralization lowers the δ13C of the porewater DIC. Elevated carbonate saturation states in the sediment porewaters (Ω > 3) were attributed to microbes from groups capable of sulfate reduction, which were abundant in the sediment below 5 cm depth. The nearshore carbonate sediments at Green Lake are mainly composed of microbialite intraclasts/oncoids, charophytes, larger calcite crystals, and authigenic micrite-each with a different origin. Authigenic micrite is interpreted to have precipitated in situ from the supersaturated porewaters from microbial metabolism. The stable carbon isotope values (δ13Ccarb) and clumped isotope values (Δ47) of bulk carbonate sediments from the same depth horizons and site varied depending on both the sampling season and the specific location within a site, indicating localized (μm to mm) controls on carbon and clumped isotope values. Our results suggest that biological processes are a dominant control on carbon chemistry within the sedimentary subsurface of the shorelines of Green Lake, from actively forming microbialites to pore space organic matter remineralization and micrite authigenesis. A combination of biological activity, hydrologic balance, and allochem composition of the sediments set the stable carbon, oxygen, and clumped isotope signals preserved by the Green Lake carbonate sediments.

A global atlas of soil viruses reveals unexplored biodiversity and potential biogeochemical impacts

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities and interactions with the soil microbiome remains limited. Here we present the Global Soil Virus Atlas, a comprehensive dataset compiled from 2,953 previously sequenced soil metagenomes and composed of 616,935 uncultivated viral genomes and 38,508 unique viral operational taxonomic units. Rarefaction curves from the Global Soil Virus Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared viral operational taxonomic units across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents an extensive characterization of soil viral diversity and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

Metagenomic-based discovery and comparison of the lignin degrading potential of microbiomes in aquatic and terrestrial ecosystems via the LCdb database

Lignin, as an abundant organic carbon, plays a vital role in the global carbon cycle. However, our understanding of the global lignin-degrading microbiome remains elusive. The greatest barrier has been absence of a comprehensive and accurate functional gene database. Here, we first developed a curated functional gene database (LCdb) for metagenomic profiling of lignin degrading microbial consortia. Via the LCdb, we draw a clear picture describing the global biogeography of communities with lignin-degrading potential. They exhibit clear niche differentiation at the levels of taxonomy and functional traits. The terrestrial microbiomes showed the highest diversity, yet the lowest correlations. In particular, there were few correlations between genes involved in aerobic and anaerobic degradation pathways, showing a clear functional redundancy property. In contrast, enhanced correlations, especially closer inter-connections between anaerobic and aerobic groups, were observed in aquatic consortia in response to the lower diversity. Specifically, dypB and dypA, are widespread on Earth, indicating their essential roles in lignin depolymerization. Estuarine and marine consortia featured the laccase and mnsod genes, respectively. Notably, the roles of archaea in lignin degradation were revealed in marine ecosystems. Environmental factors strongly influenced functional traits, but weakly shaped taxonomic groups. Null mode analysis further verified that composition of functional traits was deterministic, while taxonomic composition was highly stochastic, demonstrating that the environment selects functional genes rather than taxonomic groups. Our study not only develops a useful tool to study lignin degrading microbial communities via metagenome sequencing but also advances our understanding of ecological traits of these global microbiomes.

Towards more accurate microbial source tracking via non-negative matrix factorization (NMF)

MOTIVATION

The microbiome of a sampled habitat often consists of microbial communities from various sources, including potential contaminants. Microbial source tracking (MST) can be used to discern the contribution of each source to the observed microbiome data, thus enabling the identification and tracking of microbial communities within a sample. Therefore, MST has various applications, from monitoring microbial contamination in clinical labs to tracing the source of pollution in environmental samples. Despite promising results in MST development, there is still room for improvement, particularly for applications where precise quantification of each source's contribution is critical.

RESULTS

In this study, we introduce a novel tool called SourceID-NMF towards more precise microbial source tracking. SourceID-NMF utilizes a non-negative matrix factorization (NMF) algorithm to trace the microbial sources contributing to a target sample. By leveraging the taxa abundance in both available sources and the target sample, SourceID-NMF estimates the proportion of available sources present in the target sample. To evaluate the performance of SourceID-NMF, we conducted a series of benchmarking experiments using simulated and real data. The simulated experiments mimic realistic yet challenging scenarios for identifying highly similar sources, irrelevant sources, unknown sources, low abundance sources, and noise sources. The results demonstrate the superior accuracy of SourceID-NMF over existing methods. Particularly, SourceID-NMF accurately estimated the proportion of irrelevant and unknown sources while other tools either over- or under-estimated them. In addition, the noise sources experiment also demonstrated the robustness of SourceID-NMF for MST.

AVAILABILITY AND IMPLEMENTATION

SourceID-NMF is available online at https://github.com/ZiyiHuang0708/SourceID-NMF.

MiDAS 5: Global diversity of bacteria and archaea in anaerobic digesters

Anaerobic digestion of organic waste into methane and carbon dioxide (biogas) is carried out by complex microbial communities. Here, we use full-length 16S rRNA gene sequencing of 285 full-scale anaerobic digesters (ADs) to expand our knowledge about diversity and function of the bacteria and archaea in ADs worldwide. The sequences are processed into full-length 16S rRNA amplicon sequence variants (FL-ASVs) and are used to expand the MiDAS 4 database for bacteria and archaea in wastewater treatment systems, creating MiDAS 5. The expansion of the MiDAS database increases the coverage for bacteria and archaea in ADs worldwide, leading to improved genus- and species-level classification. Using MiDAS 5, we carry out an amplicon-based, global-scale microbial community profiling of the sampled ADs using three common sets of primers targeting different regions of the 16S rRNA gene in bacteria and/or archaea. We reveal how environmental conditions and biogeography shape the AD microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 692 genera and 1013 species. These represent 84-99% and 18-61% of the accumulated read abundance, respectively, across samples depending on the amplicon primers used. Finally, we examine the global diversity of functional groups with known importance for the anaerobic digestion process.

Microbial co-occurrence network demonstrates spatial and climatic trends for global soil diversity

Despite recent research efforts to explore the co-occurrence patterns of diverse microbes within soil microbial communities, a substantial knowledge-gap persists regarding global climate influences on soil microbiota behaviour. Comprehending co-occurrence patterns within distinct geoclimatic groups is pivotal for unravelling the ecological structure of microbial communities, that are crucial for preserving ecosystem functions and services. Our study addresses this gap by examining global climatic patterns of microbial diversity. Using data from the Earth Microbiome Project, we analyse a meta-community co-occurrence network for bacterial communities. This method unveils substantial shifts in topological features, highlighting regional and climatic trends. Arid, Polar, and Tropical zones show lower diversity but maintain denser networks, whereas Temperate and Cold zones display higher diversity alongside more modular networks. Furthermore, it identifies significant co-occurrence patterns across diverse climatic regions. Central taxa associated with different climates are pinpointed, highlighting climate's pivotal role in community structure. In conclusion, our study identifies significant correlations between microbial interactions in diverse climatic regions, contributing valuable insights into the intricate dynamics of soil microbiota.

Deep learning for predicting 16S rRNA gene copy number

Culture-independent 16S rRNA gene metabarcoding is a commonly used method for microbiome profiling. To achieve more quantitative cell fraction estimates, it is important to account for the 16S rRNA gene copy number (hereafter 16S GCN) of different community members. Currently, there are several bioinformatic tools available to estimate the 16S GCN values, either based on taxonomy assignment or phylogeny. Here we present a novel approach ANNA16, Artificial Neural Network Approximator for 16S rRNA gene copy number, a deep learning-based method that estimates the 16S GCN values directly from the 16S gene sequence strings. Based on 27,579 16S rRNA gene sequences and gene copy number data from the rrnDB database, we show that ANNA16 outperforms the commonly used 16S GCN prediction algorithms. Interestingly, Shapley Additive exPlanations (SHAP) shows that ANNA16 can identify unexpected informative positions in 16S rRNA gene sequences without any prior phylogenetic knowledge, which suggests potential applications beyond 16S GCN prediction.

Host-bacteria interactions: ecological and evolutionary insights from ancient, professional endosymbionts

Interactions between eukaryotic hosts and their bacterial symbionts drive key ecological and evolutionary processes, from regulating ecosystems to the evolution of complex molecular machines and processes. Over time, endosymbionts generally evolve reduced genomes, and their relationship with their host tends to stabilize. However, host-bacteria relationships may be heavily influenced by environmental changes. Here, we review these effects on one of the most ancient and diverse endosymbiotic groups, formed by-among others-Legionellales, Francisellaceae, and Piscirickettsiaceae. This group is referred to as Deep-branching Intracellular Gammaproteobacteria (DIG), whose last common ancestor presumably emerged about 2 Ga ago. We show that DIGs are globally distributed, but generally at very low abundance, and are mainly identified in aquatic biomes. Most DIGs harbour a type IVB secretion system, critical for host-adaptation, but its structure and composition vary. Finally, we review the different types of microbial interactions that can occur in diverse environments, with direct or indirect effects on DIG populations. The increased use of omics technologies on environmental samples will allow a better understanding of host-bacterial interactions and help unravel the definition of DIGs as a group from an ecological, molecular, and evolutionary perspective.

An optimal combined slow-release nitrogen fertilizer and urea can enhance the decomposition rate of straw and the yield of maize by improving soil bacterial community and structure under full straw returning system

Under a full straw returning system, the relationship between soil bacterial community diversity and straw decomposition, yield, and the combined application of slow-release nitrogen and urea remains unclear. To evaluate these effects and provide an effective strategy for sustainable agricultural production, a 2-year field positioning trial was conducted using maize as the research object. Six experimental treatments were set up: straw returning + no nitrogen fertilizer (S1N0), straw returning + slow-release nitrogen fertilizer:urea = 0:100% (S1N1), straw returning + slow-release nitrogen fertilizer:urea = 30%:70% (S1N2), straw returning + slow-release nitrogen fertilizer:urea = 60%:40% (S1N3), straw returning + slow-release nitrogen fertilizer:urea = 90%:10% (S1N4), and straw removal + slow-release nitrogen fertilizer:urea = 30%:70% (S0N2). Significant differences (p < 0.05) were observed between treatments for Proteobacteria, Acidobacteriota, Myxococcota, and Actinobacteriota at the jointing stage; Proteobacteria, Acidobacteriota, Myxococcota, Bacteroidota, and Gemmatimonadota at the tasseling stage; and Bacteroidota, Firmicutes, Myxococcota, Methylomirabilota, and Proteobacteria at the maturity stage. The alpha diversity analysis of the soil bacterial community showed that the number of operational taxonomic units (OTUs) and the Chao1 index were higher in S1N2, S1N3, and S1N4 compared with S0N2 at each growth stage. Additionally, the alpha diversity measures were higher in S1N3 and S1N4 compared with S1N2. The beta diversity analysis of the soil bacterial community showed that the bacterial communities in S1N3 and S1N4 were more similar or closely clustered together, while S0N2 was further from all treatments across the three growth stages. The cumulative straw decomposition rate was tested for each treatment, and data showed that S1N3 (90.58%) had the highest decomposition rate. At the phylum level, straw decomposition was positively correlated with Proteobacteria, Actinobacteriota, Myxococcota, and Bacteroidota but significantly negatively correlated with Acidobacteriota. PICRUSt2 function prediction results show that the relative abundance of bacteria in soil samples from each treatment differed significantly. The maize yield of S1N3 was 15597.85 ± 1477.17 kg/hm2, which was 12.80 and 4.18% higher than that of S1N1 and S0N2, respectively. In conclusion, a combination of slow-release nitrogen fertilizer and urea can enhance the straw decomposition rate and maize yield by improving the soil bacterial community and structure within a full straw returning system.

Genomic fingerprints of the world's soil ecosystems

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

Short-term dietary fiber interventions produce consistent gut microbiome responses across studies

The composition of the human gut microbiome varies tremendously among individuals, making the effects of dietary or treatment interventions difficult to detect and characterize. The consumption of fiber is important for gut health, yet the specific effects of increased fiber intake on the gut microbiome vary across studies. The variation in study outcomes might be due to inter-individual (or inter-population) variation or to the details of the interventions including the types of fiber, length of study, size of cohort, and molecular approaches. Thus, to identify generally (on average) consistent fiber-induced responses in the gut microbiome of healthy individuals, we re-analyzed 16S rRNA sequencing data from 21 dietary fiber interventions from 12 human studies, which included 2,564 fecal samples from 538 subjects across all interventions. Short-term increases in dietary fiber consumption resulted in highly consistent gut bacterial community responses across studies. Increased fiber consumption explained an average of 1.5% of compositional variation (vs 82% of variation attributed to the individual), reduced alpha-diversity, and resulted in phylogenetically conserved responses in relative abundances among bacterial taxa. Additionally, we identified bacterial clades, at approximately the genus level, that were highly consistent in their response (on average, increasing or decreasing in their relative abundance) to dietary fiber interventions across the studies.

IMPORTANCE

Our study is an example of the power of synthesizing and reanalyzing 16S rRNA microbiome data from many intervention studies. Despite high inter-individual variation of the composition of the human gut microbiome, dietary fiber interventions cause a consistent response both in the degree of change and the particular taxa that respond to increased fiber.

The microgeo: an R package rapidly displays the biogeography of soil microbial community traits on maps

Many R packages provide statistical approaches for elucidating the diversity of soil microbes, yet they still struggle to visualize microbial traits on a geographical map. This creates challenges in interpreting microbial biogeography on a regional scale, especially when the spatial scale is large or the distribution of sampling sites is uneven. Here, we developed a lightweight, flexible, and user-friendly R package called microgeo. This package integrates many functions involved in reading, manipulating, and visualizing geographical boundary data; downloading spatial datasets; and calculating microbial traits and rendering them onto a geographical map using grid-based visualization, spatial interpolation, or machine learning. Using this R package, users can visualize any trait calculated by microgeo or other tools on a map and can analyze microbiome data in conjunction with metadata derived from a geographical map. In contrast to other R packages that statistically analyze microbiome data, microgeo provides more-intuitive approaches in illustrating the biogeography of soil microbes on a large geographical scale, serving as an important supplement to statistically driven comparisons and facilitating the biogeographic analysis of publicly accessible microbiome data at a large spatial scale in a more convenient and efficient manner. The microgeo R package can be installed from the Gitee (https://gitee.com/bioape/microgeo) and GitHub (https://github.com/ChaonanLi/microgeo) repositories. Detailed tutorials for the microgeo R package are available at https://chaonanli.github.io/microgeo.

Growth Stage-Dependent Variation in Soil Quality and Microbial Diversity of Ancient Gleditsia sinensis

The environment monitoring of forest is vital for the ecosystem sustainable management, especially soil quality. Ancient Gleditsia sinensis is one of the most distributed ancient trees in Shaanxi. Comprehensive soil evaluate is important for the ancient tree protection. In this study, we selected the most distributed ancient tree Gleditsia sinensis and immature tree to compare the effect of growth stage to soil quality and soil bacteria. Most ancient tree soil nutrients were in good condition compared with immature tree. The bacterial community were composed with Proteobacteria (27.55%), Acidobacteriota (16.82%), Actinobacteriota (15.77%), Gemmatimonadota (6.82%), Crenarchaeota (4.61%), Bacteroidota (4.41%), Firmicutes (4.32%), Chloroflexi (4.28%), Planctomycetota (3.24%) and Verrucomicrobiota (3.04%). The level 2 ancient tree (300-400 years old) was different in bacterial community diversity. SOC and STN were important to level 2 (300-400 years old Gleditsia sinensis), and other levels were opposite. Our results suggested that the ancient tree management should not be lumped together.

Environmental and structural factors associated with bacterial diversity in household dust across the Arizona-Sonora border

We previously reported that asthma prevalence was higher in the United States (US) compared to Mexico (MX) (25.8% vs. 8.4%). This investigation assessed differences in microbial dust composition in relation to demographic and housing characteristics on both sides of the US-MX Border. Forty homes were recruited in the US and MX. Home visits collected floor dust and documented occupants' demographics, asthma prevalence, housing structure, and use characteristics. US households were more likely to have inhabitants who reported asthma when compared with MX households (30% vs. 5%) and had significantly different flooring types. The percentage of households on paved roads, with flushing toilets, with piped water and with air conditioning was higher in the US, while dust load was higher in MX. Significant differences exist between countries in the microbial composition of the floor dust. Dust from Mexican homes was enriched with Alishewanella, Paracoccus, Rheinheimera genera and Intrasporangiaceae family. A predictive metagenomics analysis identified 68 significantly differentially abundant functional pathways between US and MX. This study documented multiple structural, environmental, and demographic differences between homes in the US and MX that may contribute to significantly different microbial composition of dust observed in these two countries.

Analysis of microbial dynamics in the soybean root-associated environments from community to single-cell levels

Plant root-associated environments such as the rhizosphere, rhizoplane, and endosphere, are notably different from non-root-associated soil environments. However, the microbial dynamics in these spatially divided compartments remain unexplored. In this study, we propose a combinational analysis of single-cell genomics with 16S rRNA gene sequencing. This method enabled us to understand the entire soil microbiome and individual root-associated microorganisms. We applied this method to soybean microbiomes and revealed that their composition was different between the rhizoplane and rhizosphere in the early growth stages, but became more similar as growth progressed. In addition, a total of 610 medium- to high-quality single-amplified genomes (SAGs) were acquired, including plant growth-promoting rhizobacteria (PGPR) candidates while genomes with high GC content tended to be missed by SAGs. The whole-genome analyses of the SAGs suggested that rhizoplane-enriched Flavobacterium solubilizes organophosphate actively and Bacillus colonizes roots more efficiently. Single-cell genomics, together with 16S rRNA gene sequencing, enabled us to connect microbial taxonomy and function, and assess microorganisms at a strain resolution even in the complex soil microbiome.

Nanopore-Enabled Microbiome Analysis: Investigating Environmental and Host-Associated Samples in Rainbow Trout Aquaculture

Microbiome sequencing is at the forefront of health management development, and as such, it is becoming of great interest to monitor the microbiome in the aquaculture industry as well. Oxford Nanopore Technologies (ONT) platforms are gaining popularity to study microbial communities, enabling faster sequencing, extended read length, and therefore, improved taxonomic resolution. Despite this, there is a lack of clear guidelines to perform a metabarcoding study, especially when dealing with samples from non-mammalian species, such as aquaculture-related samples. In this article, we provide general guidelines for sampling, nucleic acid extraction, and ONT-based library preparation for both environmental (water, sediment) and host-associated (gill or skin mucus, skin, gut content, or gut mucosa) microbiome analysis. Our procedures focus specifically on rainbow trout (Oncorhynchus mykiss) reared in experimental facilities. However, these protocols can also be transferred to alternative types of samples, such as environmental DNA (eDNA) monitoring from alternative water sources, or to different fish species. The additional challenge posed by the low biomass and limited bacterial diversity inherent in fish-associated microbiomes is addressed through the implementation of troubleshooting solutions. Furthermore, we describe a bioinformatic pipeline starting from raw reads and leading to taxonomic abundance tables using currently available tools and software. Finally, we provide a set of specific guidelines and considerations related to the strategic planning of a microbiome study within the context of aquaculture. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Environmental sample collection Basic Protocol 2: Host-associated sample collection Alternate Protocol: Host-associated sample collection: Alternative sample types Basic Protocol 3: Sample pre-treatment and nucleic acid extraction Basic Protocol 4: Quality control and preparation for 16S rRNA gene sequencing Support Protocol 1: Assessment of inhibition by quantitative PCR Support Protocol 2: Bioinformatic analysis from raw files to taxonomic abundance tables.

Comparative analysis of gut microbiome of mangrove brachyuran crabs revealed patterns of phylosymbiosis and codiversification

The acquisition of microbial symbionts enables animals to rapidly adapt to and exploit novel ecological niches, thus significantly enhancing the evolutionary fitness and success of their hosts. However, the dynamics of host-microbe interactions and their evolutionary implications remain largely underexplored in marine invertebrates. Crabs of the family Sesarmidae (Crustacea: Brachyura) are dominant inhabitants of mangrove forests and are considered keystone species there. Their rapid diversification, particularly after adopting a plant-feeding lifestyle, is believed to have been facilitated by symbiotic gut microbes, enabling successful colonization of intertidal and terrestrial environments. To investigate the patterns and mechanisms shaping the microbial communities and the role of microbes in the evolution of Sesarmidae, we characterized and compared the gut microbiome compositions across 43 crab species from Sesarmidae and other mangrove-associated families using 16S metabarcoding. We found that the gut microbiome assemblages in crabs are primarily determined by host identity, with a secondary influence from environmental factors such as microhabitat and sampling location, and to a lesser extent influenced by biological factors such as sex and gut region. While patterns of phylosymbiosis (i.e. when microbial community relationships recapitulate the phylogeny of their hosts) were consistently observed in all beta-diversity metrics analysed, the strength of phylosymbiosis varied across crab families. This suggests that the bacterial assemblages in each family were differentially shaped by different degrees of host filtering and/or other evolutionary processes. Notably, Sesarmidae displayed signals of cophylogeny with its core gut bacterial genera, which likely play crucial functional roles in their hosts by providing lignocellulolytic enzymes, essential amino acids, and fatty acids supplementation. Our results support the hypothesis of microbial contribution to herbivory and terrestrialization in mangrove crabs, highlighting the tight association and codiversification of the crab holobiont.

GROND: a quality-checked and publicly available database of full-length 16S-ITS-23S rRNA operon sequences

Sequence comparison of 16S rRNA PCR amplicons is an established approach to taxonomically identify bacterial isolates and profile complex microbial communities. One potential application of recent advances in long-read sequencing technologies is to sequence entire rRNA operons and capture significantly more phylogenetic information compared to sequencing of the 16S rRNA (or regions thereof) alone, with the potential to increase the proportion of amplicons that can be reliably classified to lower taxonomic ranks. Here we describe GROND (Genome-derived Ribosomal Operon Database), a publicly available database of quality-checked 16S-ITS-23S rRNA operons, accompanied by multiple taxonomic classifications. GROND will aid researchers in analysis of their data and act as a standardised database to allow comparison of results between studies.