Decades of research have made clear that host-associated microbiomes touch all facets of health. However, effective therapies that target the microbiome have been elusive given its inherent complexity. Here, we experimentally examined diet-microbe-host interactions through a complex systems framework, centered on dietary oxalate. Using multiple, independent molecular, rodent, and in vitro experimental models, we found that microbiome composition influenced multiple oxalate-microbe-host interfaces. Importantly, the administration of the oxalate-degrading specialist, Oxalobacter formigenes, was only effective against a poor oxalate-degrading microbiota background and gives critical new insights into why clinical intervention trials with this species exhibit variable outcomes. Data suggest that, while heterogeneity in the microbiome impacts multiple diet-host-microbe interfaces, metabolic redundancy among diverse microorganisms in specific diet-microbe axes is a critical variable that may impact the efficacy of bacteriotherapies, which can help guide patient and probiotic selection criteria in probiotic clinical trials.

Fatty acids in pork are involved in cellular physiological functions and related to meat nutrition, tenderness, and flavor. Increasing evidences have suggested that short-chain fatty acids produced by the gut microbiota may affect host metabolism and energy utilization. However, the association between gut microbiota and long-chain fatty acids (LCFAs) in pork has been largely unknown. In this study, the microbial compositions of 243 cecum content samples from Erhualian pigs and 235 fecal samples from Bamaxiang pigs were determined by high throughput 16S rRNA gene sequencing. The contents of 12 LCFAs in longissimus dorsi (LD) muscle were also determined for all experimental pigs of both pig populations. We systematically evaluated the contribution of gut microbiota to the variations of muscle fatty acid contents from the α-diversity of gut microbiota, co-abundance groups (CAGs) of Amplicon Sequence Variants (ASVs), and fatty acid-associated bacterial taxa. We identified hundred ASVs and > 40 bacterial taxa that were significantly associated with muscle fatty acid contents in two pig populations. Different numbers and bacterial taxa associated with the content of specific LCFAs in muscle were detected between cecum luminal content and fecal samples, suggesting the heterogeneity of the specific LCFA-associated bacterial taxa between two gut locations. We uncovered some interesting associations between bacterial taxa and muscle fatty acid contents. The strongest association was observed between the ASV annotated to Akkermansia and the n-6/n-3 polyunsaturated fatty acid ratio (p = 6.45E-04, Z = -9.65). The gut microbiota could explain 1.47-4.62% variation of muscle contents of twelve fatty acids. The functional prediction analysis identified that the KEGG pathways related to the metabolisms of carbohydrate and lipids, and to fat digestion and absorption were positively associated with the contents of muscle fatty acids. However, adipocytokine signaling pathway and thermogenesis were negatively associated with muscle fatty acid contents. The results from this study provided the basic knowledge for improving the muscle fatty acid contents by regulating the gut microbiome.

Microbialites have the potential to record environmental changes and act as biosignatures of past geochemical conditions. As such, they could be used as indicators to decipher ancient rock records. Modern microbialites are primarily found in environments where competitors and destructors are absent or where biogeochemical conditions favor their continuous formation. Many previous studies have essentially focused on the role of photosynthetic microbes in controlling pH and carbonate speciation and potentially overlooked alternative non-photosynthetic pathways of carbonate precipitation. Given that microbial activity induces subtle geochemical changes, microbially induced carbonate precipitation (MICP) can involve several mechanisms, from extracellular polymeric substances (EPS), sulfate reduction, anaerobic oxidation of methane, to nitrogen cycling processes, such as ammonification, ureolysis, and denitrification. Moreover, the peritidal zone where temperate microbialites are mostly found today, is under the influence of both freshwater and seawater, arguing for successive biogeochemical processes leading to mineral saturation, and questioning interpretations of fossil records. This study investigates microbialites in three tide pools from the peritidal zone of Fongchueisha, Hengchun, Taiwan, to address the influence of salinity on microbial community composition and carbonate precipitation mechanisms. Microbial samples were collected across varying salinity gradients at multiple time points and analyzed using next-generation sequencing (NGS) of bacterial 16S and eukaryotic 18S rRNA genes. Our results indicate that dominant bacterial groups, including Cyanobacteria and Alphaproteobacteria, were largely influenced by salinity variations, albeit pH exhibited stronger correlation with community composition. Combining our results on geochemistry and taxonomic diversity over time, we inferred a shift in the trophic mode under high salinity conditions, during which the use of urea and amino acids as a nitrogen source outcompetes diazotrophy, ureolysis and ammonification of amino acids reinforcing carbonate precipitation dynamics by triggering an increase in both pH and dissolved inorganic carbon.

Modern agriculture faces the challenge of optimizing fertilization practices while maintaining soil resilience and microbial diversity, both critical for sustainable crop production. We evaluated the effects of multiple fertilization strategies on soil microbial communities and plant performance, comparing conventional methods (urea-based and phosphorus fertilizers applied manually or via drone-assisted precision delivery) with biofertilization using a synthetic microbial consortium (SynCom) derived from teosinte-associated microbes. This SynCom consisted of seven bacterial strains: Serratia nematodiphila EDR2, Klebsiella variicola EChLG19, Bacillus thuringiensis EML22, Pantoea agglomerans EMH25, Bacillus thuringiensis EBG39, Serratia marcescens EPLG52, and Bacillus tropicus EPP72. High-throughput sequencing revealed significant shifts in bacterial and fungal communities across treatments. Untreated soils showed limited diversity, dominated by Enterobacteriaceae (>70%). Conventional fertilization gradually reduced Enterobacteriaceae while increasing Pseudomonas and Lysinibacillus populations. Drone-assisted conventional fertilization notably enhanced Acinetobacter and Rhizobiales growth. Biofertilization treatments produced the most pronounced shifts, reducing Enterobacteriaceae below 50% while significantly increasing beneficial taxa like Bacillus, Pantoea, and Serratia. Network analysis demonstrated that microbial interaction complexity increased across treatments, with Bacillus emerging as a keystone species. Drone-assisted biofertilization fostered particularly intricate microbial networks, enhancing synergistic relationships involved in nutrient cycling and biocontrol, though maintaining the stability of these complex interactions requires careful monitoring. Our findings provide key insights into how precision biofertilization with teosinte-derived microbial consortia can sustainably reshape the maize microbiome, improving crop performance and soil resilience.

Plant-associated microorganisms can help crops to alleviate stress and increase the resilience of agricultural ecosystems to climate change. However, we still lack knowledge on the dynamics of soil and plant microbiomes and their response to changing conditions. This information is essential for the development of microbiome-based solutions to improve crop resilience to stressors associated with climate change. In this work, we explored: (i) the conformation of the bacterial and fungal assemblages of different soil and plant compartments (bulk soil, rhizosphere, roots, leaves and grains) along the crop cycle of maize in an open field trial; and (ii) the effect of water restriction on the maize microbiome, comparing optimal irrigation with a 30% reduction of water supply. Our results show a dynamic compartment-driven recruitment of microorganisms with contrasting patterns for bacteria and fungi that were intensified towards the end of the plant cycle. Roots showed the most differentiated bacterial assemblage while fungi conformed a very distinct community in the leaves, suggesting a relevant contribution of aerial fungal propagules to the microbiome of this plant organ. Regarding the grain, bacterial communities looked closer to those in the leaves, while fungal communities were more like those in the root. Despite the reductions in plant growth and yield, the microbiome of limited-watered plants did not show severe alterations. Still, significant impacts were observed within compartments, being fungi more responsive to limited watering than bacteria, with hallmark fungal ASVs for each compartment and irrigation regime. Network analysis suggests that bacteria and fungi may play different roles in the shifts observed under water limitation. Our study highlights the importance of conducting multikingdom analyses for a holistic understanding of the dynamics and evolution of the microbial assemblages in the whole plant and their roles in plant response to environmental stressors.

Bacterial vaginosis (BV) is a type of vaginal inflammation caused by bacterial overgrowth, upsetting the healthy microbiome of the vagina. Existing clinical testing for BV is primarily based upon physical and microscopic examination of vaginal secretions. Modern PCR-based clinical tests target panels of BV-associated microbes, such as the Labcorp NuSwab test that targets Atopobium (Fannyhessea) vaginae, Megasphaera-1, and Bacterial Vaginosis Associated Bacterium (BVAB)-2. Remnant clinician-collected NuSwab vaginal swabs underwent DNA extraction and 16S V3-V4 rRNA gene sequencing to profile microbes in addition to those included in the Labcorp NuSwab test. Community state types (CSTs) were determined using the most abundant taxon detected in each sample. PCR results for NuSwab panel microbial targets were compared against the corresponding microbiome profiles. Metabolic pathway abundances were characterized via metagenomic prediction from amplicon sequence variants (ASVs). 16S V3-V4 rRNA gene sequencing of 75 remnant vaginal swabs yielded 492 unique 16S V3-V4 ASVs, identifying 83 unique genera. NuSwab microbe quantification was strongly concordant with quantification by sequencing (P < 0.01). Samples in CST-I (18 of 18, 100%), CST-II (three of three, 100%), CST-III (15 of 17, 88%), and CST-V (one of one, 100%) were largely categorized as BV-negative via the NuSwab panel, while most CST-IV samples (28 of 36, 78%) were BV-positive or BV-indeterminate. BV-associated microbial and predicted metabolic signatures were shared across multiple CSTs. These findings highlight robust sequencing-based quantification of Labcorp NuSwab BV microbes, accurate discrimination of vaginal microbiome CSTs dominated by distinct Lactobacilli, and expanded the identification of BV-associated bacterial and metabolic biomarkers.IMPORTANCEBacterial vaginosis (BV) poses a significant health burden for women during reproductive years and onward. Current BV diagnostics rely on either panels of select microbes or on physical and microscopic evaluations by technicians. Here, we sequenced the microbiome profiles of samples previously diagnosed by the Labcorp NuSwab test to better understand disruptions to the vaginal microbiome during BV. We show that microbial sequencing can faithfully reproduce targeted PCR diagnostic results and can improve our knowledge of healthy and BV-associated microbial and metabolic biomarkers. This work highlights a robust, agnostic BV classification scheme with potential for future development of sequencing-based BV diagnostic tools.

Postlarval shrimp frequently face threats from acute hepatopancreatic necrosis disease (AHPND). Although AHPND affects both postlarval and adult shrimp, abiotic and biotic factors are distinct between life stages, such as rearing water nutrient levels and host life stage-dependent microbiota. The response of postlarvae-associated microbiota to AHPND, however, remains largely unexplored compared with its effects on juvenile and adult shrimp. To address this knowledge gap, a comparative analysis of postlarvae-associated microbiota and the ecological processes underlying AHPND progression was performed by sequencing the bacterial V3-V4 hypervariable region of the 16S rRNA gene. AHPND infection was validated by high copies of pirAB genes (Toxin 1) in diseased shrimp hepatopancreas. Advanced AHPND significantly altered the structure of the postlarvae-associated microbiota, with significant enrichment of Bacilli and Bdellovibrionia species in healthy larvae compared with matched AHPND-infected cohorts, although gut microbiota recovery was observed at the late disease stage, corresponding with the cessation of postlarval mortality. AHPND infection explained 11.0% (p < 0.001) of the variance in community structures, whereas postlarvae days post hatching also significantly influenced bacterial communities (7.1% variance, p < 0.001). AHPND-infected shrimp exhibited reduced homogeneous selection and increased dispersal limitation and drift governing their microbiota. These changes were primarily driven by specific microbial lineages, including enriched Bin36 Rhodobacteraceae and Bin11 Flavobacteriaceae, and suppressed Bin63 Vibrio and Bin9 Bacillus in AHPND-infected shrimp. After excluding shrimp age effect, 13 AHPND-discriminatory taxa were identified, accurately distinguishing infected shrimp from healthy individuals with 100% precision. Furthermore, AHPND outbreak weakened the network complexity and stability, which was driven by the suppressed keystone taxa that were positively associated with network robustness. Collectively, our findings deepen the understanding of the inextricable interplay between postlarval shrimp health, microbiota dynamics, and survival, as well as the underlying ecological mechanisms over AHPND progression.

Glacier surface habitats are dynamic ecosystems that respond to local climatic and thermal changes, although the assembly mechanisms of microbial communities in these environments remain unclear. This study examined microbial communities on the surface of Baishui Glacier No. 1 across the accumulation, the intense melt, and the late melt periods. The absolute abundance of Cyanobacteria increased significantly, becoming the most abundant phylum by the end of the melt period. Cyanobacteria were strongly associated with other local microorganisms, especially in community structure, community assembly, and co-occurrence networks. The correlations between Cyanobacteria and other microorganisms shifted from predominantly mutualistic interactions, to being predominantly competitive interactions, and finally to mutualistic interactions with a portion of the community. Additionally, Cyanobacteria abundance positively correlated with nitrogen metabolism multifunctionality in other microorganisms, indicating a potential link between Cyanobacteria and nitrogen cycling. These findings provide new insights into microbial community dynamics and survival strategies on glacier surfaces.

The association between the human brain and gut microbiota, known as the "brain-gut-microbiota axis", is involved in the neuropathological mechanisms of schizophrenia (SZ); however, its association patterns and correlations with symptom severity and neurocognition are still largely unknown. In this study, 43 SZ patients and 55 normal controls (NCs) were included, and resting-state functional magnetic resonance imaging (rs-fMRI) and gut microbiota data were acquired for each participant. First, the brain features of brain images and functional brain networks were computed from rs-fMRI data; the gut features of gut microbiota abundance and the gut microbiota network were computed from gut microbiota data. Second, we propose a novel methodology to construct an individual brain-gut microbiota network (BGMN) for each participant by combining the brain and gut features via multiple strategies. Third, discriminative models between SZ patients and NCs were built using the connectivity matrices of the BGMN as input features. Moreover, the correlations between the most discriminative features and the scores of symptom severity and neurocognition were analyzed in SZ patients. The results showed that the best discriminative model between SZ patients and NCs was achieved using the connectivity matrices of the BGMN when all the brain and gut features were integrated, with an accuracy of 0.90 and an area under the curve value of 0.97. The most discriminative features were related primarily to the genera Faecalibacterium and Collinsella, in which the genus Faecalibacterium was linked to the visual system and subcortical cortices and the genus Collinsella was linked to the default network and subcortical cortices. Furthermore, parts of the most discriminative features were significantly correlated with the scores of neurocognition in the SZ patients. The methodology for constructing individual BGMNs proposed in this study can help us reveal the associations between the brain and gut microbiota and understand the neuropathology of SZ.

The plant rhizosphere microbiome plays a crucial role in plant growth and health. Within this microbiome, bacteria dominate, exhibiting traits that benefit plants, such as facilitating nutrient acquisition, fixing nitrogen, controlling pathogens, and promoting root growth. This study focuses on designing synthetic bacterial consortia using key bacterial strains which have been mapped and then isolated from the sorghum rhizosphere microbiome. A large set of samples of the rhizosphere bacteriome of Sorghum bicolor was generated and analyzed across various genotypes and geographical locations. We assessed the taxonomic composition and structure of the sorghum root-associated bacterial community identifying the most prevalent and keystone taxa. A set of 321 bacterial strains was then isolated, and three multi-strain consortia were designed making use of the bacteriome data generated using culture independent methodology. Subsequently, co-existence and plant-growth promoting ability of three bacterial consortia were tested both in vitro and in planta. Consortia 3 promoted plant growth in growth-chamber conditions while Consortia 1 and 2 performed better in field-plot experiments. Despite these differences, bacterial community profiling confirmed the colonization of the inoculated consortia in the sorghum rhizosphere without significant alterations to the overall bacterial community compared to the non inoculated ones. In summary, this study focused on a method, using root bacteriome data, to design and test bacterial consortia for plant beneficial effects with the aim of translating microbiome knowledge into applications.

The prevalence of noncommunicable inflammatory disease is increasing in modern urban societies, posing significant challenges to public health. Novel prevention and therapeutic strategies are needed to effectively deal with this issue. One promising approach is leveraging microorganisms such as Mycobacterium vaccae ATCC 15483, known for its anti-inflammatory, immunoregulatory, and stress-resilience properties. This study aimed to assess whether weekly subcutaneous administrations of a whole-cell, heat-killed preparation of M. vaccae ATCC 15483 (eleven injections initiated one week before the onset of the diet intervention), relative to vehicle injections, in adolescent male C57BL/6N mice can mitigate inflammation associated with Western-style diet-induced obesity, which is considered a risk factor for a number of metabolic and inflammatory diseases. Our results show that treatment with M. vaccae ATCC 15483 prevented Western-style diet-induced excessive weight gain, visceral adipose tissue accumulation, and elevated plasma leptin concentrations. The Western-style diet, relative to a control diet condition, decreased alpha diversity and altered the community composition of the gut microbiome, increasing the Bacillota to Bacteroidota ratio (formerly referred to as the Firmicutes to Bacteroidetes ratio). Despite the finding that M. vaccae ATCC 15483 prevented Western-style diet-induced excessive weight gain, visceral adipose tissue accumulation, and elevated plasma leptin concentrations, it had no effect on the diversity or community composition of the gut microbiome, suggesting that it acts downstream of the gut microbiome to alter immunometabolic signaling. M. vaccae ATCC 15483 reduced baseline levels of biomarkers of hippocampal neuroinflammation and microglial priming, such as Nfkbia and Nlrp3, and notably decreased anxiety-like defensive behavioral responses. The current findings provide compelling evidence supporting the potential for M. vaccae ATCC 15483 as a promising intervention for prevention or treatment of adverse immunometabolic outcomes linked to the consumption of a Western-style diet and the associated dysbiosis of the gut microbiome.

The factors shaping human microbiome variation are a major focus of biomedical research. While other fields have used large sequencing compendia to extract insights requiring otherwise impractical sample sizes, the microbiome field has lacked a comparably sized resource for the 16S rRNA gene amplicon sequencing commonly used to quantify microbiome composition. To address this gap, we processed 168,464 publicly available human gut microbiome samples with a uniform pipeline. We use this compendium to evaluate geographic and technical effects on microbiome variation. We find that regions such as Central and Southern Asia differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America and that composition alone can be used to predict a sample's region of origin. We also find strong associations between microbiome variation and technical factors such as primers and DNA extraction. We anticipate this growing work, the Human Microbiome Compendium, will enable advanced applied and methodological research.

The vaginal microbiome is critical for the reproductive health of women, yet the differential impacts exerted by the host and by ambient environmental variables on the vaginal microbiome remain largely unknown. Here, we conducted a comprehensive cross-sectional study of the relationships between the vaginal microbiome and 81 matched host and environmental variables across 6755 Chinese women. By 16S rRNA sequencing, we identified four core vaginal microbiota with a prevalence of over 90% and a total median abundance of 98.8%. Twenty-four variables, including physiology, lifestyle behaviors, gynecologic history, social and environmental information, were found associated with the microbiome composition, of which bacterial vaginosis (BV) showed the largest effect size. Age was among the strongest explanatory variables and the vaginal microbiome dynamically succeeded with increasing age, especially with a composition turning point at the age of 45. Our mediation analyses indicated that the effects of age on the microbiome could be mediated by variables such as parity number and lifestyles. We further classified the vaginal microbiomes of the population into 13 "Vagitypes". Women with Lactobacillus iners- and Lactobacillus jensenii-dominated Vagitypes had significantly higher live birth rate than those with Vagitype dominated by Fannyhessea vaginae (53.40%, 59.09% vs 21.43%; OR [95% CI]: 3.62 [1.12-14.87], 5.39 [1.27-27.36]; P = 0.031, P = 0.021). This study provides a comprehensive overview of the associations between identified variables and the vaginal microbiome, representing an important step toward understanding of environment-microbe-host interactions.

Decades of research have made clear that host-associated microbiomes touch all facets of health. However, effective therapies that target the microbiome have been elusive given its inherent complexity. Here, we experimentally examined diet-microbe-host interactions through a complex systems framework, centered on dietary oxalate. Using multiple, independent molecular, animal, and in vitro experimental models, we found that microbiome composition influenced multiple oxalate-microbe-host interfaces. Importantly, administration of the oxalate-degrading specialist, Oxalobacter formigenes, was only effective against a poor oxalate-degrading microbiota background and gives critical new insights into why clinical intervention trials with this species exhibit variable outcomes. Data suggest that, while heterogeneity in the microbiome impacts multiple diet-host-microbe interfaces, metabolic redundancy among diverse microorganisms in specific diet-microbe axes is a critical variable that may impact the efficacy of bacteriotherapies, which can help guide patient and probiotic selection criteria in probiotic clinical trials.

The variation in fungal community composition within a single habitat space has been extensively studied in forest ecosystems. However, the spatial and temporal distribution of fungi across contiguous habitats, particularly at a local scale and in tropical regions, remains underexplored. In this study, we examined the fungal community composition across multiple habitats proximal to each other over two seasons in seven Fagaceae species in Taiwanese broadleaf forests. We tested how local spatial scale and habitat influence community assembly.

Using a metabarcoding approach, we sequenced ITS2 regions from 864 samples collected from four distinct habitats-leaves, twigs, litter, and soil. We identified 11,600 fungal amplicon sequence variants (ASVs), with community composition differing significantly between habitats proximal to each other. Generalized dissimilarity modeling (GDM) revealed that spatial distance, interacting with precipitation, was the strongest predictor of fungal turnover, particularly in the phyllosphere. Normalized Stochasticity Ratio (NST) analyses further highlighted contrasting assembly processes, with deterministic influences dominating in the phyllosphere habitat, while stochasticity prevailed in soil and litter. Random forest analysis accurately classified habitats based on ASVs' relative abundances, with strong predictors were mostly habitat-specific ASVs prevalent in soil. Misclassified samples were due to secondary contact of fungi between adjacent habitats. Co-occurrence network analysis revealed more complex and deterministic networks in leaf and twig habitats, while soil was driven by stochastic processes and contained most habitat-specific ASVs. A Cladosporium sp. emerged as a keystone species, maintaining network stability across forests.

This study reveals how local spatial variation and habitat shape distinct fungal communities in tropical forests, with deterministic processes dominating in some habitats and stochasticity playing a key role in others. We show extremely high turnover in fungal community are present over very short distances and that local fungal taxa are strong habitat predictors. These findings highlight the importance of studying coexisting habitats to gain a deeper understanding of fungal biogeography and ecosystem function.

Gut bacteria from the Enterobacteriaceae family are a major cause of opportunistic infections worldwide. Given their prevalence among healthy human gut microbiomes, interspecies interactions may play a role in modulating infection resistance. Here we uncover global ecological patterns linked to Enterobacteriaceae colonization and abundance by leveraging a large-scale dataset of 12,238 public human gut metagenomes spanning 45 countries. Machine learning analyses identified a robust gut microbiome signature associated with Enterobacteriaceae colonization status, consistent across health states and geographic locations. We classified 172 gut microbial species as co-colonizers and 135 as co-excluders, revealing a genus-wide signal of colonization resistance within Faecalibacterium and strain-specific co-colonization patterns of the underexplored Faecalimonas phoceensis. Co-exclusion is linked to functions involved in short-chain fatty acid production, iron metabolism and quorum sensing, while co-colonization is linked to greater functional diversity and metabolic resemblance to Enterobacteriaceae. Our work underscores the critical role of the intestinal environment in the colonization success of gut-associated opportunistic pathogens with implications for developing non-antibiotic therapeutic strategies.

Phosphorus (P)-deficient soils serve as crucial habitats for endangered plant species. Microbiomes play pivotal roles in soil element cycling and in determining a plant's adaptability to the environment. However, the relationship between the endangered plant, microbiome, and soil stoichiometric traits, and how it affects plant adaption to P-deficient habitats remain largely unexplored. In this study, we investigated the microbiome (bacteria and fungi) in the rhizosphere of Firmiana danxiaensis, an endangered plant species growing exclusively in P-deficient acidic soils on Mt. Danxia, South China; the non-endangered coexisting tree species Pinus massoniana was used as a reference. Our results showed that soil traits in the rhizosphere of F. danxiaensis differed significantly from that of P. massoniana, including higher soil pH, lower C:N, and higher N:P. The rhizosphere of F. danxiaensis harbors higher microbial diversity and different microbial communities from P. massoniana. Using the machine learning approach, we characterized 76 bacterial and 20 fungal phylotypes dominated in F. danxiaensis rhizosphere, most of which had strong impacts on microbial ecological network structure (they accounted for only 0.33% node numbers but linked 21.2% of the nodes in the network); specifically, Udaeobacter spp., a highly abundant (constituting 4.07% of the total bacterial community) member of Verrucomicrobiota exclusively accumulated in the rhizosphere of F. danxiaensis but not P. massoniana, demonstrated a pronounced ecological prefers toward F. danxiaensis rhizosphere habitat (high pH, low C:N and high N:P) and potential antagonistic indication. In contrast, P. massoniana rhizosphere harbored more Subgroup2 of Acidobacteria and Gammaproteobacterial N-fixer. Taken together, this study provided novel evidence that endangered plants recruited a unique microbiome characterized by Udaeobacter spp. favoring high N habitat. It contributes not only to our understanding of microbiome recruitment by plants in P-deficient acidic soils, but also underscores the importance of microbiome in the conservation and population restoration of endangered plants.

Rationale: Chronic kidney disease (CKD) is a progressively debilitating condition leading to kidney dysfunction and severe complications. While dysbiosis of the gut bacteriome has been linked to CKD, the alteration in the gut viral community and its role in CKD remain poorly understood. Methods: Here, we characterize the gut virome in CKD using metagenome-wide analyses of faecal samples from 425 patients and 290 healthy individuals. Results: CKD is associated with a remarkable shift in the gut viral profile that occurs regardless of host properties, disease stage, and underlying diseases. We identify 4,649 differentially abundant viral operational taxonomic units (vOTUs) and reveal that some CKD-enriched viruses are closely related to gut bacterial taxa such as Bacteroides, [Ruminococcus], Erysipelatoclostridium, and Enterocloster spp. In contrast, CKD-depleted viruses include more crAss-like viruses and often target Faecalibacterium, Ruminococcus, and Prevotella species. Functional annotation of the vOTUs reveals numerous viral functional signatures associated with CKD, notably a marked reduction in nicotinamide adenine dinucleotide (NAD+) synthesis capacity within the CKD-associated virome. Furthermore, most CKD viral signatures are reproducible in the gut viromes of diabetic kidney disease and several other common diseases, highlighting the considerable universality of disease-associated viromes. Conclusions: This research provides comprehensive resources and novel insights into the CKD-associated gut virome, offering valuable guidance for future mechanistic and therapeutic investigations.

The human microbiota-associated (HMA) mice model, especially the germ-free (GF)-humanized mice, has been widely used to probe the causal relationships between gut microbiota and human diseases such as type 1 diabetes (T1D). However, most studies have not clarified the extent to which the reconstruction of the human donor microbiota in recipient mice correlates with corresponding phenotypic reproducibility. In this study, we transplanted fecal microbiota from five patients with T1D and four healthy people into GF mice, and microbiota from each donor were transplanted into 10 mice. Mice with similar microbiota structure to the donor exhibited better phenotypic reproducibility. The characteristics of the microbial community assembly of donors also influenced the phenotypic reproducibility in mice, and individuals with a higher proportion of stochastic processes showed more severe disorders. Microbes enriched in patients with T1D had a stronger colonization potential in mice with impaired glucose metabolism, and microbiota functional features related to T1D were better reproduced in these mice. This indicates that assembly traits and colonization efficacy of microbiota influence phenotypic reproducibility in GF-humanized mice. Our findings provide important insights for using HMA mice models to explore links between gut microbiota and human diseases.

As ecosystems face unprecedented change and habitat loss, pursuing comprehensive and resilient habitat restoration will be integral to protecting and maintaining natural areas and the services they provide. Microbiomes offer an important avenue for improving restoration efforts as they are integral to ecosystem health and functioning. Despite microbiomes' importance, unresolved knowledge gaps hinder their inclusion in restoration efforts. Here, we address two critical gaps in understanding microbial roles in restoration-fungal microbiomes' importance in "reconstructive" restoration efforts and how management and restoration decisions interactively impact fungal communities and their cascading effects on trees. We combined field surveys, microbiome sequencing, and greenhouse experiments to determine how reconstructing an iconic landscape feature-tree islands-in the highly imperiled Everglades impacts fungal microbiomes and fungal effects on native tree species compared with their natural counterparts under different proposed hydrological management regimes. Constructed islands used in this research were built from peat soil and limestone collected from deep sloughs and levees nearby the restoration sites in 2003, providing 18 years for microbiome assembly on constructed islands. We found that while fungal microbiomes from natural and constructed tree islands exhibited similar diversity and richness, they differed significantly in community composition. These compositional differences arose mainly from changes to which fungal taxa were present on the islands rather than changes in relative abundances. Surprisingly, ~50% of fungal hub taxa (putative keystone fungi) from natural islands were missing on constructed islands, suggesting that differences in community composition of constructed island could be important for microbiome stability and function. The differences in fungal composition between natural and constructed islands had important consequences for tree growth. Specifically, these compositional differences interacted with hydrological regime (treatments simulating management strategies) to affect woody growth across the four tree species in our experiment. Taken together, our results demonstrate that reconstructing a landscape feature without consideration of microbiomes can result in diverging fungal communities that are likely to interact with management decisions leading to meaningful consequences for foundational primary producers. Our results recommend cooperation between restoration practitioners and ecologists to evaluate opportunities for active management and restoration of microbiomes during future reconstructive restoration.

Heat stress (HS) is an impactful condition in ruminants that negatively affects their physiological and rumen microbial composition. However, a fundamental understanding of metabolomic and metataxonomic mechanisms in goats under HS conditions is lacking. Here, we analyzed the rumen metabolomics, metataxonomics, and serum metabolomics of goats (n = 10, body weight: 41.08 ± 1.83 kg) under optimum temperature period (OTP) (HS-free, temperature humidity index (THI): 57.13 ± 3.98) and high temperature period (HTP) (HS-exposed, THI: 80.27 ± 1.22) conditions, to identify changes in key metabolites and the rumen microbiome induced by HS. Compared to the OTP and HTP conditions, metabolomic analysis revealed significant changes in rumen metabolites related to energy and amino acid metabolism, with HTP goats showing potential rumen metabolic biomarkers, such as butyrate, isopropanol, phenylacetate, and 2-oxoisocaproate (P < 0.001). Serum analysis revealed significant changes in energy metabolism and immune response, with HTP goats showing potential metabolic biomarkers, including acetate, betaine, glucuronate, and kynurenine (P < 0.05). Metataxonomic analysis revealed that HS affected the alpha diversity measurements, including the Chao1 estimate (P < 0.05) and evenness (P < 0.05) between OTP and HTP groups. Through the metabolic association of the rumen microbiome with the metabolome, we found that Fibrobacter and Ruminococcus were enriched in HTP and positively correlated with ruminal microbial metabolites, such as acetate. In addition, Prevotellaceae UCG-003, which was denoted as the keynote genus in the HTP, co-occurred with acetate-producing bacteria such as Quinella and Ruminococcus. Furthermore, we identified that Oscillospiraceae UCG-002, an enriched bacterial genus in HTP, showed a positive correlation with functional features, such as biotin and sulfur metabolism. Our study provided fundamental insights into how HS affected the physiology and rumen microbial compositions of goats and how both microbiome and host-dependent mechanisms contributed to these changes. These findings could potentially suggest strategies for mitigating the adverse effects of HS, including changes in the microbial population and energy metabolism in goats.

Current screening methods for esophageal squamous cell carcinoma (ESCC) face challenges such as low patient compliance and high costs. This study aimed to develop a model based on oral microbiome data for identifying ESCC. By analyzing 249 oral flora samples, we identified microbial markers associated with ESCC and constructed random forest classifiers that distinguished patients with ESCC from controls, achieving an area under the ROC curve (AUC) of 0.87. Key ESCC-associated microbial markers included Neisseria perflava and Haemophilus parainfluenzae. The classifier was validated within the cohort, attaining an AUC of 0.93. For comparison, traditional tumor markers carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCC-Ag) yielded AUCs of 0.84. Functional analysis identified pathways linked to ESCC, such as glycerol degradation and nitrate reduction. This study suggests a potential noninvasive method for detecting ESCC, offering a more accessible and accurate alternative to current screening methods.

Keystone species are thought to play a critical role in determining the structure and function of microbial communities. As they are important candidates for microbiome-targeted interventions, the identification and characterization of keystones is a pressing research goal. Both empirical as well as computational approaches to identify keystones have been proposed, and in particular correlation network analysis is frequently utilized to interrogate sequencing-based microbiome data. Here, we apply an established method for identifying putative keystone taxa in correlation networks. We develop a robust workflow for network construction and systematically evaluate the effects of taxonomic resolution on network properties and the identification of keystone taxa. We are able to identify correlation network keystone species and genera, but could not detect taxa with high keystone potential at lower taxonomic resolution. Based on the correlation patterns observed, we hypothesize that the identified putative keystone taxa have a stabilizing effect that is exerted on correlated taxa. Correlation network analysis further revealed subcommunities present in the dataset that are remarkably similar to previously described patterns. The interrogation of available metatranscriptomes also revealed distinct transcriptional states present in all putative keystone taxa. These results suggest that keystone taxa may have stabilizing properties in a subset of community members rather than global effects. The work presented here contributes to the understanding of correlation network keystone taxa and sheds light on their potential ecological significance.

The gut microbiota is crucial for human health, functioning as a complex adaptive system akin to a vital organ. To identify core health-relevant gut microbes, we followed the systems biology tenet that stable relationships signify core components. By analyzing metagenomic datasets from a high-fiber dietary intervention in type 2 diabetes and 26 case-control studies across 15 diseases, we identified a set of stably correlated genome pairs within co-abundance networks perturbed by dietary interventions and diseases. These genomes formed a "two competing guilds" (TCGs) model, with one guild specialized in fiber fermentation and butyrate production and the other characterized by virulence and antibiotic resistance. Our random forest models successfully distinguished cases from controls across multiple diseases and predicted immunotherapy outcomes through the use of these genomes. Our guild-based approach, which is genome specific, database independent, and interaction focused, identifies a core microbiome signature that serves as a holistic health indicator and a potential common target for health enhancement.

This study aimed to investigate the presence and diversity of fungal parasites in Arctic coastal microphytobenthic communities. These communities represent a key component in the functioning of Arctic trophic food webs. Fungal parasites, particularly Chytridiomycota (chytrids), play significant roles by controlling microalgal bloom events, impacting genetic diversity, modifying microbial interactions, and accelerating nutrient and energy transfer to higher trophic levels. In the context of rapid Arctic warming and increased glacier meltwater, which significantly affects these communities, we used high-throughput sequencing to explore fungal community composition. Our results show that chytrids dominate fungal communities in Arctic benthic habitats and that the overall fungal diversity is primarily influenced by the salinity gradient. Chytrid representation is positively correlated with the presence of potential benthic diatom (Surirella, Nitzschia, Navicula) and green algae (Ulvophyceae) hosts, while microscopic observations provide further evidence for the presence of active chytrid infections.

This study explores the role of the vaginal microbiota (VM) in the pathophysiology of asymptomatic bacteriuria (ASB) in a cohort of 1,553 pregnant women. Worldwide, E. coli remains the most common etiological agent of bacteriuria during pregnancy and also a major causative agent of newborn infections. A healthy VM is typically characterized by low diversity and is dominated by lactic acid-producing species, notably those from the Lactobacillus genus. Our results point to decreases in Lactobacillus spp associated with an increase of gut-microbiota-associated species from the Enterobacterales order. Escherichia coli exhibited the most pronounced increase in abundance within the VM during bacteriuria and was notably associated with ASB. Molecular typing and antimicrobial resistance characterization of 72 metagenome assembled E. coli genomes (MAGs) from these pregnant women revealed a genomic signature of extraintestinal pathogenic E. coli ("ExPEC") strains, which are involved in various extraintestinal infections such as urinary tract infections, newborn infections and bacteremia. Microbial diversity within the vaginal samples from which an E. coli MAG was obtained showed a substantial variation, primarily marked by a decrease in abundance of Lactobacillus species. Overall, our study shows how disruption in key bacterial group within the VM can disrupt its stability, potentially leading to the colonization by opportunistic pathogens.

The phenomenon in which the damage of plant diseases is suppressed by continuous cropping is defined as "suppressiveness" and the development of suppressive soils and key beneficial microorganisms have been identified through various previous studies. However, no studies have been conducted on microbial communities related to disease occurrence before the initial occurrence of diseases in crop monoculture.

We aimed to investigate the ecological modifications of pathogen population density in soil, disease occurrence rate, and microbiota community shifting during ginseng monoculture to better understand the tripartite social relationships in the monoculture system. To achieve the study's objectives, a long-term monoculture of ginseng was established. The microbial diversity and community structure were analyzed using high-throughput sequencing, and the pathogen population density and disease occurrence rate were determined using qPCR and observation.

The results showed that the initial rhizosphere bacterial community of ginseng had already collapsed before the development of the root rot disease. The study also identified the crucial role of soil-borne pathogens in causing disease and the loss of initial keystone taxa populations in the early stages of monoculture. Our study revealed a novel aspect of soil microbiota dynamics during ginseng monoculture, with seven distinct microbes (Beijerinckiaceae, Comamonadaceae, Devosiaceae, Rhizobiaceae, Sphingobacteriaceae, Sphingomonadaceae, and Xanthomonadaceae) participating in soil nitrogen metabolism as an 'initial community' that regulates root rot disease through nutritional competition. The findings contribute to ecological research on disease-suppressiveness soil, disease management, and sustainable agriculture.

Coral microbiomes play crucial roles in holobiont homeostasis and adaptation. The host's ability to populate broad ecological niches and to cope with environmental changes seems to be related to the flexibility of the coral microbiome. By means of high-throughput DNA sequencing we characterized simultaneously both bacterial (16S rRNA) and Symbiodiniaceae (ITS2) communities of four reef-building coral species (Mussismilia braziliensis, Mussismilia harttii, Montastraea cavernosa, and Favia gravida) that differ in geographic distribution and niche specificity. Samples were collected in a marginal reef system (Abrolhos, Brazil) in four sites of contrasting irradiance and turbidity. Biological filters governed by the host are important in shaping corals' microbiome structure. More structured associated microbial communities by reef site tend to occur in coral species with broader geographic and depth ranges, especially for Symbiodiniaceae, whereas the endemic and habitat-specialist host, M. braziliensis, has relatively more homogenous bacterial communities with more exclusive members. Our findings lend credence to the hypothesis that higher microbiome flexibility renders corals more adaptable to diverse environments, a trend that should be investigated in more hosts and reef areas.

Pythium sensu lato (s.l.) is a genus of parasitic oomycetes that poses a serious threat to agricultural production worldwide, but their severity is often neglected because little knowledge about them is available. Using an internal transcribed spacer (ITS) amplicon-based-metagenomics approach, we investigate the occurrence, abundance, and diversity of Pythium spp. s.l. in 127 corn fields of 11 European countries from the years 2019 to 2021. We also identify 73 species, with up to 20 species in a single soil sample, and the prevalent species, which show high species diversity, varying disease potential, and are widespread in most countries. Further, we show species-species co-occurrence patterns considering all detected species and link species abundance to soil parameter using the LUCAS topsoil dataset. Infection experiments with recovered isolates show that Pythium s.l. differ in disease potential, and that effective interference with plant hormone networks suppressing JA (jasmonate)-mediated defenses is an essential component of the virulence mechanism of Pythium s.l. species. This study provides a valuable dataset that enables deep insights into the structure and species diversity of Pythium s.l. communities in European corn fields and knowledge for better understanding plant-Pythium interactions, facilitating the development of an effective strategy to cope with this pathogen.

The increasing accumulation of microplastics (MPs) in agroecosystems has raised significant environmental and public health concerns, facilitating the application of biodegradable plastics. However, the comparative effects of conventional and biodegradable MPs in agroecosystem are still far from fully understood. Here we developed microcosm experiments to reveal the ecological effects of conventional (polyethylene [PE] and polypropylene [PP]) and biodegradable (polyadipate/butylene terephthalate [PBAT] and polycaprolactone [PCL]) MPs (0, 1%, 5%; w/w) in the maize-soil ecosystem. We found that PCL MPs reduced plant production by 73.6-75.2%, while PE, PP and PBAT MPs elicited almost negligible change. The addition of PCL MPs decreased specific enzyme activities critical for soil nutrients cycling by 71.5-95.3%. Biodegradable MPs tended to reduce bacterial α-diversity. The 1% treatments of PE and PBAT, and PCL enhanced bacterial networks complexity, whereas 5% of PE and PBAT, and PP had adverse effect. Moreover, biodegradable MPs appeared to reduce the α-diversity and networks complexity of fungal community. Overall, PCL reduced the ecosystem multifunctionality, mainly by inhibiting the microbial metabolic activity. This study offers evidence that biodegradable MPs can impair agroecosystem multifunctionality, and highlights the potential risks to replace the conventional plastics by biodegradable ones in agricultural practices.

Postpartum period of dairy cattle is an important phase of their life mainly associated with the changes in physiology, rumen function, and energy metabolism. Studies have shown that gut microbial composition undergoes drastic changes during the postpartum period. However, little is known about the temporal variations in digestive tract microbiota in postpartum Tibetan cattle. The aim of this study was to investigate the temporal variations in blood metabolites, ruminal fermentation, and microbial community of oral, rumen, and gut in lactating Tibetan cattle during postpartum.

We collected blood, saliva, rumen fluid, and fecal samples from lactating Tibetan cattle during 1st week (1 W), the 2nd week (2 W), the 1st month (1 M), and the 2nd month (2 M) of the postpartum period. The microbiota of saliva, rumen fluid, and fecal samples were assessed using 16S rRNA sequencing. The rumen volatile fatty acid and blood parameters were also quantified.

The content of volatile fatty acids (VFAs) and blood parameters showed opposite tendency to each other and reached to stability at 2 M. Rumen microbiota showed the highest alpha diversity compared to other two sites. At phylum level, the oral cavity was dominated by Proteobacteria, while most dominant phylum in rumen and feces were Firmicutes and Bacteroidetes, respectively. The dominant genera in oral cavity were Moraxella and Bibersteinia, while genera Prevotella 1 and Ruminococcaceae UCG-005 were dominant in rumen and fecal samples, respectively.

Microbial network analysis revealed that most of the active genera in all networks belonged to phylum Firmicutes, indicating the importance of this phyla during postpartum period of lactating cattle. The functional analysis revealed distinct division of labor among three gastrointestinal sites associated with defense, fatty acid synthesis, and maintaining health of host. All in all, our findings provide insights into the metabolic and microbial changes of lactating Tibetan cattle and help to the improvement of the management strategies.

Long-lived individuals have been extensively studied as a model to investigate the role of the gut microbiota in aging, but their gut fungi remain almost unexplored. Here, we recruited a community-dwelling cohort of 251 participants (24-108 years, including 47 centenarians) from Guangxi in China to characterize the gut mycobiome signatures. We found gut mycobiome markedly varied during aging and determined aging as a predominant factor driving these variations. For long-lived individuals, core taxa, including Penicillium and Aspergillus, were maintained and Candida enterotype was enriched when compared with old counterparts. Individuals with this enterotype were more likely to possess Bacteroides enterotype enriched in young and centenarians. Moreover, the drivers from Candida enterotype were positively linked with the bacteria components dominated in Bacteroides enterotype. We also identified potentially beneficial yeasts-enriched features to differentiate long-lived individuals from others. Our findings suggest that the gut mycobiome develops with aging, and long-lived individuals possess unique fungal signatures.

Monitoring the levels of opportunistic pathogens in drinking water is important to plan interventions and understand the ecological niches that allow them to proliferate. Quantitative PCR is an established alternative to culture methods that can provide a faster, higher-throughput, and more precise enumeration of the bacteria in water samples. However, PCR-based methods are still not routinely applied for Legionella monitoring, and techniques, such as DNA extraction, differ notably between laboratories. Here, we quantify the impact that DNA extraction methods had on downstream PCR quantification and community sequencing. Through a community science campaign, we collected 50 water samples and corresponding shower hoses, and compared two commonly used DNA extraction methodologies to the same biofilm and water phase samples. The two methods showed clearly different extraction efficacies, which were reflected in both the quantity of DNA extracted and the concentrations of Legionella enumerated in both the matrices. Notably, one method resulted in higher enumeration in nearly all samples by about one order of magnitude and detected Legionella in 21 samples that remained undetected by the other method. 16S rRNA amplicon sequencing revealed that the relative abundance of individual taxa, including sequence variants of Legionella, significantly varied depending on the extraction method employed. Given the implications of these findings, we advocate for improvement in documentation of the performance of DNA extraction methods used in drinking water to detect and quantify Legionella, and characterize the associated microbial community.IMPORTANCEMonitoring for the presence of the waterborne opportunistic pathogen Legionella is important to assess the risk of infection and plan remediation actions. While monitoring is traditionally carried on through cultivation, there is an ever-increasing demand for rapid and high-throughput molecular-based approaches for Legionella detection. This paper provides valuable insights on how DNA extraction affects downstream molecular analysis such as the quantification of Legionella through droplet digital PCR and the characterization of natural microbial communities through sequencing analysis. We analyze the results from a risk-assessment, legislative, and ecological perspective, showing how initial DNA processing is an important step to take into account when shifting to molecular-based routine monitoring and discuss the central role of consistent and detailed reporting of the methods used.

Bacterial community is strongly associated with activated sludge performance, but there still remains a knowledge gap regarding the rare bacterial community assembly and their influence on the system performance in industrial wastewater treatment plants (IWWTPs). Here, we investigated bacterial communities in 11 full-scale IWWTPs with similar process designs, aiming to uncover ecological processes and functional traits regulating abundant and rare communities. Our findings indicated that abundant bacterial community assembly was governed by stochastic processes; thereby, abundant taxa are generally present in wastewater treatment compartments across different industrial types. On the contrary, rare bacterial taxa were primarily driven by deterministic processes (homogeneous selection 61.9%-79.7%), thus they only exited in specific IWWTPs compartments and wastewater types. The co-occurrence networks analysis showed that the majority of keystone taxa were rare bacterial taxa, with rare taxa contributing more to network stability. Furthermore, rare bacteria rather than abundant bacteria in the oxic compartment contributed more to the degradation of xenobiotics compounds, and they were main potential drivers of pollutant removal. This study demonstrated the irreplaceable roles of rare bacterial taxa in maintaining system performance of IWWTPs, and called for environmental engineers and microbial ecologists to increase their attention on rare biosphere.

Colorectal polyps that develop via the conventional adenoma-carcinoma sequence [e.g., tubular adenoma (TA)] often progress to malignancy and are closely associated with changes in the composition of the gut microbiome. There is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway, such as hyperplastic polyps (HP). Exploration of microbiome alterations associated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal carcinogenesis.

To investigate gut microbiome signatures, microbial associations, and microbial functions in HP and TA patients.

Full-length 16S rRNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps [control group (CT), n = 40], patients with HP (n = 52), and patients with TA (n = 60). Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or TA. Analytical techniques in this study included differential abundance analysis, co-occurrence network analysis, and differential pathway analysis.

Colorectal cancer (CRC)-associated bacteria, including Streptococcus gallolyticus (S. gallolyticus), Bacteroides fragilis, and Clostridium symbiosum, were identified as characteristic microbial species in TA patients. Mediterraneibacter gnavus, associated with dysbiosis and gastrointestinal diseases, was significantly differentially abundant in the HP and TA groups. Functional pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively, whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis (e.g., mevalonate); S. gallolyticus was a major contributor. Co-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients, whereas TA patients exhibited co-occurrence of CRC-associated bacteria. Furthermore, the co-occurrence of SCFA-producing bacteria was lower in TA patients than HP patients.

This study revealed distinct gut microbiome signatures associated with pathways of colorectal polyp development, providing insights concerning the roles of microbial species, functional pathways, and microbial interactions in colorectal carcinogenesis.