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Depth-dependent multi-kingdom microbial interactions and biogeochemical cycling genes in eutrophic shallow lake sediments.

Microorganisms are pivotal to lake ecosystem biogeochemical cycles, yet existing research often focuses on single microbial kingdoms or surface sediments, neglecting multi-kingdom interactions and depth-resolved dynamics. To address these gaps, we used metagenomic sequencing to characterize microbial communities and their functional associations across overlying water and 0-45 cm sediments in four shallow lakes of the middle Yangtze River basin, China. Despite increasing bacterial and fungal diversity with depth, the 0-9 cm surface sediments exhibited the strongest multi-kingdom network connectivity and the greatest microbial stability. Functional genes exhibited clear depth-dependent patterns: nitrogen cycling genes, including those involved in dissimilatory nitrate reduction to ammonium, were most enriched in the upper 0-9 cm of sediment; methane cycling genes were positively correlated with depth; phosphorus cycling genes and some sulfur cycling genes, such as assimilatory sulphate reduction, declined with depth. Sediment microbial assembly was dominated by deterministic processes, in which the vertical distribution of functional genes was primarily dictated by heavy metals and conventional environmental indicators. These findings highlight depth-specific multi-kingdom microbial interactions and their associations with biogeochemical cycling, advancing lacustrine microbial ecology understanding and providing references for lake conservation under environmental change.

Lakes

Optimizing eco-engineering pedogenesis of bauxite residues: Synergistic effects of humus and FeSO4/sulfur on microbial community and function.

Eco-engineered pedogenesis represents a promising approach for soil amelioration of bauxite residues (BRs) through exogenous organic matter. However, the role of humus in mediating this process remains poorly understood, significantly impeding the eco-engineering rehabilitation of BRs. In this study, we conducted pot experiments and subsequent microbial analysis to evaluate the individual improvement of humic acid (HA), fulvic acid (FA), and corn straw (SWZ) on the BRs' pedogenesis. High-throughput sequencing analysis revealed that both FA and SWZ were more effective than HA in steering microbial community assembly, as community diversity, dominant taxa enrichment, and species' interaction were all significantly higher (p < 0.05) in the FA/SWZ treatments than in HA treatments. Notably, the combination of FA with FeSO4 specifically enriched halophilic taxa, while FA coupled with sulfur (S) significantly improved the connectivity and complexity of the microbial network, as the average connection degree increasing from 1.008 to 1.113. Hydrolytic enzyme activity assays further indicated that FA, especially when combined with S, was the most effective treatment in restoring microbial function during BR pedogenesis. These findings highlight FA as a critical driver of microbial restructuring and functional recovery in BRs. Moreover, its efficacy can be enhanced by co-amendment with FeSO4 or S. This study provides important theoretical and practical insights for optimizing organic-inorganic amendment strategies to accelerate the eco-engineering pedogenesis of bauxite residues.

Humic Substances

Functional analysis of Candida albicans protein kinases identifies Crk1 as a modulator of epithelial cell damage.

UNLABELLED: The commensal and pathogenic lifestyles of the opportunistic fungal pathogen Candida albicans require complex signaling networks regulated by protein kinases. To investigate the role of C. albicans protein kinases at the intestinal epithelial interface, we screened a comprehensive protein kinase deletion library for the capacity of the mutants to damage intestinal epithelial cells (IEC). Mutants showing altered IEC cytotoxicity relative to the wild type were further analyzed for their growth and morphology, focusing on hyper-damaging strains to identify kinases that rather prevent host cell damage. Deletion of CRK1 caused increased IEC-specific damage, despite slower growth, reduced hyphal length, and reduced adhesion as compared to wild-type cells. While tissue invasion levels and the formation of transcellular tunnels of the crk1&#x394;/&#x394; mutant were increased, the translocation capacity through the IEC barrier was reduced. Transcriptional and metabolic profiling suggested a role for Crk1 in metabolic adaptation to carbon and nitrogen sources, which was validated by showing that high glucose and amino acids are required for crk1&#x394;/&#x394; to cause increased IEC damage. Deletion of CRK1 rendered C. albicans more susceptible to cell wall and membrane stressors, but caused higher resistance to a catalase-specific and histidine biosynthesis inhibitor. This phenotypic pattern of medium- and epithelial cell type-specific cytotoxicity displayed by a C. albicans protein kinase mutant suggests that Crk1 regulates processes linked to carbon and amino acid metabolism that are relevant to interactions with intestinal epithelial cells. IMPORTANCE: Microbial signal transduction pathways regulate adaptation to changing environmental conditions and facilitate the success of many microbes during interactions with their hosts. The fungal pathobiont Candida albicans exists as a harmless commensal on mucosal surfaces of most humans but can also cause superficial and invasive infections under certain circumstances. Both lifestyles require complex signaling networks, predominantly regulated by protein kinases. The C. albicans genome was predicted to encode 108 protein kinases, yet nearly 50% remain uncharacterized. We aimed to dissect the role of C. albicans protein kinases during the transition from commensal to pathogen. We showed that multiple protein kinase genes are involved in epithelial cell damage. Particularly, the protein kinase gene Crk1 was of interest because deletion of CRK1 caused increased damage to intestinal epithelial cells under distinct conditions. Our study links Crk1 with regulation of metabolic processes relevant for commensalism and pathogenicity of C. albicans.

Candida albicans

Conserved protein folds underpin the diversification of secreted proteins in a fungal pathogen.

BACKGROUND: During host colonization, fungal plant pathogens secrete effector-like proteins that alter host cell physiology and target plant-associated microbes. However, rapid evolution and low sequence conservation hinder the study and characterization of these proteins. The fungus Zymoseptoria passerinii infects Hordeum spp. and includes lineages adapted to wild and domesticated barley. To date, the evolution of effector-like proteins in this species has not been addressed. RESULTS: We combined multiple structure-based and network analyses to unravel the secretome of Z. passerinii. We first compared AlphaFold2 and ESMFold predictions to establish the baseline for structural analyses. We identified 72 structural clusters in the secretome, revealing fold-level relationships across divergent sequences. We showed that effector-like proteins with predicted host immune-interfering functions evolved from a limited group of protein folds, whereas proteins with predicted antimicrobial properties were distributed across fold groups. Physicochemical comparisons indicate that putative antimicrobial effectors predominantly emerged through amino acid replacements on common effector-enriched scaffolds in Z. passerinii, reconfiguring surface charge and electrostatics. We analyzed intra- and interspecific variation in selected effector-enriched families by comparing Z. passerinii proteins and homologs across the genus Zymoseptoria. We describe constrained core folds, with local variation in loop and surface-exposed regions, consistent with fold stability while still enabling protein diversification. We further report that putative antimicrobial effector homologs are broadly distributed across the genus despite sequence divergence. CONCLUSIONS: The secretome of Z. passerinii is organized around common structural folds that support diverse biological roles, including host manipulation and host-associated microbial interactions. Conserved scaffolds combined with surface and physicochemical variation likely contribute to rapid adaptive evolution of effector-like proteins in Z. passerinii.

Fungal Proteins

Lesion-specific oral microbiome signatures and predicted carcinogenic pathways in oral squamous cell carcinoma: a paired-site study in Pakistan.

BACKGROUND: Oral squamous cell carcinoma accounts for over 90% of oral neoplasms. Despite therapeutic advances, the lack of reliable, non-invasive biomarkers and delayed diagnosis continues to impede effective clinical management. By combining paired lesion and non-lesion sampling with predictive metagenomics analysis, our study addresses this gap and advances the current understanding of microbiome&#x2012;tumor interactions. METHODS: We analyzed 92 buccal swab samples from 39 OSCC patients and 14 healthy controls using 16S rRNA gene (V3-V4) sequencing. Taxonomic profiling was conducted using QIIME2 and SILVA/eHOMD databases, functional pathways were predicted using PICRUSt2, and hub taxa were identified through co-abundance network analysis. RESULTS: Microbial community structure differed significantly across lesion, non-lesion, and healthy sites (PERMANOVA, p&#x2009;=&#x2009;0.001). Lesions were enriched with Selenomonas infelix and Treponema vincentii, while healthy controls harbored Streptococcus oralis and Gemella haemolysans. Co-abundance network analysis revealed lesion-specific hub species, notably T. vincentii, strongly correlated with predicted activation of pyrimidine biosynthesis pathways (r&#x2009;=&#x2009;0.69, q&#x2009;<&#x2009;1E-6), suggesting predicted metabolic alterations in the tumor microenvironment. Non-lesion sites were also characterized by two hub species, Prevotella melaninogenica and Segatella oulorum. CONCLUSION: Our findings define a lesion-specific microbial signature of OSCC characterized by the depletion of health-associated taxa, enrichment of pro-inflammatory pathobionts, and predicted associations with metabolic pathways implicated in carcinogenesis. These alterations reflect a predicted functionally altered tumor microenvironment.

16S rRNA gene

Involvement of cross-genus phages in bacterial resistance to chlorine disinfection.

Chlorine disinfection resistance in pathogenic microorganisms poses severe environmental concerns and public health risks. While phages play critical roles in host adaptation to environmental stress, how poly-host phages contribute to bacterial resistance to chlorine disinfectants remains poorly understood. Here, we investigated shifts in the population dynamics, transcriptional profiles, and function potentials of cross-genus phage-bacterial communities under exposure to chlorine disinfectants in a continuously operated anaerobic-anoxic-oxic system over a 92-day period, using integrated metagenomic and metatranscriptomic approaches. In the presence and absence of chlorine disinfectants, the genomic abundance and diversity of phage and bacterial communities showed similar variation trends, and the community structures of both exhibited clear differences. A strong significant positive correlation was observed between phage and bacterial diversity under chlorine exposure (R&#x202f;=&#x202f;0.975, p&#x202f;=&#x202f;0.00,057), whereas no significant correlation was detected in the absence of chlorine disinfection (R&#x202f;=&#x202f;-0.314, p&#x202f;=&#x202f;0.613), suggesting that chlorine disinfectants may enhance phage-bacteria interactions. Host-associated phages exhibited high consistency with their corresponding putative hosts in terms of genomic abundance (M2&#x202f;=&#x202f;0.0945, p&#x202f;=&#x202f;0.001) and transcript abundance (M2&#x202f;=&#x202f;0.3668, p&#x202f;=&#x202f;0.001), and they were also significantly correlated with cross-genus phages in both genomic abundance (R&#x202f;=&#x202f;0.97, p&#x202f;<&#x202f;2.2e-16) and transcript abundance (R&#x202f;=&#x202f;0.83, p&#x202f;<&#x202f;2.2e-16), which collectively suggests the critical role of cross-genus phages in the resistance of microbial communities to chlorine disinfectants. Bipartite association network analysis shows that cross-genus phages carry highly homologous genes to their putative hosts and may be involved in the horizontal transfer of these genes among bacteria. These homologous genes are involved in DNA repair, redox balance regulation, environmental stress adaptation and efflux pump functions, suggesting a synergistic role between cross-genus phages and their putative hosts in chlorine resistance. Our findings reveal that cross-genus phages can contribute to the resistance of bacterial communities to chlorine disinfectants, providing the theoretical foundation for evaluating the role of poly-host phages in microbial communities.

Chlorine resistance

Comparison of the antibiotic resistance mechanisms in a gram-positive and a gram-negative bacterium by gene networks analysis.

Nowadays, the emergence of some microbial species resistant to antibiotics, both gram-positive and gram-negative bacteria, is due to changes in molecular activities, biological processes and their cellular structure in order to survive. The aim of the gene network analysis for the drug-resistant Enterococcus faecium as gram-positive and Salmonella Typhimurium as gram-negative bacteria was to gain insights into the important interactions between hub genes involved in key molecular pathways associated with cellular adaptations and the comparison of survival mechanisms of these two bacteria exposed to ciprofloxacin. To identify the gene clusters and hub genes, the gene networks in drug-resistant E. faecium and S. Typhimurium were analyzed using Cytoscape. Subsequently, the putative regulatory elements were found by examining the promoter regions of the hub genes and their gene ontology (GO) was determined. In addition, the interaction between milRNAs and up-regulated genes was predicted. RcsC and D920_01853 have been identified as the most important of the hub genes in S. Typhimurium and E. faecium, respectively. The enrichment analysis of hub genes revealed the importance of efflux pumps, and different enzymatic and binding activities in both bacteria. However, E. faecium specifically increases phospholipid biosynthesis and isopentenyl diphosphate biosynthesis, whereas S. Typhimurium focuses on phosphorelay signal transduction, transcriptional regulation, and protein autophosphorylation. The similarities in the GO findings of the promoters suggest common pathways for survival and basic physiological functions of both bacteria, including peptidoglycan production, glucose transport and cellular homeostasis. The genes with the most interactions with milRNAs include dpiB, rcsC and kdpD in S. Typhimurium and EFAU004_01228, EFAU004_02016 and EFAU004_00870 in E. faecium, respectively. The results showed that gram-positive and gram-negative bacteria have different mechanisms to survive under antibiotic stress. By deciphering their intricate adaptations, we can develop more effective therapeutic approaches and combat the challenges posed by multidrug-resistant bacteria.

Anti-Bacterial Agents

Synthetic community derived from the root core microbes of a desert shrub Caragana korshinskii enhances wheat drought tolerance.

BACKGROUND: Drought, intensified by climate change, poses a mounting threat to global food security by severely constraining crop productivity. While microbial inoculants offer promise for drought tolerance, their poor adaptability remains insufficient for extremely water-deficient environments. Desert plants host unique drought-adapted microbiomes that remain largely unexplored for agricultural applications. RESULTS: Here, we investigated the microbial community of the desert shrub Caragana korshinskii and identified a core set of drought-responsive strains. A synthetic microbial community (SynCom) derived from these strains significantly improved wheat growth under drought stress. Metagenomic analyses revealed that microbial functions related to biofilm formation, quorum sensing, and carbon metabolism were enriched, with Pseudomonas identified as a key functional taxon. Guided by inter-strain interactions in biofilm assembly, we streamlined the consortium into a five-member synthetic community, where quorum-sensing signals promoted community-wide biofilm formation. Community biofilm production improved strain colonization and conferred greater drought tolerance compared to monocultures. In plants, mechanistic investigations indicated that the simplified SynCom inoculation universally upregulated MAPK and jasmonic acid signaling pathways. Furthermore, carbohydrate metabolic pathways such as starch and sucrose metabolism were specifically activated, suggesting a multi-level mechanism underlying SynCom-mediated drought tolerance. CONCLUSIONS: These findings demonstrate that SynCom constructed on the endophytic flora of desert plants can significantly enhance crop drought tolerance. Our work highlights the pivotal role of community biofilm synthesis in facilitating root colonization and activating a multidimensional drought tolerance network in plants. This study not only gives an ecological perspective on desert microbiome adaptations but also offers a strategic framework for developing effective microbial inoculants for arid-region agriculture. Video Abstract.

Caragana

Data-driven approaches in green microbiology: strategies for plant growth-promoting bacteria.

Plant growth-promoting bacteria (PGPB) are gaining attention as scalable biological solutions to enhance crop productivity and resilience. However, accurately identifying and characterizing PGPB remains challenging, particularly under variable environmental conditions where microbial functions are context-dependent and shaped by complex plant-microbe interactions. Advances in high-throughput sequencing have shifted the field from culture-dependent approaches to genome-informed strategies, enabling large-scale taxonomic and functional profiling. Although trait-based databases support the prediction of plant-beneficial genes, they capture only a fraction of the underlying biological complexity and often require labor-intensive analyses. Machine learning (ML) and deep learning (DL) have emerged as powerful tools to integrate genomic, physiological, and ecological data, enabling the prioritization of candidate strains with plant growth-promoting potential. To evaluate advances in the field, we conducted a systematic review of studies integrating ML and DL with PGPB characterization, assessing algorithm selection, performance, and target plant systems. Across 248 observations, only 6.0% of studies directly addressed PGPB screening, whereas the majority (77.4%) focused on plant disease detection, revealing a substantial gap in the application of AI to beneficial microorganisms for plant growth. Convolutional neural networks (CNNs) were the most frequently applied algorithms, largely driven by image-based phenotyping tasks. Overall, the field is constrained by limited datasets, high computational demands, and challenges in modeling multispecies and host-associated interactions. We highlight the need for integrative and interpretable ML and DL frameworks that bridge genomic data and functional validation. Such approaches represent a promising path toward scalable, data-driven discovery and deployment of bioinoculants in sustainable agriculture.

Agriculture

Bridging the airway microbiome and targeted therapy in bronchiectasis: multi-omics insights, endotypes and emerging therapies.

Bronchiectasis is a heterogeneous chronic airway disease primarily driven by persistent infection, microbial dysbiosis and dysregulated host immunity. While culture-based microbiology has historically informed clinical management, advances in high-throughput sequencing and multi-omic technologies have transformed our understanding of the airway ecosystem, revealing that disease activity is shaped not only by individual pathogens, but by complex and dynamic host-microbe interactions. Despite the breadth of descriptive microbiome data, translation into clinically actionable diagnostics or therapies has been limited. Importantly, cross-sectional correlations between microbiota and inflammation do not establish cause and effect, underscoring the need to embed host-microbiome profiling within both longitudinal and interventional therapeutic trials. In this review, we critically appraise current microbial and host multi-omics research in bronchiectasis, integrating microbiome studies with host inflammatory, proteomic and immunophenotyping data. We highlight themes emerging across cohorts, including low microbial diversity, pathogen dominance, loss of commensal networks and neutrophil-driven inflammation, and discuss how these features align with biological endotypes associated with exacerbations and treatment response. Drawing on lessons from host-directed therapeutic successes, we examine translational roadblocks limiting microbiome-guided care. We further review emerging microbiome-modulating strategies such as pathogen-specific biologics, bacteriophage therapy, live biotherapeutic products, biofilm-targeting adjuncts and precision antibiotic stewardship. Finally, we propose a roadmap toward microbiome-informed precision medicine through harmonised methodologies, integration of host and microbial biomarkers into clinical trials, and embedding multi-omics pipelines within large international registries. Collectively, these advances have the potential to shift bronchiectasis research and clinical management towards rationally designed, precision medicine-driven therapeutic strategies.

Humans

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics

The Rhizosphere Microbiome: A Key Mediator of Crop Responses to Fertilization Strategies.

The rhizosphere microbiome, the plant's "second genome" is pivotal for crop nutrient acquisition, health, and stress responses. While fertilization ensures high agricultural yields, a key challenge is reshaping this microbiome to boost crop performance. This review synthesizes how mineral, organic, and bio-organic/microbial inoculant fertilizers affect rhizosphere microbial structure, diversity, and function. Long-term excessive mineral fertilizers (especially nitrogen) reduce microbial diversity, diminish beneficial groups (e.g., diazotrophs, PGPR), and disrupt microbial networks via soil acidification and altered root exudates, causing continuous cropping obstacles. In contrast, organic fertilizers improve soil microenvironments, maintaining high microbial diversity, enriching beneficial taxa (e.g., Proteobacteria, Actinobacteria), and enhancing community complexity. Bio-organic fertilizers/microbial inoculants "engineer" the microbiome by introducing exogenous beneficial microbes (e.g., Bacillus, Pseudomonas, AMF), directly promoting growth, suppressing diseases, and "reconditioning" indigenous beneficial communities. We also clarify how fertilization regulates plant-microbe dialog via root exudates and rhizosphere chemistry (e.g., pH, ion balance), discuss current challenges (causality, lab-to-field translation, genotype-microbiome-fertilization interactions), and outline future directions. Integrating rhizosphere microbiome management into fertilization is crucial for reducing chemical fertilizer reliance and advancing agricultural green transformation.

fertilization strategies microbial community assem

Rgg144/SHP144-controlled streptolancidin D mediates intra-species competition in Streptococcus pneumoniae with cumulative effect from other bacteriocins and fratricide.

UNLABELLED: Streptococcus pneumoniae is a major colonizer of the human nasopharynx, where inter- and intra-strain competition plays a critical role in shaping population structure and influencing vaccine outcomes. Bacteriocins are key mediators of intra-species competition, yet many of their functions and regulatory mechanisms remain poorly understood. Here, we identify and characterize streptolancidin D, a previously uncharacterized bacteriocin encoded by the sldA-T locus, and demonstrate its contribution to pneumococcal competition. Using isogenic streptolancidin-producing and non-producing variants of a naturally colonizing strain, we show that sldA-T contributes to the inhibition of competitor strains in in vitro biofilms and during murine co-colonization. Importantly, streptolancidin D also inhibited in vitro a subset of genetically diverse pneumococcal isolates representing multiple serotypes, whereas non-producing variants showed no activity. This indicates that its effect is broad and not restricted to isogenic interactions. Genomic analysis of over 7,500 pneumococcal genomes revealed that sldA-T is present in ~12% of isolates, with lineage-associated distribution patterns, and is consistently encoded downstream of the Rgg144/SHP144 quorum sensing system. We further demonstrate that sldA-T is regulated by this system, with sldA-T promoter activity abolished in a SHP-deficient background and partially restored by exogenous peptide stimulation. Finally, we show that streptolancidin D acts in concert with other bacteriocin systems and competence-mediated fratricide, highlighting a multifactorial antimicrobial strategy that enhances pneumococcal competitiveness. Overall, our findings identify a quorum sensing-regulated bacteriocin that contributes to pneumococcal competition and helps shape population dynamics. IMPORTANCE: Bacteriocins are central to bacterial competition and niche occupation, particularly in structured environments like the human nasopharynx. While several pneumococcal bacteriocins have been characterized, the functions of many remain unknown, limiting our understanding of how these systems shape strain fitness and population dynamics. We characterize streptolancidin D, a bacteriocin that enhances intraspecies competitiveness in vitro and in vivo and contributes to the inhibition of genetically diverse pneumococcal strains. We demonstrate that its expression is tightly regulated by the conserved Rgg144/SHP144 quorum sensing system and that the locus is distributed and shows synteny across multiple pneumococcal lineages. Our findings reveal that streptolancidin D operates within a broader network of bacteriocins and competence-associated mechanisms that collectively shape competitive interactions. By integrating genomic, functional, and regulatory analyses, this work expands the known repertoire of pneumococcal antimicrobial systems and provides new insights into the mechanisms underpinning competition and population structure in S. pneumoniae.

Bacteriocins

Exploring the ecological drivers of bacteriophage diversity and functional viral potential in the skin of the axolotl Ambystoma altamirani.

Bacteriophages play important roles in shaping microbial community dynamics across diverse environments. In the amphibian skin, most microbiome studies have focused on bacteria and their interactions with the fungus Batrachochytrium dendrobatidis (Bd), leaving other microbial components, including viruses, largely unexplored. Here, we present the first characterization of the viral community in the amphibian skin microbiome, focusing on ecological drivers of bacteriophage diversity and functional potential in the axolotl Ambystoma altamirani. Using public shotgun metagenomes, we found that the viral fraction was dominated by bacteriophages of the class Caudoviricetes. Bacteriophage diversity was significantly associated with local physicochemical parameters at the time of sampling, and showed a strong positive correlation with bacterial diversity, whereas no significant associations were detected with the presence of Bd. In addition, seasonality influenced the composition and properties of bacteria-bacteriophage co-abundance networks. Functional annotation of assembled bacteriophage sequences revealed a diverse functional potential, including putative auxiliary metabolic genes, superinfection exclusion, toxin-antitoxin, and virulence factors. Overall, these findings highlight the ecological relevance of bacteriophages in amphibian skin microbiomes and underscore the need for further studies on their role in the amphibian host's health.

Animals

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome

Phylum-wide propionate degradation and its potential connection to poly-gamma-glutamate biosynthesis in Candidatus Cloacimonadota phylum.

The candidate phylum Cloacimonadota is frequently detected in anoxic environments such as anaerobic digestion (AD) reactors, hydrothermal vents, and deep-sea sediments, yet its metabolism remains poorly understood. Metagenomic evidence suggests capacities for amino acid fermentation, carbohydrate degradation, as well as a potential role in syntrophic propionate oxidation (SPO), a key bottleneck in AD. However, a complete methylmalonyl-CoA (mmc) pathway, central to SPO, has not been previously identified in Cloacimonadota genomes. Here, we report results from an acidified lab-scale anaerobic baffled reactor fed with sugar beet pulp, where an increase in the relative abundance of Cloacimonadota correlated with recovery of methanogenesis, resulting in increased methane content in the produced biogas. Metagenomic and metatranscriptomic analyses enabled metabolic reconstruction of the dominant Cloacimonadota operational taxonomic unit (OTU). Furthermore, using a curated database of 204 genome-resolved Cloacimonadota species, we characterized the phylum-level metabolic potential. Comparative genomics revealed alternative proteins, including 2-oxoglutarate:ferredoxin oxidoreductase and aspartate aminotransferase, likely to substitute for missing enzymes in the classical mmc pathway. These proteins were widely distributed and highly conserved across the analyzed Cloacimonadota genomes, suggesting that this variant of the SPO pathway could represent a phylum-specific trait. Moreover, we hypothesize that these alternative pathway steps may link propionate metabolism to protein degradation and poly-&#x3b3;-glutamate biosynthesis. Network analysis identified the methanogenic archaeon Methanothrix as a potential syntrophic partner, an interaction further supported by propionate-fed enrichment cultures showing co-occurrence of Cloacimonadota and Methanothrix species. Our study sheds light on the Cloacimonadota metabolism, advancing our understanding of their ecological roles and potential for biotechnological applications.

Propionates

Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in&#xa0;gastric cancer, colorectal cancer, and inflammatory bowel disease.

INTRODUCTION: Gastrointestinal disorders (GIDs) affect nearly 40% of the global population, with gut microbiome-metabolome interactions playing a crucial role in gastric cancer (GC), colorectal cancer (CRC), and inflammatory bowel disease (IBD). This study aims to investigate how microbial and metabolic alterations contribute to disease development and assess whether biomarkers identified in one disease could potentially be used to predict another, highlighting cross-disease applicability. METHODS: Microbiome and metabolome datasets from Erawijantari et al. (GC: n&#x2009;=&#x2009;42, Healthy: n&#x2009;=&#x2009;54), Franzosa et al. (IBD: n&#x2009;=&#x2009;164, Healthy: n&#x2009;=&#x2009;56), and Yachida et al. (CRC: n&#x2009;=&#x2009;150, Healthy: n = 127) were subjected to three machine learning algorithms, eXtreme gradient boosting (XGBoost), Random Forest, and Least Absolute Shrinkage and Selection Operator (LASSO). Feature selection identified microbial and metabolite biomarkers unique to each disease and shared across conditions. A microbial community (MICOM) model simulated gut microbial growth and metabolite fluxes, revealing metabolic differences between healthy and diseased states. Finally, network analysis uncovered metabolite clusters associated with disease traits. RESULTS: Combined machine learning models demonstrated strong predictive performance, with Random Forest achieving the highest Area Under the Curve(AUC) scores for GC(0.94[0.83-1.00]), CRC (0.75[0.62-0.86]), and IBD (0.93[0.86-0.98]). These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. CONCLUSION: These findings emphasize the potential of microbial and metabolic profiling in cross-disease characterization particularly for GIDs, advancing biomarker discovery for improved diagnostics and targeted therapies.

Humans

Orchard netting impacts on biodiversity leading to cascading effects at the ecosystem level.

Agriculture must ensure food production without further compromising the ecosystem functions upon which it depends. Agricultural practices should therefore avoid harming farmland biodiversity, especially of taxa that supply the key ecosystem services (e.g. pollination, pest control and nutrient uptake) that ultimately support crop production. Orchards are among the largest permanent plantations worldwide and are increasingly characterised by the spread of plastic nets used to protect fruits/nuts from either abiotic (anti-hail, anti-rain, shade nets) or biotic (exclusion nets) hazards. Despite having received little attention to date, these nets may impact natural communities, acting both as physical barriers and as drivers of habitat changes to which biota must respond. Species-level responses to netting depend on the organism's ability to enter the netted environment and successfully exploit available resources. Net-mediated ecological filtering and plastic behavioural responses may alter species interactions, leading to cascading ecological impacts that may create species-poorer 'netted communities' with simplified ecological networks. Such changes may erode biological control potential, other ecosystem functions, and overall system stability. We conducted a systematic review on the effects of protection nets on biota, and reported novel empirical evidence on anti-hail nets' impacts on communities of orchard-dwelling birds, flower-visiting insects, and rodents. In total, we identified 48 studies from the literature, however this literature was strongly biased towards apple orchards, western countries, and pest taxa. Net deployment was highly effective in deterring target pest species, in some cases regardless of their original function, as even weather-protection nets limited pest populations. Side effects on non-target taxa were also often reported, such as decreases in pollinators and natural enemies, and/or increases in secondary pests or microbial diseases. However, most assessments largely disregarded non-pest taxa and the broader ecological consequences of netting. The few studies that addressed the effects of nets at the guild/community level, including our empirical study, confirmed that orchard netting resulted in species-poor assemblages, with possible ecosystem-level consequences. We propose that future assessments should pay more attention to the indirect effects of netting on non-target taxa, and on the supply of crop-supporting ecosystem services mediated by wild species occurring in agroecosystems. Due to the trade-offs between these services and net-mediated crop protection, integrated alternatives should be tested to improve the environmental sustainability of food production and biodiversity conservation in farmed landscapes.

Biodiversity