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Listeria monocytogenes, as a significant foodborne pathogen, is not frequently encountered; however, when infections do occur, they can prove highly lethal to specific populations. Antibiotics are still regarded as the primary treatment option for Listeria infections. Nevertheless, under the global antibiotic crisis, there is an urgent demand for innovative and alternative strategies. In our study, we identified taurine, a sulfur-containing free amino acid that can be extracted from a wide variety of foods, as an effective inhibitor of Listeria growth. Furthermore, our findings revealed that taurine administration significantly reduced bacterial burden and concurrently mitigated host-derived inflammation in the mouse model. It was observed that taurine stimulated T-cell proliferation and inhibited pyroptosis via mitogen-activated protein kinase and NLRP3/caspase-1/GSDMD pathways. Our research outcomes position taurine as a promising therapeutic candidate for combating Listeria infections, with an inherent advantage of reduced likelihood for inducing antibiotic resistance compared to conventional antibiotic treatments.

Importance: Listeria monocytogenes infections are lethal to specific groups. With the antibiotic crisis, new treatments are needed. Taurine, a safe dietary compound, was found to inhibit Listeria growth. It targets both L. monocytogenes virulence and host immunopathology, stimulated T-cell proliferation, and inhibited pyroptosis. We establish taurine as the non-antibiotic agent that decouples bacterial cytotoxicity from inflammation-driven tissue damage, offering an immediately translatable strategy for high-risk infections amid the antibiotic resistance crisis.

Depression and obesity are highly comorbid and likely involve common risk factors and pathophysiological mechanisms, which could crosslink to gut microbiome dysfunction. Here, we performed a case-control study with a total of 105 subjects, 43 with major depressive disorder (MDD) and 62 non-depressed controls free from psychiatric comorbidities, to identify gut microbiome signatures associated with MDD and dissect its relation to body mass index (BMI) and lifestyle (diet and exercise). We performed shotgun metagenomics, followed by taxonomic and functional annotations. Using different machine learning methods, we were able to classify subjects into depressed and non-depressed controls with a balanced accuracy of 0.90 and into depressed or non-depressed and normal weight or overweight with a balanced accuracy of 0.78 based solely on taxonomic profiles. We identify novel bacterial taxa associated with depression, including reductions in Butyrivibrio hungatei and Anaerocolumna sedimenticola, and also replicate previously reported associations, such as decreased Faecalibacterium prausnitzii in patients with MDD. Functional annotation of metagenomes shows differences in pathways linked to the synthesis of fundamental nutrients, which have been associated with diet, as well as inflammation. Strikingly, we found an increase in tryptophan degradation and a decrease in queuosine synthesis pathways, both of which are directly related to a decrease in monoaminergic neurotransmitter availability. Additionally, our functional analysis shows that most of the functions that are more abundant in controls than in depressed subjects are encoded by F. prausnitzii. These findings reveal distinct microbial and functional signatures associated with depression, including taxa and pathways linked to neurotransmitter metabolism and independent of other covariates. This suggests that gut microbiome profiling could support diagnosis and the development of gut-directed depression treatments.

Importance: This study identifies gut microbiome signatures that are predictive of major depressive disorder (MDD) and explores their links to body mass index (BMI). We uncover bacterial species and metabolic pathways that are associated with MDD, some of them related to neurotransmitter metabolism and inflammation. Among the differences identified, depletion of Faecalibacterium prausnitzii stands out as an important feature in the MDD microbiome, which suggests the possible use of this species to improve depression symptoms. Importantly, we demonstrate shared microbiome features between MDD and BMI, suggesting common underlying mechanisms. This research not only provides a framework for developing microbiome-based diagnostics but also informs future stratified interventions targeting gut microbial functions to improve mental health outcomes.

Introns are generally considered rare in bacteria, yet they are frequently observed in Patescibacteria, which have highly reduced genomes. To systematically explore the diversity, roles, and evolution of introns in Patescibacteria, we first focused on the tRNA introns. Using 95 complete genomes, we identified tRNA^Asn and tRNA^Asp genes previously undetected by standard annotation tools due to group I introns inserted at an unusual position, 35/36, in the anticodon loop. In vitro splicing assays confirmed that these introns catalyze precise self-splicing, validating our computational approach. A large-scale survey of complete bacterial genomes revealed that intron insertions at position 35/36 are highly enriched in Patescibacteria but rare in other phyla. Subgroup classification indicated that 81% of all tRNA introns belong to the IC subgroup, whereas nearly all Patescibacteria introns were classified as IA. As most tRNA introns lack homing endonuclease genes, horizontal transfer appears limited. Comparative analysis across bacterial phyla showed that Patescibacteria and Cyanobacteriota exhibit the highest prevalence of group I introns (~40% of genomes). In contrast, group II introns, which require protein cofactors for activity, were more common in other bacteria, including Cyanobacteriota, but absent in Patescibacteria. Collectively, these findings suggest that Patescibacteria harbor introns with phylum-specific trends in abundance, structure, and evolutionary lineage. The coexistence of extensive genome reduction and persistent group I introns may reflect an adaptive strategy, where introns serve as efficient RNA-based regulatory elements, potentially substituting for complex protein-mediated systems.IMPORTANCEIntrons were traditionally thought to be rare in bacteria, yet their occurrence and diversity may have been underestimated. Here, we present the first comprehensive overview of group I and group II introns in Patescibacteria. While most introns are readily identified, group I introns inserted at position 35/36 within the anticodon loop often escape detection by standard annotation tools; through experimental verification, we demonstrate that these introns are accurately spliced despite their unusual insertion site. Notably, approximately 40% of genomes in both Patescibacteria and Cyanobacteriota harbor group I introns; however, while around 20% of Cyanobacteriota genomes also contain group II introns, none were detected in Patescibacteria. These results illustrate a previously overlooked phylogenetic distribution of group I and group II introns across the bacterial domain.

Proton pump inhibitors (PPIs) are standard therapy for gastroesophageal reflux disease (GERD), but long-term use causes dysbiosis, gastrointestinal side effects, and symptom relapse after discontinuation. Probiotics may offer adjunctive benefits by modulating the gut ecosystem. The study aimed to evaluate the efficacy of a multi-strain probiotic (Lihuo) with rabeprazole in GERD and its impact on gut microbiota and metabolome. A randomized, double-blind, placebo-controlled trial was conducted in 120 GERD patients assigned to receive rabeprazole with either Lihuo (n = 64) or placebo (n = 56) for 8 weeks, followed by 4 weeks of probiotic or placebo alone. The primary outcome was change in the Reflux Disease Questionnaire (RDQ) score. Secondary outcomes included Gastrointestinal Symptom Rating Scale, endoscopic healing, and multi-omics profiling (shotgun metagenomics, phageome, and untargeted/targeted metabolomics). Compared with the placebo group, the probiotic group exhibited a pronounced 36.51% reduction in RDQ scores after 12 weeks of intervention (P = 0.017), alongside a higher numerical endoscopic healing rate (36.84% vs 12.50%; P = 0.365). Metagenomics revealed enrichment of Bifidobacterium animalis, Lactiplantibacillus plantarum, and Clostridium sp900540255, with reductions in Bacteroides uniformis and Clostridium Q fessum. Metabolomics showed increased γ-aminobutyric acid, succinate, citrulline, and short-chain fatty acids levels, with interesting microbe-metabolite correlations such as Bifidobacterium animalis-γ-aminobutyric acid and Bacteroides fragilis-succinate (r ≥ 0.30, P < 0.01). Our findings support that adjunctive probiotic therapy sustains post-PPI symptom relief, associated with targeted modulation of gut microbiota and bioactive metabolites.IMPORTANCELong-term proton pump inhibitor use in gastroesophageal reflux disease (GERD) may disrupt gut microbiota and cause symptom relapse after discontinuation. We found that adjunctive probiotic therapy sustained reflux reduction post-proton pump inhibitor. Probiotic use enriched beneficial taxa (Bifidobacterium and Lactiplantibacillus plantarum) and increased γ-aminobutyric acid, succinate, citrulline, and short-chain fatty acids. Strong correlations linked microbial shifts to metabolic and clinical improvements. This study demonstrates that adjunctive probiotic therapy enhances symptom control and supports microbial-metabolic homeostasis in GERD.CLINICAL TRIALSThis study is registered with the Chinese Clinial Trial Registry as ChiCTR2000038409.

Whole-genome sequencing has boosted our ability to explore microbial diversity by enabling the recovery of metagenome-assembled genomes (MAGs) directly from environmental DNA. As a result, the vast availability of sequencing data has prompted the development of numerous bioinformatics pipelines for MAG reconstruction, along with challenges to identify the most suitable pipeline to perform the analysis according to the user needs. This report briefly discusses the computational requirements of these pipelines; presents the variety of interfaces, workflow managers, and package managers they feature; and describes the typical modular structure. Also, it provides a compacted technical overview of 41 publicly available pipelines or platforms to build MAGs starting from short and/or long sequences. Moreover, recognizing the overwhelming number of factors to consider when selecting an appropriate pipeline, we introduce an interactive decision-support web application, 2Pipe, that helps users to identify a suitable workflow based on their input data characteristics, desired outcomes, and computational constraints. The tool presents a question-driven interface to customize the recommendation, a pipeline gallery to offer a summarized description, and a pipeline comparison based on key factors used for the questionnaire. Beyond this and foreseeing the release of novel pipelines in the near future, we include a quick form and detailed instructions for developers to append their workflow in the application. Altogether, this review and the application equip the researchers with a general outlook of the growing metagenomics pipeline landscape and guide the users toward deciding the workflow that best fits their expectations and infrastructure.

Acetosyringone (AS), a prototypical syringyl-type monomer of lignin, functions as a model compound for the study of microbial catabolism of S-lignin-derived aromatics. In this study, we present the discovery of a novel metabolic pathway for AS catabolism, initiated by a previously uncharacterized FAD-dependent oxidoreductase, designated AsdA. In contrast to the sole previously documented AS funneling route, which entails side chain modification and conversion to syringic acid, AsdA catalyzes direct hydroxylation of the aromatic core. This represents a mechanistically distinct entry into central metabolism. The identification of this enzyme was achieved through metagenomic and functional analyses of a bacterial consortium enriched on AS as the sole carbon source. The consortium, predominantly comprising Pseudomonas rhizophila, exhibited co-metabolic transformation of the chlorinated pollutants 2,4,6-trichlorophenol (2,4,6-TCP) and 2,6-dichlorophenol. Subsequent functional assays substantiated the hypothesis that AsdA facilitates the transformation of both AS and 2,4,6-TCP. Induction assays employing a biosensor strain derived from the bacterial isolate Pseudomonas rhizophila AS1 confirmed AS-specific upregulation of the asd gene cluster. A survey of publicly available metagenomes has revealed that asdA is narrowly distributed but enriched in rhizosphere environments, pointing to its ecological significance. In summary, the present study unveils a hitherto unrecognized route for AS transformation and identifies an enzyme that exhibits dual functions in lignin-derived aromatic catabolism and environmental pollutant transformation. While the mechanisms underlying TCP degradation are well-established, the specific enzyme responsible for the conversion to 2,6-dichloro-p-hydroquinone had remained elusive-a knowledge gap that has now been addressed by AsdA.IMPORTANCEThe microbial conversion of lignin monomers is central to the global carbon cycle, yet pathways for syringyl-derived aromatics remain poorly resolved. Here, we identify AsdA, an enzyme initiating a previously unrecognized route for acetosyringone catabolism, providing new insight into how this abundant plant-derived compound is integrated into microbial metabolism. Beyond expanding the mechanistic diversity of lignin degradation, AsdA also catalyzes a key step in the transformation of the chlorinated pollutant 2,4,6-trichlorophenol, linking natural and anthropogenic compounds within a shared metabolic framework. The restricted yet rhizosphere-enriched distribution of asdA underscores its specialized role in plant-microbe interactions. By integrating enzyme function, microbial community context, and metagenomic distribution, we demonstrate how a single catalytic activity connects metabolic pathways and ecosystem processes, illustrating a multi-scale systems biology perspective on aromatic compound turnover.

Microbial iron (Fe) redox cycling underpins key biogeochemical processes, yet the functional diversity, ecological roles, and trait architectures of iron-transforming microbes remain poorly synthesized across global environments. Here, we present a systematic review and trait-based meta-analysis of 387 microbial taxa spanning 314 studies and 76 years of research, integrating phenotypic, genomic, and environmental data to define ecologically coherent microbial iron redox cycle guilds. Rather than relying on taxonomy, our framework delineates first-order functional guilds-Fe(III) reducers, Fe(II) oxidizers, and dual-capacity Fe oxidizers/reducers-and resolves second-order guilds based on trait syndromes, such as acidophily, redox flexibility, or metabolic breadth. Trait profiling revealed that iron-cycling capacities frequently transcend phylogenetic boundaries, with multiple guilds converging in chemically stratified hotspots like hot springs, hydrothermal vents, and acid mine drainages. Dual-capacity Fe oxidizers/reducers (e.g., Acidithiobacillus ferrooxidans and Metallosphaera sedula) emerged as overlooked mediators of "cryptic" iron cycling, possessing genomic repertoires capable of toggling between oxidative and reductive modes in response to redox oscillations. Hierarchical clustering and kernel density analyses of ecophysiological traits highlighted niche partitioning along key environmental filters, including pH, iron availability, salinity, and temperature. Collectively, this work introduces the Guild Exploitation Pattern as a conceptual lens for understanding iron microbiome assembly, providing a data-driven foundation for predicting microbial contributions to iron cycling under changing environmental conditions.

Importance: Iron redox reactions shape nutrient turnover, contaminant mobility, and primary productivity, yet the microbes driving these processes are often studied in isolation. By integrating decades of data into a trait-based guild framework, we reveal the ecophysiological diversity and niche differentiation of microbial iron redox cycling taxa across environments. Our synthesis exposes major gaps, such as limited trait data for >80% of dual-capacity Fe oxidizing/reducing species and highlights the need for functional trait surveys to complement metagenomics and cultivation efforts. The guild framework presented here advances predictive microbial ecology by linking metabolic traits with environmental gradients, offering a robust foundation for incorporating iron cycling into ecosystem models and biogeochemical forecasts.

Mobile genetic elements (MGEs) are major drivers of horizontal gene transfer, including the spread of antimicrobial resistance (AMR) genes. However, determining the microbial host of an MGE in complex microbiomes remains challenging. Here, we spike a niche-aspecific Bacillus velezensis strain carrying a plasmid and linear phage-plasmid into a batch bioreactor simulating the human gut, and use it as a spike-in control to assess the performance of Hi-C sequencing and Oxford Nanopore Technologies (ONT)-enabled DNA methylation detection to identify MGE-host pairs. To improve recovery of low-abundance genomes, we used a novel ONT adaptive sampling (AS) strategy that depletes de novo assembled, sample-specific high-abundance contigs, rather than relying on reference genomes. This approach led to an approximately twofold enrichment of low-abundance replicons, including the spike-in strain. Methylation-based host assignment failed for the B. velezensis MGEs, likely due to the absence of DNA methylation. In contrast, Hi-C successfully linked the phage-plasmid to its host, but not the plasmid, likely due to non-intact cells, and only after removing artefactual signals through bioinformatic processing. For a native Escherichia coli strain, Hi-C and methylation data linked it to two plasmids. Selective isolation and whole-genome sequencing of both the native E. coli and spike-in B. velezensis then confirmed the metagenomic observations. Our results highlight that Hi-C and methylation data can provide powerful insights into MGE-host associations, but their interpretation requires careful computational analysis and biological validation. Moreover, our AS strategy offers a cost-efficient method to boost coverage of low-abundance genomes, improving metagenomic investigation of MGEs in complex microbiomes.

Importance: Mobile genetic elements are important contributors to horizontal gene transfer, including of antimicrobial resistance genes. Understanding which microbes carry these mobile elements is vital to assess the spread of resistance. Here, we use a nanopore adaptive sampling approach to increase detection of low-abundance bacteria and mobile elements and use DNA methylation detection and Hi-C sequencing to determine mobile element hosts. By introducing a known bacterium and isolating a native strain, we could evaluate the performance of these methods, indicating that although powerful, they require careful experimental design, interpretation, and validation. However, when combined, these approaches enable a comprehensive investigation of mobile elements and gene transfer dynamics in complex environments.