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Sinks contaminated with opportunistic pathogens are a source of hospital-acquired infections, responsible for morbidity and mortality in neonatal intensive care units (NICUs). Understanding pathogen behavior in sinks is essential for preventing their spread. Only a few studies have examined how sink environments affect pathogen distribution through changes in drain microbiota. This research uses an integrative approach to study three major bacterial pathogens: Pseudomonas aeruginosa, Stenotrophomonas maltophilia, and Serratia marcescens. Sink drains in two NICUs were sampled during 2-month and 5-month periods. The diversity and abundance of opportunistic pathogens were determined at the genotypic level. Their occurrence was analyzed considering microbial communities, water parameters, faucet design, and sink usage. P. aeruginosa, S. marcescens, and S. maltophilia were found in 47%, 39%, and 67% of drain samples, respectively. Low genotype diversity was observed within sinks, with 1-3 genotypes per species/sample. Dominant genotypes persisted throughout the sampling periods, showing the persistence of opportunistic pathogen strains in drains. Quantification of the studied bacterial sequence types ranged from 10³ to 10⁷ DNA copies/mL. The heterogeneous spatial distribution of the three species between individual sink drains was primarily attributed to changes in community composition, chlorine concentrations, and faucet design. We isolated a strain of Delftia tsuruhatensis (Dt1S33), whose presence in the sink environment was negatively correlated with the three opportunistic pathogens. Dt1S33 reduced the capacity of the pathogens to form biofilms in laboratory co-cultures. These findings underscore the key roles of biotic and abiotic factors in the colonization of sink drains by pathogens.IMPORTANCEHospital sinks are critical reservoirs for opportunistic pathogens (OPs), increasing the risk of healthcare-associated infections, especially in vulnerable populations such as neonatal intensive care unit (NICU) patients. Our study found that 39%-67% of sink drains were persistently colonized by Pseudomonas aeruginosa, Serratia marcescens, and Stenotrophomonas maltophilia, with a limited number of genotypes dominating for months. Colonization patterns in drains varied between NICUs, mainly influenced by microbial community composition and sink design. Notably, Delftia tsuruhatensis presence was negatively correlated with OP colonization and inhibited OP biofilm formation in vitro. These results highlight the interplay of abiotic and biotic factors in sink colonization and suggest that antagonistic bacteria could help reduce pathogen persistence. Understanding these dynamics is crucial for developing targeted interventions to mitigate infection risks in high-risk hospital settings.

The human gastrointestinal tract is home to a diverse community of microorganisms from all domains of life, collectively referred to as the gut microbiome. While gut bacteria have been studied extensively in relation to human host health and physiology, other constituents remain underexplored. This includes the gut virome, the collection of bacteriophages, eukaryotic viruses, and other mobile genetic elements present in the intestine. Like gut bacteria, the gut virome has been causatively linked to human health and disease. However, the gut virome is substantially more difficult to characterize, given its high diversity and complexity, as well as multiple challenges related to in vitro cultivation and in silico detection and annotation. In this mini-review, we describe various methodologies for examining the gut virome using both culture-dependent and culture-independent tools. We highlight in vitro and in vivo approaches to cultivate viruses and characterize viral-bacterial host dynamics, as well as high-throughput screens to interrogate these relationships. We also outline a general workflow for identifying and characterizing uncultivated viral genomes from fecal metagenomes, along with several key considerations throughout the process. More broadly, we aim to highlight the opportunities to synergize and streamline wet- and dry-lab techniques to robustly and comprehensively interrogate the human gut virome.

The human gut microbiome is a dynamic ecosystem. Host behaviors (e.g., diet) provide a regular source of environmental variation that induces fluctuations in the abundances of resident microbiota. Despite these displacements, microbial community members remain highly resilient. Population abundances tend to fluctuate around a characteristic steady-state over long timescales in healthy human hosts. These temporary excursions from steady-state abundances, known as sojourn trajectories, have the potential to inform our understanding of the fundamental dynamics of the microbiome. However, to our knowledge, the macroecology of sojourn trajectories has yet to be systematically characterized. In this study, we leverage theoretical tools from the study of random walks to characterize the duration of sojourn trajectories, their shape, and the degree that diverse community members exhibit similar qualitative and quantitative dynamics. We apply the stochastic logistic model as a theoretical lens for interpreting our empirical observations. We find that the typical timescale of a sojourn trajectory does not depend on the mean abundance of a community member (i.e., carrying capacity), although it is strongly related to its coefficient of variation (i.e., environmental noise). This work provides fundamental insight into the dynamics, timescales, and fluctuations exhibited by diverse microbial communities.IMPORTANCEMicroorganisms in the human gut often fluctuate around a characteristic abundance in healthy hosts over extended periods of time. These typical abundances can be viewed as steady states, meaning that fluctuating abundances do not continue towards extinction or dominance but rather return to a specific value over a typical timescale. Here, we empirically characterize the (i) length (i.e., number of days), (ii) relationship between length and height, and (iii) typical deviation of a sojourn trajectory. These three patterns can be explained and unified through an established minimal model of ecological dynamics, the stochastic logistic model of growth.

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.