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ObjectiveWe aim to compare the effects of proton pump inhibitors (PPIs) and histamine-2 receptor antagonists (H2RAs) on the gut microbiota through longitudinal analysis.DesignHealthy volunteers were randomly assigned to receive either PPI (n=23) or H2RA (n=26) daily for seven consecutive days. We collected oral (saliva) and faecal samples before and after the intervention for metagenomic next-generation sequencing. We analysed intervention-induced alterations in the oral and gut microbiome including microbial abundance and growth rates, oral-to-gut transmissions, and compared differences between the PPI and H2RA groups.ResultsBoth interventions disrupted the gut microbiota, with PPIs demonstrating more pronounced effects. PPI usage led to a significantly higher extent of oral-to-gut transmission and promoted the growth of specific oral microbes in the gut. This led to a significant increase in both the number and total abundance of oral species present in the gut, including the identification of known disease-associated species like Fusobacterium nucleatum and Streptococcus anginosus. Overall, gut microbiome-based machine learning classifiers could accurately distinguish PPI from non-PPI users, achieving an area under the receiver operating characteristic curve (AUROC) of 0.924, in contrast to an AUROC of 0.509 for H2RA versus non-H2RA users.ConclusionOur study provides evidence that PPIs have a greater impact on the gut microbiome and oral-to-gut transmission than H2RAs, shedding light on the mechanism underlying the higher risk of certain diseases associated with prolonged PPI use.Trial registration numberChiCTR2300072310.

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

Buffalo is an important livestock species. Here, we present a comprehensive metagenomic survey of the microbial communities along the buffalo digestive tract. We analysed 695 samples covering eight different sites in three compartments (four-chambered stomach, intestine, and rectum). We mapped ~85% of the raw sequence reads to 4,960 strain-level metagenome-assembled genomes (MAGs) and 3,255 species-level MAGs, 90% of which appear to correspond to new species. In addition, we annotated over 5.8 million nonredundant proteins from the MAGs. In comparison with the rumen microbiome of cattle, the buffalo microbiota seems to present greater potential for fibre degradation and less potential for methane production. Our catalogue of microbial genomes and the encoded proteins provides insights into microbial functions and interactions at distinct sites along the buffalo digestive tract. Buffalo is an important livestock in Asia. Here, the authors present a comprehensive metagenomic analysis of the microbial communities present in different sites and compartments along the buffalo digestive tract.

Silicone rubber mold (SRM) is capable of reducing the cost and time in a new product development phase and has many applications for the pilot runs. Unfortunately, the SRM after injection molding has a poor cooling efficiency due to its low thermal conductivity. To improve the cooling efficiency, the thermal conductivity of the SRM was improved by adding fillers into the SRM. An optimal recipe for fabricating a high cooling efficiency low-pressure injection mold with conformal cooling channel fabricated by fused deposition modeling technology was proposed and implemented. This study proposes a recipe combining 52.6 wt.% aluminum powder, 5.3 wt.% graphite powder, and 42.1 wt.% liquid silicon rubber can be used to make SRM with excellent cooling efficiency. The price–performance ratio of this SRM made by the proposed recipe is around 55. The thermal conductivity of the SRM made by the proposed recipe can be increased by up to 77.6% compared with convention SRM. In addition, the actual cooling time of the injection molded product can be shortened up to 69.1% compared with the conventional SRM. The actual cooling time obtained by the experiment is in good agreement with the simulation results with the relative error rate about 20%.

Evaluating the quality of metagenomic assemblies is important for constructing reliable metagenome-assembled genomes and downstream analyses. Here, we present metaMIC ( https://github.com/ZhaoXM-Lab/metaMIC ), a machine learning-based tool for identifying and correcting misassemblies in metagenomic assemblies. Benchmarking results on both simulated and real datasets demonstrate that metaMIC outperforms existing tools when identifying misassembled contigs. Furthermore, metaMIC is able to localize the misassembly breakpoints, and the correction of misassemblies by splitting at misassembly breakpoints can improve downstream scaffolding and binning results.

BackgroundNatural killer/T-cell lymphoma (NKTCL) is a highly aggressive malignancy with a dismal prognosis, and gaps remain in understanding the determinants influencing disease outcomes.ObjectiveTo characterise the gut microbiota feature and identify potential probiotics that could ameliorate the development of NKTCL.DesignThis cross-sectional study employed shotgun metagenomic sequencing to profile the gut microbiota in two Chinese NKTCL cohorts, with validation conducted in an independent Korean cohort. Univariable and multivariable Cox proportional hazards analyses were applied to assess associations between identified marker species and patient outcomes. Tumour-suppressing effects were investigated using comprehensive in vivo and in vitro models. In addition, metabolomics, RNA sequencing, chromatin immunoprecipitation sequencing, Western blot analysis, immunohistochemistry and lentiviral-mediated gene knockdown system were used to elucidate the underlying mechanisms.ResultsWe first unveiled significant gut microbiota dysbiosis in NKTCL patients, prominently marked by a notable reduction in Faecalibacterium prausnitzii which correlated strongly with shorter survival among patients. Subsequently, we substantiated the antitumour properties of F. prausnitzii in NKTCL mouse models. Furthermore, F. prausnitzii culture supernatant demonstrated significant efficacy in inhibiting NKTCL cell growth. Metabolomics analysis revealed butyrate as a critical metabolite underlying these tumour-suppressing effects, validated in three human NKTCL cell lines and multiple tumour-bearing mouse models. Mechanistically, butyrate suppressed the activation of Janus kinase-signal transducer and activator of transcription pathway through enhancing histone acetylation, promoting the expression of suppressor of cytokine signalling 1.ConclusionThese findings uncover a distinctive gut microbiota profile in NKTCL and provide a novel perspective on leveraging the therapeutic potential of F. prausnitzii to ameliorate this malignancy.

Some microbial eukaryotes, such as the extremophilic red alga Galdieria sulphuraria, live in hot, toxic metal-rich, acidic environments. To elucidate the underlying molecular mechanisms of adaptation, we sequenced the 13.7-megabase genome of G. sulphuraria. This alga shows an enormous metabolic flexibility, growing either photoautotrophically or heterotrophically on more than 50 carbon sources. Environmental adaptation seems to have been facilitated by horizontal gene transfer from various bacteria and archaea, often followed by gene family expansion. At least 5% of protein-coding genes of G. sulphuraria were probably acquired horizontally. These proteins are involved in ecologically important processes ranging from heavy-metal detoxification to glycerol uptake and metabolism. Thus, our findings show that a pan-domain gene pool has facilitated environmental adaptation in this unicellular eukaryote.

Background Compromised intestinal barrier (CIB) has been associated with many enteropathies, including colorectal cancer (CRC) and inflammatory bowel disease (IBD). We hypothesized that CIB could lead to increased host-derived contents including epithelial cells into the gut, change its physio-metabolic properties, and globally alter microbial community and metabolic capacities. Results Consistently, we found host DNA contents (HDCs), calculated as the percentage of metagenomic sequencing reads mapped to the host genome, were significantly elevated in patients of CRC and Crohn’s disease (CD). Consistent with our hypothesis, we found that HDC correlated with microbial- and metabolic-biomarkers of these diseases, contributed significantly to machine-learning models for patient stratification and was consequently ranked as a top contributor. CD patients with treatment could partially reverse the changes of many CD-signature species over time, with reduced HDC and fecal calprotectin (FCP) levels. Strikingly, HDC showed stronger correlations with the reversing changes of the CD-related species than FCP, and contributed greatly in classifying treatment responses, suggesting that it was also a biomarker for effective treatment. Conclusions Together, we revealed that association between HDCs and gut dysbiosis, and identified HDC as a novel biomarker from fecal metagenomics for diagnosis and effective treatment of intestinal diseases; our results also suggested that host-derived contents may have greater impact on gut microbiota than previously anticipated.