Gut Microbes最新文献

Excessive intake of added sugars is a global public health concern, given its established links with cardiometabolic disease and other chronic conditions. Emerging evidence suggests that the gut microbiota might mediate the harms of high sugar intake. In this review, we summarize evidence from animal and human studies regarding the impact of added sugar intake on gut microbiota diversity and composition, and discuss potential mechanisms linking sugar-induced microbial changes to health outcomes. Added sugars, including glucose, fructose, and sucrose, can alter gut microbial diversity, enrich sugar-utilizing taxa, and deplete short-chain fatty acid-producing bacteria. These microbial changes may impair gut barrier integrity, increase luminal oxygen and alternative electron acceptors under inflammatory conditions, reduce short-chain fatty acid production, alter bile acid and amino acid metabolism, and promote translocation of endotoxin across the gut barrier into the bloodstream. Collectively, these pathways may link added sugar intake to irritable bowel syndrome, obesity, liver steatosis, diabetes, and cardiovascular diseases. However, inconsistent results on alterations in the gut microbiota related to added sugar intake were observed across studies, which may be due to differences in sugar dose and form (liquid vs. solid), as well as population variation in background diet, host genetics, and gut microbial ecology. Future research should focus on mechanistic investigations, characterization of inter-individual variability in response to added sugar intake, and clinical studies to assess whether dietary or therapeutic interventions can reverse sugar-induced gut microbial changes and improve host health outcomes.

MICOMWeb is a user-friendly website for modeling microbial community metabolism in the human gut. This website tackles three constraints when generating in silico metagenome-scale metabolic models: i) the prior Python user knowledge for metabolic modeling using flux balance analysis with the MICOM Python package, ii) predefined and user-defined diets to generate ad hoc metabolic models, and iii) the high-throughput computational infrastructure required to obtain the simulated growth and metabolic exchange fluxes, using real abundance from metagenomic shotgun or 16S amplicon sequencing; we present MICOMWeb's features to easily run in silico experiments as a functional hypothesis generator for experimental validation on three previously published databases. MICOMWeb has a constant run-time independent of the number of samples provided and database complexity. In practical terms, this behavior is upper-bounded by the sample with the greatest microbiota diversity, i.e., the sample with the largest metabolic reconstruction model size. The evidence suggests that the bigger the database, the better the MICOMWeb performs compared to MICOM in terms of consumed RAM (from 3.52 up to 7.13 folds) and total execution time (from 10.87 up to 205.05 folds).

Background: Staphylococcus (S.) aureus remains a frequent pathogen for neonatal late-onset bloodstream infections (BSIs). The impact of colonization screening on BSI incidence is less understood.

Methods: We assessed the epidemiology of late-onset S. aureus BSI in two independent multicenter cohorts of preterm infants born at < 33 weeks' gestation, the German Neonatal Network (GNN, very low birth weight infants) and PRIMAL (infants with a gestational age 28-32 weeks). In the PRIMAL cohort, we determined S. aureus colonization in fecal samples by culture and shotgun metagenomic sequencing (metaG) during the first year of life. In addition, we integrated publicly available metaG data from preterm infant cohorts born at 23-34 weeks' gestation.

Results: Late-onset S. aureus BSI was noted in 1.5% (336/21491) in preterm infants in the GNN cohort and 0.5% (3/638) in the PRIMAL cohort, respectively. At day 30 of life, 7.6% (42/553) of fecal samples were positive for S. aureus, while available metaG data of corresponding samples revealed S. aureus positivity in 36.6% (159/434). Every 10-fold increase in S. aureus relative abundance (metaG) was associated with a 2.9-fold higher odds of S. aureus detection in blood culture. We also confirmed S. aureus detection in 22% (393/1782) of samples across several published cohorts of preterm infants by metaG, while 95 samples carried at least one Staphylococcus-specific virulence gene (SVG).

Conclusion: Our study demonstrates that metagenomic quantification of pathobionts such as S. aureus in intestinal samples provides a stronger predictor of colonization than culture. Future prevention strategies should focus on promoting S. aureus colonization resistance through microbiome-informed approaches.

Next-generation sequencing (NGS) data usage is widespread, but its compositional nature poses challenges. We evaluated four normalization methods (relative abundance, CLR, TMM, DESeq2) for identifying true signals in compositional microbiota data using simulations. Two experiments were conducted: one with only increases in specific taxa, and a 1:1 increase/decrease in specific taxa. Simulated sequencing produced compositional data, which were normalized using the four methods. The study compared absolute abundance data and the normalized compositional data using variance explained and false discovery rates. All normalization methods showed decreased variance explained and increased false positives and negatives compared to absolute abundance data. CLR, TMM, and DESeq2 did not improve over relative abundance data and sometimes worsened false discovery rates. The study highlights that false positives and negatives are common in compositional NGS datasets, and current normalization methods do not consistently address these issues. Compositionality artefacts should be considered when interpreting NGS results and obtaining absolute abundances of features/taxa is recommended to distinguish biological signals from artefacts.

The small intestine is a key site for nutrient sensing and host-microbiota interactions, yet how it functionally adapts to dietary changes remains poorly understood. Using a translational porcine model, we investigated the impact of moderate dietary fat increase on the gut microbiota and metabolome across five locations in the digestive tract. Pigs were fed either a low-fat (3%) or a medium-fat (12%) diet for 12 weeks without developing obesity. Multiomics profiling revealed significant dietary effects on bile and duodenojejunal metabolomic profiles, particularly lipid and stachydrine, with notable sex-specific responses. These metabolite shifts were accompanied by segment- and sex-specific changes in microbial communities, including the depletion of metabolically beneficial taxa (e.g., Limosilactobacillus reuteri and Lactobacillus johnsonii) and the enrichment of bacteria linked to metabolic dysfunction (e.g., Streptococcus alactolyticus). In the small intestine lumen, multiple bacterial-metabolite associations correlated with host metabolic markers, suggesting early diet-induced alterations with potential relevance for metabolic disease onset. Our findings position the small intestine as a critical site for early diet-induced microbial and metabolic remodeling, potentially influencing metabolic disease risk and shaping the downstream intestinal environment. This study also underscores the importance of considering both region- and sex-specific responses in diet-microbiota-metabolome research.

Early-life exposure to colibactin-producing pks+ gut bacteria is hypothesized to imprint mutations on the colorectal epithelium, increasing the risk of colorectal cancer later in life. We demonstrate an extremely high prevalence of pks+  bacteria (>50% of infants) during the first 2 y of life, suggesting carriage is likely normal during early-life microbiome development. Further investigation is required to understand the circumstances in which carriage can lead to mutagenesis.

Exposure to food antigens that can trigger aberrant type-2 immunity is ubiquitous. However, only a subset of individuals develops allergy, implicating environmental drivers of sensitization, among which diet- and antibiotic-induced changes in intestinal microbiome activity stand out for their ability to alter host-microbe interactions at the gut mucosa. While efforts seek microbial signatures and microbiome-based therapies, the same microbes or pathways may foster either tolerance or sensitization depending on host and environmental context, which must be considered when designing interventions. We synthesize recent molecular insights into mucosal host-microbiome crosstalk, focusing on regulatory T cells, the colonic mucus barrier, and host immunoglobulins (IgA and IgE). Using examples of microbiome functional duality in which diet-driven altered microbial activities and secreted molecules such as lipopolysaccharides and flagellins yield opposing effects, we discuss the context-dependent mechanisms by which microbes either protect against or promote food allergy.