ArticleLaboratory investigation; a journal of technical methods and pathology2024
Metabolomic and Transcriptomic Correlative Analyses in Germ-Free Mice Link Lacticaseibacillus rhamnosus GG-Associated Metabolites to Host Intestinal Fatty Acid Metabolism and β-Oxidation.
Article in Laboratory investigation; a journal of technical methods and pathology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Article
- The Impact of Bioactive Molecules from Probiotics on Child Health: A Comprehensive Review.Nutrients · 2024Review
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
Intestinal microbiota confers susceptibility to diet-induced obesity, yet many probiotic species that synthesize tryptophan (trp) actually attenuate this effect, although the underlying mechanisms are unclear. We monocolonized germ-free mice with a widely consumed probiotic Lacticaseibacillus rhamnosus GG (LGG) under trp-free or -sufficient dietary conditions. We obtained untargeted metabolomics from the mouse feces and serum using liquid chromatography-mass spectrometry and obtained intestinal transcriptomic profiles via bulk-RNA sequencing. When comparing LGG-monocolonized mice with germ-free mice, we found a synergy between LGG and dietary trp in markedly promoting the transcriptome of fatty acid metabolism and β-oxidation. Upregulation was specific and was not observed in transcriptomes of trp-fed conventional mice and mice monocolonized with Ruminococcus gnavus. Metabolomics showed that fecal and serum metabolites were also modified by LGG-host-trp interaction. We developed an R-Script-based MEtabolome-TRanscriptome Correlation Analysis algorithm and uncovered LGG- and trp-dependent metabolites that were positively or negatively correlated with fatty acid metabolism and β-oxidation gene networks. This high-throughput metabolome-transcriptome correlation strategy can be used in similar investigations to reveal potential interactions between specific metabolites and functional or disease-related transcriptomic networks.
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Registered trials
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