RESUMEN
Characterization of microbial community metabolic output is crucial to understanding their functions. Construction of genome-scale metabolic models from metagenome-assembled genomes (MAG) has enabled prediction of metabolite production by microbial communities, yet little is known about their accuracy. Here, we examined the performance of two approaches for metabolite prediction from metagenomes, one that is MAG-guided and another that is taxonomic reference-guided. We applied both on shotgun metagenomics data from human and environmental samples, and validated findings in the human samples using untargeted metabolomics. We found that in human samples, where taxonomic profiling is optimized and reference genomes are readily available, when number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach. The two approaches showed significant overlap but each identified metabolites not predicted in the other. Pathway enrichment analyses identified significant differences in inferences derived from data based on the approach, highlighting the need for caution in interpretation. In environmental samples, when the number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach for total metabolites in both sample types and non-redundant metabolites in seawater samples. Nonetheless, as was observed for the human samples, the approaches overlapped substantially but also predicted metabolites not observed in the other. Our findings report on utility of a complementary input to genome-scale metabolic model construction that is less computationally intensive forgoing MAG assembly and refinement, and that can be applied on shallow shotgun sequencing where MAGs cannot be generated.IMPORTANCELittle is known about the accuracy of genome-scale metabolic models (GEMs) of microbial communities despite their influence on inferring community metabolic outputs and culture conditions. The performance of GEMs for metabolite prediction from metagenomes was assessed by applying two approaches on shotgun metagenomics data from human and environmental samples, and validating findings in the human samples using untargeted metabolomics. The performance of the approach was found to be dependent on sample type, but collectively, the reference-guided approach predicted more metabolites than the MAG-guided approach. Despite the differences, the predictions from the approaches overlapped substantially but each identified metabolites not predicted in the other. We found significant differences in biological inferences based on the approach, with some examples of uniquely enriched pathways in one group being invalidated when using the alternative approach, highlighting the need for caution in interpretation of GEMs.
RESUMEN
Host molecular responses to fecal microbiota transplantation (FMT) in ulcerative colitis are not well understood. Here, we profile the human colonic mucosal transcriptome prior to and following FMT or placebo to identify molecules regulated during disease remission. FMT alters the transcriptome above the effect of placebo (n = 75 vs 3 genes, q < 0.05), including modulation of structural, metabolic and inflammatory pathways. This response is attributed to responders with no consistency observed in non-responders. Regulated pathways in responders include tight junctions, calcium signalling and xenobiotic metabolism. Genes significantly regulated longitudinally in responders post-FMT could discriminate them from responders and non-responders at baseline and non-responders post-FMT, with GBP5 and IRF4 downregulation being associated with remission. Female mice with a deletion of GBP5 are more resistant to developing colitis than their wild-type littermates, showing higher colonic IRF4 phosphorylation. The colonic mucosal response discriminates UC remission following FMT, with GBP5 playing a detrimental role in colitis.
Asunto(s)
Colitis Ulcerosa , Trasplante de Microbiota Fecal , Animales , Femenino , Humanos , Ratones , Heces , Proteínas de Unión al GTP , Mucosa Intestinal , Resultado del TratamientoRESUMEN
Little is known of the relationships among paediatric upper gastrointestinal microbiotas, and the impact of medication use and disease on their diversity. Here, we investigated the diversity of three microbiotas in the upper gastrointestinal tract of paediatric patients in relation to each other and to host factors. Oral, oesophageal and gastric microbiotas from a prospective paediatric cohort (n=54) were profiled using the 16S rRNA gene and ITS2 amplicon sequencing. 16S rRNA gene amplicon sequencing of oesophageal biopsies from a retrospective paediatric cohort (n=96) and shotgun metagenomics data from oesophageal brushings (n=88) were employed for genomic signature validation. Bacterial diversity and composition showed substantial differences across oral, oesophageal and gastric fluid samples that were not replicated for fungi, and the presence of reflux led to increased homogeneity in the bacterial component of these three microbiotas. The oral and oesophageal microbiotas were associated with age, sex, history of oesophageal atresia and presence of oesophageal metaplasia, with the latter characterized by Prevotella enrichment. Proton pump inhibitor use was associated with increased oral bacterial richness in the gastric fluid, and this correlated with increased levels of gastric pro-inflammatory cytokines. Profiling of oesophageal biopsies from a retrospective paediatric cohort confirmed an increased Prevotella prevalence in samples with metaplasia. Analysis of metagenome-derived oesophageal Prevotella melaninogenica genomes identified strain-specific features that were significantly increased in prevalence in samples with metaplasia. Prevotella enrichment is a signature associated with paediatric oesophageal metaplasia, and proton pump inhibitor use substantially alters the paediatric gastric microenvironment.