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Lifestyle factors, such as diet, strongly influence the structure, diversity, and composition of the microbiome. While we have witnessed over the last several years a resurgence of interest in fermented foods, no study has specifically explored the effects of their consumption on gut microbiota in large cohorts. To assess whether the consumption of fermented foods is associated with a systematic signal in the gut microbiome and metabolome, we used a multi-omic approach (16S rRNA amplicon sequencing, metagenomic sequencing, and untargeted mass spectrometry) to analyze stool samples from 6,811 individuals from the American Gut Project, including 115 individuals specifically recruited for their frequency of fermented food consumption for a targeted 4-week longitudinal study. We observed subtle but statistically significant differences between consumers and nonconsumers in beta diversity as well as differential taxa between the two groups. We found that the metabolome of fermented food consumers was enriched with conjugated linoleic acid (CLA), a putatively health-promoting molecule. Cross-omic analyses between metagenomic sequencing and mass spectrometry suggest that CLA may be driven by taxa associated with fermented food consumers. Collectively, we found modest yet persistent signatures associated with fermented food consumption that appear present in multiple -omic types which motivate further investigation of how different types of fermented food impact the gut microbiome and overall health.IMPORTANCE Public interest in the effects of fermented food on the human gut microbiome is high, but limited studies have explored the association between fermented food consumption and the gut microbiome in large cohorts. Here, we used a combination of omics-based analyses to study the relationship between the microbiome and fermented food consumption in thousands of people using both cross-sectional and longitudinal data. We found that fermented food consumers have subtle differences in their gut microbiota structure, which is enriched in conjugated linoleic acid, thought to be beneficial. The results suggest that further studies of specific kinds of fermented food and their impacts on the microbiome and health will be useful.

A data fusion approach was applied to a commercial honey data set analysed by H-nuclear magnetic resonance (NMR) 400 MHz and liquid chromatography-high resolution mass spectrometry (LC-HRMS). The latter was performed using two types of mass spectrometers: an Orbitrap-MS and a time of flight (TOF)-MS. Fifty-six honey samples from four monofloral origins (acacia, orange blossom, lavender and eucalyptus) and multifloral sources from various geographical origins were analysed using the three instruments. The discriminating power of the results was examined by PCA first considering each technique separately, and then combining NMR and LC-HRMS together with or without variable selection. It was shown that the discriminating potential is increased through the data fusion, allowing for a better separation of eucalyptus, orange blossom and lavender. The NMR-Orbitrap-MS and NMR-TOF-MS mid-level fusion models with variable selection were preferred as a good discrimination was obtained with no misclassification observed for the latter. This study opens the path to new comprehensive food profiling approaches combining more than one technique in order to benefit from the advantages of several technologies. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]