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de Vos, R. C. H.

Publications and source records attributed to de Vos, R. C. H..

2 recordsLinked to original sources

An optimised approach to evaluate variability in gut health markers in healthy adults.

Despite advances in gut health research, the variability of important gut markers within individuals over time remains underexplored. We investigated the intra-individual variation of various faecal gut health markers using an optimised processing protocol aimed at reducing variability. Faecal samples from ten healthy adults over three consecutive days demonstrated marker-specific intra-individual coefficients of variation (CV%), namely: stool consistency (16.5%), water content (5.7%), pH (3.9%), total SCFAs (17.2%), total BCFAs (27.4%), total bacteria and fungi copies (40.6% and 66.7%), calprotectin and myeloperoxidase (63.8% and 106.5%), and untargeted metabolites (on average 40%). For thirteen microbiota genera, including Bifidobacterium and Akkermansia, variability exceeded 30%, whereas microbiota diversity was less variable (Phylogenetic Diversity 3.3%, Inverse Simpson 17.2%). Mill-homogenisation of frozen faeces significantly reduced the replicates CV% for total SCFAs (20.4% to 7.5%) and total BCFAs (15.9% to 7.8%), and untargeted metabolites compared to only faecal hammering, without altering mean concentrations. Our results show the potential need for repeated sampling to accurately represent specific gut health markers. We also demonstrated the effectiveness of optimised preprocessing of stool samples in reducing overall analytical variability.

microbiology↗

Local adaptation shapes metabolic diversity in the global population of Arabidopsis thaliana

The biosynthesis, structure and accumulation of secondary metabolites in plants are largely controlled by genetic factors, which can vary substantially among genotypes within a species. Here we studied a global population of Arabidopsis thaliana accessions for qualitative and quantitative variation in volatile and non-volatile secondary metabolites using essentially untargeted metabolomics. Genome-wide association (GWA) mapping revealed that metabolic variation mainly traces back to genetic variation in dedicated biosynthesis genes. Effect sizes of genetic variants, estimated by a Bayesian procedure, indicate that most of the genetic variation in the accumulation of secondary metabolites is explained by large-effect genes and defined by multiple polymorphisms. The various genetic variants resulted from independent mutation events and combined into distinctive haplotypes, which are representative for specific geographical regions. A strong relationship between the effect-size of regulatory loci, their allele frequencies and fixation index indicates that selection forces discriminate between haplotypes, resulting in different phytochemical profiles. Finally, we demonstrate that haplotype frequencies deviate from neutral theory predictions, suggesting that metabolic profiles are shaped by local adaptation and co-evolution of independent loci.

genetics↗