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vazquez, m.

Publications and source records attributed to vazquez, m..

2 recordsLinked to original sources

Exploring the interplay of complex carbohydrate intake, the microbiome CAZymes pool and short-chain fatty acid production in the human gut: insights from different cohorts in the Argentine population

Carbohydrate-active enzyme (CAZyme) activity in the gut microbiome has significant implications for health, including the release of nutrients otherwise inaccessible to the host and the enhancement of digestive efficiency. The primary end products of indigestible carbohydrate fermentation are short-chain fatty acids (SCFAs). We hypothesized that increased dietary fiber consumption could lead to greater SCFA production in the human gut. To investigate this, we examined the relationship between complex carbohydrate intake, CAZyme activity in the human gut microbiome, and SCFA production at the whole metagenomic level across three cohorts: a healthy reference-controlled cohort, an average cohort of individuals living in industrialized cities, and a cohort of patients with inflammatory bowel disease (IBD). Metagenomic sequencing and bioinformatic analyses were utilized to assess the diversity, abundance, and functionality of CAZymes, as well as the metabolic capacity for SCFA production. The average cohort exhibited higher alpha diversity of CAZyme families compared to the reference-controlled cohort, although subfamily composition was similar between both. A moderate negative correlation was identified between CAZyme abundance and SCFA production, indicating that a higher number of these enzymes does not directly translate to increased SCFA synthesis. In IBD patients, a decrease in the diversity and composition of CAZyme subfamilies was observed, suggesting a disruption in enzymatic functions associated with the disease. However, the overall functionality of CAZymes remained relatively stable across different health conditions, highlighting the resilience of the gut microbiome for these functions. These findings deepen our understanding of the gut microbiomes role in health and disease, emphasizing that despite variations in microbial diversity, key enzymatic functions persist. The study underscores the complexity of the non-linear relationship between complex carbohydrate metabolism and SCFA production, laying the groundwork for future research on microbiome-targeted therapeutic/dietary profile interventions in both non-disease and chronic diseases conditions.

genomics↗

Generation of a robust reference gut microbiome dataset for an urban population in Argentina optimized by a machine learning approach

Robust human microbiome analysis requires robust reference datasets obtained from a population that presents similar habits to the one we are trying to assess. We reported here the construction of a robust reference dataset of healthy individuals from urban and surrounding rural areas of the Argentine population. We screened 200 volunteers with strict inclusion/exclusion criteria. Volunteers were also screened with routine blood clinical test analysis and a complete metabolome profile from blood and urine to remove outliers before inclusion in the Next Generation Sequencing dataset. Sequencing was done on an Illumina MiSeq using the V3-V4 16S rRNA. Using these data, we performed de novo community structure prediction by applying clustering methodology based on seven distance and dissimilarity metrics and two clustering methods to the reference set. Using this approach, we discovered four different enterotypes in this community structure. We then trained a model for the classification of any new sample into the structure of the reference set. Once the new sample was classified, it was compared to the reference ranges of both the enterotype-specific subset and the whole reference set. Finally, we challenged the robustness of this methodology using samples from two test case volunteers with clinically proven gut dysbiosis in a time-series sampling with dietary interventions. Our results pointed to the need to carefully analyze the results of gut microbiome in the context of enterotype-specific rather than to a whole population dataset.

microbiology↗