Reduced gut microbiota diversity in patients with congenital generalized lipodystrophy.

BACKGROUND: Previous studies suggest intestinal dysbiosis is associated with metabolic diseases. However, the causal relationship between them is not fully elucidated. Gut microbiota evaluation of patients with congenital generalized lipodystrophy (CGL), a disease characterized by the absence of subcutaneous adipose tissue, insulin resistance, and diabetes since the first years of life, could provide insights into these relationships. METHODS: A cross-sectional study was conducted with patients with CGL (n = 17) and healthy individuals (n = 17). The gut microbiome study was performed by sequencing the 16S rRNA gene through High-Throughput Sequencing (BiomeHub Biotechnologies, Brazil). RESULTS: The median age was 20.0 years old, and 64.7% were female. There was no difference between groups in pubertal stage, BMI, ethnicity, origin (rural or urban), delivery, breastfeeding, caloric intake, macronutrient, or fiber consumption. Lipodystrophic patients presented a lower alpha diversity (Richness index: 54.0 versus 67.5; p = 0.008). No differences were observed in the diversity parameters when analyzing the presence of diabetes, its complications, or the CGL subtype. CONCLUSION: In this study, we demonstrate for the first time a reduced gut microbiota diversity in individuals with CGL. Dysbiosis was present despite dietary treatment and was also observed in young patients. Our findings allow us to speculate that the loss of intestinal microbiota diversity may be due to metabolic abnormalities present since the first years of life in CGL. Longitudinal studies are needed to confirm these findings, clarifying the possible causal link between dysbiosis and insulin resistance in humans.

Large Scale Genome-Centric Metagenomic Data from the Gut Microbiome of Food-Producing Animals and Humans.

The One Health concept is a global strategy to study the relationship between human and animal health and the transfer of pathogenic and non-pathogenic species between these systems. However, to the best of our knowledge, no data based on One Health genome-centric metagenomics are available in public repositories. Here, we present a dataset based on a pilot-study of 2,915 metagenome-assembled genomes (MAGs) of 107 samples from the human (N = 34), cattle (N = 28), swine (N = 15) and poultry (N = 30) gut microbiomes. Samples were collected from the five Brazilian geographical regions. Of the draft genomes, 1,273 were high-quality drafts (≥90% of completeness and ≤5% of contamination), and 1,642 were medium-quality drafts (≥50% of completeness and ≤10% of contamination). Taxonomic predictions were based on the alignment and concatenation of single-marker genes, and the most representative phyla were Bacteroidota, Firmicutes, and Proteobacteria. Many of these species represent potential pathogens that have already been described or potential new families, genera, and species with potential biotechnological applications. Analyses of this dataset will highlight discoveries about the ecology and functional role of pathogens and uncultivated Archaea and Bacteria from food-producing animals and humans. Furthermore, it also represents an opportunity to describe new species from underrepresented taxonomic groups.