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Comparison of Argentinean microbiota with other geographical populations reveals different taxonomic and functional signatures associated with obesity.

ABSTRACT: Accumulating evidence suggests that various genetic and environmental factors contribute to the development of obesity. Among the latter, the gut microbiota has emerged as a critical player in the regulation of human metabolism and health and the development of non-communicable chronic diseases. Considering that no information on this matter is available in Argentina, our aim was to identify the microorganisms associated with obesity as well as their potential functionality. Using high throughput sequencing of 16SrRNA bacterial gene and diverse bioinformatics tools, we observed that the gut microbiota of obese and overweight individuals differs qualitatively and quantitatively from that from their lean counterparts. The comparison of the gut microbiota composition in obese subjects from Argentina, US and UK showed that the beta diversity significantly differs among the three countries, indicating that obesity-associated microbiota composition changes according to the geographical origin of the individuals. Moreover, four distinct microbiotypes were identified in obese individuals, whose prevalence and metabolic pathway signature differed according to the country, indicating that obesity associated dysbiosis would comprise several structures. In summary, identification of distinct taxonomic signatures associated with obesity might be a novel promising tool to stratify patients based on their microbiome configuration to design strategies for managing obesity.

SUBMITTER: Pesoa SA

PROVIDER: S-EPMC8032766 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Intestinal diseases caused by opportunistic pathogens seriously threaten the health and survival of giant pandas. However, our understanding of gut pathogens in different populations of giant pandas, especially in the wild populations, is still limited. Here, we conducted a study based on 52 giant panda metagenomes to investigate the composition and distribution of gut pathogens and virulence factors (VFs) in five geographic populations (captive: GPCD and GPYA; wild: GPQIN, GPQIO, and GPXXL). The results of the beta-diversity analyzes revealed a close relationship and high similarity in pathogen and VF compositions within the two captive groups. Among all groups, Proteobacteria, Firmicutes, and Bacteroidetes emerged as the top three abundant phyla. By using the linear discriminant analysis effect size method, we identified pathogenic bacteria unique to different populations, such as Klebsiella in GPCD, Salmonella in GPYA, Hafnia in GPQIO, Pedobacter in GPXXL, and Lactococcus in GPQIN. In addition, we identified 12 VFs that play a role in the intestinal diseases of giant pandas, including flagella, CsrA, enterobactin, type IV pili, alginate, AcrAB, capsule, T6SS, urease, type 1 fimbriae, polar flagella, allantoin utilization, and ClpP. These VFs influence pathogen motility, adhesion, iron uptake, acid resistance, and protein regulation, thereby contributing to pathogen infection and pathogenicity. Notably, we also found a difference in virulence of Pseudomonas aeruginosa between GPQIN and non-GPQIN wild populations, in which the relative abundance of VFs (0.42%) of P. aeruginosa was the lowest in GPQIN and the highest in non-GPQIN wild populations (GPXXL: 23.55% and GPQIO: 10.47%). In addition to enhancing our understanding of gut pathogens and VFs in different geographic populations of giant pandas, the results of this study provide a specific theoretical basis and data support for the development of effective conservation measures for giant pandas.

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Comparison of Argentinean microbiota with other geographical populations reveals different taxonomic and functional signatures associated with obesity.

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