Lifestyle and geographic insights into the distinct gut microbiota in elderly women from two different geographic locations

BACKGROUND: A large number of microorganisms reside within the gastrointestinal tract, especially in the colon, and play important roles in human health and disease. The composition of the human gut microbiota is determined by intrinsic host factors and environmental factors. While investigating environmental factors to promote human health is of great interest, few studies have focused on their effect on the gut microbiota. This study aimed to investigate differences in gut microbiota composition according to lifestyle and geographical area, even in people with similar genetic background. METHODS: We enrolled ten and nine elderly women in their seventies from island and inland areas, respectively. Fecal samples were obtained from individuals, and bacterial 16S ribosomal RNA genes were analyzed by next-generation sequencing to define the gut microbiota composition. We assessed their diet, which can influence the gut microbial community. We also conducted physical examination and determined the physical activity levels of the subjects. RESULTS: The inland subjects had a significantly higher rectal temperature, systolic blood pressure, and heart rate and a significantly lower physical activity score than the island subjects. Fecal samples from the island group showed a tendency to have greater microbial diversity than those from the inland group. Interestingly, the microbial community composition differed significantly between the two groups. Catenibacterium was enriched in subjects from the island area. Catenibacterium showed a negative correlation with rectal temperature and a positive correlation with the dietary level of animal fat. In contrast, Butyricimonas was enriched in the inland subjects. A positive correlation was found between Butyricimonas and mean arterial pressure. CONCLUSIONS: This study identified differences in the gut microbiota composition between elderly women from different parts of South Korea, and our findings suggest that further studies of the human gut microbiota should evaluate aspects of the living environment

Interrogation of the perturbed gut microbiota in gouty arthritis patients through in silico metabolic modeling

Recent studies have shown perturbed gut microbiota associated with gouty arthritis, a metabolic disease characterized by an imbalance between uric acid production and excretion. To mechanistically investigate altered microbiota metabolism associated with gout disease, 16S rRNA gene amplicon sequence data from stool samples of gout patients and healthy controls were computationally analyzed through bacterial community metabolic models. Patient-specific community models constructed with the metagenomics modeling pipeline, mgPipe, were used to perform k-means clustering of samples according to their metabolic capabilities. The clustering analysis generated statistically significant partitioning of samples into a Bacteroides-dominated, high gout cluster and a Faecalibacterium-elevated, low gout cluster. The high gout cluster was predicted to allow elevated synthesis of the amino acids D-alanine and L-alanine and byproducts of branched-chain amino acid catabolism, while the low gout cluster allowed higher production of butyrate, the sulfur-containing amino acids L-cysteine and L-methionine, and the L-cysteine catabolic product H2S. By expanding the capabilities of mgPipe to provide taxa-level resolution of metabolite exchange rates, acetate, D-lactate and succinate exchanged from Bacteroides to Faecalibacterium were predicted to enhance butyrate production in the low gout cluster. Model predictions suggested that sulfur-containing amino acid metabolism generally and H2S more specifically could be novel gout disease markers