Machine Learning Reveals Microbial Taxa Associated with a Swim across the Pacific Ocean.

ABSTRACT: Purpose: This study aimed to characterize the association between microbial dynamics and excessive exercise. Methods: Swabbed fecal samples, body composition (percent body fat), and swimming logs were collected (n = 94) from a single individual over 107 days as he swam across the Pacific Ocean. The V4 region of the 16S rRNA gene was sequenced, generating 6.2 million amplicon sequence variants. Multivariate analysis was used to analyze the microbial community structure, and machine learning (random forest) was used to model the microbial dynamics over time using R statistical programming. Results: Our findings show a significant reduction in percent fat mass (Pearson; p < 0.01, R = -0.89) and daily swim distance (Spearman; p < 0.01, R = -0.30). Furthermore

SUBMITTER: Lewis G 

PROVIDER: S-EPMC11504845 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature