Shigella flexneri infection is the main cause of diarrhea in humans worldwide. The emergence of antimicrobial resistance (AMR) of S. flexneri is a growing public health threat worldwide, while large-scale studies monitoring the longitudinal AMR trends of isolates remain scarce. Here, the AMR gene (ARG) profiles of 717 S. flexneri isolates from 1920 to 2020 worldwide were determined. The results showed that the average number of ARGs in isolates has increased significantly, from 19.2 ± 2.4 before 1970 to 29.6 ± 5.3 after 2010. In addition, mobile genetic elements were important contributors to ARGs in S. flexneri isolates. The results of the structural equation model showed that the human development index drove the consumption of antibiotics and indirectly promoted the antibiotic resistance. Finally, a machine learning algorithm was used to predict the antibiotic resistance risk of global terrestrial S. flexneri isolates and successfully map the antibiotic resistance threats in global land habitats with over 80% accuracy. Collectively, this study monitored the longitudinal AMR trends, quantitatively surveilled the health risk of S. flexneri AMR, and provided a theoretical basis for mitigating the threat of antibiotic resistance.
Keywords: genomic analysis; human development index; machine learning; mobile genetic elements; pathogenic bacteria.