Jiexi Yan, Qingmiao Ren, Xiaomin He, Haiyun Du, Lijuan He, Zhaoyu Zheng, Yaya Qi, Xiaohong Xian
These findings demonstrate obvious spatial and temporal variability in microbial and ARG profiles across ICU environments, supporting the development of targeted infection control strategies.
BACKGROUND: Intensive care units (ICUs) are high-risk settings for healthcare-acquired infections (HAIs). It is essential to characterize the microorganisms and antimicrobial resistance genes (ARGs) in ICU environments for prevention and control of HAIs.
METHODS: Totally, 206 environmental and patient samples were collected from general ICU (GICU), emergency ICU (EICU), pediatric ICU (PICU), and neonatal ICU (NICU). Longitudinal sampling was conducted in PICU at four time points from May 2024 to March 2025. All samples were subjected to metagenomic sequencing. The differences of microbial and ARG profiles were further analyzed across different ICU types as well as sampling areas and times.
RESULTS: Alpha diversity did not differ among ICU types. In contrast, microbial community composition varied across ICUs (PERMANOVA, p = 0.001). GICU and EICU samples clustered together, enriched with Acinetobacter baumannii and Klebsiella pneumoniae, whereas NICU and PICU samples showed greater similarity, with enrichment of Streptococcus pneumoniae and Burkholderia cepacia. Sampling areas also exhibited differences in both alpha diversity (p < 0.001) and beta diversity (p = 0.001). Similar spatial patterns were observed for ARGs. Although ARG alpha diversity remained relatively stable, beta diversity differed significantly among ICU types and sampling areas (p = 0.001). Temporal variation was also evident in the PICU, where both microbial and ARG profiles changed over time (p = 0.001), and clinically relevant pathogens reached their highest abundance in November.
CONCLUSIONS: These findings demonstrate obvious spatial and temporal variability in microbial and ARG profiles across ICU environments, supporting the development of targeted infection control strategies.