High-Throughput Single-Cell Metabolic Labeling, Sorting, and Sequencing of Active Antibiotic-Resistant Bacteria in the Environment
Wenfang Lin, Ruilong Li, Shaoheng Cao, Hong-Zhe Li, Kai Yang, Zhugen Yang, Jian‐Qiang Su, Yong‐Guan Zhu, Cui Li
Abstract
Active antibiotic-resistant bacteria (ARB) play a major role in spreading antimicrobial resistance (AMR) in the environment; however, they have remained largely unexplored. Herein, we coupled bio-orthogonal noncanonical amino acid tagging with high-throughput fluorescence-activated single-cell sorting (FACS) and sequencing to characterize the phenome and genome of active ARB in complex environmental matrices. Active ARB, conferring resistance to six antibiotics throughout wastewater treatment, were distinguished and quantified. The percentage and concentration of active ARB ranged from 0.28% to 45.3% and from 1.1 × 10 4 to 2.09 × 10 7 cells/mL, respectively. Notably, the final effluents retained up to 4.79 × 10 4 cells/mL of active ARB. Targeted FACS and genomic sequencing revealed a distinct taxonomic composition of active ARB compared with that of the overall population. The coexistence of antibiotic resistome and mobilome in active ARB was also identified, including three high-quality metagenomic assembly genomes assigned to pathogenic bacteria, highlighting the substantial health risks due to their activity, phenotypic resistance, mobility, and pathogenicity. This study advances our understanding of previously overlooked active ARB in the environment by linking their resistance phenotype to their genotype. This high-throughput method will enable efficient quantitative surveillance of active AMR, providing valuable insights into risk control and management.