Metabolic Labeling and Digital Microfluidic Single‐Cell Sequencing for Single Bacterial Genotypic‐Phenotypic Analysis

• Published in: Small (Weinheim an der Bergstrasse, Germany) Vol. 20; no. 45; pp. e2402177 - n/a
• Main Authors: Guo, Junnan, Sun, Di, Li, Kunjie, Dai, Qi, Geng, Shichen, Yang, Yuanyuan, Mo, Mengwu, Zhu, Zhi, Shao, Chen, Wang, Wei, Song, Jia, Yang, Chaoyong, Zhang, Huimin
• Format: Journal Article
• Language: English
• Published: Germany Wiley Subscription Services, Inc 01.11.2024
• Subjects: Acid resistance; Amino acids; antibiotic resistance analysis; Antibiotics; Bacteria; digital microfluidics; Drug resistance; Fluorescence; Gene sequencing; Genomes; Labeling; metabolic labeling; Microfluidics; Resistance factors; single‐cell genome sequencing; digital microfluidics; metabolic labeling; antibiotic resistance analysis; single‐cell genome sequencing
• ISSN: 1613-6810; 1613-6829; 1613-6829
• DOI: 10.1002/smll.202402177

Accurate assessment of phenotypic and genotypic characteristics of bacteria can facilitate comprehensive cataloguing of all the resistance factors for better understanding of antibiotic resistance. However, current methods primarily focus on individual phenotypic or genotypic profiles across different colonies. Here, a Digital microfluidic‐based automated assay for whole‐genome sequencing of single‐antibiotic‐resistant bacteria is reported, enabling Genotypic and Phenotypic Analysis of antibiotic‐resistant strains (Digital‐GPA). Digital‐GPA can efficiently isolate and sequence antibiotic‐resistant bacteria illuminated by fluorescent D‐amino acid (FDAA)‐labeling, producing high‐quality single‐cell amplified genomes (SAGs). This enables identifications of both minor and major mutations, pinpointing substrains with distinctive resistance mechanisms. Digital‐GPA can directly process clinical samples to detect and sequence resistant pathogens without bacterial culture, subsequently provide genetic profiles of antibiotic susceptibility, promising to expedite the analysis of hard‐to‐culture or slow‐growing bacteria. Overall, Digital‐GPA opens a new avenue for antibiotic resistance analysis by providing accurate and comprehensive molecular profiles of antibiotic resistance at single‐cell resolution. Digital‐GPA, a digital microfluidic‐based automated assay, enables simultaneous detection of phenotypes and genotypes in individual bacterial cells via fluorescent D‐amino acid (FDAA) metabolic labeling and single‐cell whole‐genome sequencing (sbWGS). It accurately identifies bacterial antibiotic susceptibility, correlates resistant phenotypes with genomes, and enhances understanding of antibiotic resistance mechanisms, showing significant potential for bacterial resistance research and clinical applications.