Microfluidic Chip for Detection of Drug Resistance at the Single-cell Level
-
Published:2022-12-25
Issue:1
Volume:14
Page:46
-
ISSN:2072-666X
-
Container-title:Micromachines
-
language:en
-
Short-container-title:Micromachines
Author:
Song Kena,Yu Zhangqing,Zu Xiangyang,Huang Lei,Fu Dongliao,Yao Jingru,Hu Zhigang,Xue Yun
Abstract
Drug-resistant bacterial strains seriously threaten human health. Rapid screening of antibiotics is urgently required to improve clinical treatment. Conventional methods of antimicrobial susceptibility testing rely on turbidimetry that is evident only after several days of incubation. The lengthy time of the assay can delay clinical treatment. Here, we proposed a single-cell level rapid system based on a microfluidic chip. The detection period of 30 min to 2 h was significantly shorter than the conventional turbidity-based method. To promote detection efficiency, 16 independent channels were designed, permitting the simultaneous screening of 16 drugs in the microfluidic chip. Prepositioning of drugs in the chip permitted prolonged transportation and storage. This may allow for the widespread use of the novel system, particularly in the regions where medical facilities are scarce. The growth curves were reported rapidly through a custom code in Matlab after tracking and photographing the bacteria during microscopy examination. The capability of the proposed system was validated by antimicrobial susceptibility testing trials with standard strains. The system provides a potentially useful detection tool for drug-resistant bacteria.
Funder
National Natural Science Foundation of China
key specialized research and development breakthrough of He’nan province
key scientific research projects of He’nan colleges and universities
Luoyang Public Security Project
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering
Reference30 articles.
1. World Health Organization (WHO) (2014). Antimicrobial Resistance: Global Report on Surveillance 2014.
2. La Rosa, R., Johansen, H.K., and Molin, S. (2022). Persistent bacterial infections, antibiotic treatment failure, and microbial adaptive evolution. Antibiotics, 11.
3. Tackling antimicrobial resistance in neonatal sepsis;Folgori;Lancet Glob. Health,2017
4. Transmission surveillance for antimicrobial-resistant organisms in the health system;Pitout;Microbiol. Spectr.,2018
5. Antimicrobial Resistance Collaborators (2020). Global burden of bacterial antimicrobial resistance in 2019: A systematic analysis. Lancet, 399, 629–655.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献