Single-cell microfluidics enabled dynamic evaluation of drug combinations on antibiotic resistance bacteria

Li, X., Song, Y. , Chen, X., Yin, J., Wang, P., Huang, H. and Yin, H. (2023) Single-cell microfluidics enabled dynamic evaluation of drug combinations on antibiotic resistance bacteria. Talanta, 265, 124814. (doi: 10.1016/j.talanta.2023.124814)

Abstract

The rapid spread of antibiotic resistance has become a significant threat to global health, yet the development of new antibiotics is outpaced by emerging new resistance. To treat multidrug-resistant bacteria and prolong the lifetime of existing antibiotics, a productive strategy is to use combinations of antibiotics and/or adjuvants. However, evaluating drug combinations is primarily based on end-point checkerboard measurements, which provide limited information to study the mechanism of action and the discrepancies in the clinical outcomes. Here, single-cell microfluidics is used for rapid evaluation of the efficacy and mode of action of antibiotic combinations within 3 h. Focusing on multidrug-resistant Acinetobacter baumannii, the combination between berberine hydrochloride (BBH, as an adjuvant) and carbapenems (meropenem, MEM) or β-lactam antibiotic is evaluated. Real-time tracking of individual cells to programmable delivered antibiotics reveals multiple phenotypes (i.e., susceptible, resistant, and persistent cells) with fidelity. Our study discovers that BBH facilitates the accumulation of antibiotics within cells, indicating synergistic effects (FICI = 0.5). For example, the combination of 256 mg/L BBH and 16 mg/L MEM has a similar killing effect (i.e., the inhibition rates >90%) as the MIC of MEM (64 mg/L). Importantly, the synergistic effect of a combination can diminish if the bacteria are pre-stressed with any single drug. Such information is vital for understanding the underlying mechanisms of combinational treatments. Overall, our platform provides a promising approach to evaluate the dynamic and heterogenous response of a bacterial population to antibiotics, which will facilitate new drug discovery and reduce emerging antibiotic resistance.

• Item Type: Articles
• Additional Information: This work was supported by grants from National Key Research and Development Project (No. 2019YFA0905600), Science and Technology Program of Tianjin, China (No. 22YFZCSN00090). We thank the support of NERC (NE/S008721/1) and EPSRC IAA (EP/R511705/1).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yin, Professor Huabing and Song, Dr Yanqing and Li, Xiaobo
• Authors: Li, X., Song, Y., Chen, X., Yin, J., Wang, P., Huang, H., and Yin, H.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Engineering > Biomedical Engineering
• Journal Name: Talanta
• Publisher: Elsevier
• ISSN: 0039-9140
• ISSN (Online): 1873-3573
• Published Online: 16 June 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Talanta 265:124814
• Publisher Policy: Reproduced under a Creative Commons license

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
304198		LinkPI: Linking Phenotype function with Identity: a novel integrated single-cell technology and metagenomics approach	Huabing Yin	Natural Environment Research Council (NERC)	NE/S008721/1	ENG - Biomedical Engineering
309324		Optimisation of prediction models for red blood cell demand	Alice Miller	Engineering and Physical Sciences Research Council (EPSRC)	EP/R511705/1	Computing Science