Li Xiaobo, Song Yanqing, Chen Xiuzhao, Yin Jianan, Wang Ping, Huang He, Yin Huabing
School of Chemical Engineering and Technology, Key Laboratory of Systems Bioengineering (Ministry of Education), Frontiers Science Center for Synthetic Biology, Tianjin University, Tianjin, 300072, China; James Watt School of Engineering, University of Glasgow, G12 8LT, UK.
James Watt School of Engineering, University of Glasgow, G12 8LT, UK.
Talanta. 2023 Dec 1;265:124814. doi: 10.1016/j.talanta.2023.124814. Epub 2023 Jun 16.
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.
抗生素耐药性的迅速传播已成为对全球健康的重大威胁，然而新抗生素的研发速度却跟不上新出现的耐药性。为了治疗多重耐药细菌并延长现有抗生素的使用寿命，一种有效的策略是使用抗生素和/或佐剂的组合。然而，评估药物组合主要基于终点棋盘法测量，这种方法提供的信息有限，难以研究其作用机制以及临床结果的差异。在此，单细胞微流控技术用于在3小时内快速评估抗生素组合的疗效和作用方式。以多重耐药鲍曼不动杆菌为研究对象，评估了盐酸小檗碱（BBH，作为佐剂）与碳青霉烯类抗生素（美罗培南，MEM）或β-内酰胺类抗生素之间的组合。对单个细胞进行实时跟踪以检测可编程递送的抗生素，结果显示出多种表型（即敏感、耐药和持续存活细胞），且具有较高的保真度。我们的研究发现，BBH促进抗生素在细胞内的积累，表明存在协同作用（FICI = 0.5）。例如，256 mg/L BBH与16 mg/L MEM的组合具有与MEM的最低抑菌浓度（64 mg/L）相似的杀菌效果（即抑制率>90%）。重要的是，如果细菌先用任何一种单一药物进行预处理，组合的协同作用可能会减弱。这些信息对于理解联合治疗的潜在机制至关重要。总体而言，我们的平台为评估细菌群体对抗生素的动态和异质性反应提供了一种有前景的方法，这将有助于新药研发并减少新出现的抗生素耐药性。
