Center for Microbial Ecology and Technology, Faculty of Bioscience Engineering, Ghent University, Gent, Belgium.
Department of Oral Health Sciences, KU Leuven & Dentistry (Periodontology), University Hospitals Leuven, Leuven, Belgium.
Microbiol Spectr. 2024 Apr 2;12(4):e0393123. doi: 10.1128/spectrum.03931-23. Epub 2024 Mar 14.
Antimicrobial resistance is one of the greatest challenges to global health. While the development of new antimicrobials can combat resistance, low profitability reduces the number of new compounds brought to market. Elucidating the mechanism of action is crucial for developing new antimicrobials. This can become expensive as there are no universally applicable pipelines. Phenotypic heterogeneity of microbial populations resulting from antimicrobial treatment can be captured through flow cytometric fingerprinting. Since antimicrobials are classified into limited groups, the mechanism of action of known compounds can be used for predictive modeling. We demonstrate a cost-effective flow cytometry approach for determining the mechanism of action of new compounds. Cultures of and were treated with different antimicrobials and measured by flow cytometry. A Gaussian mixture mask was applied over the data to construct phenotypic fingerprints. Fingerprints were used to assess statistical differences between mechanism of action groups and to train random forest classifiers. Classifiers were then used to predict the mechanism of action of cephalothin. Statistical differences were found among the different mechanisms of action groups. Pairwise comparison showed statistical differences for 35 out of 45 pairs for and for 32 out of 45 pairs for after 3.5 h of treatment. The best-performing random forest classifier yielded a Matthews correlation coefficient of 0.92 and the mechanism of action of cephalothin could be successfully predicted. These findings suggest that flow cytometry can be a cheap and fast alternative for determining the mechanism of action of new antimicrobials.IMPORTANCEIn the context of the emerging threat of antimicrobial resistance, the development of novel antimicrobials is a commonly employed strategy to combat resistance. Elucidating the mechanism of action of novel compounds is crucial in this development but can become expensive, as no universally applicable pipelines currently exist. We present a novel flow cytometry-based approach capable of determining the mechanism of action swiftly and cost-effectively. The workflow aims to accelerate drug discovery and could help facilitate a more targeted approach for antimicrobial treatment of patients.
抗微生物药物耐药性是全球健康面临的最大挑战之一。虽然开发新的抗微生物药物可以对抗耐药性，但低利润率减少了推向市场的新化合物数量。阐明作用机制对于开发新的抗微生物药物至关重要。由于没有普遍适用的途径，因此这可能会变得很昂贵。由于抗微生物药物被分类为有限的几类，因此可以使用已知化合物的作用机制来进行预测建模。我们展示了一种经济有效的流式细胞术方法，用于确定新化合物的作用机制。用不同的抗微生物药物处理 和 培养物，并通过流式细胞术进行测量。将高斯混合掩模应用于数据以构建表型指纹。使用指纹评估作用机制组之间的统计差异，并训练随机森林分类器。然后，将分类器用于预测头孢噻吩的作用机制。发现不同作用机制组之间存在统计学差异。在 3.5 小时的治疗后， 有 35 对中的 45 对和 有 32 对中的 45 对之间存在统计学差异。表现最好的随机森林分类器产生了 0.92 的马修斯相关系数，并且可以成功预测头孢噻吩的作用机制。这些发现表明，流式细胞术可以作为一种廉价且快速的替代方法，用于确定新的抗微生物药物的作用机制。重要性在抗微生物药物耐药性这一新兴威胁的背景下，开发新型抗微生物药物是对抗耐药性的常用策略。阐明新型化合物的作用机制在这一发展中至关重要，但由于目前不存在普遍适用的途径，因此可能会变得很昂贵。我们提出了一种新的基于流式细胞术的方法，能够快速、经济有效地确定作用机制。该工作流程旨在加速药物发现，并有助于为患者的抗微生物治疗提供更有针对性的方法。
