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采用台式扫描电子显微镜对亚胺培南和强力霉素的杀菌和抑菌效果进行早期预测。

Early prediction of the bactericidal and bacteriostatic effect of imipenem and doxycycline using tabletop scanning electron microscopy.

机构信息

IHU - Méditerranée Infection, Marseille, France.

Aix Marseille Univ, MEPHI, Marseille, France.

出版信息

Front Cell Infect Microbiol. 2024 Aug 29;14:1431141. doi: 10.3389/fcimb.2024.1431141. eCollection 2024.

Abstract

INTRODUCTION

Our work aims at establishing a proof-of-concept for a method that allows the early prediction of the bactericidal and bacteriostatic effects of antibiotics on bacteria using scanning electron microscopy (SEM) as compared to traditional culture-based methods.

METHODS

We tested these effects using Imipenem (bactericidal) and Doxycycline (bacteriostatic) with several strains of sensitive and resistant . We developed a SEM-based predictive score based on three main criteria: Bacterial Density, Morphology/Ultrastructure, and Viability. We determined the results for each of these criteria using SEM micrographs taken with the TM4000Plus II-Tabletop-SEM (Hitachi, Japan) following an optimized, rapid, and automated acquisition and analysis protocol. We compared our method with the traditional culture colony counting gold standard method and classic definitions of the two effects.

RESULTS

Our method revealed total agreement with the CFU method and classic definition by visualizing the effect of the antibiotic at 60 minutes and 120 minutes using SEM.

DISCUSSION

This early prediction allows a rapid and early identification of the bactericidal and bacteriostatic effects as compared to culture that would take a minimum of 18 hours. This has several future applications in the development of SEM-automated assays coupled to machine learning models that identify the antibiotic effect and facilitate determination of bacterial susceptibility.

摘要

简介

我们的工作旨在建立一种方法的概念验证,该方法使用扫描电子显微镜 (SEM) 与传统的基于培养的方法相比,可以早期预测抗生素对细菌的杀菌和抑菌作用。

方法

我们使用亚胺培南(杀菌)和多西环素(抑菌)对几种敏感和耐药的 进行了这些效果的测试。我们开发了一种基于 SEM 的预测评分,基于三个主要标准:细菌密度、形态/超微结构和活力。我们使用 TM4000Plus II-台式-SEM(日立,日本)拍摄的 SEM 显微照片确定了这些标准中的每一个的结果,遵循优化的、快速的和自动化的采集和分析协议。我们将我们的方法与传统的培养菌落计数金标准方法和两种效应的经典定义进行了比较。

结果

我们的方法通过在 60 分钟和 120 分钟使用 SEM 可视化抗生素的作用,与 CFU 方法和经典定义完全一致。

讨论

与至少需要 18 小时的培养相比,这种早期预测允许快速和早期识别杀菌和抑菌作用。这在开发 SEM 自动化测定与机器学习模型的结合方面具有未来的应用,这些模型可以识别抗生素的作用并促进确定细菌的敏感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e46/11390654/e1ea1bdf16b8/fcimb-14-1431141-g001.jpg

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