Bellali Sara, Haddad Gabriel, Iwaza Rim, Fontanini Anthony, Hisada Akiko, Ominami Yusuke, Raoult Didier, Khalil Jacques Bou
Institut Hospitalo-Universitaire Méditerranée Infection, Marseille 13385, France.
Aix-Marseille Université, Institut de Recherche pour le Développement (IRD), UMR Microbes Evolution Phylogeny and Infections (MEPHI), Marseille 13385, France.
Curr Res Microb Sci. 2022 Jul 2;3:100154. doi: 10.1016/j.crmicr.2022.100154. eCollection 2022.
The rapid detection of resistant bacteria has become a challenge for microbiologists worldwide. Numerous pathogens that cause nosocomial infections are still being treated empirically and have developed resistance mechanisms against key antibiotics. Thus, one of the challenges for researchers has been to develop rapid antimicrobial susceptibility testing (AST) to detect resistant isolates, ensuring better antibiotic stewardship. In this study, we established a proof-of-concept for a new strategy of phenotypic AST on Gram-positive cocci towards vancomycin using scanning electron microscopy (SEM). Our study evaluated the profiling of and after brief incubation with vancomycin. Sixteen isolates were analysed aiming to detect ultrastructural modifications at set timepoints, comparing bacteria with and without vancomycin. After optimising slides preparation and micrographs acquisition, two analytical strategies were used. The high magnification micrographs served to analyse the division of cocci based on the ratio of septa, along with the bacterial size. Susceptible strains with vancomycin showed a reduced septa percentage and the average surface area was consequently double that of the controls. The resistant bacteria revealed multiple septa occurring at advanced timepoints. Low magnification micrographs made it possible to quantify the pixels at different timepoints, confirming the profiling of cocci towards vancomycin. This new phenotypic AST strategy proved to be a promising tool to discriminate between resistant and susceptible cocci within an hour of contact with vancomycin. The analysis strategies applied here would potentially allow the creation of artificial intelligence algorithms for septa detection and bacterial quantification, subsequently creating a rapid automated SEM-AST assay.
耐药菌的快速检测已成为全球微生物学家面临的一项挑战。许多引起医院感染的病原体仍在进行经验性治疗，并且已对关键抗生素产生了耐药机制。因此，研究人员面临的挑战之一是开发快速抗菌药物敏感性测试（AST）以检测耐药菌株，确保更好地管理抗生素的使用。在本研究中，我们利用扫描电子显微镜（SEM）建立了一种针对革兰氏阳性球菌对万古霉素进行表型AST新策略的概念验证。我们的研究评估了与万古霉素短暂孵育后球菌的形态特征。分析了16株菌株，旨在在设定的时间点检测超微结构的变化，比较有和没有万古霉素作用的细菌。在优化载玻片制备和显微照片采集后，采用了两种分析策略。高倍显微照片用于根据隔膜比例以及细菌大小分析球菌的分裂情况。使用万古霉素的敏感菌株隔膜百分比降低，平均表面积因此是对照菌株的两倍。耐药菌在较晚时间点出现多个隔膜。低倍显微照片能够对不同时间点的像素进行量化，证实了球菌对万古霉素的形态特征。这种新的表型AST策略被证明是一种很有前景的工具，可在与万古霉素接触一小时内区分耐药和敏感球菌。这里应用的分析策略可能会允许创建用于隔膜检测和细菌定量的人工智能算法，随后创建一种快速自动化的SEM-AST检测方法。
