| Autor: |
Sara Bellali, Gabriel Haddad, Rim Iwaza, Anthony Fontanini, Akiko Hisada, Yusuke Ominami, Didier Raoult, Jacques Bou Khalil |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Current Research in Microbial Sciences, Vol 3, Iss , Pp 100154- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2666-5174 |
| DOI: |
10.1016/j.crmicr.2022.100154 |
| Popis: |
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 Enterococcus faecalis, Enterococcus faecium and Staphylococcus aureus 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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