Evaluation of MALDI-TOF MS for rapid characterization of antimicrobial resistance (AMR) of mastitis-causing pathogens

• Grant number: 24/03176-7
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: August 01, 2024
• End date: June 30, 2027
• Field of knowledge: Agronomical Sciences - Veterinary Medicine - Preventive Veterinary Medicine
• Principal Investigator: Marcos Veiga dos Santos
• Grantee: Carlos Eduardo Fidelis
• Host Institution: Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 21/05400-3 - Responsible use of antimicrobials and bacterial resistance in dairy herds, AP.TEM

Abstract

The irresponsible use of antimicrobials (ATM) in human, veterinary medicine and animal production has been correlated with the antimicrobial resistance (AMR) globally. In this scenario, the rapid and reliable identification of potential pathogens and AMR patterns is extremely important for the responsible use of antimicrobials. Aiming to face this scientific challenge, this proposal is structured into three subprojects, with the objectives of: I) developing machine learning (ML) models based on MALDI-TOF results to detect antimicrobial resistance characteristics in bovine mastitis pathogens; II) develop ML models associated with MALDI-TOF MS for presumptive detection of Staph resistance and virulence factors. aureus causing bovine mastitis; III) characterize by MALDI-TOF MS the enzymatic activity of beta-lactamase and carbapenemase directly from isolates and milk samples. To carry out subproject I, a training dataset will be constructed with Staph isolates. aureus (n=150) and Streptococcus uberis (n=150), Escherichia coli (n=150) and Klebsiella pneumoniae (n=150) together with the sensitivity profile of ten different antimicrobials. Next, ten ML models (LightGBM, gradient boosting, logistic regression, extreme gradient boosting, extra trees, random forest, linear SVM, decision tree, K neighbors and naive Bayes) will be evaluated for the characterization of AMR in bacterial isolates from the test groups (n=400) based on the mass spectrum pattern. For subproject II, a local training group will be created with 206 Staph isolates. aureus (103 MC; 103 MSC) together with the molecular profile for genes related to enterotoxins (seh, sei, seo, seul1, seul2, selw and selx), RAM (mecA, blaZ), cell adhesion (icaA, icaD) and hemolysin ( hla, hlb). Next, ten ML models will be used to characterize the virulence factors and AMR in the test group (n=400) based on the mass spectrum pattern. For subproject III, 250 milk samples experimentally contaminated with isolates of Escherichia coli, Enterobacter spp. and Klebsiella will be subjected to evaluation of beta-lactamases and carbapenemases activity by MALDI-TOF, using the MBT-STAR-Cepha and MBT STAR-Carba kits. The results of the present study will enable the development of diagnostic tests based on ML and MALDI-TOF MS for rapid detection of AMR patterns, and thus contribute to reducing cases of resistance and assisting in the rational use of ATM in milk production.