"Omic" Approaches to Bacteria and Antibiotic Resistance Identification
Overview
Chemistry
Molecular Biology
Affiliations
The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of "-omics" approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.
Lopez-Cortes X, Manriquez-Troncoso J, Sepulveda A, Soto P Int J Mol Sci. 2025; 26(3).
PMID: 39940908 PMC: 11817502. DOI: 10.3390/ijms26031140.
Bergman N, Bergquist J, Hedeland M, Palmblad M J Am Soc Mass Spectrom. 2024; 35(10):2507-2515.
PMID: 39308355 PMC: 11457301. DOI: 10.1021/jasms.4c00293.
Wood P Metabolites. 2024; 14(7).
PMID: 39057701 PMC: 11278827. DOI: 10.3390/metabo14070378.
Alidoosti F, Giyahchi M, Moien S, Moghimi H Microb Cell Fact. 2024; 23(1):210.
PMID: 39054471 PMC: 11271216. DOI: 10.1186/s12934-024-02485-z.
Diagnostic Stewardship in Clinical Microbiology: An Indispensable Component of Patient Care.
Singhal L, Gupta P, Gupta V Infect Disord Drug Targets. 2024; 25(2):e030724231543.
PMID: 38963103 DOI: 10.2174/0118715265294425240607110713.