Strain-level Staphylococcus differentiation by CeO2-metal oxide laser ionization mass spectrometry fatty acid profiling. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Saichek, Nicholas; Cox, Christopher; Kim, Seungki; Harrington, Peter; Stambach, Nicholas; Voorhees, Kent
• Is Part Of: BMC microbiology. Volume 16:Issue 1(2016)
• Page Start: 1
• Page End: 11
• Publication Date: 2016-12
• Subjects: MALDI–MS -- MOLI MS -- Staphylococcus -- MRSA -- Fatty acids; Microbiology -- Periodicals; 579.05
• DOI: 10.1186/s12866-016-0658-y
• Languages: English
• ISSNs: 1471-2180

Abstract

Abstract Background TheStaphylococcus genus is composed of 44 species, withS. aureus being the most pathogenic. Isolates ofS. aureus are generally susceptible to β-lactam antibiotics, but extensive use of this class of drugs has led to increasing emergence of resistant strains. Increased occurrence of coagulase-negative staphylococci as well asS. aureus infections, some with resistance to multiple classes of antibiotics, has driven the necessity for innovative options for treatment and infection control. Despite these increasing needs, current methods still only possess species-level capabilities and require secondary testing to determine antibiotic resistance. This study describes the use of metal oxide laser ionization mass spectrometry fatty acid (FA) profiling as a rapid, simultaneousStaphylococcus identification and antibiotic resistance determination method. Results Principal component analysis was used to classify 50Staphyloccocus isolates. Leave-one-spectrum-out cross-validation indicated 100 % correct assignment at the species and strain level. Fuzzy rule building expert system classification and self-optimizing partial least squares discriminant analysis, with more rigorous evaluations, also consistently achieved greater than 94 and 84 % accuracy, respectively. Preliminary analysis differentiating MRSA from MSSA demonstrated the feasibility of simultaneous determination of strain identification and antibiotic resistance. Conclusion The utility of CeO2 -MOLI MS FA profiling coupled with multivariate statistical analysis for performing strain-level differentiation of variousStaphylococcus species proved to be a fast and reliable tool for identification. The simultaneous strain-level detection and antibiotic resistance determination achieved with this method should greatly improve outcomes and reduce clinical costs for therapeutic management and infection control.