Rapid Microbial Identification and Antibiotic Resistance Detection by Mass Spectrometric Analysis of Membrane Lipids

• Published in: Analytical chemistry (Washington) Vol. 91; no. 2; pp. 1286 - 1294
• Main Authors: Liang, Tao, Leung, Lisa M, Opene, Belita, Fondrie, William E, Lee, Young In, Chandler, Courtney E, Yoon, Sung Hwan, Doi, Yohei, Ernst, Robert K, Goodlett, David R
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 15.01.2019
• Subjects: Acetic acid; Antibiotic resistance; Antibiotics; Chemistry; Drug resistance; Fungi; Global health; Hospitals; Infectious diseases; Intensive care units; Ionization; Lipids; Mass spectra; Mass spectrometry; Mass spectroscopy; Membranes; Microbiology; Microorganisms; Pathogens; Proteins; Sample preparation; Sodium; Sodium acetate
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.8b02611

Infectious diseases have a substantial global health impact. Clinicians need rapid and accurate diagnoses of infections to direct patient treatment and improve antibiotic stewardship. Current technologies employed in routine diagnostics are based on bacterial culture followed by morphological trait differentiation and biochemical testing, which can be time-consuming and labor-intensive. With advances in mass spectrometry (MS) for clinical diagnostics, the U.S. Food and Drug Administration has approved two microbial identification platforms based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS analysis of microbial proteins. We recently reported a novel and complementary approach by comparing MALDI-TOF mass spectra of microbial membrane lipid fingerprints to identify ESKAPE pathogens. However, this lipid-based approach used a sample preparation method that required more than a working day from sample collection to identification. Here, we report a new method that extracts lipids efficiently and rapidly from microbial membranes using an aqueous sodium acetate (SA) buffer that can be used to identify clinically relevant Gram-positive and -negative pathogens and fungal species in less than an hour. The SA method also has the ability to differentiate antibiotic-susceptible and antibiotic-resistant strains, directly identify microbes from biological specimens, and detect multiple pathogens in a mixed sample. These results should have positive implications for the manner in which bacteria and fungi are identified in general hospital settings and intensive care units.