Rapid and accurate identification of microorganisms using ion mobility–mass spectrometry

Abstract

Accurate identification of microorganisms to the strain and substrain levels in clinical and environmental samples is essential to provide an appropriate antibiotherapy to the patients and reduce the prescription of broad-spectrum antimicrobials to minimize antibiotic resistance. Unfortunately, the current diagnosis methods are often slow, expensive, or laborious, which limits their use in resource-limited regions. Therefore, there is a strong unmet need for new technologies that can rapidly identify microorganisms in complex samples to complement the existing commercially available technologies. This Young Scientist Perspective demonstrates the value of combining the attributes of ion mobility-mass spectrometry and ambient ionization, enabling rapid and accurate discrimination of bacteria to the species level after only a 4-h culturing period and showing that various bacterial species can have different isomers and conformers of their biomarkers. However, to discriminate closely-related bacterial strains, we needed to include other separation techniques in our workflow, such as liquid chromatography. Also, we utilized whole organism fingerprints, which include metabolites, lipids, and peptides, using our optimized workflow and machine learning to analyze a wide set of E. coli strains in artificially contaminated urine samples. Moreover, the various challenges for routine identification of microorganisms using our optimized techniques in medical, environmental, and security fields and future outlooks are discussed.