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662. Identification of Clinically Relevant Microbes with the MasSpec Pen
BACKGROUND: In the age of antimicrobial resistance, rapid identification of infectious agents is critical for antimicrobial stewardship and effective therapy. To this end, ambient ionization mass spectrometry techniques have been applied for rapid identification of microbes directly from culture iso...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777927/ http://dx.doi.org/10.1093/ofid/ofaa439.855 |
Sumario: | BACKGROUND: In the age of antimicrobial resistance, rapid identification of infectious agents is critical for antimicrobial stewardship and effective therapy. To this end, ambient ionization mass spectrometry techniques have been applied for rapid identification of microbes directly from culture isolates. We have developed a handheld, mass spectrometry-based device, the MasSpec Pen, that permits direct molecular analysis of a biological sample in seconds (Scheme 1). Here, we employ the MasSpec Pen to identify clinically relevant microbes directly from culture isolates. METHODS: Staphylococcus aureus, Staphylococcus epidermidis, Group A and B Streptococcus, Kingella kingae (K.k), and Pseudomonas aeruginosa (P.a) were cultured on 5% sheep’s blood nutrient agar at 37 °C overnight. Colonies were transferred to a glass slide where they were analyzed directly with the MasSpec Pen coupled to a Q Exactive mass spectrometer (Thermo Scientific) in negative ion mode. For MasSpec Pen analysis, a 10 µL droplet of water was held in contact with the sample surface for 3 seconds and then aspirated to the mass spectrometer for analysis. Data was normalized and the molecular features resulting from the analysis solvent and nutrient medium were removed. The least absolute shrinkage and selection operator (lasso) statistical method was used to build classification models for prediction of bacterial identity. Model performance was evaluated by leave-one-out cross-validation and a validation set of samples. Scheme 1: MasSpec Pen workflow [Image: see text] RESULTS: Various small molecules were detected including metabolites and glycerophospholipid species. The mass spectral profiles for each species exhibited qualitative differences among them (Figure 1). Additionally, several quorum-sensing molecules were observed in P.a. including hydroxy-heptyl-quinoline (m/z 242.155). Lasso statistical classifiers were created to differentiate organisms at the level of Gram type, genus, and species with each model comprised of a sparse set of molecular features. Accuracies of 90% or greater were achieved for all lasso models and as high as 98% for the differentiation of Staphylococcus (Staph.) and Streptococcus (Strep.). Figure 1: Molecular profiles of species analyzed [Image: see text] Figure 2: Statistical classification results [Image: see text] CONCLUSION: These results demonstrate the potential of the MasSpec Pen as a tool for clinical analysis of infected biospecimens. DISCLOSURES: Sydney C. Povilaitis, BA, MS Pen Technologies, Inc. (Other Financial or Material Support, Patent) Livia Eberlin, PhD, MS Pen Technolpogies, Inc. (Board Member, Shareholder) |
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