Identifying Clinically Relevant Bacteria Directly from Culture and Clinical Samples with a Handheld Mass Spectrometry Probe

Author:

Povilaitis Sydney C1,Chakraborty Ashish1,Kirkpatrick Lindsey M2,Downey Rachel D3ORCID,Hauger Sarmistha B4,Eberlin Livia S5ORCID

Affiliation:

1. Department of Chemistry, The University of Texas at Austin , Austin, TX 78712 , USA

2. Department of Pediatrics, Division of Pediatric Infectious Diseases, J.W. Riley Hospital for Children, Indiana University School of Medicine , Indianapolis, IN 46202 , USA

3. Department of Pediatric Infectious Diseases, Dell Children's Medical Group , Austin, TX 78723 , USA

4. Department of Pediatrics, Dell Medical School, The University of Texas at Austin , Austin, TX 78712 , USA

5. Department of Surgery, Baylor College of Medicine , Houston, TX 77030 , USA

Abstract

Abstract Background Rapid identification of bacteria is critical to prevent antimicrobial resistance and ensure positive patient outcomes. We have developed the MasSpec Pen, a handheld mass spectrometry-based device that enables rapid analysis of biological samples. Here, we evaluated the MasSpec Pen for identification of bacteria from culture and clinical samples. Methods A total of 247 molecular profiles were obtained from 43 well-characterized strains of 8 bacteria species that are clinically relevant to osteoarticular infections, including Staphylococcus aureus, Group A and B Streptococcus, and Kingella kingae, using the MasSpec Pen coupled to a high-resolution mass spectrometer. The molecular profiles were used to generate statistical classifiers based on metabolites that were predictive of Gram stain category, genus, and species. Then, we directly analyzed samples from 4 patients, including surgical specimens and clinical isolates, and used the classifiers to predict the etiologic agent. Results High accuracies were achieved for all levels of classification with a mean accuracy of 93.3% considering training and validation sets. Several biomolecules were detected at varied abundances between classes, many of which were selected as predictive features in the classifiers including glycerophospholipids and quorum-sensing molecules. The classifiers also enabled correct identification of Gram stain type and genus of the etiologic agent from 3 surgical specimens and all classification levels for clinical specimen isolates. Conclusions The MasSpec Pen enables identification of several bacteria at different taxonomic levels in seconds from cultured samples and has potential for culture-independent identification of bacteria directly from clinical samples based on the detection of metabolic species.

Funder

NIH/NICHD

NCI/NIH

Gordon and Betty Moore Foundation

Welch Foundation

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

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