Rapid Multi-Omics for Bacterial Identification Using Flow Injection–Ion Mobility–Mass Spectrometry

The implementation of mass spectrometry (MS) in clinical microbiology has made a significant improvement in the turnaround time from positive culture to identification, but current protein-based approaches can struggle with species-level identification because of the high degree of homology within a genus. However, other MS-based strategies for bacterial identification that are based on lipids and small molecules have shown promise toward species-level identification and detection of specific phenotypes, including those related to antibiotic resistance. We are leveraging rapid gas-phase ion mobility (IM) separations coupled to MS to simultaneously detect the lipids and metabolites in bacterial pathogens. Using flow-injection (FI) rather than liquid chromatography (LC), we instead rely more directly on the structural separation of the IM dimension to resolve features from different biochemical classes and aid in identification. A head-to-head comparison demonstrates that the FI-IM-MS multiomic strategy performs similarly to LC-IM-MS in its ability to distinguish 24 strains of the high-concern ESKAPE pathogens, while shortening overall analysis time from 17 to 2 min per injection. We demonstrate that the IM dimension has excellent stability and reproducibility, which enables extracted IM peak areas to be used in lieu of chromatographic peak areas. Furthermore, the same features that are important for the discrimination of bacterial species and strains are found within both the FI-IM-MS and HILIC-IM-MS data sets. These results showcase the capabilities of mobility-enabled rapid multiomics and open the possibility to detect subtle strain-level differences and resistance phenotypes in bacterial pathogens by including additional classes of biomolecules.

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Publication Details

Journal
Analytical Chemistry
Published
2025-06-24
DOI
https://doi.org/10.1021/acs.analchem.5c00417
Citations
3
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
3.96

Funders

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article

Rapid Multi-Omics for Bacterial Identification Using Flow Injection–Ion Mobility–Mass Spectrometry

Jana M. Carpenter, Hannah M. Hynds, Kelly M. Hines
3 citations
Analytical Chemistry
Bacterial Identification and Susceptibility Testing
3.96
article

Rapid Multi-Omics for Bacterial Identification Using Flow Injection–Ion Mobility–Mass Spectrometry

Jana M. Carpenter, Hannah M. Hynds, Kelly M. Hines
article en
3 citations

Abstract

The implementation of mass spectrometry (MS) in clinical microbiology has made a significant improvement in the turnaround time from positive culture to identification, but current protein-based approaches can struggle with species-level identification because of the high degree of homology within a genus. However, other MS-based strategies for bacterial identification that are based on lipids and small molecules have shown promise toward species-level identification and detection of specific phenotypes, including those related to antibiotic resistance. We are leveraging rapid gas-phase ion mobility (IM) separations coupled to MS to simultaneously detect the lipids and metabolites in bacterial pathogens. Using flow-injection (FI) rather than liquid chromatography (LC), we instead rely more directly on the structural separation of the IM dimension to resolve features from different biochemical classes and aid in identification. A head-to-head comparison demonstrates that the FI-IM-MS multiomic strategy performs similarly to LC-IM-MS in its ability to distinguish 24 strains of the high-concern ESKAPE pathogens, while shortening overall analysis time from 17 to 2 min per injection. We demonstrate that the IM dimension has excellent stability and reproducibility, which enables extracted IM peak areas to be used in lieu of chromatographic peak areas. Furthermore, the same features that are important for the discrimination of bacterial species and strains are found within both the FI-IM-MS and HILIC-IM-MS data sets. These results showcase the capabilities of mobility-enabled rapid multiomics and open the possibility to detect subtle strain-level differences and resistance phenotypes in bacterial pathogens by including additional classes of biomolecules.

Analytical ChemistryVol. 97(26)
University of Georgia (US)
University of Georgia, Achievement Rewards for College Scientists Foundation
Openalex Percentile: Top 6%
Bacterial Identification and Susceptibility Testing
3.96
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