Haworth-Duff, Adam, Smith, Barry L 
ORCID: 0000-0001-5571-3647, Sham, Tung-Ting, Boisdon, Cedric, Loughnane, Paul, Burnley, Mark, Hawcutt, Daniel B ORCID: 0000-0002-8120-6507, Raval, Rasmita and Maher, Simon
(2024)
Direct and Reagentless Atmospheric Pressure Photoionisation Mass Spectrometry: Rapid and Accurate Differentiation of Cystic Fibrosis Related Bacteria by Monitoring VOCs.
[Preprint]
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Abstract
<jats:title>Abstract</jats:title> <jats:p>Breath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person’s lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R<jats:sup>2</jats:sup> > 0.99 and limits of detection < 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples of Escherichia coli (EC), Pseudomonas aeruginosa (PSA) and Staphylococcus aureus (SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system.</jats:p>
| Item Type: | Preprint |
|---|---|
| Uncontrolled Keywords: | Lung, Clinical Trials and Supportive Activities, Prevention, Clinical Research, Bioengineering, Infection, 3 Good Health and Well Being |
| Divisions: | Faculty of Health and Life Sciences Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 21 Mar 2024 09:14 |
| Last Modified: | 11 Apr 2024 21:56 |
| DOI: | 10.21203/rs.3.rs-3976993/v1 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3179763 |
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