Skip to main content
DORAS
DCU Online Research Access Service
Login (DCU Staff Only)
Multi-strain volatile profiling of pathogenic and commensal cutaneous bacteria

Fitzgerald, Shane ORCID: 0000-0002-6570-4485, Duffy, Emer ORCID: 0000-0003-4557-6487, Holland, Linda ORCID: 0000-0002-0103-0151 and Morrin, Aoife ORCID: 0000-0003-1061-8528 (2020) Multi-strain volatile profiling of pathogenic and commensal cutaneous bacteria. Scientific Reports, 10 . ISSN 2045-2322

Full text available as:

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
2MB

Abstract

The detection of volatile organic compounds (VOC) emitted by pathogenic bacteria has been proposed as a potential non-invasive approach for characterising various infectious diseases as well as wound infections. Studying microbial VOC profiles in vitro allows the mechanisms governing VOC production and the cellular origin of VOCs to be deduced. However, inter-study comparisons of microbial VOC data remains a challenge due to the variation in instrumental and growth parameters across studies. In this work, multiple strains of pathogenic and commensal cutaneous bacteria were analysed using headspace solid phase micro-extraction coupled with gas chromatography–mass spectrometry. A kinetic study was also carried out to assess the relationship between bacterial VOC profiles and the growth phase of cells. Comprehensive bacterial VOC profiles were successfully discriminated at the species-level, while strain-level variation was only observed in specific species and to a small degree. Temporal emission kinetics showed that the emission of particular compound groups were proportional to the respective growth phase for individual S. aureus and P. aeruginosa samples. Standardised experimental workflows are needed to improve comparability across studies and ultimately elevate the field of microbial VOC profiling. Our results build on and support previous literature and demonstrate that comprehensive discriminative results can be achieved using simple experimental and data analysis workflows.

Item Type:Article (Published)
Refereed:Yes
Additional Information:Article number: 17971
Uncontrolled Keywords:Bacteria; Bioanalytical chemistry; Mass spectrometry
Subjects:Biological Sciences > Biochemistry
Biological Sciences > Microbiology
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Science and Health > School of Biotechnology
DCU Faculties and Schools > Faculty of Science and Health > School of Chemical Sciences
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Publisher:Nature Research
Official URL:https://dx.doi.org/10.1038/s41598-020-74909-w
Copyright Information:© 2020 The Authors. Open Access (CC-BY 4.0)
Funders:Insight SFI Research Centre for Data Analytics under the Science Foundation Ireland (SFI) Supplemental PhD funding scheme. E., European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska-Curie Grant agreement number 796289
ID Code:27391
Deposited On:26 Jul 2022 10:47 by Thomas Murtagh . Last Modified 27 Jul 2022 12:03

Downloads

Downloads per month over past year

Archive Staff Only: edit this record

Altmetric
- Altmetric
+ Altmetric
  • Student Email
  • Staff Email
  • Student Apps
  • Staff Apps
  • Loop
  • Disclaimer
  • Privacy
  • Contact Us