Surface enhanced Raman spectroscopy and machine learning for identification of beta-lactam antibiotics resistance gene fragment in bacterial plasmid
SERS-ML allowed express detection of bacterial plasmids containing a characteristic gene fragment up to the 10<sup>-7</sup> concentration of the initial plasmid, despite the complex composition of the biological sample, including the presence of interfering plasmids. Our approach offers a promising alternative to existing methods for monitoring antibiotic-resistant bacteria, characterized by its simplicity, low detection limit, and the potential for rapid and straightforward analysis.
Authors
- A. Trelin (ORCID: https://orcid.org/0000-0003-2829-2837)
- Alexandra G. Pershina (ORCID: https://orcid.org/0000-0001-7604-9722)
- Barbora Vokatá (ORCID: https://orcid.org/0000-0002-9580-2852)
- Oleksiy Lyutakov (ORCID: https://orcid.org/0000-0001-8781-9796)
- Olga Guselnikova (ORCID: https://orcid.org/0000-0002-2594-9605)
- Václav Švorčı́k (ORCID: https://orcid.org/0000-0003-0580-959X)
- Anastasia Skvortsova
Institutions
- National Research Tomsk State University (RU)
- Siberian State Medical University (RU)
- Tomsk Polytechnic University (RU)
- University of Chemistry and Technology, Prague (CZ)
Publication Details
- Journal
- Analytica Chimica Acta
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1016/j.aca.2024.343118
- Citations
- 8
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 5.30
Funders
- European Commission
- Ministerstvo Školství, Mládeže a Tělovýchovy
- Grantová Agentura České Republiky