Evgeniia Igosheva
Education:
Master’s degree in Human nutrition (2021-2023)
Bachelor’s degree in Food Science and Technology (2015-2019)
Research areas:
Food science
Brief description of the P.h.D. project:
MALDI-TOF mass spectrometry is currently the gold-standard for rapid microbial identification. The promising use of MALDI-TOF for bacterial typing, direct diagnostics, and rapid identification of antibiotic resistance is reported, as well as use of Artificial Intelligence (AI) techniques in the field of microbiology for the construction of informative and predictive models from complex biological data. The protein mass spectra profiles obtained from MALDI-TOF in combination with the training of AI algorithms may assess intra and inter species genetic diversity among strains. Nonetheless, its real application in food safety is scarce, and it suffers from several drawbacks. The research aims are to:
1) develop rapid diagnostic methods for the detection of foodborne pathogens directly from food
2) investigate the strains’ virulence and antimicrobial resistance
3) create a mass spectra profiles’ database of pathogenic strains isolated from human, animal, food and environment
4) develop training of Machine learning algorithms for typing screening studies.
This work will better clarify the role that MALDI-TOF may play in surveillance systems and will create a multidisciplinary and low-cost network.
Supervisor and co-supervisor:
Prof. Federica Giacometti
Prof. Cristian Taccioli
Publications:
https://scholar.google.com/citations?user=zzlgkV8AAAAJ&hl=ru&oi=ao
Contacts:
