Přehled
Title: Real-time identification of pathogenic bacteria during nanopore sequencing
Study program: Biomedical Technology and Bioinformatics
Supervisor: Ing. Helena Vítková, Ph.D.
Topic description:
Recent advances in third-generation sequencing technologies have enabled routine DNA sequencing of microbial samples in clinical practice. This greatly increases our ability to identify and analyze dangerous bacterial species and allows a more effective approach preventing their spread in the human population. Although the whole-genome sequencing is becoming a leading technique in clinical microbiology, its full-scale deployment is still limited by the high time and computational demands of sequencing data processing. Analysis of sequencing data still takes from tens of hours, for individual samples, to days and weeks for massive deployment of parallelized sequencing of large numbers of
samples. The most time-consuming phase of this process is basecalling, i.e. decoding DNA from the „raw“ signals. For nanopore sequencing, this phase starts during the sequencing run and for the highprecision models required for clinical diagnostics, it continues for days after the sequencing run is complete. The topic of this dissertation is focused on designing a new method based on machine learning techniques to identify features of bacterial resistance and virulence directly from raw signals without the need to decode the DNA sequence. The advantage of this approach is that complete genetic information of the bacteria is not needed to identify these features, only the partial information available during the first hours of the sequencing run is sufficient. Thus, identification of potential epidemiological risks can be achieved before the sequencing run is finished.
The project will be primarily carried out at the Department of Biomedical Engineering, with expected collaboration with the Center for Molecular Biology and Genetics, FN Brno, and Mendel University in Brno. PhD students will complete six-month internships at prestigious partner universities abroad as part of their studies. DBME provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.
Your task:
- Develop advanced computational methods for the identification of bacterial pathogens.
- Present your research at international conferences and publish in scientific journals.
- Write and submit applications for junior research funding (e.g., PhD Talent, IGA, etc.).
Requirements:
- Proficiency in programming (e.g., Python, R); experience with Linux-based environments and Bash scripting is an advantage.
- Basic experience with bioinformatics tools and software applications.
- Strong analytical thinking and ability to work independently as well as in a research team.
- English proficiency allowing effective communication, writing, and presenting.
We offer:
- Participation in GAČR and AZV projects addressing current and relevant scientific challenges.
- Being part of a progressive and growing research team (BioSys_BUT).
- Opportunity to present research findings at prestigious international conferences.
- Flexible working hours, the possibility of home office, and team-building activities.
For more information about this topic please contact Helena Vítková – vitkovah@vut.cz
Relevant publications:
Can Firtina et al. RawHash: enabling fast and accurate real-time analysis of raw nanopore signals for large genomes, Bioinformatics, 2023, doi: 10.1093/bioinformatics/btad272
How to apply:
Please apply and submit your motivation letter and CV via university website from April 1 to April 30, https://www.vut.cz/eprihlaska/cs/zadani/vybrat-obor/fakulta/5
Funding:
Funding is provided as a combination of part-time or full-time research projects and/or regular scholarships.
