Dr. Olga Bochkareva

Postdoctoral Researcher at the Centre for Microbiology and Environmental Systems Science

I’m working on the intersection of comparative genomics, algorithmic biology, and evolutionary biology to build a deep understanding of bacterial genome organization and the molecular mechanisms providing complex dynamic genotype-phenotype connections. How many genotypes are present simultaneously in a pure bacterial colony? What is responsible for the rates of genotype switching in a one cell line? What are the limitations of the classic model ‘one bacterial colony - one genome’ which is still a basis of genome assemblers? To answer these fundamental question, I established the “Bacterial genome instability’ research group. Under the confines of a single laboratory we develop computational methods and set-up experimental assays of engineered cultures to study complex genetic mechanisms leading to bacterial adaptation to dynamic environments characterized by multiple pressures: fluctuating nutrient availability, phages, host immune system etc.

Research Topics and Interests

molecular mechanisms of phase variation, their impact on colony fitness in diverse environment
dynamics of genotypes in pure bacterial colonies
bacteria - host cells and bacteria - phage interactions and co-evolution

Research Projects

Genotype-phenotype heterogeneity of bacterial colonies

CUBE Research Topics

Understanding the genotype to phenotype connection is one of the key open questions in biology.

Funding and Awards

2022 ESPRIT Programme (“Early Stage Programme: Research, Innovation and Training”), funding from Austrian Science Fund (FWF), total amount – 294.015€

2019 ISTplus postdoctoral fellowship, funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 754411.

Publications

Jain K, Hauschild R, Bochkareva OO, Roemhild R, Tkačik G, Guet CC. Pulsatile basal gene expression as a fitness determinant in bacteria. Proceedings of the National Academy of Sciences of the United States of America. 2025 Apr 7;122(15):e2413709122. doi: 10.1073/pnas.2413709122

Yurtseven A, Buyanova S, Agrawal AA, Bochkareva O, Kalinina O. Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis. BMC Microbiology. 2023 Dec 20;23(1):404. Epub 2023 Sept. doi: 10.1186/s12866-023-03147-7

Vostokova E, Dranenko N, Gelfand MS, Bochkareva O. Genome rearrangements drive evolution of ANK genes in Wolbachia. bioRxiv : the preprint server for biology. 2023 Oct 27. doi: 10.1101/2023.10.25.563763