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Research

My research interests cover various topics of microbial genomics from development of new methodology and their application for medical purposes to fundamental questions of genome organization and evolution. Current projects I am working on are:

Detecting the impact of large-scale genomic features on bacterial phenotypes

Research picture

The main goal of the project is to connect the structural variants with phenotypic changes and to understand the underlying molecular mechanisms connecting them. There are two main processes that generate the variability that can be leveraged to explore the genotype to phenotype connection: parallel adaptation to new environments (e.g. new ecological niche or host organism) and small colony variation (sustaining variability of phenotypes in pathogenic populations to avoid the host organism’s immune system response).

The project is supported by the FWF grant #ESP 253-B

Role of gene paralogs in bacterial chromosome maintainance

Research picture

The project aims to investigate the patterns on genomic repeats across the circular bacterial chromosome to reveal interplay between chromosome topology and gene paralogization. Copy number variation is the important genomic trait associated with bacterial phenotype. In particular, number of rRNA gene operons is species-specific and supposed to be associated with ecological niches. On the other hand, such genomic repeats provide substrates for intra-genomic recombination leading to genome rearrangements. We assume that recombination events as well as composition of genomic repeats are shaped by selection forces balancing profit and damages on different levels of chromosome organization.

The project is supported by the FWF grant #ESP 253-B

Machine learning and phylogenetic analysis for prediction of antibiotic resistance

*A collaboration with Prof. Olga Kalinina, HIPS Germany

Research picture

The project is aimed to develop ML models for discovery of antibiotics resistance markers. phylogeny-related measure to increase the performance of machine learning models. We introduce a novel phylogeny-related parallelism score (PRPS), which measures whether a certain feature is correlated with the population structure of a set of samples. We demonstrate that PRPS can be used, in combination with SVM- and random forest-based models, to reduce the number of features in the analysis, while simultaneously increasing models’ performance.

The project is supported by the FWF grant #ESP 253-B

preprint

Role of non-canonical start codons in bacteria

*A collaboration with Prof. Calin Guet, IST Austria

Research picture

The project is aimed to reconstruct the evolution of start codons in bacterial genes While ATG starts are most common among bacteria genes, TTG and GTG codons are also present in genomes. For example, an analysis of 620 bacterial genomes revealed that ~80% of annotated genes initiate at AUG codons, ~12% at GUG and ~8% at UUG, with variable incidences of AUU and AUC across species citation. In our research we reconstruct the evolution of genes with weak start codons and analyse the functions of these genes.

Fitness effects of short random peptides

*A collaboration with Prof. Dan I. Andersson, Uppsala University and Dr. Roderich Кromhild, IST Austria

Research picture

The project is aimed to estimate the distribution of fitness effects of random non-coding DNA in microbial cells. It is generally assumed that new genes arise through duplication and/or recombination of existing genes. Previous experimental work confirmed that new functional genes could arise out of random non-coding DNA. In our research we estimate the fitness effects of de-novo transcribed random DNA in E. coli.

Development of bioinformatic tools for detection and analysis of large-scale genomic variants in bacterial genomes

*A collaboration with Dr. Nikita Alexeev

Research picture

The project aims to develop bioinformatic software to detect large-sclae genomic variants in bacterial genomes and linked them with bacterial phenotypes. We have developed a strategy for extract information form genomic data to detect parallel rearrangements in bacterial populations. The approach will be used for the study of rapid emergence of new bacterial phenotypes, understanding the molecular basis of antibiotic resistance mechanisms and formation of small colony variants, and the study of the selective forces in genomic evolution underlying complex phenotypes. The application of this approach and the concomitant understanding of connections between detected genome rearrangements and medically-relevant phenotypes may contribute to the efficient development of drugs and vaccines.

The PaReBrick toolkit Paper

Origin and evolution of the multi-chromosome bacterial genomes

*A collaboration with Prof. Mikhail Gelfand

Research picture

The project aims to understand organization and evolutionary benefits of bacterial genomes with secondary replicons. Most bacterial genomes have a single chromosome that may be supplemented by a few smaller, dispensable plasmids. But approximately 10% of the bacteria with completely sequenced genome, mostly pathogens and plant symbionts, have essential megaplasmids and/or chromids. However, the advantages of multi­chromosomal genome organiza­tion remain unclear.

The project was supported by the Marie Skłodowska­Curie Grant No. 754411.

Conference paper, Preprint

Evolution of virulence factors in human-host and non-human-host invasive Escherichia

Research picture

The project aims to describe composition and evolution of ipaH genes, effectors of Type 3 secretion system, in pathogens of different hosts. These genes are key factors of Shigella invasion that which are used for disease genotyping. Until recently, Shigella were thought to be primate-restricted pathogens. However, recent genomic studies confirmed ipaH genes in genome of Escherichia marmotae, a potential marmot pathogen, and of an E. coli extracted from fecal samples of bovine calves, suggesting that non-human hosts may also be infected by these potentially pathogenic to humans strains. We employ a computational approach to predict whether different Escherichia may also be an infectious agent of non-human hosts, which, therefore, may serve as a reservoir of human pathogens and virulence genes.

Paper

Сooperation partners:

2023-present Prof. David Berry, University of Vienna, Vienna, Austria. Project: Identification of shafflons in gut microbiomes. 2022-present Prof. Fyodor Kondrashov, OIST, Okinawa, Japan. Project: Selection forces in multipartite bacterial genomes. 2022-present Prof. Calin Guet IST Austria, Klosterneuburg, Austria. Project: Conservation of non-canonical start codons in mar operon genes. 2022-present Prof. Olga Kalinina, Helmholtz Institute for Pharmazeutical Research Saarland (HIPS), Germany. Project: Machine learning and phylogenetic analysis improves predicting antibiotic resistance in M. tuberculosis 2021-present Prof. Dan I. Andersson, Uppsala University, Sweden. Project: Fitness effects of short random peptides. 2021-present Prof. Mikhail Gelfand, IITP RAS, Russia. Project: Evolution of multi-partite genomes. 2020-2022 Dr. Nikita Alexeev, ITMO University, Saint Petersburg, Russia. Project: Development of the bioinformatic toolkit for whole-genome analysis. 2020-2022 Prof. Christoph Gasche, Medical University of Vienna, Vienna, Austria. Project: Genetic factors under biofilms formation in pathogenic E.coli. 2016-2018 Prof. Marc Robinson-Rechavi, Evolutionary Bioinformatics Lab, Department of Ecology and Evolution, Université de Lausanne, Lausanne, Switzerland. Project: Positive selection and horizontal gene transfer in prokaryotes. 2010-2014 Prof. Pavel Pevzner, University of California at San Diego, California, USA. Project: Application of the MGRA (Multiple Genome Rearrangements and Ancestors) algorithm to microbial data.