Publication detail

Bacterial phenotype prediction based on methylation site profiles

NYKRÝNOVÁ, M. BEZDÍČEK, M. LENGEROVÁ, M. ŠKUTKOVÁ, H.

Original Title

Bacterial phenotype prediction based on methylation site profiles

Type

conference paper

Language

English

Original Abstract

Methylated site mapping in the DNA sequences plays a key role in understanding the physiology and pathology of cells and organisms. Thanks to third-generation DNA sequencers, these epigenetic modifications can be detected already when reading genetic information. Therefore, not only genotypic classification but also phenotypic specifications can be determined based on a single sequencing run. However, for phenotyping purposes, there is still a lack of effective standardized tools to design uniform classification schemes for different laboratories. Here, we present a simple tool for comparing DNA methylation site profiles, utilizing sequencing reads mapping to the reference genome similar to core genome analysis in bacterial genotyping. The proposed pipeline maps sequence reads with marked positions of methylated bases to a single representative reference. Thus the output consists of the uniformly aligned methylated site positions in a set of bacterial genomes. This allows for the evaluation of common methylated sites across all genomes, i.e. ,,core methylome”, as well as unique methylated sites in gene and intergenic regions. Thus, determining the sequence type can be further refined by predicting bacterial behaviour such as antibiotic resistance or virulence.

Keywords

methylation; 5mC; phenotype; bacteria; nanopore sequencing

Authors

NYKRÝNOVÁ, M.; BEZDÍČEK, M.; LENGEROVÁ, M.; ŠKUTKOVÁ, H.

Released

29. 8. 2023

Publisher

IEEE

ISBN

979-8-3503-1017-7

Book

2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Pages from

1

Pages to

6

Pages count

6

URL

BibTex

@inproceedings{BUT184591,
  author="Markéta {Jakubíčková} and Matěj {Bezdíček} and Martina {Lengerová} and Helena {Vítková}",
  title="Bacterial phenotype prediction based on methylation site profiles",
  booktitle="2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)",
  year="2023",
  pages="6",
  publisher="IEEE",
  doi="10.1109/CIBCB56990.2023.10264900",
  isbn="979-8-3503-1017-7",
  url="https://ieeexplore.ieee.org/document/10264900"
}