Evidence map›Paper›PMID 41728957›Full record

ArticleNucleic acids research2026

Diversity and distribution of bacterial DNA polymerases.

Kęstutis Timinskas, Darius Kazlauskas, Albertas Timinskas, Česlovas Venclovas

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kęstutis TiminskasInstitute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, Vilnius, LT-10257, Lithuania.
Darius KazlauskasInstitute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, Vilnius, LT-10257, Lithuania.ORCID 0000-0001-6135-8549
Albertas TiminskasInstitute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, Vilnius, LT-10257, Lithuania.
Česlovas VenclovasInstitute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, Vilnius, LT-10257, Lithuania.ORCID 0000-0002-4215-0213

Funding

Lithuanian Research Library Consortium LMBA affiliatedResearch Council of Lithuania S-MIP-24-82
6 · The paper itself

Abstract

DNA polymerases are key players in DNA replication, repair, and maintenance. However, the overall abundance, diversity, and distribution of bacterial DNA polymerases have not been systematically explored. To close this knowledge gap, we computationally identified and characterized DNA polymerases and their homologs from A, B, C, X, and Y families in over 3000 representative bacterial species with complete genomes. We found that Y-family is the most abundant, followed by C and A families, whereas B and X families are rare. All species have replicative C-family polymerases, 96% have A-family polymerases, and 88% have Y-family members. In each family, we identified and annotated distinct groups, proofreading nucleases, and interaction motifs. Based on conserved associations for DnaE2 and Y-family groups, we identified 11 types of putative multimeric error-prone DNA polymerases supported by AlphaFold modeling. Approximately 90% of the complexes belong to four major types, exemplified by Meiothermus silvanus PolY-RecA complex, Mycobacterium tuberculosis ImuA-ImuB-DnaE2, Escherichia coli Pol V (UmuC-UmuD'2-RecA), and Bacillus subtilis YqjW-YqjX-RecA. We found that distribution patterns of distinct polymerase groups and multimeric complexes are shaped by bacterial lineages, replication-system types, and environmental factors. Our results thus provide a comprehensive picture of DNA polymerase diversity and distribution across the bacterial domain.

Indexed as

BacteriaBacterial ProteinsDNA-Directed DNA PolymeraseDNA ReplicationGenome, BacterialModels, MolecularPhylogenyBacterial ProteinsDNA-Directed DNA Polymerase

Identifiers

PMID41728957
PMCPMC12926913

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.