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EDITORIAL article

Front. Microbiol., 11 November 2025

Sec. Systems Microbiology

Volume 16 - 2025 | https://doi.org/10.3389/fmicb.2025.1719919

This article is part of the Research TopicResources for Developing Plasmid DatabasesView all 8 articles

Editorial: Resources for developing plasmid databases

  • 1Faculty of Environment and Information Studies, Keio University, Fujisawa, Kanagawa, Japan
  • 2Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo, Japan
  • 3Faculty of Engineering, Shizuoka University, Shizuoka, Japan
  • 4Graduate School of Integrated Science and Technology, Shizuoka University, Shizuoka, Japan
  • 5Research Institute of Green Science and Technology, Shizuoka University, Shizuoka, Japan
  • 6Japan Collection of Microorganisms, RIKEN BioResource Research Center, Ibaraki, Japan

Editorial on the Research Topic
Resources for developing plasmid databases

Plasmids are extrachromosomal DNA elements that play pivotal roles in microbial metabolism, virulence, and antimicrobial resistance (AMR). By facilitating horizontal gene transfer, they drive rapid bacterial evolution and gene flow across diverse environments. Since the 1970s, plasmid studies have shaped our understanding of microbial genetics, with early pioneering work inspiring global efforts. Despite the vast accumulation of plasmid sequence data in international repositories, such as IMG/PR (Camargo et al., 2024) and PLSDB (Galata et al., 2018; Schmartz et al., 2022; Molano et al., 2024), existing databases suffer from misannotations, incompleteness, and data bias. Addressing these challenges requires a combination of expert knowledge, experimental validation, and innovative computational tools.

This Research Topic brings together contributions that span clinical case studies of AMR, evolutionary insights from environmental microbiology, and the development of bioinformatics methods and broad-host delivery vectors. Collectively, these works highlight both the urgency and opportunity to enhance the accuracy and utility of plasmid resources.

In the clinical domain, several studies underscore the continuing threat of plasmids carrying AMR genes, such as carbapenemase genes. A study on Klebsiella pneumoniae revealed IncX3 plasmids with blaNDM − 1 and a rare integron. In 1765, showing complex genetic architectures that complicate treatment options (Ma et al.). Complementary work on K. pneumoniae isolates from Pakistan revealed multiple plasmids encoding 34 resistance genes across six antimicrobial classes, suggesting intense plasmid exchange within a single hospital environment (Lascols et al.). Adding to this, the first report of blaNDM − 1-carrying Enterobacter chengduensis in China identified IncC plasmids and potential intrahospital clonal transmission (Fu et al.). Together, these case studies demonstrate how rapidly plasmids can disseminate AMR genes in diverse clinical settings, underscoring the urgent need for accurate plasmid characterization and surveillance.

Beyond the clinic, plasmids play crucial roles in environmental adaptation. Research on the acidophile Fervidacidithiobacillus caldus identified over 30 plasmids and 50 defense systems, revealing an inverse correlation between plasmid diversity and host defense complexity (Pacheco-Acosta et al.). In cyanobacteria, novel replication proteins (Slr6031 and Slr6090) were discovered on large plasmids of Synechocystis, expanding the repertoire of Rep factors and opening avenues for genetic engineering (Ohdate et al.). These findings broaden our understanding of plasmid biology, showing that their roles extend far beyond resistance to shaping microbial ecology and providing tools for biotechnology.

From a technological perspective, new strategies for harnessing plasmids are also emerging. A systematic analysis of antimicrobial resistant isolates identified 22 conjugative plasmids with broad host potential, offering a toolbox for microbiome engineering and synthetic biology (Loyola Irizarry and Brito). In parallel, computational innovation is exemplified by plASgraph2, which employs graph neural networks to classify plasmid contigs from assembly graphs with high accuracy even on short sequences (Sielemann et al.). These contributions demonstrate how the integration of large-scale datasets with advanced algorithms can accelerate plasmid discovery and classification.

Collectively, the works in this Research Topic trace a trajectory: from urgent case studies of AMR pathogens, through eco-evolutionary perspectives, to computational and engineering frameworks. Each study illuminates a facet of plasmid diversity, while all converge on a central challenge—how to curate, annotate, and interlink plasmid data to build reliable, accessible, and comprehensive resources. Looking forward, the integration of expert curation, innovative machine learning, and experimental validation will be indispensable for transforming plasmid databases into true knowledge bases. Such efforts will not only strengthen public health surveillance and antimicrobial stewardship but will also open new opportunities in microbial ecology, biotechnology, and synthetic biology. Ultimately, advancing plasmid resources requires interdisciplinary collaboration across clinical microbiology, environmental microbiology, computational biology, and bioengineering, a collective endeavor to unlock the full potential of plasmids as both a global challenge and a global resource.

Author contributions

HS: Writing – review & editing. MSu: Writing – review & editing. MSi: Writing – review & editing, Writing – original draft.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

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References

Camargo, A. P., Call, L., Roux, S., Nayfach, S., Huntemann, M., Palaniappan, K., et al. (2024). IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata. Nucleic Acids Res. 52, D164–D173. doi: 10.1093/nar/gkad964

PubMed Abstract | Crossref Full Text | Google Scholar

Galata, V., Fehlmann, T., Backes, C., and Keller, A. (2018). PLSDB: a resource of complete bacterial plasmids. Nucleic Acids Res. 47(D1), D195–D202. doi: 10.1093/nar/gky1050

PubMed Abstract | Crossref Full Text | Google Scholar

Molano, L.-A. G., Hirsch, P., Hannig, M., Müller, R., and Keller, A. (2024). The PLSDB 2025 update: enhanced annotations and improved functionality for comprehensive plasmid research. Nucleic Acids Res. 53(D1), D189–D196. doi: 10.1093/nar/gkae1095

PubMed Abstract | Crossref Full Text | Google Scholar

Schmartz, G. P., Hartung, A., Hirsch, P., Kern, F., Fehlmann, T., Müller, R., et al. (2022). PLSDB: advancing a comprehensive database of bacterial plasmids. Nucleic Acids Res. 50, D273–D278. doi: 10.1093/nar/gkab1111

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: plasmid, database, host, replication, antimicrobial resistance

Citation: Suzuki H, Suzuki M and Shintani M (2025) Editorial: Resources for developing plasmid databases. Front. Microbiol. 16:1719919. doi: 10.3389/fmicb.2025.1719919

Received: 07 October 2025; Accepted: 27 October 2025;
Published: 11 November 2025.

Edited by:

George Tsiamis, University of Patras, Greece

Reviewed by:

Vassiliki Karapapa, Municipality of Agrinio, Greece

Copyright © 2025 Suzuki, Suzuki and Shintani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Haruo Suzuki, aGFydW9Ac2ZjLmtlaW8uYWMuanA=; Masato Suzuki, c3V6dWtpLW1AbmlpZC5nby5qcA==; Masaki Shintani, c2hpbnRhbmkubWFzYWtpQHNoaXp1b2thLmFjLmpw

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.