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Microorganisms
Volume 13
Issue 6
10.3390/microorganisms13061252
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Prediction of Antibiotic Resistance Genes in Cyanobacterial Strains by Whole Genome Sequencing

by
Duarte Balata
1,
Tânia Rosado
2,
Francisco Pina-Martins
1,
Vera Manageiro
3,4,5,
Carina Menezes
2,
Eugénia Ferreira
3,
Octávio S. Paulo
1,
Manuela Caniça
3,4,5 and
Elsa Dias
2,4,5,*
1
Centre for Ecology, Evolution and Environmental Changes (CE3C) & CHANGE—Global Change and Sustainability Institute, Faculty of Sciences, University of Lisbon, 1749-016 Lisbon, Portugal
2
Laboratory of Biology and Ecotoxicology, Department of Environmental Health, National Institute of Health Dr. Ricardo Jorge (INSA), 1649-016 Lisbon, Portugal
3
National Reference Laboratory of Antibiotic Resistance and Healthcare Associated Infections, Department of Infectious Diseases, National Institute of Health Dr. Ricardo Jorge, 1649-016, Lisbon, Portugal
4
Centre for the Studies of Animal Science (CECA), Institute of Agrarian and Agri-Food Sciences and Technologies, University of Porto, 4099-002 Porto, Portugal
5
Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), 1300-477 Lisbon, Portugal
*
Author to whom correspondence should be addressed.
Microorganisms 2025, 13(6), 1252; https://doi.org/10.3390/microorganisms13061252
Submission received: 16 April 2025 / Revised: 21 May 2025 / Accepted: 23 May 2025 / Published: 28 May 2025
(This article belongs to the Special Issue New Insights into the Antibiotic Resistance of Aquatic Microorganisms)
Versions Notes

Abstract

Cyanobacteria are ubiquitous in freshwater environments, but their role in aquatic resistome remains unclear. In this work, we performed whole genome sequencing on 43 cyanobacterial strains isolated from Portuguese fresh/wastewaters. From 43 available non-axenic unicyanoabacterial cultures (containing only one cyanobacterial strain and their co-occurring bacteria), it was possible to recover 41 cyanobacterial genomes from the genomic assemblies using a genome binning software, 26 of which were classified as high-quality based on completeness, contamination, N50 and contig number thresholds. By using the comprehensive antibiotic resistance database (CARD) on the assembled samples, we detected four antibiotic resistance gene (ARG) variants, conferring resistance in pathogenic bacteria to tetracyclines, fluoroquinolones (adeF-type) and macrolides (ermF-type, mefC-type and mphG-type). Among these, adeF-type was the most prevalent gene, found across 11 cyanobacterial genomes from the Nostocales order. Planktothrix presented the highest variety of close ARG matches, with hits for the macrolide resistance genes ermF-type, mefC-type and mphG-type. An analysis of the genomic assemblies also revealed an additional 12 ARGs in bacteria from the phyla Firmicutes, Proteobacteria and Bacteroidetes, present in the cyanobacterial cultures, foreseeing the horizontal gene transfer of ARGs with cyanobacteria. Additionally, more than 200 partial ARGs were detected on each recovered cyanobacterial genome, allowing for future studies of antibiotic resistance genotype/phenotype in cyanobacteria. These findings highlight the importance of further efforts to understand the role of cyanobacteria on the aquatic resistome from a One Health perspective.
Keywords: antibiotic resistance; aquatic resistome; freshwater bacteria; cyanobacteria; genome; bioinformatics pipeline antibiotic resistance; aquatic resistome; freshwater bacteria; cyanobacteria; genome; bioinformatics pipeline

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MDPI and ACS Style

Balata, D.; Rosado, T.; Pina-Martins, F.; Manageiro, V.; Menezes, C.; Ferreira, E.; Paulo, O.S.; Caniça, M.; Dias, E. Prediction of Antibiotic Resistance Genes in Cyanobacterial Strains by Whole Genome Sequencing. Microorganisms 2025, 13, 1252. https://doi.org/10.3390/microorganisms13061252

AMA Style

Balata D, Rosado T, Pina-Martins F, Manageiro V, Menezes C, Ferreira E, Paulo OS, Caniça M, Dias E. Prediction of Antibiotic Resistance Genes in Cyanobacterial Strains by Whole Genome Sequencing. Microorganisms. 2025; 13(6):1252. https://doi.org/10.3390/microorganisms13061252

Chicago/Turabian Style

Balata, Duarte, Tânia Rosado, Francisco Pina-Martins, Vera Manageiro, Carina Menezes, Eugénia Ferreira, Octávio S. Paulo, Manuela Caniça, and Elsa Dias. 2025. "Prediction of Antibiotic Resistance Genes in Cyanobacterial Strains by Whole Genome Sequencing" Microorganisms 13, no. 6: 1252. https://doi.org/10.3390/microorganisms13061252

APA Style

Balata, D., Rosado, T., Pina-Martins, F., Manageiro, V., Menezes, C., Ferreira, E., Paulo, O. S., Caniça, M., & Dias, E. (2025). Prediction of Antibiotic Resistance Genes in Cyanobacterial Strains by Whole Genome Sequencing. Microorganisms, 13(6), 1252. https://doi.org/10.3390/microorganisms13061252

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