COMPARISON OF BACTERIA TAXONOMIC PROFILING METHODS VIA 16S RRNA GENE SEQUENCING USING ILLUMINA AND NANOPORE TECHNOLOGIES ON OIL SAMPLES
A. S. Burlachenko,
A. D. Nekrasova,
M. Yu. Donnikov,
A. M. Ermakov,
E. S. Zhdanova,
L. V. Kovalenko,
L. G. Danilov,
O. S. Glotov https://doi.org/10.35266/2949-3447-2025-2-11
Abstract
The use of modern sequencing methods enables us to determine the taxonomic biodiversity of various bacterial communities. Specifically, it allows to assess the diversity of bacterial strains that are not cultured. At present, there are two generations of sequencing technologies that enable the determination of microbial community diversity: 2nd generation (represented by Illumina and BGI) and 3rd generation (Nanopore and PacBio). However, as these technologies use different approaches to sequencing, there is a question of reproducibility of the results. This research revealed that using Illumina and Nanopore sequencing methods differs in terms of diversity indices and taxonomic diversity. This data emphasizes the requirement to develop advanced methods for sample preparation and DNA sequencing to achieve an unequivocal microbial community profile.
About the Authors
A. S. Burlachenko
Surgut State University, Surgut;
Pediatric Research and Clinical Center for Infectious Diseases under the Federal Medical Biological Agency, Saint Petersburg
Russian Federation
Russian Federation
Junior Researcher
A. D. Nekrasova
ООО “Cerbalab”, Saint Petersburg
Russian Federation
Russian Federation
Candidate of Sciences (Pharmaceutics), Bioinformatician
M. Yu. Donnikov
Surgut State University, Surgut
Russian Federation
Russian Federation
Geneticist, Candidate of Sciences (Medicine), Leading Researcher
A. M. Ermakov
Institute of Theoretical and Experimental Biophysics of Russian Academy of Sciences, Pushchino
Russian Federation
Russian Federation
Head of Laboratory
E. S. Zhdanova
Institute of Theoretical and Experimental Biophysics of Russian Academy of Sciences, Pushchino
Russian Federation
Russian Federation
Junior Researcher
L. V. Kovalenko
Surgut State University, Surgut
Russian Federation
Russian Federation
Doctor of Sciences (Medicine), Professor, Head of Pathophysiology and General Pathology Department, Director of Medical Institute
L. G. Danilov
Saint-Petersburg State University, Saint Petersburg
Russian Federation
Russian Federation
Junior Researcher
O. S. Glotov
Pediatric Research and Clinical Center for Infectious Diseases under the Federal Medical Biological Agency, Saint Petersburg
Russian Federation
Russian Federation
Doctor of Sciences (Biology), Head of the Experimental Medical Virology, Molecular Genetics and Biobanking Department
References
1. Rang F. J., Kloosterman W. P., de Ridder J. From squiggle to basepair: Computational approaches for improving nanopore sequencing read accuracy // Genome Biology. 2018. Vol. 19.
2. Wick R. R., Judd L. M., Gorrie C. L. et al. Completing bacterial genome assemblies with multiplex MinION sequencing // Microbial Genomics. 2017. Vol. 3, no. 10. https://doi.org/10.1099/mgen.0.000132.
3. Karst S. M., Dueholm M. S., McIlroy S. J. et al. Retrieval of a million high-quality, full-length microbial 16S and 18S rRNA gene sequences without primer bias // Nature Biotechnology. 2018. Vol. 36. P. 190–195. https://doi.org/10.1038/nbt.4045.
4. Kerkhof L. J., Dillon K. P., Häggblom M. M. et al. Profiling bacterial communities by MinION sequencing of ribosomal operons // Microbiome. 2017. Vol. 5.
5. Бурлаченко А. С., Данилов Л. Г., Глотов О. С. Оптимизация метода выделения бактериальной ДНК из нефтяных образцов // Бюллетень Оренбургского научного центра УрО РАН. 2024. № 4. С. 9.
6. Klindworth A., Pruesse E., Schweer T. et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies // Nucleic Acids Research. 2012. Vol. 41, no. 1.
7. Neubeck A., Sun L., Müller B. et al. Microbial community structure in a serpentine-hosted abiotic gas seepage at the Chimaera Ophiolite, Turkey // Applied and Environmental Microbiology. 2017. Vol. 83, no. 12.
8. The R Project for Statistical Computing. URL: https://www.r-project.org/ (дата обращения: 01.04.2025).
9. Callahan B. J., McMurdie P. J., Rosen M. J. et al. DADA2: Highresolution sample inference from Illumina amplicon data // Nature Methods. 2016. Vol. 13. P. 581–583. https://doi.org/10.1038/nmeth.3869.
10. Quast C., Pruesse E., Yilmaz P. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools // Nucleic Acids Research. 2013. Vol. 41. P. D590–D596. https://doi.org/10.1093/nar/gks1219.
11. McMurdie P. J., Holmes S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data // PLoS ONE. 2013. Vol. 8, no. 4. https://doi.org/10.1371/journal.pone.0061217.
12. Oksanen J., Simpson G. L., Blanchet F. G. et al. vegan: Community Ecology Package. URL: https://CRAN.R-project.org/package=vegan (дата обращения: 01.04.2025).
Review
For citations:
Burlachenko A.S., Nekrasova A.D., Donnikov M.Yu., Ermakov A.M., Zhdanova E.S., Kovalenko L.V., Danilov L.G., Glotov O.S. COMPARISON OF BACTERIA TAXONOMIC PROFILING METHODS VIA 16S RRNA GENE SEQUENCING USING ILLUMINA AND NANOPORE TECHNOLOGIES ON OIL SAMPLES. Vestnik SurGU. Meditsina. 2025;18(2):81-87. (In Russ.) https://doi.org/10.35266/2949-3447-2025-2-11
Views:
136
Email this article 
