1887

Abstract

The reconstruction of complete bacterial genomes is essential for microbial research, offering insights into genetic content, ontology and regulation. While Pacific Biosciences (PacBio) provides high-quality genomes, its cost remains a limitation. Oxford Nanopore Technologies (ONT) offers long reads at a lower cost, yet its error rate raises scepticism. Recent ONT advancements, such as new Flow cells (R10.4.1), chemistry (V14) and duplex mode, improve data quality. Our study compares ONT with PacBio and Illumina, including hybrid data. We used , a bacterium with a genome known for being difficult to reconstruct. By combining data from ONT’s Native Barcoding and a custom-developed BARSEQ method, we achieved high-quality, near-perfect genome assemblies. Our findings demonstrate, for the first time, that the combination of nanopore-only long-native with shorter PCR DNA reads (~3 kb) results in high-quality genome reconstruction, comparable to hybrid data assembly from two sequencing platforms. This endorses ONT as a cost-effective, stand-alone strategy for bacterial genome reconstruction. Additionally, we compared methylated motif detection between PacBio and ONT R10.4.1 data, showing that results comparable to PacBio are achievable using ONT, especially when utilizing the advanced Nanomotif tool.

Funding
This study was supported by the:
  • Milk Levy fund (Award CASSANDRA)
    • Principle Award Recipient: LukaszKrych
  • Horizon 2020 Framework Programme (Award H2020-MSCA-IF grant nr. 845658)
    • Principle Award Recipient: PaulinaDeptula
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2024-11-11
2024-12-09
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References

  1. Ghazi AR, Münch PC, Chen D, Jensen J, Huttenhower C. Strain identification and quantitative analysis in microbial communities. J Mol Biol 2022; 434:167582 [View Article] [PubMed]
    [Google Scholar]
  2. Zhao W, Zeng W, Pang B, Luo M, Peng Y et al. Oxford nanopore long-read sequencing enables the generation of complete bacterial and plasmid genomes without short-read sequencing. Front Microbiol 2023; 14: [View Article]
    [Google Scholar]
  3. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 2017; 13:e1005595 [View Article] [PubMed]
    [Google Scholar]
  4. Achaz G, Rocha EPC, Netter P, Coissac E. Origin and fate of repeats in bacteria. Nucleic Acids Res 2002; 30:2987–2994 [View Article] [PubMed]
    [Google Scholar]
  5. Siguier P, Perochon J, Lestrade L, Mahillon J, Chandler M. ISfinder: the reference centre for bacterial insertion sequences. Nucleic Acids Res 2006; 34:D32–6 [View Article] [PubMed]
    [Google Scholar]
  6. Eid J. Real-time DNA sequencing from single polymerase molecules. Science 1979; 323:133–138
    [Google Scholar]
  7. Ip CLC. MinION analysis and reference consortium: phase 1 data release and analysis. F1000Res 2015; 4:
    [Google Scholar]
  8. Delahaye C, Nicolas J. Sequencing DNA with nanopores: troubles and biases. PLoS One 2021; 16:e0257521 [View Article] [PubMed]
    [Google Scholar]
  9. Marx V. Method of the year: long-read sequencing. Nat Methods 2023; 20:6–11 [View Article]
    [Google Scholar]
  10. Zimin AV, Salzberg SL. The genome polishing tool POLCA makes fast and accurate corrections in genome assemblies. PLoS Comput Biol 2020; 16:e1007981 [View Article] [PubMed]
    [Google Scholar]
  11. Bouras G, Judd LM, Edwards RA, Vreugde S, Stinear TP et al. How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies. Microb Genom 2024; 10:001254 [View Article] [PubMed]
    [Google Scholar]
  12. Wick RR, Holt KE. Polypolish: short-read polishing of long-read bacterial genome assemblies. PLoS Comput Biol 2022; 18:e1009802 [View Article] [PubMed]
    [Google Scholar]
  13. Bouras G, Houtak G, Wick RR, Mallawaarachchi V, Roach MJ et al. Hybracter: enabling scalable, automated, complete and accurate bacterial genome assemblies. Microb Genom 2024; 10:001244 [View Article] [PubMed]
    [Google Scholar]
  14. Lerminiaux N, Fakharuddin K, Mulvey MR, Mataseje L. Do we still need illumina sequencing data? evaluating oxford nanopore technologies R10.4.1 flow cells and the rapid v14 library prep kit for gram negative bacteria whole genome assemblies. Can J Microbiol 2024; 70:178–189
    [Google Scholar]
  15. Wang Y, Zhao Y, Bollas A, Wang Y, Au KF. Nanopore sequencing technology, bioinformatics and applications. Nat Biotechnol 2021; 39:1348–1365 [View Article] [PubMed]
    [Google Scholar]
  16. Vilella A. Rhymes with haystack. In New Oxford Nanopore ‘Dark Mode’ Sequencing 2023
    [Google Scholar]
  17. Deptula P, Laine PK, Roberts RJ, Smolander O-P, Vihinen H et al. De novo assembly of genomes from long sequence reads reveals uncharted territories of Propionibacterium freudenreichii. BMC Genomics 2017; 18:790 [View Article] [PubMed]
    [Google Scholar]
  18. Ojala T, Laine PKS, Ahlroos T, Tanskanen J, Pitkänen S et al. Functional genomics provides insights into the role of Propionibacterium freudenreichii ssp. shermanii JS in cheese ripening. Int J Food Microbiol 2017; 241:39–48 [View Article] [PubMed]
    [Google Scholar]
  19. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 2015; 25:1043–1055 [View Article] [PubMed]
    [Google Scholar]
  20. Malik AC, Reinbold GW, Vedamuthu ER. An evaluation of the taxonomy of Propionibacterium. Can J Microbiol 1968; 14:1185–1191 [View Article] [PubMed]
    [Google Scholar]
  21. De Coster W, D’Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics 2018; 34:2666–2669 [View Article] [PubMed]
    [Google Scholar]
  22. Kolmogorov M, Yuan J, Lin Y, Pevzner PA. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 2019; 37:540–546 [View Article] [PubMed]
    [Google Scholar]
  23. Boostrom I, Portal EAR, Spiller OB, Walsh TR, Sands K. Comparing long-read assemblers to explore the potential of a sustainable low-cost, low-infrastructure approach to sequence antimicrobial resistant bacteria with oxford nanopore sequencing. Front Microbiol 2022; 13:796465 [View Article] [PubMed]
    [Google Scholar]
  24. Hall M. Rasusa: randomly subsample sequencing reads to a specified coverage. JOSS 2022; 7:3941 [View Article]
    [Google Scholar]
  25. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article] [PubMed]
    [Google Scholar]
  26. Chin C-S, Alexander DH, Marks P, Klammer AA, Drake J et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 2013; 10:563–569 [View Article] [PubMed]
    [Google Scholar]
  27. Hunt M, Silva ND, Otto TD, Parkhill J, Keane JA et al. Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biol 2015; 16:294 [View Article] [PubMed]
    [Google Scholar]
  28. Wick RR, Judd LM, Monk IR, Seemann T, Stinear TP. Improved genome sequence of Australian methicillin-resistant Staphylococcus aureus strain JKD6159. Microbiol Resour Announc 2023; 12:e0112922 [View Article] [PubMed]
    [Google Scholar]
  29. Wick RR, Judd LM, Holt KE. Assembling the perfect bacterial genome using Oxford Nanopore and Illumina sequencing. PLoS Comput Biol 2023; 19:e1010905 [View Article] [PubMed]
    [Google Scholar]
  30. Wick RR, Judd LM, Cerdeira LT, Hawkey J, Méric G et al. Trycycler: consensus long-read assemblies for bacterial genomes. Genome Biol 2021; 22:266 [View Article] [PubMed]
    [Google Scholar]
  31. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 2017; 27:722–736 [View Article] [PubMed]
    [Google Scholar]
  32. Vaser R, Šikić M. Time- and memory-efficient genome assembly with Raven. Nat Comput Sci 2021; 1:332–336 [View Article] [PubMed]
    [Google Scholar]
  33. Li H. Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 2016; 32:2103–2110 [View Article]
    [Google Scholar]
  34. Wick RR, Holt KE. Benchmarking of long-read assemblers for prokaryote whole genome sequencing. F1000Res 2019; 8:2138 [View Article] [PubMed]
    [Google Scholar]
  35. Chen Y, Nie F, Xie S-Q, Zheng Y-F, Dai Q et al. Efficient assembly of nanopore reads via highly accurate and intact error correction. Nat Commun 2021; 12: [View Article]
    [Google Scholar]
  36. Hu J, Wang Z, Sun Z, Hu B, Ayoola AO et al. NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads. Genome Biol 2024; 25:107 [View Article] [PubMed]
    [Google Scholar]
  37. Hu J, Fan J, Sun Z, Liu S. NextPolish: a fast and efficient genome polishing tool for long-read assembly. Bioinformatics 2020; 36:2253–2255 [View Article] [PubMed]
    [Google Scholar]
  38. Wick R. Yet Another ONT Accuracy Test: Dorado v0.5.0 2023 [View Article]
    [Google Scholar]
  39. Wick R. A perfect bacterial genome from pacbio hifi reads. Zenodo 2023 [View Article]
    [Google Scholar]
  40. Bouras G, Grigson SR, Papudeshi B, Mallawaarachchi V, Roach MJ. Dnaapler: a tool to reorient circular microbial genomes. JOSS 2024; 9:5968 [View Article]
    [Google Scholar]
  41. Li H. New strategies to improve minimap2 alignment accuracy. Bioinformatics 2021; 37:4572–4574 [View Article]
    [Google Scholar]
  42. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  43. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015; 31:3691–3693 [View Article] [PubMed]
    [Google Scholar]
  44. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article] [PubMed]
    [Google Scholar]
  45. Heidelbach S, Dall SM, Bøjer JS, Nissen J, van der Maas LNL et al. Nanomotif: identification and exploitation of dna methylation motifs in metagenomes using Oxford Nanopore Sequencing. Bioinformatics 2 3 [View Article]
    [Google Scholar]
  46. Crits-Christoph A, Kang SC, Lee HH, Ostrov N. MicrobeMod: a computational toolkit for identifying prokaryotic methylation and restriction-modification with nanopore sequencing. Microbiology [View Article]
    [Google Scholar]
  47. Clark TA, Murray IA, Morgan RD, Kislyuk AO, Spittle KE et al. Characterization of DNA methyltransferase specificities using single-molecule, real-time DNA sequencing. Nucleic Acids Res 2012; 40:e29 [View Article]
    [Google Scholar]
  48. Flusberg BA, Webster DR, Lee JH, Travers KJ, Olivares EC et al. Direct detection of DNA methylation during single-molecule, real-time sequencing. Nat Methods 2010; 7:461–465 [View Article] [PubMed]
    [Google Scholar]
  49. Korlach J, Turner SW. Going beyond five bases in DNA sequencing. Curr Opin Struct Biol 2012; 22:251–261 [View Article] [PubMed]
    [Google Scholar]
  50. Roberts RJ, Vincze T, Posfai J, Macelis D. REBASE: a database for DNA restriction and modification: enzymes, genes and genomes. Nucleic Acids Res 2023; 51:D629–D630 [View Article] [PubMed]
    [Google Scholar]
  51. Hiraoka S, Okazaki Y, Anda M, Toyoda A, Nakano S-I et al. Metaepigenomic analysis reveals the unexplored diversity of DNA methylation in an environmental prokaryotic community. Nat Commun 2019; 10:159 [View Article] [PubMed]
    [Google Scholar]
  52. Tourancheau A, Mead EA, Zhang XS, Fang G. Discovering multiple types of DNA methylation from bacteria and microbiome using nanopore sequencing. Nat Methods 2021; 18:491–498 [View Article] [PubMed]
    [Google Scholar]
  53. Laehnemann D, Borkhardt A, McHardy AC. Denoising DNA deep sequencing data-high-throughput sequencing errors and their correction. Brief Bioinform 2016; 17:154–179 [View Article] [PubMed]
    [Google Scholar]
  54. Petersen LM, Martin IW, Moschetti WE, Kershaw CM, Tsongalis GJ. Third-Generation Sequencing in the Clinical Laboratory: Exploring the Advantages and Challenges of Nanopore Sequencing 2019
    [Google Scholar]
  55. Sereika M, Kirkegaard RH, Karst SM, Michaelsen TY, Sørensen EA et al. Oxford Nanopore R10.4 long-read sequencing enables the generation of near-finished bacterial genomes from pure cultures and metagenomes without short-read or reference polishing. Nat Methods 2022; 19:823–826 [View Article] [PubMed]
    [Google Scholar]
  56. Sanderson ND, Kapel N, Rodger G, Webster H, Lipworth S et al. Comparison of R9.4.1/Kit10 and R10/Kit12 Oxford Nanopore flowcells and chemistries in bacterial genome reconstruction. Microb Genom 2023; 9:mgen000910 [View Article] [PubMed]
    [Google Scholar]
  57. Falentin H, Deutsch S-M, Jan G, Loux V, Thierry A et al. The complete genome of Propionibacterium freudenreichii CIRM-BIA1, a hardy actinobacterium with food and probiotic applications. PLoS One 2010; 5:e11748 [View Article] [PubMed]
    [Google Scholar]
  58. Meurice G, Jacob D, Deborde C, Chaillou S, Rouault A et al. Whole genome sequencing project of a dairy Propionibacterium freudenreichii subsp. shermanii genome: progress and first bioinformatic analysis. Lait 2004; 84:15–24
    [Google Scholar]
  59. Benjamini Y, Speed TP. Summarizing and correcting the GC content bias in high-throughput sequencing. Nucleic Acids Res 2012; 40:e72 [View Article] [PubMed]
    [Google Scholar]
  60. Chen YC, Liu T, Yu CH, Chiang TY, Hwang CC. Effects of GC bias in next-generation-sequencing data on de novo genome assembly. PLoS One 2013; 8:e62856 [View Article]
    [Google Scholar]
  61. Sato MP, Ogura Y, Nakamura K, Nishida R, Gotoh Y et al. Comparison of the sequencing bias of currently available library preparation kits for Illumina sequencing of bacterial genomes and metagenomes. DNA Res 2019; 26:391–398 [View Article] [PubMed]
    [Google Scholar]
  62. Wick R. Duplex basecalling for whole-genome assembly. Zenodo 2024 [View Article]
    [Google Scholar]
  63. Browne PD, Nielsen TK, Kot W, Aggerholm A, Gilbert MTP et al. GC bias affects genomic and metagenomic reconstructions, underrepresenting GC-poor organisms. Gigascience 2020; 9:giaa008 [View Article] [PubMed]
    [Google Scholar]
  64. Wick RR, Judd LM, Wyres KL, Holt KE. Recovery of small plasmid sequences via Oxford Nanopore sequencing. Microb Genom 2021; 7:000631 [View Article] [PubMed]
    [Google Scholar]
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