A high fidelity approach to assembling the complex Borrelia genome.
Borrelia burgdorferi
De novo assembly
Genome reconstruction pipeline
Genomics
HiFi sequencing
Plasmids
Journal
BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258
Informations de publication
Date de publication:
17 Jul 2023
17 Jul 2023
Historique:
received:
16
03
2023
accepted:
30
06
2023
medline:
19
7
2023
pubmed:
18
7
2023
entrez:
17
7
2023
Statut:
epublish
Résumé
Bacteria of the Borrelia burgdorferi sensu lato (s.l.) complex can cause Lyme borreliosis. Different B. burgdorferi s.l. genospecies vary in their host and vector associations and human pathogenicity but the genetic basis for these adaptations is unresolved and requires completed and reliable genomes for comparative analyses. The de novo assembly of a complete Borrelia genome is challenging due to the high levels of complexity, represented by a high number of circular and linear plasmids that are dynamic, showing mosaic structure and sequence homology. Previous work demonstrated that even advanced approaches, such as a combination of short-read and long-read data, might lead to incomplete plasmid reconstruction. Here, using recently developed high-fidelity (HiFi) PacBio sequencing, we explored strategies to obtain gap-free, complete and high quality Borrelia genome assemblies. Optimizing genome assembly, quality control and refinement steps, we critically appraised existing techniques to create a workflow that lead to improved genome reconstruction. Despite the latest available technologies, stand-alone sequencing and assembly methods are insufficient for the generation of complete and high quality Borrelia genome assemblies. We developed a workflow pipeline for the de novo genome assembly for Borrelia using several types of sequence data and incorporating multiple assemblers to recover the complete genome including both circular and linear plasmid sequences. Our study demonstrates that, with HiFi data and an ensemble reconstruction pipeline with refinement steps, chromosomal and plasmid sequences can be fully resolved, even for complex genomes such as Borrelia. The presented pipeline may be of interest for the assembly of further complex microbial genomes.
Sections du résumé
BACKGROUND
BACKGROUND
Bacteria of the Borrelia burgdorferi sensu lato (s.l.) complex can cause Lyme borreliosis. Different B. burgdorferi s.l. genospecies vary in their host and vector associations and human pathogenicity but the genetic basis for these adaptations is unresolved and requires completed and reliable genomes for comparative analyses. The de novo assembly of a complete Borrelia genome is challenging due to the high levels of complexity, represented by a high number of circular and linear plasmids that are dynamic, showing mosaic structure and sequence homology. Previous work demonstrated that even advanced approaches, such as a combination of short-read and long-read data, might lead to incomplete plasmid reconstruction. Here, using recently developed high-fidelity (HiFi) PacBio sequencing, we explored strategies to obtain gap-free, complete and high quality Borrelia genome assemblies. Optimizing genome assembly, quality control and refinement steps, we critically appraised existing techniques to create a workflow that lead to improved genome reconstruction.
RESULTS
RESULTS
Despite the latest available technologies, stand-alone sequencing and assembly methods are insufficient for the generation of complete and high quality Borrelia genome assemblies. We developed a workflow pipeline for the de novo genome assembly for Borrelia using several types of sequence data and incorporating multiple assemblers to recover the complete genome including both circular and linear plasmid sequences.
CONCLUSION
CONCLUSIONS
Our study demonstrates that, with HiFi data and an ensemble reconstruction pipeline with refinement steps, chromosomal and plasmid sequences can be fully resolved, even for complex genomes such as Borrelia. The presented pipeline may be of interest for the assembly of further complex microbial genomes.
Identifiants
pubmed: 37460975
doi: 10.1186/s12864-023-09500-4
pii: 10.1186/s12864-023-09500-4
pmc: PMC10353223
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
401Informations de copyright
© 2023. The Author(s).
Références
Genome Res. 2020 Sep;30(9):1291-1305
pubmed: 32801147
Nucleic Acids Res. 2016 Aug 19;44(14):6614-24
pubmed: 27342282
BMC Genomics. 2017 Feb 15;18(1):165
pubmed: 28201991
Trends Microbiol. 2002 Feb;10(2):74-9
pubmed: 11827808
PLoS One. 2018 Jun 11;13(6):e0198135
pubmed: 29889842
PLoS Pathog. 2018 May 29;14(5):e1007106
pubmed: 29813137
Nat Methods. 2013 Jun;10(6):563-9
pubmed: 23644548
Genome Announc. 2016 Jul 14;4(4):
pubmed: 27417836
Brief Bioinform. 2008 Jul;9(4):299-306
pubmed: 18417537
Plasmid. 2013 Sep;70(2):161-7
pubmed: 23727020
Curr Issues Mol Biol. 2021;42:409-454
pubmed: 33328355
J Bacteriol. 2017 Feb 28;199(6):
pubmed: 28069820
Int J Syst Evol Microbiol. 2020 Feb;70(2):849-856
pubmed: 31793856
Bioinformatics. 2016 Apr 1;32(7):1009-15
pubmed: 26589280
Appl Environ Microbiol. 2013 Jul;79(13):4115-28
pubmed: 23624478
BMC Genomics. 2018 Mar 27;19(1):218
pubmed: 29580205
PLoS One. 2016 Dec 28;11(12):e0168994
pubmed: 28030649
Bioinformatics. 2007 Nov 1;23(21):2947-8
pubmed: 17846036
Nature. 1997 Dec 11;390(6660):580-6
pubmed: 9403685
Mol Microbiol. 1997 Nov;26(3):581-96
pubmed: 9402027
Infect Genet Evol. 2018 Dec;66:72-81
pubmed: 30240834
Genome Biol. 2013;14(9):R101
pubmed: 24034426
Genome Res. 2012 Nov;22(11):2270-7
pubmed: 22829535
Mol Phylogenet Evol. 2019 Feb;131:93-98
pubmed: 30423440
BMC Genomics. 2020 Jan 6;21(1):16
pubmed: 31906865
Mol Microbiol. 2000 Feb;35(3):490-516
pubmed: 10672174
Nat Rev Microbiol. 2012 Jan 09;10(2):87-99
pubmed: 22230951
Ticks Tick Borne Dis. 2021 Sep;12(5):101766
pubmed: 34161868
Microbiol Resour Announc. 2019 Dec 12;8(50):
pubmed: 31831613
J Bacteriol. 2004 Jul;186(13):4134-41
pubmed: 15205414
Int J Syst Evol Microbiol. 2013 Nov;63(Pt 11):4284-4288
pubmed: 23838444
Annu Rev Microbiol. 2010;64:185-202
pubmed: 20536352
J Bacteriol. 2002 Dec;184(23):6403-5; discusion 6405
pubmed: 12426324
Genome Biol. 2020 Sep 14;21(1):245
pubmed: 32928274
Mol Microbiol. 2018 Jan;107(1):104-115
pubmed: 29105221
Infect Genet Evol. 2011 Oct;11(7):1545-63
pubmed: 21843658
J Bacteriol. 1996 Jun;178(11):3357-61
pubmed: 8655522
Sci Rep. 2018 Jul 12;8(1):10552
pubmed: 30002414
Genome Res. 2017 May;27(5):737-746
pubmed: 28100585
Genome Announc. 2017 Feb 2;5(5):
pubmed: 28153903
Science. 1987 Jul 24;237(4813):409-11
pubmed: 3603026
Nat Biotechnol. 2019 Oct;37(10):1155-1162
pubmed: 31406327
Nat Rev Microbiol. 2006 Sep;4(9):660-9
pubmed: 16894341
Genome Announc. 2018 Jan 4;6(1):
pubmed: 29301891
BMC Genomics. 2013 Oct 10;14:693
pubmed: 24112474
BMC Genomics. 2017 May 30;18(1):422
pubmed: 28558786
Mol Biol Evol. 2013 Dec;30(12):2725-9
pubmed: 24132122
Curr Opin Microbiol. 2015 Feb;23:110-20
pubmed: 25461581
BMC Genomics. 2020 Oct 8;21(1):702
pubmed: 33032522
Genome Announc. 2017 Sep 14;5(37):
pubmed: 28912318
Gene. 2009 Sep 15;445(1-2):26-37
pubmed: 19505540
J Comput Biol. 2012 May;19(5):455-77
pubmed: 22506599
Zentralbl Bakteriol Mikrobiol Hyg A. 1986 Dec;263(1-2):112-8
pubmed: 3577473
Mol Biol Evol. 2018 Feb 1;35(2):518-522
pubmed: 29077904
Mol Biol Evol. 2015 Jan;32(1):268-74
pubmed: 25371430
Lancet Infect Dis. 2016 Jun;16(6):637-638
pubmed: 27301919
Lancet. 2012 Feb 4;379(9814):461-73
pubmed: 21903253
Bioinformatics. 2013 Apr 15;29(8):1072-5
pubmed: 23422339
Mol Microbiol. 2007 Jun;64(5):1358-74
pubmed: 17542926
Mol Microbiol. 1990 May;4(5):811-20
pubmed: 2388560
Ticks Tick Borne Dis. 2015 Apr;6(3):344-51
pubmed: 25766392
PLoS One. 2012;7(3):e33280
pubmed: 22432010
Mol Ecol. 2023 Feb;32(4):786-799
pubmed: 36461660
J Mol Microbiol Biotechnol. 2000 Oct;2(4):401-10
pubmed: 11075912
BMC Bioinformatics. 2009 Dec 15;10:421
pubmed: 20003500
J Mol Biol. 1990 Oct 5;215(3):403-10
pubmed: 2231712