1887

Microbial Genomics logo

Volume 6, Issue 7

Detection of extended-spectrum beta-lactamase (ESBL) genes and plasmid replicons in using PlasmidSPAdes assembly of short-read sequence data Open Access

Abstract

Knowledge of the epidemiology of plasmids is essential for understanding the evolution and spread of antimicrobial resistance. PlasmidSPAdes attempts to reconstruct plasmids using short-read sequence data. Accurate detection of extended-spectrum beta-lactamase (ESBL) genes and plasmid replicon genes is a prerequisite for the use of plasmid assembly tools to investigate the role of plasmids in the spread and evolution of ESBL production in . This study evaluated the performance of PlasmidSPAdes plasmid assembly for in terms of detection of ESBL-encoding genes, plasmid replicons and chromosomal wgMLST genes, and assessed the effect of k-mer size. Short-read sequence data for 59 ESBL-producing were assembled with PlasmidSPAdes using different k-mer sizes (21, 33, 55, 77, 99 and 127). For every k-mer size, the presence of ESBL genes, plasmid replicons and a selection of chromosomal wgMLST genes in the plasmid assembly was determined. Out of 241 plasmid replicons and 66 ESBL genes detected by whole-genome assembly, 213 plasmid replicons [88 %; 95 % confidence interval (CI): 83.9–91.9] and 43 ESBL genes (65 %; 95 % CI: 53.1–75.6) were detected in the plasmid assemblies obtained by PlasmidSPAdes. For most ESBL genes (83.3 %) and plasmid replicons (72.0 %), detection results did not differ between the k-mer sizes used in the plasmid assembly. No optimal k-mer size could be defined for the number of ESBL genes and plasmid replicons detected. For most isolates, the number of chromosomal wgMLST genes detected in the plasmid assemblies decreased with increasing k-mer size. Based on our findings, PlasmidSPAdes is not a suitable plasmid assembly tool for short-read sequence data for ESBL-encoding plasmids of .

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): ESBL , plasmids and PlasmidSPAdes
Funding
This study was supported by the:
  • ZonMw (Award 205100010)
    • Principle Award Recipient: Not Applicable
© 2020 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000400
2020-06-26
2024-04-27
Loading full text...

Full text loading...

/deliver/fulltext/mgen/6/7/mgen000400.html?itemId=/content/journal/mgen/10.1099/mgen.0.000400&mimeType=html&fmt=ahah

References

  1. Partridge SR, Kwong SM, Firth N, Jensen SO. Mobile genetic elements associated with antimicrobial resistance. Clin Microbiol Rev 2018; 31:1–61 [View Article]
     [Google Scholar]
  2. Carattoli A. Resistance plasmid families in Enterobacteriaceae . Antimicrob Agents Chemother 2009; 53:2227–2238 [View Article][PubMed]
     [Google Scholar]
  3. Carattoli A. Plasmids and the spread of resistance. Int J Med Microbiol 2013; 303:298–304 [View Article][PubMed]
     [Google Scholar]
  4. Couturier M, Bex F, Bergquist PL, Maas WK. Identification and classification of bacterial plasmids. Microbiol Rev 1988; 52:375–395 [View Article][PubMed]
     [Google Scholar]
  5. Rodriguez-Baño J, Gutiérrez-Gutiérrez B, Machuca I, Pascual A. Treatment of infections caused by extended-spectrum-beta-. Clin Microbiol Rev 2018; 31:1–42
     [Google Scholar]
  6. Lanza VF, de Toro M, Garcillán-Barcia MP, Mora A, Blanco J et al. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences. PLoS Genet 2014; 10:e1004766 [View Article]
     [Google Scholar]
  7. Carattoli A, Zankari E, García-Fernández A, Voldby Larsen M, Lund O et al. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother 2014; 58:3895–3903 [View Article][PubMed]
     [Google Scholar]
  8. Zhou F, Xu Y. cBar: a computer program to distinguish plasmid-derived from chromosome-derived sequence fragments in metagenomics data. Bioinformatics 2010; 26:2051–2052 [View Article][PubMed]
     [Google Scholar]
  9. Rozov R, Brown Kav A, Bogumil D, Shterzer N, Halperin E et al. Recycler: an algorithm for detecting plasmids from de novo assembly graphs. Bioinformatics 2017; 33:475–482 [View Article][PubMed]
     [Google Scholar]
  10. Antipov D, Hartwick N, Shen M, Raiko M, Lapidus A et al. plasmidSPAdes: assembling plasmids from whole genome sequencing data. Bioinformatics 2016; 32:btw493–3387 [View Article][PubMed]
     [Google Scholar]
  11. Page AJ, Wailan A, Shao Y, Judge K, Dougan G et al. PlasmidTron: assembling the cause of phenotypes and genotypes from NGS data. Microb Genom 2018; 4:1–6 [View Article][PubMed]
     [Google Scholar]
  12. Robertson J, Nash JHE. MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. Microb Genom 2018; 4: [View Article][PubMed]
     [Google Scholar]
  13. Müller R, Chauve C. HyAsP, a greedy tool for plasmids identification. Bioinformatics 2019; 35:4436–4439 [View Article][PubMed]
     [Google Scholar]
  14. Arredondo-Alonso S, Willems RJ, van Schaik W, Schürch AC. On the (im)possibility of reconstructing plasmids from whole-genome short-read sequencing data. Microb Genom 2017; 3:e000128 [View Article][PubMed]
     [Google Scholar]
  15. Laczny CC, Galata V, Plum A, Posch AE, Keller A. Assessing the heterogeneity of in silico plasmid predictions based on whole-genome-sequenced clinical isolates. Brief Bioinform 2019; 20:857–865 [View Article][PubMed]
     [Google Scholar]
  16. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829 [View Article][PubMed]
     [Google Scholar]
  17. Nurk S, Bankevich A, Antipov D et al. Assembling genomes and Mini-metagenomes from highly chimeric reads. In 2013158–170
     [Google Scholar]
  18. Chikhi R, Medvedev P. Informed and automated k-mer size selection for genome assembly. Bioinformatics 2014; 30:31–37 [View Article][PubMed]
     [Google Scholar]
  19. Kluytmans-van den Bergh MFQ, Rossen JWA, Bruijning-Verhagen PCJ, Bonten MJM, Friedrich AW et al. Whole-Genome multilocus sequence typing of extended-spectrum-beta-lactamase-producing Enterobacteriaceae. J Clin Microbiol 2016; 54:2919–2927 [View Article][PubMed]
     [Google Scholar]
  20. Mikheenko A, Prjibelski A, Saveliev V, Antipov D, Gurevich A. Versatile genome assembly evaluation with QUAST-LG. Bioinformatics 2018; 34:i142–i150 [View Article][PubMed]
     [Google Scholar]
  21. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 2012; 67:2640–2644 [View Article][PubMed]
     [Google Scholar]
  22. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article][PubMed]
     [Google Scholar]
  23. Wick RR, Schultz MB, Zobel J, Holt KE. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 2015; 31:3350–3352 [View Article][PubMed]
     [Google Scholar]
  24. García A, Navarro F, Miró E, Villa L, Mirelis B et al. Acquisition and diffusion of bla CTX-M-9 gene by R478-IncHI2 derivative plasmids. FEMS Microbiol Lett 2007; 271:71–77 [View Article][PubMed]
     [Google Scholar]
  25. Miró E, Segura C, Navarro F, Sorlí L, Coll P et al. Spread of plasmids containing the bla(VIM-1) and bla(CTX-M) genes and the qnr determinant in Enterobacter cloacae, Klebsiella pneumoniae and Klebsiella oxytoca isolates. J Antimicrob Chemother 2010; 65:661–665 [View Article][PubMed]
     [Google Scholar]
  26. Nilsen E, Haldorsen BC, Sundsfjord A, Simonsen GS, Ingebretsen A et al. Large IncHI2-plasmids encode extended-spectrum β-lactamases (ESBLs) in Enterobacter spp. bloodstream isolates, and support ESBL-transfer to Escherichia coli . Clin Microbiol Infect 2013; 19:E516–E518 [View Article][PubMed]
     [Google Scholar]
  27. Rozwandowicz M, Brouwer MSM, Fischer J, Wagenaar JA, Gonzalez-Zorn B et al. Plasmids carrying antimicrobial resistance genes in Enterobacteriaceae. J Antimicrob Chemother 2018; 73:1121–1137 [View Article][PubMed]
     [Google Scholar]
  28. Stohr JJJM, Verweij JJ, Buiting AGM, Rossen JWA, Kluytmans JAJW. Within-patient plasmid dynamics in Klebsiella pneumoniae during an outbreak of a carbapenemase-producing Klebsiella pneumoniae. PLoS One 2020; 15:e0233313 [View Article][PubMed]
     [Google Scholar]
  29. Lemon JK, Khil PP, Frank KM, Dekker JP. Rapid nanopore sequencing of plasmids and resistance gene detection in clinical isolates. J Clin Microbiol 2017; 55:3530–3543 [View Article][PubMed]
     [Google Scholar]
  30. Decano AG, Ludden C, Feltwell T, Judge K, Parkhill J et al. Complete Assembly of Escherichia coli Sequence Type 131 genomes using long reads demonstrates antibiotic resistance gene variation within diverse plasmid and chromosomal contexts. mSphere 2019; 4:1–12 [View Article]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000400
Loading
Detection of extended-spectrum beta-lactamase (ESBL) genes and plasmid replicons in Enterobacteriaceae using PlasmidSPAdes assembly of short-read sequence data
M Gen 6, e000400 (2020); https://doi.org/10.1099/mgen.0.000400
/content/journal/mgen/10.1099/mgen.0.000400
/content/journal/mgen/10.1099/mgen.0.000400
Loading

Data & Media loading...

Supplements

Loading data from figshare Loading data from figshare

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error