Whole-genome sequencing of Neisseria gonorrhoeae in a forensic transmission case

  1. Francés Cuesta, Carlos 1
  2. de la Caba, Idoia
  3. Idígoras Viedma, Pedro
  4. Fernández Rodríguez, Amparo
  5. Valle Pérez, David del
  6. Marimón, Jose Maria
  7. González Candelas, Fernando
  1. 1 Universitat de València
    info

    Universitat de València

    Valencia, España

    ROR https://ror.org/043nxc105

Revista:
Forensic Science International: Genetics

ISSN: 1872-4973

Año de publicación: 2019

Volumen: 42

Páginas: 141-146

Tipo: Artículo

DOI: 10.1016/J.FSIGEN.2019.07.003 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Forensic Science International: Genetics

Resumen

Molecular epidemiology and phylogenetic analyses are frequently used in the investigation of viral transmission cases in forensic contexts. Here, we present the methods and results of the analysis of a bacterial transmission episode in an alleged child abuse case using complete genome sequences obtained by high-throughput sequencing (HTS) methods. We obtained genomes of Neisseria gonorrhoeae from the victim, the suspect, and 29 unrelated controls. The analysis of the genomes revealed that the victim and suspect isolates had identical sequences in both the bacterial chromosome and the single plasmid present in them. One of the local controls was very similar (differing in only 2 SNPs) to the case sequences, but the remaining controls were very divergent. Additional cases of identity and very high similarity among controls were observed occasionally, pointing at recent transmission cases. These results were more discriminative than the previous molecular epidemiology analyses performed at the hospital’s Microbiology Service, as Multi-Locus Sequence Typing (MLST) could not distinguish between the suspect/victim and the controls isolates, and Pulse Field Gel Electrophoresis (PFGE) was not able to distinguish between the suspect/victim and one of the local controls. These results lead us to conclude that complete bacterial genome sequences obtained with HTS technologies may be a valuable tool for establishing recent transmission cases and, although more studies are needed, they have a great potential for being used in forensic analyses.

Referencias bibliográficas

  • Ou, (1992), Science, 256, pp. 1165, 10.1126/science.256.5060.1165
  • Birch, (2000), J. Infect. Dis., 182, pp. 941, 10.1086/315751
  • Machuca, (2001), Clin. Diagn. Lab. Immunol., 8, pp. 884, 10.1128/CDLI.8.5.884-890.2001
  • Metzker, (2002), Proc. Nat. Acad. Sci. U. S. A., 99, pp. 14292, 10.1073/pnas.222522599
  • Scaduto, (2010), Proc. Nat. Acad. Sci. U. S. A., 107, pp. 21242, 10.1073/pnas.1015673107
  • González-Candelas, (2013), BMC Biol., 11, pp. 76, 10.1186/1741-7007-11-76
  • Jernigan, (2002), Emerging Infect. Dis., 8, pp. 1019, 10.3201/eid0810.020353
  • Hoffmaster, (2002), Emerging Infect. Dis., 8, pp. 1111, 10.3201/eid0810.020394
  • Rasko, (2011), Proc. Nat. Acad. Sci. U. S. A., 108, pp. 5027, 10.1073/pnas.1016657108
  • Budowle, (2005), Int. J. Legal Med., 119, pp. 317, 10.1007/s00414-005-0535-y
  • Budowle, (2014), Investig. Genet., 5, pp. 1, 10.1186/2041-2223-5-9
  • Newman, (2015), PLoS One, 10, 10.1371/journal.pone.0143304
  • Unemo, (2014), Clin. Microbiol. Rev., 27, pp. 587, 10.1128/CMR.00010-14
  • Van de Laar, (2012), EuroSurveillance., 17, pp. 29, 10.2807/ese.17.29.20225-en
  • European Centre for Disease Prevention and Control, (2015)
  • World Health Organization, (2016)
  • European Centre for Disease Prevention and Control, (2017)
  • Unemo, (2017), Nat. Rev. Urol., 14, pp. 139, 10.1038/nrurol.2016.268
  • Vicente, (2006), Clin. Microbiol. Infect., 12, pp. 812, 10.1111/j.1469-0691.2006.01451.x
  • Inouye, (2014), Genome Med., 6, pp. 90, 10.1186/s13073-014-0090-6
  • Schmieder, (2011), Bioinformatics, 27, pp. 863, 10.1093/bioinformatics/btr026
  • Unemo, (2016), J. Antimicrob. Chemother., 71, pp. 3096, 10.1093/jac/dkw288
  • Li, (2009), Bioinformatics., 25, pp. 1754, 10.1093/bioinformatics/btp324
  • Li, (2009), Bioinformatics, 25, pp. 2078, 10.1093/bioinformatics/btp352
  • Nguyen, (2015), Mol. Biol. Evol., 32, pp. 268, 10.1093/molbev/msu300
  • Kalyaanamoorthy, (2017), Nat Meth., 14, pp. 587, 10.1038/nmeth.4285
  • Minh, (2013), Mol. Biol. Evol., 30, pp. 1188, 10.1093/molbev/mst024
  • Paradis, (2004), Bioinformatics, 20, pp. 289, 10.1093/bioinformatics/btg412
  • R Core Team, (2019)
  • Peng, (2012), Bioinformatics, 28, pp. 1420, 10.1093/bioinformatics/bts174
  • Bankevich, (2012), J. Comput. Biol., 19, pp. 455, 10.1089/cmb.2012.0021
  • Gurevich, (2013), Bioinformatics, 29, pp. 1072, 10.1093/bioinformatics/btt086
  • Camacho, (2009), BMC Bioinformatics, 10, pp. 421, 10.1186/1471-2105-10-421
  • Seemann, (2014), Bioinformatics, 30, pp. 2068, 10.1093/bioinformatics/btu153
  • Lechner, (2011), BMC Bioinformatics, 12, pp. 124, 10.1186/1471-2105-12-124
  • De Silva, (2016), Lancet Infect. Dis., 16, pp. 1295, 10.1016/S1473-3099(16)30157-8
  • Maiden, (2006), Annu. Rev. Microbiol., 60, pp. 561, 10.1146/annurev.micro.59.030804.121325
  • Unemo, (2011), Clin. Microbiol. Rev., 24, pp. 447, 10.1128/CMR.00040-10
  • Sathirareuangchai, (2015), Int. J. Legal Med., 129, pp. 153, 10.1007/s00414-014-1007-z
  • Harris, (2010), Science, 327, pp. 469, 10.1126/science.1182395
  • Leopold, (2014), J. Clin. Microbiol., 52, pp. 2365, 10.1128/JCM.00262-14
  • Kovanen, (2014), J. Clin. Microbiol., 52, pp. 4147, 10.1128/JCM.01959-14
  • Lüth, (2018), Trends Food Sci. Technol., 73, pp. 67, 10.1016/j.tifs.2018.01.008
  • Quainoo, (2017), Clin. Microbiol. Rev., 30, pp. 1015, 10.1128/CMR.00016-17
  • Budowle, (2005), Crit. Rev. Microbiol., 31, pp. 233, 10.1080/10408410500304082
  • Schmedes, (2016), J. Clin. Microbiol., 54, pp. 1964, 10.1128/JCM.00046-16
  • Hammerschlag, (2010), Clin. Microbiol. Rev., 23, pp. 493, 10.1128/CMR.00024-09
  • Kellogg, (2005), Pediatrics, 116, pp. 506, 10.1542/peds.2005-1336
  • Klemm, (2016), Cell Host Microbe, 19, pp. 599, 10.1016/j.chom.2016.04.015
  • Carver, (2005), Bioinformatics, 21, pp. 3422, 10.1093/bioinformatics/bti553