Evaluation of Nanopore Sequencing as a Diagnostic Tool for the Rapid Identification of Mycoplasma bovis from Individual and Pooled Respiratory Tract Samples.
Bayesian latent class model
MALDI-TOF MS
Mycoplasma species
bronchoalveolar lavage
selective-indicative agar
Journal
Journal of clinical microbiology
ISSN: 1098-660X
Titre abrégé: J Clin Microbiol
Pays: United States
ID NLM: 7505564
Informations de publication
Date de publication:
18 11 2021
18 11 2021
Historique:
pubmed:
23
9
2021
medline:
15
12
2021
entrez:
22
9
2021
Statut:
ppublish
Résumé
Rapid identification of Mycoplasma bovis infections in cattle is a key factor to guide antimicrobial therapy and biosecurity measures. Recently, Nanopore sequencing became an affordable diagnostic tool for both clinically relevant viruses and bacteria, but the diagnostic accuracy for M. bovis identification is undocumented. Therefore, in this study Nanopore sequencing was compared to rapid identification of M. bovis with matrix-assisted laser desorption ionization-time of flight mass spectrometry (RIMM) and a triplex real-time PCR assay in a Bayesian latent class model (BLCM) for M. bovis in bronchoalveolar lavage fluid (BALf) samples obtained from calves. In practice, pooling of samples is often used to save money, but the influence on diagnostic accuracy has not been described for M. bovis. Therefore, a convenience sample of 17 pooled samples containing 5 individual BALf samples per farm was analyzed as well. The results for the pooled samples were compared with those for the individual samples to determine sensitivity and specificity. The BLCM showed good sensitivity (77.3% [95% credible interval, 57.8 to 92.8%]) and high specificity (97.4% [91.5 to 99.7%]) for Nanopore sequencing, compared to RIMM (sensitivity, 93.0% [76.8 to 99.5%]; specificity, 91.3% [82.5 to 97.0%]) and real-time PCR (sensitivity, 94.6% [89.7 to 97.7%]; specificity, 86.0% [76.1 to 93.6%]). Sensitivity and specificity of pooled analysis for M. bovis were 85.7% (95% confidence interval, 59.8 to 111.6%) and 90.0% (71.4 to 108.6%%), respectively, for Nanopore sequencing and 100% (100% to 100%) and 88.9% (68.4 to 109.4%) for RIMM. In conclusion, Nanopore sequencing is a rapid, reliable tool for the identification of M. bovis. To reduce costs and increase the chance of M. bovis identification, pooling of 5 samples for Nanopore sequencing and RIMM is possible.
Identifiants
pubmed: 34550807
doi: 10.1128/JCM.01110-21
pmc: PMC8601226
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0111021Références
Sci Rep. 2018 Jun 29;8(1):9830
pubmed: 29959349
J Neurol Sci. 2007 Apr 15;255(1-2):69-76
pubmed: 17350048
Microbiol Spectr. 2018 Jul;6(4):
pubmed: 30003864
J Vet Intern Med. 2011 Jul-Aug;25(4):772-83
pubmed: 21745245
Pathogens. 2020 Jul 19;9(7):
pubmed: 32707642
Pathogens. 2020 Jul 21;9(7):
pubmed: 32708285
BMC Vet Res. 2017 Apr 8;13(1):97
pubmed: 28390431
J Vet Intern Med. 2020 Mar;34(2):964-971
pubmed: 32030834
Clin Microbiol Infect. 2011 Jul;17(7):1007-12
pubmed: 20718803
Front Microbiol. 2016 Apr 27;7:595
pubmed: 27199926
J Dairy Sci. 2020 Mar;103(3):2556-2566
pubmed: 31954585
Vet Rec. 2002 Oct 19;151(16):472-6
pubmed: 12418530
Expert Rev Mol Diagn. 2012 Sep;12(7):731-54
pubmed: 23153240
BMC Infect Dis. 2020 Jan 3;20(1):7
pubmed: 31900105
BMC Infect Dis. 2010 Feb 25;10:39
pubmed: 20184731
Prev Vet Med. 2005 May 10;68(2-4):145-63
pubmed: 15820113
Vet Clin North Am Food Anim Pract. 2020 Jul;36(2):269-278
pubmed: 32327249
Vet Res. 2020 Sep 23;51(1):121
pubmed: 32967727
Transbound Emerg Dis. 2020 Jul;67 Suppl 2:82-93
pubmed: 31232526
Lancet Infect Dis. 2020 Nov;20(11):1231-1232
pubmed: 32530425
Pathogens. 2020 Jul 30;9(8):
pubmed: 32751555
Res Vet Sci. 2015 Aug;101:42-9
pubmed: 26267088
BMC Vet Res. 2019 Mar 12;15(1):86
pubmed: 30866933
J Clin Microbiol. 2003 Oct;41(10):4565-72
pubmed: 14532183
J Clin Microbiol. 2020 May 26;58(6):
pubmed: 32229599
Vet Clin North Am Food Anim Pract. 2010 Jul;26(2):365-79
pubmed: 20619190
Vet Clin North Am Food Anim Pract. 2020 Jul;36(2):425-444
pubmed: 32451034
J Vet Intern Med. 2017 May;31(3):946-953
pubmed: 28425146
Prev Vet Med. 2014 Mar 1;113(4):522-35
pubmed: 24485275
J Infect Dis. 1995 Sep;172(3):672-81
pubmed: 7658058
J Clin Microbiol. 2013 Oct;51(10):3314-23
pubmed: 23903545
J Dairy Sci. 2018 Sep;101(9):8284-8290
pubmed: 30126602
Microbiology (Reading). 2006 Apr;152(Pt 4):913-922
pubmed: 16549656
Vaccine. 2016 Jun 8;34(27):3051-3058
pubmed: 27156637
Nat Biotechnol. 2019 Jul;37(7):783-792
pubmed: 31235920
Bioinformatics. 2018 Aug 1;34(15):2666-2669
pubmed: 29547981
Biologicals. 2010 Mar;38(2):183-90
pubmed: 20149687
Res Vet Sci. 2019 Aug;125:185-188
pubmed: 31252368
Vaccine. 2002 Oct 4;20(29-30):3569-75
pubmed: 12297403
Vet Clin North Am Food Anim Pract. 2009 Mar;25(1):139-77, vii
pubmed: 19174287
Vet Microbiol. 2008 Nov 25;132(1-2):177-80
pubmed: 18571343
Vet Microbiol. 2018 Jul;221:105-113
pubmed: 29981695
J Clin Microbiol. 2019 Aug 26;57(9):
pubmed: 31217275
J Virol Methods. 2014 Jan;195:194-204
pubmed: 24036074
BMC Genomics. 2020 Jan 22;21(1):70
pubmed: 31969124
Anal Biochem. 2011 Apr 1;411(1):122-8
pubmed: 21094115
J Vet Intern Med. 2018 May;32(3):1241-1252
pubmed: 29671903