Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?

R. Macedo, A. Nunes, I. Portugal, S. Duarte, L. Vieira, J.P. Gomes

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Whole-genome sequencing (WGS)-based bioinformatics platforms for the rapid prediction of resistance will soon be implemented in the Tuberculosis (TB) laboratory, but their accuracy assessment still needs to be strengthened. Here, we fully-sequenced a total of 54 multidrug-resistant (MDR) and five susceptible TB strains and performed, for the first time, a simultaneous evaluation of the major four free online platforms (TB Profiler, PhyResSE, Mykrobe Predictor and TGS-TB). Overall, the sensitivity of resistance prediction ranged from 84.3% using Mykrobe predictor to 95.2% using TB profiler, while specificity was higher and homogeneous among platforms. TB profiler revealed the best performance robustness (sensitivity, specificity, PPV and NPV above 95%), followed by TGS-TB (all parameters above 90%). We also observed a few discrepancies between phenotype and genotype, where, in some cases, it was possible to pin-point some “candidate” mutations (e.g., in the rpsL promoter region) highlighting the need for their confirmation through mutagenesis assays and potential review of the anti-TB genetic databases. The rampant development of the bioinformatics algorithms and the tremendously reduced time-frame until the clinician may decide for a definitive and most effective treatment will certainly trigger the technological transition where WGS-based bioinformatics platforms could replace phenotypic drug susceptibility testing for TB. © 2018 Elsevier Ltd
Original languageEnglish
Pages (from-to)44-51
Number of pages8
JournalTuberculosis
Volume110
DOIs
Publication statusPublished - May 2018

Fingerprint

Mycobacterium tuberculosis
Tuberculosis
Genome
Computational Biology
Genetic Databases
Needs Assessment
Genetic Promoter Regions
Mutagenesis
Genotype
Phenotype
Sensitivity and Specificity
Mutation
Pharmaceutical Preparations

Keywords

  • Multidrug-resistant tuberculosis
  • Mykrobe predictor
  • PhyResSE
  • TB profiler
  • TGS-TB
  • Whole-genome sequencing

Cite this

@article{1be42472393447df98749ed66d13570e,
title = "Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?",
abstract = "Whole-genome sequencing (WGS)-based bioinformatics platforms for the rapid prediction of resistance will soon be implemented in the Tuberculosis (TB) laboratory, but their accuracy assessment still needs to be strengthened. Here, we fully-sequenced a total of 54 multidrug-resistant (MDR) and five susceptible TB strains and performed, for the first time, a simultaneous evaluation of the major four free online platforms (TB Profiler, PhyResSE, Mykrobe Predictor and TGS-TB). Overall, the sensitivity of resistance prediction ranged from 84.3{\%} using Mykrobe predictor to 95.2{\%} using TB profiler, while specificity was higher and homogeneous among platforms. TB profiler revealed the best performance robustness (sensitivity, specificity, PPV and NPV above 95{\%}), followed by TGS-TB (all parameters above 90{\%}). We also observed a few discrepancies between phenotype and genotype, where, in some cases, it was possible to pin-point some “candidate” mutations (e.g., in the rpsL promoter region) highlighting the need for their confirmation through mutagenesis assays and potential review of the anti-TB genetic databases. The rampant development of the bioinformatics algorithms and the tremendously reduced time-frame until the clinician may decide for a definitive and most effective treatment will certainly trigger the technological transition where WGS-based bioinformatics platforms could replace phenotypic drug susceptibility testing for TB. {\circledC} 2018 Elsevier Ltd",
keywords = "Multidrug-resistant tuberculosis, Mykrobe predictor, PhyResSE, TB profiler, TGS-TB, Whole-genome sequencing",
author = "R. Macedo and A. Nunes and I. Portugal and S. Duarte and L. Vieira and J.P. Gomes",
note = "Export Date: 3 May 2018 CODEN: TUBEC Correspondence Address: Macedo, R.; Department of Infectious Diseases, National Institute of Health, Avenida Padre Cruz, Portugal; email: rita.macedo@insa.min-saude.pt Funding details: FCT, Funda{\cc}{\~a}o para a Ci{\^e}ncia e a Tecnologia Funding details: CAMH, Centre for Addiction and Mental Health Funding details: UID/BIM/00009/2013 Funding details: POCI-01-0145-FEDER-022184 Funding text: This work was supported by Centre for Toxicogenomics and Human Health (ToxOmics, ref. UID/BIM/00009/2013 ) and GenomePT (ref. POCI-01-0145-FEDER-022184 ) from Funda{\cc}{\~a}o para a Ci{\^e}ncia e Tecnologia, Portugal. References: World Health Organization, Global tuberculosis report (2017); European Centre for Disease Prevention and Control/WHO Regional Office for Europe, Tuberculosis surveillance and monitoring in Europe 2017 (2017), ECDC Stockholm; World Health Organization, Global tuberculosis report (2015); Pfyffer, G.E., Wittwer, F., Incubation time of mycobacterial cultures: how long is long enough to issue a final negative report to the clinician? (2012) J Clin Microbiol, 50, p. 12; World Health Organization, Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis (2014), (WHO/HTM/TB/2014.11); Boehme, C.C., Rapid molecular detection of tuberculosis and rifampin resistance (2010) N Engl J Med, 11, pp. 1005-1015; Satta, G., Lipman, M., Smith, G., Arnold, C., Kon, O.M., McHugh, T.D., Mycobacterium tuberculosis and whole-genome sequencing: how close are we to unleash its full potential? (2017) Clin Microbiol Infect, 10, p. 1016; Satta, G., Atzeni, A., McHugh, T.D., Mycobacterium tuberculosis and whole genome sequencing: a practical guide and online tools available for the clinical microbiologist (2017) Clin Microbiol Infect, 23, pp. 69-72; Faksri, K., Tan, J.H., Chaiprasert, A., Teo, Y.Y., Ong, R.T., Bioinformatics tools and databases for whole genome sequence analysis of Mycobacterium tuberculosis (2016) Infect Genet Evol, 45, pp. 359-368; Schleusener, V., K{\"o}ser, C.U., Beckert, P., Niemann, S., Feuerriegel, S., Mycobacterium tuberculosis resistance prediction and lineage classification from genome sequencing: comparison of automated analysis tools (2017) Sci Rep, 7, p. 46327; Nikolayevskyy, V., Kranzer, K., Niemann, S., Drobniewski, F., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: a systematic review (2016) Tuberculosis, 98, pp. 77-85; European Centre for Disease Prevention and Control, Expert opinion on whole genome sequencing for public health surveillance (2016), ECDC Stockholm; Zhang, Y., Yew, W.W., Mechanisms of drug resistance in Mycobacterium tuberculosis (2009) Int J Tubercul Lung Dis, 13, pp. 1320-1330; Louw, G.E., Warren, R.M., Gey van Pittius, N.C., McEvoy, C.R., Van Helden, P.D., Victor, T.C., A balancing act: efflux/influx in mycobacterium drug resistance (2009) Antimicrob Agents Chemother, 53, pp. 3181-3189; Coll, F., Phelan, J., Hill-Cawthorne, G.A., Nair, M.B., Mallard, K., Ali, S., Abdallah, A.M., Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis (2018) Nat Genet, , [Epub ahead of print]; Manson, A.L., Cohen, K.A., Abeel, T., Desjardins, C.A., Armstrong, D.T., Barry, C.E., Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance (2017) Nat Genet, 49 (3), pp. 395-402; Papaventsis, D., Casali, N., Kontsevaya, I., Drobniewski, F., Cirillo, D.M., Nikolayevskyy, V., Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review (2017) Clin Microbiol Infect, 23 (2), pp. 61-68; Walker, T.M., Kohl, T.A., Omar, S.V., Hedge, J., Del Ojo Elias, C., Bradley, P., Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study (2015) Lancet Infect Dis, 15 (10), pp. 1193-1202; Coll, F., McNerney, R., Preston, M.D., Guerra-Assun{\cc}{\~a}o, J.A., Warry, A., Hill-Cawthorne, G., Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences (2015) Genome Med, 7, p. 51; Feuerriegel, S., Schleusenerc, V., Beckerta, P., Kohla, T.A., Miotto, P., Cirillo, D.M., PhyResSE: a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from whole-genome sequencing data (2015) JCM, 6, p. 53; Sekizuka, T., Yamashita, A., Murase, Y., Iwamoto, T., Mitarai, S., Kato, S., Kuroda, M., TGS-TB: total genotyping solution for Mycobacterium tuberculosis using short-read whole-genome sequencing (2015) PLoS One, 10 (11), p. e0142951; Bradley, P., Gordon, N.C., Walker, T.M., Dunn, L., Heys, S., Huang, B., Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis (2015) Nature communication, 6, p. 10063; Zhang, Y., Yew, W.W., Mechanisms of drug resistance in Mycobacterium tuberculosis: update (2015) Int J Tubercul Lung Dis, 19 (11), pp. 1276-1289; Nikolayevskyy, V., Hillemann, D., Richter, E., Ahmed, N., van der Werf, M.J., Kodmon, C., External quality assessment for tuberculosis diagnosis and drug resistance in the European union: a five year multicentre implementation study (2016) PLoS One, 11 (4), p. e0152926; Whitfield, M.G., Soeters, H.M., Warren, R.M., York, T., Sampson, S.L., Streicher, E.M., A global perspective on pyrazinamide resistance: systematic review and meta-analysis (2015) PLoS One, 10 (7), p. e0133869; Chatterjee, A., Nilgiriwala, Saranath, D., Rodrigues, C., Mistry, N., Whole genome sequencing of clinical strains of Mycobacetrium tuberculosis from Mumbai, India: a potential tool for determining drug-resistance and strain lineage (2017) Tuberculosis, 107, pp. 63-72; Phelan, J., O´Sullivan, D., Machado, D., Ramos, J., Whale, A., O´Grady, J., The variability and reproducibility of whole genome sequencing technology for detecting resistance to anti-tuberculous drugs (2016) Genome Med, 8, p. 132; Borges, V., Nunes, A., Sampaio, D.A., Vieira, L., Machado, J., Sim{\~o}es, M.J., Legionella pneumophila strain associated with the first evidence of person-to-person transmission of Legionnaires’ disease: a unique mosaic genetic backbone (2016) Sci Rep, 6, p. 26261; Miotto, P., Tessema, B., Tagliani, E., Chindelevitch, L., Starks, A.M., Emerson, C., A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis (2017) Eur Respir J, 50, p. 1701354. , https://doi.org/10.1183/13993003.01354-2017; Feuerriegel, S., K{\"o}ser, C.U., Niemann, S., Phylogenetic polymorphisms in antibiotic resistance genes of the Mycobacterium tuberculosis complex (2014) J Antimicrob Chemother, 69 (5), pp. 1205-1210; Coll, F., McNerney, R., Guerra-Assun{\cc}{\~a}o, J.A., Glynn, J.R., Perdig{\~a}o, J., Viveiros, M., A robust SNP barcode for typing Mycobacterium tuberculosis complex strains (2014) Nat Commun, 5, p. 4812; Campbell, P.J., Morlock, G.P., Sikes, R.D., Dalton, T.L., Metchock, B., Starks, A.M., Molecular detection of mutations associated with first- and second-line drug resistance compared with conventional drug susceptibility testing of Mycobacterium tuberculosis (2011) Antimicrob Agents Chemother, 55 (5), pp. 2032-2041; Plinke, C., Cox, H.S., Zarkua, N., Karimovich, H.A., Braker, K., Diel, R., embCAB sequence variation among ethambutol-resistant Mycobacterium tuberculosis isolates without embB306 mutation (2010) J Antimicrob Chemother, 65 (7), pp. 1359-1367; Margaryan, H., R{\"u}sch-Gerdes, S., Hayrapetyan, A., Mirzoyan, A., Ethambutol-resistance testing by mutation detection using MTBDRsl (2016) International Journal of Mycobacteriology, 5 (1); Ellington, M.J., Ekelund, O., Aarestrup, F.M., Canton, R., Doumith, M., Cet al, G., The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee (2017) Clin Microbiol Infect, 23 (1), pp. 2-22; Mphahlele, M., Syre, H., Valvatne, H., Stavrum, R., Manns{\aa}ker, T., Muthivhi, T., Pyrazinamide resistance among South African multidrug-resistant Mycobacterium tuberculosis isolates (2008) J Clin Microbiol, 46, pp. 3459-3464; Martinez, E., Holmes, N., Jelfs, P., Sintchenko, V., Genome sequencing reveals novel deletions associated with secondary resistance to pyrazinamide in MDR Mycobacterium tuberculosis (2015) J Antimicrob Chemother, 70, pp. 2511-2514; Blanchard, J.S., Molecular mechanisms of drug resistance in Mycobacterium tuberculosis (1996) Annu Rev Biochem, 65, pp. 215-239; Takayama, K., Wang, L., David, H.L., Effect of isoniazid on the in vivo mycolic acid synthesis, cell growth, and viability of Mycobacterium tuberculosis (1972) Antimicrob Agents Chemother, 2 (1), pp. 29-35; Banerjee, A., Dubnau, E., Quemard, A., Balasubramanian, V., Um, K.S., Wilson, T., inhA, a gene encoding a target for isoniazid and ethionamide in Mycobacterium tuberculosis (1994) Science, 26 3 (5144), pp. 227-230; Larsen, M.H., Vilch{\`e}ze, C., Kremer, L., Besra, G.S., Parsons, L., Salfinger, M., Overexpression of inhA, but not kasA, confers resistance to isoniazid and ethionamide in Mycobacterium smegmatis, M. bovis BCG and M. tuberculosis (2002) Mol Microbiol, 46 (2), pp. 453-466; Lee, H., Cho, S.N., Bang, H.E., Lee, J.H., Bai, G.H., Kim, S.J., Kim, J.D., Exclusive mutations related to isoniazid and ethionamide resistance among Mycobacterium tuberculosis isolates from Korea (2000) Int J Tubercul Lung Dis, 4 (5), pp. 441-447; Morlock, G.P., Crawford, J.T., Butler, W.R., Brim, S.E., Sikes, D., Mazurek, G.H., Phenotypic characterization of pncA mutants of Mycobacterium tuberculosis (2000) Antimicrob Agents Chemother, 44 (9), pp. 2291-2295; Scorpio, A., Zhang, Y., Mutations in pncA, a gene encoding pyrazinamidase/nicotinamidase, cause resistance to the antituberculous drug pyrazinamide in tubercle bacillus (1996) Nat Med, 2 (6), pp. 662-667; de Welzen, L., Eldholm, V., Maharaj, K., Manson, A.L., Earl, A.M., Pym, A.S., Whole-transcriptome and -genome analysis of extensively drug-resistant Mycobacterium tuberculosis clinical isolates identifies downregulation of ethA as a mechanism of ethionamide resistance (2017) Antimicrob Agents Chemother, 22 (12), p. 61; Morlock, G.P., Metchock, B., Sikes, D., Crawford, J.T., Cooksey, R.C., ethA, inhA, and katG loci of ethionamide-resistant clinical Mycobacterium tuberculosis isolates (2003) Antimicrob Agents Chemother, 47 (12), pp. 3799-3805; Baulard, A.R., Betts, J.C., Engohang-Ndong, J., Quan, S., McAdam, R.A., Brennan, P.J., Activation of the pro-drug ethionamide is regulated in mycobacteria (2000) J Biol Chem, 275 (36), pp. 28326-28331; DeBarber, A.E., Mdluli, K., Bosman, M., Bekker, L.G., Barry, C.E., Ethionamide activation and sensitivity in multidrug-resistant Mycobacterium tuberculosis (2000) Proc Natl Acad Sci USA, 97 (17), pp. 9677-9682; Abe, C., Kobayashi, I., Mitarai, S., Wada, M., Kawabe, Y., Takashima, T., Biological and molecular characteristics of Mycobacterium tuberculosis clinical isolates with low-level resistance to isoniazid in Japan (2008) J Clin Microbiol, 46 (7), pp. 2263-2268; Pankhurst, L.J., Del Ojo Elias, C., Votintseva, A.A., Walker, T.M., Cole, K., Davies, J., Rapid, comprehensive, and affordable mycobacterial diagnosis with whole genome sequencing: a prospective study (2016) Lancet Respir Med, 4, pp. 49-58; Koser, C.U., Bryant, J.M., Becq, J., Torok, M.E., Ellington, M.J., Marti-Renom, M.A., Whole-genome sequencing for rapid susceptibility testing of M. tuberculosis (2013) N Engl J Med, 369 (3), pp. 290-292; PHE, England world leaders in the use of whole genome sequencing to diagnose TB (2017), https://www.gov.uk/government/news/england-world-leaders-in-the-use-of-whole-genome-sequencing-to-diagnose-tb, (Accessed 30 May 2017); Stucki, D., Gagneux, S., Single nucleotide polymorphisms in Mycobacterium tuberculosis and the need for a curated database (2013) Tuberculosis, 93 (1), pp. 30-39; Salamon, H., Yamaguchi, K.D., Cirillo, D.M., Miotto, P., Schito, M., Posey, J., Integration of published information into a resistance-associated mutation database for Mycobacterium tuberculosis (2015) J Infect Dis, 211 (2), pp. S50-S57",
year = "2018",
month = "5",
doi = "10.1016/j.tube.2018.03.009",
language = "English",
volume = "110",
pages = "44--51",
journal = "Tuberculosis",
issn = "1472-9792",
publisher = "CHURCHILL LIVINGSTONE",

}

Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance? / Macedo, R.; Nunes, A.; Portugal, I.; Duarte, S.; Vieira, L.; Gomes, J.P.

In: Tuberculosis, Vol. 110, 05.2018, p. 44-51.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?

AU - Macedo, R.

AU - Nunes, A.

AU - Portugal, I.

AU - Duarte, S.

AU - Vieira, L.

AU - Gomes, J.P.

N1 - Export Date: 3 May 2018 CODEN: TUBEC Correspondence Address: Macedo, R.; Department of Infectious Diseases, National Institute of Health, Avenida Padre Cruz, Portugal; email: rita.macedo@insa.min-saude.pt Funding details: FCT, Fundação para a Ciência e a Tecnologia Funding details: CAMH, Centre for Addiction and Mental Health Funding details: UID/BIM/00009/2013 Funding details: POCI-01-0145-FEDER-022184 Funding text: This work was supported by Centre for Toxicogenomics and Human Health (ToxOmics, ref. UID/BIM/00009/2013 ) and GenomePT (ref. POCI-01-0145-FEDER-022184 ) from Fundação para a Ciência e Tecnologia, Portugal. References: World Health Organization, Global tuberculosis report (2017); European Centre for Disease Prevention and Control/WHO Regional Office for Europe, Tuberculosis surveillance and monitoring in Europe 2017 (2017), ECDC Stockholm; World Health Organization, Global tuberculosis report (2015); Pfyffer, G.E., Wittwer, F., Incubation time of mycobacterial cultures: how long is long enough to issue a final negative report to the clinician? (2012) J Clin Microbiol, 50, p. 12; World Health Organization, Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis (2014), (WHO/HTM/TB/2014.11); Boehme, C.C., Rapid molecular detection of tuberculosis and rifampin resistance (2010) N Engl J Med, 11, pp. 1005-1015; Satta, G., Lipman, M., Smith, G., Arnold, C., Kon, O.M., McHugh, T.D., Mycobacterium tuberculosis and whole-genome sequencing: how close are we to unleash its full potential? (2017) Clin Microbiol Infect, 10, p. 1016; Satta, G., Atzeni, A., McHugh, T.D., Mycobacterium tuberculosis and whole genome sequencing: a practical guide and online tools available for the clinical microbiologist (2017) Clin Microbiol Infect, 23, pp. 69-72; Faksri, K., Tan, J.H., Chaiprasert, A., Teo, Y.Y., Ong, R.T., Bioinformatics tools and databases for whole genome sequence analysis of Mycobacterium tuberculosis (2016) Infect Genet Evol, 45, pp. 359-368; Schleusener, V., Köser, C.U., Beckert, P., Niemann, S., Feuerriegel, S., Mycobacterium tuberculosis resistance prediction and lineage classification from genome sequencing: comparison of automated analysis tools (2017) Sci Rep, 7, p. 46327; Nikolayevskyy, V., Kranzer, K., Niemann, S., Drobniewski, F., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: a systematic review (2016) Tuberculosis, 98, pp. 77-85; European Centre for Disease Prevention and Control, Expert opinion on whole genome sequencing for public health surveillance (2016), ECDC Stockholm; Zhang, Y., Yew, W.W., Mechanisms of drug resistance in Mycobacterium tuberculosis (2009) Int J Tubercul Lung Dis, 13, pp. 1320-1330; Louw, G.E., Warren, R.M., Gey van Pittius, N.C., McEvoy, C.R., Van Helden, P.D., Victor, T.C., A balancing act: efflux/influx in mycobacterium drug resistance (2009) Antimicrob Agents Chemother, 53, pp. 3181-3189; Coll, F., Phelan, J., Hill-Cawthorne, G.A., Nair, M.B., Mallard, K., Ali, S., Abdallah, A.M., Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis (2018) Nat Genet, , [Epub ahead of print]; Manson, A.L., Cohen, K.A., Abeel, T., Desjardins, C.A., Armstrong, D.T., Barry, C.E., Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance (2017) Nat Genet, 49 (3), pp. 395-402; Papaventsis, D., Casali, N., Kontsevaya, I., Drobniewski, F., Cirillo, D.M., Nikolayevskyy, V., Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review (2017) Clin Microbiol Infect, 23 (2), pp. 61-68; Walker, T.M., Kohl, T.A., Omar, S.V., Hedge, J., Del Ojo Elias, C., Bradley, P., Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study (2015) Lancet Infect Dis, 15 (10), pp. 1193-1202; Coll, F., McNerney, R., Preston, M.D., Guerra-Assunção, J.A., Warry, A., Hill-Cawthorne, G., Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences (2015) Genome Med, 7, p. 51; Feuerriegel, S., Schleusenerc, V., Beckerta, P., Kohla, T.A., Miotto, P., Cirillo, D.M., PhyResSE: a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from whole-genome sequencing data (2015) JCM, 6, p. 53; Sekizuka, T., Yamashita, A., Murase, Y., Iwamoto, T., Mitarai, S., Kato, S., Kuroda, M., TGS-TB: total genotyping solution for Mycobacterium tuberculosis using short-read whole-genome sequencing (2015) PLoS One, 10 (11), p. e0142951; Bradley, P., Gordon, N.C., Walker, T.M., Dunn, L., Heys, S., Huang, B., Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis (2015) Nature communication, 6, p. 10063; Zhang, Y., Yew, W.W., Mechanisms of drug resistance in Mycobacterium tuberculosis: update (2015) Int J Tubercul Lung Dis, 19 (11), pp. 1276-1289; Nikolayevskyy, V., Hillemann, D., Richter, E., Ahmed, N., van der Werf, M.J., Kodmon, C., External quality assessment for tuberculosis diagnosis and drug resistance in the European union: a five year multicentre implementation study (2016) PLoS One, 11 (4), p. e0152926; Whitfield, M.G., Soeters, H.M., Warren, R.M., York, T., Sampson, S.L., Streicher, E.M., A global perspective on pyrazinamide resistance: systematic review and meta-analysis (2015) PLoS One, 10 (7), p. e0133869; Chatterjee, A., Nilgiriwala, Saranath, D., Rodrigues, C., Mistry, N., Whole genome sequencing of clinical strains of Mycobacetrium tuberculosis from Mumbai, India: a potential tool for determining drug-resistance and strain lineage (2017) Tuberculosis, 107, pp. 63-72; Phelan, J., O´Sullivan, D., Machado, D., Ramos, J., Whale, A., O´Grady, J., The variability and reproducibility of whole genome sequencing technology for detecting resistance to anti-tuberculous drugs (2016) Genome Med, 8, p. 132; Borges, V., Nunes, A., Sampaio, D.A., Vieira, L., Machado, J., Simões, M.J., Legionella pneumophila strain associated with the first evidence of person-to-person transmission of Legionnaires’ disease: a unique mosaic genetic backbone (2016) Sci Rep, 6, p. 26261; Miotto, P., Tessema, B., Tagliani, E., Chindelevitch, L., Starks, A.M., Emerson, C., A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis (2017) Eur Respir J, 50, p. 1701354. , https://doi.org/10.1183/13993003.01354-2017; Feuerriegel, S., Köser, C.U., Niemann, S., Phylogenetic polymorphisms in antibiotic resistance genes of the Mycobacterium tuberculosis complex (2014) J Antimicrob Chemother, 69 (5), pp. 1205-1210; Coll, F., McNerney, R., Guerra-Assunção, J.A., Glynn, J.R., Perdigão, J., Viveiros, M., A robust SNP barcode for typing Mycobacterium tuberculosis complex strains (2014) Nat Commun, 5, p. 4812; Campbell, P.J., Morlock, G.P., Sikes, R.D., Dalton, T.L., Metchock, B., Starks, A.M., Molecular detection of mutations associated with first- and second-line drug resistance compared with conventional drug susceptibility testing of Mycobacterium tuberculosis (2011) Antimicrob Agents Chemother, 55 (5), pp. 2032-2041; Plinke, C., Cox, H.S., Zarkua, N., Karimovich, H.A., Braker, K., Diel, R., embCAB sequence variation among ethambutol-resistant Mycobacterium tuberculosis isolates without embB306 mutation (2010) J Antimicrob Chemother, 65 (7), pp. 1359-1367; Margaryan, H., Rüsch-Gerdes, S., Hayrapetyan, A., Mirzoyan, A., Ethambutol-resistance testing by mutation detection using MTBDRsl (2016) International Journal of Mycobacteriology, 5 (1); Ellington, M.J., Ekelund, O., Aarestrup, F.M., Canton, R., Doumith, M., Cet al, G., The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee (2017) Clin Microbiol Infect, 23 (1), pp. 2-22; Mphahlele, M., Syre, H., Valvatne, H., Stavrum, R., Mannsåker, T., Muthivhi, T., Pyrazinamide resistance among South African multidrug-resistant Mycobacterium tuberculosis isolates (2008) J Clin Microbiol, 46, pp. 3459-3464; Martinez, E., Holmes, N., Jelfs, P., Sintchenko, V., Genome sequencing reveals novel deletions associated with secondary resistance to pyrazinamide in MDR Mycobacterium tuberculosis (2015) J Antimicrob Chemother, 70, pp. 2511-2514; Blanchard, J.S., Molecular mechanisms of drug resistance in Mycobacterium tuberculosis (1996) Annu Rev Biochem, 65, pp. 215-239; Takayama, K., Wang, L., David, H.L., Effect of isoniazid on the in vivo mycolic acid synthesis, cell growth, and viability of Mycobacterium tuberculosis (1972) Antimicrob Agents Chemother, 2 (1), pp. 29-35; Banerjee, A., Dubnau, E., Quemard, A., Balasubramanian, V., Um, K.S., Wilson, T., inhA, a gene encoding a target for isoniazid and ethionamide in Mycobacterium tuberculosis (1994) Science, 26 3 (5144), pp. 227-230; Larsen, M.H., Vilchèze, C., Kremer, L., Besra, G.S., Parsons, L., Salfinger, M., Overexpression of inhA, but not kasA, confers resistance to isoniazid and ethionamide in Mycobacterium smegmatis, M. bovis BCG and M. tuberculosis (2002) Mol Microbiol, 46 (2), pp. 453-466; Lee, H., Cho, S.N., Bang, H.E., Lee, J.H., Bai, G.H., Kim, S.J., Kim, J.D., Exclusive mutations related to isoniazid and ethionamide resistance among Mycobacterium tuberculosis isolates from Korea (2000) Int J Tubercul Lung Dis, 4 (5), pp. 441-447; 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PY - 2018/5

Y1 - 2018/5

N2 - Whole-genome sequencing (WGS)-based bioinformatics platforms for the rapid prediction of resistance will soon be implemented in the Tuberculosis (TB) laboratory, but their accuracy assessment still needs to be strengthened. Here, we fully-sequenced a total of 54 multidrug-resistant (MDR) and five susceptible TB strains and performed, for the first time, a simultaneous evaluation of the major four free online platforms (TB Profiler, PhyResSE, Mykrobe Predictor and TGS-TB). Overall, the sensitivity of resistance prediction ranged from 84.3% using Mykrobe predictor to 95.2% using TB profiler, while specificity was higher and homogeneous among platforms. TB profiler revealed the best performance robustness (sensitivity, specificity, PPV and NPV above 95%), followed by TGS-TB (all parameters above 90%). We also observed a few discrepancies between phenotype and genotype, where, in some cases, it was possible to pin-point some “candidate” mutations (e.g., in the rpsL promoter region) highlighting the need for their confirmation through mutagenesis assays and potential review of the anti-TB genetic databases. The rampant development of the bioinformatics algorithms and the tremendously reduced time-frame until the clinician may decide for a definitive and most effective treatment will certainly trigger the technological transition where WGS-based bioinformatics platforms could replace phenotypic drug susceptibility testing for TB. © 2018 Elsevier Ltd

AB - Whole-genome sequencing (WGS)-based bioinformatics platforms for the rapid prediction of resistance will soon be implemented in the Tuberculosis (TB) laboratory, but their accuracy assessment still needs to be strengthened. Here, we fully-sequenced a total of 54 multidrug-resistant (MDR) and five susceptible TB strains and performed, for the first time, a simultaneous evaluation of the major four free online platforms (TB Profiler, PhyResSE, Mykrobe Predictor and TGS-TB). Overall, the sensitivity of resistance prediction ranged from 84.3% using Mykrobe predictor to 95.2% using TB profiler, while specificity was higher and homogeneous among platforms. TB profiler revealed the best performance robustness (sensitivity, specificity, PPV and NPV above 95%), followed by TGS-TB (all parameters above 90%). We also observed a few discrepancies between phenotype and genotype, where, in some cases, it was possible to pin-point some “candidate” mutations (e.g., in the rpsL promoter region) highlighting the need for their confirmation through mutagenesis assays and potential review of the anti-TB genetic databases. The rampant development of the bioinformatics algorithms and the tremendously reduced time-frame until the clinician may decide for a definitive and most effective treatment will certainly trigger the technological transition where WGS-based bioinformatics platforms could replace phenotypic drug susceptibility testing for TB. © 2018 Elsevier Ltd

KW - Multidrug-resistant tuberculosis

KW - Mykrobe predictor

KW - PhyResSE

KW - TB profiler

KW - TGS-TB

KW - Whole-genome sequencing

U2 - 10.1016/j.tube.2018.03.009

DO - 10.1016/j.tube.2018.03.009

M3 - Article

VL - 110

SP - 44

EP - 51

JO - Tuberculosis

JF - Tuberculosis

SN - 1472-9792

ER -