Whole-genome sequencing to establish relapse or re-infection with Mycobacterium tuberculosis: a retrospective observational study

Josephine M Bryant, Simon R Harris, Julian Parkhill, Rodney Dawson, Andreas H Diacon, Paul van Helden, Alex Pym, Aziah A Mahayiddin, Charoen Chuchottaworn, Ian M Sanne, Cheryl Louw, Martin J Boeree, Michael Hoelscher, Timothy D McHugh, Anna L C Bateson, Robert D Hunt, Solomon Mwaigwisya, Laura Wright, Stephen H Gillespie, Stephen D Bentley, Josephine M Bryant, Simon R Harris, Julian Parkhill, Rodney Dawson, Andreas H Diacon, Paul van Helden, Alex Pym, Aziah A Mahayiddin, Charoen Chuchottaworn, Ian M Sanne, Cheryl Louw, Martin J Boeree, Michael Hoelscher, Timothy D McHugh, Anna L C Bateson, Robert D Hunt, Solomon Mwaigwisya, Laura Wright, Stephen H Gillespie, Stephen D Bentley

Abstract

Background: Recurrence of tuberculosis after treatment makes management difficult and is a key factor for determining treatment efficacy. Two processes can cause recurrence: relapse of the primary infection or re-infection with an exogenous strain. Although re-infection can and does occur, its importance to tuberculosis epidemiology and its biological basis is still debated. We used whole-genome sequencing-which is more accurate than conventional typing used to date-to assess the frequency of recurrence and to gain insight into the biological basis of re-infection.

Methods: We assessed patients from the REMoxTB trial-a randomised controlled trial of tuberculosis treatment that enrolled previously untreated participants with Mycobacterium tuberculosis infection from Malaysia, South Africa, and Thailand. We did whole-genome sequencing and mycobacterial interspersed repetitive unit-variable number of tandem repeat (MIRU-VNTR) typing of pairs of isolates taken by sputum sampling: one from before treatment and another from either the end of failed treatment at 17 weeks or later or from a recurrent infection. We compared the number and location of SNPs between isolates collected at baseline and recurrence.

Findings: We assessed 47 pairs of isolates. Whole-genome sequencing identified 33 cases with little genetic distance (0-6 SNPs) between strains, deemed relapses, and three cases for which the genetic distance ranged from 1306 to 1419 SNPs, deemed re-infections. Six cases of relapse and six cases of mixed infection were classified differently by whole-genome sequencing and MIRU-VNTR. We detected five single positive isolates (positive culture followed by at least two negative cultures) without clinical evidence of disease.

Interpretation: Whole-genome sequencing enables the differentiation of relapse and re-infection cases with greater resolution than do genotyping methods used at present, such as MIRU-VNTR, and provides insights into the biology of recurrence. The additional clarity provided by whole-genome sequencing might have a role in defining endpoints for clinical trials.

Funding: Wellcome Trust, European Union, Medical Research Council, Global Alliance for TB Drug Development, European and Developing Country Clinical Trials Partnership.

Copyright © 2013 Bryant et al. Open Access article distributed under the terms of CC BY. Published by .. All rights reserved.

Figures

Figure 1
Figure 1
Distribution of the case outcomes for study patients based on sequencing quality data, sequence comparison, and clinical evaluation
Figure 2
Figure 2
Pair-wise distances between pairs of isolates from the same patient For each patient pair, the calculated pair-wise distance is based on the number of high quality base differences between the samples.
Figure 3
Figure 3
MIRU-VNTR loci differing between pairs of isolates from the same patient (A) Number of loci differing between pairs of isolates from the same patient with relapse, re-infection, mixed infection, and single isolated positives identified by whole genome sequencing. (B) Comparison of differences detected by whole genome sequence data and MIRU-VNTR; red=relapse, blue=re-infection. MIRU-VNTR=mycobacterial interspersed repetitive unit-variable number of tandem repeat.

References

    1. WHO . Global Tuberculosis Report 2012. World Health Organisation; Geneva: 2012.
    1. Warren RM, Victor TC, Streicher EM. Patients with active tuberculosis often have different strains in the same sputum specimen. Am J Respir Crit Care Med. 2004;169:610–614.
    1. Uys PW, van Helden PD, Hargrove JW. Tuberculosis reinfection rate as a proportion of total infection rate correlates with the logarithm of the incidence rate: a mathematical model. J R Soc Interface. 2009;6:11–15.
    1. Verver S, Warren RM, Beyers N. Rate of reinfection tuberculosis after successful treatment is higher than rate of new tuberculosis. Am J Respir Crit Care Med. 2005;171:1430–1435.
    1. Glynn JR, Murray J, Bester A, Nelson G, Shearer S, Sonnenberg P. High rates of recurrence in HIV-infected and HIV-uninfected patients with tuberculosis. J Infect Dis. 2010;201:704–711.
    1. Narayanan S, Swaminathan S, Supply P. Impact of HIV infection on the recurrence of tuberculosis in south India. J Infect Dis. 2010;201:691–703.
    1. Comas I, Chakravartti J, Small PM. Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved. Nat Genet. 2010;42:498–503.
    1. Gardy JL, Johnston JC, Ho Sui SJ. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med. 2011;364:730–739.
    1. Walker TM, Ip CLC, Harrell RH. Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: a retrospective observational study. Lancet Infect Dis. 2013;13:137–146.
    1. Ford CB, Lin PL, Chase MR. Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infection. Nat Genet. 2011;43:482–486.
    1. Bryant JM, Schurch AC, van Deutekom H. Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data. BMC Infect Dis. 2013;13:110.
    1. Cole ST, Brosch R, Parkhill J. Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature. 1998;393:537–544.
    1. Talarico S, Cave MD, Marrs CF, Foxman B, Zhang L, Yang Z. Variation of the Mycobacterium tuberculosis PE_PGRS 33 gene among clinical isolates. J Clin Microbiol. 2005;43:4954–4960.
    1. Talarico S, Zhang L, Marrs CF. Mycobacterium tuberculosis PE_PGRS16 and PE_PGRS26 genetic polymorphism among clinical isolates. Tuberculosis. 2008;88:283–294.
    1. McEvoy CR, Cloete R, Muller B. Comparative analysis of Mycobacterium tuberculosis PE and PPE genes reveals high sequence variation and an apparent absence of selective constraints. PLoS One. 2012;7:e30593.
    1. Friedrich SO, Rachow A, Saathoff E. Assessment of the sensitivity and specificity of Xpert MTB/RIF assay as an early sputum biomarker of response to tuberculosis treatment. Lancet Respir Med. 2013;1:462–470.
    1. Kent L, McHugh TD, Billington O, Dale JW, Gillespie SH. Demonstration of homology between IS6110 of Mycobacterium tuberculosis and DNAs of other Mycobacterium spp.? J Clin Microbiol. 1995;33:2290–2293.
    1. Supply P, Allix C, Lesjean S. Proposal for standardization of optimized mycobacterial interspersed repetitive unit-variable-number tandem repeat typing of Mycobacterium tuberculosis. J Clin Microbiol. 2006;44:4498–4510.
    1. Quail MA, Otto TD, Gu Y. Optimal enzymes for amplifying sequencing libraries. Nat Methods. 2011;9:10–11.
    1. Casali N, Nikolayevskyy V, Balabanova Y. Microevolution of extensively drug-resistant tuberculosis in Russia. Genome Res. 2012;22:735–745.
    1. Harris SR, Feil EJ, Holden MT. Evolution of MRSA during hospital transmission and intercontinental spread. Science. 2010;327:469–474.
    1. Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics. 2006;22:2688–2690.
    1. Li H, Handsaker B, Wysoker A. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–2079.
    1. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18:821–829.
    1. Stucki D, Malla B, Hostettler S. Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages. PLoS One. 2012;7:e41253.
    1. Kamerbeek J, Schouls L, Kolk A. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J Clin Microbiol. 1997;35:907–914.
    1. van Embden JD, Cave MD, Crawford JT. Strain identification of Mycobacterium tuberculosis by DNA fingerprinting: recommendations for a standardized methodology. J Clin Microbiol. 1993;31:406–409.
    1. Niemann S, Koser CU, Gagneux S. Genomic diversity among drug sensitive and multidrug resistant isolates of Mycobacterium tuberculosis with identical DNA fingerprints. PLoS One. 2009;4:e7407.
    1. Comas I, Homolka S, Niemann S, Gagneux S. Genotyping of genetically monomorphic bacteria: DNA sequencing in Mycobacterium tuberculosis highlights the limitations of current methodologies. PLoS One. 2009;4:e7815.
    1. Martin A, Herranz M, Navarro Y. Evaluation of the inaccurate assignment of mixed infections by Mycobacterium tuberculosis as exogenous reinfection and analysis of the potential role of bacterial factors in reinfection. J Clin Microbiol. 2011;49:1331–1338.
    1. Mitchison DA, Keyes AB, Edwards EA, Ayuma P, Byfield SP, Nunn AJ. Quality control in tuberculosis bacteriology. 2. The origin of isolated positive cultures from the sputum of patients in four studies of short course chemotherapy in Africa. Tubercle. 1980;61:135–144.
    1. Aber VR, Allen BW, Mitchison DA, Ayuma P, Edwards EA, Keyes AB. Quality control in tuberculosis bacteriology. 1. Laboratory studies on isolated positive cultures and the efficiency of direct smear examination. Tubercle. 1980;61:123–133.
    1. Ruddy M, McHugh TD, Dale JW. Estimation of the rate of unrecognized cross-contamination with mycobacterium tuberculosis in London microbiology laboratories. J Clin Microbiol. 2002;40:4100–4104.

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