Cryptic Microheteroresistance Explains Mycobacterium tuberculosis Phenotypic Resistance - PubMed (original) (raw)
Cryptic Microheteroresistance Explains Mycobacterium tuberculosis Phenotypic Resistance
John Z Metcalfe et al. Am J Respir Crit Care Med. 2017.
Abstract
Rationale: Minority drug-resistant Mycobacterium tuberculosis subpopulations can be associated with phenotypic resistance but are poorly detected by Sanger sequencing or commercial molecular diagnostic assays.
Objectives: To determine the role of targeted next-generation sequencing in resolving these minor variant subpopulations.
Methods: We used single molecule overlapping reads (SMOR), a targeted next-generation sequencing approach that dramatically reduces sequencing error, to analyze primary cultured isolates phenotypically resistant to rifampin, fluoroquinolones, or aminoglycosides, but for which Sanger sequencing found no resistance-associated variants (RAVs) within respective resistance-determining regions (study group). Isolates also underwent single-colony selection on antibiotic-containing agar, blinded to sequencing results. As a positive control, isolates with multiple colocalizing chromatogram peaks were also analyzed (control group).
Measurements and main results: Among 61 primary culture isolates (25 study group and 36 control group), SMOR described 66 (49%) and 45 (33%) of 135 total heteroresistant RAVs at frequencies less than 5% and less than 1% of the total mycobacterial population, respectively. In the study group, SMOR detected minor resistant variant subpopulations in 80% (n = 20/25) of isolates with no Sanger-identified RAVs (median subpopulation size, 1.0%; interquartile range, 0.2-3.9%). Single-colony selection on drug-containing media corroborated SMOR results for 90% (n = 18/20) of RAV-containing specimens, and the absence of RAVs in 60% (n = 3/5) of isolates. Overall, Sanger sequencing was concordant with SMOR for 77% (n = 53/69) of macroheteroresistant (5-95% total population), but only 5% of microheteroresistant (<5%) subpopulations (n = 3/66) across both groups.
Conclusions: Cryptic minor variant mycobacterial subpopulations exist below the resolving capability of current drug susceptibility testing methodologies, and may explain an important proportion of false-negative resistance determinations.
Keywords: Sanger sequencing; diagnostics; drug-resistant tuberculosis; next-generation sequencing.
Figures
Figure 1.
Flow diagram of specimen selection and analysis. DST = drug susceptibility testing; RAV = resistance-associated variant; RDR = resistance-determining region; RIF = rifampin; SA NHLS = South African National Health Laboratory Service; w.t. = wild-type; XDR = extensively drug resistant. *Three isolates in the control group were analyzed for both gyrA and rrs.
Figure 2.
Distribution of single molecule overlapping reads–determined microheteroresistant subpopulations. The heat maps indicate targeted deep sequencing–determined resistant Mycobacterium tuberculosis populations as follows: dark blue, minor resistant subpopulation, 1% of the total M. tuberculosis population; light blue, minor resistant subpopulation, between 1% and 5% of the total M. tuberculosis population; light red, macroheteroresistant subpopulation, 5–95% of the total M. tuberculosis population; red, fixed resistance mutations, >95% total M. tuberculosis population. (A) Study group. The study group consisted of isolates with phenotypic drug resistance (subheading, y-axis) without Sanger sequencing–determined genotypic resistance within respective resistance-determining regions (black outlined boxes). Note that microheteroresistant subpopulations were often detected within rpoB and gyrA, consistent with phenotypic resistance, despite lack of Sanger-identified resistance-associated variant. (B) Control group. The control group was selected on the basis of multiple chromatographic peaks within resistance-determining regions corresponding to phenotypic drug resistance (subheading, y-axis) for each analyzed drug (black outlined boxes). Open circles indicate resistance-associated variants also detected by Sanger sequencing. *Most reads for sample R_2362 identified the 9-bp deletion del516_525. †According to national tuberculosis control program policy at the time, second-line DST was not performed for the RIF-monoresistant group. DST = drug susceptibility testing; FQ = fluoroquinolone; INH = isoniazid; PXDR = pre–extensively drug resistant (RIF and INH resistance, with additional resistance to either FQ or SLI); RIF = rifampin; RIF-R = rifampin monoresistance; SLI = second-line injectable medication; XDR = extensively drug resistant (RIF and INH resistance, with additional resistance to FQ and SLI).
Figure 3.
Comparison of Sanger sequencing and single molecule overlapping reads (SMOR) for detection of Mycobacterium tuberculosis heteroresistant subpopulations. Each circle represents 1 of 135 total heteroresistant resistance-associated variants detected by next-generation sequencing (NGS) within the resistance-determining regions of interest, stratified by study group (Sanger-identified wild-type resistance-determining regions) or control group (Sanger-identified multiple colocalizing chromatogram peaks within resistance-determining regions), and whether they were detected by SMOR but not by Sanger (NGS Only), or by both SMOR and Sanger sequencing (NGS and Sanger). The dashed line represents the 5% resistant subpopulation cut point defining microheteroresistance. The blue box plots represent the first quartile, median, and third quartile of the heteroresistant subpopulation distribution in each category. Note that two resistance-associated variants were detected by Sanger sequencing but not by SMOR; these were omitted for clarity.
Figure 4.
Proportional subpopulation size stratified by resistance-associated variant. The frequencies and relative proportions of subphenotypic (dark blue), microheteroresistant (light blue), and macroheteroresistant (light red) subpopulations are presented for each resistance-associated variant analyzed.
References
- World Health Organization. Global Tuberculosis Report. 2016 [accessed 2017 May 1]. Available from: http://www.who.int/tb/publications/global_report/en/
- Dalton T, Cegielski P, Akksilp S, Asencios L, Campos Caoili J, Cho SN, Erokhin VV, Ershova J, Gler MT, Kazennyy BY, et al. Global PETTS Investigators. Prevalence of and risk factors for resistance to second-line drugs in people with multidrug-resistant tuberculosis in eight countries: a prospective cohort study. Lancet. 2012;380:1406–1417. -PMC -PubMed
- Sotgiu G, Tiberi S, D’Ambrosio L, Centis R, Alffenaar JW, Caminero JA, Abdo Arbex M, Alarcon Guizado V, Aleksa A, Dore S, et al. International Carbapenem Study Group. Faster for less: the new “shorter” regimen for multidrug-resistant tuberculosis. Eur Respir J. 2016;48:1503–1507. -PubMed
- Cegielski JP, Dalton T, Yagui M, Wattanaamornkiet W, Volchenkov GV, Via LE, Van Der Walt M, Tupasi T, Smith SE, Odendaal R, et al. Global Preserving Effective TB Treatment Study (PETTS) Investigators. Extensive drug resistance acquired during treatment of multidrug-resistant tuberculosis. Clin Infect Dis. 2014;59:1049–1063. -PMC -PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical