Genetic diversity within diagnostic sputum samples is mirrored in the culture of Mycobacterium tuberculosis across different settings.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
05 Sep 2024
05 Sep 2024
Historique:
received:
06
03
2024
accepted:
02
08
2024
medline:
6
9
2024
pubmed:
6
9
2024
entrez:
5
9
2024
Statut:
epublish
Résumé
Culturing and genomic sequencing of Mycobacterium tuberculosis (MTB) from tuberculosis (TB) cases is the basis for many research and clinical applications. The alternative, culture-free sequencing from diagnostic samples, is promising but poses challenges to obtain and analyse the MTB genome. Paradoxically, culture is assumed to impose a diversity bottleneck, which, if true, would entail unexplored consequences. To unravel this paradox we generate high-quality genomes of sputum-culture pairs from two different settings after developing a workflow for sequencing from sputum and a tailored bioinformatics analysis. Careful downstream comparisons reveal sources of sputum-culture incongruences due to false positive/negative variation associated with factors like low input MTB DNA or variable genomic depths. After accounting for these factors, contrary to the bottleneck dogma, we identify a 97% variant agreement within sputum-culture pairs, with a high correlation also in the variants' frequency (0.98). The combined analysis from five different settings and more than 100 available samples shows that our results can be extrapolated to different TB epidemic scenarios, demonstrating that for the cases tested culture accurately mirrors clinical samples.
Identifiants
pubmed: 39237504
doi: 10.1038/s41467-024-51266-0
pii: 10.1038/s41467-024-51266-0
doi:
Substances chimiques
DNA, Bacterial
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7114Informations de copyright
© 2024. The Author(s).
Références
Meehan, C. J. et al. Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues. Nat. Rev. Microbiol. 17, 533–545 (2019).
pubmed: 31209399
doi: 10.1038/s41579-019-0214-5
Gagneux, S. Ecology and evolution of Mycobacterium tuberculosis. Nat. Rev. Microbiol. 16, 202–213 (2018).
pubmed: 29456241
doi: 10.1038/nrmicro.2018.8
Gagneux, S. et al. The competitive cost of antibiotic resistance in Mycobacterium tuberculosis. Science 312, 1944–1946 (2006).
pubmed: 16809538
doi: 10.1126/science.1124410
Miotto, P., Cabibbe, A. M., Borroni, E., Degano, M. & Cirillo, D. M. Role of disputed mutations in the rpob gene in interpretation of automated liquid MGIT culture results for rifampin susceptibility testing of Mycobacterium tuberculosis. J. Clin. Microbiol. 56, e01599–17 (2018).
pubmed: 29540456
pmcid: 5925711
doi: 10.1128/JCM.01599-17
Gehre, F. et al. Deciphering the growth behaviour of Mycobacterium africanum. PLoS Negl. Trop. Dis. 7, e2220 (2013).
pubmed: 23696911
pmcid: 3656116
doi: 10.1371/journal.pntd.0002220
Dhillon, J., Fourie, P. B. & Mitchison, D. A. Persister populations of Mycobacterium tuberculosis in sputum that grow in liquid but not on solid culture media. J. Antimicrob. Chemother. 69, 437–440 (2014).
pubmed: 24072170
doi: 10.1093/jac/dkt357
Mohamed, S., Köser, C. U., Salfinger, M., Sougakoff, W. & Heysell, S. K. Targeted next-generation sequencing: a Swiss army knife for mycobacterial diagnostics? Eur. Respir. J. 57, 2002132 (2021).
doi: 10.1183/13993003.04077-2020
Goig, G. A., Blanco, S., Garcia-Basteiro, A. L. & Comas, I. Contaminant DNA in bacterial sequencing experiments is a major source of false genetic variability. BMC Biol. 18, 1–15 (2020).
doi: 10.1186/s12915-020-0748-z
Eshetie, S. & van Soolingen, D. The respiratory microbiota: new insights into pulmonary tuberculosis. BMC Infect. Dis. 19, 92 (2019).
pubmed: 30683056
pmcid: 6347808
doi: 10.1186/s12879-019-3712-1
Goig, G. A. et al. Whole-genome sequencing of Mycobacterium tuberculosis directly from clinical samples for high-resolution genomic epidemiology and drug resistance surveillance: an observational study. Lancet Microbe 1, e175–e183 (2020).
pubmed: 35544271
doi: 10.1016/S2666-5247(20)30060-4
Votintseva, A. A. et al. Same-day diagnostic and surveillance data for tuberculosis via whole-genome sequencing of direct respiratory samples. J. Clin. Microbiol. 55, 1285–1298 (2017).
pubmed: 28275074
pmcid: 5405248
doi: 10.1128/JCM.02483-16
Brown, A. C. et al. Rapid whole-genome sequencing of Mycobacterium tuberculosis isolates directly from clinical samples. J. Clin. Microbiol. 53, 2230–2237 (2015).
pubmed: 25972414
pmcid: 4473240
doi: 10.1128/JCM.00486-15
Shockey, A. C., Dabney, J. & Pepperell, C. S. Effects of host, sample, and in vitro culture on genomic diversity of pathogenic mycobacteria. Front. Genet. 10, 477 (2019).
pubmed: 31214242
pmcid: 6558051
doi: 10.3389/fgene.2019.00477
Doyle, R. M. et al. Direct whole-genome sequencing of sputum accurately identifies drug-resistant mycobacterium tuberculosis faster than MGIT culture sequencing. J. Clin. Microbiol. 56, e00666–18 (2018).
pubmed: 29848567
pmcid: 6062781
doi: 10.1128/JCM.00666-18
Nilgiriwala, K. et al. Genomic sequencing from sputum for tuberculosis disease diagnosis, lineage determination, and drug susceptibility. Prediction. J. Clin. Microbiol. 61, e0157822 (2023).
pubmed: 36815861
doi: 10.1128/jcm.01578-22
Nimmo, C. et al. Whole genome sequencing Mycobacterium tuberculosis directly from sputum identifies more genetic diversity than sequencing from culture. BMC Genomics 20, 389 (2019).
pubmed: 31109296
pmcid: 6528373
doi: 10.1186/s12864-019-5782-2
Goossens, S. N. et al. Detection of minor variants in Mycobacterium tuberculosis whole genome sequencing data. Brief. Bioinform. 23, bbab541 (2022).
pubmed: 34962257
doi: 10.1093/bib/bbab541
Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).
pubmed: 20080505
pmcid: 2828108
doi: 10.1093/bioinformatics/btp698
Structural variants and the SAM format—the long (reads) and short (reads) of it. https://cmdcolin.github.io/posts/2022-02-06-sv-sam .
Coll, F. et al. A robust SNP barcode for typing Mycobacterium tuberculosis complex strains. Nat. Commun. 5, 1–5 (2014).
doi: 10.1038/ncomms5812
Mann, B. C., Jacobson, K. R., Ghebrekristos, Y., Warren, R. M. & Farhat, M. R. Assessment and validation of enrichment and target capture approaches to improve Mycobacterium tuberculosis WGS direct patient samples. J. Clin. Microbiol. 61, e0038223 (2023).
pubmed: 37728909
doi: 10.1128/jcm.00382-23
Use of targeted next-generation sequencing to detect drug-resistant tuberculosis. https://www.who.int/publications/i/item/9789240076372 .
Moreno-Molina, M. et al. Genomic analyses of Mycobacterium tuberculosis from human lung resections reveal a high frequency of polyclonal infections. Nat. Commun. 12, 2716 (2021).
pubmed: 33976135
pmcid: 8113332
doi: 10.1038/s41467-021-22705-z
Lieberman, T. D. et al. Genomic diversity in autopsy samples reveals within-host dissemination of HIV-associated Mycobacterium tuberculosis. Nat. Med. 22, 1470–1474 (2016).
pubmed: 27798613
pmcid: 5508070
doi: 10.1038/nm.4205
Van Deun, A. et al. Mycobacterium tuberculosis borderline rpoB mutations: emerging from the unknown. Eur. Respir. J. 58, 2100783 (2021).
pubmed: 33926970
doi: 10.1183/13993003.00783-2021
Pandey, P. et al. Mycobacterium tuberculosis polyclonal infections through treatment and recurrence. PLoS ONE 15, e0237345 (2020).
pubmed: 32813724
pmcid: 7437862
doi: 10.1371/journal.pone.0237345
Mukamolova, G. V., Turapov, O., Malkin, J., Woltmann, G. & Barer, M. R. Resuscitation-promoting factors reveal an occult population of tubercle Bacilli in Sputum. Am. J. Respir. Crit. Care Med. 181, 174–180 (2010).
pubmed: 19875686
doi: 10.1164/rccm.200905-0661OC
Chengalroyen, M. D. et al. Detection and quantification of differentially culturable tubercle bacteria in sputum from patients with tuberculosis. Am. J. Respir. Crit. Care Med. 194, 1532–1540 (2016).
pubmed: 27387272
pmcid: 5215032
doi: 10.1164/rccm.201604-0769OC
Kubica, G. P., Dye, W. E., Cohn, M. L. & Middlebrook, G. Sputum digestion and decontamination with N-acetyl-L-cysteine—sodium hydroxide for culture of mycobacteria. Am. Rev. Respir. Dis. 87, 775–779 (1963).
pubmed: 13927224
Tripathi, K. et al. Modified Petroff’s method: an excellent simplified decontamination technique in comparison with Petroff’s method. Int J. Recent Trends Sci. Technol. 10, 461–464 (2014).
Somerville, W., Thibert, L., Schwartzman, K. & Behr, M. A. Extraction of Mycobacterium tuberculosis DNA: a question of containment. J. Clin. Microbiol. 43, 2996–2997 (2005).
pubmed: 15956443
pmcid: 1151963
doi: 10.1128/JCM.43.6.2996-2997.2005
Goig, G. A. et al. Towards next-generation diagnostics for tuberculosis: identification of novel molecular targets by large-scale comparative genomics. Bioinformatics 36, 985–989 (2020).
pubmed: 31580405
doi: 10.1093/bioinformatics/btz729
Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).
pubmed: 30423086
pmcid: 6129281
doi: 10.1093/bioinformatics/bty560
Wood, D. E. & Salzberg, S. L. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 15, R46 (2014).
pubmed: 24580807
pmcid: 4053813
doi: 10.1186/gb-2014-15-3-r46
Comas, I. et al. Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved. Nat. Genet. 42, 498–503 (2010).
pubmed: 20495566
pmcid: 2883744
doi: 10.1038/ng.590
Koboldt, D. C. et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics 25, 2283–2285 (2009).
pubmed: 19542151
pmcid: 2734323
doi: 10.1093/bioinformatics/btp373
Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).
pubmed: 33590861
pmcid: 7931819
doi: 10.1093/gigascience/giab008
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
pubmed: 20644199
pmcid: 2928508
doi: 10.1101/gr.107524.110
Marin, M. et al. Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome. Bioinformatics 38, 1781–1787 (2022).
pubmed: 35020793
pmcid: 8963317
doi: 10.1093/bioinformatics/btac023
McHugh, M. L. Interrater reliability: the kappa statistic. Biochem. Med. 22, 276–282 (2012).
doi: 10.11613/BM.2012.031
Walker, T. M. et al. The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis. Lancet Microbe 3, e265–e273 (2022).
pubmed: 35373160
pmcid: 7612554
doi: 10.1016/S2666-5247(21)00301-3
Stucki, D. et al. Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages. Nat. Genet. 48, 1535–1543 (2016).
pubmed: 27798628
pmcid: 5238942
doi: 10.1038/ng.3704
Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).
pubmed: 30016406
doi: 10.1093/bioinformatics/bty633
Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).
pubmed: 29722887
pmcid: 5967553
doi: 10.1093/molbev/msy096