The genomes of 16 clinical Mycobacterium tuberculosis isolates were subjected to whole-genome sequencing to identify mutations related to resistance to one or more anti-Mycobacterium drugs. The sequence data will help in understanding the genomic characteristics of M. tuberculosis isolates and their resistance mutations prevalent in South India.
ABSTRACT
The genomes of 16 clinical Mycobacterium tuberculosis isolates were subjected to whole-genome sequencing to identify mutations related to resistance to one or more anti-Mycobacterium drugs. The sequence data will help in understanding the genomic characteristics of M. tuberculosis isolates and their resistance mutations prevalent in South India.
ANNOUNCEMENT
Tuberculosis (TB) is the leading cause of death due to a single infectious agent worldwide. As per a World Health Organization (WHO) report, an estimated 10 million people developed TB in 2017 (1). The emergence of strains of multidrug-resistant tuberculosis (MDR-TB) that are resistant to the most effective drugs (rifampin and isoniazid) poses a threat to TB control programs. These constitute 82% of the 558,000 rifampin-resistant cases reported in 2017 worldwide. Among the MDR-TB cases, 8.5% are identified as extensively drug-resistant TB (XDR-TB) and have additional resistance to one of the fluoroquinolones and aminoglycosides. India alone contributed to 2,650 notified cases of XDR-TB in 2017 (1, 2). Early and accurate diagnosis of MDR and XDR-TB followed by appropriate treatment is of critical importance if the number of new cases is to be reduced worldwide. Here, we describe the use of whole-genome sequencing (WGS) technology to define the genetic mutations in isolates from a part of the world that lacks such data and which could contribute to the genetic prediction of a tailored treatment regimen for TB patients in the future.
We report the whole-genome sequence of 16 Mycobacterium tuberculosis isolates from patients in Chennai, India. These have a range of drug resistance patterns that categorize them as MDR, polydrug-resistant (PDR), or XDR. In order to obtain the mycobacterial DNA for WGS, M. tuberculosis strains were isolated from sputum samples of pulmonary tuberculosis patients treated at NIRT, Chennai and grown on Lowenstein-Jensen (LJ) medium, and colonies were scraped from the 3+ growth on the medium into Tris-ethylenediaminetetraacetic acid (TE) buffer (3–5) followed by genomic DNA extraction with a cetyltrimethylammonium bromide-sodium chloride (CTAB–NaCl) extraction method (6). Drug susceptibility of the M. tuberculosis isolates was tested with an automated MGIT 960 instrument as per the manufacturer’s protocol (7, 8). DNA purity and concentration were determined with Nanodrop (9) and Qubit 3.0 fluorometers, respectively (10). Library preparation was performed with the NEXTFLEX DNA library kit as defined by the manufacturer’s protocol (11). Briefly, genomic DNA was sheared to generate fragments of approximately 200 to 600 bp. The fragment size distribution was checked using an Agilent Bioanalyzer (Agilent Technologies) according to the manufacturer’s instructions (12). These adapter ligated fragments were subjected to 10 rounds of PCR with primers provided in the NEXTFLEX DNA sequencing kit. The libraries were quantified using quantitative PCR (qPCR, KAPA library quantification kit, Kappabiosystems) normalized to 1 nM and denatured with 0.1 N NaOH before sequencing with MiSeq v2 cluster chemistry (Illumina). Raw sequence reads were filtered with Trimmomatic v0.36 (13) (quality >20) and assembled with SPAdes v3.11.0 (14) with default parameters, and the contigs larger than 500 bp were filtered for further analysis. The filtered reads were also aligned to H37Rv (GenBank accession number NC_000962) using bwa v0.7.12 (15). The alignment obtained was processed for correction of alignments at indels by the local realignment with a combination of Picard v2.2.4 (http://broadinstitute.github.io/picard/) and GATK v3.5 (16). The variants were identified with SAMtools v1.3.1 (17) and were filtered based on the following parameters: base quality greater than 50, depth greater than 20, mapping quality greater than 30, and alternate allele proportion greater than 75%. The variants were further annotated using a custom Python script (https://github.com/kumarnaren/mtb_vcf_annotator).
Table 1 lists the characteristics of the 16 genomes that were sequenced. The complete length of the assembled genomes ranged from 4,220,229 to 438,963 bp, with coverage depth ranging from 52× to 198×. Examination of the genetic variants revealed the presence of the well-known mutations S315T in katG and S450L in rpoB (18, 19) to be the predominant mutations in isoniazid- and rifampin-resistant isolates, respectively. Isolates were assigned to lineages 1 to 4 based on the presence or absence of phylogenetic single nucleotide polymorphisms (SNPs) reported by Coll et al. (18). Lineage 1 was dominant in our collection of 16 isolates, which is consistent with our previous reports (3, 5) based on spoligotyping and WGS of drug-susceptible clinical isolates of M. tuberculosis.
TABLE 1.
Summary of sequence details, drug resistance category, and lineage prediction for M. tuberculosis isolates
| NCBI identification no.a | Assembly accession no. | Coverage depth (×) | Read length (bp) | GC content (%) | N50 value (bp) | No. of contigs >500 | Genome size (bp) | Reference coverage (H37Rv) (%) | No. of tRNAs | No. of rRNAs | No. of coding DNA sequences | Lineage |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| NIRTX002_PDR | SDOU00000000 | 74 | 151 | 65.58 | 90,381 | 103 | 4,220,229 | 99.3 | 44 | 0 | 3,997 | 1 |
| NIRTX003_XDR | SDOT00000000 | 131 | 151 | 65.58 | 98,656 | 107 | 4,375,554 | 99.2 | 45 | 3 | 4,139 | 3 |
| NIRTX004_XDR | SDOS00000000 | 79 | 100 | 65.35 | 57,187 | 136 | 4,233,503 | 96.3 | 45 | 2 | 4,112 | 4 |
| NIRTX005_XDR | SDOR00000000 | 80 | 150 | 65.37 | 60,784 | 140 | 4,262,450 | 96.8 | 45 | 4 | 4,163 | 4 |
| NIRTX006_XDR | SDOQ00000000 | 75 | 76 | 65.59 | 98,740 | 114 | 4,350,302 | 98.6 | 45 | 3 | 4,119 | 2 |
| NIRTX007_PDR | SDOP00000000 | 85 | 76 | 65.58 | 85,411 | 133 | 4,389,631 | 99.5 | 45 | 3 | 4,145 | 1 |
| NIRTX008_XDR | SDOO00000000 | 52 | 76 | 65.67 | 114,871 | 89 | 4,300,325 | 97.5 | 45 | 1 | 4,068 | 4 |
| NIRTX009_XDR | SDON00000000 | 91 | 76 | 65.59 | 108,252 | 91 | 4,379,992 | 99.3 | 45 | 3 | 4,103 | 1 |
| NIRTX010_PDR | SDOM00000000 | 69 | 76 | 65.61 | 72,683 | 127 | 4,329,145 | 98.1 | 45 | 3 | 4,118 | 2 |
| NIRTX011_XDR | SDOL00000000 | 60 | 76 | 65.59 | 115,334 | 96 | 4,384,136 | 99.4 | 45 | 3 | 4,113 | 1 |
| NIRTX015_MDR | SDOK00000000 | 198 | 76 | 65.59 | 105,690 | 109 | 4,366,330 | 99.0 | 45 | 3 | 4,113 | 1 |
| NIRTX016_MDR | SDOJ00000000 | 71 | 76 | 65.59 | 104,750 | 99 | 4,378,706 | 99.3 | 45 | 3 | 4,123 | 1 |
| NIRTX019_MDR | SDOI00000000 | 53 | 76 | 65.56 | 97,386 | 98 | 4,370,427 | 99.1 | 45 | 3 | 4,113 | 1 |
| NIRTX022_MDR | SDOH00000000 | 174 | 151 | 65.61 | 94,182 | 101 | 4,362,069 | 98.9 | 45 | 3 | 4,136 | 4 |
| NIRTX024_MDR | SDOG00000000 | 68 | 151 | 65.56 | 105,728 | 92 | 4,383,766 | 99.4 | 45 | 3 | 4,152 | 1 |
| NIRTX025_MDR | SDOF00000000 | 92 | 151 | 65.54 | 25,670 | 323 | 4,380,819 | 99.9 | 49 | 8 | 4,295 | 1 |
MDR, multidrug-resistant TB; XDR, extensively drug-resistant TB; PDR, polydrug-resistant TB.
The sequenced genomes of these isolates will contribute toward an understanding of the genomic characteristics of strains of M. tuberculosis that are prevalent in India, including the genetic mutations that cause resistance. In particular, these data add to knowledge about isolates from South India and provide a resource for future studies of M. tuberculosis in the region.
Data availability.
The whole-genome sequence reads of the Mycobacterium tuberculosis isolates reported here are deposited in the Sequence Read Archive (SRA) under accession number PRJNA492975. This whole-genome shotgun project (assembly) has been deposited in GenBank under the accession numbers SDOF00000000 to SDOU00000000. The versions described in this paper are accession numbers SDOF01000000 to SDOU01000000.
ACKNOWLEDGMENTS
This publication presents research supported by the MRC-DBT-funded partnership between the National Institute for Research in Tuberculosis, Chennai, India (Indian Council of Medical Research, New Delhi 5/2-8/LDCE/2014 for S.K., Department of Biotechnology [BT/IN/DBT-MRC (UK)/12/SS/2015-2016] for D.N., M.N., S.P.T., S.S., and U.D.R.) and the University of Cambridge (UK Medical Research Council [MR/N501864/1] for N.K. and S.P.).
REFERENCES
- 1.WHO. 2017. WHO: global tuberculosis report 2017. WHO, Geneva, Switzerland. [Google Scholar]
- 2.RNTCP. 2018. India TB report 2018. RNTCP, New Delhi, India. [Google Scholar]
- 3.Manson AL, Abeel T, Galagan JE, Sundaramurthi JC, Salazar A, Gehrmann T, Shanmugam SK, Palaniyandi K, Narayanan S, Swaminathan S, Earl AM. 2017. Mycobacterium tuberculosis whole genome sequences from Southern India suggest novel resistance mechanisms and the need for region-specific diagnostics. Clin Infect Dis 64:1494–1501. doi: 10.1093/cid/cix169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Martin RS, Sumarah RK, Robart EM. 1975. Comparison of four culture media for the isolation of Mycobacterium tuberculosis: a 2-year study. J Clin Microbiol 2:438–440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Shanmugam S, Selvakumar N, Narayanan S. 2011. Drug resistance among different genotypes of Mycobacterium tuberculosis isolated from patients from Tiruvallur, South India. Infect Genet Evol 11:980–986. doi: 10.1016/j.meegid.2011.03.011. [DOI] [PubMed] [Google Scholar]
- 6.Baess I. 1974. Isolation and purification of deoxyribonucleic acid from mycobacteria. Acta Pathol Microbiol Scand B 82:780–784. doi: 10.1111/j.1699-0463.1974.tb02375.x. [DOI] [PubMed] [Google Scholar]
- 7.Kam KM, Sloutsky A, Yip CW, Bulled N, Seung KJ, Zignol M, Espinal M, Jun SC, Kim SJ. 2010. Determination of critical concentrations of second-line anti-tuberculosis drugs with clinical and microbiological relevance. Int J Tuberc Lung Dis 14:282–288. [PubMed] [Google Scholar]
- 8.Siddiqi S, Ahmed A, Asif S, Behera D, Javaid M, Jani J, Jyoti A, Mahatre R, Mahto D, Richter E, Rodrigues C, Visalakshi P, Rüsch-Gerdes S. 2012. Direct drug susceptibility testing of Mycobacterium tuberculosis for rapid detection of multidrug resistance using the Bactec MGIT 960 system: a multicenter study. J Clin Microbiol 50:435–440. doi: 10.1128/JCM.05188-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Desjardins P, Conklin D. 2010. NanoDrop microvolume quantitation of nucleic acids. J Vis Exp 45:e2565. doi: 10.3791/2565. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Nakayama Y, Yamaguchi H, Einaga N, Esumi M. 2016. Pitfalls of DNA quantification using DNA-binding fluorescent dyes and suggested solutions. PLoS One 11:e0150528. doi: 10.1371/journal.pone.0150528. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Xia S, Huang C-C, Le M, Dittmar R, Du M, Yuan T, Guo Y, Wang Y, Wang X, Tsai S, Suster S, Mackinnon AC, Wang L. 2015. Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls. Lung Cancer 90:78–84. doi: 10.1016/j.lungcan.2015.07.002. [DOI] [PubMed] [Google Scholar]
- 12.Brena RM, Auer H, Kornacker K, Hackanson B, Raval A, Byrd JC, Plass C. 2006. Accurate quantification of DNA methylation using combined bisulfite restriction analysis coupled with the Agilent 2100 Bioanalyzer platform. Nucleic Acids Res 34:e17. doi: 10.1093/nar/gnj017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. doi: 10.1093/bioinformatics/btu170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477. doi: 10.1089/cmb.2012.0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Li H, Durbin R. 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760. doi: 10.1093/bioinformatics/btp324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. 2010. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303. doi: 10.1101/gr.107524.110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078–2079. doi: 10.1093/bioinformatics/btp352. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Coll F, McNerney R, Guerra-Assunção JA, Glynn JR, Perdigão J, Viveiros M, Portugal I, Pain A, Martin N, Clark TG. 2014. A robust SNP barcode for typing Mycobacterium tuberculosis complex strains. Nat Commun 5:4812. doi: 10.1038/ncomms5812. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Zeng X, Kwok JS-L, Yang KY, Leung KS-S, Shi M, Yang Z, Yam W-C, Tsui SK-W. 2018. Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance. BMC Genomics 19:365. doi: 10.1186/s12864-018-4734-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
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Data Availability Statement
The whole-genome sequence reads of the Mycobacterium tuberculosis isolates reported here are deposited in the Sequence Read Archive (SRA) under accession number PRJNA492975. This whole-genome shotgun project (assembly) has been deposited in GenBank under the accession numbers SDOF00000000 to SDOU00000000. The versions described in this paper are accession numbers SDOF01000000 to SDOU01000000.