TGS-TB: Total Genotyping Solution for Mycobacterium tuberculosis Using Short-Read Whole-Genome Sequencing - PubMed (original) (raw)

TGS-TB: Total Genotyping Solution for Mycobacterium tuberculosis Using Short-Read Whole-Genome Sequencing

Tsuyoshi Sekizuka et al. PLoS One. 2015.

Abstract

Whole-genome sequencing (WGS) with next-generation DNA sequencing (NGS) is an increasingly accessible and affordable method for genotyping hundreds of Mycobacterium tuberculosis (Mtb) isolates, leading to more effective epidemiological studies involving single nucleotide variations (SNVs) in core genomic sequences based on molecular evolution. We developed an all-in-one web-based tool for genotyping Mtb, referred to as the Total Genotyping Solution for TB (TGS-TB), to facilitate multiple genotyping platforms using NGS for spoligotyping and the detection of phylogenies with core genomic SNVs, IS6110 insertion sites, and 43 customized loci for variable number tandem repeat (VNTR) through a user-friendly, simple click interface. This methodology is implemented with a KvarQ script to predict MTBC lineages/sublineages and potential antimicrobial resistance. Seven Mtb isolates (JP01 to JP07) in this study showing the same VNTR profile were accurately discriminated through median-joining network analysis using SNVs unique to those isolates. An additional IS6110 insertion was detected in one of those isolates as supportive genetic information in addition to core genomic SNVs. The results of in silico analyses using TGS-TB are consistent with those obtained using conventional molecular genotyping methods, suggesting that NGS short reads could provide multiple genotypes to discriminate multiple strains of Mtb, although longer NGS reads (≥ 300-mer) will be required for full genotyping on the TGS-TB web site. Most available short reads (~100-mer) can be utilized to discriminate the isolates based on the core genome phylogeny. TGS-TB provides a more accurate and discriminative strain typing for clinical and epidemiological investigations; NGS strain typing offers a total genotyping solution for Mtb outbreak and surveillance. TGS-TB web site: https://gph.niid.go.jp/tgs-tb/.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1

Fig 1. Schematic representation of the TGS-TB system.

Fig 2

Fig 2. Sample results obtained from TGS-TB.

The NGS reads of seven Mtb isolates were investigated, and the resulting basic information, such as number of trimmed map reads and the coverage region-depth, is shown. In total, 21,805 core-genome SNVs are available in the TGS-TB; 20,928 (95.98%) SNVs are characterized, and 219 additional strain-specific SNVs sites can be implemented in the original dataset. The respective results for lineage, AMR, core genome phylogenetic tree (maximum-likelihood method with x100 bootstrapping), spoligotyping, IS_6110_ insertion and sMIRU-VNTR typing can be viewed in a new window tab and retrieved using the “download all” button. The KvarQ script predicts the lineages/sublineages and AMRs, and the sample queries are assigned as a lineage 2/Beijing sublineage without AMRs (S2 Fig). The AMR target list in the original KvarQ (v2.0) program has been improved with the addition of more reliable genetic alterations for the embA, gyrA, katG, pncA, rpoB, rpsL, rrs and inhA genes (S1 Text).

Fig 3

Fig 3. The core genome phylogeny obtained by the maximum-likelihood method with x100 bootstrapping.

Fig 4

Fig 4. Median-joining network of the seven outbreak isolates based on the detected core genomic variations.

A) The variations are summarized as nexus format files (.nex), and PopART visualizes the epidemiological linkages among the isolates through a user specified network method. The bars on the edge indicate the number of SNVs between the nodes (isolates). B) In addition to three SNV differences between JP05 and the outbreak isolates (JP03, JP04, JP06, and JP07), an additional IS_6110_ insertion was detected at the 1,531,598 nt genome position in JP05, suggesting that JP05 could be unrelated to the outbreak, although the VNTR profile is consistent.

Fig 5

Fig 5. Schematic representation of the IS_6110_ insertion detection strategy.

A) The IS_6110_ sequence (Acc.# X94955 and X94956)-positive short reads are collected (A1-2), rearranged (A3), trimmed (A4), subtracted (A5) and mapped to the Mtb H37Rv chromosome (NC_000962.3) [30] using BWA-SW mapping [29]. B) Typical read mapping profile for the detection of the IS_6110_ insertion site in both directions.

Similar articles

Cited by

References

    1. Global tuberculosis report. [Internet]. http://www.who.int/tb/publications/global_report/gtbr13_main_text.pdf (accessed Jan 10, 2014). 2013
    1. Barnes PF, Cave MD. Molecular epidemiology of tuberculosis. The New England journal of medicine. 2003;349(12):1149–56. 10.1056/NEJMra021964 . - DOI - PubMed
    1. van Embden JD, Cave MD, Crawford JT, Dale JW, Eisenach KD, Gicquel B, et al. Strain identification of Mycobacterium tuberculosis by DNA fingerprinting: recommendations for a standardized methodology. Journal of clinical microbiology. 1993;31(2):406–9. - PMC - PubMed
    1. Kamerbeek J, Schouls L, Kolk A, van Agterveld M, van Soolingen D, Kuijper S, et al. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. Journal of clinical microbiology. 1997;35(4):907–14. - PMC - PubMed
    1. Kremer K, van Soolingen D, Frothingham R, Haas WH, Hermans PW, Martin C, et al. Comparison of methods based on different molecular epidemiological markers for typing of Mycobacterium tuberculosis complex strains: interlaboratory study of discriminatory power and reproducibility. Journal of clinical microbiology. 1999;37(8):2607–18. - PMC - PubMed

Publication types

MeSH terms

Grants and funding

This research was funded through a Grant-in-Aid for Research on Emerging and Re-emerging Infectious Diseases (H25-Shinko-Ippan-015) from the Ministry of Health Labour and Welfare Programs of Japan, and also through Research Program on Emerging and Re-emerging Infectious Diseases (15fk0108011h0003 and 15fk0108004h0001) from Japan Agency for Medical Research and development, AMED. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

LinkOut - more resources