Whole-genome-based Mycobacterium tuberculosis surveillance: a standardized, portable, and expandable approach

Abstract

Whole-genome sequencing (WGS) allows for effective tracing of Mycobacterium tuberculosis complex (MTBC) (tuberculosis pathogens) transmission. However, it is difficult to standardize and, therefore, is not yet employed for interlaboratory prospective surveillance. To allow its widespread application, solutions for data standardization and storage in an easily expandable database are urgently needed. To address this question, we developed a core genome multilocus sequence typing (cgMLST) scheme for clinical MTBC isolates using the Ridom SeqSphere(+) software, which transfers the genome-wide single nucleotide polymorphism (SNP) diversity into an allele numbering system that is standardized, portable, and not computationally intensive. To test its performance, we performed WGS analysis of 26 isolates with identical IS6110 DNA fingerprints and spoligotyping patterns from a longitudinal outbreak in the federal state of Hamburg, Germany (notified between 2001 and 2010). The cgMLST approach (3,041 genes) discriminated the 26 strains with a resolution comparable to that of SNP-based WGS typing (one major cluster of 22 identical or closely related and four outlier isolates with at least 97 distinct SNPs or 63 allelic variants). Resulting tree topologies are highly congruent and grouped the isolates in both cases analogously. Our data show that SNP- and cgMLST-based WGS analyses facilitate high-resolution discrimination of longitudinal MTBC outbreaks. cgMLST allows for a meaningful epidemiological interpretation of the WGS genotyping data. It enables standardized WGS genotyping for epidemiological investigations, e.g., on the regional public health office level, and the creation of web-accessible databases for global TB surveillance with an integrated early warning system.

FIG 1

IS6110 DNA fingerprint and spoligotyping patterns of the 26 outbreak isolates investigated. IS6110 band positions were normalized, in order to enable mutual comparison of all isolate fingerprints. Spoligotyping results are displayed in 43-digit barcode signals in which a black box means spacer present and a white box means spacer not present.

FIG 2

Established epidemiological links among the 26 cluster patients. The 26 patients are presented in boxes with the specific strain number. Established epidemiological links are visualized by color coding and position in the figure. All patients without a defined epidemiological link are in white boxes.

FIG 3

Minimum spanning tree based on the concatenated sequences of the 322 SNPs determined by WGS analysis. Colors are concordant with grouping of strains in the different epidemiological scenarios as outlined in Fig. 2. Numbers correspond with SNP differences between two nodes in the tree.

FIG 4

Minimum spanning tree based on the allele diversity determined by analysis of 3,041 cgMLST genes using the SeqSphere⁺ software. Colors are concordant with grouping of strains in the different epidemiological scenarios as outlined in Fig. 2. Numbers correspond with allele differences between two nodes in the tree.

FIG 5

Variation among patient isolates with epidemiological links. White boxes give first the distance in variant SNP positions and then the number of allele differences. Out of 14 epidemiological links, 10 were confirmed by WGS with a maximum variation of 3 SNPs or allele differences (marked in green). In four cases, SNP-based analysis suggests a different transmission chain (red lines), while cgMLST analysis refutes only one epidemiological link (dashed line).