Comparison of in silico predicted Mycobacterium tuberculosis spoligotypes and lineages from whole genome sequencing data

• Published in: Scientific reports 2023-07, Vol.13 (1), p.11368-11368, Article 11368
• Main Authors: Napier, Gary, Couvin, David, Refrégier, Guislaine, Guyeux, Christophe, Meehan, Conor J., Sola, Christophe, Campino, Susana, Phelan, Jody, Clark, Taane G.
• Format: Article
• Language: English
• Subjects: 631/1647/2217; 631/1647/48; Bacterial Typing Techniques; Beijing; Computer Science; Cryptography and Security; Distributed, Parallel, and Cluster Computing; Drug Resistance; Emerging Technologies; Genomes; Genotype; Genotyping; Geographical distribution; Host-pathogen interactions; Humanities and Social Sciences; Humans; Modeling and Simulation; Multiagent Systems; multidisciplinary; Mycobacterium tuberculosis; Nomenclature; Science; Science (multidisciplinary); Single-nucleotide polymorphism; Software Engineering; Spoligotyping; Tuberculosis; Tuberculosis - microbiology; Ubiquitous Computing; Virulence; Whole genome sequencing
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-38384-3

Bacterial strain-types in the Mycobacterium tuberculosis complex underlie tuberculosis disease, and have been associated with drug resistance, transmissibility, virulence, and host–pathogen interactions. Spoligotyping was developed as a molecular genotyping technique used to determine strain-types, though recent advances in whole genome sequencing (WGS) technology have led to their characterization using SNP-based sub-lineage nomenclature. Notwithstanding, spoligotyping remains an important tool and there is a need to study the congruence between spoligotyping-based and SNP-based sub-lineage assignation. To achieve this, an in silico spoligotype prediction method (“Spolpred2”) was developed and integrated into TB-Profiler. Lineage and spoligotype predictions were generated for > 28 k isolates and the overlap between strain-types was characterized. Major spoligotype families detected were Beijing (25.6%), T (18.6%), LAM (13.1%), CAS (9.4%), and EAI (8.3%), and these broadly followed known geographic distributions. Most spoligotypes were perfectly correlated with the main MTBC lineages (L1-L7, plus animal). Conversely, at lower levels of the sub-lineage system, the relationship breaks down, with only 65% of spoligotypes being perfectly associated with a sub-lineage at the second or subsequent levels of the hierarchy. Our work supports the use of spoligotyping (membrane or WGS-based) for low-resolution surveillance, and WGS or SNP-based systems for higher-resolution studies.