cg/wgMLST dynamic approach for Legionella pneumophila typing
Introduction Sequence-based typing (SBT) relying on seven loci has been the standard for understanding Legionella pneumophila relationships for twenty years. However, given their higher discriminatory power, genome-scale typing approaches, namely core genome (cg) or whole-genome (wg) multilocus sequence typing (MLST) methods, are being adopted by the scientific community. In this context, we established the Legionella International Typing (LIT) workgroup to develop, evaluate, and disseminate a new cgMLST schema with enhanced wgMLST resolution for investigation and source attribution of L. pneumophila outbreaks, as compared to a previously developed cgMLST schema. Methods The schema was created with the chewBBACA software using a selected subset of 4402 high-quality genome assemblies representative of the species diversity. A multi-step refinement workflow, considering loci prevalence in a large and diverse global dataset (n=9657 assemblies), allelic diversity and presence/absence profile across the “species” tree, was performed to select loci for the final cg/wgMLST schema. Cluster congruence analysis was performed to compare the performance of the novel cgMLST schema with a previously established 1521-loci cgMLST schema and assess its correlation with SBT classification. Results The novel cg/wgMLST schema includes 2009 loci present in 98% of the global dataset forming the static cgMLST schema for routine genomic surveillance, plus 2698 accessory loci, which compose the wgMLST schema for a dynamic in-depth analysis at lineage or outbreak level. The novel cgMLST schema maintains compatibility with SBT classification and revealed high congruence with genetic clustering from an existing 1521-loci cgMLST schema, while offering higher cluster resolution. Analysis of epidemiologically confirmed related isolates using a dynamic wgMLST approach—by extending the cgMLST schema with accessory loci shared among related isolates—demonstrated increased confidence in isolate discrimination and source attribution. Conclusions The novel cg/wgMLST schema, developed through this international collaboration, has already attracted interest from several leading national and international entities for short-term implementation. Its adoption is expected to contribute significantly to accelerating and harmonizing genomic surveillance of Legionnaires' disease at both local and global levels.
Introduction Sequence-based typing (SBT) relying on seven loci has been the standard for understanding Legionella pneumophila relationships for twenty years. However, given their higher discriminatory power, genome-scale typing approaches, namely core genome (cg) or whole-genome (wg) multilocus sequence typing (MLST) methods, are being adopted by the scientific community. In this context, we established the Legionella International Typing (LIT) workgroup to develop, evaluate, and disseminate a new cgMLST schema with enhanced wgMLST resolution for investigation and source attribution of L. pneumophila outbreaks, as compared to a previously developed cgMLST schema. Methods The schema was created with the chewBBACA software using a selected subset of 4402 high-quality genome assemblies representative of the species diversity. A multi-step refinement workflow, considering loci prevalence in a large and diverse global dataset (n=9657 assemblies), allelic diversity and presence/absence profile across the “species” tree, was performed to select loci for the final cg/wgMLST schema. Cluster congruence analysis was performed to compare the performance of the novel cgMLST schema with a previously established 1521-loci cgMLST schema and assess its correlation with SBT classification. Results The novel cg/wgMLST schema includes 2009 loci present in 98% of the global dataset forming the static cgMLST schema for routine genomic surveillance, plus 2698 accessory loci, which compose the wgMLST schema for a dynamic in-depth analysis at lineage or outbreak level. The novel cgMLST schema maintains compatibility with SBT classification and revealed high congruence with genetic clustering from an existing 1521-loci cgMLST schema, while offering higher cluster resolution. Analysis of epidemiologically confirmed related isolates using a dynamic wgMLST approach—by extending the cgMLST schema with accessory loci shared among related isolates—demonstrated increased confidence in isolate discrimination and source attribution. Conclusions The novel cg/wgMLST schema, developed through this international collaboration, has already attracted interest from several leading national and international entities for short-term implementation. Its adoption is expected to contribute significantly to accelerating and harmonizing genomic surveillance of Legionnaires' disease at both local and global levels.
CIRI-Inserm-U1111