Dataset Information

Microbial species delineation using whole genome sequences.

ABSTRACT: Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness. In this work, we demonstrate that the combination of gANI and the alignment fraction (AF) between two genomes accurately reflects their genomic relatedness. We introduce an efficient implementation of AF,gANI and discuss its successful application to 86.5M genome pairs between 13,151 prokaryotic genomes assigned to 3032 species. Subsequently, by comparing the genome clusters obtained from complete linkage clustering of these pairs to existing taxonomy, we observed that nearly 18% of all prokaryotic species suffer from anomalies in species definition. Our results can be used to explore central questions such as whether microorganisms form a continuum of genetic diversity or distinct species represented by distinct genetic signatures. We propose that this precise and objective AF,gANI-based species definition: the MiSI (Microbial Species Identifier) method, be used to address previous inconsistencies in species classification and as the primary guide for new taxonomic species assignment, supplemented by the traditional polyphasic approach, as required.

SUBMITTER: Varghese NJ

PROVIDER: S-EPMC4538840 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Microbial species delineation using whole genome sequences.

Varghese Neha J NJ Mukherjee Supratim S Ivanova Natalia N Konstantinidis Konstantinos T KT Mavrommatis Kostas K Kyrpides Nikos C NC Pati Amrita A

Nucleic acids research 20150706 14

Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness. In this work, we demonstrate that the combination of gANI and the alignment fracti ...[more]

PMID: 26150420

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Project description:For facilitating tuberculosis (TB) control, we used a whole-genome sequencing (WGS)-based approach to delineate transmission networks in a country with an intermediate burden of TB. A cluster was defined as Mycobacterium tuberculosis isolates with identical genotypes, and an outbreak was defined as clustered cases with epidemiological links (epi-links). To refine a cluster predefined using space oligonucleotide typing and mycobacterial interspersed repetitive unit variable tandem repeat typing, we analyzed one pansusceptible TB (C1) and three multidrug-resistant (MDR)-TB (C2-C4) clusters from different scenarios. Pansusceptible TB cluster (C1) consisting of 28 cases had ≤5 single nucleotide polymorphisms (SNPs) difference between their isolates. C1 was a definite outbreak, with cases attending the same junior high school in 2012. Three MDR-TB clusters (C2-C4) with distinct genotypes were identified, each consisting of 12-22 cases. Some of the cases had either ≤5 or ≤15 SNPs difference with clear or probable epi-links. Of note, even though WGS could effectively assist TB contact tracing, we still observed missing epi-links in some cases within the same cluster. Our results showed that thresholds of ≤5 and ≤15 SNPs difference between isolates were used to categorize definite and probable TB transmission, respectively. Furthermore, a higher SNP threshold might be required to define an MDR-TB outbreak. WGS still needs to be combined with classical epidemiological methods for improving outbreak investigations. Importantly, different SNP thresholds have to be applied to define outbreaks.ImportanceTB is a chronic disease. Depending on host factors and TB burden, clusters of cases may continue to increase for several years. Conventional genotyping methods overestimate TB transmission, hampering precise detection of outbreaks and comprehensive surveillance. WGS can be used to obtain SNP information of M. tuberculosis to improve discriminative limitations of conventional methods and to strengthen delineation of transmission networks. It is important to define the country-specific SNP thresholds for investigation of transmission. This study demonstrated the use of thresholds of ≤5 and ≤15 SNPs difference between isolates to categorize definite and probable transmission, respectively. Different SNP thresholds should be applied while a higher cutoff was required to define an MDR-TB outbreak. The utilization of SNP thresholds proves to be crucial for guiding public health interventions, eliminating the need for unnecessary public health actions, and potentially uncovering undisclosed TB transmissions.

Dataset Information

Microbial species delineation using whole genome sequences.

Publications

Microbial species delineation using whole genome sequences.

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