Microbial species delineation using whole genome sequences

By Neha J. Varghese, Supratim Mukherjee, Natalia N. Ivanova, Konstantinos T. Konstantinidis, Kostas Mavrommatis, Nikos Kyrpides, Amrita Pati. Nucleic Acids Research, 2015

666 citations recorded by the source corpus.

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.

Subfields: Food Science, Molecular Biology, Periodontics

View Paper: https://www.semanticscholar.org/paper/a822e1111cebf5dd45108ea9a18c3c2ab2b27cc1

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Citations in the corpus

Assembly of seed-associated microbial communities within and across successive plant generations (2017, background): “…Institute, Michigan State University, East Lansing, MI 48824, USA drought tolerance (Lau and Lennon 2012; Rolli et al. 2015), flowering time (Wagner et al. 2014; PankeBuisse et al. 2015; Dombrowski et al. 2017) and disease resistance (Busby et al. 2016; Ritpitakphong et al. 2016; Mendes…”
Using average nucleotide identity to improve taxonomic assignments in prokaryotic genomes at the NCBI (2018, positive): “It also represents a straightforward measure that has proven to have practical scalability for large data sets [12].”
dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication (2017, methodology): “…combines checkM for completeness-based genome filtering (Parks et al., 2015), Mash (Ondov et al., 2016) for fast grouping of similar genomes, gANI (Varghese et al., 2015) or ANIm (Richter and Rosselló-Móra, 2009) for accurate genomic comparisons, and Scipy (Jones et al., 2001) for hierarchical…”
An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography (2016, background): “…species groups to avoid inconsistent, erroneous, and incomplete annotations that afflict some microbial taxonomies (Mende et al. 2013) and to expand and improve upon previous efforts to systematically delineate bacterial species (Mende et al. 2013; Schloissnig et al. 2013; Varghese et al. 2015).”
IMG/M: integrated genome and metagenome comparative data analysis system (2016, methodology): “ANI is a measure of nucleotide level similarity between the coding regions of two genomes, which can be used to infer species relationship and divergence (22).”
The IMG/M data management and analysis system v.6.0: new tools and advanced capabilities (2020, methodology): “Other computations available for genome sequences include Average Nucleotide Identity (ANI) (28) distance matrix computations, and biosynthetic clusters (29,30), as previously described.”
IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes (2018, methodology): “As part of this development, we have recently implemented a Microbial Species Identifier (MiSI) system, which is the first IMG microservice providing ANI data (22) to IMG users through API access.”