LINgroups as a Robust Principled Approach to Compare and Integrate Multiple Bacterial Taxonomies

As a central organizing principle of biology, bacteria and archaea are classified into a hierarchical structure across taxonomic ranks from kingdom to subspecies. Traditionally, this organization was based on observable characteristics of form and chemistry but recently, bacterial taxonomy has been robustly quantified using comparisons of sequenced genomes, as exemplified in the Genome Taxonomy Database (GTDB). Such genome-based taxonomies resolve genomes down to genera and species and are useful in many contexts yet lack the flexibility and resolution of a fine-grained approach. The Life Identification Number (LIN) approach is a common, quantitative framework to tie existing (and future) bacterial taxonomies together, increase the resolution of genome-based discrimination of taxa, and extend taxonomic identification below the species level in a principled way. Utilizing LINgroup as an organizational concept helps resolve some of the confusion and unforeseen negative effects resulting from nomenclature changes of microorganisms that are closely related by overall genomic similarity (often due to genome-based reclassification). Our experimental results demonstrate the value of LINs and LINgroups in mapping between taxonomies, translating between different nomenclatures, and integrating them into a single taxonomic framework. They also reveal the robustness of LIN assignment to hyper-parameter changes when considering within-species taxonomic groups.

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Publication Details

Journal
IEEE/ACM Transactions on Computational Biology and Bioinformatics
Published
2024-10-07
DOI
https://doi.org/10.1109/tcbb.2024.3475917
Citations
3
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.70

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article

LINgroups as a Robust Principled Approach to Compare and Integrate Multiple Bacterial Taxonomies

Parul Sharma, C. Titus Brown, N. Tessa Pierce‐Ward, Reza Mazloom et al.
3 citations
IEEE/ACM Transactions on Computational Biology and Bioinformatics
Genomics and Phylogenetic Studies
0.70
article

LINgroups as a Robust Principled Approach to Compare and Integrate Multiple Bacterial Taxonomies

Parul Sharma, C. Titus Brown, N. Tessa Pierce‐Ward, Reza Mazloom, Leighton Pritchard, Lenwood S. Heath, Boris Alexander Vinatzer
article en
3 citations

Abstract

As a central organizing principle of biology, bacteria and archaea are classified into a hierarchical structure across taxonomic ranks from kingdom to subspecies. Traditionally, this organization was based on observable characteristics of form and chemistry but recently, bacterial taxonomy has been robustly quantified using comparisons of sequenced genomes, as exemplified in the Genome Taxonomy Database (GTDB). Such genome-based taxonomies resolve genomes down to genera and species and are useful in many contexts yet lack the flexibility and resolution of a fine-grained approach. The Life Identification Number (LIN) approach is a common, quantitative framework to tie existing (and future) bacterial taxonomies together, increase the resolution of genome-based discrimination of taxa, and extend taxonomic identification below the species level in a principled way. Utilizing LINgroup as an organizational concept helps resolve some of the confusion and unforeseen negative effects resulting from nomenclature changes of microorganisms that are closely related by overall genomic similarity (often due to genome-based reclassification). Our experimental results demonstrate the value of LINs and LINgroups in mapping between taxonomies, translating between different nomenclatures, and integrating them into a single taxonomic framework. They also reveal the robustness of LIN assignment to hyper-parameter changes when considering within-species taxonomic groups.

IEEE/ACM Transactions on Computational Biology and BioinformaticsVol. 21(6)
University of Strathclyde (GB), University of California, Davis (US), Virginia Tech (US)
Biotechnology and Biological Sciences Research Council
Zero hunger
Openalex Percentile: Top 29%
Genomics and Phylogenetic Studies
0.70
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