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Improving Virus Taxonomy by Recontextualizing Sequence-Based Classification with Biologically Relevant Data: the Case of the Alphacoronavirus 1 Species.

ABSTRACT: The difficulties related to virus taxonomy have been amplified by recent advances in next-generation sequencing and metagenomics, prompting the field to revisit the question of what constitutes a useful viral classification. Here, taking a challenging classification found in coronaviruses, we argue that consideration of biological properties in addition to sequence-based demarcations is critical for generating useful taxonomy that recapitulates complex evolutionary histories. Within the Alphacoronavirus genus, the Alphacoronavirus 1 species encompasses several biologically distinct viruses. We carried out functionally based phylogenetic analysis, centered on the spike gene, which encodes the main surface antigen and primary driver of tropism and pathogenesis. Within the Alphacoronavirus 1 species, we identify clade A (encompassing serotype I feline coronavirus [FCoV] and canine coronavirus [CCoV]) and clade B (grouping serotype II FCoV and CCoV and transmissible gastroenteritis virus [TGEV]-like viruses). We propose this clade designation, along with the newly proposed Alphacoronavirus 2 species, as an improved way to classify the Alphacoronavirus genus. IMPORTANCE Our work focuses on improving the classification of the Alphacoronavirus genus. The Alphacoronavirus 1 species groups viruses of veterinary importance that infect distinct mammalian hosts and includes canine and feline coronaviruses and transmissible gastroenteritis virus. It is the prototype species of the Alphacoronavirus genus; however, it encompasses biologically distinct viruses. To better characterize this prototypical species, we performed phylogenetic analyses based on the sequences of the spike protein, one of the main determinants of tropism and pathogenesis, and reveal the existence of two subgroups or clades that fit with previously established serotype demarcations. We propose a new clade designation to better classify Alphacoronavirus 1 members.

SUBMITTER: Whittaker GR

PROVIDER: S-EPMC5750389 | biostudies-literature | 2018 Jan-Feb

REPOSITORIES: biostudies-literature

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Improving Virus Taxonomy by Recontextualizing Sequence-Based Classification with Biologically Relevant Data: the Case of the <i>Alphacoronavirus 1</i> Species.

Whittaker Gary R GR André Nicole M NM Millet Jean Kaoru JK

mSphere 20180103 1

The difficulties related to virus taxonomy have been amplified by recent advances in next-generation sequencing and metagenomics, prompting the field to revisit the question of what constitutes a useful viral classification. Here, taking a challenging classification found in coronaviruses, we argue that consideration of biological properties in addition to sequence-based demarcations is critical for generating useful taxonomy that recapitulates complex evolutionary histories. Within the <i>Alpha ...[more]

PMID: 29299531

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Project description:The cosmopolitan subfamily Acidocerinae (Coleoptera: Hydrophilidae) is one of the largest and most taxonomically challenging lineages of water scavenger beetles. Recent phylogenetic studies have substantially advanced our understanding of acidocerine relationships but also illuminated the twin challenges of poorly delineated generic concepts and a classification broadly incompatible with the phylogeny. Here, these two challenges are addressed by providing a comprehensive synthesis and taxonomic tools for the Acidocerinae, including (1) a brief history and the current state of acidocerine classification, (2) a review of acidocerine ecology and collection methods, (3) the current knowledge of larval and fossil acidocerines, (4) a morphological primer on characters of taxonomic and systematic importance within the lineage, (5) a key to the world genera of Acidocerinae, (6) diagnoses, habitus, and aedeagal images, distribution maps, and summary of knowledge for each of the 23 extant genera in the subfamily, and (7) a complete annotated taxonomic catalog including the published distributions, synonyms, and references for all described 541 acidocerine species recognized as of 1 April 2021. The following nomenclatural acts are proposed to bring the phylogeny and classification into alignment: Colossochares gen. nov. is established to accommodate two African species previously described as Helochares (s. str.); Novochares gen. nov. is newly established to accommodate 15 Neotropical species previously included in Helochares (s. str.); the remaining Helochares subgenera Helocharimorphus Kuwert syn. nov. and Hydrobaticus MacLeay syn. nov. are synonymized with Helochares Mulsant. Peltochares Régimbart sensu nov. is redefined to include eight Old World species previously included in Helochares (s. str.). A lectotype is designated for Peltochares conspicuus Régimbart, the type species of the genus. The taxonomic and morphological circumscription of Helochares sensu nov. is narrowed and redefined.

Project description:BackgroundThe use of 3-D similarity techniques in the analysis of biological data and virtual screening is pervasive, but what is a biologically meaningful 3-D similarity value? Can one find statistically significant separation between "active/active" and "active/inactive" spaces? These questions are explored using 734,486 biologically tested chemical structures, 1,389 biological assay data sets, and six different 3-D similarity types utilized by PubChem analysis tools.ResultsThe similarity value distributions of 269.7 billion unique conformer pairs from 734,486 biologically tested compounds (all-against-all) from PubChem were utilized to help work towards an answer to the question: what is a biologically meaningful 3-D similarity score? The average and standard deviation for the six similarity measures STST-opt, CTST-opt, ComboTST-opt, STCT-opt, CTCT-opt, and ComboTCT-opt were 0.54 ± 0.10, 0.07 ± 0.05, 0.62 ± 0.13, 0.41 ± 0.11, 0.18 ± 0.06, and 0.59 ± 0.14, respectively. Considering that this random distribution of biologically tested compounds was constructed using a single theoretical conformer per compound (the "default" conformer provided by PubChem), further study may be necessary using multiple diverse conformers per compound; however, given the breadth of the compound set, the single conformer per compound results may still apply to the case of multi-conformer per compound 3-D similarity value distributions. As such, this work is a critical step, covering a very wide corpus of chemical structures and biological assays, creating a statistical framework to build upon.The second part of this study explored the question of whether it was possible to realize a statistically meaningful 3-D similarity value separation between reputed biological assay "inactives" and "actives". Using the terminology of noninactive-noninactive (NN) pairs and the noninactive-inactive (NI) pairs to represent comparison of the "active/active" and "active/inactive" spaces, respectively, each of the 1,389 biological assays was examined by their 3-D similarity score differences between the NN and NI pairs and analyzed across all assays and by assay category types. While a consistent trend of separation was observed, this result was not statistically unambiguous after considering the respective standard deviations. While not all "actives" in a biological assay are amenable to this type of analysis, e.g., due to different mechanisms of action or binding configurations, the ambiguous separation may also be due to employing a single conformer per compound in this study. With that said, there were a subset of biological assays where a clear separation between the NN and NI pairs found. In addition, use of combo Tanimoto (ComboT) alone, independent of superposition optimization type, appears to be the most efficient 3-D score type in identifying these cases.ConclusionThis study provides a statistical guideline for analyzing biological assay data in terms of 3-D similarity and PubChem structure-activity analysis tools. When using a single conformer per compound, a relatively small number of assays appear to be able to separate "active/active" space from "active/inactive" space.

Dataset Information

Improving Virus Taxonomy by Recontextualizing Sequence-Based Classification with Biologically Relevant Data: the Case of the Alphacoronavirus 1 Species.

Publications

Improving Virus Taxonomy by Recontextualizing Sequence-Based Classification with Biologically Relevant Data: the Case of the <i>Alphacoronavirus 1</i> Species.

Similar Datasets

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