Dataset Information

Genomic-based taxonomic classification of the family Erythrobacteraceae.

ABSTRACT: The family Erythrobacteraceae, belonging to the order Sphingomonadales, class Alphaproteobacteria, is globally distributed in various environments. Currently, this family consist of seven genera: Altererythrobacter, Croceibacterium, Croceicoccus, Erythrobacter, Erythromicrobium, Porphyrobacter and Qipengyuania. As more species are identified, the taxonomic status of the family Erythrobacteraceae should be revised at the genomic level because of its polyphyletic nature evident from 16S rRNA gene sequence analysis. Phylogenomic reconstruction based on 288 single-copy orthologous clusters led to the identification of three separate clades. Pairwise comparisons of average nucleotide identity, average amino acid identity (AAI), percentage of conserved protein and evolutionary distance indicated that AAI and evolutionary distance had the highest correlation. Thresholds for genera boundaries were proposed as 70 % and 0.4 for AAI and evolutionary distance, respectively. Based on the phylo-genomic and genomic similarity analysis, the three clades were classified into 16 genera, including 11 novel ones, for which the names Alteraurantiacibacter, Altericroceibacterium, Alteriqipengyuania, Alteripontixanthobacter, Aurantiacibacter, Paraurantiacibacter, Parerythrobacter, Parapontixanthobacter, Pelagerythrobacter, Tsuneonella and Pontixanthobacter are proposed. We reclassified all species of Erythromicrobium and Porphyrobacter as species of Erythrobacter. This study is the first genomic-based study of the family Erythrobacteraceae, and will contribute to further insights into the evolution of this family.

SUBMITTER: Xu L

PROVIDER: S-EPMC7660246 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Genomic-based taxonomic classification of the family Erythrobacteraceae.

Xu Lin L Sun Cong C Fang Chen C Oren Aharon A Xu Xue-Wei XW

International journal of systematic and evolutionary microbiology 20200729 8

The family Erythrobacteraceae, belonging to the order Sphingomonadales, class Alphaproteobacteria, is globally distributed in various environments. Currently, this family consist of seven genera: Altererythrobacter, Croceibacterium, Croceicoccus, Erythrobacter, Erythromicrobium, Porphyrobacter and Qipengyuania. As more species are identified, the taxonomic status of the family Erythrobacteraceae should be revised at the ...[more]

PMID: 32726199

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Project description:BackgroundMetagenomics, or the sequencing and analysis of collective genomes (metagenomes) of microorganisms isolated from an environment, promises direct access to the "unculturable majority". This emerging field offers the potential to lay solid basis on our understanding of the entire living world. However, the taxonomic classification is an essential task in the analysis of metagenomics data sets that it is still far from being solved. We present a novel strategy to predict the taxonomic origin of environmental genomic fragments. The proposed classifier combines the idea of the k-nearest neighbor with strategies from kernel-based learning.ResultsOur novel strategy was extensively evaluated using the leave-one-out cross validation strategy on fragments of variable length (800 bp - 50 Kbp) from 373 completely sequenced genomes. TACOA is able to classify genomic fragments of length 800 bp and 1 Kbp with high accuracy until rank class. For longer fragments > or = 3 Kbp accurate predictions are made at even deeper taxonomic ranks (order and genus). Remarkably, TACOA also produces reliable results when the taxonomic origin of a fragment is not represented in the reference set, thus classifying such fragments to its known broader taxonomic class or simply as "unknown". We compared the classification accuracy of TACOA with the latest intrinsic classifier PhyloPythia using 63 recently published complete genomes. For fragments of length 800 bp and 1 Kbp the overall accuracy of TACOA is higher than that obtained by PhyloPythia at all taxonomic ranks. For all fragment lengths, both methods achieved comparable high specificity results up to rank class and low false negative rates are also obtained.ConclusionAn accurate multi-class taxonomic classifier was developed for environmental genomic fragments. TACOA can predict with high reliability the taxonomic origin of genomic fragments as short as 800 bp. The proposed method is transparent, fast, accurate and the reference set can be easily updated as newly sequenced genomes become available. Moreover, the method demonstrated to be competitive when compared to the most current classifier PhyloPythia and has the advantage that it can be locally installed and the reference set can be kept up-to-date.

Project description:The application of phylogenetic taxonomic procedures led to improvements in the classification of bacteria assigned to the phylum Actinobacteria but even so there remains a need to further clarify relationships within a taxon that encompasses organisms of agricultural, biotechnological, clinical, and ecological importance. Classification of the morphologically diverse bacteria belonging to this large phylum based on a limited number of features has proved to be difficult, not least when taxonomic decisions rested heavily on interpretation of poorly resolved 16S rRNA gene trees. Here, draft genome sequences of a large collection of actinobacterial type strains were used to infer phylogenetic trees from genome-scale data using principles drawn from phylogenetic systematics. The majority of taxa were found to be monophyletic but several orders, families, and genera, as well as many species and a few subspecies were shown to be in need of revision leading to proposals for the recognition of 2 orders, 10 families, and 17 genera, as well as the transfer of over 100 species to other genera. In addition, emended descriptions are given for many species mainly involving the addition of data on genome size and DNA G+C content, the former can be considered to be a valuable taxonomic marker in actinobacterial systematics. Many of the incongruities detected when the results of the present study were compared with existing classifications had been recognized from 16S rRNA gene trees though whole-genome phylogenies proved to be much better resolved. The few significant incongruities found between 16S/23S rRNA and whole genome trees underline the pitfalls inherent in phylogenies based upon single gene sequences. Similarly good congruence was found between the discontinuous distribution of phenotypic properties and taxa delineated in the phylogenetic trees though diverse non-monophyletic taxa appeared to be based on the use of plesiomorphic character states as diagnostic features.

Project description:BackgroundThe International Committee on Taxonomy of Viruses (ICTV) classifies viruses into families, genera and species and provides a regulated system for their nomenclature that is universally used in virus descriptions. Virus taxonomic assignments have traditionally been based upon virus phenotypic properties such as host range, virion morphology and replication mechanisms, particularly at family level. However, gene sequence comparisons provide a clearer guide to their evolutionary relationships and provide the only information that may guide the incorporation of viruses detected in environmental (metagenomic) studies that lack any phenotypic data.ResultsThe current study sought to determine whether the existing virus taxonomy could be reproduced by examination of genetic relationships through the extraction of protein-coding gene signatures and genome organisational features. We found large-scale consistency between genetic relationships and taxonomic assignments for viruses of all genome configurations and genome sizes. The analysis pipeline that we have called 'Genome Relationships Applied to Virus Taxonomy' (GRAViTy) was highly effective at reproducing the current assignments of viruses at family level as well as inter-family groupings into orders. Its ability to correctly differentiate assigned viruses from unassigned viruses, and classify them into the correct taxonomic group, was evaluated by threefold cross-validation technique. This predicted family membership of eukaryotic viruses with close to 100% accuracy and specificity potentially enabling the algorithm to predict assignments for the vast corpus of metagenomic sequences consistently with ICTV taxonomy rules. In an evaluation run of GRAViTy, over one half (460/921) of (near)-complete genome sequences from several large published metagenomic eukaryotic virus datasets were assigned to 127 novel family-level groupings. If corroborated by other analysis methods, these would potentially more than double the number of eukaryotic virus families in the ICTV taxonomy.ConclusionsA rapid and objective means to explore metagenomic viral diversity and make informed recommendations for their assignments at each taxonomic layer is essential. GRAViTy provides one means to make rule-based assignments at family and order levels in a manner that preserves the integrity and underlying organisational principles of the current ICTV taxonomy framework. Such methods are increasingly required as the vast virosphere is explored.

Dataset Information

Genomic-based taxonomic classification of the family Erythrobacteraceae.

Publications

Genomic-based taxonomic classification of the family <i>Erythrobacteraceae</i>.

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