Dataset Information

Revisiting the Taxonomic Status of the Biomedically and Industrially Important Genus Amycolatopsis, Using a Phylogenomic Approach.

ABSTRACT: Strains belonging to the genus Amycolatopsis are well known for the production of a number of important antimicrobials and other bioactive molecules. In this study, we have sequenced the genomes of five Amycolatopsis strains including Amycolatopsis circi DSM 45561^T, Amycolatopsis palatopharyngis DSM 44832^T and Amycolatopsis thermalba NRRL B-24845^T. The genome sequences were analyzed with 52 other publically available Amycolatopsis genomes, representing 34 species, and 12 representatives from related genera including Saccharomonospora, Saccharopolyspora, Saccharothrix, Pseudonocardia and Thermobispora. Based on the core genome phylogeny, Amycolatopsis strains were subdivided into four major clades and several singletons. The genus Amycolatopsis is homogeneous with only three strains noted to group with other genera. Amycolatopsis halophila YIM93223^T is quite distinct from other Amycolatopsis strains, both phylogenetically and taxonomically, and belongs to a distinct genus. In addition, Amycolatopsis palatopharyngis DSM 44832^T and Amycolatopsis marina CGMCC4 3568^T grouped in a clade with Saccharomonospora strains and showed similar taxogenomic differences to this genus as well as other Amycolatopsis strains. The study found a number of strains, particularly those identified as Amycolatopsis orientalis, whose incorrect identification could be resolved by taxogenomic analyses. Similarly, some unclassified strains could be assigned with species designations. The genome sequences of some strains that were independently sequenced by different laboratories were almost identical (99-100% average nucleotide and amino acid identities) consistent with them being the same strain, and confirming the reproducibility and robustness of genomic data. These analyses further demonstrate that whole genome sequencing can reliably resolve intra- and, inter-generic structures and should be incorporated into prokaryotic systematics.

SUBMITTER: Sangal V

PROVIDER: S-EPMC6171478 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Colorectal cancer (CRC) is one of the most prevalent cancers in the world, especially in developed countries. In different studies, the association between CRC and dysbiosis of gut microbiome has been reported. However, most of these works focus on the taxonomic variation of the microbiome, which presents little, if any, functional insight about the reason behind and/or consequences of microbiome dysbiosis. In this study, we used a previously reported metagenome dataset which is obtained by sequencing 156 microbiome samples of healthy individuals as the control group (Co), as well as microbiome samples of patients with advanced colorectal adenoma (Ad) and colorectal carcinoma (Ca). Features of the microbiome samples have been analyzed at the level of species, as well as four functional levels, i.e., gene, KEGG orthology (KO) group, Enzyme Commission (EC) number, and reaction. It was shown that, at each of these levels, certain features exist which show significant changing trends during cancer progression. In the next step, a list of these features were extracted, which were shown to be able to predict the category of Co, Ad, and Ca samples with an accuracy of >85%. When only one group of features (species, gene, KO group, EC number, reaction) was used, KO-related features were found to be the most successful features for classifying the three categories of samples. Notably, species-related features showed the least success in sample classification. Furthermore, by applying an independent test set, we showed that these performance trends are not limited to our original dataset. We determined the most important classification features at each of the four functional levels. We propose that these features can be considered as biomarkers of CRC progression. Finally, we show that the intra-diversity of each sample at the levels of bacterial species and genes is much more than those of the KO groups, EC numbers, and reactions of that sample. Therefore, we conclude that the microbiome diversity at the species level, or gene level, is not necessarily associated with the diversity at the functional level, which again indicates the importance of KO-, EC-, and reaction-based features in metagenome analysis. The source code of proposed method is freely available from https://www.bioinformatics.org/mamed.

Dataset Information

Revisiting the Taxonomic Status of the Biomedically and Industrially Important Genus Amycolatopsis, Using a Phylogenomic Approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets