Published January 8, 2025 | Version 1.0.0
Dataset Open

EsMeCaTa precomputed database

  • 1. Univ. Grenoble Alpes, Inria, 38000 Grenoble, France
  • 2. Université Grenoble Alpes, CNRS, LIPhy, Grenoble, France
  • 3. Gricad, Inria, CNRS, Université Grenoble Alpes, Grenoble INP, Grenoble, France

Contributors

  • 1. Univ. Grenoble Alpes, Inria, 38000 Grenoble, France
  • 2. Université Grenoble Alpes, CNRS, LIPhy, Grenoble, France

Description

EsMeCaTa precomputed database

Presentation

EsMeCaTa is a software application to infer consensus proteomes and metabolic functions from taxonomic affiliations. EsMeCaTa uses ete3 and the NCBI Taxonomy database to parse the taxonomic affiliations and query the UniProt Proteomes database to find associated proteomes. These proteomes are clustered using MMseqs2 to create consensus proteomes, which are then annotated with eggNOG-mapper. EsMeCaTa can be time-consuming to run and requires a large number of resources to perform its various steps. A precomputed database has been created to facilitate its use.

The EsMeCaTa database has been compiled by taking from UniProt all taxa having at least five proteomes and being of the taxonomic rank of "species", "genus", "family", "order", "class", or "phylum".  EsMeCaTa was applied to these taxa leading to the creation of the database as a zip file.

For each taxonomic rank, you can find in the following table the number of taxa that were used by EsMeCaTa to make the predictions:

Taxonomic rank Number of taxa
Species 467
Genus 964
Family 497
Order 277
Class 132
Phylum 89

Each taxon contained in the database is associated with two files:

  • a protein file in the FASTA format containing the consensus sequences predicted by EsMeCaTa for this taxon.
  • an annotation file resulting from a run of eggNOG-mapper on the consensus sequences.

Usage

The precomputed database can be used by EsMeCaTa to make predictions on a tabulated file containing taxonomic affiliations. Two inputs are required:

  • this database.
  • a taxonomic affiliations file in the tsv format looking like this:
observation_name taxonomic_affiliation
Cluster_1 Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Spirochaetaceae;Sphaerochaeta;unknown species
Cluster_2 Bacteria;Chloroflexi;Anaerolineae;Anaerolineales;Anaerolineaceae;ADurb.Bin120;unknown species
Cluster_3 Bacteria;Cloacimonetes;Cloacimonadia;Cloacimonadales;Cloacimonadaceae;Candidatus Cloacimonas;unknown species

Furthermore, it is recommended to use the same NCBI Taxonomy database as the one used to create the EsMeCaTa database. This version of the NCBI Taxonomy database is also included in this archive ('taxdmp_2024-10-01.tar.gz'). To use this version of the database, EsMeCaTa relies on the ete3 package to import it with the following command:

python3 -c "from ete3 import NCBITaxa; ncbi = NCBITaxa(); ncbi.update_taxonomy_database('taxdmp_2024-10-01.tar.gz')"

After these preparatory steps, EsMeCaTa can be called with the following command line:

esmecata precomputed -i taxonomic_affiliations.tsv -d esmecata_database.zip -o output_folder

This requires at least EsMaCaTa version 0.5.0. For the information on the output of EsMeCaTa, you can look at the GitHub readme.

Dendencies used to create the database

Dependencies Version
UniProt 2024_05
Date October 2024
NCBI Taxonomy database 2024-10-01
esmecata 0.6.0
mmseqs2 15.6f452
eggnog database 5.0.2
eggnog-mapper 2.1.12
ete3 3.1.3
pandas 2.2.2
biopython 1.84
requests 2.31.0
SPARQLWrapper 2.0.0

Acknowledgements

Most of the computations presented in this work were performed using the GRICAD infrastructure (https://gricad.univ-grenoble-alpes.fr), which is supported by the Grenoble research community.

The work was funded by the ANR project HyLife (ANR-23-CETP-0002) associated with the CETP project HyLife.

Files

esmecata_database.zip

Files (4.1 GB)

Name Size Download all
md5:a7adcde6fd96fea544e6c8e3314e1fe0
4.0 GB Preview Download
md5:3119b4b0706ef472e5cdcc878c387494
67.2 MB Download

Additional details

Related works

Is documented by
Software: https://github.com/AuReMe/esmecata (URL)

Funding

Agence Nationale de la Recherche
HyLife – Microbial risks associated to hydrogen underground storage in Europe ANR-23-CETP-0002

Software

Repository URL
https://github.com/AuReMe/esmecata
Programming language
Python
Development Status
Active