Cargando…

GENPPI: standalone software for creating protein interaction networks from genomes

BACKGROUND: Bacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourho...

Descripción completa

Detalles Bibliográficos
Autores principales: Anjos, William F., Lanes, Gabriel C., Azevedo, Vasco A., Santos, Anderson R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8680239/
https://www.ncbi.nlm.nih.gov/pubmed/34915867
http://dx.doi.org/10.1186/s12859-021-04501-0
_version_ 1784616703161794560
author Anjos, William F.
Lanes, Gabriel C.
Azevedo, Vasco A.
Santos, Anderson R.
author_facet Anjos, William F.
Lanes, Gabriel C.
Azevedo, Vasco A.
Santos, Anderson R.
author_sort Anjos, William F.
collection PubMed
description BACKGROUND: Bacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results. RESULTS: We developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 min on a conventional computer. Moreover, the interaction networks that our software creates reflect correct evolutionary relationships between species, which we confirmed with average nucleotide identity analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user’s choice regarding which set of genomes they are going to study. CONCLUSIONS: GENPPI can help fill the gap concerning the considerable number of novel genomes assembled monthly and our ability to process interaction networks considering the noncore genes for all completed genome versions. With GENPPI, a user dictates how many and how evolutionarily correlated the genomes answer a scientific query.
format Online
Article
Text
id pubmed-8680239
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-86802392021-12-20 GENPPI: standalone software for creating protein interaction networks from genomes Anjos, William F. Lanes, Gabriel C. Azevedo, Vasco A. Santos, Anderson R. BMC Bioinformatics Software BACKGROUND: Bacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results. RESULTS: We developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 min on a conventional computer. Moreover, the interaction networks that our software creates reflect correct evolutionary relationships between species, which we confirmed with average nucleotide identity analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user’s choice regarding which set of genomes they are going to study. CONCLUSIONS: GENPPI can help fill the gap concerning the considerable number of novel genomes assembled monthly and our ability to process interaction networks considering the noncore genes for all completed genome versions. With GENPPI, a user dictates how many and how evolutionarily correlated the genomes answer a scientific query. BioMed Central 2021-12-16 /pmc/articles/PMC8680239/ /pubmed/34915867 http://dx.doi.org/10.1186/s12859-021-04501-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Anjos, William F.
Lanes, Gabriel C.
Azevedo, Vasco A.
Santos, Anderson R.
GENPPI: standalone software for creating protein interaction networks from genomes
title GENPPI: standalone software for creating protein interaction networks from genomes
title_full GENPPI: standalone software for creating protein interaction networks from genomes
title_fullStr GENPPI: standalone software for creating protein interaction networks from genomes
title_full_unstemmed GENPPI: standalone software for creating protein interaction networks from genomes
title_short GENPPI: standalone software for creating protein interaction networks from genomes
title_sort genppi: standalone software for creating protein interaction networks from genomes
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8680239/
https://www.ncbi.nlm.nih.gov/pubmed/34915867
http://dx.doi.org/10.1186/s12859-021-04501-0
work_keys_str_mv AT anjoswilliamf genppistandalonesoftwareforcreatingproteininteractionnetworksfromgenomes
AT lanesgabrielc genppistandalonesoftwareforcreatingproteininteractionnetworksfromgenomes
AT azevedovascoa genppistandalonesoftwareforcreatingproteininteractionnetworksfromgenomes
AT santosandersonr genppistandalonesoftwareforcreatingproteininteractionnetworksfromgenomes