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An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851
BACKGROUND: Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Instituto Oswaldo Cruz, Ministério da Saúde
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565603/ https://www.ncbi.nlm.nih.gov/pubmed/36259790 http://dx.doi.org/10.1590/0074-02760220111 |
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author | Chagas, Márcia da Silva Medeiros, Fernando dos Santos, Marcelo Trindade de Menezes, Marcio Argollo Carvalho-Assef, Ana Paula D’Alincourt da Silva, Fabricio Alves Barbosa |
author_facet | Chagas, Márcia da Silva Medeiros, Fernando dos Santos, Marcelo Trindade de Menezes, Marcio Argollo Carvalho-Assef, Ana Paula D’Alincourt da Silva, Fabricio Alves Barbosa |
author_sort | Chagas, Márcia da Silva |
collection | PubMed |
description | BACKGROUND: Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets. OBJECTIVES: In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties. METHODS: We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process. FINDINGS: Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa. MAIN CONCLUSIONS: Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge. |
format | Online Article Text |
id | pubmed-9565603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Instituto Oswaldo Cruz, Ministério da Saúde |
record_format | MEDLINE/PubMed |
spelling | pubmed-95656032022-10-17 An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 Chagas, Márcia da Silva Medeiros, Fernando dos Santos, Marcelo Trindade de Menezes, Marcio Argollo Carvalho-Assef, Ana Paula D’Alincourt da Silva, Fabricio Alves Barbosa Mem Inst Oswaldo Cruz Research Article BACKGROUND: Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets. OBJECTIVES: In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties. METHODS: We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process. FINDINGS: Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa. MAIN CONCLUSIONS: Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge. Instituto Oswaldo Cruz, Ministério da Saúde 2022-10-14 /pmc/articles/PMC9565603/ /pubmed/36259790 http://dx.doi.org/10.1590/0074-02760220111 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License |
spellingShingle | Research Article Chagas, Márcia da Silva Medeiros, Fernando dos Santos, Marcelo Trindade de Menezes, Marcio Argollo Carvalho-Assef, Ana Paula D’Alincourt da Silva, Fabricio Alves Barbosa An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 |
title | An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 |
title_full | An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 |
title_fullStr | An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 |
title_full_unstemmed | An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 |
title_short | An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851 |
title_sort | updated gene regulatory network reconstruction of multidrug-resistant pseudomonas aeruginosa ccbh4851 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565603/ https://www.ncbi.nlm.nih.gov/pubmed/36259790 http://dx.doi.org/10.1590/0074-02760220111 |
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