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Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data
The repertoire of 304 DNA-binding transcription factors (TFs) in Escherichia coli K-12 has been described recently, with 196 TFs experimentally characterized and 108 proteins predicted by sequence comparisons. Based on 303 expression profile patterns retrieved from the Colombos database 12 clusters...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6055005/ https://www.ncbi.nlm.nih.gov/pubmed/30050664 http://dx.doi.org/10.1016/j.csbj.2018.03.003 |
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author | Flores-Bautista, Emanuel Cronick, Carenne Ludeña Fersaca, Anny Rodriguez Martinez-Nuñez, Mario Alberto Perez-Rueda, Ernesto |
author_facet | Flores-Bautista, Emanuel Cronick, Carenne Ludeña Fersaca, Anny Rodriguez Martinez-Nuñez, Mario Alberto Perez-Rueda, Ernesto |
author_sort | Flores-Bautista, Emanuel |
collection | PubMed |
description | The repertoire of 304 DNA-binding transcription factors (TFs) in Escherichia coli K-12 has been described recently, with 196 TFs experimentally characterized and 108 proteins predicted by sequence comparisons. Based on 303 expression profile patterns retrieved from the Colombos database 12 clusters were identified, including hypothetical and experimentally characterized TFs, using a spectral clustering algorithm based on a 3NN graph built using 14 principal components that represent 65% of the variance of the expression data. In a posterior step, clusters were characterized in terms of their associated overrepresented functions, based on KEGG, Supfam annotations and Pfam assignments among other functional categories using an enrichment test, reinforcing the notion that the identified clusters are functionally similar among them. Based on these data, the we identified 12 clusters in which hypothetical and known TFs share similar regulatory and physiological functions, such as module associations of toxin-antitoxin (TA) systems with DNA repair mechanisms, amino acid biosynthesis, and carbon metabolism/transport, among others. This analysis has increased our knowledge about gene regulation in E. coli K-12 and can be further expanded to other organisms. |
format | Online Article Text |
id | pubmed-6055005 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-60550052018-07-26 Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data Flores-Bautista, Emanuel Cronick, Carenne Ludeña Fersaca, Anny Rodriguez Martinez-Nuñez, Mario Alberto Perez-Rueda, Ernesto Comput Struct Biotechnol J Research Article The repertoire of 304 DNA-binding transcription factors (TFs) in Escherichia coli K-12 has been described recently, with 196 TFs experimentally characterized and 108 proteins predicted by sequence comparisons. Based on 303 expression profile patterns retrieved from the Colombos database 12 clusters were identified, including hypothetical and experimentally characterized TFs, using a spectral clustering algorithm based on a 3NN graph built using 14 principal components that represent 65% of the variance of the expression data. In a posterior step, clusters were characterized in terms of their associated overrepresented functions, based on KEGG, Supfam annotations and Pfam assignments among other functional categories using an enrichment test, reinforcing the notion that the identified clusters are functionally similar among them. Based on these data, the we identified 12 clusters in which hypothetical and known TFs share similar regulatory and physiological functions, such as module associations of toxin-antitoxin (TA) systems with DNA repair mechanisms, amino acid biosynthesis, and carbon metabolism/transport, among others. This analysis has increased our knowledge about gene regulation in E. coli K-12 and can be further expanded to other organisms. Research Network of Computational and Structural Biotechnology 2018-03-27 /pmc/articles/PMC6055005/ /pubmed/30050664 http://dx.doi.org/10.1016/j.csbj.2018.03.003 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Flores-Bautista, Emanuel Cronick, Carenne Ludeña Fersaca, Anny Rodriguez Martinez-Nuñez, Mario Alberto Perez-Rueda, Ernesto Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data |
title | Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data |
title_full | Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data |
title_fullStr | Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data |
title_full_unstemmed | Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data |
title_short | Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data |
title_sort | functional prediction of hypothetical transcription factors of escherichia coli k-12 based on expression data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6055005/ https://www.ncbi.nlm.nih.gov/pubmed/30050664 http://dx.doi.org/10.1016/j.csbj.2018.03.003 |
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