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Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model
Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857382/ https://www.ncbi.nlm.nih.gov/pubmed/29424683 http://dx.doi.org/10.1099/mgen.0.000157 |
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author | Omony, Jimmy de Jong, Anne Krawczyk, Antonina O. Eijlander, Robyn T. Kuipers, Oscar P. |
author_facet | Omony, Jimmy de Jong, Anne Krawczyk, Antonina O. Eijlander, Robyn T. Kuipers, Oscar P. |
author_sort | Omony, Jimmy |
collection | PubMed |
description | Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes. |
format | Online Article Text |
id | pubmed-5857382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Microbiology Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-58573822018-04-05 Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model Omony, Jimmy de Jong, Anne Krawczyk, Antonina O. Eijlander, Robyn T. Kuipers, Oscar P. Microb Genom Research Article Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes. Microbiology Society 2018-02-09 /pmc/articles/PMC5857382/ /pubmed/29424683 http://dx.doi.org/10.1099/mgen.0.000157 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Omony, Jimmy de Jong, Anne Krawczyk, Antonina O. Eijlander, Robyn T. Kuipers, Oscar P. Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model |
title | Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model |
title_full | Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model |
title_fullStr | Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model |
title_full_unstemmed | Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model |
title_short | Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model |
title_sort | dynamic sporulation gene co-expression networks for bacillus subtilis 168 and the food-borne isolate bacillus amyloliquefaciens: a transcriptomic model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857382/ https://www.ncbi.nlm.nih.gov/pubmed/29424683 http://dx.doi.org/10.1099/mgen.0.000157 |
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