Cargando…
Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea
Saccharopolyspora erythraea produces a large number of secondary metabolites with biological activities, including erythromycin. Elucidation of the mechanisms through which the production of these secondary metabolites is regulated may help to identify new strategies for improved biosynthesis of ery...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827479/ https://www.ncbi.nlm.nih.gov/pubmed/24236194 http://dx.doi.org/10.1371/journal.pone.0080676 |
_version_ | 1782478248990474240 |
---|---|
author | Liu, Wei-Bing Shi, Yang Yao, Li-Li Zhou, Ying Ye, Bang-Ce |
author_facet | Liu, Wei-Bing Shi, Yang Yao, Li-Li Zhou, Ying Ye, Bang-Ce |
author_sort | Liu, Wei-Bing |
collection | PubMed |
description | Saccharopolyspora erythraea produces a large number of secondary metabolites with biological activities, including erythromycin. Elucidation of the mechanisms through which the production of these secondary metabolites is regulated may help to identify new strategies for improved biosynthesis of erythromycin. In this paper, we describe the systematic prediction and analysis of small non-coding RNAs (sRNAs) in S. erythraea, with the aim to elucidate sRNA-mediated regulation of secondary metabolite biosynthesis. In silico and deep-sequencing technologies were applied to predict sRNAs in S. erythraea. Six hundred and forty-seven potential sRNA loci were identified, of which 382 cis-encoded antisense RNA are complementary to protein-coding regions and 265 predicted transcripts are located in intergenic regions. Six candidate sRNAs (sernc292, sernc293, sernc350, sernc351, sernc361, and sernc389) belong to four gene clusters (tpc3, pke, pks6, and nrps5) that are involved in secondary metabolite biosynthesis. Deep-sequencing data showed that the expression of all sRNAs in the strain HL3168 E3 (E3) was higher than that in NRRL23338 (M), except for sernc292 and sernc361 expression. The relative expression of six sRNAs in strain M and E3 were validated by qRT-PCR at three different time points (24, 48, and 72 h). The results showed that, at each time point, the transcription levels of sernc293, sernc350, sernc351, and sernc389 were higher in E3 than in M, with the largest difference observed at 72 h, whereas no signals for sernc292 and sernc361 were detected. sernc293, sernc350, sernc351, and sernc389 probably regulate iron transport, terpene metabolism, geosmin synthesis, and polyketide biosynthesis, respectively. The major significance of this study is the successful prediction and identification of sRNAs in genomic regions close to the secondary metabolism-related genes in S. erythraea. A better understanding of the sRNA-target interaction would help to elucidate the complete range of functions of sRNAs in S. erythraea, including sRNA-mediated regulation of erythromycin biosynthesis. |
format | Online Article Text |
id | pubmed-3827479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38274792013-11-14 Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea Liu, Wei-Bing Shi, Yang Yao, Li-Li Zhou, Ying Ye, Bang-Ce PLoS One Research Article Saccharopolyspora erythraea produces a large number of secondary metabolites with biological activities, including erythromycin. Elucidation of the mechanisms through which the production of these secondary metabolites is regulated may help to identify new strategies for improved biosynthesis of erythromycin. In this paper, we describe the systematic prediction and analysis of small non-coding RNAs (sRNAs) in S. erythraea, with the aim to elucidate sRNA-mediated regulation of secondary metabolite biosynthesis. In silico and deep-sequencing technologies were applied to predict sRNAs in S. erythraea. Six hundred and forty-seven potential sRNA loci were identified, of which 382 cis-encoded antisense RNA are complementary to protein-coding regions and 265 predicted transcripts are located in intergenic regions. Six candidate sRNAs (sernc292, sernc293, sernc350, sernc351, sernc361, and sernc389) belong to four gene clusters (tpc3, pke, pks6, and nrps5) that are involved in secondary metabolite biosynthesis. Deep-sequencing data showed that the expression of all sRNAs in the strain HL3168 E3 (E3) was higher than that in NRRL23338 (M), except for sernc292 and sernc361 expression. The relative expression of six sRNAs in strain M and E3 were validated by qRT-PCR at three different time points (24, 48, and 72 h). The results showed that, at each time point, the transcription levels of sernc293, sernc350, sernc351, and sernc389 were higher in E3 than in M, with the largest difference observed at 72 h, whereas no signals for sernc292 and sernc361 were detected. sernc293, sernc350, sernc351, and sernc389 probably regulate iron transport, terpene metabolism, geosmin synthesis, and polyketide biosynthesis, respectively. The major significance of this study is the successful prediction and identification of sRNAs in genomic regions close to the secondary metabolism-related genes in S. erythraea. A better understanding of the sRNA-target interaction would help to elucidate the complete range of functions of sRNAs in S. erythraea, including sRNA-mediated regulation of erythromycin biosynthesis. Public Library of Science 2013-11-13 /pmc/articles/PMC3827479/ /pubmed/24236194 http://dx.doi.org/10.1371/journal.pone.0080676 Text en © 2013 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Liu, Wei-Bing Shi, Yang Yao, Li-Li Zhou, Ying Ye, Bang-Ce Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea |
title | Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea
|
title_full | Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea
|
title_fullStr | Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea
|
title_full_unstemmed | Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea
|
title_short | Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea
|
title_sort | prediction and characterization of small non-coding rnas related to secondary metabolites in saccharopolyspora erythraea |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827479/ https://www.ncbi.nlm.nih.gov/pubmed/24236194 http://dx.doi.org/10.1371/journal.pone.0080676 |
work_keys_str_mv | AT liuweibing predictionandcharacterizationofsmallnoncodingrnasrelatedtosecondarymetabolitesinsaccharopolysporaerythraea AT shiyang predictionandcharacterizationofsmallnoncodingrnasrelatedtosecondarymetabolitesinsaccharopolysporaerythraea AT yaolili predictionandcharacterizationofsmallnoncodingrnasrelatedtosecondarymetabolitesinsaccharopolysporaerythraea AT zhouying predictionandcharacterizationofsmallnoncodingrnasrelatedtosecondarymetabolitesinsaccharopolysporaerythraea AT yebangce predictionandcharacterizationofsmallnoncodingrnasrelatedtosecondarymetabolitesinsaccharopolysporaerythraea |