Dataset Information

Mycoplasma pneumoniae transcriptome analysis

ABSTRACT: Two main articles have used this data. The small bacterium Mycoplasma pneumoniae with its annotated 689 protein-coding genes and 44 RNAs constitutes an ideal system for global and conditional transcription analysis in bacteria. We have combined spotted arrays under more than 120 conditions with several strand-specific, high resolution tiling arrays to obtain an unprecedented level of detail of bacterial gene expression. We have found 68 new non-annotated transcripts, of which the vast majority are potential regulatory RNAs, 53 of them in antisense to known genes. Integration of all data confirmed a dynamic and complex view of bacterial transcription: Under reference conditions in a rich medium, 138 polycistronic and 212 monocistronic transcripts could be identified, with almost half of the polycistronic operons showing a ‘staircase’-like expression pattern, i.e. the expression level within each gene is constant, but succeeding genes have lower expression. Furthermore, under different conditions, operons can divide into smaller transcriptional units, possibly by utilization of internal promoters resulting in many alternative transcripts. More complex bacteria show similar responses to external stresses, although M. pneumoniae lacks the respective transcription regulators, indicating the existence of yet uncharacterized common response mechanisms. This is supported by the concerted expression of genes, some of which with common upstream DNA motifs, form distinct operons under different conditions indicating additional factors regulating their expression. Frequent antisense transcripts, alternative transcripts and multiple regulators per gene thus cannot longer be seen as indicators of eukaryote-specific regulatory complexity. Keywords: stress response, time series

ORGANISM(S): Mycoplasmoides pneumoniae M129

PROVIDER: GSE14014 | GEO | 2009/12/11

SECONDARY ACCESSION(S): PRJNA114529

REPOSITORIES: GEO

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Project description:LlorénsRico2016 - Effects of cis-Encoded antisense RNAs (asRNAs) - Case1 Three putative effects of the asRNAs were considered in this study: in case 1 (this model) , the binding of the asRNA to the corresponding mRNA induces degradation of the duplex. In case 2, the binding of the asRNA to the mRNA induces degradation of the mRNA, but not of the asRNA. In case 3, the mRNA and the asRNA bind reversibly to form a stable duplex, preventing translation of the mRNA. In all the three cases, binding to the ribosome protects the mRNA from the effect of the asRNA. This model is described in the article: Bacterial antisense RNAs are mainly the product of transcriptional noise. Lloréns-Rico V, Cano J, Kamminga T, Gil R, Latorre A, Chen WH, Bork P, Glass JI, Serrano L, Lluch-Senar M. Sci Adv 2016 Mar; 2(3): e1501363 Abstract: cis-Encoded antisense RNAs (asRNAs) are widespread along bacterial transcriptomes. However, the role of most of these RNAs remains unknown, and there is an ongoing discussion as to what extent these transcripts are the result of transcriptional noise. We show, by comparative transcriptomics of 20 bacterial species and one chloroplast, that the number of asRNAs is exponentially dependent on the genomic AT content and that expression of asRNA at low levels exerts little impact in terms of energy consumption. A transcription model simulating mRNA and asRNA production indicates that the asRNA regulatory effect is only observed above certain expression thresholds, substantially higher than physiological transcript levels. These predictions were verified experimentally by overexpressing nine different asRNAs in Mycoplasma pneumoniae. Our results suggest that most of the antisense transcripts found in bacteria are the consequence of transcriptional noise, arising at spurious promoters throughout the genome. This model is hosted on BioModels Database and identified by: MODEL1511170000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:LlorénsRico2016 - Effects of cis-Encoded antisense RNAs (asRNAs) - Case3 Three putative effects of the asRNAs were considered in this study: in case 1, the binding of the asRNA to the corresponding mRNA induces degradation of the duplex. In case 2, the binding of the asRNA to the mRNA induces degradation of the mRNA, but not of the asRNA. In case 3 (this model), the mRNA and the asRNA bind reversibly to form a stable duplex, preventing translation of the mRNA. In all the three cases, binding to the ribosome protects the mRNA from the effect of the asRNA. This model is described in the article: Bacterial antisense RNAs are mainly the product of transcriptional noise. Lloréns-Rico V, Cano J, Kamminga T, Gil R, Latorre A, Chen WH, Bork P, Glass JI, Serrano L, Lluch-Senar M. Sci Adv 2016 Mar; 2(3): e1501363 Abstract: cis-Encoded antisense RNAs (asRNAs) are widespread along bacterial transcriptomes. However, the role of most of these RNAs remains unknown, and there is an ongoing discussion as to what extent these transcripts are the result of transcriptional noise. We show, by comparative transcriptomics of 20 bacterial species and one chloroplast, that the number of asRNAs is exponentially dependent on the genomic AT content and that expression of asRNA at low levels exerts little impact in terms of energy consumption. A transcription model simulating mRNA and asRNA production indicates that the asRNA regulatory effect is only observed above certain expression thresholds, substantially higher than physiological transcript levels. These predictions were verified experimentally by overexpressing nine different asRNAs in Mycoplasma pneumoniae. Our results suggest that most of the antisense transcripts found in bacteria are the consequence of transcriptional noise, arising at spurious promoters throughout the genome. This model is hosted on BioModels Database and identified by: MODEL1511170002. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Mycoplasma pneumoniae transcriptome analysis

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