Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability
Abstract Within individual cells, two molecular processes have been implicated as sources of noise in gene expression: (i) Poisson fluctuations in mRNA abundance arising from random birth and death of individual mRNA transcripts or (ii) promoter fluctuations arising from stochastic promoter transiti...
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| Format: | Article |
| Language: | English |
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Springer Nature
2012-08-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.1038/msb.2012.38 |
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| author | Abhyudai Singh Brandon S Razooky Roy D Dar Leor S Weinberger |
| author_facet | Abhyudai Singh Brandon S Razooky Roy D Dar Leor S Weinberger |
| author_sort | Abhyudai Singh |
| collection | DOAJ |
| description | Abstract Within individual cells, two molecular processes have been implicated as sources of noise in gene expression: (i) Poisson fluctuations in mRNA abundance arising from random birth and death of individual mRNA transcripts or (ii) promoter fluctuations arising from stochastic promoter transitions between different transcriptional states. Steady‐state measurements of variance in protein levels are insufficient to discriminate between these two mechanisms, and mRNA single‐molecule fluorescence in situ hybridization (smFISH) is challenging when cellular mRNA concentrations are high. Here, we present a perturbation method that discriminates mRNA birth/death fluctuations from promoter fluctuations by measuring transient changes in protein variance and that can operate in the regime of high molecular numbers. Conceptually, the method exploits the fact that transcriptional blockage results in more rapid increases in protein variability when mRNA birth/death fluctuations dominate over promoter fluctuations. We experimentally demonstrate the utility of this perturbation approach in the HIV‐1 model system. Our results support promoter fluctuations as the primary noise source in HIV‐1 expression. This study illustrates a relatively simple method that complements mRNA smFISH hybridization and can be used with existing GFP‐tagged libraries to include or exclude alternate sources of noise in gene expression. |
| format | Article |
| id | doaj-art-69b51e7ef3b143ffbe73dd77da4b86d8 |
| institution | Kabale University |
| issn | 1744-4292 |
| language | English |
| publishDate | 2012-08-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-69b51e7ef3b143ffbe73dd77da4b86d82025-08-20T04:02:44ZengSpringer NatureMolecular Systems Biology1744-42922012-08-01811910.1038/msb.2012.38Dynamics of protein noise can distinguish between alternate sources of gene‐expression variabilityAbhyudai Singh0Brandon S Razooky1Roy D Dar2Leor S Weinberger3Department of Chemistry and Biochemistry, University of CaliforniaDepartment of Chemistry and Biochemistry, University of CaliforniaThe Gladstone Institute of Virology and ImmunologyDepartment of Chemistry and Biochemistry, University of CaliforniaAbstract Within individual cells, two molecular processes have been implicated as sources of noise in gene expression: (i) Poisson fluctuations in mRNA abundance arising from random birth and death of individual mRNA transcripts or (ii) promoter fluctuations arising from stochastic promoter transitions between different transcriptional states. Steady‐state measurements of variance in protein levels are insufficient to discriminate between these two mechanisms, and mRNA single‐molecule fluorescence in situ hybridization (smFISH) is challenging when cellular mRNA concentrations are high. Here, we present a perturbation method that discriminates mRNA birth/death fluctuations from promoter fluctuations by measuring transient changes in protein variance and that can operate in the regime of high molecular numbers. Conceptually, the method exploits the fact that transcriptional blockage results in more rapid increases in protein variability when mRNA birth/death fluctuations dominate over promoter fluctuations. We experimentally demonstrate the utility of this perturbation approach in the HIV‐1 model system. Our results support promoter fluctuations as the primary noise source in HIV‐1 expression. This study illustrates a relatively simple method that complements mRNA smFISH hybridization and can be used with existing GFP‐tagged libraries to include or exclude alternate sources of noise in gene expression.https://doi.org/10.1038/msb.2012.38constitutive gene‐expressionHIV‐1 LTR promotermRNA single‐molecule FISHstochastic fluctuationstranscription |
| spellingShingle | Abhyudai Singh Brandon S Razooky Roy D Dar Leor S Weinberger Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability Molecular Systems Biology constitutive gene‐expression HIV‐1 LTR promoter mRNA single‐molecule FISH stochastic fluctuations transcription |
| title | Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability |
| title_full | Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability |
| title_fullStr | Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability |
| title_full_unstemmed | Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability |
| title_short | Dynamics of protein noise can distinguish between alternate sources of gene‐expression variability |
| title_sort | dynamics of protein noise can distinguish between alternate sources of gene expression variability |
| topic | constitutive gene‐expression HIV‐1 LTR promoter mRNA single‐molecule FISH stochastic fluctuations transcription |
| url | https://doi.org/10.1038/msb.2012.38 |
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