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Kallestad L, Blackshaw S, Khalil AM, Palczewski K. Tissue- and Species-Specific Patterns of RNA metabolism in Post-Mortem Mammalian Retina and Retinal Pigment Epithelium. Sci Rep 2019; 9:14821. [PMID: 31616038 PMCID: PMC6794289 DOI: 10.1038/s41598-019-51379-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 09/29/2019] [Indexed: 12/13/2022] Open
Abstract
Accurate analysis of gene expression in human tissues using RNA sequencing is dependent on the quality of source material. One major source of variation in mRNA quality is post-mortem time. While it is known that individual transcripts show differential post-mortem stability, few studies have directly and comprehensively analyzed mRNA stability following death, and in particular the extent to which tissue- and species-specific factors influence post-mortem mRNA stability are poorly understood. This knowledge is particularly important for ocular tissues studies, where tissues obtained post-mortem are frequently used for research or therapeutic applications. To directly investigate this question, we profiled mRNA levels in both neuroretina and retinal pigment epithelium (RPE) from mouse and baboon over a series of post-mortem intervals. We found substantial changes in gene expression as early as 15 minutes in the mouse and as early as three hours in the baboon eye tissues. Importantly, our findings demonstrate both tissue- and species- specific patterns of RNA metabolism, by identifying a set of genes that are either rapidly degraded or very stable in both species and/or tissues. Taken together, the data from this study lay the foundation for understanding RNA regulation post-mortem and provide novel insights into RNA metabolism in the tissues of the mammalian eye.
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Affiliation(s)
- Les Kallestad
- Gavin Herbert Eye Institute and the Department of Ophthalmology, University of California-Irvine, Irvine, CA, 92657, USA.
| | - Seth Blackshaw
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Ahmad M Khalil
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Krzysztof Palczewski
- Gavin Herbert Eye Institute and the Department of Ophthalmology, University of California-Irvine, Irvine, CA, 92657, USA.
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Bocci F, Jolly MK, Levine H, Onuchic JN. Quantitative Characteristic of ncRNA Regulation in Gene Regulatory Networks. Methods Mol Biol 2019; 1912:341-366. [PMID: 30635901 DOI: 10.1007/978-1-4939-8982-9_14] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
RNA is mostly known for its role in protein synthesis, where it encodes information for protein sequence in its messenger RNA (mRNA) form (translation). Yet, RNA molecules regulate several cellular processes other than translation. Here, we present an overview of several mathematical models that help understanding and characterizing the role of noncoding RNA molecules (ncRNAs) in regulating gene expression and protein synthesis. First, we discuss relatively simple models where ncRNAs can modulate protein synthesis via targeting a mRNA. Then, we consider the case of feedback interactions between ncRNAs and their target proteins, and discuss several biological applications where these feedback architectures modulate a cellular phenotype and control the levels of intrinsic and extrinsic noise. Building from these simple circuit motifs, we examine feed-forward circuit motifs involving ncRNAs that generate precise spatial and temporal patterns of protein expression. Further, we investigate the competition between ncRNAs and other endogenous RNA molecules and show that the cross talk between coding and noncoding RNAs can form large genetic circuits that involve up to hundreds of chemical species. Finally, we discuss the role of ncRNAs in modulating cell-cell signaling pathways and therefore the dynamics of spatiotemporal pattern formation in a tissue.
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Affiliation(s)
- Federico Bocci
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA.,Department of Chemistry, Rice University, Houston, TX, USA
| | - Mohit Kumar Jolly
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA. .,Department of Chemistry, Rice University, Houston, TX, USA. .,Department of Bioengineering, Rice University, Houston, TX, USA. .,Department of Physics and Astronomy, Rice University, Houston, TX, USA.
| | - José Nelson Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA. .,Department of Chemistry, Rice University, Houston, TX, USA. .,Department of Physics and Astronomy, Rice University, Houston, TX, USA. .,Department of Biosciences, Rice University, Houston, TX, USA.
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3
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Stevens JT, Carothers JM. Programming Gene Expression by Engineering Transcript Stability Control and Processing in Bacteria. Synth Biol (Oxf) 2018. [DOI: 10.1002/9783527688104.ch10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Jason T. Stevens
- University of Washington; Center for Synthetic Biology, Molecular Engineering and Sciences Institute, Departments of Chemical Engineering and Bioengineering; 4000 15th Ave NE, Seattle WA 98195-1654 USA
| | - James M. Carothers
- University of Washington; Center for Synthetic Biology, Molecular Engineering and Sciences Institute, Departments of Chemical Engineering and Bioengineering; 4000 15th Ave NE, Seattle WA 98195-1654 USA
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Hadjilouka A, Molfeta C, Panagiotopoulou O, Paramithiotis S, Mataragas M, Drosinos EH. Expression of Listeria monocytogenes key virulence genes during growth in liquid medium, on rocket and melon at 4, 10 and 30 °C. Food Microbiol 2016; 55:7-15. [DOI: 10.1016/j.fm.2015.11.008] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Revised: 10/19/2015] [Accepted: 11/17/2015] [Indexed: 10/22/2022]
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Noorbakhsh J, Lang AH, Mehta P. Intrinsic noise of microRNA-regulated genes and the ceRNA hypothesis. PLoS One 2013; 8:e72676. [PMID: 23991139 PMCID: PMC3749174 DOI: 10.1371/journal.pone.0072676] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2012] [Accepted: 07/16/2013] [Indexed: 12/12/2022] Open
Abstract
MicroRNAs are small noncoding RNAs that regulate genes post-transciptionally by binding and degrading target eukaryotic mRNAs. We use a quantitative model to study gene regulation by inhibitory microRNAs and compare it to gene regulation by prokaryotic small non-coding RNAs (sRNAs). Our model uses a combination of analytic techniques as well as computational simulations to calculate the mean-expression and noise profiles of genes regulated by both microRNAs and sRNAs. We find that despite very different molecular machinery and modes of action (catalytic vs stoichiometric), the mean expression levels and noise profiles of microRNA-regulated genes are almost identical to genes regulated by prokaryotic sRNAs. This behavior is extremely robust and persists across a wide range of biologically relevant parameters. We extend our model to study crosstalk between multiple mRNAs that are regulated by a single microRNA and show that noise is a sensitive measure of microRNA-mediated interaction between mRNAs. We conclude by discussing possible experimental strategies for uncovering the microRNA-mRNA interactions and testing the competing endogenous RNA (ceRNA) hypothesis.
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Affiliation(s)
- Javad Noorbakhsh
- Physics Department, Boston University, Boston, Massachusetts, United States of America
| | - Alex H. Lang
- Physics Department, Boston University, Boston, Massachusetts, United States of America
| | - Pankaj Mehta
- Physics Department, Boston University, Boston, Massachusetts, United States of America
- * E-mail:
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6
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Deneke C, Lipowsky R, Valleriani A. Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA. PLoS One 2013; 8:e55442. [PMID: 23408982 PMCID: PMC3569439 DOI: 10.1371/journal.pone.0055442] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2012] [Accepted: 12/23/2012] [Indexed: 11/18/2022] Open
Abstract
Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data.
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Affiliation(s)
- Carlus Deneke
- Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
| | - Reinhard Lipowsky
- Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
| | - Angelo Valleriani
- Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
- * E-mail:
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Platini T, Jia T, Kulkarni RV. Regulation by small RNAs via coupled degradation: mean-field and variational approaches. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2011; 84:021928. [PMID: 21929039 DOI: 10.1103/physreve.84.021928] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2011] [Revised: 07/11/2011] [Indexed: 05/31/2023]
Abstract
Regulatory genes called small RNAs (sRNAs) are known to play critical roles in cellular responses to changing environments. For several sRNAs, regulation is effected by coupled stoichiometric degradation with messenger RNAs (mRNAs). The nonlinearity inherent in this regulatory scheme indicates that exact analytical solutions for the corresponding stochastic models are intractable. Here, we present a variational approach to analyze a well-studied stochastic model for regulation by sRNAs via coupled degradation. The proposed approach is efficient and provides accurate estimates of mean mRNA levels as well as higher-order terms. Results from the variational ansatz are in excellent agreement with data from stochastic simulations for a wide range of parameters, including regions of parameter space where mean-field approaches break down. The proposed approach can be applied for quantitative modeling of stochastic gene expression in complex regulatory networks.
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Affiliation(s)
- Thierry Platini
- Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA.
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Elgart V, Jia T, Fenley AT, Kulkarni R. Connecting protein and mRNA burst distributions for stochastic models of gene expression. Phys Biol 2011; 8:046001. [PMID: 21490380 DOI: 10.1088/1478-3975/8/4/046001] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression.
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Affiliation(s)
- Vlad Elgart
- Department of Physics, Virginia Tech, Blacksburg, VA 24061, USA.
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Abstract
In eukaryotic cells, many genes are transcribed into noncoding RNAs. Such RNAs may associate with mRNAs and inhibit their translation and facilitate degradation. To clarify what may happen in this case, we propose a kinetic model describing the effect of noncoding RNAs on a mRNA-protein network with the hierarchical three-layer architecture. For positive regulation of the layers, our model predicts either bistability with a fairly narrow hysteresis loop or a unique steady state. For negative or mixed regulation, the steady state is found to be unique.
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Affiliation(s)
- Vladimir P Zhdanov
- Department of Applied Physics, Chalmers University of Technology, S-41296 Göteborg, Sweden.
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10
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Evidence for an autonomous 5' target recognition domain in an Hfq-associated small RNA. Proc Natl Acad Sci U S A 2010; 107:20435-40. [PMID: 21059903 DOI: 10.1073/pnas.1009784107] [Citation(s) in RCA: 142] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The abundant class of bacterial Hfq-associated small regulatory RNAs (sRNAs) parallels animal microRNAs in their ability to control multiple genes at the posttranscriptional level by short and imperfect base pairing. In contrast to the universal length and seed pairing mechanism of microRNAs, the sRNAs are heterogeneous in size and structure, and how they regulate multiple targets is not well understood. This paper provides evidence that a 5' located sRNA domain is a critical element for the control of a large posttranscriptional regulon. We show that the conserved 5' end of RybB sRNA recognizes multiple mRNAs of Salmonella outer membrane proteins by ≥7-bp Watson-Crick pairing. When fused to an unrelated sRNA, the 5' domain is sufficient to guide target mRNA degradation and maintain σ(E)-dependent envelope homeostasis. RybB sites in mRNAs are often conserved and flanked by 3' adenosine. They are found in a wide sequence window ranging from the upstream untranslated region to the deep coding sequence, indicating that some targets might be repressed at the level of translation, whereas others are repressed primarily by mRNA destabilization. Autonomous 5' domains seem more common in sRNAs than appreciated and might improve the design of synthetic RNA regulators.
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