scholarly journals Signaling Mechanism of Transcriptional Bursting: A Technical Resolution-Independent Study

Biology ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 339
Author(s):  
Yaolai Wang ◽  
Jiaming Qi ◽  
Jie Shao ◽  
Xu-Qing Tang
Keyword(s):  
Frequency Modulation ◽  
Transcription Initiation ◽  
Burst Size ◽  
Independent Study ◽  
Transcriptional Activators ◽  
Signaling Mechanism ◽  
Theoretical Predictions ◽  
Support Size ◽  
Analytical Research ◽  
Transcriptional Bursting

Gene transcription has been uncovered to occur in sporadic bursts. However, due to technical difficulties in differentiating individual transcription initiation events, it remains debated as to whether the burst size, frequency, or both are subject to modulation by transcriptional activators. Here, to bypass technical constraints, we addressed this issue by introducing two independent theoretical methods including analytical research based on the classic two-model and information entropy research based on the architecture of transcription apparatus. Both methods connect the signaling mechanism of transcriptional bursting to the characteristics of transcriptional uncertainty (i.e., the differences in transcriptional levels of the same genes that are equally activated). By comparing the theoretical predictions with abundant experimental data collected from published papers, the results exclusively support frequency modulation. To further validate this conclusion, we showed that the data that appeared to support size modulation essentially supported frequency modulation taking into account the existence of burst clusters. This work provides a unified scheme that reconciles the debate on burst signaling.

scholarly journals Transcriptional bursting explains the noise-versus-mean relationship in mRNA and protein levels

2016 ◽  
Author(s):  
Roy D. Dar ◽  
Sydney M. Schaffer ◽  
Siddarth S. Dey ◽  
Jonathan E. Foley ◽  
Abhyudai Singh ◽  
...  
Keyword(s):  
Conflict Of Interest ◽  
Burst Size ◽  
Inverse Correlation ◽  
Recent Analysis ◽  
Mrna Levels ◽  
Burst Frequency ◽  
Expression Variability ◽  
Protein Levels ◽  
Transcriptional Bursting ◽  
Cell Expression

Recent analysis (Dey et al, 2015), demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-to-cell expression variability (noise) and mean are uncorrelated, a significant deviation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-size manifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.Conflict of InterestThe authors declare that they have no conflict of interest.

scholarly journals Transient-state Kinetic Analysis of Transcriptional Activator·DNA Complexes Interacting with a Key Coactivator

2011 ◽  
Vol 286 (18) ◽  
pp. 16238-16245 ◽  
Author(s):  
Amberlyn M. Wands ◽  
Ningkun Wang ◽  
Jenifer K. Lum ◽  
John Hsieh ◽  
Carol A. Fierke ◽  
...  
Keyword(s):  
Conformational Change ◽  
Transcriptional Activation ◽  
Transcription Initiation ◽  
Transient State ◽  
Transcriptional Activators ◽  
Binding Mechanism ◽  
Future Design ◽  
Binding Surface ◽  
Time Courses

Several lines of evidence suggest that the prototypical amphipathic transcriptional activators Gal4, Gcn4, and VP16 interact with the key coactivator Med15 (Gal11) during transcription initiation despite little sequence homology. Recent cross-linking data further reveal that at least two of the activators utilize the same binding surface within Med15 for transcriptional activation. To determine whether these three activators use a shared binding mechanism for Med15 recruitment, we characterized the thermodynamics and kinetics of Med15·activator·DNA complex formation by fluorescence titration and stopped-flow techniques. Combination of each activator·DNA complex with Med15 produced biphasic time courses. This is consistent with a minimum two-step binding mechanism composed of a bimolecular association step limited by diffusion, followed by a conformational change in the Med15·activator·DNA complex. Furthermore, the equilibrium constant for the conformational change (K2) correlates with the ability of an activator to stimulate transcription. VP16, the most potent of the activators, has the largest K2 value, whereas Gcn4, the least potent, has the smallest value. This correlation is consistent with a model in which transcriptional activation is regulated at least in part by the rearrangement of the Med15·activator·DNA ternary complex. These results are the first detailed kinetic characterization of the transcriptional activation machinery and provide a framework for the future design of potent transcriptional activators.

Modelling transcriptional feedback loops: the role of Gro/TLE1 in Hes1 oscillations

2006 ◽  
Vol 364 (1842) ◽  
pp. 1155-1170 ◽  
Author(s):  
Samuel Bernard ◽  
Branka Čajavec ◽  
Laurent Pujo-Menjouet ◽  
Michael C Mackey ◽  
Hanspeter Herzel
Keyword(s):  
Transcription Initiation ◽  
Periodic Pattern ◽  
Transcriptional Repressors ◽  
Helix Loop Helix ◽  
Family Protein ◽  
Theoretical Predictions ◽  
Numerical Bifurcation ◽  
Enhancer Of Split ◽  
Transcriptional Feedback

The transcriptional repressor Hes1, a basic helix-loop-helix family protein, periodically changes its expression in the presomitic mesoderm. Its periodic pattern of expression is retained in a number of cultured murine cell lines. In this paper, we introduce an extended mathematical model for Hes1 oscillatory expression that includes regulation of Hes1 transcription by Drosophila Groucho (Gro) or its vertebrate counterpart, the transducine-like enhancer of split/Groucho-related gene product 1 (TLE1). Gro/TLE1 is a necessary corepressor required by a number of DNA-binding transcriptional repressors, including Hes1. Models of direct repression via Hes1 typically display an expression overshoot after transcription initiation which is not seen in the experimental data. However, numerical simulation and theoretical predictions of our model show that the cofactor Gro/TLE1 reduces the overshoot and is thus necessary for a rapid and finely tuned response of Hes1 to activation signals. Further, from detailed linear stability and numerical bifurcation analysis and simulations, we conclude that the cooperativity coefficient ( h ) for Hes1 self-repression should be large (i.e. h ≥4). Finally, we introduce the characteristic turnaround duration, and show that for our model the duration of the repression loop is between 40 and 60 min.

scholarly journals Single-molecule imaging reveals the interplay between transcription factors, nucleosomes, and transcriptional bursting

2018 ◽  
Author(s):  
Benjamin T. Donovan ◽  
Anh Huynh ◽  
David A. Ball ◽  
Michael G. Poirier ◽  
Daniel R. Larson ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Single Molecule ◽  
Target Genes ◽  
Burst Size ◽  
Yeast Cells ◽  
Single Molecule Imaging ◽  
Transcriptional Bursting

SummaryTranscription factors show rapid and reversible binding to chromatin in living cells, and transcription occurs in sporadic bursts, but how these phenomena are related is unknown. Using a combination of in vitro and in vivo single-molecule imaging approaches, we directly correlated binding of the transcription factor Gal4 with the transcriptional bursting kinetics of the Gal4 target genes GAL3 and GAL10 in living yeast cells. We find that Gal4 dwell times sets the transcriptional burst size. Gal4 dwell time depends on the affinity of the binding site and is reduced by orders of magnitude by nucleosomes. Using a novel imaging platform, we simultaneously tracked transcription factor binding and transcription at one locus, revealing the timing and correlation between Gal4 binding and transcription. Collectively, our data support a model where multiple polymerases initiate during a burst as long as the transcription factor is bound to DNA, and a burst terminates upon transcription factor dissociation.

scholarly journals Structural Basis for the Interaction between p53 Transactivation Domain and the Mediator Subunit MED25

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2726 ◽  
Author(s):  
Min-Sung Lee ◽  
Kyungeun Lim ◽  
Mi-Kyung Lee ◽  
Seung-Wook Chi
Keyword(s):  
Molecular Interaction ◽  
Transcription Initiation ◽  
Structural Model ◽  
Structural Basis ◽  
Titration Calorimetry ◽  
Virus Protein ◽  
Sequence Motif ◽  
Transactivation Domain ◽  
Transcriptional Activators ◽  
Interaction Domain

Eukaryotic transcription initiation is mediated by interactions between transcriptional activators and the mediator coactivator complex. Molecular interaction of p53 transcription factor with mediator complex subunit 25 (MED25) is essential for its target gene transcription. In this study, we characterized the molecular interaction between p53 transactivation domain (p53TAD) and activator interaction domain (ACID) of MED25 using nuclear magnetic resonance (NMR) spectroscopy. The NMR chemical shift perturbation and isothermal titration calorimetry (ITC) data showed that p53TAD interacted with MED25 ACID mainly through the p53TAD2 sequence motif. Taken together with the mutagenesis data, the refined structural model of MED25 ACID/p53TAD2 peptide complex showed that an amphipathic α-helix of p53TAD2 peptide bound an elongated hydrophobic groove of MED25 ACID. Furthermore, our results revealed the highly conserved mechanism of MED25 interaction with intrinsically unfolded acidic TADs from the transcriptional activators p53, ERM (Ets-related molecule), and herpes simplex virus protein 16 (VP16).

scholarly journals PENGARUH KEBIASAAN BELAJAR TERHADAP KEPUASAN HASIL UJIAN PADA MATA KULIAH KONSEP KEBIDANAN

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Yunik Windarti
Keyword(s):  
Learning Outcomes ◽  
Research Study ◽  
Statistical Tests ◽  
Sampling Technique ◽  
Independent Study ◽  
Study Habits ◽  
Learning Activities ◽  
Probability Sampling ◽  
Large Sample ◽  
Analytical Research

The effect of habitual learning towards satisfaction of the results of tests on the course concepts of midwifery. Factors influenced the results of tests from the satisfaction of learning activities that are done by the student itself. In fact, many of the students who learn only at certain times, especially during exams. This research aims to analyze the effect of habitual learning towards satisfaction of the results of tests on the course concepts of midwifery. Design of analytical research, the population of students of the Semester I Prodi D-III Kebidanan FKK UNUSA of 123 people, a large sample of 123 people, taken with a probability sampling technique with total sampling. Independent study habits variables, variable dependent satisfaction exam results. The data is analyzed using kruskal wallis test. The results showed almost entirely (78,9%) students had the habit of learning outcomes and is almost entirely (75,6%) students were declared not satisfied against the results of the test. The results of statistical tests obtained ρ = 0,023 < α = 0,05, H0 is rejected then it means there is a significant learning habits influence towards the satisfaction of the results tests on the course concepts of midwifery. The conclusion of this research study is not good habits will cause discontent against the examination results are obtained. For students is expected to change the habit of studying, focus more on the material obtained, multiply the reading, often visited the library, the science danmenimba from various media rather than just rely on from the material presented lecturer.

scholarly journals Kinetic characteristics of transcriptional bursting in a complex gene model with cyclic promoter structure

2021 ◽  
Author(s):  
Xiyan Yang ◽  
Zihao Wang ◽  
Yahao Wu ◽  
Tianshou Zhou ◽  
Jiajun Zhang
Keyword(s):  
Experimental Data ◽  
Geometric Distribution ◽  
Burst Size ◽  
Mrna Expression Level ◽  
Kinetic Characteristics ◽  
Exponential Distributions ◽  
Gene Model ◽  
Promoter Structure ◽  
Transcriptional Bursting ◽  
Cell To Cell Variability

While transcription occurs often in a bursty manner, various possible regulations can lead to complex promoter patterns such as promoter cycles, giving rise to an important issue: How do promoter kinetics shape transcriptional bursting kinetics? Here we introduce and analyze a general model of the promoter cycle consisting of multi-OFF states and multi-ON states, focusing on the effects of multi-ON mechanisms on transcriptional bursting kinetics. The derived analytical results indicate that bust size follows a mixed geometric distribution rather than a single geometric distribution assumed in previous studies, and ON and OFF times obey their own mixed exponential distributions. In addition, we find that the multi-ON mechanism can lead to bimodal burst-size distribution, antagonistic timing of ON and OFF, and diverse burst frequencies, each further contributing to cell-to-cell variability in the mRNA expression level. These results not only reveal essential features of transcriptional bursting kinetics patterns shaped by multi-state mechanisms but also can be used to the inferences of transcriptional bursting kinetics and promoter structure based on experimental data.

scholarly journals Differential context-specific impact of individual core promoter elements on transcriptional dynamics

2017 ◽  
Vol 28 (23) ◽  
pp. 3360-3370 ◽  
Author(s):  
Oliver Hendy ◽  
John Campbell ◽  
Jocelyn D. Weissman ◽  
Daniel R. Larson ◽  
Dinah S. Singer
Keyword(s):  
Mhc Class I ◽  
Core Promoter ◽  
Burst Size ◽  
Promoter Elements ◽  
Transcriptional Dynamics ◽  
Transcriptional Bursting ◽  
Γ Interferon ◽  
I Gene ◽  
Mhc Class I Gene ◽  
Individual Core

Eukaryotic transcription occurs in bursts that vary in size and frequency, but the contribution of individual core promoter elements to transcriptional bursting is not known. Here we analyze the relative contributions to bursting of the individual core promoter elements—CCAAT, TATAA-like, Sp1BS, and Inr—of an MHC class I gene in primary B-cells during both basal and activated transcription. The TATAA-like, Sp1BS, and Inr elements all function as negative regulators of transcription, and each was found to contribute differentially to the overall bursting pattern of the promoter during basal transcription. Whereas the Sp1BS element regulates burst size, the Inr element regulates burst frequency. The TATAA-like element contributes to both. Surprisingly, each element has a distinct role in bursting during transcriptional activation by γ-interferon. The CCAAT element does not contribute significantly to the constitutive transcriptional dynamics of primary B-cells, but modulates both burst size and frequency in response to γ-interferon activation. The ability of core promoter elements to modulate transcriptional bursting individually allows combinatorial fine-tuning of the level of MHC class I gene expression in response to intrinsic and extrinsic signals.

scholarly journals Transcriptional bursts explain autosomal random monoallelic expression and affect allelic imbalance

2021 ◽  
Vol 17 (3) ◽  
pp. e1008772
Author(s):  
Anton J. M. Larsson ◽  
Christoph Ziegenhain ◽  
Michael Hagemann-Jensen ◽  
Björn Reinius ◽  
Tina Jacob ◽  
...  
Keyword(s):  
Allelic Imbalance ◽  
Burst Size ◽  
Single Cells ◽  
Expression Patterns ◽  
Allelic Expression ◽  
Monoallelic Expression ◽  
Burst Frequency ◽  
Biallelic Expression ◽  
High Consistency ◽  
Transcriptional Bursting

Transcriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of allelic expression resulting from transcriptional bursting and how it compared to the amount biallelic, monoallelic and allele-biased expression observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain the allelic expression patterns observed in single cells, including the frequent observations of autosomal monoallelic gene expression. Importantly, we identified that the burst frequency largely determined the fraction of cells with monoallelic expression, whereas the burst size had little effect on monoallelic observations. The high consistency between the bursting model predictions and scRNA-seq observations made it possible to assess the heterogeneity of a group of cells as their deviation in allelic observations from the expected. Finally, both burst frequency and size contributed to allelic imbalance observations and reinforced that studies of allelic imbalance can be confounded from the inherent noise in transcriptional bursting. Altogether, we demonstrate that allele-level transcriptional bursting renders widespread, although predictable, amounts of monoallelic and biallelic expression in single cells and cell populations.

scholarly journals Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data

2019 ◽  
Author(s):  
Chen Jia
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Negative Binomial ◽  
Burst Size ◽  
Dropout Rate ◽  
Quantitative Relation ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Transcriptional Bursting ◽  
Over Dispersion

AbstractSingle-cell RNA sequencing data have complex features such as dropout events, over-dispersion, and high-magnitude outliers, resulting in complicated probability distributions of mRNA abundances that are statistically characterized in terms of a zero-inflated negative binomial (ZINB) model. Here we provide a mesoscopic kinetic foundation of the widely used ZINB model based on the biochemical reaction kinetics underlying transcription. Using multiscale modeling and simplification techniques, we show that the ZINB distribution of mRNA abundance and the phenomenon of transcriptional bursting naturally emerge from a three-state stochastic transcription model. We further reveal a nontrivial quantitative relation between dropout events and transcriptional bursting, which provides novel insights into how and to what extent the burst size and burst frequency could reduce the dropout rate. Three different biophysical origins of over-dispersion are also clarified at the single-cell level.

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