Multiplex Eukaryotic Transcription (In)activation: Timing, Bursting and Cycling of a Ratchet Clock Mechanism

Abstract

Activation of eukaryotic transcription is an intricate process that relies on a multitude of regulatory proteins forming complexes on chromatin. Chromatin modifications appear to play a guiding role in protein-complex assembly on chromatin. Together, these processes give rise to stochastic, often bursting, transcriptional activity. Here we present a model of eukaryotic transcription that aims to integrate those mechanisms. We use stochastic and ordinary-differential-equation modeling frameworks to examine various possible mechanisms of gene regulation by multiple transcription factors. We find that the assembly of large transcription factor complexes on chromatin via equilibrium-binding mechanisms is highly inefficient and insensitive to concentration changes of single regulatory proteins. An alternative model that lacks these limitations is a cyclic ratchet mechanism. In this mechanism, small protein complexes assemble sequentially on the promoter. Chromatin modifications mark the completion of a protein complex assembly, and sensitize the local chromatin for the assembly of the next protein complex. In this manner, a strict order of protein complex assemblies is attained. Even though the individual assembly steps are highly stochastic in duration, a sequence of them gives rise to a remarkable precision of the transcription cycle duration. This mechanism explains how transcription activation cycles, lasting for tens of minutes, derive from regulatory proteins residing on chromatin for only tens of seconds. Transcriptional bursts are an inherent feature of such transcription activation cycles. Bursting transcription can cause individual cells to remain in synchrony transiently, offering an explanation of transcriptional cycling as observed in cell populations, both on promoter chromatin status and mRNA levels.

Gene transcription in bursting: a unified mode for realizing accuracy and stochasticity

“…(6) Low-affinity DNA binding sites, unstable protein complexes, and DNA supercoiling can play crucial roles in regulating transcription. Investigating transcriptional dynamics necessitates both live imaging methods with high resolution (Skupsky et al, 2010;Suter et al, 2011;Evans et al, 2012;Friedman, Mumm, & Gelles, 2013;Gebhardt et al, 2013;Hocine et al, 2013;Kouno et al, 2013;Lickwar, Mueller, & Lieb, 2013;Yunger et al, 2013;Sidaway-Lee et al, 2014;Annibale & Gratton, 2015;Camunas-Soler et al, 2015;Gocheva et al, 2015;Roberts et al, 2015;Rybakova et al, 2015a;Corrigan et al, 2016;Tantale et al, 2016) and quantitative computer simulations with appropriate theories and models (Skupsky et al, 2010;Suter et al, 2011;Wang et al, 2012;Maina et al, 2014;Choubey, Kondev, & Sanchez, 2015;Stefan et al, 2015;Rybakova et al, 2015a,b;Corrigan et al, 2016;Tantale et al, 2016). Specifically, integrating diverse sets of data makes it possible to present a coherent dynamic picture of gene transcription in bacteria ).…”

“…For some genes, chromatin has a primary role in shaping transcriptional dynamics Métivier, Reid, & Gannon, 2006;Rybakova et al, 2015a). The promoter state, which is determined by how the promoter is chemically modified and how the associated proteins are structurally assembled and chemically modified, evolves sequentially due to successive occurrence of irreversible molecular reactions [e.g.…”

“…Typical genes obeying such dynamics include the oestrogen receptor α-regulated pS2 gene in human cells and the copper receptor Ace1p-regulated CUP1 gene in yeast cells Karpova et al, 2008;Wang et al, 2014). Once induced simultaneously by oestrogen or copper, a population of the promoters exhibits synchronized transcriptional activity for a relatively long time (Lemaire et al, 2006;Wang et al, 2014;Rybakova et al, 2015a).…”

An open-loop approach to calculate noise-induced transitions

“…Such reactions make the potential barrier between the two stable steady states higher, which slow down the transitions (Hsu et al, 2016a). On the other hand, noise is largely determined by copy number and extrinsic fluctuations (Rybakova et al, 2015;Vinuelas et al, 2013), which can also have dramatic effect on the MFPT (Horsthemke and Lefever, 1984;Hsu et al, 2012;Jaruszewicz et al, 2013). Thus, the Fokker-Planck equation (FPE) is in principle an ideal tool to calculate the MFPT since noise (and hence diffusion) and the deterministic drift are often measured separately.…”

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

“…[142]). This has been extended to the intricacies of transcriptional regulation in mammalian systems in the context of epigenetics and chromatin modification [143], although more work is needed here. Mathematically, the dynamics of a synthetic gene-metabolic pathway can be expressed by combining the expression of (2.1) and (4.1), and we can further break down the dynamics of the protein concentrations (4.1) into transcription (mRNA dynamics) and translation.…”