Cooperative RNA polymerase molecules behavior on a stochastic sequence-dependent model for transcription elongation

VarGibbs Usage in the Optimization of Nearest-Neighbor Parameters and Prediction of Melting Temperature of RNA Duplexes

The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.

DNA supercoiling-mediated collective behavior of co-transcribing RNA polymerases

Multiple RNA polymerases (RNAPs) transcribing a gene have been known to exhibit collective group behavior, causing the transcription elongation rate to increase with the rate of transcription initiation. Such behavior has long been believed to be driven by a physical interaction or ‘push’ between closely spaced RNAPs. However, recent studies have posited that RNAPs separated by longer distances may cooperate by modifying the DNA segment under transcription. Here, we present a theoretical model incorporating the mechanical coupling between RNAP translocation and the DNA torsional response. Using stochastic simulations, we demonstrate DNA supercoiling-mediated long-range cooperation between co-transcribing RNAPs. We find that inhibiting transcription initiation can slow down the already recruited RNAPs, in agreement with recent experimental observations, and predict that the average transcription elongation rate varies non-monotonically with the rate of transcription initiation. We further show that while RNAPs transcribing neighboring genes oriented in tandem can cooperate, those transcribing genes in divergent or convergent orientations can act antagonistically, and that such behavior holds over a large range of intergenic separations. Our model makes testable predictions, revealing how the mechanical interplay between RNAPs and the DNA they transcribe can govern transcriptional dynamics.

DNA Supercoiling Drives a Transition between Collective Modes of Gene Synthesis

Transcription of genes can be affected by both biochemical and mechanical factors. Recent experiments suggested that the mechanical stress associated with transcription-induced DNA supercoiling is responsible for the transition from cooperative to antagonistic group dynamics of RNA polymerases (RNAPs) upon promoter repression. To underpin the mechanism behind this drastic transition, we developed a continuum deterministic model for transcription under torsion. In our model, the speed of an RNAP is affected by the local DNA supercoiling, as well as two global factors: (i) the number of RNAPs on the gene affecting the torsional stress experienced by individual RNAPs and (ii) transcription factors blocking the diffusion of DNA supercoils. Our minimal model can successfully reproduce the experimental findings and helps elucidate the interplay of mechanical and biological factors in the collective dynamics of molecular machines involved in gene expression.

Cooperative and sequence-dependent model for RNAP dynamics: Application to ribosomal gene transcription

Escherichia coli ribosomal genes are a well-established experimental model used to investigate the transcription process. These genes are essential to cell physiology and are therefore strongly expressed. Multiple transcription units collaborate in rrn expression. Experiments involving electron microscopy have shown the non-uniform density of the RNA polymerases transcribing these ribosomal operons. Here, we investigate RNAP collaborative transcription in E. coli ribosomal genes using a stochastic sequence-dependent model that included interactions among the RNAPs. We achieved results consistent with experimental data using a model with variable parametrization for genic and intergenic regions, compared with previous attempts that used uniform parameters for genic and intergenic regions. Our model also showed that cooperative behaviour reduced the dwell times in pause sites predicted by the single-round approach but induced a new pausing event at an upstream position. This work may stimulate new experimental research and provide other scenarios to test our model predictions.

Replacing salt correction factors with optimized RNA nearest-neighbour enthalpy and entropy parameters

We calculate the nearest-neighbour enthalpies and entropies at 5 salt concentrations of 18 RNA sequences, each for at least 9 different species concentrations, totalling 757 melting temperatures, using a melting temperature optimization method. These new parameters do not need to be salt-corrected and are shown to provide overall improved melting temperature predictions. They show a marked quadratic dependence with salt concentrations which are compensated to form linear Gibbs free energies. Two different parameter schemes were tested, with fixed or variable initial parameters. We have found that using variable initial parameters provides better predictive results than using salt correction factors and that the prediction uncertainty is considerably reduced for a validation set of independent sequences. An interpolation scheme is introduced to generate model parameters for arbitrary salt concentrations which performs better against a validation set than predictions using salt corrections.

Stationary RNA polymerase fluctuations during transcription elongation

We study fluctuation effects of nonsteric molecular interactions between RNA polymerase (RNAP) motors that move simultaneously on the same DNA track during transcription elongation. Based on a stochastic model that allows for the exact analytical computation of the stationary distribution of RNAPs as a function of their density, interaction strength, nucleoside triphosphate concentration, and rate of pyrophosphate release we predict an almost geometric headway distribution of subsequent RNAP transcribing on the same DNA segment. The localization length which characterizes the decay of the headway distribution depends directly only the average density of RNAP and the interaction strength, but not on specific single-RNAP properties. Density correlations are predicted to decay exponentially with the distance (in units of DNA base pairs), with a correlation length that is significantly shorter than the localization length.

Thermodynamic modeling of variations in the rate of RNA chain elongation of E. coli rrn operons

Previous electron-microscopic imaging has shown high RNA polymerase occupation densities in the 16S and 23S encoding regions and low occupation densities in the noncoding leader, spacer, and trailer regions of the rRNA (rrn) operons in E. coli. This indicates slower transcript elongation within the coding regions and faster elongation within the noncoding regions of the operon. Inactivation of four of the seven rrn operons increases the transcript initiation frequency at the promoters of the three intact operons and reduces the time for RNA polymerase to traverse the operon. We have used the DNA sequence-dependent standard free energy variation of the transcription complex to model the experimentally observed changes in the elongation rate along the rrnB operon. We also model the stimulation of the average transcription rate over the whole operon by increasing rate of transcript initiation. Monte Carlo simulations, taking into account initiation of transcription, translocation, and backward and forward tracking of RNA polymerase, partially reproduce the observed transcript elongation rate variations along the rrn operon and fully account for the increased average rate in response to increased frequency of transcript initiation.