Translation inhibition and resource balance in the TX-TL cell-free gene expression system.

Quantifying the effect of vital resources on transcription (TX) and translation (TL) helps to understand the degree to which the concentration of each resource must be regulated for achieving homeostasis. Utilizing the synthetic TX-TL system, we study the impact of nucleotide triphosphates (NTPs) and magnesium (Mg) on gene expression. Recent observations of the counter-intuitive phenomenon of suppression of gene expression at high NTP concentrations have led to the speculation that such suppression is due to the consumption of resources by TX, hence leaving fewer resources for TL.

Breaking an epigenetic chromatin switch: curious features of hysteresis in Saccharomyces cerevisiae telomeric silencing.

In addition to gene network switches, local epigenetic modifications to DNA and histones play an important role in all-or-none cellular decision-making. Here, we study the dynamical design of a well-characterized epigenetic chromatin switch: the yeast SIR system, in order to understand the origin of the stability of epigenetic states. We study hysteresis in this system by perturbing it with a histone deacetylase inhibitor.

Locus dependence in epigenetic chromatin silencing.

Current biological models of epigenetic switches built on chromatin modifications lead to strong constraints on the repertoire of dynamic behaviors for the system. We use the structure of the bifurcation diagram of the underlying dynamical system to explain the existing single cell data in silencing by the SIR system in yeast.

OHMM: a Hidden Markov Model accurately predicting the occupancy of a transcription factor with a self-overlapping binding motif.

Background: DNA sequence binding motifs for several important transcription factors happen to be self-overlapping. Many of the current regulatory site identification methods do not explicitly take into account the overlapping sites. Moreover, most methods use arbitrary thresholds and fail to provide a biophysical interpretation of statistical quantities.

Better estimation of protein-DNA interaction parameters improve prediction of functional sites.

Background: Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment) method designed to produce many such sequences.

Combined analysis of expression data and transcription factor binding sites in the yeast genome.

Background: The analysis of gene expression using DNA microarrays provides genome wide profiles of the genes controlled by the presence or absence of a specific transcription factor. However, the question arises of whether a change in the level of transcription of a specific gene is caused by the transcription factor acting directly at the promoter of the gene or through regulation of other transcription factors working at the promoter.

Results: To address this problem we have devised a computational method that combines microarray expression and site preference data.