Biophysics and bioinformatics of transcription regulation
Mathematical Biosciences Institute, The Ohio State University
(October 6, 2005 10:30 AM - 11:30 AM)
SELEX experiments allow extracting, from an initially random pool of DNA, those oligomers with high affinity for a given DNA-binding protein. We address what is a suitable experimental and computational procedure to infer parameters of protein-DNA interaction from SELEX experiments. To answer this, we use a biophysical model of protein-DNA interactions to quantitatively model SELEX and show that the standard procedure is unsuitable for obtaining the interaction parameters. However, we show that a suitably modified experiment allows robust generation of an appropriate data set. Based on our quantitative model, we propose a novel bioinformatic method of data analysis. Our method results in a significantly improved false positive/false negative trade-off, as compared to the standard information-theory based method.
In the second part of the talk, I will discuss analysis of virulent bacteriophage gene expression strategies. Most of genes of virulent Xp10 bacteriophage are organized similarly to lambdoid phages that rely only on host RNA polymerase for their development. However, unlike the lambdoid phages, Xp10 encodes its own RNA polymerase. We perform global transcription profiling, kinetic modeling and bioinformatics analyses, in order to understand the role of both host and phage RNA polymerases in the Xp10 gene expression. Our analysis results in the quantitative estimates of contributions of both RNA polymerases to the rates of transcription of all Xp10 genes, and in the identification of the previously unknown promoter sequence for Xp10 RNA polymerase. Developed methods of data analysis can be used to efficiently infer transcription strategies of other novel bacterial viruses.