Biomedical subjects

Marko Djordjevic

Publications and source records attributed to Marko Djordjevic.

6 recordsLinked to original sources

PubMed2006

Temporal regulation of viral transcription during development of Thermus thermophilus bacteriophage phiYS40.

Regulation of gene expression of lytic bacteriophage varphiYS40 that infects the thermophilic bacterium Thermus thermophilus was investigated and three temporal classes of phage genes, early, middle, and late, were revealed. varphiYS40 does not encode a (RNAP) and must rely on host RNAP for transcription of its genes. Bioinformatic analysis using a model of Thermus promoters predicted 43 putative sigma(A)-dependent -10/-35 class phage promoters. A randomly chosen subset of those promoters was shown to be functional in vivo and in vitro and to belong to the early temporal class. Macroarray analysis, primer extension, and bioinformatic predictions identified 36 viral middle and late promoters. These promoters have a single common consensus element, which resembles host sigma(A) RNAP holoenzyme -10 promoter consensus element sequence. The mechanism responsible for the temporal control of the three classes of promoters remains unknown, since host sigma(A) RNAP holoenzyme purified from either infected or uninfected cells efficiently transcribed all varphiYS40 promoters in vitro. Interestingly, our data showed that during infection, there is a significant increase and decrease of transcript amounts of host translation initiation factors IF2 and IF3, respectively. This finding, together with the fact that most middle and late varphiYS40 transcripts were found to be leaderless, suggests that the shift to late viral gene expression may also occur at the level of mRNA translation.

Bacteriophages↗

PubMed2006

Quantitative analysis of a virulent bacteriophage transcription strategy.

An increasingly large number of bacteriophage genomes are being sequenced each year. What is an efficient experimental and computational procedure to analyze transcription strategies of newly sequenced novel bacteriophages? We address this issue using an example of bacteriophage Xp10, which infects rice pathogen Xanthomonas oryzae. This phage is particularly challenging for analysis, since part of its genome is jointly transcribed by two (host and viral) RNA polymerases. To understand the roles played by the two RNA polymerases, we developed a novel method of data analysis which combines quantitative analysis of Xp10 global gene expression data and kinetic modeling of the infection process. To generalize our approach, we discuss how our method can be applied to other systems and argue that genomic array experiments combined with the methods of data analysis that we present provide an efficient way to analyze gene expression strategies of novel bacteriophages.

Bacteriophages↗

PubMed2005

Quantitative modeling and data analysis of SELEX experiments.

SELEX (systematic evolution of ligands by exponential enrichment) is an experimental procedure that allows the extraction, from an initially random pool of DNA, of 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 transcription factor-DNA interaction from SELEX experiments. To answer this, we use a biophysical model of transcription factor-DNA interactions to quantitatively model SELEX. We show that a standard procedure is unsuitable for obtaining accurate interaction parameters. However, we theoretically show that a modified experiment in which chemical potential is fixed through different rounds of the experiment allows robust generation of an appropriate dataset. Based on our quantitative model, we propose a novel bioinformatic method of data analysis for such a modified experiment and apply it to extract the interaction parameters for a mammalian transcription factor CTF/NFI. From a practical point of view, our method results in a significantly improved false positive/false negative trade-off, as compared to both the standard information theory based method and a widely used empirically formulated procedure.

Animals↗

PubMed2005

The tale of two RNA polymerases: transcription profiling and gene expression strategy of bacteriophage Xp10.

Bacteriophage Xp10 infects rice pathogen Xanthomonas oryzae. Xp10 encodes its own single-subunit RNA polymerase (RNAP), similar to that found in phages of the T7 family. On the other hand, most of Xp10 genes are organized in a manner typical of lambdoid phages that are known to rely only on host RNAP for their development. To better understand the temporal pattern of viral transcription during Xp10 development, we performed global transcription profiling, primer extension, chemical kinetic modelling and bioinformatic analyses of Xp10 gene expression. Our results indicate that true to its mosaic nature, Xp10 relies on both host and viral RNAPs for expression of genes coding for virion components and host lysis. The joint transcription of the same set of genes by two types of RNA polymerases is unprecedented for a bacteriophage. Curiously, such a situation is realized in chloroplasts.

Bacterial Proteins↗

PubMed2003

A biophysical approach to transcription factor binding site discovery.

Identification of transcription factor binding sites within regulatory segments of genomic DNA is an important step toward understanding of the regulatory circuits that control expression of genes. Here, we describe a novel bioinformatics method that bases classification of potential binding sites explicitly on the estimate of sequence-specific binding energy of a given transcription factor. The method also estimates the chemical potential of the factor that defines the threshold of binding. In contrast with the widely used information-theoretic weight matrix method, the new approach correctly describes saturation in the transcription factor/DNA binding probability. This results in a significant improvement in the number of expected false positives, particularly in the ubiquitous case of low-specificity factors. In the strong binding limit, the algorithm is related to the "support vector machine" approach to pattern recognition. The new method is used to identify likely genomic binding sites for the E. coli transcription factors collected in the DPInteract database. In addition, for CRP (a global regulatory factor), the likely regulatory modality (i.e., repressor or activator) of predicted binding sites is determined.

Algorithms↗

PubMed2002

Specificity and robustness in transcription control networks.

Recognition by transcription factors of the regulatory DNA elements upstream of genes is the fundamental step in controlling gene expression. How does the necessity to provide stability with respect to mutation constrain the organization of transcription control networks? We examine the mutation load of a transcription factor interacting with a set of n regulatory response elements as a function of the factor/DNA binding specificity and conclude on theoretical grounds that the optimal specificity decreases with n. The predicted correlation between variability of binding sites (for a given transcription factor) and their number is supported by the genomic data for Escherichia coli. The analysis of E. coli genomic data was carried out using an algorithm suggested by the biophysical model of transcription factor/DNA binding. Complete results of the search for candidate transcription factor binding sites are available at http://www.physics.rockefeller.edu/~boris/public/search_ecoli.

Algorithms↗