Yumin Teng

The mapping of nucleosomes and regulatory protein binding sites at the Saccharomyces cerevisiae MFA2 gene: a high resolution approach

We have developed an end-labelling approach to map the positions of nucleosomes and protein binding sites at nucleotide resolution by footprinting micrococcal nuclease (MNase)-sensitive sites. Using this approach we determined that the MFA2 gene and its upstream control regions have four positioned nucleosomes when transcription is repressed in mating type alpha cells and that the nucleosomes lose their positioning when the gene became transcriptionally active in mating type a cells. We also detected MNase-hypersensitive sites in the alpha2 operator region of MFA2 in alpha cells but not in a cells. These probably result from the change in the local DNA conformation due to protein(s) binding in this region that governs MFA2 transcription.

Complementary Roles of Yeast Rad4p and Rad34p in Nucleotide Excision Repair of Active and Inactive rRNA Gene Chromatin

ABSTRACT Nucleotide excision repair (NER) removes a plethora of DNA lesions. It is performed by a large multisubunit protein complex that finds and repairs damaged DNA in different chromatin contexts and nuclear domains. The nucleolus is the most transcriptionally active domain, and in yeast, transcription-coupled NER occurs in RNA polymerase I-transcribed genes (rDNA). Here we have analyzed the roles of two members of the xeroderma pigmentosum group C family of proteins, Rad4p and Rad34p, during NER in the active and inactive rDNA. We report that Rad4p is essential for repair in the intergenic spacer, the inactive rDNA coding region, and for strand-specific repair at the transcription initiation site, whereas Rad34p is not. Rad34p is necessary for transcription-coupled NER that starts about 40 nucleotides downstream of the transcription initiation site of the active rDNA, whereas Rad4p is not. Thus, although Rad4p and Rad34p share sequence homology, their roles in NER in the rDNA locus are almost entirely distinct and complementary. These results provide evidences that transcription-coupled NER and global genome NER participate in the removal of UV-induced DNA lesions from the transcribed strand of active rDNA. Furthermore, nonnucleosome rDNA is repaired faster than nucleosome rDNA, indicating that an open chromatin structure facilitates NER in vivo.

RAD9, RAD24, RAD16 and RAD26 are required for the inducible nucleotide excision repair of UV-induced cyclobutane pyrimidine dimers from the transcribed and non-transcribed regions of the Saccharomyces cerevisiae MFA2 gene.

In this study, the effect of a prior UV irradiation on the removal of cyclobutane pyrimidine dimers (CPDs) from the transcribed strand (TS) and non-transcribed strand (NTS) of the MFA2 gene in haploid Saccharomyces cerevisiae (S. cerevisiae) cells was investigated. In NER competent cells, the pre-irradiation with a dose of 20J/m2 enhances the removal of CPDs induced by a second UV dose of 100J/m2 in the TS and the NTS of MFA2 gene except for the CPDs in the region +258 to +298 in the NTS, where the enhanced repair was absent. No inducible repair was observed in rad9, rad24, rad16 and rad26 cells, indicating two checkpoint genes RAD9 and RAD24, the global repair gene RAD16 and the transcription coupled repair gene RAD26 are essential for inducible NER.

A Role for Checkpoint Kinase-Dependent Rad26 Phosphorylation in Transcription-Coupled DNA Repair in Saccharomyces cerevisiae

ABSTRACT Upon DNA damage, eukaryotic cells activate a conserved signal transduction cascade known as the DNA damage checkpoint (DDC). We investigated the influence of DDC kinases on nucleotide excision repair (NER) in Saccharomyces cerevisiae and found that repair of both strands of an active gene is affected by Mec1 but not by the downstream checkpoint kinases, Rad53 and Chk1. Repair of the nontranscribed strand (by global genome repair) requires new protein synthesis, possibly reflecting the involvement of Mec1 in the activation of repair genes. In contrast, repair of the transcribed strand by transcription-coupled NER (TC-NER) occurs in the absence of new protein synthesis, and DNA damage results in Mec1-dependent but Rad53-, Chk1-, Tel1-, and Dun1-independent phosphorylation of the TC-NER factor Rad26, a member of the Swi/Snf group of ATP-dependent translocases and yeast homologue of Cockayne syndrome B. Mutation of the Rad26 phosphorylation site results in a decrease in the rate of TC-NER, pointing to direct activation of Rad26 by Mec1 kinase. These findings establish a direct role for Mec1 kinase in transcription-coupled repair, at least partly via phosphorylation of Rad26, the main transcription-repair coupling factor.

Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure

ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable comparative analyses of enrichment levels derived from datasets examining different experimental conditions. This restricts the use of the technology to binary comparisons of presence or absence of features between datasets. Here we present the R package Sandcastle — Software for the Analysis and Normalisation of Data from ChIP-chip AssayS of Two or more Linked Experiments — which allows for comparative analyses of data from multiple experiments by normalising all datasets to a common background. Relative changes in binding levels between experimental datasets can thus be determined, enabling the extraction of latent information from ChIP-chip experiments. Novel enrichment detection and peak calling algorithms are also presented, with a range of graphical tools, which facilitate these analyses. The software and documentation are available for download from http://reedlab.cardiff.ac.uk/sandcastle.

Emerging technologies in genotoxicity testing: measuringDNA damage in entire genomes at high resolution [Abstract]

The Syrian hamster embryo (SHE) assay (pH6.7) is being touted as a ‘‘3R’s’’ alternative in animal laboratory studies. In the SHE assay, traditionally, colonies are counted and scored by eye to determine the transforming potential of test chemicals. Application of infrared (IR) spectroscopy opens up the possibility of comparing test chemicals with negative and positive controls in a high-throughput fashion (1) through objective pattern recognition methods. Such methods are under development under the 1) ‘‘openness’’, and 2) multiple-class requirements: 1) computer systems need to be ‘‘open’’ to new data to refine existing classifiers; 2) furthermore, the existence of multiple classes (i.e., chemical treatment conditions) calls for composite architectures containing many simple classifiers instead a single complicated one. In this study we present two classification strategies contemplating these two principles. The proposed strategies are compared to well established ‘‘closed’’, single-model classifiers. The dataset used in the study was derived from a SHE assay where eight treatment conditions were present [vehicle control (DMSO), D-M, B[a]P, 3-MCA, Anthracene, o-T, 2,4-dT, and MNNG] (2). From the assay, IR spectra (n¼14,000) were obtained using attenuated total reflection Fourier-transform IR spectroscopy. Gradual feeding of the proposed models with training data is shown to gradually improve the classification of test data. Segregation of data along chemical mode of action was observed. Overall, the results strengthen arguments towards using the SHE assay in toxicological assessments and point to IR spectroscopy as a possible alternative to visual scoring.DNA is not chemically inert but faces constant challenges to its stability. One of these is the fusion of adjacent pyrimidine bases by ultra violet (UV) radiation to create cyclobutane pyrimidine dimers (CPDs). Numerous methods of DNA repair have evolved within cells, of which nucleotide excision repair (NER) is responsible for the removal of CPDs and other bulky adducts. To investigate this and other repair pathways various techniques have been developed to detect DNA damage at low resolutions in whole genomes or high resolutions over small sections of a genome. We have developed a novel microarray based method for the genome wide high resolution analysis of DNA damage in yeast which combines the advantages of these, allowing detailed measurement of repair across entire genomes. A program has been written to predict the expected CPD formation based on sequence; this has shown that the genome wide damage detection method is accurate. Additionally, ChIPchip has been used to determine the binding positions of proteins involved in NER and analyse histone modifications after damage induction. Combining these datasets allows protein binding and acetylation levels to be correlated with repair rates. These datasets require bioinformatic tools to analyse and extract results. I have developed a suite of novel tools to process, normalise, display and interrogate these datasets including a new normalisation method which allows accurate comparisons to be made between different factors, revealing changes in acetylation profiles following UV and between different mutant strains, a peak detection method to distinguish protein binding peaks from a background of nonbound regions, revealing many novel binding sites for proteins such as Abf1 and Rad16, and graphical displays to determine patterns that occur at multiple positions throughout genomes, revealing patterns of varying repair rates at regions such as centromeres and telomeres.

Bioinformatic analyses of genome wide nucleotideexcision repair datasets in Saccharomyces cerevisiae [Abstract]

The Syrian hamster embryo (SHE) assay (pH6.7) is being touted as a ‘‘3R’s’’ alternative in animal laboratory studies. In the SHE assay, traditionally, colonies are counted and scored by eye to determine the transforming potential of test chemicals. Application of infrared (IR) spectroscopy opens up the possibility of comparing test chemicals with negative and positive controls in a high-throughput fashion (1) through objective pattern recognition methods. Such methods are under development under the 1) ‘‘openness’’, and 2) multiple-class requirements: 1) computer systems need to be ‘‘open’’ to new data to refine existing classifiers; 2) furthermore, the existence of multiple classes (i.e., chemical treatment conditions) calls for composite architectures containing many simple classifiers instead a single complicated one. In this study we present two classification strategies contemplating these two principles. The proposed strategies are compared to well established ‘‘closed’’, single-model classifiers. The dataset used in the study was derived from a SHE assay where eight treatment conditions were present [vehicle control (DMSO), D-M, B[a]P, 3-MCA, Anthracene, o-T, 2,4-dT, and MNNG] (2). From the assay, IR spectra (n¼14,000) were obtained using attenuated total reflection Fourier-transform IR spectroscopy. Gradual feeding of the proposed models with training data is shown to gradually improve the classification of test data. Segregation of data along chemical mode of action was observed. Overall, the results strengthen arguments towards using the SHE assay in toxicological assessments and point to IR spectroscopy as a possible alternative to visual scoring.DNA is not chemically inert but faces constant challenges to its stability. One of these is the fusion of adjacent pyrimidine bases by ultra violet (UV) radiation to create cyclobutane pyrimidine dimers (CPDs). Numerous methods of DNA repair have evolved within cells, of which nucleotide excision repair (NER) is responsible for the removal of CPDs and other bulky adducts. To investigate this and other repair pathways various techniques have been developed to detect DNA damage at low resolutions in whole genomes or high resolutions over small sections of a genome. We have developed a novel microarray based method for the genome wide high resolution analysis of DNA damage in yeast which combines the advantages of these, allowing detailed measurement of repair across entire genomes. A program has been written to predict the expected CPD formation based on sequence; this has shown that the genome wide damage detection method is accurate. Additionally, ChIPchip has been used to determine the binding positions of proteins involved in NER and analyse histone modifications after damage induction. Combining these datasets allows protein binding and acetylation levels to be correlated with repair rates. These datasets require bioinformatic tools to analyse and extract results. I have developed a suite of novel tools to process, normalise, display and interrogate these datasets including a new normalisation method which allows accurate comparisons to be made between different factors, revealing changes in acetylation profiles following UV and between different mutant strains, a peak detection method to distinguish protein binding peaks from a background of nonbound regions, revealing many novel binding sites for proteins such as Abf1 and Rad16, and graphical displays to determine patterns that occur at multiple positions throughout genomes, revealing patterns of varying repair rates at regions such as centromeres and telomeres.