Monitoring Repair of UV-Induced 6-4-Photoproducts with a Purified DDB2 Protein Complex

Because cells are constantly subjected to DNA damaging insults, DNA repair pathways are critical for genome integrity [1]. DNA damage recognition protein complexes (DRCs) recognize DNA damage and initiate DNA repair. The DNA-Damage Binding protein 2 (DDB2) complex is a DRC that initiates nucleotide excision repair (NER) of DNA damage caused by ultraviolet light (UV) [2]-[4]. Using a purified DDB2 DRC, we created a probe ("DDB2 proteo-probe") that hybridizes to nuclei of cells irradiated with UV and not to cells exposed to other genotoxins. The DDB2 proteo-probe recognized UV-irradiated DNA in classical laboratory assays, including cyto- and histo-chemistry, flow cytometry, and slot-blotting. When immobilized, the proteo-probe also bound soluble UV-irradiated DNA in ELISA-like and DNA pull-down assays. In vitro, the DDB2 proteo-probe preferentially bound 6-4-photoproducts [(6-4)PPs] rather than cyclobutane pyrimidine dimers (CPDs). We followed UV-damage repair by cyto-chemistry in cells fixed at different time after UV irradiation, using either the DDB2 proteo-probe or antibodies against CPDs, or (6-4)PPs. The signals obtained with the DDB2 proteo-probe and with the antibody against (6-4)PPs decreased in a nearly identical manner. Since (6-4)PPs are repaired only by nucleotide excision repair (NER), our results strongly suggest the DDB2 proteo-probe hybridizes to DNA containing (6-4)PPs and allows monitoring of their removal during NER. We discuss the general use of purified DRCs as probes, in lieu of antibodies, to recognize and monitor DNA damage and repair

Studies of local and global properties of interactome networks

Classical genetic approaches have successfully assigned functional descriptors to thousands of genes across many species. However, daunting challenges remain ahead to associate genotype-phenotype relationships considering that rarely is a gene responsible for a single function. The central hypothesis of systems biology considers that complex and intricate networks of interacting genes and macromolecules, interactomes, underlie cellular functions. Here, we describe efforts to experimentally chart the first binary proteome-scale systematic protein-protein interactome network map for a plant. Through an empirical framework, we demonstrate that the resulting dataset is of similar quality to well-documented interactions from the literature. We then describe an experimental strategy based on reference sets to standardized experimental methods for quality control of binary interactome data sets. Finally, we explore three types of interactome network alterations that can help understand interactome function and help assign genotype-phenotype relationships: (1) engineered interaction-specific perturbation, (2) natural pathogen perturbation and, (3) perturbations of interaction through rewiring at the scale of evolution. We show that specific phenotypes can be associated to specific interaction loss.Les approches génétiques classiques ont permis l’attribution de descripteurs fonctionels à des milliers de gènes pour de nombreuses espèces. Cependant, l’identification de toutes les relations génotype-phénotype représente toujours un défi de taille, particulièrement parce qu’il apparait clair que rarement un gène est-il responsable d’une seule fonction biologique. L’hypothèse centrale de la biologie des systèmes propose que des réseaux denses et complexes, composés de gènes et macromolécules en interactions, ou interactomes, sous-tendent les fonctions cellulaires. Nous décrivons nos travaux pour établir, de manière expérimentale et systématique, à l’échelle du protéome entier, la première carte de l’interactome d’une plante. Nous démontrons, grâce à un cadre empirique structuré, que l’ensemble des données résultant est de qualité équivalente aux interactions bien documentées de la litérature. Nous décrivons ensuite une stratégie expérimentale basée sur des référentiels d’interactions, pour standardiser les méthodes de controle de qualité des données d’interactomes binaires. Enfin, nous explorons trois types d’altérations de réseaux qui peuvent permettre une meilleure compréhension du fonctionnement des interactomes et ainsi permettre l’établissement de relations génotype-phénotype: (1) ingénierie de perturbation d’interactions spécifiques, (2) perturbations naturelles par des pathogènes, et (3) remaniement d’interactions à l’échelle de l’évolution. Nous démontrons que des phénotypes spécifiques peuvent être associés à des pertes d’interactions spécifiques.(DOCSC03) -- FUNDP, 201

Protein-protein interactions and networks: forward and reverse edgetics.

Phenotypic variations of an organism may arise from alterations of cellular networks, ranging from the complete loss of a gene product to the specific perturbation of a single molecular interaction. In interactome networks that are modeled as nodes (macromolecules) connected by edges (interactions), these alterations can be thought of as node removal and edge-specific or "edgetic" perturbations, respectively. Here we present two complementary strategies, forward and reverse edgetics, to investigate the phenotypic outcomes of edgetic perturbations of binary protein-protein interaction networks. Both approaches are based on the yeast two-hybrid system (Y2H). The first allows the determination of the interaction profile of proteins encoded by alleles with known phenotypes to identify edgetic alleles. The second is used to directly isolate edgetic alleles for subsequent in vivo characterization

A purified DDB2 protein complex can be used to detect UV-induced DNA damage.

<p>(<b>A</b>) Experimental strategy to prepare the DDB2 proteo-probe. (<b>B</b>) Signal obtained by hybridization of the DDB2 proteo-probe onto fibroblasts with or without damaging treatments. Hybridized DDB2 proteo-probe is revealed by anti-HA immunofluorescence. Nuclei are visualized by DAPI staining. Nuclei are delineated based on DAPI staining and using CellProfiler <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085896#pone.0085896-Carpenter1" target="_blank">[26]</a>.</p

The decrease of DDB2 proteo-probe and 6-4 PP signals over time are nearly identical.

<p>(<b>A</b>) Typical signals after UV damage observed <i>in situ</i> with the DDB2 proteo-probe, an anti-CPD antibody, or an anti-(6-4)PP antibody. Nuclei are delineated based on DAPI staining and using CellProfiler. (<b>B</b>) The DDB2 proteo-probe signal decreases exponentially with time. Average signal per nucleus normalized to signal at 5 minutes. Red dashed curve: one phase exponential decay fit calculated with a non-linear least square method (R² = 0.86). (<b>C</b>) The anti-(6-4)PP signal decreases exponentially with time. Average signal per nucleus normalized to signal at 5 minutes. Blue dashed curve: one phase exponential decay fit calculated with a non-linear least square method (R² = 0.83). (<b>D</b>) The anti-CPD signal remains constant over a two hour period. Average signal per nucleus normalized to signal at 5 minutes. Black dashed line: linear fit on the α-CPD signal (R² = 0.18). (<b>B</b>), (<b>C</b>), and (<b>D</b>): cells were irradiated with UV-C (10 J/m²). The average of three replicas is shown. Each replica represents an average of at least 60 cells. Error bars: s.e.m. (<b>E</b>) A single one phase exponential decay model summarizes the kinetic of (6-4)PPs removal <i>in situ</i>. The single model is based on the decay fits obtained with DDB2 proteo-probe and anti-(6-4)PP data. The grey band represents the area enclosing the true decay curve with 99% confidence. The dotted line indicates the predicted half-life (<i>t</i>_1/2) of (6-4)PPs <i>in situ</i> after UV irradiation.</p

The DDB2 proteo-probe recognizes 6-4-photoproducts <i>in vitro</i>.

<p>(<b>A</b>) The DDB2 proteo-probe signal increases linearly with fluence (J/m²). Fibroblasts were irradiated with different doses of UV-C. Each point is an average of three replicas. Each replica represents an average of at least 60 cells. Dashed line: linear fit (R² = 0.94). Error bars: s.e.m. (<b>B</b>) The DDB2 proteo-probe signal is DNA-dependent. Fibroblasts were irradiated with UV-C (10 J/m²), and untreated or treated with DNase. Nuclei are visualized by DAPI staining. (<b>C</b>) The DDB2 proteo-probe signal can be competed with UV-treated plasmid DNA. Fibroblasts and plasmid DNA were irradiated with UV-C (10 J/m² and 300 J/m², respectively). The DDB2 proteo-probe was incubated with plasmid DNA prior to hybridization onto irradiated fibroblasts. Dashed line: no plasmid control proteo-probe signal level. Each point is an average of three replicas. Each replica represents an average of at least 400 cells. Error bars: s.e.m. (<b>D</b>) The DDB2 proteo-probe binds preferentially to 6-4-photoproducts [(6-4)PP] over cyclobutane pyrimidine dimers (CPD). The DDB2 proteo-probe was immobilized on agarose beads, and incubated with the DNA restriction fragments of a plasmid containing, or not, a unique lesion [(6-4)PP or CPD]. The average ratio of the amount of lesion-containing over lesion-free DNA fragments bound to the proteo-probe is shown (<i>n</i> = 3). Error bars: s.e.m.</p