EDGEdb: a transcription factor-DNA Interaction database for the analysis of C. elegans differential gene expression

BACKGROUND: Transcription regulatory networks are composed of protein-DNA interactions between transcription factors and their target genes. A long-term goal in genome biology is to map protein-DNA interaction networks of all regulatory regions in a genome of interest. Both transcription factor -and gene-centered methods can be used to systematically identify such interactions. We use high-throughput yeast one-hybrid assays as a gene-centered method to identify protein-DNA interactions between regulatory sequences (e.g. gene promoters) and transcription factors in the nematode Caenorhabditis elegans. We have already mapped several hundred protein-DNA interactions and analyzed the transcriptional consequences of some by examining differential gene expression of targets in the presence or absence of an upstream regulator. The rapidly increasing amount of protein-DNA interaction data at a genome scale requires a database that facilitates efficient data storage, retrieval and integration. DESCRIPTION: Here, we report the implementation of a C. elegans differential gene expression database (EDGEdb). This database enables the storage and retrieval of protein-DNA interactions and other data that relate to differential gene expression. Specifically, EDGEdb contains: i) sequence information of regulatory elements, including gene promoters, ii) sequence information of all 934 predicted transcription factors, their DNA binding domains, and, where available, their dimerization partners and consensus DNA binding sites, iii) protein-DNA interactions between regulatory elements and transcription factors, and iv) expression patterns conferred by regulatory elements, and how such patterns are affected by interacting transcription factors. CONCLUSION: EDGEdb provides a protein-DNA -and protein-protein interaction resource for C. elegans transcription factors and a framework for similar databases for other organisms. The database is available at

Protein Kinase CK2 Mutants Defective in Substrate Recognition PURIFICATION AND KINETIC ANALYSIS

Five mutants of protein kinase CK2 α subunit in which altogether 14 basic residues were singly to quadruply replaced by alanines (K74A,K75A,K76A,K77A; K79A, R80A,K83A; R191A,R195A,K198A; R228A; and R278A, K279A,R280A) have been purified to near homogeneity either as such or after addition of the recombinant β subunit. By this latter procedure five mutated tetrameric holoenzymes were obtained as judged from their subunit composition, sedimentation coefficient on sucrose gradient ultracentrifugation, and increased activity toward a specific peptide substrate as compared with the isolated α subunits. The kinetic constants and the phosphorylation efficiencies (Vmax/Km) of all the mutants with the parent peptide RRRADDSDDDDD and a series of derivatives, in which individual aspartic acids were replaced by alanines, have been determined. Three mutants, namely K74A,K75A,K76A,K77A; K79A,R80A, K83A; and R191A,R195A,K198A display dramatically lower phosphorylation efficiency and 8-50-fold higher Km values with the parent peptide, symptomatic of reduced attitude to bind the peptide substrate as compared with CK2 wild type. Such differences either disappear or are attenuated if the mutants R191A,R195A, K198A; K79A,R80A,K83A; and K74A,K75A,K76A,K77A are assayed with the peptides RRRADDSADDDD, RRRADDSDDADD, and RRRADDSDDDAA, respectively. In contrast, the phosphorylation efficiencies of the other substituted peptides decrease more markedly with these mutants than with CK2 wild type. These data show that one or more of the basic residues clustered in the 191-198, 79-83, and 74-77 sequences are implicated in the recognition of the acidic determinants at positions +1, +3, and +4/+5, respectively, and that if these residues are mutated, the relevance of the other acidic residues surrounding serine is increased. In contrast the other two mutants, namely R228A and R278A,K279A, R280A, display with all the peptides Vmax values higher than CK2 wild type, counterbalanced however by somewhat higher Kmvalues. It can be concluded from these data that all the five mutations performed are compatible with the reconstitution of tetrameric holoenzyme, but all of them influence the enzymatic efficiency of CK2 to different extents. Although the basic residues mutated in the 74-77, 79-83, and 191-198 sequences are clearly implicated in substrate recognition by interacting with acidic determinants at variable positions downstream from serine, the other basic residues seem to play a more elusive and/or indirect role in catalysis

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

Key words. Phosphatases, cdc25C, S-phase, Human Cells

International audienceIn view of the common regulatory mechanism that induces transcription of the mitotic phosphatase cdc25C and cyclin A at the beginning of S-phase, we investigated whether cdc25C was required for S-phase transit. Here, we show that in both nontransformed human fibroblasts and HeLa cells, cdc25C protein levels significantly increased concomitant with S-phase onset and cyclin A synthesis. Activity measurements on immunoprecipitates from synchronized HeLa cells revealed a sharp rise in cdc25C-associated phosphatase activity that coincided with S-phase. Microinjection of various antisense-cdc25C molecules led to inhibition of DNA synthesis in both HeLa cells and human fibroblasts. Furthermore, transfection of small interfering RNA directed against cdc25C specifically depleted cdc25C in HeLa cells without affecting cdc25A or cdc25B levels. Cdc25C RNA interference was also accompanied by S-phase inhibition. In cells depleted of cdc25C by antisense or siRNA, normal cell cycle progression could be re-established through microinjection of wild-type cdc25C protein but not inactive C377S mutant protein. Taken together, these results show that cdc25C not only plays a role at the G2/M transition but also in the modulation of DNA replication where its function is distinct from that of cdc25A

ICeE an interface for C. elegans experiments

International audienceAn increasing number of laboratories are using the COPAS Biosort TM to implement high-throughput approaches to tackle diverse biological problems. While providing a powerful tool for generating quantitative data, the utility of the Biosort is currently limited by the absence of resources for data management. We describe a simple electronic database designed to allow easy storage and retrieval of Biosort data for C. elegans, but that has a wide potential application for organizing electronic files and data sets. ICeE is an Open Source application. The code and accompanying documentation are freely available via the web a

Identification of Potential Interaction Networks Using Sequence-Based Searches for Conserved Protein-Protein Interactions or “Interologs”

Protein interaction maps have provided insight into the relationships among the predicted proteins of model organisms for which a genome sequence is available. These maps have been useful in generating potential interaction networks, which have confirmed the existence of known complexes and pathways and have suggested the existence of new complexes and or crosstalk between previously unlinked pathways. However, the generation of such maps is costly and labor intensive. Here, we investigate the extent to which a protein interaction map generated in one species can be used to predict interactions in another species

High-Throughput Expression of C. elegans Proteins

Proteome-scale studies of protein three-dimensional structures should provide valuable information for both investigating basic biology and developing therapeutics. Critical for these endeavors is the expression of recombinant proteins. We selected Caenorhabditis elegans as our model organism in a structural proteomics initiative because of the high quality of its genome sequence and the availability of its ORFeome, protein-encoding open reading frames (ORFs), in a flexible recombinational cloning format. We developed a robotic pipeline for recombinant protein expression, applying the Gateway cloning/expression technology and utilizing a stepwise automation strategy on an integrated robotic platform. Using the pipeline, we have carried out heterologous protein expression experiments on 10,167 ORFs of C. elegans. With one expression vector and one Escherichia coli strain, protein expression was observed for 4854 ORFs, and 1536 were soluble. Bioinformatics analysis of the data indicates that protein hydrophobicity is a key determining factor for an ORF to yield a soluble expression product. This protein expression effort has investigated the largest number of genes in any organism to date. The pipeline described here is applicable to high-throughput expression of recombinant proteins for other species, both prokaryotic and eukaryotic, provided that ORFeome resources become available