Nerve injury induces a Gem-GTPase-dependent downregulation of P/Q-type Ca2+ channels contributing to neurite plasticity in dorsal root ganglion neurons.

Small RGK GTPases, Rad, Gem, Rem1, and Rem2, are potent inhibitors of high-voltage-activated (HVA) Ca(2+) channels expressed in heterologous expression systems. However, the role of this regulation has never been clearly demonstrated in the nervous system. Using transcriptional analysis, we show that peripheral nerve injury specifically upregulates Gem in mice dorsal root ganglia. Following nerve injury, protein expression was increased in ganglia and peripheral nerve, mostly under its phosphorylated form. This was confirmed in situ and in vitro in dorsal root ganglia sensory neurons. Knockdown of endogenous Gem, using specific small-interfering RNA (siRNA), increased the HVA Ca(2+) current only in the large-somatic-sized neurons. Combining pharmacological analysis of the HVA Ca(2+) currents together with Gem siRNA-transfection of larger sensory neurons, we demonstrate that only the P/Q-type Ca(2+) channels were enhanced. In vitro analysis of Gem affinity to various CaVßx-CaV2.x complexes and immunocytochemical studies of Gem and CaVß expression in sensory neurons suggest that the specific inhibition of the P/Q channels relies on both the regionalized upregulation of Gem and the higher sensitivity of the endogenous CaV2.1-CaVß4 pair in a subset of sensory neurons including the proprioceptors. Finally, pharmacological inhibition of P/Q-type Ca(2+) current reduces neurite branching of regenerating axotomized neurons. Taken together, the present results indicate that a Gem-dependent P/Q-type Ca(2+) current inhibition may contribute to general homeostatic mechanisms following a peripheral nerve injury.

Characterization of the first honeybee Ca²âº channel subunit reveals two novel species- and splicing-specific modes of regulation of channel inactivation.

The honeybee is a model system to study learning and memory, and Ca(2+) signals play a key role in these processes. We have cloned, expressed, and characterized the first honeybee Ca(2+) channel subunit. We identified two splice variants of the Apis CaVß Ca(2+) channel subunit (Am-CaVß) and demonstrated expression in muscle and neurons. Although AmCaVß shares with vertebrate CaVß subunits the SH3 and GK domains, it beholds a unique N terminus that is alternatively spliced in the first exon to produce a long (a) and short (b) variant. When expressed with the CaV2 channels both, AmCaVßa and AmCaVßb, increase current amplitude, shift the voltage-sensitivity of the channel, and slow channel inactivation as the vertebrate CaVß2a subunit does. However, as opposed to CaVß2a, slow inactivation induced by Am-CaVßa was insensitive to palmitoylation but displayed a unique PI3K sensitivity. Inactivation produced by the b variant was PI3K-insensitive but staurosporine/H89-sensitive. Deletion of the first exon suppressed the sensitivity to PI3K inhibitors, staurosporine, or H89. Recording of Ba(2+) currents in Apis neurons or muscle cells evidenced a sensitivity to PI3K inhibitors and H89, suggesting that both AmCaVß variants may be important to couple cell signaling to Ca(2+) entry in vivo. Functional interactions with phospho-inositide and identification of phosphorylation sites in AmCaVßa and AmCaVßb N termini, respectively, suggest that AmCaVß splicing promoted two novel and alternative modes of regulation of channel activity with specific signaling pathways. This is the first description of a splicing-dependent kinase switch in the regulation of Ca(2+) channel activity by CaVß subunit.

Construction and use of gene expression covariation matrix.

BACKGROUND: One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. RESULTS: We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I), decreased (D), or not changed (N). As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1)/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM) are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their strings of symbols. CONCLUSION: This new method, applied to four different large data sets, has allowed us to construct distinct covariation matrices with similar properties. We have also developed a technique to translate these covariation networks into graphical 3D representations and found that the local assignation of the probe sets was conserved across the four chip set models used which encompass three different species (humans, mice, and rats). The application of adapted clustering methods succeeded in delineating six conserved functional regions that we characterized using Gene Ontology information.

Chromosomal distribution of PcG proteins during Drosophila development.

Polycomb group (PcG) proteins are able to maintain the memory of silent transcriptional states of homeotic genes throughout development. In Drosophila, they form multimeric complexes that bind to specific DNA regulatory elements named PcG response elements (PREs). To date, few PREs have been identified and the chromosomal distribution of PcG proteins during development is unknown. We used chromatin immunoprecipitation (ChIP) with genomic tiling path microarrays to analyze the binding profile of the PcG proteins Polycomb (PC) and Polyhomeotic (PH) across 10 Mb of euchromatin. We also analyzed the distribution of GAGA factor (GAF), a sequence-specific DNA binding protein that is found at most previously identified PREs. Our data show that PC and PH often bind to clustered regions within large loci that encode transcription factors which play multiple roles in developmental patterning and in the regulation of cell proliferation. GAF co-localizes with PC and PH to a limited extent, suggesting that GAF is not a necessary component of chromatin at PREs. Finally, the chromosome-association profile of PC and PH changes during development, suggesting that the function of these proteins in the regulation of some of their target genes might be more dynamic than previously anticipated.

Gene expression profiling of the effects of intravenous immunoglobulin in human whole blood.

Intravenous immunoglobulin (IVIG) is involved in many complex mechanisms that act in synergy including expression and function of Fc receptors, complement activation, the cytokine network, interaction with the anti-idiotypic network and modulation of B and T cell activation. To gain insight into the early effects of IVIG on this broad range of activities at the gene level we performed DNA microarray analysis. Human whole blood was incubated in vitro for 4 h followed by extraction of RNA which was hybridized to a chip containing 8793 genes. About 75 upregulated genes and 21 downregulated genes were identified using a cut off for the false discovery rate of 5%. These genes are associated with a wide range of cellular immune functions in line with the broad mechanism of action of IVIG. A striking upregulation of a series of genes coding for chemokines was measured. This finding was confirmed at the protein level as pharmacologically relevant concentrations of CXCL9 and CXCL10 were measured in serum. Interestingly, IVIG shows a partial overlap of its gene expression program with lipopolysaccharide. Our data suggests multiple hypotheses regarding the pharmacology of IVIG that must be validated by complementary studies.

Clustering methods for analyzing large data sets: gonad development, a study case.

With the development of data set repositories, it is now possible to collate high numbers of related results by gathering data from experiments carried out in different laboratories and addressing similar questions or using a single type of biological material under different conditions. To address the challenge posed by the heterogeneous nature of multiple data sources, this chapter presents several methods used routinely for assessing the quality of data (i.e., reproducibility of replicates and similarity between experimental points obtained under identical or similar biological conditions). As gene clustering on large data sets is not straightforward, this chapter also presents a rapid gene clustering method that involves translating variation profiles from an ordered set of comparisons into chains of symbols. In addition, it shows that lists of genes assembled based on the presence of a common term in their functional description can be used to find the most informative comparisons and to construct from them exemplar chains of symbols that are useful for clustering similar genes. Finally, this symbolic approach is extended to the overall set of biological conditions under study and shows how the resultant collection of variation profiles can be used to construct transcriptional networks, which in turn can be used as powerful tools for gene clustering.

Mapping the distribution of chromatin proteins by ChIP on chip.

The ChIP on chip method combines chromatin immunoprecipitation (ChIP) with hybridization on DNA microarrays (chip). The ChIP technique allows one to obtain a DNA sample enriched in sequences bound by transcription factors or chromatin-associated proteins. Usually, ChIP is used to test whether specific candidate sequences are bound by a transcription factor, but microarrays are a powerful tool that allows testing large pools of sequences at once. This chapter presents the pipeline of a ChIP on chip method that can be applied to map the binding sites of chromatin-associated proteins along Drosophila chromosomes at different developmental stages. This chapter provides protocols for ChIP, for quality control tests of ChIP samples, for microarray design, for hybridization of the ChIP samples onto microarrays, and for initial analysis of the data. In addition, this chapter discusses the most important steps in each of the protocols as well as the importance of bioinformatic analysis in order to extract valuable biological information from the data sets.

Binding of Kif23-iso1/CHO1 to 14-3-3 is regulated by sequential phosphorylations at two LATS kinase consensus sites.

Kif23 kinesin is an essential actor of cytokinesis in animals. It exists as two major isoforms, known as MKLP1 and CHO1, the longest of which, CHO1, contains two HXRXXS/T NDR/LATS kinase consensus sites. We demonstrate that these two sites are readily phosphorylated by NDR and LATS kinases in vitro, and this requires the presence of an upstream -5 histidine residue. We further show that these sites are phosphorylated in vivo and provide evidence revealing that LATS1,2 participate in the phosphorylation of the most C-terminal S814 site, present on both isoforms. This S814 phosphosite was previously reported to constitute a 14-3-3 binding site, which plays a role in Kif23 clustering during cytokinesis. Surprisingly, we found that phosphorylation of the upstream S716 NDR/LATS consensus site, present only in the longest Kif23 isoform, is required for efficient phosphorylation at S814, thus revealing sequential phosphorylation at these two sites, and differential regulation of Kif23-14-3-3 interaction for the two Kif23 isoforms. Finally, we provide evidence that Kif23 is largely unphosphorylated on S814 in post-abscission midbodies, making this Kif23 post-translational modification a potential marker to probe these structures.

Lysosomes and unfolded protein response, determinants of differential resistance of melanoma cells to vinca alkaloids.

On account of its strong ability to become chemoresistant after a primary response to drugs, malignant melanoma (MM) remains a therapeutic challenge. This study focuses on acquired resistance to vinca alkaloids (VAs) using VA-resistant MM cell lines (CAL1R-VCR, CAL1R-VDS, and CAL1R-VRB), established by long-term continuous exposure of parental CAL1-wt cells to vincristine (VCR), vindesine (VDS), or vinorelbine (VRB), respectively. Transcriptomic profiling using rma and rdam methods led to distinguish two cell groups: CAL1R-VCR and CAL1R-VDS, CAL1R-VRB, and CAL1-wt. mgsa of the specifically altered genes in the first group evidenced the GO terms 'lysosomal lumen' and 'vacuolar lumen' linked to underexpressed genes, and 'endoplasmic reticulum (ER) stress response' associated with overexpressed genes. A specific reduction of lysosomal enzymes, independent of acidic vacuole organelle (AVO) turnover, was observed (LTG probe) in CAL1R-VCR and CAL1R-VDS cells. It was associated with the specific lowering of cathepsin B and L, known to be involved in the lysosomal pathway of apoptosis. Confirming gene profiling, the same groups (CAL1R-VCR and CAL1R-VDS, CAL1-wt and CAL1R-VRB) could be distinguished regarding the VA-mediated changes on mean size areas and on acidic compartment volumes. These two parameters were reduced in CAL1R-VCR and CAL1R-VDS cells, suggesting a smaller AVO accumulation and thus a reduced sensitivity to lysosomal membrane permeabilization-mediated apoptosis. In addition, 'ER stress response' inhibition by tauroursodeoxycholic acid induced a higher VA sensitization of the first cell group. In conclusion, lysosomes and unfolded protein response could be key determinants of the differential resistance of MM to VAs.

Regulation of neuronal high-voltage activated Ca(V)2 Ca(2+) channels by the small GTPase RhoA.

High-Voltage-Activated (HVA) Ca(2+) channels are known regulators of synapse formation and transmission and play fundamental roles in neuronal pathophysiology. Small GTPases of Rho and RGK families, via their action on both cytoskeleton and Ca(2+) channels are key molecules for these processes. While the effects of RGK GTPases on neuronal HVA Ca(2+) channels have been widely studied, the effects of RhoA on the HVA channels remains however elusive. Using heterologous expression in Xenopus laevis oocytes, we show that RhoA activity reduces Ba(2+) currents through CaV2.1, CaV2.2 and CaV2.3 Ca(2+) channels independently of CaVß subunit. This inhibition occurs independently of RGKs activity and without modification of biophysical properties and global level of expression of the channel subunit. Instead, we observed a marked decrease in the number of active channels at the plasma membrane. Pharmacological and expression studies suggest that channel expression at the plasma membrane is impaired via a ROCK-sensitive pathway. Expression of constitutively active RhoA in primary culture of spinal motoneurons also drastically reduced HVA Ca(2+) current amplitude. Altogether our data revealed that HVA Ca(2+) channels regulation by RhoA might govern synaptic transmission during development and potentially contribute to pathophysiological processes when axon regeneration and growth cone kinetics are impaired.

Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data.

BACKGROUND: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals between two biological conditions. RESULTS: We describe a new method, Rank Difference Analysis of Microarrays (RDAM), which estimates the total number of truly varying genes and assigns a p-value to each signal variation. Information on a group of differentially expressed genes includes the sensitivity and the false discovery rate. We demonstrate the feasibility and efficiency of our approach by applying it to a large synthetic expression data set and to a biological data set obtained by comparing vegetatively-growing wild type and tor2-mutant yeast strains. In both cases we observed a significant improvement of the power of analysis when our method is compared to another popular nonparametric method. CONCLUSIONS: This study provided a valuable new statistical method to analyze microarray data. We conclude that the good quality of the results obtained by RDAM is mainly due to the quasi-perfect equalization of variation distribution, which is related to the standardization procedure used and to the measurement of variation by rank difference.

Estimating the similarity of alternative Affymetrix probe sets using transcriptional networks.

BACKGROUND: The usefulness of the data from Affymetrix microarray analysis depends largely on the reliability of the files describing the correspondence between probe sets, genes and transcripts. Particularly, when a gene is targeted by several probe sets, these files should give information about the similarity of each alternative probe set pair. Transcriptional networks integrate the multiple correlations that exist between all probe sets and supply much more information than a simple correlation coefficient calculated for two series of signals. In this study, we used the PSAWN (Probe Set Assignment With Networks) programme we developed to investigate whether similarity of alternative probe sets resulted in some specific properties. FINDINGS: PSAWNpy delivered a full textual description of each probe set and information on the number and properties of secondary targets. PSAWNml calculated the similarity of each alternative probe set pair and allowed finding relationships between similarity and localisation of probes in common transcripts or exons. Similar alternative probe sets had very low negative correlation, high positive correlation and similar neighbourhood overlap. Using these properties, we devised a test that allowed grouping similar probe sets in a given network. By considering several networks, additional information concerning the similarity reproducibility was obtained, which allowed defining the actual similarity of alternative probe set pairs. In particular, we calculated the common localisation of probes in exons and in known transcripts and we showed that similarity was correctly correlated with them. The information collected on all pairs of alternative probe sets in the most popular 3' IVT Affymetrix chips is available in tabular form at http://bns.crbm.cnrs.fr/download.html. CONCLUSIONS: These processed data can be used to obtain a finer interpretation when comparing microarray data between biological conditions. They are particularly well adapted for searching 3' alternative poly-adenylation events and can be also useful for studying the structure of transcriptional networks. The PSAWNpy, (in Python) and PSAWNml (in Matlab) programmes are freely available and can be downloaded at http://code.google.com/p/arraymatic. Tutorials and reference manuals are available at BMC Research Notes online (Additional file 1) or from http://bns.crbm.cnrs.fr/softwares.html.

The Ume6 regulon coordinates metabolic and meiotic gene expression in yeast.

The Ume6 transcription factor in yeast is known to both repress and activate expression of diverse genes during growth and meiotic development. To obtain a more complete profile of the functions regulated by this protein, microarray analysis was used to examine transcription in wild-type and ume6Delta diploids during vegetative growth in glucose and acetate. Two different genetic backgrounds (W303 and SK1) were examined to identify a core set of strain-independent Ume6-regulated genes. Among genes whose expression is controlled by Ume6 in both backgrounds, 82 contain homologies to the Ume6-binding site (URS1) and are expected to be directly regulated by Ume6. The vast majority of those whose functions are known participate in carbon/nitrogen metabolism and/or meiosis. Approximately half of the Ume6 direct targets are induced during meiosis, with most falling into the early meiotic expression class (cluster 4), and a smaller subset in the middle and later classes (clusters 5-7). Based on these data, we propose that Ume6 serves a unique role in diploid cells, coupling metabolic responses to nutritional cues with the initiation and progression of meiosis. Finally, expression patterns in the two genetic backgrounds suggest that SK1 is better adapted to respiration and W303 to fermentation, which may in part account for the more efficient and synchronous sporulation of SK1.