LitInspector: literature and signal transduction pathway mining in PubMed abstracts

LitInspector is a literature search tool providing gene and signal transduction pathway mining within NCBI's PubMed database. The automatic gene recognition and color coding increases the readability of abstracts and significantly speeds up literature research. A main challenge in gene recognition is the resolution of homonyms and rejection of identical abbreviations used in a ‘non-gene’ context. LitInspector uses automatically generated and manually refined filtering lists for this purpose. The quality of the LitInspector results was assessed with a published dataset of 181 PubMed sentences. LitInspector achieved a precision of 96.8%, a recall of 86.6% and an F-measure of 91.4%. To further demonstrate the homonym resolution qualities, LitInspector was compared to three other literature search tools using some challenging examples. The homonym MIZ-1 (gene IDs 7709 and 9063) was correctly resolved in 87% of the abstracts by LitInspector, whereas the other tools achieved recognition rates between 35% and 67%. The LitInspector signal transduction pathway mining is based on a manually curated database of pathway names (e.g. wingless type), pathway components (e.g. WNT1, FZD1), and general pathway keywords (e.g. signaling cascade). The performance was checked for 10 randomly selected genes. Eighty-two per cent of the 38 predicted pathway associations were correct. LitInspector is freely available at http://www.litinspector.org/

The phosphoproteome of toll-like receptor-activated macrophages

First global and quantitative analysis of phosphorylation cascades induced by toll-like receptor (TLR) stimulation in macrophages identifies nearly 7000 phosphorylation sites and shows extensive and dynamic up-regulation and down-regulation after lipopolysaccharide (LPS).In addition to the canonical TLR-associated pathways, mining of the phosphorylation data suggests an involvement of ATM/ATR kinases in signalling and shows that the cytoskeleton is a hotspot of TLR-induced phosphorylation.Intersecting transcription factor phosphorylation with bioinformatic promoter analysis of genes induced by LPS identified several candidate transcriptional regulators that were previously not implicated in TLR-induced transcriptional control

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

NMR assignment of human HSP90 N-terminal domain bound to a long residence time resorcinol ligand

International audienceHSP90 is a major molecular chaperone that helps both folding and stabilization of various client proteins often implicated in growth control and cell survival such as kinases and transcription factors. However, among HSP90 clients are also found numerous oncoproteins and, through its assistance to them, HSP90 has consequently been reported as a promising anticancer target. Several ligand chemotypes, including resorcinol type ligands, were found to inhibit HSP90, most of them in an ATP competitive manner. Binding of some of these ligands modify significantly the NMR spectrum of the HSP90 ATP binding domain compared to the apo protein spectrum, hampering assignment transfer from the previously assigned human HSP90 apo state. Here we report the assignment of the 1HN, 15N, 13C', 13Cα, 13Cβ, 1Hmethyl, and 13Cmethyl chemical shifts of the 29 kDa HSP90 N-terminal domain bound to a long residence time resorcinol type inhibitor: 5-[4-(2-Fluoro-phenyl)-5-oxo-4,5-dihydro-1H-[1,2,4]triazol-3-yl]-N-furan-2-ylmethyl-2,4-dihydroxy-N-methyl-benzamide. 92% of the backbone resonances and 100% of the [1H, 13C]-resonances of Aβ, Mε, Tγ, Lδ2, Vγ2 and Iδ1 methyl groups were successfully assigned, including for the first time the assignment of the segment covering the nucleotide/drug binding site. Secondary structure predictions based on the NMR assignment reveal a structural rearrangement of HSP90 N-terminal domain upon ligand binding. The long residence time ligand induces the formation of a continuous helix covering the ligand binding site of HSP90 N-terminal domain accounting for the large differences observed in the NMR spectra between the apo and bound proteins

In Silico Prediction of Scaffold/Matrix Attachment Regions in Large Genomic Sequences

Scaffold/matrix attachment regions (S/MARs) are essential regulatory DNA elements of eukaryotic cells. They are major determinants of locus control of gene expression and can shield gene expression from position effects. Experimental detection of S/MARs requires substantial effort and is not suitable for large-scale screening of genomic sequences. In silico prediction of S/MARs can provide a crucial first selection step to reduce the number of candidates. We used experimentally defined S/MAR sequences as the training set and generated a library of new S/MAR-associated, AT-rich patterns described as weight matrices. A new tool called SMARTest was developed that identifies potential S/MARs by performing a density analysis based on the S/MAR matrix library (http://www.genomatix.de/cgi-bin/smartest_pd/smartest.pl). S/MAR predictions were evaluated by using six genomic sequences from animal and plant for which S/MARs and non-S/MARs were experimentally mapped. SMARTest reached a sensitivity of 38% and a specificity of 68%. In contrast to previous algorithms, the SMARTest approach does not depend on the sequence context and is suitable to analyze long genomic sequences up to the size of whole chromosomes. To demonstrate the feasibility of large-scale S/MAR prediction, we analyzed the recently published chromosome 22 sequence and found 1198 S/MAR candidates

Proton NMR Studies of Transforming and Nontransforming H−ras p21 Mutants

One− and two−dimensional nuclear magnetic resonance spectroscopy (1D and 2D NMR) and site−directed mutagenesis were used to study the influence of mutations on the conformation of the H−ras oncogene product p21. No severe structural differences between the different mutants, whether they were transforming or nontransforming, could be detected. Initially, selective incorporation of 3,5−deuterated tyrosyl residues into p21 and 2D NMR were used to identify the resonances representing the spin systems of the imidazole rings of the three histidyl residues in the protein, of six of the nine tyrosyl rings, and of four of the five phenylalanyl rings. The spin systems of the phenyl rings of Phe28, Phe78, and Pheg2 could be assigned by using mutant proteins, since no severe structure−induced spectral changes in the aromatic part of the spectra of the mutant proteins were detected. Sequence−specific assignments of the histidine imidazole resonances could be obtained by comparison of the distance information obtained by nuclear Overhauser enhancement spectroscopy (NOESY) experiments with the crystal structure. The change in the chemical shift values of the HI' proton and the a−phosphate of the bound GDP in the NMR spectra of the p21(F28L) mutant and the 28−fold increase in the GDP dissociation rate constants of this mutant suggest a strong interaction between Phe28 and the p21−bound nucleotide. In solution, the p21−bound GDP.Mg2+ has an anti conformation, and the phenyl ring of Phe28 is close to the ribose of the bound GDP.Mg2