The crystal structure of gankyrin, an oncoprotein found in complexes with cyclin-dependent kinase 4, a 19 S proteasomal ATPase regulator, and the tumor suppressors Rb and p53

Gankyrin is a 25-kDa hepatocellular carcinoma-associated protein that mediates protein-protein interactions in cell cycle control and protein degradation. It has been reported to form complexes with cyclin-dependent kinase 4, retinoblastoma protein, the S6b ATPase subunit of the 19 S regulator of the 26 S proteasome, and Mdm2, an E3 ubiquitin ligase involved in p53 degradation. It is the first protein described to bind both to the 26 S proteasome and to proteins in other complexes containing cyclin-dependent kinase(s) and p53 ubiquitylating activities, thus providing a mechanism for delivering cell cycle regulating machinery and ubiquitylated substrates to the proteasome for degradation. Gankyrin contains a 33-residue motif known as the ankyrin repeat that occurs five and a half to six times in the sequence. As a step toward understanding gankyrin interactions with its protein partners we have determined its three-dimensional crystal structure to 2.0-A resolution. It reveals that the entire 226-residue gankyrin polypeptide folds into seven ankyrin repeat elements. The ankyrin repeats, consisting of an antiparallel beta-hairpin followed by a perpendicularly oriented helix-loop-helix, pack side-by-side, creating an extended curved structure with a groove running across the long concave surface. Comparison with the structures of other ankyrin repeat proteins suggests that interactions with partner proteins are mediated by residues situated on this concave surface.     

DNA microarray for discrimination between pathogenic 0157:H7 EDL933 and non-pathogenic Escherichia coli strains

The primary technique currently used to detect biological agents is based on immunoassays. Although sensitive and specific, currently employed immunoassays generally rely on the detection of a single epitope, and therefore often cannot discriminate subtle strain-specific differences. Since DNA microarrays can hybridize hundreds to thousands of genomic targets simultaneously and do not rely on phenotypic expression of these genetic features for identification purposes, they have enormous potential to provide inexpensive, flexible and specific strain-specific detection and identification of pathogens. In this study, pathogenic Escherichia coli O157:H7-specific genes, non-pathogenic K12-specific genes, common E. coli genes, and negative control genes were polymerase chain reaction-amplified and spotted onto the surface of treated glass slides. After labeled bacterial cDNA samples were hybridized with probes on the microarray, specific fluorescence patterns were obtained, enabling identification of pathogenic E. coli O157:H7 and non-pathogenic E. coli K12. To test the utility of this microarray device to detect genetically engineered bacteria, E. coli BL21 (a B strain derivative with antibiotic resistance gene, ampR) and E. coli JM107 (a K12 strain derivative lacking the gene ompT) were also employed. The array successfully confirmed the strain genotypes and demonstrated that antibiotic resistance can also be detected. The ability to assess multiple data points makes this array method more efficient and accurate than a typical immunoassay, which detects a single protein product.     

DNMT1 is a component of a multiprotein DNA replication complex

DNA methylation is a major determinant of epigenetic inheritance and plays an important role in genome stability. The accurate propagation of DNA methylation patterns with cell division requires that methylation be closely coupled to DNA replication, however the precise molecular determinants of this interaction have not been defined. In the present study, we show that the predominant DNA methyltransferase species in somatic cells, DNMT1, is a component of a multiprotein DNA replication complex termed the DNA synthesome that fully supports semi-conservative DNA replication in a cell-free system. DNMT1 protein and activity were found to co-purify with the human DNA synthesome through a series of subcellular fractionation and chromatography steps, resulting in an enrichment of methyltransferase specific activity from two human cell lines. DNA methyltransferase activity co-eluted with in vitro replication activity and DNA polymerase alpha activity on sucrose density gradients suggesting that DNMT1 is a tightly bound, core component of the replication complex. The synthesome-associated pool of DNA methyltransferase exhibited both maintenance and de novo methyltransferase activity and the ratio of the two was similar to that observed in whole cell lysates and for recombinant DNMT1. These data indicate that interactions within the synthesome complex do not influence the intrinsic preference of DNMT1 for hemimethylated DNA, but suggest that newly replicated DNA may be subject to low level de novo methylation. The data indicate that DNA methylation is tightly coupled to replication through physical interaction of DNMT1 and core components of the replication machinery. The definition of the molecular interactions between DNMT1 and other proteins in the replication complex in normal and neoplastic cells will provide further insight into the regulation of DNA methylation and the mechanisms underlying the alteration of DNA methylation patterns during carcinogenesis.     

Mycobacterial Dihydrofolate Reductase Inhibitors Identified Using Chemogenomic Methods and In Vitro Validation

The lack of success in target-based screening approaches to the discovery of antibacterial agents has led to reemergence of phenotypic screening as a successful approach of identifying bioactive, antibacterial compounds. A challenge though with this route is then to identify the molecular target(s) and mechanism of action of the hits. This target identification, or deorphanization step, is often essential in further optimization and validation studies. Direct experimental identification of the molecular target of a screening hit is often complex, precisely because the properties and specificity of the hit are not yet optimized against that target, and so many false positives are often obtained. An alternative is to use computational, predictive, approaches to hypothesize a mechanism of action, which can then be validated in a more directed and efficient manner. Specifically here we present experimental validation of an in silico prediction from a large-scale screen performed against Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. The two potent anti-tubercular compounds studied in this case, belonging to the tetrahydro-1,3,5-triazin-2-amine (THT) family, were predicted and confirmed to be an inhibitor of dihydrofolate reductase (DHFR), a known essential Mtb gene, and already clinically validated as a drug target. Given the large number of similar screening data sets shared amongst the community, this in vitro validation of these target predictions gives weight to computational approaches to establish the mechanism of action (MoA) of novel screening hit.     

Systematic association of genes to phenotypes by genome and literature mining

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene–phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases.     

HOMGL-comparing genelists across species and with different accession numbers

Homology Gene List (HOMGL) is a web-based tool for comparing gene lists with different accession numbers and identifiers and between different organisms. UniGene, LocusLink, HomoloGene and Ensembl databases are utilized to map between these lists and to retrieve upstream or transcribed sequences for genes in these lists. We illustrate the use of HOMGL with respect to microarray studies and promoter analysis. AVAILABILITY: http://homgl.biologie.hu-berlin.de/     

Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm

A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH.     

Inferring Mathematical Equations Using Crowdsourcing

Crowdsourcing, understood as outsourcing work to a large network of people in the form of an open call, has been utilized successfully many times, including a very interesting concept involving the implementation of computer games with the objective of solving a scientific problem by employing users to play a game—so-called crowdsourced serious games. Our main objective was to verify whether such an approach could be successfully applied to the discovery of mathematical equations that explain experimental data gathered during the observation of a given dynamic system. Moreover, we wanted to compare it with an approach based on artificial intelligence that uses symbolic regression to find such formulae automatically. To achieve this, we designed and implemented an Internet game in which players attempt to design a spaceship representing an equation that models the observed system. The game was designed while considering that it should be easy to use for people without strong mathematical backgrounds. Moreover, we tried to make use of the collective intelligence observed in crowdsourced systems by enabling many players to collaborate on a single solution. The idea was tested on several hundred players playing almost 10,000 games and conducting a user opinion survey. The results prove that the proposed solution has very high potential. The function generated during weeklong tests was almost as precise as the analytical solution of the model of the system and, up to a certain complexity level of the formulae, it explained data better than the solution generated automatically by Eureqa, the leading software application for the implementation of symbolic regression. Moreover, we observed benefits of using crowdsourcing; the chain of consecutive solutions that led to the best solution was obtained by the continuous collaboration of several players.     

Pb-Induced Avoidance-Like Chloroplast Movements in Fronds of Lemna trisulca L.

Lead ions are particularly dangerous to the photosynthetic apparatus, but little is known about the effects of trace metals, including Pb, on regulation of chloroplast redistribution. In this study a new effect of lead on chloroplast distribution patterns and movements was demonstrated in mesophyll cells of a small-sized aquatic angiosperm Lemna trisulca L. (star duckweed). An analysis of confocal microscopy images of L. trisulca fronds treated with lead (15 μM Pb²⁺, 24 h) in darkness or in weak white light revealed an enhanced accumulation of chloroplasts in the profile position along the anticlinal cell walls, in comparison to untreated plants. The rearrangement of chloroplasts in their response to lead ions in darkness was similar to the avoidance response of chloroplasts in plants treated with strong white light. Transmission electron microscopy X-ray microanalysis showed that intracellular chloroplast arrangement was independent of the location of Pb deposits, suggesting that lead causes redistribution of chloroplasts, which looks like a light-induced avoidance response, but is not a real avoidance response to the metal. Furthermore, a similar redistribution of chloroplasts in L. trisulca cells in darkness was observed also under the influence of exogenously applied hydrogen peroxide (H₂O₂). In addition, we detected an enhanced accumulation of endogenous H₂O₂ after treatment of plants with lead. Interestingly, H₂O₂-specific scavenger catalase partly abolished the Pb-induced chloroplast response. These results suggest that H₂O₂ can be involved in the avoidance-like movement of chloroplasts induced by lead. Analysis of photometric measurements revealed also strong inhibition (but not complete) of blue-light-induced chloroplast movements by lead. This inhibition may result from disturbances in the actin cytoskeleton, as we observed fragmentation and disappearance of actin filaments around chloroplasts. Results of this study show that the mechanisms of the toxic effect of lead on chloroplasts can include disturbances in their movement and distribution pattern.