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We show that the putative N-peptide binding area in Sec1p domain 1 is important for Mso1p binding and that Mso1p can interact with Sso1p and Sso2p. Our results suggest that Mso1p mimics N-peptide binding to facilitate membrane fusion., Sec1p/Munc18 (SM) family proteins regulate SNARE complex function in membrane fusion through their interactions with syntaxins. In addition to syntaxins, only a few SM protein interacting proteins are known and typically, their binding modes with SM proteins are poorly characterized. We previously identified Mso1p as a Sec1p-binding protein and showed that it is involved in membrane fusion regulation. Here we demonstrate that Mso1p and Sec1p interact at sites of exocytosis and that the Mso1p–Sec1p interaction site depends on a functional Rab GTPase Sec4p and its GEF Sec2p. Random and targeted mutagenesis of Sec1p, followed by analysis of protein interactions, indicates that Mso1p interacts with Sec1p domain 1 and that this interaction is important for membrane fusion. In many SM family proteins, domain 1 binds to a N-terminal peptide of a syntaxin family protein. The Sec1p-interacting syntaxins Sso1p and Sso2p lack the N-terminal peptide. We show that the putative N-peptide binding area in Sec1p domain 1 is important for Mso1p binding, and that Mso1p can interact with Sso1p and Sso2p. Our results suggest that Mso1p mimics N-peptide binding to facilitate membrane fusion.

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html.

BACKGROUND: Protein trans-splicing by naturally occurring split DnaE inteins is used for protein ligation of foreign peptide fragments. In order to widen biotechnological applications of protein trans-splicing, it is highly desirable to have split inteins with shorter C-terminal fragments, which can be chemically synthesized. PRINCIPAL FINDINGS: We report the identification of new functional split sites in DnaE inteins from Synechocystis sp. PCC6803 and from Nostoc punctiforme. One of the newly engineered split intein bearing C-terminal 15 residues showed more robust protein trans-splicing activity than naturally occurring split DnaE inteins in a foreign context. During the course of our experiments, we found that protein ligation by protein trans-splicing depended not only on the splicing junction sequences, but also on the foreign extein sequences. Furthermore, we could classify the protein trans-splicing reactions in foreign contexts with a simple kinetic model into three groups according to their kinetic parameters in the presence of various reducing agents. CONCLUSION: The shorter C-intein of the newly engineered split intein could be a useful tool for biotechnological applications including protein modification, incorporation of chemical probes, and segmental isotopic labelling. Based on kinetic analysis of the protein splicing reactions, we propose a general strategy to improve ligation yields by protein trans-splicing, which could significantly enhance the applications of protein ligation by protein trans-splicing.

Background Mutations in filamin A (FLNa), an essential cytoskeletal protein with multiple binding partners, cause developmental anomalies in humans. Methodology/Principal Findings We determined the structure of the 23rd Ig repeat of FLNa (IgFLNa23) that interacts with FilGAP, a Rac-specific GTPase-activating protein and regulator of cell polarity and movement, and the effect of the three disease-related mutations on this interaction. A combination of NMR structural analysis and in silico modeling revealed the structural interface details between the C and D β-strands of the IgFLNa23 and the C-terminal 32 residues of FilGAP. Mutagenesis of the predicted key interface residues confirmed the binding constraints between the two proteins. Specific loss-of-function FLNa constructs were generated and used to analyze the importance of the FLNa-FilGAP interaction in vivo. Point mutagenesis revealed that disruption of the FLNa-FilGAP interface perturbs cell spreading. FilGAP does not bind FLNa homologs FLNb or FLNc establishing the importance of this interaction to the human FLNa mutations. Tight complex formation requires dimerization of both partners and the correct alignment of the binding surfaces, which is promoted by a flexible hinge domain between repeats 23 and 24 of FLNa. FLNa mutations associated with human developmental anomalies disrupt the binding interaction and weaken the elasticity of FLNa/F-actin network under high mechanical stress. Conclusions/Significance Mutational analysis informed by structure can generate reagents for probing specific cellular interactions of FLNa. Disease-related FLNa mutations have demonstrable effects on FLNa function.

Background The analysis of over-represented functional classes in a list of genes is one of the most essential bioinformatics research topics. Typical examples of such lists are the differentially expressed genes from transcriptional analysis which need to be linked to functional information represented in the Gene Ontology (GO). Despite the importance of this procedure, there is a little work on consistent evaluation of various GO analysis methods. Especially, there is no literature on creating benchmark datasets for GO analysis tools. Results We propose a methodology for the evaluation of GO analysis tools, which consists of creating gene lists with a selected signal level and a selected number of independent over-represented classes. The methodology starts with a real life GO data matrix, and therefore the generated datasets have similar features to real positive datasets. The user can select the signal level for over-representation, the number of independent positive classes in the dataset, and the size of the final gene list. We present the use of the effective number and various normalizations while embedding the signal to a selected class or classes and the use of binary correlation to ensure that the selected signal classes are independent with each other. The usefulness of generated datasets is demonstrated by comparing different GO class ranking and GO clustering methods. Conclusion The presented methods aid the development and evaluation of GO analysis methods as they enable thorough testing with different signal types and different signal levels. As an example, our comparisons reveal clear differences between compared GO clustering and GO de-correlation methods. The implementation is coded in Matlab and is freely available at the dedicated website http://ekhidna.biocenter.helsinki.fi/users/petri/public/POSGODA/POSGODA.html.

BackgroundWe are studying the regulation of flowering in perennial plants by using diploid wild strawberry (Fragaria vescaL.) as a model. Wild strawberry is a facultative short-day plant with an obligatory short-day requirement at temperatures above 15°C. At lower temperatures, however, flowering induction occurs irrespective of photoperiod. In addition to short-day genotypes, everbearing forms of wild strawberry are known. In 'Baron Solemacher' recessive alleles of an unknown repressor,SEASONAL FLOWERING LOCUS(SFL), are responsible for continuous flowering habit. Although flower induction has a central effect on the cropping potential, the molecular control of flowering in strawberries has not been studied and the genetic flowering pathways are still poorly understood. The comparison of everbearing and short-day genotypes of wild strawberry could facilitate our understanding of fundamental molecular mechanisms regulating perennial growth cycle in plants.ResultsWe have searched homologs for 118Arabidopsisflowering time genes fromFragariaby EST sequencing and bioinformatics analysis and identified 66 gene homologs that by sequence similarity, putatively correspond to genes of all known genetic flowering pathways. The expression analysis of 25 selected genes representing various flowering pathways did not reveal large differences between the everbearing and the short-day genotypes. However, putative floral identity and floral integrator genesAP1andLFYwere co-regulated during early floral development.AP1mRNA was specifically accumulating in the shoot apices of the everbearing genotype, indicating its usability as a marker for floral initiation. Moreover, we showed that flowering induction in everbearing 'Baron Solemacher' and 'Hawaii-4' was inhibited by short-day and low temperature, in contrast to short-day genotypes.ConclusionWe have shown that many central genetic components of the flowering pathways inArabidopsiscan be identified from strawberry. However, novel regulatory mechanisms exist, likeSFLthat functions as a switch between short-day/low temperature and long-day/high temperature flowering responses between the short-day genotype and the everbearing 'Baron Solemacher'. The identification of putative flowering gene homologs andAP1as potential marker gene for floral initiation will strongly facilitate the exploration of strawberry flowering pathways.

The prototype baculovirus, Autographa californica multiple nucleopolyhedrovirus, an insect pathogen, holds great potential as a gene therapy vector. To develop transductional targeting and gene delivery by baculovirus, we focused on characterizing the nature and regulation of its uptake in human cancer cells. Baculovirus entered the cells along fluid-phase markers from the raft areas into smooth-surfaced vesicles devoid of clathrin. Notably, regulators associated with macropinocytosis, namely EIPA, Pak1, Rab34, and Rac1, had no significant effect on viral transduction, and the virus did not induce fluid-phase uptake. The internalization and nuclear uptake was, however, affected by mutants of RhoA, and of Arf6, a regulator of clathrin-independent entry. Furthermore, the entry of baculovirus induced ruffle formation and triggered the uptake of fluorescent E. coli bioparticles. To conclude, baculovirus enters human cells via a clathrin-independent pathway, which is able to trigger bacterial uptake. This study increases our understanding of virus entry strategies and gives new insight into baculovirus-mediated gene delivery in human cells. peerReviewed

In the mammalian central nervous system (CNS) an important contingent of dopaminergic neurons are localized in the substantia nigra and in the ventral tegmental area of the ventral midbrain. They constitute an anatomically and functionally heterogeneous group of cells involved in a variety of regulatory mechanisms, from locomotion to emotional/motivational behavior. Midbrain dopaminergic neuron (mDA) primary cultures represent a useful tool to study molecular mechanisms involved in their development and maintenance. Considerable information has been gathered on the mDA neurons development and maturation in vivo, as well as on the molecular features of mDA primary cultures. Here we investigated in detail the gene expression differences between the tissue of origin and ventral midbrain primary cultures enriched in mDA neurons, using microarray technique. We integrated the results based on different re-annotations of the microarray probes. By using knowledge-based gene network techniques and promoter sequence analysis, we also uncovered mechanisms that might regulate the expression of CNS genes involved in the definition of the identity of specific cell types in the ventral midbrain. We integrate bioinformatics and functional genomics, together with developmental neurobiology. Moreover, we propose guidelines for the computational analysis of microarray gene expression data. Our findings help to clarify some molecular aspects of the development and differentiation of DA neurons within the midbrain.

Conditional gene targeting strategies are progressively used to study gene function tissue-specifically and/or at a defined time period. Instrumental to all of these strategies is the generation of targeting vectors, and any methodology that would streamline the procedure would be highly beneficial. We describe a comprehensive transposition-based strategy to produce gene-targeting vectors for the generation of mouse conditional alleles. The system employs a universal cloning vector and two custom-designed mini-Mu transposons. It produces targeting constructions directly from BAC clones, and the alleles generated are modifiable by Cre and Flp recombinases. We demonstrate the applicability of the methodology by modifying two mouse genes, Chd22 and Drapc1. This straightforward strategy should be readily suitable for high-throughput targeting vector production.

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases.

BackgroundDevelopment and maintenance of the identity of tissues is of central importance for multicellular organisms. Based on gene expression profiles, it is possible to divide genes in housekeeping genes and those whose expression is preferential in one or a few tissues and which provide specialized functions that have a strong effect on the physiology of the whole organism.ResultsWe have surveyed the gene expression in 78 normal human tissues integrating publicly available microarray gene expression data. A total amount of 1601 genes were identified as selectively expressed in one or more tissues. The tissue-selective genes covered a wide range of cellular and molecular functions, and could be linked to 361 human diseases with Mendelian inheritance. Based on the gene expression profiles, we were able to form a network of tissues reflecting their functional relatedness and, to certain extent, their development. Using co-citation driven gene network technique and promoter analysis, we predicted a transcriptional module where the co-operation of the transcription factors E2F and NF-kappaB can possibly regulate a number of genes involved in the neurogenesis that takes place in the adult hippocampus.ConclusionsHere we propose that integration of gene expression data from Affymetrix GeneChip experiments is possible through re-annotation and commonly used pre-processing methods. We suggest that some functional aspects of the tissues can be explained by the co-operation of multiple transcription factors that regulate the expression of selected groups of genes.

The increase in the size of the scientific community created an explosion in scientific production. We have analyzed the dynamics of biomedical scientific output during 1957-2007 by applying a bibliometric analysis of the PubMed database using different keywords representing specific biomedical topics. With the assumption that increased scientific interest will result in increased scientific output, we compared the output of specific topics to that of all scientific output. This analysis resulted in three broad categories of topics; those that follow the general trend of all scientific output, those that show highly variable output, and attractive topics which are new and grow explosively. The analysis of the citation impact of the scientific output resulted in a typical longtail distribution: the majority of journals and articles are of very low impact. This distribution has remained unchanged since 1957, although the interests of scientists must have shifted in this period. We therefore analyzed the distribution of articles in top journals and lower impact journals over time for the attractive topics. Novelty is rewarded by publication in top journals. Over time more articles are published in low impact journals progressively creating the longtail distribution, signifying acceptance of the topic by the community. There can be a gap of years between novelty and acceptance. Within topics temporary novelty is created with new subtopics. In conclusion, the longtail distribution is the foundation of the scientific output of the scientific community and can be used to examine different aspects of science practice.

We have cloned the operon coding for the Bacillus subtilis S complex, which has been proposed to be a component in protein secretion machinery. A lambda gt10 library of B. subtilis was screened with antiserum directed against the Staphylococcus aureus membrane-bound ribosome protein complex, which is homologous to the B. subtilis S complex. Two positive overlapping lambda clones were sequenced. The S-complex operon, 5 kilobases in size, was shown to contain four open reading frames and three putative promoters, which are located upstream of the first, the third, and the last gene. The four proteins encoded by the operon are 42, 36, 48, and 50 kilodaltons in size. All of these proteins were recognized by antisera separately raised against each protein of the S. aureus membrane-bound ribosome protein and B. subtilis S complexes, thus verifying the S-complex identity of the lambda clones. Sequence analysis revealed that all four proteins of the B. subtilis S complex are homologous to the four subunits of the human pyruvate dehydrogenase (PDH). Also, the N terminus of the 48-kilodalton protein was found to have 70% amino acid identity with the N-terminal 211 amino acids, determined so far, from the E2 subunit of B. stearothermophilus PDH. Furthermore, chromosomal mapping of the S-complex operon gave a linkage to a marker gene located close to the previously mapped B. subtilis PDH genes. Thus, the S complex is evidently identical to the B. subtilis PDH, which has been shown to contain four subunits with molecular weights very similar to those of the S complex. Therefore, we propose that the S complex is not a primary component of protein secretion.