34 research outputs found

    SeLOX—a locus of recombination site search tool for the detection and directed evolution of site-specific recombination systems

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    Site-specific recombinases have become a resourceful tool for genome engineering, allowing sophisticated in vivo DNA modifications and rearrangements, including the precise removal of integrated retroviruses from host genomes. In a recent study, a mutant form of Cre recombinase has been used to excise the provirus of a specific HIV-1 strain from the human genome. To achieve provirus excision, the Cre recombinase had to be evolved to recombine an asymmetric locus of recombination (lox)-like sequence present in the long terminal repeat (LTR) regions of a HIV-1 strain. One pre-requisite for this type of work is the identification of degenerate lox-like sites in genomic sequences. Given their nature—two inverted repeats flanking a spacer of variable length—existing search tools like BLAST or RepeatMasker perform poorly. To address this lack of available algorithms, we have developed the web-server SeLOX, which can identify degenerate lox-like sites within genomic sequences. SeLOX calculates a position weight matrix based on lox-like sequences, which is used to search genomic sequences. For computational efficiency, we transform sequences into binary space, which allows us to use a bit-wise AND Boolean operator for comparisons. Next to finding lox-like sites for Cre type recombinases in HIV LTR sequences, we have used SeLOX to identify lox-like sites in HIV LTRs for six yeast recombinases. We finally demonstrate the general usefulness of SeLOX in identifying lox-like sequences in large genomes by searching Cre type recombination sites in the entire human genome. SeLOX is freely available at http://selox.mpi-cbg.de/cgi-bin/selox/index

    Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways

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    BACKGROUND: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physical or genetic interaction data has already been successfully applied to enhance knowledge from all types of high-throughput studies. Yet, toolboxes for navigating and understanding even small gene or protein networks are poorly developed. RESULTS: We introduce two Cytoscape plug-ins, which support the generation and interpretation of experiment-based interaction networks. The virtual pathway explorer viPEr creates so-called focus networks by joining a list of experimentally determined genes with the interactome of a specific organism. viPEr calculates all paths between two or more user-selected nodes, or explores the neighborhood of a single selected node. Numerical values from expression studies assigned to the nodes serve to score identified paths. The pathway enrichment analysis tool PEANuT annotates networks with pathway information from various sources and calculates enriched pathways between a focus and a background network. Using time series expression data of atorvastatin treated primary hepatocytes from six patients, we demonstrate the handling and applicability of viPEr and PEANuT. Based on our investigations using viPEr and PEANuT, we suggest a role of the FoxA1/A2/A3 transcriptional network in the cellular response to atorvastatin treatment. Moreover, we find an enrichment of metabolic and cancer pathways in the Fox transcriptional network and demonstrate a patient-specific reaction to the drug. CONCLUSIONS: The Cytoscape plug-in viPEr integrates –omics data with interactome data. It supports the interpretation and navigation of large-scale datasets by creating focus networks, facilitating mechanistic predictions from –omics studies. PEANuT provides an up-front method to identify underlying biological principles by calculating enriched pathways in focus networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2017-z) contains supplementary material, which is available to authorized users

    The Interaction Properties of the Human Rab GTPase Family – A Comparative Analysis Reveals Determinants of Molecular Binding Selectivity

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    Rab GTPases constitute the largest subfamily of the Ras protein superfamily. Rab proteins regulate organelle biogenesis and transport, and display distinct binding preferences for effector and activator proteins, many of which have not been elucidated yet. The underlying molecular recognition motifs, binding partner preferences and selectivities are not well understood.Comparative analysis of the amino acid sequences and the three-dimensional electrostatic and hydrophobic molecular interaction fields of 62 human Rab proteins revealed a wide range of binding properties with large differences between some Rab proteins. This analysis assists the functional annotation of Rab proteins 12, 14, 26, 37 and 41 and provided an explanation for the shared function of Rab3 and 27. Rab7a and 7b have very different electrostatic potentials, indicating that they may bind to different effector proteins and thus, exert different functions. The subfamily V Rab GTPases which are associated with endosome differ subtly in the interaction properties of their switch regions, and this may explain exchange factor specificity and exchange kinetics.We have analysed conservation of sequence and of molecular interaction fields to cluster and annotate the human Rab proteins. The analysis of three dimensional molecular interaction fields provides detailed insight that is not available from a sequence-based approach alone. Based on our results, we predict novel functions for some Rab proteins and provide insights into their divergent functions and the determinants of their binding partner selectivity

    The Bicoid Stability Factor Controls Polyadenylation and Expression of Specific Mitochondrial mRNAs in Drosophila melanogaster

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    The bicoid stability factor (BSF) of Drosophila melanogaster has been reported to be present in the cytoplasm, where it stabilizes the maternally contributed bicoid mRNA and binds mRNAs expressed from early zygotic genes. BSF may also have other roles, as it is ubiquitously expressed and essential for survival of adult flies. We have performed immunofluorescence and cell fractionation analyses and show here that BSF is mainly a mitochondrial protein. We studied two independent RNAi knockdown fly lines and report that reduced BSF protein levels lead to a severe respiratory deficiency and delayed development at the late larvae stage. Ubiquitous knockdown of BSF results in a severe reduction of the polyadenylation tail lengths of specific mitochondrial mRNAs, accompanied by an enrichment of unprocessed polycistronic RNA intermediates. Furthermore, we observed a significant reduction in mRNA steady state levels, despite increased de novo transcription. Surprisingly, mitochondrial de novo translation is increased and abnormal mitochondrial translation products are present in knockdown flies, suggesting that BSF also has a role in coordinating the mitochondrial translation in addition to its role in mRNA maturation and stability. We thus report a novel function of BSF in flies and demonstrate that it has an important intra-mitochondrial role, which is essential for maintaining mtDNA gene expression and oxidative phosphorylation

    HMMerThread: Detecting Remote, Functional Conserved Domains in Entire Genomes by Combining Relaxed Sequence-Database Searches with Fold Recognition

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    Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs) are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10), a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in proteins based on weak sequence similarity. Our predictions open up new avenues for biological and medical studies. Genome-wide HMMerThread domains are available at http://vm1-hmmerthread.age.mpg.de

    morFeus: a web-based program to detect remotely conserved orthologs using symmetrical best hits and orthology network scoring

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    Background: Searching the orthologs of a given protein or DNA sequence is one of the most important and most commonly used Bioinformatics methods in Biology. Programs like BLAST or the orthology search engine Inparanoid can be used to find orthologs when the similarity between two sequences is sufficiently high. They however fail when the level of conservation is low. The detection of remotely conserved proteins oftentimes involves sophisticated manual intervention that is difficult to automate. Results: Here, we introduce morFeus, a search program to find remotely conserved orthologs. Based on relaxed sequence similarity searches, morFeus selects sequences based on the similarity of their alignments to the query, tests for orthology by iterative reciprocal BLAST searches and calculates a network score for the resulting network of orthologs that is a measure of orthology independent of the E-value. Detecting remotely conserved orthologs of a protein using morFeus thus requires no manual intervention. We demonstrate the performance of morFeus by comparing it to state-of-the-art orthology resources and methods. We provide an example of remotely conserved orthologs, which were experimentally shown to be functionally equivalent in the respective organisms and therefore meet the criteria of the orthology-function conjecture. Conclusions: Based on our results, we conclude that morFeus is a powerful and specific search method for detecting remotely conserved orthologs
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