Unified Software Solution for Efficient SPR Data Analysis in Drug Research.

Surface plasmon resonance (SPR) is a powerful method for obtaining detailed molecular interaction parameters. Modern instrumentation with its increased throughput has enabled routine screening by SPR in hit-to-lead and lead optimization programs, and SPR has become a mainstream drug discovery technology. However, the processing and reporting of SPR data in drug discovery are typically performed manually, which is both time-consuming and tedious. Here, we present the workflow concept, design and experiences with a software module relying on a single, browser-based software platform for the processing, analysis, and reporting of SPR data. The efficiency of this concept lies in the immediate availability of end results: data are processed and analyzed upon loading the raw data file, allowing the user to immediately quality control the results. Once completed, the user can automatically report those results to data repositories for corporate access and quickly generate printed reports or documents. The software module has resulted in a very efficient and effective workflow through saved time and improved quality control. We discuss these benefits and show how this process defines a new benchmark in the drug discovery industry for the handling, interpretation, visualization, and sharing of SPR data.

Extending pathways based on gene lists using InterPro domain signatures.

BACKGROUND: High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly used and well established technique to test for the statistically significant over-representation of particular pathways. A shortcoming of this method is however, that most genes that are investigated in the experiments have very sparse functional or pathway annotation and therefore cannot be the target of such an analysis. The approach presented here aims to assign lists of genes with limited annotation to previously described functional gene collections or pathways. This works by comparing InterPro domain signatures of the candidate gene lists with domain signatures of gene sets derived from known classifications, e.g. KEGG pathways. RESULTS: In order to validate our approach, we designed a simulation study. Based on all pathways available in the KEGG database, we create test gene lists by randomly selecting pathway genes, removing these genes from the known pathways and adding variable amounts of noise in the form of genes not annotated to the pathway. We show that we can recover pathway memberships based on the simulated gene lists with high accuracy. We further demonstrate the applicability of our approach on a biological example. CONCLUSION: Results based on simulation and data analysis show that domain based pathway enrichment analysis is a very sensitive method to test for enrichment of pathways in sparsely annotated lists of genes. An R based software package domainsignatures, to routinely perform this analysis on the results of high-throughput screening, is available via Bioconductor.

The full-ORF clone resource of the German cDNA Consortium.

BACKGROUND: With the completion of the human genome sequence the functional analysis and characterization of the encoded proteins has become the next urging challenge in the post-genome era. The lack of comprehensive ORFeome resources has thus far hampered systematic applications by protein gain-of-function analysis. Gene and ORF coverage with full-length ORF clones thus needs to be extended. In combination with a unique and versatile cloning system, these will provide the tools for genome-wide systematic functional analyses, to achieve a deeper insight into complex biological processes. RESULTS: Here we describe the generation of a full-ORF clone resource of human genes applying the Gateway cloning technology (Invitrogen). A pipeline for efficient cloning and sequencing was developed and a sample tracking database was implemented to streamline the clone production process targeting more than 2,200 different ORFs. In addition, a robust cloning strategy was established, permitting the simultaneous generation of two clone variants that contain a particular ORF with as well as without a stop codon by the implementation of only one additional working step into the cloning procedure. Up to 92 % of the targeted ORFs were successfully amplified by PCR and more than 93 % of the amplicons successfully cloned. CONCLUSION: The German cDNA Consortium ORFeome resource currently consists of more than 3,800 sequence-verified entry clones representing ORFs, cloned with and without stop codon, for about 1,700 different gene loci. 177 splice variants were cloned representing 121 of these genes. The entry clones have been used to generate over 5,000 different expression constructs, providing the basis for functional profiling applications. As a member of the recently formed international ORFeome collaboration we substantially contribute to generating and providing a whole genome human ORFeome collection in a unique cloning system that is made freely available in the community.

The 3of5 web application for complex and comprehensive pattern matching in protein sequences.

BACKGROUND: The identification of patterns in biological sequences is a key challenge in genome analysis and in proteomics. Frequently such patterns are complex and highly variable, especially in protein sequences. They are frequently described using terms of regular expressions (RegEx) because of the user-friendly terminology. Limitations arise for queries with the increasing complexity of patterns and are accompanied by requirements for enhanced capabilities. This is especially true for patterns containing ambiguous characters and positions and/or length ambiguities. RESULTS: We have implemented the 3of5 web application in order to enable complex pattern matching in protein sequences. 3of5 is named after a special use of its main feature, the novel n-of-m pattern type. This feature allows for an extensive specification of variable patterns where the individual elements may vary in their position, order, and content within a defined stretch of sequence. The number of distinct elements can be constrained by operators, and individual characters may be excluded. The n-of-m pattern type can be combined with common regular expression terms and thus also allows for a comprehensive description of complex patterns. 3of5 increases the fidelity of pattern matching and finds ALL possible solutions in protein sequences in cases of length-ambiguous patterns instead of simply reporting the longest or shortest hits. Grouping and combined search for patterns provides a hierarchical arrangement of larger patterns sets. The algorithm is implemented as internet application and freely accessible. The application is available at http://dkfz.de/mga2/3of5/3of5.html. CONCLUSION: The 3of5 application offers an extended vocabulary for the definition of search patterns and thus allows the user to comprehensively specify and identify peptide patterns with variable elements. The n-of-m pattern type offers an improved accuracy for pattern matching in combination with the ability to find all solutions, without compromising the user friendliness of regular expression terms.

The systematic functional characterisation of Xq28 genes prioritises candidate disease genes.

BACKGROUND: Well known for its gene density and the large number of mapped diseases, the human sub-chromosomal region Xq28 has long been a focus of genome research. Over 40 of approximately 300 X-linked diseases map to this region, and systematic mapping, transcript identification, and mutation analysis has led to the identification of causative genes for 26 of these diseases, leaving another 17 diseases mapped to Xq28, where the causative gene is still unknown. To expedite disease gene identification, we have initiated the functional characterisation of all known Xq28 genes. RESULTS: By using a systematic approach, we describe the Xq28 genes by RNA in situ hybridisation and Northern blotting of the mouse orthologs, as well as subcellular localisation and data mining of the human genes. We have developed a relational web-accessible database with comprehensive query options integrating all experimental data. Using this database, we matched gene expression patterns with affected tissues for 16 of the 17 remaining Xq28 linked diseases, where the causative gene is unknown. CONCLUSION: By using this systematic approach, we have prioritised genes in linkage regions of Xq28-mapped diseases to an amenable number for mutational screens. Our database can be queried by any researcher performing highly specified searches including diseases not listed in OMIM or diseases that might be linked to Xq28 in the future.

The LIFEdb database in 2006.

LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.

Functional profiling: from microarrays via cell-based assays to novel tumor relevant modulators of the cell cycle.

Cancer transcription microarray studies commonly deliver long lists of "candidate" genes that are putatively associated with the respective disease. For many of these genes, no functional information, even less their relevance in pathologic conditions, is established as they were identified in large-scale genomics approaches. Strategies and tools are thus needed to distinguish genes and proteins with mere tumor association from those causally related to cancer. Here, we describe a functional profiling approach, where we analyzed 103 previously uncharacterized genes in cancer relevant assays that probed their effects on DNA replication (cell proliferation). The genes had previously been identified as differentially expressed in genome-wide microarray studies of tumors. Using an automated high-throughput assay with single-cell resolution, we discovered seven activators and nine repressors of DNA replication. These were further characterized for effects on extracellular signal-regulated kinase 1/2 (ERK1/2) signaling (G1-S transition) and anchorage-independent growth (tumorigenicity). One activator and one inhibitor protein of ERK1/2 activation and three repressors of anchorage-independent growth were identified. Data from tumor and functional profiling make these proteins novel prime candidates for further in-depth study of their roles in cancer development and progression. We have established a novel functional profiling strategy that links genomics to cell biology and showed its potential for discerning cancer relevant modulators of the cell cycle in the candidate lists from microarray studies.

From ORFeome to biology: a functional genomics pipeline.

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.

High-throughput protein analysis integrating bioinformatics and experimental assays.

The wealth of transcript information that has been made publicly available in recent years requires the development of high-throughput functional genomics and proteomics approaches for its analysis. Such approaches need suitable data integration procedures and a high level of automation in order to gain maximum benefit from the results generated. We have designed an automatic pipeline to analyse annotated open reading frames (ORFs) stemming from full-length cDNAs produced mainly by the German cDNA Consortium. The ORFs are cloned into expression vectors for use in large-scale assays such as the determination of subcellular protein localization or kinase reaction specificity. Additionally, all identified ORFs undergo exhaustive bioinformatic analysis such as similarity searches, protein domain architecture determination and prediction of physicochemical characteristics and secondary structure, using a wide variety of bioinformatic methods in combination with the most up-to-date public databases (e.g. PRINTS, BLOCKS, INTERPRO, PROSITE SWISSPROT). Data from experimental results and from the bioinformatic analysis are integrated and stored in a relational database (MS SQL-Server), which makes it possible for researchers to find answers to biological questions easily, thereby speeding up the selection of targets for further analysis. The designed pipeline constitutes a new automatic approach to obtaining and administrating relevant biological data from high-throughput investigations of cDNAs in order to systematically identify and characterize novel genes, as well as to comprehensively describe the function of the encoded proteins.

LIFEdb: a database for functional genomics experiments integrating information from external sources, and serving as a sample tracking system.

We have implemented LIFEdb (http://www.dkfz.de/LIFEdb) to link information regarding novel human full-length cDNAs generated and sequenced by the German cDNA Consortium with functional information on the encoded proteins produced in functional genomics and proteomics approaches. The database also serves as a sample-tracking system to manage the process from cDNA to experimental read-out and data interpretation. A web interface enables the scientific community to explore and visualize features of the annotated cDNAs and ORFs combined with experimental results, and thus helps to unravel new features of proteins with as yet unknown functions.

CDNAs for functional genomics and proteomics: the German Consortium.

To functionally characterize numerous novel proteins encoded by cDNAs sequenced by the German Consortium, 800 were tagged with green fluorescent protein. The subcellular localizations of the fusion proteins were examined in living cells, enabling their classification in subcellular groups. Their activity in cell growth, cell death, and protein transport was screened in high throughput using robotic liquid handling and reading stations. The resulting information is integrated with functional genomics and proteomics data for further understanding of protein functions in the cellular context.

The preprotein conducting channel at the inner envelope membrane of plastids.

The preprotein translocation at the inner envelope membrane of chloroplasts so far involves five proteins: Tic110, Tic55, Tic40, Tic22 and Tic20. The molecular function of these proteins has not yet been established. Here, we demonstrate that Tic110 constitutes a central part of the preprotein translocation pore. Dependent on the presence of intact Tic110, radiolabelled preprotein specifically interacts with isolated inner envelope vesicles as well as with purified, recombinant Tic110 reconstituted into liposomes. Circular dichroism analysis reveals that Tic110 consists mainly of beta-sheets, a structure typically found in pore proteins. In planar lipid bilayers, recombinant Tic110 forms a cation-selective high-conductance channel with a calculated inner pore opening of 1.7 nm. Purified transit peptide causes strong flickering and a voltage-dependent block of the channel. Moreover, at the inner envelope membrane, a peptide-sensitive channel is described that shows properties basically identical to the channel formed by recombinant Tic110. We conclude that Tic110 has a distinct preprotein binding site and functions as a preprotein translocation pore at the inner envelope membrane.