Single object profiles regression analysis (SOPRA): a novel method for analyzing high-content cell-based screens.

BACKGROUND: High-content screening (HCS) experiments generate complex data from multiple object features for each cell within a treated population. Usually, these data are analyzed by using population-averaged values of the features of interest, increasing the amount of false positives and the need for intensive follow-up validation. Therefore, there is a strong need for novel approaches with reproducible hit prediction by identifying significantly altered cell populations. RESULTS: Here we describe SOPRA, a workflow for analyzing image-based HCS data based on regression analysis of non-averaged object features from cell populations, which can be run on hundreds of samples using different cell features. Following plate-wise normalization, the values are counted within predetermined binning intervals, generating unique frequency distribution profiles (histograms) for each population, which are then normalized to control populations (control-based normalization). These control-normalized frequency distribution profiles are analyzed using the Bioconductor R-package maSigPro, originally developed to analyze time profiles. However, statistically significant altered frequency distributions are also identified by maSigPro when integrating it into the SOPRA workflow. Finally, significantly changed profiles can be used to generate a heatmap from which altered cell populations with similar phenotypes can be identified, enabling the detection of siRNAs and compounds with the same 'on-target' profile and reducing the number of false positive hits. CONCLUSIONS: SOPRA is a novel analysis workflow for the detection of statistically significant normalized frequency distribution profiles of cellular features generated in high-throughput RNAi screens. For the validation of the SOPRA software workflow, a screen for cell cycle progression was used. We were able to identify such profiles for siRNA-mediated gene perturbations and chemical inhibitors of different cell cycle stages. The SOPRA software is freely available from Github.

Genome-wide RNAi screen identifies human host factors crucial for influenza virus replication.

Influenza A virus, being responsible for seasonal epidemics and reoccurring pandemics, represents a worldwide threat to public health. High mutation rates facilitate the generation of viral escape mutants, rendering vaccines and drugs directed against virus-encoded targets potentially ineffective. In contrast, targeting host cell determinants temporarily dispensable for the host but crucial for virus replication could prevent viral escape. Here we report the discovery of 287 human host cell genes influencing influenza A virus replication in a genome-wide RNA interference (RNAi) screen. Using an independent assay we confirmed 168 hits (59%) inhibiting either the endemic H1N1 (119 hits) or the current pandemic swine-origin (121 hits) influenza A virus strains, with an overlap of 60%. Notably, a subset of these common hits was also essential for replication of a highly pathogenic avian H5N1 strain. In-depth analyses of several factors provided insights into their infection stage relevance. Notably, SON DNA binding protein (SON) was found to be important for normal trafficking of influenza virions to late endosomes early in infection. We also show that a small molecule inhibitor of CDC-like kinase 1 (CLK1) reduces influenza virus replication by more than two orders of magnitude, an effect connected with impaired splicing of the viral M2 messenger RNA. Furthermore, influenza-virus-infected p27(-/-) (cyclin-dependent kinase inhibitor 1B; Cdkn1b) mice accumulated significantly lower viral titres in the lung, providing in vivo evidence for the importance of this gene. Thus, our results highlight the potency of genome-wide RNAi screening for the dissection of virus-host interactions and the identification of drug targets for a broad range of influenza viruses.

Helicobacter pylori proteomics by 2-DE/MS, 1-DE-LC/MS and functional data mining.

With its predicted proteome of 1550 proteins (data set Etalon) Helicobacter pylori 26695 represents a perfect model system of medium complexity for investigating basic questions in proteomics. We analyzed urea-solubilized proteins by 2-DE/MS (data set 2-DE) and by 1-DE-LC/MS (Supprot); proteins insoluble in 9 M urea but solubilized by SDS (Pellet); proteins precipitating in the Sephadex layer at the application side of IEF (Sephadex) by 1-DE-LC/MS; and proteins precipitating close to the application side within the IEF gel by LC/MS (Startline). The experimental proteomics data of H. pylori comprising 567 proteins (protein coverage: 36.6%) were stored in the Proteome Database System for Microbial Research (http://www.mpiib-berlin.mpg.de/2D-PAGE/), which gives access to raw mass spectra (MALDI-TOF/TOF) in T2D format, as well as to text files of peak lists. For data mining the protein mapping and comparison tool PROMPT (http://webclu.bio.wzw.tum.de/prompt/) was used. The percentage of proteins with transmembrane regions, relative to all proteins detected, was 0, 0.2, 0, 0.5, 3.8 and 6.3% for 2-DE, Supprot, Startline, Sephadex, Pellet, and Etalon, respectively. 2-DE does not separate membrane proteins because they are insoluble in 9 M urea/70 mM DTT and 2% CHAPS. SDS solubilizes a considerable portion of the urea-insoluble proteins and makes them accessible for separation by SDS-PAGE and LC. The 2-DE/MS analysis with urea-solubilized proteins and the 1-DE-LC/MS analysis with the urea-insoluble protein fraction (Pellet) are complementary procedures in the pursuit of a complete proteome analysis. Access to the PROMPT-generated diagrams in the Proteome Database allows the mining of experimental data with respect to other functional aspects.

Transgenic, fluorescent Leishmania mexicana allow direct analysis of the proteome of intracellular amastigotes.

Investigating the proteome of intracellular pathogens is often hampered by inadequate methodologies to purify the pathogen free of host cell material. This has also precluded direct proteome analysis of the intracellular, amastigote form of Leishmania spp., protozoan parasites that cause a spectrum of diseases that affect some 12 million patients worldwide. Here a method is presented that combines classic, isopycnic density centrifugation with fluorescent particle sorting for purification by exploiting transgenic, fluorescent parasites to allow direct proteome analysis of the purified organisms. By this approach the proteome of intracellular Leishmania mexicana amastigotes was compared with that of extracellular promastigotes that are transmitted by insect vectors. In total, 509 different proteins were identified by mass spectrometry and database search. This number corresponds to approximately 6% of gene products predicted from the reference genome of Leishmania major. Intracellular amastigotes synthesized significantly more proteins with basic pI and showed a greater abundance of enzymes of fatty acid catabolism, which may reflect their living in acidic habitats and metabolic adaptation to nutrient availability, respectively. Bioinformatics analyses of the genes corresponding to the protein data sets produced clear evidence for skewed codon usage and translational bias in these organisms. Moreover analysis of the subset of genes whose products were more abundant in amastigotes revealed characteristic sequence motifs in 3'-untranslated regions that have been linked to translational control elements. This suggests that proteome data sets may be used to identify regulatory elements in mRNAs. Last but not least, at 6% coverage the proteome identified all vaccine antigens tested to date. Thus, the present data set provides a valuable resource for selection of candidate vaccine antigens.

Identification of proteins that modify cataract of mouse eye lens.

The occurrence of a nuclear cataract in the eye lens due to disruption of the alpha3Cx46 connexin gene, Gja3, is dependent on strain background in a mouse model, implicating factors that modify the pathology. The differences upon cataractogenesis in the urea soluble proteins of the lens of two mouse strains, C57BL/6J and 129/SvJ, were analyzed by a comparative proteomics approach. Determination of the complete proteome of an organ offers the opportunity to characterize at a molecular level, differences in gene expression and PTMs occurring during pathology and between individuals. The abundance of 63 protein species was altered between the strains. A unique aspect of this study is the identification of chaperonin subunit 6A, mortalin, ERp29, and syntaxin-binding protein 6 in the eye lens. DNA polymorphisms resulting in nonconservative amino acid changes that led to altered physicochemical properties of the proteins were detected for mortalin, chaperonin subunit 6A, annexin A1, and possibly gamma-N crystallin. The results show HSP27/25 and/or ERp29 are the likely major modifying factors for cataractogenesis. Extension of the results suggests that small heat-shock proteins have a major role for influencing cataract formation in humans.

Gain and loss of multiple genes during the evolution of Helicobacter pylori.

Sequence diversity and gene content distinguish most isolates of Helicobacter pylori. Even greater sequence differences differentiate distinct populations of H. pylori from different continents, but it was not clear whether these populations also differ in gene content. To address this question, we tested 56 globally representative strains of H. pylori and four strains of Helicobacter acinonychis with whole genome microarrays. Of the weighted average of 1,531 genes present in the two sequenced genomes, 25% are absent in at least one strain of H. pylori and 21% were absent or variable in H. acinonychis. We extrapolate that the core genome present in all isolates of H. pylori contains 1,111 genes. Variable genes tend to be small and possess unusual GC content; many of them have probably been imported by horizontal gene transfer. Phylogenetic trees based on the microarray data differ from those based on sequences of seven genes from the core genome. These discrepancies are due to homoplasies resulting from independent gene loss by deletion or recombination in multiple strains, which distort phylogenetic patterns. The patterns of these discrepancies versus population structure allow a reconstruction of the timing of the acquisition of variable genes within this species. Variable genes that are located within the cag pathogenicity island were apparently first acquired en bloc after speciation. In contrast, most other variable genes are of unknown function or encode restriction/modification enzymes, transposases, or outer membrane proteins. These seem to have been acquired prior to speciation of H. pylori and were subsequently lost by convergent evolution within individual strains. Thus, the use of microarrays can reveal patterns of gene gain or loss when examined within a phylogenetic context that is based on sequences of core genes.

ALPK1- and TIFA-Dependent Innate Immune Response Triggered by the Helicobacter pylori Type IV Secretion System.

Activation of transcription factor NF-κB is a hallmark of infection with the gastric pathogen Helicobacter pylori, associated with inflammation and carcinogenesis. Genome-wide RNAi screening revealed numerous host factors involved in H. pylori-, but not IL-1ß- and TNF-α-dependent NF-κB regulation. Pathway analysis including CRISPR/Cas9-knockout and recombinant protein technology, immunofluorescence microscopy, immunoblotting, mass spectrometry, and mutant H. pylori strains identified the H. pylori metabolite D-glycero-ß-D-manno-heptose 1,7-bisphosphate (ßHBP) as a cagPAI type IV secretion system (T4SS)-dependent effector of NF-κB activation in infected cells. Upon pathogen-host cell contact, TIFA forms large complexes (TIFAsomes) including interacting host factors, such as TRAF2. NF-κB activation, TIFA phosphorylation, and TIFAsome formation depend on a functional ALPK1 kinase, highlighting the ALPK1-TIFA axis as a core innate immune pathway. ALPK1-TIFA-mediated NF-κB activation was independent of CagA protein translocation, indicating that CagA translocation and HBP delivery to host cells are distinct features of the pathogen's T4SS.

Iterative data analysis is the key for exhaustive analysis of peptide mass fingerprints from proteins separated by two-dimensional electrophoresis.

Peptide mass fingerprinting (PMF) is a powerful tool for identification of proteins separated by two-dimensional electrophoresis (2-DE). With the increase in sensitivity of peptide mass determination it becomes obvious that even spots looking well separated on a 2-DE gel may consist of several proteins. As a result the number of mass peaks in PMFs increased dramatically leaving many unassigned after a first database search. A number of these are caused by experiment-specific contaminants or by neighbor spots, as well as by additional proteins or post-translational modifications. To understand the complete protein composition of a spot we suggest an iterative procedure based on large numbers of PMFs, exemplified by PMFs of 480 Helicobacter pylori protein spots. Three key iterations were applied: (1) Elimination of contaminant mass peaks determined by MS-Screener (a software developed for this purpose) followed by reanalysis; (2) neighbor spot mass peak determination by cluster analysis, elimination from the peak list and repeated search; (3) re-evaluation of contaminant peaks. The quality of the identification was improved and spots previously unidentified were assigned to proteins. Eight additional spots were identified with this procedure, increasing the total number of identified spots to 455.

Assembling proteomics data as a prerequisite for the analysis of large scale experiments.

BACKGROUND: Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. RESULTS: In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. CONCLUSION: The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk.

Assessment of protein spot components applying correspondence analysis for peptide mass fingerprint data.

Proteins separated by two-dimensional gel electrophoresis (2-DE) may be distributed over several spots. Otherwise, one spot may contain more than one component. The same protein occurring in several spots supposedly represents differently modified protein species that might be of biological relevance. Identification of spots with peptide mass fingerprinting and database searching leads only to the detection of the major spot components. If a spot also contains additional minor protein components, quantitation of spots with protein staining techniques or antibody detection becomes misleading. In order to find spots containing minor components we applied correspondence analysis, a multivariate data exploration method, to peptide mass fingerprint data. Correspondence analysis using peak lists revealed groups of spots containing the same protein with their characteristic mass-to-charge ratio (m/z) values. In order to detect different protein spot components an interactive threshold setting and removal of m/z values with subsequent recalculation of the correspondence analysis using our software tool CorrAn are performed. The usefulness of this methodical approach was shown by a data set of peptide mass fingerprints of 284 spots of Helicobacter pylori 26695 separated by 2-DE.

A European pathogenic microorganism proteome database: construction and maintenance.

A relational database structure based on MS-Access and MySQL to store and manage proteomics data was established. This system may be used to publish two-dimensional electrophoretic proteomics data, and also may be accessed by external users who want to compare their own data with those in the databases. The maintenance of the database is managed centrally. The producers of proteomics data do not need to construct a database themselves. Users can introduce mass spectra into the database, which allows the searching of peptide mass fingerprints against their own protein sequence databases. The first release published in January 2002 contains data from Mycobacterium tuberculosis, Helicobacter pylori, Borrelia garinii, Francisella tularensis, Chlamydia pneumoniae, Mycoplasma pneumoniae, Jurkat T-cells and mouse mammary gland projects (http://www.mpiib-berlin. mpg.de/2D-PAGE/).

Presentation of differentially regulated proteins within a web-accessible proteome database system of microorganisms.

Web-accessible proteome databases represent indispensable tools for quantitative and comparative proteomics research. The majority of two-dimensional gel electrophoresis (2-DE) databases contains clickable 2-DE gel images and descriptive textual information such as protein name, Mr/pI values, methods of identification, cellular localization and other information on proteins. Although a great part of the work in comparative proteomics consists of the analysis of 2-DE gels using image analysis approaches, most proteome databases lack the ability to present protein abundance data and their alterations within experiments via the web. Now, differentially regulated proteins detected in microbial experiments by quantitative gel image analysis are presented in a web-accessible relational database DIFF (Differentially Regulated Proteins). The DIFF database is a part of the proteome database system for microbial research available at http://www.mpiib-berlin.mpg.de/2D-PAGE.

Web-accessible proteome databases for microbial research.

The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.

Identification of candidate antigens for serologic detection of Helicobacter pylori-infected patients with gastric carcinoma.

Helicobacter pylori colonizes the stomach of almost half the world population and is a causative agent of gastric carcinomas and duodenal ulcers. Only a small fraction of infected people will develop these severe illnesses and a predictive test to identify people at high risk would greatly benefit disease management. Our study aimed to identify conserved bacterial antigens that may be useful for the development of such a diagnostic test. High-resolution immunoproteomics by 2-dimensional electrophoresis of H. pylori 26695 proteins was carried out with sera from infected patients with either duodenal ulcer (n=30) or gastric carcinoma (n=30), 2 clinically divergent conditions. According to their antigen recognition patterns clear groups of patients were identified. Although this classification did not correspond to the clinical status, it may be correlated to other bacterial or host factors that influence the outcome of infection. In general antigen recognition patterns were found to be highly variable, however by utilizing powerful image analysis and statistical tests the recognition of 14 antigenic protein species was found to differ significantly (p<0.01) between both diseases. Particular protein species of GroEL, HyuA, GroES and AtpA appear to be useful surrogate markers for gastric carcinoma detection and consequently should be considered for further prospective studies to assess their predictive value. For one protein species of AtpA, evidence was found that different post-translational modifications may confer different immunogenicities.