High-throughput flow cytometry-based assay to identify apoptosis-inducing proteins

After sequencing the human genome, the challenge ahead is to systematically analyze the functions and disease relation of the proteins encoded. Here the authors describe the application of a flow cytometry-based high-throughput assay to screen for apoptosis-activating proteins in transiently transfected cells. The assay is based on the detection of activated caspase-3 with a specific antibody, in cells overexpressing proteins tagged C- or N-terminally with yellow fluorescent protein. Fluorescence intensities are measured using a flow cytometer integrated with a high-throughput autosampler. The applicability of this screen has been tested in a pilot screen with 200 proteins. The candidate proteins were all verified in an independent microscopy-based nuclear fragmentation assay, finally resulting in the identification of 6 apoptosis inducers.

Infrared-based protein detection arrays for quantitative proteomics

The advancement of efficient technologies to comply with the needs of systems biology and drug discovery has so far not received adequate attention. A substantial bottleneck for the time-resolved quantitative description of signaling networks is the limited throughput and the inadequate sensitivity of currently established methods. Here, we present an improved protein microarray-based approach towards the sensitive detection of proteins in the fg-range which is based on signal detection in the near-infrared range. The high sensitivity of the assay permits the specific quantification of proteins derived from as little as only 20,000 cells with an error rate of only 5%. The capacity is limited to the analysis of up to 500 different samples per microarray. Protein abundance is determined qualitatively, and quantitatively, if recombinant protein is available. This novel approach was called IPAQ (infrared-based protein arrays with quantitative readout). IPAQ offers a highly sensitive experimental approach superior to the established standard protein quantification technologies, and is suitable for quantitative proteomics. Employing the IPAQ approach, a detailed analysis of activated signaling networks in biopsy samples and of crosstalk between signaling modules as required in drug discovery strategies can easily be performed.

Combinatorial RNAi for quantitative protein network analysis

The elucidation of cross-talk events between intersecting signaling pathways is one main challenge in biological research. The complexity of protein networks, composed of different pathways, requires novel strategies and techniques to reveal relevant interrelations. Here, we established a combinatorial RNAi strategy for systematic single, double, and triple knockdown, and we measured the residual mRNAs and proteins quantitatively by quantitative real-time PCR and reverse-phase protein arrays, respectively, as a prerequisite for data analysis. Our results show that the parallel knockdown of at least three different genes is feasible while keeping both untargeted silencing and cytotoxicity low. The technique was validated by investigating the interplay of tyrosine kinase receptor ErbB2 and its downstream targets Akt-1 and MEK1 in cell invasion. This experimental approach combines multiple gene knockdown with a subsequent quantitative validation of reduced protein expression and is a major advancement toward the analysis of signaling pathways in systems biology.

Mapping autism risk loci using genetic linkage and chromosomal rearrangements

Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.

Allelic variants of CAMTA1 and FLJ10737 within a commonly deleted region at 1p36 in neuroblastoma

Deletion of a distal portion of 1p is seen in a wide range of human malignancies, including neuroblastoma. Here, a 1p36.3 commonly deleted region of 216 kb has been defined encompassing two genes, CAMTA1 and FLJ10737. Low expression of CAMTA1 has been recently shown to be an independent predictor of poor outcome in neuroblastoma patients. The present study surveys CAMTA1 and FLJ10737 for genetic alterations by fluorescence-based single strand conformation polymorphism (SSCP) using a panel of DNAs from 88 neuroblastomas, their matching blood samples and 97 unaffected individuals. Nucleotide variants encoding amino acid substitutions were found in both genes. One CAMTA1 variant (T1336I) was not detected in 97 unaffected individuals, another (N1177K) resides in a conserved domain of the CAMTA1 protein and was found hemizygous in six neuroblastomas. We found no evidence for somatic mutations in FLJ10737 or CAMTA1. Further investigations are needed to address the functional impact of the identified variants and their possible significance for neuroblastoma.

Identification and meta-analysis of a small gene expression signature for the diagnosis of estrogen receptor status in invasive ductal breast cancer

In breast cancer, the determination of estrogen receptor (ER) expression is crucial for the decision on therapeutic strategies. Current ER expression analysis is based on immunohistochemical (IHC) staining of ER on formalin fixed tissue sections. However, low levels of ER expression frequently escape detection because of varying sensitivities of routine histopathological laboratories. Moreover, in estimating ER by IHC the receptor protein only is tested instead of the complex underlying ER pathway, which reflects its biological activity. To overcome this limitation, we have used the microarray technology to study 56 samples of invasive ductal carcinoma. We infer a robust and reliable signature of 10 genes, which is associated with ER expression and presumably therapeutically relevant biological processes. In a meta-analysis, the signature was tested on 3 further independent microarray gene expression data sets, covering different laboratories, array platforms, and clinics. The classification based on the signature showed a very low misclassification rate. In summary, the expression of few genes is sufficient to determine ER status. Future decisions on antiestrogen based therapy in breast cancer could be based on this signature rather than on immunostaining alone.

Mutations in the ribosomal protein gene RPL10 suggest a novel modulating disease mechanism for autism

Autism has a strong genetic background with a higher frequency of affected males suggesting involvement of X-linked genes and possibly also other factors causing the unbalanced sex ratio in the etiology of the disorder. We have identified two missense mutations in the ribosomal protein gene RPL10 located in Xq28 in two independent families with autism. We have obtained evidence that the amino-acid substitutions L206M and H213Q at the C-terminal end of RPL10 confer hypomorphism with respect to the regulation of the translation process while keeping the basic translation functions intact. This suggests the contribution of a novel, possibly modulating aberrant cellular function operative in autism. Previously, we detected high expression of RPL10 by RNA in situ hybridization in mouse hippocampus, a constituent of the brain limbic system known to be afflicted in autism. Based on these findings, we present a model for autistic disorder where a change in translational function is suggested to impact on those cognitive functions that are mediated through the limbic system.

CAFTAN: a tool for fast mapping, and quality assessment of cDNAs

Background

The German cDNA Consortium has been cloning full length cDNAs and continued with their exploitation in protein localization experiments and cellular assays. However, the efficient use of large cDNA resources requires the development of strategies that are capable of a speedy selection of truly useful cDNAs from biological and experimental noise. To this end we have developed a new high-throughput analysis tool, CAFTAN, which simplifies these efforts and thus fills the gap between large-scale cDNA collections and their systematic annotation and application in functional genomics.

Results

CAFTAN is built around the mapping of cDNAs to the genome assembly, and the subsequent analysis of their genomic context. It uses sequence features like the presence and type of PolyA signals, inner and flanking repeats, the GC-content, splice site types, etc. All these features are evaluated in individual tests and classify cDNAs according to their sequence quality and likelihood to have been generated from fully processed mRNAs. Additionally, CAFTAN compares the coordinates of mapped cDNAs with the genomic coordinates of reference sets from public available resources (e.g., VEGA, ENSEMBL). This provides detailed information about overlapping exons and the structural classification of cDNAs with respect to the reference set of splice variants.

The evaluation of CAFTAN showed that is able to correctly classify more than 85% of 5950 selected "known protein-coding" VEGA cDNAs as high quality multi- or single-exon. It identified as good 80.6 % of the single exon cDNAs and 85 % of the multiple exon cDNAs.

The program is written in Perl and in a modular way, allowing the adoption of this strategy to other tasks like EST-annotation, or to extend it by adding new classification rules and new organism databases as they become available. We think that it is a very useful program for the annotation and research of unfinished genomes.

Conclusion

CAFTAN is a high-throughput sequence analysis tool, which performs a fast and reliable quality prediction of cDNAs. Several thousands of cDNAs can be analyzed in a short time, giving the curator/scientist a first quick overview about the quality and the already existing annotation of a set of cDNAs. It supports the rejection of low quality cDNAs and helps in the selection of likely novel splice variants, and/or completely novel transcripts for new experiments.

Identification of a common gene expression signature in dilated cardiomyopathy across independent microarray studies

OBJECTIVES

This study was designed to identify a common gene expression signature in dilated cardiomyopathy (DCM) across different microarray studies.

BACKGROUND

Dilated cardiomyopathy is a common cause of heart failure in Western countries. Although gene expression arrays have emerged as a powerful tool for delineating complex disease patterns, differences in platform technology, tissue heterogeneity, and small sample sizes obscure the underlying pathophysiologic events and hamper a comprehensive interpretation of different microarray studies in heart failure.

METHODS

We accounted for tissue heterogeneity and technical aspects by performing 2 genome-wide expression studies based on cDNA and short-oligonucleotide microarray platforms which comprised independent septal and left ventricular tissue samples from nonfailing (NF) (n = 20) and DCM (n = 20) hearts.

RESULTS

Concordant results emerged for major gene ontology classes between cDNA and oligonucleotide microarrays. Notably, immune response processes displayed the most pronounced down-regulation on both microarray types, linking this functional gene class to the pathogenesis of end-stage DCM. Furthermore, a robust set of 27 genes was identified that classified DCM and NF samples with >90% accuracy in a total of 108 myocardial samples from our cDNA and oligonucleotide microarray studies as well as 2 publicly available datasets.

CONCLUSIONS

For the first time, independent microarray datasets pointed to significant involvement of immune response processes in end-stage DCM. Moreover, based on 4 independent microarray datasets, we present a robust gene expression signature of DCM, encouraging future prospective studies for the implementation of disease biomarkers in the management of patients with heart failure.

Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts

Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.

Molecular characterisation of non-absorptive and absorptive enterocytes in human small intestine

BACKGROUND AND AIMS

Perturbation of differentiation of the crypt-villus axis of the human small intestine is associated with several intestinal disorders of clinical importance. At present, differentiation of small intestinal enterocytes in the crypt-villus axis is not well characterised.

SUBJECTS AND METHODS

Expression profiling of microdissected enterocytes lining the upper part of crypts or the middle of villi was performed using the Affymetrix X3P arrays and several methods for confirmation.

RESULTS

A total of 978 differentially expressed sequences representing 778 unique UniGene IDs were found and categorised into four functional groups. In enterocytes lining the upper part of crypts, cell cycle promoting genes and transcription/translation related genes were predominantly expressed, whereas in enterocytes lining the middle of villi, high expression of cell cycle inhibiting genes, metabolism related genes, and vesicle/transport related genes was found.

CONCLUSION

Two types of enterocytes were dissected at the molecular level, the non-absorptive enterocyte located in the upper part of crypts and the absorptive enterocyte found in the middle of villi. These data improve our knowledge about the physiology of the crypt-villus architecture in human small intestine and provide new insights into pathophysiological phenomena, such as villus atrophy, which is clinically important.

Molecular characterization of the porcine deleted in malignant brain tumors 1 gene (DMBT1)

The human gene deleted in malignant brain tumors 1 (DMBT1) is considered to play a role in tumorigenesis and pathogen defense. It encodes a protein with multiple scavenger receptor cysteine-rich (SRCR) domains, which are involved in recognition and binding of a broad spectrum of bacterial pathogens. The SRCR domains are encoded by highly homologous repetitive exons, whose number in humans may vary from 8 to 13 due to genetic polymorphism. Here, we characterized the porcine DMBT1 gene on the mRNA and genomic level. We assembled a 4.5 kb porcine DMBT1 cDNA sequence from RT-PCR amplified seminal vesicle RNA. The porcine DMBT1 cDNA contains an open reading frame of 4050 nt. The transcript gives rise to a putative polypeptide of 1349 amino acids with a calculated mass of 147.9 kDa. Compared to human DMBT1, it contains only four N-terminal SRCR domains. Northern blotting revealed transcripts of approximately 4.7 kb in size in the tissues analyzed. Analysis of ESTs suggested the existence of secreted and transmembrane variants. The porcine DMBT1 gene spans about 54 kb on chromosome 14q28-q29. In contrast to the characterized cDNA, the genomic BAC clone only contained 3 exons coding for N-terminal SRCR domains. In different mammalian DMBT1 orthologs large interspecific differences in the number of SRCR exons and utilization of the transmembrane exon exist. Our data suggest that the porcine DMBT1 gene may share with the human DMBT1 gene additional intraspecific variations in the number of SRCR-coding exons.

An anthropoid-specific segmental duplication on human chromosome 1q22

Segmental duplications (SDs) play a key role in genome evolution by providing material for gene diversification and creation of variant or novel functions. They also mediate recombinations, resulting in microdeletions, which have occasionally been associated with human genetic diseases. Here, we present a detailed analysis of a large genomic region (about 240 kb), located on human chromosome 1q22, that contains a tandem SD, SD1q22. This duplication occurred about 37 million years ago in a lineage leading to anthropoid primates, after their separation from prosimians but before the Old and New World monkey split. We reconstructed the hypothetical unduplicated ancestral locus and compared it with the extant SD1q22 region. Our data demonstrate that, as a consequence of the duplication, new anthropoid-specific genetic material has evolved in the resulting paralogous segments. We describe the emergence of two new genes, whose new functions could contribute to the speciation of anthropoid primates. Moreover, we provide detailed information regarding structure and evolution of the SD1q22 region that is a prerequisite for future studies of its anthropoid-specific functions and possible linkage to human genetic disorders.

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 .

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 LIFEdb database in 2006

LIFEdb () 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.

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.

[Microarrays for the identification of molecular markers in the diagnosis and therapy of renal cell carcinomas]

Within the framework of the large interdisciplinary projects in biology, in particular the human genome project, a variety of novel technologies with unprecedented value for the analysis of clinical issues have been developed. DNA microarrays are a prominent example of this: they are powerful tools to investigate global gene expression in tumors and their corresponding normal tissues, to classify tumors based on their molecular properties, and to identify novel targets for future tumor therapy. Here, we review recent results of global gene expression analyses in renal cell carcinoma and discuss their implications for the diagnosis, prognosis, and therapy of human cancer.

Large-scale protein expression for proteome research

Access to pure and soluble recombinant proteins is essential for numerous applications in proteome research, such as the production of antibodies, structural characterization of proteins, and protein microarrays. Through the German cDNA Consortium we have access to more than 1500 ORFs encoding uncharacterized proteins. Preparing a large number of recombinant proteins calls for the careful refinement and re-evaluation of protein purification tools. The expression and purification strategy should result in mg quantities of protein that can be employed in microarray-based assays. In addition, the experimental set-up should be robust enough to allow both automated protein expression screening and the production of the proteins on a mg scale. These requirements are best fulfilled by a bacterial expression system such as Escherichia coli. To develop an efficient expression strategy, 75 different ORFs were transferred into suitable expression vectors using the Gateway cloning system. Four different fusion tags (E. coli transcription-termination anti-termination factor (NusA), hexahistidine tag (6xHis), maltose binding protein (MBP) and GST) were analyzed for their effect on yield of induced fusion protein and its solubility, as determined at two different induction temperatures. Affinity-purified fusion proteins were confirmed by MALDI-TOF MS.

Analysis of pigmented villonodular synovitis with genome-wide complementary DNA microarray and tissue array technology reveals insight into potential novel therapeutic approaches

OBJECTIVE

To characterize the gene expression profile and determine potential diagnostic markers and therapeutic targets in pigmented villonodular synovitis (PVNS).

METHODS

Gene expression patterns in 11 patients with PVNS, 18 patients with rheumatoid arthritis (RA), and 19 patients with osteoarthritis (OA) were investigated using genome-wide complementary DNA microarrays. Validation of differentially expressed genes was performed by real-time quantitative polymerase chain reaction and immunohistochemical analysis on tissue arrays (80 patients with PVNS, 51 patients with RA, and 20 patients with OA).

RESULTS

The gene expression profile in PVNS was clearly distinct from those in RA and OA. One hundred forty-one up-regulated genes and 47 down-regulated genes were found in PVNS compared with RA, and 153 up-regulated genes and 89 down-regulated genes were found in PVNS compared with OA (fold change > or = 1.5; Q < or = 0.001). Genes differentially expressed in PVNS were involved in apoptosis regulation, matrix degradation, and inflammation (ALOX5AP, ATP6V1B2, CD53, CHI3L1, CTSL, CXCR4, HSPA8, HSPCA, LAPTM5, MMP9, MOAP1, and SPP1).

CONCLUSION

The gene expression signature in PVNS is similar to that of activated macrophages and is consistent with the local destructive course of the disease. The gene and protein expression patterns suggest that the ongoing proliferation in PVNS is sustained by apoptosis resistance. This result suggests the possibility of a potential novel therapeutic intervention against PVNS.

Systematic comparison of surface coatings for protein microarrays

To process large numbers of samples in parallel is one potential of protein microarrays for research and diagnostics. However, the application of protein arrays is currently hampered by the lack of comprehensive technological knowledge about the suitability of 2-D and 3-D slide surface coatings. We have performed a systematic study to analyze how both surface types perform in combination with different fluorescent dyes to generate significant and reproducible data. In total, we analyzed more than 100 slides containing 1152 spots each. Slides were probed against different monoclonal antibodies (mAbs) and recombinant fusion proteins. We found two surface coatings to be most suitable for protein and antibody (Ab) immobilization. These were further subjected to quantitative analyses by evaluating intraslide and slide-to-slide reproducibilities, and the linear range of target detection. In summary, we demonstrate that only suitable combinations of surface and fluorescent dyes allow the generation of highly reproducible data.

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.