Abstract: Antibody microarrays are a multiplexing technique for the analyses of hundreds of different analytes in parallel from small sample volumes of few microlitres only. With sensitivities in the picomolar to femtomolar range, they are gaining importance in proteomic analyses. These sensitivities can be obtained for complex protein samples without any pre-fractionation or signal amplification. Also, no expensive or elaborate protein depletion steps are needed. As with custom DNA-microarrays, the implementation of a dual-colour assay adds to assay robustness and reproducibility and was therefore a focus of our technical implementation. In order to perform antibody microarray experiments for large sets of samples and analytes in a robust manner, it was essential to optimise the experimental layout, the protein extraction, labelling and incubation as well as data processing steps. Here, we present our current protocol, which is used for the simultaneous analysis of the abundance of more than 800 proteins in plasma, urine, and tissue samples.
Abstract: Adenoviruses (Ads), especially HAdV-5, have been genetically equipped with tumor-restricted replication potential to enable applications in oncolytic cancer therapy. Such oncolytic adenoviruses have been well tolerated in cancer patients, but their anti-tumor efficacy needs to be enhanced. In this regard, it should be considered that cancer cells, dependent on their tissue of origin, can differ substantially from the normal host cells to which Ads are adapted by complex virus-host interactions. Consequently, viral replication efficiency, a key determinant of oncolytic activity, might be suboptimal in cancer cells. Therefore, we have analyzed both the replication kinetics of HAdV-5 and the virus-induced transcriptome in human bronchial epithelial cells (HBEC) in comparison to cancer cells. This is the first report on genome-wide expression profiling of Ads in their native host cells. We found that E1A expression and onset of viral genome replication are most rapid in HBEC and considerably delayed in melanoma cells. In squamous cell lung carcinoma cells, we observed intermediate HAdV-5 replication kinetics. Infectious particle production, viral spread and lytic activity of HAdV-5 were attenuated in melanoma cells versus HBEC. Expression profiling at the onset of viral genome replication revealed that HAdV-5 induced the strongest changes in the cellular transcriptome in HBEC, followed by lung cancer and melanoma cells. We identified prominent regulation of genes involved in cell cycle and DNA metabolism, replication and packaging in HBEC, which is in accord with the necessity to induce S phase for viral replication. Strikingly, in melanoma cells HAdV-5 triggered opposing regulation of said genes and, in contrast to lung cancer cells, no weak S phase induction was detected when using the E2F promoter as reporter. Our results provide a rationale for improving oncolytic adenoviruses either by adaptation of viral infection to target tumor cells or by modulating tumor cell functions to better support viral replication.
Abstract: Pancreatic cancer is one of the leading cancer-related causes of death due to high chemo-resistance and fast metastasation. Nemorosone, a polycyclic polyprenylated acylphloroglucinol, has recently been identified as a promising anticancer agent. Here, we examine its growth-inhibitory effects on pancreatic cancer cells. Based on transcription profiling, a molecular mode of action is proposed.
Abstract: An increasing amount of expressed sequence tag (EST) and genomic data, predominantly for the cnidarians Acropora, Hydra and Nematostella, reveals that cnidarians have a high genomic complexity, despite being one of the morphologically simplest multicellular animals. Considering the diversity of cnidarians, we performed an EST project on the hydroid Hydractinia echinata, to contribute towards a broader coverage of this phylum. After random sequencing of almost 9000 clones, EST characterization revealed a broad diversity in gene content. Corroborating observations in other cnidarians, Hydractinia sequences exhibited a higher sequence similarity to vertebrates than to ecdysozoan invertebrates. A significant number of sequences were hitherto undescribed in metazoans, suggesting that these may be either cnidarian innovations or ancient genes lost in the bilaterian genomes analysed so far. However, we cannot rule out some degree of contamination from commensal bacteria. The identification of unique Hydractinia sequences emphasizes that the acquired genomic information generated so far is not large enough to be representative of the highly diverse cnidarian phylum. Finally, a database was created to store all the acquired information (http://www.mchips.org/hydractinia_echinata.html).
Abstract: Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.
Abstract: The role of sulfite reductase (SiR) in assimilatory reduction of inorganic sulfate to sulfide has long been regarded as insignificant for control of flux in this pathway. Two independent Arabidopsis thaliana T-DNA insertion lines (sir1-1 and sir1-2), each with an insertion in the promoter region of SiR, were isolated. sir1-2 seedlings had 14% SiR transcript levels compared with the wild type and were early seedling lethal. sir1-1 seedlings had 44% SiR transcript levels and were viable but strongly retarded in growth. In mature leaves of sir1-1 plants, the levels of SiR transcript, protein, and enzymatic activity ranged between 17 and 28% compared with the wild type. The 28-fold decrease of incorporation of (35)S label into Cys, glutathione, and protein in sir1-1 showed that the decreased activity of SiR generated a severe bottleneck in the assimilatory sulfate reduction pathway. Root sulfate uptake was strongly enhanced, and steady state levels of most of the sulfur-related metabolites, as well as the expression of many primary metabolism genes, were changed in leaves of sir1-1. Hexose and starch contents were decreased, while free amino acids increased. Inorganic carbon, nitrogen, and sulfur composition was also severely altered, demonstrating strong perturbations in metabolism that differed markedly from known sulfate deficiency responses. The results support that SiR is the only gene with this function in the Arabidopsis genome, that optimal activity of SiR is essential for normal growth, and that its downregulation causes severe adaptive reactions of primary and secondary metabolism.
Abstract: MOTIVATION: Cross-species meta-analyses of microarray data usually require prior affiliation of genes based on orthology information that often relies on sequence similarity. RESULTS: We present an algorithm merging microarray datasets on the basis of co-expression alone, without any requirement for orthology information to affiliate genes. Combining existing methods such as co-inertia analysis, back-transformation, Hungarian matching and majority voting in an iterative non-greedy hill-climbing approach, it affiliates arrays and genes at the same time, maximizing the co-structure between the datasets. To introduce the method, we demonstrate its performance on two closely and two distantly related datasets of different experimental context and produced on different platforms. Each pair stems from two different species. The resulting cross-species dynamic Bayesian gene networks improve on the networks inferred from each dataset alone by yielding more significant network motifs, as well as more of the interactions already recorded in KEGG and other databases. Also, it is shown that our algorithm converges on the optimal number of nodes for network inference. Being readily extendable to more than two datasets, it provides the opportunity to infer extensive gene regulatory networks. Availability and Implementation: Source code (MATLAB and R) freely available for download at http://www.mchips.org/supplements/moghaddasi_source.tgz.
Abstract: Pancreatic cancer is one of the most aggressive human malignancies, with an extremely poor prognosis. The paucity of curative therapies has translated into an overall 5-year survival rate of less than 5%, underscoring a desperate need for new therapeutic options. Artesunate (ART), clinically used as anti-malarial agent, has recently revealed remarkable anti-tumor activity. However, the mechanisms underlying those activities in pancreatic cancer are not yet known. Here we evaluated the anti-tumor activity of Artesunate and the possible underlying mechanisms in pancreatic cancer. MiaPaCa-2 (poorly differentiated) and BxPC-3 (moderately differentiated) pancreatic cancer cell lines were treated with Artesunate and the effect was monitored by a tetrazolium-based assay (MTS) for evaluating cell viability and by flow cytometry and caspase 3/7 activation for apoptosis evaluation. In addition cDNA arrays were used to identify differentially expressed genes. The microarray data were then validated by RT-PCR and Western blotting. Moreover, pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis. The expression analysis identified a common set of genes that were regulated by Artesunate in pancreatic cancer. Our results provide the first in vitro evidence for the therapeutic utility of Artesunate in pancreatic cancer. Moreover, we identified Artesunate as a novel topoisomerase IIalpha inhibitor that inhibits pancreatic cancer growth through modulation of multiple signaling pathways. The present analysis is a starting point for the generation of hypotheses on candidate genes and for a more detailed dissection of the functional role of individual genes for the activity of Artesunate in tumor cells.
Abstract: BACKGROUND: Trypanosome gene expression is regulated almost exclusively at the post-transcriptional level, with mRNA degradation playing a decisive role. When trypanosomes are transferred from the blood of a mammal to the midgut of a Tsetse fly, they transform to procyclic forms: gene expression is reprogrammed, changing the cell surface and switching the mode of energy metabolism. Within the blood, trypanosomes can pre-adapt for Tsetse transmission, becoming growth-arrested stumpy forms. We describe here the transitions in gene expression that occur during differentiation of in-vitro cultured bloodstream forms to procyclic forms. RESULTS: Some mRNAs showed changes within 30 min of cis-aconitate addition, whereas others responded 12-24 hours later. For the first 12 h after addition of cis-aconitate, cells accumulated at the G1 phase of the cell cycle, and showed decreases in mRNAs required for proliferation, mimicking the changes seen in stumpy forms: many mRNAs needed for ribosomal and flagellar biogenesis showed striking co-regulation. Other mRNAs encoding components of signal transduction pathways and potential regulators were specifically induced only during differentiation. Messenger RNAs encoding proteins required for individual metabolic pathways were often co-regulated. CONCLUSION: Trypanosome genes form post-transcriptional regulons in which mRNAs with functions in particular pathways, or encoding components of protein complexes, show almost identical patterns of regulation.
Abstract: Transcript profiling by microarray analysis offers a great opportunity to reveal unknown effects in a comprehensive context. To be able to interpret the data, some basic issues in experimental setting and design including type and number of replications have to be considered and are discussed in this work. In order to facilitate and automate data interpretation, the experimental data were projected and clustered by Correspondence Analysis, subsequently associated with gene ontology (GO) terms for functional classification. We applied the technology to investigate copper metabolism in the human pathogen Candida albicans. The presented dataset gives an example of how different fluorescent labeling, biological and technical replicas and data analysis strategies for microarray experiments may influence the final outcome of the results.
Abstract: The analysis of mutations that are associated with the occurrence of drug resistance is important for monitoring the antiretroviral therapy of patients infected with human immunodeficiency virus (HIV). Here, we describe the establishment and successful application of Arrayed Primer Extension (APEX) for genotypic resistance testing in HIV as a rapid and economical alternative to standard sequencing. The assay is based on an array of oligonucleotide primers that are immobilised via their 5'-ends. Upon hybridisation of template DNA, a primer extension reaction is performed in the presence of the four dideoxynucleotides, each labelled with a distinct fluorophore. The inserted label immediately indicates the sequence at the respective position. Any mutation changes the colour pattern. We designed a microarray for the analysis of 26 and 33 codons in the HIV protease and reverse transcriptase, respectively, which are of special interest with respect to drug resistance. The enormous genome variability of HIV represents a big challenge for genotypic resistance tests, which include a hybridisation step, both in terms of specificity and probe numbers. The use of degenerated oligonucleotides resulted in a significant reduction in the number of primers needed. For validation, DNA of 94 and 48 patients that exhibited resistance to inhibitors of HIV protease and reverse transcriptase, respectively, were analysed. The validation included HIV subtype B, prevalent in industrialised countries, as well as non-subtype B samples that are more common elsewhere.
Abstract: In the African trypanosome Trypanosoma brucei nearly all control of gene expression is posttranscriptional; sequences in the 3'-untranslated regions of mRNAs determine the steady-state mRNA levels by regulation of RNA turnover. Here we investigate the roles of two related proteins, TbUBP1 and TbUBP2, containing a single RNA recognition motif, in trypanosome gene expression. TbUBP1 and TbUBP2 are in the cytoplasm and nucleus, comprise ca. 0.1% of the total protein, and are not associated with polysomes or RNA degradation enzymes. Overexpression of TbUBP2 upregulated the levels of several mRNAs potentially involved in cell division, including the CFB1 mRNA, which encodes a protein with a cyclin F-box domain. CFB1 regulation was mediated by the 3'-untranslated region and involved stabilization of the mRNA. Depletion of TbUBP2 and TbUBP1 inhibited growth and downregulated expression of the cyclin F box protein gene CFB2; trans splicing was unaffected. The results of pull-down assays indicated that all tested mRNAs were bound to TbUBP2 or TbUBP1, with some preference for CFB1. We suggest that TbUBP1 and TbUBP2 may be relatively nonspecific RNA-binding proteins and that specific effects of overexpression or depletion could depend on competition between various different proteins for RNA binding.
Abstract: OBJECTIVE: Increasing use of retroviral vector-mediated gene transfer created intense interest to characterize vector integrations on the genomic level. Techniques to determine insertion sites, mainly based on time-consuming manual data processing, are commonly applied. Since a high variability in processing methods hampers further data comparison, there is an urgent need to systematically process the data arising from such analysis. METHODS: To allow large-scale and standardized comparison of insertion sites of viral vectors we developed two programs, IntegrationSeq and IntegrationMap. IntegrationSeq can trim sequences, and valid integration sequences get further processed with IntegrationMap for automatic genomic mapping. IntegrationMap retrieves detailed information about whether integrations are located in or close to genes, the name of the gene, the exact localization in the transcriptional units, and further parameters like the distance from the transcription start site to the integration. RESULTS: We validated the method using 259 files originating from integration site analysis (LM-PCR). Sequences processed by IntegrationSeq led to an increased yield of valid integration sequence detection, which were shown to be more sensitive than conventional analysis and 15 times faster, while the specificities are equal. Output files generated by IntegrationMap were found to be 99.8% identical with results retrieved by much slower conventional mapping with the ENSEMBL alignment tool. CONCLUSION: Using IntegrationSeq and IntegrationMap, a validated, fast and standardized high-throughput analysis of insertion sites can be achieved for the first time.
Abstract: BACKGROUND: Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format. RESULTS: We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel) and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design. CONCLUSION: Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details.
Abstract: MOTIVATION: The functional interpretation of microarray datasets still represents a time-consuming and challenging task. Up to now functional categories that are relevant for one or more experimental context(s) have been commonly extracted from a set of regulated genes and presented in long lists. RESULTS: To facilitate interpretation, we integrated Gene Ontology (GO) annotations into Correspondence Analysis to display genes, experimental conditions and gene-annotations in a single plot. The position of the annotations in these plots can be directly used for the functional interpretation of clusters of genes or experimental conditions without the need for comparing long lists of annotations. Correspondence Analysis is not limited in the number of experimental conditions that can be compared simultaneously, allowing an easy identification of characterizing annotations even in complex experimental settings. Due to the rapidly increasing amount of annotation data available, we apply an annotation filter. Hereby the number of displayed annotations can be significantly reduced to a set of descriptive ones, further enhancing the interpretability of the plot. We validated the method on transcription data from Saccharomyces cerevisiae and human pancreatic adenocarcinomas. AVAILABILITY: The M-CHiPS software is accessible for collaborators at http://www.mchips.org
Abstract: The class B MADS box transcription factors DEFICIENS (DEF) and GLOBOSA (GLO) of Antirrhinum majus together control the organogenesis of petals and stamens. Toward an understanding of how the downstream molecular mechanisms controlled by DEF contribute to petal organogenesis, we conducted expression profiling experiments using macroarrays comprising >11,600 annotated Antirrhinum unigenes. First, four late petal developmental stages were compared with sepals. More than 500 ESTs were identified that comprise a large number of stage-specifically regulated genes and reveal a highly dynamic transcriptional regulation. For identification of DEF target genes that might be directly controlled by DEF, we took advantage of the temperature-sensitive def-101 mutant. To enhance the sensitivity of the profiling experiments, one petal developmental stage was selected, characterized by increased transcriptome changes that reflect the onset of cell elongation processes replacing cell division processes. Upon reduction of the DEF function, 49 upregulated and 52 downregulated petal target genes were recovered. Eight target genes were further characterized in detail by RT-PCR and in situ studies. Expression of genes responding rapidly toward an altered DEF activity is confined to different petal tissues, demonstrating the complexity of the DEF function regulating diverse basic processes throughout petal morphogenesis.
Abstract: While the deciphering of basic sequence information on a genomic scale is yielding complete genomic sequences in ever-shorter intervals, experimental procedures for elucidating the cellular effects and consequences of the DNA-encoded information become critical for further analyses. In recent years, DNA microarray technology has emerged as a prime candidate for the performance of many such functional assays. Technically, array technology has come a long way since its conception some 15 years ago, initially designed as a means for large-scale mapping and sequencing.The basic arrangement, however, could be adapted readily to serve eventually as an analytical tool in a large variety of applications. On their own or in combination with other methods, microarrays open up many new avenues of functional analysis.
Abstract: BACKGROUND: While the genome sequences for a variety of organisms are now available, the precise number of the genes encoded is still a matter of debate. For the human genome several stringent annotation approaches have resulted in the same number of potential genes, but a careful comparison revealed only limited overlap. This indicates that only the combination of different computational prediction methods and experimental evaluation of such in silico data will provide more complete genome annotations. In order to get a more complete gene content of the Drosophila melanogaster genome, we based our new D. melanogaster whole-transcriptome microarray, the Heidelberg FlyArray, on the combination of the Berkeley Drosophila Genome Project (BDGP) annotation and a novel ab initio gene prediction of lower stringency using the Fgenesh software. RESULTS: Here we provide evidence for the transcription of approximately 2,600 additional genes predicted by Fgenesh. Validation of the developmental profiling data by RT-PCR and in situ hybridization indicates a lower limit of 2,000 novel annotations, thus substantially raising the number of genes that make a fly. CONCLUSIONS: The successful design and application of this novel Drosophila microarray on the basis of our integrated in silico/wet biology approach confirms our expectation that in silico approaches alone will always tend to be incomplete. The identification of at least 2,000 novel genes highlights the importance of gathering experimental evidence to discover all genes within a genome. Moreover, as such an approach is independent of homology criteria, it will allow the discovery of novel genes unrelated to known protein families or those that have not been strictly conserved between species.
Abstract: MOTIVATION: Microarray technology provides access to expression levels of thousands of genes at once, producing large amounts of data. These datasets are valuable only if they are annotated by sufficiently detailed experiment descriptions. However, in many databases a substantial number of these annotations is in free-text format and not readily accessible to computer-aided analysis. RESULTS: The Multi-Conditional Hybridization Intensity Processing System (M-CHIPS), a data warehousing concept, focuses on providing both structure and algorithms suitable for statistical analysis of a microarray database's entire contents including the experiment annotations. It addresses the rapid growth of the amount of hybridization data, more detailed experimental descriptions, and new kinds of experiments in the future. We have developed a storage concept, a particular instance of which is an organism-specific database. Although these databases may contain different ontologies of experiment annotations, they share the same structure and therefore can be accessed by the very same statistical algorithms. Experiment ontologies have not yet reached their final shape, and standards are reduced to minimal conventions that do not yet warrant extensive description. An ontology-independent structure enables updates of annotation hierarchies during normal database operation without altering the structure. AVAILABILITY AND SUPPLEMENTARY INFORMATION: http://www.dkfz.de/tbi/services/mchips
Abstract: Management and analysis of the huge amounts of data produced by microarray experiments is becoming one of the major bottlenecks in the utilization of this high-throughput technology. We describe the basic design of a microarray gene expression database to help microarray users and their informatics teams to set up their information services. We describe two data models--a simpler one called ArrayExpressB and the complete model ArrayExpressC, and discuss some implementation issues. For latest developments see http: wwwebi.ac.uk/arrayexpress
Abstract: Plants respond to pathogen attack by deploying several defense reactions. Some rely on the activation of preformed components, whereas others depend on changes in transcriptional activity. Using cDNA arrays comprising 13,000 unique expressed sequence tags, changes in the transcriptome of Arabidopsis thaliana were monitored after attempted infection with the bacterial plant pathogen Pseudomonas syringae pv. tomato carrying the avirulence gene avrRpt2. Sampling at four time points during the first 24 h after infiltration revealed significant changes in the steady state transcript levels of approximately 650 genes within 10 min and a massive shift in gene expression patterns by 7 h involving approximately 2,000 genes representing many cellular processes. This shift from housekeeping to defense metabolism results from changes in regulatory and signaling circuits and from an increased demand for energy and biosynthetic capacity in plants fighting off a pathogenic attack. Concentrating our detailed analysis on the genes encoding enzymes in glycolysis, the Krebs cycle, the pentose phosphate pathway, the biosynthesis of aromatic amino acids, phenylpropanoids, and ethylene, we observed interesting differential regulation patterns. Furthermore, our data showed potentially important changes in areas of metabolism, such as the glyoxylate metabolism, hitherto not suspected to be components of plant defense.
Abstract: Saccharomyces cerevisiae strains frequently exhibit rather specific phenotypic features needed for adaptation to a special environment. Wine yeast strains are able to ferment musts, for example, while other industrial or laboratory strains fail to do so. The genetic differences that characterize wine yeast strains are poorly understood, however. As a first search of genetic differences between wine and laboratory strains, we performed DNA-array analyses on the typical wine yeast strain T73 and the standard laboratory background in S288c. Our analysis shows that even under normal conditions, logarithmic growth in YPD medium, the two strains have expression patterns that differ significantly in more than 40 genes. Subsequent studies indicated that these differences correlate with small changes in promoter regions or variations in gene copy number. Blotting copy numbers vs. transcript levels produced patterns, which were specific for the individual strains and could be used for a characterization of unknown samples.
Abstract: Correspondence analysis is an explorative computational method for the study of associations between variables. Much like principal component analysis, it displays a low-dimensional projection of the data, e.g., into a plane. It does this, though, for two variables simultaneously, thus revealing associations between them. Here, we demonstrate the applicability of correspondence analysis to and high value for the analysis of microarray data, displaying associations between genes and experiments. To introduce the method, we show its application to the well-known Saccharomyces cerevisiae cell-cycle synchronization data by Spellman et al. [Spellman, P. T., Sherlock, G., Zhang, M. Q., Iyer, V. R., Anders, K., Eisen, M. B., Brown, P. O., Botstein, D. & Futcher, B. (1998) Mol. Biol. Cell 9, 3273-3297], allowing for comparison with their visualization of this data set. Furthermore, we apply correspondence analysis to a non-time-series data set of our own, thus supporting its general applicability to microarray data of different complexity, underlying structure, and experimental strategy (both two-channel fluorescence-tag and radioactive labeling).
Abstract: MOTIVATION: The technology of hybridization to DNA arrays is used to obtain the expression levels of many different genes simultaneously. It enables searching for genes that are expressed specifically under certain conditions. However, the technology produces large amounts of data demanding computational methods for their analysis. It is necessary to find ways to compare data from different experiments and to consider the quality and reproducibility of the data. RESULTS: Data analyzed in this paper have been generated by hybridization of radioactively labeled targets to DNA arrays spotted on nylon membranes. We introduce methods to compare the intensity values of several hybridization experiments. This is essential to find differentially expressed genes or to do pattern analysis. We also discuss possibilities for quality control of the acquired data. AVAILABILITY: http://www.dkfz.de/tbi CONTACT: M.Vingron@dkfz-heidelberg.de
Abstract: In recent years, antibody microarrays have developed into an important tool for proteomics. As a multiplexing technique, they facilitate the highly parallel detection of hundreds of different analytes from very small sample volumes of only a few microlitres. This is combined with high sensitivity in the picomolar to femtomolar range, which is similar to the sensitivity of ELISA, the gold standard for protein quantification. In order to obtain such sensitivities in a robust and reproducible manner for sets of several hundreds of analytes simultaneously, it is essential to optimise the experimental layout, sample handling, labelling and incubation as well as data processing steps. Here, we present our current antibody microarray protocols for multiplexed expression profiling studies, which permit the analysis of the abundance of more than 800 proteins in plasma, urine and tissue samples.
