Functional interpretation of microarray experiments

Over the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.     

Study of stem cell function using microarray experiments

DNA Microarrays are used to simultaneously measure the levels of thousands of mRNAs in a sample. We illustrate here that a collection of such measurements in different cell types and states is a sound source of functional predictions, provided the microarray experiments are analogous and the cell samples are appropriately diverse. We have used this approach to study stem cells, whose identity and mechanisms of control are not well understood, generating Affymetrix microarray data from more than 200 samples, including stem cells and their derivatives, from human and mouse. The data can be accessed online (StemBase; http://www.scgp.ca:8080/StemBase/).     

Evaluation of microarray data normalization procedures using spike-in experiments

Background  

Recently, a large number of methods for the analysis of microarray data have been proposed but there are few comparisons of their relative performances. By using so-called spike-in experiments, it is possible to characterize the analyzed data and thereby enable comparisons of different analysis methods.     

Gene expression profiling in human esophageal cancers using cDNA microarray

Human esophageal cancer cell lines and human esophageal cancer tissues were profiled on cDNA microarrays. In esophageal cancer cell lines, KYAE and OE-33 (adenocarcinomas) were distinguished from KYSE series (squamous cell carcinomas). Although SK-GT-4 and TE7 were derived from adenocarcinomas, they had a comparatively similar expression profile to the KYSE series. A set of genes whose expression commonly either increased or decreased in cancer cell lines was identified. Genes that were characteristically expressed in KYAE and OE-33 were also identified. The gene expression profiles of cancer tissues (CTs) were remarkably different from those of the cancer cell lines (CCLs). Notable differences between CCLs and CTs were observed in matrix metalloproteinases, plasminogen activator, collagens, paxillin, and thrombospondin 2, etc., whose expression was not increased in CCLs but increased in CTs. Twenty-three genes were extracted to categorize patients according to their prognoses, and clustering analyses, using these genes, were performed successfully.     

Biomarker discovery using protein microarray technology platforms: antibody-antigen complex profiling

Protein microarrays represent an important new tool in proteomic systems biology. This review focuses on the contributions of protein microarrays to the discovery of novel disease biomarkers through antibody-based assays. Of particular interest is the use of protein microarrays for immune response profiling, through which a disease-specific antibody repertoire may be defined. The antigens and antibodies revealed by these studies are useful for clinical assay development, with enormous potential to aid in diagnosis, prognosis, disease staging and treatment selection. The discovery and characterization of novel biomarkers specifically tailored to disease type and stage are expected to enable personalized medicine by facilitating preventative medicine, predictive diagnostics and individualized curative therapies.     

Affinity profiling using the peptide microarray technology: a case study

Little about the reliability of measurements obtained using synthetic peptide microarrays is known. We report results from a study on the quantitative reliability of microarrays manufactured by robot-supported immobilization of presynthesized peptides for different microarray platforms. Technological precision is assessed for inter- and intra-device readout comparisons. Correlations between measured signals and known dissociation constants using a phenomenological model derived from the mass action law are discussed. Special emphasis is on discussing the pitfalls of high-throughput affinity measurements. We show that the quantitative determination of binding affinities is prone to be biased toward a mean affinity of around 10(-7)M, while the classification of peptides into either "binders" or "nonbinders" provides very high prediction accuracy. The experimental requirements needed to obtain reliable binding affinity predictions are discussed.     

Assessment of repeated microarray experiments using mixed tissue RNA reference samples

Genome-scale gene expression technologies are increasingly being applied for biological research as a whole and toxicological screening in particular. In order to monitor data quality and process drift, we adopted the use of two rat-tissue mixtures (brain, liver, kidney, and testis) previously introduced as RNA reference samples. These samples were processed every time a microarray experiment was hybridized, thereby verifying the comparability of the resulting expression data for cross-study comparison. This study presents the analysis of 21 technical replicates of these two mixed-tissue samples using Affymetrix RAE230_2 GeneChip over a period of 12 months. The results show that detection sensitivity, measured by the number of present and absent sequences, is robust, and data correlation, indicated by scatter plots, varies little over time. Receiver operating characteristic (ROC) curves show the sensitivity and specificity of the current measurements are consistent with arrays previously classified as well performing. Overall, this paper shows that the inclusion of standard samples during microarray labeling and hybridization experiments is useful to benchmark the performance of microarray experiments over time and allows discovery of any process drift that, if it occurs, may confound the comparison of these datasets.     

Determination of the differentially expressed genes in microarray experiments using local FDR

Background  

Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile.     

Optimized blood cell profiling method for genomic biomarker discovery using high-density microarray

High-quality biomarkers for disease progression, drug efficacy and toxicity liability are essential for improving the efficiency of drug discovery and development. The identification of drug-activity biomarkers is often limited by access to and the quantity of target tissue. Peripheral blood has increasingly become an attractive alternative to tissue samples from organs as source for biomarker discovery, especially during early clinical studies. However, given the heterogeneous blood cell population, possible artifacts from ex vivo activations, and technical difficulties associated with overall performance of the assay, it is challenging to profile peripheral blood cells directly for biomarker discovery. In the present study, Applied BioSystems' blood collection system was evaluated for its ability to isolate RNA suitable for use on the Affymetrix microarray platform. Blood was collected in a TEMPUS tube and RNA extracted using an ABI-6100 semi-automated workstation. Using human and rat whole blood samples, it was demonstrated that the RNA isolated using this approach was stable, of high quality and was suitable for Affymetrix microarray applications. The microarray data were statistically analysed and compared with other blood protocols. Minimal haemoglobin interference with RNA labelling efficiency and chip hybridization was found using the TEMPUS tube and extraction method. The RNA quality, stability and ease of handling requirement make the TEMPUS tube protocol an attractive approach for expression profiling of whole blood to support target and biomarker discovery.     

Comprehensive profiling of accessible surface glycans of mammalian sperm using a lectin microarray

It is well known that cell surface glycans or glycocalyx play important roles in sperm motility, maturation and fertilization. A comprehensive profile of the sperm surface glycans will greatly facilitate both basic research (sperm glycobiology) and clinical studies, such as diagnostics of infertility. As a group of natural glycan binders, lectin is an ideal tool for cell surface glycan profiling. However, because of the lack of effective technology, only a few lectins have been tested for lectin-sperm binding profiles. To address this challenge, we have developed a procedure for high-throughput probing of mammalian sperm with 91 lectins on lectin microarrays. Normal sperm from human, boar, bull, goat and rabbit were collected and analyzed on the lectin microarrays. Positive bindings of a set of ~50 lectins were observed for all the sperm of 5 species, which indicated a wide range of glycans are on the surface of mammalian sperm. Species specific lectin bindings were also observed. Clustering analysis revealed that the distances of the five species according to the lectin binding profiles are consistent with that of the genome sequence based phylogenetic tree except for rabbit. The procedure that we established in this study could be generally applicable for sperm from other species or defect sperm from the same species. We believe the lectin binding profiles of the mammalian sperm that we established in this study are valuable for both basic research and clinical studies.     

Optimized blood cell profiling method for genomic biomarker discovery using high-density microarray

High-quality biomarkers for disease progression, drug efficacy and toxicity liability are essential for improving the efficiency of drug discovery and development. The identification of drug-activity biomarkers is often limited by access to and the quantity of target tissue. Peripheral blood has increasingly become an attractive alternative to tissue samples from organs as source for biomarker discovery, especially during early clinical studies. However, given the heterogeneous blood cell population, possible artifacts from ex vivo activations, and technical difficulties associated with overall performance of the assay, it is challenging to profile peripheral blood cells directly for biomarker discovery. In the present study, Applied BioSystems’ blood collection system was evaluated for its ability to isolate RNA suitable for use on the Affymetrix microarray platform. Blood was collected in a TEMPUS tube and RNA extracted using an ABI-6100 semi-automated workstation. Using human and rat whole blood samples, it was demonstrated that the RNA isolated using this approach was stable, of high quality and was suitable for Affymetrix microarray applications. The microarray data were statistically analysed and compared with other blood protocols. Minimal haemoglobin interference with RNA labelling efficiency and chip hybridization was found using the TEMPUS tube and extraction method. The RNA quality, stability and ease of handling requirement make the TEMPUS tube protocol an attractive approach for expression profiling of whole blood to support target and biomarker discovery.     

A novel strategy for mammalian cell surface glycome profiling using lectin microarray

The glycome represents the total set of glycans expressed in a cell. The glycome has been assumed to vary between cell types, stages of development and differentiation, and during malignant transformation. Analysis of the glycome provides a basis for understanding the functions of glycans in these cellular processes. Recently, a technique called lectin microarray was developed for rapid profiling of glycosylation, although its use was mainly restricted to glycoproteins of cell lysates, and thus unable to profile the intact cell surface glycans. Here we report a simple and sensitive procedure based on this technology for direct analysis of the live mammalian cell-surface glycome. Fluorescent-labeled live cells were applied in situ to the established lectin microarray consisting of 43 immobilized lectins with distinctive binding specificities. After washing, bound cells were directly detected by an evanescent-field fluorescence scanner in a liquid phase without fixing and permeabilization. The results obtained by differential profiling of CHO and its glycosylation-defective mutant cells, and splenocytes of wild-type and beta1-3-N-acetylglucosaminyltransferase II knockout mice performed as model experiments agreed well with their glycosylation phenotypes. We also compared cell surface glycans of K562 cells before and after differentiation and found a significant increase in the expression of O-glycans on differentiated cells. These results demonstrate that the technique provides a novel strategy for profiling global changes of the mammalian cell surface glycome.     

Whole genome expression profiling using DNA microarray for determining biocompatibility of polymeric surfaces

There is an ever increasing need to find surfaces that are biocompatible for applications like medical implants and microfluidics-based cell culture systems. The biocompatibility of five different surfaces with different hydrophobicity was determined using gene expression profiling as well as more conventional methods to determine biocompatibility such as cellular growth rate, morphology and the hydrophobicity of the surfaces. HeLa cells grown on polymethylmethacrylate (PMMA) or a SU-8 surface treated with HNO3-ceric ammonium nitrate (HNO3-CAN) and ethanolamine showed no differences in growth rate, morphology or gene expression profiles as compared to HeLa cells grown in cell culture flasks. Cells grown on SU-8 treated with only HNO3-CAN showed almost the same growth rate (36 +/- 1 h) and similar morphology as cells grown in cell culture flasks (32 +/- 1 h), indicating good biocompatibility. However, more than 200 genes showed different expression levels in cells grown on SU-8 treated with HNO3-CAN compared to cells grown in cell culture flasks. This shows that gene expression profiling is a simple and precise method for determining differences in cells grown on different surfaces that are otherwise difficult to find using conventional methods. It is particularly noteworthy that no correlation was found between surface hydrophobicity and biocompatibility.