A highly specific microarray method for point mutation detection

Improvements of microarray techniques for genotyping purposes have focused on increasing the reliability of this method. Here we report the development of a genotyping method where a microarray was spotted with stemloop probes, especially designed to optimize the hybridization specificity of complementary DNA sequences. This accurate method was used to screen for four common disease-causing mutations involved in a neurological disorder called Charcot-Marie-Tooth disease (CMT). Healthy individuals' and patients' DNA were amplified and labeled by PCR and hybridized on microarray. The spot signal intensities were 81 to 408 times greater for perfect compared with mismatched target sequences, differing by only one nucleotide (discrimination ratio) for healthy individual "homozygous" DNA. On the other hand, "heterozygous" mutant DNA samples gave rise to signal intensity ratios close to 1, as expected. The genotypes obtained by this method were perfectly consistent with those determined by direct PCR sequencing. Cross-hybridization rates were very low, resulting in further multiplexing improvements. In this study, we also demonstrated the feasibility of real-time hybridization detection of labeled synthetic oligonucleotides with concentrations as low as 2.5 nM.     

Novel 3-dimensional dendrimer platform for glycolipid microarray

Glycolipids are important biological molecules that modulate cellular recognitions and pathogen adhesions. In this paper, we report a sensitive glycolipid microarray for non-covalently immobilizing glycolipids on a microarray substrate and we perform a set of immunoassays to explore glycolipid-protein interactions. This substrate utilizes a three-dimensional hydrazide-functionalized dendrimer monolayer attached onto a microscopic glass surface, which possesses the characteristics to adsorb glycoliplids non-covalently and facilitates multivalent attributes on the substrate surface. In the proof-of-concept experiments, gangliosides such as GM1, FucGM1, GM3, GD1b, GT1b, and GQ1b, and a lipoarabinomannan were tested on the substrate and interrogated with toxins and antibodies. The resulting glycolipid microarrays exhibited hypersensitivity and specificity for detection of glycolipid-protein interactions. In particular, a robust and specific binding of a pentameric cholera toxin B subunit to the GM1 glycolipid spotted on the array has demonstrated its superiority in sensitivity and specificity. In addition, this glycolipid microarray substrate was used to detect lipoarabinomannan in buffer within a limit-of-detection of 125 ng/mL. Furthermore, Mycobacterium tuberculosis (Mtb) Lipoarabinomannan was tested in human urine specimens on this platform, which can effectively identify urine samples either infected or not infected with Mtb. The results of this work suggest the possibility of using this glycolipid microarray platform to fabricate glycoconjugate microarrays, which includes free glycans and glycolipids and potential application in detection of pathogen and toxin.     

A DNA microarray platform based on direct detection of rRNA for characterization of freshwater sediment-related prokaryotic communities

A DNA microarray platform for the characterization of bacterial communities in freshwater sediments based on a heterogeneous set of 70 16S rRNA-targeted oligonucleotide probes and directly labeled environmental RNA was developed and evaluated. Application of a simple protocol for the efficient background blocking of aminosilane-coated slides resulted in an improved signal-to-noise ratio and a detection limit of 10 ng for particular 16S rRNA targets. An initial specificity test of the system using RNA from pure cultures of different phylogenetic lineages showed a fraction of false-positive signals of approximately 5% after protocol optimization and a marginal loss of correct positive signals. Subsequent microarray analysis of sediment-related community RNA from four different German river sites suggested low diversity for the groups targeted but indicated distinct differences in community composition. The results were supported by parallel fluorescence in situ hybridization in combination with sensitive catalyzed reporter deposition (CARD-FISH). In comparisons of the data of different sampling sites, specific detection of populations with relative cellular abundances down to 2% as well as a correlation of microarray signal intensities and population size is suggested. Our results demonstrate that DNA microarray technology allows for the fast and efficient precharacterization of complex bacterial communities by the use of standard single-cell hybridization probes and the direct detection of environmental rRNA, also in methodological challenging habitats such as heterogeneous lotic freshwater sediments.     

Gene structure-based splice variant deconvolution using a microarray platform

MOTIVATION: Alternative splicing allows a single gene to generate multiple mRNAs, which can be translated into functionally and structurally diverse proteins. One gene can have multiple variants coexisting at different concentrations. Estimating the relative abundance of each variant is important for the study of underlying biological function. Microarrays are standard tools that measure gene expression. But most design and analysis has not accounted for splice variants. Thus splice variant-specific chip designs and analysis algorithms are needed for accurate gene expression profiling. RESULTS: Inspired by Li and Wong (2001), we developed a gene structure-based algorithm to determine the relative abundance of known splice variants. Probe intensities are modeled across multiple experiments using gene structures as constraints. Model parameters are obtained through a maximum likelihood estimation (MLE) process/framework. The algorithm produces the relative concentration of each variant, as well as an affinity term associated with each probe. Validation of the algorithm is performed by a set of controlled spike experiments as well as endogenous tissue samples using a human splice variant array.     

Validation of fluorescence-labeled artificial nonhuman sequences for single-strand conformation polymorphism mutation detection in familial hypercholesterolemia

We developed a two-in-one, polymerase chain reaction (PCR)-based method with a specific amplification step and a universal amplification step in one tube to screen for the presence of DNA variations. The method relies on fluorescence-labeled artificial nonhuman sequences for mutation detection. To document utility, we applied this method as a high-throughput capillary single-strand conformation polymorphism screening system to identify 30 mutations in the low-density lipoprotein receptor gene. The sensitivity of mutant allele detection compared to wild-type allele detection was 93%. We conclude that the two-in-one PCR is sensitive, simple, and cost effective.     

EMMA: a platform for consistent storage and efficient analysis of microarray data

As a high throughput technique, microarray experiments produce large data sets, consisting of measured data, laboratory protocols, and experimental settings. We have implemented the open source platform EMMA to store and analyze these data. The system provides automated pipelines for data processing and has a modular architecture that can be easily extended. EMMA features detailed reports about spots and their corresponding measurements. In addition to routine data analysis algorithms, the system can be integrated with other components that contain additional data sources (e.g. genome annotation systems).     

MutS as a tool for mutation detection

MutS, a DNA mismatch-binding protein, seems to be a promising tool for mutation detection. We present three MutS based approaches to the detection of point mutations: DNA retardation, protection of mismatched DNA against exonuclease digestion, and chimeric MutS proteins. DNA retardation in polyacrylamide gels stained with SYBR-Gold allows mutation detection using 1-3 microg of Thermus thermophilus his6-MutS protein and 50-200 ng of a PCR product. The method enables the search for a broad range of mutations: from single up to several nucleotide, as mutations over three nucleotides could be detected in electrophoresis without MutS, due to the mobility shift caused by large insertion/deletion loops in heteroduplex DNA. The binding of DNA mismatches by MutS protects the complexed DNA against exonuclease digestion. The direct addition of the fluorescent dye, SYBR-Gold, allows mutation detection in a single-tube assay. The limited efficiency of T4 DNA polymerase as an exonuclease hampers the application of the method in practice. The assay required 300-400 ng of PCR products in the range of 200-700 bp and 1-3 microg of MutS. MutS binding to mismatched DNA immobilised on a solid phase can be observed thanks to the activity of a reporter domain linked to MutS. We obtained chimeric bifunctional proteins consisting of T. thermophilus MutS and reporter domains, like beta-galactosidase or GFP. Very low detection limits for beta-galactosidase could theoretically enable mutation detection not only by the examination of PCR products, but even of genomic DNA.     

WebArray: an online platform for microarray data analysis

Background  

Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments.     

Development of DNA microarray for pathogen detection

Pathogens pose a significant threat to humans, animals, and plants. Consequently, a considerable effort has been devoted to developing rapid, convenient, and accurate assays for the detection of these unfavorable organisms. Recently, DNA-microarray based technology is receiving much attention as a powerful tool for pathogen detection. After the target gene is first selected for the unique identification of microorganisms, species-specific probes are designed through bioinformatic analysis of the sequences, which uses the information present in the databases. DNA samples, which were obtained from reference and/or clinical isolates, are properly processed and hybridized with species-specific probes that are immobilized on the surface of the microarray for fluorescent detection. In this study, we review the methods and strategies for the development of DNA microarray for pathogen detection, with the focus on probe design.     

Validation of an in vitro screen for phospholipidosis using a high-content biology platform

Several cationic amphiphilic drugs cause local or systemic phospholipidosis (PLD) after chronic exposure in preclinical species. PLD is characterized by the accumulation of drug, phospholipid, and concentric lamellar bodies in cellular lysosomes. We have developed a fluorescence-based in vitro screen that is predictive of PLD using the Cellomics ArrayScan high-content screening platform, which captures and analyzes images from 96-well cell culture microtiter plates using multichannel fluorescence microscopy. I-13.35 adherent mouse spleen macrophage cells were cultured with drug and a fluorescently tagged phospholipid, N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)-1,2-dihexadecanoyl-sn-glycero-3-phosphoethanolamine (NBD-PE). Drug concentrations were used in a range from 1 to $100 μmol/L. After 24 h incubations, the cells were fixed with formalin. NBD-PE uptake was quantified in controls and treated cells. Nuclei were identified by Hoechst 33258 staining and dead cells were identified using ethidium homodimer-2 incorporation. Thus, confounding accumulation of NBD-PE due to cytotoxicity that produces false-positive results at high concentrations was eliminated from quantitation by ethidium staining and employing cell gating (dead cell rejection). The assay was found to be both sensitive and selective in that 26 of 28 positive, phospholipidogenic controls and 8 of 8 negative, nonphospholipidogenic controls were correctly called.     

A web-based platform for rice microarray annotation and data analysis

Rice (Oryza sativa) feeds over half of the global population. A web-based integrated platform for rice microarray annotation and data analysis in various biological contexts is presented, which provides a convenient query for comprehensive annotation compared with similar databases. Coupled with existing rice microarray data, it provides online analysis methods from the perspective of bioinformatics. This comprehensive bioinformatics analysis platform is composed of five modules, including data retrieval, microarray annotation, sequence analysis, results visualization and data analysis. The BioChip module facilitates the retrieval of microarray data information via identifiers of “Probe Set ID”, “Locus ID” and “Analysis Name”. The BioAnno module is used to annotate the gene or probe set based on the gene function, the domain information, the KEGG biochemical and regulatory pathways and the potential microRNA which regulates the genes. The BioSeq module lists all of the related sequence information by a microarray probe set. The BioView module provides various visual results for the microarray data. The BioAnaly module is used to analyze the rice microarray’s data set.     

MASQOT-GUI: spot quality assessment for the two-channel microarray platform

MASQOT-GUI provides an open-source, platform-independent software pipeline for two-channel microarray spot quality control. This includes gridding, segmentation, quantification, quality assessment and data visualization. It hosts a set of independent applications, with interactions between the tools as well as import and export support for external software. The implementation of automated multivariate quality control assessment, which is a unique feature of MASQOT-GUI, is based on the previously documented and evaluated MASQOT methodology. Further abilities of the application are outlined and illustrated. AVAILABILITY: MASQOT-GUI is Java-based and licensed under the GNU LGPL. Source code and installation files are available for download at http://masqot-gui.sourceforge.net/     

A secreted protein microarray platform for extracellular protein interaction discovery

Characterization of the extracellular protein interactome has lagged far behind that of intracellular proteins, where mass spectrometry and yeast two-hybrid technologies have excelled. Improved methods for identifying receptor-ligand and extracellular matrix protein interactions will greatly accelerate biological discovery in cell signaling and cellular communication. These technologies must be able to identify low-affinity binding events that are often observed between membrane-bound coreceptor molecules during cell-cell or cell-extracellular matrix contact. Here we demonstrate that functional protein microarrays are particularly well-suited for high-throughput screening of extracellular protein interactions. To evaluate the performance of the platform, we screened a set of 89 immunoglobulin (Ig)-type receptors against a highly diverse extracellular protein microarray with 686 genes represented. To enhance detection of low-affinity interactions, we developed a rapid method to assemble bait Fc fusion proteins into multivalent complexes using protein A microbeads. Based on these screens, we developed a statistical methodology for hit calling and identification of nonspecific interactions on protein microarrays. We found that the Ig receptor interactions identified using our methodology are highly specific and display minimal off-target binding, resulting in a 70% true-positive to false-positive hit ratio. We anticipate that these methods will be useful for a wide variety of functional protein microarray users.     

Glycopeptide microarray for autoantibody detection in cancer

Evaluation of: Pedersen JW, Blixt O, Bennett EP et al. Seromic profiling of colorectal cancer patients with novel glycopeptide microarray. Int. J. Cancer 128(8), 1860–1871 (2011).

Autoantibodies to cancer-associated antigens hold promise as sensitive biomarkers for cancer detection. Based on this hypothesis, and knowing that O-glycans on proteins constitute a source of possible epitopes recognized by autoantibodies, Pedersen and colleagues have generated a glycopeptide array displaying a comprehensive library of glycopeptides and glycoproteins derived from human mucins. The profiling of sera immunoreactivity of colon cancer patients allowed the identification of cancer-associated autoantibodies to various mucin (MUC)1 and MUC4 glycopeptides carrying aberrant glycosylation. This article provides evidence for the value of glycopeptides displaying cancer-associated glycans in diagnostic applications, and opens new avenues for the expansion to other protein glycoforms, as well as to further applications of such a microarray strategy for other post-translational modifications of proteins in the search for cancer biomarker.     

Methylation detection oligonucleotide microarray analysis: a high-resolution method for detection of CpG island methylation

Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non-associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25 000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter-associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.     

Glycopeptide microarray for autoantibody detection in cancer

Evaluation of: Pedersen JW, Blixt O, Bennett EP et al. Seromic profiling of colorectal cancer patients with novel glycopeptide microarray. Int. J. Cancer 128(8), 1860-1871 (2011). Autoantibodies to cancer-associated antigens hold promise as sensitive biomarkers for cancer detection. Based on this hypothesis, and knowing that O-glycans on proteins constitute a source of possible epitopes recognized by autoantibodies, Pedersen and colleagues have generated a glycopeptide array displaying a comprehensive library of glycopeptides and glycoproteins derived from human mucins. The profiling of sera immunoreactivity of colon cancer patients allowed the identification of cancer-associated autoantibodies to various mucin (MUC)1 and MUC4 glycopeptides carrying aberrant glycosylation. This article provides evidence for the value of glycopeptides displaying cancer-associated glycans in diagnostic applications, and opens new avenues for the expansion to other protein glycoforms, as well as to further applications of such a microarray strategy for other post-translational modifications of proteins in the search for cancer biomarker.