Construction and use of spotted large-insert clone DNA microarrays for the detection of genomic copy number changes

Microarray-based comparative genomic hybridization has become a widespread method for the analysis of DNA copy number changes across the human genome. Initial methods for microarray construction using large-insert clones required the preparation of DNA from large-scale cultures. This rapidly became an expensive and time-consuming process when expanded to the number of clones needed for higher resolution arrays. To overcome this problem, several PCR-based strategies have been developed to enable array construction from small amounts of cloned DNA. Here, we describe the construction of microarrays composed of human-specific large-insert clones (40-200 kb) using a specific degenerate oligonucleotide PCR strategy. In addition, we also describe array hybridization using manual and automated procedures and methods for array analysis. The technology and protocols described in this article can easily be adapted for other species dependent on the availability of clone libraries. According to our protocols, the procedure will take approximately 3 days from labeling the DNA to scanning the hybridized slides.     

Production of bulk amounts of universal RNA for DNA microarrays

In DNA microarray technology, repeatability and reliability are very important to compare multiple RNA samplesfrom different experiments. The application of common or universal RNA as a standard control equalizes the differences in hybridization parameters and array variations. For this purpose, high-quality reference RNA is necessary in bulk amounts. A novel approach was developed to get milligrams of sense or antisense RNA, starting from micrograms of pooled total RNA from different cell lines, tissues, or organisms. This method is inexpensive and allows further labeling procedures using poly(dT) or random oligomers as primers. In addition, amplified, sense reference RNA is suitable for standard labeling protocols, while the antisense reference RNA can be used with antisense RNA from the linear sample amplification method. Here we produced universal RNA for human, rat, and alfalfa and demonstrated the quality using specific cDNA microarrays.     

Biomarker discovery from pancreatic cancer secretome using a differential proteomic approach

Quantitative proteomics can be used as a screening tool for identification of differentially expressed proteins as potential biomarkers for cancers. Candidate biomarkers from such studies can subsequently be tested using other techniques for use in early detection of cancers. Here we demonstrate the use of stable isotope labeling with amino acids in cell culture (SILAC) method to compare the secreted proteins (secretome) from pancreatic cancer-derived cells with that from non-neoplastic pancreatic ductal cells. We identified 145 differentially secreted proteins (>1.5-fold change), several of which were previously reported as either up-regulated (e.g. cathepsin D, macrophage colony stimulation factor, and fibronectin receptor) or down-regulated (e.g. profilin 1 and IGFBP-7) proteins in pancreatic cancer, confirming the validity of our approach. In addition, we identified several proteins that have not been correlated previously with pancreatic cancer including perlecan (HSPG2), CD9 antigen, fibronectin receptor (integrin beta1), and a novel cytokine designated as predicted osteoblast protein (FAM3C). The differential expression of a subset of these novel proteins was validated by Western blot analysis. In addition, overexpression of several proteins not described previously to be elevated in human pancreatic cancer (CD9, perlecan, SDF4, apoE, and fibronectin receptor) was confirmed by immunohistochemical labeling using pancreatic cancer tissue microarrays suggesting that these could be further pursued as potential biomarkers. Lastly the protein expression data from SILAC were compared with mRNA expression data obtained using gene expression microarrays for the two cell lines (Panc1 and human pancreatic duct epithelial), and a correlation coefficient (r) of 0.28 was obtained, confirming previously reported poor associations between RNA and protein expression studies.     

Assessment of methylation level prediction accuracy in methyl-DNA immunoprecipitation and sodium bisulfite based microarray platforms

In this study, we verified the accuracy of two array methods—methylated DNA immunoprecipitation coupled with CpG island microarrays (MeDIP-CGI-arrays) and sodium bisulfite conversion based microarrays (BC-arrays)—in predicting regional methylation levels as measured by pyrosequencing of bisulfite converted DNA (BC-pyrosequencing). To test the accuracy of these methods we used the Agilent Human CpG island and the Illumina HumanMethylation27 microarrays respectively, and compared microarray outputs to the data from targeted BC-pyrosequencing assays from several genomic regions of corresponding samples. We observed relatively high correlation with BC-pyrosequencing data for both array platforms, R = 0.87 for BC-Array and R = 0.79 for MeDIP-CGI array. However, MeDIP-CGI array were less reliable in predicting intermediate levels of DNA methylation. Several bioinformatics strategies, to ameliorate the performance of the MeDIP-CGI-Arrays did not improve the correlation with BC-pyrosequencing data. The high scalability, low cost and simpler analysis of BC-arrays, together with the recent extended coverage may make them a more versatile methylation analysis tool.     

Error-correcting microarray design

We describe a microarray design based on the concept of error-correcting codes from digital communication theory. Currently, microarrays are unable to efficiently deal with "drop-outs," when one or more spots on the array are corrupted. The resulting information loss may lead to decoding errors in which no quantitation of expression can be extracted for the corresponding genes. This issue is expected to become increasingly problematic as the number of spots on microarrays expands to accommodate the entire genome. The error-correcting approach employs multiplexing (encoding) of more than one gene onto each spot to efficiently provide robustness to drop-outs in the array. Decoding then allows fault-tolerant recovery of the expression information from individual genes. The error-correcting method is general and may have important implications for future array designs in research and diagnostics.     

An optimized isolation and labeling platform for accurate microRNA expression profiling

MicroRNAs (miRNAs) are small, noncoding RNAs that regulate gene expression in both plants and animals. miRNA genes have been implicated in a variety of important biological processes, including development, differentiation, apoptosis, fat metabolism, viral infection, and cancer. Similar to protein-coding messenger RNAs, miRNA expression varies between tissues and developmental states. To acquire a better understanding of global miRNA expression in tissues and cells, we have developed isolation, labeling, and array procedures to measure the relative abundance of all of the known human mature miRNAs. The method relies on rapid isolation of RNA species smaller than ~40 nucleotides (nt), direct and homogenous enzymatic labeling of the mature miRNAs with amine modified ribonucleotides, and hybridization to antisense DNA oligonucleotide probes. A thorough performance study showed that this miRNA microarray system can detect subfemtomole amounts of individual miRNAs from <1 mug of total RNA, with 98% correlation between independent replicates. The system has been applied to compare the global miRNA expression profiles in 26 different normal human tissues. This comprehensive analysis identified miRNAs that are preferentially expressed in one or a few related tissues and revealed that human adult tissues have unique miRNA profiles. This implicates miRNAs as important components of tissue development and differentiation. Taken together, these results emphasize the immense potential of microarrays for sensitive and high-throughput analysis of miRNA expression in normal and disease states.     

Monitoring of cDNA microarray with common primer target and hybridization specificity with selected targets

Academic researchers are increasingly producing and using cDNA microarrays. Their quality and hybridization specificity are crucial in determining whether the generated data are accurate and interpretable. Here, we describe two methods of monitoring microarray production, the sustainability of DNA attachment, and the specificity of hybridization. The first method consists of labeling an oligonucleotide, which is one of the primers used to amplify all cDNA probes on the array (except for beta-actin and GAPDH) with fluorescent dye and hybridize it to the cDNA microarray. Attachment of the cDNAs on the array after the hybridization procedure was monitored by visualizing fluorescent signals from the spots on the array. In the second method, two selected DNA targets, beta-actin and GAPDH, were labeled with fluorescent dye to hybridize to the cDNA array. Hence, hybridization specificity was demonstrated by obtaining fluorescent signals solely from the genes corresponding to the target.     

Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based on enrichment of cellular subproteomes prior to mass spectrometric analysis can provide increased coverage of certain classes of molecules. We used a membrane protein enrichment strategy coupled with 18O labeling based quantitative proteomics to identify proteins that are highly expressed in cholangiocarcinomas. In addition to identifying several proteins previously known to be overexpressed in cholangiocarcinoma, we discovered a number of molecules that were previously not associated with cholangiocarcinoma. Using immunoblotting and immunohistochemical labeling of tissue microarrays, we validated Golgi membrane protein 1, Annexin IV and Epidermal growth factor receptor pathway substrate 8 (EPS8) as candidate biomarkers for cholangiocarcinomas. Golgi membrane protein 1 was observed to be overexpressed in 89% of cholangiocarcinoma cases analyzed by staining tissue microarrays. In light of recent reports showing that Golgi membrane protein 1 is detectable in serum, further investigation into validation of this protein has the potential to provide a biomarker for early detection of cholangiocarcinomas.     

A Strategy to Optimize the Oligo-Probes for Microarray-based Detection of Viruses

DNA microarrays have been acknowledged to represent a promising approach for the detection of viral pathogens. However, the probes designed for current arrays could cover only part of the given viral variants, that could result in false-negative or ambiguous data. If all the variants are to be covered, the requirement for more probes would render much higher spot density and thus higher cost of the arrays. Here we have developed a new strategy for oligonucleotide probe design. Using type I human immunodeficiency virus (HIV-1) tat gene as an example, we designed the array probes and validated the optimized parameters in silico. Results show that the oligo number is significantly reduced comparing with the existing methods, while specificity and hybridization efficiency remain intact. The adoption of this method in reducing the oligo numbers could increase the detection capacity for DNA microarrays, and would significantly lower the manufacturing cost for making array chips.     

Restriction site tagged (RST) microarrays: a novel technique to study the species composition of complex microbial systems

We have developed a new type of microarray, restriction site tagged (RST), for example NotI, microarrays. In this approach only sequences surrounding specific restriction sites (i.e. NotI linking clones) were used for generating microarrays. DNA was labeled using a new procedure, NotI representation, where only sequences surrounding NotI sites were labeled. Due to these modifications, the sensitivity of RST microarrays increases several hundred-fold compared to that of ordinary genomic microarrays. In a pilot experiment we have produced NotI microarrays from Gram-positive and Gram-negative bacteria and have shown that even closely related Escherichia coli strains can be easily discriminated using this technique. For example, two E.coli strains, K12 and R2, differ by less than 0.1% in their 16S rRNA sequences and thus the 16S rRNA sequence would not easily discriminate between these strains. However, these strains showed distinctly different hybridization patterns with NotI microarrays. The same technique can be adapted to other restriction enzymes as well. This type of microarray opens the possibility not only for studies of the normal flora of the gut but also for any problem where quantitative and qualitative analysis of microbial (or large viral) genomes is needed.     

A novel antibody microarray format using non-covalent antibody immobilization with chemiluminescent detection

To date, protein and antibody microarrays have been used in reverse-phase and sandwich-based methods in order to detect known proteins such as biomarkers in samples. Our group developed "libraries" of antibodies against unknown proteins, referred to as mKIAA proteins, and we attempted to discover candidate novel biomarkers by protein expression profiling.To profile mKIAA protein expression using these antibodies, we established an antibody microarray system using chemiluminescent detection. A number of techniques for protein-antibody microarrays have been reported; however, no entirely suitable protocol for crude protein samples has been established. To address this issue, we immobilized purified antibodies on hydrophilic surface polymer slides (Maxisorp, Nunc). Although our system is based on the direct labeling of crude protein samples, we achieved sufficient sensitivity (detection limit: 50 pg mL(-1)) and low backgrounds. This sensitivity is on a level with the sandwich immunoassay-based antibody array system. Using our protocol, we developed an antibody microarray spotted with 960 anti-mKIAA antibodies (total: 3888 spots for quadruplicate assessments), and we carried out protein expression profiling of mKIAA proteins. In this study, we generated an expression profile of 960 mKIAA proteins and compared the present results with those obtained via cDNA microarray.     

SW-ARRAY: a dynamic programming solution for the identification of copy-number changes in genomic DNA using array comparative genome hybridization data

Comparative genome hybridization (CGH) to DNA microarrays (array CGH) is a technique capable of detecting deletions and duplications in genomes at high resolution. However, array CGH studies of the human genome noting false negative and false positive results using large insert clones as probes have raised important concerns regarding the suitability of this approach for clinical diagnostic applications. Here, we adapt the Smith–Waterman dynamic-programming algorithm to provide a sensitive and robust analytic approach (SW-ARRAY) for detecting copy-number changes in array CGH data. In a blind series of hybridizations to arrays consisting of the entire tiling path for the terminal 2 Mb of human chromosome 16p, the method identified all monosomies between 267 and 1567 kb with a high degree of statistical significance and accurately located the boundaries of deletions in the range 267–1052 kb. The approach is unique in offering both a nonparametric segmentation procedure and a nonparametric test of significance. It is scalable and well-suited to high resolution whole genome array CGH studies that use array probes derived from large insert clones as well as PCR products and oligonucleotides.     

High reproducibility using sodium hydroxide-stripped long oligonucleotide DNA microarrays

Recently, long oligonucleotide (60- to 70-mer) microarrays for two-color experiments have been developed and are gaining widespread use. In addition, when there is limited availability of mRNA from tissue sources, RNA amplification can and is being used to produce sufficient quantities of cRNA for microarray hybridization. Taking advantage of the selective degradation of RNA under alkaline conditions, we have developed a method to "strip" glass-based oligonucleotide microarrays that use fluorescent RNA in the hybridization, while leaving the DNA oligonucleotide probes intact and usable for a second experiment. Replicate microarray experiments conducted using stripped arrays showed high reproducibility, however, we found that arrays could only be stripped and reused once without compromising data quality. The intraclass correlation (ICC) between a virgin array and a stripped array hybridized with the same sample showed a range of 0.90-0.98, which is comparable to the ICC of two virgin arrays hybridized with the same sample. Using this method, once-stripped oligonucleotide microarrays are usable, reliable, and help to reduce costs.     

A strategy to optimize the oligo-probes for microarray-based detection of viruses

DNA microarrays have been acknowledged to represent a promising approach for the detection of viral pathogens. However, the probes designed for current arrays could cover only part of the given viral variants, that could result in false-negative or ambiguous data. If all the variants are to be covered, the requirement for more probes would render much higher spot density and thus higher cost of the arrays. Here we have developed a new strategy for oligonucleotide probe design. Using type I human immunodeficiency virus (HIV-1) tat gene as an example, we designed the array probes and validated the optimized parameters in silico. Results show that the oligo number is significantly reduced comparing with the existing methods, while specificity and hybridization efficiency remain intact. The adoption of this method in reducing the oligo numbers could increase the detection capacity for DNA microarrays, and would significantly lower the manufacturing cost for making array chips. These authors contribute equally to the work.     

Development of multiplexed protein profiling and detection using near infrared detection of reverse-phase protein microarrays

Protein microarrays have been recently employed for signal pathway profiling and high-throughput protein expression analysis. Reversephase arrays, where the array consists of immobilized analytes and lysates has especially shown promise in low abundance analyte detection and signal pathway profiling using phospho-specific antibodies. A limitation to current reverse phase array methodology is the inability to multiplex proteomic-based endpoints as each array can only report one analyte endpoint. In this study, we report on the use of a dual dye based approach that can effectively double the number of endpoints observed per array allowing, for example, both phosphospecific and total protein levels to be measured and analyzed at once. The method utilizes antibody bound dyes that emit in the infrared spectral region as a means of sensitive and specific detection.