Application of Fluolid-Orange-labeled probes for DNA microarray and immunological assays

The usefulness of Fluolid-Orange, a novel fluorescent dye, for DNA microarray and immunological assays has been examined. Fluolid-Orange-labeled probes (DNA and IgG) were stable as examined by laser-photo-bleaching and under heat and dry conditions. Statistical analyses were performed to evaluate the reproducibility of the microarray assay, while stage-specific immunostaining of marker proteins, Kank1 and calretinin, was performed for renal cancers, both giving satisfactory results. The stability of the dye should provide advantages for storing fluorescently labeled probes and re-examining the specimens later in genetic and pathological diagnostics.     

Statistical methods for microarray assays

The paper shortly reviews statistical methods used in the area of DNA microarray studies. All stages of the experiment are taken into account: planning, data collection, data preprocessing, analysis and validation. Among the methods of data analysis, the algorithms for estimating differential expression, multivariate approaches, clustering methods, as well as classification and discrimination are reviewed. The need is stressed for routine statistical data processing protocols and for the search of links of microarray data analysis with quantitative genetic models.     

Possible sources of dye-related signal correlation bias in two-color DNA microarray assays

DNA microarray analyses commonly use two spectrally distinct fluorescent labels to simultaneously compare different mRNA pools. Signal correlation bias currently limits accepted resolution to twofold changes in gene expression. This bias was investigated by (i) examining fluorescence and absorption spectra and changes in relative fluorescence of DNAs labeled with the Cy3, Cy5, Alexa Fluor 555, and Alexa Fluor 647 dyes and by (ii) using homotypic hybridization assays to compare the Cy dye pair with the Alexa Fluor dye pair. Cy3 or Cy5 dye-labeled DNA exhibited reduced fluorescence and absorption anomalies that were eliminated by nuclease treatment, consistent with fluorescence quenching that arises from dye-dye or dye-DNA-dye interactions. Alexa Fluor 555 and Alexa Fluor 647 dye-labeled DNA exhibited little or no such anomalies. In microarray hybridization, the Alexa Fluor dye pair provided higher signal correlation coefficients (R2) than did the Cy dye pair; at the 95% prediction level, a 1.3-fold change in gene expression was significant using the Alexa Fluor dye pair. Lowered signal correlation of the Cy dye pair was associated with high variance in Cy5 dye signals. These results indicate that fluorescence quenching may be a source of signal bias associated with the Cy dye pair.     

A mixture model for estimating the local false discovery rate in DNA microarray analysis

MOTIVATION: Statistical methods based on controlling the false discovery rate (FDR) or positive false discovery rate (pFDR) are now well established in identifying differentially expressed genes in DNA microarray. Several authors have recently raised the important issue that FDR or pFDR may give misleading inference when specific genes are of interest because they average the genes under consideration with genes that show stronger evidence for differential expression. The paper proposes a flexible and robust mixture model for estimating the local FDR which quantifies how plausible each specific gene expresses differentially. RESULTS: We develop a special mixture model tailored to multiple testing by requiring the P-value distribution for the differentially expressed genes to be stochastically smaller than the P-value distribution for the non-differentially expressed genes. A smoothing mechanism is built in. The proposed model gives robust estimation of local FDR for any reasonable underlying P-value distributions. It also provides a single framework for estimating the proportion of differentially expressed genes, pFDR, negative predictive values, sensitivity and specificity. A cervical cancer study shows that the local FDR gives more specific and relevant quantification of the evidence for differential expression that can be substantially different from pFDR. AVAILABILITY: An R function implementing the proposed model is available at http://www.geocities.com/jg_liao/software     

A multivariate prediction model for microarray cross-hybridization

Background  

Expression microarray analysis is one of the most popular molecular diagnostic techniques in the post-genomic era. However, this technique faces the fundamental problem of potential cross-hybridization. This is a pervasive problem for both oligonucleotide and cDNA microarrays; it is considered particularly problematic for the latter. No comprehensive multivariate predictive modeling has been performed to understand how multiple variables contribute to (cross-) hybridization.     

Platinum complexes for multi-parametric assays using microarray systems

Here, we present a two novel fluorescent dyes ethylenediaminechlorocholylglycinateplatinum(II), [Pt(CG)Cl(en)] complex 1and bisursodeoxycholate(ethylenediamine)platinum(II), [Pt(UDC)₂(en)] complex 2 based on well-known cis-platin chemistry. These platinum complexes contain cholylglycinate (CG) and ursodeoxycholate (UDC) as ligands. These compounds enable qualitative detection of double-helix DNA and quantitative detection (from pg to μg). These novel compounds have absorption and emission spectra in a difference range as the common ones (for example: cyanine dyes such as Cy3, Cy5, Cy7,…); therefore, it could allow the multi-parametric detection of DNA arrays, incrementing the capacity of experimental performance per one single array. As a consequence, it will increase the amount of data info obtained per chip.The combination of the intrinsic property of this compounds with the optical properties in different fluorescence channels, can allow introducing a new molecule with a wide range of possible applications in DNA arrays.     

Particle flow assays for fluorescent protein microarray applications

Microarray technology has brought a paradigmatic change in bioanalytics. However, highly sensitive and accurate assays are still needed for a real breakthrough. We present a simple and generic approach for fluorescent signal amplification with fluorescent microparticle labels. The assay principle was demonstrated using a reverse array model consisting of spots of bovine serum albumin with a small fraction of the proteins biotinylated. Specific binding of streptavidin coated fluorescent microparticles to the spots was promoted by applying a controlled continuous microparticle flow. The surface bound beads were visualized and quantified with confocal microscopy images. Comparison with standard fluorescent and flow discrimination assays has revealed several advantages of our approach. First, non-specific particle binding could be reduced to less than 1 particle/spot making therefore the visualization of single biomolecular bonds possible. Second, the amplification scheme presented here is generic and can be applied to any fluorescent microarray. Furthermore, this assay makes use of a biotin-streptavidin linkage and can therefore be applied to all kind of assays. Finally, single fluorescent microbeads can be easily visualized with standard optical equipments, so that no high performance equipment is required.     

A meta-data based method for DNA microarray imputation

Background  

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting.     

Cooperativity of paired oligonucleotide probes for microarray hybridization assays

Synthetic DNA probes attached to microarrays usually range in length from 25 to 70 nucleotides. There is a compromise between short probes with lower sensitivity, which can be accurately synthesized in higher yields, and long probes with greater sensitivity but lower synthesis yields. Described here are microarrays printed with spots containing a mixture of two short probes, each designed to hybridize at noncontiguous sites in the same targeted sequence. We have shown that, for a printed microarray, mixed probe spots containing a pair of 30mers show significantly greater hybridization than spots containing a single 30mer and can approach the amount of hybridization to spots containing a 60mer or a 70mer. These spots with mixed oligonucleotide probes display cooperative hybridization signals greater than those that can be achieved by either probe alone. Both the higher synthesis yields of short probes and the greater sensitivity of long oligonucleotides can be utilized. This strategy provides new design options for microarray hybridization assays to detect RNA abundance, RNA splice variants, or sequence polymorphisms.     

A Bayesian mixture model for metaanalysis of microarray studies

The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs control. A recent Bayesian metaanalysis model used a prior distribution for the mean log-expression ratios that was a mixture of two normal distributions. This model centered the prior distribution of differential expression at zero, and separated genes into two groups only: expressed and nonexpressed. Here, we introduce a Bayesian three-component truncated normal mixture prior model that more flexibly assigns prior distributions to the differentially expressed genes and produces three groups of genes: up and downregulated, and nonexpressed. We found in simulations of two and five studies that the three-component model outperformed the two-component model using three comparison measures. When analyzing biological data of Bacillus subtilis, we found that the three-component model discovered more genes and omitted fewer genes for the same levels of posterior probability of differential expression than the two-component model, and discovered more genes for fixed thresholds of Bayesian false discovery. We assumed that the data sets were produced from the same microarray platform and were prescaled.     

Residual DNA in thermostable DNA polymerases - a cause of irritation in diagnostic PCR and microarray assays.

In a validation trial of a DNA microarray test for chlamydiae we repeatedly observed false-positive PCR amplicons from truly negative samples and non-template controls. Various PCR tests, microarray hybridization and DNA sequencing, revealed that residual Escherichia coli DNA from thermostable DNA polymerases was the cause of this cross-reaction. A subsequent survey showed that only five out of 23 commercial polymerases were free of E. coli DNA. When designing generic oligonucleotide sequences for PCR and PCR microarray-based assays one should be aware of such possible internal contamination, particularly when the target organism is E. coli.     

Fluorescent vesicles for signal amplification in reverse phase protein microarray assays

Developments in microarray technology promise to lead to great advancements in the biomedical and biological field. However, implementation of these analytical tools often relies on signal amplification strategies that are essential to reach the sensitivity levels required for a variety of biological applications. This is true especially for reverse phase arrays where a complex biological sample is directly immobilized on the chip. We present a simple and generic method for signal amplification based on the use of antibody-tagged fluorescent vesicles as labels for signal generation. To assess the gain in assay sensitivity, we performed a model assay for the detection of rabbit immunoglobulin G (IgG) and compared the limit of detection (LOD) of the vesicle assay with the LOD of a conventional assay performed with fluorescent reporter molecules. We evaluated the improvements for two fluorescence-based transduction setups: a high-sensitivity microarray reader (ZeptoREADER) and a conventional confocal scanner. In all cases, our strategy led to an increase in sensitivity. However, gain in sensitivity widely depended on the type of illumination; whereas an approximately 2-fold increase in sensitivity was observed for readout based on evanescent field illumination, the contribution was as high as more than 200-fold for confocal scanning.     

A low-density DNA microarray for analysis of markers in breast cancer

Breast cancer remains a major cause of death in women from Western countries. In the near future, advances in both nucleic acids technology and tumor biology should be widely exploited to improve the diagnosis, prognosis, and outcome prediction of this disease. The DNA microarray, also called biochip, is a promising tool for performing massive, simultaneous, fast, and standardized analyses of multiple molecular markers in tumor samples. However, most currently available microarrays are expensive, which is mainly due to the amount (several thousands) of different DNA capture sequences that they carry. While these high-density microarrays are best suited for basic studies, their introduction into the clinical routine remains hypothetical. We describe here the principles of a low-density microarray, carrying only a few hundreds of capture sequences specific to markers whose importance in breast cancer is generally recognized or suggested by the current medical literature. We provide a list of about 250 of these markers. We also examine some potential difficulties (homologies between marker and/or variant sequences, size of sequences, etc.) associated with the production of such a low-cost microarray.     

A method for evaluation of the quality of DNA microarray spots

To establish a method to evaluate the quality of the printed microarray and DNA fragments' immobilization. The target gene fragments that were made with the restriction display PCR (RD-PCR) technique were printed on a superamine modified glass slide, then immobilized with UV cross-linking and heat. This chip was hybridized with universal primers that were labeled with cy3-dUTP, as well as cDNA that was labeled with cy3-dCTP, as the conventional protocol. Most of the target gene fragments on the chip showed positive signals, but the negative control showed no signal, and vice versa. We established a method that enables an effective evaluation of the quality of the microarrays.     

Kinetic analysis of cAMP-activated Na+ current in the molluscan neuron. A diffusion-reaction model

cAMP-activated Na+ current (INa,cAMP) was studied in voltage-clamped neurons of the seaslug Pleurobranchaea californica. The current response to injected cAMP varied in both time course and amplitude as the tip of an intracellular injection electrode was moved from the periphery to the center of the neuron soma. The latency from injection to peak response was dependent on the amount of cAMP injected unless the electrode was centered within the cell. Decay of the INa,cAMP response was slowed by phosphodiesterase inhibition. These observations suggest that the kinetics of the INa,cAMP response are governed by cAMP diffusion and degradation. Phosphodiesterase inhibition induced a persistent inward current. At lower concentrations of inhibitor, INa,cAMP response amplitude increased as expected for decreased hydrolysis rate of injected cAMP. Higher inhibitor concentrations decreased INa,cAMP response amplitude, suggesting that inhibitor-induced increase in native cAMP increased basal INa,cAMP and thus caused partial saturation of the current. The Hill coefficient estimated from the plot of injected cAMP to INa,cAMP response amplitude was close to 1.0. An equation modeling INa,cAMP incorporated terms for diffusion and degradation. In it, the first-order rate constant of phosphodiesterase activity was taken as the rate constant of the exponential decay of the INa,cAMP response. The stoichiometry of INa,cAMP activation was inferred from the Hill coefficient as 1 cAMP/channel. The equation closely fitted the INa,cAMP response and simulated changes in the waveform of the response induced by phosphodiesterase inhibition. With modifications to accommodate asymmetric INa,cAMP activation, the equation also simulated effects of eccentric electrode position. The simple reaction-diffusion model of the kinetics of INa,cAMP may provide a useful conceptual framework within which to investigate the modulation of INa,cAMP by neuromodulators, intracellular regulatory factors, and pharmacological agents.     

Comparing transformation methods for DNA microarray data

Background  

When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer.     

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.     

Array-A-Lizer: A serial DNA microarray quality analyzer

Background  

The proliferate nature of DNA microarray results have made it necessary to implement a uniform and quick quality control of experimental results to ensure the consistency of data across multiple experiments prior to actual data analysis.     

Real-time DNA microarray analysis

We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays.