Revision of the nonequilibrium thermal dissociation and stringent washing approaches for identification of mixed nucleic acid targets by microarrays

A Novel Method That Allows SNP Discrimination with 160:1 Ratio for Biosensors Based on DNA-DNA Hybridization

Highly sensitive (high SBR) and highly specific (high SNP discrimination ratio) DNA hybridization is essential for a biosensor with clinical application. Herein, we propose a method that allows detecting multiple pathogens on a single platform with the SNP discrimination ratios over 160:1 in the dynamic range of 10¹ to 10⁴ copies per test. The newly developed SWAT method allows achieving highly sensitive and highly specific DNA hybridizations. The detection and discrimination of the MTB and NTM strain in the clinical samples with the SBR and SNP discrimination ratios higher than 160:1 indicate the high clinical applicability of the SWAT.

A revised design for microarray experiments to account for experimental noise and uncertainty of probe response

Background

Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance.

Results

Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements.

Conclusion

The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations.

Physico-chemical foundations underpinning microarray and next-generation sequencing experiments

Hybridization of nucleic acids on solid surfaces is a key process involved in high-throughput technologies such as microarrays and, in some cases, next-generation sequencing (NGS). A physical understanding of the hybridization process helps to determine the accuracy of these technologies. The goal of a widespread research program is to develop reliable transformations between the raw signals reported by the technologies and individual molecular concentrations from an ensemble of nucleic acids. This research has inputs from many areas, from bioinformatics and biostatistics, to theoretical and experimental biochemistry and biophysics, to computer simulations. A group of leading researchers met in Ploen Germany in 2011 to discuss present knowledge and limitations of our physico-chemical understanding of high-throughput nucleic acid technologies. This meeting inspired us to write this summary, which provides an overview of the state-of-the-art approaches based on physico-chemical foundation to modeling of the nucleic acids hybridization process on solid surfaces. In addition, practical application of current knowledge is emphasized.

Modeling formamide denaturation of probe-target hybrids for improved microarray probe design in microbial diagnostics

Application of high-density microarrays to the diagnostic analysis of microbial communities is challenged by the optimization of oligonucleotide probe sensitivity and specificity, as it is generally unfeasible to experimentally test thousands of probes. This study investigated the adjustment of hybridization stringency using formamide with the idea that sensitivity and specificity can be optimized during probe design if the hybridization efficiency of oligonucleotides with target and non-target molecules can be predicted as a function of formamide concentration. Sigmoidal denaturation profiles were obtained using fluorescently labeled and fragmented 16S rRNA gene amplicon of Escherichia coli as the target with increasing concentrations of formamide in the hybridization buffer. A linear free energy model (LFEM) was developed and microarray-specific nearest neighbor rules were derived. The model simulated formamide melting with a denaturant m-value that increased hybridization free energy (ΔG°) by 0.173 kcal/mol per percent of formamide added (v/v). Using the LFEM and specific probe sets, free energy rules were systematically established to predict the stability of single and double mismatches, including bulged and tandem mismatches. The absolute error in predicting the position of experimental denaturation profiles was less than 5% formamide for more than 90 percent of probes, enabling a practical level of accuracy in probe design. The potential of the modeling approach for probe design and optimization is demonstrated using a dataset including the 16S rRNA gene of Rhodobacter sphaeroides as an additional target molecule. The LFEM and thermodynamic databases were incorporated into a computational tool (ProbeMelt) that is freely available at http://DECIPHER.cee.wisc.edu.

Identification of non-specific hybridization using an empirical equation fitted to non-equilibrium dissociation curves

Non-equilibrium dissociation curves (NEDCs) have the potential to identify non-specific hybridizations on high throughput, diagnostic microarrays. We report a simple method for the identification of non-specific signals by using a new parameter that does not rely on comparison of perfect match and mismatch dissociations. The parameter is the ratio of specific dissociation temperature (T(d-w)) to theoretical melting temperature (T(m)) and can be obtained by automated fitting of a four-parameter, sigmoid, empirical equation to the thousands of curves generated in a typical experiment. The curves fit perfect match NEDCs from an initial experiment with an R(2) of 0.998±0.006 and root mean square of 108±91 fluorescent units. Receiver operating characteristic curve analysis showed low temperature hybridization signals (20-48°C) to be as effective as area under the curve as primary data filters. Evaluation of three datasets that target 16S rRNA and functional genes with varying degrees of target sequence similarity showed that filtering out hybridizations with T(d-w)/T(m)<0.78 greatly reduced false positive results. In conclusion, T(d-w)/T(m) successfully screened many non-specific hybridizations that could not be identified using single temperature signal intensities alone, while the empirical modeling allowed a simplified approach to the high throughput analysis of thousands of NEDCs.

Was the Scanner Calibration Slide used for its intended purpose?

In the article, Scanner calibration revisited, BMC Bioinformatics 2010, 11:361, Dr. Pozhitkov used the Scanner Calibration Slide, a key product of Full Moon BioSystems to generate data in his study of microarray scanner PMT response and proposed a mathematic model for PMT response [1]. In the end, the author concluded that "Full Moon BioSystems calibration slides are inadequate for performing calibration," and recommended "against using these slides." We found these conclusions are seriously flawed and misleading, and his recommendation against using the Scanner Calibration Slide was not properly supported.

Washing scaling of GeneChip microarray expression

BACKGROUND

Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities.

RESULTS

We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM) and mismatch (MM) probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values.

CONCLUSIONS

Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental 'washing data set' which might be used by the community for developing amendments of the washing correction.

Comparing microarrays and next-generation sequencing technologies for microbial ecology research

Recent advances in molecular biology have resulted in the application of DNA microarrays and next-generation sequencing (NGS) technologies to the field of microbial ecology. This review aims to examine the strengths and weaknesses of each of the methodologies, including depth and ease of analysis, throughput and cost-effectiveness. It also intends to highlight the optimal application of each of the individual technologies toward the study of a particular environment and identify potential synergies between the two main technologies, whereby both sample number and coverage can be maximized. We suggest that the efficient use of microarray and NGS technologies will allow researchers to advance the field of microbial ecology, and importantly, improve our understanding of the role of microorganisms in their various environments.

Beyond Affymetrix arrays: expanding the set of known hybridization isotherms and observing pre-wash signal intensities

Microarray hybridization studies have attributed the nonlinearity of hybridization isotherms to probe saturation and post-hybridization washing. Both processes are thought to distort ‘true’ target abundance because immobilized probes are saturated with excess target and stringent washing removes loosely bound targets. Yet the paucity of studies aimed at understanding hybridization and dissociation makes it difficult to align physicochemical theory to microarray results. To fill the void, we first examined hybridization isotherms generated on different microarray platforms using a ribosomal RNA target and then investigated hybridization signals at equilibrium and after stringent wash. Hybridization signal at equilibrium was achieved by treating the microarray with isopropanol, which prevents nucleic acids from dissolving into solution. Our results suggest that (i) the shape of hybridization isotherms varied by microarray platform with some being hyperbolic or linear, and others following a power-law; (ii) at equilibrium, fluorescent signal of different probes hybridized to the same target were not similar even with excess of target and (iii) the amount of target removed by stringent washing depended upon the hybridization time, the probe sequence and the presence/absence of nonspecific targets. Possible physicochemical interpretations of the results and future studies are discussed.

Effects of formamide on the thermal stability of DNA duplexes on biochips

In molecular biology, formamide (FA) is a commonly used denaturing agent for DNA. Although its influence on DNA duplex stability in solution is well established, little is known about immobilized DNA on microarrays. We measured thermal denaturation curves for oligonucleotides immobilized by two standard protocols: thiol self-assembling and pyrrole electrospotting. A decrease of the DNA denaturation temperature with increasing FA fraction of the solvent was observed on sequences with mutations for both surface chemistries. The average dissociation temperature decrease was found to be -0.58+/-0.05 degrees C/% FA (v/v) independently of grafting chemistry and probe sequence.

Kinetic and thermodynamic characterization of single-mismatch discrimination using single-molecule imaging

A single-molecule detection setup based on total internal reflection fluorescence (TIRF) microscopy has been used to investigate association and dissociation kinetics of unlabeled 30mer DNA strands. Single-molecule sensitivity was accomplished by letting unlabeled DNA target strands mediate the binding of DNA-modified and fluorescently labeled liposomes to a DNA-modified surface. The liposomes, acting as signal enhancer elements, enabled the number of binding events as well as the residence time for high affinity binders (K_d < 1 nM, k_off < 0.01 s⁻¹) to be collected under equilibrium conditions at low pM concentrations. The mismatch discrimination obtained from the residence time data was shown to be concentration and temperature independent in intervals of 1–100 pM and 23–46°C, respectively. This suggests the method as a robust means for detection of point mutations at low target concentrations in, for example, single nucleotide polymorphism (SNP) analysis.

Real-time DNA microarrays: reality check

DNA microarrays are plagued with inconsistent quantifications and false-positive results. Using established mechanisms of surface reactions, we argue that these problems are inherent to the current technology. In particular, the problem of multiplex non-equilibrium reactions cannot be resolved within the framework of the existing paradigm. We discuss the advantages and limitations of changing the paradigm to real-time data acquisition similar to real-time PCR methodology. Our analysis suggests that the fundamental problem of multiplex reactions is not resolved by the real-time approach itself. However, by introducing new detection chemistries and analysis approaches, it is possible to extract target-specific quantitative information from real-time microarray data. The possible scope of applications for real-time microarrays is discussed.

Probes containing runs of guanines provide insights into the biophysics and bioinformatics of Affymetrix GeneChips

The reliable interpretation of Affymetrix GeneChip data is a multi-faceted problem. The interplay between biophysics, bioinformatics and mining of GeneChip surveys is leading to new insights into how best to analyse the data. Many of the molecular processes occurring on the surfaces of GeneChips result from the high surface density of probes. Interactions between neighbouring adjacent probes affect their rate and strength of hybridization to targets. Competing targets may hybridize to the same probe, and targets may partially bind to more than one probe. The formation of these partial hybrids results in a number of probes not reaching thermodynamic equilibrium during hybridization. Moreover, some targets fold up, or cross-hybridize to other targets. Furthermore, probes may fold and can undergo chemical saturation. There are also sequence-dependent differences in the rates of target desorption during the washing stage. Improvements in the mappings between probe sequence and biological databases are leading to more accurate gene expression profiles. Moreover, algorithms that combine the intensities of multiple probes into single measures of expression are increasingly dependent upon models of the hybridization processes occurring on GeneChips. The large repositories of GeneChip data can be searched for systematic effects across many experiments. This data mining has led to the discovery of a family of thousands of probes, which show correlated expression across thousands of GeneChip experiments. These probes contain runs of guanines, suggesting that G-quadruplexes are able to form on GeneChips. We discuss the impact of these structures on the interpretation of data from GeneChip experiments.

Microfludic device for creating ionic strength gradients over DNA microarrays for efficient DNA melting studies and assay development

The development of DNA microarray assays is hampered by two important aspects: processing of the microarrays is done under a single stringency condition, and characteristics such as melting temperature are difficult to predict for immobilized probes. A technical solution to these limitations is to use a thermal gradient and information from melting curves, for instance to score genotypes. However, application of temperature gradients normally requires complicated equipment, and the size of the arrays that can be investigated is restricted due to heat dissipation. Here we present a simple microfluidic device that creates a gradient comprising zones of defined ionic strength over a glass slide, in which each zone corresponds to a subarray. Using this device, we demonstrated that ionic strength gradients function in a similar fashion as corresponding thermal gradients in assay development. More specifically, we noted that (i) the two stringency modulators generated melting curves that could be compared, (ii) both led to increased assay robustness, and (iii) both were associated with difficulties in genotyping the same mutation. These findings demonstrate that ionic strength stringency buffers can be used instead of thermal gradients. Given the flexibility of design of ionic gradients, these can be created over all types of arrays, and encompass an attractive alternative to temperature gradients, avoiding curtailment of the size or spacing of subarrays on slides associated with temperature gradients.

Quantitative rRNA-targeted solution-based hybridization assay using peptide nucleic acid molecular beacons

The potential of a solution-based hybridization assay using peptide nucleic acid (PNA) molecular beacon (MB) probes to quantify 16S rRNA of specific populations in RNA extracts of environmental samples was evaluated by designing PNA MB probes for the genera Dechloromonas and Dechlorosoma. In a kinetic study with 16S rRNA from pure cultures, the hybridization of PNA MB to target 16S rRNA exhibited a higher final hybridization signal and a lower apparent rate constant than the hybridizations to nontarget 16S rRNAs. A concentration of 10 mM NaCl in the hybridization buffer was found to be optimal for maximizing the difference between final hybridization signals from target and nontarget 16S rRNAs. Hybridization temperatures and formamide concentrations in hybridization buffers were optimized to minimize signals from hybridizations of PNA MB to nontarget 16S rRNAs. The detection limit of the PNA MB hybridization assay was determined to be 1.6 nM of 16S rRNA. To establish proof for the application of PNA MB hybridization assays in complex systems, target 16S rRNA from Dechlorosoma suillum was spiked at different levels to RNA isolated from an environmental (bioreactor) sample, and the PNA MB assay enabled effective quantification of the D. suillum RNA in this complex mixture. For another environmental sample, the quantitative results from the PNA MB hybridization assay were compared with those from clone libraries.

Simultaneous quantification of multiple nucleic acid targets in complex rRNA mixtures using high density microarrays and nonspecific hybridization as a source of information

To date, it has been problematic to accurately quantify multiple nucleic acid sequences, representing microbial targets, in multi-target mixtures using oligonucleotide microarrays, primarily due to nonspecific target binding (i.e., cross-hybridization). While some studies ignore the effects of nonspecific binding, other studies have developed approaches to minimize nonspecific binding, such as physical modeling to design highly specific probes, subtracting nonspecific signal using mismatch probes, and/or removing nonspecific duplexes by scanning through a range of wash stringencies. We have developed an alternative approach that, in contrast to previous approaches, uses nonspecific target binding as a source of information. Specifically, the new approach uses hybridization patterns (fingerprints) to quantify specific nucleic acid targets in complex target mixtures. We evaluated the approach by mixing together in vitro transcribed 28S rRNA targets at varying concentrations (up to 1.0 nM), and hybridizing the 24 mixtures to microarrays (n=3160 probes, in duplicate). Three independent Latin-square-designed experiments revealed accurate quantification of the targets. The regression between actual concentration of targets and those determined by the approach were highly positively correlated with high R(2) values (e.g., R(2)=0.90, n=6 targets; R(2)=0.84, n=8 targets; R(2)=0.82, n=10 targets).

An improved physico-chemical model of hybridization on high-density oligonucleotide microarrays

Motivation: High-density DNA microarrays provide useful tools to analyze gene expression comprehensively. However, it is still difficult to obtain accurate expression levels from the observed microarray data because the signal intensity is affected by complicated factors involving probe–target hybridization, such as non-linear behavior of hybridization, non-specific hybridization, and folding of probe and target oligonucleotides. Various methods for microarray data analysis have been proposed to address this problem. In our previous report, we presented a benchmark analysis of probe–target hybridization using artificially synthesized oligonucleotides as targets, in which the effect of non-specific hybridization was negligible. The results showed that the preceding models explained the behavior of probe–target hybridization only within a narrow range of target concentrations. More accurate models are required for quantitative expression analysis.

Results: The experiments showed that finiteness of both probe and target molecules should be considered to explain the hybridization behavior. In this article, we present an extension of the Langmuir model that reproduces the experimental results consistently. In this model, we introduced the effects of secondary structure formation, and dissociation of the probe–target duplex during washing after hybridization. The results will provide useful methods for the understanding and analysis of microarray experiments.

Availability: The method was implemented for the R software and can be downloaded from our website (http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/FHarray/).

Contact:furusawa@ist.osaka-u.ac.jp

Supplementary information: Supplementary data are available at Bioinformatics online.

Point mutation detection by surface plasmon resonance imaging coupled with a temperature scan method in a model system

The detection of point mutations in genes presents clear biological and medical interest. Various methods have been considered. In this paper, we take advantage of surface plasmon resonance imaging, a technique allowing detection of unlabeled DNA hybridization. Coupled with a temperature scan, this approach allows us to determine the presence of single-point mutations in oligonucleotide samples from the analysis of DNA's melting curves in either the homozygous or heterozygous case. Moreover, these experimental data are confirmed in good agreement with numerical calculations.

Use of a multi-thermal washer for DNA microarrays simplifies probe design and gives robust genotyping assays

DNA microarrays are generally operated at a single condition, which severely limits the freedom of designing probes for allele-specific hybridization assays. Here, we demonstrate a fluidic device for multi-stringency posthybridization washing of microarrays on microscope slides. This device is called a multi-thermal array washer (MTAW), and it has eight individually controlled heating zones, each of which corresponds to the location of a subarray on a slide. Allele-specific oligonucleotide probes for nine mutations in the beta-globin gene were spotted in eight identical subarrays at positions corresponding to the temperature zones of the MTAW. After hybridization with amplified patient material, the slides were mounted in the MTAW, and each subarray was exposed to different temperatures ranging from 22 to 40°C. When processed in the MTAW, probes selected without considering melting temperature resulted in improved genotyping compared with probes selected according to theoretical melting temperature and run under one condition. In conclusion, the MTAW is a versatile tool that can facilitate screening of a large number of probes for genotyping assays and can also enhance the performance of diagnostic arrays.

Development of a statistically robust quantification method for microorganisms in mixtures using oligonucleotide microarrays

High-density oligonucleotide arrays can be extremely useful for identifying and quantifying specific targets (i.e., ribosomal RNA of microorganisms) in mixtures. However, current array identification schemes are severely compromised by nonspecific hybridization, resulting in numerous false-positive and false-negative calls, they lack an adequate internal control for assessing the quality of identification, and are dependent on amplification of specific target sequences which introduce biases. We have developed a novel approach for the routine quantification and identification of metabolically active microorganisms in mixed samples. The advantage of our approach over conventional ones is that it avoids designing, optimizing, validating, and selecting oligonucleotide probes for arrays; also, nonspecific hybridization is no longer a problem. The basic principle of the approach is that a fluorescence pattern of a mixed sample is a superposition of the fluorescent patterns for each target. The superposition can be quantitatively deconvoluted in terms of concentrations of each microbe. We demonstrated the utility of our approach by extracting rRNA from three microorganisms, making test mixtures, labeling the rRNA, and hybridizing each test mixture to DNA oligonucleotide (20-mers, n=346,608) arrays. Comparison of known concentrations of individual targets in mixtures to those estimated by the solution revealed highly consistent results. The goodness-of-fit of the solution revealed that about 90% of the variability in the data could be explained. A new analytical approach for microbial identification and quantification has been presented in this report. Our findings demonstrate that including signal intensity values from all duplexes on the array, which are essentially nonspecific to the target organisms, significantly improved predictions of known microbial targets. To our knowledge, this is the first study to report this phenomenon. In addition, we demonstrate that the method is a self-sufficient analytical procedure since it provides statistical confidence of the quantification.