CombiMatrix oligonucleotide arrays: Genotyping and gene expression assays employing electrochemical detection

Status of biomolecular recognition using electrochemical techniques

The use of nanoscale materials (e.g., nanoparticles, nanowires, and nanorods) for electrochemical biosensing has seen explosive growth in recent years following the discovery of carbon nanotubes by Sumio Ijima in 1991. Although the resulting label-free sensors could potentially simplify the molecular recognition process, there are several important hurdles to be overcome. These include issues of validating the biosensor on statistically large population of real samples rather than the commonly reported relatively short synthetic oligonucleotides, pristine laboratory standards or bioreagents; multiplexing the sensors to accommodate high-throughput, multianalyte detection as well as application in complex clinical and environmental samples. This article reviews the status of biomolecular recognition using electrochemical detection by analyzing the trends, limitations, challenges and commercial devices in the field of electrochemical biosensors. It provides a survey of recent advances in electrochemical biosensors including integrated microelectrode arrays with microfluidic technologies, commercial multiplex electrochemical biosensors, aptamer-based sensors, and metal-enhanced electrochemical detection (MED), with limits of detection in the attomole range. Novel applications are also reviewed for cancer monitoring, detection of food pathogens, as well as recent advances in electrochemical glucose biosensors.

Split hybridisation probes for electrochemical typing of single-nucleotide polymorphisms

This paper describes the development of a highly selective single-nucleotide polymorphisms (SNPs) typing method based on the use of split hybridisation probes and demonstrates the concept through the electrochemical analysis of single-base mutations in actual patient samples. The requirement that two probes hybridised adjacent to one another to allow for stabilisation (via base-stacking) and binding of the allele-specific oligonucleotide (ASO), imparted highly stringent selectivity criteria to the assay. Simple rules for tuning the characteristics of such stacking/ASO probe pairs and achieve full mismatch discrimination at ambient conditions (with no need to strictly control the temperature) are provided. All genotyping experiments were indeed performed at room temperature, using the planar surface of disposable probe-modified gold electrodes as the genosensing platform. The ability to detect nanomolar amounts of a synthetic target even within a vast excess of single-base substituted sequences gave strong evidence of the specificity of the split probes assay. Proving the general validity of this genotyping approach, application of the analytical pathway was further demonstrated for clinical targets (amplified from the human TP53 gene) whose mutational site was poorly accessible, being part of a thermodynamically stable hairpin. In combination with use of auxiliary oligonucleotides (which restored the availability of each pre-defined hybridisation site), the assay demonstrated the ability to fully discriminate single-base mutations with detection limits in the high picomolar range (total analysis time: 60 min). Our specific probe design, hybridisation and signal transduction paths make the analytical process remarkably simple, relatively low cost and, thus, well suited for low throughput analysis of clinically relevant samples.

Novel developments for improved detection of specific mRNAs by DNA chips

Microarrays have revolutionized gene expression analysis as they allow for highly parallel monitoring of mRNA levels of thousands of genes in a single experiment. Since their introduction some 15 years ago, substantial progress has been achieved with regard to, e.g., faster or more sensitive analyses. In this review, interesting new approaches for a more sensitive detection of specific mRNAs will be highlighted. Particularly, the potential of electrical DNA chip formats that allow for faster mRNA analyses will be discussed.

Automated analytical microarrays: a critical review

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple analytes in a single experiment. The specific affinity reaction of nucleic acids (hybridization) and antibodies towards antigens is the most common bioanalytical method for generating multiplexed quantitative results. Nucleic acid-based analysis is restricted to the detection of cells and viruses. Antibodies are more universal biomolecular receptors that selectively bind small molecules such as pesticides, small toxins, and pharmaceuticals and to biopolymers (e.g. toxins, allergens) and complex biological structures like bacterial cells and viruses. By producing an appropriate antibody, the corresponding antigenic analyte can be detected on a multiplexed immunoanalytical microarray. Food and water analysis along with clinical diagnostics constitute potential application fields for multiplexed analysis. Diverse fluorescence, chemiluminescence, electrochemical, and label-free microarray readout systems have been developed in the last decade. Some of them are constructed as flow-through microarrays by combination with a fluidic system. Microarrays have the potential to become widely accepted as a system for analytical applications, provided that robust and validated results on fully automated platforms are successfully generated. This review gives an overview of the current research on microarrays with the focus on automated systems and quantitative multiplexed applications.

Conventional and future diagnostics for avian influenza

The significant and continued transboundary spread of Asian avian influenza H5N1 since 2003, paired with documented transmission from avian species to humans and other mammals, has focused global attention on avian influenza virus detection and diagnostic strategies. While the historic and conventional laboratory methods used for isolation and identification of the virus and for detection of specific antibodies continued to be widely applied, new and emerging technologies are rapidly being adapted to support avian influenza virus surveillance and diagnosis worldwide. Molecular tools in particular are advancing toward lab-on-chip and fully integrated technologies that are capable of same day detection, pathotyping, and phylogenetic characterization of influenza A viruses obtained from clinical specimens. The future of avian influenza diagnostics, rather than moving toward a single approach, is wisely adopting a strategy that takes advantage of the range of conventional and advancing technologies to be used in "fit-for-purpose" testing.

Electrochemical biochips for protein analysis

Proteins bear important functions for most life processes. It is estimated that the human proteome comprises more than 250,000 proteins. Over the last years, highly sophisticated and powerful instruments have been developed that allow their detection and characterization with great precision and sensitivity. However, these instruments need well-equipped laboratories and a well-trained staff. For the determination of proteins in a hospital, in a doctor's office, or at home, low-budget protein analysis methods are needed that are easy to perform. In addition, for a proteomic approach, highly parallel measurements with small sample sizes are required. Biochips are considered as promising tools for such applications. The following chapter describes electrochemical biochips for protein analysis that use antibodies or aptamers as recognition elements.

Label-free electrical detection of DNA hybridization for the example of influenza virus gene sequences

Microarrays based on DNA-DNA hybridization are potentially useful for detecting and subtyping viruses but require fluorescence labeling and imaging equipment. We investigated a label-free electrical detection system using electrochemical impedance spectroscopy that is able to detect hybridization of DNA target sequences derived from avian H5N1 influenza virus to gold surface-attached single-stranded DNA oligonucleotide probes. A 23-nt probe is able to detect a 120-nt base fragment of the influenza A hemagglutinin gene sequence. We describe a novel method of data analysis that is compatible with automatic measurement without operator input, contrary to curve fitting used in conventional electrochemical impedance spectroscopy (EIS) data analysis. A systematic investigation of the detection signal for various spacer molecules between the oligonucleotide probe and the gold surface revealed that the signal/background ratio improves as the length of the spacer increases, with a 12- to 18-atom spacer element being optimal. The optimal spacer molecule allows a detection limit between 30 and 100 fmol DNA with a macroscopic gold disc electrode of 1 mm radius. The dependence of the detection signal on the concentration of a 23-nt target follows a binding curve with an approximate 1:1 stoichiometry and a dissociation constant of KD=13+/-4 nM at 295 K.

Identification of upper respiratory tract pathogens using electrochemical detection on an oligonucleotide microarray

Bacterial and viral upper respiratory infections (URI) produce highly variable clinical symptoms that cannot be used to identify the etiologic agent. Proper treatment, however, depends on correct identification of the pathogen involved as antibiotics provide little or no benefit with viral infections. Here we describe a rapid and sensitive genotyping assay and microarray for URI identification using standard amplification and hybridization techniques, with electrochemical detection (ECD) on a semiconductor-based oligonucleotide microarray. The assay was developed to detect four bacterial pathogens (Bordetella pertussis, Streptococcus pyogenes, Chlamydia pneumoniae and Mycoplasma pneumoniae) and 9 viral pathogens (adenovirus 4, coronavirus OC43, 229E and HK, influenza A and B, parainfluinza types 1, 2, and 3 and respiratory syncytial virus. This new platform forms the basis for a fully automated diagnostics system that is very flexible and can be customized to suit different or additional pathogens. Multiple probes on a flexible platform allow one to test probes empirically and then select highly reactive probes for further iterative evaluation. Because ECD uses an enzymatic reaction to create electrical signals that can be read directly from the array, there is no need for image analysis or for expensive and delicate optical scanning equipment. We show assay sensitivity and specificity that are excellent for a multiplexed format.

A quantitative genotype algorithm reflecting H5N1 Avian influenza niches

MOTIVATION

Computational genotyping analyses are critical for characterizing molecular evolutionary footprints, thus providing important information for designing the strategies of influenza prevention and control. Most of the current methods that are available are based on multiple sequence alignment and phylogenetic tree construction, which are time consuming and limited by the number of taxa. Arbitrarily defining genotypes further complicates the interpretation of genotyping results.

METHODS

In this study, we describe a quantitative influenza genotyping algorithm based on the theory of quasispecies. First, the complete composition vector (CCV) was utilized to calculate the pairwise evolutionary distance between genotypes. Next, Hierarchical Bayesian Modeling using the Gibbs Sampling algorithm was applied to identify the segment genotype threshold, which is used to identify influenza segment genotype through a modularity calculation. The viral genotype was defined by combining eight segment genotypes based on the genetic reassortment feature of influenza A viruses.

RESULTS

We applied this method for H5N1 avian influenza viruses and identified 107 niches among 283 viruses with a complete genome set. The diversity of viral genotypes, and their correlation with geographic locations suggests that these viruses form local niches after being introduced to a new ecological environment through poultry trade or bird migration. This novel method allows us to define genotypes in a robust, quantitative as well as hierarchical manner.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.