Erica D. Dawson

Experimental Evaluation of the FluChip Diagnostic Microarray for Influenza Virus Surveillance

ABSTRACT Global surveillance of influenza is critical for improvements in disease management and is especially important for early detection, rapid intervention, and a possible reduction of the impact of an influenza pandemic. Enhanced surveillance requires rapid, robust, and inexpensive analytical techniques capable of providing a detailed analysis of influenza virus strains. Low-density oligonucleotide microarrays with highly multiplexed “signatures” for influenza viruses offer many of the desired characteristics. However, the high mutability of the influenza virus represents a design challenge. In order for an influenza virus microarray to be of utility, it must provide information for a wide range of viral strains and lineages. The design and characterization of an influenza microarray, the FluChip-55 microarray, for the relatively rapid identification of influenza A virus subtypes H1N1, H3N2, and H5N1 are described here. In this work, a small set of sequences was carefully selected to exhibit broad coverage for the influenza A and B viruses currently circulating in the human population as well as the avian A/H5N1 virus that has become enzootic in poultry in Southeast Asia and that has recently spread to Europe. A complete assay involving extraction and amplification of the viral RNA was developed and tested. In a blind study of 72 influenza virus isolates, RNA from a wide range of influenza A and B viruses was amplified, hybridized, labeled with a fluorophore, and imaged. The entire analysis time was less than 12 h. The combined results for two assays provided the absolutely correct types and subtypes for an average of 72% of the isolates, the correct type and partially correct subtype information for 13% of the isolates, the correct type only for 10% of the isolates, false-negative signals for 4% of the isolates, and false-positive signals for 1% of the isolates. In the overwhelming majority of cases in which incomplete subtyping was observed, the failure was due to the nucleic acid amplification step rather than limitations in the microarray.

Comparison of the MChip to Viral Culture, Reverse Transcription-PCR, and the QuickVue Influenza A+B Test for Rapid Diagnosis of Influenza

ABSTRACT The performance of a diagnostic microarray (the MChip assay) for influenza was compared in a blind study to that of viral culture, reverse transcription (RT)-PCR, and the QuickVue Influenza A+B test. The patient sample data set was composed of 102 respiratory secretion specimens collected between 29 December 2005 and 2 February 2006 at Scott & White Hospital and Clinic in Temple, Texas. Samples were collected from a wide range of age groups by using direct collection, nasal/nasopharyngeal swabs, or nasopharyngeal aspiration. Viral culture and the QuickVue assay were performed at the Texas site at the time of collection. Aliquots for each sample, identified only by study numbers, were provided to the University of Colorado and Vanderbilt University teams for blinded analysis. When referenced to viral culture, the MChip exhibited a clinical sensitivity of 98% and a clinical specificity of 98%. When referenced to RT-PCR, the MChip assay exhibited a clinical sensitivity of 92% and a clinical specificity of 98%. While the MChip assay currently requires 7 to 8 h to complete the analysis, a significant advantage of the test for influenza virus-positive samples is simultaneous detection and full subtype identification for the two subtypes currently circulating in humans (A/H3N2 and A/H1N1) and avian (A/H5N1) viruses.

Robust Sequence Selection Method Used To Develop the FluChip Diagnostic Microarray for Influenza Virus

ABSTRACT DNA microarrays have proven to be powerful tools for gene expression analyses and are becoming increasingly attractive for diagnostic applications, e.g., for virus identification and subtyping. The selection of appropriate sequences for use on a microarray poses a challenge, particularly for highly mutable organisms such as influenza viruses, human immunodeficiency viruses, and hepatitis C viruses. The goal of this work was to develop an efficient method for mining large databases in order to identify regions of conservation in the influenza virus genome. From these regions of conservation, capture and label sequences capable of discriminating between different viral types and subtypes were selected. The salient features of the method were the use of phylogenetic trees for data reduction and the selection of a relatively small number of capture and label sequences capable of identifying a broad spectrum of influenza viruses. A detailed experimental evaluation of the selected sequences is described in a companion paper. The software is freely available under the General Public License at http://www.colorado.edu/chemistry/RGHP/software/ .

Identification of Escherichia coli O157 by Using a Novel Colorimetric Detection Method with DNA Microarrays

Shiga toxin-producing Escherichia coli O157 is a leading cause of foodborne illness worldwide. To evaluate better methods to rapidly detect and genotype E. coli O157 strains, the present study evaluated the use of ampliPHOX, a novel colorimetric detection method based on photopolymerization, for pathogen identification with DNA microarrays. A low-density DNA oligonucleotide microarray was designed to target stx1 and stx2 genes encoding Shiga toxin production, the eae gene coding for adherence membrane protein, and the per gene encoding the O157-antigen perosamine synthetase. Results from the validation experiments demonstrated that the use of ampliPHOX allowed the accurate genotyping of the tested E. coli strains, and positive hybridization signals were observed for only probes targeting virulence genes present in the reference strains. Quantification showed that the average signal-to-noise ratio values ranged from 47.73 ± 7.12 to 76.71 ± 8.33, whereas average signal-to-noise ratio values below 2.5 were determined for probes where no polymer was formed due to lack of specific hybridization. Sensitivity tests demonstrated that the sensitivity threshold for E. coli O157 detection was 100-1000 CFU/mL. Thus, the use of DNA microarrays in combination with photopolymerization allowed the rapid and accurate genotyping of E. coli O157 strains.

Detection of Adamantane-Resistant Influenza on a Microarray

BACKGROUND Influenza A has the ability to rapidly mutate and become resistant to the commonly prescribed influenza therapeutics, thereby complicating treatment decisions. OBJECTIVE To design a cost-effective low-density microarray for use in detection of influenza resistance to the adamantanes. STUDY DESIGN We have taken advantage of functional genomics and microarray technology to design a DNA microarray that can detect the two most common mutations in the M2 protein associated with adamantane resistance, V27A and S31N. RESULTS In a blind study of 22 influenza isolates, the antiviral resistance-chip (AVR-Chip) had a success rate of 95% for detecting these mutations. Microarray data from a larger set of samples were further analyzed using an artificial neural network and resulted in a correct identification rate of 94% for influenza virus samples that had V27A and S31N mutations. CONCLUSIONS The AVR-Chip provided a method for rapidly screening influenza viruses for adamantane sensitivity, and the general approach could be easily extended to detect resistance to other chemotherapeutics.

Evaluation of MChip with Historic Subtype H1N1 Influenza A Viruses, Including the 1918 “Spanish Flu” Strain

ABSTRACT The robustness of a recently developed diagnostic microarray for influenza, the MChip, was evaluated with 16 historic subtype H1N1 influenza A viruses (A/H1N1), including A/Brevig Mission/1/1918. The matrix gene segments from all 16 viruses were successfully detected on the array. An artificial neural network trained with temporally related A/H1N1 viruses identified A/Brevig Mission/1/1918 as influenza virus A/H1N1 with 94% probability.

MChip, a low density microarray, differentiates among seasonal human H1N1, North American swine H1N1, and the 2009 pandemic H1N1

Please cite this paper as: Heil et al. (2010) MChip, a low density microarray, differentiates among seasonal human H1N1, North American swine H1N1, and the 2009 pandemic H1N1. Influenza and Other Respiratory Viruses 4(6), 411–416.

ampliPHOX colorimetric detection on a DNA microarray for influenza.

DNA microarrays have emerged as a powerful tool for pathogen detection. For instance, many examples of the ability to type and subtype influenza virus have been demonstrated. The identification and subtyping of influenza on DNA microarrays has applications in both public health and the clinic for early detection, rapid intervention, and minimizing the impact of an influenza pandemic. Traditional fluorescence is currently the most commonly used microarray detection method. However, as microarray technology progresses towards clinical use, replacing expensive instrumentation with low cost detection technology exhibiting similar performance characteristics to fluorescence will make microarray assays more attractive and cost-effective. The ampliPHOX colorimetric detection technology is intended for research applications, and has a limit of detection within one order of magnitude of traditional fluorescence, with a main advantage being an approximate ten-fold lower instrument cost compared to the confocal microarray scanners required for fluorescence microarray detection. Another advantage is the compact size of the instrument which allows for portability and flexibility, unlike traditional fluorescence instruments. Because the polymerization technology is not as inherently linear as fluorescence detection, however, it is best suited for lower density microarray applications in which a yes/no answer for the presence of a certain sequence is desired, such as for pathogen detection arrays. Currently the maximum spot density compatible with ampliPHOX detection is ˜1800 spots/array. Because of the spot density limitations, higher density microarrays are not suitable for ampliPHOX detection. Here, we present ampliPHOX colorimetric detection technology as a method of signal amplification on a low density microarray developed for the detection and characterization of influenza viruses (FluChip). Although this protocol uses the FluChip (a DNA microarray) as one specific application of ampliPHOX detection, any microarray incorporating biotinylated target can be labeled and detected in a similar manner. The microarray design and biotinylation of the target to be captured are the responsibility of the user. Once the biotinylated target has been captured on the array, ampliPHOX detection can be performed by first tagging the array with a streptavidin-label conjugate (ampliTAG). Upon light exposure using the ampliPHOX Reader instrument, polymerization of a monomer solution (ampliPHY) occurs only in regions containing ampliTAG-labeled targets. The polymer formed can be subsequently stained with a non-toxic solution to improve visual contrast, followed by imaging and analysis using a simple software package (ampliVIEW). The entire FluChip assay from un-extracted sample to result can be performed in about 6 hours, and the ampliPHOX detection steps described above can be completed in about 30 min.

Automated interpretation of influenza hemagglutination inhibition (HAI) assays: Is plate tilting necessary?

The hemagglutination inhibition assay (HAI) is widely used to evaluate vaccine-induced antibody responses as well as to antigenically characterize influenza viruses. The results of an HAI assay are based on an endpoint titration where the titers are generally manually interpreted and recorded by a well-trained expert. For serological applications, the lack of standardization in endpoint interpretation and interference from non-specific inhibitors in clinical samples can translate into a high degree of variability in the results. For example, tilting HAI plates at 45–60 degrees to look for a “tear drop pattern” with avian red blood cells is a common practice by many, but not all, research laboratories. In this work, we tested the hypothesis that an automated image analysis algorithm can be used to achieve an accurate and non-subjective interpretation of HAI assays—specifically without the need to tilt plates. In a side-by-side comparison study performed during FDA’s biannual serological screening process for influenza viruses, titer calls for more than 2200 serum samples were made by the Cypher One automated hemagglutination analyzer without tilting and by an expert human with tilting. The comparison yielded 95.6% agreement between the expert reader and automated interpretation method (within ± 1 dilution) for the complete dataset. Performance was also evaluated relative to the type of red blood cell (turkey and guinea pig) and influenza strain (12 different viruses). For the subset that utilized guinea pig red blood cells (~44% of the samples), for which no plate tilting was required, the agreement with an expert reader was 97.2%. For the subset that utilized turkey red blood cells (~56% of the samples), for which plate tilting was necessary by the expert reader, the agreement was 94.3%. Overall these results support the postulate that algorithm-based interpretation of a digital record with no plate tilting could replace manual reading for greater consistency in HAI assays.