Virulence signatures: microarray-based approaches to discovery and analysis

Development and Assessment of a Diagnostic DNA Oligonucleotide Microarray for Detection and Typing of Meningitis-Associated Bacterial Species

Meningitis is commonly caused by infection with a variety of bacterial or viral pathogens. Acute bacterial meningitis (ABM) can cause severe disease, which can progress rapidly to a critical life-threatening condition. Rapid diagnosis of ABM is critical, as this is most commonly associated with severe sequelae with associated high mortality and morbidity rates compared to viral meningitis, which is less severe and self-limiting. We have designed a microarray for detection and diagnosis of ABM. This has been validated using randomly amplified DNA targets (RADT), comparing buffers with or without formamide, in glass slide format or on the Alere ArrayTube^TM (Alere Technologies GmbH) microarray platform. Pathogen-specific signals were observed using purified bacterial nucleic acids and to a lesser extent using patient cerebral spinal fluid (CSF) samples, with some technical issues observed using RADT and glass slides. Repurposing the array onto the Alere ArrayTube^TM platform and using a targeted amplification system increased specific and reduced nonspecific hybridization signals using both pathogen nucleic and patient CSF DNA targets, better revealing pathogen-specific signals although sensitivity was still reduced in the latter. This diagnostic microarray is useful as a laboratory diagnostic tool for species and strain designation for ABM, rather than for primary diagnosis.

A species independent universal bio-detection microarray for pathogen forensics and phylogenetic classification of unknown microorganisms

Background

The ability to differentiate a bioterrorist attack or an accidental release of a research pathogen from a naturally occurring pandemic or disease event is crucial to the safety and security of this nation by enabling an appropriate and rapid response. It is critical in samples from an infected patient, the environment, or a laboratory to quickly and accurately identify the precise pathogen including natural or engineered variants and to classify new pathogens in relation to those that are known. Current approaches for pathogen detection rely on prior genomic sequence information. Given the enormous spectrum of genetic possibilities, a field deployable, robust technology, such as a universal (any species) microarray has near-term potential to address these needs.

Results

A new and comprehensive sequence-independent array (Universal Bio-Signature Detection Array) was designed with approximately 373,000 probes. The main feature of this array is that the probes are computationally derived and sequence independent. There is one probe for each possible 9-mer sequence, thus 4⁹ (262,144) probes. Each genome hybridized on this array has a unique pattern of signal intensities corresponding to each of these probes. These signal intensities were used to generate an un-biased cluster analysis of signal intensity hybridization patterns that can easily distinguish species into accepted and known phylogenomic relationships. Within limits, the array is highly sensitive and is able to detect synthetically mixed pathogens. Examples of unique hybridization signal intensity patterns are presented for different Brucella species as well as relevant host species and other pathogens. These results demonstrate the utility of the UBDA array as a diagnostic tool in pathogen forensics.

Conclusions

This pathogen detection system is fast, accurate and can be applied to any species. Hybridization patterns are unique to a specific genome and these can be used to decipher the identity of a mixed pathogen sample and can separate hosts and pathogens into their respective phylogenomic relationships. This technology can also differentiate between different species and classify genomes into their known clades. The development of this technology will result in the creation of an integrated biomarker-specific bio-signature, multiple select agent specific detection system.

Development and experimental validation of a predictive threshold cycle equation for quantification of virulence and marker genes by high-throughput nanoliter-volume PCR on the OpenArray platform

Development of quantitative PCR (QPCR) assays typically requires extensive screening within and across a given species to ensure specific detection and lucid identification among various pathogenic and nonpathogenic strains and to generate standard curves. To minimize screening requirements, multiple virulence and marker genes (VMGs) were targeted simultaneously to enhance reliability, and a predictive threshold cycle (C(T)) equation was developed to calculate the number of starting copies based on an experimental C(T). The empirical equation was developed with Sybr green detection in nanoliter-volume QPCR chambers (OpenArray) and tested with 220 previously unvalidated primer pairs targeting 200 VMGs from 30 pathogens. A high correlation (R(2) = 0.816) was observed between the predicted and experimental C(T)s based on the organism's genome size, guanine and cytosine (GC) content, amplicon length, and stability of the primer's 3' end. The performance of the predictive C(T) equation was tested using 36 validation samples consisting of pathogenic organisms spiked into genomic DNA extracted from three environmental waters. In addition, the primer success rate was dependent on the GC content of the target organisms and primer sequences. Targeting multiple assays per organism and using the predictive C(T) equation are expected to reduce the extent of the validation necessary when developing QPCR arrays for a large number of pathogens or other targets.

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.

Lateral flow microarrays: a novel platform for rapid nucleic acid detection based on miniaturized lateral flow chromatography

Widely used nucleic acid assays are poorly suited for field deployment where access to laboratory instrumentation is limited or unavailable. The need for field deployable nucleic acid detection demands inexpensive, facile systems without sacrificing information capacity or sensitivity. Here we describe a novel microarray platform capable of rapid, sensitive nucleic acid detection without specialized instrumentation. The approach is based on a miniaturized lateral flow device that makes use of hybridization-mediated target capture. The miniaturization of lateral flow nucleic acid detection provides multiple advantages over traditional lateral flow devices. Ten-microliter sample volumes reduce reagent consumption and yield analyte detection times, excluding sample preparation and amplification, of <120 s while providing sub-femtomole sensitivity. Moreover, the use of microarray technology increases the potential information capacity of lateral flow. Coupled with a hybridization-based detection scheme, the lateral flow microarray (LFM) enables sequence-specific detection, opening the door to highly multiplexed implementations for broad-range assays well suited for point-of-care and other field applications. The LFM system is demonstrated using an isothermal amplification strategy for detection of Bacillus anthracis, the etiologic agent of anthrax. RNA from as few as two B. anthracis cells was detected without thermocycling hardware or fluorescence detection systems.

Multiplex approach for screening genetic markers of microbial indicators

Genetic markers are expected to provide better specificity in epidemiological studies and potentially serve as better indicators of waterborne pathogens. Methods used to assess genetic markers of emerging microbial indicators include pulsed field gel electrophoresis, polymerase chain reaction (PCR), and microarrays. This paper outlines a high-throughput approach to screen for such genetic markers using a set of theoretical and experimental screening tools. The theoretical screening involves evaluating genes related to the ribosomal RNA and specific functions from emerging indicator groups, followed by experimental validation with appropriate sampling schemes and high-throughput and economical screening methods, such as microarrays, real time PCR, and on-chip PCR. Analysis of a wide range of samples covering temporal variability in location, host, and waterborne disease outbreaks is essential. The proposed approach is expected to shorten the time and cost associated with searching for new genetic markers of emerging indicators by at least 10-fold.