Evaluation of MChip with historic subtype H1N1 influenza A viruses, including the 1918 "Spanish Flu" strain

A one-step RT-PCR array for detection and differentiation of zoonotic influenza viruses H5N1, H9N2, and H1N1

BACKGROUND

Rapid and comprehensive pathogen identification is crucial in zoonotic influenza diagnosis.

METHODS

By optimizing the design of primers and probes and reverse-transcriptase polymerase chain reaction (RT-PCR) conditions, we achieved simultaneous detection of multiple influenza and zoonotic influenza viruses, including H1N1, H5N1, and H9N2 strains, in a one-step, quantitative real-time RT-PCR array (rRT-PCR array) of RNA from multiple influenza strains utilizing a single set of conditions for RT-PCR amplification. The target sequences from all targeted zoonotic influenza viruses were cloned into recombinant RNA virus particles, which were used to evaluate sensitivity, specificity, and reproducibility of the zoonotic influenza viruses RT-PCR array.

RESULTS

The detection limit of the array was shown to be between 10(0) and 10(1) copies per reaction, and the standard curve demonstrated a linear range from 10 to 10(6) copies. Thus, the analytical sensitivity of this zoonotic influenza viruses RT-PCR array is 10-100 times higher than conventional RT-PCR. Specificity of the one-step zoonotic influenza viruses RT-PCR array was verified by comparison of results obtained with retroviral-like particles (RVPs), which contained RNA from isolates of seasonal influenza viruses, zoonotic influenza viruses, and other pathogens known to cause acute respiratory disease.

CONCLUSION

The high sensitivity, rapidity, reproducibility, and specificity of this zoonotic influenza viruses rRT-PCR array has been verified as being sufficient to detect the presence of multiple zoonotic influenza viruses in a single assay. The zoonotic influenza viruses RT-PCR array might provide rapid identification of emergent zoonotic influenza viruses strains during influenza outbreaks and disease surveillance initiatives.

Updated values for molecular diagnosis for highly pathogenic avian influenza virus

Highly pathogenic avian influenza (HPAI) viruses of the H5N1 strain pose a pandemic threat. H5N1 strain virus is extremely lethal and contagious for poultry. Even though mortality is 59% in infected humans, these viruses do not spread efficiently between humans. In 1997, an outbreak of H5N1 strain with human cases occurred in Hong Kong. This event highlighted the need for rapid identification and subtyping of influenza A viruses (IAV), not only to facilitate surveillance of the pandemic potential of avian IAV, but also to improve the control and treatment of infected patients. Molecular diagnosis has played a key role in the detection and typing of IAV in recent years, spurred by rapid advances in technologies for detection and characterization of viral RNAs and proteins. Such technologies, which include immunochromatography, quantitative real-time PCR, super high-speed real-time PCR, and isothermal DNA amplification, are expected to contribute to faster and easier diagnosis and typing of IAV.

Swine influenza virus infections in man

Because pigs are susceptible to both avian and human influenza viruses, genetic reassortment between avian, human, and/or swine influenza viruses in the pig host can lead to the generation of novel influenza A viruses (Ma et al. 2009). Since the first serological evidence of a swine influenza virus (SIV) infecting humans in 1958, sporadic cases have continued to occur. In recent years, case reports have been increasing, seemingly in concert with modern pig farming and the emergence of triple reassortant SIVs in swine. SIV infections in man generally are mild or subclinical, and often are not diagnosed; however, SIV infections can be quite serious in patients with underlying medical conditions. As of August 2010, 73 case reports of symptomatic human SIV infections have been documented in the medical literature or reported by health officials (excluding cases of the 2009 pandemic H1N1 influenza virus), of which 7 infections (10 %) resulted in death. While exposure to swine is often considered a risk factor for human SIV infections, 37 of 73 (51 %) reported cases had no known exposure to pigs; consequently, SIV may be crossing the species barrier via transmission routes yet to be acknowledged. In addition, human-to-human transmission was suspected in 10 of 34 (30 %) of the cases with epidemiological investigation. This chapter discusses the observations of illness and infections in humans, risk factors associated with infection, and methods for diagnosing human infections of SIV.

Universal oligonucleotide microarray for sub-typing of Influenza A virus

A universal microchip was developed for genotyping Influenza A viruses. It contains two sets of oligonucleotide probes allowing viruses to be classified by the subtypes of hemagglutinin (H1-H13, H15, H16) and neuraminidase (N1-N9). Additional sets of probes are used to detect H1N1 swine influenza viruses. Selection of probes was done in two steps. Initially, amino acid sequences specific to each subtype were identified, and then the most specific and representative oligonucleotide probes were selected. Overall, between 19 and 24 probes were used to identify each subtype of hemagglutinin (HA) and neuraminidase (NA). Genotyping included preparation of fluorescently labeled PCR amplicons of influenza virus cDNA and their hybridization to microarrays of specific oligonucleotide probes. Out of 40 samples tested, 36 unambiguously identified HA and NA subtypes of Influenza A virus.

Detecting RNA viruses in living mammalian cells by fluorescence microscopy

Traditional methods that rely on viral isolation and culture techniques continue to be the gold standards used for detection of infectious viral particles. However, new techniques that rely on visualization of live cells can shed light on understanding virus-host interaction for early stage detection and potential drug discovery. Live-cell imaging techniques that incorporate fluorescent probes into viral components provide opportunities for understanding mRNA expression, interaction, and virus movement and localization. Other viral replication events inside a host cell can be exploited for non-invasive detection, such as single-virus tracking, which does not inhibit viral infectivity or cellular function. This review highlights some of the recent advances made using these novel approaches for visualization of viral entry and replication in live cells.

Real-time detection of influenza a, influenza B, and respiratory syncytial virus a and B in respiratory specimens by use of nanoparticle probes

Seasonal epidemics of influenza and respiratory syncytial virus are responsible for significant morbidity and mortality worldwide. Infrequently, novel or reemergent strains of influenza A virus have caused rapid, severe global pandemics resulting in millions of fatalities. The ability to efficiently and accurately detect and differentiate respiratory viruses is paramount for effective treatment, infection control, and epidemiological surveillance. We evaluated the ability of two FDA-cleared nucleic acid-based tests, the semiautomated respiratory virus nucleic acid test (VRNAT) and the fully automated respiratory virus nucleic acid test SP (RVNAT(SP)) (Nanosphere Inc., Northbrook, IL) to detect influenza A virus, influenza B virus, and respiratory syncytial virus A and B (RSV A/B) from clinical nasopharyngeal swab specimens. Detection of viral RNA in both tests is based on nucleic acid amplification followed by hybridization to capture probes immobilized on a glass slide. A novel technology utilizing gold nanoparticle-conjugated probes is utilized to detect the presence of captured target DNA. This microarray-based approach to detection has proven to be more sensitive than the traditional culture/direct fluorescent-antibody assay (DFA) method for detecting RSV and influenza viruses in clinical specimens, including the novel 2009 H1N1 strain. Specifically, we report 98.0% sensitivity and 96.5% specificity for the VRNAT compared to culture/DFA. Further, the VRNAT detected virus in an additional 58% of specimens that were culture negative. These data were confirmed using bidirectional sequencing. Evaluation of the fully automated RVNAT(SP), which is built on the same detection technology as the VRNAT but contains an updated processor enabling complete automation, revealed the two tests to be functionally equivalent. Thus, the RVNAT(SP) is a fully automated sample-to-result test capable of reliable detection of select respiratory viruses directly from clinical specimens in 3.5 h.

Neural networks

Neural networks are a class of intelligent learning machines establishing the relationships between descriptors of real-world objects. As optimisation tools they are also a class of computational algorithms implemented using statistical/numerical techniques for parameter estimate, model selection, and generalisation enhancement. In bioinformatics applications, neural networks have played an important role for classification, function approximation, knowledge discovery, and data visualisation. This chapter will focus on supervised neural networks and discuss their applications to bioinformatics.

Methods for molecular surveillance of influenza

Molecular-based techniques for detecting influenza viruses have become an integral component of human and animal surveillance programs in the last two decades. The recent pandemic of the swine-origin influenza A virus (H1N1) and the continuing circulation of highly pathogenic avian influenza A virus (H5N1) further stress the need for rapid and accurate identification and subtyping of influenza viruses for surveillance, outbreak management, diagnosis and treatment. There has been remarkable progress on the detection and molecular characterization of influenza virus infections in clinical, mammalian, domestic poultry and wild bird samples in recent years. The application of these techniques, including reverse transcriptase-PCR, real-time PCR, microarrays and other nucleic acid sequencing-based amplifications, have greatly enhanced the capability for surveillance and characterization of influenza viruses.

Design and validation of a microarray for detection, hemagglutinin subtyping, and pathotyping of avian influenza viruses

Continuing threats of devastating outbreaks in poultry and of human infections caused by highly pathogenic avian influenza virus (HPAIV) H5N1 emphasize the need for the further development of rapid and reliable methods of virus detection and characterization. Here we report on the design and comprehensive validation of a low-density microarray as a diagnostic tool for the detection and typing of avian influenza virus (AIV). The array consists of one probe for the conserved matrix gene and 97 probes targeting the HA(0) cleavage-site region. Following fragment amplification by a generic PCR approach, the array enables AIV detection, hemagglutinin (HA) subtyping, and pathotyping within a single assay. For validation, a panel of 92 influenza A viruses which included 43 reference strains representing all 16 HA subtypes was used. All reference strains were correctly typed with respect to their HA subtypes and pathotypes, including HPAIV H5N1/Asia, which caused outbreaks in Germany in 2006 and 2007. In addition, differentiation of strains of the Eurasian and North American lineages of the H5 and H7 subtypes was possible. The sensitivity of the microarray for the matrix gene is comparable to that of real-time reverse transcription-PCR (RT-PCR). It is, however, 10- to 100-fold lower than that of real-time RT-PCR with respect to HA subtyping and pathotyping. The specificity of the array was excellent, as no pathogens relevant for differential diagnosis yielded a positive reaction. Validation with field samples included 19 cloacal swab specimens from wild and domestic birds. Influenza A virus was verified in all samples, whereas the HA subtypes could be determined for 14 samples. The results demonstrate that the microarray assay described complements current methods and can accelerate the diagnosis and characterization of AIV.

DNA microarrays in the clinic: infectious diseases

We argue that the most-promising area of clinical application of microarrays in the foreseeable future is the diagnostics and monitoring of infectious diseases. Microarrays for the detection and characterization of human pathogens have already found their way into clinical practice in some countries. After discussing the persistent, yet often underestimated, importance of infectious diseases for public health, we consider the technologies that are best suited for the detection and clinical investigation of pathogens. Clinical application of microarray technologies for the detection of mycobacteria, Bacillus anthracis, HIV, hepatitis and influenza viruses, and other major pathogens, as well as the analysis of their drug-resistance patterns, illustrate our main thesis.