Single Assay for Simultaneous Detection and Differential Identification of Human and Avian Influenza Virus Types, Subtypes, and Emergent Variants

Abstract

For more than four decades the cause of most type A influenza virus infections of humans has been attributed to only two viral subtypes, A/H1N1 or A/H3N2. In contrast, avian and other vertebrate species are a reservoir of type A influenza virus genome diversity, hosting strains representing at least 120 of 144 combinations of 16 viral hemagglutinin and 9 viral neuraminidase subtypes. Viral genome segment reassortments and mutations emerging within this reservoir may spawn new influenza virus strains as imminent epidemic or pandemic threats to human health and poultry production. Traditional methods to detect and differentiate influenza virus subtypes are either time-consuming and labor-intensive (culture-based) or remarkably insensitive (antibody-based). Molecular diagnostic assays based upon reverse transcriptase-polymerase chain reaction (RT-PCR) have short assay cycle time, and high analytical sensitivity and specificity. However, none of these diagnostic tests determine viral gene nucleotide sequences to distinguish strains and variants of a detected pathogen from one specimen to the next. Decision-quality, strain- and variant-specific pathogen gene sequence information may be critical for public health, infection control, surveillance, epidemiology, or medical/veterinary treatment planning. The Resequencing Pathogen Microarray (RPM-Flu) is a robust, highly multiplexed and target gene sequencing-based alternative to both traditional culture- or biomarker-based diagnostic tests. RPM-Flu is a single, simultaneous differential diagnostic assay for all subtype combinations of type A influenza viruses and for 30 other viral and bacterial pathogens that may cause influenza-like illness. These other pathogen targets of RPM-Flu may co-infect and compound the morbidity and/or mortality of patients with influenza. The informative specificity of a single RPM-Flu test represents specimen-specific viral gene sequences as determinants of virus type, A/HN subtype, virulence, host-range, and resistance to antiviral agents.

Asymptomatic and symptomatic respiratory virus infection detected in naso-pharyngeal swabs from solid organ transplant recipients early after transplantation

“…3,4,6 The primary overall etiology of RVI was 16.3% influenza A (February-March), 7.1% adenovirus (October), 7.1% coronavirus OC43/HKU1 (March) and 7.1% parainfluenza-2 (March-April). These results are in consonance with other studies showing the highest rate of infection during February and March, 5 with the majority of the cases associated with influenza A infection, with nearly half of them symptomatic. All patients overcome the infection in the absence of severe symptoms and did not require antiviral administration.…”

“…In transplant recipients, respiratory viral infections (RVI) are associated with high rates of morbidity and mortality. 1 Although recent reports have underlined the increasing importance of RVI in solid organ transplant (SOT) recipients, [2][3][4][5][6] little is known about its incidence early after transplantation. Immunosuppressive regimens impair SOT recipients' immune system disabling the protection against infections.…”

Sequence Variability and Geographic Distribution of Lassa Virus, Sierra Leone

“…Sample preparation was conducted as previously described ( 29 ). Pathogen identification was performed using the “C3 Score” identification algorithm ( 30 ). …”

Development and clinical testing of a simple, low-density gel element array for influenza identification, subtyping, and H275Y detection

“…User subjectivity and/or involvement in microarray data analysis and interpretation are common in life science applications, especially when using high-density arrays (Kessler et al, 2004; Lodes et al, 2006; Wang et al, 2006; Han et al, 2008; Gall et al, 2009b; Lu et al, 2009; Metzgar et al, 2010; Chen et al, 2011). Clinical laboratories that perform high-complexity molecular tests are also allowed to interpret underlying threshold cycle or hybridization intensity data independent of the automated test output, and use that information to inform the reported result.…”

“…Consequently, clinical algorithms that address influenza virus detection, subtyping, and drug-resistance profiling must either perform multiple PCR tests in parallel, or utilize serial reflex assays that delay appropriate diagnosis and treatment. Microarrays may overcome these limitations, and several microarrays are described for influenza virus detection, subtyping, or detecting mutations associated with drug resistance (Sengupta et al, 2003; Liu et al, 2006; Wang et al, 2006; Mehlmann et al, 2007; Quan et al, 2007; Han et al, 2008; Townsend et al, 2008; Huang et al, 2009; Li et al, 2009; Metzgar et al, 2010; Chen et al, 2011; Teo et al, 2011). However, clinical adoption of microarray technology for diagnostic purposes has been hampered by complex workflows and user subjectivity in microarray image analysis, data analysis, and data interpretation.…”