Broad spectrum respiratory pathogen analysis of throat swabs from military recruits reveals interference between rhinoviruses and adenoviruses.

Military recruits experience a high incidence of febrile respiratory illness (FRI), leading to significant morbidity and lost training time. Adenoviruses, group A Streptococcus pyogenes, and influenza virus are implicated in over half of the FRI cases reported at recruit training center clinics, while the etiology of the remaining cases is unclear. In this study, we explore the carriage rates and disease associations of adenovirus, enterovirus, rhinovirus, Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis in military recruits using high-density resequencing microarrays. The results showed that rhinoviruses, adenoviruses, S. pneumoniae, H. influenzae, and N. meningitidis were widely distributed in recruits. Of these five agents, only adenovirus showed significant correlation with illness. Among the samples tested, only pathogens associated with FRI, such as adenovirus 4 and enterovirus 68, revealed strong temporal and spatial clustering of specific strains, indicating that they are transmitted primarily within sites. The results showed a strong negative association between adenoviral FRI and the presence of rhinoviruses in recruits, suggesting some form of viral interference.

Single assay for simultaneous detection and differential identification of human and avian influenza virus types, subtypes, and emergent variants.

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.

Cowpea mosaic virus nanoscaffold as signal enhancement for DNA microarrays.

Previous studies have shown that a functionalized viral nanoparticle can be used as a fluorescent signal-generating element and enhance detection sensitivity for immunoassays and low density microarrays. In this study, we further tested this ability in commercial DNA microarrays, including Affymetrix high density resequencing microarray. Optimum conditions for NeutrAvidin and dye coupling to a double-cysteine mutant of cowpea mosaic virus (CPMV) were found to be comparable to the commonly used streptavidin-phycoerythrin (SAPE) for high density resequencing microarray. A 3-fold signal enhancement in comparison to Cy5-dCTP controls was obtained when using nanoparticles on control scorecard expression microarrays. Hybridization results from commercially available 8000 rat expression arrays indicate an increment of 14% on the detected features when the virus complex was used as the staining reagent in comparison to Cy5-dCTP controls. The current work shows the utility of the CPMV-dye nanoparticles as a detection reagent in well-established detection platforms.

Universal detection and identification of avian influenza virus by use of resequencing microarrays.

Zoonotic microbes have historically been, and continue to emerge as, threats to human health. The recent outbreaks of highly pathogenic avian influenza virus in bird populations and the appearance of some human infections have increased the concern of a possible new influenza pandemic, which highlights the need for broad-spectrum detection methods for rapidly identifying the spread or outbreak of all variants of avian influenza virus. In this study, we demonstrate that high-density resequencing pathogen microarrays (RPM) can be such a tool. The results from 37 influenza virus isolates show that the RPM platform is an effective means for detecting and subtyping influenza virus, while simultaneously providing sequence information for strain resolution, pathogenicity, and drug resistance without additional analysis. This study establishes that the RPM platform is a broad-spectrum pathogen detection and surveillance tool for monitoring the circulation of prevalent influenza viruses in the poultry industry and in wild birds or incidental exposures and infections in humans.

Resequencing microarray probe design for typing genetically diverse viruses: human rhinoviruses and enteroviruses.

BACKGROUND: Febrile respiratory illness (FRI) has a high impact on public health and global economics and poses a difficult challenge for differential diagnosis. A particular issue is the detection of genetically diverse pathogens, i.e. human rhinoviruses (HRV) and enteroviruses (HEV) which are frequent causes of FRI. Resequencing Pathogen Microarray technology has demonstrated potential for differential diagnosis of several respiratory pathogens simultaneously, but a high confidence design method to select probes for genetically diverse viruses is lacking. RESULTS: Using HRV and HEV as test cases, we assess a general design strategy for detecting and serotyping genetically diverse viruses. A minimal number of probe sequences (26 for HRV and 13 for HEV), which were potentially capable of detecting all serotypes of HRV and HEV, were determined and implemented on the Resequencing Pathogen Microarray RPM-Flu v.30/31 (Tessarae RPM-Flu). The specificities of designed probes were validated using 34 HRV and 28 HEV strains. All strains were successfully detected and identified at least to species level. 33 HRV strains and 16 HEV strains could be further differentiated to serotype level. CONCLUSION: This study provides a fundamental evaluation of simultaneous detection and differential identification of genetically diverse RNA viruses with a minimal number of prototype sequences. The results demonstrated that the newly designed RPM-Flu v.30/31 can provide comprehensive and specific analysis of HRV and HEV samples which implicates that this design strategy will be applicable for other genetically diverse viruses.

Application of broad-spectrum, sequence-based pathogen identification in an urban population.

A broad spectrum detection platform that provides sequence level resolution of target regions would have a significant impact in public health, case management, and means of expanding our understanding of the etiology of diseases. A previously developed respiratory pathogen microarray (RPM v.1) demonstrated the capability of this platform for this purpose. This newly developed RPM v.1 was used to analyze 424 well-characterized nasal wash specimens from patients presenting with febrile respiratory illness in the Washington, D. C. metropolitan region. For each specimen, the RPM v.1 results were compared against composite reference assay (viral and bacterial culture and, where appropriate, RT-PCR/PCR) results. Across this panel, the RPM assay showed >or=98% overall agreement for all the organisms detected compared with reference methods. Additionally, the RPM v.1 results provide sequence information which allowed phylogenetic classification of circulating influenza A viruses in approximately 250 clinical specimens, and allowed monitoring the genetic variation as well as antigenic variability prediction. Multiple pathogens (2-4) were detected in 58 specimens (13.7%) with notably increased abundances of respiratory colonizers (esp. S. pneumoniae) during viral infection. This first-ever comparison of a broad-spectrum viral and bacterial identification technology of this type against a large battery of conventional "gold standard" assays confirms the utility of the approach for both medical surveillance and investigations of complex etiologies of illness caused by respiratory co-infections.

Using a resequencing microarray as a multiple respiratory pathogen detection assay.

Simultaneous testing for detection of infectious pathogens that cause similar symptoms (e.g., acute respiratory infections) is invaluable for patient treatment, outbreak prevention, and efficient use of antibiotic and antiviral agents. In addition, such testing may provide information regarding possible coinfections or induced secondary infections, such as virally induced bacterial infections. Furthermore, in many cases, detection of a pathogen requires more than genus/species-level resolution, since harmful agents (e.g., avian influenza virus) are grouped with other, relatively benign common agents, and for every pathogen, finer resolution is useful to allow tracking of the location and nature of mutations leading to strain variations. In this study, a previously developed resequencing microarray that has been demonstrated to have these capabilities was further developed to provide individual detection sensitivity ranging from 10(1) to 10(3) genomic copies for more than 26 respiratory pathogens while still retaining the ability to detect and differentiate between close genetic neighbors. In addition, the study demonstrated that this system allows unambiguous and reproducible sequence-based strain identification of the mixed pathogens. Successful proof-of-concept experiments using clinical specimens show that this approach is potentially very useful for both diagnostics and epidemic surveillance.

Broad-spectrum respiratory tract pathogen identification using resequencing DNA microarrays.

The exponential growth of pathogen nucleic acid sequences available in public domain databases has invited their direct use in pathogen detection, identification, and surveillance strategies. DNA microarray technology has offered the potential for the direct DNA sequence analysis of a broad spectrum of pathogens of interest. However, to achieve the practical attainment of this potential, numerous technical issues, especially nucleic acid amplification, probe specificity, and interpretation strategies of sequence detection, need to be addressed. In this report, we demonstrate an approach that combines the use of a custom-designed Affymetrix resequencing Respiratory Pathogen Microarray (RPM v.1) with methods for microbial nucleic acid enrichment, random nucleic acid amplification, and automated sequence similarity searching for broad-spectrum respiratory pathogen surveillance. Successful proof-of-concept experiments, utilizing clinical samples obtained from patients presenting adenovirus or influenza virus-induced febrile respiratory illness (FRI), demonstrate the ability of this approach for correct species- and strain-level identification with unambiguous statistical interpretation at clinically relevant sensitivity levels. Our results underscore the feasibility of using this approach to expedite the early surveillance of diseases, and provide new information on the incidence of multiple pathogens.