Utility of DNA Microarrays for Detection of Viruses in Acute Respiratory Tract Infections in Children

doi:10.1016/j.jpeds.2007.12.035

J Pediatr. Author manuscript; available in PMC 2011 September 15.

Published in final edited form as:

J Pediatr. 2008 July; 153(1): 76–83.

Published online 2008 March 7. doi: 10.1016/j.jpeds.2007.12.035

PMCID: PMC3174048

NIHMSID: NIHMS56385

Utility of DNA Microarrays for Detection of Viruses in Acute Respiratory Tract Infections in Children

Charles Y. Chiu,^1,^5,⁶^* Anatoly Urisman,^1,⁵^* Tara L. Greenhow,⁸ Silvi Rouskin,¹ Shigeo Yagi,⁹ David Schnurr,⁹ Carolyn Wright,³ W. Lawrence Drew,^3,^5,⁶ David Wang,¹⁰ Peggy S. Weintrub,^4,⁶ Joseph L. DeRisi,^1,^5,⁷ and Don Ganem^2,^5,^6,⁷

¹Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA.

²Department of Microbiology, University of California, San Francisco, CA, USA.

³Department of Laboratory Medicine, University of California, San Francisco, CA, USA.

⁴Department of Pediatrics, University of California, San Francisco, CA, USA.

⁵Department of Medicine, University of California, San Francisco, CA, USA.

⁶Division of Infectious Diseases, University of California, San Francisco, CA, USA.

⁷Howard Hughes Medical Institute, University of California, San Francisco, CA, USA.

⁸Department of Pediatric Infectious Diseases, Children’s Hospital and Research Center, Oakland, CA, USA.

⁹Viral and Rickettsial Disease Laboratory, California Department of Health Services, Richmond, California, USA.

¹⁰Department of Microbiology and Pathology and Immunology, Washington University, St. Louis, MO, USA.

^*These authors contributed equally to this manuscript.

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Abstract

Objective

To assess the utility of a pan-viral DNA microarray platform (Virochip) in the detection of viruses associated with pediatric respiratory tract infections.

Study design

The Virochip was compared with conventional direct fluorescent antibody (DFA) and PCR-based testing for the detection of respiratory viruses in 278 consecutive nasopharyngeal aspirate samples from 222 children.

Results

The Virochip was superior in performance to DFA, showing a 19% increase in the detection of 7 respiratory viruses included in standard DFA panels, and was similar to virus-specific PCR (sensitivity 85–90%, specificity ≥99%, PPV 94–96%, NPV 97–98%) in the detection of respiratory syncytial virus, influenza A, and rhino-/enteroviruses. The Virochip also detected viruses not routinely tested for or missed by DFA and PCR, as well as double infections and infections in critically ill patients that DFA failed to detect.

Conclusions

Given its favorable sensitivity and specificity profile and expanded spectrum for detection, microarray-based viral testing holds promise for clinical diagnosis of pediatric respiratory tract infections.

Keywords: DNA Microarrays, Pediatric Respiratory Tract Infections, Respiratory Viruses, Clinical Diagnostics

Acute respiratory tract infections (RTI) are the most common illnesses of humans and are associated with significant morbidity and mortality. In children, viruses are responsible for the majority of RTI, with bacteria and other pathogens thought to be responsible for fewer than 15% of cases (1). However, even with the best methods for viral detection currently available, a specific pathogen cannot be identified in 20 to 50% of RTI (1–4).

Existing viral diagnostic methods are limited in sensitivity and scope. Virus isolation by culture takes days to weeks, and many viruses remain fastidious or unculturable. Direct fluorescent antibody (DFA) testing has a turnaround time of 2 hours, but may suffer from low sensitivity and is available only for a limited number of viruses (5). Polymerase chain reaction (PCR) testing is rapid and highly sensitive, and has supplanted culture as the new “gold standard” for detection of respiratory viruses in research settings (3, 4). However, most PCR tests target only one virus at a time, making these assays cumbersome in routine clinical practice. For simultaneous detection of up to 20 viruses, a number of multiplex PCR assays have been proposed (3, 4, 6–10).

Recently, DNA microarrays have emerged as a promising new technology for broad-spectrum virus detection (11–13). We have previously designed an in-house microarray platform to detect all known viruses as well as novel viruses related to known viral families (Virochip, University of California, San Francisco) (13, 14). The Virochip consists of ~22,000 oligonucleotide probes representing all ~1,800 fully or partially sequenced viruses in GenBank as of Fall 2004. The performance of the Virochip in respiratory virus detection has been previously tested using virally infected tissue culture cells (13) and in selected patient cohorts (15). To date, the Virochip has not been compared directly with standard diagnostic tests for viruses in a clinical setting. Thus, in the present study we sought to compare the Virochip with conventional clinical DFA and PCR-based testing in the detection of respiratory viruses associated with RTI in children.

Methods

Study Design

This study is a prospective case series of all consecutive samples sent for viral DFA testing from pediatric patients seen at the University of California, San Francisco, from December 2003 to June 2004. All patient samples were collected according to protocols approved by the UCSF Institutional Review Board.

Sample Processing

Consecutive nasopharyngeal aspirate (NPA) samples sent for DFA to the UCSF clinical laboratory were analyzed with the Light Diagnostics Respiratory DFA Viral Screening and Identification Kit (Chemicon International) kit. This kit detects 7 common respiratory viruses: respiratory syncytial virus (RSV), influenza A and B (FluA/B), human parainfluenza virus types 1, 2, and 3 (HPIV-1/2/3), and adenovirus (AdV). Remaining sample material was transferred into a sterile 14 mL conical tube, frozen, and stored at −80°C.

For blinded Virochip analysis, frozen NPA samples were thawed, and 200 µL aliquots were used to extract RNA using the RNeasy Mini Kit (Qiagen Corporation) according to the manufacturer’s protocol, including on-column DNase digestion. Microarrays used in this study were identical to those previously described (16) (NCBI GEO platform GPL3429). RNA samples were amplified and labeled using a Round A/B random PCR method and hybridized to the Virochip as reported previously (13). Microarrays were scanned with an Axon 4000B scanner and analyzed using Axon GenePix 6 software (Axon Instruments).

Virochip Data Analysis

Virochip data analysis was carried out in two stages. First, all microarrays were analyzed by E-Predict (17), using a significance cut of p<0.01 to identify microarrays with statistically significant viral hybridization patterns (176 of 278). To generate an optimized set of oligonucleotide intensity weights for the 3^rd generation Virochip platform, we took the remaining 102 presumed negative microarrays and manually fit a set of functions with the general equation:

where w is a weight (value from 0 to1) for a given oligonucleotide, i is the median of sum-normalized intensities of that oligonucleotide across the 102 negative microarrays, and lower boundary a is the median of medians of the sum-normalized intensities of all oligonucleotides. The upper boundary condition b was expressed as b = a + cσ, where c was a constant, and σ was the standard deviation of sum-normalized intensities of the oligonucleotide across the 102 negative microarrays. Forty weight sets with c and p as fitting measurements were evaluated using E-Predict profile separation statistics (17) on 6 rhinovirus (RV), 6 RSV, 4 HPIV-3, and 2 FluA-positive microarrays. The optimal performance was achieved with weights corresponding to c = 0.15 and p = 1.5. These weights were used to generate negative null distributions based on the set of 102 negative microarrays mentioned above, and final microarray virus determinations were made by E-Predict. A microarray was considered E-predict positive for a given virus if the corresponding energy profile attained a significance score of p<0.05 (17).

PCR Analysis

Blinded RT-PCR assays for RSV, FluA, RV, and enterovirus (EV) were performed on extracted RNA from the frozen NPA samples at the Viral and Rickettsial Disease Laboratory (VRDL) at the California Department of Health Services. For detection of RSV, an RT-PCR assay for RSV targeting the fusion (F) gene was performed using the one-step Access RT-PCR System as previously described (2). For detection of FluA, primers and fluorescent probes targeting the highly conserved matrix (M) gene of FluA were used using the Roche LightCycler Real-Time PCR System (Roche Diagnostics) as previously described (18). For detection of RV/EV, we first ran an in-house RT-PCR multiplex assay on randomly primed template cDNA using primers targeting the highly conserved 5’ untranslated region (5’-UTR) of RV (15) and EV (19). Positive samples were identified by the presence of amplified PCR bands of the expected size on agarose gel electrophoresis. Follow-up real-time PCR assays for RV/EV detection on discrepant samples between the Virochip and the in-house multiplex RT-PCR then were carried out using the Roche LightCycler Real-Time PCR System as previously described (20).

Sequence Confirmation of Virochip-Positive/PCR-Negative Samples

Confirmation of two Virochip-positive/PCR-negative samples was carried out by PCR using alternative primers based on high-intensity microarray oligonucleotides and direct sequencing. The sequence from one case of RSV was 97% identical to a 155-bp fragment from the matrix (M) gene for RSV subgroup B strain 9320, and the sequence from one case of RV was 96% identical to a 302-bp fragment from the VP4/VP2 region for RV strain QPID03-0003. Another Virochip-positive/PCR-negative case, that of an EV, was confirmed by a repeat run of the real-time PCR assay (20).

Clinical Data Collection

After assay results for the NPA samples were obtained, subjects were identified and a retrospective review of the medical record was performed. Data were systematically collected using a standard form that documented the following information: age, sex, date, and location of sample collection, clinical presentation, presence of immunocompromised state, presence of acute respiratory failure, and DFA result. Location of sample collection was classified as outpatient (clinic or emergency department) or hospital admission. Presenting illness was defined as an upper respiratory infection (cough and/or congestion with or without fever or a clinician’s diagnosis), lower respiratory infection (clinician’s diagnosis of asthma exacerbation, bronchiolitis, croup, or pneumonia), or no respiratory illness (febrile illness, seizures, or DFA collected on a routine basis, such as prior to transplant surgery). Immunocompromised patients were defined as children with solid organ or bone marrow transplants, congenital or acquired immune deficiencies (including those on chemotherapy), or HIV. Patients with respiratory failure were defined as children who developed acute respiratory decompensation requiring mechanical ventilation as a result of their respiratory illness. For patients with more than one sample, a first-time sample was defined as the earliest sample collected during a single hospitalization or illness.

Results

Demographic and Clinical Data

We analyzed a total of 278 nasopharyngeal aspirate (NPA) samples collected from 222 children for the presence of viruses using DFA and Virochip. The demographic and clinical data for the 222 subjects enrolled in the study are shown in Table I. Most patients (73%) were hospitalized. Approximately 71% of enrolled patients (n=157) had an acute respiratory tract infection, and the remaining patients (n=65) had DFA sent for other reasons, most often due to non-respiratory febrile illnesses (n=46). Eighteen percent of patients (n=39) were immunocompromised, and eight percent (n=17) developed respiratory failure requiring mechanical ventilation as a result of their illness. The majority of subjects with RSV were younger (mean age 1.5 years) and required hospitalization (76%), whereas subjects with influenza tended to be older (mean age 4.1 years) and were mainly treated as outpatients (64%). All cases of human metapneumovirus (HMPV), coronavirus (CoV), and AdV were in hospitalized patients. The majority of viral infections in immunocompromised subjects (60%) were due to picornaviruses.

Table I

Demographic and Clinical Data According to Illness and Viral Pathogen

Detection of Viruses by DFA and the Virochip

Figure 1 shows the spectrum and frequency of detection of different viruses by the two methods. In patients with RTI, DFA detected a virus in only 36% of samples, whereas the Virochip detected a virus in 64%, improving the rate of detection by 75%. Detection of viruses not included in the DFA panel (non-DFA viruses) accounted for approximately one-third of all Virochip-positive identifications. Among these non-DFA viruses, picornaviruses comprised the largest group (74% of samples positive for a non-DFA virus, or 16% of all samples from patients with RTI). These picornaviruses included 16 RVs, 14 EVs, and one parechovirus. In addition to picornaviruses, the Virochip identified four HMPV and two CoV infections from patients with RTI. Human cytomegalovirus-like sequences were detected in one sample from one febrile patient with pneumonia. In seven samples, the Virochip detected viruses not typically associated with respiratory disease and of doubtful clinical significance. These viruses included polyomaviruses (SV40 and JC virus), plant viruses commonly found in the gastrointestinal tract (nanoviruses, geminiviruses) (21), and bovine leukemia virus, a virus ubiquitous in cow milk (22). A virus was detected in a higher proportion of patients with URI (68%) and bronchiolitis (77%) than with pneumonia (54%) or asthma exacerbation (41%). In patients with non-respiratory illnesses (typically febrile illnesses of uncertain origin), the Virochip detected a virus in 30% of samples, with the majority accounted for by picornaviruses, whereas DFA detected a virus in only 3%. Overall, at least one of the seven DFA viruses was identified by Virochip in 31% of RTI samples (n=86), compared with 25% identified by DFA (n=72), corresponding to a 19% overall increase in detection by the Virochip compared with DFA (p < 0.01 by χ² analysis).

Figure 1

Viruses Detected by DFA and Virochip

Virochip Detection of Double and Critical Viral Infections

Thirteen cases of simultaneous infection by two viruses were detected by the Virochip (9% of Virochip-positive samples, 5% of all samples) (Table II,; available at www.jpeds.com). In contrast, no cases of double infection were detected by DFA. The Virochip also detected a viral pathogen in 12 of 17 critically ill patients who developed respiratory failure requiring mechanical ventilation, whereas a virus was detected by DFA in only five such patients. Two double infections were identified among these life-threatening cases, one case of FluA/AdV and another of RSV/RV.

Comparison of the Virochip with PCR

To assess Virochip results that were discordant with DFA and overall sensitivity and specificity, we carried out RT-PCR assays for RSV, FluA, and RV/EV, the three major groups of viruses detected by the Virochip (Figure 2). For detection of RSV and FluA, the overall sensitivity of the Virochip (86%) relative to PCR was significantly better than that of DFA (71%, p < 0.05 by χ² analysis). The corresponding specificities were ≥99%. There was also a greater overlap in positives between Virochip and PCR than between DFA and PCR for these two viruses. 16 of of 18 (89%) of Virochip-positive/DFA-negative RSV and FluA samples were confirmed to be true positives by PCR (Figure 2, Venn diagram).

Figure 2

Comparison of the Performance of DFA and Virochip Relative to PCR

For detection of RV/EV, we first used an in-house RT-PCR multiplex assay based on methods reported previously (15, 19). Using this assay, 31 NPA samples were positive by both Virochip and PCR, 18 NPA samples were Virochip-positive/PCR-negative, and 5 NPA samples were Virochip-negative/PCR-positive. Since these results were inconsistent with the rates of detection using clinically validated PCR assays for the other viruses (RSV and FluA), we further analyzed the 23 discrepant samples in a blinded fashion using a more sensitive clinically validated real-time PCR assay for RV/EV (20). Results obtained by combining these two assays show that the Virochip has high sensitivity (90%) and specificity (99%) overall for detection of RV/EV (Figure 2C).

Virochip Detection of PCR-Negative Cases of Respiratory Virus Infection

Six cases (three picornavirus, two RSV, and one FluA) detected by the Virochip tested negative in the corresponding PCR assays (Figure 2). We hypothesized that most of these cases were viral strains that had failed detection with standard PCR primers. To investigate this possibility, we recovered viral sequence from two Virochip-positive/PCR-negative cases (one RV, one RSV) and separately confirmed a case of EV that was Virochip-positive and previously PCR-negative by repeating the real-time PCR assay. Similar attempts to confirm the remaining three Virochip-positive/PCR-negative cases with the limited amount of sample available were unsuccessful. Thus, at least three of the six Virochip-positive/PCR-negative represent PCR false-negatives and, as a result, the reported sensitivity of the Virochip may be underestimated.

Discussion

This study of pediatric RTI used a DNA microarray that aims to detect all known viral species simultaneously. The most common viral pathogens identified were RSV (19%), picornaviruses (16%), and influenza A/B (11%). Notably, most viruses detected in the respiratory tracts of patients with non-respiratory illnesses and in immunocompromised patients were picornaviruses. These findings are consistent with the observation that asymptomatic rhinovirus infections can be seen in 4 – 12% of healthy individuals and suggest that immunocompromised hosts may be more susceptible to colonization or overt respiratory illness by picornaviruses (23). Our frequency of detection of 16% for picornaviruses is consistent with that of a previously published report (18% rhinoviruses, 2.9% enteroviruses), which also used consecutive NPA samples (24).

Our comparison of the Virochip with DFA demonstrates that the sensitivity of the microarray for respiratory virus detection is superior. Importantly, about 50% of the overall increase in detection rate corresponds to samples with inconclusive DFA results due to low cellular content. Unlike DFA, nucleic-acid detection methods such as microarray and PCR are capable of detecting free viral particles in addition to virus-infected cells. Another significant advantage of a pan-viral microarray over DFA is the ability to screen for all known viruses simultaneously. DFA panels in current clinical use do not test for RV/EV, HMPV, or CoV, which, in our study, comprised more than one-third of the detected viruses in patients with RTI.

In the 17 patients presenting with an illness severe enough to require mechanical ventilation, there were three cases of critical RV infection, including one in an immunocompromised individual. RV infection is thought to comprise a spectrum of disease ranging from asymptomatic infection to life-threatening childhood pneumonia (25). Our findings of cases of critical respiratory tract illness associated with RV infection is consistent with growing evidence linking RV with hospitalizations in young children (26). The Virochip was also superior to DFA for detecting double viral infections. Two cases of double infection, in which both viruses could in principle be detected by DFA, were reported as single-virus infections by DFA. Previous studies have suggested that double infections are associated with greater severity of RTI (27). Higher efficiency of the microarray in detecting critical as well as double viral infections is an important advantage of the method, as timely detection of such infections may allow clinicians to avoid unnecessary antibiotics and invasive procedures and begin appropriate antiviral treatment, if available.

In addition to being a highly parallel methodology that utilizes thousands of oligonucleotide probes for simultaneous detection, a DNA microarray platform Virochip is expandable and adaptable. Automated oligonucleotide design methods allow straightforward addition of new probes for better detection of known viruses or to expand coverage to novel or evolving viral species (16, 28, 29). DNA microarrays also can be used for non-viral pathogen detection, including bacteria and fungi (30). Interestingly, in this study the Virochip detected Streptococcus pyogenes bacteriophage in a sample from a patient with aspiration pneumonia who also had a positive sputum culture for Streptococcus pyogenes. This result suggests a possible strategy of using phage sequences as an indirect means of detecting bacterial pathogens.

Despite its pan-virus scope, the Virochip only detected a virus in 64% of RTI cases overall. Although comparable with studies using other detection methods (1–4, 8, 9), this result is likely an underestimate of the true number of positives arising from several factors. First, some samples may have been missed by the Virochip due to low virus titers at the detection limits of PCR. Second, RNA (not DNA) was used as the source material in this study, which may have given rise to lower than expected rates of detection of DNA viruses such as adenoviruses, herpesviruses, and parvoviruses. The Virochip may not have detected any cases of human bocavirus, a recently described parvovirus (31), because this virus shares low sequence identity to parvovirus sequences currently represented on the Virochip. Finally, 32% of patients with RTI in this study were diagnosed with pneumonia, of which 35% were hospital-associated. Many of these cases of pneumonia may be non-viral in origin, as suggested by previous epidemiologic studies of pneumonia in hospitalized children (32, 33).

Using custom PCR primers, we confirmed at least three of the six microarray-positive/PCR-negative cases (one RSV, one RV, and one EV) as true positive tests for viruses. Detection of such cases by microarray is not unexpected, as the Virochip uses multiple probes that are derived from different sites in the viral genome and have a higher tolerance for sequence mismatches than the primers used in specific PCR. This results in improved detection of divergent viruses (14, 34). We suspect that of the microarray-positive/PCR-negative cases of virus infection likely were missed by clinical PCR due to mismatches between primer and target sequences (35), although specimen availability limited our efforts to show this definitively.

Although the prospect of comprehensive viral detection by use of a single microarray assay is appealing, several challenges must be addressed before use of the technology in clinical diagnosis becomes practical. First, there are significant initial start-up costs in setting up the technology including the cost of the microarray printer and viral oligonucleotides, as well as ongoing material and labor costs. Second, the turnaround time for the assay is currently ~24 hours; it may be possible to decrease the processing duration by using ultra-rapid polymerases for amplification or controlled agitation techniques during hybridization. Third, reproducibility and consistent array quality are of concern. In our study, none of the microarray assays needed to be repeated, and the inherent probe redundancy built into the method makes the assay robust for purposes of virus detection. For example, of the 300 oligonucleotide probes on the Virochip designed to hybridize to rhinoviruses, as few as four high intensity oligonucleotides are sufficient to make a successful virus identification. Statistical methods for interpreting the microarray data, as exemplified by E-Predict (17), can be completely automated, allowing ease of use and freedom from operator bias. Design of smaller microarrays aimed at detection of targeted virus sets (e.g. respiratory viruses only) would reduce cost and simplify issues of reproducibility, quality control, and data analysis.

Looking to the future, we can envision two possible ways in which a viral detection microarray could be used to impact clinical practice. One strategy is to use the platform for direct diagnosis of respiratory infections, as reported here. An alternative strategy may be to deploy a viral microarray as an instrument of discovery rather than routine detection, with the goal of identifying divergent or unexpected viruses that elude diagnosis using conventional methods. Once a candidate new pathogen is identified, a specific PCR-based or DFA-based assay then can be developed to detect the virus with a high degree of sensitivity in clinical samples. In this scenario, microarray assay would complement rather than replace existing diagnostic techniques such as PCR.

Supplementary Material

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Acknowledgments

Funding. This work was supported by a Genentech Graduate Fellowship (AU) and grants from the Glaser Pediatric Network (TG), Sandler Program for Asthma Research (JLD), Howard Hughes Medical Institute (JLD and DG), and the Doris Duke Charitable Foundation (CYC, JLD, and DG)

Footnotes

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Competing interests. The authors have declared that no competing interests exist.

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