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Brief Communications |
1 Diagnosis Division, Kuro Korea University Hospital, Seoul, Korea;
2 Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea;
3 Department of Statistics, Kyungpook National University, Daegu, Korea;
4 Chemistry Department, Dongguk University, Seoul, Korea;
5 Department of Chemistry and BK School of Molecular Science, Pohang University of Science and Technology, Pohang, Korea;
6 NanoBio Lab, National Research Laboratory, Ministry of Science and Technology, Korea.
7 These authors contributed equally to this work;
aAddress correspondence to this author at: Department of Chemistry, Dongguk University 3-26 Phil-Dong, Joong-Gu Seoul, 100-715 South Korea. Fax 82-2-2268-8204; e-mail skim99{at}paran.com, skim{at}dongguk.edu.
Abstract
Background: Hepatitis C virus (HCV) can be transmitted through blood transfusion. Screening ELISA, the most widely used method for HCV diagnosis, sometimes yields false-positive and false-negative results, so a confirmatory test is used. This secondary testing is labor-intensive and expensive, and thus is impractical for massive blood bank screening. Therefore, a new massive screening method with high accuracy is needed for sensitive and specific detection of HCV.
Methods: With sol-gel material, we designed novel antigen microarray in 96-well plates for HCV detection. Each individual well was spotted with 4 different HCV antigens. We used this new system to test 154 patient serum samples previously tested for HCV by ELISA (87 HCV positive and 67 HCV negative) (HCV EIA3.0, ABBOTT). We assessed the detection limit of our microarray system with the use of serial 10-fold dilutions of an HCV-positive sample.
Results: Our microarray assay was reproducible and displayed higher diagnostic accuracy (specificity) (98.78%) than did the ELISA (81.71%). Our method yielded significantly fewer false-positive results than did the ELISA. The detection limit of our assay was 1000 times more sensitive than that of the ELISA. In addition, we found this novel assay technology to be compatible with the currently employed automated methods used for ELISA.
Conclusion: We successfully applied the sol-gel–based protein microarray technology to a screening assay for HCV diagnosis with confirmatory test-level accuracy. This new, inexpensive method will improve the specificity and sensitivity of massive sample diagnosis.
Hepatitis C virus (HCV) is a viral pandemic, infecting more than 170 million people worldwide (1). Several methods of detecting HCV, such as ELISA, the line immunobinding assay (LIBA), the recombinant immunoblot assay, and PCR are currently being used in HCV diagnosis (2)(3)(4). Because it is quick, inexpensive, and automated, ELISA is the main method used in hospitals for HCV diagnosis. However, because this ELISA can yield false HCV-positive (5) or HCV-negative results under certain conditions, such as in immune-compromised persons (1), data obtained with the ELISA must be confirmed with complicated secondary tests, such as the LIBA or PCR-based protocols (6)(7).
The development of protein chip or microarray technology has provided a highly sensitive, high-throughput method for disease diagnosis (8)(9) by facilitating detection—in small amounts of patient samples—of antibodies to antigens from infectious viruses or bacteria (10)(11). However, the current major challenge for the advancement of protein microarray technology is the need for optimized microarray materials that maintain the native conformation of the embedded antigen or antibody (12). In addition, to compete with more standard protocols (e.g., ELISA), the support materials for a protein microarray-based assay must be easy to handle and store and suitable for rapid and inexpensive production in large quantities; furthermore, the assay must yield high-quality, reproducible results (13)(14). The immobilization of proteins within sol-gel–derived materials is an intriguing possibility for use with protein microarrays, because these materials do not require affinity-captured agents or tagged recombinant proteins, thus enabling the size entrapment of a wide variety of proteins in their native states (15). Previously, we developed a novel method for the screening of sol-gel materials that is optimal for protein microarray applications (16). We demonstrated the highly sensitive detection of antigen-antibody binding and other protein-protein interactions on protein microarrays derived from our novel sol-gel formulation (16).
Using our optimized sol-gel materials [25.5% tetramethoxysilane, 12.5% tetraethoxysilane, 5.0% PEG8000, 10 mmol/L HCl, and 10 mmol/L sodium phosphate (pH 7.5)] (16), we immobilized the marker proteins currently used for HCV diagnosis onto each well of new 96-well chip-format plates. Four different HCV marker proteins (Core, NS5, NS3, and E1/E2; LG Life Sciences), a positive control (Cy3-labeled goat antibody, Abchem), a sol-gel material spot that contained no proteins (the negative control), and an additional unrelated control protein (HIV P24, Abchem) were mixed individually with the optimized sol formulation described in (16), spotted in triplet onto the 96-well plates, and encapsulated within the matrix of the sol-gel nanoporous structures (Fig. 1
). This set of prototypes contained only markers for HCV plus one additional unrelated control protein (HIV P24), which allowed us to test the specificity of our system. We used the HCV core, NS3, NS5, and E1/E2 antigens in our protein microarray assay to allow a better comparison between our protein microarray assay results and that of the existing confirmatory test (LG HCD Confirm, LGLS), which uses the same HCV core, NS3, NS5, and E1/E2 antigens.
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We obtained 87 serum samples from HCV-positive patients and 67 serum samples from HCV-negative patients (a total of 154 samples) in whom HCV was detected by means of an HCV EIA 3.0 ELISA assay (Abbott) at Korea University Hospital. All sample donors gave informed consent. Among the 87 samples that were HCV positive according to the ELISA tests, 15 were shown to be false positives according to the LIBA-based confirmatory test (LG HCD Confirm). To avoid complications in interpreting our results, such as those that arise in patients who are immunocompromised by other viruses, we used samples from patients who were infected only with HCV and not with HIV or HBV. We applied these 154 samples to each of the wells of our prototype protein microarrays and then attempted to diagnose hepatitis in a format compatible with the current automated ELISA-based hepatitis diagnostic process. Sera from the HCV-positive and HCV-negative patients and the Cy3-labeled human secondary antibody were incubated for 30 min in the wells, which were then washed using automated ELISA equipment (Fig. 1
). The assay times and conditions that we used were the same as and compatible with the conventional ELISA HCV diagnostic assay, characteristics that should make this new technology more accessible to clinicians (17). After washing, the plate chips were scanned using a 96-well fluorescence laser scanner (FLA-500, Fuji) to measure fluorescence intensity from the Cy3 dye, and the resulting fluorescence intensity of each spot was quantified as an LAU/mm2 unit using the appropriate software (Multigauge, Fuji). For signal:noise ratios, the signal represented the Cy3 fluorescence intensity from each antigen spot after subtraction of the background fluorescence, and the noise was defined as the Cy3 fluorescence intensity from the negative control spot (without any proteins) after subtraction of the background fluorescence. The cutoff value for HCV-positive samples was determined if >2 of 4 antigen spots yielded twice as much fluorescent signal (signal) as the negative control spot (noise) (a signal:noise ratio >2) (see Supplementary Fig. 1 in the Data Supplement that accompanies the online version of this Technical Brief athttp://www.clinchem.org/content/vol54/issue2 for cutoff values and distribution of the signal:noise ratios for 154 samples).
We compared HCV diagnosis results obtained using our protein microarrays with those from the conventional ELISA assay. Fig. 1
shows representative results. Our microarray assay showed that 3 of the samples (#1, #2, and #3) were HCV positive because more than 2 of the 4 marker proteins yielded (+) signals. However, positive sample #4 showed only 1 weak (+) signal and thus was considered to be indeterminate in our protein microarray assay.
Table 1
summarizes the test results obtained with all 154 clinical samples. These data clearly demonstrate that our protein microarray assay is more accurate in diagnosing HCV infection than is the standard ELISA; indeed, the sol-gel protein microarray method reduced the number of false positives [from 15 (ELISA) to 1 (protein chip)], resulting in a higher specificity (98.78%) than that obtained with the standard ELISA (81.71%) (Table 1
; see Supplementary Table 1 in the online Data Supplement) (18). To compare our microarray method with 3 well-accepted confirmatory tests, we measured the sensitivity and specificity of 3 diagnostic methods—the ELISA, the LIBA-based assay, and our protein microarray test—for 13 patient samples. The sensitivity and specificity results (100% and 87.5%, respectively) were identical for the confirmatory and protein microarray assays (see Supplementary Table 2 in the online Data Supplement). Because comparing an HCV RNA-based PCR assay with an anti-HCV–based assay is not practical, we cannot directly compare PCR-based results with those obtained using our protein microarray assays. However, the overall accuracy of our protein microarray method is nearly equivalent or better than that of the LIBA-blot based confirmatory test (19). The inclusion of additional antigens such as NS4 would improve the specificity of this protein microarray-based assay.
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To test the detection limit of the protein microarrays, we assayed the chips with serial dilutions of 3 HCV-positive serum samples (Fig. 1B
; see Supplementary Fig. 2 in the online Data Supplement). Specifically, serum sample #37, which tested positive in the ELISA assay, was diluted up to 10 000 times with HCV- negative serum. Using the sol-gel protein microarray, we were able to detect fluorescent signals with 2 HCV marker proteins (Core and NS5) when sample #37 was diluted up to 1:1000, whereas the ELISA could detect HCV only in the undiluted HCV-positive sample (#37) (Fig. 1B
). These findings indicate that the protein microarray has a detection limit that is 1000 times that of the ELISA.
We used a sol-gel material optimization method to develop HCV diagnostic microarrays. Successful detection of HCV requires a test with both high sensitivity and high specificity. The sensitivity of the sol-gel protein microarray method is comparable to that of ELISA. With respect to specificity, the sol-gel protein microarray method greatly enhances diagnostic accuracy by decreasing the number of false-positive results. Serum samples with low titer values tend to yield false-positive results in an HCV diagnostic ELISA (see Supplementary Figs. 3 and 4 in the online Data Supplement), whereas with our method, these samples were shown to be HCV negative. Therefore, because of its high throughput, sensitivity, accuracy, and use of economical sol-gel–based techniques, our novel prototype microarray assay shows great potential for replacing the current ELISA-based diagnostic methods (16)(20). In addition, because of the compatibility of our assay with the currently employed automated methods used for ELISA, the existing equipment could be easily adapted for use with our technology. This study is the first clinical application of the sol-gel protein microarray detection system and provides an important new practical screening technology to advance the current state of infectious disease diagnosis.
Acknowledgments
Grant/funding Support: KIEST (Grant #101-051-022), MOHW (Grant #A050814), and Seoul R&BD Program to S.K. supported this work. D.-k. L. was supported by grants from the SRC/ERC program of MOST/ KOSEF (grant R11-2000-070-080010). This work was also supported by the National Research Laboratory of the Korean Ministry of Science and Technology (#M10600000251-06J0000-25110).
Financial Disclosures: None declared.
References
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