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Development of a novel peptide aptamer-based immunoassay to detect Zika virus in serum and urine.

ABSTRACT: Zika virus (ZIKV) has been identified as a cause of adverse outcomes of pregnancy, including microcephaly and other congenital diseases. Most people infected with ZIKV do not show any symptoms. Development of a method to discriminate dengue virus (DENV) and ZIKV infections has been challenging, and efficient assays for patient management are limited, attributable to high levels of cross-reactivity among co-circulating Flaviviruses. Thus, there is an urgent need for a specific high-throughput diagnostic assay to discriminate ZIKV infections from other Flavivirus infections. Methods: A novel epitope peptide of the ZIKV envelope protein was predicted using three immune epitope database analysis tools and then further modified. A molecular docking study was conducted using three-dimensional structures of the ZIKV envelope and peptide. Experimentally, interactions between the selected peptides and virus were assessed via a fluorescence-linked sandwich immunosorbent assay (FLISA), and performance of peptide-linked sandwich FLISA was evaluated in virus-spiked human serum and urine. Results: The Z_10.8 peptide (KRAVVSCAEA) was predicted to be a suitable detector, with a higher binding affinity than other candidates based on four criteria (binding affinity, root mean square deviation, position of amine residue of lysine at the N-terminus, and interactive site) in a docking study. Z_10.8 was significantly more efficient at detecting ZIKV than the other two peptides, as shown in the direct FLISA (P < 0.001). Further, the equilibrium dissociation constant (K_d) for the Z_10.8 peptide was 706.0 ± 177.9 (mean ± SD, nM), with specificity to discriminate ZIKV from DENV. The limit of detection for the sandwich FLISA was calculated as 1×10⁴ tissue culture infective dose (TCID)₅₀/mL. The presence of serum or urine did not interfere with the performance of the Z_10.8-linked sandwich FLISA. Conclusion: Four criteria are suggested for the development of an in silico modeled peptide aptamer; this computerized peptide aptamer discriminated ZIKV from DENV via immunoassay.

SUBMITTER: Kim DTH

PROVIDER: S-EPMC6037026 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Development of a novel peptide aptamer-based immunoassay to detect Zika virus in serum and urine.

Kim Do Thi Hoang DTH Bao Duong Tuan DT Park Hyun H Ngoc Nguyen Minh NM Yeo Seon-Ju SJ

Theranostics 20180607 13

Zika virus (ZIKV) has been identified as a cause of adverse outcomes of pregnancy, including microcephaly and other congenital diseases. Most people infected with ZIKV do not show any symptoms. Development of a method to discriminate dengue virus (DENV) and ZIKV infections has been challenging, and efficient assays for patient management are limited, attributable to high levels of cross-reactivity among co-circulating <i>Flaviviruses</i>. Thus, there is an urgent need for a specific high-through ...[more]

PMID: 30026871

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Project description:BackgroundHome monitoring of urine protein is a critical component of disease management in childhood nephrotic syndrome. We describe the development of a novel mobile application, UrApp - Nephrotic Syndrome Manager, to aid disease monitoring.MethodsUrApp was iteratively developed by a panel of two pediatric nephrologists and three research engineers from May 2017 to October 2018 for Apple iPhones. App features were devised by this expert panel to support urine monitoring and other home care tasks. Each feature and user-app interface element was systematically reviewed by the panel and iteratively redesigned to remove anticipated use issues. The app prototype was then refined based on two rounds of usability testing and semi-structured user interviews with a total of 20 caregivers and adolescent patients. The analytic function of UrApp in providing a camera read of the urine test strip was compared to a standard urinalysis machine using 88 patient urine samples and three iPhones, model versions 6S and 7. Exact agreement and weighted kappa were calculated between the UrApp and urinalysis machine reads.ResultsThe final UrApp features include: camera read of a urine test strip; analysis of urine protein trends and alerts for new disease relapse/remission; transmission of urine protein results to providers; education materials; and medication reminders. During the second round of UrApp usability testing, all users were able to perform each of the functions without error and all perceived UrApp to be helpful and indicated that they would use UrApp. UrApp camera results had 97% exact agreement and an overall weighted kappa value of 0.91 (95% CI, 0.85-0.97) compared with standard urinalysis machine interpretation.ConclusionsUrApp was specifically designed to support patients and families living with nephrotic syndrome by supporting disease monitoring and home management tasks. The technically innovative feature that makes this possible is the use of a smartphone camera to read the urine test strip. This novel tool has the potential to improve disease monitoring and reduce management burden.

Dataset Information

Development of a novel peptide aptamer-based immunoassay to detect Zika virus in serum and urine.

Publications

Development of a novel peptide aptamer-based immunoassay to detect Zika virus in serum and urine.

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