| Literature DB >> 33805173 |
Fanny Leon1, Elena Pinchon1, Nevzat Temurok2, François Morvan3, Jean-Jacques Vasseur3, Martine Clot2, Vincent Foulongne1, Jean-François Cantaloube1, Philippe Vande Perre1, Jean-Pierre Molès1, Aurélien Daynès2, Chantal Fournier-Wirth1.
Abstract
Arbovirus diagnostics on blood from donors and travelers returning from endemic areas is increasingly important for better patient management and epidemiological surveillance. We developed a flexible approach based on a magnetic field-enhanced agglutination (MFEA) readout to detect either genomes or host-derived antibodies. Dengue viruses (DENVs) were selected as models. For genome detection, a pan-flavivirus amplification was performed before capture of biotinylated amplicons between magnetic nanoparticles (MNPs) grafted with DENV probes and anti-biotin antibodies. Magnetization cycles accelerated this chaining process to within 5 min while simple turbidimetry measured the signal. This molecular MFEA readout was evaluated on 43 DENV RNA(+) and 32 DENV RNA(-) samples previously screened by real-time RT-PCR. The sensitivity and the specificity were 88.37% (95% CI, 78.76%-97.95%) and 96.87% (95% CI, 90.84%-100%), respectively. For anti-DENV antibody detection, 103 plasma samples from donors were first screened using ELISA assays. An immunological MFEA readout was then performed by adding MNPs grafted with viral antigens to the samples. Anti-DENV antibodies were detected with a sensitivity and specificity of 90.62% (95% CI, 83.50%-97.76%) and 97.44% (95% CI, 92.48%-100%), respectively. This adaptable approach offers flexibility to platforms dedicated to the screening of emerging infections.Entities:
Keywords: antibodies; arbovirus; innovative diagnostic; magnetic agglutination; nanoparticles; viral genomes
Year: 2021 PMID: 33805173 PMCID: PMC8064388 DOI: 10.3390/microorganisms9040674
Source DB: PubMed Journal: Microorganisms ISSN: 2076-2607
Figure 1Diagnostic of dengue virus (DENV) infection by magnetic field-enhanced agglutination readout (MFEA readout). The molecular MFEA readout aims to detect the DENV RNA during the acute phase of infection. DENV genomes are extracted and amplified using asymmetric pan-flavivirus RT-PCR amplification. The biotinylated DENV amplicons are captured between magnetic nanoparticles (MNPs) grafted with specific DENV tetrathiolated DNA probes (MNPs-Probe) and anti-biotin antibodies (MNPs-Ab). The immunological MFEA approach aims to detect the anti-DENV antibodies in plasma samples during the convalescent phase of infection. These antibodies are captured between MNPs grafted with viral DENV NS1 antigens (MNPs-NS1) in a homogeneous phase.
Figure 2Molecular MFEA readout for DENV RNA(−) and DENV RNA(+) plasma samples.
Molecular MFEA readout on biological samples.
| Sample Type | Samples, | Samples Correctly Detected, | Diagnostic Sensitivity * | Diagnostic Specificity † | Accuracy ‡ % |
|---|---|---|---|---|---|
|
| 43 | 38 | 88.37 (78.79–97.95) | / | 92 |
|
| 32 | 31 | / | 96.87 (90.84–100.00) |
Detailed results can be found in Supplemental Table S1. DENV, dengue virus; CI, confidence interval. * [number of positive samples/(number of positive samples + number of false-negative samples)] × 100. † [number of negative samples/(number of negative samples + number of false-positive samples)] × 100. ‡ [(number of negative samples + number of positive samples)/(number of negative samples + number of positive samples + number of false-negative samples + number of false-positive samples)] × 100.
Figure 3Performance of the immunological MFEA readout at detecting anti-DENV antibodies. (A) Scatterplots of the turbidity signal obtained in plasma samples classified as negative or positive for the presence of anti-DENV antibodies. Data are expressed as median turbidity signals with interquartile ranges. (B) Receiver operating characteristics (ROC) curve. The plot of True-Positive Fraction (sensitivity %) (true-positive samples/true-positive plus false-negative samples) vs. False-Positive Fraction (100 − specificity %) (false-positive samples/false-positive plus true-negative samples) generates the ROC curve. AUC: area under the ROC curve.
Immunological MFEA readout in biological samples.
| Sample Type | Samples, | Samples Correctly Detected, | Diagnostic Sensitivity * | Diagnostic Specificity † | Accuracy ‡ % |
|---|---|---|---|---|---|
|
| 64 | 58 | 90.62 (83.50–97.76) | / | 93.20 |
|
| 39 | 38 | / | 97.44 (92.48–100.00) |
DENV, dengue virus; CI, confidence interval. * [number of positive samples/(number of positive samples + number of false-negative samples)] × 100. † [number of negative samples/(number of negative samples + number of false-positive samples)] × 100. ‡ [(number of negative samples + number of positive samples)/(number of negative samples + number of positive samples + number of false-negative samples + number of false-positive samples)] × 100.