Combination of the Focus-Forming Assay and Digital Automated Imaging Analysis for the Detection of Dengue and Zika Viral Loads in Cultures and Acute Disease

Abstract

Optimized methods for the detection of flavivirus infections in hyperendemic areas are still needed, especially for working with patient serum as a starting material. The focus-forming assay (FFA) reveals critical aspects of virus-host interactions, as it is a quantitative assay to determine viral loads. Automated image analysis provides evaluations of relative amounts of intracellular viral protein at the single-cell level. Here, we developed an optimized FFA for the detection of infectious Zika virus (ZIKV) and dengue virus (DENV) viral particles in cell cultures and clinical serum samples, respectively. Vero-76 cells were infected with DENV-2 (16681) or ZIKV (PRVA BC59). Using a panel of anti-DENV and anti-ZIKV NS1-specific monoclonal antibodies (mAbs), the primary mAbs, concentration, and the optimal time of infection were determined. To determine whether intracellular accumulation of NS1 improved the efficiency of the FFA, brefeldin A was added to the cultures. Focus formation was identified by conventional optical microscopy combined with CellProfiler™ automated image analysis software. The FFA was used with spike assays for ZIKV and clinical specimens from natural infection by DENV-1 and DENV-2. mAb 7744-644 for ZIKV and mAb 724-323 for DENV used at a concentration of 1 μg/ml and a time of 24 hours postinfection produced the best detection of foci when combining conventional counting and automated digital analysis. Brefeldin A did not improve the assessment of FFUs or their digitally assessed intensity at single-cell level. The FFA showed 95% ZIKV recovery and achieved the detection of circulating DENV-1 and DENV-2 in the plasma of acutely ill patients. The combination of the two techniques optimized the FFA, allowing the study of DENV and ZIKV in culture supernatants and clinical specimens from natural infection in hyperendemic areas.

Efficiency of Automated Viral RNA Purification for Pediatric Studies of Dengue and Zika in Hyperendemic Areas

“…For the ZIKV analyses, automated RNA isolation was performed on 249 plasma samples from healthy pediatric patients taken between 2012 and 2014 (before ZIKV had come to the Americas). For the spiked experiments, 40 samples were added to in vitro known amounts of ZIKV strain PRVA BC59 previously titrated by a focus-forming assay [ 14 ] in a range of 50–100,000 focus-forming units (FFU)/mL. The study design is presented in Figure 1 .…”

“…In all experiments, a mixture of culture supernatant from Vero-76 cells infected with each of the DENV serotypes or supernatant from uninfected cells was used as a positive and negative control, respectively. strain PRVA BC59 was titrated by focus formation assays [14], then added in diferent amounts to the plasma of 40 healthy pediatric volunteers taken before the arrival of ZIKV to the Americas. Te range of FFU tested was 50-100,000 FFU/mL, all with a fnal constant volume of 200 µL that was used for purifcation with the automated protocol.…”

Current Landscape of Methods to Evaluate Antimicrobial Activity of Natural Extracts

“…The viral titer is expressed in focus-forming units per mL (FFU/mL) [ 163 , 164 ]. Additionally, with the advancement of instrumentation and the high contrast of reagents, counting can be automated for more precision and less subjectivity in a high-throughput setting [ 163 , 164 , 165 ]. Additionally, other quick and sensitive methods, such as cell-based enzyme-linked immunosorbent assay (ELISA) and quantitative real-time polymerase chain reaction (PCR), are used to determine antiviral activity by measuring the reduction in viral antigen or virus nucleic acid in infected cells in the presence of the test molecule [ 166 , 167 , 168 ].…”

UChOA‐ANN based effective diagnostic model for early detection and accurate prediction of dengue affected blood samples

“…In the past, the analysis of the blood sample is done manually to count the number of blood cells and to identify the disorders through a microscope 11 . But, microscopic image analysis is one of the challenging tasks due to the presence of weak correlation and different segments of interest that may lead to ambiguity 12 . It is also valuable in the foremost meadows of technology and medicine.…”

“…11 But, microscopic image analysis is one of the challenging tasks due to the presence of weak correlation and different segments of interest that may lead to ambiguity. 12 It is also valuable in the foremost meadows of technology and medicine. Identification and counting of cells play a vital role in feature extraction to diagnose particular diseases precisely.…”