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A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial
Anthony Petkidis1,2, Vardan Andriasyan1, Luca Murer1,3
1Department of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland.
Nature Communications
|June 15, 2024
Summary
An artificial intelligence (AI) tool called DVICE automates virus detection by analyzing cell culture images. This AI framework accurately identifies various viruses and their effects, improving infectious disease diagnostics.
Area of Science:
- Virology
- Computational Biology
- Microscopy
Background:
- Traditional virus infectivity assays are labor-intensive and require manual analysis.
- Accurate and efficient methods for detecting virus-induced cytopathic effects (CPE) are needed.
Purpose of the Study:
- To develop an artificial intelligence (AI)-powered automated framework for the detection of virus-induced cytopathic effect (DVICE).
- To assess DVICE's accuracy, specificity, and adaptability for various viruses and applications.
Main Methods:
- Utilized the convolutional neural network EfficientNet-B0 with transmitted light microscopy images of infected cell cultures.
- Tested DVICE on multiple viruses including coronavirus, influenza virus, rhinovirus, herpes simplex virus, vaccinia virus, and adenovirus.
- Employed class activation mapping for robust measurement of CPE and leave-one-out cross-validation across different cell types.
Main Results:
- DVICE accurately measures virus-induced CPE, demonstrating high accuracy for diverse viruses, including SARS-CoV-2 in human saliva.
- The AI framework showed virus class specificity for adenovirus, herpesvirus, rhinovirus, vaccinia virus, and SARS-CoV-2.
- Class activation mapping confirmed robust CPE measurement by DVICE.
Conclusions:
- DVICE provides unbiased infectivity scores for infectious agents causing CPE.
- The AI tool can be adapted for laboratory diagnostics, drug screening, serum neutralization assays, and analysis of clinical samples.
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