  We present a rapid and stain-free quantitative viral plaque assay using
lensfree holographic imaging and deep learning. This cost-effective, compact,
and automated device significantly reduces the incubation time needed for
traditional plaque assays while preserving their advantages over other virus
quantification methods. This device captures ~0.32 Giga-pixel/hour phase
information of the objects per test well, covering an area of ~30x30 mm^2, in a
label-free manner, eliminating staining entirely. We demonstrated the success
of this computational method using vesicular stomatitis virus (VSV), herpes
simplex virus (HSV-1) and encephalomyocarditis virus (EMCV). Using a neural
network, this stain-free device automatically detected the first cell lysing
events due to the VSV viral replication as early as 5 hours after the
incubation, and achieved >90% detection rate for the VSV plaque-forming units
(PFUs) with 100% specificity in <20 hours, providing major time savings
compared to the traditional plaque assays that take at least 48 hours.
Similarly, this stain-free device reduced the needed incubation time by ~48
hours for HSV-1 and ~20 hours for EMCV, achieving >90% detection rate with 100%
specificity. We also demonstrated that this data-driven plaque assay offers the
capability of quantifying the infected area of the cell monolayer, performing
automated counting and quantification of PFUs and virus-infected areas over a
10-fold larger dynamic range of virus concentration than standard viral plaque
assays. This compact, low-cost, automated PFU quantification device can be
broadly used in virology research, vaccine development, and clinical
applications.
