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. 2015 Sep 28;10(9):e0138760.
doi: 10.1371/journal.pone.0138760. eCollection 2015.

Plaque2.0-A High-Throughput Analysis Framework to Score Virus-Cell Transmission and Clonal Cell Expansion

Artur Yakimovich  1 , Vardan Andriasyan  1 , Robert Witte  1 , I-Hsuan Wang  1 , Vibhu Prasad  1 , Maarit Suomalainen  1 , Urs F Greber  1
Affiliations

Plaque2.0-A High-Throughput Analysis Framework to Score Virus-Cell Transmission and Clonal Cell Expansion

Artur Yakimovich et al. PLoS One. .

Abstract

Classical plaque assay measures the propagation of infectious agents across a monolayer of cells. It is dependent on cell lysis, and limited by user-specific settings and low throughput. Here, we developed Plaque2.0, a broadly applicable, fluorescence microscopy-based high-throughput method to mine patho-biological clonal cell features. Plaque2.0 is an open source framework to extract information from chemically fixed cells by immuno-histochemistry or RNA in situ hybridization, or from live cells expressing GFP transgene. Multi-parametric measurements include infection density, intensity, area, shape or location information at single plaque or population levels. Plaque2.0 distinguishes lytic and non-lytic spread of a variety of DNA and RNA viruses, including vaccinia virus, adenovirus and rhinovirus, and can be used to visualize simultaneous plaque formation from co-infecting viruses. Plaque2.0 also analyzes clonal growth of cancer cells, which is relevant for cell migration and metastatic invasion studies. Plaque2.0 is suitable to quantitatively analyze virus infections, vector properties, or cancer cell phenotypes.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Conventional plaque assay and Plaque2.0.
Comparison of conventional plaque assay and Plaque2.0 analyses of VACV-WR-E/L-GFP (A), or VACV-IHD-E/L-GFP (B) infections of BSC40 cells in liquid medium. Conventional plaque assays were carried out in 6-well plates with a total volume of 0.5 ml per well. Plaques appeared as white round or smeary comet-like objects after 2 days, as indicated by crystal violet staining of cells in the monolayer. Plaque2.0 analyses were carried out in 96-well plates using epi-fluorescence microscopy at 4x magnification. Four images were stitched to yield an image of the entire well. Color-coded GFP intensity is scaled from 0 (violet) to 6000 gray scale values (pseudo-colored in violet to deep red).
Fig 2
Fig 2. How to use Plaque2.0 software.
(A) Downloading and using the Plaque2.0 software in three easy steps. (B) A graphical user interface (GUI) navigates through the “Operation Log” section with text output for all operations performed by the software, including potential errors. “Parameters Section” allows to specify user-defined values of the input parameters for all the software modules. “Analysis Type Switch” allows switching between parameters for individual modules, or activating and deactivating them.
Fig 3
Fig 3. Time-lapse analyses of plaque phenotypes from VACV WR and IHD-J strains demonstrate contribution of cell-free virus to spreading.
(A) Still micrographs of representative plaque phenotypes from VACV-IHD-J-E/L-GFP and VACV-WR-GFP in either gelled or liquid medium. (B) Example of VACV-WR-E/L-GFP live microscopy plaques (24 h pi) analyzed by Plaque2.0 software. Here superimposed on the micrograph from the GFP signal, green colored pixels designate foreground pixels detected by thresholding, colored line designates plaque borders and red spots highlight local intensity maxima. This procedure allows detection of adjacent plaques. (C) The relative plaque area normalized to the plaque area from gelled medium was plotted as a function of time. Note that VACV-IHD-J plaques occupy a larger area than VACV-WR at late stages of infection owing to cell-free EEV. Results represent averages from over 50 plaques for each condition from 8 technical replicas.
Fig 4
Fig 4. Analyses of HAdV infection by population or plaque phenotypes give similar results.
(A) Plaques in 96 wells of A549 cells infected with HAdV-C2_dE3B_GFP were analyzed by thresholding GFP fluorescence with Plaque2.0 software 96 h pi. Colored lines designate plaque borders and red spots local intensity maxima. This enables to distinguish plaques in near proximity to each other. (B) Micrograph depicting the nuclei of the cells in (A) stained with Hoechst 33342. (C) Correlation of HAdV-C2_dE3B_GFP plaque formation measured by Plaque2.0, infection index defined as fraction of GFP-expressing cells per total cells, and total GFP intensity in a population assay of 2-fold serially diluted inoculum. Results are mean values from 3 replicas, and error bars represent the standard deviations of the respective means.
Fig 5
Fig 5. Plaque2.0 scores infection phenotypes in high throughput mode.
(A) Effects of Ara-C (3.2 μM) and GCA (40 μM) on HAdV-C2_dE3B_GFP plaque formation in A549 cells 2 days pi with low MOI of 50 or 10 PFU per 96 well dish, respectively. Green signals designate infected cells (GFP), and red signals highlight local GFP maxima indicative of the center of the respective plaques. (B, C) Plaque2.0 scored HAdV-C2_dE3_GFP infection index, total GFP fluorescence and plaque numbers in A549 cells treated with Ara-C (B) or GCA (C). Red dotted lines represent the number of nuclei in the respective 96 wells. Results are represented as mean values from two technical replicas, and error bars represent the standard deviations of the respective means. (D) Z’-score analyses for Plaque2.0 assay of Ara-C (0.4 μM) or GCA (40 μM) tuned HAdV-C2_dE3B_GFP infections.
Fig 6
Fig 6. Fluorescence in situ hybridization scores HRV co-infections.
(A) HRV-A1A infected HeLa cells were immunostained with anti-VP1 antibodies (white signal) 72 h pi, and processed by Plaque2.0 analyses. Yellow lines designate plaque borders and red signals local intensity maxima. (B) HRV-A1A and HRV-A16 co-infected HeLa cells were detected by RNA FISH probes stained at 488 nm (HRV-A1A, green signal) and 550 nm (HRV-A16, red signal) followed by Plaque2.0 analyses. Single infections with HRV-A1A and HRV-A16 are shown in the left and middle micrograph, respectively. (C) Bar graph of HRV-A1A and HRV-A16 plaque analyses by the Plaque2.0 software. Results from individual infections and co-infections are mean values from 3 replicas, and error bars represent the standard deviations of the respective means. (D) Nearest neighbor analyses of plaque centers from HRV-A1A and HRV-A16 infections. The nearest neighbor distances between HRV-A1A and HRV-A16 plaque centroids were not different in single infections (random) or co-infections (i.e. random). Note that self co-localization control was close to zero, as expected. Results are mean values from 3 replicas containing at least 18 plaques per condition, and error bars represent the standard deviations of the respective means.
Fig 7
Fig 7. Cell density dependent features of clonal cancer cell growth in co-cultures with normal cells.
(A) Time-lapse analyses of HeLa-H2B-mCherry cell colony formation on WI-38 fibroblasts at sub-confluent (4000 WI-38 cells per well) or confluent density (32000 cells per well). Colony outlines are indicated by dashed green lines. (B) Confocal fluorescence microscopy of HeLa-H2B-mCherry cocultured with 32000, 16000, 8000 or 4000 WI-38 cells (cell numbers determined at seeding time). The samples were fixed 5 days post HeLa cell seeding. Cells were stained with Hoechst nuclear dye (blue) and immuno-stained for ß-catenin (green). Z-sections across the cultures along the dotted lines are shown on the right side and the bottom of the images. (C) Colony phenotypes of HeLa-H2B-mCherry cells co-cultured with WI-38 fibroblasts upon live-imaging and analysis with Plaque2.0. The area of the colonies is a measure of growth cell growth, the eccentricity of the elliptic colony shapes, defined as the ratio of the distance of the elliptic foci to the major axis, serves as an indicator of the cell environment, and the crowdedness fraction is an indicator of the HeLa cell colony density. Mean values from 3 technical replicas containing at least 60 individual colonies per condition are shown, and error bars represent the standard deviations of the respective means. Statistical significance was determined by the Komogorov-Smirnov nonparametric test.
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