Future Science Group
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Supplementary Figure 2

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posted on 2019-12-18, 11:19 authored by Ying ZhuYing Zhu, József Mészáros, Roman Walle, Rongxi Fan, Ziyi Sun, Andrew J. Dwork, Pierre Trifilieff, Jonathan A. Javitch

Supplemental Figure. 2. Quantification of PLA signal with BOPSS and manual counting. Three randomly selected areas in a full counting image of each PLA condition, single (A), dual (B) and negative PLA (C) (from PI12277) were quantified with BOPSS or manually (four times independently). The puncta counted by BOPSS were marked in red in the representative images of pre-optimization (BOPSS_0, D-F) and post-optimization analysis (BOPSS, G-I). The blue arrows indicated examples of reduced non-specific detection in post-optimization analysis. The manually counted puncta were marked in black and labelled with yellow numbers with Cell Counter (Image J) (J-L). The orange and white arrows indicate examples of overcounted and undercounted puncta detected by BOPSS compared with manual counting, respectively. One-way ANOVA was performed to analyze the results of single PLA. There is no significant difference among three quantification methods (P value=0.113) (M). Two-way ANOVA was performed to compare the quantification results for dual PLA and its negative control, which had the same PLA condition as dual PLA but omit one primary antibody (N). The interaction accounts for approximately 2.5 % of the total variance and is considered not significant (P value=0.069). Both quantification methods (accounts 33.9 % of the total variance, P value is <0.001) and PLA conditions (accounts 41.6 % of the total variance, P value is <0.0001) have significant effect on the variation. Bonferroni’s multiple comparison were performed to compare BOPSS and other methods (M and N), **** multiplicity adjusted P value <0.0001, ** <0.01.


This study was supported by MH54137, MH060877 and MH090964.