Comparative Study
doi: 10.1016/j.jviromet.2010.10.010. Epub 2010 Oct 21.Evaluation of the Virus Counter® for rapid baculovirus quantitation
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- PMID:20970458
- PMCID: PMC3011032
- DOI: 10.1016/j.jviromet.2010.10.010
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Comparative Study
Evaluation of the Virus Counter® for rapid baculovirus quantitation
Matthew M Ferris et al. J Virol Methods.2011 Jan.
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Abstract
The utility of a new instrument for rapid virus quantitation, the Virus Counter, was evaluated in a blind study conducted at three sites. This instrument is a substantially improved version of the original academic research instrument described previously by Stoffel and Rowlen (2005a). The addition of hydrodynamic focusing, a self-contained fluidics system and customized software for system control and data analysis has resulted in a commercially viable and available design. Baculovirus samples were provided by Protein Sciences Corporation and blinded to InDevR and Baylor College of Medicine. Protein Sciences Corporation and Baylor College of Medicine analyzed the samples by plaque assay and InDevR analyzed the samples using the Virus Counter. Serial dilution of stock viruses into growth media and buffer allowed for comparison of measured versus intended concentrations. Direct log-scale comparison between pooled Virus Counter results and pooled plaque assay results indicated a linear relationship (slope=1.1±0.2, R(2)=0.86) with statistically significant Pearson correlation (r=0.93, p<0.001).
Copyright © 2010 Elsevier B.V. All rights reserved.
Conflict of interest statement
InDevR, Inc. is a for-profit entity and four of the eleven authors are employees of the company.
Figures
Data points represent the mean measured result of samples 1a–7a with error bars representing ±1σ from the mean. Within the Virus Counter data set (triangles), the lowest three values are shown as unfilled triangles to indicate that these values were below the SQL determined for PSFM and were not included in the linear regression fit to the data. Coefficients of determination (R2) for linear regression fits to the data were 0.81 for Protein Sciences Corporation (diamonds with a dashed line), 0.97 for Baylor College of Medicine (squares with a dot-dash line) and 1.0 for InDevR (triangles with a solid line). Slopes of the regression fits were 1.1 ± 0.2 for Protein Sciences Corporation, 0.81 ± 0.07 for Baylor College of Medicine and 1.2 ± 0.1 for InDevR. Pearson correlation coefficients for the Virus Counter, Protein Sciences Corporation and Baylor College of Medicine were r = 0.94 (p < 0.01), r = 0.90 (p < 0.01) and r = 0.99 (p < 0.001), respectively.
Data points represent the mean measured result of samples 1b–7b with error bars representing ±1σ from the mean. Within the Virus Counter data set (triangles), results for samples 5b and 6b are shown as unfilled triangles to indicate that these values were below the SQL determined for SDB and were not included in the linear regression fit to the data. Sample 7b returned a zero count and is not included in the figure or the regression fit to the data. Coefficients of determination (R2) for the linear regressions fits to the data were 0.85 for Protein Sciences Corporation (diamonds with a dashed line), 0.82 for Baylor College of Medicine (squares with a dot-dash line) and 1.0 for InDevR (triangles with a solid line). Slopes of the regression fits were 0.5 ± 0.1 for Protein Sciences Corporation, 1.0 ± 0.3 for Baylor College of Medicine and 1.32 ± 0.04 for InDevR. Pearson correlation coefficients for the Virus Counter, Protein Sciences Corporation and Baylor College of Medicine were r = 1 (p < 0.001), r = 0.92 (p < 0.01) and r = 0.90 (p < 0.05), respectively.
Mean results for all samples above SQL (i.e. both PSFM and SDB) are shown. Mean plaque assay results are the combined results from Baylor College of Medicine and Protein Sciences Corporation. Error bars represent the standard error of the mean. The solid line represents a linear regression fit to the data and was obtained with a coefficient of dertermination (R2) of 0.86 and a slope of 1.1 ± 0.2. The Pearson correlation coefficient was determined to be 0.93 (p < 0.001).
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