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Updated: Jul 3, 2026
Viral Concentration Determination Through Plaque Assays: Using Traditional and Novel Overlay Systems
Published on: November 4, 2014
An estimation of the overlap bias in plaque assay
1Bundesforschungsanstalt für Viruskrankheiten der Tiere in Tübingen, Germany.
Abstract:
A systematic underestimation of the density of PFU's of a virus suspension is caused by overlapping plaques. The degree of this bias depends on n, the number of plaques distributed over the petri dish and on d, the (mean) diameter of the plaques. The mean number of overlapping events, y, is proportional to n2 and to d2, y = cn2d2. If the experimental circumstances yield values of n or d or of both, which are too large, incorrect inferences may be drawn from the outcome of a quantitative plaque test. For example, there is danger that an existing difference in the concentration of two virus-suspensions will not be detected. It is of interest, therefore, to evaluate c, the factor of proportionality. From this an equation may be derived which relates the number of observed plaques (including the unknown number of overlapping events) directly to the expected true number of plaques on the dish. Furthermore, upper limits of the number of observed plaques, which should not be exceeded in experimentation to avoid any overlap are given at several levels of d for 5-cm dishes. The evaluation of c was performed by a set of Monte Carlo procedures.
Insights
Overlapping viral plaques systematically underestimate virus concentration. This study quantifies the overlap bias using plaque number and diameter, providing a method to correct plaque assay results for accurate virus quantification.
Area of Science:
- Virology
- Biophysical Chemistry
Background:
- Accurate virus quantification is crucial for virology research and diagnostics.
- Plaque assays are a standard method for determining virus concentration, measured in plaque-forming units (PFU).
- Overlapping plaques in standard assays lead to a systematic underestimation of the true virus concentration.
Purpose of the Study:
- To investigate the relationship between plaque number, plaque diameter, and the degree of plaque overlap.
- To develop a method for correcting PFU counts biased by plaque overlap.
- To determine the proportionality constant (c) in the equation for overlapping events (y = cn²d²).
Main Methods:
- Utilized Monte Carlo simulations to evaluate the proportionality constant (c).
- Analyzed the impact of plaque number (n) and mean plaque diameter (d) on the number of overlapping events (y).
- Derived an equation to relate observed plaque counts to the expected true PFU count.
Main Results:
- Established that the mean number of overlapping events is proportional to the square of plaque number and the square of plaque diameter (y = cn²d²).
- Quantified the proportionality constant 'c' through computational simulations.
- Provided upper limits for observed plaque counts on 5-cm dishes to avoid overlap at various plaque diameters.
Conclusions:
- Plaque overlap significantly biases virus quantification, potentially leading to missed detection of differences between virus suspensions.
- The derived equation and quantified constant 'c' allow for correction of PFU counts, improving accuracy.
- Recommendations for experimental parameters are provided to minimize overlap and ensure reliable virus titration.
