Time to revisit the endpoint dilution assay and to replace TCID$_{50}$ and PFU as measures of a virus sample's infection concentration

TL;DR

This paper proposes replacing traditional virus infectivity measures like TCID50 and PFU with a new, more accurate metric called Specific Infections (SIN), supported by a web tool that improves measurement robustness and simplicity.

Contribution

The paper introduces SIN as a novel, more reliable measure of virus infectivity and provides an open-source tool, midSIN, to calculate it from standard endpoint dilution assays.

Findings

SIN correlates directly with infection counts per volume

midSIN outperforms traditional ID50 calculations in accuracy

The method is robust to plate design variations

Abstract

The infectivity of a virus sample is measured by the infections it causes, via a plaque or focus forming assay (PFU or FFU) or an endpoint dilution (ED) assay (TCID$_{50}$, CCID$_{50}$, EID$_{50}$, etc., hereafter collectively ID$_{50}$). The counting of plaques or foci at a given dilution intuitively and directly provides the concentration of infectious doses in the undiluted sample. However, it has many technical and experimental limitations. For example, it relies on one's judgement in distinguishing between two merged plaques and a larger one, or between small plaques and staining artifacts. In this regard, ED assays are more robust because one need only determine whether infection occurred. The output of the ED assay, the 50% infectious dose (ID$_{50}$), is calculated using either the Spearman-Karber (SK, 1908,1931) or Reed-Muench (RM, 1938) mathematical approximations. However, these are often miscalculated and their ID$_{50}$ approximation is biased. We propose that the PFU and FFU assays be abandoned, and that the measured output of the ED assay, the ID$_{50}$, be replaced by a more useful measure we coined Specific INfections (SIN). We introduce a free, open-source web-application, midSIN, that computes the SIN concentration in a virus sample from a standard ED assay, requiring no changes to current experimental protocols. We demonstrate that the SIN/mL of a sample reliably corresponds to the number of infections the sample will cause per unit volume, and directly relates to the multiplicity of infection. midSIN estimates are shown to be more accurate and robust than those using the RM and SK approximations. The impact of ED plate design choices (dilution factor, replicates per dilution) on measurement accuracy is also explored. The simplicity of SIN as a measure and the greater accuracy of midSIN make them an easy, superior replacement for the PFU, FFU, and ID$_{50}$ measures.