Time to revisit the endpoint dilution assay and to replace the TCID50 as a measure of a virus sample’s infection concentration

Daniel Cresta, Donald C Warren, Christian Quirouette, Amanda P Smith, Lindey C Lane, Amber M Smith and Catherine A A Beauchemin

PLOS Computational Biology, 2021, vol. 17, issue 10, 1-20

Abstract: The endpoint dilution assay’s output, the 50% infectious dose (ID50), is calculated using the Reed-Muench or Spearman-Kärber mathematical approximations, which are biased and often miscalculated. We introduce a replacement for the ID50 that we call Specific INfection (SIN) along with a free and open-source web-application, midSIN (https://midsin.physics.ryerson.ca) to calculate it. midSIN computes a virus sample’s SIN concentration using Bayesian inference based on the results of a standard endpoint dilution assay, and requires no changes to current experimental protocols. We analyzed influenza and respiratory syncytial virus samples using midSIN and demonstrated that the SIN/mL reliably corresponds to the number of infections a sample will cause per mL. It can therefore be used directly to achieve a desired multiplicity of infection, similarly to how plaque or focus forming units (PFU, FFU) are used. midSIN’s estimates are shown to be more accurate and robust than the Reed-Muench and Spearman-Kärber approximations. The impact of endpoint dilution 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 provided by midSIN make them an easy and superior replacement for the TCID50 and other in vitro culture ID50 measures. We hope to see their universal adoption to measure the infectivity of virus samples.Author summary: The infectivity of a virus sample is measured by the infections it causes. One approach, the endpoint dilution assay, aims to estimate the number of TCID50 contained in a sample, where one TCID50 is the dose at which a virus sample is expected to infect a tissue or cell culture 50% of the time, on average. Unfortunately, the commonly used methods to estimate the TCID50 from the assay’s outcome yield biased approximations that relate poorly to the number of infections the sample will cause. We propose replacing the TCID50 with a more accurate, robust, and biologically meaningful measurement unit we call Specific INfection (SIN). It corresponds to the number of infections the virus sample will cause, which can be used directly to achieve the desired multiplicity of infection. Computing the SIN from one’s endpoint dilution assay outcome requires no change in experimental procedure, and can be done conveniently via a web-application we developed, called midSIN. midSIN can be accessed for free on any device (laptop, cellular phone, tablet) from any web browser, without the need to download and install software.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1009480

DOI: 10.1371/journal.pcbi.1009480

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