Time to revisit the endpoint dilution assay and to replace the TCID50 as a measure of a virus sample's infection concentration.
Time to revisit the endpoint dilution assay and to replace the TCID50 as a measure of a virus sample's infection concentration.
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DOI：
10.1371/journal.pcbi.1009480
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发表时间：
2021-10
影响因子：
4.3
通讯作者：
Beauchemin CAA
中科院分区：
文献类型：
--
作者：
Cresta D;Warren DC;Quirouette C;Smith AP;Lane LC;Smith AM;Beauchemin CAA
终点稀释试验的输出，即50%感染剂量（ID 50），是使用Reed-Muench或Spearman-Kärber数学近似法计算的，这是有偏差的，经常计算错误。我们引入了ID 50的替代品，我们称之为特异性感染（SIN）沿着，并使用免费开源的Web应用程序midSIN（https：midsin.physics.ryerson.ca）来计算它。midSIN基于标准终点稀释测定的结果使用贝叶斯推断计算病毒样本的SIN浓度，并且不需要更改当前的实验方案。我们使用midSIN分析了流感和呼吸道合胞病毒样本，并证明SIN/mL可靠地对应于每mL样本将引起的感染数量。因此，它可以直接用于实现所需的多重感染，类似于如何使用斑块或病灶形成单位（PFU，FFU）。midSIN的估计比Reed-Muench和Spearman-Kärber近似更准确和稳健。还探讨了终点稀释平板设计选择（稀释因子、每次稀释的重复次数）对测量准确度的影响。SIN作为测量的简单性和midSIN提供的更高准确度使其成为TCID 50和其他体外培养ID 50测量的简单和上级替代品。我们希望看到它们被普遍采用来测量病毒样本的传染性。病毒样本的传染性是通过它引起的感染来衡量的。一种方法，终点稀释试验，旨在估计样品中包含的TCID 50的数量，其中一个TCID 50是病毒样品预期在50%的时间内感染组织或细胞培养物的平均剂量。不幸的是，常用的方法来估计TCID 50从测定的结果产生偏差的近似值，相关性较差的感染的数量的样品将导致。我们建议用一个更准确，更强大，更有生物学意义的测量单位来取代TCID 50，我们称之为特异性感染（SIN）。它对应于病毒样本将引起的感染数量，可以直接用于实现所需的感染复数。从终点稀释测定结果计算SIN不需要改变实验程序，并且可以通过我们开发的称为midSIN的网络应用程序方便地完成。midSIN可以在任何设备（笔记本电脑，手机，平板电脑）上从任何Web浏览器免费访问，而无需下载和安装软件。
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. 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.
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影响因子：
3.1
作者：
LaBarre, DD;Lowy, RJ
通讯作者：
Lowy, RJ
影响因子：
3.4
作者：
Mistry, Bhaven A.;D'Orsogna, Maria R.;Chou, Tom
通讯作者：
Chou, Tom
DOI：
10.1007/bf01863914
发表时间：
1931-01-01
影响因子：
--
作者：
Karber, G
通讯作者：
Karber, G
DOI：
10.1186/2043-9113-2-5
发表时间：
2012-02-13
期刊：
Journal of clinical bioinformatics
影响因子：
--
作者：
Wulff NH;Tzatzaris M;Young PJ
通讯作者：
Young PJ
DOI：
10.1073/pnas.89.16.7581
发表时间：
1992-08-15
影响因子：
11.1
作者：
SPOUGE, JL
通讯作者：
SPOUGE, JL