Virus replication strategies and the critical CTL numbers required for the control of infection.
Virus replication strategies and the critical CTL numbers required for the control of infection.
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DOI：
10.1371/journal.pcbi.1002274
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发表时间：
2011-11
影响因子：
4.3
通讯作者：
Antia R
中科院分区：
文献类型：
--
作者：
Yates AJ;Van Baalen M;Antia R
引起保护性细胞毒性T淋巴细胞（CTL）的疫苗可以改善或增强那些主要引起抗体反应的疫苗。然而，我们几乎没有估计感染部位消毒免疫所需CTL数量的基础。为了解决这个问题，我们从测量CTL监测率和病毒生长速度得到的理论估计开始。我们展示了如何修改这一估计，以解释(i) ctl感染细胞偶联物的动力学，以及（ii）感染细胞中病毒生命周期的特征。研究表明，如果病毒接种量较低，CTL感染细胞偶联物的动力学可以忽略不计，但估计CTL密度的临界阈值需要了解病毒生活史。我们表明，考虑病毒复制策略可以提高免疫所需CTL最小密度的估计值，而不是使用病毒动力学的规范模型获得的估计值，并证明该建模框架允许我们预测和比较CTL控制不同生活史策略的病毒的能力。作为一个例子，我们预测，当净繁殖率和感染细胞寿命被控制时，裂解病毒比出芽病毒更难控制。此外，我们使用恒河猴急性SIV感染的数据来计算疫苗必须产生的CTL密度的下限，以控制进入部位的感染。我们建议使用结合病毒生活史的定量模型或使用病毒感染细胞而不是肽脉冲靶标进行体内试验，可以更好地估计临界CTL密度。在寻找能够提供可靠保护以抵御艾滋病毒-艾滋病、结核病和疟疾等重大疾病的疫苗的过程中，现在的重点是产生抗原特异性细胞毒性T淋巴细胞（CTL）群，这种免疫细胞能够识别并杀死受感染的细胞。然而，我们对疫苗需要诱导CTL的数量或密度知之甚少，以提供对特定组织感染的灭菌免疫。在这项研究中，我们使用数学模型来了解病毒的复制策略如何影响在感染部位提供免疫所需的CTL的最小密度。我们表明，忽略感染细胞内病毒生命周期的传统模型将低估这种密度。为了说明这一点，我们使用我们的建模框架来估计在恒河猴原发性SIV感染的最早阶段控制病毒传播所需的CTL密度。
Vaccines that elicit protective cytotoxic T lymphocytes (CTL) may improve on or augment those designed primarily to elicit antibody responses. However, we have little basis for estimating the numbers of CTL required for sterilising immunity at an infection site. To address this we begin with a theoretical estimate obtained from measurements of CTL surveillance rates and the growth rate of a virus. We show how this estimate needs to be modified to account for (i) the dynamics of CTL-infected cell conjugates, and (ii) features of the virus lifecycle in infected cells. We show that provided the inoculum size of the virus is low, the dynamics of CTL-infected cell conjugates can be ignored, but knowledge of virus life-histories is required for estimating critical thresholds of CTL densities. We show that accounting for virus replication strategies increases estimates of the minimum density of CTL required for immunity over those obtained with the canonical model of virus dynamics, and demonstrate that this modeling framework allows us to predict and compare the ability of CTL to control viruses with different life history strategies. As an example we predict that lytic viruses are more difficult to control than budding viruses when net reproduction rates and infected cell lifetimes are controlled for. Further, we use data from acute SIV infection in rhesus macaques to calculate a lower bound on the density of CTL that a vaccine must generate to control infection at the entry site. We propose that critical CTL densities can be better estimated either using quantitative models incorporating virus life histories or with in vivo assays using virus-infected cells rather than peptide-pulsed targets. In the search for vaccines that provide reliable protection against major diseases such as HIV-AIDS, TB and Malaria, there is now a focus on generating populations of antigen-specific cytotoxic T lymphocytes (CTL), immune cells that recognise and kill infected cells. However, we have little idea of the number or density of CTL a vaccine would need to elicit to provide sterilizing immunity to an infection in a given tissue. In this study we use mathematical models to understand how a virus's replication strategy influences the minimum density of CTL needed to provide immunity at an infection site. We show that traditional models that neglect the viral lifecycle within infected cells will underestimate this density. To illustrate, we use our modelling framework to estimate the CTL density needed to control the spread of virus at the very earliest stages of primary SIV infection in rhesus macaques.
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影响因子：
3.7
作者：
Ganusov VV;Lukacher AE;Byers AM
通讯作者：
Byers AM
影响因子：
32.4
作者：
Mempel, Thorsten R.;Pittet, Mikael J.;von Andrian, Ulrich H.
通讯作者：
von Andrian, Ulrich H.
DOI：
10.1098/rspb.2011.0453
发表时间：
2011-11-22
影响因子：
4.7
作者：
Graw, Frederik;Richter, Kirsten;Regoes, Roland R.
通讯作者：
Regoes, Roland R.
影响因子：
3.5
作者：
Pilyugin, SS;Antia, R
通讯作者：
Antia, R
影响因子：
5.4
作者：
Althaus, Christian L.;De Vos, Anneke S.;De Boer, Rob J.
通讯作者：
De Boer, Rob J.