Zhang Changwang, Zhou Shi, Groppelli Elisabetta, Pellegrino Pierre, Williams Ian, Borrow Persephone, Chain Benjamin M, Jolly Clare
Department of Computer Science, University College London, London, United Kingdom; Security Science Doctoral Research Training Centre, University College London, London, United Kingdom; School of Computer Science, National University of Defense Technology, Changsha, China.
Department of Computer Science, University College London, London, United Kingdom.
PLoS Comput Biol. 2015 Apr 2;11(4):e1004179. doi: 10.1371/journal.pcbi.1004179. eCollection 2015 Apr.
HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments' influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies.
HIV-1可通过两种机制在易感细胞间传播:病毒粒子在液相扩散后进行无细胞感染,以及在免疫细胞接触处进行高效的直接细胞间传播。这种混合传播机制也是一些重要计算机蠕虫爆发的特征,其对HIV-1在体内进展的作用尚不清楚。在此,我们提出一种新的数学模型,该模型明确纳入了HIV-1利用混合传播机制的能力,并评估其对HIV-1发病机制的影响。该模型捕捉了一组未接受过治疗的患者的HIV-1感染过程的主要阶段,还准确预测了血清转化时短期脉冲抗逆转录病毒疗法(SPARTAC)试验的结果。利用该模型,我们发现混合传播对于感染的起始和建立至关重要,并且细胞间传播和CD4+ T细胞活化增加对HIV-1进展很重要。值得注意的是,该模型预测随着感染进展,细胞间传播会变得越来越有效,因此可能构成相当大的治疗障碍。推导各种治疗对HIV-1进展影响的预测结果突出了早期干预的重要性,并表明有效靶向HIV-1细胞间传播的治疗可延缓向艾滋病的进展。这项研究表明混合传播是HIV感染的一个基本特征,并提供了一个纳入该特征的数学框架,用以评估未来的治疗策略。