Spouge J I, Shrager R I, Dimitrov D S
National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland, USA.
Math Biosci. 1996 Nov;138(1):1-22. doi: 10.1016/s0025-5564(96)00064-8.
Despite intensive experimental work on HIV-1, very little theoretical work has focused on HIV-1 spread in tissue culture. This article uses two systems of ordinary differential equations to model two modes of viral spread, cell-free virus and cell-to-cell contact. The two models produce remarkably similar qualitative results. Simulations using realistic parameter regimes showed that starting with a small fraction of cells infected, both cell-free viral spread and direct cell-to-cell transmission give an initial exponential phase of viral growth, followed by either a crash or a gradual decline, extinguishing the culture. Under some conditions, an oscillatory phase may precede the extinction. Some previous models of in vivo HIV-1 infection oscillate, but only in unrealistic parameter regimes. Experimental tissue infections sometimes display several sequential cycles of oscillation, however, so our models can at least mimic them qualitatively. Significantly, the models show that infective oscillations can be explained by infection dynamics; biological heterogeneity is not required. The models also display proportionality between infected cells and cell-free virus, which is reassuringly consistent with assumptions about the equivalence of several measures of viral load, except that the proportionality requires a relatively constant total cell concentration. Tissue culture parameter values can be determined from accurate, controlled experiments. Therefore, if verified, our models should make interpreting experimental data and extrapolating it to in vivo conditions sharper and more reliable.
尽管针对HIV-1开展了大量实验工作,但很少有理论研究聚焦于HIV-1在组织培养中的传播。本文使用两个常微分方程系统来模拟病毒传播的两种模式,即游离病毒传播和细胞间接触传播。这两个模型产生了非常相似的定性结果。使用实际参数范围进行的模拟表明,从一小部分受感染细胞开始,游离病毒传播和直接细胞间传播都会使病毒生长进入初始指数期,随后要么急剧下降,要么逐渐减少,最终导致培养物灭绝。在某些条件下,灭绝之前可能会出现振荡期。之前的一些体内HIV-1感染模型会出现振荡,但仅在不切实际的参数范围内。然而,实验性组织感染有时会显示出几个连续的振荡周期,所以我们的模型至少可以在定性上模拟它们。重要的是,这些模型表明感染性振荡可以用感染动态来解释;不需要生物异质性。这些模型还显示了受感染细胞与游离病毒之间的比例关系,这与关于几种病毒载量测量等效性的假设令人放心地一致,只是这种比例关系需要相对恒定的总细胞浓度。组织培养参数值可以通过精确、可控的实验来确定。因此,如果得到验证,我们的模型应该会使解释实验数据并将其外推到体内条件更加准确和可靠。