Santa Fe Institute, Santa Fe, NM, 87505, USA.
Department of Integrative Biology, The University of Texas at Austin, Austin, TX, 78712, USA.
Sci Rep. 2021 May 5;11(1):9622. doi: 10.1038/s41598-021-87694-x.
Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model's mechanistic parameters provide estimates of several aspects associated with the virus's intracellular dynamics. We examine distributions of parameter estimates and assess their variability to gain insight into the root causes of variability in viral growth dynamics. We also fit our model to experiments performed under various drug treatments and examine which parameters differ under these conditions. We find that parameters associated with translation and early stage viral replication processes are essential for the model to capture experimentally observed dynamics. In aggregate, our results suggest that differences in viral growth data generated under different treatments can largely be captured by steps that occur early in the replication process.
病毒在感染过程中经历选择压力，以最大限度地增加其产生的存活后代数量，从而对事件的时间和顺序进行选择。此外，它们可能会遇到细胞环境的可变性，因为单个真核细胞在细胞间的基因表达可能会有所不同。这导致了病毒必须面对的动态表型景观，以进行复制。为了研究病毒在面对这种可变景观时表现出的复制动态，我们开发了一种方法，将病毒感染的随机机制模型拟合到高通量单细胞脊髓灰质炎病毒感染实验的延时成像数据中。该模型的机制参数提供了与病毒细胞内动力学相关的几个方面的估计。我们检查参数估计的分布，并评估它们的可变性，以深入了解病毒生长动态变化的根本原因。我们还将我们的模型拟合到在不同药物处理下进行的实验中，并检查在这些条件下哪些参数不同。我们发现，与翻译和早期病毒复制过程相关的参数对于模型捕捉实验观察到的动力学至关重要。总的来说，我们的结果表明，在不同处理下生成的病毒生长数据的差异可以主要通过复制过程早期发生的步骤来捕获。
