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时空分辨病毒复制动力学的表面扩散参数的有效估计

Efficient Estimates of Surface Diffusion Parameters for Spatio-Temporally Resolved Virus Replication Dynamics.

作者信息

Knodel Markus M, Wittum Gabriel, Vollmer Jürgen

机构信息

Simulation in Technology, TechSim, 75248 Ölbronn-Dürrn, Germany.

Modelling and Simulation (MaS), Computer, Electrical and Mathematical Science and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.

出版信息

Int J Mol Sci. 2024 Mar 5;25(5):2993. doi: 10.3390/ijms25052993.

DOI:10.3390/ijms25052993
PMID:38474240
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10932359/
Abstract

Advanced methods of treatment are needed to fight the threats of virus-transmitted diseases and pandemics. Often, they are based on an improved biophysical understanding of virus replication strategies and processes in their host cells. For instance, an essential component of the replication of the hepatitis C virus (HCV) proceeds under the influence of nonstructural HCV proteins (NSPs) that are anchored to the endoplasmatic reticulum (ER), such as the NS5A protein. The diffusion of NSPs has been studied by in vitro fluorescence recovery after photobleaching (FRAP) experiments. The diffusive evolution of the concentration field of NSPs on the ER can be described by means of surface partial differential equations (sufPDEs). Previous work estimated the diffusion coefficient of the NS5A protein by minimizing the discrepancy between an extended set of sufPDE simulations and experimental FRAP time-series data. Here, we provide a scaling analysis of the sufPDEs that describe the diffusive evolution of the concentration field of NSPs on the ER. This analysis provides an estimate of the diffusion coefficient that is based only on the ratio of the membrane surface area in the FRAP region to its contour length. The quality of this estimate is explored by a comparison to numerical solutions of the sufPDE for a flat geometry and for ten different 3D embedded 2D ER grids that are derived from fluorescence z-stack data of the ER. Finally, we apply the new data analysis to the experimental FRAP time-series data analyzed in our previous paper, and we discuss the opportunities of the new approach.

摘要

需要先进的治疗方法来应对病毒传播疾病和大流行的威胁。通常，这些方法基于对病毒在宿主细胞中的复制策略和过程有更深入的生物物理理解。例如，丙型肝炎病毒（HCV）复制的一个关键组成部分是在内质网（ER）上锚定的非结构HCV蛋白（NSPs）的影响下进行的，比如NS5A蛋白。NSPs的扩散已通过光漂白后荧光恢复（FRAP）体外实验进行了研究。NSPs在ER上浓度场的扩散演化可以用表面偏微分方程（sufPDEs）来描述。先前的工作通过最小化一组扩展的sufPDE模拟与实验FRAP时间序列数据之间的差异来估计NS5A蛋白的扩散系数。在这里，我们对描述NSPs在ER上浓度场扩散演化的sufPDEs进行了标度分析。该分析仅基于FRAP区域中膜表面积与其轮廓长度的比值来估计扩散系数。通过与平面几何形状以及从ER的荧光z-stack数据导出的十个不同的3D嵌入式2D ER网格的sufPDE数值解进行比较，探讨了该估计的质量。最后，我们将新的数据分析应用于我们先前论文中分析的实验FRAP时间序列数据，并讨论了新方法的机遇。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61e4/10932359/04a5c715e3ca/ijms-25-02993-g008.jpg
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