Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, TN 37996.
Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996.
Mol Biol Cell. 2024 Dec 1;35(12):ar146. doi: 10.1091/mbc.E24-06-0248. Epub 2024 Oct 23.
The organization of cytoskeletal elements is pivotal for coordinating intracellular transport in eukaryotic cells. Several quantitative measures based on image analysis have been proposed to characterize morphometric features of fluorescently labeled actin networks. While helpful in detecting differences in actin organization between treatments or genotypes, the accuracy of these measures could not be rigorously assessed due to a lack of ground-truth data to which they could be compared. To overcome this limitation, we utilized coarse-grained computer simulations of actin filaments and cross-linkers to generate synthetic actin networks with varying levels of bundling. We converted the simulated networks into pseudofluorescence images similar to images obtained using confocal microscopy. Using both published and novel analysis procedures, we extracted a series of morphometric parameters and benchmarked them against analogous measures based on the ground-truth actin configurations. Our analysis revealed a set of parameters that reliably reports on actin network density, orientation, ordering, and bundling. Application of these morphometric parameters to root epidermal cells of revealed subtle changes in network organization between wild-type and mutant cells. This work provides robust measures that can be used to quantify features of actin networks and characterize changes in actin organization for different experimental conditions.
细胞骨架成分的组织对于协调真核细胞内的细胞内运输至关重要。已经提出了几种基于图像分析的定量测量方法来描述荧光标记肌动蛋白网络的形态特征。虽然这些测量方法有助于检测不同处理或基因型之间肌动蛋白组织的差异,但由于缺乏可与之比较的真实数据,因此无法严格评估这些测量方法的准确性。为了克服这一限制,我们利用肌动蛋白丝和交联剂的粗粒化计算机模拟来生成具有不同程度束集的合成肌动蛋白网络。我们将模拟网络转换为类似于使用共聚焦显微镜获得的伪荧光图像。使用已发表和新的分析程序,我们提取了一系列形态参数,并将其与基于真实肌动蛋白结构的类似测量进行了基准测试。我们的分析揭示了一组可靠地报告肌动蛋白网络密度、取向、有序性和束集的参数。将这些形态参数应用于揭示了野生型和突变型细胞之间网络组织的细微变化。这项工作提供了强大的测量方法,可以用于量化肌动蛋白网络的特征,并描述不同实验条件下肌动蛋白组织的变化。