Quantitative analyses of the plant cytoskeleton reveal underlying organizational principles

Abstract

The actin and microtubule (MT) cytoskeletons are vital structures for cell growth and development across all species. While individual molecular mechanisms underpinning actin and MT dynamics have been intensively studied, principles that govern the cytoskeleton organization remain largely unexplored. Here, we captured biologically relevant characteristics of the plant cytoskeleton through a network-driven imaging-based approach allowing us to quantitatively assess dynamic features of the cytoskeleton. By introducing suitable null models, we demonstrate that the plant cytoskeletal networks exhibit properties required for efficient transport, namely, short average path lengths and high robustness. We further show that these advantageous features are maintained during temporal cytoskeletal rearrangements. Interestingly, man-made transportation networks exhibit similar properties, suggesting general laws of network organization supporting diverse transport processes. The proposed network-driven analysis can be readily used to identify organizational principles of cytoskeletons in other organisms.

2D Adaptive Grid-Based Image Analysis Approach for Biological Networks

“…A comparison of the degree assortativity of treated and untreated networks using our analysis approach AG-img2net shows a statistical reduction for cytoskeleton treated with Latrunculin B (independent twosample t-test = 0.05). Both findings agree with the results using img2net approach [4], [6] (independent two-sample ttest = 0.04 < 0.05, independent two-sample t-test = 0.01 < 0.05), respectively. Moreover, the treated networks show a significant reduction in average path lengths (APL) using AGimg2net and img2net approach (independent two-sample ttest = 0.001 < 0.05, independent two-sample t-test = 0.02 < 0.05), respectively.…”

“…First, we test whether the AG-img2net identifies biologically meaningful properties by analysing cytoskeleton images analysed before by img2net and presented in [4], [6]. To do this, we have followed the same validation procedure as in [6] by comparing 18 samples of cell cytoskeleton, including cells treated with Latrunculin B and untreated ones; the obtained results are presented in Figure 7.…”

“…Alternatively to the direct network reconstruction approaches, an indirect network reconstruction approach called the img2net was proposed by [4], [6]. The img2net reconstructs a network from 2D/3D image using a two-step procedure as shown in Figure 1.…”

“…In order to clearly show the effectiveness of the adaptive grid concept (AG-img2net), we have chosen different types of networks in order to reconstruct and quantify their topology, including synthetic networks and real networks such as cytoskeleton in plant cells used in img2net [4], [6] and keratin in skin cells.…”

“…Therefore, there is an increasing need to develop an image processing approach in conjunction with biologists, combining the collaborative knowledge of biology, computer science, mathematics, and other related disciplines in order to provide the most effective ways for quantification of complex biological networks. Such an approach can also be applied to other types of networks, such as neural networks or transportation systems [4].…”