LobeFinder: A Convex Hull-Based Method for Quantitative Boundary Analyses of Lobed Plant Cells

Abstract

ORCID ID: 0000-0001-5462-524X (J.P.).Dicot leaves are composed of a heterogeneous mosaic of jigsaw puzzle piece-shaped pavement cells that vary greatly in size and the complexity of their shape. Given the importance of the epidermis and this particular cell type for leaf expansion, there is a strong need to understand how pavement cells morph from a simple polyhedral shape into highly lobed and interdigitated cells. At present, it is still unclear how and when the patterns of lobing are initiated in pavement cells, and one major technological bottleneck to addressing the problem is the lack of a robust and objective methodology to identify and track lobing events during the transition from simple cell geometry to lobed cells. We developed a convex hull-based algorithm termed LobeFinder to identify lobes, quantify geometric properties, and create a useful graphical output of cell coordinates for further analysis. The algorithm was validated against manually curated images of pavement cells of widely varying sizes and shapes. The ability to objectively count and detect new lobe initiation events provides an improved quantitative framework to analyze mutant phenotypes, detect symmetry-breaking events in time-lapse image data, and quantify the time-dependent correlation between cell shape change and intracellular factors that may play a role in the morphogenesis process.

Reassessing the Roles of PIN Proteins and Anticlinal Microtubules during Pavement Cell Morphogenesis

“…The geometric features of a cell segment that influence the probability that a new lobe will form are not known. There is evidence for a minimal lobe-spacing rule (Staff et al, 2012) and a weak correlation between the initial segment length and the probability of lobe formation (Wu et al, 2016). As expected, we found that lobes could form on segments with varying initial geometries; however, new lobes did not form within recently formed lobes.…”

“…The LobeFinder algorithm serves this purpose (Wu et al, 2016); however, it operates on closed geometric shapes. Using the findpeaks algorithm in Matlab on these segments, we found that lobes began as very small but persistent local deflections in the cell boundary that became progressively larger (Supplemental Fig.…”

“…1); 10 DAG is the terminal phenotype at which cotyledon expansion ceases (Qiu et al, 2002). We used the recently described LobeFinder algorithm to measure cell shape and count lobes because it eliminates the unavoidable variability in lobe number scoring among individuals (Wu et al, 2016).…”

“…Using time-lapse imaging, it was shown that lobe initiation is not a continuous iterative process during cell expansion. Instead, it occurs predominantly during a permissive phase of seedling development up to ;2 d after germination (DAG; Zhang et al, 2011;Armour et al, 2015;Wu et al, 2016). Subsequently, the pavement cells expand for days and increase in area largely independent of lobe initiation (Zhang et al, 2011;Armour et al, 2015;Wu et al, 2016).…”

“…Instead, it occurs predominantly during a permissive phase of seedling development up to ;2 d after germination (DAG; Zhang et al, 2011;Armour et al, 2015;Wu et al, 2016). Subsequently, the pavement cells expand for days and increase in area largely independent of lobe initiation (Zhang et al, 2011;Armour et al, 2015;Wu et al, 2016). In highly lobed pavement cells, anticlinal microtubules often are concentrated at the convex region of the cell (Wasteneys et al, 1997;Zhang et al, 2011), and this microtubule arrangement may reflect the ability of the microtubule network to maintain polarized lobe outgrowth and rearrange in response to local cell geometry and the predicted patterns of cell wall stress (Sampathkumar et al, 2014).…”