SUMMARYIntegrative studies of plant growth require spatially and temporally resolved information from high-throughput imaging systems. However, analysis and interpretation of conventional two-dimensional images is complicated by the three-dimensional nature of shoot architecture and by changes in leaf position over time, termed hyponasty. To solve this problem, Phytotyping 4D uses a light-field camera that simultaneously provides a focus image and a depth image, which contains distance information about the object surface. Our automated pipeline segments the focus images, integrates depth information to reconstruct the threedimensional architecture, and analyses time series to provide information about the relative expansion rate, the timing of leaf appearance, hyponastic movement, and shape for individual leaves and the whole rosette. Phytotyping 4D was calibrated and validated using discs of known sizes, and plants tilted at various orientations. Information from this analysis was integrated into the pipeline to allow error assessment during routine operation. To illustrate the utility of Phytotyping 4D, we compare diurnal changes in Arabidopsis thaliana wild-type Col-0 and the starchless pgm mutant. Compared to Col-0, pgm showed very low relative expansion rate in the second half of the night, a transiently increased relative expansion rate at the onset of light period, and smaller hyponastic movement including delayed movement after dusk, both at the level of the rosette and individual leaves. Our study introduces light-field camera systems as a tool to accurately measure morphological and growth-related features in plants.

We used Phytotyping 4D to investigate the contribution of clock and light signaling to the diurnal regulation of rosette expansion growth and leaf movement in Arabidopsis (Arabidopsis thaliana). Wild-type plants and clock mutants with a short (lhycca1) and long (prr7prr9) period were analyzed in a T24 cycle and in T-cycles that were closer to the mutants' period. Wild types also were analyzed in various photoperiods and after transfer to free-running light or darkness. Rosette expansion and leaf movement exhibited a circadian oscillation, with superimposed transients after dawn and dusk. Diurnal responses were modified in clock mutants. lhycca1 exhibited an inhibition of growth at the end of night and growth rose earlier after dawn, whereas prr7prr9 showed decreased growth for the first part of the light period. Some features were partly rescued by a matching T-cycle, like the inhibition in lhycca1 at the end of the night, indicating that it is due to premature exhaustion of starch. Other features were not rescued, revealing that the clock also regulates expansion growth more directly. Expansion growth was faster at night than in the daytime, whereas published work has shown that the synthesis of cellular components is faster in the day than at nighttime. This temporal uncoupling became larger in short photoperiods and may reflect the differing dependence of expansion and biosynthesis on energy, carbon, and water. While it has been proposed that leaf expansion and movement are causally linked, we did not observe a consistent temporal relationship between expansion and leaf movement.

SignificanceIn the crowded interior of a cell, diffusion alone is insufficient to master varying transport requirements for cell sustenance and growth. The dynamic actin cytoskeleton is an essential cellular component that provides transport and cytoplasmic streaming in plant cells, but little is known about its system-level organization. Here, we resolve key challenges in understanding system-level actin-based transport. We present an automated image-based, network-driven framework that accurately incorporates both actin cytoskeleton and organelle trafficking. We demonstrate that actin cytoskeleton network properties support efficient transport in both growing and elongated hypocotyl cells. We show that organelle transport can be predicted from the system-wide cellular organization of the actin cytoskeleton. Our framework can be readily applied to investigate cytoskeleton-based transport in other organisms.

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.