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Organ sizes and shapes are highly reproducible, or robust, within a species and individuals. Arabidopsis thaliana sepals, which are the leaf-like organs that enclose flower buds, have consistent size and shape, indicating robust development. Cell growth is locally heterogeneous due to intrinsic and extrinsic noise. To achieve robust organ shape, fluctuations in cell growth must average to an even growth rate, which requires that fluctuations are uncorrelated or anticorrelated in time and space. Here, we live image and quantify the development of sepals with an increased or decreased number of cell divisions (lgo mutant and LGO overexpression, respectively), a mutant with altered cell growth variability (ftsh4), and double mutants combining these. Changes in the number of cell divisions do not change the overall growth pattern. By contrast, in ftsh4 mutants, cell growth accumulates in patches of over- and undergrowth owing to correlations that impair averaging, resulting in increased organ shape variability. Thus, we demonstrate in vivo that the number of cell divisions does not affect averaging of cell growth, preserving robust organ morphogenesis, whereas correlated growth fluctuations impair averaging. [ABSTRACT FROM AUTHOR]

Arabidopsis thaliana sepals are excellent models for analyzing growth of entire organs due to their relatively small size, which can be captured at a cellular resolution under a confocal microscope. To investigate how differential growth of connected cell layers generate unique organ morphologies, it is necessary to live-image deep into the tissue. However, imaging deep cell layers of the sepal (or plant tissues in general) is practically challenging. Image processing is also difficult due to the low signal-to-noise ratio of the deeper tissue layers, an issue mainly associated with live imaging datasets. Addressing some of these challenges, we provide an optimized methodology for live imaging sepals, and subsequent image processing. For live imaging early-stage sepals, we found that the use of a bright fluorescent membrane marker, coupled with increased laser intensity and an enhanced Z- resolution produces high-quality images suitable for downstream image processing. Our optimized parameters allowed us to image the bottommost cell layer of the sepal (inner epidermal layer) without compromising viability. We used a 'voxel removal' technique to visualize the inner epidermal layer in MorphoGraphX image processing software. We also describe the MorphoGraphX parameters for creating a 2.5D mesh surface for the inner epidermis. Our parameters allow for the segmentation and parent tracking of individual cells through multiple time points, despite the weak signal of the inner epidermal cells. While we have used sepals to illustrate our approach, the methodology will be useful for researchers intending to live-image and track growth of deeper cell layers in 2.5D for any plant tissue. [ABSTRACT FROM AUTHOR]

Living tissues display fluctuations--random spatial and temporal variations of tissue properties around their reference values--at multiple scales. It is believed that such fluctuations may enable tissues to sense their state or their size. Recent theoretical studies developed specific models of fluctuations in growing tissues and predicted that fluctuations of growth show long-range correlations. Here, we elaborated upon these predictions and we tested them using experimental data. We first introduced a minimal model for the fluctuations of any quantity that has some level of temporal persistence or memory, such as concentration of a molecule, local growth rate, or mechanical property. We found that long-range correlations are generic, applying to any such quantity, and that growth couples temporal and spatial fluctuations, through a mechanism that we call "fluctuation stretching"--growth enlarges the length scale of variation of this quantity. We then analyzed growth data from sepals of the model plant Arabidopsis and we quantified spatial and temporal fluctuations of cell growth using the previously developed cellular Fourier transform. Growth appears to have long-range correlations. Wecompared different genotypes and growth conditions: mutants with lower or higher response to mechanical stress have lower temporal correlations and longer-range spatial correlations than wild-type plants. Finally, we used theoretical predictions to merge experimental data from all conditions and developmental stages into a unifying curve, validating the notion that temporal and spatial fluctuations are coupled by growth. Altogether, our work reveals kinematic constraints on spatiotemporal fluctuations that have an impact on the robustness of morphogenesis. [ABSTRACT FROM AUTHOR]

Robustness is the invariant development of phenotype despite environmental changes and genetic perturbations. In the Arabidopsis flower bud, four sepals robustly initiate and grow to a constant size to enclose and protect the inner floral organs. We previously characterized the mutant development-related myb-like 1 (drmy1), where 3-5 sepals initiate variably and grow to different sizes, compromising their protective function. The molecular mechanism underlying this loss of robustness was unclear. Here, we show that drmy1 has reduced TARGET OF RAPAMYCIN (TOR) activity, ribosomal content, and translation. Translation reduction decreases the protein level of ARABIDOPSIS RESPONSE REGULATOR7 (ARR7) and ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEIN 6 (AHP6), two cytokinin-signaling inhibitors that are normally rapidly produced before sepal initiation. The resultant upregulation of cytokinin signaling disrupts robust auxin patterning and sepal initiation. Our work shows that the homeostasis of translation, a ubiquitous cellular process, is crucial for the robust spatiotemporal patterning of organogenesis., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

One of the fundamental questions in developmental biology is how a cell is specified to differentiate as a specialized cell type. Traditionally, plant cell types were defined based on their function, location, morphology, and lineage. Currently, in the age of single-cell biology, researchers typically attempt to assign plant cells to cell types by clustering them based on their transcriptomes. However, because cells are dynamic entities that progress through the cell cycle and respond to signals, the transcriptome also reflects the state of the cell at a particular moment in time, raising questions about how to define a cell type. We suggest that these complexities and dynamics of cell states are of interest and further consider the roles signaling, stochasticity, cell cycle, and mechanical forces play in plant cell fate specification. Once established, cell identity must also be maintained. With the wealth of single-cell data coming out, the field is poised to elucidate both the complexity and dynamics of cell states.

As in origami, morphogenesis in living systems heavily relies on tissue curving and folding through the interplay between biochemical and biomechanical cues. By contrast, certain organs maintain their flat posture over several days. Here, we identified a pathway that is required for the maintenance of organ flatness, taking the sepal, the outermost floral organ, in Arabidopsis as a model system. Through genetic, cellular, and mechanical approaches, our results demonstrate that the global gene expression regulator VERNALIZATION INDEPENDENCE 4 (VIP4) fine-tunes the mechanical properties of sepal cell walls and maintains balanced growth on both sides of the sepals, mainly by orchestrating the distribution pattern of AUXIN RESPONSE FACTOR 3 (ARF3). vip4 mutation results in softer cell walls and faster cell growth on the adaxial sepal side, which eventually cause sepals to bend outward. Downstream of VIP4, ARF3 works through modulating auxin to downregulate pectin methylesterase VANGUARD1, resulting in decreased cell wall stiffness. Thus, our work unravels a 3-component module that relates hormonal patterns to organ curvature and actively maintains sepal flatness during its growth., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Arabidopsis thaliana sepals are excellent models for analyzing growth of entire organs due to their relatively small size, which can be captured at a cellular resolution under a confocal microscope. To investigate how differential growth of connected cell layers generate unique organ morphologies, it is necessary to live-image deep into the tissue. However, imaging deep cell layers of the sepal (or plant tissues in general) is practically challenging. Image processing is also difficult due to the low signal-to-noise ratio of the deeper tissue layers, an issue mainly associated with live imaging datasets. Addressing some of these challenges, we provide an optimized methodology for live imaging sepals, and subsequent image processing. For live imaging early-stage sepals, we found that the use of a bright fluorescent membrane marker, coupled with increased laser intensity and an enhanced Z- resolution produces high-quality images suitable for downstream image processing. Our optimized parameters allowed us to image the bottommost cell layer of the sepal (inner epidermal layer) without compromising viability. We used a 'voxel removal' technique to visualize the inner epidermal layer in MorphoGraphX image processing software. We also describe the MorphoGraphX parameters for creating a 2.5D mesh surface for the inner epidermis. Our parameters allow for the segmentation and parent tracking of individual cells through multiple time points, despite the weak signal of the inner epidermal cells. While we have used sepals to illustrate our approach, the methodology will be useful for researchers intending to live-image and track growth of deeper cell layers in 2.5D for any plant tissue., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Singh Yadav and Roeder.)

Development is a self-organized process that builds on cells and their interactions. Cells are heterogeneous in gene expression, growth, and division; yet how development is robust despite such heterogeneity is a fascinating question. Here, we review recent progress on this topic, highlighting how developmental robustness is achieved through self-organization. We will first discuss sources of heterogeneity, including stochastic gene expression, heterogeneity in growth rate and direction, and heterogeneity in division rate and precision. We then discuss cellular mechanisms that buffer against such noise, including Paf1C- and miRNA-mediated denoising, spatiotemporal growth averaging and compensation, mechanisms to improve cell division precision, and coordination of growth rate and developmental timing between different parts of an organ. We also discuss cases where such heterogeneity is not buffered but utilized for development. Finally, we highlight potential directions for future studies of noise and developmental robustness., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Robustness is the reproducible development of a phenotype despite stochastic noise. It often involves tradeoffs with other performance metrics, but the mechanisms underlying such tradeoffs were largely unknown. An Arabidopsis flower robustly develops four sepals from four precisely positioned auxin maxima. The development related myb-like 1 ( drmy1) mutant generates noise in auxin signaling that disrupts robustness in sepal initiation. Here, we found that increased expression of CUP-SHAPED COTYLEDON1 ( CUC1 ), a boundary specification transcription factor, in drmy1 underlies this loss of robustness. CUC1 surrounds and amplifies stochastic auxin noise in drmy1 to form variably positioned auxin maxima and sepal primordia. Removing CUC1 from drmy1 provides time for noisy auxin signaling to resolve into four precisely positioned auxin maxima, restoring robust sepal initiation. However, removing CUC1 decreases auxin maxima intensity and slows down sepal initiation. Thus, CUC1 increases morphogenesis speed but impairs robustness against auxin noise. Further, using a computational model, we found that the observed phenotype can be explained by the effect of CUC1 in repolarizing PIN FORMED1 (PIN1), a polar auxin transporter. Lastly, our model predicts that reducing global growth rate improves developmental robustness, which we validated experimentally. Thus, our study illustrates a tradeoff between speed and robustness during development., Competing Interests: COMPETING INTERESTS The authors declare no competing interests.