Combined computational modeling and experimental analysis integrating chemical and mechanical signals suggests possible mechanism of shoot meristem maintenance

Heterogeneous identity, stiffness and growth characterise the shoot apex of Arabidopsis stem cell mutants

Stem cell homeostasis in the shoot apical meristem involves a core regulatory feedback loop between the signalling peptide CLAVATA3 (CLV3), produced in stem cells, and the transcription factor WUSCHEL, expressed in the underlying organising centre. clv3 mutant meristems display massive overgrowth, which is thought to be caused by stem cell overproliferation, although it is unknown how uncontrolled stem cell divisions lead to this altered morphology. Here, we reveal local buckling defects in mutant meristems, and use analytical models to show how mechanical properties and growth rates may contribute to the phenotype. Indeed, clv3 mutant meristems are mechanically more heterogeneous than the wild type, and also display regional growth heterogeneities. Furthermore, stereotypical wild-type meristem organisation, in which cells simultaneously express distinct fate markers, is lost in mutants. Finally, cells in mutant meristems are auxin responsive, suggesting that they are functionally distinguishable from wild-type stem cells. Thus, all benchmarks show that clv3 mutant meristem cells are different from wild-type stem cells, suggesting that overgrowth is caused by the disruption of a more complex regulatory framework that maintains distinct genetic and functional domains in the meristem.

Reverse engineering morphogenesis through Bayesian optimization of physics-based models

Morphogenetic programs coordinate cell signaling and mechanical interactions to shape organs. In systems and synthetic biology, a key challenge is determining optimal cellular interactions for predicting organ shape, size, and function. Physics-based models defining the subcellular force distribution facilitate this, but it is challenging to calibrate parameters in these models from data. To solve this inverse problem, we created a Bayesian optimization framework to determine the optimal cellular force distribution such that the predicted organ shapes match the experimentally observed organ shapes. This integrative framework employs Gaussian Process Regression, a non-parametric kernel-based probabilistic machine learning modeling paradigm, to learn the mapping functions relating to the morphogenetic programs that maintain the final organ shape. We calibrated and tested the method on Drosophila wing imaginal discs to study mechanisms that regulate epithelial processes ranging from development to cancer. The parameter estimation framework successfully infers the underlying changes in core parameters needed to match simulation data with imaging data of wing discs perturbed with collagenase. The computational pipeline identifies distinct parameter sets mimicking wild-type shapes. It enables a global sensitivity analysis to support the regulation of actomyosin contractility and basal ECM stiffness to generate and maintain the curved shape of the wing imaginal disc. The optimization framework, combined with experimental imaging, identified that Piezo, a mechanosensitive ion channel, impacts fold formation by regulating the apical-basal balance of actomyosin contractility and elasticity of ECM. This workflow is extensible toward reverse-engineering morphogenesis across organ systems and for real-time control of complex multicellular systems.

Cultivating potential: Harnessing plant stem cells for agricultural crop improvement

Meristems are stem cell-containing structures that produce all plant organs and are therefore important targets for crop improvement. Developmental regulators control the balance and rate of cell divisions within the meristem. Altering these regulators impacts meristem architecture and, as a consequence, plant form. In this review, we discuss genes involved in regulating the shoot apical meristem, inflorescence meristem, axillary meristem, root apical meristem, and vascular cambium in plants. We highlight several examples showing how crop breeders have manipulated developmental regulators to modify meristem growth and alter crop traits such as inflorescence size and branching patterns. Plant transformation techniques are another innovation related to plant meristem research because they make crop genome engineering possible. We discuss recent advances on plant transformation made possible by studying genes controlling meristem development. Finally, we conclude with discussions about how meristem research can contribute to crop improvement in the coming decades.

Stem Cells: Engines of Plant Growth and Development

The development of both animals and plants relies on populations of pluripotent stem cells that provide the cellular raw materials for organ and tissue formation. Plant stem cell reservoirs are housed at the shoot and root tips in structures called meristems, with the shoot apical meristem (SAM) continuously producing aerial leaf, stem, and flower organs throughout the life cycle. Thus, the SAM acts as the engine of plant development and has unique structural and molecular features that allow it to balance self-renewal with differentiation and act as a constant source of new cells for organogenesis while simultaneously maintaining a stem cell reservoir for future organ formation. Studies have identified key roles for intercellular regulatory networks that establish and maintain meristem activity, including the KNOX transcription factor pathway and the CLV-WUS stem cell feedback loop. In addition, the plant hormones cytokinin and auxin act through their downstream signaling pathways in the SAM to integrate stem cell activity and organ initiation. This review discusses how the various regulatory pathways collectively orchestrate SAM function and touches on how their manipulation can alter stem cell activity to improve crop yield.

Computer models of cell polarity establishment in plants

Plant development is a complex task, and many processes involve changes in the asymmetric subcellular distribution of cell components that strongly depend on cell polarity. Cell polarity regulates anisotropic growth and polar localization of membrane proteins and helps to identify the cell's position relative to its neighbors within an organ. Cell polarity is critical in a variety of plant developmental processes, including embryogenesis, cell division, and response to external stimuli. The most conspicuous downstream effect of cell polarity is the polar transport of the phytohormone auxin, which is the only known hormone transported in a polar fashion in and out of cells by specialized exporters and importers. The biological processes behind the establishment of cell polarity are still unknown, and researchers have proposed several models that have been tested using computer simulations. The evolution of computer models has progressed in tandem with scientific discoveries, which have highlighted the importance of genetic, chemical, and mechanical input in determining cell polarity and regulating polarity-dependent processes such as anisotropic growth, protein subcellular localization, and the development of organ shapes. The purpose of this review is to provide a comprehensive overview of the current understanding of computer models of cell polarity establishment in plants, focusing on the molecular and cellular mechanisms, the proteins involved, and the current state of the field.

Reverse engineering morphogenesis through Bayesian optimization of physics-based models

Morphogenetic programs direct the cell signaling and nonlinear mechanical interactions between multiple cell types and tissue layers to define organ shape and size. A key challenge for systems and synthetic biology is determining optimal combinations of intra- and inter-cellular interactions to predict an organ's shape, size, and function. Physics-based mechanistic models that define the subcellular force distribution facilitate this, but it is extremely challenging to calibrate parameters in these models from data. To solve this inverse problem, we created a Bayesian optimization framework to determine the optimal cellular force distribution such that the predicted organ shapes match the desired organ shapes observed within the experimental imaging data. This integrative framework employs Gaussian Process Regression (GPR), a non-parametric kernel-based probabilistic machine learning modeling paradigm, to learn the mapping functions relating to the morphogenetic programs that generate and maintain the final organ shape. We calibrated and tested the method on cross-sections of Drosophila wing imaginal discs, a highly informative model organ system, to study mechanisms that regulate epithelial processes that range from development to cancer. As a specific test case, the parameter estimation framework successfully infers the underlying changes in core parameters needed to match simulation data with time series imaging data of wing discs perturbed with collagenase. Unexpectedly, the framework also identifies multiple distinct parameter sets that generate shapes similar to wild-type organ shapes. This platform enables an efficient, global sensitivity analysis to support the necessity of both actomyosin contractility and basal ECM stiffness to generate and maintain the curved shape of the wing imaginal disc. The optimization framework, combined with fixed tissue imaging, identified that Piezo, a mechanosensitive ion channel, impacts fold formation by regulating the apical-basal balance of actomyosin contractility and elasticity of ECM. This framework is extensible toward reverse-engineering the morphogenesis of any organ system and can be utilized in real-time control of complex multicellular systems.