Analysis of cell division patterns in the Arabidopsis shoot apical meristem

The stereotypic pattern of cell shapes in the Arabidopsis shoot apical meristem (SAM) suggests that strict rules govern the placement of new walls during cell division. When a cell in the SAM divides, a new wall is built that connects existing walls and divides the cytoplasm of the daughter cells. Because features that are determined by the placement of new walls such as cell size, shape, and number of neighbors are highly regular, rules must exist for maintaining such order. Here we present a quantitative model of these rules that incorporates different observed features of cell division. Each feature is incorporated into a “potential function” that contributes a single term to a total analog of potential energy. New cell walls are predicted to occur at locations where the potential function is minimized. Quantitative terms that represent the well-known historical rules of plant cell division, such as those given by Hofmeister, Errera, and Sachs are developed and evaluated against observed cell divisions in the epidermal layer (L1) of Arabidopsis thaliana SAM. The method is general enough to allow additional terms for nongeometric properties such as internal concentration gradients and mechanical tensile forces

Computational morphodynamics of plants: integrating development over space and time

The emerging field of computational morphodynamics aims to understand the changes that occur in space and time during development by combining three technical strategies: live imaging to observe development as it happens; image processing and analysis to extract quantitative information; and computational modelling to express and test time-dependent hypotheses. The strength of the field comes from the iterative and combined use of these techniques, which has provided important insights into plant development

Computational Morphodynamics: A Modeling Framework to Understand Plant Growth

Computational morphodynamics utilizes computer modeling to understand the development of living organisms over space and time. Results from biological experiments are used to construct accurate and predictive models of growth. These models are then used to make novel predictions that provide further insight into the processes involved, which can be tested experimentally to either confirm or rule out the validity of the computational models. This review highlights two fundamental challenges: (a) to understand the feedback between mechanics of growth and chemical or molecular signaling, and (b) to design models that span and integrate single cell behavior with tissue development. We review different approaches to model plant growth and discuss a variety of model types that can be implemented to demonstrate how the interplay between computational modeling and experimentation can be used to explore the morphodynamics of plant development

Morphogenesis of the Arabidopsis Shoot Apical Meristem

Phyllotaxis patterns in plants, or the arrangement of leaves and flowers radially around the shoot, have fascinated both biologists and mathematicians for centuries. The current model of this process involves the lateral transport of the hormone auxin through the first layer of cells in the shoot apical meristem via the auxin efflux carrier protein PIN1. Locations around the meristem with high auxin concentration are sites of organ formation and differentiation. Many of the molecular players in this process are well known and characterized. Computer models composed of all these components are able to produce many of the observed phyllotaxis patterns. To understand which parts of this model have a large effect on the phenotype I automated parameter testing and tried many different parameter combinations. Results of this showed that cell size and meristem size should have the largest effect on phyllotaxis. This lead to three questions: (1) How is cell geometry regulated? (2) Does cell size affect auxin distribution? (3) Does meristem size affect phyllotaxis? To answer the first question I tracked cell divisions in live meristems and quantified the geometry of the cells and the division planes using advanced image processing techniques. The results show that cell shape is maintained by minimizing the length of the new wall and by minimizing the difference in area of the daughter cells. To answer the second question I observed auxin patterning in the meristem, shoot, leaves, and roots of Arabidopsis mutants with larger and smaller cell sizes. In the meristem and shoot, cell size plays an important role in determining the distribution of auxin. Observations of auxin in the root and leaves are less definitive. To answer the third question I measured meristem sizes and phyllotaxis patterns in mutants with altered meristem sizes. These results show that there is no correlation between meristem size and average divergence angle. But in an extreme case, making the meristem very small does lead to a switch on observed phyllotaxis in accordance with the model

Analysis of cell division patterns in the Arabidopsis shoot apical meristem.

The stereotypic pattern of cell shapes in the Arabidopsis shoot apical meristem (SAM) suggests that strict rules govern the placement of new walls during cell division. When a cell in the SAM divides, a new wall is built that connects existing walls and divides the cytoplasm of the daughter cells. Because features that are determined by the placement of new walls such as cell size, shape, and number of neighbors are highly regular, rules must exist for maintaining such order. Here we present a quantitative model of these rules that incorporates different observed features of cell division. Each feature is incorporated into a "potential function" that contributes a single term to a total analog of potential energy. New cell walls are predicted to occur at locations where the potential function is minimized. Quantitative terms that represent the well-known historical rules of plant cell division, such as those given by Hofmeister, Errera, and Sachs are developed and evaluated against observed cell divisions in the epidermal layer (L1) of Arabidopsis thaliana SAM. The method is general enough to allow additional terms for nongeometric properties such as internal concentration gradients and mechanical tensile forces

Mutually reinforcing patterning mechanisms: authors' reply

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Radiation-Hard Complementary Integrated Circuits Based on Semiconducting Single-Walled Carbon Nanotubes

Increasingly complex demonstrations of integrated circuit elements based on semiconducting single-walled carbon nanotubes (SWCNTs) mark the maturation of this technology for use in next-generation electronics. In particular, organic materials have recently been leveraged as dopant and encapsulation layers to enable stable SWCNT-based rail-to-rail, low-power complementary metal-oxide-semiconductor (CMOS) logic circuits. To explore the limits of this technology in extreme environments, here we study total ionizing dose (TID) effects in enhancement-mode SWCNT-CMOS inverters that employ organic doping and encapsulation layers. Details of the evolution of the device transport properties are revealed by <i>in situ</i> and <i>in operando</i> measurements, identifying <i>n</i>-type transistors as the more TID-sensitive component of the CMOS system with over an order of magnitude larger degradation of the static power dissipation. To further improve device stability, radiation-hardening approaches are explored, resulting in the observation that SWNCT-CMOS circuits are TID-hard under dynamic bias operation. Overall, this work reveals conditions under which SWCNTs can be employed for radiation-hard integrated circuits, thus presenting significant potential for next-generation satellite and space applications