Model-driven discovery of calcium-related protein-phosphatase inhibition in plant guard cell signaling

DIA-Based Phosphoproteomics Identifies Early Phosphorylation Events in Response to EGTA and Mannitol in Arabidopsis

Osmotic stress significantly hampers plant growth and crop yields, emphasizing the need for a thorough comprehension of the underlying molecular responses. Previous research has demonstrated that osmotic stress rapidly induces calcium influx and signaling, along with the activation of a specific subset of protein kinases, notably the Raf-like protein (RAF)-sucrose nonfermenting-1-related protein kinase 2 (SnRK2) kinase cascades within minutes. However, the intricate interplay between calcium signaling and the activation of RAF-SnRK2 kinase cascades remains elusive. Here, in this study, we discovered that Raf-like protein (RAF) kinases undergo hyperphosphorylation in response to osmotic shocks. Intriguingly, treatment with the calcium chelator EGTA robustly activates RAF-SnRK2 cascades, mirroring the effects of osmotic treatment. Utilizing high-throughput data-independent acquisition-based phosphoproteomics, we unveiled the global impact of EGTA on protein phosphorylation. Beyond the activation of RAFs and SnRK2s, EGTA treatment also activates mitogen-activated protein kinase cascades, Calcium-dependent protein kinases, and receptor-like protein kinases, etc. Through overlapping assays, we identified potential roles of mitogen-activated protein kinase kinase kinase kinases and receptor-like protein kinases in the osmotic stress-induced activation of RAF-SnRK2 cascades. Our findings illuminate the regulation of phosphorylation and cellular events by Ca2+ signaling, offering insights into the (exocellular) Ca2+ deprivation during early hyperosmolality sensing and signaling.

A network-based modeling framework reveals the core signal transduction network underlying high carbon dioxide-induced stomatal closure in guard cells

Stomata are pores on plant aerial surfaces, each bordered by a pair of guard cells. They control gas exchange vital for plant survival. Understanding how guard cells respond to environmental signals such as atmospheric carbon dioxide (CO2) levels is not only insightful to fundamental biology but also relevant to real-world issues of crop productivity under global climate change. In the past decade, multiple important signaling elements for stomatal closure induced by elevated CO2 have been identified. Yet, there is no comprehensive understanding of high CO2-induced stomatal closure. In this work, we assemble a cellular signaling network underlying high CO2-induced stomatal closure by integrating evidence from a comprehensive literature analysis. We further construct a Boolean dynamic model of the network, which allows in silico simulation of the stomatal closure response to high CO2 in wild-type Arabidopsis thaliana plants and in cases of pharmacological or genetic manipulation of network nodes. Our model has a 91% accuracy in capturing known experimental observations. We perform network-based logical analysis and reveal a feedback core of the network, which dictates cellular decisions in closure response to high CO2. Based on these analyses, we predict and experimentally confirm that applying nitric oxide (NO) induces stomatal closure in ambient CO2 and causes hypersensitivity to elevated CO2. Moreover, we predict a negative regulatory relationship between NO and the protein phosphatase ABI2 and find experimentally that NO inhibits ABI2 phosphatase activity. The experimental validation of these model predictions demonstrates the effectiveness of network-based modeling and highlights the decision-making role of the feedback core of the network in signal transduction. We further explore the model's potential in predicting targets of signaling elements not yet connected to the CO2 network. Our combination of network science, in silico model simulation, and experimental assays demonstrates an effective interdisciplinary approach to understanding system-level biology.

Quantitative System Modeling Bridges the Gap between Macro- and Microscopic Stomatal Model

An understanding of stomatal function is vital for the carbon and water cycle in nature. In the past decades, various stomatal models with different functions have been established to investigate and predict stomatal behavior and its association with plants' responses to the changing climate, but with limited biological information provided. On the other hand, many stomatal models at the molecular level focus on simulating and predicting molecular practices and ignore the dynamic quantitative information. As a result, stomatal models are often divided between the microscopic and macroscopic scales. Quantitative systems analysis offers an effective in silico approach to explore the link between microscopic gene function and macroscopic physiological traits. As a first step, a systems model, OnGuard, is developed for the investigation of guard cell ion homeostasis and its relevance to the dynamic stomatal movements. The system model has already yielded a series of important predictions to guide molecular physiological studies in stomata. It also exhibits great potential in breeding practice, which represents a key step toward "Breeding by design" of improving plant carbon-water use efficiency. Here, the development of stomatal models is reviewed, and the future perspectives on stomatal modeling for agricultural and ecological applications are discussed.

Inference of a Boolean Network From Causal Logic Implications

Biological systems contain a large number of molecules that have diverse interactions. A fruitful path to understanding these systems is to represent them with interaction networks, and then describe flow processes in the network with a dynamic model. Boolean modeling, the simplest discrete dynamic modeling framework for biological networks, has proven its value in recapitulating experimental results and making predictions. A first step and major roadblock to the widespread use of Boolean networks in biology is the laborious network inference and construction process. Here we present a streamlined network inference method that combines the discovery of a parsimonious network structure and the identification of Boolean functions that determine the dynamics of the system. This inference method is based on a causal logic analysis method that associates a logic type (sufficient or necessary) to node-pair relationships (whether promoting or inhibitory). We use the causal logic framework to assimilate indirect information obtained from perturbation experiments and infer relationships that have not yet been documented experimentally. We apply this inference method to a well-studied process of hormone signaling in plants, the signaling underlying abscisic acid (ABA)—induced stomatal closure. Applying the causal logic inference method significantly reduces the manual work typically required for network and Boolean model construction. The inferred model agrees with the manually curated model. We also test this method by re-inferring a network representing epithelial to mesenchymal transition based on a subset of the information that was initially used to construct the model. We find that the inference method performs well for various likely scenarios of inference input information. We conclude that our method is an effective approach toward inference of biological networks and can become an efficient step in the iterative process between experiments and computations.

Boolean modelling in plant biology

Signalling and genetic networks underlie most biological processes and are often complex, containing many highly connected components. Modelling these networks can provide insight into mechanisms but is challenging given that rate parameters are often not well defined. Boolean modelling, in which components can only take on a binary value with connections encoded by logic equations, is able to circumvent some of these challenges, and has emerged as a viable tool to probe these complex networks. In this review, we will give an overview of Boolean modelling, with a specific emphasis on its use in plant biology. We review how Boolean modelling can be used to describe biological networks and then discuss examples of its applications in plant genetics and plant signalling.

Boolink: a graphical interface for open access Boolean network simulations and use in guard cell CO2 signaling

Signaling networks are at the heart of almost all biological processes. Most of these networks contain large number of components, and often either the connections between these components are not known or the rate equations that govern the dynamics of soluble signaling components are not quantified. This uncertainty in network topology and parameters can make it challenging to formulate detailed mathematical models. Boolean networks, in which all components are either on or off, have emerged as viable alternatives to detailed mathematical models that contain rate constants and other parameters. Therefore, open-source platforms of Boolean models for community use are desirable. Here, we present Boolink, a freely available graphical user interface that allows users to easily construct and analyze existing Boolean networks. Boolink can be applied to any Boolean network. We demonstrate its application using a previously published network for abscisic acid (ABA)-driven stomatal closure in Arabidopsis spp. (Arabidopsis thaliana). We also show how Boolink can be used to generate testable predictions by extending the network to include CO2 regulation of stomatal movements. Predictions of the model were experimentally tested, and the model was iteratively modified based on experiments showing that ABA effectively closes Arabidopsis stomata at near-zero CO2 concentrations (1.5-ppm CO2). Thus, Boolink enables public generation and the use of existing Boolean models, including the prior developed ABA signaling model with added CO2 signaling components.

Deep dive into CO2-dependent molecular mechanisms driving stomatal responses in plants

Recent advances are revealing mechanisms mediating CO₂-regulated stomatal movements in Arabidopsis, stomatal architecture and stomatal movements in grasses, and the long-term impact of CO₂ on growth.

Removal of pentachlorophenol from contaminated wastewater using phytoremediation and bioaugmentation processes

The phytoremediation procedure was conducted by Lemna gibba (L) and Typha angustifolia (T) and the bioaugmentation procedure used P. putida HM627618. The ability of the selected P. putida HM627618 to tolerate and remove PCP (200 mg L^-1) was measured by high performance liquid chromatography analysis and optical density at 600 nm. Five different experiments were conducted in secondary treated wastewater for PCP testing removal (100 mg L^-1) including two phytoremediation assays (T + PCP; L + PCP), three bioaugmentation-phytoremediation assays (T + B + PCP; L + B + PCP; L + T + B + PCP) and a negative control assay with PCP. Various analytical parameters were determined in this study such as bacterial count, chlorophylls a and b, COD, pH and PCP content. The main results showed that the average PCP removal by P. putida HM627618 was around 87.5% after 7 days of incubation, and 88% of PCP removal was achieved by treatment (T + B) after 9 days. During these experiments, pH, COD and chloride content showed a net increase in all treatments. The chlorophylls a and b in case of (T) and (L) Chlorophylls a and b for T and L phytoremediation showed a decrease with a value less than 10 μg/mg of fresh material after 20 days of cultivation.

The Multifaceted Regulation of SnRK2 Kinases

SNF1-related kinases 2 (SnRK2s) are central regulators of plant responses to environmental cues simultaneously playing a pivotal role in the plant development and growth in favorable conditions. They are activated in response to osmotic stress and some of them also to abscisic acid (ABA), the latter being key in ABA signaling. The SnRK2s can be viewed as molecular switches between growth and stress response; therefore, their activity is tightly regulated; needed only for a short time to trigger the response, it has to be induced transiently and otherwise kept at a very low level. This implies a strict and multifaceted control of SnRK2s in plant cells. Despite emerging new information concerning the regulation of SnRK2s, especially those involved in ABA signaling, a lot remains to be uncovered, the regulation of SnRK2s in an ABA-independent manner being particularly understudied. Here, we present an overview of available data, discuss some controversial issues, and provide our perspective on SnRK2 regulation.

Metabolic engineering: Towards water deficiency adapted crop plants

Water deficiency caused by drought is one of the severe environmental conditions limiting plant growth, development, and yield. In this review article, we will summarize the changes in transcription, metabolism, and phytohormones under drought stress conditions and show the key transcription factors in these processes. We will also highlight the recent attempts to enhance stress tolerance without growth retardation and discuss the perspective on the development of stress adapted crops by engineering transcription factors.

Signaling mechanisms in abscisic acid-mediated stomatal closure

The plant hormone abscisic acid (ABA) plays a central role in the regulation of stomatal movements under water-deficit conditions. The identification of ABA receptors and the ABA signaling core consisting of PYR/PYL/RCAR ABA receptors, PP2C protein phosphatases and SnRK2 protein kinases has led to studies that have greatly advanced our knowledge of the molecular mechanisms mediating ABA-induced stomatal closure in the past decade. This review focuses on recent progress in illuminating the regulatory mechanisms of ABA signal transduction, and the physiological importance of basal ABA signaling in stomatal regulation by CO2 and, as hypothesized here, vapor-pressure deficit. Furthermore, advances in understanding the interactions of ABA and other stomatal signaling pathways are reviewed here. We also review recent studies investigating the use of ABA signaling mechanisms for the manipulation of stomatal conductance and the enhancement of drought tolerance and water-use efficiency of plants.

Context-specific network modeling identifies new crosstalk in β-adrenergic cardiac hypertrophy

Cardiac hypertrophy is a context-dependent phenomenon wherein a myriad of biochemical and biomechanical factors regulate myocardial growth through a complex large-scale signaling network. Although numerous studies have investigated hypertrophic signaling pathways, less is known about hypertrophy signaling as a whole network and how this network acts in a context-dependent manner. Here, we developed a systematic approach, CLASSED (Context-specific Logic-bASed Signaling nEtwork Development), to revise a large-scale signaling model based on context-specific data and identify main reactions and new crosstalks regulating context-specific response. CLASSED involves four sequential stages with an automated validation module as a core which builds a logic-based ODE model from the interaction graph and outputs the model validation percent. The context-specific model is developed by estimation of default parameters, classified qualitative validation, hybrid Morris-Sobol global sensitivity analysis, and discovery of missing context-dependent crosstalks. Applying this pipeline to our prior-knowledge hypertrophy network with context-specific data revealed key signaling reactions which distinctly regulate cell response to isoproterenol, phenylephrine, angiotensin II and stretch. Furthermore, with CLASSED we developed a context-specific model of β-adrenergic cardiac hypertrophy. The model predicted new crosstalks between calcium/calmodulin-dependent pathways and upstream signaling of Ras in the ISO-specific context. Experiments in cardiomyocytes validated the model’s predictions on the role of CaMKII-Gβγ and CaN-Gβγ interactions in mediating hypertrophic signals in ISO-specific context and revealed a difference in the phosphorylation magnitude and translocation of ERK1/2 between cardiac myocytes and fibroblasts. CLASSED is a systematic approach for developing context-specific large-scale signaling networks, yielding insights into new-found crosstalks in β-adrenergic cardiac hypertrophy.

Pathological cardiac hypertrophy is a disease in which the heart grows abnormally in response to different motivators such as high blood pressure or variations in hormones and growth factors. The shape of the heart after its growth depends on the context in which it grows. Since cell signaling in the cardiac cells plays a key role in the determination of heart shape, a thorough understanding of cardiac cells signaling in each context enlightens the mechanisms which control response of cardiac cells. However, cell signaling in cardiac hypertrophy comprises a complex web of pathways with numerous interactions, and predicting how these interactions control the hypertrophic signal in each context is not achievable by only experiments or general computational models. To address this need, we developed an approach to bring together the experimental data of each context with a signaling network curated from literature to identify the main players of cardiac cells response in each context and attain the context-specific models of cardiac hypertrophy. By utilizing our approach, we identified the main regulators of cardiac hypertrophy in four important contexts. We developed a network model of β-adrenergic cardiac hypertrophy, and predicted and validated new interactions that regulate cardiac cells response in this context.

A Guard Cell Abscisic Acid (ABA) Network Model That Captures the Stomatal Resting State

Stomatal pores play a central role in the control of carbon assimilation and plant water status. The guard cell pair that borders each pore integrates information from environmental and endogenous signals and accordingly swells or deflates, thereby increasing or decreasing the stomatal aperture. Prior research shows that there is a complex cellular network underlying this process. We have previously constructed a signal transduction network and a Boolean dynamic model describing stomatal closure in response to signals including the plant hormone abscisic acid (ABA), calcium or reactive oxygen species (ROS). Here, we improve the Boolean network model such that it captures the biologically expected response of the guard cell in the absence or following the removal of a closure-inducing signal such as ABA or external Ca2+. The expectation from the biological system is reversibility, i.e., the stomata should reopen after the closing signal is removed. We find that the model's reversibility is obstructed by the previously assumed persistent activity of four nodes. By introducing time-dependent Boolean functions for these nodes, the model recapitulates stomatal reopening following the removal of a signal. The previous version of the model predicts ∼20% closure in the absence of any signal due to uncertainty regarding the initial conditions of multiple network nodes. We systematically test and adjust these initial conditions to find the minimally restrictive combinations that appropriately result in open stomata in the absence of a closure signal. We support these results by an analysis of the successive stabilization of feedback motifs in the network, illuminating the system's dynamic progression toward the open or closed stomata state. This analysis particularly highlights the role of cytosolic calcium oscillations in causing and maintaining stomatal closure. Overall, we illustrate the strength of the Boolean network modeling framework to efficiently capture cellular phenotypes as emergent outcomes of intracellular biological processes.

The Winner Takes It All: Auxin-The Main Player during Plant Embryogenesis

In plants, the first asymmetrical division of a zygote leads to the formation of two cells with different developmental fates. The establishment of various patterns relies on spatial and temporal gene expression, however the precise mechanism responsible for embryonic patterning still needs elucidation. Auxin seems to be the main player which regulates embryo development and controls expression of various genes in a dose-dependent manner. Thus, local auxin maxima and minima which are provided by polar auxin transport underlie cell fate specification. Diverse auxin concentrations in various regions of an embryo would easily explain distinct cell identities, however the question about the mechanism of cellular patterning in cells exposed to similar auxin concentrations still remains open. Thus, specification of cell fate might result not only from the cell position within an embryo but also from events occurring before and during mitosis. This review presents the impact of auxin on the orientation of the cell division plane and discusses the mechanism of auxin-dependent cytoskeleton alignment. Furthermore, close attention is paid to auxin-induced calcium fluxes, which regulate the activity of MAPKs during postembryonic development and which possibly might also underlie cellular patterning during embryogenesis.