Plasma membranes (PMs) act as primary cellular checkpoints for sensing signals and controlling solute transport. Membrane proteins communicate with intracellular processes through protein interaction ...networks. Deciphering these signaling networks provides crucial information for elucidating in vivo cellular regulation. Large-scale proteomics enables system-wide characterization of the membrane proteome, identification of ligand–receptor pairs, and elucidation of signals originating at membranes. In this review we assess recent progress in the development of mass spectrometry (MS)-based proteomic pipelines for determining membrane signaling pathways. We focus in particular on current techniques for the analysis of membrane protein phosphorylation and interaction, and how these proteins may be connected to downstream changes in gene expression, metabolism, and physiology.
Membrane receptors, kinases, and transporters communicate with intracellular processes through protein interaction networks. Characterization of plant PM proteins – especially hydrophobic proteins – remains challenging despite advances in separation and analysis techniques.Rapid advances in MS instrumentation and data analysis have enabled marked progress in deciphering the membrane proteome and mapping protein interaction partners, leading to a better understanding of PM protein complexes.Analysis of membrane protein phosphorylation under specific cellular conditions is crucial for elucidating the molecular mechanisms underlying signal sensing, transport, and metabolic processes. Phosphoproteomics allows unbiased localization and site-specific quantification of in vivo protein phosphorylation, thus facilitating the dissection of membrane signaling networks.
System theory has its roots in mathematical formalisms developed by mathematicians and physicists, such as Leibniz, Euler, and Newton, and applied by congenial chemists and biologists such as Lotka ...and Bertalanffy. In these approaches, the dynamical system—may it be either single organisms or populations of organisms in their ecosystems—is defined and formally translated into an interaction matrix and first-order ordinary differential equations (ODEs) which are then solved. This provides the background for the quantitative analysis of any linear to non-linear system. In his inspiring article “Can a biologist fix a radio?,” Lazebnik made the differences very clear between a “guilt by association” hypothesis of a modern biologist vs. a Signal–Input–Output (SIO) model of an electrical engineer. The drawback of this “Gedankenexperiment” is that two rather different approaches are compared—a forward model predictive control approach in the case of the SIO model by an engineer and an inverse or reverse approach by the biologist or ecologist. Biological and ecological systems are much too complex to estimate all the underlying ODE's, parameter and input signals that generate a probability distribution. Thus, the combination of inverse data-driven modeling and stochastic simulation is a key process for understanding the control of a biological or ecological system. The challenge of the next decades of systems biology is to link these approaches more systematically. Over the last years, we have developed a hybrid modeling approach based on the stochastic Lyapunov matrix equation for the analysis of genome-scale molecular data. This workflow connects forward and inverse strategies such as the genome-scale-based metabolic reconstruction of an organism and the calculation of dynamics around a quasi-steady state using statistical features of large-scale multiomics data. Ultimately, this workflow is linked to physiology and phenotype (the output) to unambiguously define the genotype–environment–phenotype relationship. This system-theoretical formalism establishes the generic analysis of the genotype–environment–phenotype relationship to finally result in predictability of organismal function in the environmental context. The approach is based on fundamental mathematical control theory for the analysis of dynamical systems using eigenvalues and matrix algebra, stochastic differential equations (SDEs), and Langevin- and Fokker–Planck-type equations eventually leading to the continuous stochastic Lyapunov matrix equation. The stochastic Lyapunov matrix equation is also a fundamental approach for the analysis and control of artificial intelligence systems in model predictive control and thus opens up completely new perspectives for the integration of systems engineering and systems biology. Furthermore, similar mathematical formalisms—using a community matrix instead of a stoichiometric matrix of a metabolic network—were also conceptually developed and applied by ecologists such as Levins and May in the analysis of stability and complexity of model ecosystems. Thus, the generalization of this hybrid forward–inverse approach spans from biology to ecology and promises to be a systematic iterative process that finally leads to functional units able to explain living systems up to their interaction in complex ecosystems.
Plants have evolved strategies to tightly regulate metabolism during acclimation to a changing environment. Low temperature significantly constrains distribution, growth and yield of many temperate ...plant species. Exposing plants to low but non-freezing temperature induces a multigenic processes termed cold acclimation, which eventually results in an increased freezing tolerance. Cold acclimation comprises reprogramming of the transcriptome, proteome and metabolome and affects communication and signaling between subcellular organelles. Carbohydrates play a central role in this metabolic reprogramming. This review summarizes current knowledge about the role of carbohydrate metabolism in plant cold acclimation with a focus on subcellular metabolic reprogramming, its thermodynamic constraints under low temperature and mathematical modelling of metabolism.
Since the dawn of space exploration, the survivability of terrestrial life in outer space conditions has attracted enormous attention. Space technology has enabled the development of advanced space ...exposure facilities to investigate in situ responses of microbial life to the stress conditions of space during interplanetary transfer. Significant progress has been made toward the understanding of the effects of space environmental factors, e.g., microgravity, vacuum and radiation, on microorganisms exposed to real and simulated space conditions. Of extreme importance is not only knowledge of survival potential of space-exposed microorganisms, but also the determination of mechanisms of survival and adaptation of predominant species to the extreme space environment, i.e., revealing the molecular machinery, which elicit microbial survivability and adaptation. Advanced technologies in -omics research have permitted genome-scale studies of molecular alterations of space-exposed microorganisms. A variety of reports show that microorganisms grown in the space environment exhibited global alterations in metabolic functions and gene expression at the transcriptional and translational levels. Proteomic, metabolomic and especially metabolic modeling approaches as essential instruments of space microbiology, synthetic biology and metabolic engineering are rather underrepresented. Here we summarized the molecular space-induced alterations of exposed microorganisms in terms of understanding the molecular mechanisms of microbial survival and adaptation to drastic outer space environment.
Sustaining energy homeostasis is of pivotal importance for all living organisms. In Arabidopsis thaliana, evolutionarily conserved SnRK1 kinases (Snf1-RELATED KINASE1) control metabolic adaptation ...during low energy stress. To unravel starvation-induced transcriptional mechanisms, we performed transcriptome studies of inducible knockdown lines and found that S1-basic leucine zipper transcription factors (S1-bZIPs) control a defined subset of genes downstream of SnRK1. For example, S1-bZIPs coordinate the expression of genes involved in branched-chain amino acid catabolism, which constitutes an alternative mitochondrial respiratory pathway that is crucial for plant survival during starvation. Molecular analyses defined S1-bZIPs as SnRK1-dependent regulators that directly control transcription via binding to G-box promoter elements. Moreover, SnRK1 triggers phosphorylation of group C-bZIPs and the formation of C/S1-heterodimers and, thus, the recruitment of SnRK1 directly to target promoters. Subsequently, the C/S1-bZIP-SnRK1 complex interacts with the histone acetylation machinery to remodel chromatin and facilitate transcription. Taken together, this work reveals molecular mechanisms underlying how energy deprivation is transduced to reprogram gene expression, leading to metabolic adaptation upon stress.
Sustainable crop production is the major challenge in the current global climate change scenario. Drought stress is one of the most critical abiotic factors which negatively impact crop productivity. ...In recent years, knowledge about molecular regulation has been generated to understand drought stress responses. For example, information obtained by transcriptome analysis has enhanced our knowledge and facilitated the identification of candidate genes which can be utilized for plant breeding. On the other hand, it becomes more and more evident that the translational and post-translational machinery plays a major role in stress adaptation, especially for immediate molecular processes during stress adaptation. Therefore, it is essential to measure protein levels and post-translational protein modifications to reveal information about stress inducible signal perception and transduction, translational activity and induced protein levels. This information cannot be revealed by genomic or transcriptomic analysis. Eventually, these processes will provide more direct insight into stress perception then genetic markers and might build a complementary basis for future marker-assisted selection of drought resistance. In this review, we survey the role of proteomic studies to illustrate their applications in crop stress adaptation analysis with respect to productivity. Cereal crops such as wheat, rice, maize, barley, sorghum and pearl millet are discussed in detail. We provide a comprehensive and comparative overview of all detected protein changes involved in drought stress in these crops and have summarized existing knowledge into a proposed scheme of drought response. Based on a recent proteome study of pearl millet under drought stress we compare our findings with wheat proteomes and another recent study which defined genetic marker in pearl millet.
Shifts in the duration and intensity of ambient temperature impair plant development and reproduction, particularly male gametogenesis. Stress exposure causes meiotic defects or premature spore ...abortion in male reproductive organs, leading to male sterility. However, little is known about the mechanisms underlying stress and male sterility. To elucidate these mechanisms, we imposed a moderate transient heat stress on maize (
) plants at the tetrad stage of pollen development. After completion of pollen development at optimal conditions, stress responses were assessed in mature pollen. Transient heat stress resulted in reduced starch content, decreased enzymatic activity, and reduced pollen germination, resulting in sterility. A transcriptomic comparison pointed toward misregulation of starch, lipid, and energy biosynthesis-related genes. Metabolomic studies showed an increase of Suc and its monosaccharide components, as well as a reduction in pyruvate. Lipidomic analysis showed increased levels of unsaturated fatty acids and decreased levels of saturated fatty acids. In contrast, the majority of genes involved in developmental processes such as those required for auxin and unfolded protein responses, signaling, and cell wall biosynthesis remained unaltered. It is noteworthy that changes in the regulation of transcriptional and metabolic pathway genes, as well as heat stress proteins, remained altered even though pollen could recover during further development at optimal conditions. In conclusion, our findings demonstrate that a short moderate heat stress during the highly susceptible tetrad stage strongly affects basic metabolic pathways and thus generates germination-defective pollen, ultimately leading to severe yield losses in maize.
Roots are sensors evolved to simultaneously respond to manifold signals, which allow the plant to survive. Root growth responses, including the modulation of directional root growth, were shown to be ...differently regulated when the root is exposed to a combination of exogenous stimuli compared to an individual stress trigger. Several studies pointed especially to the impact of the negative phototropic response of roots, which interferes with the adaptation of directional root growth upon additional gravitropic, halotropic or mechanical triggers. This review will provide a general overview of known cellular, molecular and signalling mechanisms involved in directional root growth regulation upon exogenous stimuli. Furthermore, we summarise recent experimental approaches to dissect which root growth responses are regulated upon which individual trigger. Finally, we provide a general overview of how to implement the knowledge gained to improve plant breeding.
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