Quantitative Phosphoproteomic and System-Level Analysis of TOR Inhibition Unravel Distinct Organellar Acclimation in Chlamydomonas reinhardtii

Rapamycin is an inhibitor of the evolutionary conserved Target of Rapamycin (TOR) kinase which promotes and coordinates translation with cell growth and division. In heterotrophic organisms, TOR regulation is based on intra- and extracellular stimuli such as amino acids level and insulin perception. However, how plant TOR pathways have evolved to integrate plastid endosymbiosis is a remaining question. Despite the close association of the TOR signaling with the coordination between protein turn-over and growth, proteome and phosphoproteome acclimation to a rapamycin treatment have not yet been thoroughly investigated in Chlamydomonas reinhardtii. In this study, we have used in vivo label-free phospho-proteomic analysis to profile both protein and phosphorylation changes at 0, 24, and 48 h in Chlamydomonas cells treated with rapamycin. Using multivariate statistics we highlight the impact of TOR inhibition on both the proteome and the phosphoproteome. Two-way ANOVA distinguished differential levels of proteins and phosphoproteins in response either to culture duration and rapamycin treatment or combined effects. Finally, protein–protein interaction networks and functional enrichment analysis underlined the relation between plastid and mitochondrial metabolism. Prominent changes of proteins involved in sulfur, cysteine, and methionine as well as nucleotide metabolism on the one hand, and changes in the TCA cycle on the other highlight the interplay of chloroplast and mitochondria metabolism. Furthermore, TOR inhibition revealed changes in the endomembrane trafficking system. Phosphoproteomics data, on the other hand, highlighted specific differentially regulated phosphorylation sites for calcium-regulated protein kinases as well as ATG7, S6K, and PP2C. To conclude we provide a first combined Chlamydomonas proteomics and phosphoproteomics dataset in response to TOR inhibition, which will support further investigations.© 2018 Roustan and Weckwert

Cereal Crop Proteomics: Systemic Analysis of Crop Drought Stress Responses Towards Marker-Assisted Selection Breeding

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.© 2017 Ghatak, Chaturvedi and Weckwert

A Benchtop Fractionation Procedure for Subcellular Analysis of the Plant Metabolome

Although compartmentation is a key feature of eukaryotic cells, biological research is frequently limited by methods allowing for the comprehensive subcellular resolution of the metabolome. It has been widely accepted that such a resolution would be necessary in order to approximate cellular biochemistry and metabolic regulation, yet technical challenges still limit both the reproducible subcellular fractionation and the sample throughput being necessary for a statistically robust analysis. Here, we present a method and a detailed protocol which is based on the non-aqueous fractionation technique enabling the assignment of metabolites to their subcellular localization. The presented benchtop method aims at unraveling subcellular metabolome dynamics in a precise and statistically robust manner using a relatively small amount of tissue material. The method is based on the separation of cellular fractions via density gradients consisting of organic, non-aqueous solvents. By determining the relative distribution of compartment-specific marker enzymes together with metabolite profiles over the density gradient it is possible to estimate compartment-specific metabolite concentrations by correlation. To support this correlation analysis, a spreadsheet is provided executing a calculation algorithm to determine the distribution of metabolites over subcellular compartments. The calculation algorithm performs correlation of marker enzyme activity and metabolite abundance accounting for technical errors, reproducibility and the resulting error propagation. The method was developed, tested and validated in three natural accessions of Arabidopsis thaliana showing different ability to acclimate to low temperature. Particularly, amino acids were strongly shuffled between subcellular compartments in a cold-sensitive accession while a cold-tolerant accession was characterized by a stable subcellular metabolic homeostasis. Finally, we conclude that subcellular metabolome analysis is essential to unambiguously unravel regulatory strategies being involved in plant-environment interactions

Comparative analysis of phytohormone-responsive phosphoproteins in Arabidopsis thaliana using TiO2-phosphopeptide enrichment and mass accuracy precursor alignment

P>Protein phosphorylation/dephosphorylation is a central post-translational modification in plant hormone signaling, but little is known about its extent and function. Although pertinent protein kinases and phosphatases have been predicted and identified for a variety of hormone responses, classical biochemical approaches have so far revealed only a few candidate proteins and even fewer phosphorylation sites. Here we performed a global quantitative analysis of the Arabidopsis phosphoproteome in response to a time course of treatments with various plant hormones using phosphopeptide enrichment and subsequent mass accuracy precursor alignment (MAPA). The use of three time points, 1, 3 and 6 h, in combination with five phytohormone treatments, abscisic acid (ABA), indole-3-acetic acid (IAA), gibberellic acid (GA), jasmonic acid (JA) and kinetin, resulted in 324 000 precursor ions from 54 LC-Orbitrap-MS analyses quantified and aligned in a data matrix with the dimension of 6000 x 54 using the ProtMax algorithm. To dissect the phytohormone responses, multivariate principal/independent components analysis was performed. In total, 152 phosphopeptides were identified as differentially regulated; these phosphopeptides are involved in a wide variety of signaling pathways. New phosphorylation sites were identified for ABA response element binding factors that showed a specific increase in response to ABA. New phosphorylation sites were also found for RLKs and auxin transporters. We found that different hormones regulate distinct amino acid residues of members of the same protein families. In contrast, tyrosine phosphorylation of the G alpha subunit appeared to be a common response for multiple hormones, demonstrating global cross-talk among hormone signaling pathways

System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism

Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism.© 2017 Wang, Sun, Weiszmann and Weckwert

Integrative molecular profiling indicates a central role of transitory starch breakdown in establishing a stable C/N homeostasis during cold acclimation in two natural accessions of Arabidopsis thaliana

Background: The variation of growth and cold tolerance of two natural Arabidopsis accessions, Cvi (cold sensitive) and Rschew (cold tolerant), was analysed on a proteomic, phosphoproteomic and metabolomic level to derive characteristic information about genotypically distinct strategies of metabolic reprogramming and growth maintenance during cold acclimation. Results: Growth regulation before and after a cold acclimation period was monitored by recording fresh weight of leaf rosettes. Significant differences in the shoot fresh weight of Cvi and Rschew were detected both before and after acclimation to low temperature. During cold acclimation, starch levels were found to accumulate to a significantly higher level in Cvi compared to Rschew. Concomitantly, statistical analysis revealed a cold-induced decrease of beta-amylase 3 (BAM3; AT4G17090) in Cvi but not in Rschew. Further, only in Rschew we observed an increase of the protein level of the debranching enzyme isoamylase 3 (ISA3; AT4G09020). Additionally, the cold response of both accessions was observed to severely affect ribosomal complexes, but only Rschew showed a pronounced accumulation of carbon and nitrogen compounds. The abundance of the Cold Regulated (COR) protein COR78 (AT5G52310) as well as its phosphorylation was observed to be positively correlated with the acclimation state of both accessions. In addition, transcription factors being involved in growth and developmental regulation were found to characteristically separate the cold sensitive from the cold tolerant accession. Predicted protein-protein interaction networks (PPIN) of significantly changed proteins during cold acclimation allowed for a differentiation between both accessions. The PPIN revealed the central role of carbon/nitrogen allocation and ribosomal complex formation to establish a new cold-induced metabolic homeostasis as also observed on the level of the metabolome and proteome. Conclusion: Our results provide evidence for a comprehensive multi-functional molecular interaction network orchestrating growth regulation and cold acclimation in two natural accessions of Arabidopsis thaliana. The differential abundance of beta-amylase 3 and isoamylase 3 indicates a central role of transitory starch degradation in the coordination of growth regulation and the development of stress tolerance. Finally, our study indicates naturally occurring differential patterns of C/N balance and protein synthesis during cold acclimation

Quantitative in vivo phosphoproteomics reveals reversible signaling processes during nitrogen starvation and recovery in the biofuel model organism Chlamydomonas reinhardtii

Background: Nitrogen deprivation and replenishment induces massive changes at the physiological and molecular level in the green alga Chlamydomonas reinhardtii, including reversible starch and lipid accumulation. Stress signal perception and acclimation involves transient protein phosphorylation. This study aims to provide the first experimental phosphoprotein dataset for the adaptation of C. reinhardtii during nitrogen depletion and recovery growth phases and its impact on lipid accumulation. Results: To decipher the signaling pathways involved in this dynamic process, we applied a label-free in vivo shotgun phosphoproteomics analysis on nitrogen-depleted and recovered samples. 1227 phosphopeptides belonging to 732 phosphoproteins were identified and quantified. 470 phosphopeptides showed a significant change across the experimental set-up. Multivariate statistics revealed the reversible phosphorylation process and the time/condition-dependent dynamic rearrangement of the phosphoproteome. Protein–protein interaction analysis of differentially regulated phosphoproteins identified protein kinases and phosphatases, such as DYRKP and an AtGRIK1 orthologue, called CDPKK2, as central players in the coordination of translational, photosynthetic, proteomic and metabolomic activity. Phosphorylation of RPS6, ATG13, and NNK1 proteins points toward a specific regulation of the TOR pathway under nitrogen deprivation. Differential phosphorylation pattern of several eukaryotic initiation factor proteins (EIF) suggests a major control on protein translation and turnover. Conclusion: This work provides the first phosphoproteomics dataset obtained for Chlamydomonas responses to nitrogen availability, revealing multifactorial signaling pathways and their regulatory function for biofuel production. The reproducibility of the experimental set-up allows direct comparison with proteomics and metabolomics datasets and refines therefore the current model of Chlamydomonas acclimation to various nitrogen levels. Integration of physiological, proteomics, metabolomics, and phosphoproteomics data reveals three phases of acclimation to N availability: (i) a rapid response triggering starch accumulation as well as energy metabolism while chloroplast structure is conserved followed by (ii) chloroplast degradation combined with cell autophagy and lipid accumulation and finally (iii) chloroplast regeneration and cell growth activation after nitrogen replenishment. Plastid development seems to be further interconnected with primary metabolism and energy stress signaling in order to coordinate cellular mechanism to nitrogen availability stress.© The Author(s) 201

System-level network analysis of nitrogen starvation and recovery in Chlamydomonas reinhardtii reveals potential new targets for increased lipid accumulation

Background: Nitrogen starvation is known to cause drastic alterations in physiology and metabolism leading to the accumulation of lipid bodies in many microalgae, and it thus presents an important alternative for biofuel production. However, despite the importance of this process, the molecular mechanisms that mediate the metabolic remodeling induced by N starvation and especially by stress recovery are still poorly understood, and new candidates for bioengineering are needed to make this process useful for biofuel production. Results: We have studied the molecular changes involved in the adaptive mechanisms to N starvation and full recovery of the vegetative cells in the microalga Chlamydomonas reinhardtii during a four-day time course. High throughput mass spectrometry was employed to integrate the proteome and the metabolome with physiological changes. N starvation led to an accumulation of oil bodies and reduced Fv/Fm.. Distinct enzymes potentially participating in the carbon-concentrating mechanism (CAH7, CAH8, PEPC1) are strongly accumulated. The membrane composition is changed, as indicated by quantitative lipid profiles. A reprogramming of protein biosynthesis was observed by increased levels of cytosolic ribosomes, while chloroplastidic were dramatically reduced. Readdition of N led to, the identification of early responsive proteins mediating stress recovery, indicating their key role in regaining and sustaining normal vegetative growth. Analysis of the data with multivariate correlation analysis, Granger causality, and sparse partial least square (sPLS) provided a functional network perspective of the molecular processes. Cell growth and N metabolism were clearly linked by the branched chain amino acids, suggesting an important role in this stress. Lipid accumulation was also tightly correlated to the COP II protein, involved in vesicle and lysosome coating, and a major lipid droplet protein. This protein, together with other key proteins mediating signal transduction and adaption (BRI1, snRKs), constitute a series of new metabolic and regulatory targets. Conclusions: This work not only provides new insights and corrects previous models by analyzing a complex dataset, but also increases our biochemical understanding of the adaptive mechanisms to N starvation in Chlamydomonas, pointing to new bioengineering targets for increased lipid accumulation, a key step for a sustainable and profitable microalgae-based biofuel production

Toward a Unification of System-Theoretical Principles in Biology and Ecology—The Stochastic Lyapunov Matrix Equation and Its Inverse Application

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.© 2019 Weckwert

Antioxidant Properties and the Formation of Iron Coordination Complexes of 8-Hydroxyquinoline

Background: The alkaloid 8-hydroxyquinoline (8HQ) is well-known for various biological activities, including antioxidant effects and especially for the formation of coordination complexes with various transition metals, such as iron, amongst others. Therefore, 8HQ was extensively explored as a promising antineurodegenerative agent. However, other authors noted pro-oxidant effects of 8HQ. Here, we explore the pro- and antioxidant properties of 8HQ, especially in context of coordination complexes with iron (II) and iron (III). Methods: Nano-electrospray−mass spectrometry, differential pulse voltammetry, deoxyribose degradation, iron (II) autoxidation, and brine shrimp mortality assays were used. Results: 8HQ formed a complex mixture of coordination complexes with iron (II) and iron (III). Furthermore, 8HQ showed antioxidant effects but no pro-oxidant ones. In the brine shrimp mortality assay, 8HQ demonstrated toxicity that decreased in the presence of iron (III). Conclusions: 8HQ is a potent antioxidant whose effects depend not only on the formation of the coordination complexes with iron ions, but surely on the scavenging activities due to the redox properties of the 8-hydroxyl group. No pro-oxidant effects were observed in the set of the used assays.© 2018 by the author