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

The High Light Response in Arabidopsis Requires the Calcium Sensor Protein CAS, a Target of STN7-and STN8-Mediated Phosphorylation

Reversible phosphorylation of thylakoid proteins contributes to photoacclimation responses in photosynthetic organisms, enabling the fine-tuning of light harvesting under changing light conditions and promoting the onset of photoprotective processes. However, the precise functional role of many of the described phosphorylation events on thylakoid proteins remains elusive. The calcium sensor receptor protein (CAS) has previously been indicated as one of the targets of the state transition kinase 8 (STN8). Here we show that in Arabidopsis thaliana, CAS is also phosphorylated by the state transition kinase 7 (STN7), as well as by another, so-far unknown, Ca2+-dependent kinase. Phosphoproteomics analysis and in vitro phosphorylation assays on CAS variants identified the phylogenetically conserved residues Thr-376, Ser-378, and Thr-380 as the major phosphorylation sites of the STN kinases. Spectroscopic analyses of chlorophyll fluorescence emission at 77K further showed that, while the cas mutant is not affected in state transition, it displays a persistent strong excitation of PSI under high light exposure, similar to the phenotype previously observed in other mutants defective in photoacclimation mechanisms. Together with the observation of a strong concomitant phosphorylation of light harvesting complex II (LHCII) and photosynthetic core proteins under high irradiance in the cas mutant this suggests a role for CAS in the STN7/STN8/TAP38 network of phosphorylation-mediated photoacclimation processes in Arabidopsis

Eurodelta multi-model simulated and observed particulate matter trends in Europe in the period of 1990-2010

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990-2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000-2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty.The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) mu g m(-3) (or between 10 % and 30 %) across most of Europe (by 0.5-2 mu g m(-3) in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large interannual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %-40 % over most of Europe, increasing to 50 %-60 % in the northern and eastern parts of the EDT domain.Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are - 0.24 and -0.22 mu g m(-3) yr(-1) for PM10 and PM2.5, which are somewhat weaker than the observed trends of - 0.35 and -0.40 mu g m(-3) yr(-1) respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are -1.7 % yr(-1) and -2.0 % yr(-1) from the model ensemble and -2.1 % yr(-1) and -2.9 % yr(-1) from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries.The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located.The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in SO42- concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of NH4+ and NO3- to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appear to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties (including the implications of not accounting for forest fires and natural mineral dust by some of the models) and the effect of inter-annual meteorological variability on the trend analysis.Peer reviewe

Air pollution trends in the EMEP region between 1990 and 2012

The present report synthesises the main features of the evolution over the 1990-2012 time period of the concentration and deposition of air pollutants relevant in the context of the Convention on Long-range Transboundary Air Pollution: (i) ozone, (ii) sulfur and nitrogen compounds and particulate matter, (iii) heavy metals and persistent organic pollutants. It is based on observations gathered in State Parties to the Convention within the EMEP monitoring network of regional background stations, as well as relevant modelling initiatives. Joint Report of: EMEP Task Force on Measurements and Modelling (TFMM), Chemical Co-ordinating Centre (CCC), Meteorological Synthesizing Centre-East (MSC-E), Meteorological Synthesizing Centre-West (MSC-W)

L'Auto-vélo : automobilisme, cyclisme, athlétisme, yachting, aérostation, escrime, hippisme / dir. Henri Desgranges

26 juin 19241924/06/26 (A25,N8594)

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

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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

Use of Polyphemus Plume in Grid model to reproduce the full chemistry and physics of Particulate matter in industrial plumes. Applications and validation for Refinery during the TEMMAS project "Teledetection, Measure, Modeling of Atmospheric pollutants on industrial Sites"

International audienceThe Polyphemus Plume-in-Grid (PinG) model, based on a 3D Eulerian model and a subgrid scaled Gaussian puff model was developed to represent the dispersion and transformation of air pollutants in industrial plumes. The PinG model computes the formation of secondary gases and PM in the plumes, resulting from the oxidation of emitted precursors in interaction with background pollutant concentrations. The model was improved to treat PM number concentrations, allowing a better representation of the ultra-fine fraction of PM concentrations. In comparison with the conventional CTM approach, this tool is able to provide a realistic assessment of the impacts of industrial sites in the first ten kilometers. To improve the validation of the Plume In Grid Model, from the stack to the ground, a research project called TEMMAS (TEledetection, Measure, Modeling of Atmospheric pollutants on industrial Sites) was supported by the French environment agency (ADEME). The project included two intensive measurement campaigns, which were conducted around a refinery in the south of France. The aim of these campaigns were to study the refinery PM microphysical signatures and its evolution with distance to the source in the first kilometers. During the campaigns different observation protocols of PM were deployed: • sample collection inside the principal stacks and around the refinery. • online measurements of microphysical properties of PM and trace gas concentrations; • optical measurement: airborne hyperspectral imagery in the reflective domain, According to the different techniques, two types of models were used, with different spatial resolutions, meteorological input (meso-scale meteorology or local measurements), and chemical transformations representations: • The Polyphemus Plume-in-Grid (PinG) model, which results are compared to measured PM in the vicinity of the refinery in terms of gas, PM mass and number concentrations, as a function of particle sizes and PM chemical compositions. • The Safety LAgrangian Model (SLAM), a lagrangian non reactive dispersion model using pre calculated CFD winds fields. The fine resolution (meter) allows to reproduce complex flows in industrial installations. This approach is better fitted for the comparison of the local scale plume dispersion with optical imaging