Stéphanie Gerin

Proteomic and functional characterization of a Chlamydomonas reinhardtii mutant lacking the mitochondrial alternative oxidase 1.

In the present work, we have isolated by RNA interference and characterized at the functional and the proteomic levels a Chlamydomonas reinhardtii strain devoid of the mitochondrial alternative oxidase 1 (AOX1). The AOX1-deficient strain displays a remarkable doubling of the cell volume and biomass without alteration of the generation time or change in total respiratory rate, with a significantly higher ROS production. To identify the molecular adaptation underlying these observations, we have carried out a comparative study of both the mitochondrial and the cellular soluble proteomes. Our results indicate a strong up-regulation of the ROS scavenging systems and important quantitative modifications of proteins involved in the primary metabolism, namely an increase of enzymes involved in anabolic pathways and a concomitant general down-regulation of enzymes of the main catabolic pathways.

Plasticity of the mitoproteome to nitrogen sources (nitrate and ammonium) in Chlamydomonas reinhardtii: The logic of Aox1 gene localization

Nitrate and ammonium constitute primary inorganic nitrogen sources that can be incorporated into carbon skeletons in photosynthetic eukaryotes. In Chlamydomonas, previous studies and the present one showed that the mitochondrial AOX is up-regulated in nitrate-grown cells in comparison with ammonium-grown cells. In this work, we have performed a comparative proteomic analysis of the soluble mitochondrial proteome of Chlamydomonas cells growth either on nitrate or ammonium. Our results highlight important proteomics modifications mostly related to primary metabolism in cells grown on nitrate. We could note an up-regulation of some TCA cycle enzymes and a down-regulation of cytochrome c1 together with an up-regulation of l-arginine and purine catabolism enzymes and of ROS scavenging systems. Hence, in nitrate-grown cells, AOX may play a dual role: (1) lowering the ubiquinone pool reduction level and (2) permitting the export of mitochondrial reducing power under the form of malate for nitrate and nitrite reduction. This role of AOX in the mitochondrial plasticity makes logical the localization of Aox1 in a nitrate assimilation gene cluster.

Modeling the dependence of respiration and photosynthesis upon light, acetate, carbon dioxide, nitrate and ammonium in Chlamydomonas reinhardtii using design of experiments and multiple regression

BackgroundIn photosynthetic organisms, the influence of light, carbon and inorganic nitrogen sources on the cellular bioenergetics has extensively been studied independently, but little information is available on the cumulative effects of these factors. Here, sequential statistical analyses based on design of experiments (DOE) coupled to standard least squares multiple regression have been undertaken to model the dependence of respiratory and photosynthetic responses (assessed by oxymetric and chlorophyll fluorescence measurements) upon the concomitant modulation of light intensity as well as acetate, CO2, nitrate and ammonium concentrations in the culture medium of Chlamydomonas reinhardtii. The main goals of these analyses were to explain response variability (i.e. bioenergetic plasticity) and to characterize quantitatively the influence of the major explanatory factor(s).ResultsFor each response, 2 successive rounds of multiple regression coupled to one-way ANOVA F-tests have been undertaken to select the major explanatory factor(s) (1st-round) and mathematically simulate their influence (2nd-round). These analyses reveal that a maximal number of 3 environmental factors over 5 is sufficient to explain most of the response variability, and interestingly highlight quadratic effects and second-order interactions in some cases. In parallel, the predictive ability of the 2nd-round models has also been investigated by k-fold cross-validation and experimental validation tests on new random combinations of factors. These validation procedures tend to indicate that the 2nd-round models can also be used to predict the responses with an inherent deviation quantified by the analytical error of the models.ConclusionsAltogether, the results of the 2 rounds of modeling provide an overview of the bioenergetic adaptations of C. reinhardtii to changing environmental conditions and point out promising tracks for future in-depth investigations of the molecular mechanisms underlying the present observations.

New features on the environmental regulation of metabolism revealed by modeling the cellular proteomic adaptations induced by light, carbon and inorganic nitrogen in Chlamydomonas reinhardtii

Microalgae are currently emerging to be very promising organisms for the production of biofuels and high-added value compounds. Understanding the influence of environmental alterations on their metabolism is a crucial issue. Light, carbon and nitrogen availability have been reported to induce important metabolic adaptations. So far, the influence of these variables has essentially been studied while varying only one or two environmental factors at the same time. The goal of the present work was to model the cellular proteomic adaptations of the green microalga Chlamydomonas reinhardtii upon the simultaneous changes of light intensity, carbon concentrations (CO2 and acetate), and inorganic nitrogen concentrations (nitrate and ammonium) in the culture medium. Statistical design of experiments (DOE) enabled to define 32 culture conditions to be tested experimentally. Relative protein abundance was quantified by two dimensional differential in-gel electrophoresis (2D-DIGE). Additional assays for respiration, photosynthesis, and lipid and pigment concentrations were also carried out. A hierarchical clustering survey enabled to partition biological variables (proteins + assays) into eight co-regulated clusters. In most cases, the biological variables partitioned in the same cluster had already been reported to participate to common biological functions (acetate assimilation, bioenergetic processes, light harvesting, Calvin cycle, and protein metabolism). The environmental regulation within each cluster was further characterized by a series of multivariate methods including principal component analysis and multiple linear regressions. This metadata analysis enabled to highlight the existence of a clear regulatory pattern for every cluster and to mathematically simulate the effects of light, carbon, and nitrogen. The influence of these environmental variables on cellular metabolism is described in details and thoroughly discussed. This work provides an overview of the metabolic adaptations contributing to maintain cellular homeostasis upon extensive environmental changes. Some of the results presented here could be used as starting points for more specific fundamental or applied investigations.