A systems-wide understanding of photosynthetic acclimation in algae and higher plants

The ability of phototrophs to colonise different environments relied on the robust protection against oxidative stress in phototrophs, a critical requirement for the successful evolutionary transition from water to land. Photosynthetic organisms have developed numerous strategies to adapt their photosynthetic apparatus to changing light conditions in order to optimise their photosynthetic yield, crucial for life to exist on Earth. Photosynthetic acclimation is an excellent example of the complexity of biological systems, in which highly diverse processes, ranging from electron excitation over protein protonation to enzymatic processes coupling ion gradients with biosynthetic activity interact on drastically different timescales, ranging from picoseconds to hours. An efficient functioning of the photosynthetic apparatus and its protection is paramount for efficient downstream processes including metabolism and growth. Modern experimental techniques can be successfully integrated with theoretical and mathematical models to promote our understanding of underlying mechanisms and principles. This Review aims to provide a retrospective analysis of multidisciplinary photosynthetic acclimation research carried out by members of the Marie Curie Initial Training Project “AccliPhot”, placing the results in a wider context. The Review also highlights the applicability of photosynthetic organisms for industry, particularly with regards to the cultivation of microalgae. It aims to demonstrate how theoretical concepts can successfully complement experimental studies broadening our knowledge of common principles in acclimation processes in photosynthetic organisms, as well as in the field of applied microalgal biotechnology

Élaboration d'un modèle biochimiquement structuré de la croissance d'une microalgue eucaryote en photobioréacteurs : application à l'algue verte unicellulaire Chlamydomonas reinhardtii

Ce travail de thèse porte sur l’élaboration d’un modèle prédictif de la croissance d’une microalgue eucaryote en photobioréacteur, basé sur une analyse du métabolisme de croissance de l’algue verte modèle Chlamydomonas reinhardtii en conditions photoautotrophes. Le modèle proposé appartient à la famille des modèles biochimiquement structurés. Outre la détermination prédictive des rendements de conversion des substrats en produits assurée par la représentation du métabolisme énergétique cellulaire, le modèle permet de décrire le comportement dynamique des microalgues en photobioréacteurs, en incluant l’adaptation de la teneur en pigments aux conditions de lumière fluctuantes, pour une large plage de conditions opératoires. Le modèle a été identifié et validé sur une base de données expérimentales obtenues pour des cultures continues et discontinues, élaborée dans le cadre de ce travail de thèse, comportant des mesures intra- et extracellulaires. Cette modélisation du comportement d’une microalgue eucaryote en photobioréacteur a été étendue à une description de la phase abiotique du bioréacteur, reposant sur une analyse et une caractérisation du transfert de matière gaz-liquide (O2 / CO2) dans les conditions étudiées. Cette modélisation de la phase abiotique a conduit au développement d’un estimateur de la concentration en biomasse basé sur la mesure de la vitesse nette de production d’oxygène. Cet outil a été validé expérimentalement, et a servi au suivi de cultures en temps réel, ainsi qu’au pilotage d’un photobioréateur en mode turbidostat.The present work deals with the elaboration of a predictive model for the growth of eukaryotic microalgae in photobioreactors, built on an analysis of the growth metabolism of the model green alga Chlamydomonas reinhardtii in photoautotrophic conditions. The proposed model belongs to the family of biochemically-based structured models. Besides a comprehensive representation of the conversion yields of substrates into products based on the description of cellular energetic metabolism, the model allows to predict the dynamic behaviour of microalgae growth in photobioreactors for a wide range of operating conditions, including pigment adaptation to fluctuating light conditions. The model has been identified and validated on an experimental dataset obtained for continuous and batch cultures carried out as part of the PhD, including intraand extracellular measurements. Modelling of microalgal growth behaviour in photobioreactors has been extended to a description of the reactor abiotic phase, relying on the analysis and characterization of gas-liquid mass transfer (O2 / CO2) under the conditions of the study. The abiotic phase modelling has led to the development of a biomass concentration estimator based on the measurement of the net oxygen production rate. This tool has been validated experimentally and has been applied to the real-time monitoring of cultures, as well as the control of a photobioreactor in turbidostat mode

Real time monitoring of photoautotrophic microalgae growth in photobioreactor, based on gas analysis

International audienceMicroalgae growth in a photobioreactor (PBR) is a complex process influenced by multiple parameters, such as photosynthetic light capture and attenuation, nutrient uptake, PBR hydrodynamics and gas – liquid (G – L) mass transfer. Like for any bioprocess, culture monitoring is a key aspect, as it allows controlling and optimizing operating parameters for improved production. In practice, real-time monitoring is mainly limited to pH and temperature. Online measurement of biomass concentration using optical density sensors needs improvements for providing accurate measurements. One alternative is to use on-line measurements such as pH, CO2 and O2 concentrations in- and off- gas stream. Software sensors based of first principle in combination with items as CO2 and O2 concentrations have been successfully implemented in fermentation since many years and in most recently in recombinant processes [1]. Despite their interest, the development of such tool in the context of microalgae application is underrepresented in the literature. Indeed, in phototrophs, CO2 and O2 are quantitatively the most important substrate and product, respectively. They allow quantifying on-line growth related parameters as net O2 production rate, CO2 uptake rate. Based on these quantities, biomass and nutrients concentrations could be estimated on-line. This study focusses on the development of such an estimation tool in the context of photoautotrophic growth cultivation of microalgae in closed PBR, in non-limiting mineral conditions. The proposed method uses a minimalistic model relying on macroscopic mass balances in liquid and gas phases and G - L mass transfer laws, without any assumption about the kinetic rate. Biomass concentration and growth rate have been estimated from net O2 production, assuming constant conversion yield. Combining in-situ O2 and CO2 measurements, the estimation of key parameters as dissolved CO2 and / or transfer coefficients is discussed. Although the methodology proposed here is rather general, online computation of net O2 and CO2 rates could be more or less complex, depending on gas vector through the PBR, G - L mass properties, and hydrodynamic conditions. A simulation study, based on a previous validated model [2] has been used to discuss limitations depending on the made assumptions. To demonstrate the methodology, the proposed tool has been experimentally implemented in a laboratory PBR throughout the photoautotrophic growth of a C. reinhardtii culture, its efficiency being proved under several operating conditions. Online estimation of biomass concentration has been in agreement with dry weight off-line measurements, even in batch operation, on a wide range of incident illumination conditions and gas flow rate through the PBR. In continuous conditions, online estimates have been successfully coupled with a feedback linearizing controller for biomass concentration. Since key process variables are available online, the proposed tool enables further control strategies. This is part of our ongoing research

Online estimation of microalgae growth in photobioreactor based on oxygen in situ measurements

International audienc

On-line estimation and feedback control of continuous photosynthetic microorganism growth

National audienc

Evaluation de la politique de developpement social des quartiers : Nantes Nord

SIGLEAvailable at INIST (FR), Document Supply Service, under shelf-number : RP 12872 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc