A mechanistic model of algal photoinhibition induced by photodamage to photosystem-II

A kinetic-assisted growth curve prediction method for Chlamydomonas reinhardtii incorporating transfer learning

Traditional predictions of microalgal growth states rely on empirical or easily implementable kinetic models, leading to significant biases and elevated cost. This study proposes a kinetic-assisted machine learning method for predicting the growth curve of microalgal biomass under small sample conditions. Firstly, a microalgae growth kinetic model is constructed based on the logistic model. A two-stage kinetic fitting strategy is specified to account for the light-dark ratio. The Box-Behnken method is employed for experimental design. Then, using Two-stage TrAdaboost.R2 algorithm, the kinetic model is utilized as the source domain, and the experimental design data serves as the target domain for training machine learning models. The results indicate that the proposed method outperforms a single machine learning model in terms of prediction and has the potential to rapidly estimate microalgal growth trends under different conditions and accurately predict harvested biomass, potentially reducing the need for laborious, expensive, and time-consuming laboratory trials.

Selection of photosynthetic traits by turbulent mixing governs formation of cyanobacterial blooms in shallow eutrophic lakes

Prediction of the complex cyanobacteria-environment interactions is vital for understanding harmful bloom formation. Most previous studies on these interactions considered specific properties of cyanobacterial cells as representative for the entire population (e.g. growth rate, mortality, and photosynthetic capacity (Pmax)), and assumed that they remained spatiotemporally unchanged. Although, at the population level, the alteration of such traits can be driven by intraspecific competition, little is known about how traits and their plasticity change in response to environmental conditions and affect the bloom formation. Here we test the hypothesis that intraspecific variations in Pmax of cyanobacteria (Microcystis spp.) play an important role in its population dynamics. We coupled a one-dimensional hydrodynamic model with a trait-based phytoplankton model to simulate the effects of physical drivers (turbulence and turbidity) on the Pmax of Microcystis populations for a range of dynamic conditions typical for shallow eutrophic lakes. Our results revealed that turbulence acts as a directional selective driver for changes in Pmax. Depending on the intensity of daily-periodic turbulence, representing wind-driven mixing, a shift in population-averaged phenotypes occurred toward either low Pmax, allowing the population to capture additional light in the upper layers, or high Pmax, enhancing the efficiency of light utilization. Moreover, we observed that a high intraspecific diversity in Pmax accelerated the formation of surface scum by up to more than four times compared to a lower diversity. This study offers insights into mechanisms by which cyanobacteria populations respond to turbulence and underscores the significance of intraspecific variations in cyanobacterial bloom formation.

HIGHLIGHTS

Experimental and theoretical investigations of rotating algae biofilm reactors (RABRs): Areal productivity, nutrient recovery, and energy efficiency

Microalgae biofilms have been demonstrated to recover nutrients from wastewater and serve as biomass feedstock for bioproducts. However, there is a need to develop a platform to quantitatively describe microalgae biofilm production, which can provide guidance and insights for improving biomass areal productivity and nutrient uptake efficiency. This paper proposes a unified experimental and theoretical framework to investigate algae biofilm growth on a rotating algae biofilm reactor (RABR). Experimental laboratory setups are used to conduct controlled experiments on testing environmental and operational factors for RABRs. We propose a differential-integral equation-based mathematical model for microalgae biofilm cultivation guided by laboratory experimental findings. The predictive mathematical model development is coordinated with laboratory experiments of biofilm areal productivity associated with ammonia and inorganic phosphorus uptake by RABRs. The unified experimental and theoretical tool is used to investigate the effects of RABR rotating velocity, duty cycle (DC), and light intensity on algae biofilm growth, areal productivity, nutrient uptake efficiency, and energy efficiency in wastewater treatment. Our framework indicates that maintaining a reasonable light intensity range improves biomass areal productivity and nutrient uptake efficiency. Our framework also indicates that faster RABR rotation benefits biomass areal productivity. However, maximizing the nutrient uptake efficiency requires a reasonably low RABR rotating speed. Energy efficiency is strongly correlated with RABR rotating speed and DC.

Photoinactivation vs repair of photosystem II as target of thermal stress in epipelic and epipsammic microphytobenthos communities

Microphytobenthos (MPB) inhabiting intertidal flats are exposed to large and sudden changes in temperature, often simultaneously with exposure to direct sunlight. These conditions are expected to negatively impact photosynthesis by exacerbating the photoinhibition under high light. This study addressed the photoinhibitory effects of short-term exposure to cold (5°C) and moderate heat (35°C) on MPB dominated by motile epipelic (EPL) and immotile epipsammic (EPM) diatom species, by evaluating the seasonal variation of photoinactivation and repair of photosystem II (PSII). The susceptibility to PSII photoinactivation and the counteracting repair capacity were measured by the constant rates kPI and kREC, respectively. The photoacclimation state was characterized by hysteresis light-response curves (HLC) of the relative electron transport rate, rETR, and of the nonphotochemical quenching index Y(NPQ). Under non-stress conditions (20°C), kREC was on average almost 10x higher than the corresponding kPI (20.4 vs 2.70 × 10-4 s-1, respectively), indicating the operation of efficient repair mechanisms. Overall, the exposure to low and high temperatures affected both PSII photoinactivation and repair but causing smaller impacts in the former than in the latter. Also, cold stress caused larger effects on repair (decrease of kREC) than on photoinactivation (increase of kPI), but heat stress affected similarly the two processes. These effects varied seasonally, suggesting a role of thermal acclimation, as heat stress had stronger effects in cold-acclimated samples and cold stress resulted in stronger effects in heat-acclimated samples. The changes in kPI and kREC occurred despite the high light-acclimated phenotype found all year round, indicating that these processes vary independently from the photoacclimation state. The results also showed that photoprotection processes, as measured by energy-dependent non-photochemical index qE, appear to have an important role, both by preventing PSII photoinactivation and by alleviating the impacts on PSII repair under acute thermal stress.

Theoretical growth rate of microalgae under high/low-flashing light

Dynamic light regimes strongly impact microalgal photosynthesis efficiency. Finding the optimal way to supply light is then a tricky problem, especially when the growth rate is inhibited by overexposition to light and, at the same time, there is a lack of light in the deepest part of the culture. In this paper, we use the Han model to study the theoretical microalgal growth rate by applying periodically two different light intensities. Two approaches are considered depending on the period of the light pattern. For a large light period, we demonstrate that the average photosynthetic rate can be improved under some conditions. Moreover, we can also enhance the growth rate at steady state as given by the PI-curve. Although, these conditions change through the depth of a bioreactor. This theoretical improvement in the range of 10-15% is due to a recovery of photoinhibited cells during the high irradiance phase. We give a minimal value of the duty cycle for which the optimal irradiance is perceived by the algae culture under flashing light regime.

Models predict planned phosphorus load reduction will make Lake Erie more toxic

Harmful cyanobacteria are a global environmental problem, yet we lack actionable understanding of toxigenic versus nontoxigenic strain ecology and toxin production. We performed a large-scale meta-analysis including 103 papers and used it to develop a mechanistic, agent-based model of Microcystis growth and microcystin production. Simulations for Lake Erie suggest that the observed toxigenic-to-nontoxigenic strain succession during the 2014 Toledo drinking water crisis was controlled by different cellular oxidative stress mitigation strategies (protection by microcystin versus degradation by enzymes) and the different susceptibility of those mechanisms to nitrogen limitation. This model, as well as a simpler empirical one, predicts that the planned phosphorus load reduction will lower biomass but make nitrogen and light more available, which will increase toxin production, favor toxigenic cells, and increase toxin concentrations.

Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive overview of the available models provides a unique toolbox for generating CFD models of photobioreactors. Directions future research should take are also discussed, mainly consisting of an extensive experimental validation of the single models for specific photobioreactor geometries, as well as more complete and sophisticated integrated models by virtue of the constant increase of the computational capacity.

New Insights From Transcriptomic Data Reveal Differential Effects of CO2 Acidification Stress on Photosynthesis of an Endosymbiotic Dinoflagellate in hospite

Ocean acidification (OA) has both detrimental as well as beneficial effects on marine life; it negatively affects calcifiers while enhancing the productivity of photosynthetic organisms. To date, many studies have focused on the impacts of OA on calcification in reef-building corals, a process particularly susceptible to acidification. However, little is known about the effects of OA on their photosynthetic algal partners, with some studies suggesting potential benefits for symbiont productivity. Here, we investigated the transcriptomic response of the endosymbiont Symbiodinium microadriaticum (CCMP2467) in the Red Sea coral Stylophora pistillata subjected to different long-term (2 years) OA treatments (pH 8.0, 7.8, 7.4, 7.2). Transcriptomic analyses revealed that symbionts from corals under lower pH treatments responded to acidification by increasing the expression of genes related to photosynthesis and carbon-concentrating mechanisms. These processes were mostly up-regulated and associated metabolic pathways were significantly enriched, suggesting an overall positive effect of OA on the expression of photosynthesis-related genes. To test this conclusion on a physiological level, we analyzed the symbiont’s photochemical performance across treatments. However, in contrast to the beneficial effects suggested by the observed gene expression changes, we found significant impairment of photosynthesis with increasing pCO₂. Collectively, our data suggest that over-expression of photosynthesis-related genes is not a beneficial effect of OA but rather an acclimation response of the holobiont to different water chemistries. Our study highlights the complex effects of ocean acidification on these symbiotic organisms and the role of the host in determining symbiont productivity and performance.

Model-Based Prediction of Perceived Light Flashing in Recirculated Inclined Wavy-Bottomed Photobioreactors

Microalgae biomass production rate in short light-path photobioreactors potentially can be improved by mixing-induced flashing light regimes. A cascade photobioreactor features a thin liquid layer flowing down a sloping, wavy-bottomed surface where liquid flow exhibits peculiar local recirculation hydrodynamics, potentially conducive to an ordered flashing light regime. This article presents a model-based analysis of the frequency distribution of perceived irradiance in said wavy-bottomed photobioreactor. The model combines a Lagrangian description of the motion of individual cells, in turn derived from the hydrodynamic parameters of the photobioreactor extracted from an experimentally validated Computational Fluid Dynamic model, with a simplified description of the irradiance field across the culture thickness, down to the spectral analysis of perceived irradiance. The main finding of the work is that the wavy bottomed photobioreactor provides a ‘robust’ spectral excitation to the circulating microalgae up to 3 Hz frequency, while in flat panels and bubble columns excitation decays evenly at a 24 db/octave rate. This analysis paves the way to improving the light flashing performance of the wavy-bottomed photobioreactor with respect to geometry (cavity size and installation inclination) and operation (flow rate).

Outdoor scale-up of Leptolyngbya sp.: Effect of light intensity and inoculum volume on photoinhibition and -oxidation

The effect of light intensity and inoculum volume on the occurrence of photooxidation for Leptolyngbya sp. QUCCCM 56 was investigated, to facilitate the transition from small‐scale laboratory experiments to large‐scale outdoor cultivation. Indoor, the strain was capable of growing at light intensities of up to 5600 µmol photons/m²/s, at inoculation densities as low as 0.1 g/L (10% inoculation volume vol/vol). Levels of chlorophyll and phycocyanin showed a significant decrease within the first 24 h, indicating some level of photooxidation, however, both were able to recover within 72 h. When cultivated under outdoor conditions in Qatar during summer, with average peak light intensities 1981 ± 41 μmol photons/m²/s, the strain had difficulties growing. The culture recovered after an initial adaptation period, and clear morphological differences were observed, such as an increase in trichome length, as well as coiling of multiple trichomes in tightly packed strands. It was hypothesized that the morphological changes were induced by UV‐radiation as an adaptation mechanism for increased self‐shading. Furthermore, the presence of contaminating ciliates could have also affected the outdoor culture. Both UV and contaminants are generally not simulated under laboratory environments, causing a mismatch between indoor optimizations and outdoor realizations.

Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo-production systems

Light attenuation is a primary challenge limiting the upscaling of photobioreactors for sustainable bio-production. One key to this challenge, is to model and optimise the light/dark cycles so that cells within the dark region can be frequently transferred to the light region for photosynthesis. Therefore, this study proposes the first mechanistic model to integrate the light/dark cycle effects into biomass growth kinetics. This model was initially constructed through theoretical derivation based on the intracellular reaction kinetics, and was subsequently modified by embedding a new parameter, effective light coefficient, to account for the effects of culture mixing. To generate in silico process data, a new multiscale reactive transport modelling strategy was developed to couple fluid dynamics with biomass growth kinetics and light transmission. By comparing against previous experimental and computational studies, the multiscale model shows to be of high accuracy. Based on its simulation result, an original correlation was proposed to link effective light coefficient with photobioreactor gas inflow rate; this has not been done before. The impact of this study is that by using the proposed mechanistic model and correlation, we can easily control and optimise photobioreactor gas inflow rates to alleviate light attenuation and maintain a high biomass growth rate.

Multiscale numerical workflow describing microalgae motion and light pattern incidence towards population growth in a photobioreactor

In this article, a numerical workflow describing the microalgal growth inside of a photobioreactor is proposed. CFD is used to compute reactor internal hydrodynamics taking into account marine impeller rotation and sparged bubbles motion. Lagrangian approach is used to track microalgae motion inside of the culture vessel. The illumination across the reactor is obtained using the classical Beer-Lambert's law. The combination of light field and cell motion allows to reconstruct the light history of each microalgae. These histories are then supplied to Han's model which predicts individual growth rate and experienced photodamages. Once computed, several thousands of trajectories are agglomerated at the population level yielding the photobioreactor performances. After having ensured properties convergence, this procedure is applied to a large range of optical density (0 to 4.0), i.e. cell concentration, and incident light intensities (0 to 2000 μmolPhoton/m2/s). From this exploration, it is possible to determine the photobioreactor response surfaces in terms of growth rate and photodamages. These are latter used to propose an optimal lighting strategy for biomass production - reducing photobioreactor operation time by 16% compared to classical two-step procedure - and assist light induced stress with the aim of triggering secondary metabolites production.

Microalgal kinetics - a guideline for photobioreactor design and process development

Kinetics generally describes bio‐(chemical) reaction rates in dependence on substrate concentrations. Kinetics for microalgae is often adapted from heterotrophs and lacks mechanistic foundation, e.g. for light harvesting. Using and understanding kinetic equations as the representation of intracellular mechanisms is essential for reasonable comparisons and simulations of growth behavior. Summarizing growth kinetics in one equation does not yield reliable models. Piecewise linear or rational functions may mimic photosynthesis irradiance response curves, but fail to represent the mechanisms. Our modeling approach for photoautotrophic growth comprises physical and kinetic modules with mechanistic foundation extracted from the literature. Splitting the light submodel into the modules for light distribution, light absorption, and photosynthetic sugar production with independent parameters allows the transfer of kinetics between different reactor designs. The consecutive anabolism depends among others on nutrient concentrations. The nutrient uptake kinetics largely impacts carbon partitioning in the reviewed stoichiometry range of cellular constituents. Consecutive metabolic steps mask each other and demand a maximum value understandable as the minimum principle of growth. These fundamental modules need to be clearly distinguished, but may be modified or extended based on process conditions and progress in research. First, discussion of kinetics helps to understand the physiological situation, for which ranges of parameter values are given. Second, kinetics should be used for photobioreactor design, but also for gassing and nutrient optimization. Numerous examples are given for both aspects. Finally, measuring kinetics more comprehensively and precisely will help in improved process development.

Optimal proteome allocation strategies for phototrophic growth in a light-limited chemostat

BACKGROUND

Cyanobacteria and other phototrophic microorganisms allow to couple the light-driven assimilation of atmospheric [Formula: see text] directly to the synthesis of carbon-based products, and are therefore attractive platforms for microbial cell factories. While most current engineering efforts are performed using small-scale laboratory cultivation, the economic viability of phototrophic cultivation also crucially depends on photobioreactor design and culture parameters, such as the maximal areal and volumetric productivities. Based on recent insights into the cyanobacterial cell physiology and the resulting computational models of cyanobacterial growth, the aim of this study is to investigate the limits of cyanobacterial productivity in continuous culture with light as the limiting nutrient.

RESULTS

We integrate a coarse-grained model of cyanobacterial growth into a light-limited chemostat and its heterogeneous light gradient induced by self-shading of cells. We show that phototrophic growth in the light-limited chemostat can be described using the concept of an average light intensity. Different from previous models based on phenomenological growth equations, our model provides a mechanistic link between intracellular protein allocation, population growth and the resulting reactor productivity. Our computational framework thereby provides a novel approach to investigate and predict the maximal productivity of phototrophic cultivation, and identifies optimal proteome allocation strategies for developing maximally productive strains.

CONCLUSIONS

Our results have implications for efficient phototrophic cultivation and the design of maximally productive phototrophic cell factories. The model predicts that the use of dense cultures in well-mixed photobioreactors with short light-paths acts as an effective light dilution mechanism and alleviates the detrimental effects of photoinhibition even under very high light intensities. We recover the well-known trade-offs between a reduced light-harvesting apparatus and increased population density. Our results are discussed in the context of recent experimental efforts to increase the yield of phototrophic cultivation.

Intrinsic kinetic model of photoautotrophic microalgae based on chlorophyll fluorescence analysis

As photoautotrophic microorganisms, microalgae feature complex mechanisms of photosynthesis and light energy transfer and as such studying their intrinsic growth kinetics is fairly difficult. In this article, the quantum yield of photochemical reaction was introduced in a study of microalgal kinetics to establish an intrinsic kinetic model of photoautotrophic microalgal growth. The blue-green algae Synechococcus sp. PCC7942 was used to verify the kinetic model developed using chlorophyll fluorescence analysis and growth kinetics determination. Results indicate that the kinetic model can realistically reflect the light energy utilization efficiency of microalgae as well as their intrinsic growth kinetic characteristics. The model and method proposed in this article may be utilized in intrinsic kinetics studies of photoautotrophic microorganisms.

Contrasting responses of photosynthesis and photochemical efficiency to ocean acidification under different light environments in a calcifying alga

Ocean acidification (OA) is predicted to enhance photosynthesis in many marine taxa. However, photophysiology has multiple components that OA may affect differently, especially under different light environments, with potentially contrasting consequences for photosynthetic performance. Furthermore, because photosynthesis affects energetic budgets and internal acid-base dynamics, changes in it due to OA or light could mediate the sensitivity of other biological processes to OA (e.g. respiration and calcification). To better understand these effects, we conducted experiments on Porolithon onkodes, a common crustose coralline alga in Pacific coral reefs, crossing pCO₂ and light treatments. Results indicate OA inhibited some aspects of photophysiology (maximum photochemical efficiency), facilitated others (α, the responsiveness of photosynthesis to sub-saturating light), and had no effect on others (maximum gross photosynthesis), with the first two effects depending on treatment light level. Light also exacerbated the increase in dark-adapted respiration under OA, but did not alter the decline in calcification. Light-adapted respiration did not respond to OA, potentially due to indirect effects of photosynthesis. Combined, results indicate OA will interact with light to alter energetic budgets and potentially resource allocation among photosynthetic processes in P. onkodes, likely shifting its light tolerance, and constraining it to a narrower range of light environments.

A model of optimal protein allocation during phototrophic growth

Photoautotrophic growth depends upon an optimal allocation of finite cellular resources to diverse intracellular processes. Commitment of a certain mass fraction of the proteome to a specific cellular function typically reduces the proteome available for other cellular functions. Here, we develop a semi-quantitative kinetic model of cyanobacterial phototrophic growth to describe such trade-offs of cellular protein allocation. The model is based on coarse-grained descriptions of key cellular processes, in particular carbon uptake, metabolism, photosynthesis, and protein translation. The model is parameterized using literature data and experimentally obtained growth curves. Of particular interest are the resulting cyanobacterial growth laws as fundamental characteristics of cellular growth. We show that the model gives rise to similar growth laws as observed for heterotrophic organisms, with several important differences due to the distinction between light energy and carbon uptake. We discuss recent experimental data supporting the model results and show that coarse-grained growth models have implications for our understanding of the limits of phototrophic growth and bridge a gap between molecular physiology and ecology.

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes.

A reductionist approach to model photosynthetic self-regulation in eukaryotes in response to light

Along with the development of several large-scale methods such as mass spectrometry or micro arrays, genome wide models became not only a possibility but an obvious tool for theoretical biologists to integrate and analyse complex biological data. Nevertheless, incorporating the dynamics of photosynthesis remains one of the major challenges while reconstructing metabolic networks of plants and other photosynthetic organisms. In this review, we aim to provide arguments that small-scale models are still a suitable choice when it comes to discovering organisational principles governing the design of biological systems. We give a brief overview of recent modelling efforts in understanding the interplay between rapid, photoprotective mechanisms and the redox balance within the thylakoid membrane, discussing the applicability of a reductionist approach in modelling self-regulation in plants and outline possible directions for further research.

Photobioreactors for microalgal cultures: A Lagrangian model coupling hydrodynamics and kinetics

Closed photobioreactors have to be optimized in terms of light utilization and overall photosynthesis rate. A simple model coupling the hydrodynamics and the photosynthesis kinetics has been proposed to analyze the photosynthesis dynamics due to the continuous shuttle of microalgae between dark and lighted zones of the photobioreactor. Microalgal motion has been described according to a stochastic Lagrangian approach adopting the turbulence model suitable for the photobioreactor configuration (single vs. two-phase flows). Effects of light path, biomass concentration, turbulence level and irradiance have been reported in terms of overall photosynthesis rate. Different irradiation strategies (internal, lateral and rounding) and several photobioreactor configurations (flat, tubular, bubble column, airlift) have been investigated. Photobioreactor configurations and the operating conditions to maximize the photosynthesis rate have been pointed out. Results confirmed and explained the common experimental observation that high concentrated cultures are not photoinhibited at high irradiance level.

A state of the art of metabolic networks of unicellular microalgae and cyanobacteria for biofuel production

The most promising and yet challenging application of microalgae and cyanobacteria is the production of renewable energy: biodiesel from microalgae triacylglycerols and bioethanol from cyanobacteria carbohydrates. A thorough understanding of microalgal and cyanobacterial metabolism is necessary to master and optimize biofuel production yields. To this end, systems biology and metabolic modeling have proven to be very efficient tools if supported by an accurate knowledge of the metabolic network. However, unlike heterotrophic microorganisms that utilize the same substrate for energy and as carbon source, microalgae and cyanobacteria require light for energy and inorganic carbon (CO2 or bicarbonate) as carbon source. This double specificity, together with the complex mechanisms of light capture, makes the representation of metabolic network nonstandard. Here, we review the existing metabolic networks of photoautotrophic microalgae and cyanobacteria. We highlight how these networks have been useful for gaining insight on photoautotrophic metabolism.

Modelling of Microalgae Culture Systems with Applications to Control and Optimization

Mathematical modeling is becoming ever more important to assess the potential, guide the design, and enable the efficient operation and control of industrial-scale microalgae culture systems (MCS). The development of overall, inherently multiphysics, models involves coupling separate submodels of (i) the intrinsic biological properties, including growth, decay, and biosynthesis as well as the effect of light and temperature on these processes, and (ii) the physical properties, such as the hydrodynamics, light attenuation, and temperature in the culture medium. When considering high-density microalgae culture, in particular, the coupling between biology and physics becomes critical. This chapter reviews existing models, with a particular focus on the Droop model, which is a precursor model, and it highlights the structure common to many microalgae growth models. It summarizes the main developments and difficulties towards multiphysics models of MCS as well as applications of these models for monitoring, control, and optimization purposes.

A dynamic growth model of Dunaliella salina: parameter identification and profile likelihood analysis

In this work, a photoautotrophic growth model incorporating light and nutrient effects on growth and pigmentation of Dunaliella salina was formulated. The model equations were taken from literature and modified according to the experimental setup with special emphasis on model reduction. The proposed model has been evaluated with experimental data of D. salina cultivated in a flat-plate photobioreactor under stressed and non-stressed conditions. Simulation results show that the model can represent the experimental data accurately. The identifiability of the model parameters was studied using the profile likelihood method. This analysis revealed that three model parameters are practically non-identifiable. However, some of these non-identifiabilities can be resolved by model reduction and additional measurements. As a conclusion, our results suggest that the proposed model equations result in a predictive growth model for D. salina.

The effect of photosynthesis time scales on microalgae productivity

Microalgae are often seen as a potential biofuel producer. In order to predict achievable productivities in the so called raceway culturing system, the dynamics of photosynthesis has to be taken into account. In particular, the dynamical effect of inhibition by an excess of light (photoinhibition) must be represented. We propose a model considering both photosynthesis and growth dynamics. This model involves three different time scales. We study the response of this model to fluctuating light with different frequencies by slow/fast approximations. Therefore, we identify three different regimes for which a simplified expression for the model can be derived. These expressions give a hint on productivity improvement which can be expected by stimulating photosynthesis with a faster hydrodynamics.

Modeling the dynamic modulation of light energy in photosynthetic algae

An integrated cell-based dynamic mathematical model that take into account the role of the photon absorbing process, the partition of excitation energy, and the photoinactivation and repair of photosynthetic units, under variable light and dissolved inorganic carbon (DIC) availability is proposed. The modeling of the photon energy absorption and the energy dissipation is based on the photoadaptive changes of the underlying mechanisms. The partition of the excitation energy is based on the relative availability of light and DIC to the cell. The modeling of the photoinactivation process is based on the common aspect that it occurs under any light intensity and the modeling of the repair process is based on the evidence that it is controlled by chloroplast and nuclear-encoded enzymes. The present model links the absorption of photons and the partitioning of excitation energy to the linear electron flow and other quenchers with chlorophyll fluorescence emission parameters, and the number of the functional photosynthetic units with the photosynthetic oxygen production rate. The energy allocation to the LEF increases as DIC availability increases and/or light intensity decreases. The rate of rejected energy increases with light intensity and with DIC availability. The resulting rate coefficient of photoinactivation increases as light intensity and/or as DIC concentration increases. We test the model against chlorophyll fluorescence induction and photosynthetic oxygen production rate measurements, obtained from cultures of the unicellular green alga Scenedesmus obliquus, and find a very close quantitative and qualitative correspondence between predictions and data.

Carrying photosynthesis genes increases ecological fitness of cyanophage in silico

Several viruses infecting marine cyanobacteria carry photosynthesis genes (e.g. psbA, hli) that are expressed, yield proteins (D1, HLIP) and help maintain the cell's photosynthesis apparatus during the latent period. This increases energy and speeds up virus production, allowing for a reduced latent period (a fitness benefit), but it also increases the DNA size, which slows down new virus production and reduces burst size (a fitness cost). How do these genes affect the net ecological fitness of the virus? Here, this question is explored using a combined systems biology and systems ecology ('systems bioecology') approach. A novel agent-based model simulates individual cyanobacteria cells and virus particles, each with their own genes, transcripts, proteins and other properties. The effect of D1 and HLIP proteins is explicitly considered using a mechanistic photosynthesis component. The model is calibrated to the available database for Prochlorococcus ecotype MED4 and podovirus P-SSP7. Laboratory- and field-scale in silico survival, competition and evolution (gene packaging error) experiments with wild type and genetically engineered viruses are performed to develop vertical survival and fitness profiles, and to determine the optimal gene content. The results suggest that photosynthesis genes are nonessential, increase fitness in a manner correlated with irradiance, and that the wild type has an optimal gene content.

PHOTOINHIBITION OF PSII IN EMILIANIA HUXLEYI (HAPTOPHYTA) UNDER HIGH LIGHT STRESS: THE ROLES OF PHOTOACCLIMATION, PHOTOPROTECTION, AND PHOTOREPAIR(1)

The response of the coccolithophorid Emiliania huxleyi (Lohmann) W. H. Hay et H. Mohler to acute exposure to high photon flux densities (PFD) was examined in terms of PSII photoinhibition, photoprotection, and photorepair. The time and light dependencies of these processes were characterized as a function of the photoacclimation state of the alga. Low-light (LL) acclimated cells displayed a higher degree of photoinhibition, measured as decline in Fv /Fm , than high-light (HL) acclimated cells. However, HL cultures were more susceptible to photodamage but also more capable of compensating for it by performing a faster repair cycle. The relation between gross photoinhibition (observed in the presence of an inhibitor of repair) and PFD to which the algae were exposed deviated from linearity at high PFD, which calls into question the universality of current concepts of photoinhibition in mechanistic models. The light dependence of the de-epoxidation state (DPS) of the xanthophyll cycle (XC) pigments on the timescale of hours was the same in cells acclimated to LL and HL. However, HL cells were more efficient in realizing nonphotochemical quenching (NPQ) on short timescales, most likely due to a larger XC pool. LL cells displayed an increase in the PSII effective cross-section (σPSII ) as a result of photoinhibition, which was observed also in HL cells when net photoinhibition was induced by blocking the D1 repair cycle. The link between σPSII and photoinhibition suggests that the population of PSII reaction centers (RCIIs) of E. huxleyi shares a common antenna, according to a "lake" organization of the light-harvesting complex.

Damage to the oxygen-evolving complex by superoxide anion, hydrogen peroxide, and hydroxyl radical in photoinhibition of photosystem II

Under strong illumination of a photosystem II (PSII) membrane, endogenous superoxide anion, hydrogen peroxide, and hydroxyl radical were successively produced. These compounds then cooperatively resulted in a release of manganese from the oxygen-evolving complex (OEC) and an inhibition of oxygen evolution activity. The OEC inactivation was initiated by an acceptor-side generated superoxide anion, and hydrogen peroxide was most probably responsible for the transportation of reactive oxygen species (ROS) across the PSII membrane from the acceptor-side to the donor-side. Besides ROS being generated in the acceptor-side induced manganese loss; there may also be a ROS-independent manganese loss in the OEC of PSII. Both superoxide anion and hydroxyl radical located inside the PSII membrane were directly identified by a spin trapping-electron spin resonance (ESR) method in combination with a lipophilic spin trap, 5-(diethoxyphosphoryl)-5-phenethyl-1-pyrroline N-oxide (DEPPEPO). The endogenous hydrogen peroxide production was examined by oxidation of thiobenzamide.

UVB Effects on the Photosystem II-D1 Protein of Phytoplankton and Natural Phytoplankton Communities

The reaction center of photosystem II is susceptible to photodamage. In particular the D1 protein located in the photosystem II core has a rapid, light-dependent turnover termed the photosystem II repair cycle that, under illumination, degrades and resynthesizes D1 protein to limit accumulation of photodamaged photosystem II. Most studies concerning the effects of UVB (280-320 nm) on this cycle have been on cyanobacteria or specific phytoplankton species rather than on natural communities of phytoplankton. During a 5-year multidisciplinary project on the effects of UV radiation (200-400 nm) on natural systems, the effects of UVB on the D1 protein of natural phytoplankton communities were assessed. This review provides an overview of photoinhibitory effects of light on cultured and natural phytoplankton, with an emphasis on the interrelation of UVB exposure, D1 protein degradation and the repair of photosystem II through D1 resynthesis. Although the UVB component of the solar spectrum contributes to the primary photoinactivation of photosystem II, we conclude that, in natural communities, inhibition of the rate of the photosystem II repair cycle is a more important influence of UVB on primary productivity. Indeed, exposing tropical and temperate phytoplankton communities to supplemented UVB had more inhibitory effect on D1 synthesis than on the D1 degradation process itself. However, the rate of net D1 damage was faster for the tropical communities, likely because of the effects of high ambient light and water temperature on mechanisms of protein degradation and synthesis.

Consequences of a deletion in dspA on transcript accumulation in Synechocystis sp. strain PCC6803

A sensor histidine kinase of Synechococcus sp. strain PCC7942, designated nblS, was previously identified and shown to be critical for the acclimation of cells to high-light and nutrient limitation conditions and to influence the expression of a number of light-responsive genes. The nblS orthologue in Synechocystis sp. strain PCC6803 is designated dspA (also called hik33). We have generated a dspA null mutant and analyzed global gene expression in both the mutant and wild-type strains under high- and low-light conditions. The mutant is aberrant for the expression of many genes encoding proteins critical for photosynthesis, phosphate and carbon acquisition, and the amelioration of stress conditions. Furthermore, transcripts from a number of genes normally detected only during exposure of wild-type cells to high-light conditions become partially constitutive in the low-light-grown dspA mutant. Other genes for which transcripts decline upon exposure of wild-type cells to high light are already lower in the mutant during growth in low light. These results suggest that DspA may influence gene expression in both a positive and a negative manner and that the dspA mutant behaves as if it were experiencing stress conditions (e.g., high-light exposure) even when maintained at near-optimal growth conditions for wild-type cells. This is discussed with respect to the importance of DspA for regulating the responses of the cell to environmental cues.

Analyzing and modeling of photobioreactors by combining first principles of physiology and hydrodynamics

Mixing in photobioreactors is known to enhance biomass productivity considerably, and flow dynamics play a significant role in the reactor's performance, as they determine the mixing and the cells' movement. In this work we focus on analyzing the effects of mixing and flow dynamics on the photobioreactor performance. Based on hydrodynamic findings from the CARPT(Computer Automated Radioactive Particle Tracking) technique, a possible mechanism for the interaction between the mixing and the physiology of photosynthesis is presented, and the effects of flow dynamics on light availability and light intensity fluctuation are discussed and quantitatively characterized. Furthermore, a dynamic modeling approach is developed for photobioreactor performance evaluation, which integrates first principles of photosynthesis, hydrodynamics, and irradiance distribution within the reactor. The results demonstrate the reliability and the possible applicability of this approach to commercially interesting microalgae/cyanobacteria culture systems.