A mathematical model of intracellular behavior of microalgae for predicting growth and intracellular components syntheses under nutrient‐replete and ‐deplete conditions

Selecting a preculture strategy for improving biomass and astaxanthin productivity of Chromochloris zofingiensis

Chromochloris zofingiensis is a potential source of natural astaxanthin; however, its rapid growth and astaxanthin enrichment cannot be achieved simultaneously. This study established autotrophic, mixotrophic, and heterotrophic preculture patterns to assess their ameliorative effect on the C. zofingiensis heterotrophic growth state. In comparison, mixotrophic preculture (MP) exhibited the best improving effect on heterotrophic biomass concentration of C. zofingiensis (up to 121.5 g L-1) in a 20 L fermenter, reaching the global leading level. The astaxanthin productivity achieved 111 mg L-1 day-1, 7.4-fold higher than the best record. The transcriptome and 13C tracer-based metabolic flux analysis were used for mechanism inquiry. The results revealed that MP promoted carotenoid and lipid synthesis, and supported synthesis preference of low unsaturated fatty acids represented by C18:1 and C16:0. The MP group maintained the best astaxanthin productivity via mastering the balance between increasing glucose metabolism and inhibition of carotenoid synthesis. The MP strategy optimized the physiological state of C. zofingiensis and realized its heterotrophic high-density growth for an excellent astaxanthin yield on a pilot scale. This strategy exhibits great application potential in the microalgae-related industry. KEY POINTS: • Preculture strategies changed carbon flux and gene expression in C. zofingiensis • C. zofingiensis realized a high-density culture with MP and fed-batch culture (FBC) • Astaxanthin productivity achieved 0.111 g L-1 day-1 with MP and FBC.

A robust multinutrient kinetic model for enhanced lutein and biomass yields in mixotrophic microalgae cultivation: A step towards successful large-scale productions

Mixotrophic cultivation holds great promise to significantly enhance the productivities of biomass and valuable metabolites from microalgae. In this study, a new kinetic model is developed, explicitly describing the effect of the most influential environmental factors on both biomass growth and the production of the high-value product lutein. This extensive study of multinutrient kinetics for Tetradesmus obliquus in a mixotrophic regime covers various nutritional conditions. Crucial nutrients governing the model include nitrate, phosphate, and glucose. Using seven state variables and 13 unknown parameters, the model's accuracy was ensured through a well-designed two-factor, four-level experimental setup, providing ample data for reliable calibration and validation. Results accurately predict dynamic concentration profiles for all validation experiments, revealing broad applicability. Optimizing nitrogen availability led to significant increases in biomass (up to fourfold) and lutein production (up to 12-fold), with observed maximum biomass concentration of 6.80 g L-1 and lutein reaching 25.58 mg L-1. Noticeably, the model exhibits a maximum specific growth rate of 4.03 day-1, surpassing reported values for photoautotrophic and heterotrophic conditions, suggesting synergistic effects. Valuable guidance is provided for applying the method to various microalgal species and results are large-scale production-ready. Future work will exploit these results to develop real-time photobioreactor operation strategies.

A reliable multi-nutrient model for the rapid production of high-density microalgal biomass over a broad spectrum of mixotrophic conditions

The superior microalgal biomass productivities obtained under mixotrophic conditions have been widely demonstrated. However, to attain the full potential of the method, optimal conditions for biomass production and resource utilization need to be determined and successfully exploited throughout the process operation. Detailed kinetic mathematical models have often proved most efficient tools for predicting process behavior and governing its overall operation. This paper presents an extensive study for obtaining a highly reliable model for mixotrophic production of microalgae covering a wide set and range of nutritional conditions (10-fold the concentration range of Bold's Basal Medium) and biomass yields up to 6.68 g.L^-1 after only 6 days. The final reduced model includes a total of five state variables and nine parameters: model calibration resulted in very small 95% confidence intervals and relative errors below 5% for all parameters. Model validation showed high reliability with R² correlation values between 0.77 and 0.99.

Altering autotrophic carbon metabolism of Nitzschia closterium to mixotrophic mode for high-value product improvement

An adaptive laboratory evolution (ALE) strategy was designed to evolve autotrophic Nitzschia closterium to mixotrophic growth for high productivity of essential amino acid (EAA), eicosapentaenoic acid (EPA) and fucoxanthin. The N. closterium growth was limited under glucose initially, but a red light emitting diode was innovatively applied to modify carbon metabolism and obtain mixotrophic strain of N. closterium GM. The N. closterium GM biomass concentration was improved by 65.07% comparing with wild type, but exhibited weak photosynthesis and strong glucose metabolism. At carbon metabolism levels, ALE promoted NADPH oxidase activity and induced protein degradation to lipid biosynthesis by elevating acetyl-CoA and pyruvate contents. It also improved carbon flux to TCA cycle, and elevated contents of glucose-6-phosphate, fructose-6-phosphate, glyceraldehyde-3-phosphate for providing sufficient ATP and NADPH. Productivities of EPA, EAA and fucoxanthin were increased by 41.0%, 18.8% and 20.4%, respectively. This ALE strategy was promising in microalgal production of high-value products.

Photosynthetic Carbon Uptake Correlates with Cell Protein Content during Lipid Accumulation in the Microalga Chlorella vulgaris NIES 227

Large-scale microalgae cultivation for biofuel production is currently limited by the possibility of maintaining high microalgae yield and high lipid content, concomitantly. In this study, the physiological changes of Chlorella vulgaris NIES 227 during lipid accumulation under nutrient limitation was monitored in parallel with the photosynthetic capacity of the microalgae to fix carbon from the proxy of oxygen productivity. In the exponential growth phase, as the biomass composition did not vary significantly (approx. 53.6 ± 7.8% protein, 6.64 ± 3.73% total lipids, and 26.0 ± 9.2% total carbohydrates of the total biomass dry-weight), the growth capacity of the microalgae was preserved (with net O2 productivity remaining above (4.44 ± 0.93) × 10−7 g O2·µmol PAR−1). Under nutrient limitation, protein content decreased (minimum of approx. 18.6 ± 6.0%), and lipid content increased (lipid content up to 56.0 ± 0.8%). The physiological change of the microalgae was associated with a loss of photosynthetic activity, down to a minimum (1.27 ± 0.26) × 10−7 g O2·µmol PAR−1. The decrease in photosynthetic O2 productivity was evidenced to correlate to the cell internal-protein content (R2 = 0.632, p = 2.04 × 10−6, N = 25). This approach could serve to develop productivity models, with the aim of optimizing industrial processes.

Optimization of the phototrophic Cyanobacteria polyhydroxybutyrate (PHB) production by kinetic model simulation

Cyanobacteria can grow using inorganic substrates, such as CO₂ from industrial sources and nutrients from wastewaters, and therefore are promising microorganisms to produce polyhydroxybutyrate in a cleaner circular context. However, this biotechnological production is highly challenging because it involves different interlinked reactions that are affected by environmental conditions, which hinders process optimization. In this study a new biokinetic mechanistic model using novel experimental approaches was developed to optimize polyhydroxybutyrate (PHB) and glycogen production. The model includes, for the first time, the production of glycogen and its conversion into PHB, which has been found as the main pathway to produce PHB. Model was successfully (r²: 0.6-0.99) calibrated and validated with experimental data from photobioreactors inoculated with Synechocystis sp. The developed model was used to determine suitable initial conditions for a lab scale batch reactor (6.4 mgN·L^-1 and 2 mgP·L^-1) and a new configuration for the continuous industrial production of PHB was proposed and optimized using this tool. The maximum productivity (5.1 mgPHB·L^-1·d^-1) and the optimal configuration and operation of the serial reactors to produce PHB in an industrial scale was achieved using a hydraulic retention time of 4 days in the growth reactor. Then, this reactor daily fed 20 batch accumulation reactors, which were discharged after 20 days. The optimal influent nutrients concentrations for this configuration was found to be 50 mgN·L^-1 and 10 mgP·L^-1. Results found in this study show the necessity to optimize biopolymers production with Cyanobacteria considering environmental conditions, and demonstrated the potential of this model as a tool to increase PHB productivity.

Coordinating Carbon Metabolism and Cell Cycle of Chlamydomonasreinhardtii with Light Strategies under Nitrogen Recovery

Nutrient supplementation is common in microalgae cultivation to enhance the accumulation of biomass and biofunctional products, while the recovery mechanism from nutrient starvation is less investigated. In this study, the influence of remodeled carbon metabolism on cell cycle progression was explored by using different light wavelengths under N-repletion and N-recovery. The results suggested that blue light enhanced cell enlargement and red light promoted cell division under N-repletion. On the contrary, blue light promoted cell division by stimulating cell cycle progression under N-recovery. This interesting phenomenon was ascribed to different carbon metabolisms under N-repletion and N-recovery. Blue light promoted the recovery of photosystem II and redirected carbon skeletons into proteins under N-recovery, which potentially accelerated cell recovery and cell cycle progression. Although red light also facilitated the recovery of photosystem II, it mitigated the degradation of polysaccharide and then arrested almost all the cells in the G1 phase. By converting light wavelengths at the 12 h of N-recovery with blue light, red and white lights were proved to increase biomass concentration better than continuous blue light. These results revealed different mechanisms of cell metabolism of Chlamydomonas reinhardtii during N-recovery and could be applied to enhance cell vitality of microalgae from nutrient starvation and boost biomass production.

Cultivation processes to select microorganisms with high accumulation ability

The microbial ability to accumulate biomolecules is fundamental for different biotechnological applications aiming at the production of biofuels, food and bioplastics. However, high accumulation is a selective advantage only under certain stressful conditions, such as nutrient depletion, characterized by lower growth rate. Conventional bioprocesses maintain an optimal and stable environment for large part of the cultivation, that doesn't reward cells for their accumulation ability, raising the risk of selection of contaminant strains with higher growth rate, but lower accumulation of products. Here in this work the physiological responses of different microorganisms (microalgae, bacteria, yeasts) under N-starvation and energy starvation are reviewed, with the aim to furnish relevant insights exploitable to develop tailored bioprocesses to select specific strains for their higher accumulation ability. Microorganism responses to starvation are reviewed focusing on cell cycle, biomass production and variations in biochemical composition. Then, the work describes different innovative bioprocess configurations exploiting uncoupled nutrient feeding strategies (feast-famine), tailored to maintain a selective pressure to reward the strains with higher accumulation ability in mixed microbial populations. Finally, the main models developed in recent studies to describe and predict microbial growth and intracellular accumulation upon N-starvation and feast-famine conditions have been reviewed.

Models of microalgal cultivation for added-value products - A review

Microalgae are considered a promising feedstock for biorefineries given that their chemical composition - rich in carbohydrate and lipid - can be directed towards the co-production of various value-added fuels and chemicals. Production of microalgal biomass for biorefinery purposes requires the identification and establishment of optimal cultivation systems, a crucial yet complicated task due to the numerous factors (e.g. media composition, light, temperature) that simultaneously regulate biomass growth and intracellular composition. Modelling these biological processes, taking into account a single or multiple growth-limiting factors, offers a valuable tool to simulate, design and optimise the dynamics of microalgae cultivation. This review provides an overview of existing models developed to describe microalgal growth processes at the macroscopic scale (also termed black-box models) and discusses their formulation in detail. The black-box kinetic modelling frameworks are compiled into single-factor (6 formulations) and multiple-factor (32 formulations - further divided into non-interactive, additive, and interactive) growth kinetic models, as reported in more than 80 studies, for the prediction of biomass growth as a function of major operational factors such as media composition (e.g. nutrient concentration) and environmental factors (e.g. transient light and temperature). In addition, the review focuses on those models that further account for the production dynamics of two microalgal intracellular products with renowned potential as biorefinery substrates: carbohydrate and lipid molecules. Models of microalgal cultivation dynamics offer a robust engineering tool to understand the natural yet complex responses of microalgae to their growing environment and can help - if used appropriately - to optimise microalgae cultivation and increase the economic viability and sustainability of microalgal systems.

Combining model structure identification and hybrid modelling for photo-production process predictive simulation and optimisation

Integrating physical knowledge and machine learning is a critical aspect of developing industrially focused digital twins for monitoring, optimisation, and design of microalgal and cyanobacterial photo-production processes. However, identifying the correct model structure to quantify the complex biological mechanism poses a severe challenge for the construction of kinetic models, while the lack of data due to the time-consuming experiments greatly impedes applications of most data-driven models. This study proposes the use of an innovative hybrid modelling approach that consists of a simple kinetic model to govern the overall process dynamic trajectory and a data-driven model to estimate mismatch between the kinetic equations and the real process. An advanced automatic model structure identification strategy is adopted to simultaneously identify the most physically probable kinetic model structure and minimum number of data-driven model parameters that can accurately represent multiple data sets over a broad spectrum of process operating conditions. Through this hybrid modelling and automatic structure identification framework, a highly accurate mathematical model was constructed to simulate and optimise an algal lutein production process. Performance of this hybrid model for long-term predictive modelling, optimisation, and online self-calibration is demonstrated and thoroughly discussed, indicating its significant potential for future industrial application.

The assimilation of glycerol into lipid acyl chains and associated carbon backbones of Nannochloropsis salina varies under nitrogen replete and deplete conditions

Mixotrophic cultivation can increase microalgae productivity, yet the associated lipid metabolism remains mostly unknown. Stable isotope labeling was used to track assimilation of glycerol into the triacylglyceride (TAG) and membrane lipids of Nannochloropsis salina. In N-replete media, glycerol uptake and ¹³ C incorporation into acyl chains were, respectively, 6-fold and 12-fold higher than in N-deplete conditions. In N-replete cultures, 42% of the carbon in the consumed glycerol was assimilated into lipid acyl chains, mostly in membrane lipids rather than TAG. In N-deplete cultures, only 11% of the limited amount of consumed glycerol was fixed into lipid acyl chains. Labeled lipid-associated glycerol backbones were predominantly ¹³ C₃ labeled, suggesting that intact glycerol molecules were directly esterified with fatty acids/polar head groups. However, the presence of singly and doubly labeled lipid-bound glycerol species suggested that some glycerol also went through the central carbon metabolism before forming glycerol-3-phosphate destined for lipid esterification. ¹³ C incorporation was higher in the saturated and monounsaturated than the polyunsaturated acyl chains of TAG, indicating the flux of carbon from glycerol went first to de novo fatty acid synthesis before acyl editing reactions. The results demonstrate that nitrogen availability influences both glycerol consumption and utilization for lipid synthesis in Nannochloropsis, providing novel insights for developing mixotrophic cultivation strategies.

Boost carbon availability and value in algal cell for economic deployment of biomass

This study elucidated storage carbon metabolism in a dynamic manner through kinetic model, metabolomics and stable metabolic flux analysis. Results revealed nutrient uptake rate, carbon availability and synthetic path rate accounted for the integration of process-compatible products. The uptake rate could be enhanced by promoting carbohydrate accumulation, inducing high performance of tricarboxylic acid cycle and anaplerotic routes. Values of specific rate for lipid from kinetic model and synthetic path rate from metabolic flux analysis revealed that conversion of carbon sinks occupied a key position in increasing productivities of lipid and astaxanthin to 302.34 and 1.83 mg g^-1 d^-1, respectively. Additionally, economic estimation was applied to link cultivation factors with market scenario and demonstrated that regulating such carbon metabolism raised 30% increase of biomass value. This study therefore provided a new orientation to boost carbon efficiency that helped to engineer carbon flux from carbon source to targeted products precisely and rapidly.