Kinetic Modeling and Numerical Simulation as Tools to Scale Microalgae Cell Membrane Permeabilization by Means of Pulsed Electric Fields (PEF) From Lab to Pilot Plants

Sustainable algal proteins, novel extraction techniques and applications in the bakery, dairy and pharmaceutical industries: A comprehensive review

Microalgae have emerged as favorable substitutes for traditional animal-based proteins in the search for sustainable protein sources. Despite being underexplored, microalgae offer the possibility of large-scale protein production via novel extraction techniques. This review synthesizes current knowledge on microalgal proteins, shedding light on their novel extraction techniques and techno-functional properties, which are still in the early stages of exploration. Additionally, it explores the miscellaneous applications of algae proteins across various industrial sectors, including bakery, dairy, pharmaceuticals, and nutrition. By discussing the techno-functional properties of algae proteins and peptides, this review underscores their potential to revolutionize the industrial landscape while addressing sustainability challenges. As research in this field progresses, microalgae are poised to emerge as a viable and environmentally friendly protein source, offering a pathway toward a more sustainable future.

Electric stimulation: a versatile manipulation technique mediated microbial applications

Electric stimulation (ES) is a versatile technique that uses an electric field to manipulate microorganisms individually. Over the past several decades, the capabilities of ES have expanded from bioremediation to the precise motion control of cells and microorganisms. However, there is limited information on the underlying mechanisms, latest advancement and broader microbial applications of ES in various fields, such as the production of extracellular polymers with upgraded properties. This review article summarizes recent advancements in ES and discusses it as a unique external manipulation technique for microorganisms with wide applications in bioremediation, industry, biofilm deactivation, disinfection, and controlled biosynthesis. One specific application of ES discussed in this review is the extracellular biosynthesis, regulation, and organization of extracellular polymers, such as bacterial cellulose nanofibrils, curdlan, and microbial nanowires. Overall, this review aims to provide a platform for microbial biotechnologists and synthetic biologists to leverage the manipulation of microorganisms using ES for bio-based applications, including the production of extracellular polymers with enhanced properties. Researchers can engineer, manipulate, and control microorganisms for various applications by harnessing the potential of electric fields.

Biphasic lipid extraction from microalgae after PEF-treatment reduces the energy demand of the downstream process

BACKGROUND

The gradual extrusion of water-soluble intracellular components (such as proteins) from microalgae after pulsed electric field (PEF) treatment is a well-documented phenomenon. This could be utilized in biorefinery applications with lipid extraction taking place after such an 'incubation' period, i.e., a post-PEF-treatment step during which the biomass is left undisturbed before any further processing. The goal of this work was to further explore how this incubation could improve lipid extraction.

RESULTS

Experiments were conducted on wet, freshly harvested Auxenochlorella protothecoides, treated with 0.25 or 1.5 MJ/kgDW and incubated for 24 h. Lipid extraction took place with a monophasic ethanol:hexane:water, 1:0.41:0.04 vol/vol/vol mixture with a 75.6 mL solvent per 1 g of dry biomass ratio. The kinetics of the extraction were studied with samples taken between 10 and 1080 min from fresh and incubated biomass. The yields at 10 min were significantly increased with incubation compared to without (31.2% dry weight compared to 1.81%, respectively). The experimental data were fitted with the Patricelli model where extraction occurs in two steps, a rapid washing of immediate available lipids and a slower diffusion one. During Nile-Red staining of microalgae and microscopy imaging, a shift of emission from both GFP and RFP channels to mostly RFP was observed indicating an increase in the polarity of the environment of Nile-Red. These led to an adaption of a biphasic ethanol:hexane:water 1:6:0.4 vol/vol/vol solvent with 37 mL solvent per 1 g of dry biomass ratio which while ineffective on fresh biomass, achieved a 27% dry weight yield from incubated microalgae. The extraction efficiency in the biphasic route was lower compared to the monophasic (i.e., 69% and 95%, respectively). It was compensated however, by the significant solvent reduction (37 mL to 75.6 mL respectively), in particular the ethanol minimization. For the extraction of 1 L lipids, it was estimated that the energy consumption ratio for the biphasic process was 1.6 compared to 9.9 for monophasic, making clearly the most preferential one.

CONCLUSIONS

This biphasic approach significantly reduces solvent consumption and the respective energy requirement for solvent recovery. Incubation thus could majorly improve the commercialization prospects of the process.

Enhancing protein extraction from heterotrophic Auxenochlorella protothecoides microalgae through emerging cell disruption technologies combined with incubation

This study evaluated pulsed electric fields (PEF) and ultrasonication (US) combined with incubation to enhance cell disruption and protein extraction from Auxenochlorella protothecoides, comparing them to conventional high-pressure homogenization (HPH). A 5 h incubation enhanced protein yield by 79.4 % for PEF- and 27.2 % for US-treated samples. Extending the incubation to 24 h resulted in a total yield increase of 122 % for PEF (0.25 ± 0.03 kgEP kgTP-1) and 51.9 % for US (0.20 ± 0.02 kgEP-1 kgTP-1). Autofermentation in untreated cells after 24 h resulted in protein release with lower yields than all other treated and incubated samples. While HPH had the highest protein yield (0.58 ± 0.04 kgEP kgTP-1), PEF-incubation after 5 h (56.6 ± 5.3 MJ kgEP-1) and 24 h (49.5 ± 3.7 MJ kgEP-1) were 1.5 and 1.7-times more energy-efficient than HPH (82.9 ± 7.8 MJ kgEP-1). PEF combined incubation is an energy-efficient and targeted protein extraction method in heterotrophic A. protothecoides biorefinery.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications

Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which hinders the scale-up and dissemination. This article reviews contemporary research and perspectives on the application of machine learning in biohydrogen production technology. Several machine learning algorithems have recently been implemented for modeling the nonlinear and complex relationships among operational and performance parameters in biohydrogen production as well as predicting the process performance and microbial population dynamics. Reinforced machine learning methods exhibited precise state prediction and retrieved the underlying kinetics effectively. Machine-learning based prediction was also improved by using microbial sequencing data as input parameters. Further research on machine learning could be instrumental in designing a process control tool to maintain reliable hydrogen production performance and identify connection between the process performance and the microbial population.

Decay of Trichomes of Arthrospira platensis After Permeabilization Through Pulsed Electric Fields (PEFs) Causes the Release of Phycocyanin

The cyanobacterium Arthrospira platensis is a promising source of edible proteins and other highly valuable substances such as the blue pigment-protein complex phycocyanin. Pulsed electric field (PEF) technology has recently been studied as a way of permeabilizing the cell membrane, thereby enhancing the mass transfer of water-soluble cell metabolites. Unfortunately, the question of the release mechanism is not sufficiently clarified in published literature. In this study, the degree of cell permeabilization (cell disintegration index) was directly measured by means of a new method using fluorescent dye propidium iodide (PI). The method allows for conclusions to be drawn about the effects of treatment time, electric field strength, and treatment temperature. Using a self-developed algorithm for image segmentation, disintegration of trichomes was observed over a period of 3 h. This revealed a direct correlation between cell disintegration index and decay of trichomes. This decay, in turn, could be brought into a direct temporal relationship with the release of phycocyanin. For the first time, this study reveals the relationship between permeabilization and the kinetics of particle decay and phycocyanin extraction, thus contributing to a deeper understanding of the release of cell metabolites in response to PEF. The results will facilitate the design of downstream processes to produce sustainable products from Arthrospira platensis.

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.