Evaluation of the Potential of Lipid-Extracted Chlorella vulgaris Residue for Yarrowia lipolytica Growth at Different pH Levels.

Projections show that the cultivation of microalgae will extend to the production of bio-based compounds, such as biofuels, cosmetics, and medicines. This will generate co-products or residues that will need to be valorized to reduce the environmental impact and the cost of the process. This study explored the ability of lipid-extracted Chlorella vulgaris residue as a sole carbon and nitrogen source for growing oleaginous yeasts without any pretreatment. Both wild-type Yarrowia lipolytica W29 and mutant JMY3501 (which was designed to accumulate more lipids without their remobilization or degradation) showed a similar growth rate of 0.28 h-1 at different pH levels (3.5, 5.5, and 7.5). However, the W29 cell growth had the best cell number on microalgal residue at a pH of 7.5, while three times fewer cells were produced at all pH levels when JMY3501 was grown on microalgal residue. The JMY3501 growth curves were similar at pH 3.5, 5.5, and 7.5, while the fatty-acid composition differed significantly, with an accumulation of α-linolenic acid on microalgal residue at a pH of 7.5. Our results demonstrate the potential valorization of Chlorella vulgaris residue for Yarrowia lipolytica growth and the positive effect of a pH of 7.5 on the fatty acid profile.

Microbial co-culturing strategies for fructo-oligosaccharide production.

Fructo-oligosaccharide (FOS) mixtures produced by fermentation contain large amounts of non-prebiotic sugars. Here we propose a mixed culture of Aureobasidium pullulans and Saccharomyces cerevisiae cells to produce FOS and consume the small saccharides simultaneously, thereby increasing FOS purity in the mixture. The use of immobilised A. pullulans in co-culture with encapsulated S. cerevisiae, inoculated after 10 h fermentation, enhanced FOS production in a 5 L bioreactor. Using this strategy, a maximal FOS concentration of 119 g L-1, and yield of 0.59 gFOS gsucrose-1, were obtained after 20 h fermentation, increasing FOS productivity from about 4.9 to 5.9 gFOS L-1 h-1 compared to a control fermentation of immobilized A. pullulans in monoculture. In addition, the encapsulated S. cerevisiae cells were able to decrease the glucose in the medium to about 7.6% (w/w) after 63 h fermentation. This provided a final fermentation mixture with 2.0% (w/w) sucrose and a FOS purity of over 67.0% (w/w). Moreover, a concentration of up to 58.0 g L-1 of ethanol was obtained through the enzymatic transformation of glucose. The resulting pre-purified FOS mixture could improve the separation and purification of FOS in downstream treatments, such as simulated moving bed chromatography.

Macroscopic Dynamic Modeling of Sequential Batch Cultures of Hybridoma Cells: An Experimental Validation.

Hybridoma cells are commonly grown for the production of monoclonal antibodies (MAb). For monitoring and control purposes of the bioreactors, dynamic models of the cultures are required. However these models are difficult to infer from the usually limited amount of available experimental data and do not focus on target protein production optimization. This paper explores an experimental case study where hybridoma cells are grown in a sequential batch reactor. The simplest macroscopic reaction scheme translating the data is first derived using a maximum likelihood principal component analysis. Subsequently, nonlinear least-squares estimation is used to determine the kinetic laws. The resulting dynamic model reproduces quite satisfactorily the experimental data, as evidenced in direct and cross-validation tests. Furthermore, model predictions can also be used to predict optimal medium renewal time and composition.

Parameter identification of a dynamic model of CHO cell cultures: an experimental case study.

In this paper, we address the problem of parameter identification in dynamic models of animal cultures, and we propose a step-by-step procedure, which gradually considers more detailed models. This procedure allows subsets of parameters to be estimated at each step, which can be used in the initialization of the next identification step. Finally, the full parameter set can be re-estimated starting from the results of the last step. The efficiency of the procedure is illustrated with a simulation case study and with the identification of a dynamic model from experimental data collected in CHO cell culture.

Parameter identification of Droop model: an experimental case study.

Mathematical modeling and the development of predictive dynamic models are of paramount importance for the optimization, state estimation, and control of bioprocesses. This study is dedicated to the identification of a simple model of microalgae growth under substrate limitation, i.e., Droop model, and describes the design and instrumentation of a lab-scale flat-plate photobioreactor, the associated on-line and off-line instrumentation, the collection of experimental data, and the parameter identification procedure. In particular, a dedicated methodology for parameter identification is discussed, including the determination of an initial parameter set using an analytical procedure, the selection of a cost function, the evaluation of confidence intervals as well as direct and cross-validation tests.

Design and test of a low-cost RGB sensor for online measurement of microalgae concentration within a photo-bioreactor.

In this study, a low-cost RGB sensor is developed to measure online the microalgae concentration within a photo-bioreactor. Two commercially available devices, i.e., a spectrophotometer for offline measurements and an immersed probe for online measurements, are used for calibration and comparison purposes. Furthermore, the potential of such a sensor for estimating other variables is illustrated with the design of an extended Luenberger observer.

Highly efficient, long life, reusable and robust photosynthetic hybrid core-shell beads for the sustainable production of high value compounds.

An efficient one-step process to synthesize highly porous (Ca-alginate-SiO2-polycation) shell: (Na-alginate-SiO2) core hybrid beads for cell encapsulation, yielding a reusable long-life photosynthetically active material for a sustainable manufacture of high-value metabolites is presented. Bead formation is based on crosslinking of an alginate biopolymer and mineralisation of silicic acid in combination with a coacervation process between a polycation and the silica sol, forming a semi-permeable external membrane. The excellent mechanical strength and durability of the monodispersed beads and the control of their porosity and textural properties is achieved by tailoring the silica and alginate loading, polycation concentration and incubation time during coacervation. This process has led to the formation of a remarkably robust hybrid material that confers exceptional protection to live cells against sheer stresses and contamination in a diverse range of applications. Dunaliella tertiolecta encapsulated within this hybrid core-shell system display high photosynthetic activity over a long duration (>1 year). This sustainable biotechnology could find use in high value chemical harvests and biofuel cells to photosynthetic solar cells (energy transformation, electricity production, water splitting technologies). Furthermore the material can be engineered into various forms from spheres to variable thickness films, broadening its potential applications.