Development of a combined mathematical and experimental approach for the design, evaluation and optimization of algae based bio-refinery processes

Lead Research Organisation: UNIVERSITY COLLEGE LONDON
Department Name: Biochemical Engineering

Abstract

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Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509577/1 30/09/2016 24/03/2022
1807432 Studentship EP/N509577/1 30/09/2016 25/12/2020 Lukmaan Kolia
 
Description Microalgae are photosynthetic organisms which are increasingly being used in bioprocessing. Light is required for photosynthesis, and in the case of Chlamydomonas reinhardtii, the colour of light used for growth has an effect on the organism's behaviour. C. reinhardtii divides by multiple fission: each mother cell can divide into 2, 4, 8, or 16 daughter cells depending on the size achieved by the mother cell.

Earlier literature shows that blue light inhibits cell division, whereas red light lifts this inhibition. Literature has already shown that blue light will result in larger mother cells which result in a larger number of daughter cells per cell cycle. However, combining this knowledge into a bioprocessing optimisation framework was missing.

Experimental results from this award have shown that by using an informed light colour switching mechanism at the appropriate time during the cell cycle, C. reinhardtii cells under blue light can be forced to grow larger than they normally would before initiating division. This is then followed by a period of red light to reduce the time delay in initiating division due to division inhibition from blue light. The result is a net increase in productivity compared to plain light conditions (control conditions).

The award also aimed to develop a mathematical model which would inform exact light switching timepoints. This is still in development and should be completed during the Completing Research Status (CRS) period.
Exploitation Route Industrial bio-processing companies making use of green microalgae could use the findings to inform their process optimisation strategies.
Sectors Manufacturing

including Industrial Biotechology