PhD Project Summary:
Perturbance of microbial communities can lead to loss or over-abundance (blooms) of individual strains with devastating consequences for natural ecosystems, industrial bioproduction or wastewater treatment. Why do small changes in growth rates of individual strains sometimes spiral out of control? Mathematical models to predict such events are essential for developing warning systems and mitigation strategies. However, experimental model testing is challenging, relying either on artificially adding or removing individual strains or substances in the growth media. This project exploits the fact that microalgae (including cyanobacteria) are differentially adapted to certain light qualities. Wavelength spectra differ with water depth, salinity and shading, and depending on their habitat strains have evolved different photoreceptors and pigments. Applying different wavelength spectra using novel LED technology (‘rainbow’ photobioreactors) therefore provides a non-invasive strategy to reversibly favour one or another strain for a short period of time.
The aim of this project is to develop advanced models for predicting the composition and development of microbial communities after short periods of growth dis-equilibrium. Cultures will be subjected to dynamic wavelength regimes and growth of known individual strains will be DNA-tracked. The data will feed mathematical modelling. This project offers training in molecular biology, biotechnology and mathematical modelling.
For more information: https://www.findaphd.com/phds/project/using-wavelength-manipulations-to-test-and-optimise-mathematical-models-predicting-strain-collapse-and-blooms-in-microbial-communities/?p133944