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Modelling the behaviour of virus-infected killer yeasts for biotech applications

last modified May 02, 2019 05:31 PM
Dr Duygu Dikicioglu’s paper on “Dynamic modelling of the killing mechanism of action by virus-infected yeasts” featured in the Journal of the Royal Society Interface
Modelling the behaviour of virus-infected killer yeasts for biotech applications

Modelling toxicity levels of virus-infected yeasts

Dr Duygu Dikicioglu’s paper on “Dynamic modelling of the killing mechanism of action by virus-infected yeasts” recently published by the Royal Society has been featured in the latest issue of the Journal of the Royal Society Interface newsletter.

Dr Dikicioglu is a Leverhulme Trust Early Career Research Fellow at CEB. Her research interests lie in understanding cellular mechanisms by formal models and exploiting this knowledge for different types of biotechnological applications. Within this domain, she is interested in the optimisation and improvement of upstream bioprocessing using predictive models, modelling and control of biotechnological processes involving multiple-species co-cultures, and systems-level analysis of disease mechanisms and identification of potential targets for intervention.

Her ground-breaking study is focused on modelling the behaviour of virus-infected killer yeasts and their toxic activity to gain insights into their role in the fermentation process and help develop relevant and effective biotechnological applications.

Organisms produce and secrete toxins to drive out competition by other species. Killer yeasts, through a viral infection, gain this ability, and their toxins are even able to kill sensitive members of their own species. Possessing a killer characteristic is beneficial due to this antifungal/antimicrobial activity in biotechnological applications, but killing their own kind can “wipe out” starter cultures in large-scale processes, and also result in “stuck” fermentations. This work provides mechanistic insights into the dynamics of the balance between the killer and the sensitive sub-populations of the same species via the construction and exploitation of mathematical models.

Dr Dikicioglu commented: “These models provide us with a useful platform to offer insight into the mechanisms and suitability of each toxin pathway for managing starter cultures in biotechnological applications. They allow us to predict optimal ratios of killer and sensitive yeast cells, and propose control actions to maintain these optimal ratios. These will assist building resilient and productive starter cultures of mixed fungal and yeast species for different biotechnological applications.”

See full article here. 

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