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Industrialisation of platform chemical production from waste biomass using diverse yeast strains (WALDRON_F17ICASE1)

Lead Research Organisation: University of East Anglia
Department Name: Graduate Office

Abstract

Yeasts and biorefinery processes are intimately linked. The Institute of Food Research hosts both the Biorefinery Centre and the NCYC which, along with the UEA make the NRP uniquely placed to carry out cutting edge research in this area. The biorefinery has a track record of developing approaches to maximise the exploitation of agri-food chain biomass through the disassembly of plant structures using physical, biochemical and chemical routes. The NCYC's unique collection of over 4000 yeast strains covers a large biodiversity which is currently virtually untapped. The recent genome sequencing of around 900 NCYC strains gives us the unique opportunity to screen these strains for bio-industrially important traits and link those to the genetic variation within the collection. The student will work with both varied yeast strains and also real world waste biomass in order to ascertain the best pre-treatments, fermentation processes and yeast strains for a given product. The metabolomics pathways will then be extrapolated and trait information established from the genomic datasets. This research will involve collaboration with an industrial biorefining partner Vireol with which the student will work throughout the project.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M011216/1 30/09/2015 31/03/2024
1941449 Studentship BB/M011216/1 30/09/2017 31/12/2021 Joseph Shepherd
NE/W503034/1 31/03/2021 30/03/2022
1941449 Studentship NE/W503034/1 30/09/2017 31/12/2021 Joseph Shepherd
 
Description Models to predict the phenotype of a yeast strain based on 60,000 specific gene locations (Single Nucleotide Polymorphisms, SNPs) that are variable within the population.
Exploitation Route Used by industry to pre-screen a library of strains to identify those most likely to produce the desired phenotype (production of specific metabolites).
Sectors Agriculture

Food and Drink

Chemicals

Healthcare

Manufacturing

including Industrial Biotechology

 
Title Electron Transfer Miner (ETMiner)- Build cytochrome operon predictions 
Description The software, fully coded by myself, creates predicted cytochrome operons based on whole genome sequence (WGS) coding sequence DNA (CDS) from RefSeq. It is good for finding novel operons in species previously not known to have any cytochromes. 
Type Of Technology Software 
Year Produced 2021 
Impact Learned app making, GUI creation and how to integrate many disparate coding elements from BLAST to graph visualisation software.