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dc.contributor.advisorGardner, Paul
dc.contributor.advisorLim, Chun Shen
dc.contributor.authorBhandari, Bikash Kumar
dc.date.available2021-11-04T01:05:25Z
dc.date.copyright2021
dc.identifier.citationBhandari, B. K. (2021). Computational tools for improving recombinant protein production (Thesis, Doctor of Philosophy). University of Otago. Retrieved from http://hdl.handle.net/10523/12416en
dc.identifier.urihttp://hdl.handle.net/10523/12416
dc.description.abstractRecombinant protein production is a cornerstone of modern biotechnology and has been utilised to produce many proteins of scientific and commercial interest. The optimality of result is dependent on the balances among the involved intricate stochastic processes. In particular, two of the critical processes are protein expression and solubility. Collectively, the failures at these two steps drop down the success rate of protein production to around 25%. Furthermore, toxicity of recombinant proteins may also significantly reduce the amount of protein produced. Therefore, prediction and optimisation of expression, solubility and an early detection of these toxic proteins could save resources and assist in better planning of the experiment. In this work, we show that mRNA accessibility, measured through the opening energy, and protein structural flexibility, measured by using the normalised B-factors, can describe protein expression and solubility respectively with a higher accuracy than other features. We also develop a new and more accurate protein solubility predicting metric called the Solubility-Weighted Index (SWI). Using these findings, we develop a gene expression prediction and optimisation tool: Translation Initiation coding region designer (TIsigner), available at https://tisigner.com/tisigner and protein solubility prediction and optimisation tool: Soluble Domain of Protein Expression (SoDoPE), available at https://tisigner.com/sodope. We also developed a third tool, Razor https://tisigner.com/razor, for the detection of toxins. To assist in maximising protein production, we also develop a pipeline for optimising protein expression, solubility and toxin detection by integrating these three tools.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Otago
dc.rightsAll items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectexpression
dc.subjectsolubility
dc.subjectproteins
dc.subjectmRNA
dc.subjectSignal peptide
dc.subjectRecombinant protein
dc.subjectmathematical optimisation
dc.titleComputational tools for improving recombinant protein production
dc.typeThesis
dc.date.updated2021-11-03T23:21:13Z
dc.language.rfc3066en
thesis.degree.disciplineBiochemistry
thesis.degree.nameDoctor of Philosophy
thesis.degree.grantorUniversity of Otago
thesis.degree.levelDoctoral
otago.openaccessOpen
otago.evidence.presentYes
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