FSE PhD President's Doctoral Scholarship: Phase-optimised PUFA Production in Oleaginous Yeast via Transcriptomics-Guided Enzyme-Constrained Metabolic Modelling

The University of Manchester; Manchester; On-site; GBP 20,000 - 24,000; Full time

Job summary

The University of Manchester invites applications for a four-year PhD studentship funded in part by UKRI. The successful candidate will receive an annual stipend at the UKRI minimum rate (£21,805) plus £1,000 per year enhancement, and a research training support grant of up to £20,000 for the full four-year programme.

The project will investigate empirical reaction-specific translation efficiency operators within phase-specific GSMMs to predict production efficiency in oleaginous yeasts and

Responsibilities

• Estimate mRNA expression levels required to achieve desired increases in reaction capacity.
• Categorise transcriptionally versus translationally bottlenecked genes under nitrogen limitation.
• Deliver predictive models of PUFA production efficiency across selected oleaginous yeasts.

Job description

This4-yearPhDstudentshipisopentobothHome(UK)andinternationalapplicants.Thesuccessfulcandidatewillreceive an annualstipendattheUKRIminimumrate(currently£21,805peryear)plus£1,000/annumenhancement,andaresearchtrainingsupportgrantofupto£20,000forthefull4-yearprogramme. This project is in competition for funding with other projects. Usually, the projects that receives the best applicants will be successful.

Wehypothesisethatdefiningempiricalreaction-specifictranslationalefficiencyoperators(TE=[E]/mRNA)withinphase-specificecGSMMswillenableresource-balancedcassettedesignandallowinferenceofenzymeabundancesfromRNA-seqdataaloneinsubsequentiterations.Combinedwithgenomicinformationandgenome-scalemodelling,thisframeworkwillpredictproductionefficiencyandidentifyphase-optimisedtargets.

Theprojectwill:

• EstimatethemRNAexpressionlevelsrequiredtoachievedesiredincreasesinreactioncapacity.
• Categorisetranscriptionallyversustranslationallybottleneckedgenesundernitrogenlimitation.
• DeliverpredictivemodelsofPUFAproductionefficiencyacrossselectedoleaginousyeasts.

Methodology(DBTL)

Design&Build

Round1:Curatealibraryofnativephase-responsivepromotersfromselectedoleaginousyeasts(examplesinclude Yarrowialipolytica, Rhodotorulatoruloides or Lipomycesstarkeyi).CharacterisepromoterkineticsusingRNAlight-upaptamers.Subsequentroundswilldesignphase-specificexpressioncassettesinformedbymodellingoutputsandassemblethemusingmodularcloningtoolkitsappropriatetothechosenhost(s).

Test

Performcontrolledfermentationsunderexponentialandnitrogen-limitedconditions.Measureprocesskinetics,lipidtitres(GC-MS),phase-resolvedRNA-seqandLC-MSproteomicstocalibrateTEoperators.LaterroundswillrelyprimarilyonRNA-seqandprocessdata.Genomicdata(genomesequences,annotationsandcomparativeanalyses)willsupportmodelconstructionandstrainselection.

Learn

Applyenzyme-constrainedfluxscanningbasedonenforcedobjectiveflux(ecFSEOF)andkineticfluxcontrolcoefficientanalysisonprotein-constrainedGSMMstoidentifysystemicpathwaydemandsandkineticbottlenecks.Verifyproteinheadroomforoverexpression.Insubsequentiterations,inferenzymestatesfromTEoperatorsandnewRNA-seqdata,rankrate-limitingconstraintsviadualvariables,andupdatemodelstoguidefurtherengineering.Genome-scalemodelswillexplicitlypredictproductionefficiency(titre,yieldandrate)underdifferentgeneticandprocessscenarios

£21,805 plus £1,000 per annum enhancement