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High-throughput FTIR-based bioprocess analysis of recombinant cyprosin production

2017-01Journal article Restricted access
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dc.contributor.authorSampaio, Pedro
dc.contributor.authorSales, Kevin C.
dc.contributor.authorRosa, Filipa O.
dc.contributor.authorB. Lopes, Marta
dc.contributor.authorCalado, Cecília
dc.date.accessioned2017-03-14T09:01:46Z
dc.date.available2017-03-14T09:01:46Z
dc.date.issued2017-01
dc.description.abstractTo increase the knowledge of the recombinant cyprosin production process in Saccharomyces cerevisiae cultures, it is relevant to implement efficient bioprocess monitoring techniques. The present work focuses on the implementation of a mid-infrared (MIR) spectroscopy-based tool for monitoring the recombinant culture in a rapid, economic, and high-throughput (using a microplate system) mode. Multivariate data analysis on the MIR spectra of culture samples was conducted. Principal component analysis (PCA) enabled capturing the general metabolic status of the yeast cells, as replicated samples appear grouped together in the score plot and groups of culture samples according to the main growth phase can be clearly distinguished. The PCA-loading vectors also revealed spectral regions, and the corresponding chemical functional groups and biomolecules that mostly contributed for the cell biomolecular fingerprint associated with the culture growth phase. These data were corroborated by the analysis of the samples' second derivative spectra. Partial least square (PLS) regression models built based on the MIR spectra showed high predictive ability for estimating the bioprocess critical variables: biomass (R (2) = 0.99, RMSEP 2.8%); cyprosin activity (R (2) = 0.98, RMSEP 3.9%); glucose (R (2) = 0.93, RMSECV 7.2%); galactose (R (2) = 0.97, RMSEP 4.6%); ethanol (R (2) = 0.97, RMSEP 5.3%); and acetate (R (2) = 0.95, RMSEP 7.0%). In conclusion, high-throughput MIR spectroscopy and multivariate data analysis were effective in identifying the main growth phases and specific cyprosin production phases along the yeast culture as well as in quantifying the critical variables of the process. This knowledge will promote future process optimization and control the recombinant cyprosin bioprocess according to Quality by Design framework.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSAMPAIO, Pedro N.; [et al] – High-throughput FTIR-based bioprocess analysis of recombinant cyprosin production. Journal of Industrial Microbiology & Biotechnology. ISSN 1367-5435. Vol. 44, N.º 1 (2017), pp. 49-61pt_PT
dc.identifier.doi10.1007/s10295-016-1865-0pt_PT
dc.identifier.issn1367-5435
dc.identifier.issn1476-5535
dc.identifier.urihttp://hdl.handle.net/10400.21/6851
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Heidelbergpt_PT
dc.relation.publisherversionhttp://download.springer.com/static/pdf/505/art%253A10.1007%252Fs10295-016-1865-0.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs10295-016-1865-0&token2=exp=1489406530~acl=%2Fstatic%2Fpdf%2F505%2Fart%25253A10.1007%25252Fs10295-016-1865-0.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252Fs10295-016-1865-0*~hmac=8c86d0f24b9ee2a29f6a8901e2e8ca98b1012089d3a28e5d701270f54b60b84bpt_PT
dc.subjectCultivationpt_PT
dc.subjectHigh-throughput analysispt_PT
dc.subjectMid-infrared spectroscopypt_PT
dc.subjectPartial least square regressionpt_PT
dc.subjectPrincipal components analysispt_PT
dc.subjectRecombinant cyprosinpt_PT
dc.titleHigh-throughput FTIR-based bioprocess analysis of recombinant cyprosin productionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage61pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage49pt_PT
oaire.citation.titleJournal of Industrial Microbiology and Biotechnologypt_PT
oaire.citation.volume44pt_PT
person.familyNameSampaio
person.familyNameB. Lopes
person.familyNameCalado
person.givenNamePedro
person.givenNameMarta
person.givenNameCecília
person.identifier1251979
person.identifier1195979
person.identifier130332
person.identifier.ciencia-idAF12-6ABA-43D8
person.identifier.ciencia-idFD16-A07F-7B12
person.identifier.ciencia-id9418-E320-3177
person.identifier.orcid0000-0003-2917-4904
person.identifier.orcid0000-0002-4135-1857
person.identifier.orcid0000-0002-5264-9755
person.identifier.ridF-5378-2011
person.identifier.ridE-2102-2014
person.identifier.scopus-author-id24178064100
person.identifier.scopus-author-id55489480400
person.identifier.scopus-author-id6603163260
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication303f3e22-ec1a-4243-9ded-98c647776e6a
relation.isAuthorOfPublication183b936b-4a1d-4c80-9405-17491abb3d64
relation.isAuthorOfPublicatione8577257-c64c-4481-9b2b-940fedb360cc
relation.isAuthorOfPublication.latestForDiscoverye8577257-c64c-4481-9b2b-940fedb360cc

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