Use of chemometrics in the selection of a <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> expression system for recombinant cyprosin B production |
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| Authors: | P N Sampaio Lisete Sousa C R C Calado M S Pais L P Fonseca |
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| Institution: | 1.Plant Systems Biology Laboratory, Center of Biodiversity, Functional and Integrative Genomics (BioFIG), Institute of Applied Science and Technology, Faculty of Sciences,University of Lisbon,Lisbon,Portugal;2.Institute of Biotechnology and Bioengineering, Chemical and Biological Engineering Center,Instituto Superior Técnico,Lisbon,Portugal;3.Department of Statistics and Operations Research, Center of Statistics and Applications (CEAUL),Faculty of Sciences of University of Lisbon,Lisbon,Portugal;4.Faculty of Engineering,Catholic University of Portugal,Rio de Mouro,Portugal |
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| Abstract: | Two multivariate statistical methods, factor analysis (FA) and hierarchical cluster analysis (HCA), were applied to experimental
data set to evaluate their usefulness in selecting the adequate expression system and optimal growth parameters for recombinant
cyprosin B production. Using FA, the large data set was reduced to two factors representing 73.4% of variability. Factor 1,
with 53.5% of variability, corresponds to recombinant cyprosin B expression and efficient secretion, while factor 2, accounting
for 19.9% of variability, represents cell growth and physiological characteristics. FA and HCA allowed the establishment of
correlations among different variables and the clusters obtained providing clear identification of the experimental parameters
related to cyprosin B production, which results on more accurate scientific output and time saving when selection of an adequate
expression system is concerned. |
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