Open AccessEvaluating online sampling probes for substrate concentration and protein production by a Design of Experiments screening approach
Author(s) -
Spadiut Oliver,
Dietzsch Christian,
Posch Andreas,
Herwig Christoph
Publication year - 2012
Publication title -
engineering in life sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 57
eISSN - 1618-2863
pISSN - 1618-0240
DOI - 10.1002/elsc.201100228
Subject(s) - sampling (signal processing) , pichia pastoris , biological system , substrate (aquarium) , computer science , transformation (genetics) , exponential function , design of experiments , process engineering , analytical chemistry (journal) , chemistry , biochemical engineering , engineering , statistics , mathematics , chromatography , filter (signal processing) , recombinant dna , biochemistry , biology , ecology , computer vision , mathematical analysis , gene
A polypropylene sampling probe and ceramic sampling probe were tested for the online measurement of substrate and protein concentrations in fed batch cultivations of a recombinant Pichia pastoris strain overexpressing the enzyme HRP. Although small substrate molecules could be determined precisely under process conditions, online and offline data for enzyme activity and protein content showed offsets for both sampling probes. An easy‐to‐do multivariate Design of Experiments ( DoE ) screening approach revealed the limitations for both sampling probes. Online and offline determined data for enzymatic activity were fitted to a suitable exponential equation. A direct correlation of these equations showed a linear relation between online and offline data for the polypropylene probe and a quadratic relation for the ceramic probe. Using the resulting formulas, observed offsets could be compensated for by mathematical transformation, which consequently could allow the use of online calculator tools to determine the enzymatic activity and the protein content in quasi real‐time. This study demonstrates the usefulness of a DoE approach to evaluate online sampling probes in a short time and introduces a strategy to obtain data with two different online sampling probes also for large target molecules despite observed offsets.