Open AccessFramework for Kriging‐based iterative experimental analysis and design: Optimization of secretory protein production in Corynebacterium glutamicum
Author(s) -
Freier Lars,
Hemmerich Johannes,
Schöler Katja,
Wiechert Wolfgang,
Oldiges Marco,
Lieres Eric
Publication year - 2016
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.201500171
Subject(s) - bioprocess , corynebacterium glutamicum , kriging , biochemical engineering , design of experiments , factorial experiment , computer science , bioprocess engineering , biological system , microbiology and biotechnology , mathematical optimization , engineering , chemistry , mathematics , biology , biochemistry , machine learning , chemical engineering , statistics , gene
The production of bulk enzymes used in food industry or organic chemistry constitutes an important part of industrial biotechnology. The development of production processes for novel proteins comprises a variety of biological engineering and bioprocess reaction engineering factors. The combinatorial explosion of these factors can be effectively countered by combining high‐throughput experimentation with advanced algorithms for data analysis and experimental design. We present an experimental optimization strategy that merges three different techniques: (1) advanced microbioreactor systems, (2) lab automation, and (3) Kriging‐based experimental analysis and design. This strategy is demonstrated by maximizing product titer of secreted green fluorescent protein (GFP), synthesized by Corynebacterium glutamicum , through systematic variation of CgXII minimal medium composition. First, relevant design parameters are identified in an initial fractional factorial screening experiment. Then, the functional relationship between selected media components and protein titer is investigated more detailed in an iterative procedure. In each iteration, Kriging interpolations are used for formulating hypotheses and planning the next round of experiments. For the optimized medium composition, GFP product titer was more than doubled. Hence, Kriging‐based experimental analysis and design has been proven to be a powerful tool for efficient process optimization.