Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 548354
Title Genetic algorithm as an optimization tool for the development of sponge cell culture media
Author(s) Munroe, Stephanie; Sandoval, Kenneth; Martens, Dirk E.; Sipkema, Detmer; Pomponi, Shirley A.
Source In Vitro Cellular & Developmental Biology. Animal 55 (2019)3. - ISSN 1071-2690 - p. 149 - 158.
DOI https://doi.org/10.1007/s11626-018-00317-0
Department(s) Bioprocess Engineering
VLAG
MolEco
WIMEK
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) Cell culture - Dysidea etheria - Genetic algorithm - Medium optimization - Metabolic activity - Sponge
Abstract

Sponges are rich sources of novel natural products. Production in cell cultures may be an option for supply of these compounds but there are currently no sponge cell lines. Because there is a lack of understanding about the precise conditions and nutritional requirements that are necessary to sustain sponge cells in vitro, there has yet to be a defined, sponge-specific nutrient medium. This study utilized a genetic algorithm approach to optimize the amino acid composition of a commercially available basal cell culture medium in order to increase the metabolic activity of cells of the marine sponge Dysidea etheria. Four generations of the algorithm were carried out in vitro in wet lab conditions and an optimal medium combination was selected for further evaluation. When compared to the basal medium control, there was a twofold increase in metabolic activity. The genetic algorithm approach can be used to optimize other components of culture media to efficiently optimize chosen parameters without the need for detailed knowledge on all possible interactions.

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