ABSTRACT
Motivation: INCA is a powerful tool for metabolic flux analysis, however, import and export of data and results can be tedious and limit the use of INCA in automated workflows. Results: The INCAWrapper enables the use of INCA purely through Python, which allows the use of INCA in common data science workflows. Availability and implementation: The INCAWrapper is implemented in Python and can be found at https://github.com/biosustain/incawrapper. It is freely available under an MIT License. To run INCA, the user needs their own MATLAB and INCA licenses. INCA is freely available for noncommercial use at mfa.vueinnovations.com.
ABSTRACT
OBJECTIVE: The rapid accumulation of crude-oil based plastics in the environment is posing a fundamental threat to the future of mankind. The biodegradable and bio-based polyhydroxyalkanoates (PHAs) can replace conventional plastics, however, their current production costs are not competitive and therefore prohibiting PHAs from fulfilling their potential. RESULTS: Different low-quality animal by-products, which were separated by thermal hydrolysis into a fat-, fat/protein-emulsion- and mineral-fat-mixture- (material with high ash content) phase, were successfully screened as carbon sources for the production of PHA. Thereby, Ralstonia eutropha Re2058/pCB113 accumulated the short- and medium-chain-length copolymer poly(hydroxybutyrate-co-hydroxyhexanoate) [P(HB-co-HHx)]. Up to 90 wt% PHA per cell dry weight with HHx-contents of 12-26 mol% were produced in shake flask cultivations. CONCLUSION: In future, the PHA production cost could be lowered by using the described animal by-product streams as feedstock.