Sustainable metabolic engineering for sustainability optimisation of industrial biotechnology

被引:11
|
作者
Stalidzans, Egils [1 ]
Dace, Elina [1 ]
机构
[1] Univ Latvia, Inst Microbiol & Biotechnol, 1 Jelgavas St, LV-1004 Riga, Latvia
关键词
Biotechnology; Genome-scale metabolic models; Mathematical modelling; Ranking; Sustainability optimisation; Sustainable metabolic engineering; GREENHOUSE-GAS EMISSIONS; GENOME-SCALE MODELS; ETHANOL; BIOLOGY;
D O I
10.1016/j.csbj.2021.08.034
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Industrial biotechnology represents one of the most innovating and labour-productive industries with an estimated stable economic growth, thus giving space for improvement of the existing and setting up new value chains. In addition, biotechnology has clear environmental advantages over the chemical industry. Still, biotechnology's environmental contribution is sometimes valued with controversy and societal aspects are frequently ignored. Environmental, economic and societal sustainability of various bioprocesses becomes increasingly important due to the growing understanding about complex and interlinked consequences of different human activities. Neglecting the sustainability issues in the development process of novel solutions may lead to sub-optimal biotechnological production, causing adverse environmental and societal problems proportional to the production volumes. In the paper, sustainable metabolic engineering (SME) concept is proposed to assess and optimize the sustainability of biotechnological production that can be derived from the features of metabolism of the exploited organism. The SME concept is optimization of metabolism where economic, environmental and societal sustainability parameters of all incoming and outgoing fluxes and produced biomass of the applied organisms are considered. The extension of characterising features of strains designed by metabolic engineering methods with sustainability estimation enables ab initio improvement of the biotechnological production design. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
引用
收藏
页码:4770 / 4776
页数:7
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