| Literature DB >> 25457387 |
Frank Delvigne1, Quentin Zune2, Alvaro R Lara3, Waleed Al-Soud4, Søren J Sørensen4.
Abstract
Phenotypic heterogeneity is a major issue in the context of industrial bioprocessing. Stochasticity of gene expression is usually considered to be the main source of heterogeneity among microbial population, but recent evidence demonstrates that metabolic reactions can also be subject to stochasticity without any intervention of gene expression. Although metabolic heterogeneity can be encountered in laboratory-scale cultivation devices, stochasticity at the level of metabolic reactions is perturbed directly by microenvironmental heterogeneities occurring in large-scale bioreactors. Accordingly, analytical tools are needed for the determination of metabolic variability in bioprocessing conditions and for the efficient design of metabolic engineering strategies. In this context, implementation of single cell technologies for bioprocess monitoring would benefit from knowledge acquired in more fundamental studies.Keywords: bioprocess optimization; metabolic engineering; microbial stress; stochasticity
Mesh:
Year: 2014 PMID: 25457387 DOI: 10.1016/j.tibtech.2014.10.002
Source DB: PubMed Journal: Trends Biotechnol ISSN: 0167-7799 Impact factor: 19.536