Bioprocess engineering through dynamic control of metabolic pathways
Final Report Abstract
Synthetic metabolic pathways are thought to be a burden for industrial microbes, because they consume cellular resources. In this project we could show that metabolic burden is also a result of missing regulation in engineered pathways. By introducing new regulatory mechanisms, we improved fitness of the host while maintaining high production rates. We could show this principle with three overproduction pathways: i) arginine, ii) glycerol, and iii) carotenoids, using E. coli as a host. In the case of arginine overproduction, we used the endogenous arginine pathway for overproduction and combined it with CRISPRi to engineer regulatory mechanisms. The results from this study showed that partial feedback dysregulation with CRISPRi is better than complete feedback dysregulation, and that the remaining transcriptional feedback in the arginine pathway (via ArgR) enables cells to better control enzyme levels in the arginine pathway, which resulted in better growth of the host at high production rates. In case of glycerol and carotenoid production, we achieved dynamic control by coupling expression of the first enzymes in these heterologous pathways to an endogenous transcription factor of E. coli (Cra). Cra senses the level of glycolysis metabolites and inhibits expression of the heterologous pathways when glycolysis metabolites are low. We showed functioning of this feedback mechanism at the molecular level using metabolomics and proteomics. Previous studies that engineered feedback in overproduction pathways have not provided such a detailed functional analysis. Therefore, this work was one of the first studies showing functioning of an engineered feedback mechanism at the molecular level (with metabolomics). With the FBP-Cra feedback the concentration of glycolysis metabolites remained sufficiently high, despite a high production of glycerol. In contrast, the unregulated expression system led to low concetrations of glycolysis metabolites which falsely activated gluconeogenesis (we termed this transcriptional missregulation). Another important discovery in this work was that allosteric feedback inhibition enforces enzyme overabundance in amino acid biosynthesis. We explored the consequences of missing allosteric feedback inhibition in seven E. coli mutants with dysregulated amino acid biosynthesis pathways. In all mutants, the amino acid product of the feedback-dysregulated pathway increased, showing that allosteric feedback inhibition is relevant to maintain end-products at a desired level. In five mutants (argA*, trpE*, hisG*, thrA*, and leuA*), we observed a downregulation of enzymes in the dysregulated pathways, because high end-products caused stronger inhibition of enzyme expression. This in turn allowed us to draw the conclusion that allosteric feedback is responsible to maintain high enzyme levels.
Publications
- (2017) Time-optimized isotope ratio LC- MS/MS for high-throughput quantification of primary metabolites. Analytical Chemistry 89, 1624–1631
Guder JC, Schramm T, Sander T, Link H
(See online at https://doi.org/10.1021/acs.analchem.6b03731) - (2018) Crosstalk between transcription and metabolism: how much enzyme is enough for a cell? Wiley Interdisciplinary Reviews: Systems Biology and Medicine 10, e1396
Donati S, Sander T, Link H
(See online at https://doi.org/10.1002/wsbm.1396) - (2018) Selective enrichment of slow-growing bacteria in a metabolism-wide CRISPRi library with a TIMER protein. ACS Synthetic Biology 7, 2775–2782
Beuter D, Gomes-Filho J, Randau L, Díaz-Pascual F, Drescher K, Link H
(See online at https://doi.org/10.1021/acssynbio.8b00379) - (2019) Allosteric feedback inhibition enables robust amino acid biosynthesis in E. coli by enforcing enzyme overabundance. Cell Systems 8, 1-10
Sander T, Farke N, Diehl C, Kuntz M, Glatter T, Link H
(See online at https://doi.org/10.1016/j.cels.2018.12.005) - (2019) CRISPRi-based downregulation of transcriptional feedback improves fitness and metabolism of arginine overproducing E. coli. ACS Synthetic Biology. 8, 1983-1990
Sander T, Wang CY, Link H
(See online at https://doi.org/10.1021/acssynbio.9b00183) - (2021) Metabolome and proteome analyses reveal transcriptional misregulation in glycolysis of engineered E. coli. Nature Communications 12, 4929
Wang CY, Lempp M, Farke N, Donati S, Glatter T, Link H
(See online at https://doi.org/10.1038/s41467-021-25142-0)
