The genetic stability of E. coli expression systems is not particularly high under production conditions, and integration of the gene of interest (GOI) into the chromosome can only help to a limited extent. Expression of the recombinant protein exerts enormous selection pressure on the cells, so that direct use of adaptive laboratory evolution (ALE) experiments is not possible because unstressed non-producers would immediately dominate the culture. [1]

The aim of this PhD thesis is to develop adaptive laboratory evolution (ALE) methods to investigate the effects of long-term recombinant gene expression at the genome level and to create more efficient periplasmic E. coli production clones. To enable targeted evolution in E. coli we will develop approaches that link the correct expression of GOI to addiction module. This implies that only producing cells are capable of growth and thus evolution can be directed in the desired direction. We will generate and evaluate different addiction modules such as antibiotic resistance, toxin-antitoxin systems or cells with specific auxotrophies known from plasmid conservation strategies [4] [5].

The best performing addiction system will then be used for screening ALE experiments in high through-put subsequent µ-bioreactor cultivations with fully induced cultures producing super folder green fluorescent protein (sfGFP) as recombinant model protein. Clones showing significant variation in sfGFP expression will be selected for genome sequencing and sequence data will be analysed to identify mutations responsible for the changes in host characteristics. [1] [2]

We expect that not only one adaption or mutation will occur in clones selected for sequencing. The ALE treated cells will have different mutations at different locations in the genome. The hypothesis is, that targeted evolution will result in clones with more variation in mutation sites. We also expect to identify mutations that allow cells to better cope with the metabolic load triggered by expression of the POI. Selected better performing candidates will be investigated in lab-scale chemostat cultivations which allow for tightly controlled conditions very close to production environment. [3]


[1] Schuller, A., Cserjan-Puschmann, M., Köppl, C., Grabherr, R., Wagenknecht, M., Schiavinato, M., Dohm, J. C., Himmelbauer, H., & Striedner, G. (2020). Adaptive Evolution in Producing Microtiter Cultivations Generates Genetically Stable Escherichia coli Production Hosts for Continuous Bioprocessing. Biotechnology Journal, 2000376.

[2] Dragosits, M., & Mattanovich, D. (2013). Adaptive laboratory evolution - principles and applications for biotechnology. Microbial Cell Factories, 12(1), 1.

[3] Sandberg, T. E., Salazar, M. J., Weng, L. L., Palsson, B. O., & Feist, A. M. (2019). The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology. Metabolic Engineering, 56(August), 1–16.

[4] Wen, Y., Behiels, E., & Devreese, B. (2014). Toxin-Antitoxin systems: Their role in persistence, biofilm formation, and pathogenicity. Pathogens and Disease, 70(3), 240–249.

[5] Lin, M. T., Fukazawa, R., Miyajima-Nakano, Y., Matsushita, S., Choi, S. K., Iwasaki, T., & Gennis, R. B. (2015). Escherichia coli Auxotroph Host Strains for Amino Acid-Selective Isotope Labeling of Recombinant Proteins. In Methods in Enzymology (1st ed., Vol. 565). Elsevier Inc.