Transcription factor-based biosensors & Evolutionary engineering
Living organisms have evolved a plethora of sensing systems for the intra- and extracellular detection of small molecules, ions and physical parameters. We exploit these sensors for the development of synthetic regulatory circuits and transcription factor-based (TF) biosensors, which are highly valuable for a wide range of biotechnological applications (Figure 4).
Using TF-based biosensors, it is our goal to harness the power of evolution for the development of microbial production strains. Evolutionary engineering represents a straightforward approach for fitness‐linked phenotypes (e.g., growth or stress tolerance) and is successfully applied to select for strains with improved properties for particular industrial applications. Our group focuses on the establishment of circuits linking metabolic productivity to growth as a selectable trait as a novel approach to improve small molecule production. We apply next‐generation sequencing and automation technologies in combination with evolutionary engineering to streamline microbial strains for bioproduction and enhance our understanding of biological systems.
Projects focus on the biotechnological platform organism Corynebacterium glutamicum and the fast growing bacterium Vibrio natriegens, representing an emerging host for molecular biology and biotechnology.
Selected publications
Stella RG, Gertzen CGW, Smits SHJ, Gätgens C, Polen T, Noack S, Frunzke J (2021)Biosensor-based growth-coupling and spatial separation as an evolution strategy to improve small molecule production of Corynebacterium glutamicum. Metab Eng, 68:162-173, doi: 10.1016/j.ymben.2021.10.003
Tenhaef N, Stella R, Frunzke J, Noack S (2021) Automated Rational Strain Construction Based on High-Throughput Conjugation. ACS Synth Biol10(3):589-599, doi: 10.1021/acssynbio.0c00599.
Wiechert J, Gätgens C, Wirtz A, and Frunzke J (2020) Inducible expression systems based on xenogeneic silencing and counter-silencing and design of a metabolic toggle switch. ACS Synth Biol, doi: 10.1021/acssynbio.0c00111
Stella RG, Wiechert J, Noack S, and Frunzke J (2019) Evolutionary engineering of Corynebacterium glutamicum. Biotechnol J, doi: 10.1002/biot.201800444
Pfeifer E, Gätgens C, Polen T, and Frunzke J (2017) Adaptive laboratory evolution of Corynebacterium glutamicum towards higher growth rates on glucose minimal medium. Sci Rep, doi: 10.1038/s41598-017-17014-9
Mahr R and Frunzke J (2016) Transcription factor-based biosensors in biotechnology: current state and future prospects. Appl Microbiol Biotechnol, doi: 10.1007/s00253-015-7090-3
Mahr R, Gätgens C, Gätgens J, Polen T, Kalinowski J, and Frunzke J (2015) Biosensor-driven adaptive laboratory evolution of l-valine production in Corynebacterium glutamicum. Metab Eng, doi: 10.1016/j.ymben.2015.09.017
Mustafi N, Grünberger A, Kohlheyer D, Bott M, and Frunzke J (2012) The development and application of a single-cell biosensor for the detection of l-methionine and branched-chain amino acids. Metab Eng, doi: 10.1016/j.ymben.2012.02.002
Funding:
