Dokument: Applications of transcription factor-based biosensors for strain development and evolutionary engineering

Titel:	Applications of transcription factor-based biosensors for strain development and evolutionary engineering
URL für Lesezeichen:	https://docserv.uni-duesseldorf.de/servlets/DocumentServlet?id=58413
URN (NBN):	urn:nbn:de:hbz:061-20220117-110531-4
Kollektion:	Dissertationen
Sprache:	Englisch
Dokumententyp:	Wissenschaftliche Abschlussarbeiten » Dissertation
Medientyp:	Text
Autor:	Dr. Stella, Roberto [Autor]
Dateien:	[Dateien anzeigen] Adobe PDF [Details] 34,41 MB in einer Datei [ZIP-Datei erzeugen] Dateien vom 21.12.2021 / geändert 21.12.2021
Beitragende:	Prof. Dr. Julia Frunzke [Gutachter] Prof. Dr. Martina Pohl [Gutachter]
Dewey Dezimal-Klassifikation:	500 Naturwissenschaften und Mathematik » 570 Biowissenschaften; Biologie
Beschreibung:	The transition of our current economy to a sustainable bioeconomy requires efficient and high performing microbial strains for the production of chemical building blocks and fuels. However, the construction and improvement of microbial producer strains is time consuming and costly. In this thesis, several ways to improve this process using transcription factor(TF)-based biosensors have been investigated. First, we used TF-based biosensors to obtain positive amino acid-producing Vibrio natriegens strains. V. natriegens is a Gram-negative, non-pathogenic slight-halophilic bacterium that has recently been demonstrated to be a promising new host for molecular biology and next generation bioprocesses. Its most remarkable property is a doubling time of under 10 minutes. In this work, the LysG biosensor from Corynebacterium glutamicum was adapted for expression in V. natriegens, to couple positive amino acid production to a fluorescent output. Afterwards, we performed a mutagenesis and screening approach, using fluorescence-activated cell sorting (FACS) to isolate highly fluorescent cells (potential producer cells). Using this approach, individual L-lysine, L-arginine and L-histidine producer cells could be obtained. Investigation of these isolates by whole genome sequencing revealed key mutations for positive amino acid production in V. natriegens. Second, we used TF-based biosensors to investigate novel evolutionary engineering strategies. Evolutionary engineering is a proven and powerful method to improve the performance of microbial producer strains. However, it is typically not possible to directly apply it to increase production of industrially interesting molecules, due to the lack of an appropriate selection regime. To address this problem, we used TF-based biosensors to couple production to growth. More specifically, the growth rate of C. glutamicum was coupled to the intracellular concentration of L-valine, L-leucine, L-isoleucine and L-methionine. This was enabled by integrating a synthetic regulatory circuit, based on the TF-based biosensor Lrp, upstream of two growth-regulating genes, pfkA and hisD. Using these strains, selection for mutants with increased growth rates should theoretically lead to the selection of mutants with increased production. Modeling and experimental data showed that evolutionary strategies based on spatial separation were required to limit the selection of ‘cheater’ cells that escaped the evolutionary pressure. This was achieved by an agar-plate based selection strategy, which enabled the high-throughput isolation of amino acid producing clones that showed a stable production phenotype during repetitive cultivations. Whole genome sequencing of the obtained L-valine producing mutants highlighted the acetohydroxyacid synthase (AHAS) as a mutational hotspot. Modeling of the AHAS enzyme provided insight into the functional effect of the different mutations. Finally, we used the construction of TF-based biosensor variants as an application example to demonstrate an automated cloning workflow for C. glutamicum rational strain construction. At present, cloning is most often a manual, time-consuming and repetitive process that would highly benefit from automation. Therefore, we designed an automated cloning workflow covering DNA part creation by PCR, DNA assembly by Gibson assembly and transformation into Escherichia coli by heat-shock transformation. The key step is an automated conjugation workflow, which enables fast, easy and high-throughput transfer of plasmids from E. coli to C. glutamicum. Using this approach, we could create and analyse 44 biosensor variants in 8 days, with a minimal amount of manual work required. Analysis of these variants led to the novel insight that Lrp possibly also has repressor functionality. In conclusion, the work presented in this thesis provides novel insights into the use of TF-based biosensors to improve strain construction workflows, including the development of new producer strains, the improvement of evolutionary engineering strategies, and the transfer from manual to automated laboratory workflows.
Lizenz:	Urheberrechtsschutz
Fachbereich / Einrichtung:	Mathematisch- Naturwissenschaftliche Fakultät
Dokument erstellt am:	17.01.2022
Dateien geändert am:	17.01.2022
Promotionsantrag am:	04.08.2021
Datum der Promotion:	18.10.2021