Transcription factor-based biosensors in biotechnology: current state and future prospects
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1 Transcription factor-based biosensors in biotechnology: current state and future Saarbrücken, 12/06/2017 Regina Mahr and Julia Frunzke (2015) Speaker: Sarah Pauli Seminar Biotechnologie
2 Structure General principle of transcription factor-based biosensors Different transcription factor-based biosensors Applications of TF-based biosensors 1. High-throughput-screening 2. Biosensor-driven adaptive evolution 3. Dynamic pathway regulation 4. Single-cell analysis Biosensor engineering Future 12/06/2017 Sarah Pauli Page Seite 2
3 General principle of transcription factorbased biosensors Part 1: Effector molecules activate and control actuator part Part 2: actuator (biosensor readout) R. Mahr and J. Frunzke (2015) 12/06/2017 Sarah Pauli Page Seite 3
4 Different transcription factor-based biosensors 1. Classical one-component TFs Metabolite-responsive TFs Younger et al Two-component signaling (TCS) 3. Extracytoplasmic function (ECF) sigma factors Podgornaia & Laub /06/2017 Sarah Pauli Page Seite 4
5 Applications of TF-based biosensors R. Mahr and J. Frunzke (2015) 12/06/2017 Sarah Pauli Page Seite 5
6 HT-screening FACS /1104feature_willis.html 12/03/17 Mustafi et al /06/2017 Sarah Pauli Page Seite 6
7 Biosensor-driven adaptive evolution FREP: feedback-regulated evolution of phenotype Adaptive control system increasing mutation rate when target increases Too much small nucleotide polymorphisms Biosensor-driven adaptive evolution: Mahr et al /06/2017 Sarah Pauli Page Seite 7
8 Dynamic pathway control Zhang et al Construction of synthetic regulatory switches to dynamically regulate metabolic fluxes 12/06/2017 Sarah Pauli Page Seite 8
9 Single-cell analysis Gene expression noise can affect growth rate fluctuations cellular heterogeneity Microfluidic chip devices or flow cytrometry (FC) e.g. analyzing subpopulations occurring during the growth of Pseudomonas putida in bioprocesses feed control using a transcriptional sensor construct 12/06/2017 Sarah Pauli Page Seite 9
10 Biosensor engineering Limitation of native transcription factors extension of promiscuous transcriptional regulators for specific or non-natural ligands R. Mahr and J. Frunzke (2015) 12/06/2017 Sarah Pauli Page Seite 10
11 Future Improving production strains Identifying non-producing subpopulations during bioprocesses Identification of bottlenecks Screening promoter libraries or transcriptome analysis Accessability to novel biosensor circuits and sensor components Ensuring sensor functionality but minimizing interference with the host system 12/06/2017 Sarah Pauli Page Seite 11
12 Thank you for attention.
13 Sources Chou, H. H. and Keasling, J.D. (2013): Programming adaptive control to evolve increased metabolite production. Nat Commun 4:2595 Loken, M. R. and Herzenberg L. A. (1975): Analysis of cell populations with a fluorescence-activated cell sorter. Annals New York Academy of Sciences, Mahr, R. et al. (2015): Biosensor-driven adaptive laboratory evolution of L-valine production in Corynebacterium glutamicum. Metabolic Engineering 32, Mustafi, N. et al. (2012): The development and application of a single-cell biosensor for the detection of L-methionine and branchedchain amino acids. Metabolic Engineering 14, Podgornaia, A. and Laub, M. T. (2013): Determinats of specificity in two-component signal transduction. Current Opinion in Microbiology 16: Silva-Rocha, R. and de Lorenzo, V. (2012): Broadening the signal specificity of prokaryotic promoters by modifying cis-regulatory elements associated with a single transcription factor. Mol BioSyst 8(7): Tang S. Y. et al. (2013): Screening for enhanced triacetic acid lactone production by recombinant Escherichia coli expressing a designed triacetic acid lactone reporter. J Am Chem Soc 135(27): van Sint Fiet, S. et al. (2006): Selection of biocatalysts for chemical synthesis. Proc Natl Acad Sci U S A 103(6): Younger, A. K. D. et al. (2016): Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcritption. ACS Synth. Biol. 2017, 6: Zhang, F. et al. (2012): Design of a dynamic sensor-regulator system for production of chemicals and fuels derived from fatty acids. Nature Biotechnology 30, 4: /03/17 Seite
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