Engineering Biomolecular Systems - NCCR MSE

Engineering Biomolecular Systems

Operon frameworks for complex synthetic systems need to be explored in a multiplexed and multilevel approach to develop design rules.
A: Several operon design elements can influence final protein expression levels.
B: E. coli expressing various fluorescent reporter protein combinations.
C: A selected set of fluorescent proteins can be quantified in an orthogonal fashion via flowcytometry.
Operon frameworks for complex synthetic systems need to be explored in a multiplexed and multilevel approach to develop design rules. A: Several operon design elements can influence final protein expression levels. B: E. coli expressing various fluorescent reporter protein combinations. C: A selected set of fluorescent proteins can be quantified in an orthogonal fashion via flowcytometry.

Molecular systems derive their functional breadth from the interplay of multiple elements. The successful cooperation of these elements is often limited to narrow windows of operation, which are often difficult to identify.

We are optimizing complex in vitro systems so they can successfully operate in these windows. For this, we develop cell free systems that allow the synthesis of multiple catalysts and other protein-based elements, and compartmentalize the synthesis in nanoliter or picoliter-sized droplets. This helps us to investigate thousands of system compositions per minute. We use this to develop design rules for multi-membered systems and prepare such droplets for analysis in a classical way (i.e., by fluorescence) and by label-free methods, such as mass-spectrometry. This way we can optimize system function for a variety of objectives, ranging from enzyme evolution to the engineering of smart systems for metabolic diseases.

Publications

P. Dittrich, N. Nuti, P. Rottmann, A. Stucki, P. Koch, S. Panke “A Multiplexed Cell-Free Assay to Screen for Antimicrobial Peptides in Double Emulsion Droplets“ Angew. Chem. Int. Ed. 2022. [DOI]
A. Baiyoumy, J. Vallapurackal, F. Schwizer, T. Heinisch, T. Kardashliev, M. Held, S. PankeT. R. Ward “Directed Evolution of a Surface-Displayed Artificial Allylic Deallylase Relying on a GFP Reporter Protein“ ACS Catal. 2021. [DOI]
T. Vornholt, F. Christoffel, M. M. Pellizzoni, S. PankeT. R. Ward, M. Jeschek “Systematic Engineering of Artificial Metalloenzymes for New-to-Nature Reactions“ Sci. Adv. 2021. [DOI]
T. Heinisch, F. Schwizer, B. Garabedian, E. Csibra, M. Jeschek, J. Vallapurackal, V. B. Pinheiro, P. Marlière, S. PankeT. R. Ward “E. coli surface display of streptavidin for directed evolution of an allylic deallylase“ Chem. Sci. 2018, 9(24):5383-5388. [DOI]
M. JeschekS. PankeT. R. Ward “Artificial Metalloenzymes on the Verge of New-to-Nature Metabolism“ Trends Biotechnol. 2017. [DOI]
S. Oesterle, D. Gerngross, S. Schmitt, T. M. Roberts, S. Panke “Efficient engineering of chromosomal ribosome binding site libraries in mismatch repair proficient Escherichia coli“ Sci. Rep. 2017, 7(1):12327. [DOI]
M. Jeschek, D. Gerngross, S. Panke “Combinatorial pathway optimization for streamlined metabolic engineering“ Curr. Opin. Biotechnol. 2017, 47:142-51. [DOI]
M. Jeschek, M. O. Bahls, V. Schneider, P. Marlière, T. R. WardS. Panke “Biotin-independent Strains of Escherichia coli for Enhanced Streptavidin Production“ Metab. Eng. 2017, 40:33-40. [DOI]
M. Jeschek, R. Reuter, T. Heinisch, C. Trindler, J. Klehr, S. PankeT. R. Ward “Directed evolution of artificial metalloenzymes for in vivo metathesis“ Nature 2016, doi:10.1038/nature19114. [DOI] [More Information]
P. Rottmann, T. R. WardS. Panke “Compartmentalization – A Prerequisite for Maintaining and Changing an Identity“ Chimia 2016, 6:428
T. M. Roberts, F. Rudolf, A. Meyer, R. Pellaux, E. Whitehead, S. Panke, M. Held “Identification and Characterisation of a pH-stable GFP“ Sci. Rep. 2016, 6:28166. [DOI]
M. JeschekS. PankeT. R. Ward “Chapter Twenty-Three-Periplasmic Screening for Artificial Metalloenzymes“ Methods Enzymol. 2016, 580:539-56. [DOI]
M. JeschekD. GerngrossS. Panke “Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort“ Nat. Commun. 2016, 7:doi:10.1038/ncomms11163. [DOI]