Sven Panke

Last Name

Panke

First Name

Sven

ORCID

0000-0002-9368-539X

Organisational unit

03602 - Panke, Sven / Panke, Sven

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Publications 1 - 10 of 38

Evolving Escherichia coli to use a tRNA with a non-canonical fold as an adaptor of the genetic code
Edelmann, Martin P.; Couperus, Sietse; Rodriguez Robles, Emilio; et al. (2024)
Nucleic Acids Research
All known bacterial tRNAs adopt the canonical cloverleaf 2D and L-shaped 3D structures. We aimed to explore whether alternative tRNA structures could be introduced in bacterial translation. To this end, we crafted a vitamin-based genetic system to evolve Escherichia coli toward activity of structurally non-canonical tRNAs. The system reliably couples (escape frequency <10(-12)) growth with the activities of a novel orthogonal histidine suppressor tRNA (HisTUAC) and of the cognate ARS (HisS) via suppression of a GTA valine codon in the mRNA of an enzyme in thiamine biosynthesis (ThiN). Suppression results in the introduction of an essential histidine and thereby confers thiamine prototrophy. We then replaced HisTUAC in the system with non-canonical suppressor tRNAs and selected for growth. A strain evolved to utilize mini HisT, a tRNA lacking the D-arm, and we identified the responsible mutation in an RNase gene (pnp) involved in tRNA degradation. This indicated that HisS, the ribosome, and EF-Tu accept mini HisT ab initio, which we confirmed genetically and through in vitro translation experiments. Our results reveal a previously unknown flexibility of the bacterial translation machinery for the accepted fold of the adaptor of the genetic code and demonstrate the power of the vitamin-based suppression system.
Systematic analysis of tRNA transcription unit deletions in E. coli reveals insights into tRNA gene essentiality and cellular adaptation
Tiefenbacher, Sanja; Pezo, Valérie; Marlière, Philippe; et al. (2024)
Scientific Reports
Transfer ribonucleic acids (tRNAs) are essential for protein synthesis, decoding mRNA sequences into amino acids. In E. coli K-12 MG1655, 86 tRNA genes are organized in 43 transcription units (TUs) and the essentiality of individual tRNA TUs in bacterial physiology remains unclear. To address this, we systematically generated 43 E. coli tRNA deletion strains in which each tRNA TU was replaced by a kanamycin resistance gene. We found that 33 TUs are not essential for survival, while 10 are essential and require the corresponding TU to be provided on plasmid. The analysis revealed E. coli’s tolerance to alterations in tRNA gene copy number and the loss of non-essential tRNAs, as most strains exhibited minimal to no growth differences under various conditions compared to the parental strain. However, deletions metZWV, alaWX and valVW led to significant growth defects under specific conditions. RNA-seq analysis of ∆alaWX and ∆valVW revealed upregulation of genes involved in translation and pilus assembly. Our results provide valuable insights into tRNA dynamics and the cellular response to tRNA TU deletions, paving the way for deeper understanding of tRNA pool complexity.
Signal Peptide Efficiency: from High-throughput Data to Prediction and Explanation
Grasso, Stefano; Dabene, Valentina; Hendriks, Margriet M.W.B.; et al. (2022)
bioRxiv
The passage of proteins across biological membranes via the general secretory (Sec) pathway is a universally conserved process with critical functions in cell physiology and important industrial applications. Proteins are directed into the Sec pathway by a signal peptide at their N-terminus. Estimating the impact of physicochemical signal peptide features on protein secretion levels has not been achieved so far, partially due to the extreme sequence variability of signal peptides. To elucidate relevant features of the signal peptide sequence that influence secretion efficiency, an evaluation of ~12,000 different designed signal peptides was performed using a novel miniaturized high-throughput assay. The results were used to train a machine learning model, and a post-hoc explanation of the model is provided. By describing each signal peptide with a selection of 156 physicochemical features, it is now possible to both quantify feature importance and predict the protein secretion levels directed by each signal peptide. Our analyses allow the detection and explanation of the relevant signal peptide features influencing the efficiency of protein secretion, generating a versatile tool for the in silico evaluation of signal peptides.
Droplet Microfluidics: High‐Throughput Optimization of Recombinant Protein Production in Microfluidic Gel Beads (Small 2/2021)
Napiorkowska, Marta; Pestalozzi, Luzius; Panke, Sven; et al. (2021)
Small
Efficient synthesis of 2,6-bis(hydroxymethyl)pyridine using whole-cell biocatalysis
Kardashliev, Tsvetan; Panke, Sven; Held, Martin (2022)
Green Chemistry
We demonstrate a novel one-pot biocatalytic process for the preparation of a versatile chemical intermediate, 2,6-bis(hydroxymethyl)pyridine, from naturally-occurring 2,6-lutidine using recombinant microbial whole cells as a catalysts. After scale up, the bioconversion enabled titers exceeding 12 g L-1 with a space-time yield of 0.8 g L-1 h(-1). This biocatalytic route offers a simpler and more sustainable alternative to multistep organic synthesis protocols.
Directed evolution of biofuel-responsive biosensors for automated optimization of branched-chain alcohol biosynthesis
Bahls, Maximilian O.; Platz, Lukas; Morgado, Gaspar; et al. (2022)
Metabolic Engineering
The biosynthesis of short-chain alcohols is a carbon-neutral alternative to petroleum-derived production, but strain screening operations are encumbered by laborious analytics. Here, we built, characterized and applied whole cell biosensors by directed evolution of the transcription factor AlkS for screening microbial strain libraries producing industrially relevant alcohols. A selected AlkS variant was applied for in situ product detection in two screening applications concerning key steps in alcohol production. Further, the biosensor strains enabled the implementation of an automated, robotic platform-based workflow with data clustering, which readily allowed the identification of significantly improved strain variants for isopentanol production.
Cellular transport system for transferring a sulfonic acid construct carrying a cargo into the cytoplasm of a cell
Künzl, Tilmann; Panke, Sven; Marlière, Philippe (2021)
A Multiplexed Cell‐Free Assay to Screen for Antimicrobial Peptides in Double Emulsion Droplets
Dittrich, Petra S.; Nuti, Nicola; Rottmann, Philipp; et al. (2022)
Angewandte Chemie. International Edition
The global surge in bacterial resistance against traditional antibiotics triggered intensive research for novel compounds, with antimicrobial peptides (AMPs) identified as a promising candidate. Automated methods to systematically generate and screen AMPs according to their membrane preference, however, are still lacking. We introduce a novel microfluidic system for the simultaneous cellfree production and screening of AMPs for their membrane specificity. On our device, AMPs are cell-free produced within water-in-oil-inwater double emulsion droplets, generated at high frequency. Within each droplet, the peptides can interact with different classes of coencapsulated liposomes, generating a membrane-specific fluorescent signal. The double emulsions can be incubated and observed in a hydrodynamic trapping array or analyzed via flow cytometry. Our approach provides a valuable tool for the discovery and development of membrane-active antimicrobials.
Data-driven protease engineering by DNA-recording and epistasis-aware machine learning
Huber, Lukas; Kucera, Tim; Höllerer, Simon; et al. (2025)
Nature Communications
Protein engineering has recently seen tremendous transformation due to machine learning (ML) tools that predict structure from sequence at unprecedented precision. Predicting catalytic activity, however, remains challenging, restricting our capabilities to design protein sequences with desired catalytic function in silico. This predicament is mainly rooted in a lack of experimental methods capable of recording sequence-activity data in quantities sufficient for data-intensive ML techniques, and the inefficiency of searches in the enormous sequence spaces inherent to proteins. Herein, we address both limitations in the context of engineering proteases with tailored substrate specificity. We introduce a DNA recorder for deep specificity profiling of proteases in Escherichia coli as we demonstrate testing 29,716 candidate proteases against up to 134 substrates in parallel. The resulting sequence-activity data on approximately 600,000 protease-substrate pairs does not only reveal key sequence determinants governing protease specificity, but allows to build a data-efficient deep learning model that accurately predicts protease sequences with desired on- and off-target activities. Moreover, we present epistasis-aware training set design as a generalizable strategy to streamline searches within enormous sequence spaces, which strongly increases model accuracy at given experimental efforts and is thus likely to have implications for protein engineering far beyond proteases.
Permeabilisation of the Outer Membrane of Escherichia coli for Enhanced Transport of Complex Molecules
Casas-Rodrigo, Ivan; Vornholt, Tobias; Castiglione, Kathrin; et al. (2025)
Microbial Biotechnology
The bacterial envelope plays a critical role in maintaining essential cellular functions by selectively regulating import and export. The selectivity of this envelope can restrict the utilisation of externally provided compounds, thereby restricting the functional space of cellular engineering. This study systematically investigates the potential of large pore outer membrane proteins (OMPs) to enhance outer membrane permeability for diverse challenging compounds. We focus on the general porin OmpF, which facilitates the diffusion of water and small molecules, and specific OMP transporters FhuA and FepA, which mediate the translocation of small hydrophilic compounds. Through comprehensive characterisation, we evaluate the effects of recombinant expression of OMPs and engineered variants for small and hydrophilic compounds, aromatic molecules and bulky molecules and apply our findings to address two critical contemporary transport challenges: the uptake of large metal-containing cofactors for artificial metalloenzymes and non-permeant fluorescent Halo-ligands for in vivo protein labelling. Notably, we demonstrate significant improvements in ArM-catalysis and labelling. This study provides a practical guide for designing experiments that include outer-membrane-transport-limiting steps. This study highlights the potential of engineered OMPs to overcome the limitations imposed by the cell envelope, enabling the incorporation of complex molecules and expanding the frontiers of cellular engineering.

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Sven Panke

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