Biology subjects

Jendrusch, M.

Publications and source records attributed to Jendrusch, M..

4 recordsLinked to original sources

bioRxiv2024

A Versatile Anti-CRISPR Platform for Opto- and Chemogenetic Control of CRISPR-Cas9 and Cas12 across a Wide Range of Orthologs

CRISPR-Cas technologies have revolutionized life sciences by enabling programmable genome editing across diverse organisms. Achieving dynamic and precise control over CRISPR-Cas activity with exogenous triggers, such as light or chemical ligands, remains an important need. Existing tools for CRISPR-Cas control are often limited to specific Cas orthologs or selected applications, restricting their versatility. Anti-CRISPR (Acr) proteins, natural inhibitors of CRISPR-Cas systems, provide a flexible regulatory layer but are constitutively active in their native forms. In this study, we built on our previously reported concept for optogenetic CRISPR-Cas control with engineered, light-switchable anti-CRISPR proteins and expanded it from ortholog-specific Acrs towards AcrIIA5 and AcrVA1, broad-spectrum inhibitors of CRISPR-Cas9 and -Cas12a, respectively. We then conceived and implemented a novel, chemogenetic anti-CRISPR platform based on engineered, circularly permuted ligand receptor domains of human origin, that together respond to six different, clinically-relevant drugs. The resulting toolbox achieves both optogenetic and chemogenetic control of genome editing in human cells with a wide range of CRISPR-Cas effectors, including type II-A and -C CRISPR-Cas9s, and -Cas12a. In sum, this work establishes a versatile platform for multidimensional control of CRISPR-Cas systems, with immediate applications in basic research and biotechnology and potential for therapeutic use in the future.

synthetic biology↗

bioRxiv2021

AlphaDesign: A de novo protein design framework based on AlphaFold

De novo protein design is a longstanding fundamental goal of synthetic biology, but has been hindered by the difficulty in reliable prediction of accurate high-resolution protein structures from sequence. Recent advances in the accuracy of protein structure prediction methods, such as AlphaFold (AF), have facilitated proteome scale structural predictions of monomeric proteins. Here we develop AlphaDesign, a computational framework for de novo protein design that embeds AF as an oracle within an optimisable design process. Our framework enables rapid prediction of completely novel protein monomers starting from random sequences. These are shown to adopt a diverse array of folds within the known protein space. A recent and unexpected utility of AF to predict the structure of protein complexes, further allows our framework to design higher-order complexes. Subsequently a range of predictions are made for monomers, homodimers, heterodimers as well as higher-order homo-oligomers - trimers to hexamers. Our analyses also show potential for designing proteins that bind to a pre-specified target protein. Structural integrity of predicted structures is validated and confirmed by standard ab initio folding and structural analysis methods as well as more extensively by performing rigorous all-atom molecular dynamics simulations and analysing the corresponding structural flexibility, intramonomer and interfacial amino-acid contacts. These analyses demonstrate widespread maintenance of structural integrity and suggests that our framework allows for fairly accurate protein design. Strikingly, our approach also reveals the capacity of AF to predict proteins that switch conformation upon complex formation, such as involving switches from -helices to {beta}-sheets during amyloid filament formation. Correspondingly, when integrated into our design framework, our approach reveals de novo design of a subset of proteins that switch conformation between monomeric and oligomeric state.

bioinformatics↗

bioRxiv2021

A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins

Deep mutational scanning is a powerful method to explore the mutational fitness landscape of proteins. Its adaptation to anti-CRISPR proteins, which are natural CRISPR-Cas inhibitors and key players in the co-evolution of microbes and phages, would facilitate their in-depth characterization and optimization. Here, we developed a robust anti-CRISPR deep mutational scanning pipeline in Escherichia coli combining synthetic gene circuits based on CRISPR interference with flow cytometry-coupled sequencing and mathematical modeling. Using this pipeline, we created and characterized comprehensive single point mutation libraries for AcrIIA4 and AcrIIA5, two potent inhibitors of Streptococcus pyogenes Cas9. The resulting mutational fitness landscapes revealed that both Acrs possess a considerable mutational tolerance as well as an intrinsic redundancy with respect to Cas9 inhibitory features, suggesting evolutionary pressure towards high plasticity and robustness. Finally, to demonstrate that our pipeline can inform the optimization and fine-tuning of Acrs for genome editing applications, we cross-validated a subset of AcrIIA4 mutants via gene editing assays in mammalian cells and in vitro affinity measurements. Together, our work establishes deep mutational scanning as powerful method for anti-CRISPR protein characterization and optimization.

synthetic biology↗

bioRxiv2019

The shared neoantigen landscape of MSI cancers reflects immunoediting during tumor evolution

The immune system can recognize and attack cancer cells, especially those with a high load of mutation-induced neoantigens. Such neoantigens are particularly abundant in DNA mismatch repair (MMR)-deficient, microsatellite-unstable (MSI) cancers. MMR deficiency leads to insertion/deletion (indel) mutations at coding microsatellites (cMS) and to neoantigen-inducing translational frameshifts. The abundance of mutational neoantigens renders MSI cancers sensitive to immune checkpoint blockade. However, the neoantigen landscape of MMR-deficient cancers has not yet been systematically mapped. In the present study, we used a novel tool to monitor neoantigen-inducing indel mutations in MSI colorectal and endometrial cancer. Our results show that MSI cancers share several highly immunogenic neoantigens that result from specific, recurrent indel mutation events. Notably, the frequency of such indel mutations was negatively correlated to the predicted immunogenicity of the resulting neoantigens. These observations suggest continuous immunoediting of emerging MMR-deficient cells during tumor evolution.\n\nOne sentence summaryQuantitative indel mutation analysis reveals evidence of immune selection in mismatch repair-deficient cancers

cancer biology↗