Artificial Biomaterials
Welcome to the Spinck Lab. We aim to genetically reprogram bacteria to synthesise artificial biomaterials, generating novel self-assembling and evolvable systems with diverse non-natural properties.
We are building a strong interdisciplinary team combining synthetic biology, chemistry, and materials science to explore new forms of programmable matter.
Research Vision
Self-assembling peptide materials offer an exciting way to design new biomaterials that can grow, organise, and adapt at the molecular level. By expanding the genetic code, we can introduce new building blocks into biology, allowing cells to produce materials with properties not found in nature. Using directed evolution, we can challenge cells in an artificial environment to generate new materials or fine-tune their properties.
Our vision is to create designed, self-assembling biomaterials that are accessible and adaptable for real-world applications, ranging from sustainable biocatalysts to advanced functional materials.
Our research receives ERC Starting Grant support
Our research into genetically programmable biomaterials has been awarded an ERC Starting Grant, supporting a new research programme at the Manchester Institute of Biotechnology. The five-year project, SynMPFs, aims to develop a new class of metal-peptide frameworks (MPFs) that can self-assemble and evolve inside living cells. By combining synthetic biology, genetic code engineering and materials science, we aim to establish a platform for discovering and optimising functional biomaterials through directed evolution. This work could open up new opportunities for sustainable applications in catalysis, bioelectronics and advanced materials.
Selected publications:
Spinck, M., Piedrafita, C., Robertson, W.E. et al. Genetically programmed cell-based synthesis of non-natural peptide and depsipeptide macrocycles. Nat. Chem. 15, 61–69 (2023). https://doi.org/10.1038/s41557-022-01082-0
Spinck, M., Guppy, A. & Chin, J.W. Automated orthogonal tRNA generation. Nat Chem Biol 21, 657–667 (2025). https://doi.org/10.1038/s41589-024-01782-3
Robertson, W. E., Rehm, F., Spinck, M., Schumann, R. L, Tian, R., et al., Escherichia coli with a 57-codon genetic code. Science 390, eady 4368 (2025).