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Yan, E. C. Y.

Publications and source records attributed to Yan, E. C. Y..

2 recordsLinked to original sources

A biofilm-derived peptide as an underwater adhesive

Wet adhesives that perform under water have broad applications in industrial and biomedical settings. To date, molecular designs for underwater adhesives have largely been inspired by marine animals including mussels and barnacles. Here, we propose bacterial biofilms as an alternative source of inspiration for underwater adhesives. Specifically, we demonstrate the application potential of a peptide derived from biofilms formed by the notorious pathogen Vibrio cholerae. We characterize the ability of this biofilm-derived peptide to adsorb onto various surfaces and to glue wet surfaces, by using a combination of confocal microscopy, molecular dynamics simulations, atomic force microscopy, lap shear tests, and spectroscopic tools. We further show that the peptide can co-aggregate with microspheres acting as an effective flocculant. Finally, we succeeded in purifying this peptide from E. coli in a functional form, setting the stage for large-scale production. Our results open new design possibilities for underwater adhesives inspired by natural biofilms. TeaserA peptide derived from biofilms adheres to diverse surfaces and shows promising potential as a wet adhesive and flocculant.

bioengineering↗

Direct Optical Quantification of Chain Collapse, Reduced Dielectric, and Water Release Driving Protein Phase Separation

Biomolecular condensates represent unique microenvironments that organize intracellular biology and promote biochemical reactions. However, the biomolecular interactions driving condensate phase separation are often weak, transient, and heterogeneous. Investigating the structural biology and chemical properties of condensate interiors has therefore proven experimentally challenging, often requiring the use of perturbative probes. To overcome this challenge, we combine label-free optical scattering and vibrational spectroscopy approaches spanning ultraviolet, visible, mid-infrared, and terahertz wavelengths with deep-learning-based ensemble prediction of intrinsically disordered protein conformations. Our experimental and computational results reveal that the intrinsically disordered N-terminal domain of the RNA Deadbox helicase 4 (DDX4) deviates from random coil behavior and undergoes chain collapse that correlates with phase separation, which leads to lower dielectric and reduced water content inside condensates. Our data support a model of DDX4 phase separation whereby chain collapse, reduced dielectric, and water release enhance the strength of multivalent protein-protein interactions within condensates, driving condensate growth and phase separation through positive feedback. Our study addresses the critical driving forces of biomolecular phase separation across a range of length scales, providing quantitative insights into protein-protein/protein-solvent interactions and the chemical properties of condensate interiors.

biophysics↗