Convergent synthesis of diversified reversible network leads to liquid metal-containing conductive hydrogel adhesives

Many features of extracellular matrices, e.g., self-healing, adhesiveness, viscoelasticity, and conductivity, are associated with the intricate networks composed of many different covalent and non-covalent chemical bonds. Whereas a reductionism approach would have the limitation to fully recapitulate various biological properties with simple chemical structures, mimicking such sophisticated networks by incorporating many different functional groups in a macromolecular system is synthetically challenging. Herein, we propose a strategy of convergent synthesis of complex polymer networks to produce biomimetic electroconductive liquid metal hydrogels. Four precursors could be individually synthesized in one to two reaction steps and characterized, then assembled to form hydrogel adhesives. The convergent synthesis allows us to combine materials of different natures to generate matrices with high adhesive strength, enhanced electroconductivity, good cytocompatibility in vitro and high biocompatibility in vivo. The reversible networks exhibit self-healing and shear-thinning properties, thus allowing for 3D printing and minimally invasive injection for in vivo experiments.

A Tug of War Between Condensate Phases in a Minimal Macromolecular System

Membraneless organelles formed via liquid-liquid phase separation (LLPS) contain a multitude of macromolecular species. A few of these species drive LLPS while most serve as regulators. The LLPS of SH35 (S) and PRM5 (P), two oppositely charged protein constructs, was promoted by a polyanion heparin (H) but suppressed by a cationic protein lysozyme (L). Here, using these four components alone, we demonstrate complex phase behaviors associated with membraneless organelles and uncover the underlying physical rules. The S:P, S:L, and P:H binaries form droplets, but the H:L binary forms precipitates, therefore setting off a tug of water between different phases within the S:P:H:L quaternary. We observe dissolution of precipitates upon compositional change, transformation from precipitates to droplet-like condensates over time, and segregation of S:L-rich and P:H-rich foci inside droplet-like condensates. A minimal macromolecular system can thus recapitulate membraneless organelles in essential ways and provide crucial physical understanding.

Bayesian weighing of electron cryo-microscopy data for integrative structural modeling

SummaryCryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternative structural models of a macromolecular system based on their consistency with a cryo-EM density map and other experimental and prior information. The accuracy of this approach is benchmarked using complexes of known structure and illustrated in three applications: the structural determination of the GroEL/GroES, RNA polymerase II, and exosome complexes. The approach is implemented in the open-source Integrative Modeling Platform (http://integrativemodeling.org), thus enabling integrative structure determination by combining cryo-EM data with other sources of information.HighlightsWe present a modeling approach to integrate cryo-EM data with other sources of informationWe benchmark our approach using synthetic data on 21 complexes of known structureWe apply our approach to the GroEL/GroES, RNA polymerase II, and exosome complexes