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Abstract Small, spherical vesicles are a widely used chassis for the formation of model protocells and investigating the beginning of compartmentalized evolution. Various methods exist for their preparation, with one of the most common approaches being gentle hydration, where thin layers of lipids are hydrated with aqueous solutions and gently agitated to form vesicles. An important benefit to gentle hydration is that the method produces vesicles without introducing any organic contaminants, such as mineral oil, into the lipid bilayer. However, compared to other methods of liposome formation, gentle hydration is much less efficient at encapsulating aqueous cargo. Improving the encapsulation efficiency of gentle hydration would be of broad use for medicine, biotechnology, and protocell research. Here, we describe a method of sequentially hydrating lipid thin films to increase encapsulation efficiency. We demonstrate that sequential gentle hydration significantly improves encapsulation of water-soluble cargo compared to the traditional method, and that this improved efficiency is dependent on buffer composition. Similarly, we also demonstrate how this method can be used to increase concentrations of oleic acid, a fatty acid commonly used in origins of life research, to improve the formation of vesicles in aqueous buffer. 

Abstract Small, spherical vesicles are a widely used chassis for the formation of model protocells and investigating the beginning of compartmentalized evolution. Various methods exist for their preparation, with one of the most common approaches being gentle hydration, where thin layers of lipids are hydrated with aqueous solutions and gently agitated to form vesicles. An important benefit to gentle hydration is that the method produces vesicles without introducing any organic contaminants, such as mineral oil, into the lipid bilayer. However, compared to other methods of liposome formation, gentle hydration is much less efficient at encapsulating aqueous cargo. Improving the encapsulation efficiency of gentle hydration would be of broad use for medicine, biotechnology, and protocell research. Here, we describe a method of sequentially hydrating lipid thin films to increase encapsulation efficiency. We demonstrate that sequential gentle hydration significantly improves encapsulation of water-soluble cargo compared to the traditional method, and that this improved efficiency is dependent on buffer composition. Similarly, we also demonstrate how this method can be used to increase concentrations of oleic acid, a fatty acid commonly used in origins of life research, to improve the formation of vesicles in aqueous buffer. 

Abstract Compartments within living cells create specialized microenvironments, allowing for multiple reactions to be carried out simultaneously and efficiently. While some organelles are bound by a lipid bilayer, others are formed by liquid-liquid phase separation, such as P-granules and nucleoli. Synthetic minimal cells have been widely used to study many natural processes, including organelle formation. Here we describe a synthetic cell expressing RGG-GFP-RGG, a phase-separating protein derived from LAF-1 RGG domains, to form artificial membraneless organelles that can sequester RNA and reduce protein expression. We create complex microenvironments within synthetic cell cytoplasm and introduce a tool to modulate protein expression in synthetic cells. Engineering of compartments within synthetic cells furthers understanding of evolution and function of natural organelles, as well as it facilitates the creation of more complex and multifaceted synthetic life-like systems. 

Designing an efficient arithmetic division circuit has long been a major challenge. Traditional binary computation methods rely on complex algorithms that require multiple cycles, complex control logic, and substantial hardware resources. Implementing division with emerging in-memory computing technologies is even more challenging due to susceptibility to noise, process variation, and the complexity of binary division. In this work, we propose an in-memory division architecture leveraging stochastic computing (SC), an emerging technology known for its high fault tolerance and low-cost design. Our approach utilizes a magnetic tunnel junction (MTJ)-based memory architecture to efficiently execute logic-in-memory operations. Experimental results across various process variation conditions demonstrate the robustness of our method against hardware variations. To assess its practical effectiveness, we apply our approach to the Retinex Algorithm for image enhancement, demonstrating its viability in real-world applications. 

Computing equilibrium concentrations of molecular complexes is generally analytically intractable and requires numerical approaches. In this work we focus on the polymer-monomer level, where indivisible molecules (monomers) combine to form complexes (polymers). Rather than employing free-energy parameters for each polymer, we focus on the athermic setting where all interactions preserve enthalpy. This setting aligns with the strongly bonded (domain-based) regime in DNA nanotechnology when strands can bind in different ways, but always with maximum overall bonding - and is consistent with the saturated configurations in the Thermodynamic Binding Networks (TBNs) model. Within this context, we develop an iterative algorithm for assigning polymer concentrations to satisfy detailed-balance, where on-target (desired) polymers are in high concentrations and off-target (undesired) polymers are in low. Even if not directly executed, our algorithm provides effective insights into upper bounds on concentration of off-target polymers, connecting combinatorial arguments about discrete configurations such as those in the TBN model to real-valued concentrations. We conclude with an application of our method to decreasing leak in DNA logic and signal propagation. Our results offer a new framework for design and verification of equilibrium concentrations when configurations are distinguished by entropic forces. 

Automated routing of droplets for DNA storage on an industrial-scale digital microfluidics platform.