Role of Negatively Charged Lipids Achieving Rapid Accumulation of Water-Soluble Molecules and Macromolecules into Cell-Sized Liposomes against a Concentration Gradient

Uphill Accumulation of Ionic Species into a Lipid Vesicle by the Concentration Gradient of Counter Ions

The "uphill (against the concentration gradient)" accumulation of a hydrophobic cation (rhodamine 6G, R6G⁺) into the inner phase of a giant unilamellar vesicle (GUV) was realized with the concentration gradient of the counter anion (X^- = ClO₄^-, BF₄^-, or Br^-) in the presence of phosphate buffer (P^-, pH = 7) in the inner and outer phase of the GUV and detected as the increase of the R6G⁺ fluorescence intensity in the inner phase using a confocal laser scanning fluorescence microscope. The addition of X^- in the outer phase of the GUV caused the accumulation of R6G⁺ in the inner phase. The degree and kinetics of the accumulation were dependent on the concentration and type of X^-; e.g., the inner concentration of R6G⁺ reached 2.5 times that in the outer phase of GUV after adding 10 mM ClO₄^-. The accumulation was theoretically simulated by assuming the distribution of ion pairs (R6G⁺ and X^-, R6G⁺, and P^-) between the aqueous phase and the lipid bilayer membrane (ion pair distribution model) and the transmembrane fluxes of R6G⁺, X^- and P^-. The theoretical simulation rationalized the accumulation degree and kinetics of the experimental results. The accumulation of the target cation by the concentration gradient of the counter anion demonstrated in this study can be an effective method for the preparation of liposomal drugs.

Machine-Learning-Enabled Design and Manipulation of a Microfluidic Concentration Gradient Generator

Microfluidics concentration gradient generators have been widely applied in chemical and biological fields. However, the current gradient generators still have some limitations. In this work, we presented a microfluidic concentration gradient generator with its corresponding manipulation process to generate an arbitrary concentration gradient. Machine-learning techniques and interpolation algorithms were implemented to help researchers instantly analyze the current concentration profile of the gradient generator with different inlet configurations. The proposed method has a 93.71% accuracy rate with a 300× acceleration effect compared to the conventional finite element analysis. In addition, our method shows the potential application of the design automation and computer-aided design of microfluidics by leveraging both artificial neural networks and computer science algorithms.

Membrane Cargo Density-Dependent Interaction between Protein and Lipid Domains on the Giant Unilamellar Vesicles

Protein cargos anchored on the lipid membrane can be segregated by fluidic domain phase separation. Lipid membranes at certain compositions may separate into lipid domains to segregate cargos, and protein cargos themselves may be involved in protein condensate domain formation with multivalent binding proteins to segregate cargos. Recent studies suggest that these two driving forces of phase separation closely interact on the lipid membranes to promote codomain formation. In this report, we studied the effect of cargo density on the outcome of the cargo phase separation on giant unilamellar vesicles. Proteins and lipids are connected only by the anchored cargos, so it was originally hypothesized that higher cargo density would increase the degree of interaction between the lipid and protein domains, promoting more phase separation. However, fluorescence image analysis on different cargo densities showed that the cooperative domain formation and steric pressure are at a tug of war opposing each other. Cooperative domain formation is dominant under lower anchor density conditions, and above a threshold density, steric pressure was dominant opposing the domain formation. The result suggests that the cargo density is a key parameter affecting the outcome of cargo organization on the lipid membranes by phase separation.

Identifying and Manipulating Giant Vesicles: Review of Recent Approaches

Giant vesicles (GVs) are closed bilayer membranes that primarily comprise amphiphiles with diameters of more than 1 μm. Compared with regular vesicles (several tens of nanometers in size), GVs are of greater scientific interest as model cell membranes and protocells because of their structure and size, which are similar to those of biological systems. Biopolymers and nano-/microparticles can be encapsulated in GVs at high concentrations, and their application as artificial cell bodies has piqued interest. It is essential to develop methods for investigating and manipulating the properties of GVs toward engineering applications. In this review, we discuss current improvements in microscopy, micromanipulation, and microfabrication technologies for progress in GV identification and engineering tools. Combined with the advancement of GV preparation technologies, these technological advancements can aid the development of artificial cell systems such as alternative tissues and GV-based chemical signal processing systems.