optimize these pathways and thus to guarantee their maximum chance of survival, cells produce enzymes at precise and constant rates. [4] However, because of cellular complexity, determination of optimal enzyme levels is still unclear, in particular because specific enzymatic functions are strongly interconnected with their cascade effects. [5] A smart manner to study the behavior of enzymes, when involved in complex reactions, consists of taking advantage of synthetic micrometer-sized compartments shaped into spherical architectural bodies. [6-8] Though these idealized models favor even partitioning of membrane proteins and simplify diffusion gradients, similarly to cells, they provide the desired membrane selectivity and permeability. [9,10] Single specific functions have been presented by combining enzymes (the catalytic compounds) with synthetic supramolecular assemblies, either intrinsically semipermeable, such as lipid-coated porous silica particles, [11] protein cages, [12] layer-by-layer capsules, [13-15] and polydopamine capsules, [16,17] or rendered permeable by the insertion of biopores/membrane proteins (acting as "gates" for the passage of molecules), as in lipid-based [7,18,19] or polymer-based [8,20-22] giant unilamellar vesicles (GUVs). At present, GUVs formed with amphiphilic block copolymers are particularly appealing because they provide enhanced structural membrane properties compared to lipids, since they possess compartments with higher chemical versatility, controlled permeability, robustness, and stability. [23] Nevertheless, common approaches to form polymer GUVs by self-assembly, as electroformation [24] and film-rehydration, [25] rely on the statistical process of encapsulation of biomolecules with a probability of finding the designed amount of one type of enzyme inside the compartments ranging from 12-57%. In the context of elementary biochemical pathways where at least two enzymes are present, this scenario is even more unsatisfactory, with co-encapsulation of two enzymes inside one compartment as low as 10-22%. [26,27] These shortcomings are worsened by the fact that these probabilities have a large uncertainty induced by specific properties of enzymes (e.g., solubility and stability). To date, scientists have struggled to work with stateof-the-art average values for number/mass of enzymes that are vastly non-representative (limited by a small sample size) Cells rely upon producing enzymes at precise rates and stoichiometry for maximizing functionalities. The reasons for this optimal control are unknown, primarily because of the interconnectivity of the enzymatic cascade effects within multi-step pathways. Here, an elegant strategy for studying such behavior, by controlling segregation/combination of enzymes/ metabolites in synthetic cell-sized compartments, while preserving vital cellular elements is presented. Therefore, compartments shaped into polymer GUVs are developed, producing via high-precision double-emulsion microfluidics that enable: i) tight control over the absolute and...

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The introduction of chirality into aqueous self-assemblies by employing isotactic block copolymers (BCPs) is an emerging field of interest as it promises special membrane properties of polymersomes not accessible by...

We have studied the primary nucleation of adipic acid from aqueous solutions in thousands of microdroplets generated in a fully automated microfluidic setup. By varying supersaturation in solution and residence time, we were able to estimate nucleation rates and growth times, while accounting for the stochastic nature of nucleation, the variability in microdroplet volumes (which is kept below 2%, thanks to a carefully designed experimental protocol), and the uncertainty in the automated image analysis procedure. Through a thorough statistical analysis we have obtained exact expressions for the expected values and the variances of all the random variables involved, all the way to the nucleation rate and the growth time associated with each supersaturation level explored and to the model parameters appearing in the corresponding constitutive equations. We have analyzed what controls the overall uncertainty in the estimation of the physical quantities above. We have shown that the distribution of droplet volumes at the level observed here is not limiting, whereas the detection technique and the image analysis algorithm play a critical role, together with the fact that the supersaturation levels and residence times that can be reasonably explored are limited. The tools and methods presented and made available to the scientific community will help in making microfluidics-based studies of nucleation more effective.

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