Biomolecules can undergo liquid-liquid phase separation (LLPS), forming dense droplets that are increasingly understood to be important for cellular function. Analogous systems are studied as early-life compartmentalization mechanisms, for applications as protocells, or as drug-delivery vehicles. In many of these situations, interactions between the droplet and enzymatic solutes are important to achieve certain functions. To explore this, we carried out experiments in which a model LLPS system, formed from DNA `nanostar' particles, interacted with a DNA-cleaving restriction enzyme, Sma~I, whose activity degraded the droplets, causing them to shrink with time. By controlling adhesion of the DNA droplet to a glass surface, we were able to carry out time-resolved imaging of this `active dissolution' process. We found that the scaling properties of droplet shrinking were sensitive to the proximity to the dissolution  (`boiling') temperature of the dense liquid: for systems far from the boiling point, enzymes acted only on the droplet surface, while systems poised near the boiling point permitted enzyme penetration. This was corroborated by the observation of enzyme-induced vacuole-formation (`bubbling') events, which can only occur through enzyme internalization, and which occurred only in systems poised near the boiling point. Overall, our results demonstrate a mechanism through which the phase stability of a liquid affects its enzymatic degradation through modulation of enzyme transport properties.

Dataset collection is described fully in the associated paper.

The text below replicates the usage notes contained in the 'ReadMe' file contained within the archive.

This document describes the data repository associated with the paper “Enzymatic degradation of liquid droplets of DNA is modulated near the phase boundary”, by Omar A. Saleh, Byoung-jin Jeon, and Tim Liedl.
The repository consists of a single .zip archive containing 11 files. The files are:

-This ReadMe file
-Six files containing trajectories of the radius of droplets versus time. These files are all .csv, and are the raw data underlying Figs. 2, S7 and S8 of the paper. The filename indicates the Figure and droplet type associated with each dataset. The data itself is stored with each row corresponding to a single droplet, and each column to a single time point. Time points are spaced by 1 minute, and begin at the 40 minute point. Values are radii, as outputted from the precision fitting routine, in units of camera pixels. To convert to microns, multiply by 1.6.
-Two files showing code associated with the high-resolution radius measurement. In fact, there are two copies of the same file, one formatted as a Mathematica notebook (.nb), and the other as a pdf. This shows how the processing of a camera image, including segmenting of ROIs around droplets, construction of the radial intensity distribution, and fitting to the distribution expected for a sphere. Refer to Figure S4 for details. 
-Two files showing code associated with the diffusion analysis. Again, there are two copies of the same file, one formatted as a Mathematica notebook (.nb), and the other as a pdf. This shows the calculations described in Section S1, along with the making of the plots in Fig S1 and Fig 3.