Asymmetry in Polymer-Solvent Interactions Yields Complex Thermoresponsive Behavior.

We introduce a lattice framework that incorporates elements of Flory-Huggins solution theory and the q-state Potts model to study the phase behavior of polymer solutions and single-chain conformational characteristics. Without empirically introducing temperature-dependent interaction parameters, standard Flory-Huggins theory describes systems that are either homogeneous across temperatures or exhibit upper critical solution temperatures. The proposed Flory-Huggins-Potts framework extends these capabilities by predicting lower critical solution temperatures, miscibility loops, and hourglass-shaped spinodal curves. We particularly show that including orientation-dependent interactions, specifically between monomer segments and solvent particles, is alone sufficient to observe such phase behavior. Signatures of emergent phase behavior are found in single-chain Monte Carlo simulations, which display heating- and cooling-induced coil-globule transitions linked to energy fluctuations. The framework also capably describes a range of experimental systems. Importantly, and by contrast to many prior theoretical approaches, the framework does not employ any temperature- or composition-dependent parameters. This work provides new insights regarding the microscopic physics that underpin complex thermoresponsive behavior in polymers.

Using MitER for 3D analysis of mitochondrial morphology and ER contacts.

We have developed an open-source workflow that allows for quantitative single-cell analysis of organelle morphology, distribution, and inter-organelle contacts with an emphasis on the analysis of mitochondria and mitochondria-endoplasmic reticulum (mito-ER) contact sites. As the importance of inter-organelle contacts becomes more widely recognized, there is a concomitant increase in demand for tools to analyze subcellular architecture. Here, we describe a workflow we call MitER (pronounced "mightier"), which allows for automated calculation of organelle morphology, distribution, and inter-organelle contacts from 3D renderings by employing the animation software Blender. We then use MitER to quantify the variations in the mito-ER networks of Saccharomyces cerevisiae, revealing significantly more mito-ER contacts within respiring cells compared to fermenting cells. We then demonstrate how this workflow can be applied to mammalian systems and used to monitor mitochondrial dynamics and inter-organelle contact in time-lapse studies.