DNA-Binding Protein Dps Protects Escherichia coli Cells against Multiple Stresses during Desiccation

Gradual dehydration is one of the frequent lethal yet poorly understood stresses that bacterial cells constantly face in the environment when their micro ecotopes dry out, as well as in industrial processes. Bacteria successfully survive extreme desiccation through complex rearrangements at the structural, physiological, and molecular levels, in which proteins are involved. The DNA-binding protein Dps has previously been shown to protect bacterial cells from many adverse effects. In our work, using engineered genetic models of E. coli to produce bacterial cells with overproduction of Dps protein, the protective function of Dps protein under multiple desiccation stresses was demonstrated for the first time. It was shown that the titer of viable cells after rehydration in the experimental variants with Dps protein overexpression was 1.5-8.5 times higher. Scanning electron microscopy was used to show a change in cell morphology upon rehydration. It was also proved that immobilization in the extracellular matrix, which is greater when the Dps protein is overexpressed, helps the cells survive. Transmission electron microscopy revealed disruption of the crystal structure of DNA-Dps crystals in E. coli cells that underwent desiccation stress and subsequent watering. Coarse-grained molecular dynamics simulations showed the protective function of Dps in DNA-Dps co-crystals during desiccation. The data obtained are important for improving biotechnological processes in which bacterial cells undergo desiccation.

In Silico Screening for Solid Dispersions: The Trouble with Solubility Parameters and χFH

The problem of predicting small molecule-polymer compatibility is relevant to many areas of chemistry and pharmaceutical science but particularly drug delivery. Computational methods based on Hildebrand and Hansen solubility parameters, and the estimation of the Flory-Huggins parameter, χ, have proliferated across the literature. Focusing on the need to develop amorphous solid dispersions to improve the bioavailability of poorly soluble drug candidates, an innovative, high-throughput 2D printing method has been employed to rapidly assess the compatibility of 54 drug-polymer pairings (nine drug compounds in six polymers). In this study, the first systematic assessment of the in silico methods for this application, neither the solubility parameter approach nor the calculated χ, correctly predicted drug-polymer compatibility. The theoretical limitations of the solubility parameter approach are discussed and used to explain why this approach is fundamentally unsuitable for predicting polymer-drug interactions. Examination of the original sources describing the method for calculating χ shows that only the enthalpic contributions to the term have been included, and the corrective entropic term is absent. The development and application of new in silico techniques, that consider all parts of the free energy of mixing, are needed in order to usefully predict small molecule-polymer compatibility and to realize the ambition of a drug-polymer screening method.