Catanionic surfactant vesicles for electrostatic molecular sequestration and separation.

Mixtures of oppositely charged surfactants, commonly called catanionic mixtures, are one of the most interesting and promising areas of colloidal chemistry. In this paper we review our previous work and report new results on electrostatic adsorption of organic solutes and DNA to the exterior surfaces of catanionic, unilamellar vesicles which form spontaneously in mixtures of sodium dodecylbenzenesulfonate (SDBS) and cetyltrimethylammonium tosylate (CTAT). Our group, along with others, has shown that organic ions and polyelectrolytes will bind to the exterior surface of oppositely charged catanionic vesicles through interactions with unpaired ionic surfactants present in the vesicle bilayer. The electrostatic sequestration of organic ions with catanionic vesicles is extremely efficient with excellent long-term stability and can be used to perform separations on mixtures of charged organic solutes. Using regular solution theory extended to vesicle-forming surfactant mixtures, we can understand how the composition of the bilayer changes with surfactant dilution, and we study this effect using fluorescence correlation spectroscopy (FCS). We employ FCS to make sensitive measurements of bilayer adsorption and compare the adsorption of a small molecular probe with that of a single-stranded, dye-labeled DNA molecule. From these FCS studies, adsorption isotherms can be obtained that report on the relative binding strengths of the two systems. The results show that DNA binds much more strongly to the exterior surface of positively charged catanionic vesicles, and can even stabilize vesicles at very low surfactant concentrations near the critical aggregation concentration (cac).

Three-Dimensional Spot Detection in Ratiometric Fluorescence Imaging For Measurement of Subcellular Organelles.

Lysosomes are subcellular organelles playing a vital role in the endocytosis process of the cell. Lysosomal acidity is an important factor in assuring proper functioning of the enzymes within the organelle, and can be assessed by labeling the lysosomes with pH-sensitive fluorescence probes. To enhance our understanding of the acidification mechanisms, the goal of this work is to develop a method that can accurately detect and characterize the acidity of each lysosome captured in ratiometric fluorescence images. We present an algorithm that utilizes the h-dome transformation and reconciles spots detected independently from two wavelength channels. We evaluated our algorithm using simulated images for which the exact locations were known. The h-dome algorithm achieved an f-score as high as 0.890. We also computed the fluorescence ratios from lysosomes in live HeLa cell images with known lysosomal pHs. Using leave-one-out cross-validation, we demonstrated that the new algorithm was able to achieve much better pH prediction accuracy than the conventional method.