Browsing by Author "Currie, Megan"

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    Macromolecular crowding effects on multi-scale diffusion of fluorescent probes
    (2017-05) Currie, Megan
    Living cells are crowded with a diverse population of macromolecules and organelles. It is not clear how macromolecular crowding affects the myriad of biochemical reactions, transport and structural stability of biomolecules that are essential to cellular function and survival. These molecular processes, with or without electrostatic interactions, in living cells are therefore expected to be distinct from those carried out in a test tube of dilute solutions where excluded volumes are absent. Thus there is an urgent need to understand the macromolecular crowding effects on cellular and molecular biophysics towards quantitative cell biology. The goal of this project is to investigate how biomimetic crowding affects both the rotational and translation diffusion of three size-dependent probes: RhG110 (507 Da), eGFP (32.7 kDa) and a FRET sensor (64 kDa). For biomimetic crowding agents, we used glycerol (homogeneous viscosity), Ficoll-70 (synthetic polymer), as well as bovine serum albumin and ovalbumin (proteins) at variable concentrations in a buffer at room temperature. The corresponding bulk viscosity was measured independently to test the validity of the Stokes-Einstein model of a diffusing species undergoing a random walk. For rotational diffusion (ps–ns time scale), we used time-resolved anisotropy measurements to examine interactions between our molecular probe and crowding agent a function of the crowding agents (surface structure and size). For translational diffusion (µs–s time scale), we used fluorescence correlation spectroscopy for single-molecule fluctuation analysis. Our results allow us to examine the diffusion model of a molecular probe in crowded environments as a function of concentration, length scale, homogeneous versus heterogeneous viscosity, size, and surface structures. These biomimetic crowding studies using non-invasive fluorescence spectroscopy methods represent an important step towards understanding cellular biophysics and quantitative cell biology.