Observation Volumes and γ-Factors in Two-Photon Fluorescence Fluctuation Spectroscopy

Fluorescence fluctuation spectroscopy has become an important measurement tool for investigating molecular dynamics, molecular interactions, and chemical kinetics in biological systems. Although the basic theory of fluctuation spectroscopy is well established, it is not widely recognized that saturation of the fluorescence excitation can dramatically alter the size and profile of the fluorescence observation volume from which fluorescence fluctuations are measured, even at relatively modest excitation levels. A precise model for these changes is needed for accurate analysis and interpretation of fluctuation spectroscopy data. We here introduce a combined analytical and computational approach to characterize the observation volume under saturating conditions and demonstrate how the variation in the volume is important in two-photon fluorescence correlation spectroscopy. We introduce a simple approach for analysis of fluorescence correlation spectroscopy data that can fully account for the effects of saturation, and demonstrate its success for characterizing the observed changes in both the amplitude and relaxation timescale of measured correlation curves. We also discuss how a quantitative model for the observed phenomena may be of broader importance in fluorescence fluctuation spectroscopy

The Intracellular Mobility of Nuclear Import Receptors and NLS Cargoes

We have investigated classical nuclear localization sequence (NLS) mediated protein trafficking by measuring biomolecular dynamics within living cells using two-photon fluorescence correlation spectroscopy. By directly observing the behavior of specific molecules in their native cellular environment, it is possible to uncover functional details that are not apparent from traditional biochemical investigations or functional assays. We show that the intracellular mobility of NLS cargoes and their import receptor proteins, karyopherin-α and karyopherin-β, can be robustly measured and that quantitative comparison of intracellular diffusion coefficients provides new insights into nuclear transport mechanisms. Import cargo complexes are assembled throughout the cytoplasm, and their diffusion is slower than predicted by molecular weight due to specific interactions. Analysis of NLS cargo diffusion in the cytoplasm indicates that these interactions are likely disrupted by NLS cargo binding. Our results suggest that delivery of import receptors and NLS cargoes to nuclear pores may complement selective translocation through the pores as a functional mechanism for regulating transport of proteins into the nucleus

Identifying a second component from simulated mixture data <i>via</i> incorrect single component analysis.

<p>These curves shown represent the chi-squared contours for the different fitting methods when fitting two-component data with a single component model. When the χ² value exceeds ∼1.3 we conclude that the single component analysis fails, indicating the presence of a second component in the sample. Four χ² surfaces demonstrate the boundary in parameter space for 1) FCS (green lines); 2) Fluorescence Lifetime (yellow lines); 3) Fluorescence Lifetime with average intensity constraint (blue lines); and 4) τFCS with average intensity constraint (red lines).</p

Molecular parameter values recovered using Global-τFCS compared to known parameter values.

<p>The accuracy of the recovered information goes well beyond previous experimental capabilities, which is more remarkable given that no fitting constraints or <i>a priori</i> assumptions were required for these fitting results.</p

τFCS analysis of binary dye mixtures with known R6G and RhB concentrations.

<p>(a) Recovery of molecular concentrations across nine known concentration ratios using τFCS. Measured concentrations are shown as red and blue squares, and the solid lines show the known concentration of each dye mixture. (b) Sample parameters detailing concentrations, diffusion coefficients, molecular brightnesses and fluorescence lifetimes of the prepared R6G and RhB mixtures. Recovery of RhB diffusion coefficient (c), molecular brightness (d), and fluorescence lifetime (e) respectively. Data points and error bars represent the average and standard deviation of three repeated experiments.</p

Phase Networks of Cross-β Peptide Assemblies

Recent evidence suggests that simple peptides can access diverse amphiphilic phases, and that these structures underlie the robust and widely distributed assemblies implicated in nearly 40 protein misfolding diseases. Here we exploit a minimal nucleating core of the Aβ peptide of Alzheimer’s disease to map its morphologically accessible phases that include stable intermolecular molten particles, fibers, twisted and helical ribbons, and nanotubes. Analyses with both fluorescence lifetime imaging microscopy (FLIM) and transmission electron microscopy provide evidence for liquid–liquid phase separations, similar to the coexisting dilute and dense protein-rich liquid phases so critical for the liquid–solid transition in protein crystallization. We show that the observed particles are critical for transitions to the more ordered cross-β peptide phases, which are prevalent in all amyloid assemblies, and identify specific conditions that arrest assembly at the phase boundaries. We have identified a size dependence of the particles in order to transition to the para-crystalline phase and a width of the cross-β assemblies that defines the transition between twisted fibers and helically coiled ribbons. These experimental results reveal an interconnected network of increasing molecularly ordered cross-β transitions, greatly extending the initial computational models for cross-β assemblies

Propagators and Time-Dependent Diffusion Coefficients for Anomalous Diffusion

Complex diffusive dynamics are often observed when one is investigating the mobility of macromolecules in living cells and other complex environments, yet the underlying physical or chemical causes of anomalous diffusion are often not fully understood and are thus a topic of ongoing research interest. Theoretical models capturing anomalous dynamics are widely used to analyze mobility data from fluorescence correlation spectroscopy and other experimental measurements, yet there is significant confusion regarding these models because published versions are not entirely consistent and in some cases do not appear to satisfy the diffusion equation. Further confusion is introduced through variations in how fitting parameters are reported. A clear definition of fitting parameters and their physical significance is essential for accurate interpretation of experimental data and comparison of results from different studies acquired under varied experimental conditions. This article aims to clarify the physical meaning of the time-dependent diffusion coefficients associated with commonly used fitting models to facilitate their use for investigating the underlying causes of anomalous diffusion. We discuss a propagator for anomalous diffusion that captures the power law dependence of the mean-square displacement and can be shown to rigorously satisfy the extended diffusion equation provided one correctly defines the time-dependent diffusion coefficient. We also clarify explicitly the relation between the time-dependent diffusion coefficient and fitting parameters in fluorescence correlation spectroscopy