Image correlation spectroscopy: mapping correlations in space, time, and reciprocal space

Of numbers and movement - understanding transcription factor pathogenesis by advanced microscopy

Transcription factors (TFs) are life-sustaining and, therefore, the subject of intensive research. By regulating gene expression, TFs control a plethora of developmental and physiological processes, and their abnormal function commonly leads to various developmental defects and diseases in humans. Normal TF function often depends on gene dosage, which can be altered by copy-number variation or loss-of-function mutations. This explains why TF haploinsufficiency (HI) can lead to disease. Since aberrant TF numbers frequently result in pathogenic abnormalities of gene expression, quantitative analyses of TFs are a priority in the field. In vitro single-molecule methodologies have significantly aided the identification of links between TF gene dosage and transcriptional outcomes. Additionally, advances in quantitative microscopy have contributed mechanistic insights into normal and aberrant TF function. However, to understand TF biology, TF-chromatin interactions must be characterised in vivo, in a tissue-specific manner and in the context of both normal and altered TF numbers. Here, we summarise the advanced microscopy methodologies most frequently used to link TF abundance to function and dissect the molecular mechanisms underlying TF HIs. Increased application of advanced single-molecule and super-resolution microscopy modalities will improve our understanding of how TF HIs drive disease.

Raster Image Correlation Spectroscopy Performance Evaluation

Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracting the mobility, concentration, and stoichiometry of diffusing fluorescent molecules from confocal image stacks. The method works by calculating a spatial correlation function for each image and analyzing the average of those by model fitting. Rules of thumb exist for RICS image acquisitioning, yet a rigorous theoretical approach to predict the accuracy and precision of the recovered parameters has been lacking. We outline explicit expressions to reveal the dependence of RICS results on experimental parameters. In terms of imaging settings, we observed that a twofold decrease of the pixel size, e.g., from 100 to 50 nm, decreases the error on the translational diffusion constant (D) between three- and fivefold. For D = 1 μm2 s-1, a typical value for intracellular measurements, ∼25-fold lower mean-squared relative error was obtained when the optimal scan speed was used, although more drastic improvements were observed for other values of D. We proposed a slightly modified RICS calculation that allows correcting for the significant bias of the autocorrelation function at small (≪50 × 50 pixels) sizes of the region of interest. In terms of sample properties, at molecular brightness E = 100 kHz and higher, RICS data quality was sufficient using as little as 20 images, whereas the optimal number of frames for lower E scaled pro rata. RICS data quality was constant over the nM-μM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical least-squares approach in terms of coverage probability of the true value of D. We validated the theory via in vitro experiments of enhanced green fluorescent protein at different buffer viscosities. Finally, we outline robust practical guidelines and provide free software to simulate the parameter effects on recovery of the diffusion coefficient.

Fluorescence fluctuation spectroscopy: an invaluable microscopy tool for uncovering the biophysical rules for navigating the nuclear landscape

Nuclear architecture is fundamental to the manner by which molecules traverse the nucleus. The nucleoplasm is a crowded environment where dynamic rearrangements in local chromatin compaction locally redefine the space accessible toward nuclear protein diffusion. Here, we review a suite of methods based on fluorescence fluctuation spectroscopy (FFS) and how they have been employed to interrogate chromatin organization, as well as the impact this structural framework has on nuclear protein target search. From first focusing on a set of studies that apply FFS to an inert fluorescent tracer diffusing inside the nucleus of a living cell, we demonstrate the capacity of this technology to measure the accessibility of the nucleoplasm. Then with a baseline understanding of the exploration volume available to nuclear proteins during target search, we review direct applications of FFS to fluorescently labeled transcription factors (TFs). FFS can detect changes in TF mobility due to DNA binding, as well as the formation of TF complexes via changes in brightness due to oligomerization. Collectively, we find that FFS-based methods can uncover how nuclear proteins in general navigate the nuclear landscape.

Image Correlation Spectroscopy with Second Harmonic Generating Nanoparticles in Suspension and in Cells

The absence of photobleaching, blinking, and saturation combined with a high contrast provides unique advantages of higher-harmonic generating nanoparticles over fluorescent probes, allowing for prolonged correlation spectroscopy studies. We apply the coherent intensity fluctuation model to study the mobility of second harmonic generating nanoparticles. A concise protocol is presented for quantifying the diffusion coefficient from a single spectroscopy measurement without the need for separate point-spread-function calibrations. The technique's applicability is illustrated on nominally 56 nm LiNbO₃ nanoparticles. We perform label-free raster image correlation spectroscopy imaging in aqueous suspension and spatiotemporal image correlation spectroscopy in A549 human lung carcinoma cells. In good agreement with the expected theoretical result, the measured diffusion coefficient in water at room temperature is (7.5 ± 0.3) μm²/s. The diffusion coefficient in the cells is more than 10³ times lower and heterogeneous, with an average of (3.7 ± 1.5) × 10^-3 μm²/s.

Ligand-Induced Coupling between Oligomers of the M2 Receptor and the Gi1 Protein in Live Cells

Uncertainty over the mechanism of signaling via G protein-coupled receptors (GPCRs) relates in part to questions regarding their supramolecular structure. GPCRs and heterotrimeric G proteins are known to couple as monomers under various conditions. Many GPCRs form oligomers under many of the same conditions, however, and the biological role of those complexes is unclear. We have used dual-color fluorescence correlation spectroscopy to identify oligomers of the M₂ muscarinic receptor and of G_i1 in purified preparations and live Chinese hamster ovary cells. Measurements on differently tagged receptors (i.e., eGFP-M₂ and mCherry-M₂) and G proteins (i.e., eGFP-Gα_i1β₁γ₂ and mCherry-Gα_i1β₁γ₂) detected significant cross-correlations between the two fluorophores in each case, both in detergent micelles and in live cells, indicating that both the receptor and G_i1 can exist as homo-oligomers. Oligomerization of differently tagged G_i1 decreased upon the activation of co-expressed wild-type M₂ receptor by an agonist. Measurements on a tagged M₂ receptor (M₂-mCherry) and eGFP-Gα_i1β₁γ₂ co-expressed in live cells detected cross-correlations only in the presence of an agonist, which therefore promoted coupling of the receptor and the G protein. The effect of the agonist was retained when a fluorophore-tagged receptor lacking the orthosteric site (i.e., M₂(D103A)-mCherry) was co-expressed with the wild-type receptor and eGFP-Gα_i1β₁γ₂, indicating that the ligand acted via an oligomeric receptor. Our results point to a model in which an agonist promotes transient coupling of otherwise independent oligomers of the M₂ receptor on the one hand and of G_i1 on the other and that an activated complex leads to a reduction in the oligomeric size of the G protein. They suggest that GPCR-mediated signaling proceeds, at least in part, via oligomers.

PAM: A Framework for Integrated Analysis of Imaging, Single-Molecule, and Ensemble Fluorescence Data

Fluorescence microscopy and spectroscopy data hold a wealth of information on the investigated molecules, structures, or organisms. Nowadays, the same fluorescence data set can be analyzed in many ways to extract different properties of the measured sample. Yet, doing so remains slow and cumbersome, often requiring incompatible software packages. Here, we present PAM (pulsed interleaved excitation analysis with MATLAB), an open-source software package written in MATLAB that offers a simple and efficient workflow through its graphical user interface. PAM is a framework for integrated and robust analysis of fluorescence ensemble, single-molecule, and imaging data. Although it was originally developed for the analysis of pulsed interleaved excitation experiments, PAM has since been extended to support most types of data collection modalities. It combines a multitude of powerful analysis algorithms, ranging from time- and space-correlation analysis, over single-molecule burst analysis, to lifetime imaging microscopy, while offering intrinsic support for multicolor experiments. We illustrate the key concepts and workflow of the software by discussing data handling and sorting and provide step-by-step descriptions for the individual usage cases.

Fluctuation correlation models for receptor immobilization

Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.

Investigating the effect of poly-l-lactic acid nanoparticles carrying hypericin on the flow-biased diffusive motion of HeLa cell organelles

OBJECTIVES

In this study, we investigate in human cervical epithelial HeLa cells the intracellular dynamics and the mutual interaction with the organelles of the poly-l-lactic acid nanoparticles (PLLA NPs) carrying the naturally occurring hydrophobic photosensitizer hypericin.

METHODS

Temporal and spatiotemporal image correlation spectroscopy was used for the assessment of the intracellular diffusion and directed motion of the nanocarriers by tracking the hypericin fluorescence. Using image cross-correlation spectroscopy and specific fluorescent labelling of endosomes, lysosomes and mitochondria, the NPs dynamics in association with the cell organelles was studied. Static colocalization experiments were interpreted according to the Manders' overlap coefficient.

KEY FINDINGS

Nanoparticles associate with a small fraction of the whole-organelle population. The organelles moving with NPs exhibit higher directed motion compared to those moving without them. The rate of the directed motion drops substantially after the application of nocodazole. The random component of the organelle motions is not influenced by the NPs.

CONCLUSIONS

Image correlation and cross-correlation spectroscopy are most appropriate to unravel the motion of the PLLA nanocarrier and to demonstrate that the rate of the directed motion of organelles is influenced by their interaction with the nanocarriers. Not all PLLA-hypericin NPs are associated with organelles.

3D Protein Dynamics in the Cell Nucleus

The three-dimensional (3D) architecture of the cell nucleus plays an important role in protein dynamics and in regulating gene expression. However, protein dynamics within the 3D nucleus are poorly understood. Here, we present, to our knowledge, a novel combination of 1) single-objective based light-sheet microscopy, 2) photoconvertible proteins, and 3) fluorescence correlation microscopy, to quantitatively measure 3D protein dynamics in the nucleus. We are able to acquire >3400 autocorrelation functions at multiple spatial positions within a nucleus, without significant photobleaching, allowing us to make reliable estimates of diffusion dynamics. Using this tool, we demonstrate spatial heterogeneity in Polymerase II dynamics in live U2OS cells. Further, we provide detailed measurements of human-Yes-associated protein diffusion dynamics in a human gastric cancer epithelial cell line.

3D full-field quantification of cell-induced large deformations in fibrillar biomaterials by combining non-rigid image registration with label-free second harmonic generation

To advance our current understanding of cell-matrix mechanics and its importance for biomaterials development, advanced three-dimensional (3D) measurement techniques are necessary. Cell-induced deformations of the surrounding matrix are commonly derived from the displacement of embedded fiducial markers, as part of traction force microscopy (TFM) procedures. However, these fluorescent markers may alter the mechanical properties of the matrix or can be taken up by the embedded cells, and therefore influence cellular behavior and fate. In addition, the currently developed methods for calculating cell-induced deformations are generally limited to relatively small deformations, with displacement magnitudes and strains typically of the order of a few microns and less than 10% respectively. Yet, large, complex deformation fields can be expected from cells exerting tractions in fibrillar biomaterials, like collagen. To circumvent these hurdles, we present a technique for the 3D full-field quantification of large cell-generated deformations in collagen, without the need of fiducial markers. We applied non-rigid, Free Form Deformation (FFD)-based image registration to compute full-field displacements induced by MRC-5 human lung fibroblasts in a collagen type I hydrogel by solely relying on second harmonic generation (SHG) from the collagen fibrils. By executing comparative experiments, we show that comparable displacement fields can be derived from both fibrils and fluorescent beads. SHG-based fibril imaging can circumvent all described disadvantages of using fiducial markers. This approach allows measuring 3D full-field deformations under large displacement (of the order of 10 μm) and strain regimes (up to 40%). As such, it holds great promise for the study of large cell-induced deformations as an inherent component of cell-biomaterial interactions and cell-mediated biomaterial remodeling.

An Intermittent Model for Intracellular Motions of Gold Nanostars by k-Space Scattering Image Correlation

Anisotropic metallic nanoparticles have been devised as powerful potential tools for in vivo imaging, photothermal therapy, and drug delivery thanks to plasmon-enhanced absorption and scattering cross sections, ease in synthesis and functionalization, and controlled cytotoxicity. The rational design of all these applications requires the characterization of the nanoparticles intracellular trafficking pathways. In this work, we exploit live-cell time-lapse confocal reflectance microscopy and image correlation in both direct and reciprocal space to investigate the intracellular transport of branched gold nanostars (GNSs). Different transport mechanisms, spanning from pure Brownian diffusion to (sub-)ballistic superdiffusion, are revealed by temporal and spatio-temporal image correlation spectroscopy on the tens-of-seconds timescale. According to these findings, combined with numerical simulations and with a Bayesian (hidden Markov model-based) analysis of single particle tracking data, we ascribe the superdiffusive, subballistic behavior characterizing the GNSs dynamics to a two-state switching between Brownian diffusion in the cytoplasm and molecular motor-mediated active transport. For the investigation of intermittent-type transport phenomena, we derive an analytical theoretical framework for Fourier-space image correlation spectroscopy (kICS). At first, we evaluate the influence of all the dynamic and kinetic parameters (the diffusion coefficient, the drift velocity, and the transition rates between the diffusive and the active transport regimes) on simulated kICS correlation functions. Then we outline a protocol for data analysis and employ it to derive whole-cell maps for each parameter underlying the GNSs intracellular dynamics. Capable of identifying even simpler transport phenomena, whether purely diffusive or ballistic, our intermittent kICS approach allows an exhaustive investigation of the dynamics of GNSs and biological macromolecules.

Measuring fast stochastic displacements of bio-membranes with dynamic optical displacement spectroscopy

Stochastic displacements or fluctuations of biological membranes are increasingly recognized as an important aspect of many physiological processes, but hitherto their precise quantification in living cells was limited due to a lack of tools to accurately record them. Here we introduce a novel technique—dynamic optical displacement spectroscopy (DODS), to measure stochastic displacements of membranes with unprecedented combined spatiotemporal resolution of 20 nm and 10 μs. The technique was validated by measuring bending fluctuations of model membranes. DODS was then used to explore the fluctuations in human red blood cells, which showed an ATP-induced enhancement of non-Gaussian behaviour. Plasma membrane fluctuations of human macrophages were quantified to this accuracy for the first time. Stimulation with a cytokine enhanced non-Gaussian contributions to these fluctuations. Simplicity of implementation, and high accuracy make DODS a promising tool for comprehensive understanding of stochastic membrane processes.

Precise quantification of stochastic motions of biological membranes is limited by a lack of suitable detection methods. Here Monzel et al. develop dynamic optical displacement spectroscopy to measure stochastic membrane displacements at 20 nm/10 μs spatiotemporal resolution.

Coherent intensity fluctuation model for autocorrelation imaging spectroscopy with higher harmonic generating point scatterers-a comprehensive theoretical study

We present a general analytical model for the intensity fluctuation autocorrelation function for second and third harmonic generating point scatterers. Expressions are derived for a stationary laser beam and for scanning beam configurations for specific correlation methodologies. We discuss free translational diffusion in both three and two dimensions. At low particle concentrations, the expressions for fluorescence are retrieved, while at high particle concentrations a rescaling of the function parameters is required for a stationary illumination beam, provided that the phase shift per unit length of the beam equals zero.

Intracellular dynamics and fate of polystyrene nanoparticles in A549 Lung epithelial cells monitored by image (cross-) correlation spectroscopy and single particle tracking

Novel insights in nanoparticle (NP) uptake routes of cells, their intracellular trafficking and subcellular targeting can be obtained through the investigation of their temporal and spatial behavior. In this work, we present the application of image (cross-) correlation spectroscopy (IC(C)S) and single particle tracking (SPT) to monitor the intracellular dynamics of polystyrene (PS) NPs in the human lung carcinoma A549 cell line. The ensemble kinetic behavior of NPs inside the cell was characterized by temporal and spatiotemporal image correlation spectroscopy (TICS and STICS). Moreover, a more direct interpretation of the diffusion and flow detected in the NP motion was obtained by SPT by monitoring individual NPs. Both techniques demonstrate that the PS NP transport in A549 cells is mainly dependent on microtubule-assisted transport. By applying spatiotemporal image cross-correlation spectroscopy (STICCS), the correlated motions of NPs with the early endosomes, late endosomes and lysosomes are identified. PS NPs were equally distributed among the endolysosomal compartment during the time interval of the experiments. The cotransport of the NPs with the lysosomes is significantly larger compared to the other cell organelles. In the present study we show that the complementarity of ICS-based techniques and SPT enables a consistent elaborate model of the complex behavior of NPs inside biological systems.

Recent applications of fluorescence correlation spectroscopy in live systems

Fluorescence correlation spectroscopy (FCS) is a widely used technique in biophysics and has helped address many questions in the life sciences. It provides important advantages compared to other fluorescence and biophysical methods. Its single molecule sensitivity allows measuring proteins within biological samples at physiological concentrations without the need of overexpression. It provides quantitative data on concentrations, diffusion coefficients, molecular transport and interactions even in live organisms. And its reliance on simple fluorescence intensity and its fluctuations makes it widely applicable. In this review we focus on applications of FCS in live samples, with an emphasis on work in the last 5 years, in the hope to provide an overview of the present capabilities of FCS to address biologically relevant questions.

Imaging fluorescence fluctuation spectroscopy: new tools for quantitative bioimaging

Fluorescence fluctuation spectroscopy (FFS) techniques provide information at the single-molecule level with excellent time resolution. Usually applied at a single spot in a sample, they have been recently extended into imaging formats, referred to as imaging FFS. They provide spatial information at the optical diffraction limit and temporal information in the microsecond to millisecond range. This review provides an overview of the different modalities in which imaging FFS techniques have been implemented and discusses present imaging FFS capabilities and limitations. A combination of imaging FFS and nanoscopy would allow one to record information with the detailed spatial information of nanoscopy, which is ∼20 nm and limited only by fluorophore size and labeling density, and the time resolution of imaging FFS, limited by the fluorescence lifetime. This combination would provide new insights into biological events by providing spatiotemporal resolution at unprecedented levels.