Fluorescence fluctuation microscopy: a diversified arsenal of methods to investigate molecular dynamics inside cells

Addressing spatiotemporal signal variations in pair correlation function analysis

Fluorescence correlation spectroscopy (FCS) is a cornerstone technique in optical microscopy to measure, for example, the concentration and diffusivity of fluorescent emitters and biomolecules in solution. The application of FCS to complex biological systems, however, is fraught with inherent intricacies that impair the interpretation of correlation patterns. Critical among these intricacies are temporal variations beyond diffusion in the quantity, intensity, and spatial distribution of fluorescent emitters. These variations introduce distortions into correlated intensity data, thus compromising the accuracy and reproducibility of the analysis. This issue is accentuated in imaging-based approaches such as pair correlation function (pCF) analysis due to their broader regions of interest compared with point-detector-based approaches. Despite ongoing developments in FCS, attention to systems characterized by a spatiotemporal-dependent probability distribution function (ST-PDF) has been lacking. To address this knowledge gap, we developed a new analytical framework for ST-PDF systems that introduces a dual-timescale model function within the conventional pCF analysis. Our approach selectively differentiates the signals associated with rapid processes, such as particle diffusion, from signals stemming from spatiotemporal variations in the distribution of fluorescent emitters occurring at extended delay timescales. To corroborate our approach, we conducted proof-of-concept experiments on an ST-PDF system, wherein the, initially, uniform distribution of fluorescent microspheres within a microfluidic channel changes into a localized accumulation of microspheres over time. Our framework is offering a comprehensive solution for investigating various phenomena such as biomolecular binding, sedimentation, and particle accumulation.

Studying Macromolecular Interactions of Cellular Machines by the Combined Use of Analytical Ultracentrifugation, Light Scattering, and Fluorescence Spectroscopy Methods

Cellular machines formed by the interaction and assembly of macromolecules are essential in many processes of the living cell. These assemblies involve homo- and hetero-associations, including protein-protein, protein-DNA, protein-RNA, and protein-polysaccharide associations, most of which are reversible. This chapter describes the use of analytical ultracentrifugation, light scattering, and fluorescence-based methods, well-established biophysical techniques, to characterize interactions leading to the formation of macromolecular complexes and their modulation in response to specific or unspecific factors. We also illustrate, with several examples taken from studies on bacterial processes, the advantages of the combined use of subsets of these techniques as orthogonal analytical methods to analyze protein oligomerization and polymerization, interactions with ligands, hetero-associations involving membrane proteins, and protein-nucleic acid complexes.

Fluorescence-Based Detection of Proteins and Their Interactions in Live Cells

Recent advances in fluorescence-based microscopy techniques, such as single molecule fluorescence, Förster resonance energy transfer (FRET), fluorescence intensity fluctuations analysis, and super-resolution microscopy have expanded our ability to study proteins in greater detail within their native cellular environment and to investigate the roles that protein interactions play in biological functions, such as inter- and intracellular signaling and cargo transport. In this Perspective, we provide an up-to-date overview of the current state of the art in fluorescence-based detection of proteins and their interactions in living cells with an emphasis on recent developments that have facilitated the characterization of the spatial and temporal organization of proteins into oligomeric complexes in the presence and absence of natural and artificial ligands. Further advancements in this field will only deepen our understanding of the underlying mechanisms of biological processes and help develop new therapeutic targets.

Insights into receptor structure and dynamics at the surface of living cells

Evaluating protein structures in living cells remains a challenge. Here, we investigate Interleukin-4 receptor alpha (IL-4Rα) into which the non-canonical amino acid bicyclo[6.1.0]nonyne-lysine (BCNK) is incorporated by genetic code expansion. Bioorthogonal click labeling is performed with tetrazine-conjugated dyes. To quantify the reaction yield in situ, we develop brightness-calibrated ratiometric imaging, a protocol where fluorescent signals in confocal multi-color images are ascribed to local concentrations. Screening receptor mutants bearing BCNK in the extracellular domain uncovered site-specific variations of both click efficiency and Interleukin-4 binding affinity, indicating subtle well-defined structural perturbations. Molecular dynamics and continuum electrostatics calculations suggest solvent polarization to determine site-specific variations of BCNK reactivity. Strikingly, signatures of differential click efficiency, measured for IL-4Rα in ligand-bound and free form, mirror sub-angstrom deformations of the protein backbone at corresponding locations. Thus, click efficiency by itself represents a remarkably informative readout linked to protein structure and dynamics in the native plasma membrane.

Multicolor fluorescence fluctuation spectroscopy in living cells via spectral detection

Signaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about intermolecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be implemented on commercial confocal microscopes, allowing the investigation of interactions between multiple protein species at the plasma membrane. We demonstrate that SFSCS enables cross-talk-free cross-correlation, diffusion, and oligomerization analysis of up to four protein species labeled with strongly overlapping fluorophores. As an example, we investigate the interactions of influenza A virus (IAV) matrix protein 2 with two cellular host factors simultaneously. We furthermore apply raster spectral image correlation spectroscopy for the simultaneous analysis of up to four species and determine the stoichiometry of ternary IAV polymerase complexes in the cell nucleus.

Analyses of p73 Protein Oligomerization and p73-MDM2 Interaction in Single Living Cells Using In Situ Single Molecule Spectroscopy

Protein oligomerization and protein-protein interaction are crucial to regulate protein functions and biological processes. p73 protein is a very important transcriptional factor and can promote apoptosis and cell cycle arrest, and its transcriptional activity is regulated by p73 oligomerization and p73-MDM2 interaction. Although extracellular studies on p73 oligomerization and p73-MDM2 interaction have been carried out, it is unclear how p73 oligomerization and p73-MDM2 interaction occur in living cells. In our study, we described an in situ method for studying p73 oligomerization and p73-MDM2 interaction in living cells by combining fluorescence cross-correlation spectroscopy with a fluorescent protein labeling technique. Lentiviral transfection was used to transfect cells with a plasmid for either p73 or MDM2, each fused to a different fluorescent protein. p73 oligomerization was evaluated using brightness per particle, and the p73-MDM2 interaction was quantified using the cross-correlation value. We constructed a series of p73 mutants in three domains (transactivation domain, DNA binding domain, and oligomerization domain) and MDM2 mutants. We systematically studied p73 oligomerization and the effects of p73 oligomerization and the p73 and MDM2 structures on the p73-MDM2 interaction in single living cells. We have found that the p73 protein can form oligomers and that the p73 structure changes in the oligomerization domain significantly influence its oligomerization. p73 oligomerization and the structure changes significantly affect the p73-MDM2 interaction. Furthermore, the effects of inhibitors on p73 oligomerization and p73-MDM2 interaction were studied.

A Method for High-Throughput Measurements of Viscosity in Sub-micrometer-Sized Membrane Systems

To unravel the underlying principles of membrane adaptation in small systems like bacterial cells, robust approaches to characterize membrane fluidity are needed. Currently available relevant methods require advanced instrumentation and are not suitable for high-throughput settings needed to elucidate the biochemical pathways involved in adaptation. We developed a fast, robust, and financially accessible quantitative method to measure the microviscosity of lipid membranes in bulk suspension using a commercially available plate reader. Our approach, which is suitable for high-throughput screening, is based on the simultaneous measurements of absorbance and fluorescence emission of a viscosity-sensitive fluorescent dye, 9-(2,2-dicyanovinyl)julolidine (DCVJ), incorporated into a lipid membrane. We validated our method using artificial membranes with various lipid compositions over a range of temperatures and observed values that were in good agreement with previously published results. Using our approach, we were able to detect a lipid phase transition in the ruminant pathogen Mycoplasma mycoides.

Determination of oligomerization state of Drp1 protein in living cells at nanomolar concentrations

Biochemistry in living cells is an emerging field of science. Current quantitative bioassays are performed ex vivo, thus equilibrium constants and reaction rates of reactions occurring in human cells are still unknown. To address this issue, we present a non-invasive method to quantitatively characterize interactions (equilibrium constants, K_D) directly within the cytosol of living cells. We reveal that cytosolic hydrodynamic drag depends exponentially on a probe's size, and provide a model for its determination for different protein sizes (1-70 nm). We analysed oligomerization of dynamin-related protein 1 (Drp1, wild type and mutants: K668E, G363D, C505A) in HeLa cells. We detected the coexistence of wt-Drp1 dimers and tetramers in cytosol, and determined that K_D for tetramers was 0.7 ± 0.5 μM. Drp1 kinetics was modelled by independent simulations, giving computational results which matched experimental data. This robust method can be applied to in vivo determination of K_D for other protein-protein complexes, or drug-target interactions.

Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies

The promyelocytic leukemia (pml) gene product PML is a tumor suppressor localized mainly in the nucleus of mammalian cells. In the cell nucleus, PML seeds the formation of macromolecular multiprotein complexes, known as PML nuclear bodies (PML NBs). While PML NBs have been implicated in many cellular functions including cell cycle regulation, survival and apoptosis their role as signaling hubs along major genome maintenance pathways emerged more clearly. However, despite extensive research over the past decades, the precise biochemical function of PML in these pathways is still elusive. It remains a big challenge to unify all the different previously suggested cellular functions of PML NBs into one mechanistic model. With the advent of genetically encoded fluorescent proteins it became possible to trace protein function in living specimens. In parallel, a variety of fluorescence fluctuation microscopy (FFM) approaches have been developed which allow precise determination of the biophysical and interaction properties of cellular factors at the single molecule level in living cells. In this report, we summarize the current knowledge on PML nuclear bodies and describe several fluorescence imaging, manipulation, FFM, and super-resolution techniques suitable to analyze PML body assembly and function. These include fluorescence redistribution after photobleaching, fluorescence resonance energy transfer, fluorescence correlation spectroscopy, raster image correlation spectroscopy, ultraviolet laser microbeam-induced DNA damage, erythrocyte-mediated force application, and super-resolution microscopy approaches. Since most if not all of the microscopic equipment to perform these techniques may be available in an institutional or nearby facility, we hope to encourage more researches to exploit sophisticated imaging tools for their research in cancer biology.

Out of the Randomness: Correlating Noise in Biological Systems

The study of the dynamics of biological systems requires one to follow relaxation processes in time with micron-size spatial resolution. This need has led to the development of different fluorescence correlation techniques with high spatial resolution and a tremendous (from nanoseconds to seconds) temporal dynamic range. Spatiotemporal information can be obtained even on complex dynamic processes whose time evolution is not forecast by simple Brownian diffusion. Our discussion of the most recent applications of image correlation spectroscopy to the study of anomalous sub- or superdiffusion suggests that this field still requires the development of multidimensional image analyses based on analytical models or numerical simulations. We focus in particular on the framework of spatiotemporal image correlation spectroscopy and examine the critical steps in getting information on anomalous diffusive processes from the correlation maps. We point out how a dual space-time correlative analysis, in both the direct and the Fourier space, can provide quantitative information on superdiffusional processes when these are analyzed through an empirical model based on intermittent active dynamics. We believe that this dual space-time analysis, potentially amenable to mathematical treatment and to the exact fit of experimental data, could be extended to include the rich phenomenology of subdiffusive processes, thereby quantifying relevant parameters for the various motivating biological problems of interest.

Fluorescence-based monitoring of electronic state and ion exchange kinetics with FCS and related techniques: from T-jump measurements to fluorescence fluctuations

In this review, we give a historical view of how our research in the development and use of fluorescence correlation spectroscopy (FCS) and related techniques has its roots and how it originally evolved from the pioneering work of Manfred Eigen, his colleagues, and coworkers. Work on temperature-jump (T-jump) experiments, conducted almost 50 years ago, led on to the development of the FCS technique. The pioneering work in the 1970s, introducing and demonstrating the concept for FCS, in turn formed the basis for the breakthrough use of FCS more than 15 years later. FCS can be used for monitoring reaction kinetics, based on fluctuations at thermodynamic equilibrium, rather than on relaxation measurements following perturbations. In this review, we more specifically discuss FCS measurements on photodynamic, electronic state transitions in fluorophore molecules, and on proton exchange dynamics in solution and on biomembranes. In the latter case, FCS measurements have proven capable of casting new light on the mechanisms of proton exchange at biological membranes, of central importance to bioenergetics and signal transduction. Finally, we describe the transient-state (TRAST) spectroscopy/imaging technique, sharing features with both relaxation (T-jump) and equilibrium fluctuation (FCS) techniques. TRAST is broadly applicable for cellular and molecular studies, and we briefly outline how TRAST can provide unique information from fluorophore blinking kinetics, reflecting e.g., cellular metabolism, rare molecular encounters, and molecular stoichiometries.

Photophysical Behavior of mNeonGreen, an Evolutionarily Distant Green Fluorescent Protein

Fluorescent proteins (FPs) feature complex photophysical behavior that must be considered when studying the dynamics of fusion proteins in model systems and live cells. In this work, we characterize mNeonGreen (mNG), a recently introduced FP from the bilaterian Branchiostoma lanceolatum, in comparison to the well-known hydrozoan variants enhanced green fluorescent protein (EGFP) and Aequorea coerulescens GFP by steady-state spectroscopy and fluorescence correlation spectroscopy in solutions of different pH. Blind spectral unmixing of sets of absorption spectra reveals three interconverting electronic states of mNG: a nonfluorescent protonated state, a bright state showing bell-shaped pH dependence, and a similarly bright state dominating at high pH. The gradual population of the acidic form by external protonation is reflected by increased flickering at low pH in fluorescence correlation spectroscopy measurements, albeit with much slower flicker rates and lower amplitudes as compared to Aequorea GFPs. In addition, increased flickering of mNG indicates a second deprotonation step above pH 10 leading to a slight decrease in fluorescence. Thus, mNG is distinguished from Aequorea GFPs by a two-step protonation response with opposite effects that reflects a chemically distinct chromophore environment. Despite the more complex pH dependence, mNG represents a superior FP under a broad range of conditions.

A study of the diffusion dynamics and concentration distribution of gold nanospheres (GNSs) without fluorescent labeling inside live cells using fluorescence single particle spectroscopy

Colloidal gold nanospheres (GNSs) have become important nanomaterials in biomedical applications due to their special optical properties, good chemical stability, and biocompatibility. However, measuring the diffusion coefficients or concentration distribution of GNSs within live cells accurately without any extra fluorescent labeling in situ has still not been resolved. In this work, a single particle method is developed to study the concentration distribution of folic acid-modified GNSs (FA-GNSs) internalized via folate receptors, and investigates their diffusion dynamics within live cells using single particle fluorescence correlation spectroscopy (FCS). We optimized the experimental conditions and verified the feasibility of 30 nm GNSs without extra fluorescence labeling being used for single particle detection inside live cells. Then, the FCS characterization strategy was used to measure the concentration and diffusion coefficient distributions of GNSs inside live cells and the obtained results were basically in agreement with those obtained by TEM. The results demonstrate that our strategy is characterized as an in situ, nondestructive, rapid and dynamic method for the assay of live cells, and it may be widely used in the further design of GNP-based drug delivery and therapeutics.

Deblurring Signal Network Dynamics

To orchestrate the function and development of multicellular organisms, cells integrate intra- and extracellular information. This information is processed via signal networks in space and time, steering dynamic changes in cellular structure and function. Defects in those signal networks can lead to developmental disorders or cancer. However, experimental analysis of signal networks is challenging as their state changes dynamically and differs between individual cells. Thus, causal relationships between network components are blurred if lysates from large cell populations are analyzed. To directly study causal relationships, perturbations that target specific components have to be combined with measurements of cellular responses within individual cells. However, using standard single-cell techniques, the number of signal activities that can be monitored simultaneously is limited. Furthermore, diffusion of signal network components limits the spatial precision of perturbations, which blurs the analysis of spatiotemporal processing in signal networks. Hybrid strategies based on optogenetics, surface patterning, chemical tools, and protein design can overcome those limitations and thereby sharpen our view into the dynamic spatiotemporal state of signal networks and enable unique insights into the mechanisms that control cellular function in space and time.

Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features

Cell signaling dynamics and transcriptional regulatory activities are variable within specific cell types responding to an identical stimulus. In addition to studying the network interactions, there is much interest in utilizing single cell scale data to elucidate the non-random aspects of the variability involved in cellular decision making. Previous studies have considered the information transfer between the signaling and transcriptional domains based on an instantaneous relationship between the molecular activities. These studies predict a limited binary on/off encoding mechanism which underestimates the complexity of biological information processing, and hence the utility of single cell resolution data. Here we pursue a novel strategy that reformulates the information transfer problem as involving dynamic features of signaling rather than molecular abundances. We pursue a computational approach to test if and how the transcriptional regulatory activity patterns can be informative of the temporal history of signaling. Our analysis reveals (1) the dynamic features of signaling that significantly alter transcriptional regulatory patterns (encoding), and (2) the temporal history of signaling that can be inferred from single cell scale snapshots of transcriptional activity (decoding). Immediate early gene expression patterns were informative of signaling peak retention kinetics, whereas transcription factor activity patterns were informative of activation and deactivation kinetics of signaling. Moreover, the information processing aspects varied across the network, with each component encoding a selective subset of the dynamic signaling features. We developed novel sensitivity and information transfer maps to unravel the dynamic multiplexing of signaling features at each of these network components. Unsupervised clustering of the maps revealed two groups that aligned with network motifs distinguished by transcriptional feedforward vs feedback interactions. Our new computational methodology impacts the single cell scale experiments by identifying downstream snapshot measures required for inferring specific dynamical features of upstream signals involved in the regulation of cellular responses.

Single cell studies have shown that differential patterns in the dynamics of signaling proteins, transcription factor activity, gene expression, etc. produce distinct downstream outcomes. The opposite also holds true where particular cellular outcomes have been found to be associated with the dynamical pattern of one or more signaling molecules. Signaling pathways, therefore, serve as signal processing units to inform specific downstream regulation. However, the functional capabilities of the dynamic aspects of signaling are not well understood. To address this issue, we developed a new approach that evaluates information processing between dynamic features in signaling patterns and transcriptional regulatory activity. Our work demonstrates that the information transfer occur through decoding of temporal history of signals rather than only through instantaneous correlations. Moreover, our results identify regulatory network motifs as the critical components in the information processing and filtering of variability in signaling dynamics to produce distinct patterns of downstream transcriptional responses. Our methodology can be broadly applied to single cell scale data on experimentally accessible downstream measures to infer dynamic aspects of upstream signaling.

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.

Imaging Fos-Jun transcription factor mobility and interaction in live cells by single plane illumination-fluorescence cross correlation spectroscopy

We collected mobility and interaction maps of c-Fos-eGFP and c-Jun-mRFP1 transcription factors within living cell nuclei. c-Fos dimerizes with c-Jun to form the transcription activator protein-1 (AP-1) which binds to the specific recognition site. To monitor this process, we used fluorescence cross-correlation spectroscopy on a single plane illumination microscope (SPIM-FCCS), which provides diffusion coefficient and protein-protein interaction data in the whole image plane simultaneously, instead of just one point on conventional confocal FCS. We find a strong correlation between diffusional mobility and interaction: regions of strong interaction show slow mobility. Controls containing either an eGFP-mRFP dimer, separately expressing eGFP and mRPF, or c-Fos-eGFP and c-Jun-mRFP1 mutants lacking dimerization and DNA-binding domains, showed no such correlation. These results extend our earlier findings from confocal FCCS to include spatial information.

Nature's lessons in design: nanomachines to scaffold, remodel and shape membrane compartments

Our understanding of the membrane sculpting capabilities of proteins from experimental model systems could be used to construct functional compartmentalised architectures for the engineering of synthetic cells.