Diffusion and binding analyzed with combined point FRAP and FCS: Combined Point FRAP and FCS

CM-FRAP-Continuum Mechanics-Based Fluorescence Recovery After Photobleaching

Fluorescence recovery after photobleaching (FRAP) is widely used to evaluate intracellular molecular turnover or repeated translocation of molecules using confocal laser scanning microscopy. While numerous models have been developed for the analysis of FRAP responses, in which chemical interactions and/or fast diffusion processes are involved, it is inherently difficult to evaluate the long-term behavior of molecular turnover because of the presence of intracellular flow and microscopic deformation of bleached regions. To overcome these difficulties, we have developed a novel continuum mechanics-based FRAP (CM-FRAP) approach that enables simultaneous evaluation of long-term molecular turnover and intracellular flow/deformation. Here we demonstrate the utility of CM-FRAP by using actin molecules associated with stress fibers in rat aortic smooth muscle cells with clarification of the experimental setup and data analysis. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Plasmid construction and sample preparation Basic Protocol 2: How to perform FRAP experiments Basic Protocol 3: Data analysis based on CM-FRAP.

Analysis of chemomechanical behavior of stress fibers by continuum mechanics-based FRAP

Fluorescence recovery after photobleaching (FRAP) is a common technique to analyze the turnover of molecules in living cells. Numerous physicochemical models have been developed to quantitatively evaluate the rate of turnover driven by chemical reaction and diffusion that occurs in a few seconds to minutes. On the other hand, they have limitations in interpreting long-term FRAP responses where intracellular active movement inevitably provides target molecular architectures with additional effects other than chemical reaction and diffusion, namely directed transport and structural deformation. To overcome the limitations, we develop a continuum mechanics-based model that allows for decoupling FRAP response into the intrinsic turnover rate and subcellular mechanical characteristics such as displacement vector and strain tensor. Our approach was validated using fluorescently labeled β-actin in an actomyosin-mediated contractile apparatus called stress fibers, revealing spatially distinct patterns of the multi-physicochemical events, in which the turnover rate, which represents effective off-rate of β-actin, was significantly higher at the center of the cell. We also found that the turnover rate is negatively correlated with the rate of displacement or velocity along stress fibers but, interestingly, not with the absolute magnitude of strain. Moreover, stress fibers are subjected to centripetal flow that is facilitated by the circulation of actin molecules. Taken together, this novel framework for long-term FRAP analysis allows for unveiling the contribution of overlooked microscopic mechanics to molecular turnover in living cells.

Fluorescence Recovery after Photobleaching in Colloidal Science: Introduction and Application

FRAP (fluorescence recovery after photo bleaching) is a method for determining diffusion in material science. In industrial applications such as medications, foods, Medtech, hygiene, and textiles, the diffusion process has a substantial influence on the overall qualities of goods. All these complex and heterogeneous systems have diffusion-based processes at the local level. FRAP is a fluorescence-based approach for detecting diffusion; in this method, a high-intensity laser is made for a brief period and then applied to the samples, bleaching the fluorescent chemical inside the region, which is subsequently filled up by natural diffusion. This brief Review will focus on the existing research on employing FRAP to measure colloidal system heterogeneity and explore diffusion into complicated structures. This description of FRAP will be followed by a discussion of how FRAP is intended to be used in colloidal science. When constructing the current Review, the most recent publications were reviewed for this assessment. Because of the large number of FRAP articles in colloidal research, there is currently a dearth of knowledge regarding the growth of FRAP's significance to colloidal science. Colloids make up only 2% of FRAP papers, according to ISI Web of Knowledge.

DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks

Conventional analysis of fluorescence recovery after photobleaching (FRAP) data for diffusion coefficient estimation typically involves fitting an analytical or numerical FRAP model to the recovery curve data using non-linear least squares. Depending on the model, this can be time consuming, especially for batch analysis of large numbers of data sets and if multiple initial guesses for the parameter vector are used to ensure convergence. In this work, we develop a completely new approach, DeepFRAP, utilizing machine learning for parameter estimation in FRAP. From a numerical FRAP model developed in previous work, we generate a very large set of simulated recovery curve data with realistic noise levels. The data are used for training different deep neural network regression models for prediction of several parameters, most importantly the diffusion coefficient. The neural networks are extremely fast and can estimate the parameters orders of magnitude faster than least squares. The performance of the neural network estimation framework is compared to conventional least squares estimation on simulated data, and found to be strikingly similar. Also, a simple experimental validation is performed, demonstrating excellent agreement between the two methods. We make the data and code used publicly available to facilitate further development of machine learning-based estimation in FRAP. LAY DESCRIPTION: Fluorescence recovery after photobleaching (FRAP) is one of the most frequently used methods for microscopy-based diffusion measurements and broadly used in materials science, pharmaceutics, food science and cell biology. In a FRAP experiment, a laser is used to photobleach fluorescent particles in a region. By analysing the recovery of the fluorescence intensity due to the diffusion of still fluorescent particles, the diffusion coefficient and other parameters can be estimated. Typically, a confocal laser scanning microscope (CLSM) is used to image the time evolution of the recovery, and a model is fit using least squares to obtain parameter estimates. In this work, we introduce a new, fast and accurate method for analysis of data from FRAP. The new method is based on using artificial neural networks to predict parameter values, such as the diffusion coefficient, effectively circumventing classical least squares fitting. This leads to a dramatic speed-up, especially noticeable when analysing large numbers of FRAP data sets, while still producing results in excellent agreement with least squares. Further, the neural network estimates can be used as very good initial guesses for least squares estimation in order to make the least squares optimization convergence much faster than it otherwise would. This provides for obtaining, for example, diffusion coefficients as soon as possible, spending minimal time on data analysis. In this fashion, the proposed method facilitates efficient use of the experimentalist's time which is the main motivation to our approach. The concept is demonstrated on pure diffusion. However, the concept can easily be extended to the diffusion and binding case. The concept is likely to be useful in all application areas of FRAP, including diffusion in cells, gels and solutions.

An extended model of vesicle fusion at the plasma membrane to estimate protein lateral diffusion from TIRF microscopy images

BACKGROUND

Characterizing membrane dynamics is a key issue to understand cell exchanges with the extra-cellular medium. Total internal reflection fluorescence microscopy (TIRFM) is well suited to focus on the late steps of exocytosis at the plasma membrane. However, it is still a challenging task to quantify (lateral) diffusion and estimate local dynamics of proteins.

RESULTS

A new model was introduced to represent the behavior of cargo transmembrane proteins during the vesicle fusion to the plasma membrane at the end of the exocytosis process. Two biophysical parameters, the diffusion coefficient and the release rate parameter, are automatically estimated from TIRFM image sequences, to account for both the lateral diffusion of molecules at the membrane and the continuous release of the proteins from the vesicle to the plasma membrane. Quantitative evaluation on 300 realistic computer-generated image sequences demonstrated the efficiency and accuracy of the method. The application of our method on 16 real TIRFM image sequences additionally revealed differences in the dynamic behavior of Transferrin Receptor (TfR) and Langerin proteins.

CONCLUSION

An automated method has been designed to simultaneously estimate the diffusion coefficient and the release rate for each individual vesicle fusion event at the plasma membrane in TIRFM image sequences. It can be exploited for further deciphering cell membrane dynamics.

Single plane illumination microscopy as a tool for studying nucleome dynamics

Single plane illumination microscopy (SPIM) is a new optical method that has become extremely important in recent years. It is based on the formation of a "light slice" in the specimen in which fluorescently tagged molecules are observed. The spatial resolution is close to that of confocal optics, but without the disadvantages inherent to scanning or high laser irradiation doses. A recent development is light sheet fluctuation microscopy, which exploits the dynamic information contained in the fluorescence intensity fluctuations of each image pixel. Here we review the principles of this method and show some recent applications to the dynamics of transcription factors and chromatin. We show that the dimerization of Fos and Jun proteins is directly linked to their binding to DNA; that nuclear receptor activation changes their intranuclear dynamics; and that the viscoelastic behavior of interphase chromatin strongly depends on the presence of lamin A.

Dynamic properties of independent chromatin domains measured by correlation spectroscopy in living cells

Background

Genome organization into subchromosomal topologically associating domains (TADs) is linked to cell-type-specific gene expression programs. However, dynamic properties of such domains remain elusive, and it is unclear how domain plasticity modulates genomic accessibility for soluble factors.

Results

Here, we combine and compare a high-resolution topology analysis of interacting chromatin loci with fluorescence correlation spectroscopy measurements of domain dynamics in single living cells. We identify topologically and dynamically independent chromatin domains of ~1 Mb in size that are best described by a loop-cluster polymer model. Hydrodynamic relaxation times and gyration radii of domains are larger for open (161 ± 15 ms, 297 ± 9 nm) than for dense chromatin (88 ± 7 ms, 243 ± 6 nm) and increase globally upon chromatin hyperacetylation or ATP depletion.

Conclusions

Based on the domain structure and dynamics measurements, we propose a loop-cluster model for chromatin domains. It suggests that the regulation of chromatin accessibility for soluble factors displays a significantly stronger dependence on factor concentration than search processes within a static network.

Electronic supplementary material

The online version of this article (doi:10.1186/s13072-016-0093-1) contains supplementary material, which is available to authorized users.

Making a big thing of a small cell--recent advances in single cell analysis

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.

Dynamic architecture of the purinosome involved in human de novo purine biosynthesis

Enzymes in human de novo purine biosynthesis have been demonstrated to form a reversible, transient multienzyme complex, the purinosome, upon purine starvation. However, characterization of purinosomes has been limited to HeLa cells and has heavily relied on qualitative examination of their subcellular localization and reversibility under wide-field fluorescence microscopy. Quantitative approaches, which are particularly compatible with human disease-relevant cell lines, are necessary to explicitly understand the purinosome in live cells. In this work, human breast carcinoma Hs578T cells have been utilized to demonstrate the preferential utilization of the purinosome under purine-depleted conditions. In addition, we have employed a confocal microscopy-based biophysical technique, fluorescence recovery after photobleaching, to characterize kinetic properties of the purinosome in live Hs578T cells. Quantitative characterization of the diffusion coefficients of all de novo purine biosynthetic enzymes reveals the significant reduction of their mobile kinetics upon purinosome formation, the dynamic partitioning of each enzyme into the purinosome, and the existence of three intermediate species in purinosome assembly under purine starvation. We also demonstrate that the diffusion coefficient of the purine salvage enzyme, hypoxanthine phosphoribosyltransferase 1, is not sensitive to purine starvation, indicating exclusion of the salvage pathway from the purinosome. Furthermore, our biophysical characterization of nonmetabolic enzymes clarifies that purinosomes are spatiotemporally different cellular bodies from stress granules and cytoplasmic protein aggregates in both Hs578T and HeLa cells. Collectively, quantitative analyses of the purinosome in Hs578T cells led us to provide novel insights for the dynamic architecture of the purinosome assembly.

Quantification of cytosolic interactions identifies Ede1 oligomers as key organizers of endocytosis

Clathrin-mediated endocytosis is a highly conserved intracellular trafficking pathway that depends on dynamic protein-protein interactions between up to 60 different proteins. However, little is known about the spatio-temporal regulation of these interactions. Using fluorescence (cross)-correlation spectroscopy in yeast, we tested 41 previously reported interactions in vivo and found 16 to exist in the cytoplasm. These detected cytoplasmic interactions included the self-interaction of Ede1, homolog of mammalian Eps15. Ede1 is the crucial scaffold for the organization of the early stages of endocytosis. We show that oligomerization of Ede1 through its central coiled coil domain is necessary for its localization to the endocytic site and we link the oligomerization of Ede1 to its function in locally concentrating endocytic adaptors and organizing the endocytic machinery. Our study sheds light on the importance of the regulation of protein-protein interactions in the cytoplasm for the assembly of the endocytic machinery in vivo.

Molecular diffusion and binding analyzed with FRAP

Intracellular molecular transport and localization are crucial for cells (plant cells as much as mammalian cells) to proliferate and to adapt to diverse environmental conditions. Here, some aspects of the microscopy-based method of fluorescence recovery after photobleaching (FRAP) are introduced. In the course of the last years, this has become a very powerful tool to study dynamic processes in living cells and tissue, and it is expected to experience further increasing demand because quantitative information on biological systems becomes more and more important. This review introduces the FRAP methodology, including some theoretical background, describes challenges and pitfalls, and presents some recent advanced applications.