Fluorescence Recovery After Photobleaching
Proteins within the cell continuously turnover. Understanding how organelles and cytoskeletal structures are assembled and regulated from a theoretical point of view requires knowledge of the kinetic turnover rate constants associated with each of the binding events that are involved in forming the structure of interest. These kinetics have generally been investigated using Fluorescence recovery after photo-bleaching experiments (FRAP) where a small region of interest is bleached by exposure to laser light and fluorescence recovery is monitored (Fig. 1 a). The results of such experiments are quantified by fitting fluorescence recovery curves with exponential recovery functions to measure the half-time of fluorescence recovery (Fig. 1 b). This is a crude measure that does not give any information on the biochemical processes that underlie turnover. One alternative has been to determine protein association/dissociation kinetics in vitro. While this offers a well-controlled environment in which to effect precise measurements, it is becoming increasingly clear that protein association/ dissociation kinetics in the complex intracellular environment differ markedly from those measured in vitro. Other approaches involve complex simulations of protein interaction networks to interpret FRAP data. However, these necessitate many assumptions that cannot easily be verified experimentally. Thus, the ideal method would measure protein association/dissociation kinetics in cells using minimal specialized equipment and minimally complex fitting procedures.
To fill this technical gap, we reasoned that the turnover kinetics of a given protein should depend on the association/dissociation kinetics of its subdomains. We verified this experimentally and showed that the fluorescence recovery of most proteins consists of multiple first-order exponential recovery processes rather than just one. Having determined how many first-order processes participate in recovery, the next challenge is to identify what molecular and biophysical processes underlie each of these. By analyzing the recovery kinetics of different domain-deletion mutants of the protein of interest, we have shown that the recovery of the full-length protein is a convolution of the recovery kinetics of each of its subdomains measured individually.
Super-Resolved Traction Force Microscopy (STFM)
Animal cells continuously sense and respond to mechanical force. Quantifying these forces remains a major challenge across biomedical disciplines; yet such measurements are essential for the understanding of cellular function.
Traction force microscopy is one of the most successful and broadly-used force probing technologies, chosen for the simplicity of its implementation, flexibility to mimic cellular conditions, and well-established analysis pipe-line. We improve the spatial resolution and accuracy of TFM using STED microscopy. The increased spatial resolution of STED-TFM (STFM) allows a greater than 5-fold higher sampling of the forces generated by the cell than conventional TFM, accessing the nano instead of the micron scale. This improvement is highlighted by computer simulations and an activating RBL cell model system.
In light of the increasing discovery of the importance of mechanobiology in cell physiology, we envisage traction force microscopy to remain a major player for quantifying mechanical forces in living cells.
Thus, by analyzing FRAP recovery curves in terms of multi-exponential recovery processes and by measuring the individual recovery rates of the protein’s subdomains, one can gain detailed insight into how each subdomain contributes to turnover as well as the relative importance of each molecular process for overall recovery. Hence, our analysis provides a level of characterization far greater than previous methods. Indeed, changes in the half-time of recovery generally reported in FRAP experiments can result from changes in the number of first-order processes participating in recovery, changes in the rates of some or all of the processes, changes in relative importance of some or all of the processes, or a combination of all of these factors. Our analysis and process identification strategy enable determination of all of these changes, thereby providing valuable quantitative data for systems biology approaches measured in physiologically relevant conditions.
Please contact for further information: marco.fritzsche (at) rdm.ox.ac.uk.
Fritzsche M & Charras GT, Dissecting protein reaction dynamics in living cells by fluorescence recovery after photobleaching., Nature Protocols, 2015.
Fritzsche M, Thorogate R, and Charras GT, Analysis of Ezrin turnover dynamics at the submembranous actin cortex., Biophysical Journal, 2014.
Fritzsche M, Lewalle A, Duke T, and Charras GT. Analysis of turnover dynamics of the submembranous actin cortex., Molecular Biology of the Cell, 2013 (Faculty 1000).
Contact: Please contact for further information: huw.colinyork (at) pmb.ox.ac.uk and marco.fritzsche (at) rdm.ox.ac.uk.
Colin-York H, Fritzsche M, The future of traction force microscopy, Current Opinion in Biomedical Engineering, 2017.
Colin-York H, Eggeling C, Fritzsche M, Dissection of mechanical force in living cells by super-resolved traction force microscopy, Nature Protocols, 2017.
Colin-York H, Shrestha D, Felce JH, Waithe D, Moeendarbary E, Davis SJ, Eggeling C, and Fritzsche M, Super-resolved Traction Force Microscopy (STFM)., Nano Letters, 2016.