ANALYSIS OF SIMULATED AND EXPERIMENTAL FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING - DATA FOR 2 DIFFUSING COMPONENTS

Citation
Gw. Gordon et al., ANALYSIS OF SIMULATED AND EXPERIMENTAL FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING - DATA FOR 2 DIFFUSING COMPONENTS, Biophysical journal, 68(3), 1995, pp. 766-778
Citations number
34
Categorie Soggetti
Biophysics
Journal title
ISSN journal
00063495
Volume
68
Issue
3
Year of publication
1995
Pages
766 - 778
Database
ISI
SICI code
0006-3495(1995)68:3<766:AOSAEF>2.0.ZU;2-O
Abstract
Fluorescence recovery after photobleaching has been a popular techniqu e to quantify the lateral mobility of membrane components. A variety o f analysis methods have been used to determine the lateral diffusional mobility, D. However, many of these methods suffer from the drawbacks that they are not able to discern two-component diffusion (i.e., thre e-point fit), cannot solve for two components (linearization procedure s), and do not perform well at low signal-to-noise. To overcome these limitations, we have adopted the approach of fitting fluorescence reco very after photobleaching curves by the full series solution using a M arquardt algorithm. Using simulated data of one or two diffusing compo nents, determinations of the accuracy and reliability of the method wi th regard to extraction of diffusion parameters and the differentiatio n of one- versus two-component recovery curves were made under a varie ty of conditions comparable with those found in actual experimental si tuations. The performance of the method was also examined in experimen ts on artificial liposomes and fibroblast membranes labeled with fluor escent lipid and/or protein components. Our results indicate that: 1) the method was capable of extracting one- and two-component D values o ver a large range of conditions; 2) the D of a one-component recovery can be measured to within 10% with a small signal (100 prebleach photo n counts per channel); 3) a two-component recovery requires more than 100-fold greater signal level than a one-component recovery for the sa me error; and 4) for two-component fits, multiple recovery curves may be needed to provide adequate signal to achieve the desired level of c onfidence in the fitted parameters and in the differentiation of one- and two-component diffusion.