Combining PALM and SOFI for quantitative imaging of focal adhesions in living cells

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00349482" target="_blank" >RIV/68407700:21230/17:00349482 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1117/12.2252865" target="_blank" >https://doi.org/10.1117/12.2252865</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/12.2252865" target="_blank" >10.1117/12.2252865</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Combining PALM and SOFI for quantitative imaging of focal adhesions in living cells

Popis výsledku v původním jazyce

Focal adhesions are complicated assemblies of hundreds of proteins that allow cells to sense their extracellular matrix and adhere to it. Although most focal adhesion proteins have been identified, their spatial organization in living cells remains challenging to observe. Photo-activated localization microscopy (PALM) is an interesting technique for this purpose, especially since it allows estimation of molecular parameters such as the number of fluorophores. However, focal adhesions are dynamic entities, requiring a temporal resolution below one minute, which is difficult to achieve with PALM. In order to address this problem, we merged PALM with super-resolution optical fluctuation imaging (SOFI) by applying both techniques to the same data. Since SOFI tolerates an overlap of single molecule images, it can improve the temporal resolution compared to PALM. Moreover, an adaptation called balanced SOFI (bSOFI) allows estimation of molecular parameters, such as the fluorophore density. We therefore performed simulations in order to assess PALM and SOFI for quantitative imaging of dynamic structures. We demonstrated the potential of our PALM-SOFI concept as a quantitative imaging framework by investigating moving focal adhesions in living cells.

Název v anglickém jazyce

Combining PALM and SOFI for quantitative imaging of focal adhesions in living cells

Popis výsledku anglicky

Focal adhesions are complicated assemblies of hundreds of proteins that allow cells to sense their extracellular matrix and adhere to it. Although most focal adhesion proteins have been identified, their spatial organization in living cells remains challenging to observe. Photo-activated localization microscopy (PALM) is an interesting technique for this purpose, especially since it allows estimation of molecular parameters such as the number of fluorophores. However, focal adhesions are dynamic entities, requiring a temporal resolution below one minute, which is difficult to achieve with PALM. In order to address this problem, we merged PALM with super-resolution optical fluctuation imaging (SOFI) by applying both techniques to the same data. Since SOFI tolerates an overlap of single molecule images, it can improve the temporal resolution compared to PALM. Moreover, an adaptation called balanced SOFI (bSOFI) allows estimation of molecular parameters, such as the fluorophore density. We therefore performed simulations in order to assess PALM and SOFI for quantitative imaging of dynamic structures. We demonstrated the potential of our PALM-SOFI concept as a quantitative imaging framework by investigating moving focal adhesions in living cells.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10306 - Optics (including laser optics and quantum optics)

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Single Molecule Spectroscopy and Superresolution Imaging X

ISBN

978-1-5106-0583-1

ISSN

0277-786X

e-ISSN

2410-9045

Počet stran výsledku

7

Strana od-do

—

Název nakladatele

SPIE

Místo vydání

Bellingham (stát Washington)

Místo konání akce

San Francisco

Datum konání akce

28. 1. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000406422600002