Fluctuation Correlation Spectroscopy with a Laser-Scanning Microscope: Exploiting the Hidden Time Structure

Digman, Michelle A.; Sengupta, Parijat; Wiseman, Paul W.; Brown, Claire M.; Horwitz, Alan Rick; Gratton, Enrico

doi:10.1529/biophysj.105.061788

Cited by 202 publications

(193 citation statements)

References 7 publications

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“…The introduction of fluorescence intensity fluctuation analysis in imaging offers the possibility to achieve quantitative fluorescence imaging with single-molecule sensitivity, an accomplishment that would considerably advance our understanding of biological processes at the molecular level. To this point, introduction of fluorescence intensity fluctuation analysis in imaging was successfully pursued in the form of fluorescence fluctuation correlation in image correlation spectroscopy (ICS) (23), raster image correlation spectroscopy (RICS) (24,25), and photon-counting histogram analysis (PCH) (26,27).…”

Section: Discussionmentioning

confidence: 99%

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Quantitative single-molecule imaging by confocal laser scanning microscopy

Vukojević

Heidkamp

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

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A new approach to quantitative single-molecule imaging by confocal laser scanning microscopy (CLSM) is presented. It relies on fluorescence intensity distribution to analyze the molecular occurrence statistics captured by digital imaging and enables direct determination of the number of fluorescent molecules and their diffusion rates without resorting to temporal or spatial autocorrelation analyses. Digital images of fluorescent molecules were recorded by using fast scanning and avalanche photodiode detectors. In this way the signal-to-background ratio was significantly improved, enabling direct quantitative imaging by CLSM. The potential of the proposed approach is demonstrated by using standard solutions of fluorescent dyes, fluorescently labeled DNA molecules, quantum dots, and the Enhanced Green Fluorescent Protein in solution and in live cells. The method was verified by using fluorescence correlation spectroscopy. The relevance for biological applications, in particular, for live cell imaging, is discussed.fluorescence correlation spectroscopy ͉ live cells ͉ sensitivity L imited sensitivity and spatial resolution impede the usage of fluorescent microscopy for quantitative analysis of low copy numbers of biologically relevant molecules in live cells. Therefore, methodological and instrumental advancements are required. The aim of our work is to explore the benefits of integrating confocal laser scanning microscopy (CLSM) with fluorescence correlation spectroscopy (FCS) (1-4) as a platform for quantitative imaging of the spatiotemporal dynamics of cellular processes in real time.Fast scanning was suggested as a possible way to increase signal intensity in CLSM (5-8), but has not been systematically pursued. A contributing factor is that for increased scanning speed the number of detected photons becomes lower. With low photon counts, detector properties become increasingly relevant because the internal noise of the detector may considerably limit the quality of the image. Therefore, our first aim was to build an instrument for CLSM imaging with improved detection efficiency. We achieved this by introducing avalanche photodiodes (APDs) as detectors. Compared with the photomultiplier tubes (PMTs), normally used as detectors in conventional CLSM, the APDs are characterized by higher quantum and collection efficiency-Ϸ70% in APDs compared with 15-25% in PMTs; higher gain, faster response time, and lower dark current (6, 9). The considerably improved signal-tonoise ratio that was achieved by the introduction of APDs enabled the implementation of fast scanning. Fast scanning offers additional advantages: increased fluorescence yield by avoiding intersystem crossing, data collection at higher encountering frequency and from independent volumes, further significantly improving the signal-tobackground ratio (SBR) in imaging.We first demonstrate that improved SBRs enabled us to quantify the average number of molecules in the observation volume element by analyzing the image statistics, without resorting to temporal or...

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Section: Discussionmentioning

confidence: 99%

“…The ensemble of photon counts acquired at time intervals of different lengths is analyzed to determine the average number of molecules and their mobility, without using temporal autocorrelation analysis. This is an alternative to RICS (24,25), which relies on temporal autocorrelation analysis.…”

Section: Discussionmentioning

confidence: 99%

Quantitative single-molecule imaging by confocal laser scanning microscopy

Vukojević

Heidkamp

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

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“…ICS is currently limited by scan speeds, which must be greater than the speed of the molecule under consideration, thus restricting the use of this method to relativity slow processes. Raster ICS overcomes this limitation by incorporating a time delay between pixels and rows of pixels in the image (Digman et al 2005). Other correlation microscopy methods include tools for analyzing single particles in dense environments, such as particle ICS (PICS) (Semrau and Schmidt 2007;Kolin and Wiseman 2007), total internal reflection FCS (TIR-FCS) which uses exponentially decaying EM waves to excite a thin layer of a specimen (Hassler et al 2005), and selective plane imaging microscopy FCS (SPIM-FCS), which enables measurement with high time resolution in a 3D image field (Wohland et al 2010).…”

Section: Dynamic Imagingmentioning

confidence: 99%

Imaging stress

Brielle

Gura

Kaganovich

2015

Cell Stress and Chaperones

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Recent innovations in cell biology and imaging approaches are changing the way we study cellular stress, protein misfolding, and aggregation. Studies have begun to show that stress responses are even more variegated and dynamic than previously thought, encompassing nano-scale reorganization of cytosolic machinery that occurs almost instantaneously, much faster than transcriptional responses. Moreover, protein and mRNA quality control is often organized into highly dynamic macromolecular assemblies, or dynamic droplets, which could easily be mistaken for dysfunctional Baggregates,^but which are, in fact, regulated functional compartments. The nano-scale architecture of stressresponse ranges from diffraction-limited structures like stress granules, P-bodies, and stress foci to slightly larger quality control inclusions like juxta nuclear quality control compartment (JUNQ) and insoluble protein deposit compartment (IPOD), as well as others. Examining the biochemical and physical properties of these dynamic structures necessitates live cell imaging at high spatial and temporal resolution, and techniques to make quantitative measurements with respect to movement, localization, and mobility. Hence, it is important to note some of the most recent observations, while casting an eye towards new imaging approaches that offer the possibility of collecting entirely new kinds of data from living cells. StressProtecting the cell from protein-associated damage is a matter of having the correct proteins at the right place at the right time: the cellular environment changes rapidly in different folding and stress conditions in order to avoid catastrophic consequences of too many misfolded polypeptides or not enough functional proteins. When a cell is exposed to stresses such as heat-shock, cold-shock, osmotic stress, starvation, or amino-acid analogues which cause rampant mutations, the cellular response propagates across the entire network of protein biogenesis.Although much research has focused on how these stresses affect protein synthesis, we are only now beginning to look closely at how stress effects protein localization and distribution. Whereas expression takes time, and is more difficult to accomplish under stress, protein localization is substantially more dynamic and therefore changes in protein distribution can be affected quickly, in time to deal with the stress. Hence, regulation of protein distribution deserves careful attention in the study of stress response. Indeed, recent work has shown that in the single cell eukaryote Saccharomyces cerevisiae more than half of the proteome radically changes its localization under different stress condition (Breker et al. 2013). By altering the spatial positioning of proteins, cells can change Electronic supplementary material The online version of this article

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“…All of these methods compute the correlation function of an entire fluorescence imaging movie instead of relying on localization and tracking, and like fluorescence correlation spectroscopy, these powerful image correlation approaches can be extended to measure 2D maps of heterogeneous diffusion (18,26) and very fast diffusion (27). Particle image correlation spectroscopy measures diffusion dynamics by computing a similar correlation function from data that have already been processed with the Gaussian localization used in SPT and other methods (28).…”

Section: Introductionmentioning

confidence: 99%

“…If a confocal microscope is available, extremely fast diffusion (>100 mm 2 /s) can be measured with raster image correlation spectroscopy, which uses a scanning mirror to eliminate image blur (27,29). Here, we instead focus on developing STICS to extend the capabilities of a single-molecule imaging microscope beyond the limits of SPT (maximum measurable diffusion coefficient,~10 mm 2 /s (30)) to an order-of-magnitude-faster motion.…”

Section: Introductionmentioning

confidence: 99%

Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy

Rowland

Tuson

Biteen

2016

Biophysical Journal

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By following single fluorescent molecules in a microscope, single-particle tracking (SPT) can measure diffusion and binding on the nanometer and millisecond scales. Still, although SPT can at its limits characterize the fastest biomolecules as they interact with subcellular environments, this measurement may require advanced illumination techniques such as stroboscopic illumination. Here, we address the challenge of measuring fast subcellular motion by instead analyzing single-molecule data with spatiotemporal image correlation spectroscopy (STICS) with a focus on measurements of confined motion. Our SPT and STICS analysis of simulations of the fast diffusion of confined molecules shows that image blur affects both STICS and SPT, and we find biased diffusion rate measurements for STICS analysis in the limits of fast diffusion and tight confinement due to fitting STICS correlation functions to a Gaussian approximation. However, we determine that with STICS, it is possible to correctly interpret the motion that blurs single-molecule images without advanced illumination techniques or fast cameras. In particular, we present a method to overcome the bias due to image blur by properly estimating the width of the correlation function by directly calculating the correlation function variance instead of using the typical Gaussian fitting procedure. Our simulation results are validated by applying the STICS method to experimental measurements of fast, confined motion: we measure the diffusion of cytosolic mMaple3 in living Escherichia coli cells at 25 frames/s under continuous illumination to illustrate the utility of STICS in an experimental parameter regime for which in-frame motion prevents SPT and tight confinement of fast diffusion precludes stroboscopic illumination. Overall, our application of STICS to freely diffusing cytosolic protein in small cells extends the utility of singlemolecule experiments to the regime of fast confined diffusion without requiring advanced microscopy techniques.

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Fluctuation Correlation Spectroscopy with a Laser-Scanning Microscope: Exploiting the Hidden Time Structure

Cited by 202 publications

References 7 publications

Quantitative single-molecule imaging by confocal laser scanning microscopy

Quantitative single-molecule imaging by confocal laser scanning microscopy

Imaging stress

Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy

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