Imaging Live-Cell Dynamics and Structure at the Single-Molecule Level

Molecular Cell

Review Imaging Live-Cell Dynamics and Structure at the Single-Molecule Level Zhe Liu,1,* Luke D. Lavis,1,* and Eric Betzig1,* 1Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA *Correspondence: [email protected] (Z.L.), [email protected] (L.D.L.), [email protected] (E.B.) http://dx.doi.org/10.1016/j.molcel.2015.02.033

Observation of molecular processes inside living cells is fundamental to a quantitative understanding of how biological systems function. Specifically, decoding the complex behavior of single molecules enables us to measure kinetics, transport, and self-assembly at this fundamental level that is often veiled in ensemble experiments. In the past decade, rapid developments in fluorescence microscopy, fluorescence correlation spectroscopy, and fluorescent labeling techniques have enabled new experiments to investigate the robustness and stochasticity of diverse molecular mechanisms with high spatiotemporal resolution. This review discusses the concepts and strategies of structural and functional imaging in living cells at the single-molecule level with minimal perturbations to the specimen.

Over the past several decades, a combination of biochemical, genetic, and genomic approaches have offered critical insights into the molecular underpinnings of various biological systems. Many of these classic techniques use cell-population-based endpoint assays, however, and are unable to provide detailed information about the kinetics, dynamics, and 3D architecture of the molecular machines that operate in living cells. Moreover, fixation procedures in traditional imaging methods introduce artifacts and distortions, obscuring true animate structure features (Schnell et al., 2012). Elucidating the links between molecular and cellular behaviors in live specimens overcomes these drawbacks and bridges the existing gaps between biochemistry, genetics, and developmental biology and is fundamental to our understanding of how stereotypical regulations in development and altered states in diseases emerge from largely stochastic molecular phenomena. The ability to decipher the molecular dynamics and structure inside living cells is governed by the spatial and temporal limits of noninvasive imaging and additional limits of labeling technology. Emerging developments in live-cell microscopy, fluorescence correlation spectroscopy, and fluorescent labeling have begun to open unique opportunities to reveal the control logic and dynamics of biological systems with high spatiotemporal details. Here, we will review recent advances in microscopy and fluorescent probes for single-molecule studies, and discuss the strategies to efficiently extract the in vivo molecular dynamic and structural information at the single-molecule level with minimal perturbations to the living biological system. The Diffraction Limit The observation of molecular-scale structural details with light microscopes is difficult because of the Abbe diffraction limit, d, which is given by the equation d = 0.61l/NA, where l is the emission wavelength and NA is the numerical aperture of the objective. Specifically, the image of an infinitely small self-luminous object in a microscopy is a finite-size diffraction pattern (i.e., the point spread function, PSF) created by the 644 Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc.

action of interference in the image plane. The image consists of a central spot surrounded by a series of higher-order diffraction rings (Figure 1A). The central spot, which contains most (
84%) of the photons from the point source, is called the Airy disk. The Airy disk radius is equal to d, explaining why the light microscope cannot resolve objects that are closer than this distance. When digital cameras are used, the image of the spot is spread across multiple pixels. Here, we focus on diffraction-limited optical microscopy systems where the pixel size is relatively small compared to the diffraction PSF. In the past two decades, various super-resolution microscopy techniques have been developed to break the diffraction limit either by single-molecule localization or by using patterned light to spatially modulate the fluorescence emission to improve the optical resolution. Specifically, the latter approaches include near-field scanning optical microscopy (NSOM) as well as far-field techniques such as stimulated emission depletion microscopy (STED), reversible saturable optical fluorescence transitions (RESOLFT), and structured illumination microscopy (SIM) (reviewed in Schermelleh et al., 2010). Here we focus on imaging techniques that permit direct measurements of the live-cell molecular dynamic and structural information at the single-molecule level. Single-Molecule Localization and Tracking As first noted by Heisenberg (Heisenberg et al., 1930), the position of a particle of subdiffractive size can be measured to much greater precision than its apparent width in a diffraction-limited microscope by finding the centroid of its fluorescence distribution (Betzig and Chichester, 1993; Bobroff, 1986). Single-molecule localization algorithms have been optimized throughout the years, and the localization precision can be estimated by simple equations (Mortensen et al., 2010; Thompson et al., 2002). Commonly, a Gaussian (plus a background) is least-square fitted to the distribution (Figure 1A). The lateral localization precision (i.e., variance) can then be estimated by the following equation (Mortensen

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Figure 1. Basic Concepts of Single-Molecule Localization, Tracking, and Fluorescence Correlation Spectroscopy (A) Schematics illustrating the relative size of a single emitter, the resulting Airy disk in the image plane, the PSF as observed on the microscope camera, and single-molecule probability distribution of position as determined by Gaussian fitting. (B) An example of temporally separating single-molecule detections in densely labeled samples for super-resolution imaging. Photoactivable fluorescent proteins attached to a diffraction limited structure were repeatedly activated, imaged and bleached (Ba–Bd). Summing the molecular images across all frames results in a diffraction-limited image (Be and Bf). However, if the location of each molecule is first determined by fitting the expected molecular image given by the PSF of the microscope (Bg, center) to the actual molecular image (Bg, left), the molecule can be plotted (Bg, right) as a Gaussian that has a standard deviation equal to the precision in the fitted position. Repeating with all molecules across all frames (Ba0 –Bd0 ) and summing the results yields a super-resolution image (Be0 and Bf0 ). Credit, Betzig et al., 2006. (C) An example of 3D SPT of HaloTag-Sox2 expressed in a single embryonic stem cell and labeled with tetramethylrhodamine (TMR) using multifocus microscopy. Volume rendering of a Sox2 single-molecule image (purple) superimposed with single-molecule trajectories. Three molecules with distinct behaviors were selectively displayed on the top (from left to right, freely diffusing particle, particle undergoing a free/bound transition, and immobile molecule). Color bar shows the corresponding frame number. Scale bar, 2 mm. Credit, Chen et al., 2014b. (D) Typical confocal FCS optical layout (top left) and the observation volume (pink, top right). Fluorescence fluctuation curves for fast (middle left) and slow (middle right) diffusion. Autocorrelation curves (bottom) for varied molecular concentrations and diffusion properties of a single-component system. DM, dichroic mirror.

et al., 2010; Rieger and Stallinga, 2014; Thompson et al., 2002),   s2 + a2 12 16 + 4t ; (Equation 1) D2 = 9 N =

where t is roughly equal to the ratio between the background intensity and the peak signal intensity, s is the standard deviation from the fit, a is the pixel size, and N is the total photon count. This equation reveals two fundamental approaches that we will discuss later to improve the localization precision: (1) applying fluorophores that emit more photons, and (2) designing imaging strategies that increase the signal-to-background ratio (SBR). For densely labeled samples, molecules within the diffraction limit cannot be resolved spatially at the same time. However, it was proposed that if individual molecules can be distinguished by their differing optical characteristics, super-resolution imaging can be achieved by their individual isolation and subsequent localization (Betzig, 1995). An early implementation of this method used the narrow spectral linewidths of individual molecules near absolute zero to resolve seven molecules within one diffraction-limited 3D focus (van Oijen et al., 1998). However, it is common to locate far more than seven molecules at a single focus in biological specimens, and it is indeed necessary to do so in order to achieve resolution well beyond the Abbe limit. A

resolution of
20 nm was obtained in fixed cells when more than 2,000 molecules were resolved in one diffraction-limited region through the serial photoactivation of fluorescent proteins or caged dyes (Betzig et al., 2006). The same principle was demonstrated in vitro with other photoactive fluorophores such as PA-GFP (Hess et al., 2006) or dyes with long-lived dark states (Rust et al., 2006) in the same year, albeit at much lower molecular densities. Eventually, a range of directly excited photoactive dyes was developed in different colors (Dempsey et al., 2011; Heilemann et al., 2008, 2009). The underlying principle for all these techniques is the same: a subset of individually labeled molecules are stochastically activated and imaged in a given frame. The individual molecules are then localized and these positions combined to provide a high-resolution map of molecular locations (Figure 1B). Another application of localization is single-particle particle tracking (SPT). In this method, single-molecule detections are localized across successive temporally separated images to reconstruct of molecular diffusion trajectories through time and space (Figure 1C). Live-cell SPT was shown to accurately quantify the dynamics of low-density lipoprotein receptors in live fibroblast cells two decades ago (Ghosh and Webb, 1994). Subsequent applications were restricted to the exterior face of the plasma membrane because of the difficulty of Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc. 645

Molecular Cell

Review delivering fluorescent probes past this barrier in live cells. This situation changed with the advent of genetically encoded FPs (review in Ferna´ndez-Sua´rez and Ting, 2008), which enabled the investigation of intracellular molecular dynamics. Several initial studies demonstrated the power of this approach, including the measurement of the dynamics of individual lac repressors of gene expression in live bacteria (Elf et al., 2007; Tokunaga et al., 2008). However, since these approaches illuminated the entire field of view simultaneously, the FP-fusion protein expression needed to be extremely low to ensure that the molecules were sufficiently well isolated to be localized precisely. This strictly limited the number of events that could be measured. This problem was eventually circumvented by tracking many temporally separated subsets of photoswitchable FP-tagged molecules in live-cell PALM experiments (sptPALM) (Hess et al., 2007; Manley et al., 2008). The high density of trajectories so obtained supplies enough statistical information to reconstruct high-resolution diffusion maps and infer distinct modes of diffusion. Subsequently, this technique has been successfully applied to a wide range of biological systems, including the characterization of dynamics of neurotransmitter receptors in axons, integrins inside focal adhesions, and transcription factors (Constals et al., 2014; Frost et al., 2010; Heidbreder et al., 2012; Hoze et al., 2012; Izeddin et al., 2014; Nair et al., 2013; Rossier et al., 2012; Shrivastava et al., 2013; Yang et al., 2012). Unfortunately, even the most photostable FPs do not emit enough photons to enable high-precision single-molecule localization for long track lengths over long times. However, recent development (see below) of highly photostable cell-permeable organic dyes targeted to genetically encoded, protein-specific attachment sites in live cells (e.g., Snap-tag and HaloTag), as well as advances in imaging geometries, have expanded the spatiotemporal range of single-molecule localization and tracking experiments (Chen et al., 2014a, 2014b; Grimm et al., 2015; Liu et al., 2014b). Despite these advances, it is important to note that precise single-molecule localization requires the fluorophore to move slowly on a scale compared to the desired precision during the period of image acquisition. The minimum acquisition time is in turn influenced by several factors, including the imaging modality, camera sensitivity and speed, excitation intensity, background, and brightness of the dye. These considerations make SPT techniques more suited for detecting slow diffusion events. Fluorescence Correlation Spectroscopy Fluorescence correlation spectroscopy (FCS) is a method capable of measuring molecular concentrations, diffusion rates, and molecular interaction dynamics in live cells (Magde et al., 1972). The measurement is based on observation of a single molecule or several molecules within a diffraction-limited spot in solution or in a living cell (Figure 1D, top panel). A confocal pinhole is used to reject photons from outside of the desired illumination volume. Emission photons are usually collected by using a high-sensitivity single photon counting detector (such as avalanche photodiode [APD] or photomultiplier tube [PMT]), with subnanosecond time resolution. In a confocal single-photon 646 Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc.

FCS microscope, the detection volume is approximately 1 fL. An important requirement for FCS measurements is a low concentration (typically <100 nM) of the fluorescently labeled molecules to ensure few emitters are present in the detection volume. Under this regime, the random diffusion of fluorescent molecules results in time-dependent fluorescence fluctuations in the observed volume (Figure 1D, middle panel). The temporal profile of these fluctuations is dependent on both the molecular diffusion rate and the concentration of the fluorescent molecule. Specifically, if the fluorophore diffuses rapidly in and out of the excitation volume, the photon burst is short-lived. If the fluorophore diffuses more slowly, the photon burst displays a longer duration. The standard way of analyzing FCS data involves auto- or cross-correlation analysis of the temporal fluorescent intensity data. The resulting correlation functions are further explained by specific diffusion models to extracting molecular concentrations, diffusion coefficients, and other molecular details (Figure 1D, bottom panel). Unlike SPT, FCS-based diffusion analysis is an indirect measurement of molecular dynamics and thus is subject to population averaging effects. To fit the FCS correlation curves with a particular diffusion model, prior knowledge of the underlying system is required or assumptions must be made. For example, if multiple diffusion modes coexist in the same molecular system—common for biomolecules in live cells—it becomes difficult to use FCS to resolve the dynamics associated with each species. Focused illumination in the FCS set-up might induce local photodamage in the sample, which could in turn affect the validity of the measurements. However, FCS has advantages that complement SPT measurements. First, the observed molecules are replenished continuously by diffusion into the spatially restricted excitation volume. Thus, FCS allows observation for longer durations and does not require selection of specific molecules for observation. Second, since FCS measurements rely on fluorescence fluctuations rather than single-molecule localization, fast detection paradigms can be used that make technique sensitive enough to measure diffusion events on a much faster scale than is possible by SPT. While traditionally used in a confocal modality, two-photon FCS (Berland et al., 1995) has been used to produce a more precisely defined excitation volume (essential for accurate diffusion measurements) while also eliminating out-of-focus photobleaching. Likewise, STED FCS has been used to reduce the excitation volume, which permits specimens with high fluorophore concentrations (>100 nM) to be measured (Hedde et al., 2013). Fo¨rster resonance energy transfer (FRET) FCS and two-color crosscorrelation (FCCS) has enabled measurement of the dynamics of inter- and intramolecular interaction of two species in live cells (Bacia and Schwille, 2007; Torres and Levitus, 2007), while scanning FCS (sFCS), TIRF-FCS, and FCS based on selective plane illumination microscopy (SPIM-FCS) have turned FCS into an imaging tool for comprehensive mapping of diffusion coefficients, flow velocities and concentrations in 2D or 3D across large fields of view (Brazda et al., 2014; Guo et al., 2014; Petra´sek et al., 2010). These improvements have greatly expanded the application space of FCS and have allowed cross-validation of SPT data with this complementary technique.

Molecular Cell

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Figure 2. Trade-Offs in Live-cell Imaging and Spatiotemporal Dimensions in Biology (A) The limited photon budget from the specimen can be spent to improve spatial resolution, temporal resolution, or the depth of imaging. However, in some cases, it is used inefficiently, which only contributes to unnecessary phototoxicity. (B) Photobleaching and phototoxicity depend not only on the total amount of excitation photons delivered to the sample but also nonlinearly on the instantaneous peak intensity applied to the specimen. (C) (Upper) Low labeling density and poor incorporation of fluorescently tagged proteins into the structures of interest limit the ability to visualize them clearly. (Lower) Nyquist sampling criterion, to unambiguously resolve structure features with size close to d, in average one localization event in 1/2 d spatial unit need to be sampled. For example, when distances between closest labeling events are comparable to the size of the smaller ps (50% labeling density panel), they become illegible. (D) p is legible again after particle averaging of partially labeled smaller ps in (C). (E) General spatial and temporal length scales in biology.

Principles for Noninvasive Live-Cell Imaging Live-cell imaging via fluorescence poses unique challenges and trade-offs for both microscopy and labeling technologies. The central issue to any fluorescence imaging experiment is the ‘‘photon budget’’—there is a finite number of fluorescently labeled molecules in the sample at a given time and each fluorophore emits a finite number of photons before photobleaching. Each experiment must be optimized to economically spend this photon budget to extract the maximal amount of information with minimal amount of perturbation to the living system. Importantly, there is a direct trade-off between spatial resolution, imaging speed and phototoxicity, as higher resolution requires more measurements and more collected photons, which takes more time, and requires delivering more potentially damaging light to the specimen. Furthermore, aberrations and scattering complicate noninvasive imaging at depth with high spatiotemporal resolution (Figure 2A). Phototoxicity itself is a complex process. Excitation of molecules such as chromophores inside the cell can generate reactive oxygen species (ROSs) that can damage a variety of cellular constituents (e.g., protein, DNA, lipid) and either alter the biological process of interest or elicit cell-cycle arrest or cell death (Dixit and Cyr, 2003). Generally, high-energy short

wavelength light is more toxic than longer wavelength light and this damage often depends supra-linearly on peak intensity (Figure 2B) (Chen et al., 2014a; Gao et al., 2012). Thus, with the same total integrated excitation power, uniform illumination induces less photodamage compared to point- or line-scanning methods. Labeling density in single-molecule microscopy also plays into the issue of cellular toxicity. The labeling process itself can result in non-physiological behavior, either due to the stress of introducing exogenous labels past the plasma membrane and then targeting them with sufficient specificity to desired structures, or due to overexpression of FPs. For SPT experiments, the density of standard FP- and dye-based labels is often initially too high to isolate single molecules, so prebleaching is then required to reduce the concentration to where single-molecule imaging is possible. This can also contribute significant initial stress on the cell. No pre-bleach is required in sptPALM, but the prolonged exposure to weak (typically <1 W/cm2) near UV light for activation and intense (>1 kW/cm2) visible light for singlemolecule excitation can also produce significant damage. Prolonged light exposure becomes an even more important concern in imaging structure by live-cell PALM, as opposed to the simpler goal of particle tracking. The problem is that, even Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc. 647

Molecular Cell

Review Table 1. Super-Resolution Imaging Methods

STED RESOLFT Localization

SIM

Reported Nyquist Limited Resolutions (nm)

Photon Increase (Fold)

Laser Intensity (W/cm2)

Acquisition Time (s)

xy: 20 nm (2D)

100

104–109

>60

xyz: 30 nm (3D)

1,070

xy: 20 nm (2D)

100

xy: 10 nm; z: 20 nm (3D)

14,400

xy: 100 nm (2D)

4

xy: 100 nm; z: 370 nm (3D)

8


1,000 3

10 –10

4

>20
1,500

10–102

0.1–1
10

Nyquist criterion: N-fold resolution increase in D dimension requires NDfold more protons.

if the individual molecules can be localized precisely, high labeling densities are required to extract high-resolution structural information: by the Nyquist criterion, the mean separation between fluorescent labels must be no greater than half of the desired spatial resolution (Figure 2C). To isolate and localize the number of molecules thereby required at 50 nm resolution or below requires long imaging times at high intensities (Table 1), which is not conducive to cell health or the imaging fast structural dynamics. It is for these reasons that the first demonstration of live-cell PALM by the Nyquist criterion (Shroff et al., 2008) used a photon-tolerant cell line (Chinese hamster ovary, CHO) and operated in a TIRF configuration in order to expose only the small fraction of the total cellular volume near the substrate to the intense light. Furthermore, a very slowly evolving process (the evolution of focal adhesions) was studied to minimize motion-induced artifacts during the lengthy acquisition of each frame. Subsequent demonstrations of live-cell localization microscopy (Jones et al., 2011; Klein et al., 2011; Shim et al., 2012) typically operated in a wide-field geometry, required even higher intensities, or recorded insufficient localization events for high Nyquist-defined resolution. One new and interesting application of spatially resolved livecell localization microscopy with density requirements between those of SPT and Nyquist-level imaging of arbitrarily dense and complex structures is the mapping of spatially heterogeneous regions of constrained diffusion or binding of transcription factors (TFs) in the nucleus. In these studies, the differing kinetics of single TFs provides a contrast mechanism to identify heterogeneous regions of genome organization (e.g., Figure 6, upper left) and their spatiotemporal relationship to other nuclear constituents such as heterochromatin or partner TFs (Chen et al., 2014a, 2014b; Grimm et al., 2015; Izeddin et al., 2014). Another means of dealing with the labeling density problem which has proven very effective is the study of stereotypic structures in fixed cells, where particle averaging techniques can be used to combine the data from many images of many such structures to fill in the gaps from incomplete labeling (Figure 2D) (Lo¨schberger et al., 2012; Szymborska et al., 2013). By these means, the radial position of specific proteins in the nuclear pore has been determined to subnanometer precision (Figure 6, upper right). However, it remains to be seen if these approaches 648 Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc.

can be applied across a large population of live cells in order to uncover unique spatially resolved single-molecule behaviors or macromolecular structures while reducing the imaging stress on single cells. Although outside the scope of this single-molecule review, it is worth noting that structured illumination microscopy is far better suited for live-cell imaging (Fiolka et al., 2012; Kner et al., 2009; Shao et al., 2011) than any other super-resolution method. Although in linear form it offers resolution only 2-fold better than the Abbe limit, this weakness is also its strength: far lower label densities are required; conventional fluorescent labels can be used (facilitating multicolor imaging); far fewer raw images need be acquired (leading to imaging as fast as 11 frames/s in 2D); and illumination intensities are 102–103 lower than in localization microscopy and 103–108 lower than in RESOLFT and STED (Table 1). The combination of live-cell SIM with sptPALM would be a powerful tool to study single-molecule diffusion, active transport, and macromolecular assembly in conjunction with direct imaging of the subcellular structures that regulate these events. Indeed, a comprehensive understanding of any complex biological process requires interrogation of molecular behaviors of multiple components across a wide range of samples and experiments with different spatiotemporal length scales. This requires imaging techniques with different spatial sweet spots, from nanometers to millimeters, and diverse temporal resolutions, from nanoseconds to days (Figure 2E). This broad span of spatiotemporal resolution requirements necessitates the further development of live-cell imaging platforms and labeling techniques to work within the constraints outlined above and enable new or improved biological experiments. Single-Molecule Imaging Modalities Wide-Field and Confocal Microscopy Traditional fluorescence microscopy involves a wide-field configuration where the illumination laser is delivered to the sample exciting all the fluorophores in a near-cylindrical volume (Figure 3A). Wide-field microscopy is commonly used to image single molecules but suffers from significant drawbacks. Only the fluorescent molecules near the focal plane are well-localized. Due to the lack of intrinsic optical sectioning, the photons emitted from out-of-focus molecules contribute to background, lowering the SBR of single-molecule detection and decreasing the localization precision. Confocal microscopy places a pinhole at an image plane conjugate to the sample, thereby rejecting light from out-of-focus molecules (Nie et al., 1994). However, due to the relatively slow point-scanning acquisition, confocal microscopy is limited in its ability to detect fast molecular dynamics. For both of these approaches, the illumination extends through the entire bulk of the specimen. However, the photons emitted by fluorophores well beyond the focal plane do not contain any useful spatiotemporal information. This inefficient expenditure of the photon budget results in premature bleaching of labeled molecules and phototoxicity. Conceptually, if only molecules around the focal plane are selectively illuminated, both the background problem and photon inefficiency issues can be avoided. The past few decades have seen significant

Molecular Cell

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Figure 3. Rapidly Advancing Illumination Methods (A) Schematic comparisons on the optical sectioning power and the axial depth adjusting flexibility of different illumination techniques. (B) Differences between a single scanned Bessel beam, scanned parallel, noninterfering Bessel beams, and lattice light-sheet illumination. (C) Images of molecules that have displacements larger than the localization precision (D) within the illumination duration (dt) suffer from motion burring. Stroboscopic illumination reduces motion blurring effects by shortening the temporal width of the illumination. The maximum diffusion coefficient (Dmax) without inducing significant motion blurring is calculated according to Brownian diffusion model.

advances in illumination and detection strategies that achieve this goal. For example, two photon excitation (TPE) generates little out-of-focus emission. However, the application of this technique to SPT is limited by the need for time-consuming point scanning to reconstruct an image, as well as by the high intensities involved and the resulting potential for substantial nonlinear damage in live cells. Total Internal Reflection Fluorescence Microscopy Another method to restrict the illumination volume is total internal reflection fluorescence (TIRF) microscopy (Axelrod et al., 1984). This technique exploits the exponential decay of evanescent waves near a glass surface when a laser beam with an incident angle larger than the critical angle is completely reflected at the glass-culture medium interface. TIRF illuminates a region 50–200 nm deep into the specimen, smaller than the diffraction limit. Due to its highly restricted illumination range, TIRF-based microscopy techniques are limited to studying molecular kinetics of membrane-bound proteins near the cell membrane or labeled biomolecules on a surface in vitro. On the other hand, only a very small fraction of the cellular volume is illuminated in TIRF, and hence it can be much less phototoxic than other methods of single-molecule microscopy, and can image for far longer periods if new fluorescent molecules are recruited to the TIRF zone. In addition, background is negligible, so high precision localization is generally much easier in TIRF. From its initial use in single-molecule imaging (Funatsu et al., 1995; Schmidt et al., 1996), the applications of TIRF have expanded tremendously including characterization of the dynamics of motor

proteins, DNA replication machinery, RNA polymerase, and protein-nucleic acid interactions in vitro (Cai et al., 2009; Churchman et al., 2005; Ha, 2001; Harada et al., 1999; Kurth et al., 2013; Reck-Peterson et al., 2006; Roy et al., 2008; Sako et al., 2000; van Oijen, 2011; Yildiz et al., 2003). HILO and Gaussian Light-Sheet Illumination To selectively illuminate regions deeper than the TIRF range, highly inclined and laminated optical sheet (HILO) microscopy uses a laser beam with an incident angle at the substrate-specimen interface slightly smaller than the critical angle. This creates a slightly inclined light sheet through the specimen and just above the substrate. Using this approach, a light sheet with a full width at half maximum (FWHM) of about
3 mm and has been used for intracellular single-molecule detection of GFPtagged proteins (Tokunaga et al., 2008). The quest for selective illumination at the focal plane has further evolved to light-sheet microscopy, where a separate illumination objective, placed perpendicular to the detection objective, generates a light-sheet either by using a cylindrical lens or a scanning Gaussian beam. This technique is particularly useful for imaging with low background within thick samples. Indeed, single-molecule light-sheet imaging has been demonstrated in vivo at depths up to 200 mm (Ritter et al., 2010) and applied to super-resolution localization microscopy in multicellular specimens (Cella Zanacchi et al., 2011). Unlike TIRF or HILO microscopy, light-sheet microscopy permits the illumination plane to be placed at any desired position in the specimen. However, the inverse relationship between the width and the Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc. 649

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Review divergence of a Gaussian beam near its focus causes a tradeoff in the minimum thickness of the light sheet and the area over which the beam thickness remains reasonably uniform: when imaging a 50 mm diameter field of view, an optimized Gaussian light sheet diverges to a FWHM thickness of 2.8 mm at either end (Planchon et al., 2011). This is considerably larger than the
0.7 mm depth of focus of a typical high NA objective used for single-molecule detection, and hence single-molecule experiments with Gaussian light sheets are often plagued by significant background from autofluorescence and out-of-focus molecules. Furthermore, many of these out-of-focus molecules can bleach prematurely before they can be localized and contribute to tracking data or super-resolution image reconstruction, thus wasting the photon budget. Bessel Beam Selective-Plane Illumination To mitigate the trade-off between the length and thickness of conventional Gaussian light sheet, a new illumination strategy based on a Bessel beam was developed (Gao et al., 2014; Planchon et al., 2011). The Bessel beam is ‘‘nondiffracting’’ and produces a thinner, uniform light sheet with a FWHM approaching 500 nm across a 50 mm field of view. A caveat of this illumination method is the presence of concentric side lobes in the Bessel beam, which can create substantial out-of-focus excitation as the beam is swept in a plane. Fortunately, these side lobes become progressive weaker with distance (16%, 9%, and 6% of the central peak intensity for the first three side lobes, respectively), so the fluorescence they generate is negligible compared to that from the central peak when TPE is used. In practice, Bessel beam illumination using TPE and a high NA (1.1) detection objective can achieve nearly isotropic 3D resolution of
230 nm laterally and
350 nm axially (Gao et al., 2014; Planchon et al., 2011). It is worth noting that the Bessel TPE mode might offer an optimal strategy for the deep-tissue single-molecule detection due to reduced scattering by the specimen. Using linear excitation with multiple coherent swept Bessel beams, singlemolecule detection of key pluripotency regulators (Sox2 and Oct4) in the single-living embryonic stem cell nucleus was achieved with significantly increased SBR compared to widefield microscopy (Chen et al., 2014b). Lattice Light-Sheet Illumination An initial refinement of Bessel beam microscopy involved spreading the excitation across multiple noninteracting Bessel beams, which was found to reduce photodamage presumably arising from nonlinear mechanisms (Gao et al., 2012). To build upon this and further improve compatibility with live cells, a lattice light-sheet illumination scheme was developed by generating an ultrathin 2D light sheet using a binary phase pattern on a spatial light modulator (SLM) to form multiple beams of tightly controlled spacing that interact with each other constructively in the central plane but destructively in the slide lobes outside this plane (Figure 3B) (Chen et al., 2014a). This optical lattice uniformly spreads the excitation power across a large view of field (
20–40 mm in the direction of propagation, and 80 mm in the direction perpendicular to it) while producing a light sheet only
0.4–0.6 mm thick—thinner than the depth of focus of the detection objective. Thus, the approach produces nearly TIRF-like SBR even in thick, fluorescently dense specimens. Used in conjunction with an improved rhodamine label (Janelia 650 Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc.

Fluor 549) (Grimm et al., 2015), lattice light-sheet microscopy enabled long-term continuous 3D single-molecule mapping of transcription factor stable binding sites in living embryonic stem cells (Liu et al., 2014b), and also was used to demonstrate single-molecule imaging across multiple cells simultaneously within a 3D stem cell spheroid (Chen et al., 2014a). Despite the introduction of these newer illumination strategies, traditional wide-field imaging with uniform excitation of the entire specimen remains the dominant modality for single-molecule imaging, thanks to its simplicity. However, its lack of optical sectioning introduces substantial costs (Figure 4E)—increased phototoxicity, reduced localization precision due to increased background from out-of-focus molecules and autofluorescence, premature bleaching of out-of-focus molecules before they can be localized (thereby reducing the achievable localization density), and slower imaging in PALM and sptPALM—as the mean separation of molecules in each raw image frame must increase to prevent overlap of the larger PSFs of defocused molecules. While these disadvantages are manageable in specimens on the order of the depth of focus in thickness (e.g.,
0.5–1.5 mm), techniques such as lattice light-sheet microscopy are needed to extend the full panoply of single-molecule imaging methods to thicker specimens, including whole living multicellular organisms. Strategies to Counter or Exploit Motion Blur As mentioned above, a requirement for accurate single-molecule localization is that the spatial displacement within camera’s acquisition time must be smaller than the localization precision (D, Equation 1) (Figure 3C). Otherwise, the singlemolecule measurement suffers from motion blur, which compromises localization precision. Two strategies are available to counter the motion blur effect. The first involves using stroboscopic illumination in which a high-intensity laser pulse with a duration much less than the imaging acquisition time is delivered to the sample. In this case, although the camera speed is limited, the degree of motion blur depends upon the temporal width of the laser pulse, which can be much shorter (Elf et al., 2007; Xie et al., 2008). Nonetheless, the high-intensity laser pulses in this technique may induce more nonlinear photodamage (Figure 2B), and the labeling density must be low to reduce background. Another viable strategy is to use cameras with higher imaging speed and sensitivity. For example, with modern sCMOS cameras, imaging at up to 32 reconstructed super-resolution images per second has been demonstrated in localization microscopy (Huang et al., 2013). Even higher speeds of molecular imaging may be possible with temporal pixel multiplexing (Bub et al., 2010). Motion blur can also be exploited to selectively image immobile or slow diffusion events such as transcription factor-DNA interactions in live cells (Chen et al., 2014b; Etheridge et al., 2014). Usually, in these experiments, long acquisition times and low-excitation powers are used to augment the blurring effect to observe only those molecules with long residence times (Figure 3C). This principle is also used in the localization microscopy method known as PAINT (point accumulation and imaging of nanoscale topography), which relies on the transient binding of molecules to the desired target for isolation, rather

Molecular Cell

Review

Figure 4. Detection Methods to Access the Axial Dimension (A) The schematic shows the concept of multifocal microscopy. (B) Examples of engineering axial depth sensitive PSFs. Credit, Huang et al., 2008; Jia et al., 2014; Pavani et al., 2009. (C) Schematics and operating principle of multiphase interferometric microscope illustrating how z position is resolved. The electric field from a point source with z position d propagates both upward and downward. These two fields interfere in a special beam splitter that produces three output beams with 120 relative phase shifts between the two input fields. (Bottom) The interfered beams are sent to the three color-coded CCD cameras, and the intensity of the point source on each oscillates out of phase with the others depending on the axial position of the point source. Credit, Shtengel et al., 2009. (D) Reported performance summary of different single-molecule axial detection strategies. (E) The relationship between illumination thickness, SBR, and allowed labeling density for single-molecule imaging.

than the more common photoactivation principle of PALM/ STORM (Sharonov and Hochstrasser, 2006). Detection Methods to Access the Axial Dimension Wide-field, HILO, TIRF, and the various forms of light-sheet microscopy all permit the simultaneous illumination of multiple single molecules across a broad field of view (Figure 4D), without the need for time-intensive point scanning (Figure 3A). Additional innovations in detection have enabled the extraction of axial position information from these molecules, allowing 3D SPT at high temporal resolution. One of the oldest methods is to obtain this information from the dependence of the shape and size of the measured, defocused PSF on the distance from the focal plane (Speidel et al., 2003) (Figure 4A). Using two cameras, axial localization to
40 nm precision was achieved by this method across a z depth of 2.5 mm (Ram et al., 2008). In a similar vein, another technique used a diffractive grating to form aberration-corrected images from nine different focal planes simultaneously on the same camera, from which the axial positions of single molecules could be measured over

an axial range of
4 mm (Abrahamsson et al., 2013). This tool is unique in its ability to track rapidly diffusing single molecules in 3D, in the regime where most other methods are defeated by the need to serially scan the focal plane. On the other hand, the signal from each molecule is divided into nine parts, of which only one or two (those with focal planes near the molecule) provide significant position information. The others simply contribute background that reduce the precision with which other molecules at other focal planes can be localized. Several approaches to axial position measurement are based on engineering an axially sensitive PSF (Figure 4B). In one case, a cylindrical lens is used to introduce astigmatism which causes the image of the molecule to become increasingly elliptical in orthogonal directions above and below the focal plane. It has been applied across an axial range of 0.8 mm (Huang et al., 2008; Izeddin et al., 2012; Kao and Verkman, 1994). Related strategies use a spatial light modulator (SLM) to generate either a double helix PSF (Pavani et al., 2009) or a self-bending PSF (Jia et al., 2014) that allows precise axial single-molecule localization across a range of 2–3 mm. Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc. 651

Molecular Cell

Review

Figure 5. Labeling Strategies and Chemical Fluorophores Used in Single-Molecule Assays (A–E) Schematics of different labeling strategies useful for live-cell microscopy. The biomolecule components and fluorophores are represented by gray and green shapes, respectively. (F) Structures and spectral properties of fluorophores useful for single-molecule imaging. The dyes are ordered according to the absorption maxima of the dye (dashed line). Structures are colored according to the emission maxima. Cell-impermeant fluorophores are above the wavelength scale, and cell-permeable dyes are below the wavelength scale.

Although straightforward, these aberration-based approaches have a number of limitations. First, by introducing an aberration, the peak signal (i.e., the Strehl ratio) is reduced even at the focal plane, reducing the localization precision. Second, most methods create a larger spot with increasing distance from the focal plane, trading off lateral precision for axial. The double helix approach maintains a more uniform size with axial distance, but is then broader than other methods at the focal plane itself. Finally the optical elements used to generate the aberration can be light inefficient, particularly diffractive approaches (diffractive optical elements or spatial light modulators) that spread the emission across multiple diffraction orders. One important and fundamentally different method with the highest axial localization precision uses multiphase interferometry in conjunction with PALM (iPALM) (Shtengel et al., 2009). In this approach, the electric fields produced by an emitting fluorescent molecule but propagating in opposite directions are collected by two opposed objectives on either side of the specimen and coherently interfered at three different cameras, each with a 1/3 wavelength difference in phase between them (Figure 4C). The collection of twice as much light, and the use of phase information, results in axial precision of
10 nm, even with weakly emitting fluorescent proteins. This has been used to unravel the vertical architecture of focal adhesions (Kancha652 Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc.

nawong et al., 2010), the 3D organization of nucleoids in mitochondria (Kopek et al., 2012), and the location of ESCRT proteins relative to the plasma membrane and budding HIV particles (Van Engelenburg et al., 2014). Developments in Labeling Strategies and Dyes Two critical elements of any fluorescence imaging experiment are (1) the labeling strategy and (2) the fluorescent label. The labeling strategy determines the degree of perturbation on the biological system, and the label dictates the imaging wavelengths and the photon budget of the experiment. The use of classic fluorophore labeling strategies such as amine-reactive N-hydroxysuccinimidyl (NHS) esters (Figure 5A) allows the formation of stable bioconjugates with organic fluorophores (Hermanson, 2013). However, the introduction of the resulting labeled proteins or oligonucleotides into live cells is difficult, typically requiring microinjection (Ponti et al., 2004), bead loading (Stasevich et al., 2014), or transient membrane permeablization (Sharonov and Hochstrasser, 2006). The discovery of genetically encoded fluorophores such as green fluorescent protein (GFP) and related proteins (e.g., YFP, mEOS, Dendra2) revolutionized intracellular labeling in live-cell imaging (Kremers et al., 2011). Fluorescent proteins have been utilized in singlemolecule imaging experiments such as SPT and localization

Molecular Cell

Review microscopy and have been reviewed extensively (Ferna´ndezSua´rez and Ting, 2008). However, there are three major caveats of fluorescent proteins: relatively poor photostability compared to organic dyes, potential formation of homo-oligomers (Landgraf et al., 2012; Zhang et al., 2012), and limited choices in spectral wavelengths especially in the red region of the visible spectrum (Xia et al., 2013). These issues limit the photon budget, labeling fidelity, and available spectral regions in single-molecule experiments using genetically encoded proteins. Hybrid approaches that combine the genetic specificity of fluorescent proteins with the favorable photophysics of organic dyes are needed to advance single-molecule experiments in live cells. Forming Bioconjugates inside Living Cells Over the past two decades a number of labeling strategies have been developed to attach chemical fluorophores to biomolecules inside cells (Figures 5B–5E). One strategy relies on bioorthogonal chemical reactions between motifs on the biomolecule and the dye. Examples of bioorthogonal functional groups include strained alkenes such as trans-cyclooctene (Figure 5B), which can be installed into proteins using unnatural amino acid technology. This group reacts quickly and selectively with tetrazines and allow attachment of fluorescent labels  et al., 2014). Another labeling at defined positions (Nikic scheme involves inherent or engineered affinity of the fluorescent label for the biomolecule of interest. Some dyes have inherent affinity for a biological structure, which can allow super-resolution imaging under the PAINT regime (Sharonov and Hochstrasser, 2006). Alternatively affinity can be engineered by attaching a fluorophore to an antibody, oligonucleotide, toxin, or drug (Figure 5C); the resulting conjugate can be ius et al., used to stain distinct cellular assemblies (Lukinavic 2014; Stasevich et al., 2014). The affinity tag concept has been expanded in the development of genetically encoded tags that bind small molecule fluorogenic dyes. These tags can be expressed as fusions with the protein of interest; incubation with the cognate small molecule ligand allows specific labeling (Yan et al., 2014). A direct corollary to fluorescent proteins are the ‘‘self-labeling tags’’ such as the HaloTag (Figure 5D). This labeling system is based on a dehalogenase enzyme that reacts with a short chloroalkane motif that can be attached to a small molecule fluorophore. By mutating active-site residues, the catalytic cycle of the enzyme stops at the ester intermediate, resulting in rapid, specific covalent labeling of a protein of interest inside living cells (Los et al., 2008). Other tags based on the same concept, such as the Snap-tag or Clip-tag (Gautier et al., 2008), are orthogonal to the HaloTag, allowing multicolor labeling. Finally, enzymes can be used in a different way to label proteins. Enzymes such as lipoic acid ligase (LplA) or sortase (Figure 5E) can efficiently catalyze the attachment of a fluorophore bearing a short aliphatic acid reminiscent of lipoic acid or a sortase recognition motif, respectively, to target protein (Liu et al., 2014a; Theile et al., 2013). Every labeling strategy for live-cell experiments possesses trade-offs between cell permeability, speed of labeling, tag size, and compatibility with different dye types. Incorporation of an unnatural amino acid is a minor perturbation but is still an

emerging technique, requiring the delivery of the exogenous amino acid and several pieces of biochemical machinery to achieve labeling. Small, cell-permeable affinity tags can be ius et al., 2014), but the target used in live-cell imaging (Lukinavic scope of these simple probes is limited. More generalizable affinity tag systems (antibodies or oligonucelotides) are larger and typically membrane impermeant. The enzyme-based selflabeling tags are currently the best option for labeling for live-cell single-molecule experiments. They consist of a single protein, the cognate ligand motif is small and cell-permeable, and they exhibit faster labeling kinetics than bioorthogonal chemical reactions. The two major drawbacks of these tags are the large size of the tag and the limited choices of available chemistries and fluorophores, which restricts multicolor applications. Ligase systems such as LplA utilize a small, nonperturbing peptide tag and rapid enzyme-mediated ligation, but the compatible dye palette is small (Liu et al., 2014a). Sortase-mediated ligation also utilizes small tag consisting of a few amino acids. However, this system requires a large excess of fluorophore ligand for efficient conversion, making it most useful for in vitro labeling applications where the conjugate can be purified (Theile et al., 2013). Collectively, improving the delivery of the dye labels to cells and tissue, decreasing the size of the genetically encoded tag, and expanding the compatibility with different fluorophores will open new avenues for single-molecule experiments in live cells. With genome editing techniques gradually become accessible (Charpentier and Doudna, 2013), we also expect a future trend of directly tagging and labeling protein at the endogenous gene loci, which could make the fusion protein expressed at physiologically-relevant levels and thus potentially increase the labeling density and functional integration efficiency into the desired cellular structures. Small-Molecule Fluorophores for Live-Cell Labeling The most familiar organic fluorophores are the commercial series of dyes such as Alexa Fluor, ATTO, and Cy. In most cases these compounds are modified versions of classic fluorophores that were discovered a century ago (Lavis and Raines, 2008, 2014). Several of these fluorophores exhibit the appropriate brightness and photostability for single-molecule experiments in vitro (Figure 5F). The CyDyes such as Cy2, Cy3, Cy5, and Cy7 (Figure 5F) are sulfonated derivatives of classic cyanine dyes (Mujumdar et al., 1993). Sulfonation renders the dyes highly water soluble, resulting in improved performance as labels. Cy3 and Cy5, along with the structurally similar Alexa Fluor 555 and Alexa Fluor 647, have been widely employed as labels for single-molecule experiments in vitro and in fixed cells (Zhang et al., 2014). Sulfonation was also employed on rhodamines to prepare some of the Alexa Fluor dyes such as Alexa Fluor 488 and Alexa Fluor 594 (Panchuk-Voloshina et al., 1999). Other important dyes for single-molecule imaging experiments include the carborhodamine ATTO 647N (Santangelo et al., 2009) and the oxazinebased ATTO 655 (Wilmes et al., 2012). The commercial series of dyes were developed primarily as biomolecule labels for in vitro experiments and improvements in brightness and photostability were made by significant structural modifications such as rigidification of the structure and sulfonation (Mujumdar et al., 1993; Panchuk-Voloshina et al., 1999). As a result, many of these dyes exhibit poor Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc. 653

Molecular Cell

Review cell permeability, relegating their utility to labels in vitro or on the cell exterior (Bosch et al., 2014). Intracellular labeling has instead utilized classic, net neutral fluorophores such as rhodamine 110 and tetramethylrhodamine (TMR; Figure 5F). In particular, TMR has proven an excellent fluorophore for several labeling strategies and has been used for both super-resolution imaging and tracking experiments inside live cells (Chen et al., 2014b; Wombacher et al., 2010; Zhao et al., 2014). Nonetheless, TMR and similar dyes exhibit modest quantum yield values due to rapid nonradiative decay of the excited state. This process is suppressed by replacing the dimethylamino groups in TMR with four-memebered azetidine rings to give Janelia Fluor 549 (JF549). This minor substitution—a net addition of two carbon atoms—preserves the spectral properties and excellent cell permeability of TMR but elicits a 2-fold increase in both brightness and photostability (Grimm et al., 2015). This strategy can be extended to red-shifted rhodamine analogs, such as the silicon-containing JF646, allowing multicolor experiments and imaging with longer, less damaging wavelengths (Bosch et al., 2014). Further improvements in the chemistry of small molecule fluorescent probes will enable the discovery of other small structural modifications with a large impact on fluorophore brightness and photostability. In addition to labels for biomolecules inside living cells, histochemistry has also discovered fluorophores with inherent affinity for biological structures. Such dyes are useful in PAINT applications, especially if there is a change in fluorescence properties upon binding. The archetype PAINT probe is the oxazine dye Nile Red (Figure 5F), which is excited by orange light in aqueous solution, but green light in a lipophilic environment. This shift allows selective excitation of lipid-bound molecules, resulting in high-resolution images of cellular membranes (Sharonov and Hochstrasser, 2006). The PAINT imaging technique is useful but limited to structures with known ligands. Improving the generality of the system, using antibody-based technology (Jungmann et al., 2014) or perhaps a genetically encoded binding element with tunable kinetics and affinity, will greatly improve the utility of this technique for cellular experiments, especially in live cells. Computational Analysis: Finding and Connecting the Dots The diversified applications of super-resolution and singlemolecule imaging modalities in biology place substantial demands on computational approaches to automatically process and evaluate the data. In addition, easy-to-use computer-aided graphic programs are needed for data visualization and comparisons. These needs have driven the development of several open-source programs and algorithms to extract and visualize the information contained in 2D and 3D single-molecule data sets. For single-molecule localization, a number of algorithms have been developed to fit discrete single-molecule images or even high-density overlapping single-molecules (reviewed and compared in Small and Stahlheber, 2014). The U-track platform and the MTT program can be used to extract trajectories of single-molecule movement from localization data (Jaqaman et al., 2008; Serge´ et al., 2008). For diffusion anal654 Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc.

ysis, a range of diffusion models have been established based on the mean square displacement (MSD) curves of long SPT trajectories (Saxton and Jacobson, 1997). vbSPT (a hidden Markov model based method) has been developed to infer molecular diffusion states from short tracks generated by techniques such as sptPALM (Persson et al., 2013). A mathematic method that serves the basis for characterizing structural organizations is the introduction of pair auto or cross correlation functions to quantify molecular unevenness and spatial colocalization (Sengupta et al., 2011). Future Directions and Challenges: Faster, Deeper, and More Colorful Direct observation of molecular processes at single-cell, singlemolecule levels overcomes the loss of information due to population averaging and allows us to access extensive dynamic and structural information about sub-populations that can provide new insights into how spatiotemporal regulation of these processes emerges from largely stochastic molecular events. In the future, we envision an integrated and multifaceted approach to probe the control mechanisms and logic associated with key biological systems (Figure 6). Using eukaryotic gene regulation as an example, several SPT studies have reported the detection of transcription factor-DNA interaction kinetics in live cells (Gebhardt et al., 2013; Izeddin et al., 2014; Morisaki et al., 2014). In addition, a single-cell, single-molecule imaging method has been developed to systematically characterize the target search dynamics of the embryonic stem cell-specific transcription factors Sox2/Oct4 in live cells (Chen et al., 2014b). Finally, kinetic information has been extracted from structural data using time-counting PALM (tcPALM): analyzing the temporal bursts of localization counts within specific regions of the nucleus revealed highly dynamic sites associated with Pol II clusters (Cisse et al., 2013). Single-molecule FRET experiments are also poised to make greater contributions due to the development of the new imaging and labeling technologies described above. FRET-based singlemolecule biosensors (Miyawaki, 2011) might be used with greater sensitivity and generality, and single-molecule FRET measurements of the conformation, folding and activation of individual proteins might be studied in living cells (Murakoshi et al., 2004; Sakon and Weninger, 2010) less invasively and for longer durations, even in fluorescently dense organelles such as the Golgi apparatus and the rough endoplasmic reticulum. One of the most exciting possibilities, however, is for accurate counting of single molecules in assemblies. In the past, incomplete labeling, misfolding of FPs, or molecular blinking have made it difficult to access the exact stoichiometry of nanoscale structures. However, recent advances in statistical algorithms and calibrating control experiments have met with some successes (Durisic et al., 2014; Rollins et al., 2014). With continued refinement, the ability to directly image and count the exact number of molecules of a desired type in a nanoscale structure would represent a major advantage of localization microscopy over other super-resolution techniques. Another need apparent from recent single-molecule experiments is the ability to obtain 5D information: 3D localization over time, of multiple moieties in different colors, in order

Molecular Cell

Review

Figure 6. Workflow and Applications Shown is a unified and multifaceted imaging framework to study spatiotemporal controls and molecular mechanisms of key biological systems in live cells at the single-molecule level.

to study the spatiotemporal kinetics of functionally linked events in the same live cell. For example, it is highly desirable to study TF dynamics, 3D enhancer organization, and gene activities at the same time. Developing microscopes and labeling techniques that are compatible with fast, noninvasive, multicolor 2D or 3D live-cell imaging remains a key challenge (Grimm et al., 2015). Finally, instead of imaging cultured cells on a coverslip, it will become increasingly important to directly access molecular dynamic and structural information in tissue or in vivo in whole

organisms. This is a key step toward understanding the links between the dynamics of single molecules and the specification of cell fate and behavior during development. However, these challenging samples exhibit substantial scattering and aberrations that rapidly degrade the ability to precisely localize or even detect single molecules. Thus, adaptive optics to correct for these aberrations (Ji et al., 2012; Wang et al., 2014a, 2014b) and possibly brighter genetically encoded labels (Bothma et al., 2014; Hocine et al., 2013) will be needed to obtain a more comprehensive and quantitative understanding of the Molecular Cell 58, May 21, 2015 ª2015 Elsevier Inc. 655

Molecular Cell

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