Toward an Axial Nanoscale Ruler for Fluorescence Microscopy Sabrina Simoncelli,‡ Maria Makarova,† William Wardley,§ and Dylan M. Owen*,∥ ‡
Blackett Laboratory, Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom Francis Crick Institute and Randall Division of Cell and Molecular Biophysics, King’s College London, London NW1 1AT, United Kingdom § Department of Physics, King’s College London, London WC2R 2LS, United Kingdom ∥ Department of Physics and Randall Division of Cell and Molecular Biophysics, King’s College London, London SE1 1UL, United Kingdom †
ABSTRACT: In the discussion of resolution in optical microscopy, axial precision has often come second to its lateral counterpart. However, biological systems make no special arrangements for our preferred direction of imaging. The ability to measure axial distances, that is, the heights of fluorophores relative to a plane of reference, is thus of paramount importance and has been the subject of several recent advances. A novel method is to modify the fluorescence emission based on the height of the individual fluorophore, such that its z-position is encoded somehow in the detected signal. One such approach is metal-enhanced energy transfer, recently extended to multicolor distance measurements and applied to study the topography of the nuclear membrane. Here, the fluorescence lifetime is shortened due to the proximity of the fluorophores to a thin metallic surface. Fluorescence lifetime imaging can therefore be used as an axial ruler with nanometer precision.
I
n this issue of ACS Nano, Chizhik et al. make a compelling case for studying the nanoscale topography and architecture of the nuclear membrane.1,2 The nuclear envelope serves as a protective case for the genome and provides a versatile communication interface between the cytosol and the nuclear interior. As a part of the endoplasmic reticulum, the nuclear envelope consists of two membrane sheets: the outer nuclear membrane, which is continuous with the endoplasmic reticulum, and the inner nuclear membrane, which merges with the outer membrane at specific sites. At these locales, the two membranes fuse to form a pore containing a large, multiprotein assembly, the nuclear pore complex. Nuclear pore complexes function as selective gates for nuclear-cytoplasmic transport and consist of a family of proteins called nuclearporins. Not only is the nuclear envelope continuous with the endoplasmic reticulum, it also connects with the cell cytoskeleton through linker of the nucleoskeleton and cytoskeleton (LINC) complexes. These LINC complexes sense various mechanical stimuli and enable the transmission of mechanical force from the extracellular matrix inward to the nucleus. It has been suggested that the nucleus not only passively binds to the cytoskeleton but also serves as a center that actively senses mechanical challenges and dynamically responds to them.2 In this issue of ACS Nano, Chizhik et al. make a compelling case for studying the nanoscale topography and architecture of the nuclear membrane. © 2017 American Chemical Society
In this issue of ACS Nano, Chizhik et al. make a compelling case for studying the nanoscale topography and architecture of the nuclear membrane. The protein repertoires of the outer and inner nuclear membranes are distinct such that the outer membrane resembles the endoplasmic reticulum and the inner nuclear membrane forms a unique platform that facilitates the interaction with the nuclear lamina, a dense meshwork of intermediate filaments on the nuclei internal surface, analogous to the cortical actin meshwork at the plasma membrane. This coupling between the inner nuclear membrane and the nuclear lamina in turn supports its physical barrier function and the mechanical coupling of the nuclear envelope with the genetic information itself in the form of heterochromatin. Dynamic rearrangements of the nuclear envelope occur during various processes such as stress response and mechanical deformation, remodelling during mitosis, and cellular differentiation.3 Nuclear envelope architecture responds to various force loads that the cell can experience. For example, it has been shown that upon force load some nuclear envelope components Published: November 21, 2017 11762
DOI: 10.1021/acsnano.7b07133 ACS Nano 2017, 11, 11762−11767
Perspective
www.acsnano.org
ACS Nano
Perspective
of new adhesion sites, which subsequently migrate in retrograde fashion, from the cell’s frame of reference.12 Similar membrane undulations and ruffles have also been observed in the spreading of immune cells over their target cells. For example, one of the most widely accepted mechanisms for the regulation of T-cell activation is known as the kinetic segregation model (Figure 1b).13 T cells survey antigenpresenting cells (APCs) for signs of pathogenic infection by forming a tight cell−cell junction known as an immunological synapse.14 Here, complex and highly regulated signaling pathways determine whether the T cell should activate or not. The model holds that the intramembrane spacing between the cells is variable, being regulated by the various adhesion molecules on the surfaces of the two cell types. Negative regulators of cell signaling, such as the phosphatase CD45, have large extracellular domains and are excluded from the synaptic interface due to their size. In effect, negative regulators are spatially segregated away from the active signaling zone by careful control of the cell−cell intramembrane space. This segregation has important consequences. For example, many studies generate artificial T-cell synapses against activating, antibody-coated glass coverslips or planar-supported lipid bilayers, both for convenience and to enable the use of total internal reflection fluorescence (TIRF) microscopy. However, the kinetic segregation model shows that the hard, rigid coverslip surface might induce at least partial activation of the T cells in the absence of the activating signal via the exclusion of CD45. To test the model, researchers have turned to numerous approaches. One approach involves generating inert polymers of dextran of well-defined size, each fluorescently labeled. By observing which lengths of polymer are able to diffuse into the intermembrane space, the gap between the membranes can be inferred.15 Interference reflection microscopy (IRM) is frequently used in the study of immune cell synapses, and fluorescence anisotropy has been applied to the study of membrane curvature and ruffling in other immune cell synapses, such as those of natural killer cells.16
can undergo post-translational modifications to alter nuclear stiffness.4 Dramatic morphological and topographical deformation of the nuclear envelope accompanies mitotic processes and chromosome segregation. In higher eukaryotes, for example, the nuclear envelope completely disassembles at the onset of mitosis and reassembles around the daughter nuclei, with multiple factors driving deformation and fusion events.5 We now know that chromosomes are arranged nonrandomly in the nucleus and their interactions with specific landmarks on the nuclear envelope contribute to transcriptional activation or repression. During cellular differentiation, for example, gene expression is activated by the movement of silenced loci from the nuclear periphery to a more internal site where they are expressed.6 In some cases, transcription factors and their binding sites are located on the nuclear pore complex, regulating gene expression.7 Therefore, a narrative emerges of a link between cellular mechanosensing, force transmission to the nuclear lamina, and nuclear envelope deformation, and, ultimately, regulated gene expression. Related to this, numerous links have been identified between nuclear envelope components, envelope remodelling defects, and human diseases. Muscular dystrophies, for example, are associated with mutations in lamina components, laminopathies.8 In another example, neutrophils of the immune system possess a nuclear morphological hallmark, multilobed nuclei, which are a result of a specific expression pattern of nuclear envelope components. Deregulation of this pattern results in an anomaly that perturbs neutrophil migration and, therefore, a functional immune response.9 In addition to the nuclear membrane, there are a host of biological phenomena in which nanoscale membrane topography is thought to play a central role.10 One such example is the migration of cells, which are driven by a combination of adhesion complexes attached to the substrate, actin retrograde flow, and a complex molecular clutch (Figure 1a). The threedimensional (3D) nature of focal adhesions has recently been elucidated by single-molecule microscopy, indicating a layered structure of adhesion molecules, adhesion regulators, actin linkers, and actin regulators.11 As actin polymerization drives the plasma membrane forward, the roles of membrane and cortical actin topography become important for the generation
CURRENT METHODS Probably the most common tool employed to study membrane topography is IRM. Using polarized illumination, the method interferes reflected light from the structure of interest (e.g., the plasma membrane) and from the coverslip−water interface. Depending on the height of the membrane above the coverslip, constructive or destructive interference can occur. However, because the refractive indices of the sample may not be known and the absolute light intensities are difficult to calibrate, IRM is usually only used as a qualitative, rather than quantitative, measure of membrane topography. Total internal reflection fluorescence microscopy is the go-to method for imaging studies of cell membranes.17 By illuminating with collimated laser light above the critical angle, total internal reflection is achieved from the coverslip−water interface, and the sample is therefore only illuminated by the exponentially decaying evanescent field, which typically has a characteristic penetration depth of around 100 nm. Although the exact penetration depth can be quite well calibrated, using the intensity of the detected fluorescence as a quantitative measure of height within the evanescent field is difficult to achieve because the sample intensity is not usually known. However, TIRF microscopy can be used to give nanoscale axial precision by the sequential imaging and photobleaching of the sample by evanescent waves of different penetration depths,
Figure 1. Importance of membrane topography and intermembrane spacing. (a) Cell migration via a combination of retrograde actin flow, focal adhesions, and a three-dimensional, nanoscale molecular clutch. (b) The kinetic segregation model of T-cell activation excluding the negative regulator, CD45, from the close central cell−cell contact zone. 11763
DOI: 10.1021/acsnano.7b07133 ACS Nano 2017, 11, 11762−11767
ACS Nano
Perspective
Figure 2. Metal-induced fluorescence lifetime changes. (a) The interaction of a fluorophore with a metal surface results in a shortening of the molecule’s fluorescence lifetime. (b, c) Calculated lifetime-distance dependence calibration curves for (b) different fluorophores supported on glass cover slides coated with a 10 nm-thick layer of gold or for (c) mCherry placed in the vicinity of different types (aluminum, platinum, gold) and thickness (10 or 20 nm) of metal surfaces.
of the PSFs can cause them to overlap, making fitting more difficult. Both these methods deliver axial resolution in the 50−100 nm range together with lateral localization precisions of 10−30 nm. Other systems, such as dual objective PALM/ STORM28 and interference-based techniques29 can achieve isotropic resolution, at the cost of significant experimental complexity. Being single-molecule methods based on stochastic molecular localization, all of these methods are typically slow and therefore are mostly applied to fixed samples.
which are achieved by varying the laser illumination angle.18 An axial resolution of up to 20 nm is possible; however, the requirement for serial photobleaching can make this approach time-consuming. A related method is to image supercritical angle fluorescence, which exploits the nonisotropic direction of fluorescence emission as the fluorophores approach a material of different refractive index. Collection of fluorescence from these specific directions preferentially images fluorophores close to the interface (analogous to TIRF, which preferentially excited fluorophores close to the interface).19 Using an appropriate arrangement for collection, both the supercritical fluorescence (SAF) and conventional under-critical (UAF) signal from higher fluorophores can be collected simultaneously, enabling a ratiometric approach and the construction of an axial ruler.20 Single-molecule imaging based on photoactivated localization microscopy (PALM)21 or stochastic optical reconstruction microscopy (STORM)22 are frequently used as rulers to measure molecular separation in the lateral direction. In fact, the nuclear pore complex is a frequent calibration and demonstration system for such types of microscopy because of its welldefined eight-fold symmetry. DNA origami nanostructures have been used for the same reason.23 Although the great majority of PALM and STORM studies are implemented using a TIRFbased illumination system (to maximize the signal-to-noise ratio and, hence, the localization precision), 3D PALM and STORM are also possible. Three-dimensional PALM/STORM typically utilizes either wide-field or epi illumination but has also been demonstrated using highly inclined and laminated optical sheets (HiLO) and light-sheet-based illumination.24,25 These arrangements typically represent a compromise between illumination volume (axial extent of the imaged volume) and signal-to-noise ratio. The key to 3D single-molecule localization microscopy typically lies in the detection and, specifically, depends on how the z-position is calculated. One of the most intuitive methods is to image two different focal planes at the same time, biplane imaging, either using an image-splitter or two cameras.26 By observing the same point spread function (PSF) at two different focal planes, an analysis of how out of focus the PSF is in each can enable a calculation of the z-position. This method is relatively simple to implement; however, the axial localization precision is not uniform over the imaged volume and can, therefore, give non-uniform z resolution. Another implementation is astigmatism in which a cylindrical lens is inserted before the camera.27 This method generates asymmetrical PSFs in which the z-position is encoded in the aspect ratio of the now elliptical PSF. The system is also simple to implement, but the elongation
METAL-INDUCED ENERGY TRANSFER AND FLUORESCENCE LIFETIME IMAGING In this issue of ACS Nano, Chizhik et al. expand the membrane topographic reconstruction toolkit into an exacting direction: 3D metal-induced energy transfer (MIET) imaging.1 Metalinduced energy transfer relies on measuring the fluorescence lifetime of fluorophores, which changes as those fluorophores approach a thin metal surface. The fluorescence lifetime is a measure of how long the electron stays in the excited state after photon absorption. This length of time depends on the numerous different decay routes by which the fluorophore can lose excited-state energy; the fluorescent lifetime is simply one over the total (radiative and nonradiative) decay rates. The presence of a metal surface in the vicinity of the excited fluorophore changes this excited-state lifetime.30,31 As the distance between the fluorophore and the metal decreases, the fluorophore’s energy couples to surface plasmons in the metal and thus shortening the fluorescence lifetime (Figure 2a). In this sense, it is similar in its observed effect to the shortening of the fluorescence lifetime detected during Förster resonance energy transfer (FRET) when two fluorophores are brought into close proximity.32Chizhik et al. expanded the membrane topographic reconstruction toolkit into an exacting novel direction: threedimensional metal-induced energy transfer imaging.
Chizhik et al. expanded the membrane topographic reconstruction toolkit into an exacting novel direction: threedimensional metal-induced energy transfer imaging. The main difference between MIET and FRET is the spatial extent over which these two energy-transfer mechanisms operate. Whereas in FRET, the efficiency of the energy transfer depends on the sixth power of the distance between donor and acceptor 11764
DOI: 10.1021/acsnano.7b07133 ACS Nano 2017, 11, 11762−11767
ACS Nano
Perspective
medium. Therefore, another challenge of this technique is related to the susceptibility of the fluorescence lifetime of a fluorophore inside a living cell due to changes in the pH, redox state, and Ca2+ influx while imaging. As such, it might limit the extent of applicability of the technique for live-cell imaging, at least without careful experimental design. Finally, it is important to note that lateral resolution in MIET is limited to FLIM capabilities, which are often diffraction limited. This limitation is now being addressed.37
molecules, limiting its applications for distances greater than ∼10 nm, in MIET, the planar geometry of the metal film provides a more gradual lifetime-distance dependency. Accordingly, MIET can work over a range of distances from zero up to 100−200 nm above a coated surface, a similar range to that accessible by TIRF and supercritical angle imaging. The well-understood physical process of how the proximity of a metal planar surface decreases the fluorescence lifetime of a fluorophore makes MIET a simple yet powerful tool. Nonradiative energy transfer from an excited molecule to a metal surface was first pointed out by Purcell in 1946.33 Since then, the interaction of fluorophores with metal surfaces has been extensively studied not only for fundamental understanding but also for its practical implications. Some examples of the synergy between nanoscopy and near-field plasmonics include the use of plasmon-interference patterns in order to improve structured illumination microscopy (SIM)34 and the use of plasmonic nanoparticles to enhance the resolution in stimulated emission depletion (STED) nanoscopy.35 Whereas these aforementioned approaches are based on improving lateral resolution, MIET came to fill a gap in plasmon-enhanced super-resolution fluorescence imaging techniques, proving seminal advancements in the axial counterpart, that is, up to ∼3 nm axial resolution.36 Metal-induced energy transfer for live cell nanoscopy is particularly interesting because the resolution limit can be pushed by selectively engineering the interplay between the fluorophore and the metal surface. The amplitude and modulation of the fluorescence lifetime signal are not only dependent on the chromophore−surface distance but also on the molecular fluorescence emission quantum yield, the material and thickness of the metal layer, and the overlap between the plasmon and the molecular transition bands (Figure 2b, c). By quantitatively analyzing the predictable lifetime-distance dependence, MIET provides an extremely versatile and straightforward tool to image topography in cells and to determine axial distances between proteins when used in its multicolor variant, as demonstrated in this issue of ACS Nano.1 Contrary to other axial super-resolution imaging techniques, MIET does not require specialized equipment or particular mounting mediums for the probes. Therefore, this technique can easily be implemented in any conventional fluorescence-lifetime imaging microscope (FLIM). By either exploiting the features of the fluorophores (intrinsic fluorescence lifetime and quantum yield, emission spectra) or by tailoring the parameters of the coated substrate (number of layers, materials, thickness), it is possible to adapt the capabilities of any FLIM setup (temporal accuracy and resolution, laser wavelength, etc.) to address the specific axial distance range and sensitivity required for the biological problem under investigation. Furthermore, the possibility of placing intermediate layers between the sample and the metal surface makes this technique compatible with standard immunofluorescence staining procedures. In addition to the various advantages of this technique, MIET should address several challenges in order to compete with the current advances in 3D super-resolution imaging. Metal-induced energy transfer is limited to axial distances of up to ∼100−200 nm above the sample surface. This axial range, though of interest for addressing biological process such as cell migration, cell differentiation, and cellular adhesion, might not be suitable to measure processes such as cell migration in 3D microenvironments or cell−cell interactions. The axial nanometer accuracy attained with MIET is extremely sensitive to the intrinsic fluorescence lifetime of the fluorophore in the sample’s
FUTURE DEVELOPMENTS State-of-the-art wide-field fluorescence lifetime imaging techniques can collect a large-area lifetime image in a fraction of a second with picosecond accuracy.38 Currently, there are two different acquisition schemes for wide-field FLIM: the frequency and the time domain. In the frequency domain, the fluorescence emission is analyzed by determining the phase and modulation of the emission with respect to the sinusoidally modulated excitation light. In the time domain, the sample is excited with ultrafast laser pulses, and the fluorescence decay is determined by recording the fluorescence intensity distribution at various delays after the excitation. Time-domain methods can usually measure shorter lifetimes with higher accuracy than can frequencydomain methods.39 Most modern implementations of wide-field FLIM employ a microchannel plate as single-photon-counting technology. However, single-photon avalanche diode arrays and superconducting detectors are also rising as promising new technologies in the field due to their increased photon count rate and infrared photon sensitivity, respectively.38 Wide-field FLIM has two main advantages with respect to the conventional laser scanning FLIM methodologies: (i) faster fluorescence imaging speed and (ii) low excitation power. The combination of these two advantages makes wide-field FLIM an ideal approach to study dynamics in live cells and to track individual molecules or particle trajectories. By linking the fast acquisition speeds of wide-field FLIM and the new ideas of super-resolution imaging with the concepts of metal-induced energy transfer, we envisage that 3D MIET will emerge as an exciting new contender in the choices for 3D super-resolution microscopy.We envisage that three-dimensional (3D) metalinduced energy transfer will emerge as an exciting new contender in the choices for 3D super-resolution microscopy.
We envisage that three-dimensional (3D) metal-induced energy transfer will emerge as an exciting new contender in the choices for 3D super-resolution microscopy. Of particular interest for MIET imaging are the recent advancements in the analysis of fluorescence lifetime imaging data for accurate conversion of axial distances. In time-domain FLIM, fluorescence lifetimes (and their contributions) are usually modeled and calculated using multiexponential decay fittings. A limitation of this approach is that it requires assumptions of the components contributing to the fluorescence decay profiles and many fluorescent proteins display complex decay behaviors. To tackle these complications, Gratton et al. presented an alternative fit-free phasor technique based on Fourier transform to calculate fluorescence lifetimes.40 The power of phasor analysis has been proven useful for studying a wide 11765
DOI: 10.1021/acsnano.7b07133 ACS Nano 2017, 11, 11762−11767
ACS Nano
Perspective
(4) Guilluy, C.; Osborne, L. D.; Van Landeghem, L.; Sharek, L.; Superfine, R.; Garcia-Mata, R.; Burridge, K. Isolated Nuclei Adapt to Force and Reveal a Mechanotransduction Pathway in the Nucleus. Nat. Cell Biol. 2014, 16, 376−381. (5) Makarova, M.; Oliferenko, S. Mixing and Matching Nuclear Envelope Remodeling and Spindle Assembly Strategies in the Evolution of Mitosis. Curr. Opin. Cell Biol. 2016, 41, 43−50. (6) Peric-Hupkes, D.; Meuleman, W.; Pagie, L.; Bruggeman, S. W. M.; Solovei, I.; Brugman, W.; Gräf, S.; Flicek, P.; Kerkhoven, R. M.; van Lohuizen, M.; Reinders, M.; Wessels, L.; van Steensel, B. Molecular Maps of the Reorganization of Genome-Nuclear Lamina Interactions during Differentiation. Mol. Cell 2010, 38, 603−613. (7) Pascual-Garcia, P.; Capelson, M. Nuclear Pores as Versatile Platforms for Gene Regulation. Curr. Opin. Genet. Dev. 2014, 25, 110− 117. (8) Roux, K. J.; Burke, B. Nuclear Envelope Defects in Muscular Dystrophy. Biochim. Biophys. Acta, Mol. Basis Dis. 2007, 1772, 118− 127. (9) Rowat, A. C.; Jaalouk, D. E.; Zwerger, M.; Ung, W. L.; Eydelnant, I. A.; Olins, D. E.; Olins, A. L.; Herrmann, H.; Weitz, D. A.; Lammerding, J. Nuclear Envelope Composition Determines the Ability of Neutrophil-Type Cells To Passage through Micron-Scale Constrictions. J. Biol. Chem. 2013, 288, 8610−8618. (10) Parmryd, I.; Onfelt, B. Consequences of Membrane Topography. FEBS J. 2013, 280, 2775−2784. (11) Kanchanawong, P.; Shtengel, G.; Pasapera, A. M.; Ramko, E. B.; Davidson, M. W.; Hess, H. F.; Waterman, C. M. Nanoscale Architecture of Integrin-Based Cell Adhesions. Nature 2010, 468, 580−584. (12) Borm, B.; Requardt, R. P.; Herzog, V.; Kirfel, G. Membrane Ruffles in Cell Migration: Indicators of Inefficient Lamellipodia Adhesion and Compartments of Actin Filament Reorganization. Exp. Cell Res. 2005, 302, 83−95. (13) Choudhuri, K.; Kearney, A.; Bakker, T. R.; van der Merwe, P. A. Immunology: How Do T Cells Recognize Antigen? Curr. Biol. 2005, 15, R382−R385. (14) Fooksman, D. R.; Vardhana, S.; Vasiliver-Shamis, G.; Liese, J.; Blair, D. A.; Waite, J.; Sacristán, C.; Victora, G. D.; Zanin-Zhorov, A.; Dustin, M. L. Functional Anatomy of T Cell Activation and Synapse Formation. Annu. Rev. Immunol. 2010, 28, 79−105. (15) Cartwright, A. N. R.; Griggs, J.; Davis, D. M. The Immune Synapse Clears and Excludes Molecules Above a Size Threshold. Nat. Commun. 2014, 5, 5479. (16) Benninger, R. K. P.; Vanherberghen, B.; Young, S.; Taner, S. B.; Culley, F. J.; Schnyder, T.; Neil, M. A. A.; Wüstner, D.; French, P. M. W.; Davis, D. M.; Ö nfelt, B. Live Cell Linear Dichroism Imaging Reveals Extensive Membrane Ruffling within the Docking Structure of Natural Killer Cell Immune Synapses. Biophys. J. 2009, 96, L13−L15. (17) Axelrod, D. Evanescent Excitation and Emission in Fluorescence Microscopy. Biophys. J. 2013, 104, 1401−1409. (18) Fu, Y.; Winter, P. W.; Rojas, R.; Wang, V.; McAuliffe, M.; Patterson, G. H. Axial Superresolution Via Multiangle TIRF Microscopy with Sequential Imaging and Photobleaching. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 4368−4373. (19) Ruckstuhl, T.; Verdes, D. Supercritical Angle Fluorescence (SAF) Microscopy. Opt. Express 2004, 12, 4246−4254. (20) Bourg, N.; Mayet, C.; Dupuis, G.; Barroca, T.; Bon, P.; Lécart, S.; Fort, E. Lévêque Fort, S. Direct Optical Nanoscopy with Axially Localized Detection. Nat. Photonics 2015, 9, 587−593. (21) Betzig, E.; Patterson, G. H.; Sougrat, R.; Lindwasser, O. W.; Olenych, S.; Bonifacino, J. S.; Davidson, M. W.; Lippincott-Schwartz, J.; Hess, H. F. Imaging Intracellular Fluorescent Proteins at Nanometer Resolution. Science 2006, 313, 1642−1645. (22) Rust, M. J.; Bates, M.; Zhuang, X. Sub-Diffraction-Limit Imaging by Stochastic Optical Reconstruction Microscopy (STORM). Nat. Methods 2006, 3, 793−796. (23) Schmied, J. J.; Gietl, A.; Holzmeister, P.; Forthmann, C.; Steinhauer, C.; Dammeyer, T.; Tinnefeld, P. Fluorescence and Super-
range of biophysical topics, such as stem cell differentiation, oxidative stress in tumors, membrane domains, cardiomyocytes, and metabolic states in bacteria among others.41−44 In the future, it is clear that the easy-to-implement MIET imaging technique will combine with phasor analysis to monitor axial topography in cells quickly, providing even higher axial precision. Another possible avenue for development of the MIET technology is to use nanostructured surfaces to decrease the fluorescence lifetime of the excited states further. Metallic nanostructures, both two-dimensional surfaces and metasurfaces and 3D nanostructures and metamaterials, rely on plasmonic effects to confine and to enhance the electric (or magnetic) field component of light, enabling it to be controlled and directed on much smaller scales than conventional dielectric-based microscopy.45 In addition, nanostructuring of the environment can lead to even greater reduction of excited lifetimes due to the increase in the local density of states.46 The use of a large-area self-assembled nanorod metamaterial has recently demonstrated a 30-fold reduction of the spontaneous emission lifetime of emitters located in their vicinity due to the presence of unique electromagnetic states propagating within the metamaterial.47 Similar effects have also been demonstrated in surface-enhanced Raman spectroscopy (SERS), particularly in the case of resonant SERS, or SERRS,48 and combinatorial techniques could easily lead to significant enhancements for both imaging and detection. Additional benefits to these approaches can be found by exploiting the optical properties of the biological material itself, particularly the ultraviolet fluorescence behavior of some biomolecules by enhancing autofluorescence through the choice of metal for the nanostructured substrate. Traditionally, plasmonics has been focused on the use of the coinage metals (silver, gold, copper, etc.), but these are not suitable for use in the ultraviolet region where many autofluorescent species excite due to inter- and intraband transitions. The prime candidate for this role, due to both its optical and physical properties, is aluminum.49 The combination of ultraviolet optics with nanostructuring or metamaterial techniques applied to aluminum could potentially lead to single-molecule detection or imaging in unstained biological samples.
AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS The authors gratefully acknowledge support from the European Research Council, grant 337187. REFERENCES (1) Chizhik, A.; Ruhlandt, D.; Pfaff, J.; Karedla, N.; Chizhik, A.; Gregor, I.; Kehlenbach, R.; Enderlein, J. Three Dimensional Reconstruction of Nuclear Envelope Architecture Using Dual-Color Metal-Induced Energy Transfer Imaging. ACS Nano 2017, DOI: 10.1021/acsnano.7b04671. (2) Alam, S.; Lovett, D. B.; Dickinson, R. B.; Roux, K. J.; Lele, T. P. Chapter Eight: Nuclear Forces and Cell Mechanosensing. In Progress in Molecular Biology and Translational Science; Engler, A. J., Kumar, S., Eds.; Academic Press: Waltham, MA, 2014; Vol. 126, pp 205−215. (3) Ungricht, R.; Kutay, U. Mechanisms and Functions of Nuclear Envelope Remodelling. Nat. Rev. Mol. Cell Biol. 2017, 18, 229−245. 11766
DOI: 10.1021/acsnano.7b07133 ACS Nano 2017, 11, 11762−11767
ACS Nano
Perspective
Resolution Standards Based on DNA Origami. Nat. Methods 2012, 9, 1133−1134. (24) Tokunaga, M.; Imamoto, N.; Sakata-Sogawa, K. Highly Inclined Thin Illumination Enables Clear Single-Molecule Imaging in Cells. Nat. Methods 2008, 5, 159−161. (25) Legant, W. R.; Shao, L.; Grimm, J. B.; Brown, T. A.; Milkie, D. E.; Avants, B. B.; Lavis, L. D.; Betzig, E. High-Density ThreeDimensional Localization Microscopy Across Large Volumes. Nat. Methods 2016, 13, 359. (26) Juette, M. F.; Gould, T. J.; Lessard, M. D.; Mlodzianoski, M. J.; Nagpure, B. S.; Bennett, B. T.; Hess, S. T.; Bewersdorf, J. ThreeDimensional Sub-100 nm Resolution Fluorescence Microscopy of Thick Samples. Nat. Methods 2008, 5, 527−529. (27) Huang, B.; Wang, W.; Bates, M.; Zhuang, X. Three-Dimensional Super-Resolution Imaging by Stochastic Optical Reconstruction Microscopy. Science 2008, 319, 810−813. (28) Xu, K.; Babcock, H. P.; Zhuang, X. Dual-Objective STORM Reveals Three-Dimensional Filament Organization in the Actin Cytoskeleton. Nat. Methods 2012, 9, 185−188. (29) Shtengel, G.; Galbraith, J. A.; Galbraith, C. G.; LippincottSchwartz, J.; Gillette, J. M.; Manley, S.; Sougrat, R.; Waterman, C. M.; Kanchanawong, P.; Davidson, M. W.; Fetter, R. D.; Hess, H. F. Interferometric Fluorescent Super-Resolution Microscopy Resolves 3D Cellular Ultrastructure. Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 3125−3130. (30) Chance, R. R.; Prock, A.; Silbey, R. Molecular Fluorescence and Energy Transfer Near Interfaces. In Advances in Chemical Physics; John Wiley & Sons, Inc.: Hoboken, NJ, 2007; pp 1−65. (31) Ford, G. W.; Weber, W. H. Electromagnetic Interactions of Molecules with Metal Surfaces. Phys. Rep. 1984, 113, 195−287. (32) Jares-Erijman, E. A.; Jovin, T. M. FRET Imaging. Nat. Biotechnol. 2003, 21, 1387−1395. (33) Purcell, E. M. Spontaneous Emission Probabliities at Radio Frquencies. Phys. Rev. 1946, 69, 681. (34) Wei, F.; Liu, Z. Plasmonic Structured Illumination Microscopy. Nano Lett. 2010, 10, 2531−2536. (35) Cortés, E.; Huidobro, P. A.; Sinclair, H. G.; Guldbrand, S.; Peveler, W. J.; Davies, T.; Parrinello, S.; Görlitz, F.; Dunsby, C.; Neil, M. A. A.; Sivan, Y.; Parkin, I. P.; French, P. M. W.; Maier, S. A. Plasmonic Nanoprobes for Stimulated Emission Depletion Nanoscopy. ACS Nano 2016, 10, 10454−10461. (36) Chizhik, A. I.; Rother, J.; Gregor, I.; Janshoff, A.; Enderlein, J. Metal-Induced Energy Transfer for Live Cell Nanoscopy. Nat. Photonics 2014, 8, 124−127. (37) Auksorius, E.; Boruah, B. R.; Dunsby, C.; Lanigan, P. M. P.; Kennedy, G.; Neil, M. A. A.; French, P. M. W. Stimulated Emission Depletion Microscopy with a Supercontinuum Source and Fluorescence Lifetime Imaging. Opt. Lett. 2008, 33, 113−115. (38) Hirvonen, L. M.; Suhling, K. Wide-Field TCSPC: Methods and Applications. Meas. Sci. Technol. 2017, 28, 012003. (39) Collier, B. B.; McShane, M. J. Dynamic Windowing Algorithm for the Fast and Accurate Determination of Luminescence Lifetimes. Anal. Chem. 2012, 84, 4725−4731. (40) Digman, M. A.; Caiolfa, V. R.; Zamai, M.; Gratton, E. The Phasor Approach to Fluorescence Lifetime Imaging Analysis. Biophys. J. 2008, 94, L14−16. (41) Stringari, C.; Cinquin, A.; Cinquin, O.; Digman, M. A.; Donovan, P. J.; Gratton, E. Phasor Approach to Fluorescence Lifetime Microscopy Distinguishes Different Metabolic States of Germ Cells in a Live Tissue. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 13582−13587. (42) Owen, D. M.; Williamson, D. J.; Magenau, A.; Gaus, K. SubResolution Lipid Domains Exist in the Plasma Membrane and Regulate Protein Diffusion and Distribution. Nat. Commun. 2012, 3, 1256. (43) Bhattacharjee, A.; Datta, R.; Gratton, E.; Hochbaum, A. I. Metabolic Fingerprinting of Bacteria by Fluorescence Lifetime Imaging Microscopy. Sci. Rep. 2017, 7, 3743. (44) Datta, R.; Heylman, C.; George, S. C.; Gratton, E. Label-Free Imaging of Metabolism and Oxidative Stress in Human Induced
Pluripotent Stem Cell-Derived Cardiomyocytes. Biomed. Opt. Express 2016, 7, 1690−1701. (45) Schuller, J. A.; Barnard, E. S.; Cai, W.; Jun, Y. C.; White, J. S.; Brongersma, M. L. Plasmonics for Extreme Light Concentration and Manipulation. Nat. Mater. 2010, 9, 193−204. (46) Jacob, Z.; Smolyaninov, I. I.; Narimanov, E. E. Broadband Purcell effect: Radiative Decay Engineering with Metamaterials. Appl. Phys. Lett. 2012, 100, 181105. (47) Ginzburg, P.; Roth, D. J.; Nasir, M. E.; Segovia, P.; Krasavin, A. V.; Levitt, J.; Hirvonen, L. M.; Wells, B.; Suhling, K.; Richards, D.; Podolskiy, V. A.; Zayats, A. V. Spontaneous Emission in Non-Local Materials. Light: Sci. Appl. 2016, 6, e16273. (48) McNay, G.; Eustace, D.; Smith, W. E.; Faulds, K.; Graham, D. Surface-Enhanced Raman Scattering (SERS) and Surface-Enhanced Resonance Raman Scattering (SERRS): A Review of Applications. Appl. Spectrosc. 2011, 65, 825−837. (49) Gérard, D.; Gray, S. K. Aluminium Plasmonics. J. Phys. D: Appl. Phys. 2015, 48, 184001.
11767
DOI: 10.1021/acsnano.7b07133 ACS Nano 2017, 11, 11762−11767
