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Posts Tagged ‘electron microscopy’


Visualizing metal-impregnated neurons with spectral confocal microscopy

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Novel Imaging Captures Beauty of Metal-Labeled Neurons in 3D

These are silver-impregnated dendrites from an insect motor neuron, captured through spectral confocal microscopy. (Credit: Grant M. Barthel, Karen A. Mesce, Karen J. Thompson)

Researchers have discovered a dazzling new method of visualizing neurons that promises to benefit neuroscientists and cell biologists alike: by using spectral confocal microscopy to image tissues impregnated with silver or gold.

Rather than relying on the amount of light reflecting off metal particles, this novel process, to be presented in the journal eLife, involves delivering light energy to silver or gold nanoparticles deposited on neurons and imaging the higher energy levels resulting from their vibrations, known as surface plasmons.

This technique is particularly effective as the light emitted from metal particles is resistant to fading, meaning that decades-old tissue samples achieved through other processes, such as the Golgi stain method from the late 1880s, can be imaged repeatedly.

The new process was achieved by using spectral detection on a Laser Scanning Confocal Microscope (LSCM), first made available in the late 1980s and, until now, used most extensively for fluorescent imaging.

Paired with such methods, silver- and gold-based cell labeling is poised to unlock new information in a myriad of archived specimens. Furthermore, silver-impregnated preparations should retain their high image quality for a century or more, allowing for archivability that could aid in clinical research and disease-related diagnostic techniques for cancer and neurological disorders.

“For the purposes of medical diagnostics, older and newer specimens could be compared with the knowledge that signal intensity would remain fairly uniform regardless of sample age or repeated light exposure,” says contributing author Karen Mesce from the University of Minnesota.

“With the prediction that superior resolution microscopic techniques will continue to evolve, older archived samples could be reimagined with newer technologies and with the confidence that the signal in question was preserved. The progression or stability of a cancer or other disease could therefore be charted with accuracy over long periods of time.”

To appreciate the enhanced image quality produced by the new technique, the team first examined a conventional brightfield image of a metal-labelled neuron within a grasshopper’s abdominal ganglion, a type of mini-brain which, even at that size, presented out-of-focus structures.

They then imaged the same ganglion with the spectral LSCM adjusted to the manufacturer’s traditional fluorescence settings, resulting only in strong natural fluorescence and a collective dark blur in place of the silver-labelled neurons.

However, after collecting the light energy emitted from vibrating surface plasmons in the spectral LSCM, the team obtained spectacular three-dimensional computer images of silver and gold-impregnated neurons. This holds enormous potential for stimulating a re-examination of archived preparations, including Golgi-stained and cobalt/silver-labelled nervous systems.

Additionally, by using a number of different metal-based cell-labeling techniques in combination with the new LSCM protocols, tissue and cell specimens can be generated and imaged with ease and in great three-dimensional detail. Changes in even small structural details of neurons can be identified, which are often important indicators of neurological disease, learning and memory, and brain development.

“Both new and archived preparations are essentially permanent and the information gathered from them increases the data available for characterizing neurons as individuals or as members of classes for comparative studies, adding to emerging neuronal banks,” says co-first author Karen Thompson from Agnes Scott College.

“Just as plasmon resonance can explain the continued intensity of the red (caused by silver nanoparticles) and yellow (gold nanoparticles) colors in centuries-old medieval stained glass and other works of art, metal-impregnated neurons are also likely never to fade, neither in the information they provide nor in their intrinsic beauty,” adds Mesce.

 

 

This chapter is partly modified from:

Towards a 3D View of Cellular Architecture: Correlative Light Microscopy and Electron Tomography.

Valentijn J.A.; van Driel L.F.; Jansen K.A.; Valentijn K.M.; Koster A.J.
Book chapter in: Reiner Salzer. Biomedical Imaging: Principles and Applications. Wiley, 2010.

The present thesis reports on newly developed tools and strategies for correlative light and electron microscopy, and their application to cell biology research aimed at furthering our understanding of the structure-functional mechanisms of varying current biological applications. Accordingly, this Introduction consists of two main parts: the first one will discuss past and present strategies for correlative light and electron microscopy (CLEM) as an introduction to the subsequent chapters in this thesis, all of which will describe new developments and applications in the field; the second one will elaborate on the rationale behind the biological applications that were undertaken.

The term ‘correlative microscopy’ is employed in the biomedical literature to designate any combination of two or more microscopic techniques applied to the same region in a biological specimen. The purpose of correlative microscopy is to obtain complementary data, each imaging modality providing different information, on the specimen that is under investigation. Correlative light and electron microscopy (CLEM) is by far the most widespread form of correlative microscopy. CLEM makes use of the fact that imaging with photons on the one hand, and electrons on the other hand, each offers specific advantages over one another. For instance, the low-magnification range inherent to light microscopy (LM) is particularly well-suited for the rapid scanning of large and heterogeneous sample areas, while the high magnification and -resolution that can be achieved by electron microscopy (EM) allows for the subsequent zooming in on selected areas of interest to obtain ultrastructural detail. A further advantage of LM is that it can be used to study dynamic processes, up to the molecular level, in living cells and tissues. The recent surge in live cell imaging research has catalyzed a renewed interest in CLEM methodologies, as the interpretation of the dynamic processes observed by LM often requires high-resolution information from EM data. CLEM is also gaining in momentum in the field of cryo-electron microscopy where the low contrast conditions and low electron dose requirements put a constraint on the detection efficacy.

Current CLEM procedures face a number of challenges. Firstly, sample preparation methods for LM and EM can be quite divergent due to different requirements for preservation, embedding, sectioning, and counterstaining. Therefore, alternative sample preparation protocols need to be devised that are suitable for both LM and EM. Secondly, CLEM often requires the correlated localization of specific molecules in cells or tissues, for which specialized detection systems need to be developed. Standard detection methods are based on tagging of molecules either with fluorochromes for LM, or with gold particles for EM, whereas some CLEM applications require a tag to be visible in both modalities. Thirdly, the transition from imaging by LM to EM may involve handling and additional processing of samples, which can lead to changes in orientation and morphology of the sample. This in turn can hamper the finding back of, and correlation with previously established areas of interest.

In the present post-genomics climate, EM is coming back with a vengeance. Despite the dip in EM-based research during the previous decade, the development of novel EM technologies moved forward at a steady pace, resulting in several breakthrough applications. Among them are electron tomography and cryo-electron tomography, which are techniques for high-resolution 3D visualization and which are gradually becoming mainstream tools in structural molecular biology. As will be discussed in more detail below, (cryo-)electron tomography is often hampered by the lack of landmarks in the 2D views used to select areas of interest.

The diversity of goals to be achieved by CLEM constrains the development of universally applicable protocols. For instance, correlating live cell imaging data of a fluorescent protein with an ultrastructural endpoint requires a different CLEM approach than if the main goal is to pinpoint a rarely occurring structure of interest for EM investigation. CLEM can also be used as an alternative for immuno-EM, or to locate structures for cryo-EM if high-resolution structural details are required. As a consequence of the diversity of applications, there are to date numerous methods to correlate LM and EM data, and more developments, improvements, and applications, are likely to follow. Depending on the purpose of the application, three groups of CLEM methodologies can be distinguished:

  • Those that combine live cell imaging with ultrastructural information (see figure 1),
  • Those that combine LM of fixed or immobilized samples with ultrastructural information (figure 2),
  • Those that combine LM and EM data from the same sections (figure 3)

 

 

Using Laser Scanning Confocal Microscopy as a Guide for Electron Microscopic Study: A Simple Method for Correlation of Light and Electron Microscopy’

XUE J. SUN, LESLIE P. TOLBERT,2 and JOHN G. HILDEBRAND
J Histochem and Cytochcem 1995; 43(3):329-335

 

Anatomic study of synaptic connections in the nervous system is laborious and difficult, especially when neurons are large or have fine branches embedded among many other processes. Although electron microscopy provides a powerful tool for such study, the correlation of light microscopic appearance and electron microscopic detail is very time consuming. We report here a simple method combining laser scanning confocal microscopy and electron microscopy for study of the synaptic relationships of the neurons in the antennal lobe, the first central neuropil in the olfactory pathway, of the moth Manduca sexta. Neurons were labeled intracellularly with neurobiotin or biocytin, two widely used stains. The tissue was then sectioned on a vibratome and processed with both streptavidin-nanogold (for electron microscopic study) and streptavidin-Cy3 (for confocal microscopic study) and embedded in epon/araldite. Interesting areas of the labeled neuron were imaged in the epon/araldite sectioned at the indicated depth for electron microscopic study. This method provides an easy, reliable way to correlate three-dimensional light miaoscopic information with electron microscopic detail, and can be very useful in studies of synaptic connections.

Introduction Study of synaptic connections is fundamental to an understanding of nervous system function. Physiological recording in combination with cell staining with different dyes yields especially useful information about the functional properties and morphology of neurons in various nervous systems. Light microscopic (LM) analysis of neurons, however, often raises the question of whether synaptic connections occur at specialized regions of the neurites. Knowledge of whether synaptic connections between two neurons exist and where on the neuritic tree they occur provides valuable information about how signals are integrated by the neurons and thus about the role the neurons play in a given pathway. Electron microscopy (EM) provides a powerful tool for this type of study. Unfortunately, correlation of three-dimensional LM data with EM detail is often difficult, as neurons are often large (ranging up to hundreds of micrometers in length) with complex branching patterns. Moreover, EM data usually lose most large-scale three- dimensional information. Much work has been done to attempt to overcome these problems (3,4,8,10,14,19,21,25,26,31,34,35). To date, the most successful methods for correlating EM and threedimensional data have been

(a) three-dimensional reconstruction of thin sections,

(b) semi-thin sectioning of tissue, serial reconstruction of the neuron at the light microscopic level, re-embedment, and finally thin-sectioning of selected semi-thin sections for electron microscopic study, and

(c) high-voltage EM observation of relatively thick sections and reconstruction of high-voltage EM data.

Although combination of these techniques or computer-assisted three-dimensional reconstruction and image processing techniques greatly facilitate the task, it is still very time-consuming to pursue this type of study.

Recently, laser scanning confocal microscopy (LSCM) has provided a convenient way to obtain three-dimensional morphology of neurons, as optical sections of relatively thick tissue can be obtained easily and rapidly (5-7,20,24,27,28,30). Equally importantly, information is gathered as digitized optical sections and is readily displayed as three-dimensional stacks. Combination of LSCM and EM appears to be a promising way to study synaptic connections.

 

Several different techniques have been used to bridge the gap between LM and EM (3,4,8,10,14,19,21,25,26,31,34,35). One common way is to section the block into semi-thin sections, make a threedimensional reconstruction of the neuron at the LM level, and then thin-section areas of interest (4,8,10,19,21). However, three-dimensional reconstruction from sections is tedious, and valuable tissue may be lost during reembedding and resectioning. High-voltage EM is a reasonable alternative, as relatively thicker sections can be observed, thus reducing the number of sections needed to span a neuron. This method, however, requires access to a high-voltage EM. We have developed a technique using LSCM as a guide for EM study. A biotin-labeled neuron is rendered detectable by both fluorescence (for LSCM) and immunogold (for EM). After such double labeling, interesting areas of physiologically identified and intracellularly labeled neurons can be investigated at the EM level to see where synaptic connections are formed. Although with our method three-dimensional reconstruction might also be needed, the number of vibratome sections needed to span a neuron is small (two to four in our case with 80-pm sections). This greatly reduces the task.

The major challenge in correlation of LSCM and EM is the compatibility of the labeling methods. Visualization methods using diaminobenzidine (either in a peroxidase reaction or in a reaction catalyzed by photo-oxidation of fluorescent dyes) and Golgi staining have been used widely for both LM and EM observations (see, e.g., 8,26,35). The light- and electron-dense label, however, is not suitable for LSCM imaging, which is best performed on fluorescent  labels. One possibility is to use fluorescent labels, perform LSCM, and, after LSCM imaging, convert the fluorescent dyes into electron-dense materials by using either photo-oxidation of fluorescent dyes [such as Lucifer Yellow (16) or DiI as suggested by Vischer and Durrenberger (32)] in the presence of diaminobenzidine or an antibody against the dye injected into the cell. It is possible to determine the position of an interesting area of a neuron by LSCM with this method, but relocating the same area after plastic embedding is much more difficult than the presently reported method because of shrinkage of the tissue during tissue processing for EM and the inability to monitor the exact position by LSCM during sectioning. The reflection mode of LSCM has been applied successfully to detect electron-dense label in several systems (6,7,22,33). With this mode of imaging, Deitch et al. (6) have proposed another way of combining LSCM and EM. Reflection signals in the LSCM are often weak, however, and do not take full advantage of the excellent resolving capabilities of the confocal microscope.

……

The unending fascination with the Golgi method

Y Koyama*
Department of Anatomy and Neuroscience, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
http://www.oapublishinglondon.com/article/848

In the second half of the 19th century, Camillo Golgi provided a breakthrough staining technique for visualizing whole neurons, which are seen as black bodies due to intracellular staining with microcrystalline silver chromate. The high contrast, selective staining properties enabled identification of complete neuronal morphology. This staining technique, termed the Golgi method, was later improved by Ramón y Cajal and popularised through his tireless experiments. Morphological analysis, using the Golgi method, led to the discovery of neuronal microstructures such as dendritic spines and growth cones and helped give rise to the ‘neuron doctrine’. Many post-mortem human brains as well as brains of experimental animals have since been stained using this method. In combination with other morphological techniques (e.g. electron microscopy and immunohistochemistry), the Golgi method has allowed us to glean more information regarding the neuronal networks present in various brain regions. However, the Golgi method is a difficult first choice for morphological analysis since it is capricious, complicated and time-consuming and has poor reproducibility.

Recent increases in the number of in vivo animal experiments and of post-mortem brains collected following neurological disorders heighten the need for the Golgi method to be viewed as a crucial morphological tool for assessing abnormalities in single neurons, as well as in neuronal networks. Fortunately, over 100 years of neuroanatomical diligence has seen significant contributions to overcoming the shortfalls of this method. The advent of modified Golgi methods with potential use as routine techniques, together with the development of the kit-based Golgi–Cox method, has made the Golgi method more accessible to neuroanatomists.

This review surveys the technical fundamentals, history and evolution of Golgi methods and intends to spark an interest in the Golgi method within every neuroscientist, novice and old pro alike and to allow them to appreciate this useful technique.

Conclusion

Many neuroanatomists, including us, feel a strong attraction to the Golgi method as a powerful morphological tool. Our researchers have identified unwanted issues of the various Golgi methods and then have been working to remedy these problems. We encourage the reader to adopt staining using the Golgi method as its utility continues to evolve.

 

While studying the brain function, it is extremely important to investigate the precise shape and morphological changes of individual neurons. A neuron is a specialised cell that emits an electrical signal to allow information exchange, a characteristic not found in the cells of other organs. Both the short ‘dendrite’, which is intricately branched like a tree branch and the long ‘axon’ emanate from the nerve cell body. In addition, neuronal spines located on dendrites receive electric signals from other neurons and are involved in neuronal plasticity. Thus, together with neural cells such as neuroglia, neurons form complicated networks known as ‘neural circuits’.

To appreciate the complexity of such intricate neural networks, staining methods that allow the visualisation of neuronal cells in thinly sliced brain sections are used. In particular, Nissl stains and silver impregnation are commonly used. Nissl staining, which is based on a mechanism combining a basic aniline dye with Nissl granules, can stain both the cell nucleoli and rough endoplasmic reticula in neurons. In contrast, silver impregnation using neuronal argent affinity can stain an entire neuron, but not the myelin sheath. Neural circuitry refers to the combination of many interacting neural cells and is immensely complex morphologically, with many neurons intertwined with one another within a restricted space. Unfortunately, because the above techniques stain all neural cells with equal probability, it is difficult to identify and appreciate the morphology of a single cell amongst the mass of other stained cells.

In contrast, the Golgi method, focused in this review, has allowed for the visualisation of entire neurons and glia in high detail and with good contrast. Moreover, compared to Nissl staining and silver impregnation, the Golgi method has the beneficial feature of characteristically selective staining. Because neurons are stained only sparsely with the Golgi method, it is a powerful staining technique for providing a complete, detailed representation of a single neuron. The aim of this review was to discuss the history and evolution of the Golgi method.

………

Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse models

In neurodegenerative disorders, such as Alzheimer’s disease, neuronal dendrites and dendritic spines undergo significant pathological changes. Because of the determinant role of these highly dynamic structures in signaling by individual neurons and ultimately in the functionality of neuronal networks that mediate cognitive functions, a detailed understanding of these changes is of paramount importance. Mutant murine models, such as the Tg2576 APP mutant mouse and the rTg4510 tau mutant mouse have been developed to provide insight into pathogenesis involving the abnormal production and aggregation of amyloid and tau proteins, because of the key role that these proteins play in neurodegenerative disease. This review showcases the multidimensional approach taken by our collaborative group to increase understanding of pathological mechanisms in neurodegenerative disease using these mouse models. This approach includes analyses of empirical 3D morphological and electrophysiological data acquired from frontal cortical pyramidal neurons using confocal laser scanning microscopy and whole-cell patch-clamp recording techniques, combined with computational modeling methodologies. These collaborative studies are designed to shed insight on the repercussions of dystrophic changes in neocortical neurons, define the cellular phenotype of differential neuronal vulnerability in relevant models of neurodegenerative disease, and provide a basis upon which to develop meaningful therapeutic strategies aimed at preventing, reversing, or compensating for neurodegenerative changes in dementia.

Keywords: Alzheimer’s disease, Amyloid, Computational modeling, Dendritic spine, Tau, Whole-cell patch-clamp

Neocortical pyramidal neurons possess extensive apical and basilar dendritic trees, which integrate information from thousands of excitatory and inhibitory synaptic inputs. Dendrites respond to inputs with postsynaptic potentials, which are relayed to the soma where they are summed; if a threshold potential is exceeded, an action potential is generated. Voltage attenuation in space and time along dendrites is fundamental to summation and is influenced by a number of interacting morphological properties (such as diameter and length) and active properties (such as distribution of ion channels) of the dendritic shaft (Hausser et al. 2000; Kampa et al. 2007; Stuart and Spruston 2007; Henry et al. 2008). Further complexity arises from the presence of thousands of biophysically active dendritic spines, the principal receptive site for excitatory glutamatergic inputs to a neuron.

Dendrites and dendritic spines in particular are dynamic structures, which undergo significant changes across the life span. Under non-pathological conditions, the number of spines on pyramidal neuron dendrites increases substantially over the course of development, is reduced during maturation to adulthood, and remains relatively stable during adulthood (for review see Bhatt et al. 2009). Then, during normal aging, significant changes in spine number, distribution, and morphology occur (Duan et al. 2003). Spines also undergo significant structural modifications under conditions where synaptic strength is experimentally modified, usually with protocols designed to evoke longterm potentiation or long-term depression (for review see Alvarez and Sabatini 2007; Bhatt et al. 2009; Holtmaat and Svoboda 2009). In many neurodegenerative diseases, significant alterations in the dendritic arbor occur, together with substantial spine loss and alterations in spine morphology (reviewed in Halpain et al. 2005). Gaining an understanding of these sublethal changes to neurons, which detrimentally impact neuronal signaling, and ultimately cognitive function, is an important goal.

Transgenic mouse models have been useful for elucidating mechanisms of amyloid-and tau-induced pathology, although no single model fully recapitulates human disease (for review see Duff and Suleman 2004; Spires et al. 2005). Two of the most commonly employed mouse models of neurodegenerative disease are the Tg2576 amyloid precursor protein (APP) mutant mouse and the rTg4510 tau mutant mouse, which develop significant pathological aggregations of amyloid-beta (Aβ) and tau proteins, respectively. Tg2576 transgenic mice overexpress the Swedish double mutation of the human APP gene, which leads to progressive formation of soluble Aβ peptides and fibrillar Aβ deposits in the form of amyloid plaques. Increased Aβ levels in these mice are associated with progressive structural changes to neurons (although not with neuron death), and cognitive impairment (Hsiao et al. 1996). In the rTg4510 mouse model, expression of the P301L mutant human tau variant leads to progressive development of neurofibrillary tangles (NFTs), neuronal death, and memory impairment reminiscent of the pathology observed in human tauopathies (Santacruz et al. 2005).

In this review, we discuss changes in the structure and function of dendrites and spines of pyramidal neurons that are associated with pathological aggregation of Aβ and tau in these and other mouse models of neurodegenerative disease. We also discuss, as a point of comparison, the impact of normal brain aging on the morphofunctional properties of pyramidal neurons in aged macaque monkeys. This is not a comprehensive review of the literature on such changes in human neurodegenerative diseases or of the many studies of these changes in mouse models (for reviews see Duff and Suleman 2004; Spires and Hyman 2004;Lewis and Hutton 2005; Duyckaerts et al. 2008; Giannakopoulos et al. 2009). Rather, the focus here is specifically on our multidimensional collaborative efforts to understand the functional consequences of pathological changes in the structure of individual layer 3 frontal cortical pyramidal neurons in commonly employed mouse models of neurodegeneration. These studies focus on layer 3 pyramidal neurons in the neocortex because they are the principal neurons involved in corticocortical circuits that mediate many cognitive functions of the frontal cortex and may be selectively targeted in neurodegenerative disease (Morrison and Hof 1997, 2002; Hof and Morrison 2004).

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Structural properties of mouse neocortical pyramidal neurons. a 40 × CLSM image of a layer 3 pyramidal cell from the frontal cortex of a wild-type mouse. The neuron was filled with biocytin during patch-clamp recording and subsequently labeled with Alexastreptavidin 488. b100 × CLSM image of the spiny dendrite shown within the red box in (a). c Electron micrograph showing the ultrastructure of a pyramidal neuron spine, with a prominent postsynaptic density and spine apparatus. Courtesy of Dr. Alan Peters. Scale bars a 40, b 5, c 0.5 μm

The structural properties of dendrites underlie their passive membrane (cable) properties, which are membrane capacitance Cm, specific membrane resistance Rm and axial resistivity Ra. These cable properties determine, at a fundamental level, the degree of summation of synaptic inputs and the spatial distribution of electrical signals. Because summation of synaptic inputs by dendrites is determined in large part by their structure, dendritic morphology plays a critical role in action potential generation (Mainen and Sejnowski 1996; Koch and Segev 2000; Euler and Denk 2001; Vetter et al. 2001; Krichmar et al. 2002; Ascoli 2003). Importantly, both branching topology and surface irregularities including dendritic varicosities (Surkis et al. 1998) contribute to the excitable properties of neurons. For example, recent simulation studies have demonstrated that marked differences in the efficacy of action potential back propagation in different neural types are attributable in large part to variations in dendritic morphology (for review see Stuart et al. 1997;Waters et al. 2005).

Integration of synaptic inputs by dendrites is mediated not only by basic passive cable properties, but also by active properties, which include the number and distribution of voltage, ligand, as well as second messenger-gated transmembrane ionic channels (reviewed in Migliore and Shepherd 2002; Magee and Johnston 2005;Johnston and Narayanan 2008; Nusser 2009). Dendrites possess a rich array of sodium, calcium, and potassium channels that are distributed either uniformly or non-uniformly across a given dendrite (for reviews, see Johnston et al. 1996; Migliore and Shepherd 2002; Magee and Johnston 2005; Johnston and Narayanan 2008; Nusser 2009). For example, layer 5 cortical pyramidal neuron dendrites possess a gradient of the hyperpolarization-activated mixed cationic HCN channels that increase in density from the soma to the apical tuft (Berger et al. 2001; Lorincz et al. 2002). The interaction of intrinsic ionic and synaptic conductances with passive properties determined by dendritic morphology can effectively alter the cable properties of the dendritic tree (Bernander et al. 1991; Segev and London 2000; Bekkers and Hausser 2007) adding a further layer of complexity to signaling by individual neurons. Computational modeling approaches have been extensively employed to shed light on dendritic structure–function relationships and into potential interactions between a multitude of dendritic active and passive properties. These approaches, as discussed at the end of this review, have been useful for gaining insight on dendrites that are too thin to be studied with electrophysiological approaches, and for providing empirical researchers with testable hypotheses relevant to the functional consequences of dendritic dystrophy in neurodegenerative diseases.

Dendritic spines

Dendrites of glutamatergic pyramidal neurons are studded by thousands of dendritic spines, which are the site of most of the glutamatergic synapses in the brain, that confer further functional complexity to these processes. Spine density, shape, and distribution are all important contributors to neuronal excitability that are superimposed on the electrophysiological properties of dendritic shafts (Wilson 1988; Stratford et al. 1989;Baer and Rinzel 1991; Tsay and Yuste 2002). Spines are small appendages that extend from approximately 0.5–3 lm from dendritic shafts and are usually <1 μm in diameter (Fig. 1b, c). Mouse layer 3 frontal cortical pyramidal neurons typically possess approximately 6,000 dendritic spines (Rocher et al. 2008). Spines can be broadly categorized as falling into one of several different morphological types, namely “thin”, “stubby”, “mushroom”, and “filopodia” which are normally seen in large numbers only during development (for review see Yuste and Bonhoeffer 2004; Bourne and Harris 2007). Although most spines do fall into one of these broad categories, serial electron microscopy reveals that there is also a continuum between the different morphological subtypes (Bourne and Harris 2007). Spine morphology determines the strength, stability and function of excitatory synaptic connections that subserve the neuronal networks underlying cognitive function. Smaller spines, such as the thin and filopodia types are less stable and more motile (Trachtenberg et al. 2002; Kasai et al. 2003; Holtmaat et al. 2005) and as a result, are more plastic than large spines such as the mushroom and stubby types (Grutzendler et al. 2002). The size and morphology of the spine head is correlated with the number of docked presynaptic vesicles (Schikorski and Stevens 1999) and the number of postsynaptic receptors (Nusser et al. 1998), and hence with the size of synaptic currents and synapse strength. In addition, a small head size permits fast diffusion of calcium within the spine, while the neck length shapes the time constant for calcium compartmentalization (for review see Yuste and Bonhoeffer 2001; Nimchinsky et al. 2002), modulating postsynaptic mechanisms that play an important role in synaptic plasticity linked to functions, such as learning and memory (Holthoff et al. 2002; Alvarez and Sabatini 2007; Bloodgood and Sabatini 2007). Spine neck length and diameter also affect diffusional coupling between dendrite and spine (Svoboda et al. 1996; Yuste et al. 2000; Bloodgood and Sabatini 2005), and spine density and shape regulate the degree of anomalous diffusion of chemical signals within the dendrite (Santamaria et al. 2006). Spine morphology also varies dynamically in response to synaptic activity (Lendvai et al. 2000; Hering and Sheng 2001; Zuo et al. 2005).

Over the past few decades, it has become increasingly evident that local dendritic spine structure and distribution (Matus and Shepherd 2000) play a key role in the electrical and biochemical signaling of dendrites (Nimchinsky et al. 2002; Matus 2005; Bourne and Harris 2007). However, spines present challenges to the standard cable model of dendrites. The common way to model the effects of spines in a passive cable equation model is to reduce the membrane resistance and increase the membrane capacitance by a factor proportional to the increased membrane surface area due to spines (Jaslove 1992). This modification predicts that voltage should attenuate more drastically in space along spiny dendrites, relative to their smooth counterparts. Because of their capacity for plasticity and because they are the location of most excitatory synapses in the cerebral cortex, accurately characterizing the structure of dendritic spines is essential for understanding their contributions to neuronal, and ultimately to cognitive function.

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Analytical methods to quantify morphological structure. a xy projection of the montage of CLSM tiled image stacks from a wildtype mouse layer 3 frontal cortical pyramidal neuron. Scale bar 40 μm. b Tree structure from the data shown in (a), extracted using NeuronStudio. cAutomatic spine detection and visualization in NeuronStudio. Left automatically detected spines overlaid on a maximum projection of a typical dataset; right the same data and spines volume-rendered in 3D. d Left 2D Rayburst sample used for diameter estimation. Rays cast using the sampling core is shown in orange with the one chosen as the diameter shown in blue. The green line indicates the surface detected by the Rayburst samples. Right spine diameter estimation using a 2D Rayburst run at the center of mass (small green squares) of a single layer. Theblue line indicates the resulting width of the structure as calculated by Rayburst, and provides an approximate length of 0.7 μm. e Optimized fits of scaling exponents (black fitted lines) and optimal scaling regions (gray shaded bands) for the apical dendrites of a typical layer 3 pyramidal cell projecting from superior temporal cortex to area 46 (see Kabaso et al. (2009) for details). f Contributions of branching and tapering exponents to global mass scaling (measured by total area exponent dA) in spine-corrected apical dendrites of long projection neurons of young rhesus monkeys, in the proximal and medial scaling regions (I, II in e). The total branching and tapering vary across the two scaling regions, yet the total area in each region is conserved [modified from Wearne et al. (2005) and Kabaso et al. (2009)]

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Dendritic spine loss in pyramidal neurons from Tg2576 and rTg4510 mice. CLSM images of dendritic segments with spines of neurons from wild-type (top) and transgenic (bottom) mice. Scale bars 10 μm [modified from Rocher et al. (2008, 2009)]

3D reconstruction and analytical approaches

Early methods for digitizing 3D neuronal structures relied on interactive manual tracing from a computer screen (Capowski 1985). These methods were time-consuming, subjective, and lacked precision. In recent years, automated methods have been developed that use image analysis algorithms to extract neuronal morphology directly from 3D microscopy and overcome the limitations of manual techniques (Koh et al. 2002; He et al. 2003; Wearne et al. 2005). Newer methods use pattern recognition routines to track or detect a structure locally without the need for global image operations (Al-Kofahi et al. 2002; Streekstra and van Pelt 2002; Schmitt et al. 2004; Myatt et al. 2006; Santamaria-Pang et al. 2007). Most are designed to work on a broad range of signal-to-noise ratios and even on multiple imaging modalities. This results in increased computational complexity, which makes the use of these methods as interactive reconstruction tools for high-resolution data less than optimal.

In our studies of neuronal structure, morphological reconstruction is performed using NeuronStudio, a neuron morphology reconstruction software tool (http://www.mssm.edu/cnic/tools.html), developed by Wearne et al. (2005) and Rodriguez et al. (2006, 2008, 2009). Neuron- Studio has been designed for low computational complexity to allow interactive semi-automated extraction of neuronal morphology from medium to high-quality de-convolved 3D CLSM and MPLSM image stacks of fluorescently labeled neurons. It features automated extraction of dendrites and dendritic spines as well as a rich set of manual editing and visualization modalities. Figure 2a shows an xy projection of CLSM data from a wild-type mouse layer 3 cortical pyramidal neuron and Fig. 2b shows the automated reconstruction of the neuron’s dendritic arbor obtained using NeuronStudio. Because fluorescence intensity can vary with adequacy of filling, imaging depth and xyspatial extent in CLSM and MPLSM image stacks, data segmentation within NeuronStudio adapts the iterative self-organizing data analysis (ISODATA) method (Ridler and Calvard 1978) to compute local thresholds dynamically. This method is appropriate for datasets exhibiting a bimodal distribution of intensity values, such as the grayscale images characteristic of de-convolved LSM image stacks.

Automated 3D reconstruction of dendritic spines

The assessment of spine numbers and distribution and their classification into subtypes has historically been a labor intensive and relatively inaccurate process. Spine numbers could only be estimated because spines extending primarily in the z plane relative to the dendritic shaft could not be counted. With the advent of CLSM, accurate 3D spine assessment came a step closer, but was still a highly timeconsuming and labor-intensive undertaking. Improving upon previous spine detection algorithms (Koh et al. 2002; Cheng et al. 2007), Rodriguez et al. (2008) devised an efficient and robust method for automated spine detection, available in NeuronStudio.

3D measures of spatial complexity

Traditionally, Sholl analysis (1953) has been used in two dimensions to quantify the spatial complexity of dendritic branching patterns with increasing distance from the soma. Fractal analyses have also been used (Smith et al. 1989; Caserta et al. 1995; Jelinek and Elston 2001; Henry et al. 2002) to quantify spatial complexity as a power law scaling exponent, describing the rate of change of the number of branches over a large portion of the dendrites, and best visualized as the slope of a log–log plot of these two quantities. We have recently extended this work (Rothnie et al. 2006; Kabaso et al. 2009) to include three power law exponents describing global spatial complexity: rates of change of dendritic mass, branching, and taper.

…..

In conclusion, these analytical tools provide rapid, objective analyses of the high-resolution data that we collect from wild-type and transgenic mouse neurons. With NeuronStudio, we are able to perform analyses of differences in dendrite diameter and spine shapes that were not available previously, and these kinds of studies are currently ongoing in our laboratories. Moving forward, we will evaluate whether the global patterns in spatial complexity observed in rhesus monkey pyramidal neurons are similarly present in mouse neurons. We will also compare the spatial complexity of wild-type and transgenic neurons to determine whether global mass homeostasis is conserved in neurodegeneration as it seems to be in aging.

Alterations in the structure of dendrites and spines of cortical pyramidal neurons in Tg2576 and rTg4510 mutant mice

Dendritic changes in neurodegenerative disease ….

Clearly, there is a need for many more studies on the functional electrophysiological consequences to individual neurons of the significant structural changes in neurodegenerative disease. Given the lack of such studies, and also technical considerations such as space clamp limitations and the impossibility of recording from distal dendrites or spines, the use of modeling methods to understand potential functional consequences of structural changes is very important.

Insights from modeling

For nearly 60 years, mathematical models have been used to investigate neuronal function. Hodgkin and Huxley’s (1952) mathematical model of action potential generation predicted the existence of ion channels, decades before ion channels were observed experimentally (Neher and Sakmann 1976). Other models were groundbreaking in describing how dendrites filter signals as passive electrical cables (Rall 1959; Goldstein and Rall 1974), but were limited in their ability to apply directly to realistic morphologic data. Since then, applications of mathematical techniques (Fitzhugh 1961; Nagumo et al. 1962; Rinzel and Ermentrout 1989), advances in computational software (Bower and Beeman 1998; Carnevale and Hines 2006), model reduction (Clements and Redman 1989; Pinsky and Rinzel 1994), and computing power have resulted in models that have great potential for yielding insights into neuronal function. In particular, models have shown that morphology is a critical determinant of neuronal firing properties (Zador et al. 1995; Mainen and Sejnowski 1996; Vetter et al. 2001; Schaefer et al. 2003; Stiefel and Sejnowski 2007). The effects of morphology are further amplified by the actions of ion channels distributed throughout the dendrites (for review see Johnston and Narayanan 2008), both of which shape patterns of synaptic input. Our ability to understand neuronal function depends largely on analysis of the nonlinear interactions between morphology, electrical membrane properties, and synaptic input.

……..

Our modeling results make several predictions that may apply to transgenic mouse models of neurodegeneration. First, changes in dendrite length, diameter, and spine densities/numbers in transgenic neurons compared to wildtype neurons may significantly impact the attenuation of signals to and from the soma. This may happen over an entire neuron, or in limited regions, such as dendrites passing through or near fibrillar amyloid deposits, or in apical tufts that undergo atrophy. Long projection neurons are particularly vulnerable in AD (Hof et al. 1990; Bussiére et al. 2003; Hof and Morrison 2004), giving greater weight to the significant differences in voltage attenuation observed in long projection neurons (Kabaso et al. 2009). Second, changes in spine density may affect the diffusion rate of intracellular messengers and ions. Elongated dendrites may result in less trapping of electrical and chemical signals within spines; this phenomenon may be functionally significant. We must also consider how spine loss might impact the amount of excitatory input that a neuron receives. Finally, it is likely that interactions between morphology and active parameters vary between wild-type and transgenic neurons. To study this more fully we must measure both detailed morphological properties and ionic currents in wild-type and transgenic neurons. To evaluate the degree to which these predictions truly apply to the transgenic mouse models, we will apply the mathematical methods described here directly to the transgenic data that we have collected. These computational studies will likely lead to explicit predictions of which parameters to change, and by how much, to counteract morphological changes that affect physiological function in neurodegenerative disease.

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Development Of Super-Resolved Fluorescence Microscopy

 

Author and Curator: Larry H. Bernstein, MD, FCAP

CSO, Leaders in Pharmaceutical Business Intelligence

Development Of Super-Resolved Fluorescence Microscopy

 

Part I. Nobel Prize For Chemistry 2014: Eric Betzig, Stefan W. Hell
and William E. Moerner Honored For Development Of Super-
Resolved Fluorescence Microscopy

The 2014 Nobel Prize in Chemistry was awarded on 10/08/2014 to
Eric Betzig, Stefan W. Hell and William E. Moerner for
“the development of super-resolved fluorescence microscopy.”

The invention of the electron microscope by Max Knoll and Ernst Ruska at the
Berlin Technische Hochschule in 1931 finally overcame the barrier to higher
resolution that had been imposed by the limitations of visible light. Since then
resolution has defined the progress of the technology.

The ultimate goal was atomic resolution – the ability to see atoms – but this would
have to be approached incrementally over the course of decades. The earliest microscopes merely proved the concept: electron beams could, indeed, be tamed
to provide visible images of matter. By the late 1930s electron microscopes with theoretical resolutions of 10 nm were being designed and produced, and by 1944
this was further reduced to 2 nm. (The theoretical resolution of a an optical light microscope is 200 nm.)

Increases in the accelerating voltage of the electron beam accounted for much of
the improvement in resolution. But voltage was not everything. Improvements in electron lens technology minimized aberrations and provided a clearer picture,
which also contributed to improved resolution, as did better vacuum systems and brighter electron guns. So increasing the resolution of electron microscopes was a main driving force throughout the instrument’s development.

With nanoscopy, scientists could observe viruses, proteins and molecules there
are smaller than 0.0000002 metres.

Three researchers won the 2014 Nobel Prize in Chemistry on Wednesday,
October 8, for giving microscopes much sharper vision than was thought possible, letting scientists peer into living cells with unprecedented detail to seek the roots
of disease.  It was awarded to U.S. researchers Eric Betzig and William Moerner
and German scientist Stefan Hell. They found ways to use molecules that glow on demand to overcome what was considered a fundamental limitation for optical microscopes.

Hell, 52, of Germany, is the director at the Max Planck Institute for Biophysical Chemistry and the division head at the German Cancer Research Center in
Heidelberg. He was honored for his work on fluorescence microscopy, a kind
of nano-flashlight where scientists use fluorescent molecules to see parts of a
cell. Later in his career, he developed the STED microscope, which collects light
from “a multitude of small volumes to create a whole.”

Moerner, a 61-year-old professor in chemistry and applied physics at Stanford University in California, is the recipient of the 2008 Wolf Prize in Chemistry, the
2009 Irving Langmuir Award and the 2013 Peter Debye Award. In 1989, he
was the first scientist to be able to measure the light absorption of a single molecule.
This inspired many chemists to begin focusing on single molecules, including Betzig.

Betzig, 54, the group leader at Janelia Farm Research campus at the Howard
Hughes Medical Institute in Virginia, developed new optical imaging tools for
biology. His work involved taking images of the same area multiple times, and illuminating just a few molecules each time. These images were then
superimposed to create a dense super image at the nano level,

The limitation of optical microscopy was thought to have been determined in a calculation published in 1873 that defined the limit of how tiny a detail could be revealed by optical microscopes. Based on experimental evidence and basic principles of physics, Ernst Abbe and Lord Rayleigh defined and formulated
this diffraction-limited resolution in the late 19th century (Abbe, 1873; Rayleigh,
1896
).  However, only cellular structure and objects that were at least 200 to
350 nm apart could be resolved by light microscopy because, the optical resolution
of light microscopy was limited to approximately half of the wavelength of the light used.  Later key innovations—including fluorescence and confocal laser scanning microscopy (CLSM)—made optical microscopy one of the most powerful and
versatile diagnostic tools in modern cell biology. Using highly specific fluorescent labeling techniques such as immunocytochemistry, in situ hybridization, or
fluorescent protein tags, the spatial distribution and dynamics of virtually every subcellular structure, protein, or genomic sequence of interest can be analyzed in chemically fixed or living samples (Conchello and Lichtman, 2005; Giepmans et al., 2006).

The result of their advance is “really a window into the cell which we didn’t have before,” said Catherine Lewis, director of the cell biology and biophysics division
of the National Institute of General Medical Sciences in Bethesda, Maryland.

“You can observe the behavior of individual molecules in living cells in real time.
You can see … molecules moving around inside the cell. You can see them interacting with each other.”

The research of the three men has let scientists study diseases such as
Parkinson’s, Alzheimer’s and Huntington’s at a molecular level, the Royal
Swedish Academy of Sciences said.

Part II. Electron microscopy limitations

Manfred Von Ardenne in Berlin produced the earliest scanning-transmission
electron microscope in 1937. At the University of Toronto in Canada, Cecil Hall, James Hillier, and Albert Prebus, working under the direction of Eli Burton,
produced an advanced 1938 Toronto Model electron microscope that would
later become the basis for Radio Corporation of America’s Model B, the first commercial electron microscope in North America. Ruska at Siemens in
Germany produced the first commercial electron microscope in the world in 938.

Starting in 1939, scientists in Japan gathered to decide on the best way to build
an electron microscope. This group evolved into the Japan Electron Optics Laboratory (JEOL) that would eventually produce more models and varieties
of electron microscopes than any other company. Hitachi and Toshiba in Japan
also played a major role in the early development process.

The 1960s through the 1990s produced many innovative instruments and trends.
The introduction of the first commercial scanning electron microscopes (SEMs)
in 1965 opened up a new world of analysis for materials scientists. Ultrahigh
voltage TEM instruments (up to 3 MeV at CEMES-LOE/CNRS in Toulouse,
France, and at Hitachi in Tokyo, Japan), in the 1960s and 1970s gave electrons higher energy to penetrate more deeply into thick samples. The evolution and incorporation of other detectors (electron microprobes, electron energy loss spectroscopy (EELS), etc.) made the SEM into a true analytical electron
microscope (AEM) beginning in the 1970s. The development of brighter
electron sources, such as the lanthanum hexaboride filament (LAB6) and the
field emission gun in the 1960s, and their commercialization in the 1970s
brought researchers a brighter source of electrons and with it better imaging
and resolution. Tilting specimen stages permitting examination of the specimen
from different angles aided significantly in the determination of crystal structure.
In the late 1980s and throughout the 1990s, the environmental electron
microscopes that allow scientists to examine samples under more natural
conditions of temperature and pressure have dramatically expanded the
types of samples that can be examined.

In medicine, the EM made a unique contribution to diagnostic anatomic
pathology in renal biopsy analysis. However, the small sample had to be
embedded, and in the early days one cut the specimen by breaking glass
for the cutting of the specimen. But even though EM ushered in a new era of molecular pathology, the contribution was limited, despite incremental
improvements.

In the past, the use of microscopes was limited by a physical restriction;
scientists could only see items that were larger than roughly half the
wavelength of light (.2 micrometers)
. However, the groundbreaking work
of the Nobel laureates bypassed the maximum resolution of traditional
microscopes and launched optical microscopy into the nanodimension.

Part III. Super resolution fluorescence microscopy

Bo Huang,1,2 Mark Bates,3 and Xiaowei Zhuang1,2,4
Author information ► Copyright and License information ►
Annu Rev Biochem. 2009; 78: 993–1016.
http://dx.doi.org:/10.1146/annurev.biochem.77.061906.092014
PMCID: PMC2835776  NIHMSID: NIHMS179491

Achieving a spatial resolution that is not limited by the diffraction of
light, recent developments of super-resolution fluorescence microscopy
techniques allow the observation of many biological structures not
resolvable in conventional fluorescence microscopy. New advances
in these techniques now give them the ability to image three-dimensional
(3D) structures, measure interactions by multicolor colocalization, and
record dynamic processes in living cells at the nanometer scale. It is
anticipated that super-resolution fluorescence microscopy will become
a widely used tool for cell and tissue imaging to provide previously
unobserved details of biological structures and processes.

Keywords: Sub-diffraction limit, single-molecule, multicolor imaging,
three-dimensional imaging, live cell imaging, single-particle tracking,
photoswitchable probe

Among the various microscopy techniques, fluorescence microscopy is
one of the most widely used because of its two principal advantages:
Specific cellular components may be observed through molecule-specific
labeling, and light microscopy allows the observation of structures inside
a live sample in real time. Compared to other imaging techniques such
as electron microscopy (EM), however, conventional fluorescence
microscopy is limited by relatively low spatial resolution because of the
diffraction of light. This diffraction limit, about 200–300 nm in the lateral
direction and 500–700 nm in the axial direction, is comparable to or larger
than many subcellular structures, leaving them too small to be observed in
detail. In recent years, a number of “super-resolution” fluorescence microscopy techniques have been invented to overcome the diffraction barrier, including techniques that employ nonlinear effects to sharpen the point-spread function
of the microscope, such as stimulated emission depletion (STED) microscopy
(1, 2), related methods using other reversible saturable optically linear
fluorescence transitions (RESOLFTs) (3), and saturated structured-illumination microscopy (SSIM) (4), as well as techniques that are based on the localization
of individual fluorescent molecules, such as stochastic optical reconstruction microscopy (STORM) (5), photoactivated localization microscopy (PALM) (6),
and fluorescence photoactivation localization microscopy (FPALM) (7). These methods have yielded an order of magnitude improvement in spatial resolution
in all three dimensions over conventional light microscopy.

THE RESOLUTION LIMIT IN OPTICAL MICROSCOPY

Microscopes can be used to visualize fine structures in a sample by providing
a magnified image. However, even an arbitrarily high magnification does not
translate into the ability to see infinitely small details. Instead, the resolution
of light microscopy is limited because light is a wave and is subject to diffraction.

The diffraction limit

An optical microscope can be thought of as a lens system that produces a
magnified image of a small object. In this imaging process, light rays from
each point on the object converge to a single point at the image plane. However,
the diffraction of light prevents exact convergence of the rays, causing a sharp
point on the object to blur into a finite-sized spot in the image. The three-
dimensional (3D) intensity distribution of the image of a point object is called
the point spread function (PSF). The size of the PSF determines the resolution
of the microscope: Two points closer than the full width at half-maximum
(FWHM) of the PSF will be difficult to resolve because their images overlap substantially.

The FWHM of the PSF in the lateral directions (the x–y directions perpendicular
to the optical axis) can be approximated as Δxy ≈ 0.61λ / NA, where λ is the wavelength of the light, and NA is the numerical aperture of the objective
defined as NA = n sinα, with n being the refractive index of the medium and
α being the half-cone angle of the focused light produced by the objective.
The axial width of the PSF is about 2–3 times as large as the lateral width
for ordinary high NA objectives. When imaging with visible light (λ ≈ 550 nm),
the commonly used oil immersion objective with NA = 1.40 yields a PSF with
a lateral size of ~200 nm and an axial size of ~500 nm in a refractive index-
matched medium (Figure 1) (8).

Figure 1

The PSF of a common oil immersion objective with NA = 1.40, showing the
focal spot of 550 nm light in a medium with refractive index n = 1.515. The
intensity distribution in the x-z plane of the focus spot is computed numerically.

PFS of oil immersion microscope

PFS of oil immersion microscope

Because the loss of high-frequency spatial information in optical microscopy
results from the diffraction of light when it propagates through a distance larger
than the wavelength of the light (far field), near-field microscopy is one of the
earliest approaches sought to achieve high spatial resolution. By exciting the fluorophores or detecting the signal through the nonpropagating light near the fluorophore, high-resolution information be retained. Near-field scanning optical microscopy (NSOM) acquires an image by scanning a sharp probe tip across
the sample, typically providing a resolution of 20–50 nm (911). Wide-field
imaging has also been recently demonstrated in the near-field regime using
a super lens with negative refractive index (12, 13). However, the short range
of the near-field region (tens of nanometers) compromises the ability of light microscopy to look into a sample, limiting the application of near-field microscopy
to near-surface features only. This limit highlights the need to develop far-field
high-resolution imaging methods.

Among far-field fluorescence microscopy techniques, confocal and multiphoton microscopy are among the most widely used to moderately enhance the spatial resolution (14, 15). By combining a focused laser for excitation and a pinhole for detection, confocal microscopy can, in principle, have a factor of √2 improvement
in the spatial resolution. In multiphoton microscopy, nonlinear absorption processes reduce the effective size of the excitation PSF. However, this gain in the PSF size
is counteracted by the increased wavelength of the excitation light. Thus, instead
of improving the resolution, the main advantage of confocal and multi-photon microscopy over wide-field microscopy is the reduction of out-of-focus fluorescence background, allowing optical sectioning in 3D imaging.

Two techniques, 4Pi and I5M microscopy, approach this ideal situation by using
two opposing objectives for excitation and/or detection (16, 17). By acquiring
multiple images with illumination patterns of different phases and orientations,
a high-resolution image can be reconstructed. Because the illumination pattern
itself is also limited by the diffraction of light, structured illumination microscopy
(SIM) is only capable of doubling the spatial resolution by combining two diffraction-limited sources of information.  The best achievable result using these methods
would be an isotropic PSF with an additional factor of 2 in resolution improvement. This would correspond to ~100-nm image resolution in all three dimensions, as
has been demonstrated by the I5S technique, which combines I5M and SIM (22). Albeit a significant improvement, this resolution is still fundamentally limited by
the diffraction of light.

SUPER RESOLUTION FLUORESCENCE MICROSCOPY BY SPATIALLY PATTERNED EXCITATION

One approach to attain a resolution far beyond the limit of diffraction, i.e., to
realize super-resolution microscopy, is to introduce sub-diffraction-limit features
in the excitation pattern so that small-length-scale information can be read out.
We refer to this approach, including STED, RESOLFT, and SSIM, as super-
resolution microscopy by spatially patterned excitation or the “patterned excitation” approach.

The concept of STED microscopy was first proposed in 1994 (1) and subsequently demonstrated experimentally (2). Simply speaking, it uses a second laser (STED laser) to suppress the fluorescence emission from the fluorophores located off the center of the excitation. This suppression is achieved through stimulated emission: When an excited-state fluorophores encounters a photon that matches the energy difference between the excited and the ground state, it can be brought back to
the ground state through stimulated emission before spontaneous fluorescence emission occurs. This process effectively depletes excited-state fluorophores
capable of fluorescence emission (Figure 2a,b).

Figure 2

The principle of STED microscopy. (a) The process of stimulated emission. A
ground state (S0) fluorophore can absorb a photon from the excitation light and
jump to the excited state (S1).

STED microsopy

STED microsopy

The pattern of the STED laser is typically generated by inserting a phase mask
into the light path to modulate its phase-spatial distribution (Figure 2b). One such phase mask generates a donut-shaped STED pattern in the xy plane (Figure 2c)
and has provided an xy resolution of ~30 nm (24). STED can also be employed
in 4Pi microscopy (STED-4Pi), resulting in an axial resolution of 30–40 nm (25). STED has been applied to biological samples either immuno-stained with
fluorophore labeled antibodies (26) or genetically tagged with fluorescent
proteins (FPs) (27). Dyes with high photostability under STED conditions and
large stimulated emission cross sections in the visible to near infrared (IR) range
are preferred. Atto 532 and Atto 647N are among the most often used dyes for
STED microscopy.

Stimulated emission is not the only mechanism capable of suppressing
undesired fluorescence emission. A more general scheme using saturable
depletion to achieve super resolution has been formalized with the name
RESOLFT microscopy (3). This scheme employs fluorescent probes that
can be reversibly photoswitched between a fluorescent on state and a dark
off state. The off state can be the ground state of a fluorophores as in the
case of STED, the triplet state as in ground-state-depletion microscopy
(28, 29), or the dark state of a reversibly photoswitchable fluorophore (30).  RESOLFT has been demonstrated using a reversibly photoswitchable
fluorescent protein as FP595 which leads to a resolution better than 100 nm
at a depletion laser intensity of 600 W/cm2(30).

The same concept of employing saturable processes can also be applied
to SIM by introducing sub-diffraction-limit spatial features into the excitation
pattern. SSIM has been demonstrated using the saturation of fluorescence
emission, which occurs when a fluorophore is illuminated by a very high
intensity of excitation light (4). Under this strong excitation, it is immediately
pumped to the excited state each time it returns to the ground state. In SSIM,
where the sample is illuminated with a sinusoidal pattern of strong excitation
light, the peaks of the excitation pattern can be clipped by fluorescence
saturation and become flat, whereas fluorescence emission is still absent
from the zero points in the valleys (Figure 3a). These effects add higher order
spatial frequencies to the excitation pattern. Mixing this excitation pattern with
the high-frequency spatial features in the sample can effectively bring the sub-diffraction-limit spatial features into the detection range of the microscopy
(Figure 3b).

Figure 3

The principle of SSIM. (a) The generation of the illumination pattern. A
diffractive grating in the excitation path splits the light into two beams. Their interference after emerging from the objective and reaching the sample creates
a sinusoidal illumination

SSIM

SSIM

Although the image of a single fluorophore, which resembles the PSF, is a
finite-sized spot, the precision of determining the fluorophores position from
its image can be much higher than the diffraction limit, as long as the image
results from multiple photons emitted from the fluorophore. Fitting an image
consisting of N photons can be viewed as N measurements of the fluorophore position, each with an uncertainty determined by the PSF (8), thus leading to
a localization precision approximated by:

Δloc≈ΔN−−√

where Δloc is the localization precision and Δ is the size of the PSF. This
scaling of the localization precision with the photon number allows super-
resolution microscopy with a resolution not limited by the diffraction of light.

High-precision localization of bright light has reached a precision as high
as ~1 Å (33). Taking advantage of single-molecule detection and imaging
(34, 35), nanometer localization precision has been achieved for single
fluorescent molecules (36).

Using fluorescent probes that can switch between a fluorescent and a dark
state, a recent invention overcomes this barrier by separating in the time
domain the otherwise spatially overlapping fluorescent images. In this approach, molecules within a diffraction limited region can be activated at different time
points so that they can be individually imaged, localized, and subsequently deactivated (Figure 4). Massively parallel localization is achieved through
wide-field imaging, so that the coordinates of many fluorophores can be
mapped and a super-resolution images subsequently reconstructed. This
concept has been independently conceived and implemented by three labs,
and it was given the names STORM (5), PALM (6), and FPALM (7), respectively.

Iterating the activation and imaging process allows the locations of many
fluorophores to be mapped and a super-resolution image to be constructed
from these fluorophore locations. In the following, we refer to this approach
as super-resolution microscopy by single-molecule localization.

Figure 4

The principle of stochastic optical reconstruction microscopy (STORM), photoactivated localization microscopy (PALM), and fluorescence photo-
activation localization microscopy (FPALM). Different fluorescent probes
marking the sample structure are activated.

STORM

STORM

After capturing the images with a digital camera, the point-spread functions
of the individual molecules are localized with high precision based on the
photon output before the probes spontaneously photo-bleach or switch to
a dark state. The positions of localized molecular centers are indicated with
black crosses. The process is repeated in Figures (c) through (e) until all of
the fluorescent probes are exhausted due to photo-bleaching or because the background fluorescence becomes too high. The final super-resolution image
(Figure (f)) is constructed by plotting the measured positions of the fluorescent probes.
http://microscopyu.com/tutorials/flash/superresolution/storm/index.html

The resolution of this technique is limited by the number of photons detected
per photoactivation event, which varies from several hundred for FPs (6) to
several thousand for cyanine dyes such as Cy5 (5, 46). These numbers
theoretically allow more than an order of magnitude improvement in spatial
resolution according to the √N scaling rule. In practice, a lateral resolution
of ~20 nm has been established experimentally using the photoswitchable
cyanine dyes (5, 46). Super-resolution images of biological samples have
been reported with directly labeled DNA structures and immunostained DNA-
protein complexes in vitro (5) as well as with FPtagged or immunostained
cellular structures (6, 44, 46).

Table 1   Photoswitchable fluorophores used in super resolution
fluorescence microscopy

Photoswitchable fluorophores

Photoswitchable fluorophores

Recent advances in super-resolution fluorescence microscopy
(including the capability for 3D, multicolor, live-cell imaging) enable
new applications in biological samples. These technical advances
were made possible through the development of both imaging optics
and fluorescent probes.

  • 3D imaging using the single-molecule localization approach
  • 3D imaging using the patterned excitation approach
  • Multicolor imaging
  • Multicolor imaging using the patterned excitation approach
  • Multicolor imaging using the single-molecule localization approach
  • Live cell imaging

Fluorescence imaging of a live cell has two requirements: specific labeling
of the cell and a time resolution that is high enough to record relevant
dynamics in the cell.  Many fluorescent proteins and organic dyes, including
cyanine dyes (46) and caged dyes, have been shown switchable in live cells.

Because STED has a much smaller PSF than scanning confocal microscopy,
STED would inherently take more time to scan though the same size of image
field. By increasing the scanning speed and limiting the field of view to a few µm, Westphal and coworkers have observed Brownian motion of a dense suspension
of nanoparticles with an impressive rate of 80 frames per second (fps) using
STED microscopy (63). More recently, they have demonstrated video-rate
(28 fps) imaging of live hippocampal neurons and observed the movement of individual synaptic vesicles with 60–80-nm resolution (64).

Sub-diffraction-limit imaging of focal adhesion proteins in live cells has recently
been demonstrated (65). Photoswitchable fluorescent protein, EosFP, was used
to label the focal adhesion protein paxillin. A time resolution of ~25–60 seconds
per frame was obtained, and during this time interval, approximately 103
fluorophores were activated and localized per square micrometer, providing
an effective resolution of 60–70 nm by the Nyquist criterion (65). More recently, super-resolution imaging has also been demonstrated in live bacteria with photoswitchable enhanced yellow fluorescent protein (EYFP), allowing the
MreB structure in the cell to be traced (66).

The optical resolution

Optical resolution is the intrinsic ability of a given method to resolve a structure
and can be defined as the ability to distinguish two point sources in proximity.
For the patterned excitation approaches, such as STED, SSIM, and RESOLFT,
the optical resolution is represented by the size of the effective PSF. For the
single-molecule localization approach, such as STORM/PALM/FPALM, the
precision of determining the positions of individual fluorescent probes is the
principal measure of optical resolution.

By using a spatially patterned excitation profile, this approach achieves super resolution by generating an effective excitation volume with dimensions far
below the diffraction limit. Taking STED as an example, the sharpness of the
PSF results from the saturation of depletion of excited-state fluorophores in
the region neighboring the zero point of the STED laser (which coincide with
the focal point of the excitation laser). With an increasing STED laser power,
the saturated region expands toward the zero point, but fluorophores at the
zero point are not affected by the STED laser if the zero point is strictly kept
at zero intensity. Therefore, a theoretically unlimited gain in spatial resolution
may be achieved if the zero point in the depletion pattern is ideal.

The single-molecule localization approach achieves super resolution through
high precision localization of individual fluorophores. The number of photons
collected from a fluorophore is a principal factor limiting the localization
precision and hence the resolution of the final image.

Several photoswitchable fluorophores have been reported to give thousands
of photons detected per activation event [e.g., 6000 from Cy5 (46)].With the
PSF fitting procedure and the mechanical stability of the system optimized,
the background signal suppressed, and the nonuniformity of camera pixels
corrected, optical resolution of just a few nanometers could potentially be
achieved, reaching the molecular scale. As in the case of the patterned
excitation approach, the optical resolution here is also unlimited, in principle,
given a sufficient number of photons detected from the fluorescent probes.

Part III. A guide to super-resolution fluorescence microscopy

L Schermelleh1R Heintzmann2,3,4, and H Leonhardt1
JCB Jul 19, 2010 // 190(2): 165-175
The Rockefeller University Press,
http://dx.doi.org:/10.1083/jcb.201002018

Based on experimental evidence and basic principles of physics, Ernst Abbe
and Lord Rayleigh defined and formulated this diffraction-limited resolution in
the late 19th century (Abbe, 1873Rayleigh, 1896). Later key innovations—including fluorescence and confocal laser scanning microscopy (CLSM)—made optical microscopy one of the most powerful and versatile diagnostic
tools in modern cell biology.

The optical resolution defines the physical limit of the smallest structure it
can resolve. When imaging a biological sample, the effective resolution is
also affected by several sample-specific factors, including the labeling density,
probe size, and how well the ultrastructures are preserved during sample
preparation.

The diffraction (Abbe) limit of detection

Resolution is often defined as the largest distance at which the image of
two point-like objects seems to amalgamate. Thus, most resolution criteria
(Rayleigh limit,Sparrow limit, full width at half maximum of the PSF) directly
relate to properties of the PSF. These are useful resolution criteria for visible
observation of specimen, but there are several shortcomings of such a definition
of resolution: (1) Knowing that the image is an image of two particles, these
can in fact be discriminated with the help of a computer down to arbitrary
smaller distances. Determining the positions of two adjacent particles thus
becomes a question of experimental precision and most notably photon statistics
rather than being described by the Rayleigh limit. (2) These limits do not
necessarily correspond well to what level of detail can be seen in images or
real world objects; e.g., the Rayleigh limit is defined as the distance from the
center to the first minimum of the point spread function, which can be made
arbitrarily small with the help of ordinary linear optics (e.g., Toraldo-filters),
albeit at the expense of the side lobes becoming much higher than the central
maximum. (3)

Abbe’s formulation of a resolution limit avoids all of the above shortcomings
at the expense of a less direct interpretation. The process of imaging can be
described by a convolution operation. With the help of a Fourier transformation,
every object (whether periodic or not) can uniquely be described as a sum of
sinusoidal curves with different spatial frequencies (where higher frequencies
represent fine object details and lower frequencies represent coarse details).
The rather complex process of convolution can be greatly simplified by looking
at the equivalent operation in Fourier space: The Fourier-transformed object
just needs to be multiplied with the
Fourier-transformed PSF to yield the Fourier-transformed ideal image (without
the noise). Because the Fourier-transformed PSF now describes how well each
spatial frequency of the Fourier-transformed object gets transferred to appear in the
image, this Fourier-transformed PSF is called the optical transfer function, OTF
(right panel). Its strength at each spatial frequency (e.g., measured in oscillations
per meter) conveniently describes the contrast that a sinusoidal object would
achieve in an image.

Abbe limit

Abbe limit

Interestingly, the detection OTF of a microscope has a fixed frequency
border (Abbe limit frequency, right panel). The maximum-to-maximum
distance Λmin of the corresponding sine curve is commonly referred to
as Abbe’s limit (left panel). In other words: The Abbe limit is the smallest
periodicity in a structure, which can be discriminated in its image. As a
point object contains all spatial frequencies, this Abbe limit sine curve
needs to also be present in the PSF. A standard wide-field microscope
creates an image of a point object (e.g., an emitting molecule) by capturing
the light from that molecule at various places of the objective lens, and
processing it with further lenses to then interfere at the image plane.
Conveniently due to the reciprocity principle in optics, the Abbe limit Λmin
along an in-plane direction in fluorescence imaging corresponds to the
maximum-to-maximum distance of the intensity structure one would get by
interfering two waves at extreme angles captured by the objective lens:
where λ/n is the wavelength of light in the medium of refractive index n.
The term NA = n sin(α) conveniently combines the half opening angle α
of the objective and the refractive index n of the embedding medium.

Abbe’s famous resolution limit is so attractive because it simply depends
on the maximal relative angle between different waves leaving the
object and being captured by the objective lens to be sent to the image.
It describes the smallest level of detail that can possibly be imaged with
this PSF “brush”. No periodic object detail smaller than this shortest
wavelength can possibly be transferred to the image.

Confocal laser scanning microscopy employs a redesigned optical
path and specialized hardware. A tightly focused spot of laser light is
used to scan the sample and a small aperture (or pinhole) in the
confocal image plane of the light path allows only light originating
from the nominal focus to pass (Cremer and Cremer, 1978Sheppard
and Wilson, 1981
Brakenhoff et al., 1985). The emitted light is
detected by a photomultiplier tube (PMT) or an avalanche photodiode
(APD) and the image is then constructed by mapping the detected
light in dependence of the position of the scanning spot. CLSM can
achieve a better resolution than wide-field fluorescence microscopy
but, to obtain a significant practical advantage, the pinhole needs to
be closed to an extent where most of the light is discarded
(Heintzmann et al., 2003).

Wide-field deconvolution and CLSM have long been the gold standards
in optical bioimaging, but we are now witnessing a revolution in light
microscopy that will fundamentally expand our perception of the cell.
Recently, several new technologies,collectively termed super-resolution
microscopy or nanoscopy, have been developed that break or bypass
the classical diffraction limit and shift the optical resolution down to
macromolecular or even molecular levels (Table I).

Super-resolution light microscopy methods

super resolution microscopy

super resolution microscopy

http://zeiss-campus.magnet.fsu.edu/articles/superresolution/introduction.html

Conceptually, one can discern near-field from far-field methods and
whether the subdiffraction resolution is based on a linear or nonlinear
response of the sample to its locally illuminating (exciting or depleting) irradiance. The required nonlinearity is currently achieved by using reversible saturable optical fluorescence transitions (RESOLFT) between molecular states (Hofmann et al., 2005Hell, 2007).

Besides these saturable optical fluorescence transitions also other
approaches, e.g., Rabi oscillations, could be used to generate the
required nonlinear response.

Note that each of the novel imaging modes has its individual signal-
to-noise consideration depending on various factors.  A full
discussion of this issue is beyond the scope of this review, but as a
general rule, single-point scanning systems, albeit fundamentally limited
in speed by fluorescence saturation effects, can have better signal-
to-noise performance for thicker samples.

With three-dimensional SIM (3D-SIM), an additional twofold increase
in the axial resolution can be achieved by generating an excitation
light modulation along the z-axis using three-beam interference
(Gustafsson et al., 2008Schermelleh et al.,2008) and processing a
z-stack of images accordingly. Thus, with 3D-SIM an approximately eightfold smaller volume can be resolved in comparison to conventional microscopy (Fig. 2). To computationally reconstruct a three-dimensional dataset of a typical mammalian cell of 8-µm height with a
z-spacing of 125 nm, roughly 1,000 raw images (512 × 512 pixels) are
recorded. Because no special photophysics is needed, virtually all modern fluorescent labels can be used provided they are sufficiently photostable
to accommodate the additional exposure cycles.

Resolvable volumes obtained with current commercial super-resolution microscopes.

A schematic 3D representation of focal volumes is shown for the indicated
emission maxima. The approximate lateral (x,y) and axial (z) resolution
and resolvable volumes are listed. Note that STED/CW-STED and 3D-SIM
can reach up to 20 µm into the sample, whereas PALM/STORM is usually
confined to the evanescent wave field near the sample bottom. It should be
noted that deconvolution approaches can further improve STED resolution.
For comparison the “focal volume” for PALM/STORM was estimated based
on the localization precision in combination with the z-range of TIRF.

Resolvable volumes obtained

Resolvable volumes obtained

Super-resolution microscopy of biological samples.

(A) Conventional wide-field image (left) and 3D-SIM image of a mouse
C2C12 prometaphase cell stained with primary antibodies against
lamin B and tubulin, and secondary antibodies conjugated to Alexa 488
(green) and Alexa 594 (red), respectively. Nuclear chromatin was stained
with DAPI (blue). 3D image stacks were acquired with a DeltaVision OMX
prototype system (Applied Precision). The bottom panel shows the
respective orthogonal cross sections. (B) HeLa cell stained with primary
antibodies against the nuclear pore complex protein Nup153 and
secondary antibodies conjugated with ATTO647N. The image was
acquired with a TCS STED confocal microscope (Leica). (C) TdEosFP-
paxillin expressed in a Hep G2 cell to label adhesion complexes at
the lower surface. The image was acquired on an ELYRA P.1
prototype system (Carl Zeiss, Inc.) using TIRF illumination. Single
molecule positional information was projected from 10,000 frames
recorded at 30 frames per second. On the left, signals were summed
up to generate a TIRF image with conventional wide-field lateral
resolution. Bars: 5 µm (insets, 0.5 µm).

biological images

biological images

APPLICATIONS IN BIOLOGICAL SYSTEMS

The cytoskeleton of mammalian cells, especially microtubules
(Figure 5a) (29444652), is the most commonly used benchmark
structure for super-resolution imaging. Other cytoskeletal structures
imaged so far include actin filaments in the lamellipodium (6),
keratin intermediate filaments (59), neurofilaments (2683) and
MreB in Caulobacter (66).

Figure 5

cytoskeleton. f5.

cytoskeleton. f5.

Examples of super-resolution images of biological samples.
(a) Two-color STORM imaging of immunostained microtubule (green)
and clathrin-coated pits (red) (From Reference 46. Reprinted with
permission from AAAS).

Organelles, such as the endoplasmic reticulum (27), lysosome (6),
endocytic and exocytic vesicles (465264), and mitochondria
(65356), have also been imaged. For example, using the single-molecule localization approach, 3D STORM imaging has clearly
resolved the ~150-nm diameter, hemispherical cage shape of clathrin-coated pits (4652), which only appear as diffraction-limited spots
without any feature in conventional fluorescence microscopy (Figure 5a,b).
Two-color 3D STED has resolved the hollow shape of the mitochondrial
outer membrane (marked by the translocase protein Tom20), enclosing
a matrix protein Hsp60 (56), even though the diameter of mitochondria is
only about 300–500 nm (Figure 5c). The outer membrane structure of
mitochondria and their interactions with microtubules have been resolved
by two-color 3D STORM (53). The transport of synaptic vesicles
has been recorded at video rate using 2D STED (Figure 5d ) (64).

Many plasma membrane proteins or membrane associated protein
complexes have also been studied by super-resolution fluorescence
microscopy. For example, synaptotagmin clusters after exocytosis in
primary cultured hippocampal neurons (84), the donut-shaped
clusters of Drosophila protein Bruchpilot at the neuromuscular
synaptic active zone (85), and the size distribution of syntaxin clusters
have all been imaged (8687). Photoactivation has enabled the tracking
of the influenza protein hemagglutinin and the retroviral protein Gag in
live cells, revealing the membrane microdomains (67) and the spatial
heterogeneity of membrane diffusion (68). The morphology and transport
of the focal adhension complex has also been observed using live-cell
PALM (Figure 5e) (65).

Summary points

  1. Super resolution fluorescence microscopy with a spatial resolution not limited by the diffraction of
    light has been implemented using saturated depletion/excitation or single-molecule localization
    of switchable fluorophores.
  2. Three-dimensional imaging with an optical resolution as high as ~20 nm in the lateral direction
    and 40–50 nm in axial dimension has been achieved.
  3. The resolution of these super-resolution fluorescence microscopy techniques can in principle
    reach molecular scale.
  4. In practice, the resolution of the images are not only limited by the intrinsic optical resolution,
    but also by sample specific factors including the labeling density, probe size and sample preservation.
  5. Multicolor super resolution imaging has been implemented, allowing colocalization measurements
    to be performed at nanometer scale resolution and molecular interaction to be more précisely
    identified in cells.
  6. Super-resolution fluorescence imaging allows dynamic processes to be investigated at the tens of
    nanometer resolution in living cells.
  7. Many cellular structures have been imaged at sub-diffraction-limit resolution.

Future issues

  1. Achieving molecular scale resolution (a few nanometers or less).
  2. Fast super resolution imaging of a large view field by multi-point scanning or high-speed single-molecule switching/localization.
  3. Developing new fluorescent probes that are brighter, more photostable and switchable fluorophores
    that have high on-off contrast and fast switching rate.
  4. Developing fluorescent labeling methods that can stain the target with small molecules at high specificity,
    high density and good ultrastructure preservation.
  5. Application of super resolution microscopy to provide novel biological insights

Acronyms

FP

Fluorescent Protein

FPALM

Fluorescence PhotoActivation Localization Microscopy

I5M

Combination of I2M (Illumination Interference Microscopy) and I3M
(Incoherent Imaging Interference Microscopy)

PALM

PhotoActivated Localization Microscopy

PSF

Point Spread Function

RESOLFT

REversible Saturable Optically Linear Fluorescence Transition

SIM

Structured Illumination Microscopy

SSIM

Saturated Structured Illumination Microscopy

STED

STimulated Emission Depletion

STORM

STochastic Optical Reconstruction Microscopy

glossary

Numerical aperture (NA)

The numerical aperture of an objective characterizes the solid angle
of light collected from a point light source at the focus of the objective.

Stimulated emission

The process that an excited state molecule or atom jumps to the
ground state by emitting another photon that is identical to the incoming
photon. It is the basis of laser.

Fluorescence saturation

At high excitation intensity, the fluorescence lifetime instead of the excitation
rate becomes the rate limiting step of fluorescence emission, causing the
fluorescence signal not to increase proportionally with the excitation intensity.

Nyquist criterion

To determine a structure, the sampling interval needs to be no larger than
half of the feature size.

Mitochondria

Organelles in eukaryotic cells for APT generation, consisting of two
membrane (inner and outer) enclosing the inter membrane space and
the matrix inside the inner membrane.

Clathrin-coated pit

Vesicle forming machinery involved in endocytosis and intracellular
vesicle transport, consisting of clathrin coats, adapter proteins, and
other regulatory proteins.

Focal adhesion

The macromolecular complex serving as the mechanical connection
and signaling hub between a cell and the extracellular matrix or other cells.

Selected references with abstract

Near-Field Optics: Microscopy, Spectroscopy, and Surface
Modification Beyond the Diffraction Limit
Eric Betzig,  Jay K. Trautman
AT&T Bell Laboratories, Murray Hill, NJ 07974
Science 10 Jul 1992; 257(5067) pp. 189-195
http://dx.doi.org:/0.1126/science.257.5067.189

 The near-field optical interaction between a sharp probe and a sample
of interest can be exploited to image, spectroscopically probe, or modify
surfaces at a resolution (down to ∼12 nm) inaccessible by traditional far-field
techniques. Many of the attractive features of conventional optics are
retained, including noninvasiveness, reliability, and low cost. In addition, most
optical contrast mechanisms can be extended to the near-field regime,
resulting in a technique of considerable versatility. This versatility
is demonstrated by several examples, such as the imaging of nanometric-scale features in mammalian tissue sections and the creation of ultrasmall,
magneto-optic domains having implications for high density data storage.
Although the technique may find uses in many diverse fields, two of the
most exciting possibilities are localized optical spectroscopy of semiconductors
and the fluorescence imaging of living cells.

Imaging Intracellular Fluorescent Proteins at Nanometer Resolution

 E Betzig1,2,*,†, GH. Patterson3, R Sougrat3, O.W Lindwasser3,
S Olenych4, JS. Bonifacino3, MW. Davidson4, JL Schwartz3, HF. Hess5,*  1 Howard Hughes Medical Institute, Janelia Farm Research Campus,
Ashburn, VA   2 New Millennium Research, LLC, Okemos, MI.   3 Cell Biology and Metabolism Branch, National Institute of Child Health
and Human Development (NICHD), Bethesda, MD.  4 National High
Magnetic Field Laboratory, Florida State University, Tallahassee, FL.
5 NuQuest Research, LLC, La Jolla, CA.
Science 15 Sep 2006; 313(5793): pp. 1642-1645
http://dx.doi.org:/10.1126/science.1127344

We introduce a method for optically imaging intracellular proteins at
nanometer spatial resolution. Numerous sparse subsets of photo-activatable fluorescent protein molecules were activated, localized
(to ∼2 to 25 nanometers), and then bleached. The
aggregate position information from all subsets was then assembled
into a super-resolution image. We used this method—termed photo-
activated localization microscopy to image specific target proteins
in thin sections of lysosomes and mitochondria; in fixed whole cells,
we imaged vinculin at focal adhesions, actin within a lamellipodium,
and the distribution of the retroviral protein Gag at the plasma
membrane.

Toward fluorescence nanoscopy.

Hell SW.   Author information 
Nat Biotechnol. 2003 Nov; 21(11):1347-55.
http://www.ncbi.nlm.nih.gov/pubmed/14595362

For more than a century, the resolution of focusing light microscopy
has been limited by diffraction to 180 nm in the focal plane and to
500 nm along the optic axis. Recently, microscopes have been
reported that provide three- to seven-fold improved axial
resolution in live cells. Moreover, a family of concepts has emerged
that overcomes the diffraction barrier altogether. Its first exponent,
stimulated emission depletion microscopy, has so far displayed a
resolution down to 28 nm. Relying on saturated optical transitions,
these concepts are limited only by the attainable saturation level.
As strong saturation should be feasible at low light intensities,
nanoscale imaging with focused light may be closer than ever.
PMID: 14595362

Far-field optical nanoscopy.

Hell SW.  Author information 
Science. 2007 May 25;316(5828):1153-8.
http://www.ncbi.nlm.nih.gov/pubmed/17525330

In 1873, Ernst Abbe discovered what was to become a well-known
paradigm: the inability of a lens-based optical microscope to
discern details that are closer together than half of the wavelength
for its most popular imaging mode, fluorescence microscopy, the
diffraction barrier is crumbling. Here, I discuss the physical concepts
that have pushed fluorescence microscopy to the nanoscale, once
the prerogative of electron and scanning probe microscopes. Initial
applications indicate that emergent far-field optical nanoscopy will
have a strong impact in the life sciences and in other areas benefiting
from nanoscale visualization.
PMID:  17525330

Imaging intracellular fluorescent proteins at nanometer resolution.

Betzig E1, Patterson GHSougrat RLindwasser OWOlenych S,
Bonifacino JSDavidson MWLippincott-Schwartz JHess HF.
Author information
Science. 2006 Sep 15;313(5793):1642-5. Epub 2006 Aug 10
http://www.ncbi.nlm.nih.gov/pubmed/16902090

We introduce a method for optically imaging intracellular proteins at
nanometer spatial resolution. Numerous sparse subsets of photo-ctivatable fluorescent protein molecules were activated, localized
(to approximately 2 to 25 nanometers), and then bleached. The
aggregate position information from all subsets was then assembled
into a super-resolution image. We used this method–termed photo-activated localization microscopy–to image specific target proteins in
thin sections of lysosomes and mitochondria; in fixed whole cells,
we imaged vinculin at focal adhesions, actin within a lamellipodium,
and the distribution of the retroviral protein Gag at the plasma
membrane.

Comment in

PMID:  16902090  [PubMed – indexed for MEDLINE]

Illuminating single molecules in condensed matter.

Moerner WE1, Orrit M.  Author information 
Science. 1999 Mar 12;283(5408):1670-6.
http://www.ncbi.nlm.nih.gov/pubmed/10073924

Efficient collection and detection of fluorescence coupled with careful
minimization of background from impurities and Raman scattering
now enable routine optical microscopy and study of single molecules
in complex condensed matter environments. This ultimate method
for unraveling ensemble averages leads to the observation of
new effects and to direct measurements of stochastic fluctuations.
Experiments at cryogenic temperatures open new directions in
molecular spectroscopy, quantum optics, and solid-state dynamics.
Room-emperature investigations apply several techniques
(polarization microscopy, single-molecule imaging, emission time
dependence, energy transfer, lifetime studies, and the like) to a
growing array of biophysical problems where new insight may be
gained from direct observations of hidden static and dynamic
inhomogeneity.  PMID: 10073924

Fluorescence microscopy with super-resolved optical sections.

Egner A1, Hell SW.  Author information 
Trends Cell Biol. 2005 Apr;15(4):207-15.
http://www.ncbi.nlm.nih.gov/pubmed/15817377

The fluorescence microscope, especially its confocal variant, has
become a standard tool in cell biology research for delivering
3D-images of intact cells. However, the resolution of any standard
optical microscope is atleast 3 times poorer along the axis of the
lens that in its focal plane. Here, we review principles and applications
of an emerging family of fluorescence microscopes, such as 4Pi
microscopes, which improve axial resolution by a factor of seven by
employing two opposing lenses. Noninvasive axial sections of 80-160 nm
thickness deliver more faithful 3D-images of subcellular features,
providing a new opportunity to significantly enhance our understanding
of cellular structure and function. PMID: 15817377

4Pi-confocal microscopy provides three-dimensional images of the
microtubule network with 100- to 150-nm resolution.

Nagorni M1, Hell SW.  Author information 
J Struct Biol. 1998 Nov;123(3):236-47.

We show the applicability of 4Pi-confocal microscopy to three-dimensional imaging of the microtubule network in a fixed mouse
fibroblast cell.Comparison with two-photon confocal resolution
reveals a fourfold better axial resolution in the 4Pi-confocal case.
By combining 4Pi-confocal microscopy with Richardson-Lucy
image restoration a further resolution increase is achieved.
Featuring a three-dimensional resolution in the range 100-150 nm,
the 4Pi-confocal (restored) images are intrinsically more detailed
than their confocal counterparts. Our images constitute what
to our knowledge are the best-resolved three-dimensional
images of entangled cellular microtubules obtained with light
to date.  PMID: 9878578

Part IV. Super-resolution microscopy

Super-resolution microscopy is a form of light microscopy. Due
to the diffraction of light, the resolution of conventional light
microscopy is limited as stated by Ernst Abbe in 1873.[1]
A good approximation of the resolution attainable is the full
width at half maximum 
 (FWHM) of the point spread function,
and a precise wide-field microscope with high numerical
aperture
 and visible light usually reaches a resolution of ~250 nm.

Super-resolution techniques allow the capture of images with
a higher resolution than the diffraction limit. They fall into
two broad categories,
“true” super-resolution techniques, which capture information
contained in evanescent waves, and “functional” super-
resolution techniques, which use clever experimental
techniques and known limitations on the matter being
imaged to reconstruct a super-resolution image.[2]

True subwavelength imaging techniques include those that
utilize the Pendry Superlens and near field scanning optical
microscopy
, the 4Pi Microscope and structured illumination
microscopy technologies like SIM and SMI. However, the
majority of techniques of importance in biological imaging
fall into the functional category.

Groups of methods for functional super-resolution microscopy:

  1. Deterministic super-resolution: The most commonly used emitters in biological
    microscopy, fluorophores, show a nonlinear response to excitation, and this
    nonlinear response can be exploited to enhance resolution. These
    methods include STEDGSDRESOLFTand SSIM.
  2. Stochastic super-resolution: The chemical complexity of many molecular
    light sources gives them a complex temporal behaviour, which can be used
    to make several close-by fluorophores emit light at separate times and
    thereby become resolvable in time.  These methods include SOFI and all
    single-molecule localization methods (SMLM) such as SPDM,
    SPDMphymodPALM, FPALM, STORM and dSTORM.

Part V. HIV-1

Conformational dynamics of single HIV-1 envelope
trimers on the surface of native virions

James B. Munro1,*,Jason Gorman2Xiaochu Ma1,
Zhou Zhou3James Arthos4,
Dennis R. Burton5,6, et al.
1Department of Microbial Pathogenesis, Yale University
School of Medicine, New Haven, CT. 2Vaccine Research
Center, National Institute of Allergy and Infectious
Diseases, National Institutes of Health, Bethesda, MD .
3Department of Physiology and Biophysics, Weill
Cornell Medical College of Cornell University, New York, NY .
4Laboratory of Immunoregulation, National Institute of Allergy
and Infectious Diseases, National Institutes of Health, Bethesda,
MD . 5Department of Immunology and Microbial Science, and
IAVI Neutralizing Antibody Center, The Scripps Research
Institute, La Jolla, CA . 6Ragon Institute of MGH, MIT, and
Harvard, Cambridge, MA. 7International AIDS Vaccine Initiative
(IAVI), New York, NY . 8Department of
Chemistry, University of Pennsylvania, Philadelphia, PA.

The HIV-1 envelope (Env) mediates viral entry into host cells.
To enable the direct imaging of conformational dynamics
within Env we introduced fluorophores into variable
regions of the gp120 subunit and measured single-molecule
fluorescence resonance energy transfer (smFRET) within
the context of native trimers on the surface of HIV-1 virions.
Our observations revealed unliganded HIV-1 Env to be
intrinsically dynamic, transitioning between three distinct
pre-fusion conformations, whose relative occupancies
were remodeled by receptor CD4 and antibody binding.
The distinct properties of neutralization-sensitive and
neutralization-resistant HIV-1 isolates support a dynamics-based mechanism of immune evasion and ligand recognition.

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