In optical microscopy, fine structural details are resolved by using refraction to magnify images of a specimen. We discovered that by synthesizing a swellable polymer network within a specimen, it can be physically expanded, resulting in physical magnification. By covalently anchoring specific labels located within the specimen directly to the polymer network, labels spaced closer than the optical diffraction limit can be isotropically separated and optically resolved, a process we call expansion microscopy (ExM). Thus, this process can be used to perform scalable superresolution microscopy with diffraction-limited microscopes. We demonstrate ExM with apparent ~70-nanometer lateral resolution in both cultured cells and brain tissue, performing three-color superresolution imaging of ~107 cubic micrometers of the mouse hippocampus with a conventional confocal microscope.

Expansion microscopy (ExM) is a recently developed technique that enables nanoscale-resolution imaging of preserved cells and tissues on conventional diffraction-limited microscopes via isotropic physical expansion of the specimens before imaging. In ExM, biomolecules and/or fluorescent labels in the specimen are linked to a dense, expandable polymer matrix synthesized evenly throughout the specimen, which undergoes 3-dimensional expansion by ∼4.5 fold linearly when immersed in water. Since our first report, versions of ExM optimized for visualization of proteins, RNA, and other biomolecules have emerged. Here we describe best-practice, step-by-step ExM protocols for performing analysis of proteins (protein retention ExM, or proExM) as well as RNAs (expansion fluorescence in situ hybridization, or ExFISH), using chemicals and hardware found in a typical biology lab. Furthermore, a detailed protocol for handling and mounting expanded samples and for imaging them with confocal and light-sheet microscopes is provided. © 2018 by John Wiley & Sons, Inc.

Expansion microscopy (ExM) is a physical form of magnification that increases the effective resolving power of any microscope. Here, we describe the fundamental principles of ExM, as well as how recently developed ExM variants build upon and apply those principles. We examine applications of ExM in cell and developmental biology for the study of nanoscale structures as well as ExM's potential for scalable mapping of nanoscale structures across large sample volumes. Finally, we explore how the unique anchoring and hydrogel embedding properties enable postexpansion molecular interrogation in a purified chemical environment. ExM promises to play an important role complementary to emerging live-cell imaging techniques, because of its relative ease of adoption and modification and its compatibility with tissue specimens up to at least 200 μm thick. Expected final online publication date for the , Volume 35 is October 7, 2019. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Expansion microscopy (ExM) is an innovative approach to achieve super-resolution images without using super-resolution microscopes, based on the physical expansion of the sample. The advent of ExM has unlocked the detail of super-resolution images for a broader scientific circle, lowering the cost and entry skill requirements for the field. One of its branches, ultrastructure expansion microscopy (U-ExM), has become popular among research groups studying apicomplexan parasites, including the acute stage of Toxoplasma gondii infection. Here, we show that the chronic cyst-forming stage of Toxoplasma, however, resists U-ExM expansion, impeding precise protein localization. We then solve the in vitro cyst's resistance to denaturation required for successful U-ExM. As the cyst's main structural protein CST1 contains a mucin domain, we added an enzymatic digestion step using the pan-mucinase StcE prior to the expansion protocol. This allowed full expansion of the cysts in fibroblasts and primary neuronal cell culture without disrupting immunofluorescence analysis of parasite proteins. Using StcE-enhanced U-ExM, we clarified the localization of the GRA2 protein, which is important for establishing a normal cyst, observing GRA2 granules spanning across the CST1 cyst wall. The StcE-U-ExM protocol allows accurate pinpointing of proteins in the bradyzoite cyst, which will greatly facilitate investigation of the underlying biology of cyst formation and its vulnerabilities.

Determining the spatial organization and morphological characteristics of molecularly defined cell types is a major bottleneck for characterizing the architecture underpinning brain function. We developed Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to survey gene expression in brain tissue, as well as a turnkey computational pipeline to rapidly process large EASI-FISH image datasets. EASI-FISH was optimized for thick brain sections (300 µm) to facilitate reconstruction of spatio-molecular domains that generalize across brains. Using the EASI-FISH pipeline, we investigated the spatial distribution of dozens of molecularly defined cell types in the lateral hypothalamic area (LHA), a brain region with poorly defined anatomical organization. Mapping cell types in the LHA revealed nine novel spatially and molecularly defined subregions. EASI-FISH also facilitates iterative re-analysis of scRNA-Seq datasets to determine marker-genes that further dissociated spatial and morphological heterogeneity. The EASI-FISH pipeline democratizes mapping molecularly defined cell types, enabling discoveries about brain organization.

The excitability of individual dendritic branches is a plastic property of neurons. We found that experience in an enriched environment increased propagation of dendritic Na(+) spikes in a subset of individual dendritic branches in rat hippocampal CA1 pyramidal neurons and that this effect was mainly mediated by localized downregulation of A-type K(+) channel function. Thus, dendritic plasticity might be used to store recent experience in individual branches of the dendritic arbor.

The hippocampus is critical for producing stable representations of familiar spaces. How these representations arise is poorly understood, largely because changes to hippocampal inputs have not been measured during spatial learning. Here, using intracellular recording, we monitored inputs and plasticity-inducing complex spikes (CSs) in CA1 neurons while mice explored novel and familiar virtual environments. Inputs driving place field spiking increased in amplitude - often suddenly - during novel environment exploration. However, these increases were not sustained in familiar environments. Rather, the spatial tuning of inputs became increasingly similar across repeated traversals of the environment with experience - both within fields and throughout the whole environment. In novel environments, CSs were not necessary for place field formation. Our findings support a model in which initial inhomogeneities in inputs are amplified to produce robust place field activity, then plasticity refines this representation into one with less strongly modulated, but more stable, inputs for long-term storage.

Synaptic plasticity in adult neural circuits may involve the strengthening or weakening of existing synapses as well as structural plasticity, including synapse formation and elimination. Indeed, long-term in vivo imaging studies are beginning to reveal the structural dynamics of neocortical neurons in the normal and injured adult brain. Although the overall cell-specific morphology of axons and dendrites, as well as of a subpopulation of small synaptic structures, are remarkably stable, there is increasing evidence that experience-dependent plasticity of specific circuits in the somatosensory and visual cortex involves cell type-specific structural plasticity: some boutons and dendritic spines appear and disappear, accompanied by synapse formation and elimination, respectively. This Review focuses on recent evidence for such structural forms of synaptic plasticity in the mammalian cortex and outlines open questions.

From 1980 to 1992, a series of influential papers reported on the discovery, genetics, and evolution of a periodic cycling of the interval between Drosophila male courtship song pulses. The molecular mechanisms underlying this periodicity were never described. To reinitiate investigation of this phenomenon, we previously performed automated segmentation of songs but failed to detect the proposed rhythm [Arthur BJ, et al. (2013) BMC Biol 11:11; Stern DL (2014) BMC Biol 12:38]. Kyriacou et al. [Kyriacou CP, et al. (2017) Proc Natl Acad Sci USA 114:1970-1975] report that we failed to detect song rhythms because (i) our flies did not sing enough and (ii) our segmenter did not identify many of the song pulses. Kyriacou et al. manually annotated a subset of our recordings and reported that two strains displayed rhythms with genotype-specific periodicity, in agreement with their original reports. We cannot replicate this finding and show that the manually annotated data, the original automatically segmented data, and a new dataset provide no evidence for either the existence of song rhythms or song periodicity differences between genotypes. Furthermore, we have reexamined our methods and analysis and find that our automated segmentation method was not biased to prevent detection of putative song periodicity. We conclude that there is no evidence for the existence of Drosophila courtship song rhythms.

Adult zebra finches require auditory feedback to maintain their songs. It has been proposed that the lateral magnocellular nucleus of the anterior nidopallium (LMAN) mediates song plasticity based on auditory feedback. In this model, neurons in LMAN, tuned to the spectral and temporal properties of the bird’s own song (BOS), are thought to compute the difference between the auditory feedback from the bird’s vocalizations and an internal song template. This error-correction signal is then used to initiate changes in the motor system that make future vocalizations a better match to the song template. This model was tested by recording from single LMAN neurons while manipulating the auditory feedback heard by singing birds. In contrast to the model predictions, LMAN spike patterns are insensitive to manipulations of auditory feedback. These results suggest that BOS tuning in LMAN is not used for error detection and constrain the nature of any error signal from LMAN to the motor system. Finally, LMAN neurons produce spikes locked precisely to the bird’s song, independent of the auditory feedback heard by the bird. This finding suggests that a large portion of the input to this nucleus is from the motor control signals that generate the song rather than from auditory feedback.