Abstract:Time lapse fluorescence imaging has become one of the most important approaches in neurobiological research. In particular, both confocal and two-photon microscopy have been used to study activity-dependent changes in synaptic morphology. However, the diffraction-limited resolution of light microscopy is often inadequate, forcing researchers to complement the live cell imaging strategy by EM. Here, we report on the first use of a far-field optical technique with subdiffraction resolution to noninvasively image… Show more
“…This illustrates a physical limitation of traditional diffraction-limited microscopy that can only be cured by reducing the size of the PSF, e.g. by STED microscopy (Nägerl et al, 2008;Takasaki et al, 2008;Testa et al, 2012). In the real 2PM images of the same dendritic section, recall was comparable, but several false-positive spines were detected in the background (low precision, Fig.…”
Highlights Spine tracking over time using statistical models and probability maps Correlative two-photon/electron microscopy datasets used for benchmarking Analysis of spine orientation and detection precision in organotypic slice culture Application 1: Automatic identification of synaptically connected spines Application 2: Automatic analysis of organelle motility in spines
AbstractDendritic spines may be tiny in volume, but are of major importance for neuroscience. They are the main receivers for excitatory synaptic connections, and their constant changes in number and in shape reflect the dynamic connectivity of the brain. Two-photon microscopy allows following the fate of individual spines in brain slice preparations and in live animals. The diffraction-limited and non-isotropic resolution of this technique, however, makes detection of such tiny structures rather challenging, especially along the optical axis (z-direction). Here we present a novel spine detection algorithm based on a statistical dendrite intensity model and a corresponding spine probability model. To quantify the fidelity of spine detection, we generated correlative datasets: Following twophoton imaging of live pyramidal cell dendrites, we used serial block-face scanning electron microscopy (SBEM) to reconstruct dendritic ultrastructure in 3D. Statistical models were trained on synthetic fluorescence images generated from SBEM datasets via point spread function (PSF) convolution. After the training period, we tested automatic spine detection on real two-photon datasets and compared the result to ground truth (correlative SBEM data). The performance of our algorithm allowed tracking changes in spine volume automatically over several hours. Using a second fluorescent protein targeted to the endoplasmic reticulum, we could analyze the motion of this organelle inside individual spines. Furthermore, we show that it is possible to distinguish activated spines from non-stimulated neighbors by detection of fluorescently labeled presynaptic vesicle clusters. These examples illustrate how automatic segmentation in 5D (x, y, z, t, λ) allows us to investigate brain dynamics at the level of individual synaptic connections.
“…This illustrates a physical limitation of traditional diffraction-limited microscopy that can only be cured by reducing the size of the PSF, e.g. by STED microscopy (Nägerl et al, 2008;Takasaki et al, 2008;Testa et al, 2012). In the real 2PM images of the same dendritic section, recall was comparable, but several false-positive spines were detected in the background (low precision, Fig.…”
Highlights Spine tracking over time using statistical models and probability maps Correlative two-photon/electron microscopy datasets used for benchmarking Analysis of spine orientation and detection precision in organotypic slice culture Application 1: Automatic identification of synaptically connected spines Application 2: Automatic analysis of organelle motility in spines
AbstractDendritic spines may be tiny in volume, but are of major importance for neuroscience. They are the main receivers for excitatory synaptic connections, and their constant changes in number and in shape reflect the dynamic connectivity of the brain. Two-photon microscopy allows following the fate of individual spines in brain slice preparations and in live animals. The diffraction-limited and non-isotropic resolution of this technique, however, makes detection of such tiny structures rather challenging, especially along the optical axis (z-direction). Here we present a novel spine detection algorithm based on a statistical dendrite intensity model and a corresponding spine probability model. To quantify the fidelity of spine detection, we generated correlative datasets: Following twophoton imaging of live pyramidal cell dendrites, we used serial block-face scanning electron microscopy (SBEM) to reconstruct dendritic ultrastructure in 3D. Statistical models were trained on synthetic fluorescence images generated from SBEM datasets via point spread function (PSF) convolution. After the training period, we tested automatic spine detection on real two-photon datasets and compared the result to ground truth (correlative SBEM data). The performance of our algorithm allowed tracking changes in spine volume automatically over several hours. Using a second fluorescent protein targeted to the endoplasmic reticulum, we could analyze the motion of this organelle inside individual spines. Furthermore, we show that it is possible to distinguish activated spines from non-stimulated neighbors by detection of fluorescently labeled presynaptic vesicle clusters. These examples illustrate how automatic segmentation in 5D (x, y, z, t, λ) allows us to investigate brain dynamics at the level of individual synaptic connections.
“…STED imaging can be performed on fusion constructs of fluorescent proteins that also span most of the visible spectrum: green (GFP [112]), yellow (YFP [113] and citrine [114]) and far-red emitting proteins (TagRFP657 [115] and the tetrametric E2-Crimson [116]). Several reversible photoswitchable proteins have also been demonstrated suitable for RESOLFT imaging, exploiting their reversible switching behaviour to deplete the periphery of the focal spot (Dronpa and its counterpart Padron derivative [15,22], rsEGFP2 [23] and Dreiklang [117]).…”
Section: Fluorescent Probes For Sted Imagingmentioning
confidence: 99%
“…Super-resolution of fixed brain sections is also feasible: The morphological plasticity of dendritic spines in living brain slices has been described using YFP as a volume label with time-lapse STED microscopy [113].…”
Fluorescence nanoscopy refers to the experimental techniques and analytical methods used for fluorescence imaging at a resolution higher than conventional, diffractionlimited, microscopy. This review explains the concepts behind fluorescence nanoscopy and focuses on the latest and promising developments in acquisition techniques, labelling strategies to obtain highly detailed super-resolved images and in the quantitative methods to extract meaningful information from them.
“…Simons's originally controversial theory, proposed in 1988 , held that certain lipids and proteins in a cell membrane form temporary clumps to, for example, facilitate the transmission of signals across the membrane 4 . But the proposed rafts would have been as small as 30 nanometres in diameter -invisible until STED microscopy came along.…”
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