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Correlative immuno Light Electron Microscopy ( CLEM ) of subcellular compartments

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Correlative light and electron microscopy (CLEM) methods integrate light and electron microscopy on a single sample, literally bridging the gap between these two microscopy techniques. Most methods use fluorescent microscopy of thin or semi‐thin sections to define a region‐of‐interest, which then is traced back in the EM to provide subcellular context information (e.g. membrane organization, non‐labeled surroundings of the fluorescent structure). The most powerful application of CLEM is correlative live cell imaging‐EM, by which dynamic information is inferred to structures seen in static EM pictures. By merging the strengths of the two techniques a novel and integrated type of image is created that combines parameters that cannot ‐ or not easily ‐ be obtained when using separate images of related events. However, because imaging requirements are intrinsically different between light and electron microscopy, creating conditions that are ideal for both modalities is a challenging process. Moreover, correlating fluorescent labeling to the cellular architecture seen in the EM is not always straightforward. The most pressing challenges in CLEM are currently therefore 1. development of sample preparation methods that are appropriate for both LM and EM imaging. 2. development of bi‐modal probes that are visible in both LM and EM and 3. development of software that allows for rapid and accurate correlation of LM and EM images. The focus of our research is to develop new probes and CLEM pipelines that allow us to efficiently and with high accuracy define the three‐dimensional (3D) ultrastructural context of fluorescently‐tagged proteins previously localized in fixed or living cells. We apply our technologies to study the cellular pathways and mechanisms that control the cell's digestive system – i.e. the endo‐lysosomal system ‐ in health and disease conditions. The main CLEM technology that we use in the lab is based on the use of immunogold labeling of ultrathin cryosections (the Tokuyasu technique) [1]. Most CLEM approaches, however, are restricted in their EM approach by the lack of 3D structural information. To overcome this limitation, we apply Focused Ion Beam Scanning Electron Microscopy (FIB‐SEM) as 3D‐EM approach in a live cell‐CLEM set up. To visualize endo‐lysosomes in live cells we combine fluorescent tagged endo‐lysosomal proteins (such as LAMP1‐mGFP) with endocytic tracers (such as fluorescently labeled dextran). This approach enables live‐cell tracking of specific endo‐lysosomal compartments, after which the samples are fixed, stained and resin‐embedded for FIB‐SEM imaging. Figure 1 presents an example of Dextran‐Alexa646 and/or LAMP1‐mGFP labeled endo‐lysosomal compartments in live cells (A) and in 3D‐EM (D), providing the cellular context at ultrastructural resolution. In my presentation I will show various examples of both immunoEM and FIB.SEM‐based CLEM approaches, which are designed to optimally image individual, membrane‐bounded compartments.
Title: Correlative immuno Light Electron Microscopy ( CLEM ) of subcellular compartments
Description:
Correlative light and electron microscopy (CLEM) methods integrate light and electron microscopy on a single sample, literally bridging the gap between these two microscopy techniques.
Most methods use fluorescent microscopy of thin or semi‐thin sections to define a region‐of‐interest, which then is traced back in the EM to provide subcellular context information (e.
g.
membrane organization, non‐labeled surroundings of the fluorescent structure).
The most powerful application of CLEM is correlative live cell imaging‐EM, by which dynamic information is inferred to structures seen in static EM pictures.
By merging the strengths of the two techniques a novel and integrated type of image is created that combines parameters that cannot ‐ or not easily ‐ be obtained when using separate images of related events.
However, because imaging requirements are intrinsically different between light and electron microscopy, creating conditions that are ideal for both modalities is a challenging process.
Moreover, correlating fluorescent labeling to the cellular architecture seen in the EM is not always straightforward.
The most pressing challenges in CLEM are currently therefore 1.
development of sample preparation methods that are appropriate for both LM and EM imaging.
2.
development of bi‐modal probes that are visible in both LM and EM and 3.
development of software that allows for rapid and accurate correlation of LM and EM images.
The focus of our research is to develop new probes and CLEM pipelines that allow us to efficiently and with high accuracy define the three‐dimensional (3D) ultrastructural context of fluorescently‐tagged proteins previously localized in fixed or living cells.
We apply our technologies to study the cellular pathways and mechanisms that control the cell's digestive system – i.
e.
the endo‐lysosomal system ‐ in health and disease conditions.
The main CLEM technology that we use in the lab is based on the use of immunogold labeling of ultrathin cryosections (the Tokuyasu technique) [1].
Most CLEM approaches, however, are restricted in their EM approach by the lack of 3D structural information.
To overcome this limitation, we apply Focused Ion Beam Scanning Electron Microscopy (FIB‐SEM) as 3D‐EM approach in a live cell‐CLEM set up.
To visualize endo‐lysosomes in live cells we combine fluorescent tagged endo‐lysosomal proteins (such as LAMP1‐mGFP) with endocytic tracers (such as fluorescently labeled dextran).
This approach enables live‐cell tracking of specific endo‐lysosomal compartments, after which the samples are fixed, stained and resin‐embedded for FIB‐SEM imaging.
Figure 1 presents an example of Dextran‐Alexa646 and/or LAMP1‐mGFP labeled endo‐lysosomal compartments in live cells (A) and in 3D‐EM (D), providing the cellular context at ultrastructural resolution.
In my presentation I will show various examples of both immunoEM and FIB.
SEM‐based CLEM approaches, which are designed to optimally image individual, membrane‐bounded compartments.

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