Hierarchical imaging: a new concept for targeted imaging of large volumes from cells to tissues.

BACKGROUND: Imaging large volumes such as entire cells or small model organisms at nanoscale resolution seemed an unrealistic, rather tedious task so far. Now, technical advances have lead to several electron microscopy (EM) large volume imaging techniques. One is array tomography, where ribbons of ultrathin serial sections are deposited on solid substrates like silicon wafers or glass coverslips. RESULTS: To ensure reliable retrieval of multiple ribbons from the boat of a diamond knife we introduce a substrate holder with 7 axes of translation or rotation specifically designed for that purpose. With this device we are able to deposit hundreds of sections in an ordered way in an area of 22 × 22 mm, the size of a coverslip. Imaging such arrays in a standard wide field fluorescence microscope produces reconstructions with 200 nm lateral resolution and 100 nm (the section thickness) resolution in z. By hierarchical imaging cascades in the scanning electron microscope (SEM), using a new software platform, we can address volumes from single cells to complete organs. In our first example, a cell population isolated from zebrafish spleen, we characterize different cell types according to their organelle inventory by segmenting 3D reconstructions of complete cells imaged with nanoscale resolution. In addition, by screening large numbers of cells at decreased resolution we can define the percentage at which different cell types are present in our preparation. With the second example, the root tip of cress, we illustrate how combining information from intermediate resolution data with high resolution data from selected regions of interest can drastically reduce the amount of data that has to be recorded. By imaging only the interesting parts of a sample considerably less data need to be stored, handled and eventually analysed. CONCLUSIONS: Our custom-designed substrate holder allows reproducible generation of section libraries, which can then be imaged in a hierarchical way. We demonstrate, that EM volume data at different levels of resolution can yield comprehensive information, including statistics, morphology and organization of cells and tissue. We predict, that hierarchical imaging will be a first step in tackling the big data issue inevitably connected with volume EM.

Array tomography: characterizing FAC-sorted populations of zebrafish immune cells by their 3D ultrastructure.

For 3D reconstructions of whole immune cells from zebrafish, isolated from adult animals by FAC-sorting we employed array tomography on hundreds of serial sections deposited on silicon wafers. Image stacks were either recorded manually or automatically with the newly released ZEISS Atlas 5 Array Tomography platform on a Zeiss FEGSEM. To characterize different populations of immune cells, organelle inventories were created by segmenting individual cells. In addition, arrays were used for quantification of cell populations with respect to the various cell types they contained. The detection of immunological synapses in cocultures of cell populations from thymus or WKM with cancer cells helped to identify the cytotoxic nature of these cells. Our results demonstrate the practicality and benefit of AT for high-throughput ultrastructural imaging of substantial volumes.

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes.

Targeting specific cells at ultrastructural resolution within a mixed cell population or a tissue can be achieved by hierarchical imaging using a combination of light and electron microscopy. Samples embedded in resin are sectioned into arrays consisting of ribbons of hundreds of ultrathin sections and deposited on pieces of silicon wafer or conductively coated coverslips. Arrays are imaged at low resolution using a digital consumer like smartphone camera or light microscope (LM) for a rapid large area overview, or a wide field fluorescence microscope (fluorescence light microscopy (FLM)) after labeling with fluorophores. After post-staining with heavy metals, arrays are imaged in a scanning electron microscope (SEM). Selection of targets is possible from 3D reconstructions generated by FLM or from 3D reconstructions made from the SEM image stacks at intermediate resolution if no fluorescent markers are available. For ultrastructural analysis, selected targets are finally recorded in the SEM at high-resolution (a few nanometer image pixels). A ribbon-handling tool that can be retrofitted to any ultramicrotome is demonstrated. It helps with array production and substrate removal from the sectioning knife boat. A software platform that allows automated imaging of arrays in the SEM is discussed. Compared to other methods generating large volume EM data, such as serial block-face SEM (SBF-SEM) or focused ion beam SEM (FIB-SEM), this approach has two major advantages: (1) The resin-embedded sample is conserved, albeit in a sliced-up version. It can be stained in different ways and imaged with different resolutions. (2) As the sections can be post-stained, it is not necessary to use samples strongly block-stained with heavy metals to introduce contrast for SEM imaging or render the tissue blocks conductive. This makes the method applicable to a wide variety of materials and biological questions. Particularly prefixed materials e.g., from biopsy banks and pathology labs, can directly be embedded and reconstructed in 3D.

High-throughput screening of zebrafish embryos using automated heart detection and imaging.

Over the past decade, the zebrafish has become a key model organism in genetic screenings and drug discovery. A number of genes have been identified to affect the development of the shape and functioning of the heart, leading to zebrafish mutants with heart defects. The development of semiautomated microscopy systems has allowed for the investigation of drugs that reverse a disease phenotype on a larger scale. However, there is a lack of automated feature detection, and commercially available computer-aided microscopes are expensive. Screening of the zebrafish heart for drug discovery typically includes the identification of heart parameters, such as the frequency or fractional shortening. Until now, screening processes have been characterized by manual handling of the larvae and manual microscopy. Here, an intelligent robotic microscope is presented, which automatically identifies the orientation of a zebrafish in a micro well. A predefined region of interest, such as the heart, is detected automatically, and a video with higher magnification is recorded. Screening of a 96-well plate takes 35 to 55 min, depending on the length of the videos. Of the zebrafish hearts, 75% are recorded accurately without any user interaction. A description of the system, including the graphical user interface, is given.