Technical Setup of the PALM Micro Beam System

1.2.1. RoboMover and RoboStage II

A fully robotic unit called RoboMover functions as a multipurpose collection device, with adapters for routine microfuge tubes, multicap strips, and microtiter plate formats. Guided by the entries in the element list (Fig. 5; see Color Plate 4 following p.18.), complex experimental setups can be planned and processed automatically. The highly automated sample capture device is supported by the second generation of RoboStage. This newly developed microscope stage can travel large distances in x/y directions with high-accuracy relocation of selected areas, and allows collection of samples from various object dishes fitting into versatile customized holders like PALM DuplexDishes, Membrane-Slides, microtiter plate formats, and so on. Successful sample capture can easily be controlled using the so-called cap-check function of the RoboStage II. This fully automated generation of samples by the noncontact LMPC process for subsequent analyses vastly increases the throughput in routine and research laboratories.

A special software feature allows linking of similar regions of serial sections of a sample on different slides at the same time. Here, on the source slide (i.e., first slide), areas of interest can be outlined by the user and matched to the linked subset of the following serial sections (i.e., destination slides). The selected areas are individually addressed and adjusted to their actual shape, which may differ owing to torsions occurring during sectioning. By staining only the source slide and leaving the destination slides unstained, it becomes possible to recover unaltered proteins for further downstream proteomic analysis.

1.2.2. PALM RoboSoftware for Automated Microdissection and Catapulting

The controlling software of the PALM MicroBeam system is the so-called RoboSoftware, which manages the motion of the motorized microscope, the motorized microscope stage, the RoboMover capture device, and the optional fluorescence equipment. An intuitive graphical user interface for all software functions facilitates the use of this system. The RoboSoftware includes automated process routines as well as additional functions: a wide palette of drawing tools for marking the incision path in a preselected mode allows the outlining and color coding of independent target areas all over the entire slide or even from different slides after serial sectioning. These selected target areas are listed in an element list protocol, which allows target grouping and experimental scheduling. The list of elements (Fig. 5, lower right) is the main tool for summary and display of the outlined samples and corresponding area measures, the color-dependent sorting of the outlined areas, and laser activation. Choosing from the color chart, the computer will microdissect and/or catapult only elements with the designated color. Saving of the selected elements with respect to a reference position in personal files allows the relocation of the stored elements on each individual slide. Thus the slide can be taken out for later sample capture.

Noncontact laser microdissection and catapulting, as realized in PALM MicroBeam-HT, allows the largely automated and highly reliable capture of thousands of cells within a short time, thus allowing higher throughput specimen sampling, which is especially important for array techniques or proteomic studies (Fig. 1).

1.2.3. Automated Cell Recognition

Modern detection methods are often based on fluorescence techniques. Thus the PALM MicroBeam can optionally be equipped with features for fluorescence microscopy, allowing simultaneous fluorescence observation and LMPC. The high degree of automation realized in the latest generation of PALM systems (MicroBeam-HT) can be optionally augmented by image-analyzing software modules allowing automated fast scanning functions for specimen identification and image processing. Both fluorescence and bright field microscopy can be used for automated detection of cells or regions of interest. Coupled with any one of these software modules, the MicroBeam system is able to scan, detect, isolate, and finally capture the specimen of interest, e.g., immunostained areas (Fig. 6A; See Color Plate 6 following p.18.), metaphases, or fluorescent-labeled rare cells (Fig. 6B), in a fully automated manner. Recognized areas can subsequently be extracted automatically by the appropriate laser function. These versatile automated scanning software modules also have the advantage of fast and reliable detection and autoevaluation of particular cells, cell components or chromosomes, based on either optimized classifiers or rule sets by means of morphological

Fig. 6. (Top) Automatic recognition of defined sample. Left, Immunostained section of murine colon. Middle left, Autodetected crypt-containing areas. Middle right, Outlining of autodetected immunopositive tissue areas. Right, Generation of shape files for LMPC processing. (Bottom) Automatic detection of fluorescent-labeled samples. Integrated image analysis software provides unique high-performance slide scanning capacities with different modular concepts for the automated detection of, e.g., metaphases (left) and rare cells (right). LMPC, Laser microdissection and catapulting. (See Color Plate 5 and 6 following p.18.)

Fig. 6. (Top) Automatic recognition of defined sample. Left, Immunostained section of murine colon. Middle left, Autodetected crypt-containing areas. Middle right, Outlining of autodetected immunopositive tissue areas. Right, Generation of shape files for LMPC processing. (Bottom) Automatic detection of fluorescent-labeled samples. Integrated image analysis software provides unique high-performance slide scanning capacities with different modular concepts for the automated detection of, e.g., metaphases (left) and rare cells (right). LMPC, Laser microdissection and catapulting. (See Color Plate 5 and 6 following p.18.)

phenotypes. The efficient detection algorithms are trained by P.A.L.M. Microlaser Technologies to achieve integrated, interactive classifiers and rule sets for optimized recognition and accurate results.

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