H. Piyadasa was supported by the Canadian Institutes of Health Research (CIHR) Fellowship (MFE-176490). B. Oberlton was supported by the National Science Foundation (NSF) Fellowship (2020298220). A. Tsai was supported by a Damon Runyon Cancer Research Foundation (DRCRF) Fellowship (DRG-118-16), the Stanford Department of Pathology, the Annelies Gramberg Fund, and NIH 1U54HL165445-01. Additional acknowledgments go to Dr. Avery Lam, Dr. Davide Franchina, and Mako Goldston for helping to test and debug the program.

1. Loading of TSAI
<ol>
	<li>Run TSAI by opening&#160;https://tsai.stanford.edu/research/mibi_tsai in the web browser of the MIBI user control computer.
	<ol>
		<li>This instance of TSAI contains custom presets which do not apply to all instruments. When using it, build tiles only from template FOV(s) as generated&#160;below in step 2.6. TSAI runs locally within the web browser, and no image, .json, or file name data is sent to or stored on the server.</li>
	</ol>
	</li>
	<li>Alternatively, set up TSAI on any website with custom presets for any instrument.
	<ol>
		<li>Go to https://github.com/ag-tsai/mibi_tsai and download the mibi_tsai_standalone directory. Alternatively, download the&#160;Supplementary Coding File 1 .zip file and unzip the contents to a directory titled mibi_tsai_standalone.</li>
		<li>Open mibi_tsai_standalone/_resources/index.js in any text editor.</li>
		<li>If necessary, edit the FOV size, dwell time/timing choice, raster size, FOV JSON, and recommended preset settings in index.js to match the instrument&#39;s settings. This mainly applies to customized instruments, but dwell time/timing choice pairs should be checked regardless. Save index.js.</li>
		<li>Upload mibi_tsai_standalone to any web server accessible through the internet, e.g., a lab web site or university-hosted web site.</li>
		<li>Open mibi_tsai_standalone/index.html in the web browser of the MIBI user control computer.</li>
	</ol>
	</li>
</ol>
2. Loading the MIBI slide and creating a template file
<ol>
	<li>Log into the MIBI experiment tracker (manufacturer-provided web interface for managing scan-related metadata) in the web browser.</li>
	<li>In the Slides tab, add&#160;a new slide and add a new section (Supplementary Figure 2A-B). In the Resources tab, select or create a marker panel (Supplementary Figure 2C).</li>
	<li>In the Sections tab, add the new section to the panel (Supplementary Figure 2D).</li>
	<li>Log into the MIBI user control interface in the web browser. Load the MIBI slide by clicking Exchange Sample and selecting the new slide (Supplementary Figure 3A).</li>
	<li>Create a template FOV by clicking Add FOV (Supplementary Figure 3B) and setting the frame dimensions, FOV size, dwell time, imaging mode, and section ID.</li>
	<li>Export (download) the FOV list to a .json file (Supplementary Figure 3C). Download the optical image as a .png file (Supplementary Figure 3D).</li>
</ol>
3. Optical image-stage motor coregistration
<ol>
	<li>Open the TSAI web UI in the web browser. If coregistration has not been previously performed, the optical coregistration menu should open automatically. If it has been performed and is adequate, do not repeat these steps.</li>
	<li>Open the Optical Coregistration menu. Click Copy Automatic Coregistration Code to Clipboard (Supplementary Figure 4A).</li>
	<li>Open the MIBI user control interface in the web browser. Press Ctrl+Shift+J to open the browser console, or right-click on the page and click Inspect, then open the Console tab (Supplementary Figure 4B).</li>
	<li>Paste the code into the console and press Enter. Click the link generated in the console (Supplementary Figure 4C). This will load the coregistration into the TSAI web UI and save it as a cookie, so it persists and does not need to be repeated unless there is a change to the instrument hardware.</li>
</ol>
4. Tiled SED scan
<ol>
	<li>Load the optical image .png and .json files from step&#160;2.6&#160;by dragging and dropping them onto the TSAI web UI.</li>
	<li>Open the SED Tiler menu and click on a text box in the top row (Supplementary Figure 5A).</li>
	<li>Click (&#177;&#160;drag) on the optical image to select the top left corner for the SED scan (Supplementary Figure 5B).</li>
	<li>Press the D key or click on a text box in the second row in the SED Tiler menu.</li>
	<li>Click (&#177;&#8203;&#160;drag) on the optical image to select the bottom right corner for the SED scan.</li>
	<li>In the SED Tiler menu, click Copy SED Scan and Shift Correction Code to Clipboard (Supplementary Figure 5C).</li>
	<li>Open the MIBI user control interface in the web browser. Paste the code into the console and press Enter (Supplementary Figure 5D).</li>
	<li>Put the MIBI into SED mode on the QC - 300 &#181;m setting, move to an area that will not be acquired, and adjust the gain, focus, and stigmation.
	<ol>
		<li>Adjust the brightness and contrast of the SED image without changing the gain. Press B to increase the brightness or Shift+B to decrease it. Press C to increase the contrast or Shift+C to decrease it. Press Shift+V to reset both the brightness and contrast.</li>
	</ol>
	</li>
	<li>Press Shift+T to start the tiled SED scan.</li>
	<li>When finished, it should automatically save a new .png file of the tiled SED image (Figure 3). Characters may be added to the beginning of the file name but do not modify any other part of the file name.</li>
	<li>If specific tiles are out of focus or otherwise improperly scanned, rescan them.
	<ol>
		<li>Press Shift+R to add a tile to the rescan queue. A dialog box will open, prompting the user for the row and column of the tile. The numbers are zero-indexed, thus entering 8,0 queues the ninth row, the first column.</li>
		<li>After adding all the relevant tiles to the queue, press Shift+T to rescan. When finished, it should automatically save a new .png file of the tiled SED image.</li>
	</ol>
	</li>
	<li>Critical step: Inspect the tiled SED scan for large misalignments (Figure 3C-D). If present, contact manufacturer support to adjust the motor and imaging beam or attempt manual software correction using the keyboard controls in steps 4.12.1 to 4.12.9 (Supplementary Figure 6A).
	<ol>
		<li>To check SED-stage motor alignment, move to an area of the slide without tissue. Press Shift+5 to burn five 400 &#181;m FOVs in a checkerboard pattern (Supplementary Figure 6B-C) or Shift+9 to burn a 3 x 3 pattern of 400 &#181;m FOVs (Supplementary Figure 6D-E).</li>
		<li>If the FOV columns are too far apart, press 1 and set the x f(x) value to a negative decimal, typically between -0.0025 and -0.1.</li>
		<li>If the third-row FOVs are shifted leftward relative to the first-row FOVs, press 2 and set the x f(y) value to a positive decimal, typically between 0.0025 and 0.1.</li>
		<li>If the third column FOVs are shifted downward relative to the first column FOVs, press 3 and set the y f(x) value to a negative decimal, typically between -0.0025 and -0.1.</li>
		<li>If the FOV rows are too far apart, press 4 and set the y f(y) value to a negative decimal, typically between -0.0025 and -0.1.</li>
		<li>Iteratively repeat steps 4.12.1 to 4.12.5 until the checkerboard and 3 x 3 patterns form a roughly straight grid (Supplementary Figure 6C, E).</li>
		<li>Press S to save a .png image of the pattern with the correction values in the file name.</li>
		<li>Drag and drop this .png file onto the TSAI web UI to load the values and save them to the browser cookie.</li>
		<li>Perform tiled SED scans to check the coefficients. Based upon the same principles as in steps 4.12.2 to 4.12.5, make further adjustments to the coefficients to correct any misalignments in the tiled SED images.</li>
	</ol>
	</li>
	<li>If the tiled SED is adequate, press Escape. Return to the TSAI web UI.</li>
	<li>Drag and drop the tiled SED .png file onto the TSAI web UI (Supplementary Figure 5E).</li>
	<li>Click on the SED tab and adjust the zoom (Supplementary Figure 5F).</li>
	<li>To adjust image brightness and contrast and/or drawing options such as line thickness and cursor size, use the slide options menu above the SED image.</li>
	<li>Keyboard shortcuts are available and most shown next to the image controls: Press Z to zoom in and Shift+Z to zoom out. Press B to increase brightness or Shift+B to decrease it. Press C to increase contrast or Shift+C to decrease it. Press Shift+V to reset both the brightness and contrast. Press L to toggle labels above the tiles. Press O to toggle 5 mm radius circles drawn around focus sites.</li>
</ol>
5. Tissue microarray (TMA)
<ol>
	<li>If setting FOVs for a grid of TMA spots, first set the pattern of FOVs to be replicated. In the relevant tile of the Tiles column, adjust the columns and rows (Figure 4A) and check/uncheck the boxes in the map (Figure 4B), as well as adjusting other FOV settings as necessary.</li>
	<li>In the relevant tile, click TMA to open the TMA options menu (Figure 4C). Set the number of rows and columns of TMA spots (Figure 4D). If necessary, add a naming prefix (Figure 4E) and edit the starting row and column numbering (Figure 4F).</li>
	<li>On the slide image, click on the four corners of the TMA (Figure 4G-J). Click and drag the circled corners to adjust the positioning of the crosshairs so they best match the TMA spots.</li>
	<li>Click Build TMA from the TMA options menu (Figure 4K).</li>
	<li>Hover over each tile in the tiles column to check its positioning. To adjust, click Move (Figure 4L). Then click and drag on the slide image or press the keyboard arrow keys.
	<ol>
		<li>Hold the Shift key while pressing arrow keys to move a farther distance. Hold the Alt (Windows) or Opt (Mac) key while pressing arrow keys to move a shorter distance.</li>
		<li>When move is selected, press T to uncheck the checkbox next to the tile name, remove it from view, and omit it from any subsequently generated .json files. Alternatively, uncheck the checkbox directly with the mouse (Figure 4M) or remove it entirely by clicking Delete.</li>
		<li>When move is selected, press 2, 4, or 8 to set the FOV size to 200 &#181;m, 400 &#181;m, or 800 &#181;m, respectively, and the raster dimensions will be scaled proportionately such that the imaging resolution remains unchanged.</li>
		<li>When move is selected, press A to go to the previous tile or&#160;press D to go to the next tile.</li>
		<li>To adjust other tile settings, click&#160;the&#160;&#8801; button to expand the settings menu if it is not visible.</li>
	</ol>
	</li>
</ol>
6. Area/polygon tile
<ol>
	<li>If setting FOVs to cover a contiguous area of tissue, first adjust FOV settings as necessary in the relevant tile of the Tiles&#160;column.</li>
	<li>In the relevant tile, click Polygon (Figure 5A). Click on the slide image to set the vertices/corners of the area to be tiled (Figure 5B-C). Double-click to close the polygon and cover the area with FOVs (Figure 5D).</li>
	<li>Scroll to the bottom of the Tiles&#160;column and click the&#160;&#8801; button (^ when expanded, Figure 5E) in the new polygon tile to see the tile map.</li>
	<li>Toggle individual tiles ON or OFF by clicking on the tile map (Figure 5F), or by clicking Clicker (Figure 5G) and clicking on the tiled FOVs in the slide image.</li>
	<li>To toggle off multiple FOVs, click on Eraser and then click and drag on the tiled FOVs in the slide image (Figure 5H).</li>
	<li>To toggle on multiple FOVs, click on Clicker (Figure 5G) and then click and drag on the empty areas in the slide image covered by the tile map.</li>
	<li>To insert the rows above, click the &#9650; button (Figure 5I). To insert columns to the left, click the &#9668; button (Figure 5J).</li>
	<li>To adjust tile positioning, click Move (Figure 5K). Then click and drag on the slide image, press the keyboard Arrow keys, or use other controls described in steps 5.5.1 to 5.5.5.</li>
</ol>
7. FOV navigation and adjustment
<ol>
	<li>If SED tiling is misaligned or the optical image crosshair does not reflect the actual stage motor position, adjust FOV positions in SED mode in the MIBI user control interface with the aid of the below keyboard controls.</li>
	<li>Open the FOV navigation/adjustment menu below the slide (optical or SED) image. Click Copy FOV Navigation Code to Clipboard.</li>
	<li>Open the MIBI user control interface in the web browser. Put the MIBI into SED mode and adjust the gain, focus, and stigmation.</li>
	<li>Press Ctrl+Shift+J to open the browser console, or right-click on the page and click Inspect, then open the Console tab.</li>
	<li>Paste the code into the console and press Enter. The code will automatically navigate to the first FOV and the exact FOV positioning displayed in the SED image of the MIBI user control interface.</li>
	<li>Adjust the brightness and contrast of the SED image without changing the gain. Press B to increase the brightness or Shift+B to decrease it. Press C to increase the contrast or Shift+C to decrease it. Press Shift+V to reset both the brightness and contrast.</li>
	<li>To adjust the SED magnification, press M (200 &#181;m), , (400 &#181;m), . (800 &#181;m), or / (maximum) keys.</li>
	<li>To move the FOV, press the keyboard Arrow keys. Save the position by pressing W. Hold the Shift key while pressing arrow keys to move a farther distance. Hold the Alt (Windows) or Opt (Mac) key while pressing arrow keys to move a shorter distance. Note that only R1C1 of any given tile can be moved.</li>
	<li>To toggle an FOV ON or OFF, press T. To change the FOV size, press 2 (200 &#181;m), 4 (400 &#181;m), or 8 (800 &#181;m). The raster dimensions will be scaled proportionately such that the imaging resolution remains the same.</li>
	<li>To save an image file of the SED image and overlaid crosshair, press S. To save a draft of the adjustments to a .txt file, press X.</li>
	<li>When satisfied, press D to go to the next FOV, or A to go back to the previous FOV. Repeat steps 7.6&#160;to 7.11&#160;for all FOVs.</li>
	<li>When finished with all FOVs, press X or Escape. Adjustments will be saved to a .txt file and copied to the clipboard.</li>
	<li>Return to the TSAI web UI. Drag and drop the .txt file onto the TSAI web UI or paste the adjustments into the text box in the FOV navigation/adjustment menu.</li>
	<li>Click Adjust to apply adjustments to the tiles in the Tiles&#160;column.</li>
</ol>
8. JSON file generation and import
<ol>
	<li>Below the Tiles&#160;column, under Output, check the list of tiles and estimated run time (Supplementary Figure 7A).</li>
	<li>Under Group, select an option for FOV grouping (Supplementary Figure 7B). Grouping has no effect on the sequentially ordered .json file.
	<ol>
		<li>For the randomized .json file, grouping FOVs by tile will order FOVs such that all the FOVs within a given tile stay together, even though the tiles are in random order.</li>
		<li>For the randomized .json file, do not group FOVs will randomly order FOVs such that FOVs from different tiles are intermixed.</li>
		<li>If in-run autofocus has been specified, FOVs will automatically be grouped by the closest autofocus site.</li>
	</ol>
	</li>
	<li>Under split, select an option for splitting into multiple .json files (Supplementary Figure 7C).
	<ol>
		<li>Do not split will keep all FOVs in only one .json file.</li>
		<li>Split by every # FOVs will split FOVs across multiple .json files, where each file contains the specified number of FOVs.</li>
		<li>Split by every # hours # minutes will split FOVs across multiple .json files, where each file&#39;s estimated run time is roughly the specified amount of time.</li>
	</ol>
	</li>
	<li>View and rearrange the order of FOVs in the .json files by opening the Rearrange menu (Supplementary Figure 7D). To move an FOV, click and drag it to the desired position. The other FOVs will interactively rearrange around the dragged FOV.</li>
	<li>To save the .json file(s), click on the FOVs button(s) beneath the rearrange menu. The sequential .json puts FOVs in order by tile, then row, then column (Supplementary Figure 7E). The random .json randomizes FOVs within the groups as selected in step 8.2 (Supplementary Figure 7F).</li>
	<li>To save an image of the tissue with the FOVs and applied display options (tile labels, brightness, contrast, etc.), click Save Tiled Image (Supplementary Figure 7G). This is often useful for record-keeping and sharing with collaborators.</li>
	<li>Return to the MIBI user control interface. Click Import FOVs and select the generated .json file. Adjust the focus, stigmation, and current as necessary and click Start Run.</li>
</ol>

Accelerating MIBI Run Setup Using TSAI for Tissue Microarray Imaging

<ol>
	<li>Liu, C. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+Ion+Beam+Imaging:+Insights+into+Pathobiology.">Multiplexed Ion Beam Imaging: Insights into Pathobiology.</a> Annu Rev Pathol. 17, 403-423 (2022).</li><li>Keren, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MIBI-TOF:+A+multiplexed+imaging+platform+relates+cellular+phenotypes+and+tissue+structure.">MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure.</a> Sci Adv. 5 (10), 1-16 (2019).</li><li>Elhanani, O., Keren, L., Angelo, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-Dimensional+Tissue+Profiling+by+Multiplexed+Ion+Beam+Imaging.">High-Dimensional Tissue Profiling by Multiplexed Ion Beam Imaging.</a> Methods Mol Biol. 2386, 147-156 (2022).</li><li>Greenwald, N. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole-cell+segmentation+of+tissue+images+with+human-level+performance+using+large-scale+data+annotation+and+deep+learning.">Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning.</a> Nat Biotechnol. 40 (4), 555-565 (2022).</li><li>Risom, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transition+to+invasive+breast+cancer+is+associated+with+progressive+changes+in+the+structure+and+composition+of+tumor+stroma.">Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma.</a> Cell. 185 (2), 299.e18-310.e18 (2022).</li><li>McCaffrey, E. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+immunoregulatory+landscape+of+human+tuberculosis+granulomas.">The immunoregulatory landscape of human tuberculosis granulomas.</a> Nat. Immunol. 23 (2), 318-329 (2022).</li><li>Greenbaum, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+spatially+resolved+timeline+of+the+human+maternal&#8211;fetal+interface.">A spatially resolved timeline of the human maternal&#8211;fetal interface.</a> Nature. 619 (7970), 595-605 (2023).</li><li>Hartmann, F. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+metabolic+profiling+of+human+cytotoxic+T+cells.">Single-cell metabolic profiling of human cytotoxic T cells.</a> Nat Biotechnol. 39 (2), 186-197 (2021).</li><li>Patwa, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+imaging+analysis+of+the+tumor-immune+microenvironment+reveals+predictors+of+outcome+in+triple-negative+breast+cancer.">Multiplexed imaging analysis of the tumor-immune microenvironment reveals predictors of outcome in triple-negative breast cancer.</a> Commun Biol. 4 (1), 852 (2021).</li><li>Keren, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Structured+Tumor-Immune+Microenvironment+in+Triple+Negative+Breast+Cancer+Revealed+by+Multiplexed+Ion+Beam+Imaging.">A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging.</a> Cell. 174 (6), 1373.e19-1387.e19 (2018).</li><li>Vijayaragavan, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+spatial+proteomic+imaging+for+human+neuropathology.">Single-cell spatial proteomic imaging for human neuropathology.</a> Acta Neuropathol. Commun. 10 (1), 158 (2022).</li><li>. GitHub - angelolab/toffy: Scripts for interacting with and generating data from the commercial MIBIScope. (n.d.) Available from: <a target="_blank" href="https://github.com/angelolab/toffy">https://github.com/angelolab/toffy</a> (2023)</li><li>. HTML Living Standard Available from: <a target="_blank" href="https://html.spec.whatwg.org/multipage">https://html.spec.whatwg.org/multipage</a> (2023)</li><li>. ECMAScript 2022 Language Specification Available from: <a target="_blank" href="https://www.ecma-international.org/publications-and-standards/standards/ecma-262">https://www.ecma-international.org/publications-and-standards/standards/ecma-262</a> (2023)</li><li>. Cascading Style Sheets (CSS) Available from: <a target="_blank" href="https://www.w3.org/Style/CSS/Overview.en.html">https://www.w3.org/Style/CSS/Overview.en.html</a> (2023)</li></ol>

The authors declare no conflicts of interest.

Multiplexed ion beam imaging (MIBI) is a powerful technique for dissecting detailed cellular phenotypes and tissue histoarchitecture5,6,7,8,9,10,11. Computational efforts around MIBI have largely focused on processing the data after imaging, but little has been done to improve the instrument...

Multiplexed ion beam imaging (MIBI) is a technique to image 40+ proteins simultaneously on histologic tissue sections at up to 250 nm resolution1,2,3. After a histologic tissue section is stained using antibodies tagged with isotopically pure elemental metals, the MIBI instrument performs secondary ion mass spectrometry to simultaneously quantify all the isotopes - and thus expression of all 40+ antigens - at individual spots on the tissue. Performed across grids of millions of spots, the resulting 40+ plex images of protein expression enable the delineation of cell boundaries and identification of specific cell types while preserving spatial context1,2,3,4. This technique has been used by hundreds of users at roughly 20 sites to study the cellular composition, metabolic profiles, and/or architecture of dozens of tissue types as part of examining the immune response to tumors, tissue inflammation caused by infectious agents, neuropathology of dementia, and immune tolerance in pregnancy5,6,7,8,9,10,11.
A key bottleneck in MIBI instrument operation is setting up fields of view (FOVs) - 200&#160;x 200 &#181;m2 to 800&#160;x 800 &#181;m2 areas of the tissue - for imaging. The MIBI images one FOV at a time, up to 800&#160;x 800 &#181;m2, thus imaging larger areas requires stitching multiple FOVs together. Imaging a tissue microarray (e.g., eight circular tissues in Figure 1A) involves placing multiple FOVs spaced apart. To set up FOVs, the manufacturer interface provides 1) an optical camera image of the slide with a crosshair that roughly corresponds to the specified imaging coordinate (Figure 1A) and 2) a secondary electron detector (SED) image that shows the exact area at the coordinate, reportedly accurate to within 0.1 &#181;m (Figure 1B). First, the user roughly positions a single FOV using the optical image. Because the image resolution is only about 60 &#181;m per pixel, if the placement is off by two pixels (2 pixels&#160;x 60 &#181;m per pixel), a standard 400 &#181;m FOV will be off by 30%. Thus, the user must use the SED image to fine-tune the position - a tedious sequence of a dozen steps involving multiple popup windows, typing coordinates into text boxes, slowly nudging the SED with directional control buttons, and often even writing down coordinates on paper (Supplementary Figure 1). This process must be repeated for each spot of a 100+ core tissue microarray (TMA). Some third-party tools can help with the initial rough positioning12. However, they still require some programming knowledge, and final positioning is still done through the dozen-step process. It is also highly troublesome to position grids of adjacent FOVs, which will be later stitched together into a tiled panoramic image.
Thus, the tile/SED/array Interface (TSAI) was developed with the goal of enabling users to rapidly position large numbers of FOVs using an intuitive, interactive graphical interface. TSAI consists of two main components: 1) A web-based graphical user interface (web UI) for rapidly placing TMA points and tissue tiles, and 2) Integrations into the MIBI user control interface for generating a tiled SED image and adjusting FOV positions. If only using the optical image, many FOVs can be roughly positioned and then quickly adjusted using the FOV navigation/adjustment tools (Figure 2, TSAI, left branch). However, if the SED tiling is performed, FOVs can be accurately positioned on the tiled SED image without needing further adjustments in SED mode (Figure 2, TSAI, right branch). Of general interest to hundreds of current MIBI users, these tools make tiling and TMA positioning very simple even for novices and reduce complex MIBI run setups from several hours to a few dozen minutes.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>MIBI computer</td>
			<td>Ionpath</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIcontrol (software)</td>
			<td>Ionpath</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIscope</td>
			<td>Ionpath</td>
			<td></td>
			<td>Multiplexed Ion Beam Imaging (MIBI) microscope</td>
		</tr>
		<tr>
			<td>MIBIslide</td>
			<td>Ionpath</td>
			<td>567001</td>
			<td>Conductive slide for MIBI</td>
		</tr>
		<tr>
			<td>Tile/SED/Array Interface (TSAI) (software)</td>
			<td></td>
			<td>https://github.com/ag-tsai/mibi_tsai/</td>
			<td></td>
		</tr>
	</tbody>
</table>

rapid setup of tissue microarray and tiled area imaging on the multiplexed ion beam imaging microscope using the tile/sed/array interface

Multiplexed ion beam imaging (MIBI) is a next-generation mass spectrometry-based microscopy technique&#160;that generates 40+ plex images of protein expression in histologic tissues, enabling detailed dissection of cellular phenotypes and histoarchitectural organization. A key bottleneck in&#160;operation occurs when users select the physical locations on the tissue for imaging. As the scale and complexity of MIBI experiments have increased, the manufacturer-provided interface and third-party tools have become increasingly unwieldy for imaging large tissue microarrays and tiled tissue areas. Thus, a web-based, interactive, what-you-see-is-what-you-get (WYSIWYG) graphical interface layer - the tile/SED/array Interface (TSAI) - was developed for users to set imaging locations using familiar and intuitive mouse gestures such as drag-and-drop, click-and-drag, and polygon drawing. Written according to web standards already built into modern web browsers, it requires no installation of external programs, extensions, or compilers. Of interest to the hundreds of current MIBI users, this interface dramatically simplifies and accelerates the setup of large, complex MIBI runs.

TSAI provides two methods for setting up FOVs (Figure 2). One uses only the optical image (Figure 2, TSAI, left branch), similar to other existing methods. The second method - generating a tiled SED image - is unique to TSAI (Figure 2, TSAI, right branch). TSAI draws FOVs accurately onto this image, eliminating the need to spend hours nudging FOVs into place in the manufacturer interface SED mode. However, the correction coefficient...

Read this Scientific Article Protocol about Rapid Setup of Tissue Microarray and Tiled Area Imaging on the Multiplexed Ion Beam Imaging Microscope using the Tile/SED/Array Interface at JoVE.com

Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging

Multiplexed ion beam imaging (MIBI) is often used to image tissue microarrays and tiled, contiguous tissue areas, but current software for setting up these experiments is cumbersome. The tile/SED/array interface is an intuitive, interactive graphical tool developed to dramatically simplify and accelerate MIBI run setup.

Rapid Setup of Tissue Microarray and Tiled Area Imaging on the Multiplexed Ion Beam Imaging Microscope Using the Tile/SED/Array Interface

Multiplexed ion beam imaging (MIBI) is a next-generation mass spectrometry-based microscopy technique&#160;that generates 40+ plex images of protein ...

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Research

JoVE Journal

Biology

376 Views.  Stanford University. Multiplexed ion beam imaging, of MIBI, is een techniek om eiwitexpressie in histologische weefsels over tientallen eiwitten tegelijk in beeld te brengen. Met behulp van MIBI kunnen onderzoekers cellen in hun oorspronkelijke weefselomgeving identificeren, lokaliseren en karakteriseren. Een belangrijk knelpunt bij de werking van MIBI-instrumenten is het instellen van gezichtsvelden, of FOV's, voor beeldvorming.FOV's zijn gebieden van 200 bij 200 micron t...

Video: Author Spotlight: Introductie van de Tile/SED/Array-interface voor snelle positionering van het gezichtsveld in weefselbeeldvorming

Proper Care and Cleaning of the Microscope

Keeping the microscope optics clean is important for high-quality imaging. Dust, fingerprints, excess immersion oil, or mounting medium on or in a microscope causes reduction in contrast and resolution. DIC is especially sensitive to contamination and scratches on the lens surfaces. This protocol details the procedure for keeping the microscope clean.

Keeping the microscope optics clean is important for high-quality imaging. Dust, fingerprints, excess immersion oil, or mounting medium on or in a microscope causes reduction in contrast and resolution. DIC is especially sensitive to contamination and scratches on the lens surfaces. This protocol details the procedure for keeping the microscope clean.

Keeping the microscope optics clean is important for high-quality imaging. Dust, fingerprints, excess immersion oil, or mounting medium on or in a ...

Major Components of the Light Microscope

The light microscope is a basic tool for the cell biologist, who should have a thorough understanding of how it works, how it should be aligned for different applications, and how it should be maintained as required to obtain maximum image-forming capacity and resolution. The components of the microscope are described in detail here.

The light microscope is a basic tool for the cell biologist, who should have a thorough understanding of how it works, how it should be aligned for different applications, and how it should be maintained as required to obtain maximum image-forming capacity and resolution. The components of the microscope are described in detail here.

The light microscope is a basic tool for the cell biologist, who should have a thorough understanding of how it works, how it should be aligned for ...

Imaging of Estrogen Receptor-&alpha; in Rat Pial Arterioles using a Digital Immunofluorescent Microscope

Many of estrogen's effects on vascular reactivity are mediated through interaction with estrogen receptors 1, 2, 3. Although two sub-types exist (estrogen receptor -&alpha; and &beta;),estrogen receptor-&alpha; has been identified in both the smooth muscle and in endothelial cells of pial arterial segments using fluorescent staining combined with confocal laser scanning microscopy 4. Furthermore, ER-&alpha; is located in the nuclei and in the cytoplasm of rat basilar arteries 5. The receptors are abundant and fluoresce brightly, but clear visualization of discrete groups of receptors is difficult likely due to the numbers located in many cell layers of pial vessel segments. Additionally, many reports using immunohistochemical techniques paired with confocal microscopy poorly detail the requirements critical for reproduction of experiments 6. Our purpose for this article is to describe a simple technique to optimize the staining and visualization of ER-&alpha; using cross-sectional slices of pial arterioles obtain from female rat brains. We first perfuse rats with Evans blue dye to easily identify surface pial arteries which we isolate under a dissecting microscope. Use of a cryostat to slice 8 &mu;m cross sections of the arteries allows us to obtain thin vessel sections so that different vessel planes are more clearly visualized. Cutting across the vessel rather than use of a small vessel segment has the advantage of easier viewing of the endothelial and smooth muscle layers. In addition, use of a digital immunofluorescent microscope with extended depth software produces clear images of ten to twelve different vessel planes and is less costly than use of a confocal laser scanning microscope.

Imaging of Estrogen Receptor-&#945; in Rat Pial Arterioles using a Digital Immunofluorescent Microscope

The goal of this article is to demonstrate a method to optimize immunofluorescent detection of estrogen receptor-&#945; (ER&#945;) in rat pial arterial slices using a digital immunofluorescent microscope.

Many of estrogen's effects on vascular reactivity are mediated through interaction with estrogen receptors 1, 2, 3. Although two sub-types exist (estrogen ...

A Simple Method for Imaging Arabidopsis Leaves Using Perfluorodecalin as an Infiltrative Imaging Medium

The problem of acquiring high-resolution images deep into biological samples is widely acknowledged1. In air-filled tissue such as the spongy mesophyll of plant leaves or vertebrate lungs further difficulties arise from multiple transitions in refractive index between cellular components, between cells and airspaces and between the biological tissue and the rest of the optical system. Moreover, refractive index mismatches lead to attenuation of fluorophore excitation and signal emission in fluorescence microscopy. We describe here the application of the perfluorocarbon, perfluorodecalin (PFD), as an infiltrative imaging medium which optically improves laser scanning confocal microscopy (LSCM) sample imaging at depth, without resorting to damaging increases in laser power and has minimal physiological impact2. We describe the protocol for use of PFD with Arabidopsis thaliana leaf tissue, which is optically complex as a result of its structure (Figure 1). PFD has a number of attributes that make it suitable for this use3. The refractive index of PFD (1.313) is comparable with that of water (1.333) and is closer to that of cytosol (approx. 1.4) than air (1.000). In addition, PFD is readily available, non-fluorescent and is non-toxic. The low surface tension of PFD (19 dynes cm-1) is lower than that of water (72 dynes cm-1) and also below the limit (25 - 30 dyne cm-1) for stomatal penetration4, which allows it to flood the spongy mesophyll airspaces without the application of a potentially destructive vacuum or surfactant. Finally and crucially, PFD has a great capacity for dissolving CO2 and O2, which allows gas exchange to be maintained in the flooded tissue, thus minimizing the physiological impact on the sample. These properties have been used in various applications which include partial liquid breathing and lung inflation5,6, surgery7, artificial blood8, oxygenation of growth media9, and studies of ice crystal formation in plants10. Currently, it is common to mount tissue in water or aqueous buffer for live confocal imaging. We consider that the use of PFD as a mounting medium represents an improvement on existing practice and allows the simple preparation of live whole leaf samples for imaging.

A Simple Method for Imaging Arabidopsis Leaves Using Perfluorodecalin as an Infiltrative Imaging Medium

We describe the use of perfluorodecalin as an infiltrative mounting medium. This is a simple method for improving depth of imaging in Arabidopsis thaliana leaf tissue with minimal physiological impact.

The problem of acquiring high-resolution images deep into biological samples is widely acknowledged1. In air-filled tissue such as the spongy mesophyll of ...

Functional Imaging of Brown Fat in Mice with 18F-FDG micro-PET/CT

Brown adipose tissue (BAT) differs from white adipose tissue (WAT) by its discrete location and a brown-red color due to rich vascularization and high density of mitochondria. BAT plays a major role in energy expenditure and non-shivering thermogenesis in newborn mammals as well as the adults 1. BAT-mediated thermogenesis is highly regulated by the sympathetic nervous system, predominantly via &beta; adrenergic receptor 2, 3. Recent studies have shown that BAT activities in human adults are negatively correlated with body mass index (BMI) and other diabetic parameters 4-6. BAT has thus been proposed as a potential target for anti-obesity/anti-diabetes therapy focusing on modulation of energy balance 6-8. While several cold challenge-based positron emission tomography (PET) methods are established for detecting human BAT 9-13, there is essentially no standardized protocol for imaging and quantification of BAT in small animal models such as mice. Here we describe a robust PET/CT imaging method for functional assessment of BAT in mice. Briefly, adult C57BL/6J mice were cold treated under fasting conditions for a duration of 4 hours before they received one dose of 18F-Fluorodeoxyglucose (FDG). The mice were remained in the cold for one additional hour post FDG injection, and then scanned with a small animal-dedicated micro-PET/CT system. The acquired PET images were co-registered with the CT images for anatomical references and analyzed for FDG uptake in the interscapular BAT area to present BAT activity. This standardized cold-treatment and imaging protocol has been validated through testing BAT activities during pharmacological interventions, for example, the suppressed BAT activation by the treatment of &beta;-adrenoceptor antagonist propranolol 14, 15, or the enhanced BAT activation by &beta;3 agonist BRL37344 16. The method described here can be applied to screen for drugs/compounds that modulate BAT activity, or to identify genes/pathways that are involved in BAT development and regulation in various preclinical and basic studies.

Functional Imaging of Brown Fat in Mice with 18F-FDG micro-PET/CT

A method of functional imaging of mouse brown adipose tissue (BAT) is described in which cold-stimulated uptake of 18F-Fluorodeoxyglucose (FDG) in BAT is non-invasively assessed with a standardized micro-PET/CT protocol. This method is robust and sensitive to detect differences in BAT activities in mouse models.

Brown adipose tissue (BAT) differs from white adipose  tissue (WAT) by its discrete location and a brown-red color due to rich  vascularization and high ...

Measurement of Extracellular Ion Fluxes Using the Ion-selective Self-referencing Microelectrode Technique

Cells from animals, plants and single cells are enclosed by a barrier called the cell membrane that separates the cytoplasm from the outside. Cell layers such as epithelia also form a barrier that separates the inside from the outside or different compartments of multicellular organisms. A key feature of these barriers is the differential distribution of ions across cell membranes or cell layers. Two properties allow this distribution: 1) membranes and epithelia display selective permeability to specific ions; 2) ions are transported through pumps across cell membranes and cell layers. These properties play crucial roles in maintaining tissue physiology and act as signaling cues after damage, during repair, or under pathological condition. The ion-selective self-referencing microelectrode allows measurements of specific fluxes of ions such as calcium, potassium or sodium at single cell and tissue levels. The microelectrode contains an ionophore cocktail which is selectively permeable to a specific ion. The internal filling solution contains a set concentration of the ion of interest. The electric potential of the microelectrode is determined by the outside concentration of the ion. As the ion concentration varies, the potential of the microelectrode changes as a function of the log of the ion activity. When moved back and forth near a source or sink of the ion (i.e. in a concentration gradient due to ion flux) the microelectrode potential fluctuates at an amplitude proportional to the ion flux/gradient. The amplifier amplifies the microelectrode signal and the output is recorded on computer. The ion flux can then be calculated by Fick&#8217;s law of diffusion using the electrode potential fluctuation, the excursion of microelectrode, and other parameters such as the specific ion mobility. In this paper, we describe in detail the methodology to measure extracellular ion fluxes using the ion-selective self-referencing microelectrode and present some representative results.

Transporters in cell membranes allow differential segregation of ions across cell membranes or cell layers and play crucial roles during tissue physiology, repair and pathology. We describe the ion-selective self-referencing microelectrode that allows the measurement of specific ion fluxes at single cells and tissues in vivo.

Cells from animals, plants and single cells are enclosed by a barrier called the cell membrane that separates the cytoplasm from the outside. Cell layers ...

Imaging Spatial Reorganization of a MAPK Signaling Pathway Using the Tobacco Transient Expression System

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular fluorescent complementation (BiFC) assay in tobacco epidermal cells, from testing protein-protein interaction to monitoring spatial distribution of signal transduction in plant cells. In this protocol, we used the BiFC assay to show that the interaction and the signaling between the Arabidopsis MAPKKK YODA and MAPK6 occur at the plasma membrane. When the scaffold protein BASL was co-expressed, the YODA-MAPK interaction redistributed and spatially co-polarized with CFP-BASL. This modified tobacco expression system allows for quick examination of signaling localization and dynamic changes (less than 4 days) and can accommodate multiple of fluorescent protein colors (at least three). We also presented detailed methods to quantify protein distribution (asymmetric spatial localization, or &#34;polarization&#34;) in tobacco cells. This advanced tobacco expression system has a potential to be used widely for quick testing of dynamic signaling events in live plant cells.

At the subcellular level, signaling events are dynamically modulated by developmental and environmental cues. Here we describe a protocol that employs the tobacco transient expression system to monitor dynamic protein-protein interaction and to disclose spatial organization of signal transduction in plant cells.

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular ...

Implementation of a Coherent Anti-Stokes Raman Scattering (CARS) System on a Ti:Sapphire and OPO Laser Based Standard Laser Scanning Microscope

Laser scanning microscopes combining a femtosecond Ti:sapphire laser and an optical parametric oscillator (OPO) to duplicate the laser line have become available for biologists. These systems are primarily designed for multi-channel two-photon fluorescence microscopy. However, without any modification, complementary non-linear optical microscopy such as second-harmonic generation (SHG) or third harmonic generation (THG) can also be performed with this set-up, allowing label-free imaging of structured molecules or aqueous medium-lipid interfaces. These techniques are well suited for in-vivo observation, but are limited in chemical specificity. Chemically selective imaging can be obtained from inherent vibration signals based on Raman scattering. Confocal Raman microscopy provides 3D spatial resolution, but it requires high average power and long acquisition time. To overcome these difficulties, recent advances in laser technology have permitted the development of nonlinear optical vibrational microscopy, in particular coherent anti-Stokes Raman scattering (CARS). CARS microscopy has therefore emerged as a powerful tool for biological and live cell imaging, by chemically mapping lipids (via C-H stretch vibration), water (via O-H stretch vibrations), proteins or DNA. In this work, we describe the implementation of the CARS technique on a standard OPO-coupled multiphoton laser scanning microscope. It is based on the in-time synchronization of the two laser lines by adjusting the length of one of the laser beam path. We present a step-by-step implementation of this technique on an existing multiphoton system. A basic background in experimental optics is helpful and the presented system does not require expensive supplementary equipment. We also illustrate CARS imaging obtained on myelin sheaths of sciatic nerve of rodent, and we show that this imaging can be performed simultaneously with other nonlinear optical imaging, such as standard two-photon fluorescence technique and second-harmonic generation.

Implementation of a Coherent Anti-Stokes Raman Scattering CARS System on a Ti:Sapphire and OPO Laser Based Standard Laser Scanning Microscope

Coherent anti-Stokes Raman scattering (CARS) microscopy based on inherent vibration of molecule bonds permits label-free chemically selective live cell imaging. This work presents the implementation of a complementary microscopy technique on a standard multiphoton laser scanning microscope based on a femtosecond Ti:sapphire laser and an OPO laser.

Laser scanning microscopes combining a femtosecond Ti:sapphire laser and an optical parametric oscillator (OPO) to duplicate the laser line have become ...

Adipo-Clear: A Tissue Clearing Method for Three-Dimensional Imaging of Adipose Tissue

Adipose tissue plays a central role in energy homeostasis and thermoregulation. It is composed of different types of adipocytes, as well as adipocyte precursors, immune cells, fibroblasts, blood vessels, and nerve projections. Although the molecular control of cell type specification and how these cells interact have been increasingly delineated, a more comprehensive understanding of these adipose-resident cells can be achieved by visualizing their distribution and architecture throughout the whole tissue. Existing immunohistochemistry and immunofluorescence approaches to analyze adipose histology rely on thin paraffin-embedded sections. However, thin sections capture only a small portion of tissue; as a result, the conclusions can be biased by what portion of tissue is analyzed. We have therefore developed an adipose tissue clearing technique, Adipo-Clear, to permit comprehensive three-dimensional visualization of molecular and cellular patterns in whole adipose tissues. Adipo-Clear was adapted from iDISCO/iDISCO+, with specific modifications made to completely remove the lipid stored in the tissue while preserving native tissue morphology. In combination with light-sheet fluorescence microscopy, we demonstrate here the use of the Adipo-Clear method to obtain high-resolution volumetric images&#160;of an entire adipose tissue.

Due to the high lipid content, adipose tissue has been challenging to visualize using traditional histological methods. Adipo-Clear is a tissue clearing technique that allows robust labeling and high-resolution volumetric fluorescent imaging of adipose tissue. Here, we describe the methods for sample preparation, pretreatment, staining, clearing, and mounting for imaging.

Adipose tissue plays a central role in energy homeostasis and thermoregulation. It is composed of different types of adipocytes, as well as adipocyte ...

Targeted Studies Using Serial Block Face and Focused Ion Beam Scan Electron Microscopy

This protocol allows for the efficient and effective imaging of cell or tissue samples in three dimensions at the resolution level of electron microscopy. For many years electron microscopy (EM) has remained an inherently two-dimensional technique. With the advent of serial scanning electron microscope imaging techniques (volume EM), using either an integrated microtome or focused ion beam to slice then view embedded tissues, the third dimension becomes easily accessible. Serial block face scanning electron microscopy (SBF-SEM) uses an ultramicrotome enclosed in the SEM chamber. It has the capability to handle large specimens (1,000 &#181;m x 1,000 &#181;m) and image large fields of view at small X,Y pixel size, but is limited in the Z dimension by the diamond knife. Focused ion beam SEM (FIB-SEM) is not limited in 3D resolution, (isotropic voxels of &#8804;5 nm are achievable), but the field of view is much more limited. This protocol demonstrates a workflow for combining the two techniques to allow for finding individual regions of interest (ROIs) in a large field and then imaging the subsequent targeted volume at high isotropic voxel resolution. Preparing fixed cells or tissues is more demanding for volume EM techniques due to the extra contrasting needed for efficient signal generation in SEM imaging. Such protocols are time consuming and labor intensive. This protocol also incorporates microwave assisted tissue processing facilitating the penetration of reagents, which reduces the time needed for the processing protocol from days to hours.

Here, we present a protocol for efficiently combining serial block face and focused ion beam scanning electron microscopy to target an area of interest. This allows for efficient searching, in three dimensions, and locating rare events in a large field of view.

This protocol allows for the efficient and effective imaging of cell or tissue samples in three dimensions at the resolution level of electron microscopy. ...

Rapid Setup of Tissue Microarray and Tiled Area Imaging on the Multiplexed Ion Beam Imaging Microscope Using the Tile/SED/Array Interface

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