Name: Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection (Video) | JoVE Journal
Uploaded: 2022-07-06T12:30:00.000+00:00
Duration: 9 min 19 s
Description: Learn automated ROI selection for spatial omics using fluorescent visualization and autostainer programming. This protocol improves reproducibility in proteomics and enables precise cell population profiling with 50 µm ROIs.

ai_agent_IP

ai_agent

maintenance

instantTrialDurationMinutes

isBiopharma

enableNewMyJoveSectionDesign

educationFeatures

seoMetaApi

ai_copilot_institution_blacklist

ai_chat_institution_blacklist

freeAccessWindow

ssoRoleCapture

scheduledMaintenanceBanner

joveLabsFeatures

disable_autoplay_for_bots

extended_trial_duration

5 minutes

The authors acknowledge Thomas Wu for processing NGS files. We thank James Ziai for the results discussions and manuscript review and Meredith Triplet and Rachel Taylor for internal manuscript revision.

All human tissues were acquired from commercial biobanks or accredited tissue banks under warranty that appropriate Institutional Review Board approval and informed consent were obtained.
NOTE: The protocol is performed using the Discovery Ultra and the GeoMx Digital Spatial Profiler. See the Table of Materials for details about reagents, equipment, and software used in this protocol.
1. Automated visualization protocol for spatial proteomics assays
<ol>
	<li>Program autostainer to apply fluorescent visualization antibodies
	<ol>
		<li>In the autostainer software, click on the home button and choose Protocols. Then, click on Create/Edit Protocols and select RUO DISCOVERY Universal as the procedure.</li>
		<li>Click on First Sequence &#62; Deparaffinization &#62; Depar v2. For Medium Temperature, choose 72 Deg C, then click on Pretreatment and select Cell Conditioning and CC1 Reservoir. For Very High Temperature, choose 100 Deg C, then click on CC1 8 Min and continue clicking until CC1 64 Min is selected.</li>
		<li>Click on Inhibitor &#62; DISCOVERY Inhibitor, and for Incubation Time, choose 8 Minutes. Then, click on Antibody &#62; High Temp Ab Incubation; for Low Temperature, choose 37 Deg C; for Antibody, choose the antibody number from the dispenser label (Antibody 6 in this example); for Plus Incubation Time, select 32 Minutes. 
		NOTE: This protocol has three different antibody numbers. The first antibody is FAP, the second is Pan-Cytokeratin, and the third is Antibody X.</li>
		<li>Click on Multimer HRP &#62; Multimer HRP Blocker, then for Antibody Blocking, choose Gt Ig Block, and for Incubation Time, choose 4 Minutes. Next, on Multimer HRP Reagent, select OMap anti-Rb HRP, and for Incubation Time, choose 16 Minutes. Then, click on Cy5, and for Long Incubation Time, choose 0 Hr 8 Min.</li>
		<li>Click on Dual Sequence and choose Antibody Denaturation, then select Antibody Denature CC2-1, and for Very High Temperature, choose 100 Deg C. Ensure that incubation time is 8 min. Next, click on DS Inhibitor and select Neutralize.</li>
		<li>Click on DS Antibody, and for Very Low Temperature, choose 37 Deg C. Then, in Antibody, choose the antibody number from the dispenser label (Antibody 3 in this example), and for Plus Incubation Time, select 32 Minutes.</li>
		<li>Click on DS Multimer HRP and choose DS Multimer HRP Blocker. Then, for Antibody Blocking, select Gt Ig Block, and for Incubation Time, choose 4 Minutes. Next, on Multimer HRP Reagent, select OMap anti-Ms HRP, and for Incubation Time, choose 16 Minutes. Then, click on DS Rhodamine 6G, and for Long Incubation Time, choose 0 Hr 8 Min.</li>
		<li>Click on Triple Stain and select TS Antibody Denaturation, then select Antibody Denature CC2-2, and for Very High Temperature, select 100 Deg C. Ensure that incubation time is 8 min. Next, click on TS Inhibitor and select TS Neutralize.</li>
		<li>Click on TS Antibody, and for Very Low Temperature, select 37 Deg C. Then, in Antibody, select the antibody number from the dispenser label (Antibody 7 in this example), and for Plus Incubation Time, select 32 Minutes.</li>
		<li>Click on TS Multimer HRP and choose TS Multimer HRP Blocker. Then, for Antibody Blocking, select Gt Ig Block, and for Incubation Time, choose 4 Minutes. Next, on Multimer HRP Reagent, select OMap anti-Rb HRP, and for Incubation Time, choose 16 Minutes. Then, click on TS FAM, and for Long Incubation Time, choose 0 Hr 8 Min.</li>
		<li>Add a title to the protocol. Select a protocol number, add a comment, and click on Active followed by Save.</li>
	</ol>
	</li>
	<li>Prepare slides, print labels, and start the autostainer run
	<ol>
		<li>Bake vendor procured FFPE (Formalin-fixed, paraffin-embedded) human tissue sections in an oven set to 70 &#176;C for 20-60 min. While slides are baking, print labels by clicking Create Label in the autostainer software. Next, click on Protocols, select the protocol number, and click on Close/Print. Add relevant information on the slide label and click on Print.</li>
		<li>Remove slides from the oven and let them cool down to room temperature (RT). Apply the previously printed protocol labels to the corresponding slides.</li>
		<li>Load refillable antibody dispensers with antibodies according to the antibody label number assigned in step 1.1. In this protocol, use Antibody 6 for FAP at 1 &#181;g/mL, use Antibody 3 for Pan-Cytokeratin at 0.1 &#181;g/mL, and use Antibody 7 for Antibody X at 2.5 &#181;g/mL. Dilute each antibody in the specified diluent and prime the refillable antibody dispensers.</li>
		<li>Gather blocking, detection, and amplification pre-filled reagent dispensers mentioned above and place them on a reagent tray. Load slides in the slide trays (up to 30 slides per run) and click on Running followed by Yes. Note that DAPI is not used for nuclear counterstaining.</li>
		<li>Confirm the start of the run by checking the run duration on the autostainer software. The protocol takes ~11 h for completion and can run overnight.</li>
		<li>The next day, ensure run completion by observing green flashing lights on the slide tray slots. Then, take the slides off the instrument and rinse the slides vigorously in 1x Reaction Buffer until the liquid coverslip solution is completely removed.</li>
	</ol>
	</li>
	<li>Spatial profiling platform protocol for proteomics assay
	<ol>
		<li>Follow the spatial proteomics protocol indicated in the note below. Include the following changes to the protocol to enable the 3-plex automated labeling procedure.</li>
		<li>Perform steps 1.2.1-1.2.6&#160;the day before starting the spatial proteomics protocol and move straight to the antigen retrieval step of the spatial proteomics protocol after performing step 1.2.6. Omit the visualization procedure outlined in the spatial profiling proteomics protocol.</li>
		<li>Replace SYTO 13 with SYTO 64 at 5000 nM to enable fluorophore integration. Dilute SYTO 64 in 1x TBS and incubate in a humidity chamber for 15 min.</li>
		<li>When setting up the scan parameters in the spatial profiling platform, select the filters and focusing channels according to the fluorophores used in the visualization panel to allow 3-plex integration. Use FITC for DISCOVERY FAM and set the exposure to 200 ms, use Cy3 for DISCOVERY Rhodamine 6G and set the exposure to 200 ms, use Texas Red for SYTO 64 and set the exposure to 50 ms (specify this as the focus channel), and finally, use Cy5 for DISCOVERY Cy5, set the exposure to 200 ms, and save changes. 
		NOTE: Detailed instructions of the spatial profiling proteomics protocol are found on the official website Support tab by selecting Documentation &#62; User Manuals. Here, look for the protein protocol for nCounter using Bond RX.</li>
	</ol>
	</li>
</ol>
2. ROI selection for spatial transcriptomics assays
<ol>
	<li>Bake FFPE cell pellet sections in an oven set to 70 &#176;C for 20-60 min. Follow the spatial profiling platform NGS protocol indicated in the note below and scan slides on the spatial profiling platform, selecting sizes of 50 &#181;m and 300 &#181;m. The following recommendation is highlighted for the spatial transcriptomics assay:
	<ol>
		<li>When preparing the library, if various sizes of ROIs were selected, pool together ROIs of similar sizes to make one library per size. This is to ensure that sufficient sequencing depths are achieved for all ROIs without bias from size. 
		NOTE: Detailed instructions of the spatial profiling platform are found on the official website Support tab by selecting Documentation &#62; User Manuals. Here, look for the RNA protocol for NGS applications using Bond RX.</li>
	</ol>
	</li>
</ol>

<ol><li>Nerurkar, S. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Transcriptional+spatial+profiling+of+cancer+tissues+in+the+era+of+immunotherapy%3A+The+potential+and+promise%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">Transcriptional spatial profiling of cancer tissues in the era of immunotherapy: The potential and promise.</a> Cancers. 12 (9), 2572(2020).</li>
<li>Decalf, J., Albert, M. L., Ziai, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((New+tools+for+pathology%3A+a+user%27s+review+of+a+highly+multiplexed+method+for+in+situ+analysis+of+protein+and+RNA+expression+in+tissue%5BTitle%5D)+AND+%22Journal+of+Pathology%22%5BJournal%5D)">New tools for pathology: a user's review of a highly multiplexed method for in situ analysis of protein and RNA expression in tissue.</a> Journal of Pathology. 247 (5), 650-661 (2019).</li>
<li>McGinnis, L. M., Ibarra-Lopez, V., Rost, S., Ziai, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Clinical+and+research+applications+of+multiplexed+immunohistochemistry+and+in+situ+hybridization%5BTitle%5D)+AND+%22Journal+of+Pathology%22%5BJournal%5D)">Clinical and research applications of multiplexed immunohistochemistry and in situ hybridization.</a> Journal of Pathology. 254 (4), 405-417 (2021).</li>
<li>NanoString. GeoMx Digital Spatial Profiler. , Available from: 
 <a target="_blank" href="https://nanostring.com/products/geomx-digital-spatial-profiler/geomx-dsp-overview">https://nanostring.com/products/geomx-digital-spatial-profiler/geomx-dsp-overview</a> (2022).</li>
<li>NanoString. GeoMx Digital Spatial Profiler. , Available from: 
 <a target="_blank" href="https://nanostring.com/wp-content/uploads/BR_MK0981_GeoMx_Brochure_r19_FINAL_Single_WEB.pdf">https://nanostring.com/wp-content/uploads/BR_MK0981_GeoMx_Brochure_r19_FINAL_Single_WEB.pdf</a> (2022).</li>
<li>McCart Reed, A. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Digital+spatial+profiling+application+in+breast+cancer%3A+a+user%27s+perspective%5BTitle%5D)+AND+%22Virchows+Arch%3A+An+International+Journal+of+Pathology%22%5BJournal%5D)">Digital spatial profiling application in breast cancer: a user's perspective.</a> Virchows Arch: An International Journal of Pathology. 477 (6), 885-890 (2020).</li>
<li>McNamara, K. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Spatial+proteomic+characterization+of+HER2-positive+breast+tumors+through+neoadjuvant+therapy+predicts+response%5BTitle%5D)+AND+%22Nature+Cancer%22%5BJournal%5D)">Spatial proteomic characterization of HER2-positive breast tumors through neoadjuvant therapy predicts response.</a> Nature Cancer. 2 (4), 400-413 (2021).</li>
<li>Kim, S. W., Roh, J., Park, C. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immunohistochemistry+for+pathologists%3A+Protocols%2C+pitfalls%2C+and+tips%5BTitle%5D)+AND+%22Journal+of+Pathology+and+Translational+Medicine%22%5BJournal%5D)">Immunohistochemistry for pathologists: Protocols, pitfalls, and tips.</a> Journal of Pathology and Translational Medicine. 50 (6), 411-418 (2016).</li>
<li>Muñoz, N. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Molecularly+targeted+photothermal+ablation+improves+tumor+specificity+and+immune+modulation+in+a+rat+model+of+hepatocellular+carcinoma%5BTitle%5D)+AND+%22Communications+Biology%22%5BJournal%5D)">Molecularly targeted photothermal ablation improves tumor specificity and immune modulation in a rat model of hepatocellular carcinoma.</a> Communications Biology. 3 (1), 783(2020).</li>
<li>Coleman, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Hyaluronidase+impairs+neutrophil+function+and+promotes+Group+B+Streptococcus+invasion+and+preterm+labor+in+nonhuman+primates%5BTitle%5D)+AND+%22mBio%22%5BJournal%5D)">Hyaluronidase impairs neutrophil function and promotes Group B Streptococcus invasion and preterm labor in nonhuman primates.</a> mBio. 12 (1), 03115-03120 (2021).</li>
<li>Gupta, S., Zugazagoitia, J., Martinez-Morilla, S., Fuhrman, K., Rimm, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Digital+quantitative+assessment+of+PD-L1+using+digital+spatial+profiling%5BTitle%5D)+AND+%22Laboratory+Investigation%3B+A+Journal+of+Technical+Methods+and+Pathology%22%5BJournal%5D)">Digital quantitative assessment of PD-L1 using digital spatial profiling.</a> Laboratory Investigation; A Journal of Technical Methods and Pathology. 100 (10), 1311-1317 (2020).</li>
<li>Carter, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Characteristics+and+spatially+defined+immune+%28micro%29landscapes+of+early-stage+PD-L1-positive+triple-negative+breast+cancer%5BTitle%5D)+AND+%22Clinical+Cancer+Research%22%5BJournal%5D)">Characteristics and spatially defined immune (micro)landscapes of early-stage PD-L1-positive triple-negative breast cancer.</a> Clinical Cancer Research. 27 (20), 5628-5637 (2021).</li>
<li>Busse, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immunoprofiling+in+neuroendocrine+neoplasms+unveil+immunosuppressive+microenvironment%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">Immunoprofiling in neuroendocrine neoplasms unveil immunosuppressive microenvironment.</a> Cancers. 12 (11), 3448(2020).</li>
<li>Kulasinghe, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Profiling+of+lung+SARS-CoV-2+and+influenza+virus+infection+dissects+virus-specific+host+responses+and+gene+signatures%5BTitle%5D)+AND+%22European+Respiratory+Journal%22%5BJournal%5D)">Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures.</a> European Respiratory Journal. 59 (1), (2021).</li>
<li>Li, X., Wang, C. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((From+bulk%2C+single-cell+to+spatial+RNA+sequencing%5BTitle%5D)+AND+%22International+Journal+of+Oral+Science%22%5BJournal%5D)">From bulk, single-cell to spatial RNA sequencing.</a> International Journal of Oral Science. 13 (36), (2021).</li>
<li>Merritt, C. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multiplex+digital+spatial+profiling+of+proteins+and+RNA+in+fixed+tissue%5BTitle%5D)+AND+%22Nature+Biotechnology%22%5BJournal%5D)">Multiplex digital spatial profiling of proteins and RNA in fixed tissue.</a> Nature Biotechnology. 38 (5), 586-599 (2020).</li>
<li>Van, T. M., Blank, C. U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+user%27s+perspective+on+GeoMxTM+digital+spatial+profiling%5BTitle%5D)+AND+%22Immuno-Oncology+Technology%22%5BJournal%5D)">A user's perspective on GeoMxTM digital spatial profiling.</a> Immuno-Oncology Technology. 1, 11-18 (2019).</li>
<li>Introduction to GeoMx Normalization: Protein. White Paper. Nanostring. , Available from: 
 <a target="_blank" href="https://nanostring.com/wp-content/uploads/MK2593_GeoMx_Normalization-Protein.pdf">https://nanostring.com/wp-content/uploads/MK2593_GeoMx_Normalization-Protein.pdf</a> (2020).</li>
<li>Bergholtz, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Best+practices+for+spatial+profiling+for+breast+cancer+research+with+the+geomx+spatial+profiler%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">Best practices for spatial profiling for breast cancer research with the geomx spatial profiler.</a> Cancers. 13 (17), 4456(2021).</li>
<li>Hwang, W. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-nucleus+and+spatial+transcriptomics+of+archival+pancreatic+cancer+reveals+multi-compartment+reprogramming+after+neoadjuvant+treatment%5BTitle%5D)+AND+%22BioRxiv%22%5BJournal%5D)">Single-nucleus and spatial transcriptomics of archival pancreatic cancer reveals multi-compartment reprogramming after neoadjuvant treatment.</a> BioRxiv. , (2020).</li>
<li>Jerby-Arnon, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Opposing+immune+and+genetic+mechanisms+shape+oncogenic+programs+in+synovial+sarcoma%5BTitle%5D)+AND+%22Nature+Medicine%22%5BJournal%5D)">Opposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma.</a> Nature Medicine. 27 (2), 289-300 (2021).</li>
</ol>

Veronica Ibarra-Lopez, Sangeeta Jayakar, Yeqing Angela Yang, Zora Modrusan, and Sandra Rost&#160;are employees and stockholders of Genentech, a member of the Roche Group. Other companies that are part of Roche produce reagents and instruments used in this manuscript. Ciara Martin is a full-time employee of NanoString Technologies Inc, which produces reagents and instruments used in this manuscript.

To date, directly conjugated fluorescent antibodies in a manual protocol are most commonly used as visualization panels for spatial proteomics or spatial transcriptomics assays9,10. However, the use of directly conjugated fluorescent antibodies can be challenging for less abundant markers, limiting the selection of suitable antibodies. This protocol shows that labeling of visualization markers can be automated on an automated staining platform using TSA technolog...

Advances in multiplexing techniques continue to provide better characterization tools for targets present in tumors. The tumor microenvironment (TME) is a complex system of tumor cells, infiltrating immune cells, and stroma, where spatial information is critical to better understand and interpret mechanisms of interaction between biomarkers of interest1. With emerging techniques such as the GeoMx Digital Spatial Profiler (DSP) and 10x Visium, multiple targets can be detected and quantified simultaneously within their spatial context. The use of immunofluorescence protocols that facilitate tissue visualization can further improve the spatial profiling capabilities of these technologies.
The Spatial Omics technology we focused on for this method development consists of spatial proteomics and transcriptomics assays where oligonucleotides are attached to antibodies or RNA probes via a UV-sensitive photocleavable linker. Histological slides are labeled with these oligo-conjugated antibodies or probes and then imaged on the spatial profiling platform. Next, ROIs of different sizes and shapes are selected for illumination, and the photocleaved oligonucleotides are aspirated and collected in a 96-well plate. The photocleaved oligonucleotides are prepared to be quantified with either the Nanostring nCounter system or Next Generation Sequencing (NGS)2,3 (Figure 1)4,5.
Cell distributions vary within tissues, and the ability to characterize specific locations of cells using selected markers and different ROI sizes is of great importance to fully understand the tissue environment and identify specific features. In the Spatial Omics technology mentioned here, the standard visualization protocol uses directly conjugated antibodies and is a manual protocol. The standard markers to distinguish between tumor and stroma are panCytokeratin (panCK) and CD456,7, but additional markers are necessary to target specific cell populations of interest. Furthermore, the use of directly conjugated fluorescent antibodies lacks amplification, which limits antibody selection to abundant markers. Additionally, manual assays are subject to more variability than automated workflows8. Therefore, it is desirable to have a customizable, automated, and amplified visualization protocol for ROI selection.
Here, the study demonstrates that, for spatial proteomics assays, TSA technology can be used for visualization protocols on an automated platform resulting in a more targeted and standardized assay. In addition, TSA based assays enable the use of low-expressing markers, increasing the range of targets that can be selected for visualization. A 3-plex assay for panCK, FAP, and Antibody X was developed using an automated platform where panCK and FAP were used to differentiate between tumor and stroma, respectively. Antibody X is a stromal protein frequently encountered in tumors, but its biology and impact on anti-tumor immunity are not fully understood. Characterizing the immune contexture in areas rich in Antibody X can elucidate its role in anti-tumor immunity and therapeutic response, as well as its potential as a drug target.
While customized automated TSA visualization panels proved to be successful for spatial proteomics assays, the application of these assays for spatial transcriptomics assays could not be confirmed. This is most likely due to the reagents and the protocol used for the automated visualization protocols, which seem to compromise RNA integrity. Recognizing that an automated labeling protocol for visualization markers can be used for spatial proteomics assays but not for spatial transcriptomics assays provides important guidance on Spatial Omics technology assay designs.
Additionally, the study demonstrates that the spatial transcriptomics assay can be used to profile targets in regions as small as 50 &#181;m in diameter, or approximately 15 cells. Two different-sized ROIs were selected to test the ability of the assay to also detect transcripts in small ROIs. For each region of interest, oligos corresponding to 1,800 mRNA targets were collected and made into libraries according to the spatial profiling platform protocol. Libraries were individually indexed, subsequently pooled, and sequenced. This allowed the evaluation of both pooling efficiency and the capability of identifying specific cell populations in small ROIs.
This paper shows that for spatial proteomics assays, an automated protocol to guide ROI selection on specific markers of interest can be used to selectively target the interrogation of relevant tissue areas and characterize the spatial environment of the tissue. Furthermore, we demonstrate that smaller ROIs can be used for spatial transcriptomic assays to detect and characterize specific cell populations.

<table><tbody><tr><td>10x Tris buffered saline (TBS)</td><td>Cell Signaling Technologies</td><td>12498S</td><td>Diluted to 1x TBS in DEPC treated water</td></tr><tr><td>Antibody X (not disclosed)</td><td></td><td></td><td>antibody blinded due to confidentiality</td></tr><tr><td>DEPC-treated water</td><td>ThermoFisher</td><td>AM9922</td><td>Another can be used</td></tr><tr><td>DISCOVERY Cell Conditioning ( CC1)</td><td>Ventana</td><td>950-500</td><td></td></tr><tr><td>DISCOVERY Cy5 Kit</td><td>Ventana</td><td>760-238</td><td>Referred as Cy5</td></tr><tr><td>DISCOVERY FAM Kit</td><td>Ventana</td><td>760-243</td><td>Referred as FAM</td></tr><tr><td>DISCOVERY Goat Ig Block</td><td>Ventana</td><td>760-6008</td><td>Referred as Gt Ig Block</td></tr><tr><td>DISCOVERY OmniMap anti-Ms HRP</td><td>Ventana</td><td>760-4310</td><td>Referred as OMap anti-Ms HRP</td></tr><tr><td>DISCOVERY OmniMap anti-Rb HRP</td><td>Ventana</td><td>760-4311</td><td>Referred as OMap anti-Rb HRP</td></tr><tr><td>DISCOVERY Rhodamine 6G Kit</td><td>Ventana</td><td>760-244</td><td>Referred as Rhodamine 6G</td></tr><tr><td>DISCOVERY ULTRA Automated Slide Preparation System</td><td>Ventana</td><td>05 987 750 001 / N750-DISU-FS</td><td>Referred as autostainer on the manuscript</td></tr><tr><td>FAP [EPR20021] Antibody</td><td>Abcam</td><td>Ab207178</td><td></td></tr><tr><td>GeoMx Digital Spatial Profiler</td><td>NanoString</td><td>GMX-DSP-1Y</td><td>Referred as spatial profiling platform on the manuscript</td></tr><tr><td>Humidity chamber</td><td>Simport</td><td>M920-2</td><td>Another can be used</td></tr><tr><td>Pan-Cytokeratin [AE1/AE3] Antibody</td><td>Abcam</td><td>Ab27988</td><td></td></tr><tr><td>ProLong Gold Antifade Mountant</td><td>ThermoFisher</td><td>P36934</td><td></td></tr><tr><td>Python</td><td>Python</td><td></td><td>Statistical analysis</td></tr><tr><td>Reaction Buffer (10x)</td><td>Ventana</td><td>950-300</td><td></td></tr><tr><td>Statistical analysis software</td><td>GraphPad</td><td>Prism 7</td><td>Statistical analysis</td></tr><tr><td>SYTO 64</td><td>ThermoFisher</td><td>S11346</td><td></td></tr><tr><td>ULTRA Cell Conditioning (ULTRA CC2)</td><td>Ventana</td><td>950-223</td><td></td></tr><tr><td>Ventana Antibody Diluent with Casein</td><td>Ventana</td><td>760-219</td><td>Referred as specified diluent on the manuscript</td></tr><tr><td>Ventana Primary antibody dispenser</td><td>Ventana</td><td></td><td>Catalog number depends on dispenser number</td></tr></tbody></table>

spatial profiling of protein and rna expression in tissue: an approach to fine-tune virtual microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein and RNA multiplexing by leveraging photo-cleavable oligo-tagged antibodies and probes, respectively. Oligos are cleaved and quantified from specific regions across the tissue to elucidate the underlying biology. Here, the study demonstrates that automated custom antibody visualization protocols can be utilized to guide ROI selection in conjunction with spatial proteomics assays. This specific method did not show acceptable performance with spatial transcriptomics assays. The protocol describes the development of a 3-plex immunofluorescent (IF) assay for marker visualization on an automated platform, using tyramide signal amplification (TSA) to amplify the fluorescent signal from a given protein target and increase the antibody pool to choose from. The visualization protocol was automated using a thoroughly validated 3-plex assay to ensure quality and reproducibility. In addition, the exchange of DAPI for SYTO dyes was evaluated to allow imaging of TSA-based IF assays on the spatial profiling platform. Additionally, we tested the ability of selecting small ROIs using the spatial transcriptomics assay to allow the investigation of highly-specific areas of interest (e.g., areas enriched for a given cell type). ROIs of 50 &#181;m and 300 &#181;m diameter were collected, which corresponds to approximately 15 cells and 100 cells, respectively. Samples were made into libraries and sequenced to investigate the capability to detect signals from small ROIs and profile-specific regions of the tissue. We determined that spatial proteomics technologies highly benefit from automated, standardized protocols to guide ROI selection. While this automated visualization protocol was not compatible with spatial transcriptomics assays, we were able to test and confirm that specific cell populations can successfully be detected even in small ROIs with the standard manual visualization protocol.

Automated visualization protocol to guide ROI selection 
In this paper, we present the use of an automated, custom TSA-based IF protocol to visualize the tissue and select specific ROIs. Visualization panel development using melanoma and human normal skin as control tissues consisted of epitope stability testing, fine-tuning of marker intensities, and bleedthrough assessment through leave one out controls. To test if epitope stability of the antibodies is affected by repetitive elution steps, FAP and ...

Here, we describe a protocol for fine-tuning regions of interest (ROIs) for Spatial Omics technologies to better characterize the tumor microenvironment and identify specific cell populations. For proteomics assays, automated customized protocols can guide ROI selection, while transcriptomics assays can be fine-tuned utilizing ROIs as small as 50 &#181;m.

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein ...

spatial-profiling-protein-rna-expression-tissue-an-approach-to-fine

Research

JoVE Journal

Cancer Research

Laser microdissection was applied to analyse gene expression profiling in specific compartments of Drosophila wing disc subjected to localised RNAi in vivo. RNA extracted from equivalent areas of silenced and unsilenced compartments was analysed by quantitative RT-PCR to determine comparative gene expression profiling within the context of native tissue microecology.

Laser Microdissection Applied to Gene Expression Profiling of Subset of Cells from the Drosophila Wing Disc

We describe a protocol for laser microdissection of sub-segments of the human kidney, including the glomerulus, proximal tubule, thick ascending limb, collecting duct and interstitium. The RNA is then isolated from the obtained compartments and RNA sequencing is carried out to determine changes in the transcriptomic signature within each sub-segment.

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue

The retina exhibits complex spatial organization across its laminar structure. Modern spatial transcriptomics and sequencing techniques require tissue sections &lt; 20 µm thick, limiting their retinal research applicability. This fresh-frozen cryosectioning method produces thin en face sections of mouse retina while preserving planar spatial relationships, enabling comprehensive molecular mapping across laminae.

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

This article presents a protocol to perform comprehensive spatial transcriptomic profiling of host, viral, fungal, and microbiome RNA from formalin-fixed paraffin-embedded tissue sections using Stereo-seq, which enables high-resolution mapping of diverse transcriptomes while preserving tissue architecture.

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

This protocol includes a step-by-step workflow for calcified vascular specimens: tissue handling, decalcification, RNA validation, calcification level detection, and region-of-interest selection strategies on the Nanostring GeoMx Digital Spatial Profiler (DSP). The goal is to present a comprehensive method for preserving vascular tissue morphology and RNA for reliable spatial transcriptomic analysis.

Calcified Artery Preparation and Processing with Preserved Morphology and RNA for Digital Spatial Profiling

This protocol describes a method to isolate RNA from defined histological regions of paraformaldehyde-fixed, Optimal Cutting Temperature compound-embedded mouse liver tissue using laser capture microdissection, enabling targeted downstream gene expression analysis.

Laser Capture Microdissection of Paraformaldehyde-Fixed Mouse Liver Tissue for RNA Analysis

This study presents a spatial Trekker–CUT&amp;Tag multiome protocol combining direct spatial barcoding of a tissue section with single-cell multiome analysis. This approach enables spatially resolved single-cell profiling of gene expression and the histone H3K27ac modification simultaneously, offering mechanistic insights into gene regulation in the context of tissue microanatomy.

Spatially Resolved, Integrated Single-Cell Multiomic Profiling of the Transcriptome and Epigenomic Targets in Frozen Tissue Sections

This protocol demonstrates how to generate fluorescently marked, genetically defined clonal tumors in the Drosophila eye/antennal imaginal discs (EAD). It describes how to dissect the EAD and brain from the third instar larvae and how to process them to visualize and quantify gene expression changes and tumor invasiveness.

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

Currently, immunofluorescent staining on fixed cells is the method of choice for determination of protein expression levels when morphological information is also necessary. This protocol presented herein provides for an alternative method of immunocytochemistry on paraffin-embedded cell blocks.

Determination of Protein Expression Level in Cultured Cells by Immunocytochemistry on Paraffin-embedded Cell Blocks

The following procedure describes a method for spatial and temporal control of melanocytic tumor initiation in murine dorsal skin, using a genetically engineered mouse model. This protocol describes macroscopic as well as microscopic cutaneous melanoma initiation.

Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells

Learn automated ROI selection for spatial omics using fluorescent visualization and autostainer programming. This protocol improves reproducibility in proteomics and enables precise cell population profiling with 50 µm ROIs.

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Explore More Videos