This study was supported by the Adelson Medical Research Foundation (AMRF), the Melanoma Research Alliance (MRA), and U54CA224068. Figure 1, Figure 4, and Figure 5 were created with BioRender.com.

This study complied with all institutional guidelines regarding human tissue sampling. Informed consent was received from patients, and identifiable sample data was anonymized. Samples are collected in the operation room, placed in a solution of RPMI, saline, or PBS, and confirmed cancerous via the pathology department before use in research. All steps, except when indicated, should be carried out at 4 &#176;C or on ice. Work inside a biosafety hood when processing human tissue. See the Table of Materials for details on all materials, reagents, and instruments used in this protocol.
1. Obtaining the sample
<ol>
	<li>Obtain a solid tumor sample in a tube of media and place it on ice.
	<ol>
		<li>Instruct the operating room staff to transport the sample in a tube containing enough RPMI, saline, or PBS to completely submerge the tissue to avoid sample dehydration. 
		NOTE: Ensuring the sample is not desiccated is important, as this will decrease viability.</li>
	</ol>
	</li>
	<li>Cool down all centrifuges to 4 &#730;C and bring the thermal mixer to 37 &#730;C.</li>
	<li>Take out prepared human or mouse tumor dissociation enzymes (Table of Materials), thaw on the 37 &#730;C thermal mixer, and move to ice once thawed.</li>
	<li>Retrieve a 20 mL aliquot of RPMI.</li>
	<li>Record relevant sample information (e.g., Patient ID, de-identifier, sample type).</li>
	<li>Transfer the sample to a 60 mm tissue culture dish (placed on ice) by inverting the tube several times and pouring the contents into the dish to ensure all sample material is transferred. If the sample was not delivered in media upon arrival, add fresh RPMI media to the dish.
	<ol>
		<li>If the sample is fragmented, spin the tube containing the sample at 450 &#215; g, 4 &#730;C for 5 min, discard the supernatant, resuspend the sample in 420 &#181;L of RPMI, and move to section 2.</li>
	</ol>
	</li>
</ol>
2. Mechanical and enzymatic digestion
<ol>
	<li>Pipette 420 &#181;L of media from the 60 mm sample dish to a 1.5 mL microcentrifuge tube. Attempt to include any sample fragments suspended in the media.</li>
	<li>Transfer the sample tissue from the 60 mm dish to the 1.5 mL tube containing media using tweezers. Cut up the sample with clean scissors inside the tube so the pieces are maximum 2-3 mm in diameter.</li>
	<li>Add digestion enzymes, prepared according to manufacturer specifications (Table of Materials), to the sample in the following volumes: 42 &#181;L of Enzyme H (nonspecific proteases) for human samples, Enzyme D (nonspecific proteases) for murine samples, 21 &#181;L of enzyme R (nonspecific proteases), and 5 &#181;L of enzyme A (nuclease).</li>
	<li>Add another 420 &#181;L of media from the dish or up to the 1 mL mark on the tube. Do not exceed 420 &#181;L of media.</li>
	<li>Vortex the tube for 5 s and place it in a thermal mixer positioned vertically on its side (Figure 1B). Incubate at 37 &#730;C, 450 rpm, for 15 min. 
	NOTE: During incubation, take out all 10x Genomics materials needed for GEM generation, as these require 30 min to equilibrate to room temperature</li>
</ol>
3. Sample filtering
<ol>
	<li>Place a 50 &#181;m cell filter on top of a new 15 mL conical tube and prime the filter by passing 1 mL of fresh RPMI media through it into the tube.</li>
	<li>After digestion, transfer the sample to the 15 mL tube using a 1,000 &#181;L low-retention wide pipette tip. Wash the 1.5 mL tube with 1 mL of fresh media and transfer the media to the filter to ensure all sample material is passed through the filter.</li>
	<li>Obtain a 1 mL plastic syringe and take out just the plunger (discard the remainder of the syringe). Using the back of the syringe plunger, grind and push the sample on the filter in a twisting motion.</li>
	<li>Wash the filter with 5 mL of media and any remaining media from the dish that contained the sample (section 1) to collect any cells that might have detached from the tissue.</li>
	<li>Place a 30 &#181;m cell filter on top of a new 15 mL conical tube, prime the filter with 1 mL of media, and transfer the contents of the tube containing the dissociated sample through the filter. 
	NOTE: This step will remove large debris that might clog or cause a wetting failure when running the sample using the 10x Genomics microfluidic chips.</li>
</ol>
4. Red blood cell lysis
<ol>
	<li>Centrifuge the sample at 450 &#215; g, 4 &#730;C for 5 min. Aspirate the media, being careful not to disturb the pellet.</li>
	<li>Resuspend in ACK Lysis buffer to remove red blood cells (RBCs) and record the volume used. The volume will depend on pellet size and the extent of RBCs in the pellet. 
	NOTE: Resuspended ACK-sample solution should be colorless when enough ACK Lysis buffer has been added, as this will clear the red blood cells from the sample.</li>
	<li>Centrifuge the sample tube at 450 &#215; g, 4 &#730;C for 5 min, and aspirate the supernatant.</li>
	<li>Repeat steps 4.2-4.3 as needed until the sample pellet has no visible red color after centrifugation (Figure 2). Record any extra volumes of ACK Lysis buffer used in this step.</li>
	<li>Resuspend the sample pellet in fresh media in preparation for counting.</li>
</ol>
5. Cell counting
<ol>
	<li>Place 10 &#181;L of trypan blue in a 1.5 mL tube. Gently mix the dissociated cells, take 10 &#181;L of sample, and mix (1:1) with the trypan blue. Load 10 &#181;L on each side of a hemocytometer and count the cells.</li>
	<li>Record cell concentration, total live cell count, viability percentage, and final media volume after count.</li>
	<li>Ensure cell count is between 700 and 1,200 cells/&#181;L (7 &#215; 105- 1.2 &#215; 106/mL) for an optimal 10x Genomics run.
	<ol>
		<li>If the sample is too concentrated, dilute it with media and recount it.</li>
		<li>If the sample is too diluted, centrifuge the sample at 450 &#215; g, 4 &#730;C for 5 min, and resuspend in a lesser volume of media.</li>
		<li>If cell viability is below 80%, perform a live-dead procedure to remove dead cells.</li>
		<li>If there are under one million cells, see section 6.</li>
		<li>If there are over one million cells and viability&#160;&#62; 10%, see section 6.</li>
		<li>If there are over one million cells and viability &#60; 10%, see section 7.</li>
		<li>If cell viability is above 80%, keep the processed cells on ice and proceed immediately to GEM generation according to the manufacturer&#39;s instructions.</li>
	</ol>
	</li>
</ol>
6. Dead cell removal - Kit 1
NOTE: Work inside a biosafety hood when using the dead cell removal reagents, as these can easily get contaminated.
<ol>
	<li>Centrifuge the sample at 450 &#215; g, 4 &#730;C for 5 min.</li>
	<li>Prepare isolation media in a 15 mL conical tube and keep it at room temperature: 9.8 mL of PBS, 10 &#181;L of CaCl2, and 200 &#181;L of heat-inactivated FCS (added in a Biosafety hood).</li>
	<li>After centrifugation, aspirate the media from the pellet and resuspend in 1 mL of the isolation media.</li>
	<li>Centrifuge the tube again at 450 &#215; g, 4 &#730;C for 5 min. Aspirate the supernatant and resuspend the pellet in 100 &#181;L of isolation media.</li>
	<li>Transfer 100 &#181;L of sample in isolation media into one well of a 0.2 mL PCR strip-tube.</li>
	<li>In a biosafety hood, add 10 &#181;L of Annexin V Cocktail and 10 &#181;L of Biotin Selection Cocktail to the well containing 100 &#181;L of the sample in isolation media. Pipette mix the solution and allow it to sit at room temperature for 4 min.</li>
	<li>After 4 min, vortex the dextran-coated magnetic particles for 30 s. Add 20 &#181;L of the beads and 60 &#181;L of isolation media to the sample (a total volume of 200 &#181;L). If viability is lower than 40%, scale the amount of beads up to 40 &#181;L while adjusting the volume of isolation media (up to 40 &#181;L), keeping a total volume of 200 &#181;L. Pipette mix and allow the solution to sit at room temperature for 3 min.</li>
	<li>Place the strip tube onto a 10x Genomics Magnetic Separator (on the high setting) for 5 min at room temperature.</li>
	<li>Transfer the liquid from the strip tube without disturbing the beads into a new 1.5 mL lo-bind microcentrifuge tube. Do not remove the strip-tube from the magnet.</li>
	<li>Centrifuge the 1.5 mL tube containing the sample at 450 &#215; g, 4 &#730;C for 5 min. Aspirate the supernatant and resuspend the pellet in an appropriate volume of RPMI media based on the pellet size and count cells, as described in section 5. Repeat the dead cell removal procedure if viability remains below 80% (Figure 3 and Figure 4). 
	NOTE: Do not resuspend cells in isolation media for downstream GEM generation, as the calcium chloride will interfere with the encapsulation process and the reverse transcription (RT) step.</li>
	<li>Keep processed cells on ice if cell viability is above 80% and proceed immediately to GEM generation according to the manufacturer&#39;s instructions.</li>
</ol>
7. Dead cell removal - Kit 2
NOTE: Work inside a biosafety hood when using the kit reagents.
<ol>
	<li>Place the microbeads and the 20x Binding Buffer stock solution inside a biosafety hood.</li>
	<li>Centrifuge the sample suspension at 450 &#215; g, 4 &#730;C for 5 min.</li>
	<li>Prepare 1x buffer solution under sterile conditions using 1 mL of the 20x Binding Buffer stock solution pipetted into 19 mL of DNAse-, RNAse-free distilled water.</li>
	<li>Once the centrifugation is completed, aspirate the supernatant, add the microbeads, gently mix the sample, and incubate at room temperature for 15 min.
	<ol>
		<li>When the cell count is 107 or less, add 100 &#181;L of the microbeads.</li>
		<li>For counts higher than 107 total cells, adjust the microbeads for a final concentration of 100 &#181;L per 107 live cells.</li>
	</ol>
	</li>
	<li>During incubation, obtain one MACS positive selection column, MACS multistand, and the corresponding magnetic separator. Ensure the separator is leveled on the multistand and no other metal or magnetic object is near the stand, as the magnetic force is powerful and could affect dead cell removal efficiency. Place the column snugly into a separator holder with wings facing out.</li>
	<li>After sample incubation, if the total resuspension volume is less than 500 &#181;L, add 1x Binding Buffer until the total volume is 500 &#181;L.</li>
	<li>Place a 15 mL conical tube below the column and prime the column with 3 mL of 1x Binding Buffer.</li>
	<li>Replace the conical tube with a new 15 mL conical for cell sample collection and add the sample to the column, allowing it to flow completely through the column.</li>
	<li>Wash the column 4 x 3 mL of 1x Binding Buffer, only adding one wash at a time after the previous wash entirely flowed through the column.</li>
	<li>After the fourth wash, centrifuge the conical tube containing the isolated cells for 5 min at 450 &#215; g, 4 &#730;C. Discard the column and the remaining 1x Binding Buffer.</li>
	<li>Resuspend the sample solution in the appropriate amount of RPMI media based on pellet size and count the isolated cells using the method described in section 5 (Figure 3 and Figure 5).
	<ol>
		<li>If viability remains below 80%, and the total number of cells is 106 or less, repeat section 6.</li>
		<li>If cell viability is above 80%, keep processed cells on ice and proceed immediately to GEM generation according to the manufacturer&#39;s instructions.</li>
	</ol>
	</li>
</ol>

Tumor Dissociation Protocol for Single-Cell RNA Sequencing Analysis

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<li>Baghban, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tumor+microenvironment+complexity+and+therapeutic+implications+at+a+glance%5BTitle%5D)+AND+%22Cell+Commun+Signal%22%5BJournal%5D)">Tumor microenvironment complexity and therapeutic implications at a glance.</a> Cell Commun Signal. 18 (1), 59(2020).</li>
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<li>Ottaiano, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((From+chaos+to+opportunity%3A+decoding+cancer+heterogeneity+for+enhanced+treatment+strategies%5BTitle%5D)+AND+%22Biology%22%5BJournal%5D)">From chaos to opportunity: decoding cancer heterogeneity for enhanced treatment strategies.</a> Biology. 12 (9), 1183(2023).</li>
<li>Hwang, B., Lee, J. H., Bang, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+RNA+sequencing+technologies+and+bioinformatics+pipelines%5BTitle%5D)+AND+%22Exp+Mol+Med%22%5BJournal%5D)">Single-cell RNA sequencing technologies and bioinformatics pipelines.</a> Exp Mol Med. 50 (8), 1-14 (2018).</li>
<li>Erfanian, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Deep+learning+applications+in+single-cell+genomics+and+transcriptomics+data+analysis%5BTitle%5D)+AND+%22Biomed+Pharmacother%22%5BJournal%5D)">Deep learning applications in single-cell genomics and transcriptomics data analysis.</a> Biomed Pharmacother. 165, 115077(2023).</li>
<li>Jovic, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+RNA+sequencing+technologies+and+applications%3A+A+brief+overview%5BTitle%5D)+AND+%22Clin+Transl+Med%22%5BJournal%5D)">Single-cell RNA sequencing technologies and applications: A brief overview.</a> Clin Transl Med. 12 (3), e694(2022).</li>
<li>Burja, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((An+optimized+tissue+dissociation+protocol+for+single-cell+RNA+sequencing+analysis+of+fresh+and+cultured+human+skin+biopsies%5BTitle%5D)+AND+%22Front+Cell+Dev+Biol%22%5BJournal%5D)">An optimized tissue dissociation protocol for single-cell RNA sequencing analysis of fresh and cultured human skin biopsies.</a> Front Cell Dev Biol. 10, 872688(2022).</li>
<li>Denisenko, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Systematic+assessment+of+tissue+dissociation+and+storage+biases+in+single-cell+and+single-nucleus+RNA-seq+workflows%5BTitle%5D)+AND+%22Genome+Biol%22%5BJournal%5D)">Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows.</a> Genome Biol. 21 (1), 130(2020).</li>
<li>Sade-Feldman, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Defining+T+cell+states+associated+with+response+to+checkpoint+immunotherapy+in+melanoma%5BTitle%5D)+AND+%22Cell%22%5BJournal%5D)">Defining T cell states associated with response to checkpoint immunotherapy in melanoma.</a> Cell. 176 (1-2), 404(2019).</li>
<li>Pelka, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Spatially+organized+multicellular+immune+hubs+in+human+colorectal+cancer%5BTitle%5D)+AND+%22Cell%22%5BJournal%5D)">Spatially organized multicellular immune hubs in human colorectal cancer.</a> Cell. 184 (18), 4734-4752 (2021).</li>
<li>Bill, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((CXCL9%3ASPP1+macrophage+polarity+identifies+a+network+of+cellular+programs+that+control+human+cancers%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">CXCL9:SPP1 macrophage polarity identifies a network of cellular programs that control human cancers.</a> Science. 381 (6657), 515-524 (2023).</li>
<li>Al'Khafaji, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-throughput+RNA+isoform+sequencing+using+programmed+cDNA+concatenation%5BTitle%5D)+AND+%22Nat+Biotechnol%22%5BJournal%5D)">High-throughput RNA isoform sequencing using programmed cDNA concatenation.</a> Nat Biotechnol. 42 (4), 582-586 (2024).</li>
<li>Xing, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+effect+of+cell+isolation+methods+on+the+human+transcriptome+profiling+and+microbial+transcripts+of+peripheral+blood%5BTitle%5D)+AND+%22Mol+Biol+Rep%22%5BJournal%5D)">The effect of cell isolation methods on the human transcriptome profiling and microbial transcripts of peripheral blood.</a> Mol Biol Rep. 48 (4), 3059-3068 (2021).</li>
<li>Ma, F., Hernandez, G. E., Romay, M., Iruela-Arispe, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+RNA+sequencing+to+study+vascular+diversity+and+function%5BTitle%5D)+AND+%22Curr+Opin+Hematol%22%5BJournal%5D)">Single-cell RNA sequencing to study vascular diversity and function.</a> Curr Opin Hematol. 28 (3), 221-229 (2021).</li>
<li>Fan, X. -J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Impact+of+cold+ischemic+time+and+freeze-thaw+cycles+on+RNA%2C+DNA+and+protein+quality+in+colorectal+cancer+tissues+biobanking%5BTitle%5D)+AND+%22J+Cancer%22%5BJournal%5D)">Impact of cold ischemic time and freeze-thaw cycles on RNA, DNA and protein quality in colorectal cancer tissues biobanking.</a> J Cancer. 10 (20), 4978-4988 (2019).</li>
<li>LoCoco, P. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Reliable+approaches+to+extract+high-integrity+RNA+from+skin+and+other+pertinent+tissues+used+in+pain+research%5BTitle%5D)+AND+%22Pain+Rep%22%5BJournal%5D)">Reliable approaches to extract high-integrity RNA from skin and other pertinent tissues used in pain research.</a> Pain Rep. 5 (2), e818(2020).</li>
<li>Montanari, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Automated-mechanical+procedure+compared+to+gentle+enzymatic+tissue+dissociation+in+cell+function+studies%5BTitle%5D)+AND+%22Biomolecules%22%5BJournal%5D)">Automated-mechanical procedure compared to gentle enzymatic tissue dissociation in cell function studies.</a> Biomolecules. 12 (5), 701(2022).</li>
<li>Yosefov-Levi, O., Tornovsky, S., Parnas, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Pancreatic+tissue+dissection+to+isolate+viable+single+cells%5BTitle%5D)+AND+%22J+Vis+Exp%22%5BJournal%5D)">Pancreatic tissue dissection to isolate viable single cells.</a> J Vis Exp. (195), (2023).</li>
<li>Janssen, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+effect+of+background+noise+and+its+removal+on+the+analysis+of+single-cell+expression+data%5BTitle%5D)+AND+%22Genome+Biol%22%5BJournal%5D)">The effect of background noise and its removal on the analysis of single-cell expression data.</a> Genome Biol. 24 (1), 140(2023).</li>
<li>Adam, M., Potter, A. S., Potter, S. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Psychrophilic+proteases+dramatically+reduce+single+cell+RNA-seq+artifacts%3A+A+molecular+atlas+of+kidney+development%5BTitle%5D)+AND+%22Development%22%5BJournal%5D)">Psychrophilic proteases dramatically reduce single cell RNA-seq artifacts: A molecular atlas of kidney development.</a> Development. 144 (19), 3625-3632 (2017).</li>
<li>Sutermaster, B. A., Darling, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Considerations+for+high-yield%2C+high-throughput+cell+enrichment%3A+fluorescence+versus+magnetic+sorting%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Considerations for high-yield, high-throughput cell enrichment: fluorescence versus magnetic sorting.</a> Sci Rep. 9 (1), 227(2019).</li>
</ol>

M.S-F. received funding from Bristol Myers-Squibb, Istari Oncology, and was a consultant for Galvazine Therapeutics.

This protocol describes human or murine tumor samples dissociation into a single-cell suspension for scRNA sequencing using the 10x Genomics microfluidic system. In processing tissues that often come from rare cancers or are part of ongoing clinical trials or long experiments for murine tumors, the sample must be optimally and carefully preserved between all steps. All steps should be carried out rapidly on ice or at 4 &#730;C to keep the native cellular RNA profiles and prevent degradation, as working at room temperature for extended periods will affect the transcriptomic quality17,18.
Several steps should be taken to ensure the loss of cells throughout the procedure is minimal, especially when processing small needle core biopsies17. Ensuring that all fragments of the tumor sample are included in the digestion will lead to the most successful result, as more cells extracted from the sample will improve future 10x Genomics encapsulation and sequencing and the total number of cells and transcripts recovered for analysis. If the sample becomes lodged in the tube it arrives in, media can be added, the tube inverted, and transferred to the dish for processing. If the initial sample is fragmented or the solution is cloudy, indicating the presence of cells in suspension, ensure that all the sample is collected for enzymatic digestion by centrifuging the sample with the solution it arrived in and resuspending it in media volume for digestion (protocol section 1).
When aspirating, ensure that the pellet is not disturbed throughout the procedure. Leave extra volume when aspirating, which can be removed with a P200 pipette. If the pellet is disturbed, the volume can be dispensed back into the tube and re-centrifuged. Post ACK Lysis or post live dead removal, the sample may be in volumes as low as 25 &#181;L. Thus, it is critical not to lose any supernatant containing the cells. Proper mechanical digestion is essential to ensure the cells of interest are exposed to enzymatic digestion. Longer enzymatic digestion using the appropriate enzymes and thermal mixer might be needed for larger sample sizes9,19,20. While specific enzyme names are proprietary, the manufacturer notes enzyme A as a nuclease and enzymes H, D, and R as nonspecific proteases. Passing as much of the tumor sample through the filter is vital to ensuring the highest cell yield possible. Successful filtering will result in the filter not having any or only a tiny visible sample caught in it. Some pieces of the sample might not be able to be filtered through if it has high amounts of adipose or connective tissue. If there are visible pieces of the sample on the top of the filter, continue using the back of the syringe plunger to grind and push all the sample through using the twisting motion while also washing the top of the filter with more media.
The success of the red blood cell lysis step is determined by viewing the sample underneath the microscope once the sample is loaded on the hemocytometer for counting and viability15,21. If enough ACK is added to the sample to clear out red blood cells, there would be no red blood cells or visible redness in the pellet. If red blood cells are visible in the sample, additional ACK should be added, and the sample should be re-centrifuged at 450 &#215; g, 4 &#730;C for 5 min. Once done, the supernatant should be aspirated, and the pellet of cells can be resuspended in RPMI media for visualization and counting.
To ensure an optimal 10x Genomics run, the cell count should be between 700 and 1,200 cells/&#181;L (7 &#215; 105- 1.2 &#215; 106/mL). A high concentration will increase the doublet rate (two cells in one droplet) during droplet formation. If the count is too high, an appropriate amount of media can be added to the sample and reloaded on a hemocytometer for recounting. If the concentration is too low, the sample can be re-centrifuged at 450 &#215; g, 4 &#730;C for 5 min, the supernatant aspirated and resuspended in a lower volume of media before recounting. The sample is ready to be loaded for 10x Genomics if the live cell viability is above 80% (Figure 3).
If the sample&#39;s viability is below 80%, a live-dead procedure is needed before 10x Genomics loading16. If one round of live-dead removal has not brought the viability percentage above 80%, another round should be performed if there are over 1 &#215; 105 cells total. Higher viability will prevent clogs in the subsequent 10x Genomics protocol, increase cell recovery, and reduce the presence of ambient RNA. Kit 1&#39;s protocol has been optimized and miniaturized for rapidly dissociating smaller tissue samples with lower cell counts. The reduced volume of reagents and shortened incubation times increase cell yield and prevent a stress response gene signature (FOS, JUN, and JUNB) on various cells9,22. Alternative methods to enrich live cells include staining and sorting. However, this would result in reduced cell yield, prolonged staining incubation, which could affect cellular states (e.g., aCD3e antibodies will activate T cells), and stress induced by the machine&#39;s pressure on the cells during sorting9,22. The example shown in Figure 6 illustrates a UMAP generated after 10X Genomics Gene Expression (GEX) sequencing and the conversion of the generated cell barcodes into FASTQ files that were then concatenated and aligned via CellRanger. Subsequent sequencing results and live-dead removal comparisons were plotted, demonstrating cell populations in a sample before and after live-dead removal and improved sequencing quality. The lung sample shown in Figure 6 indicated an issue with the fraction of reads, as it was below 70%. This warning was generated due to high ambient RNA in a population of lysed or dead cells. However, after the removal of dead cells, this error was no longer present and resulted in a higher percentage of fraction reads in cells23.
Single-cell RNA sequencing is a costly and precarious process that has dramatically advanced the field of cancer immunology and cancer research. It allows for further interrogation of genes, cellular states, and programs expressed and repressed in specific cell types, divulging more about the behavior and heterogeneity of cancers. Suboptimal or low-viability tissue is more likely to generate low-quality data that can create artifacts that take away from the reality of tumor biology, emphasizing the critical importance of proper tumor dissociation and sample preparation.

Although many advancements in cancer research have led to the development and FDA approval of agents targeting inhibitory receptors expressed on immune and tumor cells, known as checkpoint blockade inhibitors, therapy resistance and identifying mechanisms that drive patient response remain challenging1. The complex challenge of characterizing tumor heterogeneity on its molecular diversity and the intricate interplay between tumor cells and the immune microenvironment necessitates new approaches to dissect this complex ecosystem at the single-cell resolution. Understanding the molecular intricacies within tumors and their microenvironments is pivotal for advancing therapeutic strategies and deciphering the complex biology underlying cancer progression2. Single-cell RNA sequencing (scRNA-seq) has become increasingly popular because it provides high-resolution analysis of individual cells within complex tumor samples3,4.
Tumor heterogeneity, encompassing genetic, epigenetic, and phenotypic diversities, poses a challenge in uncovering the intricacies of cancer biology5. The conventional methods of bulk RNA sequencing tend to obscure the unique expression profiles and phenotypes of heterogeneous cell populations present within tumors, as these methods average signals across entire cell populations4. In contrast, scRNA-seq allows the dissection of individual cell types, revealing diverse gene expression, repression patterns, and cellular states otherwise overlooked4,6. The premise of scRNA-seq lies in its capacity to decode individual cells&#39; genetic and molecular signatures, holding immense promise in discovering new cancer therapeutics7.
By deciphering the gene expression profiles of tumor cells and the surrounding stromal and immune cells, researchers can identify novel therapeutic targets and develop precision genetic medicine strategies tailored to individual patients6. Furthermore, dissecting the immune repertoire within the tumor microenvironment provides crucial insights into the interplay between tumor cells and immune effectors, paving the way for immunotherapeutic interventions3. Despite advances in using scRNAseq on clinical samples, several challenges during the processing steps can harm the cell&#39;s RNA integrity, viability, and quality of the data generated. Moreover, processing tissue with low cell viability can increase ambient RNA levels in the droplets generated during the encapsulation of individual cells, resulting in cross-contamination and incorrect annotation of cell types, while long dissociation protocols performed at 37 &#176;C can lead to the upregulation of a stress response gene signature in multiple cell types8,9,10.
The stepwise procedure (Figure 1A) outlined in this protocol commences with rapid mechanical and enzymatic dissociation of tumors, followed by filtration and the removal of dead cells, depending on the viability of each tumor sample. At present, this procedure has been verified in melanoma11, colorectal12, head and neck squamous cell carcinoma13, pancreatic and lung (unpublished data) tumor samples. These techniques ensure the generation of high-quality viable cell suspensions crucial for downstream analyses14. Notably, removing red blood cells, devoid of synthesized RNA, becomes imperative to purify the sample15. Subsequent evaluation of cell counts and the elimination of dead cells serve as a prerequisite for successful 10x Genomics Gel bead-in Emulsion (GEM) generation, barcoding, and increase the recovery of transcripts and sequenced cells without jeopardizing the exclusion of sensitive populations (e.g., neutrophils and epithelial cells)16. These steps are fundamental in unlocking the potential of single-cell resolution analysis within tumor samples9,10, uncovering novel gene expression profiles and immune signatures necessary for driving innovative therapeutic interventions, and identifying new tumor vulnerabilities.

<table><tbody><tr><td>1x PBS</td><td>Corning</td><td>21-040-CV</td><td></td></tr><tr><td>10 mL serological pipette</td><td>Corning</td><td>357551</td><td></td></tr><tr><td>1000 &amp;mu;L low-retention pipette tips</td><td>Rainin</td><td>30389213</td><td></td></tr><tr><td>1000 &amp;mu;L low-retention wide pipette tips</td><td>Rainin</td><td>30389218</td><td></td></tr><tr><td>1000 &amp;mu;L pipette tips</td><td>Rainin</td><td>30389212</td><td></td></tr><tr><td>10x Magnetic Separator</td><td>10x Genomics</td><td>120250</td><td></td></tr><tr><td>15 mL conical tubes</td><td>Corning</td><td>430052</td><td></td></tr><tr><td>2 mL aspirating pipette</td><td>Corning</td><td>357558</td><td></td></tr><tr><td>20 &amp;mu;L low-retention pipette tips</td><td>Rainin</td><td>30389226</td><td></td></tr><tr><td>20 &amp;mu;L pipette tips</td><td>Rainin</td><td>30389225</td><td></td></tr><tr><td>200 &amp;mu;L low-retention pipette tips</td><td>Rainin</td><td>30389240</td><td></td></tr><tr><td>200 &amp;mu;L pipette tips</td><td>Rainin</td><td>30389239</td><td></td></tr><tr><td>50 mL Polypropylene Conical Tube</td><td>Falcon</td><td>352098</td><td></td></tr><tr><td>60 x 15 mm Tissue Culture Dish</td><td>Falcon</td><td>353004</td><td></td></tr><tr><td>ACK Lysing Buffer</td><td>Gibco</td><td>A10492-1</td><td></td></tr><tr><td>BD 1 mL syringe</td><td>Becton, Dickinson and Company</td><td>3090659</td><td></td></tr><tr><td>Bright-Line Hemocytometer</td><td>Hausser Scientific</td><td>551660</td><td></td></tr><tr><td>Calcium Chloride Solution</td><td>Sigma Aldrich</td><td>2115-100ML</td><td></td></tr><tr><td>Cell Ranger&amp;nbsp;</td><td>10x Genomics</td><td>N/A</td><td>https://www.10xgenomics.com/support/software/cell-ranger/latest</td></tr><tr><td>Cell counting slides for TC20 cell counter</td><td>Bio-Rad</td><td>1450015</td><td></td></tr><tr><td>CellTrics 30&amp;mu;m sterile disposable filters</td><td>Sysmex</td><td>04-004-2326</td><td></td></tr><tr><td>CellTrics 50&amp;mu;m sterile disposable filters</td><td>Sysmex</td><td>04-004-2327</td><td></td></tr><tr><td>Dead Cell removal Kit&amp;nbsp;</td><td>Miltenyi Biotec</td><td>130-090-101</td><td>Store at -20 &amp;deg;C; kit 2</td></tr><tr><td>Dissecting Forceps, Fine Tip</td><td>VWR</td><td>82027-386</td><td></td></tr><tr><td>DNA LoBind Microcentrifuge tubes, 1.5 mL</td><td>Eppendorf</td><td>22431021</td><td></td></tr><tr><td>EasySepTM Dead Cell Removal&lt;br/&gt; (Annexin V) Kit</td><td>STEMCELL Technologies</td><td>17899</td><td>Store at 4 &amp;deg;C; Kit 1</td></tr><tr><td>Eppendorf centrifuge 5425R</td><td>Eppendorf</td><td>5406000640</td><td></td></tr><tr><td>Eppendorf centrifuge 5910R</td><td>Eppendorf</td><td>2231000657</td><td></td></tr><tr><td>Eppendorf Easypet 3 Electronic Pipette controller</td><td>Eppendorf</td><td>EP4430000018</td><td></td></tr><tr><td>Eppendorf Thermomixer F1.5 Model 5384</td><td>Eppendorf</td><td>EP5384000012</td><td></td></tr><tr><td>FBS</td><td>Gibco</td><td>26140-079</td><td>Store at 4 &amp;deg;C, use in a Biological hood</td></tr><tr><td>German Stainless Scissors</td><td>Fine Science Tools</td><td>14568-12</td><td></td></tr><tr><td>Leica Dmi1 Microscope</td><td>Leica Microsystems</td><td>454793</td><td></td></tr><tr><td>LS Column</td><td>Miltenyi Biotec</td><td>130-042-401</td><td></td></tr><tr><td>MACS Multistand</td><td>Miltenyi Biotec</td><td>130-042-303</td><td></td></tr><tr><td>Pipet-Lite LTS Pipette L-1000XLS+</td><td>Rainin</td><td>17014382</td><td></td></tr><tr><td>Pipet-Lite LTS Pipette L-200XLS+</td><td>Rainin</td><td>17014391</td><td></td></tr><tr><td>Pipet-Lite LTS Pipette L-20XLS+</td><td>Rainin</td><td>17014392</td><td></td></tr><tr><td>Quadro MACS Magnet</td><td>Miltenyi Biotec</td><td>130-091-051</td><td></td></tr><tr><td>RPMI Medium 1640 (1x)</td><td>Gibco</td><td>21870-076</td><td>Store at 4 &amp;deg;C</td></tr><tr><td>TempAssure 0.2 mL PCR 8-Tube strips</td><td>USA Scientific</td><td>1402-4700</td><td></td></tr><tr><td>Trypan blue stain 0.4%</td><td>Thermo Fisher Scientific</td><td>T10282</td><td></td></tr><tr><td>Tumor Dissociation Kit, Human</td><td>Miltenyi Biotec</td><td>130-095-929</td><td>Store at -20 &amp;deg;C, prepare enzymes according to kit instructions:&lt;br/&gt; Reconstitute lyophilized Enzyme H vial in 3 mL of RPMI 1640&lt;br/&gt; Reconstitute lyophilized Enzyme R vial in 2.7 mL of RPMI 1640&lt;br/&gt; Reconstitute lyophilized Enzyme A vial in 1 mL of Buffer A supplied with the kit.</td></tr><tr><td>Tumor Dissociation Kit, Mouse</td><td>Miltenyi Biotec</td><td>130-096-730</td><td>Store at -20 &amp;deg;C, prepare enzymes according to kit instructions:&lt;br/&gt; Reconstitute lyophilized Enzyme D vial in 3 mL of RPMI 1640&lt;br/&gt; Reconstitute lyophilized Enzyme R vial in 2.7 mL of RPMI 1640&lt;br/&gt; Reconstitute lyophilized Enzyme A vial in 1 mL of Buffer A supplied with the kit.</td></tr><tr><td>UltraPure Distilled Water</td><td>Invitrogen</td><td>10977-015</td><td>Store at 4 &amp;deg;C</td></tr></tbody></table>

dissociation of human and mouse tumor tissue samples for single-cell rna sequencing

Human tumor samples hold a plethora of information about their microenvironment and immune repertoire. Effective dissociation of human tissue samples into viable cell suspensions is a required input for the single-cell RNA sequencing (scRNAseq) pipeline. Unlike bulk RNA sequencing approaches, scRNAseq enables us to infer the transcriptional heterogeneity in tumor specimens at the single-cell level. Incorporating this approach in recent years has led to many discoveries, such as identifying immune and tumor cellular states and programs associated with clinical responses to immunotherapies and other types of treatments. Moreover, single-cell technologies applied to dissociated tissues can be used to identify accessible chromatin regions T and B cell receptor repertoire, and the expression of proteins, using DNA barcoded antibodies (CITEseq).
The viability and quality of the dissociated sample are critical variables when using these technologies, as these can dramatically affect the cross-contamination of single cells with ambient RNA, the quality of the data, and interpretation. Moreover, long dissociation protocols can lead to the elimination of sensitive cell populations and the upregulation of a stress response gene signature. To overcome these limitations, we devised a rapid universal dissociation protocol, which has been validated on multiple types of human and murine tumors. The process begins with mechanical and enzymatic dissociation, followed by filtration, red blood lysis, and live dead enrichment, suitable for samples with a low input of cells (e.g., needle core biopsies). This protocol ensures a clean and viable single-cell suspension paramount to the successful generation of Gel Bead-In Emulsions (GEMs), barcoding, and sequencing.

A melanoma biopsy suspended in RPMI was obtained and immediately placed on ice. The sample was transferred into a 1.5 mL microcentrifuge tube containing 420 &#181;L of RPMI and digestion enzymes, minced into small pieces using scissors, and subjected to subsequent enzymatic digestion for 15 min in a 37 &#730;C vertically positioned thermal mixer (Figure 1). Following digestion, the sample was filtered through a 50 &#181;m sterile disposable filter, and the filter was washed with fresh RPMI to increase cell yield (Figure 1). The remaining parts of the tissue left after the washes were discarded, as these are unwanted biological materials (e.g., adipose tissue).
Based on the color of the resulting cell pellet, 15 mL of ACK lysis buffer was needed to remove the red blood cells (Figure 2). Following resuspension in 3 mL of RPMI media, the total cell count was 1 &#215; 106/mL, with viability that was &#60;80% (Figure 3A). This indicated that one cycle of live cell enrichment using Kit 1 (protocol section 6) was needed before proceeding to 10x Genomics loading (Figure 4). If this sample had over 1 million cells and had a viability of less than 10%, the Dead Cell removal - Kit 2 would have been utilized instead (Figure 5). The sample was washed with isolation media, and 10 &#181;L of Annexin V and biotin selection cocktail were added, followed by 20 &#181;L of the magnetic beads and 60 &#181;L of isolation media, as described in protocol section 6 (Figure 4). After this procedure, the sample was resuspended in 500 &#181;L of media and recounted. The live cell count was 4.9 &#215; 105/mL with viability above 90% (Figure 3B), and the sample proceeded immediately to GEM generation according to the manufacturer&#39;s instructions.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66766/66766fig01.jpg" /> 
Figure 1: Tumor sample processing overview. (A) Illustration of the step-by-step process of the tissue dissociation protocol. (B) The digestion of a sample using a vertically positioned thermal mixer. <a href="https://www.jove.com/files/ftp_upload/66766/66766fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66766/66766fig02.jpg" /> 
Figure 2: Pre-ACK and Post-ACK treatment of a mildly pigmented Melanoma sample. (A) Image shows a melanoma sample that was filtered and pelleted after the digestion step before red blood cell (RBC) lysis using ACK. (B) Image shows the same melanoma sample after RBC removal using ACK buffer. <a href="https://www.jove.com/files/ftp_upload/66766/66766fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/66766/66766fig03.jpg" /> 
Figure 3: View of cells on hemocytometer under trypan blue zoomed in at 200x magnification. (A) Image showing the appearance of blue cells before live cell enrichment, representing dead cells, with viability lower than 80%. (B) Image showing the sample after live cell enrichment using the Kit 1 protocol (protocol step 6), showing increased viability above 90%. <a href="https://www.jove.com/files/ftp_upload/66766/66766fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66766/66766fig04.jpg" /> 
Figure 4: Overview of the live-dead sample cell isolation using Kit 1. This step is performed when under one million or over one million cells with viability&#160;&#62;10% are detected after cell count (protocol step 5). <a href="https://www.jove.com/files/ftp_upload/66766/66766fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/66766/66766fig05.jpg" /> 
Figure 5: Overview of the live-dead cell isolation using the dead cell removal microbeads in Kit 2. This step is performed when there are over one million cells and a viability of &#60;10%. <a href="https://www.jove.com/files/ftp_upload/66766/66766fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/66766/66766fig06.jpg" /> 
Figure 6: Validation of single-cell analysis of an unmanipulated sample after one cycle of live cell enrichment using Kit 1&#39;s modified protocol. Upper part shows a UMAP analysis demonstrating consistency in cell groups and types prior to and after live cell enrichment. Lower part summarizes the sequencing outputs generated by Cell Ranger. <a href="https://www.jove.com/files/ftp_upload/66766/66766fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

This protocol outlines the procedure for rapidly dissociating human and mouse tumor samples for single-cell RNA sequencing.

Dissociation of Human and Mouse Tumor Tissue Samples for Single-cell RNA Sequencing

Human tumor samples hold a plethora of information about their microenvironment and immune repertoire. Effective dissociation of human tissue samples into ...

dissociation-human-mouse-tumor-tissue-samples-for-single-cell-rna

Nanyang Technological University

Research

JoVE Journal

Cancer Research

2.7K Views.  Massachusetts General Hospital. This protocol outlines the procedure for rapidly dissociating human and mouse tumor samples for single-cell RNA sequencing.

Video: Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of the breadth of molecular regulation. Newer approaches such as high-resolution RNA sequencing (RNA-Seq)1 provides new and expansive information about tissue- or state-specific expression such as relative transcript levels, alternative splicing, and micro RNAs2-4. Prospects for employing the RNA-Seq method in comparative whole transcriptome profiling5 within discrete tissues or between phenotypically distinct groups of individuals affords new avenues for elucidating molecular mechanisms involved in both normal and abnormal physiological states. Recently, whole transcriptome profiling has been performed on human brain tissue, identifying gene expression differences associated with disease progression6. However, the use of next-generation sequencing has yet to be more widely integrated into mammalian studies.
Gene expression studies in mouse models have reported distinct profiles within various brain nuclei using laser capture microscopy (LCM) for sample excision7,8. While LCM affords sample collection with single-cell and discrete brain region precision, the relatively low total RNA yields from the LCM approach can be prohibitive to RNA-Seq and other profiling approaches in mouse brain tissues and may require sub-optimal sample amplification steps. Here, a protocol is presented for microdissection and total RNA extraction from discrete mouse brain regions. Set-diameter tissue corers are used to isolate 13 tissues from 750-&mu;m serial coronal sections of an individual mouse brain. Tissue micropunch samples are immediately frozen and archived. Total RNA is obtained from the samples using magnetic bead-enabled total RNA isolation technology. Resulting RNA samples have adequate yield and quality for use in downstream expression profiling. This microdissection strategy provides a viable option to existing sample collection strategies for obtaining total RNA from discrete brain regions, opening possibilities for new gene expression discoveries.

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling  |

RNA expression profiling of discrete mouse brain regions requires a precise and repeatable tissue collection strategy. A protocol that uses both coronal brain sectioning and tissue corer-assisted microdissection is described here. The yield and quality of total RNA obtained from the resulting samples confirms the utility of the outlined method.

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of ...

Neuroscience

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq

Adult diffuse gliomas exhibit inter- and intra-tumor heterogeneity. Until recently, the majority of large-scale molecular profiling efforts have focused on bulk approaches that led to the molecular classification of brain tumors. Over the last five years, single cell sequencing approaches have highlighted several important features of gliomas. The majority of these studies have utilized fresh brain tumor specimens to isolate single cells using flow cytometry or antibody-based separation methods. Moving forward, the use of fresh-frozen tissue samples from biobanks will provide greater flexibility to single cell applications. Furthermore, as the single-cell field advances, the next challenge will be to generate multi-omics data from either a single cell or the same sample preparation to better unravel tumor complexity. Therefore, simple and flexible protocols that allow data generation for various methods such as single-nucleus RNA sequencing (snRNA-seq) and single nucleus Assay for Transposase-Accessible Chromatin with high-throughput sequencing (snATAC-seq) will be important for the field.
Recent advances in the single cell field coupled with accessible microfluidic instruments such as the 10x genomics platform have facilitated single cell applications in research laboratories. To study brain tumor heterogeneity, we developed an enhanced protocol for the isolation of single nuclei from fresh frozen gliomas. This protocol merges existing single cell protocols and combines a homogenization step followed by filtration and buffer mediated gradient centrifugation. The resulting samples are pure single nuclei suspensions that can be used to generate single nucleus gene expression and chromatin accessibility data from the same nuclei preparation.

Intra-tumoral heterogeneity is an inherent feature of tumors, including gliomas. We developed a simple and efficient protocol that utilizes a combination of buffers and gradient centrifugation to isolate single nuclei from fresh frozen glioma tissues for single nucleus RNA and ATAC sequencing studies.

Adult diffuse gliomas exhibit inter- and intra-tumor heterogeneity. Until recently, the majority of large-scale molecular profiling efforts have focused ...

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly with many downstream assays such as next generation sequencing. Automated tissue dissection is a new methodology that automates and improves tumor enrichment in these common, low tumor content tissues by decreasing the user-dependent imprecision of traditional macro-dissection and time, cost, and expertise limitations of laser capture microdissection by using digital image annotation overlay onto unstained slides. Here, digital hematoxylin and eosin (H&#38;E) annotations are used to target small tumor areas using a blade that is 250 &#181;m2 in diameter in unstained formalin fixed paraffin embedded (FFPE) or fresh frozen sections up to 20 &#181;m in thickness for automated tumor enrichment prior to nucleic acid extraction and whole exome sequencing (WES). Automated dissection can harvest annotated regions in low tumor content tissues from single or multiple sections for nucleic acid extraction. It also allows for capture of extensive pre- and post-harvest collection metrics while improving accuracy, reproducibility, and increasing throughput with utilization of fewer slides. The described protocol enables digital annotation with automated dissection on animal and/or human FFPE or fresh frozen tissues with low tumor content and could also be used for any region of interest enrichment to boost adequacy for downstream sequencing applications in clinical or research workflows.

Digital annotation with automated tissue dissection provides an innovative approach to enriching tumor in low tumor content cases and is adaptable to both paraffin and frozen tissue types. The described workflow improves accuracy, reproducibility and throughput and could be applied to both research and clinical settings.

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly ...

Isolation and Genotyping of Gastrulating Mouse Embryo for Single-Cell Sequencing

Single-Cell RNA Sequencing of Mutant Whole Mouse Embryos: From the Epiblast to the End of Gastrulation

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states within samples. Before single-cell advances, the feasibility of capturing the dynamic cellular landscape and rapid cell transitions during early development was limited. In this paper, a robust pipeline was designed to perform single-cell and nuclei analysis on mouse embryos from embryonic day E6.5 to E8, corresponding to the onset and completion of gastrulation. Gastrulation is a fundamental process during development that establishes the three germinal layers: mesoderm, ectoderm, and endoderm, which are essential for organogenesis. Extensive literature is available on single-cell omics applied to wild-type perigastrulating embryos. However, single-cell analysis of mutant embryos is still scarce and often limited to FACS-sorted populations. This is partially due to the technical constraints associated with the need for genotyping, timed pregnancies, the count of embryos with desired genotypes per pregnancy, and the number of cells per embryo at these stages. Here, a methodology is presented designed to overcome these limitations. This method establishes breeding and timed pregnancy guidelines to achieve a higher chance of synchronized pregnancies with desired genotypes. Optimization steps in the embryo isolation process coupled with a same-day genotyping protocol (3 h) allow for microdroplet-based single-cell to be performed on the same day, ensuring the high viability of cells and robust results. This method further includes guidelines for optimal nuclei isolations from embryos. Thus, these approaches increase the feasibility of single-cell approaches of mutant embryos at the gastrulation stage. We anticipate that this method will facilitate the analysis of how mutations shape the cellular landscape of the gastrula.

Author Spotlight: A Pipeline to Analyze Lineage-Specific Mutant Embryos at Single-Cell Resolution

This paper establishes a pipeline for high-quality single-cell and nuclei suspensions of gastrulating mouse embryos for sequencing of single cells and nuclei.

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states ...

Developmental Biology

Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells

The use of in vitro cell line models for cancer research has been a useful tool. However, it has been shown that these models fail to reliably mimic patient tumors in different assays1. Human tumor xenografts represent the gold standard with respect to tumor biology, drug discovery, and metastasis research 2-4. Tumor xenografts can be derived from different types of material like tumor cell lines, tumor tissue from primary patient tumors4 or serially transplanted tumors. When propagated in vivo, xenografted tissue is infiltrated and vascularized by cells of mouse origin. Multiple factors such as the tumor entity, the origin of xenografted material, growth rate and region of transplantation influence the composition and the amount of mouse cells present in tumor xenografts. However, even when these factors are kept constant, the degree of mouse cell contamination is highly variable.
Contaminating mouse cells significantly impair downstream analyses of human tumor xenografts. As mouse fibroblasts show high plating efficacies and proliferation rates, they tend to overgrow cultures of human tumor cells, especially slowly proliferating subpopulations. Mouse cell derived DNA, mRNA, and protein components can bias downstream gene expression analysis, next-generation sequencing, as well as proteome analysis 5. To overcome these limitations, we have developed a fast and easy method to isolate untouched human tumor cells from xenografted tumor tissue. This procedure is based on the comprehensive depletion of cells of mouse origin by combining automated tissue dissociation with the benchtop tissue dissociator and magnetic cell sorting. Here, we demonstrate that human target cells can be can be obtained with purities higher than 96% within less than 20 min independent of the tumor type.

Human tumor xenografts are vascularized and infiltrated by cells of mouse origin during the growth phase in vivo. To circumvent the bias caused by these contaminating cells during downstream analysis, we developed a method allowing for comprehensive depletion of all mouse cells by magnetic cell sorting.

The use of in vitro cell line models for cancer research has been a useful tool. However, it has been shown that these models fail to reliably mimic ...

Medicine

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing

As resident macrophages in the central nervous system, microglia actively control brain development and homeostasis, and their dysfunctions may drive human diseases. Considerable advances have been made to uncover the molecular signatures of homeostatic microglia as well as alterations of their gene expression in response to environmental stimuli. With the advent and maturation of single-cell genomic methodologies, it is increasingly recognized that heterogenous microglia may underlie the diverse roles they play in different developmental and pathological conditions. Further dissection of such heterogeneity can be achieved through efficient isolation of microglia from a given region of interest, followed by sensitive profiling of individual cells. Here, we provide a detailed protocol for the rapid isolation of microglia from different brain regions in a single adult mouse brain hemisphere. We also demonstrate how to use these sorted microglia for plate-based deep single-cell RNA sequencing. We discuss the adaptability of this method to other scenarios and provide guidelines for improving the system to accommodate large-scale studies.

We provide a protocol for isolation of microglia from different dissected regions of an adult mouse brain hemisphere, followed by semi-automated library preparation for deep single-cell RNA sequencing of full-length transcriptomes. This method will help to elucidate functional heterogeneity of microglia in health and disease.

As resident macrophages in the central nervous system, microglia actively control brain development and homeostasis, and their dysfunctions may drive ...

Semi-Automated Mechanical-Enzymatic Tissue Dissociation for Single-Cell Analysis

Mechanical Dissociation of Tissues for Single Cell Analysis Using a Motorized Device

Being able to isolate and prepare single cells for the analysis of tissue samples has rapidly become crucial for new biomedical discoveries and research. Manual protocols for single-cell isolations are highly time-consuming and prone to user variability. Automated mechanical protocols are able to reduce processing time and sample variability but aren't easily accessible or cost-effective in lower-resourced research settings. The device described here was designed for semi-automated tissue dissociation using commercially available materials as a low-cost alternative for academic laboratories. Instructions to fabricate, assemble, and operate the device design have been provided. The dissociation protocol reliably produces single-cell suspensions with comparable cell yields and sample viability to manual preparations across multiple mouse tissues. The protocol provides the ability to process up to 12 tissue samples simultaneously per device, making studies requiring large sample sizes more manageable. The accompanying software also allows for customization of the device protocol to accommodate varying tissues and experimental constraints.

Author Spotlight: Advancements in Nanoparticle Technology for Drug Delivery and Immunotherapy

A general protocol for the combined enzymatic and semi-automated mechanical dissociation of tissues to generate single-cell suspensions for downstream analyses, such as flow cytometry, is provided. Instructions for the fabrication, assembly, and operation of the low-cost mechanical device developed for this protocol are included.

Being able to isolate and prepare single cells for the analysis of tissue samples has rapidly become crucial for new biomedical discoveries and research. ...

Bioengineering

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

The analysis of single cell gene expression across thousands of individual cells within a tissue or microenvironment is a valuable tool for identifying cell composition, discrimination of functional states, and molecular pathways underlying observed tissue functions and animal behaviors. However, the isolation of intact, healthy single cells from adult mammalian tissues for subsequent downstream single cell molecular analysis can be challenging. This protocol describes the general processes and quality control checks necessary to obtain high-quality adult single cell preparations from the nervous system or skin that enabled subsequent unbiased single cell RNA sequencing and analysis. Guidelines for downstream bioinformatic analysis are also provided.

This protocol describes the general processes and quality control checks necessary for preparing healthy adult mammalian single cells for droplet-based, high throughput single cell RNA-Seq preparations. Sequencing parameters, read alignment, and downstream single-cell bioinformatic analysis are also provided.

The analysis of single cell gene expression across thousands of individual cells within a tissue or microenvironment is a valuable tool for identifying ...

Biology

Optimized Protocol for Mouse Wound Healing Model with Stem Cell-Derived Exosomes

Mouse Wound Models and Preparation of Single-Cell Suspensions 

The management of acute full-thickness skin injuries presents a considerable challenge in clinical practice. The complexity of wound healing, involving diverse cell populations and the intricate wound microenvironment, complicates the assessment of treatment effects and their interactions using traditional experimental approaches. Single-cell transcriptome sequencing technology has revolutionized the understanding of cellular functions and mechanisms during wound healing. However, the variability in methodologies for creating mouse wound models introduces confounding factors that can impact experimental results. Furthermore, the process of dissociating mouse skin tissues presents significant technical hurdles, highlighting the critical need for high-quality single-cell suspensions for accurate transcriptome sequencing. Therefore, this study aims to optimize the construction of mouse wound models to accurately assess changes in wound closure while eliminating variables that could influence the subsequent sequencing result. Additionally, the preparation of single-cell suspensions was performed using both enzyme preparation protocols and test kit protocols to optimize cost and effectiveness.

Mouse Wound Models and Preparation of Single-Cell Suspensions

This study presents two crucial experimental techniques: the construction of a murine wound model for assessing wound closure and the preparation of single-cell suspensions from murine skin to preserve cellular viability.

The management of acute full-thickness skin injuries presents a considerable challenge in clinical practice. The complexity of wound healing, involving ...

Isolation and Profiling of Single Nuclei from Frozen Mammalian Tissues

A Simple, Quick, and Partially Automated Protocol for the Isolation of Single Nuclei from Frozen Mammalian Tissues for Single Nucleus Sequencing

Single-cell and single-nucleus RNA sequencing have become common laboratory applications due to the wealth of transcriptomic information that they provide. Single nucleus RNA sequencing, particularly, is useful for investigating gene expression in difficult-to-dissociate tissues. Furthermore, this approach is also compatible with frozen (archival) material. Here, we describe a protocol to isolate high-quality single nuclei from frozen mammalian tissues for downstream single nucleus RNA sequencing in a partially-automated manner using commercially available instruments and reagents. Specifically, a robotic dissociator is used to automate and standardize tissue homogenization, followed by an optimized chemical gradient to filter the nuclei. Lastly, we accurately and automatically count the nuclei using an automated fluorescent cell counter. The performance of this protocol is demonstrated on mouse brain, rat kidney, and cynomolgus liver and spleen tissue. This protocol is straightforward, rapid, and readily adaptable to various mammalian tissues without requiring extensive optimization and provides good quality nuclei for downstream single nuclei RNA sequencing.

Author Spotlight: Enhancing Drug Discovery - Development of Automated, Standardized Protocols for Nuclei Extraction from Frozen Tissues 

The study describes a simple, quick, and partially automated protocol to isolate high-quality nuclei from frozen mammalian tissues for downstream single nuclei RNA sequencing.

Dissociation of Human and Mouse Tumor Tissue Samples for Single-cell RNA Sequencing

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Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

Single-Cell RNA Sequencing of Mutant Whole Mouse Embryos: From the Epiblast to the End of Gastrulation

Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing

Mechanical Dissociation of Tissues for Single Cell Analysis Using a Motorized Device

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Mouse Wound Models and Preparation of Single-Cell Suspensions

A Simple, Quick, and Partially Automated Protocol for the Isolation of Single Nuclei from Frozen Mammalian Tissues for Single Nucleus Sequencing