Simultaneous single cell analysis of multiple analytes ... · Simultaneous single cell analysis of...
1
FOR RESEARCH USE ONLY. NOT FOR USE IN DIAGNOSTIC PROCEDURES. Introduction Simultaneous single cell analysis of multiple analytes resolves T cell populations at high resolution Sarah E. B. Taylor 1 , Katherine A. Pfeiffer 1 , Michael J. T. Stubbington 1 , Josephine Y. Lee 1 , Jerald Sapida 1 , Daniel P. Riordan 1 , Alvaro M. Barrio 1 , Dagmar Walter 1 , Luz Montesclaros 1 , Solongo Ziraldo 1 , Liselotte Brix 2 , Kivin Jacobsen 2 , Bertrand Yeung 3 , Xinfang Zhao 3 , Tarjei S. Mikkelsen 1 , Deanna M. Church 1 1 10x Genomics, 2 Immudex, 3 BioLegend 3. Multi-omic single cell characterization of T cell populations 2. Cell type classification of PBMCs using gene and cell surface protein expression 6. Clustering analysis of CMV specific TCR clonotypes 5. Feature Barcoding technology and flow cytometry analysis yield comparable data 4. Analysis of flow sorted populations allows identification of more antigen specific cells Conclusions 1. Feature Barcoding technology workflow • Characterization of lymphocyte types and understanding their antigen binding specificities is key to the development of effective therapeutics • 10x Genomics have enabled the integration of transcriptome, cell-surface protein, immune repertoire and TCR antigen-specificity measurements from the same single cells • Combined with developments from Immudex and BioLegend we are able to provide an end-to-end solution for analysis of the tumor microenvironment This technology allows: • Cell type characterization and identification of full length, paired TCR sequences with specificity for known antigens • Characterization of the adaptive immune response at unprecedented resolution • A truer understanding the complexity of the tumor microenvironment • The potential for the discovery of novel TCR: antigen binding relationships Feature Barcoding technology workflow for the multi-omic characterization of single cells. A. Gating strategy used in flow cytometry to isolate CD4-/CD8a+/Dextramer+ cells. B. Single Cell Immune Profiling with Feature Barcoding technology workflow where gene expression and immune repertoire libraries are generated alongside libraries from DNA barcodes conjugated to TotalSeq™-C antibodies or dCODE™ Dextramer® reagents, allowing quantification of cell surface proteins and identification of TCR specificities. Representative Bioanalyzer traces showing average size distribution for amplified cDNA and for each of the generated libraries are shown in the figure. The combination of gene expression and cell surface protein expression using labelled barcoded antibodies provides increased resolution of cell type characterization. Unsorted PBMCs and CD4-/CD8a+/Dextramer+ sorted cells were aggregated, tSNE projections generated by Cell Ranger and visualized in Loupe Cell Browser. Cells were clustered on gene expression data with graph-based clustering. Each dot is a single cell. A. i. CMV seropositive donor colored based on sample. Unsorted PBMCs = grey (6770 cells), sorted cells = green (2038 cells). B. i. CMV seronegative donor colored based on sample. Unsorted PBMCs = grey (5998 cells), sorted cells = green (1566 cells). In ii. Cell type classification was performed using both gene expression data and surface protein expression profiles. Heatmaps show the significantly enriched (blue) or significantly under-represented (red) TCR clonotypes. Each column represents a TCR clonotype. The number of T cells with specificity for a particular Dextramer® (Specific binders) and the frequency of the T cell clonotype in the whole population (Clonotype count) are outlined below each heatmap. For all samples, the top cells ranked by magnitude of their log10 p-values are shown, and at least ten cells were included for each heatmap. Feature Barcoding technology and flow cytometry identify similar frequencies of Dextramer® positive cells. A. Feature Barcoding technology analysis with a CMV-specific dCODE™ Dextramer® panel. Positive cells are above the dashed lines with the background colored in pink. B. Quantification of the fraction of positive binding cells as a percentage of the total number of CD8+ cells identified by Feature Barcoding technology and by flow cytometry. C. Flow cytometric analysis of the same CMV seropositive sample with the same dCODE™ Dextramer® panel. Positive cells are inside the dashed box with pink background. Clustering analysis of TCR clonotypes for CMV specific dCODE™ Dextramers® reveals both novel and known CDR3 amino acid sequences. Paired TCR sequences were clustered using TCRdist (Dash et al. 2017) to generate an average-linkage hierarchical tree, colored according to the number of cells that share each paired TCR sequence (at the nucleotide level). # is the frequency at which the specific clone was detected. A. dCODE™ Dextramer® A*0101 VTEHDTLLY. 31 different TCR pairs identified. B. dCODE™ Dextramer® B*0702 RPHERNGFTVL. 8 different TCR pairs identified. Analysis of TCR repertoires and their binding specificity in combination with gene and cell surface protein expression, provides a high resolution view of T cell activity at the single cell level. Cell clustering and classification of the sorted cell populations was based on: i. Gene expression ii. Cell surface protein expression based on binding of BioLegend TotalSeq™-C antibodies. iii. TCR specificity based on dCODE™ Dextramer® binding. Highlighted clusters show significantly enriched binding over the rest of the cell population, p<0.001. The paired TCR clonotype gene calls for the top 10 clonotypes in the dominant cluster, are shown. Many statistically significant specific TCR: dCODE™ Dextramer® binding events were identified in the sorted cells (i) whereas very few are identified in the unsorted PBMCs (ii). Green boxes indicates amino acid sequences that are identified with the same binding specificities in VDJdb; in B. the TCRA had a 1 amino acid substitution from the identified sequence in VDJdb. For a pdf version of this poster, visit the 10x Genomics website: https://www.10xgenomics.com/resources/posters/ Based on analysis of the CMV seropositive donor CD4-/CD8a+/Dextramer+ sorted cells. Samples were obtained from a CMV seropositive and seronegative donor. Cells were stained with panels of oligonucleotide conjugated antibodies (BioLegend) and Dextramers (Immudex). Each sample was split into two, one half was sorted for CD4- /CD8a+/Dextramer+ cells, and the other half left unsorted. The four samples (CMV seropositive and seronegative, sorted and unsorted) were taken through the workflow as outlined in Figure 1. For further information on dCODE™ Dextramers® see Immudex poster P56.
Transcript of Simultaneous single cell analysis of multiple analytes ... · Simultaneous single cell analysis of...
FOR RESEARCH USE ONLY. NOT FOR USE IN DIAGNOSTIC PROCEDURES.
Introduction
Simultaneous single cell analysis of multiple analytes resolves T cell populations at high resolution
Sarah E. B. Taylor1, Katherine A. Pfeiffer1, Michael J. T. Stubbington1, Josephine Y. Lee1, Jerald Sapida1, Daniel P. Riordan1, Alvaro M. Barrio1, Dagmar Walter1, Luz Montesclaros1, Solongo Ziraldo1, Liselotte Brix2, Kivin Jacobsen2, Bertrand Yeung3, Xinfang Zhao3, Tarjei S. Mikkelsen1, Deanna M. Church1
110x Genomics, 2Immudex, 3BioLegend
3. Multi-omic single cell characterization of T cell populations
2. Cell type classification of PBMCs using gene and cell surface protein expression
6. Clustering analysis of CMV specific TCR clonotypes
5. Feature Barcoding technology and flow cytometry analysis yield comparable data
4. Analysis of flow sorted populations allows identification of more antigen specific cells
Conclusions
1. Feature Barcoding technology workflow
• Characterization of lymphocyte types and understanding their antigen bindingspecificities is key to the development of effective therapeutics
• 10x Genomics have enabled the integration of transcriptome, cell-surfaceprotein, immune repertoire and TCR antigen-specificity measurements fromthe same single cells
• Combined with developments from Immudex and BioLegend we are able toprovide an end-to-end solution for analysis of the tumor microenvironment
This technology allows:
• Cell type characterization andidentification of full length, pairedTCR sequences with specificity forknown antigens
• Characterization of the adaptiveimmune response at unprecedentedresolution
• A truer understanding the complexityof the tumor microenvironment
• The potential for the discovery ofnovel TCR: antigen bindingrelationships
Feature Barcoding technology workflow for the multi-omic characterizationof single cells.
A. Gating strategy used in flow cytometry to isolate CD4-/CD8a+/Dextramer+ cells.B. Single Cell Immune Profiling with Feature Barcoding technology workflow where gene
expression and immune repertoire libraries are generated alongside libraries fromDNA barcodes conjugated to TotalSeq™-C antibodies or dCODE™ Dextramer®reagents, allowing quantification of cell surface proteins and identification of TCRspecificities. Representative Bioanalyzer traces showing average size distribution foramplified cDNA and for each of the generated libraries are shown in the figure.
The combination of gene expression and cell surface protein expressionusing labelled barcoded antibodies provides increased resolution of celltype characterization.
Unsorted PBMCs and CD4-/CD8a+/Dextramer+ sorted cells were aggregated, tSNEprojections generated by Cell Ranger and visualized in Loupe Cell Browser. Cells wereclustered on gene expression data with graph-based clustering. Each dot is a single cell.A. i. CMV seropositive donor colored based on sample. Unsorted PBMCs = grey (6770
cells), sorted cells = green (2038 cells).B. i. CMV seronegative donor colored based on sample. Unsorted PBMCs = grey (5998
cells), sorted cells = green (1566 cells).In ii. Cell type classification was performed using both gene expression data and surfaceprotein expression profiles.
Heatmaps show the significantly enriched (blue) or significantly under-represented (red) TCRclonotypes. Each column represents a TCR clonotype. The number of T cells with specificity fora particular Dextramer® (Specific binders) and the frequency of the T cell clonotype in the wholepopulation (Clonotype count) are outlined below each heatmap. For all samples, the top cellsranked by magnitude of their log10 p-values are shown, and at least ten cells were included foreach heatmap.
Feature Barcoding technology and flow cytometry identify similar frequencies ofDextramer® positive cells.
A. Feature Barcoding technology analysis with a CMV-specific dCODE™ Dextramer® panel.Positive cells are above the dashed lines with the background colored in pink.
B. Quantification of the fraction of positive binding cells as a percentage of the total number ofCD8+ cells identified by Feature Barcoding technology and by flow cytometry.
C. Flow cytometric analysis of the same CMV seropositive sample with the same dCODE™Dextramer® panel. Positive cells are inside the dashed box with pink background.
Clustering analysis of TCRclonotypes for CMV specificdCODE™ Dextramers® revealsboth novel and known CDR3amino acid sequences.
Paired TCR sequences were clusteredusing TCRdist (Dash et al. 2017) togenerate an average-linkagehierarchical tree, colored according tothe number of cells that share eachpaired TCR sequence (at thenucleotide level). # is the frequency atwhich the specific clone was detected.A. dCODE™ Dextramer® A*0101
VTEHDTLLY. 31 different TCRpairs identified.
B. dCODE™ Dextramer® B*0702RPHERNGFTVL. 8 different TCRpairs identified.
Analysis of TCR repertoires andtheir binding specificity incombination with gene and cellsurface protein expression,provides a high resolution viewof T cell activity at the single celllevel.
Cell clustering and classification of thesorted cell populations was based on:i. Gene expressionii. Cell surface protein expression
based on binding of BioLegendTotalSeq™-C antibodies.
iii. TCR specificity based ondCODE™ Dextramer® binding.Highlighted clusters showsignificantly enriched binding overthe rest of the cell population,p<0.001.The paired TCR clonotype genecalls for the top 10 clonotypes inthe dominant cluster, are shown.
Many statistically significant specific TCR: dCODE™ Dextramer® binding eventswere identified in the sorted cells (i) whereas very few are identified in theunsorted PBMCs (ii).
Green boxes indicates amino acid sequences that are identified with the samebinding specificities in VDJdb; in B. the TCRA had a 1 amino acid substitution fromthe identified sequence in VDJdb.
For a pdf version of this poster, visit the 10x Genomics website:https://www.10xgenomics.com/resources/posters/
Based on analysis of theCMV seropositive donorCD4-/CD8a+/Dextramer+sorted cells.
Samples were obtained from a CMVseropositive and seronegative donor.Cells were stained with panels ofoligonucleotide conjugated antibodies(BioLegend) and Dextramers(Immudex). Each sample was split intotwo, one half was sorted for CD4-/CD8a+/Dextramer+ cells, and the otherhalf left unsorted. The four samples(CMV seropositive and seronegative,sorted and unsorted) were takenthrough the workflow as outlined inFigure 1.
For further information on dCODE™ Dextramers® see Immudex poster P56.
