Massively parallel digital transcriptional profiling of single cells methods
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Single-cell RNA profiling of cryopreserved PBMCs
To determine the effect that a freeze-thaw might have on gene expression and thus on the ability of our scRNA-seq pipeline to classify cell type in frozen repository specimens, we froze the remaining fresh PBMCs from Donor A, and made a scRNA-seq library from gently thawed cells 3 weeks later where ∼3k cells were recovered (Supplementary Methods). The two data sets (fresh and frozen) showed a high similarity between their average gene expression ( r =0.96; Supplementary Methods and ). Fifty-seven genes showed twofold upregulation in the frozen sample, with ∼50% being ribosomal protein genes, and the rest not enriched in any pathways ( ). In addition, the number of genes and UMI counts detected from fresh and frozen PBMCs was very similar ( P =0.8 and 0.1, respectively), suggesting that the conversion efficiency of the system is not compromised when profiling frozen cells (...
Genotype-based method to detect individual cell populations
Next, we applied the GemCode technology to study host and donor cell chimerism in an allogeneic hematopoietic stem cell transplant (HSCT) setting. Following a stem cell transplant, it is important to monitor the proportion of donor and host cells in major cell lineages to ensure complete engraftment and as a sensitive means of detecting impending relapse. Currently, the amount of host and donor chimerism is often measured from flow-sorted cell populations using PCR assays with a panel of SNV-specific primers. Current clinical chimerism tests have a number of limitations, namely (1) the flow-sorted cell populations are limited by cell surface markers, (2) only populations with sufficient cell counts can be used for PCR assays and (3) they are not intended for the detection of minimal residual disease. Here we present a simple method that addresses these limitations, resolves host and...
Genotype-based method to detect individual cell populations
While previous studies have used existing SNVs from DNA sequencing or large-scale copy number changes in the transcriptome data to distinguish cells by genotype, these methods cannot be applied to transplant samples where donor and host genotype is not known a priori, and when donor and host are closely matched in genotype. To address these limitations, we first developed a method to infer the relative presence of host and donor genotypes in a mixed population based on SNVs directly predicted from the transcriptome data. The method identifies SNVs and infers a genotype at each SNV. It then classifies cells based on their genotypes across all SNVs (Supplementary Methods).
Single-cell analysis of transplant bone marrow samples
Single-cell RNA-seq libraries were generated from cryopreserved bone marrow mononuclear cell (BMMC) samples obtained from two patients before and after undergoing HSCT for AML (AML027 and AML035) ( ). Since HSCT samples are fragile, cells were carefully washed in PBS with 20% fetal bovine serum (FBS) before loading them into chips. Relative to BMMCs from two healthy controls, we found the median number of UMI counts per cell to be 3-5 times higher in AML samples at ∼15k reads per cell, suggesting their vastly abnormal transcriptional programs ( ). Approximately 35 and 60 SNVs per cell were detected from AML027 and AML035 pre-transplant samples, respectively ( and ). Our SNV analysis detected the presence of two genotypes in the post-transplant sample of AML027: one at 13.8% and one at 86.2% ( ). As expected, there was no evidence of multiple genotype groups in the pre-tran...
Single-cell analysis of transplant bone marrow samples
SNV and scRNA-seq analyses enable subpopulation comparison between individuals within and across multiple samples. We applied these analyses on BMMC scRNA-seq data from healthy controls and AML patients (Supplementary Methods), and observed subpopulation differences in AML patients after HSCT. First, while T cells dominate the healthy BMMCs and donor cells of the AML027 post-transplant sample as expected, erythroids constitute the largest population among AML samples ( ). Different sets of progenitor and differentiation markers (for example, CD34, GATA1, CD71 and HBA1 ) were detected among the erythroids, indicating populations at various stages of erythroid development (Supplementary Methods and ). AML027 showed the highest level of erythroid cells (>80%, consist of mostly mature erythroids) before transplant, consistent with the erythroleukaemia diagnosis of AML027 ( ). In contras...
Cell lines and transplant patient samples
Jurkat (ATCC TIB-152), 293T (ATCC CRL-11268) and 3T3 (ATCC CRL-1658) cells were acquired from ATCC and cultured according to ATCC guidelines. Fresh PBMCs, frozen PBMCs and BMMCs were purchased from ALLCELLS. Frozen PBMCs from Donor A were made from fresh PBMCs from Donor A by mixing 1e 6 cells in freezing medium (15% dimethylsulphoxide (DMSO) in Iscove's modified Dulbecco's media containing 20% FBS) gently, and chilled in CoolCell FTS30 (BioCision) in -80 °C for at least 4 h before transferring to liquid nitrogen for storage for 3 weeks.
Cell lines and transplant patient samples
The Institutional Review Board at the Fred Hutchinson Cancer Research Center approved the study on transplant samples. The procedures followed were in accordance with the Declaration of Helsinki of 1975 and the Common Rule. Samples were obtained after patients had provided written informed consent on molecular analyses. We identified patients with AML undergoing allogeneic hematopoietic stem cell transplant at the Fred Hutchinson Cancer Research Center. The diagnosis of AML was established according to the revised criteria of the World Health Organization.
Cell lines and transplant patient samples
Bone marrow aspirates were obtained for standard clinical testing 20-30 days before transplant and serially post-transplanted according to the treatment protocol. Bone marrow aspirate aliquots were processed within 2 h of the draw. The BMMCs were isolated using centrifugation through a Ficoll gradient (Histopaque-1077; Sigma Life Science, St Louis, MO, USA). The BMMCs were collected from the serum-Ficoll interface with a disposable Pasteur pipette and transferred to the 50 ml conical tube with 2% patient serum in 1 × PBS. The BMMCs were counted using a haemacytometer and viability was assessed using Trypan blue. The BMMCs were resuspended in 90% FBS, 10% DMSO freezing media and frozen using a Thermo Scientific Nalgene Mr Frosty (Thermo Scientific) in a -80 °C freezer for 24 h before being transferred to liquid nitrogen for long-term storage.
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Evidence quotes (8)
To determine the effect that a freeze-thaw might have on gene expression and thus on the ability of our scRNA-seq pipeline to classify cell type in frozen repository specimens, we froze the remaining fresh PBMCs from Donor A, and made a scRNA-seq library from gently thawed cells 3 weeks later where ∼3k cells were recovered (Supplementary Methods). The two data sets (fresh and frozen) showed a high similarity between their average gene expression ( r =0.96; Supplementary Methods and ). Fifty-seven genes showed twofold upregulation in the frozen sample, with ∼50% being ribosomal protein genes, and the rest not enriched in any pathways ( ). In addition, the number of genes and UMI counts detected from fresh and frozen PBMCs was very similar ( P =0.8 and 0.1, respectively), suggesting that the conversion efficiency of the system is not compromised when profiling frozen cells ( ). Furthermore, subpopulations were detected from frozen PBMCs at a similar proportion to that of fresh PBMCs, demonstrating the applicability of our method on frozen samples (Supplementary Methods and ).
Next, we applied the GemCode technology to study host and donor cell chimerism in an allogeneic hematopoietic stem cell transplant (HSCT) setting. Following a stem cell transplant, it is important to monitor the proportion of donor and host cells in major cell lineages to ensure complete engraftment and as a sensitive means of detecting impending relapse. Currently, the amount of host and donor chimerism is often measured from flow-sorted cell populations using PCR assays with a panel of SNV-specific primers. Current clinical chimerism tests have a number of limitations, namely (1) the flow-sorted cell populations are limited by cell surface markers, (2) only populations with sufficient cell counts can be used for PCR assays and (3) they are not intended for the detection of minimal residual disease. Here we present a simple method that addresses these limitations, resolves host and donor chimerism at single-cell resolution and enables extensive characterization of cell subtypes by integrating scRNA-seq with de novo SNV calling.
While previous studies have used existing SNVs from DNA sequencing or large-scale copy number changes in the transcriptome data to distinguish cells by genotype, these methods cannot be applied to transplant samples where donor and host genotype is not known a priori, and when donor and host are closely matched in genotype. To address these limitations, we first developed a method to infer the relative presence of host and donor genotypes in a mixed population based on SNVs directly predicted from the transcriptome data. The method identifies SNVs and infers a genotype at each SNV. It then classifies cells based on their genotypes across all SNVs (Supplementary Methods).
Single-cell RNA-seq libraries were generated from cryopreserved bone marrow mononuclear cell (BMMC) samples obtained from two patients before and after undergoing HSCT for AML (AML027 and AML035) ( ). Since HSCT samples are fragile, cells were carefully washed in PBS with 20% fetal bovine serum (FBS) before loading them into chips. Relative to BMMCs from two healthy controls, we found the median number of UMI counts per cell to be 3-5 times higher in AML samples at ∼15k reads per cell, suggesting their vastly abnormal transcriptional programs ( ). Approximately 35 and 60 SNVs per cell were detected from AML027 and AML035 pre-transplant samples, respectively ( and ). Our SNV analysis detected the presence of two genotypes in the post-transplant sample of AML027: one at 13.8% and one at 86.2% ( ). As expected, there was no evidence of multiple genotype groups in the pre-transplant host sample. We compared the major and minor inferred genotypes present in the post-transplant sample to the genotype found in the host cells. The major inferred genotype in the post-transplant sample was 97% similar to that inferred from the host sample, while the minor inferred genotype was...
SNV and scRNA-seq analyses enable subpopulation comparison between individuals within and across multiple samples. We applied these analyses on BMMC scRNA-seq data from healthy controls and AML patients (Supplementary Methods), and observed subpopulation differences in AML patients after HSCT. First, while T cells dominate the healthy BMMCs and donor cells of the AML027 post-transplant sample as expected, erythroids constitute the largest population among AML samples ( ). Different sets of progenitor and differentiation markers (for example, CD34, GATA1, CD71 and HBA1 ) were detected among the erythroids, indicating populations at various stages of erythroid development (Supplementary Methods and ). AML027 showed the highest level of erythroid cells (>80%, consist of mostly mature erythroids) before transplant, consistent with the erythroleukaemia diagnosis of AML027 ( ). In contrast, after transplant, AML027 showed the highest level of blast cells and immature erythroids ( CD34+, GATA1 +), consistent with the relapse diagnosis and return of the malignant host AML ( ). These observations would have been difficult to make with FACS analysis, with limited number of markers for...
Jurkat (ATCC TIB-152), 293T (ATCC CRL-11268) and 3T3 (ATCC CRL-1658) cells were acquired from ATCC and cultured according to ATCC guidelines. Fresh PBMCs, frozen PBMCs and BMMCs were purchased from ALLCELLS. Frozen PBMCs from Donor A were made from fresh PBMCs from Donor A by mixing 1e 6 cells in freezing medium (15% dimethylsulphoxide (DMSO) in Iscove's modified Dulbecco's media containing 20% FBS) gently, and chilled in CoolCell FTS30 (BioCision) in -80 °C for at least 4 h before transferring to liquid nitrogen for storage for 3 weeks.
The Institutional Review Board at the Fred Hutchinson Cancer Research Center approved the study on transplant samples. The procedures followed were in accordance with the Declaration of Helsinki of 1975 and the Common Rule. Samples were obtained after patients had provided written informed consent on molecular analyses. We identified patients with AML undergoing allogeneic hematopoietic stem cell transplant at the Fred Hutchinson Cancer Research Center. The diagnosis of AML was established according to the revised criteria of the World Health Organization.
Bone marrow aspirates were obtained for standard clinical testing 20-30 days before transplant and serially post-transplanted according to the treatment protocol. Bone marrow aspirate aliquots were processed within 2 h of the draw. The BMMCs were isolated using centrifugation through a Ficoll gradient (Histopaque-1077; Sigma Life Science, St Louis, MO, USA). The BMMCs were collected from the serum-Ficoll interface with a disposable Pasteur pipette and transferred to the 50 ml conical tube with 2% patient serum in 1 × PBS. The BMMCs were counted using a haemacytometer and viability was assessed using Trypan blue. The BMMCs were resuspended in 90% FBS, 10% DMSO freezing media and frozen using a Thermo Scientific Nalgene Mr Frosty (Thermo Scientific) in a -80 °C freezer for 24 h before being transferred to liquid nitrogen for long-term storage.
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