scholarly journals An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples

2019 ◽  
Author(s):  
Richa Hanamsagar ◽  
Timothy Reizis ◽  
Mathew Chamberlain ◽  
Robert Marcus ◽  
Frank O. Nestle ◽  
...  

AbstractEstablishing clinically relevant single-cell (SC) transcriptomic workflows from cryopreserved tissue is essential to move this emerging immune monitoring technology from the bench to the bedside. Improper sample preparation leads to detrimental cascades, resulting in loss of precious time, money and finally compromised data. There is an urgent need to establish protocols specifically designed to overcome the inevitable variations in sample quality resulting from uncontrollable factors in a clinical setting. Here, we explore sample preparation techniques relevant to a range of clinically relevant scenarios, where SC gene expression and repertoire analysis are applied to a cryopreserved sample derived from a small amount of blood, with unknown or partially known preservation history. We compare a total of ten cell-counting, viability-improvement, and lymphocyte-enrichment methods to highlight a number of unexpected findings. Trypan blue-based automated counters, typically recommended for single-cell sample quantitation, consistently overestimate viability. Advanced sample clean-up procedures significantly impact total cell yield, while only modestly increasing viability. Finally, while pre-enrichment of B cells from whole peripheral blood mononuclear cells (PBMCs) results in the most reliable BCR repertoire data, comparable T-cell enrichment strategies distort the ratio of CD4+ and CD8+ cells. Furthermore, we provide high-resolution analysis of gene expression and clonotype repertoire of different B cell subtypes. Together these observations provide both qualitative and quantitative sample preparation guidelines that increase the chances of obtaining high-quality single-cell transcriptomic and repertoire data from human PBMCs in a variety of clinical settings.

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Christopher S. McGinnis ◽  
David A. Siegel ◽  
Guorui Xie ◽  
George Hartoularos ◽  
Mars Stone ◽  
...  

Abstract Background Single-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures. Results Here, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets. Conclusions We demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2406-2406 ◽  
Author(s):  
Ruth-Anne Langan ◽  
Dustin Shilling ◽  
Michael Gonzalez ◽  
Charlly Kao ◽  
Hakon Hakonarson ◽  
...  

Abstract Idiopathic multicentric Castleman disease (iMCD) is a rare and deadly hematologic illness involving episodic disease flares with polyclonal lymphoproliferation, systemic inflammation, and multiple organ system dysfunction. A cytokine storm involving interleukin(IL)-6 is believed to drive disease pathogenesis in some patients. However, only 34% of patients were found to respond to anti-IL-6 therapy with siltuximab in its registrational clinical trial; no other FDA approved treatments exist for iMCD. With the 5- and 10-year mortality rates reported as 35% and 60%, respectively, there is a clear need for additional treatment options. However, the development of next generation therapeutics is challenging as the etiology, pathological cell types, and signaling pathways involved in iMCD are largely unknown. To identify pathophysiological mechanisms and cellular drivers of iMCD, we applied cutting edge single-cell RNA-sequencing (scRNA-seq) technology to investigate bulk peripheral blood mononuclear cells (PBMCs) isolated from an iMCD patient at two distinct stages of disease activity. The first sample was collected during a short remission period following the patient's first disease flare (partial remission) (clinical symptom: fatigue; laboratory tests: hemoglobin 11.2 g/dL, platelets: 225,000/µL; albumin 4.2 g/dL, creatinine 0.73 mg/dL) and a second sample was collected at the start of his second flare (flare 2) (clinical symptoms: fatigue, fever, night sweats and fluid accumulation; laboratory tests: hemoglobin 12.9 g/dL, platelets: 122,000/µL; albumin 2.3 g/dL, creatinine 1.48 mg/dL). We utilized the Cellranger pipeline (10x Genomics, v.2.1.0) for aggregation of single-cell transcriptomes and Loupe Cell Browser (10x Genomics, v.2.1.0) for initial analysis of 20,135 recovered cells from partial remission (16,283 means reads/cell, 799 median genes/cell) and 19,322 recovered cells in flare 2 (17,327 reads/cell, 823 median genes/cell). Initial analyses of clusters revealed changes in the composition and frequency of immune cell subsets between the two samples. Plasmablasts (identified as expressing CD19, CD27, CD38, CD79a, CD79b) increased 7-fold in number during flare 2 with 28 cells in partial remission and 216 cells in flare 2. Similarly, monocyte and macrophage cell populations increased in frequency from 9% of all PBMCs in the partial remission sample to 15% of all PBMCs in the flare 2 sample. Conversely, CD8+ T cell frequency in the dataset decreased from 22% of the partial remission sample to 13% in flare 2. Interrogation of gene expression profiles of immune cell clusters identified highly activated CD8+ T cells which increased in frequency during flare 2 and are characterized by an inflammatory gene signature including expression of perforin and granzyme. Additionally, inflammatory gene signatures within the myeloid cell compartment during flare were identified, including elevated expression of S100 family members. S100 proteins are implicated in the pathogenesis of a number of autoimmune diseases and contribute to immune cell migration, chemotaxis, and leukocyte invasion. To our knowledge this is the first application of cutting edge single-cell sequencing technology to PBMCs obtained from an iMCD patient in flare and remission. Our observations support a role for both T and B cell activation in iMCD flare and lead us to hypothesize that CD8+ T cells may have left circulation and migrated to sites of active inflammation during this patient's disease flare. This dataset demonstrates involvement of multiple immune cell populations and inflammatory gene programs during disease flare in this patient and provides a novel resource for understanding gene expression and cell population changes in Castleman disease. Disclosures Fajgenbaum: Janssen Pharmaceuticals, Inc.: Research Funding.


2021 ◽  
Author(s):  
Roy Oelen ◽  
Dylan H. de Vries ◽  
Harm Brugge ◽  
Gracie Gordon ◽  
Martijn Vochteloo ◽  
...  

Gene expression and its regulation can be context-dependent. To dissect this, using samples from 120 individuals, we single-cell RNA-sequenced 1.3M peripheral blood mononuclear cells exposed to three different pathogens at two time points or left unexposed. This revealed thousands of cell type-specific expression changes (eQTLs) and pathogen-induced expression changes (response QTLs) that are influenced by genetic variation. In monocytes, the strongest responder to pathogen stimulations, genetics also affected co-expression of 71.4% of these eQTL genes. For example, the pathogen recognition receptor CLEC12A showed many such co-expression interactions, but only in monocytes after 3h pathogen stimulation. Further analysis linked this to interferon-regulating transcription factors, a finding that we recapitulated in an independent cohort of patients with systemic lupus erythematosus, a condition characterized by increased interferon activity. Altogether, this study highlights the importance of context for gaining a better understanding of the mechanisms of gene regulation in health and disease.


2020 ◽  
Author(s):  
Nghia Millard ◽  
Ilya Korsunsky ◽  
Kathryn Weinand ◽  
Chamith Y. Fonseka ◽  
Aparna Nathan ◽  
...  

AbstractAs advances in single-cell technologies enable the unbiased assay of thousands of cells simultaneously, human disease studies are able to identify clinically associated cell states using case-control study designs. These studies require precious clinical samples and costly technologies; therefore, it is critical to employ study design principles that maximize power to detect cell state frequency shifts between conditions, such as disease versus healthy. Here, we present single-cell Power Simulation Tool (scPOST), a method that enables users to estimate power under different study designs. To approximate the specific experimental and clinical scenarios being investigated, scPOST takes prototype (public or pilot) single-cell data as input and generates large numbers of single-cell datasets in silico. We use scPOST to perform power analyses on three independent single-cell datasets that span diverse experimental conditions: a batch-corrected 21-sample rheumatoid arthritis dataset (5,265 cells) from synovial tissue, a 259-sample tuberculosis progression dataset (496,517 memory T cells) from peripheral blood mononuclear cells (PBMCs), and a 30-sample ulcerative colitis dataset (235,229 cells) from intestinal biopsies. Over thousands of simulations, we consistently observe that power to detect frequency shifts in cell states is maximized by larger numbers of independent clinical samples, reduced batch effects, and smaller variation in a cell state’s frequency across samples.


2020 ◽  
Author(s):  
Christopher S. McGinnis ◽  
David A. Siegel ◽  
Guorui Xie ◽  
Mars Stone ◽  
Zev J. Gartner ◽  
...  

ABSTRACTSingle-cell RNA sequencing (scRNA-seq) provides high-dimensional measurement of transcript counts in individual cells. However, high assay costs limit the study of large numbers of samples. Sample multiplexing technologies such as antibody hashing and MULTI-seq use sample-specific sequence tags to enable individual samples (e.g., different patients) to be sequenced in a pooled format before downstream computational demultiplexing. Critically, no study to date has evaluated whether the mixing of samples from different donors in this manner results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self immune antigens). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures,. Here, we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from a single donor with and without pooling with PBMCs isolated from other donors with different blood types. We find that there was no evidence of alloreactivity in the multiplexed samples following three distinct multiplexing workflows (antibody hashing, MULTI-seq, and in silico genotyping using souporcell). Moreover, we identified biases amongst antibody hashing sample classification results in this particular experimental system, as well as gene expression signatures linked to PBMC preparation method (e.g., Ficoll-Paque density gradient centrifugation with or without apheresis using Trima filtration).


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Ruoxi Yu ◽  
Yin Yang ◽  
Yuanyuan Han ◽  
Pengwei Hou ◽  
Yingshuai Li ◽  
...  

Objectives. Differences among healthy subjects and associated disease risks are of substantial interest in clinical medicine. According to the theory of “constitution-disease correlation” in traditional Chinese medicine, we try to find out if there is any connection between intolerance of cold in Yang deficiency constitution and molecular evidence and if there is any gene expression basis in specific disorders. Methods. Peripheral blood mononuclear cells were collected from Chinese Han individuals with Yang deficiency constitution (n=20) and balanced constitution (n=8) (aged 18–28) and global gene expression profiles were determined between them using the Affymetrix HG-U133 Plus 2.0 array. Results. The results showed that when the fold change was ≥1.2 and q ≤ 0.05, 909 genes were upregulated in the Yang deficiency constitution, while 1189 genes were downregulated. According to our research differential genes found in Yang deficiency constitution were usually related to lower immunity, metabolic disorders, and cancer tendency. Conclusion. Gene expression disturbance exists in Yang deficiency constitution, which corresponds to the concept of constitution and gene classification. It also suggests people with Yang deficiency constitution are susceptible to autoimmune diseases, enteritis, arthritis, metabolism disorders, and cancer, which provides molecular evidence for the theory of “constitution-disease correlation.”


Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 248
Author(s):  
Alexander A. Lehmann ◽  
Pedro A. Reche ◽  
Ting Zhang ◽  
Maneewan Suwansaard ◽  
Paul V. Lehmann

Monitoring antigen-specific T cell immunity relies on functional tests that require T cells and antigen presenting cells to be uncompromised. Drawing of blood, its storage and shipment from the clinical site to the test laboratory, and the subsequent isolation, cryopreservation and thawing of peripheral blood mononuclear cells (PBMCs) before the actual test is performed can introduce numerous variables that may jeopardize the results. Therefore, no T cell test is valid without assessing the functional fitness of the PBMC being utilized. This can only be accomplished through the inclusion of positive controls that actually evaluate the performance of the antigen-specific T cell and antigen presenting cell (APC) compartments. For Caucasians, CEF peptides have been commonly used to this extent. Moreover, CEF peptides only measure CD8 cell functionality. We introduce here universal CD8+ T cell positive controls without any racial bias, as well as positive controls for the CD4+ T cell and APC compartments. In summary, we offer new tools and strategies for the assessment of PBMC functional fitness required for reliable T cell immune monitoring.


2021 ◽  
Author(s):  
Emily Stephenson ◽  
◽  
Gary Reynolds ◽  
Rachel A. Botting ◽  
Fernando J. Calero-Nieto ◽  
...  

AbstractAnalysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ailu Chen ◽  
Maria P. Diaz-Soto ◽  
Miguel F. Sanmamed ◽  
Taylor Adams ◽  
Jonas C. Schupp ◽  
...  

Abstract Background Asthma has been associated with impaired interferon response. Multiple cell types have been implicated in such response impairment and may be responsible for asthma immunopathology. However, existing models to study the immune response in asthma are limited by bulk profiling of cells. Our objective was to Characterize a model of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA) and its response to the TLR3 agonist Poly I:C using two single-cell methods. Methods Two complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA patients and healthy controls (HC). Poly I:C-stimulated and unstimulated cells were analyzed in this study. Results PBMCs (n = 9414) from five SA (n = 6099) and three HC (n = 3315) were profiled using scRNA-Seq. Six main cell subsets, namely CD4 + T cells, CD8 + T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4 + T cells were the main cell type in SA and demonstrated a pro-inflammatory profile characterized by increased JAK1 expression. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. CyTOF profiling of Poly I:C stimulated and unstimulated PBMCs (n = 160,000) from the same individuals (SA = 5; HC = 3) demonstrated higher CD8 + and CD8 + effector T cells in SA at baseline, followed by a decrease of CD8 + effector T cells after poly I:C stimulation. Conclusions Single-cell profiling of an in vitro model using PBMCs in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8 + effector cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in this model to evaluate interferon responses in severe asthma.


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