scholarly journals Single-cell RNA sequencing of peripheral blood mononuclear cells from the patient with acute promyelocytic leukemia: a case study

2021 ◽  
Vol 6 ◽  
pp. 21-21
Author(s):  
Jun Liu ◽  
Lijuan Lu ◽  
Liting Liang ◽  
Hui Zhang ◽  
Xu Zhang
Keyword(s):  
Single Cell ◽  
Acute Promyelocytic Leukemia ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Promyelocytic Leukemia ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

scholarly journals The Characteristics of Peripheral Blood Mononuclear Cells in Takayasu Arteritis by Single Cell RNA Sequencing

2021 ◽  
Author(s):  
Qing Gao ◽  
Jinge Yu ◽  
Zuoguan Chen ◽  
Yongpeng Diao ◽  
Yuqing Miao ◽  
...  
Keyword(s):  
B Cells ◽  
Nk Cells ◽  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Takayasu Arteritis ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Objectives Takayasu Arteritis (TA) is a rare non-specific vascular inflammation and has deleterious effects on patients’ health. Recent studies have advanced in TA diagnosis and treatment, but the research on the immune cell atlas of peripheral blood is still less. For this purpose, we performed single-cell RNA sequencing (scRNA-seq) to analyze the inflammatory cell types and cell markers in TA patients’ Peripheral blood mononuclear cells (PBMCs). Methods 4 TA patients and 4 health controls were enrolled in our study from 2019.10 to 2020.5. Their PBMCs samples were collected and performed scRNA-seq. We used Seurat package (v.3.2.2) in R studio (v.3.5.3) for data analysis, and 2 tests were applied for comparing the composition ratio of each cell type by SPSS 20.0. Results CD14+ monocytes, GZMB+ NKT cells, CD56dim CD16+ NK cells, and naive B cells were significantly increased in TA patients as compared to healthy controls and the expression of THBS1, CD163, AREG, IFITM1, TXNIP, and IGHGs was elevated in the peripheral blood of TA patients. Conclusion Except CD4+ T cells, monocytes, NK cells, NKT cells, B cells also play an important role in TA pathogenesis. The elevated markers have different functions in different types of PBMCs, and they can be used as potential diagnostic markers for TA diagnosis.

scholarly journals No detectable alloreactive transcriptional responses during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

2020 ◽  
Author(s):  
Christopher S. McGinnis ◽  
David A. Siegel ◽  
Guorui Xie ◽  
Mars Stone ◽  
Zev J. Gartner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Transcriptional Responses ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

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).

scholarly journals Gene-regulatory network study of rheumatoid arthritis in single-cell chromatin landscapes of peripheral blood mononuclear cells

2021 ◽  
Author(s):  
Cantong Zhang ◽  
Xiaoping Hong ◽  
Haiyan Yu ◽  
Hongwei Wu ◽  
Huixuan Xu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells ◽  
High Resolution Map ◽  
The Impact ◽  
Accessible Chromatin

Abstract Rheumatoid arthritis is a chronic autoinflammatory disease with an elusive etiology. Assays for transposase-accessible chromatin with single-cell sequencing (scATAC-seq) contribute to the progress in epigenetic studies. However, the impact of epigenetic technology on autoimmune diseases has not been objectively analyzed. Therefore, scATAC-seq was performed to generate a high-resolution map of accessible loci in peripheral blood mononuclear cells (PBMCs) of RA patients at the single-cell level. The purpose of our project was to discover the transcription factors (TFs) that were involved in the pathogenesis of RA at single-cell resolution. In our research, we obtained 22 accessible chromatin patterns. Then, 10 key TFs were involved in the RA pathogenesis by regulating the activity of MAP kinase. Consequently, two genes (PTPRC, SPAG9) regulated by 10 key TFs were found that may be associated with RA disease pathogenesis and these TFs were obviously enriched in RA patients (p<0.05, FC>1.2). With further qPCR validation on PTPRC and SPAG9 in monocytes, we found differential expression of these two genes, which were regulated by eight TFs (ZNF384, HNF1B, DMRTA2, MEF2A, NFE2L1, CREB3L4 (var. 2), FOSL2::JUNB (var. 2), MEF2B). What is more, the eight TFs showed highly accessible binding sites in RA patients. These findings demonstrate the value of using scATAC-seq to reveal transcriptional regulatory variation in RA-derived PBMCs, providing insights on therapy from an epigenetic perspective.

scholarly journals IMMU-20. SINGLE CELL CYTOMICS OF PERIPHERAL BLOOD MONONUCLEAR CELLS REVEALS NEW AVENUES FOR GLIOMA IMMUNOTHERAPY

2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi125-vi125
Author(s):  
Sophie Dusoswa ◽  
Jan Verhoeff ◽  
Matheus Crommentuijn ◽  
Tom Würdinger ◽  
David Noske ◽  
...  
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells

scholarly journals Dynamic changes in human single cell transcriptional signatures during fatal sepsis

2021 ◽  
Author(s):  
Xinru Qiu ◽  
Jiang Li ◽  
Jeff Bonenfant ◽  
Lukasz Jaroszewski ◽  
Walter Klein ◽  
...  
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Metabolic Pathways ◽  
Mononuclear Cells ◽  
Immune Cell ◽  
Peripheral Blood Mononuclear ◽  
Repeated Measures Design ◽  
Blood Mononuclear Cells ◽  
Fatal Sepsis

AbstractSystemic infections, especially in patients with chronic diseases, result in sepsis: an explosive, uncoordinated immune response that can lead to multisystem organ failure with a high mortality rate. Sepsis survivors and non-survivors oftentimes have similar clinical phenotypes or sepsis biomarker expression upon diagnosis, suggesting that the dynamics of sepsis in the critical early stage may have an impact on these opposite outcomes. To investigate this, we designed a within-subject study of patients with systemic gram-negative bacterial sepsis with surviving and fatal outcomes and performed single-cell transcriptomic analyses of peripheral blood mononuclear cells (PBMC) collected during the critical period between sepsis recognition and 6 hours. We observed that the largest sepsis-induced expression changes over time in surviving versus fatal sepsis were in CD14+ monocytes, including gene signatures previously reported for sepsis outcomes. We further identify changes in the metabolic pathways of both monocytes and platelets, the emergence of erythroid precursors, and T cell exhaustion signatures, with the most extreme differences occurring between the non-sepsis control and the sepsis non-survivor. Our single-cell observations are consistent with trends from public datasets but also reveal specific effects in individual immune cell populations, which change within hours. In conclusion, this pilot study provides the first single-cell results with a repeated measures design in sepsis to analyze the temporal changes in the immune cell population behavior in surviving or fatal sepsis. These findings indicate that tracking temporal expression changes in specific cell-types could lead to more accurate predictions of sepsis outcomes. We also identify molecular pathways that could be therapeutically controlled to improve the sepsis trajectory toward better outcomes.Summary sentenceSingle cell transcriptomics of peripheral blood mononuclear cells in surviving and fatal sepsis reveal inflammatory and metabolic pathways that change within hours of sepsis recognition.

scholarly journals Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1297 ◽  
Author(s):  
Saskia Freytag ◽  
Luyi Tian ◽  
Ingrid Lönnstedt ◽  
Milica Ng ◽  
Melanie Bahlo
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Gold Standard ◽  
Mononuclear Cells ◽  
Rna Seq ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Silver Standard ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Background: The commercially available 10x Genomics protocol to generate droplet-based single cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as multiple silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also running time and robustness of a dozen methods. Results: We found that Seurat outperformed other methods, although performance seems to be dependent on many factors, including the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.

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