Single-Cell RNA-Sequencing of Peripheral Blood Mononuclear Cells with ddSEQ

Author(s):  
Shaheen Khan ◽  
Kelly A. Kaihara
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).


2021 ◽  
Author(s):  
Michael Hagemann-Jensen ◽  
Christoph Ziegenhain ◽  
Rickard Sandberg

Plate-based single-cell RNA-sequencing methods with full-transcript coverage typically excel at sensitivity but are more resource and time-consuming. Here, we miniaturized and streamlined the Smart-seq3 protocol for drastically reduced cost and increased throughput. Applying Smart-seq3xpress to 16,349 human peripheral blood mononuclear cells revealed a highly granular atlas complete with both common and rare cell types whose identification previously relied on additional protein measurements or the integration with a reference atlas.


Author(s):  
Qing Gao ◽  
Jinge Yu ◽  
Zuoguan Chen ◽  
Yongpeng Diao ◽  
Yuqing Miao ◽  
...  

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.


2021 ◽  
Author(s):  
Cantong Zhang ◽  
Xiaoping Hong ◽  
Haiyan Yu ◽  
Hongwei Wu ◽  
Huixuan Xu ◽  
...  

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.


2021 ◽  
Vol 12 ◽  
Author(s):  
Daniel J. B. Clarke ◽  
Alison W. Rebman ◽  
Allison Bailey ◽  
Megan L. Wojciechowicz ◽  
Sherry L. Jenkins ◽  
...  

Although widely prevalent, Lyme disease is still under-diagnosed and misunderstood. Here we followed 73 acute Lyme disease patients and uninfected controls over a period of a year. At each visit, RNA-sequencing was applied to profile patients' peripheral blood mononuclear cells in addition to extensive clinical phenotyping. Based on the projection of the RNA-seq data into lower dimensions, we observe that the cases are separated from controls, and almost all cases never return to cluster with the controls over time. Enrichment analysis of the differentially expressed genes between clusters identifies up-regulation of immune response genes. This observation is also supported by deconvolution analysis to identify the changes in cell type composition due to Lyme disease infection. Importantly, we developed several machine learning classifiers that attempt to perform various Lyme disease classifications. We show that Lyme patients can be distinguished from the controls as well as from COVID-19 patients, but classification was not successful in distinguishing those patients with early Lyme disease cases that would advance to develop post-treatment persistent symptoms.


2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi125-vi125
Author(s):  
Sophie Dusoswa ◽  
Jan Verhoeff ◽  
Matheus Crommentuijn ◽  
Tom Würdinger ◽  
David Noske ◽  
...  

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