scholarly journals Cell properties assessment using optimized dielectrophoresis-based cell stretching and lumped mechanical modeling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Imman I. Hosseini ◽  
Mahdi Moghimi Zand ◽  
Amir Ali Ebadi ◽  
Morteza Fathipour

AbstractCells mechanical property assessment has been a promising label-free method for cell differentiation. Several methods have been proposed for single-cell mechanical properties analysis. Dielectrophoresis (DEP) is one method used for single-cell mechanical property assessment, cell separation, and sorting. DEP method has overcome weaknesses of other techniques, including compatibility with microfluidics, high throughput assessment, and high accuracy. However, due to the lack of a general and explicit model for this method, it has not been known as an ideal cell mechanical property evaluation method. Here we present an explicit model using the most general electromagnetic equation (Maxwell Stress Tensor) for single-cell mechanical evaluation based on the DEP method. For proof of concept, we used the proposed model for differentiation between three different types of cells, namely erythrocytes, peripheral blood mononuclear cells (PBMC), and an epithelial breast cancer cells line (T-47D). The results show that, by a lumped parameter that depends on cells' mechanical and electrical properties, the proposed model can successfully distinguish between the mentioned cell types that can be in a single blood sample. The proposed model would open up the chance to use a mechanical assessment method for cell searching in parallel with other methods.

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.


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 ◽  
Author(s):  
Zhibin Li ◽  
chengcheng Sun ◽  
Fei Wang ◽  
Xiran Wang ◽  
Jiacheng Zhu ◽  
...  

Background: Immune cells play important roles in mediating immune response and host defense against invading pathogens. However, insights into the molecular mechanisms governing circulating immune cell diversity among multiple species are limited. Methods: In this study, we compared the single-cell transcriptomes of 77 957 immune cells from 12 species using single-cell RNA-sequencing (scRNA-seq). Distinct molecular profiles were characterized for different immune cell types, including T cells, B cells, natural killer cells, monocytes, and dendritic cells. Results: The results revealed the heterogeneity and compositions of circulating immune cells among 12 different species. Additionally, we explored the conserved and divergent cellular cross-talks and genetic regulatory networks among vertebrate immune cells. Notably, the ligand and receptor pair VIM-CD44 was highly conserved among the immune cells. Conclusions: This study is the first to provide a comprehensive analysis of the cross-species single-cell atlas for peripheral blood mononuclear cells (PBMCs). This research should advance our understanding of the cellular taxonomy and fundamental functions of PBMCs, with important implications in evolutionary biology, developmental biology, and immune system disorders


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Alex R Schuurman ◽  
Tom DY Reijnders ◽  
Anno Saris ◽  
Ivan Ramirez Moral ◽  
Michiel Schinkel ◽  
...  

The exact immunopathophysiology of community-acquired pneumonia (CAP) caused by SARS-CoV-2 (COVID-19) remains clouded by a general lack of relevant disease controls. The scarcity of single-cell investigations in the broader population of patients with CAP renders it difficult to distinguish immune features unique to COVID-19 from the common characteristics of a dysregulated host response to pneumonia. We performed integrated single-cell transcriptomic and proteomic analyses in peripheral blood mononuclear cells from a matched cohort of eight patients with COVID-19, eight patients with CAP caused by Influenza A or other pathogens, and four non-infectious control subjects. Using this balanced, multi-omics approach, we describe shared and diverging transcriptional and phenotypic patterns—including increased levels of type I interferon-stimulated natural killer cells in COVID-19, cytotoxic CD8 T EMRA cells in both COVID-19 and influenza, and distinctive monocyte compositions between all groups—and thereby expand our understanding of the peripheral immune response in different etiologies of pneumonia.


The Analyst ◽  
2019 ◽  
Vol 144 (8) ◽  
pp. 2574-2583 ◽  
Author(s):  
S. Hazra ◽  
K. S. Jayaprakash ◽  
K. Pandian ◽  
A. Raj ◽  
S. K. Mitra ◽  
...  

We present a novel label-free passive microfluidic technique for isolation of cancer cells (EpCAM+ and CD45−) from peripheral blood mononuclear cells (PBMCs) (CD45+ and EpCAM−) in aqueous two-phase system (ATPS).


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

2018 ◽  
Author(s):  
Neo Christopher Chung

AbstractSingle cell RNA sequencing (scRNA-seq) allows us to dissect transcriptional heterogeneity arising from cellular types, spatio-temporal contexts, and environmental stimuli. Cell identities of samples derived from heterogeneous subpopulations are routinely determined by clustering of scRNA-seq data. Computational cell identities are then used in downstream analysis, feature selection, and visualization. However, how can we examine if cell identities are accurately inferred? To this end, we introduce non-parametric methods to evaluate cell identities by testing cluster memberships of single cell samples in an unsupervised manner. We propose posterior inclusion probabilities for cluster memberships to select and visualize samples relevant to subpopulations. Beyond simulation studies, we examined two scRNA-seq data - a mixture of Jurkat and 293T cells and a large family of peripheral blood mononuclear cells. We demonstrated probabilistic feature selection and improved t-SNE visualization. By learning uncertainty in clustering, the proposed methods enable rigorous testing of cell identities in scRNA-seq.


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