scholarly journals Multi-Dimensional Immuno-Profiling of Drosophila Hemocytes by Single Cell Mass Cytometry

2020 ◽  
Author(s):  
József Á. Balog ◽  
Viktor Honti ◽  
Éva Kurucz ◽  
Beáta Kari ◽  
László G. Puskás ◽  
...  

AbstractSingle cell mass cytometry (SCMC) combines features of traditional flow cytometry (FACS) with mass spectrometry and allows the measurement of several parameters at the single cell level, thus permitting a complex analysis of biological regulatory mechanisms. We optimized this platform to analyze the cellular elements, the hemocytes, of the Drosophila innate immune system. We have metal-conjugated six antibodies against cell surface antigens (H2, H3, H18, L1, L4, P1), against two intracellular antigens (3A5, L2) and one anti-IgM for the detection of L6 surface antigen, as well as one anti-GFP for the detection of crystal cells in the immune induced samples. We investigated the antigen expression profile of single cells and hemocyte populations in naive, in immune induced states, in tumorous mutants (hopTum bearing a driver mutation and l(3)mbn1 carrying deficiency of a tumor suppressor) as well as in stem cell maintenance defective hdcΔ84 mutant larvae. Multidimensional analysis enabled the discrimination of the functionally different major hemocyte subsets, lamellocytes, plasmatocytes, crystal cell, and delineated the unique immunophenotype of the mutants. We have identified sub-populations of L2+/P1+ (l(3)mbn1), L2+/L4+/P1+ (hopTum) transitional phenotype cells in the tumorous strains and a sub-population of L4+/P1+ cells upon immune induction. Our results demonstrated for the first time, that mass cytometry, a recent single cell technology combined with multidimensional bioinformatic analysis represents a versatile and powerful tool to deeply analyze at protein level the regulation of cell mediated immunity of Drosophila.

2021 ◽  
Author(s):  
Lijun Cheng ◽  
Pratik Karkhanis ◽  
Birkan Gokbag ◽  
Lang Li

Background :  Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional manual gating utilized to identify new cell populations has been inadequate, inefficient, unreliable, and difficult to use, and no algorithms to identify both calibration and new cell populations has been well established. Methods :   A deep learning with graphic cluster (DGCyTOF) visualization is developed as a new integrated embedding visualization approach in identifying canonical and new cell types. The DGCyTOF combines deep-learning classification and hierarchical stable-clustering methods to sequentially build a tri-layer construct for known cell types and the identification of new cell types. First, deep classification learning is constructed to distinguish calibration cell populations from all cells by softmax classification assignment under a probability threshold, and graph embedding clustering is then used to identify new cell populations sequentially. In the middle of two-layer, cell labels are automatically adjusted between new and unknown cell populations via a feedback loop using an iteration calibration system to reduce the rate of error in the identification of cell types, and a 3-dimensional (3D) visualization platform is finally developed to display the cell clusters with all cell-population types annotated. Results : Utilizing two benchmark CyTOF databases comprising up to 43 million cells, we compared accuracy and speed in the identification of cell types among DGCyTOF, DeepCyTOF, and other technologies including dimension reduction with clustering, including Principal Component Analysis ( PCA ) , Factor Analysis ( FA ), Independent Component Analysis ( ICA ), Isometric Feature Mapping ( Isomap ), t-distributed Stochastic Neighbor Embedding ( t-SNE ), and Uniform Manifold Approximation and Projection ( UMAP ) with k -means clustering and Gaussian mixture clustering. We observed the DGCyTOF represents a robust complete learning system with high accuracy, speed and visualization by eight measurement criteria. The DGCyTOF displayed F-scores of 0.9921 for CyTOF1 and 0.9992 for CyTOF2 datasets, whereas those scores were only 0.507 and 0.529 for the t-SNE + k-means ; 0.565 and 0.59, for UMAP + k-means . Comparison of DGCyTOF with t-SNE and UMAP visualization in accuracy demonstrated its approximately 35% superiority in predicting cell types. In addition, observation of cell-population distribution was more intuitive in the 3D visualization in DGCyTOF than t-SNE and UMAP visualization. Conclusions :  The DGCyTOF model can automatically assign known labels to single cells with high accuracy using deep-learning classification assembling with traditional graph-clustering and dimension-reduction strategies. Guided by a calibration system, the model seeks optimal accuracy balance among calibration cell populations and unknown cell types, yielding a complete and robust learning system that is highly accurate in the identification of cell populations compared to results using other methods in the analysis of single-cell CyTOF data. Application of the DGCyTOF method to identify cell populations could be extended to the analysis of single-cell RNASeq data and other omics data.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 906-906
Author(s):  
Jolanda Sarno ◽  
Kara L. Davis ◽  
Angela Maria Savino ◽  
Cristina Bugarin ◽  
Stefania Pinto ◽  
...  

Abstract BACKGROUND: Rearrangements of the CRLF2 gene, present in 7-15% of childhood BCP-ALL, are responsible of the overexpression of Thymic Stromal Lymphopoietin Receptor (TSLPR) and they are correlated with poor prognosis (Chen IM Blood 2012). TSLPR overexpression can be associated with JAK2 mutations, which leads to aberrant activation of JAK/STAT and PI3K/AKT pathways. Although the cross talk of the signaling pathways is still under investigation, there is a rationale for the use of targeted tyrosine kinase inhibitors (TKIs) to treat this subgroup of patients (Maude SL Blood 2012). We focused on the dissection of CRLF2-driven signaling in primary CRLF2 rearranged(r) BCP-ALL samples by using single cell mass cytometry (CyTOF) analysis. We leveraged the high dimensional single cell capability of the CyTOF to understand, with previously unattainable resolution, the activation of these pathways simultaneously in single cells and their response to inhibition with TKIs and anti-TSLPR monoclonal antibodies (mAbs). This revealed heterogeneity in signaling response, identifying subpopulations which differentially activate intracellular signals through TSLPR and differentially respond to ex vivo treatment. METHODS: Twelve BCP-ALL primary samples, 6 CRLF2r and 6 CRLF2 wild type (wt), were investigated and the expression of 24 phenotypic and 15 functional proteins were measured at single cell level using CyTOF as previous described (Bendall SC Science 2011). To assess the response to ex-vivo TSLP stimulation (10ng/mL) and TKIs/mAbs treatment, data were normalized to the basal levels of each phosphoprotein and significance was calculated using student`s t-test. One million cells per condition were treated with different TKIs, Dasatinib, Ruxolitinib and BEZ-235, and two different clones of anti-TSLPR mAbs (130A10 and 130H3) from MRC Technology. RESULTS: As expected, we observed an aberrant TSLP-induced activation of pSTAT5 and prpS6 in CRLF2r patients as compared with CRLF2wt, used as control group (p=0.0055, p= 0.0007). Of note, we also observed a previously not described TSLP-dependent activation of pERK and pCREB (p=0.0313, p=0.0261) suggesting a cross-talk of the TSLPR-driven signaling also with the RAS/MEK pathway. Treatment with TKIs revealed strong inhibitory activity of Dasatinib, which completely inhibited the TSLP-mediated phosphorylation of STAT5, rpS6, CREB and ERK in CRLF2r treated blasts compared to CRLF2r not treated cells (p= 0.0040, 0.0017, 0.0007, 0.0114 respectively). Ruxolitinib, JAK1/2 inhibitor, also reduced rpS6, CREB and ERK phosphorylation (p=0.0025, 0.037, 0.0132). Interestingly one of the two anti-TSLPR tested mAbs (130A10) was also able to significantly inhibit the TSLP-mediated activation of STAT5, rpS6, and ERK (p= 0.0071, 0.0006, 0.0323). Finally, the PI3K/TORk inhibitor, BEZ-235, did not show any statistically significant reductions. Single cell analysis revealed a population of TSLPR overexpressing blasts (range 20-50%) in which the TSLP stimulation resulted in activation of prpS6 but not pSTAT5, present in all the CRLF2r patients. This rpS6 activation could be inhibited by anti-TSLPR mAb, Dasatinib, Ruxolitinib and BEZ-235, except for one patient in which the activation was blunted only by anti-TSLPR mAb and Dasatinib suggesting an activation of prpS6 through a non canonical pathway. This data reveals heterogeneous signaling populations present within this subtype of leukemia driven by TSLPR overexpression. Finally in 3 additional CRLF2r primary samples, we investigated signaling profile of residual blasts (MRD) at Day8 and Day15 post induction initiation. TSLPR expression was consistently maintained in all patients at both time points. Furthermore, residual blasts were still able to respond to TSLP and the induced pSTAT5 could be effectively inhibited by 130A10 anti-TSLPR clone and Ruxolitinib. CONCLUSION: In summary, these data suggest heterogeneity of TSLPR-related signaling with activation of the expected JAK/STAT and PI3K pathways but also RAS/MEK and CREB activation. Further, TSLPR+ blasts exhibit heterogeneous responses to both treatment with TSLP in combination with TKIs or mAb. Finally, the MRD detection by CyTOF allowed the study of the functional activity of the TSLPR positive resistant cells suggesting a role of CRLF2r in the persistence of the leukemic cells and its targeting to treat late and refractory stages of the disease. Disclosures Davis: Fluidigm, Inc: Honoraria. Dyer:Roche Pharmaceuticals: Speakers Bureau; Gilead: Research Funding; ONO Pharmaceuticals: Research Funding. Nolan:Fluidigm, Inc: Equity Ownership.


2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Christos Nikolaou ◽  
Kerstin Muehle ◽  
Stephan Schlickeiser ◽  
Alberto Sada Japp ◽  
Nadine Matzmohr ◽  
...  

An amendment to this paper has been published and can be accessed via the original article.


2018 ◽  
Vol 22 (1) ◽  
pp. 78-90 ◽  
Author(s):  
Chotima Böttcher ◽  
◽  
Stephan Schlickeiser ◽  
Marjolein A. M. Sneeboer ◽  
Desiree Kunkel ◽  
...  

2019 ◽  
Vol 200 ◽  
pp. 24-30 ◽  
Author(s):  
Min Sun Shin ◽  
Kristina Yim ◽  
Kevin Moon ◽  
Hong-Jai Park ◽  
Subhasis Mohanty ◽  
...  

2020 ◽  
Vol 30 (6) ◽  
pp. 1178-1191 ◽  
Author(s):  
Camila Fernández‐Zapata ◽  
Julia K. H. Leman ◽  
Josef Priller ◽  
Chotima Böttcher

Author(s):  
Felix J. Hartmann ◽  
Erin F. Simonds ◽  
Nora Vivanco ◽  
Trevor Bruce ◽  
Luciene Borges ◽  
...  
Keyword(s):  

2014 ◽  
Vol 111 (46) ◽  
pp. 16466-16471 ◽  
Author(s):  
Michael Mingueneau ◽  
Smita Krishnaswamy ◽  
Matthew H. Spitzer ◽  
Sean C. Bendall ◽  
Erica L. Stone ◽  
...  

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