RNA Content and Chromatin Structure in Cycling and Noncycling Cell Populations Studied by Flow Cytometry

Author(s):  
ZBIGNIEW DARZYNKIEWICZ ◽  
FRANK TRAGANOS
2021 ◽  
Vol 6 (3) ◽  
pp. 121
Author(s):  
Alison Luce-Fedrow ◽  
Suchismita Chattopadhyay ◽  
Teik-Chye Chan ◽  
Gregory Pearson ◽  
John B. Patton ◽  
...  

The antigenic diversity of Orientia tsutsugamushi as well as the interstrain difference(s) associated with virulence in mice impose the necessity to dissect the host immune response. In this study we compared the host response in lethal and non-lethal murine models of O. tsutsugamushi infection using the two strains, Karp (New Guinea) and Woods (Australia). The models included the lethal model: Karp intraperitoneal (IP) challenge; and the nonlethal models: Karp intradermal (ID), Woods IP, and Woods ID challenges. We monitored bacterial trafficking to the liver, lung, spleen, kidney, heart, and blood, and seroconversion during the 21-day challenge. Bacterial trafficking to all organs was observed in both the lethal and nonlethal models of infection, with significant increases in average bacterial loads observed in the livers and hearts of the lethal model. Multicolor flow cytometry was utilized to analyze the CD4+ and CD8+ T cell populations and their intracellular production of the cytokines IFNγ, TNF, and IL2 (single, double, and triple combinations) associated with both the lethal and nonlethal murine models of infection. The lethal model was defined by a cytokine signature of double- (IFNγ-IL2) and triple-producing (IL2-TNF-IFNγ) CD4+ T-cell populations; no multifunctional signature was identified in the CD8+ T-cell populations associated with the lethal model. In the nonlethal model, the cytokine signature was predominated by CD4+ and CD8+ T-cell populations associated with single (IL2) and/or double (IL2-TNF) populations of producers. The cytokine signatures associated with our lethal model will become depletion targets in future experiments; those signatures associated with our nonlethal model are hypothesized to be related to the protective nature of the nonlethal challenges.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 45.2-45
Author(s):  
I. Heggli ◽  
R. Schüpbach ◽  
N. Herger ◽  
T. A. Schweizer ◽  
A. Juengel ◽  
...  

Background:Modic type 1 changes (MC1) are vertebral bone marrow (BM) edema that associate with non-specific low back pain (LBP). Two etiologies have been described. In the infectious etiology the anaerobic aerotolerant Cutibacterium acnes (C. acnes) invades damaged intervertebral discs (IVDs) resulting in disc infection and endplate damage, which leads to the evocation of an immune response. In the autoinflammatory etiology disc and endplate damage lead to the exposure of immune privileged disc cells and matrix to leukocytes, thereby evoking an immune response in the BM. Different etiologies require different treatment strategies. However, it is unknown if etiology-specific pathological mechanisms exist.Objectives:The aim of this study was to identify etiology-specific dysregulated pathways of MC1 and to perform in-depth analysis of immune cell populations of the autoinflammatory etiology.Methods:BM aspirates and biopsies were obtained from LBP patients with MC1 undergoing spinal fusion. Aspirates/biopsies were taken prior screw insertion through the pedicle screw trajectory. From each patient, a MC1 and an intra-patient control aspiration/biopsy from the adjacent vertebral level was taken. If C. acnes in IVDs adjacent to MC1 were detected by anaerobic bacterial culture, patients were assigned to the infectious, otherwise to the autoinflammatory etiology.Total RNA was isolated from aspirates and sequenced (Novaseq) (infectious n=3 + 3, autoinflammatory n=5 + 5). Genes were considered as differentially expressed (DEG) if p-value < 0.01 and log2fc > ± 0.5. Gene ontology (GO) enrichment was performed in R (GOseq), gene set enrichment analysis (GSEA) with GSEA software.Changes in cell populations of the autoinflammatory etiology were analyzed with single cell RNA sequencing (scRNAseq): Control and MC1 biopsies (n=1 + 1) were digested, CD45+CD66b- mononuclear cells isolated with fluorescence activated cell sorting (FACS), and 10000 cells were sequenced (10x Genomics). Seurat R toolkit was used for quality-control, clustering, and differential expression analysis.Transcriptomic changes (n=5 + 5) of CD45+CD66b+ neutrophils isolated with flow cytometry from aspirates were analyzed as for total bulk RNAseq. Neutrophil activation (n=3 + 3) was measured as CD66b+ expression with flow cytometry. CD66bhigh and CD66blow fractions in MC1 and control neutrophils were compared with paired t-test.Results:Comparing MC1 to control in total bulk RNAseq, 204 DEG in the autoinflammatory and 444 DEG in the infectious etiology were identified with only 67 shared genes (Fig. 1a). GO enrichment revealed “T-cell activation” (p = 2.50E-03) in the autoinflammatory and “complement activation, classical pathway” (p=1.1E-25) in the infectious etiology as top enriched upregulated biological processes (BP) (Fig 1b). ScRNAseq of autoinflammatory MC1 showed an overrepresentation of T-cells (p= 1.00E-34, OR=1.54) and myelocytes (neutrophil progenitor cells) (p=4.00E-05, OR=2.27) indicating an increased demand of these cells (Fig. 1c). Bulk RNAseq analysis of neutrophils from the autoinflammatory etiology revealed an activated, pro-inflammatory phenotype (Fig 1d), which was confirmed with more CD66bhigh neutrophils in MC1 (+11.13 ± 2.71%, p=0.02) (Fig. 1e).Figure 1.(a) Venn diagram of DEG from total bulk RNAseq (b) Top enriched upregulated BP of autoinflammatory (left) and infectious (right) etiology (c) Cell clustering of autoinflammatory MC1 BM (d) Enrichment of “inflammatory response” gene set in autoinflammatory MC1 neutrophils (e) Representative histogram of CD66b+ expression in MC1 and control neutrophils.Conclusion:Autoinflammatory and infectious etiologies of MC1 have different pathological mechanisms. T-cell and neutrophil activation seem to be important in the autoinflammatory etiology. This has clinical implication as it could be explored for diagnostic approaches to distinguish the two MC1 etiologies and supports developing targeted treatments for both etiologies.Disclosure of Interests:None declared


1995 ◽  
Vol 10 (5) ◽  
pp. 1280-1286 ◽  
Author(s):  
Jorge Molina ◽  
Jose Antonio Castilla ◽  
Teresa Gil ◽  
Maria Luisa Hortas ◽  
Francisco Vergara ◽  
...  

1990 ◽  
Vol 116 (5) ◽  
pp. 507-512 ◽  
Author(s):  
W. Hiddemann ◽  
B. Wörmann ◽  
D. Messerer ◽  
R. Springefeld ◽  
Th. Büchner

1984 ◽  
Vol 43 (2) ◽  
pp. 222-227 ◽  
Author(s):  
B Bonvoisin ◽  
G Cordier ◽  
J P Revillard ◽  
E Lejeune ◽  
M Bouvier

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