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VEGFR3 signaling restrains the neuron-macrophage crosstalk during neurotropic viral infection

ABSTRACT: To investigate the transcriptomic characteristics of CD11b+F4/80+ cells in the brain of JEV- infected WT and Vegfr-3ΔLBD/ΔLBD mice, we sorted the CD11b+F4/80+ cells from the brain of WT and Vegfr-3ΔLBD/ΔLBD mice post 5 days of JEV infection by FACS. We then performed gene expression profiling analysis using data obtained from RNA-seq of 2 different cells.

ORGANISM(S): Mus musculus

PROVIDER: GSE228931 | GEO | 2023/05/06

REPOSITORIES: GEO

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Project description:Tumor-associated macrophages (TAMs) are highly heterogeneous, derived from myeloid monocyte/macrophages or tissue-resident macrophages, and play vital role in tumor progression. Here we adopted a C57BL/6 mouse model imitating the late-stage colorectal liver metastasis (CRLM) by Mc38 colorectal cancer cell injection via the portal vein. We defined the critical period at 7 to 9 days post injection (dpi) for tumor neovascularization on serial sections of CRLM biopsies. The tumor neovascularization was initiated from one of the liver blood vessels via vessel cooption and extended by vascular mimicry and growth of CD34+cells. In samples with increasing sized liver metastases of CRLM, infiltrated Ly6C+ CD11b+ F4/80 monocytes steadily gained the expression of F4/80, a Kupffer cell marker, and then transformed into Ly6C CD11bint F4/80+ cells, which, the same phenotype was also adapted by Ly6C CD11b F4/80+ Kupffer cells. F4/80+ TAMs showed proximity to neovascularization and tumor vessels. Depletion of macrophages or disturbance on macrophage polarization during the crucial period of neovascularization impeded tumor growth and vascularization and resulted in greatly reduced F4/80+ TAMs, yet increased CD11b+ cells due to inhibition of TAM differentiation. In summary, we showed dynamic F4/80+ TAM differentiation within the tumor microenvironment and strengthened its role as perivascular TAMs in CRLM. A set of aliquot samples (about 0.25 cm3) from for flow cytometry preparations (the above method and Fig. 4A) were used for bulk RNA-Sequencing, among these samples, Ht1 and Ht3 were identical samples; F4/80+cells and CD11b+ cells were selected from medium-sized CRLM (Mt2) with microbeads and MS column;A total of 20 samples were sent for analysis. These collected tissues were flash-frozen in liquid nitrogen, stored at - 80°C and shipped on dry ice to the sequencing provider (Novogene, www.novogene.com), who then extracted RNA from these samples and confirmed that all sample RNA were in good quality and adequate concentrations. The resulted RNA-Sequencing data were verified as the clean reads > 95%, Q30 > 90%, and error rate < 0.05%; Square of Pearson Correlation Coefficient (R2) between the biological replicates was > 0.89; R2 of the identical samples (Ht-1 and Ht-3) was > 0.98.

Project description:Purpose: We characterized the role of EKLF in erythroblast island macrophages in E13.5 mouse fetal liver by analysing the transcriptomes of F4/80+ macrophages from WT and EKLF-/- by RNA-Seq. In addition we analyzed the transcriptomes of F4/80+ fetal liver macrophages from an EKLF/GFP mouse, where GFP acts as a surrogate for EKLF expression, to determine the genes enriched in EKLF/GFP+ macrophages compared to EKLF/GFP- macrophages where EKLF is not expressed. Finally, we used single cell RNA sequencing to resolve the heterogeneous population of F4/80+ macrophages from WT. Methods: For RNA-Seq from WT and EKLF-/- F4/80+ macrophages were FACS sorted from primary E13.5 mouse fetal livers and RNA was isolated using the Trizol method. F4/80+ macrophages were also FACS sorted from the EKLF/GFP mouse and the GFP+ and GFP- populations were collected. The GFP+ population had low cell numbers and therefore RNA was isolated using an Agilent RNA Nanoprep kit. For single cell sequencing, E13.5 fetal livers were stained with F4/80-PE antibody and the F4/80-PE+ cells were purified using an EZ-Sep PE selection kit (mouse). 25,000 cells were submitted for single cell sequencing for the Chromium V3 platform. Library preparation was done using the standard Illumina Truseq workflow, and libraries were sequenced in a Hiseq 2500 for WT and EKLF-/-, or Novaseq for EKLF/GFP and single cell sequencing. Results: We found that 1954 genes are differentially expressed in EKLF-/- F4/80+ macrophages vs WT and 2330 genes are differentially enriched in EKLF/GFP+ F4/80+ macrophages using DESeq2. Of these, 504 are common and constitute the EKLF-dependent gene expression program in F4/80+ fetal liver macrophages. We resolved the F4/80+ WT macrophages into 13 clusters based on gene expression and find that 23% of the total F4/80+ cells express EKLF. Conclusions: We find that the F4/80+ fetal liver macrophage are a unique cell type. We identify the EKLF-dependent gene expression program in these macrophages and determine an important transcription circuit governed by EKLF that constitute cell cycle and other Klf and Sp family transcription factors. Single cell sequencing showed a highly heterogeneous population of macrophages with activated macrophage as well as erythro-myeloid characteristics. Based on the expression of EKLF, we identified specific cell surface markers for EKLF+ F4/80+ macrophages.

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VEGFR3 signaling restrains the neuron-macrophage crosstalk during neurotropic viral infection

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