June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Transcriptome-wide analysis of the differential activation states of retinal microglial cells
Author Affiliations & Notes
  • Madhu Sudhana Saddala
    University of Missouri School of Medicine, Columbia, Missouri, United States
  • Xu Yang
    Ophthalmology, Aier Eye Institute, Changsha, Hunan, China
  • Shibo Tang
    Ophthalmology, Aier Eye Institute, Changsha, Hunan, China
  • Hu Huang
    University of Missouri School of Medicine, Columbia, Missouri, United States
  • Footnotes
    Commercial Relationships   Madhu Saddala, None; Xu Yang, None; Shibo Tang, None; Hu Huang, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 708. doi:
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    • Get Citation

      Madhu Sudhana Saddala, Xu Yang, Shibo Tang, Hu Huang; Transcriptome-wide analysis of the differential activation states of retinal microglial cells. Invest. Ophthalmol. Vis. Sci. 2020;61(7):708.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The current study is focused on characterizing the transcriptome differences between the M1 and M2 microglia activated with Tumor necrosis factor-alpha/Interferon-gamma (TNFα/IFNY) and Interleukin-4 (IL4) respectively.

Methods : Microglia cells were isolated from neonatal mouse retina and cultured with DMEM/F12 medium supplemented with CSF1. Primary microglia cell cultures were treated with TNFα/IFNY, IL4 (10ng/ml each for 12h) and PBS control. Total RNAs were purified and submitted to deep sequencing. After adapter removal, the quality of each file was mapped with mouse reference genome. We used the aligned reads to calculate FPKM values based on transcript abundance by HTSeq-count. The output of counts was applied to the package DESeq2 in Bioconductor to identify differentially expressed genes (DEGs). Furthermore, we performed gene annotation, functional pathways and gene-gene interaction network for the DEGs.

Results : 408 genes were differentially expressed between TNFα/IFNY and PBS groups and 28 genes between IL4 and PBS groups respectively. These DEGs are involved in various KEGG pathways such as TNF signaling pathway, Inflammation mediated by chemokine and cytokine signaling pathway, Interferon Signaling, Signaling by Interleukins pathways. The 28 DEGs are involved in several KEGG pathways, such as the TGF-beta signaling pathway, Arginine biosynthesis, Phagosome and HIF-1 signaling pathway. These reveals that the TNFα treatment up-regulated the pro-inflammatory genes such as CD40, CXCL10, CXCL11, TLR9, CCL2, CXCL16, TNFSF10, JAK2, SOCS1, IL27, NOS2, HIF1A and IRF1, thus activating the M1 (pro-inflammatory) microglia cells. Treatment with IL4 activates M2 (anti-inflammatory) microglia cells by down-regulation of HIF pathway genes (Gapdh, Gapdh-ps15 and HIF-1) and up-regulation of TGF-beta signaling pathway genes (Smurf2 and Eng). The gene-gene network analysis revealed that all pathway genes interacted each other directly and involved in pro- and anti-inflammatory pathways.

Conclusions : These findings indicate that M1 microglia cells are activated by various pro-inflammatory pathway genes and M2 microglia cells are activated likely by TGF-beta signaling pathway genes. The follow-up experiment results would be to demonstrate the biological significance in retinal health and disease.

This is a 2020 ARVO Annual Meeting abstract.

 

Microglia M1 (Pro-inflammatory) and M2 (Anti-inflammatory) pathways

Microglia M1 (Pro-inflammatory) and M2 (Anti-inflammatory) pathways

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