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GATA2 Paper

Publication

Title: GATA2 controls alveolar macrophage inflammatory gene expression and metabolic function

Link: BLANK (Fill in when published)

Abstract

Alveolar macrophages (AMs) have homeostatic, anti-inflammatory programming to limit tissue damage in response to minor challenge and catabolize lipid-rich pulmonary surfactant to support gas exchange. GATA transcription factors (TFs) shape immune cell fates and GATA2 is expressed in a lung-specific manner in macrophages. Both GATA2 mutations and lung macrophage downregulation of GATA2 have been associated with chronic pulmonary pathologies in humans, but the role of GATA2 in coordinating AM function is not well defined. Using mice with myeloid-specific deletion of the GATA2 DNA binding C-terminal zinc finger domain, we show that GATA2 deficiency promotes enhanced inflammatory gene expression and metabolic dysfunction in AMs in response to type 2 stimuli. While homeostatic functions of AMs remained largely intact, GATA2 deficiency increased expression of type 2 response genes during IL-33-induced inflammation. Coincident with GATA2-dependent expression of genes in metabolic pathways, seahorse metabolic flux analysis suggests that AM metabolism is compromised in the absence of GATA2, potentially contributing to decreased numbers of AMs in the context of bleomycin-induced fibrosis. AM GATA2-dependent gene networks are enriched for targets of TFs previously demonstrated to interact with GATA2 in other cellular contexts, including PU.1, PPARγ, and other TFs that regulate AM function. Our data suggest that GATA2 modulates AM metabolic and transcriptomic programming to restrain responses and maintain AM identify during inflammation.

Repository Contents

This repository contains the code used to generate figures and perform analyses for the above publication.

Requirements

R

  • R (≥ 4.2)

Python

  • Python (≥ 3.11)

R and Python package dependencies are listed at the top of each script. For jupyter notebooks refer to requirements.txt.

This code was developed and tested with R 4.2 and Python 3.11.

Data Availability

RNA-seq data is available at: GSE298755

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