High-throughput analysis of lung immune cells in a combined murine model of agriculture dust-triggered airway inflammation with rheumatoid arthritis

Rheumatoid arthritis (RA)-associated lung disease is a leading cause of mortality in RA, yet the mechanisms linking lung disease and RA remain unknown. Using an established murine model of RA-associated lung disease combining collagen-induced arthritis (CIA) with organic dust extract (ODE)-induced airway inflammation, differences among lung immune cell populations were analyzed by single cell RNA-sequencing. Additionally, four lung myeloid-derived immune cell populations including macrophages, monocytes/macrophages, monocytes, and neutrophils were isolated by fluorescence cell sorting and gene expression was determined by NanoString analysis. Unsupervised clustering revealed 14 discrete clusters among Sham, CIA, ODE, and CIA+ODE treatment groups: 3 neutrophils (inflammatory, resident/transitional, autoreactive/suppressor), 5 macrophages (airspace, differentiating/recruited, recruited, resident/interstitial, and proliferative airspace), 2 T-cells (differentiating and effector), and a single cluster each of inflammatory monocytes, dendritic cells, B-cells and natural killer cells. Inflammatory monocytes, autoreactive/suppressor neutrophils, and recruited/differentiating macrophages were predominant with arthritis induction (CIA and CIA+ODE). By specific lung cell isolation, several interferon-related and autoimmune genes were disproportionately expressed among CIA and CIA+ODE (e.g. Oasl1, Oas2, Ifit3, Gbp2, Ifi44, and Zbp1), corresponding to RA and RA-associated lung disease. Monocytic myeloid-derived suppressor cells were reduced, while complement genes (e.g. C1s1 and Cfb) were uniquely increased in CIA+ODE mice across cell populations. Recruited and inflammatory macrophages/monocytes and neutrophils expressing interferon-, autoimmune-, and complement-related genes might contribute towards pro-fibrotic inflammatory lung responses following airborne biohazard exposures in setting of autoimmune arthritis and could be predictive and/or targeted to reduce disease burden.