Integrated multi-omics profiling landscape of organising pneumonia

Abstract

Background: Organising pneumonia (OP) is one of the most common and lethal diseases in the category of interstitial pneumonia, along with lung cancer. Reprogramming of lipid metabolism is a newly recognized hallmark of many diseases including cancer, cardiovascular disorders, as well as liver fibrosis and sclerosis. Increased levels of ceramides composed of sphingosine and fatty acid, are implicated in the development of both acute and chronic lung diseases. However, their pathophysiological significance in OP is unclear. The aim of this study was to investigate the role of lipid metabolism reprogramming in OP, focusing on inflammation and fibrosis.

Methods: Comprehensive multi-omics profiling approaches, including single-cell RNA sequencing, Visium CytAssist spatial transcriptomics, proteomics, metabolomics and mass spectrometry, were employed to analyze the tissues. OP mice model was utilized and molecular mechanisms were investigated in macrophages.

Results: The results revealed a significant association between OP and lipid metabolism reprogramming, characterized by an abnormal expression of several genes related to lipid metabolism, including CD36, SCD1, and CES1 mainly in macrophages. CD36 deficiency in alveolar macrophages, led to an increased expression of C16/24 ceramides that accumulated in mitochondria, resulting in mitophagy or mitochondrial dysfunction. The number of alveolar macrophages in OP was significantly reduced, which was probably due to the ferroptosis signaling pathway involving GSH/SLC3A2/GPX4 through CD36 downregulation in OP. Furthermore, macrophage secretion of DPP7 and FABP4 influenced epithelial cell fibrosis.

Conclusions: CD36 inhibited the ferroptosis pathway involving SLC3A2/GPX4 in alveolar macrophages of OP tissue by regulating lipid metabolism, thus representing a new anti-ferroptosis and anti-fibrosis effect of CD36 mediated, at least in part, by ceramides.

Highlights: Our findings reveal a significant association between organising pneumonia and lipid metabolism reprogramming and will make a substantial contribution to the understanding of the mechanism of organising pneumonia in patients.

Keywords: ferroptosis; lipid metabolism reprogramming; macrophage; organising pneumonia.

FIGURE 1

The cellular composition of organising pneumonia (OP) tissue. (A) Workflow of proteomics, metabolomics, single‐cell RNA sequencing (scRNA‐seq) and Visium CytAssist applied to lung tissues. (B) Unsupervised hierarchical clustering was performed on 116 label‐free quantitation protein intensities (log2) that were quantified in three replicates of the two groups' proteomes. The intensities were required to exhibit a fold change (FC) greater than 2.0 and a p‐value less than .05 in their abundance between two groups. The resulting heatmap displayed the grouped LFQ protein intensities, transformed using z‐scores and log2. (C) Gene Ontology (GO) enrichment analysis for the biological processes involving the upregulated and downregulated proteins and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis for the pathways changed between OP and healthy control (HC) groups. (D) Gene set enrichment analysis (GSEA) analysis revealed that the changed proteins were mainly enriched in metastasis, regulation of cellular component movement, lipid metabolic process and cholesterol biosynthesis. (E) UMAP of cells identified from the scRNA‐seq data of HC and OP tissues. (F) Expression matrix of cell‐type marker genes in the 13 cell types within OP tissues. (G) Proportion of each cell type in HC and OP samples. (H) Expression matrix of lipid metabolism genes in the 13 cell types within OP tissues. LFQ, label‐free quantification.

FIGURE 2

Functional analysis was performed using the differentially expressed genes (DEGs) within the related cells between organising pneumonia (OP) and healthy control (HC) tissues from the single‐cell RNA sequencing (scRNA‐seq) data. (A) The numbers of total genes and DEGs in each cell type of OP group compared to HC group. (B and C) Analysis of cell communication patterns, including secreted signalling, ECM receptor and cell‒cell contact, among monocytes, macrophages and epithelial cells. (D) Gene Ontology (GO) enrichment analysis was performed on macrophages. (E) The significant regulatory pathways of key genes were analysed by Kyoto Encyclopedia of Genes and Genomes (KEGG). (F) Gene set enrichment analysis (GSEA) revealed that the changed proteins were mainly enriched in cell‒matrix adhesion, developmental growth involved in morphogenesis, mitochondrial respiratory chain complex assembly, ATP synthesis coupled electron transport and oxidative phosphorylation in macrophages. (G) GO enrichment analysis was performed on epithelial cells. (H) The significant regulatory pathways regulated by pivotal genes were analysed by KEGG. ECM, extracellular matrixc; LFQ, label‐free quantification.

FIGURE 3

Spatial transcriptomic analysis of the immunity and energy metabolism heterogeneity in organising pneumonia (OP). (A and B) Distribution of Visium CytAssist clusters in OP samples. (C‒E) Gene Ontology (GO) enrichment of major Visium CytAssist clusters (OP/normal), including biological processes (C, BP), cellular components (D, CC) and molecular functions (E, MF). (F) Kyoto Encyclopedia of Genes and Genomes (KEGG) was used to analyse the major functional changes of OP regulated by related genes. (G) Haematoxylin and eosin (H&E) staining and immunohistochemical staining were used to analyse multiple markers (CD38, CD163 and NAPISNA) in the lungs of OP patients.

FIGURE 4

Abnormal macrophage lipid metabolism, including cholesterol ester (CE) and ceramides (Cer) in organising pneumonia (OP) patients. (A) Volcano plots revealed that 166 lipid metabolites showed significant differences, with 98 upregulated and 68 downregulated (variable important in projection >1.0 and p‐value <.05). (B) The percentile pie chart showed the proportion of different types of lipid metabolites. Among these, CE and Cer were the most abundant. (C) CE and Cer were significantly increased analysed by enzyme‐linked immunosorbent assay (ELISA) in the OP group. (D and E) Heatmap showing the expression of lipid sets associated with Cer and CE in OP tissues identified by lipid metabolomics. (F) Violin plot showing the expression levels of CD36, CES1 and SCD1 in the 13 clusters of OP. (G) Spatial expression of CD36, CES1 and SCD1 in the representative Visium CytAssist sample. The genes tended to be weakened in the OP area. (H) Immunohistochemical staining was used to analyse multiple molecules (CD36, CES1 and SCD1) in the lungs of OP patients. (I) UMAP of 4088 macrophages which were divided into three subclusters, including SCGB3A1⁺ epithelial phagocytic macrophages, VCAN⁺ monocyte‐derived macrophages (Mo‐AM, predominantly M1 subtype) and FABP4⁺ alveolar macrophages (resident macrophage TRAM, predominantly M2 subtype). (J) Dot plot showing the expression levels of marker genes for different subtypes of macrophages in the subclusters of macrophages. (K) Proportion of macrophage types in healthy control (HC) and OP samples. (L and M) Heatmap showing the expression of lipid sets associated with Cer (L) and CE (M) in FABP4⁺ lipid metabolising macrophage population identified by lipid metabolomics. (N) Lipid drops staining with Biotium/LipidSpot 488 Lipid Droplet Stain (1000×/70065‐T/20‐µL) in FABP4⁺ macrophages of the OP mouse model. (O) qRT‐PCR was used to detect the difference in expression levels of CD36, CES1 and SCD1 in lipid metabolising macrophage population of FABP4⁺. (P and Q) Western blot assay was used to detect the expression of CD36, CES1 and SCD1 in lipid metabolising macrophage population of FABP4⁺.

FIGURE 5

Reprogramming of lipid metabolism in alveolar macrophages promotes ferroptosis. (A‒D) Violin plot showing the expression levels of FTL (B) and FTH1 (C) in the 13 clusters of healthy control (HC) and organising pneumonia (OP) tissues from the single‐cell RNA sequencing (scRNA‐seq) data. (E) Network of differentially expressed proteins between CON and siCD36 groups (red represents upregulation and green represents downregulation). (F) Gene set enrichment analysis (GSEA) analysis revealed that the changed proteins were mainly enriched in lung fibrosis, mitochondria‐related metabolism, fatty acid metabolism, immune system, cell death and ferroptosis‐related pathways by knocking down CD36. (G) Heatmap showing the differentially expressed proteins related to ferroptosis in alveolar macrophages by knocking down CD36. (H and I) Western blot assay was used to detect the expression of CD36, SLC3A2, GPX4, FTH1, FTL, CES1 and SCD1 in alveolar macrophages. (J) Electron micrograph of alveolar macrophages of OP mouse model (magnification, 30 000×; red arrow, mitochondrion; red rectangle, nucleus). (K) Quantification of perinuclear mitochondrial area, number of mitochondria per square micron, mitochondrial circularity index, cristae number, cristae area, cristae volume and cristae score from (J). (L) The concentration of Fe²⁺, malondialdehyde (MDA) and glutathione (GSH) in alveolar macrophages of OP mouse model. (M and N) Electron micrograph of alveolar macrophages with siCD36 treatment. Quantification of perinuclear mitochondrial area, number of mitochondria per square micron, mitochondrial circularity index, cristae number, cristae area, cristae volume and cristae score from (M). (O) The levels of Fe²⁺, MDA and GSH in alveolar macrophages with siCD36 treatment. Statistical significance is indicated by asterisks; ^*** p ≤ .001.

FIGURE 6

The impact of C16 ceramide (Cer) on ferroptosis in alveolar macrophages. (A) The content of C16 Cer with CD36 interference in alveolar macrophages in mass spectrometry analysis. (B) Western blot assay was used to detect the expression of CD36, CES1 and SCD1 in alveolar macrophages with C16 Cer treatment. (C) Perform statistical analysis on the Western blot of (B). (D and E) Lipid drops staining with Biotium/LipidSpot 488 Lipid Droplet Stain (1000×/70065‐T/20‐µL) in alveolar macrophages with C16 Cer treatment. (F) Perform cell cycle analysis on alveolar macrophages treated with C16 Cer. (G) Intracellular reactive oxygen species (ROS) measurement by flow cytometry after two compounds treatment (Marker, BODIPY 581/591 C11). (H and I) Electron micrograph of alveolar macrophages with C16 Cer treatment. (J) The levels of Fe²⁺, malondialdehyde (MDA) and glutathione (GSH) in alveolar macrophages with C16 Cer treatment.

FIGURE 7

Alveolar macrophage secretions promote epithelial fibrosis. (A‒D) Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis for the categories of upregulated and downregulated secretions between CON and siCD36 groups. (E) The chord of GO showed the dramatically differential secretions, which regulated epithelial fibrosis and proliferation. (F and G) The levels of DPP7 and FABP4 in alveolar macrophages with siCD36 treatment. (H‒K) Western blot assay was used to detect the expression of E‐cadherin, N‐cadherin and vimentin in alveolar macrophages (H and J: MLE‐12; I and K: Beas2B cell lines) with DPP7 or FABP4 treatment. (L) A schematic of ferroptosis in alveolar macrophages and alveolar macrophage cell secretions contributing to epithelial fibrosis of organising pneumonia (OP) via CD36‐related pathway.