DBiT-seq spatial proteomics analysis of human lung fibrosis samples

Introduction: Idiopathic Pulmonary Fibrosis (IPF) is a chronic lung condition characterized by extensive fibrosis in the interstitium of the lungs that disrupts normal lung function. Despite treatments like nintedanib and pirfenidone that slow disease progression, outcomes remain fatal. The distribution of the fibrotic lesion in the lung is spatially heterogeneous, but there is currently a lack of understanding of the spatial relationship between the fibrotic cells and aberrantly remodeled ECMs. Using DBiT-seq spatial proteomics technique [1,2], the current work examined the spatial distribution of key fibrotic protein markers in the human lung fibrosis samples. This novel approach provides detailed insights into cell and ECM interactions at the fibrotic lesion site, essential for developing targeted interventions to effectively combat IPF progression.

Materials and

Methods: Human fibrotic lung tissues were obtained from NIH BioLINCC. Tissues were sectioned into 10 µm slices and mounted on poly-L-lysine coated glass slides. Following the pre-detection of fibroblast foci, the DBiT-Seq spatial omics platform was employed on fibroblast foci region. After incubation with a cocktail of Antibody-Derived Tags (ADTs), DBit-seq uses parallel microfluidic channels to deliver DNA barcodes to the surface of a tissue slide (Fig. 1A), and crossflow of two sets of barcodes, followed by ligation in situ, yielded a 2D grid of tissue pixel, each tagged with a unique barcode. The unique barcode is linked to each protein molecules within a tissue pixel. Subsequent next-generation sequencing (NGS) of the barcoded proteins enables the detailed mapping of protein expression at specific locations within the arrayed tissue pixels. The current protocol skipped the template switch (cDNA PCR) when focusing solely on proteomics [1]. Purification continues with SPRIselect beads for library preparation and sequencing. A schematic of the DBiT-Seq experimental workflow is illustrated in Figure 1B [2]. For data analysis, cDNAs derived from ADTs, went through preprocessing with a customized Python script. CITE-seq-Count 1.4.3 was used with default settings to count ADT UMI numbers, creating a protein expression matrix. Clustering and visualization were performed using Seurat version 5. Protein data were normalized using CLR transformation. Heat maps were plotted using ggplot2.

Results, Conclusions, and Discussions: Upon executing DBiT-Seq on a fibrotic human lung with a pixel size of 25 μm, quality control checkpoints including the general cDNA size and ADT library size were measured using a bioanalyzer. The results yielded satisfactory outcomes, with a peak of ~1500bp for general cDNA and ~250bp for the ADT library. Proteomic analysis detected approximately 1500 UMIs per pixel. Spatial proteomic clustering identified four major clusters correlating with four ADTs (TGF-β1, CD206, CD86, PDGFRα) utilized in the DBiT-Seq Proteomic study (Fig. 1D). Spatial distributions of the clusters show clear regional enrichment of individual proteins (Fig. 1E). Cluster validity was confirmed through heatmap analysis of differentially expressed proteins (Fig. 1F). The UMI heatmap of individual proteins is supplemented by spatial pie charts detailing cell type composition per pixel (Fig. 1G). Interestingly, there is a co-localization between TGF-β1 and CD206, suggesting the secretion of TGF-β1 by CD206+ pro-fibrotic macrophages in this area. These confirm the successful application of the DBit-seq proteomic method to the fibrotic lung samples. Current results are based on the use of four ADTs as a proof of concept and development is ongoing for an expanded ADT panel containing 12 fibrotic protein targets. This study advances pulmonary fibrosis research by employing the DBiT-Seq spatial omics platform, enabling high-resolution mapping of gene and protein expressions within lung tissue microenvironments. It enhances understanding of the fibrotic legions, potentially leading to new diagnostic tools and targeted therapies for idiopathic pulmonary fibrosis.

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