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Predictive protein biomarker signatures and the corresponding transcriptional cell state changes in human lung fibrosis

ABSTRACT: Single cell genomics enables characterization of disease specific cell states, while improvements in mass spectrometry workflows bring the clinical use of body fluid proteomics within sight. However, the correspondence of peripheral protein signatures with cell state changes in diseased organs is currently unknown. Here, we use single cell RNA-seq and proteomics from large patient cohorts of pulmonary fibrosis and establish that predictive protein signatures in body fluids correspond to specific cellular changes in the lung. We determined transcriptional changes in 45 cell types across three patient cohorts and quantified bronchoalveolar lavage fluid and plasma proteins to discover protein signatures and associated cell state changes that were linked to diagnosis, lung function, smoking and injury status. Altered expression of the novel marker of lung health CRTAC1 in alveolar epithelium is robustly reported in patient plasma. With further improvements of this concept and deeper coverage of plasma proteomes, we envision future longitudinal profiling of body fluid signatures coupled to deep learning for non-invasive prediction and monitoring of pathological cell state changes in patient organs.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung

SUBMITTER: Christoph Mayr

LAB HEAD: Herbert B. Schiller

PROVIDER: PXD017145 | Pride | 2020-09-18

REPOSITORIES: Pride

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Project description:Segmental instillation of lipopolysaccharide (LPS) by bronchoscopy can be used as a model to safely induce transient airway inflammation in the human lung. The LPS challenge model enables investigation of cellular mechanisms involved in pulmonary inflammatory processes as well as pharmacodynamic analysis of investigational drugs for the treatment of respiratory diseases. Aim of this work was to describe the transcriptomic profile of the human segmental LPS challenge model with contextualization to major respiratory diseases. Pre-challenge bronchoalveolar lavage fluid (BAL) and biopsies were sampled from twenty-eight smoking, healthy subjects, followed by segmental LPS challenge and saline control challenge. Twenty-four hours post instillation, BAL and biopsies were collected from the challenged lung segments. Total RNA of cells from BAL and biopsy samples were sequenced for subsequent data analysis. Differential gene expression analysis resulted in 6316 upregulated differentially expressed genes (DEGs) and 241 downregulated DEG in BAL, but only one downregulated DEG in biopsy samples after LPS challenge compared to saline challenge. Upregulated DEG in BAL were related to molecular functions such as “Inflammatory response” or “antimicrobial humoral immune response mediated by antimicrobial peptide”, enriched biological processes such as “chemokine receptor activity”, and upregulated pro-inflammatory pathways such as “Wnt signaling pathway”, “Ras signaling pathway” or “JAK-STAT signaling pathway”. Furthermore, the segmental LPS challenge model resembled aspects of the five most prevalent respiratory diseases chronic obstructive pulmonary disease (COPD), asthma, pneumonia, tuberculosis and lung cancer and featured similarities with acute exacerbations in COPD (AECOPD) and community-acquired pneumonia (CAP). Overall, our study provides extensive information about the transcriptomic profile from BAL cells and mucosal biopsies following LPS challenge in healthy smokers. It expands the knowledge about the LPS challenge model providing potential overlap with respiratory diseases in general and infection-triggered respiratory insults such as AECOPD in particular.

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Predictive protein biomarker signatures and the corresponding transcriptional cell state changes in human lung fibrosis

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