A research team comprised mostly of Baylor College of Medicine and Yale University scientists has identified previously unrecognized changes in gene expression and cellular interactions in distinct cell populations in chronic obstructive pulmonary disease (COPD).
The study, published recently in Nature Communications, used single-cell RNA sequencing to analyze gene expression profiles of lung tissue obtained from patients with COPD and from mice exposed to cigarette smoke. The researchers separated all the cells within the lung and measured the gene expression profile of each individual cell. They then organized this information into a cell atlas, which is available to interested researchers.
“Our analysis identified novel changes in gene expression and cellular interactions in three distinct cell populations commonly implicated in COPD: epithelial (in the lungs), endothelial (in blood vessels) and macrophage cells (part of the immune system),” says Dr. Ivan Rosas, senior author of the study and section chief of pulmonary, critical care and sleep medicine in the Department of Medicine at Baylor.
Search Antibodies Search Now Use our Antibody Search Tool to find the right antibody for your research. Filter
by Type, Application, Reactivity, Host, Clonality, Conjugate/Tag, and Isotype.
The researchers identified a subpopulation of epithelial cells in lungs with COPD that has abnormal expression of genes involved in metabolic, antioxidant and cellular stress responses, when compared to controls. They also found that endothelial cells in capillary blood vessels in the lungs of COPD patients are inflamed, and that a subpopulation of macrophages expressing high levels of metallothioneins, proteins that regulate the balance of certain metals in the body, seems to contribute to the disease.
The findings could inform new therapeutic routes to treating the disease, and builds on work done at Yale University on developing cell atlases for both healthy lungs and those with disease. The group hopes to continue developing genomic datasets to better understand the underlying pathology of chronic long disease. They are currently working on the largest COVID-19 lung fibrosis cell atlas to date.