Research

Understanding and identifying the genetic and molecular networks that determine the lung phenotype using high throughput genomic and proteomic technologies.

• Role of microRNAs in Idiopathic Pulmonary Fibrosis and other chronic lung disease
• Role of other non-coding RNAs (lincRNAs) in advanced lung disease
• Epigenomic regulation of cellular phenotypes in chronic lung disease
• The role of developmental pathways in lung injury and aberrant repair (scaring)
• Role of the microbiome in defining lung phenotypes in chronic lung disease
• The molecular basis of Cellular and Regional Heterogeneity in the IPF lung

• The role and regulation of matrix metaloproteases (MMP7, MMP19) in human pulmonary fibrosis.
• Development of microRNA based interventions (let-7, mir-29, mir-30, mir-154 families) for therapy in human Pulmonary Fibrosis
• Mechanisms and regulation of lincRNA perturbations in IPF
• Using high throughput ‘omics’ data to facilitate the implementation of novel therapies in Lung Fibrosis
• Application of single cell approaches to better assess efficacy of therapeutic interventions in IPF

• Molecular Phenotyping of Chronic Lung Disease
  • Molecular diagnosis of IPF
  • Computational approaches to Integrate clinical, biological, genomic and proteomic data
• Use of surrogate tissues to diagnose and manage chronic lung disease
  • Peripheral blood protein markers to diagnose and predict outcome in Lung Fibrosis
  • Peripheral Blood Gene Expression patterns
  • Circulating microRNAs reflect organ phenotype and disease presence and outcome
  • Markers and predictors of target engagement and response to therapy
• Genetic Markers
  • Disease predisposition
  • Outcome prediction
  • Response to therapy

• The role and regulation of matrix metalloproteases (MMP7, MMP19) in human pulmonary fibrosis
• The role and regulation of microRNAs (let-7, mir-30, mir-154 families) in human pulmonary fibrosis

IPF Cell Atlas :

The Idiopathic Pulmonary Fibrosis (IPF) Cell Atlas (www.ipfcellatlas.com) is a multi-institutional collaboration that seeks to facilitate the exploration of several single-cell RNA sequencing datasets related to IPF in the form of an easy-to-use webtool. With the simple click of a button, users can input their favorite gene(s) of interest into one of several visualization tools to assess novel disease- and cell-specific expression patterns within each of the available datasets. Additionally, a dataset comparison tool is available that allows for the cross-comparison of gene expression patterns across multiple datasets. For more information on the website itself, please consider checking out Neumark and Cosme Jr. et al., (2020): "The IPF Cell Atlas" (https://journals.physiology.org/doi/abs/10.1152/ajplung.00451.2020). For more information on the parent project overarching this collaborative effort, please see Adams and Schupp et al., (2020): "Single-cell RNA-seq reveals ectopic and aberrant lung resident-cell populations in idiopathic pulmonary fibrosis" (https://advances.sciencemag.org/content/6/28/eaba1983).

COVID Cell Atlas :

The COVID Cell Atlas (www.covidcellatlas.com) is a publicly available and interactive webtool designed to facilitate the independent exploration of single-cell RNA sequencing data generated from the peripheral blood mononuclear cells of patients diagnosed with COVID-19. With the simple click of a button, users can input their favorite gene(s) of interest into one of several visualization tools to assess novel disease- and cell-specific expression patterns within the provided dataset. Additionally, users can assess cell-specific differences in intercellular communication between diseased and healthy individuals predicted from our data through the new 'Connectome Explorer' feature. For more information on this project, please see our manuscript by Unterman and Sumida et al., (2022): "Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19" (https://www.nature.com/articles/s41467-021-27716-4).

COPD Cell Atlas :

The COPD Cell Atlas (www.copdcellatlas.com) is a publicly available and interactive webtool designed to facilitate the independent exploration of single-cell RNA sequencing data generated from the lungs of individuals diagnosed with chronic obstructive pulmonary disease (COPD). With the simple click of a button, users can input their favorite gene(s) of interest into one of several visualization tools to assess novel disease- and cell-specific expression patterns within the provided dataset. Additionally, users can explore cell-specific differences in the intercellular communication of cells within the diseased and healthy states through our 'Interactive Connectome' feature. For more information on this project, please see our preprint by Sauler and McDonough et al. (2022): "Characterization of the COPD alveolar niche using single-cell RNA sequencing" (https://www.nature.com/articles/s41467-022-28062-9).

The Lung Endothelial Cell Atlas :

The Lung Endothelial Cell Atlas (www.lungendothelialcellatlas) is a publicly available and interactive webtool designed to facilitate the independent exploration of single-cell RNA sequencing data of lung endothelial cells that has been generated from the integration of several, independently procured datasets. Users can input their favorite gene(s) of interest into one of several visualization tools to assess species- and cell-specific differences in the expression patterns of genes within the lung endothelial cells of mouse and human samples. Additionally, users can explore cell-specific intercellular communication patterns predicted from the integrated dataset through the 'Connectome Explorer' feature. For more information on this project, please see our preprint by Schupp et al., (2021) : "Integrated Single Cell Atlas of Endothelial Cells of the Human Lung" (https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.120.052318).