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Abstract A major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators’ activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-β-induced epithelial-mesenchymal transition and macrophage polarization. 

Although epithelial-mesenchymal transition (EMT) is a common feature of fibrotic lung disease, its role in fibrogenesis is controversial. Recently, aberrant basaloid cells were identified in fibrotic lung tissue as a novel epithelial cell type displaying a partial EMT phenotype. The developmental origin of these cells remains unknown. To elucidate the role of EMT in the development of aberrant basaloid cells from the bronchial epithelium, we mapped EMT-induced transcriptional changes at the population and single-cell levels. Human bronchial epithelial cells grown as submerged or air-liquid interface (ALI) cultures with or without EMT induction were analyzed by bulk and single-cell RNA-Sequencing. Comparison of submerged and ALI cultures revealed differential expression of 8,247 protein coding (PC) and 1,621 long noncoding RNA (lncRNA) genes and revealed epithelial cell-type-specific lncRNAs. Similarly, EMT induction in ALI cultures resulted in robust transcriptional reprogramming of 6,020 PC and 907 lncRNA genes. Although there was no evidence for fibroblast/myofibroblast conversion following EMT induction, cells displayed a partial EMT gene signature and an aberrant basaloid-like cell phenotype. The substantial transcriptional differences between submerged and ALI cultures highlight that care must be taken when interpreting data from submerged cultures. This work supports that lung epithelial EMT does not generate fibroblasts/myofibroblasts and confirms ALI cultures provide a physiologically relevant system to study aberrant basaloid-like cells and mechanisms of EMT. We provide a catalog of PC and lncRNA genes and an interactive browser ( https://bronc-epi-in-vitro.cells.ucsc.edu/ ) of single-cell RNA-Seq data for further exploration of potential roles in the lung epithelium in health and lung disease.