Probes for INS

Abstract

RATIONALE:

The lung ECM in IPF mediates progression of fibrosis by decreasing fibroblast expression of microRNA-29 (miR-29), a master negative regulator of ECM production. The molecular mechanism is undefined. IPF ECM is stiffer than normal. Stiffness drives fibroblast ECM production in a YAP-dependent manner; and YAP is a known regulator of miR-29. Therefore, we tested the hypothesis that negative regulation of miR-29 by IPF ECM was mediated by mechanotransduction of stiffness.

OBJECTIVES:

To determine how IPF ECM negatively regulates miR-29.

METHODS:

We decellularized lung ECM using detergents, and prepared polyacrylamide hydrogels of defined stiffness by varying acrylamide concentrations. Mechanistic studies were guided by immunohistochemistry of IPF lung and employed cell culture, RNA binding protein assays, and xenograft models.

MEASUREMENTS AND MAIN RESULTS:

Contrary to our hypothesis, we excluded fibroblast mechanotransduction of ECM stiffness as the primary mechanism deregulating miR-29. Instead, systematic examination of miR-29 biogenesis revealed a microRNA processing defect that impeded processing of miR-29 into its mature bioactive forms. Immunohistochemical analysis of the micro-RNA processing machinery in IPF lung specimens revealed decreased Dicer1 expression in the procollagen-rich myofibroblastic core of fibroblastic foci compared to the focus perimeter and adjacent alveolar walls. Mechanistically, IPF ECM increased association of the Dicer1 transcript with RNA binding protein AUF1, and Dicer1 knockdown conferred primary human lung fibroblasts with cell-autonomous fibrogenicity in zebrafish and mouse-lung xenograft models.

CONCLUSIONS:

Our data identify suppression of fibroblast Dicer1 expression in the myofibroblast-rich IPF fibroblastic focus core as a central step in the mechanism by which the ECM sustains fibrosis progression in IPF.

This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells, allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of α-cells (5%), β-cells (92%), δ-cells (1%), and pancreatic polypeptide cells (2%). We identified cell-type-specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability, low sequencing quality, or contamination resulting in the detection of more than one islet hormone. Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.

Organogenesis requires the complex interactions of multiple cell lineages that coordinate their expansion, differentiation, and maturation over time. Here, we profile the cell types within the epithelial and mesenchymal compartments of the murine pancreas across developmental time using a combination of single-cell RNA sequencing, immunofluorescence, in situ hybridization, and genetic lineage tracing. We identify previously underappreciated cellular heterogeneity of the developing mesenchyme and reconstruct potential lineage relationships among the pancreatic mesothelium and mesenchymal cell types. Within the epithelium, we find a previously undescribed endocrine progenitor population, as well as an analogous population in both human fetal tissue and human embryonic stem cells differentiating toward a pancreatic beta cell fate. Further, we identify candidate transcriptional regulators along the differentiation trajectory of this population toward the alpha or beta cell lineages. This work establishes a roadmap of pancreatic development and demonstrates the broad utility of this approach for understanding lineage dynamics in developing organs.