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Leiby, K. L.

Publications and source records attributed to Leiby, K. L..

2 recordsLinked to original sources

In vitro engineering of the lung alveolus

Therapeutic lung regeneration is predicated upon successful reconstitution of lung alveoli, the functional units of gas exchange. Here, we identify requisite multimodal cues that are critical to reconstructing the alveolar epithelium and alveoli in lung scaffolds. Alveolar reconstruction in vitro is divided into several distinct phases. In the first phase, endothelial cells coordinate with fibroblasts and select exogenous factors to promote alveolar scaffold population with surfactant-secreting alveolar epithelial type 2 cells (AEC2s). After formation of organized epithelial alveolar-like structures, subsequent withdrawal of Wnt and FGF agonism synergizes with tidal-level mechanical strain to induce differentiation of AEC2s to squamous type 1 AECs (AEC1s) in cultured alveoli, in situ. These results outline a rational strategy to engineer an alveolus of AEC2s and AEC1s contained within epithelial-mesenchymal-endothelial units, and reveal the critical interplay amongst biochemical, cellular, and mechanical niche cues within the reconstituting alveolus.

bioengineering↗

Connectome: computation and visualization of cell-cell signaling topologies in single-cell systems data

Single-cell RNA-sequencing data can revolutionize our understanding of the patterns of cell-cell and ligand-receptor connectivity that influence the function of tissues and organs. However, the quantification and visualization of these patterns are major computational and epistemological challenges. Here, we present Connectome, a software package for R which facilitates rapid calculation, and interactive exploration, of cell-cell signaling network topologies contained in single-cell RNA-sequencing data. Connectome can be used with any reference set of known ligand-receptor mechanisms. It has built-in functionality to facilitate differential and comparative connectomics, in which complete mechanistic networks are quantitatively compared between systems. Connectome includes computational and graphical tools designed to analyze and explore cell-cell connectivity patterns across disparate single-cell datasets. We present approaches to quantify these topologies and discuss some of the biologic theory leading to their design.

systems biology↗