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Biology subjects

Choi, K. M.

Publications and source records attributed to Choi, K. M..

3 recordsLinked to original sources

Lung injury epigenetically primes mesenchyme for amplified activation upon re-injury

The lungs have a remarkable capacity to repair. However, repetitive injury can lead to progressive fibrosis and end-stage organ failure. Whether tissue-resident mesenchymal cell populations retain epigenetic memory of prior injuries that contribute to this pathological process is unknown. Here we used a genetic lineage labeling approach to mark the lung mesenchyme prior to injury, then performed multi-modal analyses on isolated lung mesenchyme during the initiation, progression and resolution of the fibrotic response. Our results demonstrate the remarkable epigenetic and transcriptional plasticity of the lung mesenchyme during fibrogenic activation and de-activation. Despite this plasticity, we also find that the lung mesenchyme retains specific epigenetic traits (memory) of prior activation, resulting in amplified induction of a fibrogenic program upon re-injury. We identify Runx1 as a critical driver of both fibrogenic activation and epigenetic memory. Comparison of fresh isolated and cultured lung mesenchyme demonstrates that Runx1 is spontaneously activated in standard culture conditions, previously masking these roles of Runx1. Genetic and pharmacological targeting of Runx1 dampens fibrogenic mesenchymal cell activation in cell and tissue models, confirming its functional importance. Finally, publicly available scRNAseq data reveal selective expression of Runx1 in the fibrogenic cell subpopulations that emerge in mouse and human fibrotic lung tissue. Collectively, our findings implicate Runx1 in both the initiation and memory of fibrogenic mesenchymal cell activation that together prime amplified mesenchymal cell responses upon repeated injury.

cell biology↗

ZNF416 is a pivotal transcriptional regulator of fibroblast mechano-activation

Matrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly-isolated lung fibroblasts using assay for transposase-accessible chromatin followed by sequencing (ATAC-seq). We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known pro-fibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Similarly, motif analysis of the promoters of differentially expressed genes observed in freshly sorted fibroblasts from an experimental bleomycin lung fibrosis model also identified ZNF416 as a putative mediator of in vivo fibroblast activation. Genome occupancy analysis using chromatin-immunoprecipitation followed by sequencing (ChIP-seq) confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue-fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and pro-fibrotic transcriptional regulators. Using loss and gain of function studies we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis and contractile function. Together these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.

cell biology↗

A Portable Structural Analysis Library for Reaction Networks

The topology of a reaction network can have a significant influence on the networks dynamical properties. Such influences can include constraints on network flows and concentration changes or more insidiously result in the emergence of feedback loops. These effects are due entirely to mass constraints imposed by the network configuration and are important considerations before any dynamical analysis is made. Most established simulation software tools usually carry out some kind of structural analysis of a network before any attempt is made at dynamic simulation. In this paper we describe a portable software library, libStructural, that can carry out a variety of popular structural analyses that includes conservation analysis, flux dependency analysis and enumerating elementary modes. The library employs robust algorithms that allow it to be used on large networks with more than a two thousand nodes. The library accepts either a raw or fully labeled stoichiometry matrix or models written in SBML format. The software is written in standard C/C++ and comes with documentation and a test suite. The software is available for Windows, Mac OS X, and can be compiled easily on any Linux operating system. A language binding for Python is also available through the pip package manager making it trivial to install on any standard Python distribution. As a second example, we also create a new libStructural plugin for PathwayDesigner that allows solutions to be viewed graphically. The source code is licensed under the open source BSD license and is available on GitHub (https://github.com/sys-bio/Libstructural)

systems biology↗