Does the Extracellular Matrix Support Cell-Cell Communication by Elastic Wave Packets?

Communication between alveolar macrophages and fibroblasts via the TNFSF12-TNFRSF12A pathway promotes pulmonary fibrosis in severe COVID-19 patients

BACKGROUND

Severe COVID-19 infection has been associated with the development of pulmonary fibrosis, a condition that significantly affects patient prognosis. Understanding the underlying cellular communication mechanisms contributing to this fibrotic process is crucial.

OBJECTIVE

In this study, we aimed to investigate the role of the TNFSF12-TNFRSF12A pathway in mediating communication between alveolar macrophages and fibroblasts, and its implications for the development of pulmonary fibrosis in severe COVID-19 patients.

METHODS

We conducted single-cell RNA sequencing (scRNA-seq) analysis using lung tissue samples from severe COVID-19 patients and healthy controls. The data was processed, analyzed, and cell types were annotated. We focused on the communication between alveolar macrophages and fibroblasts and identified key signaling pathways. In vitro experiments were performed to validate our findings, including the impact of TNFRSF12A silencing on fibrosis reversal.

RESULTS

Our analysis revealed that in severe COVID-19 patients, alveolar macrophages communicate with fibroblasts primarily through the TNFSF12-TNFRSF12A pathway. This communication pathway promotes fibroblast proliferation and expression of fibrotic factors. Importantly, silencing TNFRSF12A effectively reversed the pro-proliferative and pro-fibrotic effects of alveolar macrophages.

CONCLUSION

The TNFSF12-TNFRSF12A pathway plays a central role in alveolar macrophage-fibroblast communication and contributes to pulmonary fibrosis in severe COVID-19 patients. Silencing TNFRSF12A represents a potential therapeutic strategy for mitigating fibrosis in severe COVID-19 lung disease.

Modeling the extracellular matrix in cell migration and morphogenesis: a guide for the curious biologist

The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes remains difficult to investigate comprehensively due to its complexity and structural variation within an organism. In tandem with experiments, mathematical models are helpful in refining and testing hypotheses, generating predictions, and exploring conditions outside the scope of experiments. Such models can be combined and calibrated with in vivo and in vitro data to identify critical cell-ECM interactions that drive developmental and homeostatic processes, or the progression of diseases. In this review, we focus on mathematical and computational models of the ECM in processes such as cell migration including cancer metastasis, and in tissue structure and morphogenesis. By highlighting the predictive power of these models, we aim to help bridge the gap between experimental and computational approaches to studying the ECM and to provide guidance on selecting an appropriate model framework to complement corresponding experimental studies.

High-Throughput Multiparametric Quantification of Mechanics Driven Heterogeneity in Mesenchymal Stromal Cell Population

Mesenchymal stromal or stem cells (MSCs) are one of the most promising candidates for a myriad of cell therapy applications. Despite showing promise in numerous preclinical and clinical studies, MSC-based therapy is not yet a reality for regenerative medicine due to its suboptimal outcome at the clinical endpoint. The mechanical environment is a critical determinant of MSC gene expression and function. This study reports that MSC population becomes phenotypically heterogenous and commits to an unwanted osteoprogenitor pathway when it experiences an abnormal mechanically stiff environment, compared to its native softer environment. A method is developed to measure the heterogeneity using nuclear shape, chromatin state, and CD73 marker. Heterogeneity is shown to be associated with a larger spread in the nuclear shape parameters and a smaller spread in the chromatin openness. Subsequently, intervention strategies are investigated to create a more homogeneous MSC population. Culturing MSCs on soft surfaces or inhibiting actomyosin on stiff surfaces can make them more homogeneous, while inhibiting YAP, Runx2, and actin polymerization helps maintain but does not fully homogenize them. This study offers insights for cell and tissue engineers, aiding in the design of optimal conditions and materials for MSC culture, ultimately enhancing their therapeutic potential.