Open AccessComputational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics
Author(s) -
Christopher R. Cherry,
David R. Maestas,
Jin Soo Han,
James I. Andorko,
Patrick Cahan,
Elana J. Fertig,
Lana X. Garmire,
Jennifer Elisseeff
Publication year - 2021
Publication title -
nature biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.961
H-Index - 56
ISSN - 2157-846X
DOI - 10.1038/s41551-021-00770-5
Subject(s) - signalling , microbiology and biotechnology , transcriptome , cell , computational biology , computer science , chemistry , nanotechnology , biology , materials science , biochemistry , gene expression , gene
The understanding of the foreign-body responses to implanted biomaterials would benefit from the reconstruction of intracellular and intercellular signalling networks in the microenvironment surrounding the implant. Here, by leveraging single-cell RNA-sequencing data from 42,156 cells collected from the site of implantation of either polycaprolactone or an extracellular-matrix-derived scaffold in a mouse model of volumetric muscle loss, we report a computational analysis of intercellular signalling networks reconstructed from predictions of transcription-factor activation. We found that intercellular signalling networks can be clustered into modules associated with specific cell subsets, and that biomaterial-specific responses can be characterized by interactions between signalling modules for immune, fibroblast and tissue-specific cells. In a Il17ra -/- mouse model, we validated that predicted interleukin-17-linked transcriptional targets led to concomitant changes in gene expression. Moreover, we identified cell subsets that had not been implicated in the responses to implanted biomaterials. Single-cell atlases of the cellular responses to implanted biomaterials will facilitate the design of implantable biomaterials and the understanding of the ensuing cellular responses.