Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics

Christopher Cherry, David R. Maestas, Jin Han, James I. Andorko, Patrick Cahan, Elana J. Fertig, Lana X. Garmire, Jennifer H. Elisseeff

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)1228-1238
Number of pages11
JournalNature biomedical engineering
Issue number10
StatePublished - Oct 2021

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Medicine (miscellaneous)
  • Biomedical Engineering
  • Computer Science Applications


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