biostudies-literatureCherry CNIBIB NIH HHSU.S. Department of Health & Human Services | NIH | U.S. National Library of MedicineNICHD NIH HHSNIA NIH HHSNIEHS NIH HHSU.S. Department of Health & Human Services | NIH | National Institute on AgingU.S. Department of Health & Human Services | NIH | National Institute of Environmental Health SciencesNLM NIH HHSNIAMS NIH HHSNIGMS NIH HHSU.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and BioengineeringU.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development1228-1238https://www.ebi.ac.uk/biostudies/studies/S-EPMC9894531biostudies-literatureUnknown5(10)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 modulesNature biomedical engineeringComputational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics.PMC9894531R01EB028796DP1 AR076959R01 HD084633K01 ES025434R01LM012907K01ES025434R35 GM124725R01 EB028796R01 LM012373R01 LM012907T32 AG0585275T32AG058527Cherry CElisseeff JHAndorko JICahan PFertig EJHan JMaestas DRGarmire LXfalseComputational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics.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 modules2021-01-01T00:00:00Z2021 Oct2025-04-26T18:02:58.492Z2025-04-06T15:44:02.236ZS-EPMC98945313434153410.1038/s41551-021-00770-5