A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE175890 | GEO | 2021/08/01
REPOSITORIES: GEO
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Project description: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 harvested 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 data 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–/¬– knockout mouse model, we validated that predicted IL-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.
2021-08-01 | GSE175889 | GEO
Project description: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 harvested 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 data 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–/¬– knockout mouse model, we validated that predicted IL-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.
2021-08-01 | GSE175888 | GEO
Project description:A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks
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Project description:A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [single-cell RNA-seq]
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Project description:A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [bulk RNA-seq]
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