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.

对植入生物材料的异物反应的理解将受益于植入物周围微环境中细胞内和细胞间信号网络的重建。在这里，通过利用来自 42,156 个细胞的单细胞 RNA 测序数据，这些细胞是从聚己内酯或细胞外基质衍生支架的植入部位收集的，在体积肌肉损失的小鼠模型中，我们报告了重建的细胞间信号网络的计算分析来自转录因子激活的预测。我们发现细胞间信号网络可以聚集成与特定细胞亚群相关的模块，并且生物材料特异性反应可以通过免疫、成纤维细胞和组织特异性细胞的信号模块之间的相互作用来表征。在一个Il17ra ^–/–小鼠模型，我们验证了预测的白细胞介素 17 相关转录靶标会导致基因表达的伴随变化。此外，我们确定了与植入生物材料的反应无关的细胞亚群。细胞对植入生物材料的反应的单细胞图谱将有助于植入生物材料的设计和对随后发生的细胞反应的理解。