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Updated: Feb 16, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
Developing a Single-Cell Spatial Transcriptomics Workflow for In Vivo Evaluation of Implanted Biomaterials
Alex H P Chan1, Yunfei Hu1, Billie Pardavi1
1School of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Abstract:
In vivo evaluation of biomaterials largely relies on histology to assess biocompatibility and foreign body responses. While effective for capturing end-stage outcomes, these methods offer limited insight into the cellular mechanisms driving tissue remodeling, hindering efforts to rationally design better biomaterials. Transcriptomics has revolutionized our understanding of gene activity driving cellular function, yet remains underutilized in biomaterial evaluation. Recent advances in high-resolution spatial transcriptomics now enable precise mapping of gene expression within tissue, offering detailed insight into cellular states and spatial organization. To align biomaterial research with advances in spatial biology, we develop a bioinformatics workflow for the Xenium platform to analyze in vivo responses to implanted materials. Applying this workflow to evaluate electrospun polycaprolactone (PCL) scaffolds implanted subcutaneously in mice, we identify spatially distinct macrophage and fibroblast subpopulations with unique gene expression profiles. Spatial analyses show shared phenotypic features between co-localized macrophages and fibroblasts, oriented from the scaffold body to its surface. Gene ontology linked these spatial transitions to functional roles, with immune cell recruitment occurring within the scaffold and fibrosis at the surface. These transitions were not detectable by histology, highlighting spatial transcriptomics as a powerful approach for uncovering cellular dynamics and enabling better biologically-informed design of biomaterials.
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