Developing a Single‐Cell Spatial Transcriptomics Workflow for In Vivo Evaluation of Implanted Biomaterials

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.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-02-15
DOI
https://doi.org/10.1002/advs.202513242
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Developing a Single‐Cell Spatial Transcriptomics Workflow for In Vivo Evaluation of Implanted Biomaterials

Yunfei Hu, Richard P. Tan, Steven G. Wise, Xueying Xu et al.
Advanced Science
Single-cell and spatial transcriptomics
article

Developing a Single‐Cell Spatial Transcriptomics Workflow for In Vivo Evaluation of Implanted Biomaterials

Yunfei Hu, Richard P. Tan, Steven G. Wise, Xueying Xu, Angus Grant, Lipin Loo, Alex H.P. Chan, Billie Pardavi
article en

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.

Advanced Science
The University of Sydney (AU), UNSW Sydney (AU)
University of Sydney, Australian Centre for Microscopy and Microanalysis, University of Sydney, Medical Research Council, National Health and Medical Research Council
Partnerships for the goals
Openalex Percentile: Top 55%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.