There is a newer version of the record available.

Published July 3, 2024 | Version v1
Journal article Open

Ultra-precision deconvolution of spatial transcriptomics decodes immune heterogeneity and fate-defining programs in tissues

  • 1. ROR icon Beijing Institute of Genomics
  • 2. ROR icon Chinese Academy of Sciences
  • 3. China National Center for Bioinformation (CNCB)

Description

Immune cells infiltrate tissues in response to exogenous pathogens or spontaneous tumors, generating protective immunity to safeguard tissues. Despite advancements in spatial transcriptomics (ST), the precise spatial distribution and functional specialization of immune cells within tissue microenvironments remain elusive. Here, we introduce an ultra-precision ST deconvolution algorithm (UCASpatial) that enhances the mapping of cell subpopulations to spatial locations by leveraging the contribution of genes indicative of cell identity through entropy-based weighting. Using both in silico and real ST datasets, we demonstrate that UCASpatial improves the robustness and accuracy in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to human colorectal cancer (CRC), we link genomic alterations in individual cancer clones to multi-cellular characteristics of the tumor immune microenvironment (TIME) and reveal the co-evolution of tumor cells and TIME at a clonal resolution. We show that the copy number gain on chromosome 20q (chr20q-gain) in tumor cells orchestrates a T cell-excluded TIME, indicative of resistance to immunotherapy in CRC, and is associated with tumor-intrinsic human endogenous retrovirus subfamily H (HERV-H) silencing and impaired type I interferon response. In murine wound healing models, we illuminate the spatiotemporal dynamics of individual cell subsets across various stages of the healing process. We discovered that the scarring-healing mice (C57BL/6) exhibited a replacement of Prg4+ chondrogenic progenitors to Igfbp5+ chondrocytes in the wound bed at the regeneration stage, a change not observed in the regenerative strain (MRL/MpJ). The Igfbp5+ chondrocyte, spatially coordinating with Cd36+ Gpnmb+ Il1b- macrophage and Fmod+ fibroblast, forms a pro-fibrotic community associated with regeneration failure. The cell-cell interactions within this three-cell cluster, mediated by the IL11-IL11RA axis, drive the pro-fibrotic community formation and limit regeneration in C57BL/6 mice. Our findings present UCASpatial as a versatile tool for deciphering fine-grained cellular landscapes in ST and exploring intercellular mechanisms in complex and dynamic microenvironments.

Files

Figure2.zip

Files (29.9 GB)

Name Size Download all
md5:5e9b2b225ac5c6b30bce99b43e073209
129.8 MB Download
md5:0ee82945bca30953bcca03f9428b2bbb
57.9 MB Download
md5:e9c5d35228ca5fe1b2208135cbdcd0d1
1.3 GB Preview Download
md5:2185f8b1de341edc5618d7e6a67a5b08
25.0 GB Preview Download
md5:a936a648f266ec8a8531c392cf67badc
2.4 GB Preview Download
md5:f8235f5c3835b749d2f6e774fa57dd90
948.1 MB Preview Download

Additional details

Software

Repository URL
https://github.com/BIGHanLab/UCASpatial
Programming language
R , Python