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Tissue-resident memory CD8 T cell diversity is spatiotemporally imprinted.

Miguel Reina-Campos, Alexander Monell, Amir Ferry, Vida Luna, Kitty P Cheung, Giovanni Galletti, Nicole E Scharping, Kennidy K Takehara, Sara Quon, Peter P Challita, Brigid Boland, Yun Hsuan Lin, William H Wong, Cynthia S Indralingam, Hayley Neadeau, Suzie Alarcón, Gene W Yeo, John T Chang, Maximilian Heeg, Ananda W Goldrath

Nature · 2025 · Vol. 639 (8054) · pp. 483-492

Abstract

Tissue-resident memory CD8 T (T<sub>RM</sub>) cells provide protection from infection at barrier sites. In the small intestine, T<sub>RM</sub> cells are found in at least two distinct subpopulations: one with higher expression of effector molecules and another with greater memory potential<sup>1</sup>. However, the origins of this diversity remain unknown. Here we proposed that distinct tissue niches drive the phenotypic heterogeneity of T<sub>RM</sub> cells. To test this, we leveraged spatial transcriptomics of human samples, a mouse model of acute systemic viral infection and a newly established strategy for pooled optically encoded gene perturbations to profile the locations, interactions and transcriptomes of pathogen-specific T<sub>RM</sub> cell differentiation at single-transcript resolution. We developed computational approaches to capture cellular locations along three anatomical axes of the small intestine and to visualize the spatiotemporal distribution of cell types and gene expression. Our study reveals that the regionalized signalling of the intestinal architecture supports two distinct T<sub>RM</sub> cell states: differentiated T<sub>RM</sub> cells and progenitor-like T<sub>RM</sub> cells, located in the upper villus and lower villus, respectively. This diversity is mediated by distinct ligand-receptor activities, cytokine gradients and specialized cellular contacts. Blocking TGFβ or CXCL9 and CXCL10 sensing by antigen-specific CD8 T cells revealed a model consistent with anatomically delineated, early fate specification. Ultimately, our framework for the study of tissue immune networks reveals that T cell location and functional state are fundamentally intertwined.

Linked datasets 3

GSE279255 GSE · via ncbi_elink
GEO ↗

Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted

Mus musculus

4 data files
FileTypeSize
44_R_S2_L001_I1_001.fastq.gz OTHER 4.7 GB
44_R_S2_L002_I1_001.fastq.gz OTHER 4.7 GB
SRR30949902_GSM8565271 OTHER 4.7 GB
SRR30949903_GSM8565271 OTHER 4.7 GB
GSE280895 GSE · via ncbi_elink
GEO ↗

Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted

Mus musculus

GSE279254 GSE · via ncbi_elink
GEO ↗

Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted [snRNA-Seq]

Mus musculus

32 data files
FileTypeSize
JC_EL_10XNuclei_c_dist_M1_S12_L002_R1_001.fastq.gz RNA-Seq 19.8 GB
JC_EL_10XNuclei_c_dist_M1_S8_L002_R1_001.fastq.gz RNA-Seq 17.6 GB
JC_EL_10XNuclei_c_prox_M1_S11_L002_R1_001.fastq.gz RNA-Seq 19.6 GB
JC_EL_10XNuclei_c_prox_M1_S7_L002_R1_001.fastq.gz RNA-Seq 20.6 GB
JC_EL_10XNuclei_si_dist_M1_S5_L002_R1_001.fastq.gz RNA-Seq 25.3 GB
JC_EL_10XNuclei_si_dist_M1_S9_L002_R1_001.fastq.gz RNA-Seq 10.7 GB
JC_EL_10XNuclei_si_dist_M2_S10_L002_R1_001.fastq.gz RNA-Seq 17.3 GB
JC_EL_10XNuclei_si_dist_M2_S6_L002_R1_001.fastq.gz RNA-Seq 21.2 GB
JC_EL_10XNuclei_si_mid_M1_S3_L002_R1_001.fastq.gz RNA-Seq 20.3 GB
JC_EL_10XNuclei_si_mid_M1_S7_L002_R1_001.fastq.gz RNA-Seq 21.6 GB
JC_EL_10XNuclei_si_mid_M2_S4_L002_R1_001.fastq.gz RNA-Seq 29.3 GB
JC_EL_10XNuclei_si_mid_M2_S8_L002_R1_001.fastq.gz RNA-Seq 10.2 GB
JC_EL_10XNuclei_si_prox_M1_S1_L002_R1_001.fastq.gz RNA-Seq 21.1 GB
JC_EL_10XNuclei_si_prox_M1_S5_L002_R1_001.fastq.gz RNA-Seq 17.1 GB
JC_EL_10XNuclei_si_prox_M2_S2_L002_R1_001.fastq.gz RNA-Seq 20.4 GB
JC_EL_10XNuclei_si_prox_M2_S6_L002_R1_001.fastq.gz RNA-Seq 20.9 GB
SRR30950141_GSM8565270 RNA-Seq 20.9 GB
SRR30950142_GSM8565270 RNA-Seq 21.2 GB
SRR30950143_GSM8565270 RNA-Seq 10.7 GB
SRR30950144_GSM8565270 RNA-Seq 25.3 GB
SRR30950145_GSM8565270 RNA-Seq 19.6 GB
SRR30950146_GSM8565270 RNA-Seq 20.6 GB
SRR30950147_GSM8565270 RNA-Seq 19.8 GB
SRR30950148_GSM8565270 RNA-Seq 17.6 GB
SRR30950149_GSM8565270 RNA-Seq 20.4 GB
SRR30950150_GSM8565270 RNA-Seq 17.1 GB
SRR30950151_GSM8565270 RNA-Seq 21.1 GB
SRR30950152_GSM8565270 RNA-Seq 10.2 GB
SRR30950153_GSM8565270 RNA-Seq 29.3 GB
SRR30950154_GSM8565270 RNA-Seq 21.6 GB
SRR30950155_GSM8565270 RNA-Seq 20.3 GB
SRR30950156_GSM8565270 RNA-Seq 17.3 GB

Potentially related datasets 3

These accessions were text-mined from the PMC full text. They may be referenced for comparison, cited from other studies, or otherwise mentioned without being primary data for this paper.

Accession Source Title
GSE279255 GSE · GEO GEO ↗ Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted
GSE279254 GSE · GEO GEO ↗ Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted [snRNA-Seq]
GSE280895 GSE · GEO GEO ↗ Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted

Analysis pipelines 3

Pipeline Assay Steps Dataset
GSE279254 snRNA-seq Data Processing geo_data_processing snRNA-seq 1 GSE279254
GSE279255 Spatial transcriptomics Data Processing geo_data_processing Spatial transcriptomics 2 GSE279255
GSE280895 Spatial transcriptomics Data Processing geo_data_processing Spatial transcriptomics 7 GSE280895
Funding 12 grants
Grant Funder
P30 DK120515 NIDDK NIH HHS (United States)
R01 AI150282 NIAID NIH HHS (United States)
P01 AI132122 NIAID NIH HHS (United States)
S10 OD025052 NIH HHS (United States)
F31 AI176705 NIAID NIH HHS (United States)
P30 NS047101 NINDS NIH HHS (United States)
I01 CX002396 CSRD VA (United States)
R01 AI072117 NIAID NIH HHS (United States)
R37 AI067545 NIAID NIH HHS (United States)
R01 AI179952 NIAID NIH HHS (United States)
R01 CA273432 NCI NIH HHS (United States)
K00 CA222711 NCI NIH HHS (United States)