Deep profiling deconstructs features associated with memory CD8+ T cell tissue residence [CITE-Seq]

Tissue resident memory CD8+ T cells (Trm) control infections and cancer and are defined by their lack of recirculation. Because migration is difficult to assess, residence is usually inferred by putative residence-defining phenotypic and gene signature proxies. We assessed the validity and universality of residence proxies by integrating mouse parabiosis, multi-organ sampling, intravascular staining, acute and chronic infection models, dirty mice, and single-cell multi-omics. We report that memory T cells integrate a constellation of inputs— location, stimulation history, antigen persistence, and environment— resulting in myriad differentiation states. Thus, current Trm-defining methodologies have implicit limitations, and a universal residence-specific signature may not exist. However, we define genes and phenotypes that more robustly correlate with tissue residence across the broad range of conditions that we tested. This study reveals broad adaptability of T cells to diverse stimulatory and environmental inputs and provides practical recommendations for evaluating Trm cells. To define features unique to tissue resident memory CD8+ T cells, we leveraged Cellular Indexing of Transcriptomes and Epitopes sequencing (CITE-seq). We first established parabionts containing either LCMV Armstrong- or influenza PR8-induced memory P14 cells. We then performed in vivo intravascular staining with biotin anti-CD8a, isolated lymphocytes from tissues, stained cells with CITE-seq and flow cytometry compatible antibodies, FACS sorted for P14 cells, and performed single-cell RNA-sequencing. Since our main objective was to evaluate the influence of tissue location, migration property, and vascular localization on gene expression profiles in the context of two different infections, we stained cells with CITE-seq compatible antibodies targeting congenic markers (Thy1.1 and CD45.1) and i.v. antibody-labeled cells, along with a select few cell surface markers: CD69, CD103, Ly6C, CD127, CD62L, CX3CR1, and KLRG1. For multiplexing purposes, cells from each tissue were stained with a unique TotalSeq-A anti-mouse oligonucleotide hashtag. After sorting, cells from all tissues for each parabiont (CD45.1 host or Thy1.1 host) were pooled to constitute one technical replicate. Pooled cells from the CD45.1 parabiont host were designated as replicate "A". Pooled cells from the Thy1.1 parabiont host were designated as replicate "B". We followed the 10X Genomics Chromium Single Cell 3’ v3 protocol to prepare RNA, antibody-derived-tag (ADT), and hashtag oligos (HTO) libraries. To maintain the identify of each parabiont, cells from each parabiont (CD45.1 parabiont = "A" and Thy.1 parabiont = "B") were captured separately and sequenced on separate 10X lanes. Each cell suspension was loaded onto a 10X Genomics Chromium Controller at a concentration of 1,200 cells per microliter to target about 40,000 cells per the two technical replicates, "A" and "B". RNA, ADT, and HTO libraires were sequenced with an Illumina NovaSeq S4. Reads were processed with 10X Genomics Cell Ranger v.7.0.0 with feature barcoding, where RNA reads were mapped to the mouse mm10–2.1.0 mouse reference and antibody reads mapped to known barcodes. LCMV Armstrong is shortened to "arm" in the data files for the LCMV Arm CITE-seq experiment. PR8-gp33 is shortened to "flu" in the data files for the PR8-gp33 CITE-seq experiment. [April 30, 2025] Some of the fastq files uploaded for GSE277081 were the shallow/QC sequencing files instead of the full depth sequencing files. The proper files have been linked to Samples GSM8513844-GSM8513849.