| First Author | Evrard M | Year | 2023 |
| Journal | Immunity | Volume | 56 |
| Issue | 7 | Pages | 1664-1680.e9 |
| PubMed ID | 37392736 | Mgi Jnum | J:338301 |
| Mgi Id | MGI:7511350 | Doi | 10.1016/j.immuni.2023.06.005 |
| Citation | Evrard M, et al. (2023) Single-cell protein expression profiling resolves circulating and resident memory T cell diversity across tissues and infection contexts. Immunity 56(7):1664-1680.e9 |
| abstractText | Memory CD8(+) T cells can be broadly divided into circulating (T(CIRCM)) and tissue-resident memory T (T(RM)) populations. Despite well-defined migratory and transcriptional differences, the phenotypic and functional delineation of T(CIRCM) and T(RM) cells, particularly across tissues, remains elusive. Here, we utilized an antibody screening platform and machine learning prediction pipeline (InfinityFlow) to profile >200 proteins in T(CIRCM) and T(RM) cells in solid organs and barrier locations. High-dimensional analyses revealed unappreciated heterogeneity within T(CIRCM) and T(RM) cell lineages across nine different organs after either local or systemic murine infection models. Additionally, we demonstrated the relative effectiveness of strategies allowing for the selective ablation of T(CIRCM) or T(RM) populations across organs and identified CD55, KLRG1, CXCR6, and CD38 as stable markers for characterizing memory T cell function during inflammation. Together, these data and analytical framework provide an in-depth resource for memory T cell classification in both steady-state and inflammatory conditions. |
