Multimodal human thymic profiling reveals trajectories and cellular milieu for T agonist selection [Spatial transcriptomics]
To prevent autoimmunity, thymocytes expressing self-reactive T cell receptors (TCRs) are negatively selected, however, divergence into tolerogenic, agonist-selected lineages represent an alternative fate. As thymocyte development, selection, and lineage choices are dependent on spatial context and cell-to-cell interactions, we have performed Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) and spatial transcriptomics on paediatric human thymus. Thymocytes expressing markers of strong TCR signalling diverged from the conventional developmental trajectory prior to CD4+ lineage commitment, while markers of different agonist cell populations (CD8αα(I), CD8αα(II), T(agonist), Treg(diff) and Treg) exhibited variable timing of induction. Expression profiles of chemokines and co-stimulatory molecules, together with spatial localization, supported that dendritic cells, B cells, and stromal cells contribute to agonist selection, with different subsets influencing thymocytes at specific developmental stages within distinct spatial niches. Understanding factors influencing agonist T cells is needed to benefit from their immunoregulatory effects in clinical use.
from sddb import Catalog
cohort = Catalog().collection("geo-gse207205")
cohort.members # the 8 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/") Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse207205")
coll.ordered_artifacts.to_dataframe() # the 8 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] # sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse207205 --dest data/ Licenses: 8 NCBI GEO policy
Cite this collection
doi.org/10.3389/fimmu.2022.1092028 ↗@article{Heimli_2023,
title = {Multimodal human thymic profiling reveals trajectories and cellular milieu for T agonist selection},
volume = {13},
ISSN = {1664-3224},
url = {http://dx.doi.org/10.3389/fimmu.2022.1092028},
DOI = {10.3389/fimmu.2022.1092028},
journal = {Frontiers in Immunology},
publisher = {Frontiers Media SA},
author = {Heimli, Marte and Flåm, Siri Tennebø and Hjorthaug, Hanne Sagsveen and Trinh, Don and Frisk, Michael and Dumont, Karl-Andreas and Ribarska, Teodora and Tekpli, Xavier and Saare, Mario and Lie, Benedicte Alexandra},
year = {2023},
month = Jan
}