The mechanisms that guide Th2 cell differentiation in barrier tissues are unclear but important for the development of allergic asthma. Using temporal, spatial and single cell transcriptomic tracking of house dust mite (HDM) specific T cells, we describe the molecular pathways driving allergen-specific Th2 cells. Early Blimp-1 expression occurs in a subset of CD4 T cells in the lymph node prior to lung migration driven by IL-10 from allergen-specific T cells, but was not required for GATA3 upregulation. Instead, IL-2 via STAT5 was required to directly repress Bcl6 and Bach2 to support GATA3 and Blimp-1 upregulation. Loss of Blimp-1 during priming in the lymph node ablated the formation of Th2 cells that migrate to the lung, indicating early Blimp-1 promotes the population of Th2 cells with migratory capability. Spatial microniches of IL-2 in the lymph node discriminate and support these earliest Blimp-1+ migratory Th2 cells, demonstrating that lymph node localization is a primary driver of differentiation. Our findings illuminate the molecular pathways for inhaled allergens to promote Th2 cells and identify an early requirement for IL-2 mediated spatial microniches and allergen-driven IL-10 from responding T cells that drive allergic asthma.
from sddb import Catalog
cohort = Catalog().collection("geo-gse245110")
cohort.members # the 4 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-gse245110")
coll.ordered_artifacts.to_dataframe() # the 4 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-gse245110 --dest data/Licenses: 4 NCBI GEO policy
@article{Rahimikollu_2024,
title = {SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains},
volume = {21},
ISSN = {1548-7105},
url = {http://dx.doi.org/10.1038/s41592-024-02175-z},
DOI = {10.1038/s41592-024-02175-z},
number = {5},
journal = {Nature Methods},
publisher = {Springer Science and Business Media LLC},
author = {Rahimikollu, Javad and Xiao, Hanxi and Rosengart, AnnaElaine and Rosen, Aaron B. I. and Tabib, Tracy and Zdinak, Paul M. and He, Kun and Bing, Xin and Bunea, Florentina and Wegkamp, Marten and Poholek, Amanda C. and Joglekar, Alok V. and Lafyatis, Robert A. and Das, Jishnu},
year = {2024},
month = Feb,
pages = {835–845}
}