CD4+ T cells play a critical role in sustaining the effector function of CD8+ T cells during chronic viral infection. When CD4+ T cell “help” is absent, CD8+ T cells enter a dysfunctional state, losing their capacity for viral control. Here, we applied spatial transcriptomics to explore cellular localization and potential interaction between key immune cell subsets during chronic LCMV Clone 13 infection.
from sddb import Catalog
cohort = Catalog().collection("geo-gse200720")
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-gse200720")
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-gse200720 --dest data/Licenses: 8 NCBI GEO policy
@article{Topchyan_2022,
title = {Spatial transcriptomics demonstrates the role of CD4 T cells in effector CD8 T cell differentiation during chronic viral infection},
volume = {41},
ISSN = {2211-1247},
url = {http://dx.doi.org/10.1016/j.celrep.2022.111736},
DOI = {10.1016/j.celrep.2022.111736},
number = {9},
journal = {Cell Reports},
publisher = {Elsevier BV},
author = {Topchyan, Paytsar and Zander, Ryan and Kasmani, Moujtaba Y. and Nguyen, Christine and Brown, Ashley and Lin, Siying and Burns, Robert and Cui, Weiguo},
year = {2022},
month = Nov,
pages = {111736}
}