Collections / A spatially resolved atlas of the human lung characterizes a gland-associated immune niche

A spatially resolved atlas of the human lung characterizes a gland-associated immune niche

Datasets20
Size~9.6 GB
AssayVisium
Samplehuman · lung
KindPublication
Flag a data issue
10.1038/s41588-022-01243-4 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("doi-10-1038-s41588-022-01243-4")
cohort.members        # the 20 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/")
Python · lamindb

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="doi-10.1038/s41588-022-01243-4")
coll.ordered_artifacts.to_dataframe()   # the 20 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection doi-10-1038-s41588-022-01243-4 --dest data/

Licenses: 20 CC BY-NC-SA 4.0

A spatially resolved atlas of the human lung characterizes a gland-associated immune niche.

Single-cell transcriptomics has allowed unprecedented resolution of cell types/states in the human lung, but their spatial context is less well defined. To (re)define tissue architecture of lung and airways, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and spatial transcriptomics (queryable at lungcellatlas.org ). Using computational data integration and analysis, we extend beyond the suspension cell paradigm and discover macro and micro-anatomical tissue compartments including previously unannotated cell types in the epithelial, vascular, stromal and nerve bundle micro-environments. We identify and implicate peribronchial fibroblasts in lung disease. Importantly, we discover and validate a survival niche for IgA plasma cells in the airway submucosal glands (SMG). We show that gland epithelial cells recruit B cells and IgA plasma cells, and promote longevity and antibody secretion locally through expression of CCL28, APRIL and IL-6. This new 'gland-associated immune niche' has implications for respiratory health.

Open in Vitessce
Visium
Human lung
MISC15
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TechnologyVisium
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Tissuelung
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Open in Vitessce
Visium
Human lung
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silver H&E Open in Vitessce
Open in Vitessce
Visium
Human lung
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TechnologyVisium
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Open in Vitessce
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Human lung
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TechnologyVisium
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Open in Vitessce
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Open in Vitessce
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Open in Vitessce
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Open in Vitessce
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TechnologyVisium
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Open in Vitessce
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Open in Vitessce
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Open in Vitessce
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Open in Vitessce
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human lung 408 MB 2,524 spots silver H&E
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silver H&E Open in Vitessce

Cite this collection

doi.org/10.1038/s41588-022-01243-4 ↗
BibTeX
@article{Madissoon_2022,
  title = {A spatially resolved atlas of the human lung characterizes a gland-associated immune niche},
  volume = {55},
  ISSN = {1546-1718},
  url = {http://dx.doi.org/10.1038/s41588-022-01243-4},
  DOI = {10.1038/s41588-022-01243-4},
  number = {1},
  journal = {Nature Genetics},
  publisher = {Springer Science and Business Media LLC},
  author = {Madissoon, Elo and Oliver, Amanda J. and Kleshchevnikov, Vitalii and Wilbrey-Clark, Anna and Polanski, Krzysztof and Richoz, Nathan and Ribeiro Orsi, Ana and Mamanova, Lira and Bolt, Liam and Elmentaite, Rasa and Pett, J. Patrick and Huang, Ni and Xu, Chuan and He, Peng and Dabrowska, Monika and Pritchard, Sophie and Tuck, Liz and Prigmore, Elena and Perera, Shani and Knights, Andrew and Oszlanczi, Agnes and Hunter, Adam and Vieira, Sara F. and Patel, Minal and Lindeboom, Rik G. H. and Campos, Lia S. and Matsuo, Kazuhiko and Nakayama, Takashi and Yoshida, Masahiro and Worlock, Kaylee B. and Nikolić, Marko Z. and Georgakopoulos, Nikitas and Mahbubani, Krishnaa T. and Saeb-Parsy, Kourosh and Bayraktar, Omer Ali and Clatworthy, Menna R. and Stegle, Oliver and Kumasaka, Natsuhiko and Teichmann, Sarah A. and Meyer, Kerstin B.},
  year = {2022},
  month = Dec,
  pages = {66–77}
}