Collections / Spatial sequencing of young and aged lungs following influenza A virus infection

Spatial sequencing of young and aged lungs following influenza A virus infection

Aging is known to alter the host repsonse to influenza infection. Here, we use 10x Visium spatial sequencing to identify spatial changes in mRNA expression of left lungs of young (16-week-old) and aged (80-week-old) mice following influenza infection.

Datasets6
Size~190 MB
AssayVisium
Samplemouse · lung
KindTime course
Flag a data issue
PMID:37852965 ↗
Download the whole collection
Python · sddb client 
from sddb import Catalog

cohort = Catalog().collection("geo-gse202322")
cohort.members        # the 6 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/")
Install (Python 3.12+) Docs →
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="geo-gse202322")
coll.ordered_artifacts.to_dataframe()   # the 6 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Install (Python 3.12+) Docs →
Shell 
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse202322 --dest data/
Install (Python 3.12+) Docs →

Licenses: 6 NCBI GEO policy

Member datasets · 6
Open in Vitessce
Visium
Mouse lung
GSM6108349
mouse lung influenza 29.2 MB 2,520 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuelung
Conditioninfluenza
Size29.2 MB
Spots2,520
Magnificationother · 4.311 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse lung
GSM6108351
mouse lung influenza 37.8 MB 2,969 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuelung
Conditioninfluenza
Size37.8 MB
Spots2,969
Magnificationother · 3.984 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse lung
GSM6108350
mouse lung influenza 41.3 MB 2,847 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuelung
Conditioninfluenza
Size41.3 MB
Spots2,847
Magnificationother · 3.980 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse lung
GSM6108348
mouse lung influenza 34.0 MB 2,486 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuelung
Conditioninfluenza
Size34.0 MB
Spots2,486
Magnificationother · 4.322 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse lung
GSM6108346
mouse lung 23.9 MB 1,986 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuelung
Size23.9 MB
Spots1,986
Magnificationother · 4.004 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse lung
GSM6108347
mouse lung 23.5 MB 2,218 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuelung
Size23.5 MB
Spots2,218
Magnificationother · 3.989 µm/px
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1038/s41467-023-42021-y ↗
BibTeX 
@article{Kasmani_2023,
  title = {A spatial sequencing atlas of age-induced changes in the lung during influenza infection},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-42021-y},
  DOI = {10.1038/s41467-023-42021-y},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Kasmani, Moujtaba Y. and Topchyan, Paytsar and Brown, Ashley K. and Brown, Ryan J. and Wu, Xiaopeng and Chen, Yao and Khatun, Achia and Alson, Donia and Wu, Yue and Burns, Robert and Lin, Chien-Wei and Kudek, Matthew R. and Sun, Jie and Cui, Weiguo},
  year = {2023},
  month = Oct
}