Collections / Spatial Transcriptomics of Joint-Draining Popliteal Lymph Nodes from Wild-type and TNF-Tg Mice with Early and Advanced Inflammatory-Erosive Arthritis

Spatial Transcriptomics of Joint-Draining Popliteal Lymph Nodes from Wild-type and TNF-Tg Mice with Early and Advanced Inflammatory-Erosive Arthritis

Lymphatic dysfunction is an integral aspect of rheumatoid arthritis (RA) pathogenesis. During "Early" arthritis in tumor necrosis factor transgenic (TNF-Tg) mice, the joint-draining popliteal lymph nodes (PLNs) dramatically expand in volume. After a prolonged expansion phase, at ~8-months-old the PLNs stochastically collapse with reduced bone volume and associated onset of "Advanced" inflammatory-erosive arthritis in affected joints. Through this pathologic process, B-cells are known to translocate into the PLN sinuses. Bulk tissue approaches (i.e. bulk genomics, flow cytometry, and ex vivo cell cultures) have been insufficient to specifically evaluate the transcriptional changes of B-cells within the sinuses of TNF-Tg PLNs. Thus, we utilized spatial transcriptomics technology to evaluate transcriptional changes in sinus B-cells and the functional genomic relationships with arthritic severity.

Datasets4
Size~38.1 MB
AssayVisium
Samplemouse · popliteal lymph node
KindTime course
Flag a data issue
PMID:37691918 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse195598")
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/")
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-gse195598")
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()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse195598 --dest data/

Licenses: 4 NCBI GEO policy

Open in Vitessce
Visium
Mouse popliteal lymph node
GSM5841551
mouse popliteal lymph node rheumatoid arthritis 11.3 MB 1,489 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuepopliteal lymph node
Conditionrheumatoid arthritis
Size11.3 MB
Spots1,489
Magnificationother · 3.266 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse popliteal lymph node
GSM5841550
mouse popliteal lymph node 5.8 MB 833 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuepopliteal lymph node
Size5.8 MB
Spots833
Magnificationother · 3.324 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse popliteal lymph node
GSM5841552
mouse popliteal lymph node rheumatoid arthritis 10.7 MB 2,015 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuepopliteal lymph node
Conditionrheumatoid arthritis
Size10.7 MB
Spots2,015
Magnificationother · 3.289 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse popliteal lymph node
GSM5841553
mouse popliteal lymph node rheumatoid arthritis 10.3 MB 1,782 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuepopliteal lymph node
Conditionrheumatoid arthritis
Size10.3 MB
Spots1,782
Magnificationother · 3.290 µm/px
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.3389/fimmu.2023.1237498 ↗
BibTeX
@article{Kenney_2023,
  title = {Multi-omics analysis identifies IgG2b class-switching with ALCAM-CD6 co-stimulation in joint-draining lymph nodes during advanced inflammatory-erosive arthritis},
  volume = {14},
  ISSN = {1664-3224},
  url = {http://dx.doi.org/10.3389/fimmu.2023.1237498},
  DOI = {10.3389/fimmu.2023.1237498},
  journal = {Frontiers in Immunology},
  publisher = {Frontiers Media SA},
  author = {Kenney, H. Mark and Rangel-Moreno, Javier and Peng, Yue and Chen, Kiana L. and Bruno, Jennifer and Embong, Abdul and Pritchett, Elizabeth and Fox, Jeffrey I. and Becerril-Villanueva, Enrique and Gamboa-Domínguez, Armando and Quataert, Sally and Muthukrishnan, Gowrishankar and Wood, Ronald W. and Korman, Benjamin D. and Anolik, Jennifer H. and Xing, Lianping and Ritchlin, Christopher T. and Schwarz, Edward M. and Wu, Chia-Lung},
  year = {2023},
  month = Aug
}