Collections / Spatial localization with Spatial Transcriptomics for an atlas of healthy and injured cell states and niches in the human kidney [Visium ST]

Spatial localization with Spatial Transcriptomics for an atlas of healthy and injured cell states and niches in the human kidney [Visium ST]

Datasets23
Size~5.2 GB
AssayVisium
Samplehuman · kidney
KindComparison
Flag a data issue
10.1038/s41586-023-05769-3 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("doi-10-1038-s41586-023-05769-3")
cohort.members        # the 23 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/s41586-023-05769-3")
coll.ordered_artifacts.to_dataframe()   # the 23 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-s41586-023-05769-3 --dest data/

Licenses: 23 CC BY-NC-SA 4.0

An atlas of healthy and injured cell states and niches in the human kidney.

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods<sup>1</sup>. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Open in Vitessce
Visium
Human kidney
NCBI703
human kidney diabetic kidney disease 212 MB 453 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size212 MB
Spots453
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI697
human kidney acute kidney failure 211 MB 317 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditionacute kidney failure
Size211 MB
Spots317
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI706
human kidney diabetic kidney disease 229 MB 673 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size229 MB
Spots673
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI714
human kidney 272 MB 3,007 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Size272 MB
Spots3,007
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI692
human kidney acute kidney failure 231 MB 370 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditionacute kidney failure
Size231 MB
Spots370
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI700
human kidney diabetic kidney disease 211 MB 601 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size211 MB
Spots601
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI709
human kidney 210 MB 1,034 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Size210 MB
Spots1,034
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI698
human kidney diabetic kidney disease 198 MB 407 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size198 MB
Spots407
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI704
human kidney diabetic kidney disease 219 MB 534 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size219 MB
Spots534
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI693
human kidney acute kidney failure 218 MB 507 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditionacute kidney failure
Size218 MB
Spots507
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI707
human kidney diabetic kidney disease 219 MB 673 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size219 MB
Spots673
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI711
human kidney 255 MB 2,627 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Size255 MB
Spots2,627
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI710
human kidney 215 MB 956 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Size215 MB
Spots956
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI713
human kidney 275 MB 3,627 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Size275 MB
Spots3,627
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI702
human kidney diabetic kidney disease 211 MB 461 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size211 MB
Spots461
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI696
human kidney acute kidney failure 210 MB 645 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditionacute kidney failure
Size210 MB
Spots645
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI695
human kidney acute kidney failure 223 MB 673 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditionacute kidney failure
Size223 MB
Spots673
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI699
human kidney diabetic kidney disease 226 MB 787 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size226 MB
Spots787
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI708
human kidney diabetic kidney disease 226 MB 1,322 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size226 MB
Spots1,322
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI694
human kidney acute kidney failure 214 MB 640 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditionacute kidney failure
Size214 MB
Spots640
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI712
human kidney 303 MB 4,166 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Size303 MB
Spots4,166
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI701
human kidney diabetic kidney disease 221 MB 904 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size221 MB
Spots904
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human kidney
NCBI705
human kidney diabetic kidney disease 214 MB 560 spots silver H&E
TechnologyVisium
Organismhuman
Tissuekidney
Conditiondiabetic kidney disease
Size214 MB
Spots560
silver H&E Open in Vitessce

Cite this collection

doi.org/10.1038/s41586-023-05769-3 ↗
BibTeX
@article{Lake_2023,
  title = {An atlas of healthy and injured cell states and niches in the human kidney},
  volume = {619},
  ISSN = {1476-4687},
  url = {http://dx.doi.org/10.1038/s41586-023-05769-3},
  DOI = {10.1038/s41586-023-05769-3},
  number = {7970},
  journal = {Nature},
  publisher = {Springer Science and Business Media LLC},
  author = {Lake, Blue B. and Menon, Rajasree and Winfree, Seth and Hu, Qiwen and Melo Ferreira, Ricardo and Kalhor, Kian and Barwinska, Daria and Otto, Edgar A. and Ferkowicz, Michael and Diep, Dinh and Plongthongkum, Nongluk and Knoten, Amanda and Urata, Sarah and Mariani, Laura H. and Naik, Abhijit S. and Eddy, Sean and Zhang, Bo and Wu, Yan and Salamon, Diane and Williams, James C. and Wang, Xin and Balderrama, Karol S. and Hoover, Paul J. and Murray, Evan and Marshall, Jamie L. and Noel, Teia and Vijayan, Anitha and Hartman, Austin and Chen, Fei and Waikar, Sushrut S. and Rosas, Sylvia E. and Wilson, Francis P. and Palevsky, Paul M. and Kiryluk, Krzysztof and Sedor, John R. and Toto, Robert D. and Parikh, Chirag R. and Kim, Eric H. and Satija, Rahul and Greka, Anna and Macosko, Evan Z. and Kharchenko, Peter V. and Gaut, Joseph P. and Hodgin, Jeffrey B. and Knight, Richard and Lecker, Stewart H. and Stillman, Isaac and Amodu, Afolarin A. and Ilori, Titlayo and Maikhor, Shana and Schmidt, Insa and McMahon, Gearoid M. and Weins, Astrid and Hacohen, Nir and Bush, Lakeshia and Gonzalez-Vicente, Agustin and Taliercio, Jonathan and O’toole, John and Poggio, Emilio and Cooperman, Leslie and Jolly, Stacey and Herlitz, Leal and Nguyen, Jane and Palmer, Ellen and Sendrey, Dianna and Spates-Harden, Kassandra and Appelbaum, Paul and Barasch, Jonathan M. and Bomback, Andrew S. and D’Agati, Vivette D. and Mehl, Karla and Canetta, Pietro A. and Shang, Ning and Balderes, Olivia and Kudose, Satoru and Barisoni, Laura and Alexandrov, Theodore and Cheng, Yinghua and Dunn, Kenneth W. and Kelly, Katherine J. and Sutton, Timothy A. and Wen, Yumeng and Corona-Villalobos, Celia P. and Menez, Steven and Rosenberg, Avi and Atta, Mohammed and Johansen, Camille and Sun, Jennifer and Roy, Neil and Williams, Mark and Azeloglu, Evren U. and He, Cijang and Iyengar, Ravi and Hansen, Jens and Xiong, Yuguang and Rovin, Brad and Parikh, Samir and Madhavan, Sethu M. and Anderton, Christopher R. and Pasa-Tolic, Ljiljana and Velickovic, Dusan and Troyanskaya, Olga and Sealfon, Rachel and Tuttle, Katherine R. and Laszik, Zoltan G. and Nolan, Garry and Sarwal, Minnie and Anjani, Kavya and Sigdel, Tara and Ascani, Heather and Balis, Ulysses G. J. and Lienczewski, Chrysta and Steck, Becky and He, Yougqun and Schaub, Jennifer and Blanc, Victoria M. and Murugan, Raghavan and Randhawa, Parmjeet and Rosengart, Matthew and Tublin, Mitchell and Vita, Tina and Kellum, John A. and Hall, Daniel E. and Elder, Michele M. and Winters, James and Gilliam, Matthew and Alpers, Charles E. and Blank, Kristina N. and Carson, Jonas and De Boer, Ian H. and Dighe, Ashveena L. and Himmelfarb, Jonathan and Mooney, Sean D. and Shankland, Stuart and Williams, Kayleen and Park, Christopher and Dowd, Frederick and McClelland, Robyn L. and Daniel, Stephen and Hoofnagle, Andrew N. and Wilcox, Adam and Bansal, Shweta and Sharma, Kumar and Venkatachalam, Manjeri and Zhang, Guanshi and Pamreddy, Annapurna and Kakade, Vijaykumar R. and Moledina, Dennis and Shaw, Melissa M. and Ugwuowo, Ugochukwu and Arora, Tanima and Ardayfio, Joseph and Bebiak, Jack and Brown, Keith and Campbell, Catherine E. and Saul, John and Shpigel, Anna and Stutzke, Christy and Koewler, Robert and Campbell, Taneisha and Hayashi, Lynda and Jefferson, Nichole and Pinkeney, Roy and Roberts, Glenda V. and Eadon, Michael T. and Dagher, Pierre C. and El-Achkar, Tarek M. and Zhang, Kun and Kretzler, Matthias and Jain, Sanjay},
  year = {2023},
  month = July,
  pages = {585–594}
}