Human and Murine Kidneys Contain Transcriptionally and Spatially Orthologous Resident Macrophage Subpopulations in Acute Kidney Injury
Acute kidney injury (AKI) is a major health burden in the United States. Macrophages have been shown to mediate AKI in murine models. Murine kidneys contain multiple subpopulations of kidney resident macrophages (KRM) that are transcriptionally and spatially distinct. We hypothesized the human kidney contains orthologous KRM subpopulations, both transcriptionally and spatially. We utilized kidney sections from donors diagnosed with mild to moderate AKI in order to increase the translatability of murine research to clinical settings. We used spatial transcriptomics and single cell RNA sequencing to identify five distinct human KRM subpopulations. Using the AddModuleScore function in Seurat, we were able to compare the murine KRM transcriptional profiles from pre and post-AKI to the human KRM subpopulations. As a result, we identified four orthologous to known murine KRM subpopulations. The remaining population was identified in the kidney cortex and expresses a profile similar to activate microglia, the resident macrophage population in the brain. Again, we used AddModuleScore to determine a set of marker genes that will allow for the identification of KRM subsets across species and injury.
from sddb import Catalog
cohort = Catalog().collection("geo-gse226533")
cohort.members # the 2 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-gse226533")
coll.ordered_artifacts.to_dataframe() # the 2 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-gse226533 --dest data/ Licenses: 2 NCBI GEO policy
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