Use of Organ Transplant Solution to Preserve Skeletal Muscle for Cellular and Spatial Transcriptomic Analyses
Single-cell and spatial transcriptomic technologies have revolutionized human cell and tissue research. Success of these methods critically depends on the preservation of RNA integrity, cellular viability, and structure of the explanted tissues - features that are impacted by tissue storage conditions, and pose challenges in research settings, where tissues are often collected in the operating room and transported to distant laboratories. In this study, we evaluated the effectiveness of a clinically approved organ transplant solution (TS) for preserving skeletal muscle under refrigerated conditions. Using murine and human skeletal muscle tissues we found that TS consistently maintained higher RNA quality, preserved tissue morphology, and supported successful primary cell culture and spatial transcriptomic analysis of murine and human muscle samples obtained from different surgical collection sites. These findings establish a foundation for the use of a standardized protocol for live muscle tissue preservation for reliable downstream transcriptomic analyses for multicenter research efforts.
from sddb import Catalog
cohort = Catalog().collection("geo-gse310921")
cohort.members # the 8 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-gse310921")
coll.ordered_artifacts.to_dataframe() # the 8 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-gse310921 --dest data/ Licenses: 8 NCBI GEO policy
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