Sign in
Developmental BiologyMethods and Protocols
Peer-reviewed journal article

Parsing glomerular and tubular structure variability in high-throughput kidney organoid culture

Kristiina Uusi-RauvaiD, Anniina PirttiniemiiD, Antti HassineniD, Ras TrokoviciD, Sanna H. LehtoneniD, Jukka KallijärviiD, Markku J. LehtoiD, Vineta FellmaniD, Per-Henrik Groop

Abstract

High variability in stem cell research is a well-known limiting phenomenon, with technical variation across experiments and laboratories often surpassing variation caused by genotypic effects of induced pluripotent stem cell (iPSC) lines. Evaluation of kidney organoid protocols and culture conditions across laboratories remains scarce in the literature. We used the original air-medium interface protocol to evaluate kidney organoid success rate and reproducibility with several human iPSC lines, including a novel patient-derived GRACILE syndrome iPSC line. Organoid morphology was assessed with light microscopy and immunofluorescence-stained maturing glomerular and tubular structures. The protocol was further adapted to four microplate-based high-throughput approaches utilizing spheroid culture steps. Quantitative high-content screening analysis of the nephrin-positive podocytes and ECAD-positive tubular cells revealed that the choice of approach and culture conditions were significantly associated with structure development. The culture approach, iPSC line, experimental replication, and initial cell number explained 35-77% of the variability in the logit-transformed proportion of nephrin and ECAD-positive area, when fitted into multiple linear models. Our study highlights the benefits of high-throughput culture and multivariate techniques to better distinguishing sources of technical and biological variation in morphological analysis of organoids. Our microplate-based high-throughput approach is easily adaptable for other laboratories to combat organoid size variability.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISPhipson '17Subramanian '19Schumacher '23Przepiorski '18Howden '18Maggiore '23
69% semantic matchBioinformatics
Belinda Phipson, Pei Xuan Er, Lorna J. Hale+7 more·bioRxiv·Dec 22, 2017· 5 citations