TY - JOUR
T1 - Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level
AU - Kannan, Suraj
AU - Farid, Michael
AU - Lin, Brian L.
AU - Miyamoto, Matthew
AU - Kwon, Chulan
N1 - Publisher Copyright:
© 2021 Kannan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2021/9
Y1 - 2021/9
N2 - The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues against in vivo development has not been established. Thus, maturation status is often assessed on an ad-hoc basis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with the in vivo developmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.
AB - The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues against in vivo development has not been established. Thus, maturation status is often assessed on an ad-hoc basis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with the in vivo developmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.
UR - http://www.scopus.com/inward/record.url?scp=85115404050&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85115404050&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1009305
DO - 10.1371/journal.pcbi.1009305
M3 - Article
C2 - 34534204
AN - SCOPUS:85115404050
SN - 1553-734X
VL - 17
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 9
M1 - e1009305
ER -