Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell...

Area of Science:

• Biotechnology
• Stem Cell Biology
• Genomics

Background:

• Pluripotent stem cell (PSC)-derived tissues often exhibit immaturity, hindering biomedical applications.
• Direct benchmarking of PSC-derived tissues against in vivo development is lacking, leading to ad-hoc maturation assessments.
• Single-cell RNA sequencing (scRNA-seq) is promising but limited by dataset-specific batch effects for cross-study comparisons.

Purpose of the Study:

• To develop a novel, robust method for quantifying the maturation status of PSC-derived tissues.
• To establish a cross-study, cross-species reference for cardiomyocyte (CM) maturation.
• To enable direct comparison of PSC-derived cells with in vivo developmental trajectories.

Main Methods:

• Developed a novel approach using transcriptomic entropy to quantify PSC-derived cardiomyocyte maturation.
• Analyzed over 45 scRNA-seq datasets comprising over 52,000 cardiomyocytes.
• Validated the transcriptomic entropy approach for robustness across different datasets and batch effects.

Main Results:

• Established a cross-study, cross-species reference for cardiomyocyte maturation using transcriptomic entropy.
• Quantified PSC-derived cardiomyocyte maturation by comparing them to the in vivo developmental trajectory.
• Demonstrated the extensibility of the entropy-based approach to other cell types like pancreatic beta cells and hepatocytes.

Conclusions:

• Transcriptomic entropy provides a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation.
• The developed method overcomes limitations of scRNA-seq batch effects for robust cross-study comparisons.
• This approach is extensible to various tissue engineering contexts, advancing stem cell-based therapies.