Probing transient memory of cellular states using single-cell lineages

Area of Science:

• Cellular and Molecular Biology
• Systems Biology
• Genetics

Background:

• Cellular heterogeneity arises from inherent stochasticity in gene expression.
• Intercellular variation and dynamic state transitions are challenging to quantify.
• Understanding cell state dynamics is crucial for various biological processes.

Purpose of the Study:

• To review and present a fluctuation-based methodology for inferring transient heritability of cellular states.
• To model dynamic state transitions in growing cell populations.
• To illustrate the utility of this method in diverse biological systems.

Main Methods:

• Leveraging the classical Luria-Delbrück experiment framework.
• Growing individual cells into colonies and assaying the fraction of cells in different states per colony.
• Developing and applying modeling approaches to capture dynamic state transitions and infer switching kinetics from colony-to-colony fluctuations.

Main Results:

• The fluctuation-based method allows inference of cell-state transitions from single time-point measurements.
• This approach is effective in identifying multi-generational memory of gene expression and phenotypic states.
• The methodology is applicable across diverse systems, including cancer, viral reactivation, and immune responses.

Conclusions:

• The Luria-Delbrück-inspired fluctuation assay provides a powerful tool for studying cell-state dynamics.
• This method is particularly valuable when measurements are destructive or irreversible, such as in single-cell RNA sequencing or drug treatment studies.
• It offers a robust way to understand transient heritability and cell plasticity.