A Continuous Molecular Roadmap to iPSC Reprogramming through Progression Analysis of Single-Cell Mass Cytometry

Abstract

SUMMARY To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4highKlf4high cells transitioned to a CD73highCD104highCD54low partially reprogrammed state. Ki67low cells from this intermediate population reverted to a MEF-like phenotype, but Ki67high cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like NanoghighSox2highCD54high population and a mesendoderm-like NanoglowSox2lowLin28high CD24highPDGFR-αhigh population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.

Proliferation, survival and metabolism: the role of PI3K/AKT/mTOR signalling in pluripotency and cell fate determination

“…A recent study that investigated the effect of signalling pathways in end-stage reprogramming cells revealed that PI3K/AKT/mTOR is absolutely required for the generation and maintenance of iPSCs (Zunder et al, 2015). This is consistent with the role of this pathway in maintaining ESC pluripotency.…”

Visualization and cellular hierarchy inference of single-cell data using SPADE

“…SPADE can also be adapted to analyze time-series MCM data. Recently, a modified version of the SPADE algorithm by Zunder et al 20 , called FLOW-MAP, was published. This algorithm replaces the default MST with a highly connected graph structure, in which the number of connections between cell clusters is determined by a local density.…”

“…The extra time dimension allows for a 3D visualization of SPADE. In the study by Zunder et al 20 , FLOW-MAP was applied to mouse embryonic fibroblasts to study the dynamic changes occurring during cellular reprogramming.…”

Emerging Proteomic Technologies Provide Enormous and Underutilized Potential for Brain Cancer Research

“…Using CyTOF, the Nolan group published a time resolved molecular roadmap to iPSC reprogramming (15) and identified previously unappreciated intermediate cellular states with distinct subsequent differentiation fates, suggesting that such a system can be applied to study cancer progression. Although practically more challenging for analyzing solid tumors, additional applications of the CyTOF strategy can be envisioned for solid tumor research (including brain cancers), in a way similar to recently reported single cell transcriptomics studies for glioblastoma (16).…”