Coordination of Myeloid Differentiation with Reduced Cell Cycle Progression by PU.1 Induction of MicroRNAs Targeting Cell Cycle Regulators and Lipid Anabolism

ABSTRACT

During macrophage development, myeloid progenitor cells undergo terminal differentiation coordinated with reduced cell cycle progression. Differentiation of macrophages from myeloid progenitors is accompanied by increased expression of the E26 transformation-specific transcription factor PU.1. Reduced PU.1 expression leads to increased proliferation and impaired differentiation of myeloid progenitor cells. It is not understood how PU.1 coordinates macrophage differentiation with reduced cell cycle progression. In this study, we utilized cultured PU.1-inducible myeloid cells to perform genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) analysis coupled with gene expression analysis to determine targets of PU.1 that may be involved in regulating cell cycle progression. We found that genes encoding cell cycle regulators and enzymes involved in lipid anabolism were directly and inducibly bound by PU.1 although their steady-state mRNA transcript levels were reduced. Inhibition of lipid anabolism was sufficient to reduce cell cycle progression in these cells. Induction of PU.1 reduced expression of E2f1, an important activator of genes involved in cell cycle and lipid anabolism, indirectly through microRNA 223. Next-generation sequencing identified microRNAs validated as targeting cell cycle and lipid anabolism for downregulation. These results suggest that PU.1 coordinates cell cycle progression with differentiation through induction of microRNAs targeting cell cycle regulators and lipid anabolism.

KEYWORDS:

• E2F1
• microRNA
• PU.1
• cell cycle
• differentiation
• lipid synthesis
• myeloid cells

Supplemental material for this article may be found at https://doi.org/10.1128/MCB.00013-17.

ACKNOWLEDGMENTS

We acknowledge the contribution of the staff of the Genome Quebec Innovation Centre, Montreal, Canada, for next-generation sequencing services. We acknowledge access to the Shared Hierarchical Academic Research Computing Network (SHARCNET) and Compute/Calcul Canada. We thank Peng Shao for performing RT-qPCR experiments. We thank Kristen Chadwick of the London Regional Flow Cytometry Core for assistance with cell sorting and analysis. We thank Fred Possmeyer and David Carter for helpful discussions.

This work was supported by grant 386046 from the Natural Sciences and Engineering Research Council of Canada.