Mcidas mutant mice reveal a two-step process for the specification and differentiation of multiciliated cells in mammals.
Hao LuPriyanka AnujanFeng ZhouYiliu ZhangYan Ling ChongColin D BingleSudipto RoyPublished in: Development (Cambridge, England) (2019)
Motile cilia on multiciliated cells (MCCs) function in fluid clearance over epithelia. Studies with Xenopus embryos and individuals with the congenital respiratory disorder reduced generation of multiple motile cilia (RGMC), have implicated the nuclear protein MCIDAS (MCI), in the transcriptional regulation of MCC specification and differentiation. Recently, a paralogous protein, geminin coiled-coil domain containing (GMNC), was also shown to be required for MCC formation. Surprisingly, in contrast to the presently held view, we find that Mci mutant mice can specify MCC precursors. However, these precursors cannot produce multiple basal bodies, and mature into single ciliated cells. We identify an essential role for MCI in inducing deuterosome pathway components for the production of multiple basal bodies. Moreover, GMNC and MCI associate differentially with the cell-cycle regulators E2F4 and E2F5, which enables them to activate distinct sets of target genes (ciliary transcription factor genes versus basal body amplification genes). Our data establish a previously unrecognized two-step model for MCC development: GMNC functions in the initial step for MCC precursor specification. GMNC induces Mci expression that drives the second step of basal body production for multiciliation.
Keyphrases
- induced apoptosis
- cell cycle
- mild cognitive impairment
- transcription factor
- cell cycle arrest
- genome wide
- cell proliferation
- poor prognosis
- oxidative stress
- wild type
- magnetic resonance
- signaling pathway
- binding protein
- magnetic resonance imaging
- metabolic syndrome
- genome wide identification
- cell death
- gene expression
- long non coding rna
- amino acid
- computed tomography
- high fat diet induced
- bioinformatics analysis
- big data
- insulin resistance
- deep learning
- pi k akt
- genome wide analysis
- data analysis
- nucleic acid