Nat1 promotes translation of specific proteins that induce differentiation of mouse embryonic stem cells

Abstract

Novel APOBEC1 target 1 (Nat1) (also known as "p97," "Dap5," and "Eif4g2") is a ubiquitously expressed cytoplasmic protein that is homologous to the C-terminal two thirds of eukaryotic translation initiation factor 4G (Eif4g1). We previously showed that Nat1-null mouse embryonic stem cells (mES cells) are resistant to differentiation. In the current study, we found that NAT1 and eIF4G1 share many binding proteins, such as the eukaryotic translation initiation factors eIF3 and eIF4A and ribosomal proteins. However, NAT1 did not bind to eIF4E or poly(A)-binding proteins, which are critical for cap-dependent translation initiation. In contrast, compared with eIF4G1, NAT1 preferentially interacted with eIF2, fragile X mental retardation proteins (FMR), and related proteins and especially with members of the proline-rich and coiled-coilcontaining protein 2 (PRRC2) family. We also found that Nat1-null mES cells possess a transcriptional profile similar, although not identical, to the ground state, which is established in wild-type mES cells when treated with inhibitors of the ERK and glycogen synthase kinase 3 (GSK3) signaling pathways. In Nat1-null mES cells, the ERK pathway is suppressed even without inhibitors. Ribosome profiling revealed that translation of mitogen-activated protein kinase kinase kinase 3 (Map3k3) and son of sevenless homolog 1 (Sos1) is suppressed in the absence of Nat1. Forced expression of Map3k3 induced differentiation of Nat1-null mES cells. These data collectively show that Nat1 is involved in the translation of proteins that are required for cell differentiation.Nat1 | Eif4g1 | translation control | Map3k3 | mouse embryonic stem cells

Ribosome profiling at isoform level reveals an evolutionary conserved impact of differential splicing on the proteome

“…We used ORQAS to analyze Ribo-seq and matched RNA-seq data from human and mouse glia and glioma (Gonzalez et al 2014), mouse hippocampus (Cho et al 2015), and mouse embryonic stem cells (Sugiyama et al 2017) (Supp . Table 1).…”

“…RNA-seq and Ribo-seq datasets were downloaded from Gene Expression Omnibus (GEO) for the following samples: normal glia and glioma from human and mouse (GSE51424) (Gonzalez et al 2014), mouse hippocampus (GSE72064) (Cho et al 2015), mouse embryonic stem cells (GSE89011) (Sugiyama et al 2017), and three steps of forebrain neuronal differentiation in human (GSE100007) (Blair et al 2017). Adapters in RNA-seq and Ribo-seq datasets were trimmed using cutadapt v.1.12 with additional quality filters for RNA-seq (-q = 30).…”

Artificial acceleration of mammalian cell reprogramming by bacterial proteins

“…Both database engines were used against Mus musculus proteins in UniProt/Swiss-Prot release 2016_01 (20 January 2016) with the parameters described by Sugiyama et al (2017). Peak lists generated from the ProteinPilot.group file were analyzed by Mascot v2.5 (Matrix Science).…”

“…Peak lists generated from the ProteinPilot.group file were analyzed by Mascot v2.5 (Matrix Science). Both database engines were used against Mus musculus proteins in UniProt/Swiss-Prot release 2016_01 (20 January 2016) with the parameters described by Sugiyama et al (2017).…”

RiboDiPA: A Novel tool for differential pattern analysis in Ribo-seq data

“…In this study, we shall compare unstressed yeast to yeast challenged with three different stressesosmotic stress, oxidative stress, and stationary phase growth-as well as compare wild type yeast to yeast of different genetic backgrounds, ∆eRF1 and ∆Rck2. The second data set comes from a mouse study [23] which compares mouse embryonic stem cells with different dosages of the translational regulator Nat1: wild-type, heterozygous mutant, and null. These data sets were selected because they represent two divergent model organisms of typical sample size (2)(3) replicates per condition), and more importantly, both have relatively high read counts.…”