We recently demonstrated that the expression of the importin α subtype is switched from α2 to α1 during neural differentiation in mouse embryonic stem cells (ESCs) and that this switching has a major impact on cell differentiation. In this study, we report a cell-fate determination mechanism in which importin α2 negatively regulates the nuclear import of certain transcription factors to maintain ESC properties. The nuclear import of Oct6 and Brn2 was inhibited via the formation of a transport-incompetent complex of the cargo bound to a nuclear localization signal binding site in importin α2. Unless this dominant-negative effect was downregulated upon ESC differentiation, inappropriate cell death was induced. We propose that although certain transcription factors are necessary for differentiation in ESCs, these factors are retained in the cytoplasm by importin α2, thereby preventing transcription factor activity in the nucleus until the cells undergo differentiation.

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In predicting the pathogenicity of a nonsynonymous single-nucleotide variant (nsSNV), a radical change in amino acid properties is prone to be classified as being pathogenic. However, not all such nsSNVs are associated with human diseases. We generated random forest (RF) models individually for each amino acid substitution to differentiate pathogenic nsSNVs in the Human Gene Mutation Database and common nsSNVs in dbSNP. We named a set of our models ‘Individual Meta RF’ (InMeRF). Ten-fold cross-validation of InMeRF showed that the areas under the curves (AUCs) of receiver operating characteristic (ROC) and precision–recall curves were on average 0.941 and 0.957, respectively. To compare InMeRF with seven other tools, the eight tools were generated using the same training dataset, and were compared using the same three testing datasets. ROC-AUCs of InMeRF were ranked first in the eight tools. We applied InMeRF to 155 pathogenic and 125 common nsSNVs in seven major genes causing congenital myasthenic syndromes, as well as in VANGL1 causing spina bifida, and found that the sensitivity and specificity of InMeRF were 0.942 and 0.848, respectively. We made the InMeRF web service, and also made genome-wide InMeRF scores available online (https://www.med.nagoya-u.ac.jp/neurogenetics/InMeRF/).

The functional significance of homo-and heterooligomers of G protein-coupled receptors (GPCRs) has been extensively documented (Bouvier 2001;George et al. 2002;Bulenger et al. 2005;Milligan 2007). As identification of the interface for dimerization is essential for further elucidation of the underlying molecular mechanisms, several studies on the dimer interface have been conducted using a combination of computational molecular modeling and biochemical experiments (Guo et al. 2005;de Juan et al. 2005;Fotiadis et al. 2006). In the metabotropic glutamate receptors 1 and 5, Ca Both authors contributed equally to this work.Abbreviations used: A 2A R, A 2A adenosine receptor; D 2 R, D 2 dopamine receptor; BRET, bioluminescence resonance energy transfer; DPCPX, 8-cyclopentyl-1, 3-dipropylxanthine; GFP, green fluorescent protein; GPCR, G protein-coupled receptor; HA, hemagglutinin; HEK293T, human embryonic kidney 293T; NECA, 5¢-N-ethylcarboxamidoadenosine; PBS, phosphate-buffered saline; Rluc, Renilla luciferase; SDS-PAGE, sodium dodecyl sulfate-polyacrylamide gel electrophoresis; TM, transmembrane; T X , Triton X-100; WT, wild type. AbstractDimerization between G protein-coupled receptors (GPCRs) is a clearly established phenomenon. However, limited information is currently available on the interface essential for this process. Based on structural comparisons and sequence homology between rhodopsin and A 1 adenosine receptor (A 1 R), we initially hypothesized that four residues in transmembrane (TM) 4 and TM5 are involved in A 1 R homodimerization. Accordingly, these residues were substituted with Ala by site-directed mutagenesis. Interestingly, the mutant protein displayed no significant decrease in homodimer formation compared with wild-type A 1 R, as evident from coimmunoprecipitation and BRET 2 analyses (improved bioluminescence resonance energy transfer system offered by Perkin-Elmer Life Sciences), but lost ligand binding activity almost completely. Further studies disclosed that this effect was derived from the mutation of one particular residue, Trp132, which is highly conserved among many GPCRs. Confocal immunofluorescence and cell-surface biotinylation studies revealed that the mutant receptors localized normally at transfected cell membranes, signifying that loss of ligand binding was not because of defective cellular trafficking. Molecular modeling of the A 1 R-ligand complex disclosed that Trp132 interacted with several residues located in TM3 and TM5 that stabilized agonist binding. Thus, loss of interactions of Trp with these residues may, in turn, disrupt binding to agonists. Our study provides strong evidence of the essential role of the highly conserved Trp132 in TM4 of adenosine receptors.

These two different conformational changes might result in decreased GTPase activities that trigger ADOA associated with ANSD, and are likely to be associated with mild clinical features. Molecular modeling would provide useful information in clinical practice.

Most transcription and epigenetic factors in eukaryotic cells have nuclear localization signals (NLSs) and are transported to the nucleus by nuclear transport proteins. Understanding the features of NLSs and the mechanisms of nuclear transport might help understand gene expression regulation, somatic cell reprogramming, thus leading to the treatment of diseases associated with abnormal gene expression. Although many studies analyzed the amino acid sequence of NLSs, few studies investigated their three-dimensional structure. Therefore, we conducted a statistical investigation of the dynamic structure of NLSs by extracting the conformation of these sequences from proteins examined by X-ray crystallography and using a quantity defined as conformational determination rate (a ratio between the number of amino acids determining the conformation and the number of all amino acids included in a certain region). We found that determining the conformation of NLSs is more difficult than determining the conformation of other regions and that NLSs may tend to form more heteropolymers than monomers. Therefore, these findings strongly suggest that NLSs are intrinsically disordered regions.

Oct4 is a master regulator of the induction and maintenance of cellular pluripotency, and has crucial roles in early stages of differentiation. It is the only factor that cannot be substituted by other members of the same protein family to induce pluripotency. However, although Oct4 nuclear transport and delivery to target DNA are critical events for reprogramming to pluripotency, little is known about the molecular mechanism. Oct4 is imported to the nucleus by the classical nuclear transport mechanism, which requires importin α as an adaptor to bind the nuclear localization signal (NLS). Although there are structures of complexes of the NLS of transcription factors (TFs) in complex with importin α, there are no structures available for complexes involving intact TFs. We have therefore modeled the structure of the complex of the whole Oct4 POU domain and importin α2 using protein-protein docking and molecular dynamics. The model explains how the Ebola virus VP24 protein has a negative effect on the nuclear import of STAT1 by importin α but not on Oct4, and how Nup 50 facilitates cargo release from importin α. The model demonstrates the structural differences between the Oct4 importin α bound and DNA bound crystal states. We propose that the 'expanded linker' between the two DNA-binding domains of Oct4 is an intrinsically disordered region and that its conformational changes have a key role in the recognition/binding to both DNA and importin α. Moreover, we propose that this structural change enables efficient delivery to DNA after release from importin α.

This article describes data related to a research article titled “Comprehensive analysis of the dynamic structure of nuclear localization signals” by Yamagishi et al. [1]. In this article, we provide the data covering wider range of the mammalian NLSs in UniProt (Universal Protein Resource) [2] regardless of their conformations. To be more specific as follows: We have extracted all NLSs which are clearly indicated as “NLS” with evidence type (a code from the Evidence Codes Ontology) [3] in UniProt. A total of 1364 NLSs in 1186 proteins were extracted from UniProt. The number of NLSs found in each protein (UniProt ID), the sequence length of NLSs and their distribution are shown.