Browse
Submit Data
Databases
API
Help

Dataset Information

6 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Necdin: A purposive integrator of molecular interaction networks for mammalian neuron vitality.

ABSTRACT: Necdin was originally found in 1991 as a hypothetical protein encoded by a neural differentiation-specific gene transcript in murine embryonal carcinoma cells. Virtually all postmitotic neurons and their precursor cells express the necdin gene (Ndn) during neuronal development. Necdin mRNA is expressed only from the paternal allele through genomic imprinting, a placental mammal-specific epigenetic mechanism. Necdin and its homologous MAGE (melanoma antigen) family, which have evolved presumedly from a subcomplex component of the SMC5/6 complex, are expressed exclusively in placental mammals. Paternal Ndn-mutated mice totally lack necdin expression and exhibit various types of neuronal abnormalities throughout the nervous system. Ndn-null neurons are vulnerable to detrimental stresses such as DNA damage. Necdin also suppresses both proliferation and apoptosis of neural stem/progenitor cells. Functional analyses using Ndn-manipulated cells reveal that necdin consistently exerts antimitotic, anti-apoptotic and prosurvival effects. Necdin interacts directly with a number of regulatory proteins including E2F1, p53, neurotrophin receptors, Sirt1 and PGC-1α, which serve as major hubs of protein-protein interaction networks for mitosis, apoptosis, differentiation, neuroprotection and energy homeostasis. This review focuses on necdin as a pleiotropic protein that integrates molecular interaction networks to promote neuronal vitality in modern placental mammals.

SUBMITTER: Yoshikawa K

PROVIDER: S-EPMC9290590 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Vitality of Neural Networks under Reoccurring Catastrophic Failures.

Project description:Catastrophic failures are complete and sudden collapses in the activity of large networks such as economics, electrical power grids and computer networks, which typically require a manual recovery process. Here we experimentally show that excitatory neural networks are governed by a non-Poissonian reoccurrence of catastrophic failures, where their repetition time follows a multimodal distribution characterized by a few tenths of a second and tens of seconds timescales. The mechanism underlying the termination and reappearance of network activity is quantitatively shown here to be associated with nodal time-dependent features, neuronal plasticity, where hyperactive nodes damage the response capability of their neighbors. It presents a complementary mechanism for the emergence of Poissonian catastrophic failures from damage conductivity. The effect that hyperactive nodes degenerate their neighbors represents a type of local competition which is a common feature in the dynamics of real-world complex networks, whereas their spontaneous recoveries represent a vitality which enhances reliable functionality.

| S-EPMC4987694 | biostudies-literature

Molecular basis for the interaction between Integrator subunits IntS9 and IntS11 and its functional importance.

Project description:The metazoan Integrator complex (INT) has important functions in the 3'-end processing of noncoding RNAs, including the uridine-rich small nuclear RNA (UsnRNA) and enhancer RNA (eRNA), and in the transcription of coding genes by RNA polymerase II. The INT contains at least 14 subunits, but its molecular mechanism of action is poorly understood, because currently there is little structural information about its subunits. The endonuclease activity of INT is mediated by its subunit 11 (IntS11), which belongs to the metallo-?-lactamase superfamily and is a paralog of CPSF-73, the endonuclease for pre-mRNA 3'-end processing. IntS11 forms a stable complex with Integrator complex subunit 9 (IntS9) through their C-terminal domains (CTDs). Here, we report the crystal structure of the IntS9-IntS11 CTD complex at 2.1-Å resolution and detailed, structure-based biochemical and functional studies. The complex is composed of a continuous nine-stranded ?-sheet with four strands from IntS9 and five from IntS11. Highly conserved residues are located in the extensive interface between the two CTDs. Yeast two-hybrid assays and coimmunoprecipitation experiments confirm the structural observations on the complex. Functional studies demonstrate that the IntS9-IntS11 interaction is crucial for the role of INT in snRNA 3'-end processing.

| S-EPMC5410846 | biostudies-literature

Dicer-dependent and -independent Argonaute2 protein interaction networks in mammalian cells.

Project description:Argonaute (Ago) proteins interact with small regulatory RNAs such as microRNAs (miRNAs) and facilitate gene-silencing processes. miRNAs guide Ago proteins to specific mRNAs leading to translational silencing or mRNA decay. In order to understand the mechanistic details of miRNA function, it is important to characterize Ago protein interactors. Although several proteomic studies have been performed, it is not clear how the Ago interactome changes on miRNA or mRNA binding. Here, we report the analysis of Ago protein interactions in miRNA-containing and miRNA-depleted cells. Using stable isotope labeling in cell culture in conjunction with Dicer knock out mouse embryonic fibroblasts, we identify proteins that interact with Ago2 in the presence or the absence of Dicer. In contrast to our current view, we find that Ago-mRNA interactions can also take place in the absence of miRNAs. Our proteomics approach provides a rich resource for further functional studies on the cellular roles of Ago proteins.

| S-EPMC3494177 | biostudies-literature

Nipbl Interacts with Zfp609 and the Integrator Complex to Regulate Cortical Neuron Migration.

Project description:Mutations in NIPBL are the most frequent cause of Cornelia de Lange syndrome (CdLS), a developmental disorder encompassing several neurological defects, including intellectual disability and seizures. How NIPBL mutations affect brain development is not understood. Here we identify Nipbl as a functional interaction partner of the neural transcription factor Zfp609 in brain development. Depletion of Zfp609 or Nipbl from cortical neural progenitors in vivo is detrimental to neuronal migration. Zfp609 and Nipbl overlap at genomic binding sites independently of cohesin and regulate genes that control cortical neuron migration. We find that Zfp609 and Nipbl interact with the Integrator complex, which functions in RNA polymerase 2 pause release. Indeed, Zfp609 and Nipbl co-localize at gene promoters containing paused RNA polymerase 2, and Integrator similarly regulates neuronal migration. Our data provide a rationale and mechanistic insights for the role of Nipbl in the neurological defects associated with CdLS.

| S-EPMC5263256 | biostudies-literature

Capturing context-specific regulation in molecular interaction networks.

Project description:BACKGROUND:Molecular profiles change in response to perturbations. These changes are coordinated into functional modules via regulatory interactions. The genes and their products within a functional module are expected to be differentially expressed in a manner coherent with their regulatory network. This perspective presents a promising approach to increase precision in detecting differential signals as well as for describing differential regulatory signals within the framework of a priori knowledge about the underlying network, and so from a mechanistic point of view. RESULTS:We present Coherent Network Expression (CoNE), an effective procedure for identifying differentially activated functional modules in molecular interaction networks. Differential gene expression is chosen as example, and differential signals coherent with the regulatory nature of the network are identified. We apply our procedure to systematically simulated data, comparing its performance to alternative methods. We then take the example case of a transcription regulatory network in the context of particle-induced pulmonary inflammation, recapitulating and proposing additional candidates to previously obtained results. CoNE is conveniently implemented in an R-package along with simulation utilities. CONCLUSION:Combining coherent interactions with error control on differential gene expression results in uniformly greater specificity in inference than error control alone, ensuring that captured functional modules constitute real findings.

| S-EPMC6303932 | biostudies-literature

Functional characterization and topological modularity of molecular interaction networks.

Project description:BACKGROUND: Analyzing interaction networks for functional characterization poses significant challenges arising from the noisy, incomplete, and generic nature of both the interaction data as well as functional annotation of molecules. Network-based methods focus on interacting molecules (pairs or sets) occurring in close proximity to infer functional associations. RESULTS: In this paper we perform a formal comparative investigation of the relationship between functional coherence and topological proximity in networks. We investigate the problem of assessing the coherence of sets of biomolecules (or segments thereof) taking into account functional specificity as well as the distribution of functional attributes across entity groups. We also propose novel measures of topological proximity that are more robust to noisy and incomplete interaction data. CONCLUSION: We derive the following results in this paper: (i) there exists strong correlation between functional similarity and topological proximity in various network abstractions, with domain interaction networks (DDIs) demonstrating higher correlation than protein interaction networks (PPIs); (ii) measures that quantify coherence among entire sets of proteins are superior to aggregates of known pair-wise measures; and (iii) random-walk based measures of topological proximity are better suited to existing interaction data. We validate our methods on diverse data, including experimentally and computationally derived PPIs and DDIs, as well as on sets of known biologically related groups of molecules.

| S-EPMC3009507 | biostudies-literature

Reconciling differential gene expression data with molecular interaction networks.

Project description:MotivationMany techniques have been developed to compute the response network of a cell. A recent trend in this area is to compute response networks of small size, with the rationale that only part of a pathway is often changed by disease and that interpreting small subnetworks is easier than interpreting larger ones. However, these methods may not uncover the spectrum of pathways perturbed in a particular experiment or disease.ResultsTo avoid these difficulties, we propose to use algorithms that reconcile case-control DNA microarray data with a molecular interaction network by modifying per-gene differential expression P-values such that two genes connected by an interaction show similar changes in their gene expression values. We provide a novel evaluation of four methods from this class of algorithms. We enumerate three desirable properties that this class of algorithms should address. These properties seek to maintain that the returned gene rankings are specific to the condition being studied. Moreover, to ease interpretation, highly ranked genes should participate in coherent network structures and should be functionally enriched with relevant biological pathways. We comprehensively evaluate the extent to which each algorithm addresses these properties on a compendium of gene expression data for 54 diverse human diseases. We show that the reconciled gene rankings can identify novel disease-related functions that are missed by analyzing expression data alone.AvailabilityC++ software implementing our algorithms is available in the NetworkReconciliation package as part of the Biorithm software suite under the GNU General Public License: http://bioinformatics.cs.vt.edu/?murali/software/biorithm-docs.

| S-EPMC3582271 | biostudies-literature

Environment and bladder cancer: molecular analysis by interaction networks.

Project description:Bladder cancer (BC) is the 9th most common cancer worldwide, and the 6th most common cancer in men. Its development is linked to chronic inflammation, genetic susceptibility, smoking, occupational exposures and environmental pollutants. Aim of this work was to identify a sub-network of genes/proteins modulated by environmental or arsenic exposure in BC by computational network approaches. Our studies evidenced the presence of HUB nodes both in "BC and environment" and "BC and arsenicals" networks. These HUB nodes resulted to be correlated to circadian genes and targeted by some miRNAs already reported as involved in BC, thus suggesting how they play an important role in BC development due to environmental or arsenic exposure. Through data-mining analysis related to putative effect of the identified HUB nodes on survival we identified genes/proteins and their mutations on which it will be useful to focus further experimental studies related to the evaluation of their expression in biological matrices and to their utility as biomarkers of BC development.

| S-EPMC5630327 | biostudies-literature

DyNet: visualization and analysis of dynamic molecular interaction networks.

Project description:Unlabelled: The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states.Availability and implementationDyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet).Contactdavid.lynn@sahmri.comSupplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC5013899 | biostudies-literature

Necdin-E2F4 interaction provides insulin-sensitizing effect after weight loss induced by gastric bypass surgery.

Project description:The insulin-like growth factor-1 (IGF-1) signaling pathway promotes adipocyte differentiation and, therefore, insulin sensitivity by suppression of necdin expression, which represses peroxisome proliferator-activated receptor-gamma promoter activity by interaction with E2F4 in mouse adipocytes. The aim of the present study was to test the hypothesis that this pathway represents one of the mechanisms by which Roux-en-Y gastric bypass surgery (RYGB) induces resolution of insulin resistance.Clinical samples were collected and the key biomarkers measured to test the hypothesis that the IGF-1 pathway represents 1 of the mechanisms by which RYGB induces resolution of insulin resistance in obese individuals.Free IGF-1 levels were significantly greater in the post-RYGB patients than in the pre-RYGB obese patients (2.55 ± 1.54 versus 1.32 ± .65 ?g/L, P = .03) and similar to that in normal weight controls (2.54 ± 1.27 ?g/L). Necdin and E2F4 gene expression in the adipose tissue was significantly downregulated after RYGB compared with obese and were similar to the levels observed in the controls. In mature human adipocytes cultured in vitro, treatment with des-IGF-1 induced downregulation of necdin and E2F4 gene expression in a dose-dependent manner (P = .01).After RYGB, the insulin/IGF-1 signaling pathway is activated and could account for the observed decrease in the expression of necdin, which represses peroxisome proliferator-activated receptor-gamma promoter activity by interaction with E2F4. This could represent one of the mechanisms that induce resolution of insulin resistance after RYGB.

| S-EPMC3302937 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data