Defining human ERAD networks through an integrative mapping strategy.
Ontology highlight
ABSTRACT:
SUBMITTER: Christianson JC
PROVIDER: S-EPMC3250479 | biostudies-literature | 2011 Nov
REPOSITORIES: biostudies-literature
Publications
Defining human ERAD networks through an integrative mapping strategy.
Christianson John C JC Olzmann James A JA Shaler Thomas A TA Sowa Mathew E ME Bennett Eric J EJ Richter Caleb M CM Tyler Ryan E RE Greenblatt Ethan J EJ Harper J Wade JW Kopito Ron R RR
Nature cell biology 20111127 1
Proteins that fail to correctly fold or assemble into oligomeric complexes in the endoplasmic reticulum (ER) are degraded by a ubiquitin- and proteasome-dependent process known as ER-associated degradation (ERAD). Although many individual components of the ERAD system have been identified, how these proteins are organized into a functional network that coordinates recognition, ubiquitylation and dislocation of substrates across the ER membrane is not well understood. We have investigated the fun ...[more]
Similar Datasets
Project description:In mammalian hippocampus, new neurons are continuously produced from neural stem cells throughout life. This postnatal neurogenesis may contribute to information processing critical for cognition, adaptation, learning, and memory, and is implicated in numerous neurological disorders. During neurogenesis, the immature neuron stage defined by doublecortin (DCX) expression is the most sensitive to regulation by extrinsic factors. However, little is known about the dynamic biology within this critical interval that drives maturation and confers susceptibility to regulatory signals. This study aims to test the hypothesis that DCX-expressing immature neurons progress through developmental stages via activity of specific transcriptional networks. Using single-cell RNA-seq combined with a novel integrative bioinformatics approach, we discovered that individual immature neurons can be classified into distinct developmental subgroups based on characteristic gene expression profiles and subgroup-specific markers. Comparisons between immature and more mature subgroups revealed novel pathways involved in neuronal maturation. Genes enriched in less mature cells shared significant overlap with genes implicated in neurodegenerative diseases, while genes positively associated with neuronal maturation were enriched for autism-related gene sets. Our study thus discovers molecular signatures of individual immature neurons and unveils potential novel targets for therapeutic approaches to treat neurodevelopmental and neurological diseases.
| S-EPMC6361276 | biostudies-literature
Project description:Although calcium phosphate-containing biomaterials are promising scaffolds for bone regenerative strategies, the osteoinductive capacity of such materials is poorly understood. In this study, we investigated whether endogenous mechanisms of in vivo calcium phosphate-driven, ectopic bone formation could be identified and used to induce enhanced differentiation in vitro of the same progenitor population. To accomplish this, human periosteum derived cells (hPDCs) were seeded on hydroxyapatite/collagen scaffolds (calcium phosphate rich matrix or CPRM), or on decalcified scaffolds (calcium phosphate depleted matrix or CPDM), followed by subcutaneous implantation in nude mice to trigger ectopic bone formation. In this system, osteoblast differentiation occurred in CPRM scaffolds, but not in CPDM scaffolds. Gene expression was assessed by human full-genome microarray at 20 h after seeding, and 2, 8 and 18 days after implantation. In both matrices, implantation of the cell constructs triggered a similar gene expression cascade, however, gene expression dynamics progressed faster in CPRM scaffolds than in CPDM scaffolds. The difference in gene expression dynamics was associated with differential activation of hub genes and molecular signaling pathways related to calcium signaling (CREB), inflammation (TNF?, NFkB, and IL6) and bone development (TGF?, ?-catenin, BMP, EGF, and ERK signaling). Starting from this set of pathways, a growth factor cocktail was developed that robustly enhanced osteogenesis in vitro and in vivo. Taken together, our data demonstrate that through the identification and subsequent stimulation of genes, proteins and signaling pathways associated with calcium phosphate mediated osteoinduction, a focused approach to develop targeted differentiation protocols in adult progenitor cells can be achieved.
| S-EPMC4037407 | biostudies-literature
Project description:Neurogenesis in the adult hippocampus contributes to information processing critical for cognition, adaptation, learning and memory, and is implicated in numerous neurological disorders. New neurons are continuously produced from neural stem cells via a well-controlled developmental process. The immature neuron stage defined by doublecortin (DCX) expression is the most sensitive to regulation by extrinsic factors. However, little is known about the dynamic biology within this critical interval that drives maturation and confers susceptibility to regulating signals. This study aims to test the hypothesis that DCX-expressing immature neurons in adult mouse hippocampus progress through developmental stages via activity of specific transcriptional networks. Using single-cell RNA-seq combined with a novel integrative bioinformatics approach, we discovered that individual immature neuron can be classified into distinct developmental subgroups based on characteristic gene expression profiles and subgroup-specific markers. Comparisons between immature and more mature subgroups revealed novel pathways involved in neuronal maturation. Genes enriched in more immature cells shared significant overlap with genes implicated in neurodegenerative diseases, while genes positively associated with neuronal maturation were enriched for autism-related gene sets. Our study thus discovers molecular signatures of individual adult-born immature neurons and unveils potential novel targets for therapeutic approaches to treat neurodevelopmental and neurological diseases. mRNA sequencing and expression estimation in 64 individual DCX-dsRed+ cells isolated from transgenic DCX-dsRed mice by FACS sorting
2016-02-29 | E-GEOD-75901 | biostudies-arrayexpress
Project description:Neurogenesis in the adult hippocampus contributes to information processing critical for cognition, adaptation, learning and memory, and is implicated in numerous neurological disorders. New neurons are continuously produced from neural stem cells via a well-controlled developmental process. The immature neuron stage defined by doublecortin (DCX) expression is the most sensitive to regulation by extrinsic factors. However, little is known about the dynamic biology within this critical interval that drives maturation and confers susceptibility to regulating signals. This study aims to test the hypothesis that DCX-expressing immature neurons in adult mouse hippocampus progress through developmental stages via activity of specific transcriptional networks. Using single-cell RNA-seq combined with a novel integrative bioinformatics approach, we discovered that individual immature neuron can be classified into distinct developmental subgroups based on characteristic gene expression profiles and subgroup-specific markers. Comparisons between immature and more mature subgroups revealed novel pathways involved in neuronal maturation. Genes enriched in more immature cells shared significant overlap with genes implicated in neurodegenerative diseases, while genes positively associated with neuronal maturation were enriched for autism-related gene sets. Our study thus discovers molecular signatures of individual adult-born immature neurons and unveils potential novel targets for therapeutic approaches to treat neurodevelopmental and neurological diseases.
2016-02-29 | GSE75901 | GEO
Project description:Human proximity networks are temporal networks representing the close-range proximity among humans in a physical space. They have been extensively studied in the past 15 years as they are critical for understanding the spreading of diseases and information among humans. Here we address the problem of mapping human proximity networks into hyperbolic spaces. Each snapshot of these networks is often very sparse, consisting of a small number of interacting (i.e., non-zero degree) nodes. Yet, we show that the time-aggregated representation of such systems over sufficiently large periods can be meaningfully embedded into the hyperbolic space, using methods developed for traditional (non-mobile) complex networks. We justify this compatibility theoretically and validate it experimentally. We produce hyperbolic maps of six different real systems, and show that the maps can be used to identify communities, facilitate efficient greedy routing on the temporal network, and predict future links with significant precision. Further, we show that epidemic arrival times are positively correlated with the hyperbolic distance from the infection sources in the maps. Thus, hyperbolic embedding could also provide a new perspective for understanding and predicting the behavior of epidemic spreading in human proximity systems.
| S-EPMC7679465 | biostudies-literature
Project description:Protein-protein interaction (PPI) networks serve as a powerful tool for unraveling protein functions, disease-gene and disease-disease associations. However, a direct strategy for integrating protein interaction, protein function and diseases is still absent. Moreover, the interrelated relationships among these three levels are poorly understood. Here we present a novel systematic method to integrate protein interaction, function, and disease networks. We first identified topological modules in human protein interaction data using the network topological algorithm (NeTA) we previously developed. The resulting modules were then associated with functional terms using Gene Ontology to obtain functional modules. Finally, disease modules were constructed by associating the modules with OMIM and GWAS. We found that most topological modules have cohesive structure, significant pathway annotations and good modularity. Most functional modules (70.6%) fully cover corresponding topological modules, and most disease modules (88.5%) are fully covered by the corresponding functional modules. Furthermore, we identified several protein modules of interest that we describe in detail, which demonstrate the power of our integrative approach. This approach allows us to link genes, and pathways with their corresponding disorders, which may ultimately help us to improve the prevention, diagnosis and treatment of disease.
| S-EPMC4585831 | biostudies-other
Project description:Organisms engage in extensive cross-species molecular dialog, yet the underlying molecular actors are known for only a few interactions. Many techniques have been designed to uncover genes involved in signaling between organisms. Typically, these focus on only one of the partners. We developed an expression quantitative trait locus (eQTL) mapping-based approach to identify cause-and-effect relationships between genes from two partners engaged in an interspecific interaction. We demonstrated the approach by assaying expression of 98 isogenic plants (Medicago truncatula), each inoculated with a genetically distinct line of the diploid parasitic nematode Meloidogyne hapla With this design, systematic differences in gene expression across host plants could be mapped to genetic polymorphisms of their infecting parasites. The effects of parasite genotypes on plant gene expression were often substantial, with up to 90-fold (P = 3.2 × 10-52) changes in expression levels caused by individual parasite loci. Mapped loci included a number of pleiotropic sites, including one 87-kb parasite locus that modulated expression of >60 host genes. The 213 host genes identified were substantially enriched for transcription factors. We distilled higher-order connections between polymorphisms and genes from both species via network inference. To replicate our results and test whether effects were conserved across a broader host range, we performed a confirmatory experiment using M. hapla-infected tomato. This revealed that homologous genes were similarly affected. Finally, to validate the broader utility of cross-species eQTL mapping, we applied the strategy to data from a Salmonella infection study, successfully identifying polymorphisms in the human genome affecting bacterial expression.
| S-EPMC5560814 | biostudies-literature
Project description:Human cells make use of hundreds of unique ubiquitin E3 ligases to ensure proteome fidelity and control cellular functions by promoting protein degradation. These processes require exquisite selectivity, but the individual roles of most E3s remain poorly characterized in part due to the challenges associated with identifying, quantifying, and validating substrates for each E3. We report an integrative mass spectrometry (MS) strategy for characterizing protein fragments that interact with KLHDC2, a human E3 that recognizes the extreme C-terminus of substrates. Using a combination of native MS, native top-down MS, MS of destabilized samples, and liquid chromatography MS, we identified and quantified a near complete fraction of the KLHDC2-binding peptidome in E. coli cells. This degronome includes peptides that originate from a variety of proteins. Although all identified protein fragments are terminated by diglycine or glycylalanine, the preceding amino acids are diverse. These results significantly expand our understanding of the sequences that can be recognized by KLHDC2, which provides insight into the potential substrates of this E3 in humans. We anticipate that this integrative MS strategy could be leveraged more broadly to characterize the degronomes of other E3 ligase substrate receptors, including those that adhere to the more common N-end rule for substrate recognition. Therefore, this work advances "degronomics," i.e., identifying, quantifying, and validating functional E3:peptide interactions in order to determine the individual roles of each E3.
| S-EPMC6959985 | biostudies-literature
Project description:Cell surface glycans form a critical interface with the biological milieu, informing diverse processes from the inflammatory cascade to cellular migration. Assembly of discrete carbohydrate structures requires the coordinated activity of a repertoire of proteins, including glycosyltransferases and glycosidases. Little is known about the regulatory networks controlling this complex biosynthetic process. Recent work points to a role for microRNA (miRNA) in the regulation of specific glycan biosynthetic enzymes. Herein we take a unique systems-based approach to identify connections between miRNA and the glycome. By using our glycomic analysis platform, lectin microarrays, we identify glycosylation signatures in the NCI-60 cell panel that point to the glycome as a direct output of genomic information flow. Integrating our glycomic dataset with miRNA data, we map miRNA regulators onto genes in glycan biosynthetic pathways (glycogenes) that generate the observed glycan structures. We validate three of these predicted miRNA/glycogene regulatory networks: high mannose, fucose, and terminal ?-GalNAc, identifying miRNA regulation that would not have been observed by traditional bioinformatic methods. Overall, our work reveals critical nodes in the global glycosylation network accessible to miRNA regulation, providing a bridge between miRNA-mediated control of cell phenotype and the glycome.
| S-EPMC3964104 | biostudies-literature
Project description:Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches.
| S-EPMC4945645 | biostudies-literature