Noncanonical Form of ERAD Regulates Cardiac Hypertrophy.

BACKGROUND: Cardiac hypertrophy increases demands on protein folding, which causes an accumulation of misfolded proteins in the endoplasmic reticulum (ER). These misfolded proteins can be removed by the adaptive retrotranslocation, polyubiquitylation, and a proteasome-mediated degradation process, ER-associated degradation (ERAD), which, as a biological process and rate, has not been studied in vivo. To investigate a role for ERAD in a pathophysiological model, we examined the function of the functional initiator of ERAD, valosin-containing protein-interacting membrane protein (VIMP), positing that VIMP would be adaptive in pathological cardiac hypertrophy in mice. METHODS: We developed a new method involving cardiac myocyte-specific adeno-associated virus serovar 9-mediated expression of the canonical ERAD substrate, TCRα, to measure the rate of ERAD, ie, ERAD flux, in the heart in vivo. Adeno-associated virus serovar 9 was also used to either knock down or overexpress VIMP in the heart. Then mice were subjected to transverse aortic constriction to induce pressure overload-induced cardiac hypertrophy. RESULTS: ERAD flux was slowed in both human heart failure and mice after transverse aortic constriction. Surprisingly, although VIMP adaptively contributes to ERAD in model cell lines, in the heart, VIMP knockdown increased ERAD and ameliorated transverse aortic constriction-induced cardiac hypertrophy. Coordinately, VIMP overexpression exacerbated cardiac hypertrophy, which was dependent on VIMP engaging in ERAD. Mechanistically, we found that the cytosolic protein kinase SGK1 (serum/glucocorticoid regulated kinase 1) is a major driver of pathological cardiac hypertrophy in mice subjected to transverse aortic constriction, and that VIMP knockdown decreased the levels of SGK1, which subsequently decreased cardiac pathology. We went on to show that although it is not an ER protein, and resides outside of the ER, SGK1 is degraded by ERAD in a noncanonical process we call ERAD-Out. Despite never having been in the ER, SGK1 is recognized as an ERAD substrate by the ERAD component DERLIN1, and uniquely in cardiac myocytes, VIMP displaces DERLIN1 from initiating ERAD, which decreased SGK1 degradation and promoted cardiac hypertrophy. CONCLUSIONS: ERAD-Out is a new preferentially favored noncanonical form of ERAD that mediates the degradation of SGK1 in cardiac myocytes, and in so doing is therefore an important determinant of how the heart responds to pathological stimuli, such as pressure overload.

Selenoprotein S: A versatile disordered protein.

Selenoprotein S (selenos) is a small, intrinsically disordered membrane protein that is associated with various cellular functions, such as inflammatory processes, cellular stress response, protein quality control, and signaling pathways. It is primarily known for its contribution to the ER-associated degradation (ERAD) pathway, which governs the extraction of misfolded proteins or misassembled protein complexes from the ER to the cytosol for degradation by the proteasome. However, selenos's other cellular roles in signaling are equally vital, including the control of transcription factors and cytokine levels. Consequently, genetic polymorphisms of selenos are associated with increased risk for diabetes, dyslipidemia, and cardiovascular diseases, while high expression levels correlate with poor prognosis in several cancers. Its inhibitory role in cytokine secretion is also exploited by viruses. Since selenos binds multiple protein complexes, however, its specific contributions to various cellular pathways and diseases have been difficult to establish. Thus, the precise cellular functions of selenos and their interconnectivity have only recently begun to emerge. This review aims to summarize recent insights into the structure, interactome, and cellular roles of selenos.

Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival.

Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric measure of variable importance (VIMP). A current limitation of VIMP, however, is that no systematic method exists for estimating its variance. As a solution, we propose a subsampling approach that can be used to estimate the variance of VIMP and for constructing confidence intervals. The method is general enough that it can be applied to many useful settings, including regression, classification, and survival problems. Using extensive simulations, we demonstrate the effectiveness of the subsampling estimator and in particular find that the delete-d jackknife variance estimator, a close cousin, is especially effective under low subsampling rates due to its bias correction properties. These 2 estimators are highly competitive when compared with the .164 bootstrap estimator, a modified bootstrap procedure designed to deal with ties in out-of-sample data. Most importantly, subsampling is computationally fast, thus making it especially attractive for big data settings.

Valosin-containing protein-interacting membrane protein (VIMP) links the endoplasmic reticulum with microtubules in concert with cytoskeleton-linking membrane protein (CLIMP)-63.

The distribution and morphology of the endoplasmic reticulum (ER) in mammalian cells depend on both dynamic and static interactions of ER membrane proteins with microtubules (MTs). Cytoskeleton-linking membrane protein (CLIMP)-63 is exclusively localized in sheet-like ER membranes, typical structures of the rough ER, and plays a pivotal role in the static interaction with MTs. Our previous study showed that the 42-kDa ER-residing form of syntaxin 5 (Syn5L) regulates ER structure through the interactions with both CLIMP-63 and MTs. Here, we extend our previous study and show that the valosin-containing protein/p97-interacting membrane protein (VIMP)/SelS is also a member of the family of proteins that shape the ER by interacting with MTs. Depletion of VIMP causes the spreading of the ER to the cell periphery and affects an MT-dependent process on the ER. Although VIMP can interact with CLIMP-63 and Syn5L, it does not interact with MT-binding ER proteins (such as Reep1) that shape the tubular smooth ER, suggesting that different sets of MT-binding ER proteins are used to organize different ER subdomains.

Selenoprotein S Interacts with the Replication and Transcription Complex of SARS-CoV-2 by Binding nsp7.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replicates and evades detection using ER membranes and their associated protein machinery. Among these hijacked human proteins is selenoprotein S (selenos). This selenoprotein takes part in the protein quality control, signaling, and the regulation of cytokine secretion. While the role of selenos in the viral life cycle is not yet known, it has been reported to interact with SARS-CoV-2 nonstructural protein 7 (nsp7), a viral protein essential for the replication of the virus. We set to study whether selenos and nsp7 interact directly and if they can still bind when nsp7 is bound to the replication and transcription complex of the virus. Using biochemical assays, we show that selenos binds directly to nsp7. In addition, we found that selenos can bind to nsp7 when it is in a complex with the coronavirus's minimal replication and transcription complex, comprised of nsp7, nsp8, and the RNA-dependent RNA polymerase nsp12. In addition, through crosslinking experiments, we mapped the interaction sites of selenos and nsp7 in the replication complex and showed that the hydrophobic segment of selenos is essential for binding to nsp7. This arrangement leaves an extended helix and the intrinsically disordered segment of selenos-including the reactive selenocysteine-exposed and free to potentially recruit additional proteins to the replication and transcription complex.

Applying selenocysteine-mediated expressed protein ligation to prepare the membrane enzyme selenoprotein S.

The intrinsically disordered membrane-bound selenoprotein s (selenos) takes part in the protein quality control pathway, vesicle trafficking, and NF-kB signaling. The reactive selenocysteine (Sec) at the penultimate position is responsible for its enzymatic activity. We report the preparation of the soluble segment as well as the full-length selenos using expressed protein ligation. This chapter discusses the practical considerations of expressed protein ligation using selenopeptides and describes our optimized procedure for the semi-synthesis of selenos.

Structural basis for nucleotide-modulated p97 association with the ER membrane.

Association of the cytosolic AAA (ATPases associated with various cellular activities) protein p97 to membranes is essential for various cellular processes including endoplasmic reticulum (ER)-associated degradation. The p97 consists of two ATPase domains and an N domain that interacts with numerous cofactors. The N domain of p97 is known to undergo a large nucleotide-dependent conformation switch, but its physiological relevance is unclear. Here we show p97 is recruited to canine ER membranes predominantly by interacting with VCP-interacting membrane protein (VIMP), an ER-resident protein. We found that the recruitment is modulated through a nucleotide-dependent conformation switch of the N domain in wild-type p97, but this modulation is absent in pathogenic mutants. We demonstrate the molecular mechanism of the modulation by a series of structures of p97, VIMP and their complexes and suggest a physiological role of the nucleotide-dependent N domain conformation switch. The lack of modulation in pathogenic mutants is caused by changes in interactions between the N and D1 domain, as demonstrated by multiple intermediate positions adopted by N domains of mutant p97. Our findings suggest the nucleotide-modulated membrane association may also have a role in other p97-dependent processes.

Enhancing Multimedia Imbalanced Concept Detection Using VIMP in Random Forests.

Recent developments in social media and cloud storage lead to an exponential growth in the amount of multimedia data, which increases the complexity of managing, storing, indexing, and retrieving information from such big data. Many current content-based concept detection approaches lag from successfully bridging the semantic gap. To solve this problem, a multi-stage random forest framework is proposed to generate predictor variables based on multivariate regressions using variable importance (VIMP). By fine tuning the forests and significantly reducing the predictor variables, the concept detection scores are evaluated when the concept of interest is rare and imbalanced, i.e., having little collaboration with other high level concepts. Using classical multivariate statistics, estimating the value of one coordinate using other coordinates standardizes the covariates and it depends upon the variance of the correlations instead of the mean. Thus, conditional dependence on the data being normally distributed is eliminated. Experimental results demonstrate that the proposed framework outperforms those approaches in the comparison in terms of the Mean Average Precision (MAP) values.