TMEM126A is a mitochondrial located mRNA (MLR) protein of the mitochondrial inner membrane

Background

Hereditary optic neuropathies (HONs) are a heterogeneous group of disorders that affect retinal ganglion cells (RGCs) and axons that form the optic nerve. Leber's Hereditary Optic Neuropathy and the autosomal dominant optic atrophy related to OPA1 mutations are the most common forms. Nonsyndromic autosomal recessive optic neuropathies are rare and their existence has been long debated. We recently identified the first gene responsible for these conditions, TMEM126A. This gene is highly expressed in retinal cellular compartments enriched in mitochondria and supposed to encode a mitochondrial transmembrane protein of unknown function.

Methods

A specific polyclonal antibody targeting the TMEM126A protein has been generated. Quantitative fluorescent in situ hybridization, cellular fractionation, mitochondrial membrane association study, mitochondrial sub compartmentalization analysis by both proteolysis assays and transmission electron microscopy, and expression analysis of truncated TMEM126A constructs by immunofluorescence confocal microscopy were carried out.

Results

TMEM126A mRNAs are strongly enriched in the vicinity of mitochondria and encode an inner mitochondrial membrane associated cristae protein. Moreover, the second transmembrane domain of TMEM126A is required for its mitochondrial localization.

Conclusions

TMEM126A is a mitochondrial located mRNA (MLR) that may be translated in the mitochondrial surface and the protein is subsequently imported to the inner membrane. These data constitute the first step toward a better understanding of the mechanism of action of TMEM126A in RGCs and support the importance of mitochondrial dysfunction in the pathogenesis of HON.

General significance

Local translation of nuclearly encoded mitochondrial mRNAs might be a mechanism for rapid onsite supply of mitochondrial membrane proteins.     

Esub8: A novel tool to predict protein subcellular localizations in eukaryotic organisms

Background

Subcellular localization of a new protein sequence is very important and fruitful for understanding its function. As the number of new genomes has dramatically increased over recent years, a reliable and efficient system to predict protein subcellular location is urgently needed.

Results

Esub8 was developed to predict protein subcellular localizations for eukaryotic proteins based on amino acid composition. In this research, the proteins are classified into the following eight groups: chloroplast, cytoplasm, extracellular, Golgi apparatus, lysosome, mitochondria, nucleus and peroxisome. We know subcellular localization is a typical classification problem; consequently, a one-against-one (1-v-1) multi-class support vector machine was introduced to construct the classifier. Unlike previous methods, ours considers the order information of protein sequences by a different method. Our method is tested in three subcellular localization predictions for prokaryotic proteins and four subcellular localization predictions for eukaryotic proteins on Reinhardt's dataset. The results are then compared to several other methods. The total prediction accuracies of two tests are both 100% by a self-consistency test, and are 92.9% and 84.14% by the jackknife test, respectively. Esub8 also provides excellent results: the total prediction accuracies are 100% by a self-consistency test and 87% by the jackknife test.

Conclusions

Our method represents a different approach for predicting protein subcellular localization and achieved a satisfactory result; furthermore, we believe Esub8 will be a useful tool for predicting protein subcellular localizations in eukaryotic organisms.

     

Structural determinants of PINK1 topology and dual subcellular distribution

Background  

PINK1 is a mitochondria-targeted kinase that constitutively localizes to both the mitochondria and the cytosol. The mechanism of how PINK1 achieves cytosolic localization following mitochondrial processing remains unknown. Understanding PINK1 subcellular localization will give us insights into PINK1 functions and how mutations in PINK1 lead to Parkinson's disease. We asked how the mitochondrial localization signal, the transmembrane domain, and the kinase domain participate in PINK1 localization.     

ProLoc-GO: Utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization

Background  

Gene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuclear localization. Existing GO-based prediction methods for protein subcellular localization use the known accession numbers of query proteins to obtain their annotated GO terms. An accurate prediction method for predicting subcellular localization of novel proteins without known accession numbers, using only the input sequence, is worth developing.     

Endoplasmic reticulum protein 29 (ERp29), a protein related to sperm maturation is involved in sperm-oocyte fusion in mouse

Background  

Sperm-oocyte fusion is a critical step in fertilization, which requires a series of proteins from both spermatozoa and oocyte to mediate membrane adhesion and subsequent fusion. A rat spermatozoa membrane protein is endoplasmic reticulum protein 29 (ERp29), which significantly increases on the sperm surface as well as in the cytoplasm of epididymal epithelia from caput to cauda as the sperm undergo epididymal maturation. Moreover, ERp29 facilitates viral infection via mediating membrane penetration. We determined if in addition to promoting sperm maturation ERp29 may also play a role in facilitating gamete fusion during the fertilization process.     

Localization of plasma membrane t-SNAREs syntaxin 2 and 3 in intracellular compartments

Background  

Membrane fusion requires the formation of a complex between a vesicle protein (v-SNARE) and the target membrane proteins (t-SNAREs). Syntaxin 2 and 3 are t-SNAREs that, according to previous over-expression studies, are predominantly localized at the plasma membrane. In the present study we investigated localization of the endogenous syntaxin 2 and 3.     

Method: automatic segmentation of mitochondria utilizing patch classification,contour pair classification,and automatically seeded level sets

Background  

While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps.     

CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources

Background  

The functions of proteins are strongly related to their localization in cell compartments (for example the cytoplasm or membranes) but the experimental determination of the sub-cellular localization of proteomes is laborious and expensive. A fast and low-cost alternative approach is in silico prediction, based on features of the protein primary sequences. However, biologists are confronted with a very large number of computational tools that use different methods that address various localization features with diverse specificities and sensitivities. As a result, exploiting these computer resources to predict protein localization accurately involves querying all tools and comparing every prediction output; this is a painstaking task. Therefore, we developed a comprehensive database, called CoBaltDB, that gathers all prediction outputs concerning complete prokaryotic proteomes.     

Immunological identification of yeast SCO1 protein as a component of the inner mitochondrial membrane

Summary The SCO1 gene of Saccharomyces cerevisiae encodes a 30 kDa protein which is specifically required for a post-translational step in the accumulation of subunits 1 and 2 of cytochrome c oxidase (COXI and COXII). Antibodies directed against a -Gal::SCO1 fusion protein detect SCO1 in the mitochondrial fraction of yeast cells. The SCO1 protein is an integral membrane protein as shown by its resistance to alkaline extraction and by its solubilization properties upon treatment with detergents. Based on the results obtained by isopycnic sucrose gradient centrifugation and by digitonin treatment of mitochondria, SCO1 is a component of the inner mitochondrial membrane. Membrane localization is mediated by a stretch of 17 hydrophobic amino acids in the amino-terminal region of the protein. A truncated SCO1 derivative lacking this segment, is no longer bound to the membrane and simultaneously loses its biological function. The observation that membrane localization of SCO1 is affected in mitochondria of a rho ⁰ strain, hints at the possible involvement of mitochondrially coded components in ensuring proper membrane insertion.     

Disruption of occludin function in polarized epithelial cells activates the extrinsic pathway of apoptosis leading to cell extrusion without loss of transepithelial resistance

Background  

Occludin is a tetraspanin protein normally localized to tight junctions. The protein interacts with a variety of pathogens including viruses and bacteria, an interaction that sometimes leads to its extrajunctional localization.     

Combination of scoring schemes for protein docking

Background  

Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function.     

NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

Background  

Nuclear localization signals (NLSs) are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood.     

Large-scale prediction of protein-protein interactions from structures

Background  

The prediction of protein-protein interactions is an important step toward the elucidation of protein functions and the understanding of the molecular mechanisms inside the cell. While experimental methods for identifying these interactions remain costly and often noisy, the increasing quantity of solved 3D protein structures suggests that in silico methods to predict interactions between two protein structures will play an increasingly important role in screening candidate interacting pairs. Approaches using the knowledge of the structure are presumably more accurate than those based on sequence only. Approaches based on docking protein structures solve a variant of this problem, but these methods remain very computationally intensive and will not scale in the near future to the detection of interactions at the level of an interactome, involving millions of candidate pairs of proteins.     

Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins

Background  

While occurring enzymatically in biological systems, O-linked glycosylation affects protein folding, localization and trafficking, protein solubility, antigenicity, biological activity, as well as cell-cell interactions on membrane proteins. Catalytic enzymes involve glycotransferases, sugar-transferring enzymes and glycosidases which trim specific monosaccharides from precursors to form intermediate structures. Due to the difficulty of experimental identification, several works have used computational methods to identify glycosylation sites.     

Expression and localization of nuclear proteins in autosomal-dominant Emery-Dreifuss muscular dystrophy with LMNA R377H mutation

Background  

The autosomal dominant form of Emery-Dreifuss muscular dystrophy (AD-EDMD) is caused by mutations in the gene encoding for the lamins A and C (LMNA). Lamins are intermediate filament proteins which form the nuclear lamina underlying the inner nuclear membrane. We have studied the expression and the localization of nuclear envelope proteins in three different cell types and muscle tissue of an AD-EDMD patient carrying a point mutation R377H in the lamin A/C gene.     

Identification of MarvelD3 as a tight junction-associated transmembrane protein of the occludin family

Background

Protein translocation across the membrane of the Endoplasmic Reticulum (ER) is the first step in the biogenesis of secretory and membrane proteins. Proteins enter the ER by the Sec61 translocon, a proteinaceous channel composed of three subunits, α, β and γ. While it is known that Sec61α forms the actual channel, the function of the other two subunits remains to be characterized.

Results

In the present study we have investigated the function of Sec61β in Drosophila melanogaster. We describe its role in the plasma membrane traffic of Gurken, the ligand for the Epidermal Growth Factor (EGF) receptor in the oocyte. Germline clones of the mutant allele of Sec61β show normal translocation of Gurken into the ER and transport to the Golgi complex, but further traffic to the plasma membrane is impeded. The defect in plasma membrane traffic due to absence of Sec61β is specific for Gurken and is not due to a general trafficking defect.

Conclusion

Based on our study we conclude that Sec61β, which is part of the ER protein translocation channel affects a post-ER step during Gurken trafficking to the plasma membrane. We propose an additional role of Sec61β beyond protein translocation into the ER.