Mapping subcellular localizations of unannotated microproteins and alternative proteins with MicroID

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Characterization of human proteins with different subcellular localizations by topological and biological properties

Knowing the protein localization can provide valuable information resource for elucidating protein function. In recent years, with the advances of human genomics and proteomics, it is possible to characterize human proteins that are located in different subcellular localizations. In this study, we used the topological properties and biological properties to characterize human proteins with six subcellular localizations. Almost all of these properties were found to be significantly different among six protein categories. Network topology analysis indicated that several significant topological properties, including the degree and k-core, were higher for the mitochondrial proteins. Biological property analysis showed that the nuclear proteins appeared to be correlated with important biological function. We hope these findings may provide some important help for comprehensive understanding the biological function of proteins, and prediction of protein subcellular localizations in human.     

Characterization of proteins in different subcellular localizations for Escherichia coli K12

Knowing the comprehensive knowledge about the protein subcellular localization is an important step to understand the function of the proteins. Recent advances in system biology have allowed us to develop more accurate methods for characterizing the proteins at subcellular localization level. In this study, the analysis method was developed to characterize the topological properties and biological properties of the cytoplasmic proteins, inner membrane proteins, outer membrane proteins and periplasmic proteins in Escherichia coli (E. coli). Statistical significant differences were found in all topological properties and biological properties among proteins in different subcellular localizations. In addition, investigation was carried out to analyze the differences in 20 amino acid compositions for four protein categories. We also found that there were significant differences in all of the 20 amino acid compositions. These findings may be helpful for understanding the comprehensive relationship between protein subcellular localization and biological function     

Different subcellular localizations and functions of Arabidopsis myosin VIII

Background  

Myosins are actin-activated ATPases that use energy to generate force and move along actin filaments, dragging with their tails different cargos. Plant myosins belong to the group of unconventional myosins and Arabidopsis myosin VIII gene family contains four members: ATM1, ATM2, myosin VIIIA and myosin VIIIB.     

Coordinate expression and independent subcellular targeting of multiple proteins from a single transgene

A variety of conventional methods allow the expression of multiple foreign proteins in plants by transgene stacking or pyramiding. However, most of these approaches have significant drawbacks. We describe a novel alternative, using a single transgene to coordinate expression of multiple proteins that are encoded as a polyprotein capable of dissociating into component proteins on translation. We demonstrate that this polyprotein system is compatible with the need to target proteins to a variety of subcellular locations, either cotranslationally or posttranslationally. It can also be used to coordinate the expression of selectable marker genes and effect genes or to link genes that are difficult to assay to reporter genes that are easily monitored. The unique features of this polyprotein system are based on the novel activity of the 2A peptide of Foot-and-mouth disease virus (FMDV) that acts cotranslationally to effect a dissociation of the polyprotein while allowing translation to continue. This polyprotein system has many applications both as a research tool and for metabolic engineering and protein factory applications of plant biotechnology.     

iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites

Predicting protein subcellular localization is a challenging problem, particularly when query proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing methods can only be used to deal with the single-location proteins. Actually, multiple-location proteins should not be ignored because they usually bear some special functions worthy of our notice. By introducing the "multi-labeled learning" approach, a new predictor, called iLoc-Plant, has been developed that can be used to deal with the systems containing both single- and multiple-location plant proteins. As a demonstration, the jackknife cross-validation was performed with iLoc-Plant on a benchmark dataset of plant proteins classified into the following 12 location sites: (1) cell membrane, (2) cell wall, (3) chloroplast, (4) cytoplasm, (5) endoplasmic reticulum, (6) extracellular, (7) Golgi apparatus, (8) mitochondrion, (9) nucleus, (10) peroxisome, (11) plastid, and (12) vacuole, where some proteins belong to two or three locations but none has ≥ 25% pairwise sequence identity to any other in a same subset. The overall success rate thus obtained by iLoc-Plant was 71%, which is remarkably higher than those achieved by any existing predictors that also have the capacity to deal with such a stringent and complicated plant protein system. As a user-friendly web-server, iLoc-Plant is freely accessible to the public at the web-site or . Moreover, for the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematic equations presented in this paper for its integrity. It is anticipated that iLoc-Plant may become a useful bioinformatics tool for Molecular Cell Biology, Proteomics, Systems Biology, and Drug Development.     

Erratum to: Rhesus macaque MHC class I molecules show differential subcellular localizations

The MHC class I gene family of rhesus macaques is characterised by considerable gene duplications. While a HLA-C-orthologous gene is absent, the Mamu-A and in particular the Mamu-B genes have expanded, giving rise to plastic haplotypes with differential gene content. Although some of the rhesus macaque MHC class I genes are known to be associated with susceptibility/resistance to infectious diseases, the functional significance of duplicated Mamu-A and Mamu-B genes and the expression pattern of their encoded proteins are largely unknown. Here, we present data of the subcellular localization of AcGFP-tagged Mamu-A and Mamu-B molecules. We found strong cell surface and low intracellular expression for Mamu-A1, Mamu-A2 and Mamu-A3-encoded molecules as well as for Mamu-B*01704, Mamu-B*02101, Mamu-B*04801, Mamu-B*06002 and Mamu-B*13401. In contrast, weak cell surface and strong intracellular expression was seen for Mamu-A4*1403, Mamu-B*01202, Mamu-B*02804, Mamu-B*03002, Mamu-B*05704, Mamu-I*010201 and Mamu-I*0121. The different expression patterns were assigned to the antigen-binding α1 and α2 domains, suggesting failure of peptide binding is responsible for retaining ‘intracellular’ Mamu class I molecules in the endoplasmic reticulum. These findings indicate a diverse functional role of the duplicated rhesus macaque MHC class I genes.     

Functional analysis of Plasmodium vivax VIR proteins reveals different subcellular localizations and cytoadherence to the ICAM-1 endothelial receptor

The subcellular localization and function of variant subtelomeric multigene families in Plasmodium vivax remain vastly unknown. Among them, the vir superfamily is putatively involved in antigenic variation and in mediating adherence to endothelial receptors. In the absence of a continuous in vitro culture system for P. vivax, we have generated P. falciparum transgenic lines expressing VIR proteins to infer location and function. We chose three proteins pertaining to subfamilies A (VIR17), C (VIR14) and D (VIR10), with domains and secondary structures that predictably traffic these proteins to different subcellular compartments. Here, we showed that VIR17 remained inside the parasite and around merozoites, whereas VIR14 and VIR10 were exported to the membrane of infected red blood cells (iRBCs) in an apparent independent pathway of Maurer's clefts. Remarkably, VIR14 was exposed at the surface of iRBCs and mediated adherence to different endothelial receptors expressed in CHO cells under static conditions. Under physiological flow conditions, however, cytoadherence was only observed to ICAM-1, which was the only receptor whose adherence was specifically and significantly inhibited by antibodies against conserved motifs of VIR proteins. Immunofluorescence studies using these antibodies also showed different subcellular localizations of VIR proteins in P. vivax-infected reticulocytes from natural infections. These data suggest that VIR proteins are trafficked to different cellular compartments and functionally demonstrates that VIR proteins can specifically mediate cytoadherence to the ICAM-1 endothelial receptor.     

Biochemical characteristics and subcellular localizations of rat liver neuraminidase isozymes: A paradox resolved

A striking discrepancy in the abilities of two analytical approaches (fluorometric and electrophoretic) to detect the effect of a gene,Neu-2, on rat liver neuraminidase phenotypes led us to examine the biochemical and physical properties of the liver isozymes NEU-1 and NEU-2 that might be responsible for this difference. Cell fractionation via Percoll gradient centrifugation revealed NEU-1 activity almost exclusively in the lysosomal cell fraction, while NEU-2 was strictly cytosolic in distribution. The two isozymes were also found to differ inpH activity curves and optima (optima: 4.6–4.8 and 5.4–5.8 for NEU-1 and NEU-2, respectively) and in solubility characteristics (NEU-2 highly soluble; NEU-1 relatively insoluble but solubilized by freezing/thawing). Both isozymes were found to be freeze-thaw stable in crude, whole-cell extracts, but NEU-1 was destabilized in the enriched (partially purified) lysosomal subcellular fraction. Consideration of these properties relative to those described previously for unidentified cytosolic and membrane bound (lysosomal) rat liver neuraminidases (Tulsiani, D. R. P., and Carubelli, R.,J. Biol. Chem. 245:1821, 1970) leads us to believe that NEU-2 also is destabilized by partial purification and that NEU-1 and NEU-2 have very different relative abundances within the cell. The biochemical and physical differences between NEU-1 and NEU-2 can account for the discrepant abilities of the fluorometric and electrophoretic approaches to detect the effects ofNeu-2. Ways to increase the sensitivity of the fluorometric approach for quantitative assays of specific NEU-1 and NEU-2 activity are discussed.     

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.

     

iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites

Although numerous efforts have been made for predicting the subcellular locations of proteins based on their sequence information, it still remains as a challenging problem, particularly when query proteins may have the multiplex character, i.e., they simultaneously exist, or move between, two or more different subcellular location sites. Most of the existing methods were established on the assumption: a protein has one, and only one, subcellular location. Actually, recent evidence has indicated an increasing number of human proteins having multiple subcellular locations. This kind of multiplex proteins should not be ignored because they may bear some special biological functions worthy of our attention. Based on the accumulation-label scale, a new predictor, called iLoc-Hum, was developed for identifying the subcellular localization of human proteins with both single and multiple location sites. As a demonstration, the jackknife cross-validation was performed with iLoc-Hum on a benchmark dataset of human proteins that covers the following 14 location sites: centrosome, cytoplasm, cytoskeleton, endoplasmic reticulum, endosome, extracellular, Golgi apparatus, lysosome, microsome, mitochondrion, nucleus, peroxisome, plasma membrane, and synapse, where some proteins belong to two, three or four locations but none has 25% or higher pairwise sequence identity to any other in the same subset. For such a complicated and stringent system, the overall success rate achieved by iLoc-Hum was 76%, which is remarkably higher than that by any of the existing predictors that also have the capacity to deal with this kind of system. Further comparisons were also made via two independent datasets; all indicated that the success rates by iLoc-Hum were even more significantly higher than its counterparts. As a user-friendly web-server, iLoc-Hum is freely accessible to the public at or . For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results by choosing either a straightforward submission or a batch submission, without the need to follow the complicated mathematical equations involved.     

Transglutaminase 2: a multi-functional protein in multiple subcellular compartments

Transglutaminase 2 (TG2) is a multifunctional protein that can function as a transglutaminase, G protein, kinase, protein disulfide isomerase, and as an adaptor protein. These multiple biochemical activities of TG2 account for, at least in part, its involvement in a wide variety of cellular processes encompassing differentiation, cell death, inflammation, cell migration, and wound healing. The individual biochemical activities of TG2 are regulated by several cellular factors, including calcium, nucleotides, and redox potential, which vary depending on its subcellular location. Thus, the microenvironments of the subcellular compartments to which TG2 localizes, such as the cytosol, plasma membrane, nucleus, mitochondria, or extracellular space, are important determinants to switch on or off various TG2 biochemical activities. Furthermore, TG2 interacts with a distinct subset of proteins and/or substrates depending on its subcellular location. In this review, the biological functions and molecular interactions of TG2 will be discussed in the context of the unique environments of the subcellular compartments to which TG2 localizes.     

Identification of a novel domain of Ras and Rap1 that directs their differential subcellular localizations

The small GTPase Ha-Ras and Rap1A exhibit high mutual sequence homology and share various target proteins. However, they exert distinct biological functions and exhibit differential subcellular localizations; Rap1A is predominantly localized in the perinuclear region including the Golgi apparatus and endosomes, whereas Ha-Ras is predominantly localized in the plasma membrane. Here, we have identified a small region in Rap1A that is crucial for its perinuclear localization. Analysis of a series of Ha-Ras-Rap1A chimeras shows that Ha-Ras carrying a replacement of amino acids 46-101 with that of Rap1 exhibits the perinuclear localization. Subsequent mutational studies indicate that Rap1A-type substitutions within five amino acids at positions 85-89 of Ha-Ras, such as NNTKS85-89TAQST, NN85-86TA, and TKS87-89QST, are sufficient to induce the perinuclear localization of Ha-Ras. In contrast, substitutions of residues surrounding this region, such as FAI82-84YSI and FEDI90-93FNDL, have no effect on the plasma membrane localization of Ha-Ras. A chimeric construct consisting of amino acids 1-134 of Rap1A and 134-189 of Ha-Ras, which harbors both the palmitoylation and farnesylation sites of Ha-Ras, exhibits the perinuclear localization like Rap1A. Introduction of a Ha-Ras-type substitution into amino acids 85-89 (TAQST85-89NNTKS) of this chimeric construct causes alteration of its predominant subcellular localization site from the perinuclear region to the plasma membrane. These results indicate that a previously uncharacterized domain spanning amino acids 85-89 of Rap1A plays a pivotal role in its perinuclear localization. Moreover, this domain acts dominantly over COOH-terminal lipid modification of Ha-Ras, which has been considered to be essential and sufficient for the plasma membrane localization.     

Non-canonical signaling and localizations of heterotrimeric G proteins

Heterotrimeric G proteins typically transduce signals from G protein-coupled receptors (GPCRs) to effector proteins. In the conventional G protein signaling paradigm, the G protein is located at the cytoplasmic surface of the plasma membrane, where, after activation by an agonist-bound GPCR, the GTP-bound Gα and free Gβγ bind to and regulate a number of well-studied effectors, including adenylyl cyclase, phospholipase Cβ, RhoGEFs and ion channels. However, research over the past decade or more has established that G proteins serve non-canonical roles in the cell, whereby they regulate novel effectors, undergo activation independently of a GPCR, and/or function at subcellular locations other than the plasma membrane. This review will highlight some of these non-canonical aspects of G protein signaling, focusing on direct interactions of G protein subunits with cytoskeletal and cell adhesion proteins, the role of G proteins in cell division, and G protein signaling at diverse organelles.     

Aspergillus niger G proteins: subcellular localization

Aspergillus niger postmitochondrial fraction, which contains high GTPase activity and high GTP binding capacity, has been subjected to subcellular fractionation on a sucrose gradient. A cytosolic and four membranous populations have been separated according to their relative density. The main difficulty has been the characterization of the plasma membrane of the fungus. This fraction, which does not contain any typical enzyme, has been identified after iodination of the outer proteins of protoplasts from A. niger. The immunological detection has shown the occurrence of cytosolic G proteins and membranous small G proteins located not only in the plasma membrane but also in the membranes of the endoplasmic reticulum.