Mechanisms governing subcellular localization and function of human RGS2

RGS proteins negatively regulate heterotrimeric G proteins at the plasma membrane. RGS2-GFP localizes to the nucleus, plasma membrane, and cytoplasm of HEK293 cells. Expression of activated G(q) increased RGS2 association with the plasma membrane and decreased accumulation in the nucleus, suggesting that signal-induced redistribution may regulate RGS2 function. Thus, we identified and characterized a conserved N-terminal domain in RGS2 that is necessary and sufficient for plasma membrane localization. Mutational and biophysical analyses indicated that this domain is an amphipathic alpha-helix that binds vesicles containing acidic phospholipids. However, the plasma membrane targeting function of the amphipathic helical domain did not appear to be essential for RGS2 to attenuate signaling by activated G(q). Nevertheless, truncation mutants indicated that the N terminus is essential, potentially serving as a scaffold that binds receptors, signaling proteins, or nuclear components. Indeed, the RGS2 N terminus directs nuclear accumulation of GFP. Although RGS2 possesses a nuclear targeting motif, it lacks a nuclear import signal and enters the nucleus by passive diffusion. Nuclear accumulation of RGS2 does not limit its ability to attenuate G(q) signaling, because excluding RGS2 from the nucleus was without effect. RGS2 may nonetheless regulate signaling or other processes in the nucleus.     

Refining protein subcellular localization

The study of protein subcellular localization is important to elucidate protein function. Even in well-studied organisms such as yeast, experimental methods have not been able to provide a full coverage of localization. The development of bioinformatic predictors of localization can bridge this gap. We have created a Bayesian network predictor called PSLT2 that considers diverse protein characteristics, including the combinatorial presence of InterPro motifs and protein interaction data. We compared the localization predictions of PSLT2 to high-throughput experimental localization datasets. Disagreements between these methods generally involve proteins that transit through or reside in the secretory pathway. We used our multi-compartmental predictions to refine the localization annotations of yeast proteins primarily by distinguishing between soluble lumenal proteins and soluble proteins peripherally associated with organelles. To our knowledge, this is the first tool to provide this functionality. We used these sub-compartmental predictions to characterize cellular processes on an organellar scale. The integration of diverse protein characteristics and protein interaction data in an appropriate setting can lead to high-quality detailed localization annotations for whole proteomes. This type of resource is instrumental in developing models of whole organelles that provide insight into the extent of interaction and communication between organelles and help define organellar functionality.     

Variable subcellular localization of glycosphingolipids

Although most glycosphingolipids (GSLs) are thought to be locatedin the outer leaflet of the plasma membrane, recent evidenceindicates that GSLs are also associated with intracellular organelles.We now report that the subcellular localization of GSLs variesdepending on the GSL structure and cell type. GSL localizationwas determined by indirect immunofluorescence microscopy offixed permeabilized cells. A single GSL exhibited variable subcellularlocalization in different cells. For example, antibody to GalCeris localized primarily to the plasma membrane of HaCaT II-3keratinocytes, but to intracellular organelies in other epithelialcells. GalCer is localized to small vesicles and tubulovesicularstructures in MDCK cells, and to the surface of phase-denselipid droplets in HepG2 hepatoma cells. Furthermore, withina single cell type, individual GSLs were found to exhibit differentpatterns of subcellular localization. In HepG2 cells, LacCerwas associated with small vesicles, which differed from thephase-dense vesicles stained by anti-GalCer, and Gb4Cer wasassociated with the intermediate filaments of the cytoskeleton.Both anti-GalCer and monoclonal antibody A2B5, which binds polysialogangliosides,localized to mitochondria. The distinct subcellular localizationpatterns of GSLs raise interesting questions about their functionsin different organelles. Together with published data on theenrichment of GSLs in specific organelles and in apical plasmamembrane, these findings indicate the existence of specificsorting mechanisms that regulate the intracellular transportand localization of GSLs. cytoskeleton glycosphingolipid intracellular organelles mitochondria subcellular localization     

Predicting subcellular localization with AdaBoost Learner

Protein subcellular localization, which tells where a protein resides in a cell, is an important characteristic of a protein, and relates closely to the function of proteins. The prediction of their subcellular localization plays an important role in the prediction of protein function, genome annotation and drug design. Therefore, it is an important and challenging role to predict subcellular localization using bio-informatics approach. In this paper, a robust predictor, AdaBoost Learner is introduced to predict protein subcellular localization based on its amino acid composition. Jackknife cross-validation and independent dataset test were used to demonstrate that Adaboost is a robust and efficient model in predicting protein subcellular localization. As a result, the correct prediction rates were 74.98% and 80.12% for the Jackknife test and independent dataset test respectively, which are higher than using other existing predictors. An online server for predicting subcellular localization of proteins based on AdaBoost classifier was available on http://chemdata.shu. edu.cn/sl12.     

On the subcellular localization of the polyamines

Putrescine, spermidine and spermine were determined in the nuclear fraction of rat liver which was obtained by density gradient centrifugation in non-aqueous media, i.e. under conditions which avoid migration of water-soluble compounds. Calculations of the distribution of the polyamines between nuclear and extranuclear compartments were based on the assumption that the DNA is concentrated in the nuclei. No significant losses of the polyamines occurred during fractionation. From the polyamine determination in tissue and nuclear fraction it appeared that 16-17% of the liver spermidine and spermine, and about 8% of the putrescine content was localized in the nuclei. The spermidine/spermine-ratios in nuclei and whole tissue were not significantly different. Pretreatment of the animals with inhibitors of ornithine decarboxylase caused a decrease of putrescine exclusively in the extranuclear compartments, in agreement with a higher proportion of the inhibitors in the cytoplasm. Since the nuclear volume of rat liver corresponds to about 5% of total liver volume, the concentration of spermidine and spermine is higher in the nucleus than in extranuclear compartments. Published histochemical localizations of the polyamines suggested very low polyamine concentrations in the nuclei of non-dividing liver and HeLa cells, but dramatic polyamine accumulations in metaphase and anaphase nuclei. These results are in disagreement with previously reported autoradiographic data, subcellular localizations based on density gradient centrifugations, and with our present results. Since subcellular localization is a key issue in all attempts to clarify cellular functions of the polyamines the careful revision of the techniques involved in subcellular polyamine localizations seems imperative.     

Cellular and subcellular localization of phototropin 1

Phototropin 1 (phot1) is a Ser/Thr photoreceptor kinase that binds two molecules of flavin mononucleotide as its chromophores and undergoes autophosphorylation in response to blue light. Phot1 is plasma membrane associated and, as with phot2, has been shown to function as a photoreceptor for phototropism, blue light-induced chloroplast movement, and blue light-induced stomatal opening. Phot1 likely also plays a redundant role with phot2 in regulating the rate of leaf expansion. Understanding the mechanism(s) by which phot1 initiates these four different responses requires, at minimum, knowledge of where the photoreceptor is located. Therefore, we transformed a phot1 null mutant of Arabidopsis with a construct encoding translationally fused phot1-green fluorescent protein (GFP) under the control of the endogenous PHOT1 promoter and investigated its cellular and subcellular distribution. This PHOT1-GFP construct complements the mutant phenotype, restoring second positive curvature. Phot1 is expressed strongly in dividing and elongating cortical cells in the apical hook and in the root elongation zone in etiolated seedlings. It is localized evenly to the plasma membrane region in epidermal cells but is confined largely to the plasma membrane region of the transverse cell walls in the cortical cells of both root and hypocotyl. It is found at both apical and basal ends of these cortical cells. In light-grown plants, phot1-GFP is localized largely in the plasma membrane regions adjacent to apical and basal cell end walls in the elongating inflorescence stem, where the photoreceptor is expressed strongly in the vascular parenchyma and leaf vein parenchyma. Phot1 also is localized to the plasma membrane region of leaf epidermal cells, mesophyll cells, and guard cells, where its distribution is uniform. Although phot1 is localized consistently to the plasma membrane region in etiolated seedlings, a fraction becomes released to the cytoplasm in response to blue light. Possible relationships between observed phot1 distribution and the various physiological responses activated by blue light are discussed.     

Identification of the subcellular localization of mycobacterial proteins using localization motifs

Mycobacterium, the most common disease-causing genus, infects billions of people and is notoriously difficult to treat. Understanding the subcellular localization of mycobacterial proteins can provide essential clues for protein function and drug discovery. In this article, we present a novel approach that focuses on local sequence information to identify localization motifs that are generated by a merging algorithm and are selected based on a binomially distributed model. These localization motifs are employed as features for identifying the subcellular localization of mycobacterial proteins. Our approach provides more accurate results than previous methods and was tested on an independent dataset recently obtained from an experimental study to provide a first and reasonably accurate prediction of subcellular localization. Our approach can also be used for large-scale prediction of new protein entries in the UniportKB database and of protein sequences obtained experimentally. In addition, our approach identified many local motifs involved with the subcellular localization that also interact with the environment. Thus, our method may have widespread applications both in the study of the functions of mycobacterial proteins and in the search for a potential vaccine target for designing drugs.     

Determinants of mRNA localization

RNA localization provides a mechanism for protein targeting within developing or differentiating cells. Specific cis-acting sequences on mRNA mediate this process. Such 'localizer' or 'zipcode' nucleic acid sequences have been restricted to the 3' untranslated region of several mRNAs. The presence of genetic information denoting a spatial component of translation adds a new dimension to gene expression.     

LPA-induced mutually exclusive subcellular localization of active RhoA and Arp2 mRNA revealed by sequential FRET and FISH

We previously demonstrated that mRNAs for the subunits of the Arp2/3 complex localize to protrusions in fibroblasts (Mingle et al. in J Cell Sci 118:2425–2433, 2005). However, the signaling pathway that regulates Arp2/3 complex mRNA localization remains unknown. In this study we have identified lysophosphatidic acid (LPA) as a potent inducer of Arp2 mRNA localization to protrusions in fibroblasts via the RhoA-ROCK pathway. As RhoA is known to be activated locally in the cells, we sought to understand how spatial activation of Rho affects Arp2 mRNA localization. By sequentially performing fluorescence resonance energy transfer (FRET) and fluorescence in situ hybridization (FISH), we have visualized active RhoA and Arp2 mRNA in the same cells. Upon LPA stimulation, approximately two times more cells than those in the serum-free medium showed mutually exclusive localization of active RhoA and Arp2 mRNA. These results demonstrate the importance of localized activation of Rho in Arp2 mRNA localization and provide new insights as to how Rho regulates Arp2/3 complex mRNA localization. To our best knowledge, this is the first report in which FRET and FISH are combined to detect localized protein activity and mRNA in the same cells. This method should be easily adopted for the detection of other fluorescence protein based biosensors and DNA/RNA in the same cells.     

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.     

BaCelLo: a balanced subcellular localization predictor

MOTIVATION: The knowledge of the subcellular localization of a protein is fundamental for elucidating its function. It is difficult to determine the subcellular location for eukaryotic cells with experimental high-throughput procedures. Computational procedures are then needed for annotating the subcellular location of proteins in large scale genomic projects. RESULTS: BaCelLo is a predictor for five classes of subcellular localization (secretory pathway, cytoplasm, nucleus, mitochondrion and chloroplast) and it is based on different SVMs organized in a decision tree. The system exploits the information derived from the residue sequence and from the evolutionary information contained in alignment profiles. It analyzes the whole sequence composition and the compositions of both the N- and C-termini. The training set is curated in order to avoid redundancy. For the first time a balancing procedure is introduced in order to mitigate the effect of biased training sets. Three kingdom-specific predictors are implemented: for animals, plants and fungi, respectively. When distributing the proteins from animals and fungi into four classes, accuracy of BaCelLo reach 74% and 76%, respectively; a score of 67% is obtained when proteins from plants are distributed into five classes. BaCelLo outperforms the other presently available methods for the same task and gives more balanced accuracy and coverage values for each class. We also predict the subcellular localization of five whole proteomes, Homo sapiens, Mus musculus, Caenorhabditis elegans, Saccharomyces cerevisiae and Arabidopsis thaliana, comparing the protein content in each different compartment. AVAILABILITY: BaCelLo can be accessed at http://www.biocomp.unibo.it/bacello/.