Systematic analysis of protein subcellular localization and interaction using high-throughput transient transformation of Arabidopsis seedlings

The functional genomics approach requires systematic analysis of protein subcellular distribution and interaction networks, preferably by optimizing experimental simplicity and physiological significance. Here, we present an efficient in planta transient transformation system that allows single or multiple expression of constructs containing various fluorescent protein tags in Arabidopsis cotyledons. The optimized protocol is based on vacuum infiltration of agrobacteria directly into young Arabidopsis seedlings. We demonstrate that Arabidopsis epidermal cells show a subcellular distribution of reference markers similar to that in tobacco epidermal cells, and can be used for co-localization or bi-molecular fluorescent complementation studies. We then used this new system to investigate the subcellular distribution of enzymes involved in sphingolipid metabolism. In contrast to transformation systems using tobacco epidermal cells or cultured Arabidopsis cells, our system provides the opportunity to take advantage of the extensive collections of mutant and transgenic lines available in Arabidopsis. The fact that this assay uses conventional binary vectors and a conventional Agrobacterium strain, and is compatible with a large variety of fluorescent tags, makes it a versatile tool for construct screening and characterization before stable transformation. Transient expression in Arabidopsis seedlings is thus a fast and simple method that requires minimum handling and potentially allows medium- to high-throughput analyses of fusion proteins harboring fluorescent tags in a whole-plant cellular context.     

Systematic analysis of the impact of phosphorylation and O-GlcNAcylation on protein subcellular localization

1. Download : Download high-res image (214KB)
2. Download : Download full-size image

     

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.     

Prediction of protein subcellular localization

Because the protein's function is usually related to its subcellular localization, the ability to predict subcellular localization directly from protein sequences will be useful for inferring protein functions. Recent years have seen a surging interest in the development of novel computational tools to predict subcellular localization. At present, these approaches, based on a wide range of algorithms, have achieved varying degrees of success for specific organisms and for certain localization categories. A number of authors have noticed that sequence similarity is useful in predicting subcellular localization. For example, Nair and Rost (Protein Sci 2002;11:2836-2847) have carried out extensive analysis of the relation between sequence similarity and identity in subcellular localization, and have found a close relationship between them above a certain similarity threshold. However, many existing benchmark data sets used for the prediction accuracy assessment contain highly homologous sequences-some data sets comprising sequences up to 80-90% sequence identity. Using these benchmark test data will surely lead to overestimation of the performance of the methods considered. Here, we develop an approach based on a two-level support vector machine (SVM) system: the first level comprises a number of SVM classifiers, each based on a specific type of feature vectors derived from sequences; the second level SVM classifier functions as the jury machine to generate the probability distribution of decisions for possible localizations. We compare our approach with a global sequence alignment approach and other existing approaches for two benchmark data sets-one comprising prokaryotic sequences and the other eukaryotic sequences. Furthermore, we carried out all-against-all sequence alignment for several data sets to investigate the relationship between sequence homology and subcellular localization. Our results, which are consistent with previous studies, indicate that the homology search approach performs well down to 30% sequence identity, although its performance deteriorates considerably for sequences sharing lower sequence identity. A data set of high homology levels will undoubtedly lead to biased assessment of the performances of the predictive approaches-especially those relying on homology search or sequence annotations. Our two-level classification system based on SVM does not rely on homology search; therefore, its performance remains relatively unaffected by sequence homology. When compared with other approaches, our approach performed significantly better. Furthermore, we also develop a practical hybrid method, which combines the two-level SVM classifier and the homology search method, as a general tool for the sequence annotation of subcellular localization.     

Systematic analysis of protein pools, isoforms, and modifications affecting turnover and subcellular localization

In higher eukaryotes many genes encode protein isoforms whose properties and biological roles are often poorly characterized. Here we describe systematic approaches for detection of either distinct isoforms, or separate pools of the same isoform, with differential biological properties. Using information from ion intensities we have estimated protein abundance levels and using rates of change in stable isotope labeling with amino acids in cell culture isotope ratios we measured turnover rates and subcellular distribution for the HeLa cell proteome. Protein isoforms were detected using three data analysis strategies that evaluate differences between stable isotope labeling with amino acids in cell culture isotope ratios for specific groups of peptides within the total set of peptides assigned to a protein. The candidate approach compares stable isotope labeling with amino acids in cell culture isotope ratios for predicted isoform-specific peptides, with ratio values for peptides shared by all the isoforms. The rule of thirds approach compares the mean isotope ratio values for all peptides in each of three equal segments along the linear length of the protein, assessing differences between segment values. The three in a row approach compares mean isotope ratio values for each sequential group of three adjacent peptides, assessing differences with the mean value for all peptides assigned to the protein. Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices. The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides. Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.     

Investigation of binding mechanisms of nuclear proteins using confocal scanning laser microscopy and FRAP

Fluorescence recovery after photobleaching (FRAP) measurements offer an important tool towards analysing diffusion processes within living biological cells. A model is presented that aims to provide a rigorous theoretical framework from which binding information of proteins from FRAP data can be extracted. A single binding reaction is considered and a set of mathematical equations is introduced that incorporates the concentration of free proteins, vacant binding sites and bound complexes in addition to the on- and off-rates of the proteins. To allow a realistic FRAP model, characteristics of the instruments used to perform FRAP measurements are included in the equation. The proposed model has been designed to be applied to biological samples with a confocal scanning laser microscope (CSLM) equipped with the feature to bleach regions characterised by a radially Gaussian distributed profile. Binding information emerges from FRAP simulations considering the diffusion coefficient, radial extent of the bleached volume and bleach constant as parameters derived from experimental data. The proposed model leads to FRAP curves that depend on the on- and off-rates. Analytical expressions are used to define the boundaries of on- and off-rate parameter space in simplified cases when molecules can move on an infinite domain. A similar approach is ensued when movement is restricted in a compartment with a finite size. The theoretical model can be used in conjunction to experimental data acquired by CSLM to investigate the biophysical properties of proteins in living cells.     

Different subcellular localization and phosphoinositides binding of insulin receptor substrate protein pleckstrin homology domains

Insulin evokes diverse biological effects through receptor-mediated tyrosine phosphorylation of the insulin receptor substrate (IRS) proteins. Here, we show that, in vitro, the IRS-1, -2 and -3 pleckstrin homology (PH) domains bind with different specificities to the 3-phosphorylated phosphoinositides. In fact, the IRS-1 PH domain binds preferentially to phosphatidylinositol 3,4,5-trisphosphate (PtdIns-3,4,5-P3), the IRS-2 PH domain to phosphatidylinositol 3,4-bisphosphate (PtdIns-3,4-P2), and the IRS-3 PH domain to phosphatidylinositol 3-phosphate. When expressed in NIH-IR fibroblasts and L6 myocytes, the IRS-1 and -2 PH domains tagged with green fluorescent protein (GFP) are localized exclusively in the cytoplasm. Stimulation with insulin causes a translocation of the GFP-IRS-1 and -2 PH domains to the plasma membrane within 3-5 min. This translocation is blocked by the phosphatidylinositol 3-kinase (PI 3-K) inhibitors, wortmannin and LY294002, suggesting that this event is PI 3-K dependent. Interestingly, platelet-derived growth factor (PDGF) did not induce translocation of the IRS-1 and -2 PH domains to the plasma membrane, indicating the existence of specificity for insulin. In contrast, the GFP-IRS-3 PH domain is constitutively localized to the plasma membrane. These results reveal a differential regulation of the IRS PH domains and a novel positive feedback loop in which PI 3-K functions as both an upstream regulator and a downstream effector of IRS-1 and -2 signaling.     

Characterization and subcellular localization of the Clostridium thermocellum scaffoldin dockerin binding protein SdbA.

This article reports the characterization of the Clostridium thermocellum SdbA protein thought to anchor the cellulosome to the bacterial cell surface. The NH2-terminal region of SdbA consists of a cohesin domain which specifically binds the dockerin domain of the cellulosomal scaffolding protein CipA. The COOH-terminal region consists of a triplicated segment, termed SLH repeats, which is present in the sequence of many bacterial cell surface polypeptides. The binding parameters of the interaction between the dockerin domain of CipA and the cohesin domain of SdbA were studied by using, as a probe, the chimeric polypeptide CelC-DSCipA, which carries the dockerin domain of CipA fused to endoglucanase CelC. In the presence of Ca2+, CelC-DSCipA bound to SdbA with an affinity constant of 1.26 x 10(7) M(-1). Binding of CelC-DSCipA to SdbA as a function of Ca2+ concentration was sigmoidal, corresponding to a Hill coefficient of 2 and an affinity constant for Ca2+ of 4 x 10(6) M(-2). This suggested the presence of two cooperatively bound Ca2+ ions in the cohesin-dockerin complex. Immunoblotting of C. thermocellum subcellular fractions and electron microscopy of immunocytochemically labeled cells indicated that SdbA is located on the cell surface and is a component of the cellulosome. Together, the data confirm that SdbA could mediate anchoring of the cellulosome to the surface of C. thermocellum cells by interacting with the dockerin domain of CipA.     

HIV-1 TAT-mediated protein transduction and subcellular localization using novel expression vectors

Several novel prokaryotic and eukaryotic expression vectors were constructed for protein transduction and subcellular localization. These vectors employed an N-terminal stretch of 11 basic amino acid residues (47-57) from the human immunodeficiency virus type 1 (HIV-1) TAT protein transduction domain (PTD) for protein translocation and cellular localization. The vectors also contained a six-histidine (His(6)) tag at the N- or C-terminus for convenient purification and detection, and a multiple cloning site for easy insertion of foreign genes. Some heterologous genes including HSV-TK, Bcl-rambo, Smac/DIABLO and GFP were fused in-frame to TAT PTD and successfully overexpressed in Escherichia coli. The purified TAT-GFP fusion protein was able to transduce into the mammalian cells and was found to locate mainly in the cytosol when exogenously added to the cell culture medium. However, using a transfection system, mammalian-expressed TAT-GFP predominantly displayed a nuclear localization and nucleolar accumulation in mammalian cell lines. This discrepancy implies that the exact subcellular localization of transduced protein may depend on cell type, the nature of imported proteins and delivery approach. Taken together, our results demonstrate that a TAT PTD length of 11 amino acids was sufficient to confer protein internalization and its subsequent cellular localization. These novel properties allow these vectors to be useful for studying protein transduction and nuclear import.     

The Plasmodium falciparum translationally controlled tumor protein: subcellular localization and calcium binding.

Artemisinin derivatives are endoperoxide antimalarials widely used to treat falciparum malaria in areas where drug resistance is common. In Plasmodium falciparum-infected erythrocytes, radiolabeled artemisinin derivatives have been shown to react with malarial proteins, one of which is the Translationally Controlled Tumor Protein (TCTP). The P. falciparum TCTP was found by immunofluorescence to be located in both the cytoplasm and food vacuoles. Immunoelectron microscopy shows that it is present in the parasite cytoplasm as well as in its food vacuolar and limiting membranes. Like other TCTPs, the P. falciparum protein binds to calcium. Further studies on the physiological role of TCTP may aid in understanding the mechanism of action of endoperoxide antimalarials.     

Vitellogenin uptake and vitellin localization in insect follicles examined using monoclonal antibodies and confocal scanning microscopy

Summary

Confocal scanning immunofluorescent microscopy and monoclonal antibodies were used to examine the route of uptake of vitellogenin (VG) by vitellogenic follicles and the ooplasmic localization of vitellin (VN) in the cricket, Acheta domesticus, and the stick insect, Carausius morosus. Uptake and cytoplasmic regionalization of a non-vitellogenic sulfated protein, sp 157/85, by C. morosus oocytes were also examined. By indirect immunofluorescence VG in both species and sp 157/85 were visualized in spaces between follicle cells and in peripheral yolk spheres. One cricket VG polypeptide had a regionalized distribution in the folliclular epithelium, and VN polypeptides in both species and sp 157/85 in C. morosus had regionalized distributions within the ooplasm. Localization of sp 157/85 to the anterior pole of the oocyte appeared to be stage-specific.     

The subcellular localization of 3-phosphoinositide-dependent protein kinase is controlled by caveolin-1 binding

3-Phosphoinositide-dependent protein kinase 1 (PDK1), a member of the serine/threonine kinase family, has been demonstrated to be crucial for cellular survival, differentiation, and metabolism. Here, we present evidence that PDK1 is associated with caveolin-1, a 22-kDa integral membrane protein, which is the principal structural and regulatory component of the caveolae membranes in COS-1. First, we noted the presence of two potential caveolin-1 binding motifs ((141)FFVKLYFTF(149) and (299)YDFPEKFF(306)) in the PDK1 catalytic domain. Using a pull-down approach, we observed that PDK1 interacts physically with caveolin-1 both in vivo and in vitro. Second, we detected the co-localization of PDK1 and caveolin-1 via confocal microscopy. The localization of PDK1 to the plasma membrane was disrupted by caveolin binding. Third, in transient transfection assays, interaction with caveolin-1 induced a substantial reduction in the in vivo serine/threonine phosphorylation of PDK1, whereas the caveolin-1 binding site mutant ((141)FFVKLYFTF(149) and (299)YDFPEKFF(306) change to (141)AFVKLAFTA(149) and (299)ADAPEFLA(306)) did not. Furthermore, a caveolin-1 scaffolding peptide (amino acids 82-101) functionally suppressed the self-phosphorylation and kinase activities of purified recombinant PDK1 protein. Thus, our observations indicated that PDK1 binds to caveolin-1 through its caveolin-binding motifs, and also that the protein-protein interaction between PDK1 and caveolin-1 regulates PDK1 self-phosphorylation, kinase activity, and subcellular localization.     

The subcellular localization of 3-phosphoinositide-dependent protein kinase is controlled by caveolin-1 binding

3-Phosphoinositide-dependent protein kinase 1 (PDK1), a member of the serine/threonine kinase family, has been demonstrated to be crucial for cellular survival, differentiation, and metabolism. Here, we present evidence that PDK1 is associated with caveolin-1, a 22-kDa integral membrane protein, which is the principal structural and regulatory component of the caveolae membranes in COS-1. First, we noted the presence of two potential caveolin-1 binding motifs (¹⁴¹FFVKLYFTF¹⁴⁹ and ²⁹⁹YDFPEKFF³⁰⁶) in the PDK1 catalytic domain. Using a pull-down approach, we observed that PDK1 interacts physically with caveolin-1 both in vivo and in vitro. Second, we detected the co-localization of PDK1 and caveolin-1 via confocal microscopy. The localization of PDK1 to the plasma membrane was disrupted by caveolin binding. Third, in transient transfection assays, interaction with caveolin-1 induced a substantial reduction in the in vivo serine/threonine phosphorylation of PDK1, whereas the caveolin-1 binding site mutant (¹⁴¹FFVKLYFTF¹⁴⁹ and ²⁹⁹YDFPEKFF³⁰⁶ change to ¹⁴¹AFVKLAFTA¹⁴⁹ and ²⁹⁹ADAPEFLA³⁰⁶) did not. Furthermore, a caveolin-1 scaffolding peptide (amino acids 82-101) functionally suppressed the self-phosphorylation and kinase activities of purified recombinant PDK1 protein. Thus, our observations indicated that PDK1 binds to caveolin-1 through its caveolin-binding motifs, and also that the protein-protein interaction between PDK1 and caveolin-1 regulates PDK1 self-phosphorylation, kinase activity, and subcellular localization.     

pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties

Background  

Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of prediction algorithms have been developed based on amino acid compositions or on the N-terminal characteristics (signal peptides) of proteins. However, such approaches lead to a loss of contextual information. Moreover, where information about the physicochemical properties of amino acids has been used, the methods employed to exploit that information are less than optimal and could use the information more effectively.     

Methods for predicting bacterial protein subcellular localization

The computational prediction of the subcellular localization of bacterial proteins is an important step in genome annotation and in the search for novel vaccine or drug targets. Since the 1991 release of PSORT I--the first comprehensive algorithm to predict bacterial protein localization--many other localization prediction tools have been developed. These methods offer significant improvements in predictive performance over PSORT I and the accuracy of some methods now rivals that of certain high-throughput laboratory methods for protein localization identification.     

蛋白质亚细胞定位预测中的序列编码技术

蛋白质序列的编码是亚细胞定位预测问题中的关键技术之一。该文较为详细地介绍了目前已有的蛋白质序列编码算法;并指出了序列编码中存在的一些问题及可能的发展方向。     

Systematic subcellular localization of novel proteins identified by large-scale cDNA sequencing

As a first step towards a more comprehensive functional characterization of cDNAs than bioinformatic analysis, which can only make functional predictions for about half of the cDNAs sequenced, we have developed and tested a strategy that allows their systematic and fast subcellular localization. We have used a novel cloning technology to rapidly generate N- and C-terminal green fluorescent protein fusions of cDNAs to examine the intracellular localizations of >100 expressed fusion proteins in living cells. The entire analysis is suitable for automation, which will be important for scaling up throughput. For >80% of these new proteins a clear intracellular localization to known structures or organelles could be determined. For the cDNAs where bioinformatic analyses were able to predict possible identities, the localization was able to support these predictions in 75% of cases. For those cDNAs where no homologies could be predicted, the localization data represent the first information.