hCKSAAP_UbSite: Improved prediction of human ubiquitination sites by exploiting amino acid pattern and properties

As one of the most common post-translational modifications, ubiquitination regulates the quantity and function of a variety of proteins. Experimental and clinical investigations have also suggested the crucial roles of ubiquitination in several human diseases. The complicated sequence context of human ubiquitination sites revealed by proteomic studies highlights the need of developing effective computational strategies to predict human ubiquitination sites. Here we report the establishment of a novel human-specific ubiquitination site predictor through the integration of multiple complementary classifiers. Firstly, a Support Vector Machine (SVM) classier was constructed based on the composition of k-spaced amino acid pairs (CKSAAP) encoding, which has been utilized in our previous yeast ubiquitination site predictor. To further exploit the pattern and properties of the ubiquitination sites and their flanking residues, three additional SVM classifiers were constructed using the binary amino acid encoding, the AAindex physicochemical property encoding and the protein aggregation propensity encoding, respectively. Through an integration that relied on logistic regression, the resulting predictor termed hCKSAAP_UbSite achieved an area under ROC curve (AUC) of 0.770 in 5-fold cross-validation test on a class-balanced training dataset. When tested on a class-balanced independent testing dataset that contains 3419 ubiquitination sites, hCKSAAP_UbSite has also achieved a robust performance with an AUC of 0.757. Specifically, it has consistently performed better than the predictor using the CKSAAP encoding alone and two other publicly available predictors which are not human-specific. Given its promising performance in our large-scale datasets, hCKSAAP_UbSite has been made publicly available at our server (http://protein.cau.edu.cn/cksaap_ubsite/).     

mUbiSiDa: A Comprehensive Database for Protein Ubiquitination Sites in Mammals

Motivation

Protein ubiquitination is one of the important post-translational modifications by attaching ubiquitin to specific lysine (K) residues in target proteins, and plays important regulatory roles in many cell processes. Recent studies indicated that abnormal protein ubiquitination have been implicated in many diseases by degradation of many key regulatory proteins including tumor suppressor, oncoprotein, and cell cycle regulator. The detailed information of protein ubiquitination sites is useful for scientists to investigate the mechanism of many cell activities and related diseases.

Results

In this study we established mUbiSida for mammalian Ubiquitination Site Database, which provides a scientific community with a comprehensive, freely and high-quality accessible resource of mammalian protein ubiquitination sites. In mUbiSida, we deposited about 35,494 experimentally validated ubiquitinated proteins with 110,976 ubiquitination sites from five species. The mUbiSiDa can also provide blast function to predict novel protein ubiquitination sites in other species by blast the query sequence in the deposit sequences in mUbiSiDa. The mUbiSiDa was designed to be a widely used tool for biologists and biomedical researchers with a user-friendly interface, and facilitate the further research of protein ubiquitination, biological networks and functional proteomics. The mUbiSiDa database is freely available at http://reprod.njmu.edu.cn/mUbiSiDa.     

Sequence and structure-based characterization of ubiquitination sites in human and yeast proteins using Chou's sample formulation

Ubiquitination is an important post-translational event responsible for half-life and turnover of proteins inside the cell. Proteins are ubiquitinated by forming an iso-peptide bond between their lysine residue and C-terminal glycine residue of ubiquitin leading to rapid degradation of proteins by 26S proteosome complex. Deregulation of ubiquitination is manifested by aberrant expression of E3-ligase activity or mutation in the surroundings of ubiquitination sites. Many new experimentally validated ubiquitinated lysines have been recently identified that motivated the study of the environments surrounding the ubiquitinated lysines. With the help of known ubiquitinated proteins, here we present a comprehensive study of sequence and spatial environment of ubiquitination sites of human and yeast proteins. To identify position-specific features, this work distinguishes the spatial environments as proximity and distal regions. Certain amino acids specific to these regions, well differentiate the ubiquitination sites from non-ubiquitination sites are revealed. Additionally, amino acid signatures that contribute for protein disordered regions and solvent accessibility of amino acids are found to be contributing factors in ubiquitination sites. These results suggest that the ubiquitination site environment of the substrate determines the recognition and unfolding of substrate to facilitate the entry into 26S proteosomal complex. We believe that these findings will help in better prediction of ubiquitination sites using the sequence and spatial information.     

Structural Propensities of Human Ubiquitination Sites: Accessibility,Centrality and Local Conformation

The existence and function of most proteins in the human proteome are regulated by the ubiquitination process. To date, tens of thousands human ubiquitination sites have been identified from high-throughput proteomic studies. However, the mechanism of ubiquitination site selection remains elusive because of the complicated sequence pattern flanking the ubiquitination sites. In this study, we perform a systematic analysis of 1,330 ubiquitination sites in 505 protein structures and quantify the significantly high accessibility and unexpectedly high centrality of human ubiquitination sites. Further analysis suggests that the higher centrality of ubiquitination sites is associated with the multi-functionality of ubiquitination sites, among which protein-protein interaction sites are common targets of ubiquitination. Moreover, we demonstrate that ubiquitination sites are flanked by residues with non-random local conformation. Finally, we provide quantitative and unambiguous evidence that most of the structural propensities contain specific information about ubiquitination site selection that is not represented by the sequence pattern. Therefore, the hypothesis about the structural level of the ubiquitination site selection mechanism has been substantially approved.     

Predicting DNA-binding sites of proteins based on sequential and 3D structural information

Protein–DNA interactions play important roles in many biological processes. To understand the molecular mechanisms of protein–DNA interaction, it is necessary to identify the DNA-binding sites in DNA-binding proteins. In the last decade, computational approaches have been developed to predict protein–DNA-binding sites based solely on protein sequences. In this study, we developed a novel predictor based on support vector machine algorithm coupled with the maximum relevance minimum redundancy method followed by incremental feature selection. We incorporated not only features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, solvent accessibility, but also five three-dimensional (3D) structural features calculated from PDB data to predict the protein–DNA interaction sites. Feature analysis showed that 3D structural features indeed contributed to the prediction of DNA-binding site and it was demonstrated that the prediction performance was better with 3D structural features than without them. It was also shown via analysis of features from each site that the features of DNA-binding site itself contribute the most to the prediction. Our prediction method may become a useful tool for identifying the DNA-binding sites and the feature analysis described in this paper may provide useful insights for in-depth investigations into the mechanisms of protein–DNA interaction.     

Prediction of lysine ubiquitination with mRMR feature selection and analysis

Ubiquitination, one of the most important post-translational modifications of proteins, occurs when ubiquitin (a small 76-amino acid protein) is attached to lysine on a target protein. It often commits the labeled protein to degradation and plays important roles in regulating many cellular processes implicated in a variety of diseases. Since ubiquitination is rapid and reversible, it is time-consuming and labor-intensive to identify ubiquitination sites using conventional experimental approaches. To efficiently discover lysine-ubiquitination sites, a sequence-based predictor of ubiquitination site was developed based on nearest neighbor algorithm. We used the maximum relevance and minimum redundancy principle to identify the key features and the incremental feature selection procedure to optimize the prediction engine. PSSM conservation scores, amino acid factors and disorder scores of the surrounding sequence formed the optimized 456 features. The Mathew’s correlation coefficient (MCC) of our ubiquitination site predictor achieved 0.142 by jackknife cross-validation test on a large benchmark dataset. In independent test, the MCC of our method was 0.139, higher than the existing ubiquitination site predictor UbiPred and UbPred. The MCCs of UbiPred and UbPred on the same test set were 0.135 and 0.117, respectively. Our analysis shows that the conservation of amino acids at and around lysine plays an important role in ubiquitination site prediction. What’s more, disorder and ubiquitination have a strong relevance. These findings might provide useful insights for studying the mechanisms of ubiquitination and modulating the ubiquitination pathway, potentially leading to potential therapeutic strategies in the future.     

Ubiquitination of the PEST-like endocytosis signal of the yeast a-factor receptor

A 58-residue-long, PEST-like sequence within the yeast a-factor receptor (Ste3p) specifies the ubiquitination, endocytosis, and consequent vacuolar degradation of the receptor protein (Roth, A. F., Sullivan, D. M., and Davis, N. G. (1998) J. Cell Biol. 142, 949-961). The present work investigates three lysyl residues that map within this sequence as the potential ubiquitin acceptor sites. Lys --> Arg substitution mutants were tested for effects on both ubiquitination and endocytosis. Results indicate that the three lysines function redundantly; a severe blockade to both ubiquitination and endocytosis is seen only for receptors having all three lysines replaced. Of the three, Lys(432) plays the predominant role; ubiquitination and turnover are significantly impaired for receptors having just the K432R mutation. CNBr fragmentation of the receptor protein, used for the physical mapping of the ubiquitin attachment sites, showed PEST-like sequence lysines to be modified both with single ubiquitin moieties as well with short multi-ubiquitin chains, two or three ubiquitins long. Thus, in addition to being the signal for ubiquitination, the Ste3p PEST-like sequence also provides the site for ubiquitin attachment. To test if this endocytosis signal functions solely for ubiquitination, we have asked if the requirement for the PEST-like sequence in endocytosis might be bypassed through pre-attachment of ubiquitin to the receptor protein. Indeed, Ste3-ubiquitin translational fusions that have a ubiquitin moiety fused to the receptor in place of the PEST-like signal do undergo rapid endocytosis and vacuolar turnover. We conclude that ubiquitin alone, with no required contribution from receptor sequences, provides the sufficient signal for initiating uptake. In addition, our results confirm conclusions originally drawn from studies with the alpha-factor receptor (Terrell, J., Shih, S., Dunn, R., and Hicke, L. (1998) Mol. Cell 1, 193-202), namely that mono-ubiquitin, and not multi-ubiquitin chains provide the primary recognition determinant for uptake. Although mono-ubiquitination suffices, our results indicate that multi-ubiquitination serves to augment the rate of uptake.     

It’s Time for Some “Site”-Seeing: Novel Tools to Monitor the Ubiquitin Landscape in Arabidopsis thaliana

Ubiquitination, the covalent binding of the small protein modifier ubiquitin to a target protein, is an important and frequently studied posttranslational protein modification. Multiple reports provide useful insights into the plant ubiquitinome, but mostly at the protein level without comprehensive site identification. Here, we implemented ubiquitin combined fractional diagonal chromatography (COFRADIC) for proteome-wide ubiquitination site mapping on Arabidopsis thaliana cell cultures. We identified 3009 sites on 1607 proteins, thereby greatly increasing the number of known ubiquitination sites in this model plant. Finally, The Ubiquitination Site tool (http://bioinformatics.psb.ugent.be/webtools/ubiquitin_viewer/) gives access to the obtained ubiquitination sites, not only to consult the ubiquitination status of a given protein, but also to conduct intricate experiments aiming to study the roles of specific ubiquitination events. Together with the antibodies recognizing the ubiquitin remnant motif, ubiquitin COFRADIC represents a powerful tool to resolve the ubiquitination maps of numerous cellular processes in plants.     

Large-scale prediction of protein ubiquitination sites using a multimodal deep architecture

Background

Ubiquitination, which is also called “lysine ubiquitination”, occurs when an ubiquitin is attached to lysine (K) residues in targeting proteins. As one of the most important post translational modifications (PTMs), it plays the significant role not only in protein degradation, but also in other cellular functions. Thus, systematic anatomy of the ubiquitination proteome is an appealing and challenging research topic. The existing methods for identifying protein ubiquitination sites can be divided into two kinds: mass spectrometry and computational methods. Mass spectrometry-based experimental methods can discover ubiquitination sites from eukaryotes, but are time-consuming and expensive. Therefore, it is priority to develop computational approaches that can effectively and accurately identify protein ubiquitination sites.

Results

The existing computational methods usually require feature engineering, which may lead to redundancy and biased representations. While deep learning is able to excavate underlying characteristics from large-scale training data via multiple-layer networks and non-linear mapping operations. In this paper, we proposed a deep architecture within multiple modalities to identify the ubiquitination sites. First, according to prior knowledge and biological knowledge, we encoded protein sequence fragments around candidate ubiquitination sites into three modalities, namely raw protein sequence fragments, physico-chemical properties and sequence profiles, and designed different deep network layers to extract the hidden representations from them. Then, the generative deep representations corresponding to three modalities were merged to build the final model. We performed our algorithm on the available largest scale protein ubiquitination sites database PLMD, and achieved 66.4% specificity, 66.7% sensitivity, 66.43% accuracy, and 0.221 MCC value. A number of comparative experiments also indicated that our multimodal deep architecture outperformed several popular protein ubiquitination site prediction tools.

Conclusion

The results of comparative experiments validated the effectiveness of our deep network and also displayed that our method outperformed several popular protein ubiquitination site prediction tools. The source codes of our proposed method are available at https://github.com/jiagenlee/deepUbiquitylation.

     

On the packing density of the unbound protein-protein interaction interface and its implications in dynamics

Background

In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. In the ubiquitin-proteasome pathway, E3 ligases play important roles by recognizing a specific protein substrate and catalyzing the attachment of ubiquitin to a lysine (K) residue. As more and more experimental data on ubiquitin conjugation sites become available, it becomes possible to develop prediction models that can be scaled to big data. However, no development that focuses on the investigation of ubiquitinated substrate specificities has existed. Herein, we present an approach that exploits an iteratively statistical method to identify ubiquitin conjugation sites with substrate site specificities.

Results

In this investigation, totally 6259 experimentally validated ubiquitinated proteins were obtained from dbPTM. After having filtered out homologous fragments with 40% sequence identity, the training data set contained 2658 ubiquitination sites (positive data) and 5532 non-ubiquitinated sites (negative data). Due to the difficulty in characterizing the substrate site specificities of E3 ligases by conventional sequence logo analysis, a recursively statistical method has been applied to obtain significant conserved motifs. The profile hidden Markov model (profile HMM) was adopted to construct the predictive models learned from the identified substrate motifs. A five-fold cross validation was then used to evaluate the predictive model, achieving sensitivity, specificity, and accuracy of 73.07%, 65.46%, and 67.93%, respectively. Additionally, an independent testing set, completely blind to the training data of the predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (76.13%) and outperform other ubiquitination site prediction tool.

Conclusion

A case study demonstrated the effectiveness of the characterized substrate motifs for identifying ubiquitination sites. The proposed method presents a practical means of preliminary analysis and greatly diminishes the total number of potential targets required for further experimental confirmation. This method may help unravel their mechanisms and roles in E3 recognition and ubiquitin-mediated protein degradation.

     

Predicted functional RNAs within coding regions constrain evolutionary rates of yeast proteins

Functional RNAs (fRNAs) are being recognized as an important regulatory component in biological processes. Interestingly, recent computational studies suggest that the number and biological significance of functional RNAs within coding regions (coding fRNAs) may have been underestimated. We hypothesized that such coding fRNAs will impose additional constraint on sequence evolution because the DNA primary sequence has to simultaneously code for functional RNA secondary structures on the messenger RNA in addition to the amino acid codons for the protein sequence. To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes. We predict that as much as 5% of the genes in the yeast genome contain at least one functional RNA secondary structure within their protein-coding region. We then analyzed the impact of coding fRNAs on the evolutionary rate of protein-coding genes because a decrease in evolutionary rate implies constraint due to biological functionality. We found that our predicted coding fRNAs have a significant influence on evolutionary rates (especially at synonymous sites), independent of other functional measures. Thus, coding fRNA may play a role on sequence evolution. Given that coding regions of humans and flies contain many more predicted coding fRNAs than yeast, the impact of coding fRNAs on sequence evolution may be substantial in genomes of higher eukaryotes.     

Methods for quantification of in vivo changes in protein ubiquitination following proteasome and deubiquitinase inhibition

Ubiquitination plays a key role in protein degradation and signal transduction. Ubiquitin is a small protein modifier that is adducted to lysine residues by the combined function of E1, E2, and E3 enzymes and is removed by deubiquitinating enzymes. Characterization of ubiquitination sites is important for understanding the role of this modification in cellular processes and disease. However, until recently, large-scale characterization of endogenous ubiquitination sites has been hampered by the lack of efficient enrichment techniques. The introduction of antibodies that specifically recognize peptides with lysine residues that harbor a di-glycine remnant (K-ε-GG) following tryptic digestion has dramatically improved the ability to enrich and identify ubiquitination sites from cellular lysates. We used this enrichment technique to study the effects of proteasome inhibition by MG-132 and deubiquitinase inhibition by PR-619 on ubiquitination sites in human Jurkat cells by quantitative high performance mass spectrometry. Minimal fractionation of digested lysates prior to immunoaffinity enrichment increased the yield of K-ε-GG peptides three- to fourfold resulting in detection of up to ~3300 distinct K-GG peptides in SILAC triple encoded experiments starting from 5 mg of protein per label state. In total, we identify 5533 distinct K-ε-GG peptides of which 4907 were quantified in this study, demonstrating that the strategy presented is a practical approach to perturbational studies in cell systems. We found that proteasome inhibition by MG-132 and deubiquitinase inhibition by PR-619 induces significant changes to the ubiquitin landscape, but that not all ubiquitination sites regulated by MG-132 and PR-619 are likely substrates for the ubiquitin-proteasome system. Additionally, we find that the proteasome and deubiquitinase inhibitors studied induced only minor changes in protein expression levels regardless of the extent of regulation induced at the ubiquitin site level. We attribute this finding to the low stoichiometry of the majority ubiquitination sites identified in this study.     

Ubiquitination of Neuronal Nitric-oxide Synthase in the Calmodulin-binding Site Triggers Proteasomal Degradation of the Protein

Nitric-oxide synthase, a cytochrome P450-like hemoprotein enzyme, catalyzes the synthesis of nitric oxide, a critical signaling molecule in a variety of physiological processes. Our laboratory has discovered that certain drugs suicide-inactivate neuronal nitric-oxide synthase (nNOS) and lead to the preferential ubiquitination of the inactivated nNOS by an Hsp70- and CHIP (C terminus of Hsc70-interacting protein)-dependent process. To further understand the process by which altered nNOS is recognized, ubiquitinated, and proteasomally degraded, we examined the sites of ubiquitination on nNOS. We utilized an in vitro ubiquitination system containing purified E1, E2 (UbcH5a), Hsp70, and CHIP that recapitulates the ability of the cells to selectively recognize and ubiquitinate the altered forms of nNOS. LC-MS/MS analysis of the tryptic peptides obtained from the in vitro ubiquitinated nNOS identified 12 ubiquitination sites. Nine of the sites were within the oxygenase domain and two were in the calmodulin-binding site, which links the oxygenase and reductase domains, and one site was in the reductase domain. Mutational analysis of the lysines in the calmodulin-binding site revealed that Lys-739 is a major site for poly-ubiquitination of nNOS in vitro and regulates, in large part, the CHIP-dependent degradation of nNOS in HEK293 cells, as well as in in vitro studies with fraction II. Elucidating the exact site of ubiquitination is an important step in understanding how chaperones recognize and trigger degradation of nNOS.     

Substrate properties of ubiquitin carboxyl-terminally derived peptide probes for protein ubiquitination

Protein ubiquitination is a widespread protein posttranslational modification in eukaryotes that regulates essentially every aspect of cellular processes. The attachment of ubiquitin to a protein substrate is accomplished through an enzymatic cascade involving the actions of an activating enzyme (E1), a conjugating enzyme (E2), and a ligase (E3). There are more than 600 E3 ligases estimated to exist in the human genome that regulate the targeting specificity of protein ubiquitination. To understand the dynamic role of protein ubiquitination in biological processes, robust tools need to be developed which can be employed to establish the substrate specificity of each of these E3 ligases. In this report, we show that the ubiquitin carboxyl-terminally derived peptide probes can serve as modest ubiquitin surrogates for the ubiquitination pathway. In the E1-catalyzed probe adenylation assay, peptide probe 3 with a RLRGG recognition sequence exhibited the highest activity, with the k cat/ K 1/2 determined to be 1.1 x 10 (4) M (-1) s (-1), roughly 470-fold lower than that of ubiquitin. The rate of transfer from the E1 peptide probe thioesters to E2 showed clear sequence dependency, with peptide probe 4 with an LRLRGG recognition sequence showed the fastest rate ( t 1/2 = 0.9 min), essentially identical to that of ubiquitin ( t 1/2 = 0.8 min) under our assay conditions. Furthermore, peptide probes 4 and 8 also exhibited the selective, parkin-mediated labeling of tubulins in a semipurified tubulin-parkin complex. Finally, these carboxyl-terminally derived peptide probes were shown to label the ubiquitination substrates in fraction II of the rabbit reticulocyte lysate with an efficiency parallel to their substrate properties. The selective use of these ubiquitin carboxyl-terminally derived peptide probes by the ubiquitination pathway suggests that perhaps more potent peptide ubiquitination probes based on the ubiquitin C-terminal scaffold can be developed through additional structural optimization.     

Sequence and structure continuity of evolutionary importance improves protein functional site discovery and annotation

Protein functional sites control most biological processes and are important targets for drug design and protein engineering. To characterize them, the evolutionary trace (ET) ranks the relative importance of residues according to their evolutionary variations. Generally, top‐ranked residues cluster spatially to define evolutionary hotspots that predict functional sites in structures. Here, various functions that measure the physical continuity of ET ranks among neighboring residues in the structure, or in the sequence, are shown to inform sequence selection and to improve functional site resolution. This is shown first, in 110 proteins, for which the overlap between top‐ranked residues and actual functional sites rose by 8% in significance. Then, on a structural proteomic scale, optimized ET led to better 3D structure‐function motifs (3D templates) and, in turn, to enzyme function prediction by the Evolutionary Trace Annotation (ETA) method with better sensitivity of (40% to 53%) and positive predictive value (93% to 94%). This suggests that the similarity of evolutionary importance among neighboring residues in the sequence and in the structure is a universal feature of protein evolution. In practice, this yields a tool for optimizing sequence selections for comparative analysis and, via ET, for better predictions of functional site and function. This should prove useful for the efficient mutational redesign of protein function and for pharmaceutical targeting.     

A tool for the prediction of functionally important sites in proteins using a library of functional templates

Understanding and characterizing the biochemical and evolutionary information within the wealth of protein sequence and structural data, particularly at functionally important sites, is very important. A comprehensive analysis of physico-chemical properties and evolutionary conservation patterns at the molecular and biological function level is expected to yield important clues for identifying similar sites in as-yet uncharacterized proteins. We present a library of protein functional templates (PFTs) designed to represent the compositional and evolutionary conservation patterns of functional sites at the molecular and biological function level. Subsequently we developed LIMACS (LInear MAtching of Conservation Scores), a software tool that uses the template library for the prediction of functionally important sites in a multiple sequence alignment, transferring the molecular function annotation from the most-similar functional site in the template library to a predicted site.     

Predicting protein sumoylation sites from sequence features

Protein sumoylation is a post-translational modification that plays an important role in a wide range of cellular processes. Small ubiquitin-related modifier (SUMO) can be covalently and reversibly conjugated to the sumoylation sites of target proteins, many of which are implicated in various human genetic disorders. The accurate prediction of protein sumoylation sites may help biomedical researchers to design their experiments and understand the molecular mechanism of protein sumoylation. In this study, a new machine learning approach has been developed for predicting sumoylation sites from protein sequence information. Random forests (RFs) and support vector machines (SVMs) were trained with the data collected from the literature. Domain-specific knowledge in terms of relevant biological features was used for input vector encoding. It was shown that RF classifier performance was affected by the sequence context of sumoylation sites, and 20 residues with the core motif ΨKXE in the middle appeared to provide enough context information for sumoylation site prediction. The RF classifiers were also found to outperform SVM models for predicting protein sumoylation sites from sequence features. The results suggest that the machine learning approach gives rise to more accurate prediction of protein sumoylation sites than the other existing methods. The accurate classifiers have been used to develop a new web server, called seeSUMO (http://bioinfo.ggc.org/seesumo/), for sequence-based prediction of protein sumoylation sites.     

A method of mapping protein sumoylation sites by mass spectrometry using a modified small ubiquitin-like modifier 1 (SUMO-1) and a computational program

Post-translational modification by small ubiquitin-like modifier 1 (SUMO-1) is a highly conserved process from yeast to humans and plays important regulatory roles in many cellular processes. Sumoylation occurs at certain internal lysine residues of target proteins via an isopeptide bond linkage. Unlike ubiquitin whose carboxyl-terminal sequence is RGG, the tripeptide at the carboxyl terminus of SUMO is TGG. The presence of the arginine residue at the carboxyl terminus of ubiquitin allows tryptic digestion of ubiquitin conjugates to yield a signature peptide containing a diglycine remnant attached to the target lysine residue and rapid identification of the ubiquitination site by mass spectrometry. The absence of lysine or arginine residues in the carboxyl terminus of mammalian SUMO makes it difficult to apply this approach to mapping sumoylation sites. We performed Arg scanning mutagenesis by systematically substituting amino acid residues surrounding the diglycine motif and found that a SUMO variant terminated with RGG can be conjugated efficiently to its target protein under normal sumoylation conditions. We developed a Programmed Data Acquisition (PDA) mass spectrometric approach to map target sumoylation sites using this SUMO variant. A web-based computational program designed for efficient identification of the modified peptides is described.     

The internalization of yeast Ste6p follows an ordered series of events involving phosphorylation, ubiquitination, recognition and endocytosis

A general pathway for the internalization of plasma membrane proteins that involves phosphorylation, ubiquitination, recognition and endocytosis has recently emerged from multiple studies in yeast. We refer to this series of events as the PURE pathway. Here we investigate whether the yeast a-factor transporter Ste6p, an ATP-binding cassette protein, utilizes the PURE pathway. Deletion of a 52-amino acid sequence (the 'A box') within the linker region of Ste6p has previously been shown to block ubiquitination and endocytosis (Kolling R, Losko S. EMBO J 1997; 16:2251-2261). Using wild-type and mutant forms of GFP-tagged Ste6p, we identified two residues (T(613) and S(623)) within the A box as likely sites of Ste6p phosphorylation important for internalization. Mutation of these residues to alanine blocked ubiquitination and endocytosis of Ste6p, similar to the effect of deleting the entire A box, while substitution with glutamic acid (to mimic phosphorylation) suppressed the ubiquitination and endocytic defects. Importantly, a translational fusion of monoubiquitin to the C-terminus of Ste6p-T(613)A, S(623)A or Ste6p-DeltaA restored endocytosis, providing strong evidence that the role of phosphorylation is to direct ubiquitination, which in turn is a critical signal for Ste6p internalization. We also identified multiple (five) lysine residues in the linker that are important for Ste6p ubiquitination. Our results demonstrate that Ste6p follows the PURE pathway and that GFP-tagged Ste6p provides a powerful model protein for studies of endocytosis and post-endocytic events in yeast.