Predicting pupylation sites in prokaryotic proteins using semi-supervised self-training support vector machine algorithm

As one important post-translational modification of prokaryotic proteins, pupylation plays a key role in regulating various biological processes. The accurate identification of pupylation sites is crucial for understanding the underlying mechanisms of pupylation. Although several computational methods have been developed for the identification of pupylation sites, the prediction accuracy of them is still unsatisfactory. Here, a novel bioinformatics tool named IMP–PUP is proposed to improve the prediction of pupylation sites. IMP–PUP is constructed on the composition of k-spaced amino acid pairs and trained with a modified semi-supervised self-training support vector machine (SVM) algorithm. The proposed algorithm iteratively trains a series of support vector machine classifiers on both annotated and non-annotated pupylated proteins. Computational results show that IMP–PUP achieves the area under receiver operating characteristic curves of 0.91, 0.73, and 0.75 on our training set, Tung's testing set, and our testing set, respectively, which are better than those of the different error costs SVM algorithm and the original self-training SVM algorithm. Independent tests also show that IMP–PUP significantly outperforms three other existing pupylation site predictors: GPS–PUP, iPUP, and pbPUP. Therefore, IMP–PUP can be a useful tool for accurate prediction of pupylation sites. A MATLAB software package for IMP–PUP is available at https://juzhe1120.github.io/.     

Reconstitution of the Mycobacterium tuberculosis pupylation pathway in Escherichia coli

Prokaryotic ubiquitin-like protein (Pup) is a post-translational modifier that attaches to more than 50 proteins in Mycobacteria. Proteasome accessory factor A (PafA) is responsible for Pup conjugation to substrates, but the manner in which proteins are selected for pupylation is unknown. To address this issue, we reconstituted the pupylation of model Mycobacterium proteasome substrates in Escherichia coli, which does not encode Pup or PafA. Surprisingly, Pup and PafA were sufficient to pupylate at least 51 E. coli proteins in addition to the mycobacterial proteins. These data suggest that pupylation signals are intrinsic to targeted proteins and might not require Mycobacterium-specific cofactors for substrate recognition by PafA in vivo.     

Computational Identification of Protein Pupylation Sites by Using Profile-Based Composition of k-Spaced Amino Acid Pairs

Prokaryotic proteins are regulated by pupylation, a type of post-translational modification that contributes to cellular function in bacterial organisms. In pupylation process, the prokaryotic ubiquitin-like protein (Pup) tagging is functionally analogous to ubiquitination in order to tag target proteins for proteasomal degradation. To date, several experimental methods have been developed to identify pupylated proteins and their pupylation sites, but these experimental methods are generally laborious and costly. Therefore, computational methods that can accurately predict potential pupylation sites based on protein sequence information are highly desirable. In this paper, a novel predictor termed as pbPUP has been developed for accurate prediction of pupylation sites. In particular, a sophisticated sequence encoding scheme [i.e. the profile-based composition of k-spaced amino acid pairs (pbCKSAAP)] is used to represent the sequence patterns and evolutionary information of the sequence fragments surrounding pupylation sites. Then, a Support Vector Machine (SVM) classifier is trained using the pbCKSAAP encoding scheme. The final pbPUP predictor achieves an AUC value of 0.849 in10-fold cross-validation tests and outperforms other existing predictors on a comprehensive independent test dataset. The proposed method is anticipated to be a helpful computational resource for the prediction of pupylation sites. The web server and curated datasets in this study are freely available at http://protein.cau.edu.cn/pbPUP/.     

Prokayrotic Ubiquitin-Like Protein (Pup) Proteome of Mycobacterium tuberculosis

Prokaryotic ubiquitin-like protein (Pup) in Mycobacterium tuberculosis (Mtb) is the first known post-translational small protein modifier in prokaryotes, and targets several proteins for degradation by a bacterial proteasome in a manner akin to ubiquitin (Ub) mediated proteolysis in eukaryotes. To determine the extent of pupylation in Mtb, we used tandem affinity purification to identify its “pupylome”. Mass spectrometry identified 55 out of 604 purified proteins with confirmed pupylation sites. Forty-four proteins, including those with and without identified pupylation sites, were tested as substrates of proteolysis in Mtb. Under steady state conditions, the majority of the test proteins did not accumulate in degradation mutants, suggesting not all targets of pupylation are necessarily substrates of the proteasome under steady state conditions. Four proteins implicated in Mtb pathogenesis, Icl (isocitrate lyase), Ino1 (inositol-1-phosphate synthase), MtrA (Mtb response regulator A) and PhoP (phosphate response regulator P), showed altered levels in degradation defective Mtb. Icl, Ino1 and MtrA accumulated in Mtb degradation mutants, suggesting these proteins are targeted to the proteasome. Unexpectedly, PhoP was present in wild type Mtb but undetectable in the degradation mutants. Taken together, these data demonstrate that pupylation regulates numerous proteins in Mtb and may not always lead to degradation.     

Dop functions as a depupylase in the prokaryotic ubiquitin‐like modification pathway

Post‐translational modification of proteins with prokaryotic ubiquitin‐like protein (Pup) is the bacterial equivalent of ubiquitination in eukaryotes. Mycobacterial pupylation is a two‐step process in which the carboxy‐terminal glutamine of Pup is first deamidated by Dop (deamidase of Pup) before ligation of the generated γ‐carboxylate to substrate lysines by the Pup ligase PafA. In this study, we identify a new feature of the pupylation system by demonstrating that Dop also acts as a depupylase in the Pup proteasome system in vivo and in vitro. Dop removes Pup from substrates by specific cleavage of the isopeptide bond. Depupylation can be enhanced by the unfolding activity of the mycobacterial proteasomal ATPase Mpa.     

Deletion of dop in Mycobacterium smegmatis abolishes pupylation of protein substrates in vivo

Proteasome‐bearing bacteria make use of a ubiquitin‐like modification pathway to target proteins for proteasomal turnover. In a process termed pupylation, proteasomal substrates are covalently modified with the small protein Pup that serves as a degradation signal. Pup is attached to substrate proteins by action of PafA. Prior to its attachment, Pup needs to undergo deamidation at its C‐terminal residue, converting glutamine to glutamate. This step is catalysed in vitro by Dop. In order to characterize Dop activity in vivo, we generated a dop deletion mutant in Mycobacterium smegmatis. In the Δdop strain, pupylation is severely impaired and the steady‐state levels of two known proteasomal substrates are drastically increased. Pupylation can be re‐established by complementing the mutant with either DopWt or a Pup variant carrying a glutamate at its ultimate C‐terminal position (PupGGE). Our data show that Pup is deamidated by Dop in vivo and that likely Dop alone is responsible for this activity. Furthermore, we demonstrate that a putative N‐terminal ATP‐binding motif is crucial for catalysis, as a single point mutation (E10A) in this motif abolishes Dop activity both in vivo and in vitro.     

Prokaryotic ubiquitin-like protein remains intrinsically disordered when covalently attached to proteasomal target proteins

Background

The post-translational modification pathway referred to as pupylation marks proteins for proteasomal degradation in Mycobacterium tuberculosis and other actinobacteria by covalently attaching the small protein Pup (prokaryotic ubiquitin-like protein) to target lysine residues. In contrast to the functionally analogous eukaryotic ubiquitin, Pup is intrinsically disordered in its free form. Its unfolded state allows Pup to adopt different structures upon interaction with different binding partners like the Pup ligase PafA and the proteasomal ATPase Mpa. While the disordered behavior of free Pup has been well characterized, it remained unknown whether Pup adopts a distinct structure when attached to a substrate.

Results

Using a combination of NMR experiments and biochemical analysis we demonstrate that Pup remains unstructured when ligated to two well-established pupylation substrates targeted for proteasomal degradation in Mycobacterium tuberculosis, malonyl transacylase (FabD) and ketopantoyl hydroxylmethyltransferase (PanB). Isotopically labeled Pup was linked to FabD and PanB by in vitro pupylation to generate homogeneously pupylated substrates suitable for NMR analysis. The single target lysine of PanB was identified by a combination of mass spectroscopy and mutational analysis. Chemical shift comparison between Pup in its free form and ligated to substrate reveals intrinsic disorder of Pup in the conjugate.

Conclusion

When linked to the proteasomal substrates FabD and PanB, Pup is unstructured and retains the ability to interact with its different binding partners. This suggests that it is not the conformation of Pup attached to these two substrates which determines their delivery to the proteasome, but the availability of the degradation complex and the depupylase.

     

Pupylated proteins in Corynebacterium glutamicum revealed by MudPIT analysis

In a manner similar to ubiquitin, the prokaryotic ubiquitin‐like protein (Pup) has been shown to target proteins for degradation via the proteasome in mycobacteria. However, not all actinobacteria possessing the Pup protein also contain a proteasome. In this study, we set out to study pupylation in the proteasome‐lacking non‐pathogenic model organism Corynebacterium glutamicum. A defined pup deletion mutant of C. glutamicum ATCC 13032 grew aerobically as the parent strain in standard glucose minimal medium, indicating that pupylation is dispensable under these conditions. After expression of a Pup derivative carrying an aminoterminal polyhistidine tag in the Δpup mutant and Ni²⁺‐chelate affinity chromatography, pupylated proteins were isolated. Multidimensional protein identification technology (MudPIT) and MALDI‐TOF‐MS/MS of the elution fraction unraveled 55 proteins being pupylated in C. glutamicum and 66 pupylation sites. Similar to mycobacteria, the majority of pupylated proteins are involved in metabolism or translation. Our results define the first pupylome of an actinobacterial species lacking a proteasome, confirming that other fates besides proteasomal degradation are possible for pupylated proteins.     

Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites

Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites through effector molecules. Owing to their significance in determining protein function, the identification of protein functional and regulatory binding sites is widely acknowledged as an important biological problem. In this work, we present a novel binding site prediction method, Active and Regulatory site Prediction (AR-Pred), which supplements protein geometry, evolutionary, and physicochemical features with information about protein dynamics to predict putative active and allosteric site residues. As the intrinsic dynamics of globular proteins plays an essential role in controlling binding events, we find it to be an important feature for the identification of protein binding sites. We train and validate our predictive models on multiple balanced training and validation sets with random forest machine learning and obtain an ensemble of discrete models for each prediction type. Our models for active site prediction yield a median area under the curve (AUC) of 91% and Matthews correlation coefficient (MCC) of 0.68, whereas the less well-defined allosteric sites are predicted at a lower level with a median AUC of 80% and MCC of 0.48. When tested on an independent set of proteins, our models for active site prediction show comparable performance to two existing methods and gains compared to two others, while the allosteric site models show gains when tested against three existing prediction methods. AR-Pred is available as a free downloadable package at https://github.com/sambitmishra0628/AR-PRED_source .     

The pupylation pathway and its role in mycobacteria

Pupylation is a post-translational protein modification occurring in actinobacteria through which the small, intrinsically disordered protein Pup (prokaryotic ubiquitin-like protein) is conjugated to lysine residues of proteins, marking them for proteasomal degradation. Although functionally related to ubiquitination, pupylation is carried out by different enzymes that are evolutionarily linked to bacterial carboxylate-amine ligases. Here, we compare the mechanism of Pup-conjugation to target proteins with ubiquitination, describe the evolutionary emergence of pupylation and discuss the importance of this pathway for survival of Mycobacterium tuberculosis in the host.     

Activity of the mycobacterial proteasomal ATPase Mpa is reversibly regulated by pupylation

Pupylation is a bacterial post-translational modification of target proteins on lysine residues with prokaryotic ubiquitin-like protein Pup. Pup-tagged substrates are recognized by a proteasome-interacting ATPase termed Mpa in Mycobacterium tuberculosis. Mpa unfolds pupylated substrates and threads them into the proteasome core particle for degradation. Interestingly, Mpa itself is also a pupylation target. Here, we show that the Pup ligase PafA predominantly produces monopupylated Mpa modified homogeneously on a single lysine residue within its C-terminal region. We demonstrate that this modification renders Mpa functionally inactive. Pupylated Mpa can no longer support Pup-mediated proteasomal degradation due to its inability to associate with the proteasome core. Mpa is further inactivated by rapid Pup- and ATPase-driven deoligomerization of the hexameric Mpa ring. We show that pupylation of Mpa is chemically and functionally reversible. Mpa regains its enzymatic activity upon depupylation by the depupylase Dop, affording a rapid and reversible activity control over Mpa function.     

Proteome-wide prediction of PKA phosphorylation sites in eukaryotic kingdom

Protein phosphorylation is one of the most essential post-translational modifications (PTMs), and orchestrates a variety of cellular functions and processes. Besides experimental studies, numerous computational predictors implemented in various algorithms have been developed for phosphorylation sites prediction. However, large-scale predictions of kinase-specific phosphorylation sites have not been successfully pursued and remained to be a great challenge. In this work, we raised a “kiss farewell” model and conducted a high-throughput prediction of cAMP-dependent kinase (PKA) phosphorylation sites. Since a protein kinase (PK) should at least “kiss” its substrates and then run away, we proposed a PKA-binding protein to be a potential PKA substrate if at least one PKA site was predicted. To improve the prediction specificity, we reduced false positive rate (FPR) less than 1% when the cut-off value was set as 4. Successfully, we predicted 1387, 630, 568 and 912 potential PKA sites from 410, 217, 173 and 260 PKA-interacting proteins in Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens, respectively. Most of these potential phosphorylation sites remained to be experimentally verified. In addition, we detected two sites in one of PKA regulatory subunits to be conserved in eukaryotes as potentially ancient regulatory signals. Our prediction results provide an excellent resource for delineating PKA-mediated signaling pathways and their system integration underlying cellular dynamics and plasticity.     

N-terminal N-myristoylation of proteins: prediction of substrate proteins from amino acid sequence

Myristoylation by the myristoyl-CoA:protein N-myristoyltransferase (NMT) is an important lipid anchor modification of eukaryotic and viral proteins. Automated prediction of N-terminal N-myristoylation from the substrate protein sequence alone is necessary for large-scale sequence annotation projects but it requires a low rate of false positive hits in addition to a sufficient sensitivity.Our previous analysis of substrate protein sequence variability, NMT sequences and 3D structures has revealed motif properties in addition to the known PROSITE motif that are utilized in a new predictor described here. The composite prediction function (with separate ad hoc parameterization (a) for queries from non-fungal eukaryotes and their viruses and (b) for sequences from fungal species) consists of terms evaluating amino acid type preferences at sequences positions close to the N terminus as well as terms penalizing deviations from the physical property pattern of amino acid side-chains encoded in multi-residue correlation within the motif sequence. The algorithm has been validated with a self-consistency and two jack-knife tests for the learning set as well as with kinetic data for model substrates. The sensitivity in recognizing documented NMT substrates is above 95 % for both taxon-specific versions. The corresponding rate of false positive prediction (for sequences with an N-terminal glycine residue) is close to 0.5 %; thus, the technique is applicable for large-scale automated sequence database annotation. The predictor is available as public WWW-server with the URL http://mendel.imp.univie.ac.at/myristate/. Additionally, we propose a version of the predictor that identifies a number of proteolytic protein processing sites at internal glycine residues and that evaluates possible N-terminal myristoylation of the protein fragments.A scan of public protein databases revealed new potential NMT targets for which the myristoyl modification may be of critical importance for biological function. Among others, the list includes kinases, phosphatases, proteasomal regulatory subunit 4, kinase interacting proteins KIP1/KIP2, protozoan flagellar proteins, homologues of mitochondrial translocase TOM40, of the neuronal calcium sensor NCS-1 and of the cytochrome c-type heme lyase CCHL. Analyses of complete eukaryote genomes indicate that about 0.5 % of all encoded proteins are apparent NMT substrates except for a higher fraction in Arabidopsis thaliana ( approximately 0.8 %).     

Pupylation as a signal for proteasomal degradation in bacteria

Posttranslational modifications in the form of covalently attached proteins like ubiquitin (Ub), were long considered an exclusive feature of eukaryotic organisms. The discovery of pupylation, the modification of lysine residues with a prokaryotic, ubiquitin-like protein (Pup), demonstrated that certain bacteria use a tagging pathway functionally related to ubiquitination in order to target proteins for proteasomal degradation. However, functional analogies do not translate into structural or mechanistic relatedness. Bacterial Pup, unlike eukaryotic Ub, does not adopt a β-grasp fold, but is intrinsically disordered. Furthermore, isopeptide bond formation in the pupylation process is carried out by enzymes evolutionary descendent from glutamine synthetases. While in eukaryotes, the proteasome is the main energy-dependent protein degradation machine, bacterial proteasomes exist in addition to other architecturally related degradation complexes, and their specific role along with the role of pupylation is still poorly understood. In Mycobacterium tuberculosis (Mtb), the Pup–proteasome system contributes to pathogenicity by supporting the bacterium's persistence within host macrophages. Here, we describe the mechanism and structural framework of pupylation and the targeting of pupylated proteins to the proteasome complex. Particular attention is given to the comparison of the bacterial Pup–proteasome system and the eukaryotic ubiquitin–proteasome system. Furthermore, the involvement of pupylation and proteasomal degradation in Mtb pathogenesis is discussed together with efforts to establish the Pup–proteasome system as a drug target. This article is part of a Special Issue entitled: Ubiquitin–Proteasome System. Guest Editors: Thomas Sommer and Dieter H. Wolf.     

GPS-CCD: a novel computational program for the prediction of calpain cleavage sites

As one of the most essential post-translational modifications (PTMs) of proteins, proteolysis, especially calpain-mediated cleavage, plays an important role in many biological processes, including cell death/apoptosis, cytoskeletal remodeling, and the cell cycle. Experimental identification of calpain targets with bona fide cleavage sites is fundamental for dissecting the molecular mechanisms and biological roles of calpain cleavage. In contrast to time-consuming and labor-intensive experimental approaches, computational prediction of calpain cleavage sites might more cheaply and readily provide useful information for further experimental investigation. In this work, we constructed a novel software package of GPS-CCD (Calpain Cleavage Detector) for the prediction of calpain cleavage sites, with an accuracy of 89.98%, sensitivity of 60.87% and specificity of 90.07%. With this software, we annotated potential calpain cleavage sites for hundreds of calpain substrates, for which the exact cleavage sites had not been previously determined. In this regard, GPS-CCD 1.0 is considered to be a useful tool for experimentalists. The online service and local packages of GPS-CCD 1.0 were implemented in JAVA and are freely available at: http://ccd.biocuckoo.org/.     

GPS-ARM: computational analysis of the APC/C recognition motif by predicting D-boxes and KEN-boxes

Anaphase-promoting complex/cyclosome (APC/C), an E3 ubiquitin ligase incorporated with Cdh1 and/or Cdc20 recognizes and interacts with specific substrates, and faithfully orchestrates the proper cell cycle events by targeting proteins for proteasomal degradation. Experimental identification of APC/C substrates is largely dependent on the discovery of APC/C recognition motifs, e.g., the D-box and KEN-box. Although a number of either stringent or loosely defined motifs proposed, these motif patterns are only of limited use due to their insufficient powers of prediction. We report the development of a novel GPS-ARM software package which is useful for the prediction of D-boxes and KEN-boxes in proteins. Using experimentally identified D-boxes and KEN-boxes as the training data sets, a previously developed GPS (Group-based Prediction System) algorithm was adopted. By extensive evaluation and comparison, the GPS-ARM performance was found to be much better than the one using simple motifs. With this powerful tool, we predicted 4,841 potential D-boxes in 3,832 proteins and 1,632 potential KEN-boxes in 1,403 proteins from H. sapiens, while further statistical analysis suggested that both the D-box and KEN-box proteins are involved in a broad spectrum of biological processes beyond the cell cycle. In addition, with the co-localization information, we predicted hundreds of mitosis-specific APC/C substrates with high confidence. As the first computational tool for the prediction of APC/C-mediated degradation, GPS-ARM is a useful tool for information to be used in further experimental investigations. The GPS-ARM is freely accessible for academic researchers at: http://arm.biocuckoo.org.     

Proteomic screening for Rho-kinase substrates by combining kinase and phosphatase inhibitors with 14-3-3ζ affinity chromatography

The small GTPase RhoA is a molecular switch in various extracellular signals. Rho-kinase/ROCK/ROK, a major effector of RhoA, regulates diverse cellular functions by phosphorylating cytoskeletal proteins, endocytic proteins, and polarity proteins. More than twenty Rho-kinase substrates have been reported, but the known substrates do not fully explain the Rho-kinase functions. Herein, we describe the comprehensive screening for Rho-kinase substrates by treating HeLa cells with Rho-kinase and phosphatase inhibitors. The cell lysates containing the phosphorylated substrates were then subjected to affinity chromatography using beads coated with 14-3-3 protein, which interacts with proteins containing phosphorylated serine or threonine residues, to enrich the phosphorylated proteins. The identities of the molecules and phosphorylation sites were determined by liquid chromatography tandem mass spectrometry (LC/MS/MS) after tryptic digestion and phosphopeptide enrichment. The phosphorylated proteins whose phosphopeptide ion peaks were suppressed by treatment with the Rho-kinase inhibitor were regarded as candidate substrates. We identified 121 proteins as candidate substrates. We also identified phosphorylation sites in Partitioning defective 3 homolog (Par-3) at Ser143 and Ser144. We found that Rho-kinase phosphorylated Par-3 at Ser144 both in vitro and in vivo. The method used in this study would be applicable and useful to identify novel substrates of other kinases.     

Interactions in native binding sites cause a large change in protein dynamics

Cellular functions are regulated by molecules that interact with proteins and alter their activities. To enable such control, protein activity, and therefore protein conformational distributions, must be susceptible to alteration by molecular interactions at functional sites. Here we investigate whether interactions at functional sites cause a large change in the protein conformational distribution. We apply a computational method, called dynamics perturbation analysis (DPA), to identify sites at which interactions have a large allosteric potential D(x), which is the Kullback-Leibler divergence between protein conformational distributions with and without an interaction. In DPA, a protein is decorated with surface points that interact with neighboring protein atoms, and D(x) is calculated for each of the points in a coarse-grained model of protein vibrations. We use DPA to examine hundreds of protein structures from a standard small-molecule docking test set, and find that ligand-binding sites have elevated values of D(x): for 95% of proteins, the probability of randomly obtaining values as high as those in the binding site is 10(-3) or smaller. We then use DPA to develop a computational method to predict functional sites in proteins, and find that the method accurately predicts ligand-binding-site residues for proteins in the test set. The performance of this method compares favorably with that of a cleft analysis method. The results confirm that interactions at small-molecule binding sites cause a large change in the protein conformational distribution, and motivate using DPA for large-scale prediction of functional sites in proteins. They also suggest that natural selection favors proteins whose activities are capable of being regulated by molecular interactions.