Unveiling Protein Functions through the Dynamics of the Interaction Network

Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes

Cysteine String Protein Functions Directly in Regulated Exocytosis

Cysteine string protein (Csp) is essential for neurotransmitter release in Drosophila. It has been suggested that Csp functions by regulating the activity of presynaptic Ca2+ channels, thus controlling exocytosis. We have examined the effect of overexpressing Csp1 in PC12 cells, a neuroendocrine cell line. PC12 cell clones overexpressing Csp1 did not show any changes in morphology, granule number or distribution, or in the levels of other key exocytotic proteins. This overexpression did not affect intracellular Ca2+ signals after depolarization, suggesting that Csp1 has no gross effect on Ca2+ channel activity in PC12 cells. In contrast, we show that Csp1 overexpression enhances the extent of exocytosis from permeabilized cells in response to Ca2+ or GTPγS in the absence of Ca2+. Because secretion from permeabilized cells is not influenced by Ca2+ channel activity, this represents the first demonstration that Csp has a direct role in regulated exocytosis.

Nutritional regulation of the fatty acid synthase promoter in vivo: Sterol regulatory element binding protein functions through an upstream region containing a sterol regulatory element

The transcription of fatty acid synthase (FAS), a central enzyme in de novo lipogenesis, is dramatically induced by fasting/refeeding and insulin. We reported that upstream stimulatory factor binding to the −65 E-box is required for induction of the FAS transcription by insulin in 3T3-L1 adipocytes. On the other hand, we recently found that two upstream 5′ regions are required for induction in vivo by fasting/refeeding and insulin; one at −278 to −131 albeit at a low level, and the other at −444 to −278 with an E-box at −332 where upstream stimulatory factor functions for maximal induction. Here, we generated double transgenic mice carrying the chloramphenicol acetyltransferase reporter driven by the various 5′ deletions of the FAS promoter region and a truncated active form of the sterol regulatory element (SRE) binding protein (SREBP)-1a. We found that SREBP participates in the nutritional regulation of the FAS promoter and that the region between −278 and −131 bp is required for SREBP function. We demonstrate that SREBP binds the −150 canonical SRE present between −278 and −131, and SREBP can function through the −150 SRE in cultured cells. These in vivo and in vitro results indicate that SREBP is involved in the nutritional induction of the FAS promoter via the −278/−131 region and that the −150 SRE is the target sequence.

Mso1p: A yeast protein that functions in secretion and interacts physically and genetically with Sec1p

The yeast Sec1p protein functions in the docking of secretory transport vesicles to the plasma membrane. We previously have cloned two yeast genes encoding syntaxins, SSO1 and SSO2, as suppressors of the temperature-sensitive sec1–1 mutation. We now describe a third suppressor of sec1–1, which we call MSO1. Unlike SSO1 and SSO2, MSO1 is specific for sec1 and does not suppress mutations in any other SEC genes. MSO1 encodes a small hydrophilic protein that is enriched in a microsomal membrane fraction. Cells that lack MSO1 are viable, but they accumulate secretory vesicles in the bud, indicating that the terminal step in secretion is partially impaired. Moreover, loss of MSO1 shows synthetic lethality with mutations in SEC1, SEC2, and SEC4, and other synthetic phenotypes with mutations in several other late-acting SEC genes. We further found that Mso1p interacts with Sec1p both in vitro and in the two-hybrid system. These findings suggest that Mso1p is a component of the secretory vesicle docking complex whose function is closely associated with that of Sec1p.

The implications of alternative splicing in the ENCODE protein complement.

Alternative premessenger RNA splicing enables genes to generate more than one gene product. Splicing events that occur within protein coding regions have the potential to alter the biological function of the expressed protein and even to create new protein functions. Alternative splicing has been suggested as one explanation for the discrepancy between the number of human genes and functional complexity. Here, we carry out a detailed study of the alternatively spliced gene products annotated in the ENCODE pilot project. We find that alternative splicing in human genes is more frequent than has commonly been suggested, and we demonstrate that many of the potential alternative gene products will have markedly different structure and function from their constitutively spliced counterparts. For the vast majority of these alternative isoforms, little evidence exists to suggest they have a role as functional proteins, and it seems unlikely that the spectrum of conventional enzymatic or structural functions can be substantially extended through alternative splicing.

Glial fibrillary acidic protein (GFAP): modulation by growth factors and its implication in astrocyte differentiation

Intermediate filament (IF) proteins constitute an extremely large multigene family of developmentally and tissue-regulated cytoskeleton proteins abundant in most vertebrate cell types. Astrocyte precursors of the CNS usually express vimentin as the major IF. Astrocyte maturation is followed by a switch between vimentin and glial fibrillary acidic protein (GFAP) expression, with the latter being recognized as an astrocyte maturation marker. Levels of GFAP are regulated under developmental and pathological conditions. Upregulation of GFAP expression is one of the main characteristics of the astrocytic reaction commonly observed after CNS lesion. In this way, studies on GFAP regulation have been shown to be useful to understand not only brain physiology but also neurological disease. Modulators of GFAP expression include several hormones such as thyroid hormone, glucocorticoids and several growth factors such as FGF, CNTF and TGFß, among others. Studies of the GFAP gene have already identified several putative growth factor binding domains in its promoter region. Data obtained from transgenic and knockout mice have provided new insights into IF protein functions. This review highlights the most recent studies on the regulation of IF function by growth factors and hormones.

A structural analysis of M protein in coronavirus assembly and morphology

The M protein of coronavirus plays a central role in virus assembly, turning cellular membranes into workshops where virus and host factors come together to make new virus particles. We investigated how M structure and organization is related to virus shape and size using cryo-electron microscopy, tomography and statistical analysis. We present evidence that suggests M can adopt two conformations and that membrane curvature is regulated by one M conformer. Elongated M protein is associated with rigidity, clusters of spikes and a relatively narrow range of membrane curvature. In contrast, compact M protein is associated with flexibility and low spike density. Analysis of several types of virus-like particles and virions revealed that S protein, N protein and genomic RNA each help to regulate virion size and variation, presumably through interactions with M. These findings provide insight into how M protein functions to promote virus assembly.

Automatic classification of enzyme family in protein annotation

Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

In vitro properties of the first ORF protein from mouse LINE-1 support its role in ribonucleoprotein particle formation during retrotransposition

LINEs are transposable elements, widely distributed among eukaryotes, that move via reverse transcription of an RNA intermediate. Mammalian LINEs have two ORFs (ORF1 and ORF2). The proteins encoded by these ORFs play important roles in the retrotransposition process. Although the predicted amino acid sequence of ORF1 is not closely related to any known proteins, it is highly basic; thus, it has long been hypothesized that ORF1 protein functions to bind LINE-1 (L1) RNA during retrotransposition. Cofractionation of ORF1 protein and L1 RNA in extracts from both mouse and human embryonal carcinoma cells indicated that ORF1 protein binds L1 RNA, forming a ribonucleoprotein particle. Based on UV crosslinking and electrophoretic mobility-shift assays using purified components, we demonstrate here that the ORF1 protein encoded by mouse L1 binds nucleic acids with a strong preference for RNA and other single-stranded nucleic acids. Furthermore, multiple copies of ORF1 protein appear to bind single-stranded nucleic acid in a manner suggesting positive cooperativity; such binding characteristics are likely to be facilitated by the protein–protein interactions detected among molecules of ORF1 polypeptide by coimmunoprecipitation. These observations are consistent with the formation of ribonucleoprotein particles containing L1 RNA and ORF1 protein and provide additional evidence for the role of ORF1 protein during retrotransposition of L1.

Interaction between the phage HK022 Nun protein and the nut RNA of phage lambda.

The nun gene product of prophage HK022 excludes phage lambda infection by blocking the expression of genes downstream from the lambda nut sequence. The Nun protein functions both by competing with lambda N transcription-antitermination protein and by actively inducing transcription termination on the lambda chromosome. We demonstrate that Nun binds directly to a stem-loop structure within nut RNA, boxB, which is also the target for the N antiterminator. The two proteins show comparable affinities for boxB and they compete with each other. Their interactions with boxB are similar, as shown by RNase protection experiments, NMR spectroscopy, and analysis of boxB mutants. Each protein binds the 5' strand of the boxB stem and the adjacent loop. The stem does not melt upon the binding of Nun or N, as the 3' strand remains sensitive to a double-strand-specific RNase. The binding of RNA partially protects Nun from proteolysis and changes its NMR spectra. Evidently, although Nun and N bind to the same surface of boxB RNA, their respective complexes interact differently with RNA polymerase, inducing transcription termination or antitermination, respectively.

Development and Application of Covalent-Labeling Strategies for the Large-Scale Thermodynamic Analysis of Protein Folding and Ligand Binding

Thermodynamic stability measurements on proteins and protein-ligand complexes can offer insights not only into the fundamental properties of protein folding reactions and protein functions, but also into the development of protein-directed therapeutic agents to combat disease. Conventional calorimetric or spectroscopic approaches for measuring protein stability typically require large amounts of purified protein. This requirement has precluded their use in proteomic applications. Stability of Proteins from Rates of Oxidation (SPROX) is a recently developed mass spectrometry-based approach for proteome-wide thermodynamic stability analysis. Since the proteomic coverage of SPROX is fundamentally limited by the detection of methionine-containing peptides, the use of tryptophan-containing peptides was investigated in this dissertation. A new SPROX-like protocol was developed that measured protein folding free energies using the denaturant dependence of the rate at which globally protected tryptophan and methionine residues are modified with dimethyl (2-hydroxyl-5-nitrobenzyl) sulfonium bromide and hydrogen peroxide, respectively. This so-called Hybrid protocol was applied to proteins in yeast and MCF-7 cell lysates and achieved a ~50% increase in proteomic coverage compared to probing only methionine-containing peptides. Subsequently, the Hybrid protocol was successfully utilized to identify and quantify both known and novel protein-ligand interactions in cell lysates. The ligands under study included the well-known Hsp90 inhibitor geldanamycin and the less well-understood omeprazole sulfide that inhibits liver-stage malaria. In addition to protein-small molecule interactions, protein-protein interactions involving Puf6 were investigated using the SPROX technique in comparative thermodynamic analyses performed on wild-type and Puf6-deletion yeast strains. A total of 39 proteins were detected as Puf6 targets and 36 of these targets were previously unknown to interact with Puf6. Finally, to facilitate the SPROX/Hybrid data analysis process and minimize human errors, a Bayesian algorithm was developed for transition midpoint assignment. In summary, the work in this dissertation expanded the scope of SPROX and evaluated the use of SPROX/Hybrid protocols for characterizing protein-ligand interactions in complex biological mixtures.

Prediction of Phosphorylation Sites from Protein Sequences

Phosphorylation is amongst the most crucial and well-studied post-translational modifications. It is involved in multiple cellular processes which makes phosphorylation prediction vital for understanding protein functions. However, wet-lab techniques are labour and time intensive. Thus, computational tools are required for efficiency. This project aims to provide a novel way to predict phosphorylation sites from protein sequences by adding flexibility and Sezerman Grouping amino acid similarity measure to previous methods, as discovering new protein sequences happens at a greater rate than determining protein structures. The predictor – NOPAY - relies on Support Vector Machines (SVMs) for classification. The features include amino acid encoding, amino acid grouping, predicted secondary structure, predicted protein disorder, predicted protein flexibility, solvent accessibility, hydrophobicity and volume. As a result, we have managed to improve phosphorylation prediction accuracy for Homo sapiens by 3% and 6.1% for Mus musculus. Sensitivity at 99% specificity was also increased by 6% for Homo sapiens and for Mus musculus by 5% on independent test sets. In this study, we have managed to increase phosphorylation prediction accuracy for Homo sapiens and Mus musculus. When there is enough data, future versions of the software may also be able to predict other organisms.

Papillomavirus research update: highlights of the Barcelona HPV 2000 international papillomavirus conference

The 18th international papillomavirus conference took place in Barcelona, Spain in July 2000. The HPV clinical workshop was jointly organised with the annual meeting of the Spanish Association of Cervical Pathology and Colposcopy. The conference included 615 abstracts describing ongoing research in epidemiology, diagnosis/screening, treatment/prognosis, immunology/human immunodeficiency virus, vaccine development/trials, transformation/progression, replication, transcription/translation, viral protein functions, and viral and host interactions. This leader summarises the highlights presented at the conference (the full text of the abstracts and lectures can be found at www.hpv2000.com). Relevant material in Spanish can be found at www.aepcc. org.

Five new CYLD mutations in skin appendage tumors and evidence that aspartic acid 681 in CYLD is essential for deubiquitinase activity.

Brooke-Spiegler syndrome, familial cylindromatosis, and familial trichoepithelioma are autosomal-dominant genetic predispositions for benign tumors of skin appendages caused by mutations in the CYLD gene localized on chromosome 16q12-q13. The encoded protein functions as ubiquitin-specific protease (UBP), which negatively regulates NF-kappaB and c-Jun N-terminal kinase (JNK) signaling. We investigated five families affected with these skin neoplasms and identified four premature stop codons and the novel missense mutation D681G in a family in which 11 of 12 investigated tumors were trichoepitheliomas. CYLD protein harboring this missense mutation had a significant reduced ability to inhibit TNF receptor-associated factor (TRAF)2- and TRAF6-mediated NF-kappaB activation, tumor necrosis factor-alpha (TNFalpha)-induced JNK signaling, and to deubiquitinate TRAF2. CYLD-D681G was coimmunoprecipitated by TRAF2, but was unable to cleave K63-linked polyubiquitin chains. Aspartic acid 681 is highly conserved in CYLD homologues and other members of the UBP family, but does not belong to the Cys and His boxes providing the CYLD catalytic triad (Cys601, His871, and Asp889). As reported previously, the homologous residue D295 of HAUSP/USP-7 forms a hydrogen bond with the C-terminal end of ubiquitin and is important for the enzymatic activity. These results underline that D681 in CYLD is required for cleavage of K63-linked polyubiquitin chains.