A prophenoloxidase from the Chinese mitten crab Eriocheir sinensis: Gene cloning, expression and activity analysis

Prophenoloxidase (proPO) is a conserved copper-containing enzyme that plays important roles in immune response of crustaceans and insects. In the present study, the full-length cDNA of a prophenoloxidase (designated EsproPO) was cloned from haemocytes of Chinese mitten crab Eriocheir sinensis by expressed sequence tag (EST) and PCR techniques. The isolated 3549 bp full-length cDNA of EsproPO contained a 2040 bp open reading frame (ORF) encoding a putative proPO protein of 679 amino acids, a 5'-untranslated region (UTR) of 68 bp, and a long 3'-UTR of 1441 bp. Two putative copper-binding sites, a proteolytic activation site, and a complement-like motif (GCGWPQHM) were identified in the deduced amino acid sequence of EsproPO. Homology analysis revealed that EsproPO was highly similar to other proPOs from crustaceans with identities from 52% to 68%. The conserved domains and motifs, and higher similarity with other proPOs suggested that EsproPO was a member of the proPO family. The mRNA expression of EsproPO and PO specific activities in the tissues of hepatopancreas, gill, gonad, muscle, heart, eye and haemocytes were measured by quantitative real-time PCR and colorimetric assay, respectively. The mRNA transcripts of EsproPO and PO specific activities could be detected in all the examined tissues with the highest level both in hepatopancreas. Three peaks of EsproPO mRNA expression were recorded at 2 h, 12 h and 48 h in haemocytes of Chinese mitten crab post Vibrio anguillarum challenge, which was consistent with the temporal profile of PO specific activity. The mRNA expression pattern and the activity fluctuation of EsproPO post V. anguillarum stimulation indicated that it was potentially involved in the acute response against invading bacteria in Chinese mitten crab. (c) 2007 Elsevier Ltd. All rights reserved.

Drug-protein interaction studied by technique of microdialysis combined with high performance liquid chromatography

Drug-protein binding is an important process in determining the activity and fate of a pharmaceutical agent once it has entered the body. This review examines the method of microdialysis combined with high-performance liquid chromatography (HPLC) that has been developed;by ours to study such interactions, in which the microdialysis was applied to sample the free drug in the mixed solution of drug with protein, and HPLC to quantify the concentration of free drug in the microdialysate. This technique has successfully been used for determining various types of binding interactions between the low affinity drugs, high affinity drugs and enantiomers to HSA. For the case of competitive binding of two drugs to a protein in solution, a displacement equation has been derived and examined with four nonsteroidal anti-inflammatory drugs and HSA as model drugs and protein, respectively. Microdialysis with HPLC was adopted to determine simultaneously the free solute and displacing agent in drug-protein solutions. The method is able to locate the binding site and determine affinity constants even up to 10(7) L/mol accurately.

Integration of relational and hierarchical network information for protein function prediction

BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

Platinum resistant cancer cells conserve sensitivity to BH3 domains and obatoclax induced mitochondrial apoptosis

Resistance to cisplatin chemotherapy remains a major hurdle preventing effective treatment of many solid cancers. BAX and BAK are pivotal regulators of the mitochondrial apoptosis pathway, however little is known regarding their regulation in cisplatin resistant cells. Cisplatin induces DNA damage in both sensitive and resistant cells, however the latter exhibits a failure to initiate N-terminal exposure of mitochondrial BAK or mitochondrial SMAC release. Both phenotypes are highly sensitive to mitochondrial permeabilisation induced by exogenous BH3 domain peptides derived from BID, BIM, NOXA (which targets MCL-1 and A1), and there is no significant change in their prosurvival BCL2 protein expression profiles. Obatoclax, a small molecule inhibitor of pro-survival BCL-2 family proteins including MCL-1, decreases cell viability irrespective of platinum resistance status across a panel of cell lines selected for oxaliplatin resistance. In summary, selection for platinum resistance is associated with a block of mitochondrial death signalling upstream of BAX/BAK activation. Conservation of sensitivity to BH3 domain induced apoptosis can be exploited by agents such as obatoclax, which directly target the mitochondria and BCL-2 family.

Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that these models are lacking crucial structural features present in protein interaction networks on a mesoscopic scale. This observation reveals our incomplete understanding of the structural evolution of protein networks on the module level. © 2012 Emmert-Streib.

Complement factor H is a serum-binding protein for adrenomedullin, and the resulting complex modulates the bioactivities of both partners

Adrenomedullin (AM) is an important regulatory peptide involved in both physiological and pathological states. We have previously demonstrated the existence of a specific AM-binding protein (AMBP-1) in human plasma. In the present study, we developed a nonradioactive ligand blotting assay, which, together with high pressure liquid chromatography/SDS-polyacrylamide gel electrophoresis purification techniques, allowed us to isolate AMBP-1 to homogeneity. The purified protein was identified as human complement factor H. We show that AM/factor H interaction interferes with the established methodology for quantification of circulating AM. Our data suggest that this routine procedure does not take into account the AM bound to its binding protein. In addition, we show that factor H affects AM in vitro functions. It enhances AM-mediated induction of cAMP in fibroblasts, augments the AM-mediated growth of a cancer cell line, and suppresses the bactericidal capability of AM on Escherichia coli. Reciprocally, AM influences the complement regulatory function of factor H by enhancing the cleavage of C3b via factor I. In summary, we report on a potentially new regulatory mechanism of AM biology, the influence of factor H on radioimmunoassay quantification of AM, and the possible involvement of AM as a regulator of the complement cascade.

Association Study of 167 Candidate Genes for Schizophrenia Selected by a Multi-Domain Evidence-Based Prioritization Algorithm and Neurodevelopmental Hypothesis

Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n = 3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this
ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

Mitotic Arrest Deficiency Protein 2 (MAD2) and Histone Deacetylase 6 (HDAC6) Present a Complex Relationship in Their Regulation and Expression and Subsequent Impact on Chemoresponsiveness

Introduction:
Ovarian cancer patients presenting with advanced stage (III/IV)
canceraretreatedwithcarboplatinumincombinationwithpaclitaxel.Despitea
significant initial response rate, fewer than 20% of patients become long-term
survivors. We have published that low MAD2 expression levels associate with
reduced progression free survival (PFS) in patients with high-grade serous
epithelial ovarian cancer (EOC). Moreover, we have demonstrated that MAD2
expressionisdown-regulatedbythemicroRNAmiR-433(
Furlong et al., 2011
).
Interestingly, miR-433 also down-regulates HDAC6 (
Simon et al., 2010
), which
uniquely deacetylates
a
-tubulin prior to HDAC6s binding to
b
-tubulin.
In vitro
studies have shown that HDAC6 inhibition in combination with paclitaxel
treatment enhances chemoresistant cancer cell death. To date, an interaction
between MAD2 and HDAC6 has not been reported.
Experimental design:
MAD2 and HDAC6 immunohistochemistry (IHC) and
Western blot analyses were performed to investigate the role of HDAC6 and
MAD2 in chemoresistance to paclitaxel in high-grade serous EOC.
Results and Discussion:
In vitro
experiments demonstrated that overex-
pression of pre-miR-433, which targets MAD2, resulted in down-regulation
of HDAC6 in EOC cell lines. High levels of HDAC6 are co-expressed with
MAD2 in the paclitaxel resistant UPN251 and OVCAR7 cell lines. While, all
4 paclitaxel resistant EOC cell lines express higher levels of miR-433 than
the paclitaxel sensitive A2780 cells, only ovca432 and ovca433 demonstrated
down-regulation of both HDAC6 and MAD2. Paclitaxel binds to
b
-tubulin and
causesmicrotubulepolymerizationinpaclitaxelsensitivecellsasdemonstrated
by tubulin acetylation in A2780 cells. However, paclitaxel failed to cause a
significant acetylation of
a
-tubulin and microtubule stabilisation in the resistant
UPN251 cells. Therefore resistance in this cell line may be mediated by
aberrantly high HDAC6 activity. We have previously shown that MAD2 knock-
down cells are resistant to paclitaxel (
Furlong F., et al., 2011; Prencipe M.,
et al., 2009
). We measured HDAC6 protein expression in MAD2 knockdown
cells and showed that MAD2 knockdown is associated with concomitant
up-regulation of HDAC6. We hypothesise that the up-regulation of HDAC6
by MAD2 knockdown renders cancer cells more resistant to paclitaxel and
increases the invasive potential of these cells. On-going experiments will test
this hypothesis. Lastly we have observed differential MAD2 and HDAC6 IHC
staining intensity in formalin fixed paraffin embedded EOC samples.
In conclusion
, we have reported on a novel interaction between MAD2 and
HDAC6 which may have important consequences for paclitaxel resistant EOC.
Moreover, understanding chemo-responsiveness in ovarian tumours will lead
to improved patient management and treatment options for women diagnosed
with this disease

DED or alive: assembly and regulation of the death effector domain complexes.

Death effector domains (DEDs) are protein-protein interaction domains initially identified in proteins such as FADD, FLIP and caspase-8 involved in regulating apoptosis. Subsequently, these proteins have been shown to have important roles in regulating other forms of cell death, including necroptosis, and in regulating other important cellular processes, including autophagy and inflammation. Moreover, these proteins also have prominent roles in innate and adaptive immunity and during embryonic development. In this article, we review the various roles of DED-containing proteins and discuss recent developments in our understanding of DED complex formation and regulation. We also briefly discuss opportunities to therapeutically target DED complex formation in diseases such as cancer.

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium.

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.

Mechanisms of G protein activation via the D-2 dopamine receptor: evidence for persistent receptor/G protein interaction after agonist stimulation

Background and purpose: The aim of this report is to study mechanisms of G protein activation by agonists. Experimental approach: The association and dissociation of guanosine 5'-O-(3-[S-35] thio) triphosphate ([S-35] GTP gamma S) binding at G proteins in membranes of CHO cells stably transfected with the human dopamine D-2short receptor was studied in the presence of a range of agonists. Key results: Binding of [S-35] GTPgS was dissociable in the absence of agonist and dissociation was accelerated both in rate and extent by dopamine, an effect which was blocked by the dopamine D-2 receptor antagonist raclopride and by suramin, which inhibits receptor/G protein interaction. A range of agonists of varying efficacy increased the rate of dissociation of [S-35] GTPgS binding, with the more efficacious agonists resulting in faster dissociation. Agonists were able to dissociate about 70% of the pre-bound [S-35] GTPgS, leaving a component which may not be accessible to the agonist-bound receptor. The dissociable component of the [S-35] GTPgS binding was reduced with longer association times and increased [S-35] GTPgS concentrations. Conclusions and implications: These data are consistent with [S-35] GTPgS binding being initially to receptor-linked G proteins and then to G proteins which have separated from the agonist bound receptor. Under the conditions used typically for [S-35] GTPgS binding assays, therefore, much of the agonist-receptor complex remains in proximity to G proteins after they have been activated by agonist.

Role of alpha 7 Nicotinic Acetylcholine Receptor in Calcium Signaling Induced by Prion Protein Interaction with Stress-inducible Protein 1

The prion protein (PrP(C)) is a conserved glycosylphosphatidyl-inositol-anchored cell surface protein expressed by neurons and other cells. Stress-inducible protein 1 (STI1) binds PrP(C) extracellularly, and this activated signaling complex promotes neuronal differentiation and neuroprotection via the extracellular signal-regulated kinase 1 and 2 (ERK1/2) and cAMP-dependent protein kinase 1 (PKA) pathways. However, the mechanism by which the PrPC-STI1 interaction transduces extracellular signals to the intracellular environment is unknown. We found that in hippocampal neurons, STI1-PrP(C) engagement induces an increase in intracellular Ca(2+) levels. This effect was not detected in PrP(C)-null neurons or wild-type neurons treated with an STI1 mutant unable to bind PrP(C). Using a best candidate approach to test for potential channels involved in Ca(2+) influx evoked by STI1-PrP(C), we found that alpha-bungarotoxin, a specific inhibitor for alpha 7 nicotinic acetylcholine receptor (alpha 7nAChR), was able to block PrP(C)-STI1-mediated signaling, neuroprotection, and neuritogenesis. Importantly, when alpha 7nAChR was transfected into HEK 293 cells, it formed a functional complex with PrP(C) and allowed reconstitution of signaling by PrP(C)-STI1 interaction. These results indicate that STI1 can interact with the PrP(C).alpha 7nAChR complex to promote signaling and provide a novel potential target for modulation of the effects of prion protein in neurodegenerative diseases.

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

Sdo1p, the yeast orthologue of Shwachman-Bodian-Diamond syndrome protein, binds RNA and interacts with nuclear rRNA-processing factors

The Shwachman-Bodian-Diamond syndrome protein (SBDS) is a member of a highly conserved protein family of not well understood function, with putative orthologues found in different organisms ranging from Archaea, yeast and plants to vertebrate animals. The yeast orthologue of SBDS, Sdo1p, has been previously identified in association with the 60S ribosomal subunit and is proposed to participate in ribosomal recycling. Here we show that Sdo1p interacts with nucleolar rRNA processing factors and ribosomal proteins, indicating that it might bind the pre-60S complex and remain associated with it during processing and transport to the cytoplasm. Corroborating the protein interaction data, Sdo1p localizes to the nucleus and cytoplasm and co-immunoprecipitates precursors of 60S and 40S subunits, as well as the mature rRNAs. Sdo1p binds RNA directly, suggesting that it may associate with the ribosomal subunits also through RNA interaction. Copyright (C) 2009 John Wiley & Sons, Ltd.

High functional coherence in k-partite protein cliques of protein interaction networks

We introduce a new topological concept called k-partite protein cliques to study protein interaction (PPI) networks. In particular, we examine functional coherence of proteins in k-partite protein cliques. A k-partite protein clique is a k-partite maximal clique comprising two or more nonoverlapping protein subsets between any two of which full interactions are exhibited. In the detection of PPI’s k-partite maximal cliques, we propose to transform PPI networks into induced K-partite graphs with proteins as vertices where edges only exist among the graph’s partites. Then, we present a k-partite maximal clique mining (MaCMik) algorithm to enumerate k-partite maximal cliques from K-partite graphs. Our MaCMik algorithm is applied to a yeast PPI network. We observe that there does exist interesting and unusually high functional coherence in k-partite protein cliques—most proteins in k-partite protein cliques, especially those in the same partites, share the same functions. Therefore, the idea of k-partite protein cliques suggests a novel approach to characterizing PPI networks, and may help function prediction for unknown proteins.