Cystatin B and SOD1: Protein–Protein Interaction and Possible Relation to Neurodegeneration

Cystatin B (CSTB), an inhibitor of the cysteine proteases, belongs to the cathepsin family and it is known to interact with a number of proteins involved in cytoskeletal organization. CSTB has an intrinsic tendency to form aggregates depending on the redox environment. The gene encoding for CSTB is frequently mutated in association with the rare neurodegenerative condition progressive myoclonus epilepsy. Increased levels of CSTB have been observed in the spinal cord of transgenic mice modeling SOD1-linked familial amyotrophic lateral sclerosis, a fatal neurodegenerative disease affecting motoneurons. In the present study, we have investigated the relationship occurring between the expression of SOD1 and CSTB either wild-type or double-cysteine substitution mutant (Cys 3 and Cys 64). Whether or not there is a physical interaction between the two proteins was also investigated in overexpression experiments using a human neuroblastoma cell line and mouse-immortalized motoneurons. Here we report evidences for a reciprocal influence of CSTB and SOD1 at the gene expression level and for a direct interaction of the two proteins.     

Protein–Protein and Protein–Membrane Associations in the Lignin Pathway

Supramolecular organization of enzymes is proposed to orchestrate metabolic complexity and help channel intermediates in different pathways. Phenylpropanoid metabolism has to direct up to 30% of the carbon fixed by plants to the biosynthesis of lignin precursors. Effective coupling of the enzymes in the pathway thus seems to be required. Subcellular localization, mobility, protein–protein, and protein–membrane interactions of four consecutive enzymes around the main branch point leading to lignin precursors was investigated in leaf tissues of Nicotiana benthamiana and cells of Arabidopsis thaliana. CYP73A5 and CYP98A3, the two Arabidopsis cytochrome P450s (P450s) catalyzing para- and meta-hydroxylations of the phenolic ring of monolignols were found to colocalize in the endoplasmic reticulum (ER) and to form homo- and heteromers. They moved along with the fast remodeling plant ER, but their lateral diffusion on the ER surface was restricted, likely due to association with other ER proteins. The connecting soluble enzyme hydroxycinnamoyltransferase (HCT), was found partially associated with the ER. Both HCT and the 4-coumaroyl-CoA ligase relocalized closer to the membrane upon P450 expression. Fluorescence lifetime imaging microscopy supports P450 colocalization and interaction with the soluble proteins, enhanced by the expression of the partner proteins. Protein relocalization was further enhanced in tissues undergoing wound repair. CYP98A3 was the most effective in driving protein association.     

Protein–Protein Docking: Past,Present, and Future

The Protein Journal - The biological significance of proteins attracted the scientific community in exploring their characteristics. The studies shed light on the interaction patterns and functions...     

Protein engineering to stabilize soluble amyloid β-protein aggregates for structural and functional studies

The molecular biology underlying protein aggregation and neuronal death in Alzheimer's disease is not yet completely understood, but small soluble nonamyloid aggregates of the amyloid β-protein (Aβ) have been shown to play a fundamental neurotoxic role. The composition and biological action of such aggregates, known as oligomers and protofibrils, are therefore areas of intense study. However, research is complicated by the multitude of different interconverting aggregates that Aβ can form in vitro and in vivo, and by the inhomogeneity and instability of in vitro preparations. Here we review recent studies in which protein engineering, and in particular disulfide engineering, has been applied to stabilize different Aβ aggregates. For example, several techniques now exist to obtain stable and neurotoxic protofibrillar forms of Aβ, and engineered Aβ dimers, or larger aggregates formed by these, have been shown to specifically induce neuronal damage in a way that mimics Alzheimer's disease pathology. Disulfide engineering has also revealed structural properties of neurotoxic aggregates, for instance that Aβ in protofibrils and globular oligomers adopts a β-hairpin conformation that is similar to, but topologically distinct from, the conformation of Aβ in mature amyloid fibrils. Protein engineering is therefore a workable strategy to address many of the outstanding questions relating to the structure, interconversion and biological effects of oligomers and protofibrils of Aβ.     

Mac-1 Directly Binds to the Endothelial Protein C-Receptor: A Link between the Protein C Anticoagulant Pathway and Inflammation?

Objective

The endothelial protein C-receptor (EPCR) is an endothelial transmembrane protein that binds protein C and activated protein C (APC) with equal affinity, thereby facilitating APC formation. APC has anticoagulant, antiapoptotic and antiinflammatory properties. Soluble EPCR, released by the endothelium, may bind activated neutrophils, thereby modulating cell adhesion. EPCR is therefore considered as a possible link between the anticoagulant properties of protein C and the inflammatory response of neutrophils. In the present study, we aimed to provide proof of concept for a direct binding of EPCR to the β₂ –integrin Mac-1 on monocytic cells under static and physiological flow conditions.

Measurements and Main Results

Under static conditions, human monocytes bind soluble EPCR in a concentration dependent manner, as demonstrated by flow cytometry. Binding can be inhibited by specific antibodies (anti-EPCR and anti-Mac-1). Specific binding was confirmed by a static adhesion assay, where a transfected Mac-1 expressing CHO cell line (Mac-1+ cells) bound significantly more recombinant EPCR compared to Mac-1+ cells blocked by anti-Mac-1-antibody and native CHO cells. Under physiological flow conditions, monocyte binding to the endothelium could be significantly blocked by both, anti-EPCR and anti-Mac-1 antibodies in a dynamic adhesion assay at physiological flow conditions. Pre-treatment of endothelial cells with APC (drotrecogin alfa) diminished monocyte adhesion significantly in a comparable extent to anti-EPCR.

Conclusions

In the present study, we demonstrate a direct binding of Mac-1 on monocytes to the endothelial protein C receptor under static and flow conditions. This binding suggests a link between the protein C anticoagulant pathway and inflammation at the endothelium side, such as in acute vascular inflammation or septicaemia.     

Are Cellulosome Scaffolding Protein CipC and CBM3-Containing Protein HycP,Involved in Adherence of Clostridium cellulolyticum to Cellulose?

Clostridium cellulolyticum, a mesophilic anaerobic bacterium, produces highly active enzymatic complexes called cellulosomes. This strain was already shown to bind to cellulose, however the molecular mechanism(s) involved is not known. In this context we focused on the gene named hycP, encoding a 250-kDa protein of unknown function, containing a Family-3 Carbohydrate Binding Module (CBM3) along with 23 hyaline repeat modules (HYR modules). In the microbial kingdom the gene hycP is only found in C. cellulolyticum and the very close strain recently sequenced Clostridium sp BNL1100. Its presence in C. cellulolyticum guided us to analyze its function and its putative role in adhesion of the cells to cellulose. The CBM3 of HycP was shown to bind to crystalline cellulose and was assigned to the CBM3b subfamily. No hydrolytic activity on cellulose was found with a mini-protein displaying representative domains of HycP. A C. cellulolyticum inactivated hycP mutant strain was constructed, and we found that HycP is neither involved in binding of the cells to cellulose nor that the protein has an obvious role in cell growth on cellulose. We also characterized the role of the cellulosome scaffolding protein CipC in adhesion of C. cellulolyticum to cellulose, since cellulosome scaffolding protein has been proposed to mediate binding of other cellulolytic bacteria to cellulose. A second mutant was constructed, where cipC was inactivated. We unexpectedly found that CipC is only partly involved in binding of C. cellulolyticum to cellulose. Other mechanisms for cellulose adhesion may therefore exist in C. cellulolyticum. In addition, no cellulosomal protuberances were observed at the cellular surface of C. cellulolyticum, what is in contrast to reports from several other cellulosomes producing strains. These findings may suggest that C. cellulolyticum has no dedicated molecular mechanism to aggregate the cellulosomes at the cellular surface.     

Maize Ribosome-Inactivating Protein Uses Lys158–Lys161 to Interact with Ribosomal Protein P2 and the Strength of Interaction Is Correlated to the Biological Activities

Ribosome-inactivating proteins (RIPs) inactivate prokaryotic or eukaryotic ribosomes by removing a single adenine in the large ribosomal RNA. Here we show maize RIP (MOD), an atypical RIP with an internal inactivation loop, interacts with the ribosomal stalk protein P2 via Lys158–Lys161, which is located in the N-terminal domain and at the base of its internal loop. Due to subtle differences in the structure of maize RIP, hydrophobic interaction with the ‘FGLFD’ motif of P2 is not as evidenced in MOD-P2 interaction. As a result, interaction of P2 with MOD was weaker than those with trichosanthin and shiga toxin A as reflected by the dissociation constants (K_D) of their interaction, which are 1037.50±65.75 µM, 611.70±28.13 µM and 194.84±9.47 µM respectively.Despite MOD and TCS target at the same ribosomal protein P2, MOD was found 48 and 10 folds less potent than trichosanthin in ribosome depurination and cytotoxicity to 293T cells respectively, implicating the strength of interaction between RIPs and ribosomal proteins is important for the biological activity of RIPs. Our work illustrates the flexibility on the docking of RIPs on ribosomal proteins for targeting the sarcin-ricin loop and the importance of protein-protein interaction for ribosome-inactivating activity.     

A Comprehensive Benchmark of Kernel Methods to Extract Protein–Protein Interactions from Literature

The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein–protein interactions (PPIs) reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate goal is to identify the one method that performs best in real-life scenarios, where information extraction is performed on unseen text and not on specifically prepared evaluation data. We performed a comprehensive benchmarking of nine different methods for PPI extraction that use convolution kernels on rich linguistic information. Methods were evaluated on five different public corpora using cross-validation, cross-learning, and cross-corpus evaluation. Our study confirms that kernels using dependency trees generally outperform kernels based on syntax trees. However, our study also shows that only the best kernel methods can compete with a simple rule-based approach when the evaluation prevents information leakage between training and test corpora. Our results further reveal that the F-score of many approaches drops significantly if no corpus-specific parameter optimization is applied and that methods reaching a good AUC score often perform much worse in terms of F-score. We conclude that for most kernels no sensible estimation of PPI extraction performance on new text is possible, given the current heterogeneity in evaluation data. Nevertheless, our study shows that three kernels are clearly superior to the other methods.     

Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.     

Induced Dimerization of the Amyloid Precursor Protein Leads to Decreased Amyloid-�� Protein Production

The amyloid precursor protein (APP) plays a central role in Alzheimer disease (AD) pathogenesis because sequential cleavages by β- and γ-secretase lead to the generation of the amyloid-β (Aβ) peptide, a key constituent in the amyloid plaques present in brains of AD individuals. In several studies APP has recently been shown to form homodimers, and this event appears to influence Aβ generation. However, these studies have relied on APP mutations within the Aβ sequence itself that may affect APP processing by interfering with secretase cleavages independent of dimerization. Therefore, the impact of APP dimerization on Aβ production remains unclear. To address this question, we compared the approach of constitutive cysteine-induced APP dimerization with a regulatable dimerization system that does not require the introduction of mutations within the Aβ sequence. To this end we generated an APP chimeric molecule by fusing a domain of the FK506-binding protein (FKBP) to the C terminus of APP. The addition of the synthetic membrane-permeant drug AP20187 induces rapid dimerization of the APP-FKBP chimera. Using this system we were able to induce up to 70% APP dimers. Our results showed that controlled homodimerization of APP-FKBP leads to a 50% reduction in total Aβ levels in transfected N2a cells. Similar results were obtained with the direct precursor of β-secretase cleavage, C99/SPA4CT-FKBP. Furthermore, there was no modulation of different Aβ peptide species after APP dimerization in this system. Taken together, our results suggest that APP dimerization can directly affect γ-secretase processing and that dimerization is not required for Aβ production.The mechanism of β-amyloid protein (Aβ)² generation from the amyloid precursor protein is of major interest in Alzheimer disease research because Aβ is the major constituent of senile plaques, one of the neuropathological hallmarks of Alzheimer disease (1, 2). In the amyloidogenic pathway Aβ is released from the amyloid precursor protein (APP) (3) after sequential cleavages by β-secretase BACE1 (4–6) and by the γ-secretase complex (7, 8). BACE1 cleavage releases the large ectodomain of APP while generating the membrane-anchored C-terminal APP fragment (CTF) of 99 amino acids (C99). Cleavage of β-CTF by γ-secretase leads to the secretion of Aβ peptides of various lengths and the release of the APP intracellular domain (AICD) into the cytosol (9–11). The γ-secretase complex consists of at least four proteins: presenilin, nicastrin, Aph-I, and Pen-2 (12). Presenilin is thought to be the catalytic subunit of the enzyme complex (13), but how the intramembrane scission is carried out remains to be elucidated. Alternatively, APP can first be cleaved in the non-amyloidogenic pathway by α-secretase within the Aβ domain between Lys-16 and Leu-17 (14, 15). This cleavage releases the APP ectodomain (APPsα) while generating the membrane-bound C-terminal fragment (α-CTF) of 83 amino acids (C83). The latter can be further processed by the γ-secretase complex, resulting in the secretion of the small 3-kDa fragment p3 and the release of AICD.APP, a type I transmembrane protein (16) of unclear function, may act as a cell surface receptor (3). APP and its two homologues, APLP1 and APLP2, can dimerize in a homotypic or heterotypic manner and, in so doing, promote intercellular adhesion (17). In vivo interaction of APP, APLP1, and APLP2 was demonstrated by cross-linking studies from brain homogenates (18). To date at least four domains have been reported to promote APP dimerization; that is, the E1 domain containing the N-terminal growth factor-like domain and copper binding domain (17), the E2 domain containing the carbohydrate domain in the APP ectodomain (19), the APP juxtamembrane region (20), and the transmembrane domain (21, 22). In the latter domain the dimerization appears to be mediated by the GXXXG motif near the luminal face of the transmembrane region (21, 23). In addition to promoting cell adhesion, APP dimerization has been proposed to increase susceptibility to cell death (20, 24).Interestingly, by introducing cysteine mutations into the APP juxtamembrane region, it was shown that stable dimers through formation of these disulfide linkages result in significantly enhanced Aβ production (25). This finding is consistent with the observation that stable Aβ dimers are found intracellularly in neurons and in vivo in brain (26). Taken together, these results have led to the idea that APP dimerization can positively regulate Aβ production. However, other laboratories have not been able to confirm some of these observations using slightly different approaches (23, 27).To further address the question of how dimerization of APP affects cleavage by α-, β-, and γ-secretase, we chose to test this with a controlled dimerization system. Accordingly, we engineered a chimeric APP molecule by fusing a portion of the FK506-binding protein (FKBP) to the C terminus of APP such that the addition of the synthetic membrane-permeant bifunctional compound, AP20187, will induce dimerization of the APP-FKBP chimera in a controlled manner by binding to the FKBP domains. Using this system, efficient dimerization of APP up to 70% can be achieved in a time and concentration-dependent fashion. Our studies showed that controlled homodimerization of APP-FKBP leads to decreased total Aβ levels in transfected N2a cells. Homodimerization of the β-CTF/C99 fragment, the direct precursor of γ-secretase cleavage, showed comparable results. In addition, induced dimerization of APP did not lead to a modulation of different Aβ peptides as it was reported for GXXXG mutants within the transmembrane domain of APP (21).     

Binding between Prion Protein and Aβ Oligomers Contributes to the Pathogenesis of Alzheimer's Disease

A plethora of evidence suggests that protein misfolding and aggregation are underlying mechanisms of various neurodegenerative diseases, such as prion diseases and Alzheimer's disease(AD). Like prion diseases, AD has been considered as an infectious disease in the past decades as it shows strain specificity and transmission potential. Although it remains elusive how protein aggregation leads to AD, it is becoming clear that cellular prion protein(PrP~C ) plays an important role in AD pathogenesis. Here, we briefly reviewed AD pathogenesis and focused on recent progresses how PrP~C contributed to AD development. In addition, we proposed a potential mechanism to explain why infectious agents, such as viruses, conduce AD pathogenesis. Microbe infections cause Aβ deposition and upregulation of PrP~C , which lead to high affinity binding between Aβ oligomers and PrP~C . The interaction between PrP~C and Aβ oligomers in turn activates the Fyn signaling cascade, resulting in neuron death in the central nervous system(CNS). Thus, silencing PrP~C expression may turn out be an effective treatment for PrP~C dependent AD.     

Rab2 Utilizes Glyceraldehyde-3-phosphate Dehydrogenase and Protein Kinase C�� to Associate with Microtubules and to Recruit Dynein

Rab2 requires glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and atypical protein kinase Cι (aPKCι) for retrograde vesicle formation from vesicular tubular clusters that sort secretory cargo from recycling proteins returned to the endoplasmic reticulum. However, the precise role of GAPDH and aPKCι in the early secretory pathway is unclear. GAPDH was the first glycolytic enzyme reported to co-purify with microtubules (MTs). Similarly, aPKC associates directly with MTs. To learn whether Rab2 also binds directly to MTs, a MT binding assay was performed. Purified Rab2 was found in a MT-enriched pellet only when both GAPDH and aPKCι were present, and Rab2-MT binding could be prevented by a recombinant fragment made to the Rab2 amino terminus (residues 2-70), which directly interacts with GAPDH and aPKCι. Because GAPDH binds to the carboxyl terminus of α-tubulin, we characterized the distribution of tyrosinated/detyrosinated α-tubulin that is recruited by Rab2 in a quantitative membrane binding assay. Rab2-treated membranes contained predominantly tyrosinated α-tubulin; however, aPKCι was the limiting and essential factor. Tyrosination/detyrosination influences MT motor protein binding; therefore, we determined whether Rab2 stimulated kinesin or dynein membrane binding. Although kinesin was not detected on membranes incubated with Rab2, dynein was recruited in a dose-dependent manner, and binding was aPKCι-dependent. These combined results suggest a mechanism by which Rab2 controls MT and motor recruitment to vesicular tubular clusters.The small GTPase Rab2 is essential for membrane trafficking in the early secretory pathway and associates with vesicular tubular clusters (VTCs)² located between the endoplasmic reticulum (ER) and the cis-Golgi compartment (1, 2). VTCs are pleomorphic structures that sort anterograde-directed cargo from recycling proteins and trafficking machinery retrieved to the ER (3-6). Rab2 bound to a VTC microdomain stimulates recruitment of soluble factors that results in the release of vesicles containing the recycling protein p53/p58 (7). In that regard, we have previously reported that glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and atypical PKC ι (aPKCι) are Rab2 effectors that interact directly with the Rab2 amino terminus and with each other (8, 9). Their interaction requires Src-dependent tyrosine phosphorylation of GAPDH and aPKCι (10). Moreover, GAPDH is a substrate for aPKCι (11). GAPDH catalytic activity is not required for ER to Golgi transport indicating that GAPDH provides a specific function essential for membrane trafficking from VTCs independent of glycolytic function (9). Indeed, phospho-GAPDH influences MT dynamics in the early secretory pathway (11).GAPDH was the first glycolytic enzyme reported to co-purify with microtubules (MTs) (12) and subsequently was shown to interact with the carboxyl terminus of α-tubulin (13). The binding of GAPDH to MTs promotes formation of cross-linked parallel MT arrays or bundles (14, 15). GAPDH has also been reported to possess membrane fusogenic activity, which is inhibited by tubulin (16). Similarly, aPKC associates directly with tubulin and promotes MT stability and MT remodeling at specific intracellular sites (17-21). It may not be coincidental that these two Rab2 effectors influence MT dynamics because recent studies indicate that the cytoskeleton plays a central role in the organization and operation of the secretory pathway (22).MTs are dynamic structures that grow or shrink by the addition or loss of α- and β-tubulin heterodimers from the ends of protofilaments (23). Their assembly and stability is regulated by a variety of proteins traditionally referred to as microtubule-associated proteins (MAPs). In addition to the multiple α/β isoforms that are present in eukaryotes, MTs undergo an assortment of post-translational modifications, including acetylation, glycylation, glutamylation, phosphorylation, palmitoylation, and detyrosination, which further contribute to their biochemical heterogeneity (24, 25). It has been proposed that these tubulin modifications regulate intracellular events by facilitating interaction with MAPs and with other specific effector proteins (24). For example, the reversible addition of tyrosine to the carboxyl terminus of α-tubulin regulates MT interaction with plus-end tracking proteins (+TIPs) containing the cytoskeleton-associated protein glycine-rich (CAP-Gly) motif and with dynein-dynactin (27-29). Additionally, MT motility and cargo transport rely on the cooperation of the motor proteins kinesin and dynein (30). Kinesin is a plus-end directed MT motor, whereas cytoplasmic dynein is a minus-end MT-based motor, and therefore the motors transport vesicular cargo toward the opposite end of a MT track (31).Although MT assembly does not appear to be directly regulated by small GTPases, Rab proteins provide a molecular link for vesicle movement along MTs to the appropriate target (22, 32-34). In this study, the potential interaction of Rab2 with MTs and motor proteins was characterized. We found that Rab2 does not bind directly to preassembled MTs but does associate when both GAPDH and aPKCι are present and bound to MTs. Moreover, the MTs predominantly contained tyrosinated α-tubulin (Tyr-tubulin) suggesting that a dynamic pool of MTs that differentially binds MAPs/effector proteins/motors associates with VTCs in response to Rab2. To that end, we determined that Rab2-promoted dynein/dynactin binding to membranes and that the recruitment required aPKCι.     

Protein phosphatase 4 is phosphorylated and inactivated by Cdk in response to spindle toxins and interacts with γ-tubulin

Many pharmaceuticals used to treat cancer target the cell cycle or mitotic spindle dynamics, such as the anti-tumor drug, paclitaxel, which stabilizes microtubules. Here we show that, in cells arrested in mitosis with the spindle toxins, nocodazole, or paclitaxel, the endogenous protein phosphatase 4 (Ppp4) complex Ppp4c-R2-R3A is phosphorylated on its regulatory (R) subunits, and its activity is inhibited. The phosphorylations are blocked by roscovitine, indicating that they may be mediated by Cdk1-cyclin B. Endogenous Ppp4c is enriched at the centrosomes in the absence and presence of paclitaxel, nocodazole, or roscovitine, and the activity of endogenous Ppp4c-R2-R3A is inhibited from G₁/S to the G₂/M phase of the cell cycle. Endogenous γ-tubulin and its associated protein, γ-tubulin complex protein 2, both of which are essential for nucleation of microtubules at centrosomes, interact with the Ppp4 complex. Recombinant γ-tubulin can be phosphorylated by Cdk1-cyclin B or Brsk1 and dephosphorylated by Ppp4c-R2-R3A in vitro. The data indicate that Ppp4c-R2-R3A regulates microtubule organization at centrosomes during cell division in response to stress signals such as spindle toxins, paclitaxel, and nocodazole, and that inhibition of the Ppp4 complex may be advantageous for treatment of some cancers.     

Protein kinase Cζ and glucose uptake

Protein kinase Cζ (PKCζ) is a member of the PKC family, serving downstream of insulin receptor and phosphatidylinositol (PI) 3-kinase. Many evidences suggest that PKCζ plays a very important role in activating glucose transport response. Not only insulin but also glucose and exercise can activate PKCζ through diverse pathways. PKCζ activation and activity are impaired with insulin resistance in muscle and adipose tissues of type II diabetes individuals, but heightened in liver tissue, wherein it also increases lipid synthesis mediated by SREBP-1c (sterol-regulatory element-binding protein). Many studies have focused on linkage between PKCζ and GLUT4 translocation and activation. Exploring the molecular mechanisms and pathways by which PKCζ mediates glucose transport will highlight the insulin-signaling pathway. Published in Russian in Biokhimiya, 2006, Vol. 71, No. 7, pp. 869–875. Co-first authors.