Role of Molecular Chaperones in G Protein ��5/Regulator of G Protein Signaling Dimer Assembly and G Protein �¦� Dimer Specificity

The G protein βγ subunit dimer (Gβγ) and the Gβ5/regulator of G protein signaling (RGS) dimer play fundamental roles in propagating and regulating G protein pathways, respectively. How these complexes form dimers when the individual subunits are unstable is a question that has remained unaddressed for many years. In the case of Gβγ, recent studies have shown that phosducin-like protein 1 (PhLP1) works as a co-chaperone with the cytosolic chaperonin complex (CCT) to fold Gβ and mediate its interaction with Gγ. However, it is not known what fraction of the many Gβγ combinations is assembled this way or whether chaperones influence the specificity of Gβγ dimer formation. Moreover, the mechanism of Gβ5-RGS assembly has yet to be assessed experimentally. The current study was undertaken to directly address these issues. The data show that PhLP1 plays a vital role in the assembly of Gγ2 with all four Gβ1–4 subunits and in the assembly of Gβ2 with all twelve Gγ subunits, without affecting the specificity of the Gβγ interactions. The results also show that Gβ5-RGS7 assembly is dependent on CCT and PhLP1, but the apparent mechanism is different from that of Gβγ. PhLP1 seems to stabilize the interaction of Gβ5 with CCT until Gβ5 is folded, after which it is released to allow Gβ5 to interact with RGS7. These findings point to a general role for PhLP1 in the assembly of all Gβγ combinations and suggest a CCT-dependent mechanism for Gβ5-RGS7 assembly that utilizes the co-chaperone activity of PhLP1 in a unique way.Eukaryotic cells utilize receptors coupled to heterotrimeric GTP-binding proteins (G proteins)³ to mediate a vast array of responses ranging from nutrient-induced migration of single-celled organisms to neurotransmitter-regulated neuronal activity in the human brain (1). Ligand binding to a G protein-coupled receptor (GPCR) initiates GTP exchange on the G protein heterotrimer (composed of Gα, Gβ, and Gγ subunits), which in turn causes the release of Gα-GTP from the Gβγ dimer (2–4). Both Gα-GTP and Gβγ propagate and amplify the signal by interacting with effector enzymes and ion channels (1, 5). The duration and amplitude of the signal is dictated by receptor phosphorylation coupled with arrestin binding and internalization (6) and by regulators of G protein signaling (RGS) proteins, which serve as GTPase-activating proteins for the GTP-bound Gα subunit (7, 8). The G protein signaling cycle is reset as the inactive Gα-GDP reassembles with the Gβγ dimer and Gαβγ re-associates with the GPCR (5).To fulfill its essential role in signaling, the G protein heterotrimer must be assembled post-translationally from its nascent polypeptides. Significant progress has been made recently regarding the mechanism by which this process occurs. It has been clear for some time that the Gβγ dimer must assemble first, followed by subsequent association of Gα with Gβγ (9). What has not been clear was how Gβγ assembly would occur given the fact that neither Gβ nor Gγ is structurally stable without the other. An important breakthrough was the finding that phosducin-like protein 1 (PhLP1) functions as a co-chaperone with the chaperonin containing tailless complex polypeptide 1 (CCT) in the folding of nascent Gβ and its association with Gγ (10–15). CCT is an important chaperone that assists in the folding of actin and tubulin and many other cytosolic proteins, including many β propeller proteins like Gβ (16). PhLP1 has been known for some time to interact with Gβγ and was initially believed to inhibit Gβγ function (17). However, several recent studies have demonstrated that PhLP1 and CCT work together in a highly orchestrated manner to form the Gβγ dimer (10–15).Studies on the mechanism of PhLP1-mediated Gβγ assembly have focused on the most common dimer Gβ1γ2 (10, 13, 14), leaving open questions about the role of PhLP1 in the assembly of the other Gβγ combinations. These are important considerations given that humans possess 5 Gβ genes and 12 Gγ genes with some important splice variants (18, 19), resulting in more than 60 possible combinations of Gβγ dimers. Gβ1–4 share between 80 and 90% sequence identity and are broadly expressed (18, 19). Gβ5, the more atypical isoform, shares only ∼53% identity with Gβ1, carries a longer N-terminal domain, and is only expressed in the central nervous system and retina (20). The Gγ protein family is more heterogeneous than the Gβ family. The sequence identity of the 12 Gγ isoforms extends from 10 to 70% (21), and the Gγ family can be separated into 5 subfamilies (21–23). All Gγ proteins carry C-terminal isoprenyl modifications, which contribute to their association with the cell membrane, GPCRs, Gαs, and effectors (9). Subfamily I Gγ isoforms are post-translationally farnesylated, whereas all others are geranylgeranylated (22, 24).There is some inherent selectivity in the assembly of different Gβγ combinations, but in general Gβ1–4 can form dimers with most Gγ subunits (25). The physiological purpose of this large number of Gβγ combinations has intrigued researchers in the field for many years, and a large body of research indicates that GPCRs and effectors couple to a preferred subset of Gβγ combinations based somewhat on specific sequence complementarity, but even more so on cellular expression patterns, subcellular localization, and post-translational modifications (18).In contrast to Gβ1–4, Gβ5 does not interact with Gγ subunits in vivo, but it instead forms irreversible dimers with RGS proteins of the R7 family, which includes RGS proteins 6, 7, 9, and 11 (26). All R7 family proteins contain an N-terminal DEP (disheveled, Egl-10, pleckstrin) domain, a central Gγ-like (GGL) domain, and a C-terminal RGS domain (8, 26). The DEP domain interacts with the membrane anchoring/nuclear shuttling R7-binding protein, and the GGL domain binds to Gβ5 in a manner similar to other Gβγ associations (27, 28). Like Gβγs, Gβ5 and R7 RGS proteins form obligate dimers required for their mutual stability (26). Without their partner, Gβ5 and R7 RGS proteins are rapidly degraded in cells (26, 29). Gβ5-R7 RGS complexes act as important GTPase-accelerating proteins for G_i/oα and G_qα subunits in neuronal cells and some immune cells (26).It has been recently shown that all Gβ isoforms are able to interact with the CCT complex, but to varying degrees (15). Gβ4 and Gβ1 bind CCT better than Gβ2 and Gβ3, whereas Gβ5 binds CCT poorly (15). These results suggest that Gβ1 and Gβ4 might be more dependent on PhLP1 than the other Gβs, given the co-chaperone role of PhLP1 with CCT in Gβ1γ2 assembly. However, another report has indicated that Gγ2 assembly with Gβ1 and Gβ2 is more PhLP1-dependent than with Gβ3 and Gβ4 (30). Thus, it is not clear from current information whether PhLP1 and CCT participate in assembly of all Gβγ combinations or whether they contribute to the specificity of Gβγ dimer formation, nor is it clear whether they or other chaperones are involved in Gβ5-R7 RGS dimer formation. This report was designed to address these issues.     

Identification of G Protein α Subunit-Palmitoylating Enzyme

The heterotrimeric G protein α subunit (Gα) is targeted to the cytoplasmic face of the plasma membrane through reversible lipid palmitoylation and relays signals from G-protein-coupled receptors (GPCRs) to its effectors. By screening 23 DHHC motif (Asp-His-His-Cys) palmitoyl acyl-transferases, we identified DHHC3 and DHHC7 as Gα palmitoylating enzymes. DHHC3 and DHHC7 robustly palmitoylated Gα_q, Gα_s, and Gα_i2 in HEK293T cells. Knockdown of DHHC3 and DHHC7 decreased Gα_q/11 palmitoylation and relocalized it from the plasma membrane into the cytoplasm. Photoconversion analysis revealed that Gα_q rapidly shuttles between the plasma membrane and the Golgi apparatus, where DHHC3 specifically localizes. Fluorescence recovery after photobleaching studies showed that DHHC3 and DHHC7 are necessary for this continuous Gα_q shuttling. Furthermore, DHHC3 and DHHC7 knockdown blocked the α_1A-adrenergic receptor/Gα_q/11-mediated signaling pathway. Together, our findings revealed that DHHC3 and DHHC7 regulate GPCR-mediated signal transduction by controlling Gα localization to the plasma membrane.G-protein-coupled receptors (GPCRs) form the largest family of cell surface receptors, consisting of more than 700 members in humans. GPCRs respond to a variety of extracellular signals, including hormones and neurotransmitters, and are involved in various physiologic processes, such as smooth muscle contraction and synaptic transmission (20, 25). Heterotrimeric G proteins, composed of α, β, and γ subunits, transduce signals from GPCRs to their effectors and play a central role in the GPCR signaling pathway (13, 21, 24, 32). Although the Gα subunit seems to localize stably at the cytosolic face of the plasma membrane (PM), a recent report suggested that Gα_o, a Gα isoform, shuttles rapidly between the PM and intracellular membranes (2). The PM targeting of Gα requires both interaction with the Gβγ complex and subsequent lipid palmitoylation of Gα (22). Thus, palmitoylation of Gα is a critical determinant of membrane targeting of the heterotrimer Gαβγ.Protein palmitoylation is a common posttranslational modification with lipid palmitate and regulates protein trafficking and function (7, 18). Gα is a classic and representative palmitoyl substrate (19, 38), and recent studies revealed that protein palmitoylation modifies virtually almost all the components of G-protein signaling, including GPCRs, Gα subunits, several members of the RGS (regulators of G-protein signaling) family of GTPase-activating proteins, GPCR kinase GRK6, and some small GTPases (7, 33). This common lipid modification plays an important role in compartmentalizing G-protein signaling to the specific microdomain, such as membrane caveolae and lipid raft (26). The palmitoyl thioester bond is relatively labile, and palmitates on substrates turn over rapidly, allowing proteins to shuttle between the cytoplasm/intracellular organelles and the PM (2, 3, 27). For example, binding of isoproterenol to the β-adrenergic receptor markedly accelerates the depalmitoylation of the associated Gα_s, shifting Gα_s to the cytoplasm (37). This receptor activation-induced depalmitoylation was also observed in a major postsynaptic PSD-95 scaffold, which anchors the AMPA (alpha-amino-3-hydroxy-5-methyl-isoxazole-4-propionic acid)-type glutamate receptor at the excitatory postsynapse through stargazin (6). On glutamate receptor activation, accelerated depalmitoylation of PSD-95 dissociates PSD-95 from postsynaptic sites and causes AMPA receptor endocytosis (6). Thus, palmitate turnover on Gα_s and PSD-95 is accelerated by receptor activation, contributing to downregulation of the signaling pathway. However, the enzymes that add palmitate to proteins (palmitoyl-acyl transferases [PATs]) and those that cleave the thioester bond (palmitoyl-protein thioesterases) were long elusive.Recent genetic studies in Saccharomyces cerevisiae identified Erf2/Erf4 (1, 40) and Akr1 (29) as PATs for yeast Ras and yeast casein kinase 2, respectively. Erf2 and Akr1 have four- to six-pass transmembrane domains and share a common domain, referred to as a DHHC domain, a cysteine-rich domain with a conserved Asp-His-His-Cys signature motif. Because the DHHC domain is essential for the PAT activity, we isolated 23 mammalian DHHC domain-containing proteins (DHHC proteins) and developed a systematic screening method to identify the specific enzyme-substrate pairs (11, 12): DHHC2, -3, -7, and -15 for PSD-95 (11); DHHC21 for endothelial NO synthase (10); and DHHC3 and -7 for GABA_A receptor γ2 subunit (9). Several other groups also reported that DHHC9 with GCP16 mediates palmitoylation toward H- and N-Ras (36) and that DHHC17, also known as HIP14, palmitoylates several neuronal proteins: huntingtin (14), SNAP-25, and CSP (14, 23, 35). However, the existence of PATs for Gα has been controversial because spontaneous palmitoylation of Gα could occur in vitro (4).In this study, we screened the 23 DHHC clones to examine which DHHC proteins can palmitoylate Gα. We found that DHHC3 and -7 specifically and robustly palmitoylate Gα at the Golgi apparatus. Inhibition of DHHC3 and -7 reduces Gα_q/11 palmitoylation levels and delocalizes it from the PM to the cytoplasm in HeLa cells and primary hippocampal neurons. Also, DHHC3 and -7 are necessary for the continuous Gα_q shuttling between the Golgi apparatus and the PM. Finally, blocking DHHC3 and -7 inhibits the α_1A-adrenergic receptor [α_1A-AR]/Gα_q-mediated signaling pathway, indicating that DHHC3 and -7 play an essential role in GPCR signaling by regulating Gα localization.     

Integration of G Protein α (Gα) Signaling by the Regulator of G Protein Signaling 14 (RGS14)

RGS14 contains distinct binding sites for both active (GTP-bound) and inactive (GDP-bound) forms of Gα subunits. The N-terminal regulator of G protein signaling (RGS) domain binds active Gα_i/o-GTP, whereas the C-terminal G protein regulatory (GPR) motif binds inactive Gα_i1/3-GDP. The molecular basis for how RGS14 binds different activation states of Gα proteins to integrate G protein signaling is unknown. Here we explored the intramolecular communication between the GPR motif and the RGS domain upon G protein binding and examined whether RGS14 can functionally interact with two distinct forms of Gα subunits simultaneously. Using complementary cellular and biochemical approaches, we demonstrate that RGS14 forms a stable complex with inactive Gα_i1-GDP at the plasma membrane and that free cytosolic RGS14 is recruited to the plasma membrane by activated Gα_o-AlF₄⁻. Bioluminescence resonance energy transfer studies showed that RGS14 adopts different conformations in live cells when bound to Gα in different activation states. Hydrogen/deuterium exchange mass spectrometry revealed that RGS14 is a very dynamic protein that undergoes allosteric conformational changes when inactive Gα_i1-GDP binds the GPR motif. Pure RGS14 forms a ternary complex with Gα_o-AlF₄⁻ and an AlF₄⁻-insensitive mutant (G42R) of Gα_i1-GDP, as observed by size exclusion chromatography and differential hydrogen/deuterium exchange. Finally, a preformed RGS14·Gα_i1-GDP complex exhibits full capacity to stimulate the GTPase activity of Gα_o-GTP, demonstrating that RGS14 can functionally engage two distinct forms of Gα subunits simultaneously. Based on these findings, we propose a working model for how RGS14 integrates multiple G protein signals in host CA2 hippocampal neurons to modulate synaptic plasticity.     

Inhibition of Dopamine Transporter Activity by G Protein βγ Subunits

Uptake through the Dopamine Transporter (DAT) is the primary mechanism of terminating dopamine signaling within the brain, thus playing an essential role in neuronal homeostasis. Deregulation of DAT function has been linked to several neurological and psychiatric disorders including ADHD, schizophrenia, Parkinson’s disease, and drug addiction. Over the last 15 years, several studies have revealed a plethora of mechanisms influencing the activity and cellular distribution of DAT; suggesting that fine-tuning of dopamine homeostasis occurs via an elaborate interplay of multiple pathways. Here, we show for the first time that the βγ subunits of G proteins regulate DAT activity. In heterologous cells and brain tissue, a physical association between Gβγ subunits and DAT was demonstrated by co-immunoprecipitation. Furthermore, in vitro pull-down assays using purified proteins established that this association occurs via a direct interaction between the intracellular carboxy-terminus of DAT and Gβγ. Functional assays performed in the presence of the non-hydrolyzable GTP analog GTP-γ-S, Gβγ subunit overexpression, or the Gβγ activator mSIRK all resulted in rapid inhibition of DAT activity in heterologous systems. Gβγ activation by mSIRK also inhibited dopamine uptake in brain synaptosomes and dopamine clearance from mouse striatum as measured by high-speed chronoamperometry in vivo. Gβγ subunits are intracellular signaling molecules that regulate a multitude of physiological processes through interactions with enzymes and ion channels. Our findings add neurotransmitter transporters to the growing list of molecules regulated by G-proteins and suggest a novel role for Gβγ signaling in the control of dopamine homeostasis.     

Characterization of Protein–Protein Interfaces

We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and non-interface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues having the same solvent accessibility as the interfaces. This strategy reveals residue distribution propensities that are not observable by comparing interfaces with protein cores and non-interface surfaces. Our conclusions are that there are larger numbers of hydrophobic residues, particularly aromatic residues, in interfaces, and the interactions apparently favored in interfaces include the opposite charge pairs and hydrophobic pairs. Surprisingly, Pro-Trp pairs are over represented in interfaces, presumably because of favorable geometries. The analysis is repeated using three datasets having different constraints on sequence similarity and structure quality. Consistent results are obtained across these datasets. We have also investigated separately the characteristics of heteromeric interfaces and homomeric interfaces.     

Differentiation of Human T Cells Alters Their Repertoire of G Protein α-Subunits

Because T cell differentiation leads to an expanded repertoire of chemokine receptors, a subgroup of G protein-coupled receptors, we hypothesized that the repertoire of G proteins might be altered in parallel. We analyzed the abundance of mRNA and/or protein of six G protein α-subunits in human CD4⁺ and CD8⁺ T cell subsets from blood. Although most G protein α-subunits were similarly expressed in all subsets, the abundance of Gα_o, a protein not previously described in hematopoietic cells, was much higher in memory versus naive cells. Consistent with these data, activation of naive CD4⁺ T cells in vitro significantly increased the abundance of Gα_o in cells stimulated under nonpolarizing or T_H17 (but not T_H1 or T_H2)-polarizing conditions. In functional studies, the use of a chimeric G protein α-subunit, Gα_qo5, demonstrated that chemokine receptors could couple to Gα_o-containing G proteins. We also found that Gα_i1, another α-subunit not described previously in leukocytes, was expressed in naive T cells but virtually absent from memory subsets. Corresponding to their patterns of expression, siRNA-mediated knockdown of Gα_o in memory (but not naive) and Gα_i1 in naive (but not memory) CD4⁺ T cells inhibited chemokine-dependent migration. Moreover, although even in Gα_o- and Gα_i1-expressing cells mRNAs of these α-subunits were much less abundant than Gα_i2 or Gα_i3, knockdown of any of these subunits impaired chemokine receptor-mediated migration similarly. Together, our data reveal a change in the repertoire of Gα_i/o subunits during T cell differentiation and suggest functional equivalence among Gα_i/o subunits irrespective of their relative abundance.     

Double Suppression of the Gα Protein Activity by RGS Proteins

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Effect of Iboga Alkaloids on μ-Opioid Receptor-Coupled G Protein Activation

Objective

The iboga alkaloids are a class of small molecules defined structurally on the basis of a common ibogamine skeleton, some of which modify opioid withdrawal and drug self-administration in humans and preclinical models. These compounds may represent an innovative approach to neurobiological investigation and development of addiction pharmacotherapy. In particular, the use of the prototypic iboga alkaloid ibogaine for opioid detoxification in humans raises the question of whether its effect is mediated by an opioid agonist action, or if it represents alternative and possibly novel mechanism of action. The aim of this study was to independently replicate and extend evidence regarding the activation of μ-opioid receptor (MOR)-related G proteins by iboga alkaloids.

Methods

Ibogaine, its major metabolite noribogaine, and 18-methoxycoronaridine (18-MC), a synthetic congener, were evaluated by agonist-stimulated guanosine-5´-O-(γ-thio)-triphosphate ([³⁵S]GTPγS) binding in cells overexpressing the recombinant MOR, in rat thalamic membranes, and autoradiography in rat brain slices.

Results And Significance

In rat thalamic membranes ibogaine, noribogaine and 18-MC were MOR antagonists with functional Ke values ranging from 3 uM (ibogaine) to 13 uM (noribogaine and 18MC). Noribogaine and 18-MC did not stimulate [³⁵S]GTPγS binding in Chinese hamster ovary cells expressing human or rat MORs, and had only limited partial agonist effects in human embryonic kidney cells expressing mouse MORs. Ibogaine did not did not stimulate [³⁵S]GTPγS binding in any MOR expressing cells. Noribogaine did not stimulate [³⁵S]GTPγS binding in brain slices using autoradiography. An MOR agonist action does not appear to account for the effect of these iboga alkaloids on opioid withdrawal. Taken together with existing evidence that their mechanism of action also differs from that of other non-opioids with clinical effects on opioid tolerance and withdrawal, these findings suggest a novel mechanism of action, and further justify the search for alternative targets of iboga alkaloids.     

Computational Prediction of Protein–Protein Interactions

Recently a number of computational approaches have been developed for the prediction of protein–protein interactions. Complete genome sequencing projects have provided the vast amount of information needed for these analyses. These methods utilize the structural, genomic, and biological context of proteins and genes in complete genomes to predict protein interaction networks and functional linkages between proteins. Given that experimental techniques remain expensive, time-consuming, and labor-intensive, these methods represent an important advance in proteomics. Some of these approaches utilize sequence data alone to predict interactions, while others combine multiple computational and experimental datasets to accurately build protein interaction maps for complete genomes. These methods represent a complementary approach to current high-throughput projects whose aim is to delineate protein interaction maps in complete genomes. We will describe a number of computational protocols for protein interaction prediction based on the structural, genomic, and biological context of proteins in complete genomes, and detail methods for protein interaction network visualization and analysis.     

Inhibition of Heterotrimeric G Protein Signaling by a Small Molecule Acting on G�� Subunit

The simultaneous activation of many distinct G protein-coupled receptors (GPCRs) and heterotrimeric G proteins play a major role in various pathological conditions. Pan-inhibition of GPCR signaling by small molecules thus represents a novel strategy to treat various diseases. To better understand such therapeutic approach, we have characterized the biomolecular target of BIM-46187, a small molecule pan-inhibitor of GPCR signaling. Combining bioluminescence and fluorescence resonance energy transfer techniques in living cells as well as in reconstituted receptor-G protein complexes, we observed that, by direct binding to the Gα subunit, BIM-46187 prevents the conformational changes of the receptor-G protein complex associated with GPCR activation. Such a binding prevents the proper interaction of receptors with the G protein heterotrimer and inhibits the agonist-promoted GDP/GTP exchange. These observations bring further evidence that inhibiting G protein activation through direct binding to the Gα subunit is feasible and should constitute a new strategy for therapeutic intervention.G protein-coupled receptors (GPCRs)³ represent the largest superfamily of signaling proteins with a very high impact on drug discovery (1). Approximately 30% of the current drug targets are indeed GPCRs and these latter are involved in all major disease areas (2). The classical drug discovery process selects and optimizes compounds that interact selectively with a specific receptor (1), but recent reports show that certain critical conditions such as cancer (3) or pain (4) are driven by the concomitant activation of many different GPCRs (5). Novel therapeutic strategies could therefore emerge from the simultaneous blockade of the various GPCRs involved in such pathologies. The GPCR signaling downstream cascade triggers several protein/protein interactions that may be blocked or modulated by small molecules (6). Such protein/protein interactions involve the GPCR transmembrane domain and the heterotrimeric G protein complex, composed of an α subunit (Gα) and a βγ dimer (Gβγ), which interact sequentially with several partners (e.g. guanine nucleotides, effectors, and regulatory proteins) (7). This offers multiple possibilities to develop small molecules controlling heterotrimeric G protein signaling (6, 8, 9). For example, Higashijima et al. (10, 11) showed that Mastoparan, a peptide toxin from wasp venom, directly acts on G proteins to mimic the role played by the activated receptors. The anti-helminthic drug Suramin and some analogs represent a second class of compounds that directly interact with G proteins and interfere with nucleotide exchange (12–14). Small molecules modulating regulator of G protein signaling proteins have also been proposed for drug development (15). More recently, Bonacci et al. (16) have described fluorescein analogs that display central pain relief activity via binding to the Gβγ subunits. From our own group, we have reported in vivo inhibition of the GPCR signaling pathway by two closely related imidazopirazine containing small molecules, displaying potent antiproliferative activity (BIM-46174) (17) and potent pain relief activity (BIM-46187) (18).Here, we examined the molecular mechanisms underlying the biological activity of BIM-46187 with the various constituents of the GPCR signaling pathways. We report that this small molecule prevents GPCR-G protein signaling through a selective binding to the Gα protein subunit. Our results support the concept of targeting and inhibiting the heterotrimeric G protein complex as an approach to treat certain pathologies involving simultaneous activation of several GPCRs and/or heterotrimeric G proteins.     

Effect of 1-Methyladenine on Localization of Gαi Protein in Starfish Oocytes

Localization and quantitative dynamics of _i subunit of G protein was studied by electron immunocytochemistry and immunoenzyme assay after hormonal induction of oocyte maturation in starfish Asterias amurensis. G_i protein was chiefly localized in the plasma membrane of immature oocytes; 1-methyladenine induced redistribution of the _i protein from the plasma membrane to intracellular structure up to the breakdown of the germinal vesicle.     

Yeast One-Hybrid Gγ Recruitment System for Identification of Protein Lipidation Motifs

Fatty acids and isoprenoids can be covalently attached to a variety of proteins. These lipid modifications regulate protein structure, localization and function. Here, we describe a yeast one-hybrid approach based on the Gγ recruitment system that is useful for identifying sequence motifs those influence lipid modification to recruit proteins to the plasma membrane. Our approach facilitates the isolation of yeast cells expressing lipid-modified proteins via a simple and easy growth selection assay utilizing G-protein signaling that induces diploid formation. In the current study, we selected the N-terminal sequence of Gα subunits as a model case to investigate dual lipid modification, i.e., myristoylation and palmitoylation, a modification that is widely conserved from yeast to higher eukaryotes. Our results suggest that both lipid modifications are required for restoration of G-protein signaling. Although we could not differentiate between myristoylation and palmitoylation, N-terminal position 7 and 8 play some critical role. Moreover, we tested the preference for specific amino-acid residues at position 7 and 8 using library-based screening. This new approach will be useful to explore protein-lipid associations and to determine the corresponding sequence motifs.     

Drosophila GoLoco-Protein Pins Is a Target of Gαo-mediated G Protein–coupled Receptor Signaling

G protein–coupled receptors (GPCRs) transduce their signals through trimeric G proteins, inducing guanine nucleotide exchange on their Gα-subunits; the resulting Gα-GTP transmits the signal further inside the cell. GoLoco domains present in many proteins play important roles in multiple trimeric G protein–dependent activities, physically binding Gα-subunits of the Gα_i/o class. In most cases GoLoco binds exclusively to the GDP-loaded form of the Gα-subunits. Here we demonstrate that the poly-GoLoco–containing protein Pins of Drosophila can bind to both GDP- and GTP-forms of Drosophila Gα_o. We identify Pins GoLoco domain 1 as necessary and sufficient for this unusual interaction with Gα_o-GTP. We further pinpoint a lysine residue located centrally in this domain as necessary for the interaction. Our studies thus identify Drosophila Pins as a target of Gα_o-mediated GPCR receptor signaling, e.g., in the context of the nervous system development, where Gα_o acts downstream from Frizzled and redundantly with Gα_i to control the asymmetry of cell divisions.     

Structural and Functional Analysis of the Regulator of G Protein Signaling 2-Gαq Complex

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Highlights? Two structures of the RGS2-Gα_q complex were determined by X-ray crystallography ? RGS2 binds Gα_q in a manner distinct from how other RGS proteins bind Gα_i/o ? In its distinct pose, RGS2 forms extensive contacts with the α-helical domain of Gα_q ? Helical domain contacts contribute to binding affinity and GAP potency of RGS2     

A Critical Assessment of Information-guided Protein–Protein Docking Predictions

The structures of protein complexes are increasingly predicted via protein–protein docking (PPD) using ambiguous interaction data to help guide the docking. These data often are incomplete and contain errors and therefore could lead to incorrect docking predictions. In this study, we performed a series of PPD simulations to examine the effects of incompletely and incorrectly assigned interface residues on the success rate of PPD predictions. The results for a widely used PPD benchmark dataset obtained using a new interface information-driven PPD (IPPD) method developed in this work showed that the success rate for an acceptable top-ranked model varied, depending on the information content used, from as high as 95% when contact relationships (though not contact distances) were known for all residues to 78% when only the interface/non-interface state of the residues was known. However, the success rates decreased rapidly to ∼40% when the interface/non-interface state of 20% of the residues was assigned incorrectly, and to less than 5% for a 40% incorrect assignment. Comparisons with results obtained by re-ranking a global search and with those reported for other data-guided PPD methods showed that, in general, IPPD performed better than re-ranking when the information used was more complete and more accurate, but worse when it was not, and that when using bioinformatics-predicted information on interface residues, IPPD and other data-guided PPD methods performed poorly, at a level similar to simulations with a 40% incorrect assignment. These results provide guidelines for using information about interface residues to improve PPD predictions and reveal a bottleneck for such improvement imposed by the low accuracy of current bioinformatic interface residue predictions.Proteins work in close association with other proteins to mediate the intricate functions of a cell. The atomic resolution of the structure of a protein complex can therefore help one understand a protein''s function in detail. Protein–protein docking (PPD),¹ a computational approach that complements experimental structure determinations, has attracted increasing research interest (1, 2), in part because it remains challenging to determine most structures of protein complexes via experimental techniques (3).To improve the performance of PPD predictions, experimentally derived data (e.g. distances) and information (e.g. the identity of interface residues) have been used either as a filter allowing less plausible docking solutions to be disregarded (4–9) or as a constraint to guide the docking process (10, 11). Various types of data and information have been used to aid PPD (12); these range from distances between, or the relative orientation of, the two interacting proteins to simple identification of the amino acid residues directly involved in the binding of the two proteins (13). Despite considerable success, the caveat for all these data-guided PPD predictions is that the data or information used must be correct in order to avoid spurious results caused by misguiding (12). It is therefore pertinent and important to evaluate the effects of errors in the incorporated data or information on the quality of PPD solutions.We have recently shown that the use of just a few distance constraints can improve the success rates of PPD such that they rival, or are even better than, those of a global search ranked using a sophisticated energy function, and that errors in the distance data significantly decrease the success rates of prediction (11). However, because distance data for interacting proteins are usually hard to obtain, other types of data or information, even if “ambiguous” (10), are increasingly used in PPD predictions (12, 14). In this study, we investigated the effects of incompletely and incorrectly assigned interface/non-interface residues, a major source of the so-called ambiguous data, on information-guided PPD predictions.As illustrated in Fig. 1, the information content of interface/non-interface residues can be rich enough to reveal the identity of every pair of residues in contact, but not their contact distances, or so poor as to reveal the interface/non-interface state of these residues but not their pairing relationship, for one or both of the two interacting proteins. To determine how these different levels of residue information content can help PPD predictions and the extent to which the use of incorrectly assigned residues degrades prediction success rates, we have developed a new interface information-driven PPD method (IPPD) and carried out a series of PPD simulations on a well-tested benchmark dataset. The results showed that when the information content was rich, excellent predictions (success rates for producing an acceptable top-ranked model > 70%) could be made via IPPD or by re-ranking a global search''s solutions using the same interface information, and that, encouragingly, the success of predictions remained respectable (top-ranked success rates > 15%) when the content was poor. However, when enough of the interface residues were incorrectly assigned, as would be the case when using interface residues predicted by a state-of-the-art bioinformatics method such as CPORT (15), few models ranked first by IPPD or other PPD methods, including HADDOCK (10), a popular ambiguous data-driven PPD method, came close to being acceptable. These results suggest that we can greatly increase the power of PPD predictions for practical applications only if the accuracy of current bioinformatics methods for predicting the interface residues of protein complexes can be significantly improved.Open in a separate windowFig. 1.Contact matrix of two interacting proteins, A and B, and the contact vectors of their residues. In the contact matrix, M_ij = 1 or 0, respectively, denotes contact or a lack of contact between residue i in protein A and residue j in protein B. In the contact vectors, V_Ai = 1 or 0, respectively, when residue Ai has, or does not have, at least one contact with any residue of protein B.     

A Second-generation Protein–Protein Interaction Network of Helicobacter pylori

Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein–protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.Helicobacter pylori is a Gram-negative, microaerophilic bacterium that colonizes the stomach, an unusual highly acidic niche for microorganisms. In 1983, Warren and Marshall found it to be associated with gastric inflammation and duodenal ulcer disease (1, 2). A chronic infection with H. pylori can lead to development of stomach carcinoma and MALT lymphoma (reviewed in (3)). Hence, the World Health Organization has classified H. pylori as a class I carcinogen (4). It is estimated that half of the world′s population harbors H. pylori but with large variations in the geographical and socioeconomic distribution while causing annually 700,000 deaths worldwide (reviewed in (5)).The pathogenesis of H. pylori has been extensively studied, including the effector CagA, cytotoxin VacA, its adhesins and urease (reviewed in (3, 5–7)). The latter allows the bacterium to neutralize the stomach acid through ammonia production. However, H. pylori is not a classical model organism and thus many gaps in our knowledge still exist.The genome of H. pylori reference strain 26695 was completely sequenced in 1997 (8) and encodes 1587 proteins of which about 950 (61%) have been assigned functions (excluding “putatives”; Uniprot, CMR (9)). These numbers indicate that a large fraction of the proteins of H. pylori has not been functionally characterized.Protein–protein interactions (PPIs)¹ are required for nearly all biological processes. Unbiased interactomes are helpful to understand proteins or pathways and how they are linking poorly or uncharacterized proteins via their interactions. For instance, our study of the Treponema pallidum interactome (10) has led to the characterization of several previously “unknown” proteins such as YbeB, a ribosomal silencing factor (11), or TP0658, a regulator of flagellar translation and assembly (12, 13). However, only a few other comprehensive bacterial interactome studies have been published to date, including Campylobacter jejuni (14), Synechocystis sp. (15), Mycobacterium tuberculosis (16), Mesorhizobium loti (17), and recently Escherichia coli (18). In addition, partial interactomes are available for Bacillus subtilis (19) and H. pylori (20). Most of them used the yeast two-hybrid (Y2H) screening technology (21) which allows the pairwise detection of PPIs. Furthermore, a few other studies (22–25) systematically identified protein complexes and their compositions in bacteria.In 2001, Rain and colleagues have established a partial interactome of H. pylori, the first published protein interaction network of a bacterium (20). In this study, 261 bait constructs were screened against a random prey pool library resulting in the detection of over 1500 PPIs. Although this network likely represents a small fraction of all PPIs that occur in H. pylori, many downstream studies were motivated by these results (see below).Recent studies have disproved the notion that Y2H data sets are of poor quality (26, 27). Similarly, a high false-negative rate can be avoided by multiple Y2H expression vector systems (28–30) or protein fragments as opposed to full-length constructs (31). The aim of this study was to systematically screen the H. pylori proteome for binary protein interactions using a complementary approach to that of Rain et al. to produce an extended protein–protein interaction map of H. pylori. As a result, we have roughly doubled the number of known binary protein–protein interactions for H. pylori in this study.     

Degradation of Amyloid �� Protein by Purified Myelin Basic Protein

The progressive accumulation of β-amyloid (Aβ) in senile plaques and in the cerebral vasculature is the hallmark of Alzheimer disease and related disorders. Impaired clearance of Aβ from the brain likely contributes to the prevalent sporadic form of Alzheimer disease. Several major pathways for Aβ clearance include receptor-mediated cellular uptake, blood-brain barrier transport, and direct proteolytic degradation. Myelin basic protein (MBP) is the major structural protein component of myelin and plays a functional role in the formation and maintenance of the myelin sheath. MBP possesses endogenous serine proteinase activity and can undergo autocatalytic cleavage liberating distinct fragments. Recently, we showed that MBP binds Aβ and inhibits Aβ fibril formation (Hoos, M. D., Ahmed, M., Smith, S. O., and Van Nostrand, W. E. (2007) J. Biol. Chem. 282, 9952–9961; Hoos, M. D., Ahmed, M., Smith, S. O., and Van Nostrand, W. E. (2009) Biochemistry 48, 4720–4727). Here we show that Aβ40 and Aβ42 peptides are degraded by purified human brain MBP and recombinant human MBP, but not an MBP fragment that lacks autolytic activity. MBP-mediated Aβ degradation is inhibited by serine proteinase inhibitors. Similarly, Cos-1 cells expressing MBP degrade exogenous Aβ40 and Aβ42. In addition, we demonstrate that purified MBP also degrades assembled fibrillar Aβ in vitro. Mass spectrometry analysis identified distinct degradation products generated from Aβ digestion by MBP. Lastly, we demonstrate in situ that purified MBP can degrade parenchymal amyloid plaques as well as cerebral vascular amyloid that form in brain tissue of Aβ precursor protein transgenic mice. Together, these findings indicate that purified MBP possesses Aβ degrading activity in vitro.The progressive accumulation of β-amyloid (Aβ)³ in senile/neuritic plaques and the cerebral vasculature is the hallmark of Alzheimer disease (AD) and is widely used in the pathological diagnosis of the disease. Aβ is generated by proteolytic cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase (1, 2). The main species of Aβ are 40 and 42 amino acids in length. Aβ42 is much more amyloidogenic than Aβ40 because of its two additional hydrophobic amino acids at the carboxyl-terminal end of the peptide (3). The Aβ42 peptide is the predominant form in senile plaques, forming a β-sheet structure, which is insoluble and resistant to proteolysis.Although increased production of Aβ has been implicated in the onset of familial forms of AD, it has been hypothesized that the more common sporadic forms of AD may be caused by the impaired clearance of Aβ peptides from the CNS. Several major pathways for Aβ clearance have been proposed including receptor-mediated cellular uptake, blood-brain barrier transport into the circulation, and direct proteolytic degradation (4–6). In the latter case, several proteinases or peptidases have been identified that are capable of degrading Aβ, including neprilysin (7, 8), insulin-degrading enzyme (9), the urokinase/tissue plasminogen activator-plasmin system (10), endothelin-converting enzyme (11), angiotensin-converting enzyme (12), gelatinase A (matrix metalloproteinase-2) (13, 14), gelatinase B (matrix metalloproteinase-9) (15), and acylpeptide hydrolase (16). Each of these enzymes has been shown to cleave Aβ peptides at multiple sites (5). However, only neprilysin, insulin-degrading enzyme, endothelin-converting enzyme, and matrix metalloproteinase-9 have been shown to have a significant role in regulating Aβ levels in the brains of experimental animal models (8, 17, 18).The “classic” myelin basic proteins (MBP) are major structural components of myelin sheaths accounting for 30% of total myelin protein. There are four different major isoforms generated from alternative splicing with molecular masses of 17.3, 18.5, 20.2, and 21.5 kDa. The 18.5-kDa variant, composed of 180 amino acids including 19 Arg and 12 Lys basic residues, is most abundant in mature myelin (19). One of the major functions of MBP is to hold together the cytoplasmic leaflets of myelin membranes to maintain proper compaction of the myelin sheath through the electrostatic interaction between the positive Arg and Lys residues of MBP and the negatively charged phosphate groups of the membrane lipid (20). MBP plays an important role in the pathology of multiple sclerosis, which is an autoimmune disease characterized by demyelination within white matter (21). Recently, it was reported that purified MBP exhibits autocleavage activity, generating distinct peptide fragments (22). In this study, serine 151 was reported as the active site serine residue involved in autocatalysis.In the early stages of AD, appreciable and diffuse myelin breakdown in the white matter is observed (23). Also, in white matter regions there are much fewer fibrillar amyloid deposits than are commonly found in gray matter regions. Recently, our laboratory has shown that MBP strongly interacts with Aβ peptides and prevents their assembly into mature amyloid fibrils (24, 25). Through the course of these studies we observed that upon longer incubations the levels of Aβ peptides were reduced upon treatment with MBP. In light of this observation, coupled with the report that MBP possesses proteolytic activity, we hypothesized that MBP may degrade Aβ peptides. In the present study, we show that purified human brain MBP and recombinantly expressed human MBP can degrade soluble Aβ40 and Aβ42 peptides in vitro. Purified MBP also degraded fibrillar Aβ in vitro. Mass spectrometry analysis identified distinct degradation products generated from soluble and fibrillar Aβ digestion by MBP. Furthermore, purified MBP degraded parenchymal and vascular fibrillar amyloid deposits in situ in the brain tissue of APP transgenic mice. Together, these findings indicate that purified MBP possesses Aβ degrading activity in vitro.     

Protein 4.1 G localizes in rodent microglia

Although it was reported that protein 4.1 G, a cytoskeletal protein characterized by its general expression in the body, interacts with some signal transduction molecules in the central nervous system (CNS), its distribution and significance in vivo remained to be elucidated. In the present study, we have identified 4.1 G-positive cells in the rodent CNS, and demonstrated its immunolocalization in the developing mouse CNS. In the rodent CNS, 4.1 G was colocalized with markers for microglia, such as CD45, OX-42 and ionized calcium-binding adapter molecule 1 (Iba1), but not with markers for neuronal or other glial cells. Additionally, colocalization of 4.1 G and A1 adenosine receptor was observed in the mouse cerebrum. In a mixed glial culture, most OX-42-positive microglia were positive for 4.1 G, and 4.1 G isoforms of the same molecular weight as in the rat brain were expressed in cultured microglia, where 4.1 G mRNA was detected by RT-PCR. In the developing mouse cerebral cortex, 4.1 G was detected in immature microglia, which were positive for Iba1. These results indicate that 4.1 G in the CNS is mainly distributed in microglia in vivo. Considering the interactions between 4.1 G and the signal transduction molecules, putative roles have been propsed for 4.1 G in microglial functions in the CNS.