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The inhibitor peptide DT-2 (YGRKKRRQRRRPPLRKKKKKH) is the most potent and selective inhibitor of the cGMP-dependent protein kinase (PKG) known today. DT-2 is a construct of a PKG tight binding sequence (W45, LRKKKKKH, KI = 0.8 μm) and a membrane translocating sequence (DT-6, YGRKKRRQRRRPP, KI = 1.1 μm), that combined strongly inhibits PKG catalyzed phosphorylation (KI = 12.5 nm) with ∼1000-fold selectivity toward PKG over protein kinase A, the closest relative of PKG. However, the molecular mechanism behind this inhibition is not entirely understood. Using a combination of photoaffinity labeling, stable isotope labeling, and mass spectrometry, we have located the binding sites of PKG-specific substrate and inhibitor peptides. Covalent linkage of a PKG-specific substrate analogue was localized in the catalytic core on residues 356–372, also known as the glycine-rich loop, essential for ATP binding. By analogy, the individual inhibitor peptides W45 and DT-6 were also found to cross-link near the glycine-rich loop, suggesting these are both substrate competitive inhibitors. A bifunctional photoreactive analogue of DT-2 was found to generate dimers of PKG. This cross-linking induced covalent PKG dimerization was not observed for an N-terminal deletion mutant of PKG, which lacks the dimerization domain. In addition, non-covalent mass spectrometry was used to determine binding stoichiometry and binding order of the inhibitor peptides. Dimeric PKG binds two W45 and DT-6 peptides, whereas only one DT-2 molecule was observed to bind to the dimeric PKG. Taken together, these findings imply that (i) the two individual components making up DT-2 are both targeted against the substrate-binding site and (ii) binding of a single DT-2 molecule inactivates both PKG monomers simultaneously, which is an indication that (iii) in cGMP-activated PKG the catalytic centers of both subunits may be in each other''s proximity.Among the superfamily of protein kinases the two cyclic nucleotide-regulated protein kinases, cAMP-dependent protein kinase and cGMP-dependent protein kinase, form a closely related subfamily of serine/threonine protein kinases (14). Both proteins share several structural elements, such as the N-terminal dimerization domain, an autoinhibition site, two in-tandem cyclic nucleotide-binding sites, and a highly conserved catalytic core (Fig. 1, A and B). Despite these similarities, these two enzymes display differences, which account for their unique properties. Whereas PKA2 is nearly ubiquitous, PKG is primarily found in the lung, cerebellum, and smooth muscles (5, 6). From a structural point of view these cyclic nucleotide-dependent protein kinases differ as well. The holoenzyme of PKA is a tetramer composed of two regulatory and two catalytic subunits. The catalytic subunits are non-covalently attached to the regulatory subunit dimer. Upon interaction with cAMP, the catalytic subunits dissociate from the holoenzyme and are free to catalyze heterophosphorylation (Fig. 1C). The mammalian type I PKGs are homodimeric cytosolic proteins containing two identical polypeptides of ∼76 kDa. Alternative mRNA splicing produces type Iα and type Iβ PKG, which are identical proteins apart from their first ∼100 N-terminal residues (7). Each PKG subunit is composed of a regulatory and a catalytic domain on a single polypeptide chain. Consequently, when cGMP activates PKG, the catalytic and regulatory components remain physically attached (Fig. 1D). Within the catalytic domain PKA and PKG share a strong primary sequence homology (8). Not surprisingly, these enzymes also exhibit overlapping substrate specificities, a feature that often interferes with efforts to elucidate their distinct biological pathways. Peptide substrates with a primary amino acid sequence motif RRX(S/T)X are in general recognized by both PKA and PKG (9). Besides this strong overlapping substrate specificity, several studies report on subtle differences in determinants that discriminate for PKA and PKG substrate specificity (1016). To specifically discriminate between PKG and PKA activity in biological assays a highly specific PKG peptide inhibitor was developed (17). This peptide, YGRKKRRQRRRPPLRKKKKKH (DT-2), is the most potent and selective PKG inhibitor known today. Recently, the validity of DT-2 as a superior inhibitor of PKG in terms of potency, selectivity, and membrane permeability has been demonstrated (1824). The inhibitor is a construct of a substrate competitive sequence, LRKKKKKH (W45), derived from a library screen that selected for tight PKG binding sequences, with a significant specificity toward PKG over PKA, and a membrane translocating signal peptide, YGRKKRRQRRRPP (DT-6). DT-2 strongly inhibits PKG-catalyzed phosphorylation (Ki = 12.5 nm), however, the molecular nature of DT-2 inhibition is not entirely understood (25). Because high resolution structural data are not available for PKG, one of our goals is to elucidate binding sites for PKG-specific substrates and inhibitors in more detail using a combination of mass spectrometric techniques and photoaffinity labeling. To further delineate the nature of inhibition we have developed photoaffinity analogues of DT-2 and related inhibitory peptides, as well as a high affinity peptide substrate. The method of photoaffinity labeling enables the direct probing of target proteins through a covalent bond, which is photochemically introduced between a ligand and its specific receptor (26). In combination with modern mass spectrometric techniques this is a powerful approach for the characterization of peptide-protein interactions (27). Substrate and inhibitor peptides containing photoactivatable analogues of phenylalanine, 4-benzoyl-l-phenylalanine (Phe(Bz)) or 4′-(3-(trifluoromethyl)-3H-diazirin-3-yl)-l-phenylalanine (Phe(Tmd)) were synthesized and used to locate their substrate/inhibitor-binding sites on PKG. These measurements indicate that the substrate peptide resides near the glycine-rich loop within the catalytic domain and that the inhibitor peptides are directed similarly toward this substrate-binding site, thereby acting as competitive inhibitors. In addition, nanoflow electrospray ionization time of flight mass spectrometry (ESI-TOF-MS) was performed to study the interaction between DT-2 and PKG in more detail. ESI-MS has proven to be a useful tool to analyze the non-covalent interaction of proteins with ligands, oligonucleotides, peptides, or other proteins (2831). Using this technique, important information on conformational changes (3235), measurement of relative dissociation constants (36, 37), and sequential binding order and cooperativity (38, 39) can be obtained. ESI-MS confirms that PKG is primarily a homodimer and is able to bind four cGMP molecules. Binding of DT-2 was strongly enhanced in the presence of cGMP. Surprising is the observation that only one DT-2 molecule binds to dimeric PKG. The information derived from these measurements allows for molecular modeling and structural refinements of the next generation of PKG-selective inhibitors.Open in a separate windowFIGURE 1.Linear arrangement of the functional domains of the regulatory and catalytic subunit of PKA (A) and PKG (B) type I and schematic representation of the current working models of the activation process of PKA (C) and PKG (D) type 1. Binding of cAMP to the PKA induces a conformational change that results in the dissociation of the catalytic subunits. Binding of cGMP to PKG also induces a conformational change, which exposes the catalytic domains, but both catalytic domains remain near each other via the N-terminal dimerization domain. (Images adapted from Scholten et al. (4).)

TABLE 1

Inhibition contants (KI) of PKA- or PKG-specific peptide inhibitors and the PKA/PKG specificity index
PeptideSequencePKGKiPKAKiSpecificity index (PKA/PKG)Ref.
μmμm
PKI(5–24)TTYDFIASGRTGRRNAIHD-NH21500.0030.0002(11)
WW21TQAKRKKALAMA-NH27.5750100(11)
W45LRKKKKKH0.82 ± 0.33559680(17)
DT-6YGRGGRRQRRRPP1.1 ± 0.2226 ± 423.6(17)
DT-2YGRKKRRQRRRPPLRKKKKKH0.0125 ± 0.00316.5 ± 3.81320(17)
Open in a separate window  相似文献   

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Forty-five different point mutations in POLG, the gene encoding the catalytic subunit of the human mitochondrial DNA polymerase (pol γ), cause the early onset mitochondrial DNA depletion disorder, Alpers syndrome. Sequence analysis of the C-terminal polymerase region of pol γ revealed a cluster of four Alpers mutations at highly conserved residues in the thumb subdomain (G848S, c.2542g→a; T851A, c.2551a→g; R852C, c.2554c→t; R853Q, c.2558g→a) and two Alpers mutations at less conserved positions in the adjacent palm subdomain (Q879H, c.2637g→t and T885S, c.2653a→t). Biochemical characterization of purified, recombinant forms of pol γ revealed that Alpers mutations in the thumb subdomain reduced polymerase activity more than 99% relative to the wild-type enzyme, whereas the palm subdomain mutations retained 50–70% wild-type polymerase activity. All six mutant enzymes retained physical and functional interaction with the pol γ accessory subunit (p55), and none of the six mutants exhibited defects in misinsertion fidelity in vitro. However, differential DNA binding by these mutants suggests a possible orientation of the DNA with respect to the polymerase during catalysis. To our knowledge this study represents the first structure-function analysis of the thumb subdomain in pol γ and examines the consequences of mitochondrial disease mutations in this region.As the only DNA polymerase found in animal cell mitochondria, DNA polymerase γ (pol γ)3 bears sole responsibility for DNA synthesis in all replication and repair transactions involving mitochondrial DNA (1, 2). Mammalian cell pol γ is a heterotrimeric complex composed of one catalytic subunit of 140 kDa (p140) and two 55-kDa accessory subunits (p55) that form a dimer (3). The catalytic subunit contains an N-terminal exonuclease domain connected by a linker region to a C-terminal polymerase domain. Whereas the exonuclease domain contains essential motifs I, II, and III for its activity, the polymerase domain comprising the thumb, palm, and finger subdomains contains motifs A, B, and C that are crucial for polymerase activity. The catalytic subunit is a family A DNA polymerase that includes bacterial pol I and T7 DNA polymerase and possesses DNA polymerase, 3′ → 5′ exonuclease, and 5′-deoxyribose phosphate lyase activities (for review, see Refs. 1 and 2). The 55-kDa accessory subunit (p55) confers processive DNA synthesis and tight binding of the pol γ complex to DNA (4, 5).Depletion of mtDNA as well as the accumulation of deletions and point mutations in mtDNA have been observed in several mitochondrial disorders (for review, see Ref. 6). mtDNA depletion syndromes are caused by defects in nuclear genes responsible for replication and maintenance of the mitochondrial genome (7). Mutation of POLG, the gene encoding the catalytic subunit of pol γ, is frequently involved in disorders linked to mutagenesis of mtDNA (8, 9). Presently, more than 150 point mutations in POLG are linked with a wide variety of mitochondrial diseases, including the autosomal dominant (ad) and recessive forms of progressive external ophthalmoplegia (PEO), Alpers syndrome, parkinsonism, ataxia-neuropathy syndromes, and male infertility (tools.niehs.nih.gov/polg) (9).Alpers syndrome, a hepatocerebral mtDNA depletion disorder, and myocerebrohepatopathy are rare heritable autosomal recessive diseases primarily affecting young children (1012). These diseases generally manifest during the first few weeks to years of life, and symptoms gradually develop in a stepwise manner eventually leading to death. Alpers syndrome is characterized by refractory seizures, psychomotor regression, and hepatic failure (11, 12). Mutation of POLG was first linked to Alpers syndrome in 2004 (13), and to date 45 different point mutations in POLG (18 localized to the polymerase domain) are associated with Alpers syndrome (9, 14, 15). However, only two Alpers mutations (A467T and W748S, both in the linker region) have been biochemically characterized (16, 17).During the initial cloning and sequencing of the human, Drosophila, and chicken pol γ genes, we noted a highly conserved region N-terminal to motif A in the polymerase domain that was specific to pol γ (18). This region corresponds to part of the thumb subdomain that tracks DNA into the active site of both Escherichia coli pol I and T7 DNA polymerase (1921). A high concentration of disease mutations, many associated with Alpers syndrome, is found in the thumb subdomain.Here we investigated six mitochondrial disease mutations clustered in the N-terminal portion of the polymerase domain of the enzyme (Fig. 1A). Four mutations (G848S, c.2542g→a; T851A, c.2551a→g; R852C, c.2554c→t; R853Q, c.2558g→a) reside in the thumb subdomain and two (Q879H, c.2637g→t and T885S, c.2653a→t) are located in the palm subdomain. These mutations are associated with Alpers, PEO, mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), ataxia-neuropathy syndrome, Leigh syndrome, and myocerebrohepatopathy (
POLG mutationDiseaseGeneticsReference
G848SAlpers syndromeIn trans with A467T, Q497H, T251I-P587L, or W748S-E1143G in Alpers syndrome15, 35, 4350
Leigh syndromeIn trans with R232H in Leigh syndrome49
MELASIn trans with R627Q in MELAS38
PEO with ataxia-neuropathyIn trans with G746S and E1143G in PEO with ataxia50
PEOIn trans with T251I and P587L in PEO51, 52
T851AAlpers syndromeIn trans with R1047W48, 53
In trans with H277C
R852CAlpers syndromeIn trans with A467T14, 48, 50
In cis with G11D and in trans with W748S-E1143G or A467T
Ataxia-neuropathyIn trans with G11D-R627Q15
R853QMyocerebrohepatopathyIn trans with T251I-P587L15
Q879HAlpers syndrome with valproate-induced hepatic failureIn cis with E1143G and in trans with A467T-T885S35, 54
T885SAlpers syndrome with valproate-induced hepatic failureIn cis with A467T and in trans with Q879H-E1143G35, 54
Open in a separate windowOpen in a separate windowFIGURE 1.POLG mutations characterized in this study. A, the location of the six mutations characterized is shown in red in the primary sequence of pol γ. Four mutations, the G848S, T851A, R852C, and R853Q, are located in the thumb domain, whereas two mutations, the Q879H and T885S, are in the palm domain of the polymerase region. B, sequence alignment of pol γ from yeast to humans. The amino acids characterized in this study are shown in red. Yellow-highlighted amino acids are highly conserved, and blue-highlighted amino acids are moderately conserved.  相似文献   

6.
Molecular and Biochemical Characterization of the Protein Template Controlling Biosynthesis of the Lipopeptide Lichenysin     
Dirk Konz  Sascha Doekel  Mohamed A. Marahiel 《Journal of bacteriology》1999,181(1):133-140
Lichenysins are surface-active lipopeptides with antibiotic properties produced nonribosomally by several strains of Bacillus licheniformis. Here, we report the cloning and sequencing of an entire 26.6-kb lichenysin biosynthesis operon from B. licheniformis ATCC 10716. Three large open reading frames coding for peptide synthetases, designated licA, licB (three modules each), and licC (one module), could be detected, followed by a gene, licTE, coding for a thioesterase-like protein. The domain structure of the seven identified modules, which resembles that of the surfactin synthetases SrfA-A to -C, showed two epimerization domains attached to the third and sixth modules. The substrate specificity of the first, fifth, and seventh recombinant adenylation domains of LicA to -C (cloned and expressed in Escherichia coli) was determined to be Gln, Asp, and Ile (with minor Val and Leu substitutions), respectively. Therefore, we suppose that the identified biosynthesis operon is responsible for the production of a lichenysin variant with the primary amino acid sequence l-Gln–l-Leu–d-Leu–l-Val–l-Asp–d-Leu–l-Ile, with minor Leu and Val substitutions at the seventh position.Many strains of Bacillus are known to produce lipopeptides with remarkable surface-active properties (11). The most prominent of these powerful lipopeptides is surfactin from Bacillus subtilis (1). Surfactin is an acylated cyclic heptapeptide that reduces the surface tension of water from 72 to 27 mN m−1 even in a concentration below 0.05% and shows some antibacterial and antifungal activities (1). Some B. subtilis strains are also known to produce other, structurally related lipoheptapeptides (Table (Table1),1), like iturin (32, 34) and bacillomycin (3, 27, 30), or the lipodecapeptides fengycin (50) and plipastatin (29).

TABLE 1

Lipoheptapeptide antibiotics of Bacillus spp.
LipopeptideOrganismStructureReference
Lichenysin AB. licheniformisFAa-L-Glu-L-Leu-D-Leu-L-Val-L-Asn-D-Leu-L-Ile51, 52
Lichenysin BFAa-L-Glu-L-Leu-D-Leu-L-Val-L-Asp-D-Leu-L-Leu23, 26
Lichenysin CFAa-L-Glu-L-Leu-D-Leu-L-Val-L-Asp-D-Leu-L-Ile17
Lichenysin DFAa-L-Gln-L-Leu-D-Leu-L-Val-L-Asp-D-Leu-L-IleThis work
Surfactant 86B. licheniformisFAa-L-Glxd-L-Leu-D-Leu-L-Val-L-Asxd-D-Leu-L-Ilee14, 15
L-Val
SurfactinB. subtilisFAa-L-Glu-L-Leu-D-Leu-L-Val-L-Asp-D-Leu-L-Leu1, 7, 49
EsperinB. subtilisFAb-L-Glu-L-Leu-D-Leu-L-Val-L-Asp-D-Leu-L-Leue45
L-Val 
Iturin AB. subtilisFAc-L-Asn-D-Tyr-D-Asn-L-Gln-L-Pro-D-Asn-L-Ser32
Iturin CFAc-L-Asn-D-Tyr-D-Asn-L-Gln-L-Pro-D-Asne-L-Asne34
D-Ser-L-Thr 
Bacillomycin LB. subtilisFAc-L-Asp-D-Tyr-D-Asn-L-Ser-L-Gln-D-Proe-L-Thr3
D-Ser- 
Bacillomycin DFAc-L-Asp-D-Tyr-D-Asn-L-Pro-L-Glu-D-Ser-L-Thr30, 31
Bacillomycin FFAc-L-Asn-D-Tyr-D-Asn-L-Gln-L-Pro-D-Asn-L-Thr27
Open in a separate windowaFA, β-hydroxy fatty acid. The β-hydroxy group forms an ester bond with the carboxy group of the C-terminal amino acid. bFA, β-hydroxy fatty acid. The β-hydroxy group forms an ester bond with the carboxy group of Asp5. cFA, β-amino fatty acid. The β-amino group forms a peptide bond with the carboxy group of the C-terminal amino acid. dOnly the following combinations of amino acid 1 and 5 are allowed: Gln-Asp or Glu-Asn. eWhere an alternative amino acid may be present in a structure, the alternative is also presented. In addition to B. subtilis, several strains of Bacillus licheniformis have been described as producing the lipopeptide lichenysin (14, 17, 23, 26, 51). Lichenysins can be grouped under the general sequence l-Glx–l-Leu–d-Leu–l-Val–l-Asx–d-Leu–l-Ile/Leu/Val (Table (Table1).1). The first amino acid is connected to a β-hydroxyl fatty acid, and the carboxy-terminal amino acid forms a lactone ring to the β-OH group of the lipophilic part of the molecule. In contrast to the lipopeptide surfactin, lichenysins seem to be synthesized during growth under aerobic and anaerobic conditions (16, 51). The isolation of lichenysins from cells growing on liquid mineral salt medium on glucose or sucrose basic has been studied intensively. Antimicrobial properties and the ability to reduce the surface tension of water have also been described (14, 17, 26, 51). The structural elucidation of the compounds revealed slight differences, depending on the producer strain. Various distributions of branched and linear fatty acid moieties of diverse lengths and amino acid variations in three defined positions have been identified (Table (Table11).In contrast to the well-defined methods for isolation and structural characterization of lichenysins, little is known about the biosynthetic mechanisms of lichenysin production. The structural similarity of lichenysins and surfactin suggests that the peptide moiety is produced nonribosomally by multifunctional peptide synthetases (7, 13, 25, 49, 53). Peptide synthetases from bacterial and fungal sources describe an alternative route in peptide bond formation in addition to the ubiquitous ribosomal pathway. Here, large multienzyme complexes affect the ordered recognition, activation, and linking of amino acids by utilizing the thiotemplate mechanism (19, 24, 25). According to this model, peptide synthetases activate their substrate amino acids as aminoacyl adenylates by ATP hydrolysis. These unstable intermediates are subsequently transferred to a covalently enzyme-bound 4′-phosphopantetheinyl cofactor as thioesters. The thioesterified amino acids are then integrated into the peptide product through a stepwise elongation by a series of transpeptidations directed from the amino terminals to the carboxy terminals. Peptide synthetases have not only awakened interest because of their mechanistic features; many of the nonribosomally processed peptide products also possess important biological and medical properties.In this report we describe the identification and characterization of a putative lichenysin biosynthesis operon from B. licheniformis ATCC 10716. Cloning and sequencing of the entire lic operon (26.6 kb) revealed three genes, licA, licB, and licC, with structural patterns common to peptide synthetases and a gene designated licTE, which codes for a putative thioesterase. The modular organization of the sequenced genes resembles the requirements for the biosynthesis of the heptapeptide lichenysin. Based on the arrangement of the seven identified modules and the tested substrate specificities, we propose that the identified genes are involved in the nonribosomal synthesis of the portion of the lichenysin peptide with the primary sequence l-Gln–l-Leu–d-Leu–l-Val–l-Asp–d-Leu–l-Ile (with minor Val and Leu substitutions).  相似文献   

7.
Neurodegeneration and Alzheimer's disease (AD). What Can Proteomics Tell Us About the Alzheimer's Brain?     
Guillermo Moya-Alvarado  Noga Gershoni-Emek  Eran Perlson  Francisca C. Bronfman 《Molecular & cellular proteomics : MCP》2016,15(2):409-425
  相似文献   

8.
RNA Polymerase I Transcription Silences Noncoding RNAs at the Ribosomal DNA Locus in Saccharomyces cerevisiae     
Elisa Cesarini  Francesca Romana Mariotti  Francesco Cioci  Giorgio Camilloni 《Eukaryotic cell》2010,9(2):325-335
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9.
Single-cell-type Proteomics: Toward a Holistic Understanding of Plant Function     
Shaojun Dai  Sixue Chen 《Molecular & cellular proteomics : MCP》2012,11(12):1622-1630
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10.
Biological Activity of Nerve Growth Factor Precursor Is Dependent upon Relative Levels of Its Receptors     
Raheleh Masoudi  Maria S. Ioannou  Michael D. Coughlin  Promila Pagadala  Kenneth E. Neet  Oliver Clewes  Shelley J. Allen  David Dawbarn    Margaret Fahnestock 《The Journal of biological chemistry》2009,284(27):18424-18433
Nerve growth factor (NGF) is produced as a precursor called pro-nerve growth factor (proNGF), which is secreted by many tissues and is the predominant form of NGF in the central nervous system. In Alzheimer disease brain, cholinergic neurons degenerate and can no longer transport NGF as efficiently, leading to an increase in untransported NGF in the target tissue. The protein that accumulates in the target tissue is proNGF, not the mature form. The role of this precursor is controversial, and both neurotrophic and apoptotic activities have been reported for recombinant proNGFs. Differences in the protein structures, protein expression systems, methods used for protein purification, and methods used for bioassay may affect the activity of these proteins. Here, we show that proNGF is neurotrophic regardless of mutations or tags, and no matter how it is purified or in which system it is expressed. However, although proNGF is neurotrophic under our assay conditions for primary sympathetic neurons and for pheochromocytoma (PC12) cells, it is apoptotic for unprimed PC12 cells when they are deprived of serum. The ratio of tropomyosin-related kinase A to p75 neurotrophin receptor is low in unprimed PC12 cells compared with primed PC12 cells and sympathetic neurons, altering the balance of proNGF-induced signaling to favor apoptosis. We conclude that the relative level of proNGF receptors determines whether this precursor exhibits neurotrophic or apoptotic activity.Nerve growth factor (NGF)3 regulates neuronal survival, neurite outgrowth, and differentiation in the peripheral and central nervous systems (1). The mature form of NGF forms a non-covalent homodimer and binds with high affinity (kd ≈ 10−11 m) to tropomyosin-related kinase A (TrkA) and with low affinity (kd ≈ 10−9 m) to the common neurotrophin receptor p75NTR (p75 neurotrophin receptor) (2). NGF promotes cell survival and growth in cells expressing TrkA through activation of the phosphatidylinositol 3-kinase/AKT pathway and the Ras/mitogen-activated protein kinase (MAPK) pathway (3, 4). p75NTR plays diverse roles, ranging from cell survival to cell death depending on the cellular context in which it is expressed. Through activation of the NF-κB pathway, p75NTR can contribute to cell survival in sensory neurons (5), it is involved in axonal growth via regulation of Rho activity (6), and it can interact with Trks to enhance neurotrophin affinity (at low concentration of ligand) and specificity of binding to Trks (79). High levels of p75NTR expression can induce apoptosis when there are low levels of Trk or when Trk is absent (10, 11). Apoptosis occurs through increased ceramide production (12), activation of c-Jun N-terminal kinase (JNK1), and p53 (10, 13). p75NTR requires a co-receptor called sortilin to induce cell death (14).NGF is produced as a precursor called pro-nerve growth factor (proNGF) (15). ProNGF is secreted by many tissues such as prostate cells, spermatids, hair follicles, oral mucosal keratinocytes, sympathetic neurons, cortical astrocytes, heart, and spleen (1620). ProNGF is the predominant form of NGF in the central and peripheral nervous systems, whereas little or no mature NGF can be detected (2124). In Alzheimer disease brain, retrograde transport from the cortex and hippocampus to basal forebrain cholinergic neurons is reduced as these neurons degenerate, with concomitant proNGF accumulation in the cortex and hippocampus (21, 23). This suggested that proNGF mediates biological activity besides its prodomain function of promoting protein folding and regulation of neurotrophin secretion (2528). To study the role of proNGF protein in vitro, point mutations were inserted at the cleavage site used by furin, a proprotein convertase known to cleave proNGF (29), to minimize the conversion of proNGF to mature NGF. The resulting recombinant, cleavage-resistant proNGFs reportedly exhibit either apoptotic activity (30, 31) or neurotrophic activity (32, 33). These recombinant proteins differ in several ways (ProNGF(R−1G)ProNGFhisProNGFEProNGF123WT-NGFhisMutations−1 (R to G)−2 and −1 (RR to AA), 118 and 119 (RR to AA)−1 and +1 (RS to AA)−73 and −72 (RR to AA), −43 and −42 (KKRR to KAAR), −2 and −1 (KR to AA)None: cleavable proNGFTagNo tagHistidine tagNo tagNo tagHistidine tagExpression systemInsect cellsInsect cells, mammalian cellsBacteriaInsect cellsInsect cells, mammalian cellsPurificationNo purificationNickel columnRefolded from inclusion bodies, FPLCCation exchange chromatography, immunoaffinity chromatographyNickel columnOpen in a separate window  相似文献   

11.
Protein Identification Using Top-Down Spectra     
Xiaowen Liu  Yakov Sirotkin  Yufeng Shen  Gordon Anderson  Yihsuan S. Tsai  Ying S. Ting  David R. Goodlett  Richard D. Smith  Vineet Bafna  Pavel A. Pevzner 《Molecular & cellular proteomics : MCP》2012,11(6)
In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set.In the past two decades, proteomics was dominated by bottom-up mass spectrometry that analyzes digested peptides rather than intact proteins. Bottom-up approaches, although powerful, do have limitations in analyzing protein species, e.g. various proteolytic forms of the same protein or various protein isoforms resulting from alternative splicing. Top-down mass spectrometry focuses on analyzing intact proteins and large peptides (110) and has advantages in localizing multiple post-translational modifications (PTMs)1 in a coordinated fashion (e.g. combinatorial PTM code) and identifying multiple protein species (e.g. proteolytically processed protein species) (11). Until recently, most top-down studies were limited to single purified proteins (1215). Top-down studies of protein mixtures were restricted by difficulties in separating and fragmenting intact proteins and a shortage of robust computational tools.In the last two years, because of advances in protein separation and top-down instrumentation, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples containing hundreds and even thousands of proteins (1621). Because algorithms for interpreting top-down spectra are still in their infancy, many recent developments include computational innovations in protein identification.Because top-down spectra are complex, the first step in top-down spectral interpretation is usually spectral deconvolution, which converts a complex top-down spectrum to a list of monoisotopic masses (a deconvolved spectrum). Every protein (possibly with modifications) can be scored against a top-down deconvoluted spectrum, resulting in a Protein-Spectrum-Match (PrSM). The top-down protein identification problem is finding a protein in a database with the highest scoring PrSM for a top-down spectrum and further output the PrSM if it is statistically significant. There are several software tools for top-down protein identification (SoftwareIdentification of unexpected modificationsProteogenomics search against 6-frame translationSpeedEstimation of statistical significanceProSightPC+/−a+Fast/Slowb+PIITA+/−−Fast−UStag++Fast−MS-TopDown+−Slow−MS-Align+++Fast+Open in a separate windowa ProSightPC has various search modes that contribute to bridging the gap between blind and restrictive modes of MS/MS database search. It can identify truncated proteins by using biomarker search and identify unexpected modifications by using Δm mode and setting the error tolerance of precursor mass to a large value (e.g., 1999 Da). However, it is not designed for identifying truncated proteins with unexpected PTMs which are not represented in the “shotgun annotated” database.b In its most advances mode, ProSightPC can search the annotated top-down database that contains various protein species. However, ProSightPC searches in this mode become an order of magnitude slower.
  • ProSightPC—ProSightPC is the most commonly used tool for top-down protein identification (22, 23). ProSightPC searches spectra against a “shotgun annotated” protein database, which is generated by considering all expected PTMs. The “shotgun annotated” protein database is much larger than the original protein database. ProSightPC can identify some (but not all) proteins with unexpected PTMs using advanced search options, such as biomarker search and Δm mode, but it is not designed for identifying truncated proteins with unexpected PTMs that are not represented in the “shotgun annotated” database. ProSightPC is a fast tool that reports the statistical significance of PrSMs.
  • PIITA—Unlike ProSightPC, PIITA (19) is a precursor independent method that uses only fragment ions for protein identification. It is capable of identifying protein species with unexpected PTMs on N- or C-termini, but it cannot directly identify protein species with PTMs on both N- and C-termini. PIITA is a fast tool that provides FIT scores and Δ scores rather than statistical significance estimates.
  • USTag—Unique Sequence Tag (USTag) (17) generates long (6 amino acids or longer) peptide sequence tags to identify PrSMs. This approach, although fast, relies on long peptide sequence tags that may be difficult to obtain for some spectra. It also does not provide an estimate of the statistical significance of PrSMs.
  • MS-TopDown—MS-TopDown (24) is based on spectral alignment (25). MS-TopDown allows one to match top-down spectra to proteins with unexpected PTMs, i.e. without knowing which PTMs are present in the sample. However, MS-TopDown is rather slow when searching against large proteomes and does not provide the statistical significance of PrSMs, making it difficult to select good PrSMs.
  • In addition, MASCOT, SEQUEST, and OMSSA (16, 26, 27) have been used for top-down protein identification.
We describe MS-Align+, a fast software tool for top-down protein identification. MS-Align+ shares the spectral alignment approach with MS-TopDown, but greatly improves on speed, statistical analysis (providing E-values of PrSMs), and the number of identified PrSMs (e.g. by finding spectral alignments between spectra and truncated proteins). We benchmarked various tools for top-down protein identification on two data sets from Saccharomyces cerevisiae (SC) and Salmonella typhimurium (ST). We demonstrate that MS-Align+ significantly increase the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the ST data set, MS-Align+ outperforms ProSightPC on the more complex SC data set.  相似文献   

12.
Expression of the Bacillus subtilis acsA Gene: Position and Sequence Context Affect cre-Mediated Carbon Catabolite Repression          下载免费PDF全文
Jill M. Zalieckas  Lewis V. Wray  Jr.    Susan H. Fisher 《Journal of bacteriology》1998,180(24):6649-6654
  相似文献   

13.
Inhibition of Lysine Acetyltransferase KAT3B/p300 Activity by a Naturally Occurring Hydroxynaphthoquinone, Plumbagin     
Kodihalli C. Ravindra  B. Ruthrotha Selvi  Mohammed Arif  B. A. Ashok Reddy  Gali R. Thanuja  Shipra Agrawal  Suman Kalyan Pradhan  Natesh Nagashayana  Dipak Dasgupta    Tapas K. Kundu 《The Journal of biological chemistry》2009,284(36):24453-24464
  相似文献   

14.
Mass Spectrometry Based Glycoproteomics—From a Proteomics Perspective     
Sheng Pan  Ru Chen  Ruedi Aebersold  Teresa A. Brentnall 《Molecular & cellular proteomics : MCP》2011,10(1):R110.003251
Glycosylation is one of the most important and common forms of protein post-translational modification that is involved in many physiological functions and biological pathways. Altered glycosylation has been associated with a variety of diseases, including cancer, inflammatory and degenerative diseases. Glycoproteins are becoming important targets for the development of biomarkers for disease diagnosis, prognosis, and therapeutic response to drugs. The emerging technology of glycoproteomics, which focuses on glycoproteome analysis, is increasingly becoming an important tool for biomarker discovery. An in-depth, comprehensive identification of aberrant glycoproteins, and further, quantitative detection of specific glycosylation abnormalities in a complex environment require a concerted approach drawing from a variety of techniques. This report provides an overview of the recent advances in mass spectrometry based glycoproteomic methods and technology, in the context of biomarker discovery and clinical application.With recent advances in proteomics, analytical and computational technologies, glycoproteomics—the global analysis of glycoproteins—is rapidly emerging as a subfield of proteomics with high biological and clinical relevance. Glycoproteomics integrates glycoprotein enrichment and proteomics technologies to support the systematic identification and quantification of glycoproteins in a complex sample. The recent development of these techniques has stimulated great interest in applying the technology in clinical translational studies, in particular, protein biomarker research.While glycomics is the study of glycome (repertoire of glycans), glycoproteomics focuses on studying the profile of glycosylated proteins, i.e. the glycoproteome, in a biological system. Considerable work has been done to characterize the sequences and primary structure of the glycan moieties attached to proteins (13), and their structural alterations related to cancer (46). Recent reports have provided a comprehensive overview of the concept of glycomics and its prospective in biomarker research (710). In contrast, this review is focused on recent developments in glycoproteomic techniques and their unique application and technical challenge to biomarker discovery.

Glycoproteomics in Biomarker Discovery and Clinical Study

Most secretory and membrane-bound proteins produced by mammalian cells contain covalently linked glycans with diverse structures (2). The glycosylation form of a glycoprotein is highly specific at each glycosylation site and generally stable for a given cell type and physiological state. However, the glycosylation form of a protein can be altered significantly because of changes in cellular pathways and processes resulting from diseases, such as cancer, inflammation, and neurodegeneration. Such disease-associated alterations in glycoproteins can happen in one or both of two ways: 1) protein glycosylation sites are either hypo, hyper, or newly glycosylated and/or; 2) the glycosylation form of the attached carbohydrate moiety is altered. In fact, altered glycosylation patterns have long been recognized as hallmarks in cancer progression, in which tumor-specific glycoproteins are actively involved in neoplastic progression and metastasis (5, 6, 11, 12). Sensitive detection of such disease-associated glycosylation changes and abnormalities can provide a unique avenue to develop glycoprotein biomarkers for diagnosis and prognosis. In addition, intervention in the glycosylation and carbohydrate-dependent cellular pathways represent a potential new modality for cancer therapies (6, 11, 13). 14, 15) that are glycosylated proteins or protein complexes.

Table I

Listing of some of the US Food and Drug Administration (FDA) approved cancer biomarkers
Protein targetGlycosylationDetectionSourceDiseaseClinical biomarker
α-FetoproteinYesGlycoproteinSerumNonseminomatous testicular cancerDiagnosis
Human chorionic gonadotropin-βYesGlycoproteinSerumTesticular cancerDiagnosis
CA19–9YesCarbohydrateSerumPancreatic cancerMonitoring
CA125YesGlycoproteinSerumOvarian cancerMonitoring
CEA (carcinoembryonic antigen)YesProteinSerumColon cancerMonitoring
Epidermal growth factor receptorYesProteinTissueColon cancerTherapy selection
KITYesProtein (IHC)TissueGastrointestinal (GIST) cancerDiagnosis/Therapy selection
ThyroglobulinYesProteinSerumThyroid cancerMonitoring
PSA-prostate-specific antigen (Kallikrein 3)YesProteinSerumProstate cancerScreening/Monitoring/Diagnosis
CA15–3YesGlycoproteinSerumBreast cancerMonitoring
CA27–29YesGlycoproteinSerumBreast cancerMonitoring
HER2/NEUYesProtein (IHC), ProteinTissue, SerumBreast cancerPrognosis/Therapy selection/Monitoring
Fibrin/FDP-fibrin degradation proteinYesProteinUrineBladder cancerMonitoring
BTA-bladder tumour-associated antigen (Complement factor H related protein)YesProteinUrineBladder cancerMonitoring
CEA and mucin (high molecular weight)YesProtein (Immunofluorescence)UrineBladder cancerMonitoring
Open in a separate windowProtein biomarker development is a complex and challenging task. The criteria and approach applied for developing each individual biomarker can vary, depending on the purpose of the biomarker and the performance requirement for its clinical application (16, 17). In general, it has been suggested that the preclinical exploratory phase of protein biomarker development can be technically defined into four stages (18), including initial discovery of differential proteins; testing and selection of qualified candidates; verification of a subset of candidates; assay development and pre-clinical validation of potential biomarkers. Thanks to recent technological advances, mass spectrometry based glycoproteomics is now playing a major role in the initial phase of discovering aberrant glycoproteins associated with a disease. Glycoprotein enrichment techniques, coupled with multidimensional chromatographic separation and high-resolution mass spectrometry have greatly enhanced the analytical dynamic range and limit of detection for glycoprotein profiling in complex samples such as plasma, serum, other bodily fluids, or tissue. In addition, candidate-based quantitative glycoproteomics platforms have been introduced recently, allowing targeted detection of glycoprotein candidates in complex samples in a multiplexed fashion, providing a complementary tool for glycoprotein biomarker verification in addition to antibody based approaches. It is clear that glycoproteomics is gaining momentum in biomarker research.

Glycoproteomics Approaches

Glycoproteomic analysis is complicated not only by the variety of carbohydrates, but also by the complex linkage of the glycan to the protein. Glycosylation can occur at several different amino acid residues in the protein sequence. The most common and widely studied forms are N-linked and O-linked glycosylation. O-linked glycans are linked to the hydroxyl group on serine or threonine residues. N-linked glycans are attached to the amide group of asparagine residues in a consensus Asn-X-Ser/Thr sequence (X can be any amino acid except proline) (19). Other known, but less well studied forms of glycosylation include glycosylphosphatidylinositol anchors attached to protein carboxyl terminus, C-glycosylation that occurs on tryptophan residues (20), and S-linked glycosylation through a sulfur atom on cysteine or methionine (21, 22). Our following discussion is focused on glycoproteomic analysis of the most common N-linked and O-linked glycoproteins.A comprehensive analysis of glycoproteins in a complex biological sample requires a concerted approach. Although the specific methods for sample preparation can be different for different types of samples (e.g. plasma, serum, tissue, and cell lysate), a glycoproteomics pipeline typically consists of glycoprotein or glycopeptide enrichment, multidimensional protein or peptide separation, tandem mass spectrometric analysis, and bioinformatic data interpretation. For glycoprotein-based enrichment methods, proteolytic digestion can be performed before or after glycan cleavage, depending on the specific workflow and enrichment methods used. For glycopeptide enrichment, proteolytic digestion is typically performed before the isolation step so that glycopeptides, instead of glycoproteins, can be captured. For quantitative glycoproteomics profiling, additional steps, such as differential stable isotope labeling of the sample and controls, are required. Fig. 1 illustrates the general strategy for an integrated glycoproteomics analysis.Open in a separate windowFig. 1.The strategies of mass spectrometry based glycoproteomic analysis.Glycoproteins or glycopeptides can be effectively enriched using a variety of techniques (see below). Following the enrichment step, the workflow then splits into two directions: glycan analysis and glycoprotein analysis. The strategies for glycan analysis have been discussed in several reviews and will not be covered in this report. For glycoprotein analysis, bottom-up workflows (“shotgun proteomics”—peptide based proteomics analysis) (23) are still most common, providing not only detailed information of a glycoprotein profile, but also the specific mapping of glycosylation sites. It is notable that the reliable analysis of mass spectrometric data in glycoproteomic studies largely relies on bioinformatic tools and glyco-related databases that are available. An increasing number of algorithms and databases for glycan analysis have been developed and well documented in several recent reviews (2426). For glycoprotein and glycopeptide sequence analysis, a large number of well-characterized and annotated glycoproteins can be found in the UniProt Knowledgebase. In addition, many glycopeptide mass spectra are now available in the continually expanding PeptideAtlas library (27), which stores millions of high-resolution peptide fragment ion mass spectra acquired from a variety of biological and clinical samples for peptide and protein identification. Ultimately, all the data obtained from different aspects of the workflow need to be merged and interpreted in an integrated fashion so that the full extent of glycosylation changes associated with a particular biological state can be better revealed. To the best of our knowledge, the complete glycoform analysis of any glycoprotein in a specific cell type under any specific condition has not yet been accomplished for any glycoprotein with multiple glycosylation sites. Current technology can define the glycan compliment and profile the glycoproteins, but is not capable of putting them together to define the molecular species present. To date, such integrated studies still remain highly challenging, even with advanced tandem mass spectrometry technologies and growing bioinformatic resources (26, 2831).

Enrichment of the Glycoproteome

Characterization of the glycoproteome in a complex biological sample such as plasma, serum, or tissue, is analytically challenging because of the enormous complexity of protein and glycan constituents and the vast dynamic range of protein concentration in the sample. The selective enrichment of the glycoproteome is one of the most efficient ways to simplify the enormous complexity of a biological sample to achieve an in-depth glycoprotein analysis. Two approaches for glycoprotein enrichment have been widely applied: lectin affinity based enrichment methods (3136) and hydrazide chemistry-based solid phase extraction methods (3742). Recent studies have demonstrated that the two methods are complementary and a very effective means for the enrichment of glycoproteins or glycopeptides from human plasma and other bodily fluids (38, 39, 43). In addition, glycoprotein and glycopeptide enrichment using boronic acid (44, 45), size-exclusion chromatography (46), hydrophilic interaction (47) and a graphite powder microcolumn (48) have been reported.Lectin affinity enrichment is based on the specific binding interaction between a lectin and a distinct glycan structure attached on a glycoprotein (49, 50). There are a variety of lectin species that can selectively bind to different oligosaccharide epitopes. For instance, concanavalin A (ConA) binds to mannosyl and glucosyl residues of glycoproteins (51); wheat germ agglutinin (WGA) binds to N-acetyl-glucosamine and sialic acid (52); and jacalin (JAC) specifically recognizes galactosyl (β-1,3) N acetylgalactosamine and O-linked glycoproteins (53). Lectin affinity enrichment has been designed to enrich glycoproteins with specific glycan attachment from plasma, serum, tissue, and other biological samples through affinity chromatography and other methods. Multiple lectin species can also be combined to isolate multiple types of glycoproteins in complex biological samples (5459). Concanavalin A and wheat germ agglutinin, as well as jacalin are often used together to achieve a more extensive glycproteome characterization (31, 34, 57, 59, 60). Several reports have demonstrated a multilectin column approach to achieve a global enrichment of glycoproteins with various glycan attachments from serum and plasma (31, 34, 59, 61, 62). A recent study has developed a “filter aided sample preparation (FASP)” based method, which allows highly efficient enrichment of glycopeptides using multi-lectins (63). To date, most of the work using lectin affinity for targeted glycoprotein enrichment has focused on N-glycosylation because the binding specificity of lectin for O-glycosylation is less satisfactory. To overcome such caveat, efforts have been made using serial lectin columns of concanavalin A and jacelin in tandem to isolate O-glycopeptides from human serum (35).A hydrazide chemistry-based method has been applied to isolate glycoproteins and glycopeptides through the formation of covalent bonding between the glycans and the hydrazide groups (37). The carbohydrates on glycoproteins are first oxidized to form aldehyde groups, which sequentially react with hydrazide groups that are immobilized on a solid surface. The chemical reaction conjugates the glycoproteins to the solid phase by forming the covalent hydrazone bond. Although, conceptually, the majority of the glycoproteins in a biological sample can be captured using this method, the further analysis of the captured glycoproteins is practically limited by the method that can cleave glycoproteins or glycopeptides from the solid phase. Because there is a lack of efficient enzymes or chemicals that can specifically deglycosylate and/or release O-linked glycoproteins or glycopeptides from the solid phase, most of the studies have applied this method solely for N-linked glycoprotein analysis. PNGase F is the enzyme that can specifically release an N-glycosylated proteins or peptides (except those carrying α1→3 linked core fucose (38)) from its corresponding oligosaccharide groups. The hydrazide chemistry method is not only highly efficient in enriching N-linked glycoproteins or glycopeptides from a complex environment, but also allows great flexibility in its applications, such as capturing extracellular N-glycoproteins on live cells to monitor their abundant changes because of cell activation, differentiation, or other cellular activities (64). This method can be readily automated for analyzing a large quantity of samples.Recent studies have compared glycoprotein isolation methods. One study assessed lectin-based protocols and hydrophilic interaction chromatography for their performance in enriching glycoproteins and glycopeptides from serum (65). Other studies compared lectin affinity and hydrazide chemistry methods for their efficiency in isolating glycoproteins and glycopeptides from a complex biological sample (39, 66, 67). The methods are complementary in enriching glycoproteins because of their different mechanisms of glycoprotein capturing. When both methods were applied, it significantly improves the coverage of the glycoproteome, resulting in an increased number of glycoproteins identified. The lectin affinity method can be tailored to target glycoproteins with specific glycan structure(s) for isolation using different lectins, thus, affording flexibility for its application in glycoproteomic studies. The application of hydrazide chemistry method has been widely used for N-linked glycosylation study. The hydrazide chemistry essentially reacts with all the proteins with carbonyl groups, which may include glycoproteins with oxidized glycans (37, 40) and other oxidized proteins that carry carbonyl groups (6870). The high specificity of this method may mainly result from the specificity of PNGase F, the enzyme cleaving N-glycosidic bonds to release N-glycoproteins and peptides from the solid phase. This method affords high efficiency and specificity in enriching N-linked glycoproteins or glycopeptides from a complex sample, and can be easily incorporated into a proteomics workflow for integrated analysis. In addition to the lectin and hydrazide chemistry-based methods, it has been suggested that boronic acid-based solid phase extraction may also be useful for an overall glycoproteome enrichment (44, 45), on the basis of the evidence that boronic acid can form diester bonds with most glycans, including both N-linked and O-linked glycosylation (71).

Mass Spectrometric Analysis of Glycoproteome

Mass spectrometry, because of its high sensitivity and selectivity, has been one of the most versatile and powerful tools in glycoprotein analysis, to identify the glycoproteins, evaluate glycosylation sites, and elucidate the oligosaccharide structures (56, 72, 73). The utility of a top-down approach (intact protein based proteomics analysis) (74) for glycoprotein characterization in a complex sample is still technically challenging with the current technology. The most versatile and widely used current glycoproteomics methods are based on characterizing glycopeptides generated by the digestion of glycoproteins, analyzing either deglycosylated glycopeptides or intact glycopeptides with glycan attachment, as illustrated in Fig. 1.The direct analysis of intact glycopeptides with carbohydrate attachments is complicated by the mixed information obtained from the fragment ion spectra, which may include fragment ions from the peptide backbone, the carbohydrate group and the combinations of both. Although it is technically challenging to comprehensively analyze intact glycopeptides in a global scale for a complex biological sample, complementary information regarding peptide backbone and glycan structure can likely be obtained in a single measurement. Early work using collision-induced dissociation (CID)1 has identified a few key features that are characteristics of the fragmentation of glycopeptides, providing the basis for intact glycopeptide identification (7579). The analysis of intact glycopeptides has been carried out using a variety of different instruments, including electrospray ionization (EST)-based ion trap (IT) (8084), quadrupole ion trap (QIT) (8587), Fourier transform ion cyclotron resonance (FTICR) (31, 57, 88, 89), ion trap/time-of-flight (IT/TOF) (90, 91), and quadrupole/time-of-flight (Q/TOF) (9297); matrix-assisted laser desorption/ionization (MALDI) based Q/TOF (98100), quadrupole ion trap/time-of-flight (QIT/TOF) (86, 101, 102), and tandem time-of-flight (TOF/TOF) (81, 82, 101, 103105) mass spectrometers. In general, the CID generated MS/MS spectrum of a glycopeptide is dominated by B- and Y-type glycosidic cleavage ions (carbohydrate fragments) (106), and b- and y-type peptide fragments from the peptide backbone. However, the MS/MS fragmentation data obtained from different instruments can have pronounced difference in providing structure information on glycan and peptide backbone, depending on the experimental setting and instrumentation used for mass analysis, including ionization methods, collision techniques and mass analyzers. Low energy CID with electrospray ionization-based ion trap, Fourier transform-ion cyclotron resonance, and Q/TOF instrument predominantly generates fragments of glycosidic bonds. The increase of collision energy using Fourier transform-ion cyclotron resonance, and Q/TOF instruments result in the more efficient fragmentation of b- and y- ions from the peptide backbone. MALDI ionization generates predominantly singly charged precursor ions, which are more stable and usually fragmented using higher energies via CID or post-source decay (PSD), generating fragments from both the peptide backbone and the glycan (98100, 103, 107110). Although Q/TOF instruments have been widely used for intact glycopeptide characterization, one unique feature of the ion trap instrument is that it allows repeated ion isolation/CID fragmentation cycles, which can provide a wealth of complementary information to interpret the structure of a glycan moiety and peptide backbone (56, 86, 111). Recently, fragmentation techniques using different mechanisms from CID have been introduced and applied for glycopeptide analysis, including infrared multiphoton dissociation (IRMPD) (112115), electon-capture dissociation (ECD) (112120) and electron-transfer disassociation (ETD) (85, 121123). The application of infrared multiphoton dissociation and electon-capture dissociation is largely performed with Fourier transform-ion cyclotron resonance instruments. Complementary to CID fragmentation, electon-capture dissociation and electron-transfer disassociation tend to cleave the peptide backbone with no loss of the glycan moiety, providing specific information on localizing the glycosidic modification. More details regarding mass spectrometric analysis of intact glycopeptides can be found in recent reviews (56, 124). Although great efforts have been made to apply a variety of mass spectrometry techniques to study both N-linked (32, 56, 86, 87, 112114, 125130) and O-linked (90, 116, 119, 120, 130140) glycopeptides, the interpretation of the fragment spectrum of an intact glycopeptide still requires intensive manual assignment and evaluation. A recent study has demonstrated the feasibility to develop an automated workflow for analyzing intact glycopeptides in mixtures (141). In general, however, a high throughput, large scale profiling of intact glycopeptides in a complex sample still remains a challenge with current technology.The analysis of deglycosylated peptides requires the removal of glycan attachments from glycopeptides. Fortunately, for N-linked glycopeptides, the N-glycosidic bond can be specifically cleaved using the enzyme PNGase F, providing deglycosylated peptides, which can then be analyzed directly using shotgun proteomics. The PNGase F-catalyzed deglycosylation results in the conversion of asparagine to aspartic acid in the glycopeptide sequence, which introduces a mass difference of 0.9840 Da. Such distinct mass differences can be used to precisely map the N-linked glycosylation sites using high resolution mass spectrometers. Stable isotope labeling introduced by enzymatic cleavage of glycans in H218O has also been used to enhance the precise identification of N-glycosylation sites (33, 142, 143). The removal of O-linked glycans is less straightforward, most assays rely on chemical deglycosylation methods, such as trifluoromethansulfonic acid (144), hydrazinolysis (145), β-elimination (146), and periodate oxidation (35, 147). The application of these methods suffers from a variety of limitations, such as low specificity for O-linked glycosylation, degradation of the peptide backbone, and modifications of the amino acid residues—all of which can complicate or compromise O-linked glycoproteomics analysis in a complex sample. Most of the large scale glycoproteomics studies using the deglycosylation approach have been focused on N-glycoproteins, which are prevalent in blood and a rich source for biomarker discovery. O-glycosylation lacks a common core, consensus sequence, and universal enzyme that can specifically remove the glycans from the peptide backbone, thus, is more challenging to analyze for large scale profiling.Following deglycosylation, the glycopeptides can be treated and analyzed as stripped peptides using a shotgun proteomics pipeline. MS/MS fragment spectra with b-ions and y-ions generated from CID are searched against protein databases using search algorithms, such as SEQUEST (148), MASCOT (149), and X!tandem (150), and subsequently validated via statistical analysis (151154), to provide peptide and protein identifications with known false discovery rate. The N-glycosylation sites can be precisely mapped using the consensus sequence of Asn-X-Ser/Thr, in which asparagine is converted to aspartic acid following enzyme cleavage introducing a mass difference of 0.9840 Dalton. A variety of mass spectrometers have been used to analyze glycoproteins, in particular N-linked glycoproteins, in complex biological and clinical samples using the deglycosylation approach. These studies include electrospray ionization-based ion trap (3739, 41, 67, 155157), Orbitrap (158), Q/TOF (33, 35, 142, 155), triple quadrupole (159), Fourier transform-ion cyclotron resonance (64, 160); and MALDI based TOF/TOF (41, 161) and Q/TOF (37). Recently, an attempt was made to apply ion mobility-mass spectrometry (IM-MS) to characterize deglycosylated glycopeptides and the corresponding carbohydrates simultaneously (162) in a single measurement. The approach of analyzing deglycosylated glycopeptides makes it possible to utilize available proteomics technology for large-scale glycoproteome profiling, especially N-linked glycoproteins, in a high-throughput fashion.

Glycoproteomics Analysis in Blood and Other Bodily Fluids

An important target for blood-based diagnostic assays involves the detection and quantification of glycosylated proteins. Glycosylated proteins, especially N-linked glycoproteins, are ubiquitous among the proteins destined for extracellular environments (163), such as plasma or serum. A systematic and in-depth global profiling of the blood glycoproteome can provide fundamental knowledge for blood biomarker development, and is now possible with the development of glycoproteomics technologies. In the past few years, several large scale proteomics studies on profiling the glycoproteome of human plasma and serum have been reported (34, 35, 37, 38, 43, 61, 65, 164166), adding significant numbers of glycoproteins into the blood glycoproteome database. In one study (38), immunoaffinity subtraction and hydrazide chemistry were applied to enrich N-glycoproteins from human plasma. The captured plasma glycoproteins were subjected to two-dimensional liquid chromatography separation followed by tandem mass spectrometric analysis. A total of 2053 different N-glycopeptides were identified, covering 303 nonredundant glycoproteins, including many glycoproteins with low abundance in blood (38). In a different study, hydrazide chemistry-based solid phase extraction method was applied to enhance the detection of tissue-derived proteins in human plasma (167). Other studies have applied lectin affinity-based approaches to characterize the serum and plasma glycoproteome (34, 43, 166). These studies provide detailed identification regarding the individual N-glycosylation sites using high-resolution mass spectrometry. The efforts made in global profiling of glycoproteins in plasma and serum have not only greatly enhanced our understanding of the blood glycoproteome, but also have facilitated the development of new technologies that can be used for glycoprotein biomarker discovery. A variety of experimental designs and strategies for blood glycoprotein profiling have been applied for clinical disease studies, including prostate cancer (168), hepatocellular carcinoma (164, 168170), lung adenocarcinoma (61, 171), breast cancer (58, 165, 172), atopic dermatitis (169), ovarian cancer (173, 174), congenital disorders of glycosylation (175), and pancreatic cancer (156, 176). Most of these studies focused on the early stages of glycoprotein biomarker discovery and many of them exploited multilectin affinity techniques to isolate glycoproteins from serum or plasma.Glycoproteomics techniques have also been applied to study the glycoproteome of other bodily fluids. The complementary application of hydrazide chemistry-based solid phase extraction and lectin affinity method have led to the identification of 216 glycoproteins in human cerebrospinal fluid (CSF), including many low abundant ones (39). A hydrazide chemistry based study on human saliva has characterized 84 N-glycosylated peptides in 45 glycoproteins (177). The study on tear fluid identified 43 N-linked glycoproteins, including 19 proteins that have not been discovered in tear fluid previously (178). Other glycoproteomics studies on bodily fluids include N-glycoprotein profiling of lung adenocarcinoma pleural effusions (179), urine glycoprotein profiling (180), and urine glycoprotein signature identification for bladder cancer (181). In the urine glycoprotein profiling study, 150 annotated glycoproteins in addition to 43 predicted glycoproteins were identified (180). In our own study, 48 glycoproteins have so far been identified in pancreatic juice (unpublished data), adding complementary information to the pancreatic juice protein database (182184).

Glycoproteomics Analysis of Tissue and Cell Lysates

Protein glycosylation has been increasingly recognized as one of the prominent alterations involved in tumorigenesis, inflammation, and other disease states. The study of glycoproteins in cell and tissue carries great promise for defining biomarkers for diagnotic and therapeutic targets. The glycoproteomics studies in liver tissue (185, 186) and cell lines (187) have provided a fundamental understanding of the liver glycoproteome and identified protein candidates that are associated with highly metastatic liver cancer cells. In one of the studies, hydrazide chemistry and multiple enzyme digestion provided a complementary identification of 939 N-glycosylation sites covering 523 nonredundant glycoproteins in human liver tissue (185). Studies on ovarian cancer have focused on discovering putative glycoprotein biomarkers for improving diagnosis (173, 174) and therapeutic treatment (188). Glycoproteomics studies have also been carried out to study hepatocelluar carcinoma. Magnetic nanoparticle immobilized Concanavalin A was used to selectively enrich N-glycoproteins in a hepatocelluar carcinoma cell line leading to the identification of 184 glycosylation sites corresponding to 101 glycoproteins (189). In a different study, complementary methods of hydrophilic affinity and hydrazide chemistry were applied to investigate the secreted glycoproteins from a hepatocelluar carcinoma cell line, in which 300 different glycosylation sites within 194 glycoproteins were identified (190). While many of these studies focused on N-glycoproteins, mucin-type O-linked glycoproteins are the predominant forms of O-linked glycosylation and are difficult to analyze. A metabolic labeling method was developed to facilitate their identification in complex cell lysates using proteomic strategies (191).Cell surface and membrane proteins are particularly appealing for biomarker discovery, and many of them are glycosylated proteins. Both hydrazide chemistry- and lectin affinity-based approaches have been applied to specifically study cell surface and membrane N-glycoproteins that are associated with diseases, including colon carcinoma (192), breast cancer (158), and thyroid cancer (157). One study applied hydrazide chemistry to covalently label extracellular glycan moieties on live cells, providing highly specific and selective identification of cell surface N-glycoproteins (64). A complementary application of hydrazide chemistry and lectin affinity methods was demonstrated to profile cell membrane glycoproteins, significantly enhancing the glycoprotein identification (67).

Quantitative Glycoprotein Profiling

One of the major goals of clinical proteomics is to effectively identify dysregulated proteins that are specifically associated with a biological state, such as a disease. In the past decade, different quantitative proteomics techniques have been introduced and applied to study a wide variety of disease settings. These techniques are based on different mechanisms to facilitate mass spectrometric-based quantitative analysis, including stable isotopic or isobaric labeling using chemical reactions (e.g. ICAT and iTRAQ) (193195), metabolic incorporation (e.g. SILAC) (196) and enzymatic reactions (e.g. 18O labeling) (197, 198); as well as less quantitatively accurate label-free approaches (199, 200). The overview and comparison of these quantitative techniques can be found in several reports in the literature and are not discussed in this review. Most of these isotopic labeling techniques can be adapted and utilized for glycoproteomics analysis to quantitatively compare the glycoproteome of a diseased sample to a control, thus revealing the glycosylation occupancy of individual glycosylation sites that may be involved in a disease. In addition to the well-established labeling methods cited above, several more experimental labeling strategies have been described in the field of glycoproteomics. One study demonstrated the feasibility of using stable isotope labeled succinic anhydride for quantitative analysis of glycoproteins isolated from serum via hydrazide chemistry (37). In a different report, the heavy and light version of N-acetoxy-succinimide combining with lectin affinity selection was used to quantitatively profile serum glycopeptides in canine lymphoma and transitional cell carcinoma (201). Stable isotope labeled 2-nitrobenzenesulfenyl was also used for chemical labeling in a quantitative glycoprotein profiling study on the sera from patients with lung adenocarcinoma (202). O-Linked N-acetylglucosamine (O-GlcNAc) is an intracellular, reversible form of glycosylation that shares many features with phosphorylation (203). Studies have suggested that O-GlcNAc may play an important role in many biological processes (204). A quantitative study on O-GlcNAc glycosylation has been reported, in which a method termed quantitative isotopic and chemoenzymatic tagging (QUIC-Tag) was described using a biotin-avidin affinity strategy for O-GlcNAc glycopeptide enrichment and stable isotope-labeled formaldehyde for mass spectrometric quantification (205). Recently, the isobaric tag for relative and absolute quantitation (iTRAQ) technique, combined with different glycoprotein enrichment approaches, has been utilized in several quantitative glycoproteomics studies. In the study of hepatocellular carcinoma, N-linked glycoproteins were enriched from hepatocellular carcinoma patients and controls using multilectin column and then quantitatively compared using iTRAQ to reveal the differential proteins associated with hepatocellular carcinoma (206). In a different study, the approach of using narrow selectivity lectin affinity chromatography followed by iTRAQ labeling was demonstrated to selectively identify differential glycoproteins in plasma samples from breast cancer patients (165). Another study utilized hydrazide chemistry-based solid phase extraction and iTRAQ to investigate the tear fluid of patients with climatic droplet keratopathy in comparison of normal controls, identifying multiple N-glycosylation sites with differential occupancy associated with climatic droplet keratopathy (178).In addition to using chemical reactions to incorporate stable isotope tag for quantitative mass spectrometric analysis, 18O can be introduced into N-glycopeptides during enzymatic reactions, such as tryptic digestion (incorporation of two 18O into the peptide carboxyl-terminal) and PNGase F mediated hydrolysis (incorporation of one 18O into the asparagine of N-glycosylation sites (33)). Attempts have been made to apply this approach to identify differentially expressed N-glycosylation associated with ovarian cancer in serum (207). In a different approach, the SILAC technique allows incorporation of stable isotope-labeled amino acids into proteins during cell culturing process (196), and was applied to investigate the difference in cell surface N-glycoproteins among different cell types (64). A label-free approach has also been used for glycoproteomics profiling, including a method developed to profile intact glycopeptides in a complex sample (208) and a study that compares the plasma glycoproteome between psoriasis patients and healthy controls (209).

Targeted Glycoproteomics Analysis

Mass spectrometry based targeted proteomics has recently emerged as a multiplexed quantitative technique that affords highly specific and candidate-based detection of targeted peptides and proteins in a complex biological sample (18, 210214). The technique is based on the concept of stable isotope dilution utilizing stable isotope-labeled synthetic reference peptides, which precisely mimic their endogenous counterparts, to achieve targeted quantification (214). Such techniques can be applied to target specific glycoproteins or glycopeptides, to precisely quantify the status of candidate glycosylation sites and assess the glycosylation occupancy at the molecular level. However, it is technically impractical to use synthetic peptides to precisely mimic a large number of natural glycopeptides with intact a glycan moiety as internal standards because of the structure complexity and variation of the sugar chain. To overcome these technical obstacles, an alternative approach was proposed for targeted analysis of N-glycosylation occupancy, in which stable isotope-labeled peptides were synthesized to mimic the deglycosylated form of candidate glycopeptides as internal references (161). It is known that the deglycosylation step using PNGase F results in a conversion of asparagine to aspartic acid in the peptide sequence, introducing a mass difference of 0.9840 Da. This phenomenon was utilized to design a synthetic peptide to mimic the endogenous N-linked glycopeptide in its deglycosylation form with exact amino acid sequence of its endogenous counterpart and with 13C and 15N labeling on one of its amino acids (161). Therefore, each matched pair of reference and endogenous candidate glycopeptides should share the same chromatographic and mass spectrometric characteristics, and can only be distinguished by their mass difference and isotopic pattern because of isotopic labeling. This design conceptually ensures that the synthetic internal standard of a candidate glycopeptide will be detected simultaneously with its endogenous form under the same analytical conditions, thus, minimizing the systematic variation and providing reliable quantification (214). The strategy for targeted glycoproteomics analysis is schematically illustrated in Fig. 2.Open in a separate windowFig. 2.Targeted analysis of N-glycopeptides.The targeted glycoproteomics technique was first demonstrated to analyze N-glycopeptides that were extracted from human serum using an integrated pipeline combining a hydrazide chemistry-based solid phase extraction method and a data-driven liquid chromatography MALDI TOF/TOF mass spectrometric analysis to quantify 21 N-glycopeptides in human serum (161). A similar mass spectrometric platform was then applied in a different study to assess a subset of glycoprotein biomarker candidates in the sera from prostate cancer patients (215). The targeted glycoproteomics analysis has also been demonstrated using a triple Q/linear ion trap instrument with the selected reaction monitoring (also referred to as multiple reaction monitoring) technique for highly sensitive targeted detection of N-glycoproteins in plasma (159). The technique was applied to detect tissue inhibitor of metalloproteinase 1 (TIMP1), an aberrant glycoprotein associated with colorectal cancer, in the sera of colorectal cancer patients (216) using a tandem enrichment strategy, combing lectin glycoprotein enrichment followed by the method of stable isotope standards and capture by antipeptide antibodies (SISCAPA), to enhance the detection of tissue inhibitor of metalloproteinase 1 (216). These studies demonstrate an integrated pipeline for candidate-based glycoproteomics analysis with precise mapping of targeted N-linked motifs and absolute quantification of the glycoprotein targets in a complex biological sample. Such targeted glycoproteomics can reach a detection sensitivity at the nanogram per milliliter level for serum and plasma detection (159, 214216).

Concluding Remarks

The major challenge for a comprehensive glycoproteomics analysis arises not only from the enormous complexity and nonlinear dynamic range in protein constituent in a clinical sample, but also the profound biological intricacy within the molecule of a glycoprotein, involving the flexibility in glycan structures and the complex linkage with the corresponding protein. In the past decade, significant efforts have been made to structurally or quantitatively characterize the glycoproteome of a variety of biological samples, and to investigate the significant glycoproteins in a wide assortment of diseases. Shotgun proteomics-based techniques are still the most effective and versatile approach in glycoproteomics analysis, allowing high throughput and detailed analysis on individual glycosylation sites. Although glycoproteomics is quickly emerging as an important technique for clinical proteomics study and biomarker discovery, a comprehensive, quantitative glycoproteomics analysis in a complex biological sample still remains challenging. It is anticipated that with the continued evolution in mass spectrometry, separation technology, and bioinformatics many of the technical limitations associated with current glycoproteomics may be transient. There is no doubt that glycoproteomics is playing an increasingly important role in biomarker discovery and clinical study.  相似文献   

15.
Normalization and Statistical Analysis of Multiplexed Bead-based Immunoassay Data Using Mixed-effects Modeling     
David C. Clarke  Melody K. Morris  Douglas A. Lauffenburger 《Molecular & cellular proteomics : MCP》2013,12(1):245-262
  相似文献   

16.
Peptidoglycan Fine Structure of the Radiotolerant Bacterium Deinococcus radiodurans Sark     
José Carlos Quintela  Francisco García-del Portillo  Ernst Pittenauer  Günter Allmaier  Miguel A. de Pedro 《Journal of bacteriology》1999,181(1):334-337
Peptidoglycan from Deinococcus radiodurans was analyzed by high-performance liquid chromatography and mass spectrometry. The monomeric subunit was: N-acetylglucosamine–N-acetylmuramic acid–l-Ala–d-Glu-(γ)–l-Orn-[(δ)Gly-Gly]–d-Ala–d-Ala. Cross-linkage was mediated by (Gly)2 bridges, and glycan strands were terminated in (1→6)anhydro-muramic acid residues. Structural relations with the phylogenetically close Thermus thermophilus are discussed.The gram-positive bacterium Deinococcus radiodurans is remarkable because of its extreme resistance to ionizing radiation (14). Phylogenetically the closest relatives of Deinococcus are the extreme thermophiles of the genus Thermus (4, 11). In 16S rRNA phylogenetic trees, the genera Thermus and Deinococcus group together as one of the older branches in bacterial evolution (11). Both microorganisms have complex cell envelopes with outer membranes, S-layers, and ornithine-Gly-containing mureins (7, 12, 19, 20, 22, 23). However, Deinococcus and Thermus differ in their response to the Gram reaction, having positive and negative reactions, respectively (4, 14). The murein structure for Thermus thermophilus HB8 has been recently elucidated (19). Here we report the murein structure of Deinococcus radiodurans with similar detail.D. radiodurans Sark (23) was used in the present study. Cultures were grown in Luria-Bertani medium (13) at 30°C with aeration. Murein was purified and subjected to amino acid and high-performance liquid chromatography (HPLC) analyses as previously described (6, 9, 10, 19). For further analysis muropeptides were purified, lyophilized, and desalted as reported elsewhere (6, 19). Purified muropeptides were subjected to plasma desorption linear time-of-flight mass spectrometry (PDMS) as described previously (1, 5, 16, 19). Positive and negative ion mass spectra were obtained on a short linear 252californium time-of-flight instrument (BioIon AB, Uppsala, Sweden). The acceleration voltage was between 17 and 19 kV, and spectra were accumulated for 1 to 10 million fission events. Calibration of the mass spectra was done in the positive ion mode with H+ and Na+ ions and in the negative ion mode with H and CN ions. Calculated m/z values are based on average masses.Amino acid analysis of muramidase (Cellosyl; Hoechst, Frankfurt am Main, Germany)-digested sacculi (50 μg) revealed Glu, Orn, Ala, and Gly as the only amino acids in the muramidase-solubilized material. Less than 3% of the total Orn remained in the muramidase-insoluble fraction, indicating an essentially complete solubilization of murein.Muramidase-digested murein samples (200 μg) were analyzed by HPLC as described in reference 19. The muropeptide pattern (Fig. (Fig.1)1) was relatively simple, with five dominating components (DR5 and DR10 to DR13 [Fig. 1]). The muropeptides resolved by HPLC were collected, desalted, and subjected to PDMS. The results are presented in Table Table11 compared with the m/z values calculated for best-matching muropeptides made up of N-acetylglucosamine (GlucNAc), N-acetylmuramic acid (MurNAc), and the amino acids detected in the murein. The more likely structures are shown in Fig. Fig.1.1. According to the m/z values, muropeptides DR1 to DR7 and DR9 were monomers; DR8, DR10, and DR11 were dimers; and DR12 and DR13 were trimers. The best-fitting structures for DR3 to DR8, DR11, and DR13 coincided with muropeptides previously characterized in T. thermophilus HB8 (19) and had identical retention times in comparative HPLC runs. The minor muropeptide DR7 (Fig. (Fig.1)1) was the only one detected with a d-Ala–d-Ala dipeptide and most likely represents the basic monomeric subunit. The composition of the major cross-linked species DR11 and DR13 confirmed that cross-linking is mediated by (Gly)2 bridges, as proposed previously (20). Open in a separate windowFIG. 1HPLC muropeptide elution patterns of murein purified from D. radiodurans. Muramidase-digested murein samples were subjected to HPLC analysis, and the A204 of the eluate was recorded. The most likely structures for each muroeptide as deduced by PDMS are shown. The position of residues in brackets is the most likely one as deduced from the structures of other muropeptides but could not be formally demonstrated. R = GlucNac–MurNac–l-Ala–d-Glu-(γ)→.

TABLE 1

Calculated and measured m/z values for the molecular ions of the major muropeptides from D. radiodurans
MuropeptideaIonm/z
ΔmbError (%)cMuropeptide composition
Muropeptide abundance (mol%)
CalculatedMeasuredNAGdNAMeGluOrnAlaGly
DR1[M+H]+699.69700.10.410.0611101012.0
DR2[M+H]+927.94928.30.360.041111125.7
DR3[M+Na]+1,006.971,007.50.530.051111133.0
DR4[M+Na]+963.95964.60.650.071111212.5
DR5[M+H]+999.02999.80.780.0811112227.7
[M−H]997.00997.30.300.03
DR6[M+Na]+1,078.51,078.80.750.071111232.4
DR7[M+H]+1,070.091,071.00.900.081111322.2
DR8[M+Na]+1,520.531,521.61.080.071122442.2
DR9[M+Na]+701.64702.10.460.0311f10105.0
DR10[M+H]+1,907.941,907.80.140.0122223410.1
[M−H]1,905.921,906.60.680.04
DR11[M+H]+1,979.011,979.10.090.0122224419.1
[M−H]1,977.001,977.30.300.02
DR12[M+H]+2,887.932,886.5−1.43−0.053333564.4
[M−H]2,885.912,885.8−0.11−0.01
DR13[M+H]+2,959.002,957.8−1.20−0.043333663.6
[M−H]2,956.992,955.9−1.09−0.04
Open in a separate windowaDR5 and DR10 to DR13 were analyzed in both the positive and negative ion modes. Muropeptides DR1 to DR4 and DR6 to DR9 were analyzed in the positive mode only due to the small amounts of sample available. bMass difference between measured and calculated quasimolecular ion values. c[(Measured mass−calculated mass)/calculated mass] × 100. dN-Acetylglucosamine. eN-Acetylmuramitol. f(1→6)Anhydro-N-acetylmuramic acid. Structural assignments of muropeptides DR1, DR2, DR8 to DR10, and DR12 deserve special comments. The low m/z value measured for DR1 (700.1) fitted very well with the value calculated for GlucNAc–MurNAc–l-Ala–d-Glu (699.69). Even smaller was the mass deduced for DR9 from the m/z value of the molecular ion of the sodium adduct (702.1) (Fig. (Fig.2).2). The mass difference between DR1 and DR9 (19.9 mass units) was very close indeed to the calculated difference between N-acetylmuramitol and the (1→6)anhydro form of MurNAc (20.04 mass units). Therefore, DR9 was identified as GlucNAc–(1→6)anhydro-MurNAc–l-Ala–d-Glu (Fig. (Fig.1).1). Muropeptides with (1→6)anhydro muramic acid have been identified in mureins from diverse origins (10, 15, 17, 19), indicating that it might be a common feature among peptidoglycan-containing microorganisms. Open in a separate windowFIG. 2Positive-ion linear PDMS of muropeptide DR9. Muropeptide DR9 was purified, desalted by HPLC, and subjected to PDMS to determine the molecular mass. The masses for the dominant molecular ions are indicated.The measured m/z value for the [M+Na]+ ion of DR8 was 1,521.6, very close to the mass calculated for a cross-linked dimer without one disaccharide moiety (1,520.53) (Fig. (Fig.1;1; Table Table1).1). Such muropeptides, also identified in T. thermophilus HB8 and other bacteria (18, 19), are most likely generated by the enzymatic clevage of MurNAc–l-Ala amide bonds in murein by an N-acetylmuramyl–l-alanine amidase (21). In particular, DR8 could derive from DR11. The difference between measured m/z values for DR8 and DR11 was 478.7, which fits with the mass contribution of a disaccharide moiety (480.5) within the mass accuracy of the instrument.The m/z values for muropeptides DR2, DR10, and DR12 supported the argument for structures in which the two d-Ala residues from the d-Ala–d-Ala C-terminal dipeptide were lost, leaving Orn as the C-terminal amino acid.The position of one Gly residue in muropeptides DR2, DR8, and DR10 to DR13 could not be formally demonstrated. One of the Gly residues could be at either the N- or the C-terminal positions. However, the N-terminal position seems more likely. The structure of the basic muropeptide (DR7), with a (Gly)2 acylating the δ-NH2 group of Orn, suggests that major muropeptides should present a (Gly)2 dipeptide. The scarcity of DR3 and DR6, which unambiguously have Gly as the C-terminal amino acid (Fig. (Fig.1),1), supports our assumption.Molar proportions for each muropeptide were calculated as proposed by Glauner et al. (10) and are shown in Table Table1.1. For calculations the structures of DR10 to DR13 were assumed to be those shown in Fig. Fig.1.1. The degree of cross-linkage calculated was 47.2%. Trimeric muropeptides were rather abundant (8 mol%) and made a substantial contribution to total cross-linkage. However, higher-order oligomers were not detected, in contrast with other gram-positive bacteria, such as Staphylococcus aureus, which is rich in such oligomers (8). The proportion of muropeptides with (1→6)anhydro-muramic acid (5 mol%) corresponded to a mean glycan strand length of 20 disaccharide units, which is in the range of values published for other bacteria (10, 17).The results of our study indicate that mureins from D. radiodurans and T. thermophilus HB8 (19) are certainly related in their basic structures but have distinct muropeptide compositions. In accordance with the phylogenetic proximity of Thermus and Deinococcus (11), both mureins are built up from the same basic monomeric subunit (DR7 in Fig. Fig.1),1), are cross-linked by (Gly)2 bridges, and have (1→6)anhydro-muramic acid at the termini of glycan strands. Most interestingly, Deinococcus and Thermus are the only microorganisms identified at present with the murein chemotype A3β as defined by Schleifer and Kandler (20). Nevertheless, the differences in muropeptide composition were substantial. Murein from D. radiodurans was poor in d-Ala–d-Ala- and d-Ala–Gly-terminated muropeptides (2.2 and 2.4 mol%, respectively) but abundant in Orn-terminated muropeptides (23.8 mol%) and in muropeptides with a peptide chain reduced to the dipeptide l-Ala–d-Glu (18 mol%). In contrast, neither Orn- nor Glu-terminated muropeptides have been detected in T. thermophilus HB8 murein, which is highly enriched in muropeptides with d-Ala–d-Ala and d-Ala–Gly (19). Furthermore, no traces of phenyl acetate-containing muropeptides, a landmark for T. thermophilus HB8 murein (19), were found in D. radiodurans. Cross-linkage was definitely higher in D. radiodurans than in T. thermophilus HB8 (47.4 and 27%, respectively), largely due to the higher proportion of trimers in the former.The similarity in murein basic structure suggests that the difference between D. radiodurans and T. thermophilus HB8 with respect to the Gram reaction may simply be a consequence of the difference in the thickness of cell walls (2, 3, 23). Interestingly, D. radiodurans murein turned out to be relatively simple for a gram-positive organism, possibly reflecting the primitive nature of this genus as deduced from phylogenetic trees (11). Our results illustrate the phylogenetic proximity between Deinococcus and Thermus at the cell wall level but also point out the structural divergences originated by the evolutionary history of each genus.  相似文献   

17.
The Chlamydomonas reinhardtii ODA3 Gene Encodes a Protein of the Outer Dynein Arm Docking Complex     
Anthony Koutoulis  Gregory J. Pazour  Curtis G. Wilkerson  Kazuo Inaba  Hong Sheng  Saeko Takada  George B. Witman 《The Journal of cell biology》1997,137(5):1069-1080
  相似文献   

18.
A Systematic Proteomic Analysis of Listeria monocytogenes House-keeping Protein Secretion Systems     
Sven Halbedel  Swantje Reiss  Birgit Hahn  Dirk Albrecht  Gopala Krishna Mannala  Trinad Chakraborty  Torsten Hain  Susanne Engelmann  Antje Flieger 《Molecular & cellular proteomics : MCP》2014,13(11):3063-3081
  相似文献   

19.
Critical Factors Determining Dimerization of Human Antizyme Inhibitor     
Kuo-Liang Su  Ya-Fan Liao  Hui-Chih Hung    Guang-Yaw Liu 《The Journal of biological chemistry》2009,284(39):26768-26777
Ornithine decarboxylase (ODC) is the first enzyme involved in polyamine biosynthesis, and it catalyzes the decarboxylation of ornithine to putrescine. ODC is a dimeric enzyme, whereas antizyme inhibitor (AZI), a positive regulator of ODC that is homologous to ODC, exists predominantly as a monomer and lacks decarboxylase activity. The goal of this paper was to identify the essential amino acid residues that determine the dimerization of AZI. The nonconserved amino acid residues in the putative dimer interface of AZI (Ser-277, Ser-331, Glu-332, and Asp-389) were substituted with the corresponding residues in the putative dimer interface of ODC (Arg-277, Tyr-331, Asp-332, and Tyr-389, respectively). Analytical ultracentrifugation analysis was used to determine the size distribution of these AZI mutants. The size-distribution analysis data suggest that residue 331 may play a major role in the dimerization of AZI. Mutating Ser-331 to Tyr in AZI (AZI-S331Y) caused a shift from a monomer configuration to a dimer. Furthermore, in comparison with the single mutant AZI-S331Y, the AZI-S331Y/D389Y double mutant displayed a further reduction in the monomer-dimer Kd, suggesting that residue 389 is also crucial for AZI dimerization. Analysis of the triple mutant AZI-S331Y/D389Y/S277R showed that it formed a stable dimer (Kd value = 1.3 μm). Finally, a quadruple mutant, S331Y/D389Y/S277R/E332D, behaved as a dimer with a Kd value of ∼0.1 μm, which is very close to that of the human ODC enzyme. The quadruple mutant, although forming a dimer, could still be disrupted by antizyme (AZ), further forming a heterodimer, and it could rescue the AZ-inhibited ODC activity, suggesting that the AZ-binding ability of the AZI dimer was retained.Polyamines (putrescine, spermidine, and spermine) have been shown to have both structural and regulatory roles in protein and nucleic acid biosynthesis and function (13). Ornithine decarboxylase (ODC,3 EC 4.1.1.17) is a central regulator of cellular polyamine synthesis (reviewed in Refs. 1, 4, 5). This enzyme catalyzes the pyridoxal 5-phosphate (PLP)-dependent decarboxylation of ornithine to putrescine, and it is the first and rate-limiting enzyme in polyamine biosynthesis (2, 3, 6, 7). ODC and polyamines play important roles in a number of biological functions, including embryonic development, cell cycle, proliferation, differentiation, and apoptosis (815). They also have been associated with human diseases and a variety of cancers (1626). Because the regulation of ODC and polyamine content is critical to cell proliferation (11), as well as in the origin and progression of neoplastic diseases (23, 24), ODC has been identified as an oncogenic enzyme, and the inhibitors of ODC and the polyamine pathway are important targets for therapeutic intervention in many cancers (6, 11).ODC is ubiquitously found in organisms ranging from bacteria to humans. It contains 461 amino acid residues in each monomer and is a 106-kDa homodimer with molecular 2-fold symmetry (27, 28). Importantly, ODC activity requires the formation of a dimer (2931). X-ray structures of the ODC enzyme reveal that this dimer contains two active sites, both of which are formed at the interface between the N-terminal domain of one monomer, which provides residues involved in PLP interactions, and the C-terminal domain of the other subunit, which provides the residues that interact with substrate (27, 3241).ODC undergoes a unique ubiquitin-independent proteasomal degradation via a direct interaction with the regulatory protein antizyme (AZ). Binding of AZ promotes the dissociation of the ODC homodimers and targets ODC for degradation by the 26 S proteasome (4246). Current models of antizyme function indicate that increased polyamine levels promote the fidelity of the AZ mRNA translational frameshift, leading to increased concentrations of AZ (47). The AZ monomer selectively binds to dimeric ODC, thereby inactivating ODC by forming inactive AZ-ODC heterodimers (44, 4850). AZ acts as a regulator of polyamine metabolism that inhibits ODC activity and polyamine transport, thus restricting polyamine levels (4, 5, 51, 52). When antizymes are overexpressed, they inhibit ODC and promote ubiquitin-independent proteolytic degradation of ODC. Because elevated ODC activity is associated with most forms of human malignancies (1), it has been suggested that antizymes may function as tumor suppressors.In contrast to the extensive studies on the oncogene ODC, the endogenous antizyme inhibitor (AZI) is less well understood. AZI is homologous to the enzyme ODC. It is a 448-amino acid protein with a molecular mass of 50 kDa. However, despite the homology between these proteins, AZI does not possess any decarboxylase activity. It binds to antizyme more tightly than does ODC and releases ODC from the ODC-antizyme complex (53, 54). Both the AZI and AZ proteins display rapid ubiquitin-dependent turnover within a few minutes to 1 h in vivo (5). However, AZ binding actually stabilizes AZI by inhibiting its ubiquitination (55).AZI, which inactivates all members of the AZ family (53, 56), restores ODC activity (54), and prevents the proteolytic degradation of ODC, may play a role in tumor progression. It has been reported that down-regulation of AZI is associated with the inhibition of cell proliferation and reduced ODC activity, presumably through the modulation of AZ function (57). Moreover, overexpression of AZI has been shown to increase cell proliferation and promote cell transformation (5860). Furthermore, AZI is capable of direct interaction with cyclin D1, preventing its degradation, and this effect is at least partially independent of AZ function (60, 61). These results demonstrate a role for AZI in the positive regulation of cell proliferation and tumorigenesis.It is now known that ODC exists as a dimer and that AZI may exist as a monomer physiologically (62). Fig. 1 shows the dimeric structures of ODC (Fig. 1A) and AZI (Fig. 1B). Although structural studies indicate that both ODC and AZI crystallize as dimers, the dimeric AZI structure has fewer interactions at the dimer interface, a smaller buried surface area, and a lack of symmetry of the interactions between residues from the two monomers, suggesting that the AZI dimer may be nonphysiological (62). In this study, we identify the critical amino acid residues governing the difference in dimer formation between ODC and AZI. Our preliminary studies using analytical ultracentrifugation indicated that ODC exists as a dimer, whereas AZI exists in a concentration-dependent monomer-dimer equilibrium. Multiple sequence alignments of ODC and AZI from various species have shown that residues 277, 331, 332, and 389 are not conserved between ODC and AZI (Open in a separate windowFIGURE 1.Crystal structure and the amino acid residues at the dimer interface of human ornithine decarboxylase (hODC) and mouse antizyme inhibitor (mAZI). A, homodimeric structure of human ODC with the cofactor PLP analog, LLP (Protein Data Bank code 1D7K). B, putative dimeric structure of mouse AZI (Protein Data Bank code 3BTN). The amino acid residues in the dimer interface are shown as a ball-and-stick model. The putative AZ-binding site is colored in cyan. This figure was generated using PyMOL (DeLano Scientific LLC, San Carlos, CA).

TABLE 1

Amino acid residues at the dimer interface of human ODC and AZI
Human ODCResidueHuman AZI
Nonconserved
    Arg277Ser
    Tyr331Ser
    Asp332Glu
    Tyr389Asp

Conserved
    Asp134Asp
    Lys169Lys
    Lys294Lys
    Tyr323Tyr
    Asp364Asp
    Gly387Gly
    Phe397Phe
Open in a separate window  相似文献   

20.
Chimeric Nitrogenase-like Enzymes of (Bacterio)chlorophyll Biosynthesis     
Denise W?tzlich  Markus J. Br?cker  Frank Uliczka  Markus Ribbe  Simone Virus  Dieter Jahn  Jürgen Moser 《The Journal of biological chemistry》2009,284(23):15530-15540
Nitrogenase-like light-independent protochlorophyllide oxidoreductase (DPOR) is involved in chlorophyll biosynthesis. Bacteriochlorophyll formation additionally requires the structurally related chlorophyllide oxidoreductase (COR). During catalysis, homodimeric subunit BchL2 or ChlL2 of DPOR transfers electrons to the corresponding heterotetrameric catalytic subunit, (BchNB)2 or (ChlNB)2. Analogously, subunit BchX2 of the COR enzymes delivers electrons to subunit (BchYZ)2. Various chimeric DPOR enzymes formed between recombinant subunits (BchNB)2 and BchL2 from Chlorobaculum tepidum or (ChlNB)2 and ChlL2 from Prochlorococcus marinus and Thermosynechococcus elongatus were found to be enzymatically active, indicating a conserved docking surface for the interaction of both DPOR protein subunits. Biotin label transfer experiments revealed the interaction of P. marinus ChlL2 with both subunits, ChlN and ChlB, of the (ChlNB)2 tetramer. Based on these findings and on structural information from the homologous nitrogenase system, a site-directed mutagenesis approach yielded 10 DPOR mutants for the characterization of amino acid residues involved in protein-protein interaction. Surface-exposed residues Tyr127 of subunit ChlL, Leu70 and Val107 of subunit ChlN, and Gly66 of subunit ChlB were found essential for P. marinus DPOR activity. Next, the BchL2 or ChlL2 part of DPOR was exchanged with electron-transferring BchX2 subunits of COR and NifH2 of nitrogenase. Active chimeric DPOR was generated via a combination of BchX2 from C. tepidum or Roseobacter denitrificans with (BchNB)2 from C. tepidum. No DPOR activity was observed for the chimeric enzyme consisting of NifH2 from Azotobacter vinelandii in combination with (BchNB)2 from C. tepidum or (ChlNB)2 from P. marinus and T. elongatus, respectively.Chlorophyll and bacteriochlorophyll biosynthesis, as well as nitrogen fixation, are essential biochemical processes developed early in the evolution of life (1). During biological fixation of nitrogen, nitrogenase catalyzes the reduction of atmospheric dinitrogen to ammonia (2). Enzyme systems homologous to nitrogenase play a crucial role in the formation of the chlorin and bacteriochlorin ring system of chlorophylls (Chl)2 and bacteriochlorophylls (Bchl) (3, 4) (Fig. 1a). For the synthesis of both Chl and Bchl, the stereospecific reduction of the C-17-C-18 double bond of ring D of protochlorophyllide (Pchlide) catalyzed by the nitrogenase-like enzyme light-independent (dark-operative) protochlorophyllide oxidoreductase (DPOR) results in the formation of chlorophyllide (Chlide) (Fig. 1a, left) (5, 6). DPOR enzymes consist of three protein subunits which are designated BchN, BchB and BchL in Bchl-synthesizing organisms and ChlN, ChlB and ChlL in Chl-synthesizing organisms. A second reduction step at ring B (C-7-C-8) unique to the synthesis of Bchl converts the chlorin Chlide into a bacteriochlorin ring structure to form bacteriochlorophyllide (Bchlide) (Fig. 1a, right, Bchlide). This reaction is catalyzed by another nitrogenase-like enzyme, termed chlorophyllide oxidoreductase (COR) (7). COR enzymes are composed of subunits BchY, BchZ, and BchX.Open in a separate windowFIGURE 1.Comparison of the three subunit enzymes DPOR, COR, and nitrogenase. a, during Chl and Bchl biosynthesis, ring D is stereospecifically reduced by the nitrogenase-like enzyme DPOR (subunit composition BchL2/(BchNB)2 or ChlL2/(ChlNB)2) leading to the chlorin Chlide. Subunits N, B, and L are named ChlN, ChlB, and ChlL in Chl-synthesizing organisms and BchN, BchB, and BchL in Bchl-synthesizing organisms. The synthesis of Bchl additionally requires the stereospecific B ring reduction by a second nitrogenase-like enzyme called COR, with the subunit composition BchX2/(BchYZ)2. COR catalyzes the formation of the bacteriochlorin Bchlide. Subunits Y, Z, and X of the COR enzyme are named BchY, BchZ, and BchX. b, the homologous nitrogenase complex has the subunit composition NifH2/(NifD/NifK)2. Rings A–E and the carbon atoms are designated according to IUPAC nomenclature (41). R is either a vinyl or an ethyl moiety. The position marked by an asterisk indicates either a vinyl or a hydroxyethyl moiety (42).All subunits share significant amino acid sequence homology to the corresponding subunits of nitrogenase, which are designated NifD, NifK, and NifH, respectively (1) (compare Fig. 1, a and b). Whereas subunits BchL or ChlL, BchX and NifH exhibit a sequence identity at the amino acid level of ∼33%, subunits BchN or ChlN, BchY, NifD, and BchB or ChlB, BchZ, and NifK, respectively, show lower sequence identities of ∼15% (1). For all enzymes a common oligomeric protein architecture has been proposed consisting of the heterotetrameric complexes (BchNB)2 or (ChlNB)2, (BchYZ)2, and (NifD/NifK)2, which are completed by a homodimeric protein subunit BchL2 or ChlL2, BchX2, and NifH2, respectively (compare Fig. 1, a and b) (3, 7, 8).Nitrogenase is a well characterized protein complex that catalyzes the reduction of nitrogen to ammonia in a reaction that requires at least 16 molecules of MgATP (2, 9, 10). During nitrogenase catalysis, subunit NifH2 (Fe protein) associates with and dissociates from the (NifD/NifK)2 complex (MoFe protein). Binding, hydrolysis of MgATP and structural rearrangements are coupled to sequential intersubunit electron transfer. For this purpose, NifH2 contains an ATP-binding motif and an intersubunit [4Fe-4S] cluster coordinated by two cysteine residues from each NifH monomer (1, 11). Electrons from this [4Fe-4S] cluster are transferred via a [8Fe-7S] cluster (P-cluster) onto the [1Mo-7Fe-9S-X-homocitrate] cluster (MoFe cofactor). Both of the latter clusters are located on (NifD/NifK)2, where dinitrogen is reduced to ammonia (10). Three-dimensional structures of NifH2 in complex with (NifD/NifK)2 revealed a detailed picture of the dynamic interaction of both subcomplexes (8, 12).Based on biochemical and bioinformatic approaches, it has been proposed that the initial steps of DPOR reaction strongly resemble nitrogenase catalysis. Key amino acid residues essential for DPOR function have been identified by mutagenesis of the enzyme from Chlorobaculum tepidum (formerly denoted as Chlorobium tepidum) (3). The catalytic mechanism of DPOR includes the electron transfer from a “plant-type” [2Fe-2S] ferredoxin onto the dimeric DPOR subunit, BchL2, carrying an intersubunit [4Fe-4S] redox center coordinated by Cys97 and Cys131 in C. tepidum. Analogous to nitrogenase, Lys10 in the phosphate-binding loop (P-loop) and Leu126 in the switch II region of DPOR were found essential for DPOR catalysis. Moreover, it was shown that the BchL2 protein from C. tepidum does not form a stable complex with the catalytic (BchNB)2 subcomplex. Therefore, a transient interaction responsible for the electron transfer onto protein subunit (BchNB)2 has been proposed (3).The subsequent [Fe-S] cluster-dependent catalysis and the specific substrate recognition at the active site located on subunit (BchNB)2 are unrelated to nitrogenase. The (BchNB)2 subcomplex was shown to carry a second [4Fe-4S] cluster, which was proposed to be ligated by Cys21, Cys46, and Cys103 of the BchN subunit and Cys94 of subunit BchB (C. tepidum numbering) (3). No evidence for any type of additional cofactor was obtained from biochemical and EPR spectroscopic analyses (5, 13). Thus, despite the same common oligomeric architecture, the catalytic subunits (BchNB)2 and (ChlNB)2 clearly differ from the corresponding nitrogenase complex, as no molybdenum-containing cofactor or P-cluster equivalent is employed (5, 14). From these results it was concluded that electrons from the [4Fe-4S] cluster of (BchNB)2 or (ChlNB)2 are transferred directly onto the Pchlide substrate at the active site of DPOR.The second nitrogenase-like enzyme, COR, catalyzes the reduction of ring B of Chlide during the biosynthesis of Bchl (7). Therefore, an accurate discrimination of the ring systems of the individual substrates is required. COR subunits share an overall amino acid sequence identity of 15–22% for BchY and BchZ and 31–35% for subunit BchX when compared with the corresponding DPOR subunits (supplemental Figures S2–S4). In amino acid sequence alignments of BchX proteins with the closely related BchL or ChlL subunits of DPOR, both cysteinyl ligands responsible for [4Fe-4S] cluster formation and residues for ATP binding are conserved (1). Furthermore, all cysteinyl residues characterized as ligands for a catalytic [4Fe-4S] cluster in (BchNB)2 or (ChlNB)2 are conserved in the sequences of subunits BchY and BchZ of COR (7). These findings correspond to a recent EPR study in which a characteristic signal for a [4Fe-4S] cluster was obtained for the COR subunit BchX2 as well as for subunit (BchYZ)2 (15). These results indicate that the catalytic mechanism of COR strongly resembles DPOR catalysis. In vitro assays for nitrogenase as well as for DPOR and COR make use of the artificial electron donor dithionite in the presence of high concentrations of ATP (7, 16, 17).

TABLE 1

Amino acid sequence identities of the individual subunits of DPOR, COR, and nitrogenaseAmino acid sequences of the individual subunits of DPOR, COR, and nitrogenase employed in the present study (compareFig. 3A) were aligned by using the ClustalW method in MegAlign (DNASTAR), and sequence identities were calculated.
DPOR
COR
Nitrogenase
NBLYZXNifDNifKNifH
DPOR
    N37–5815–1812–20
    B34–6215–2214–18
    L51–6931–3531–38

COR
    Y35–7813–15
    Z39–8111–16
    X42–8329–36

Nitrogenase
    NifD17–70
    NifK37–58
    NifH67–75
Open in a separate windowIn this study, we investigated the transient interaction of the dimeric subunit BchL2 or ChlL2 with the heterotetrameric (BchNB)2 or (ChlNB)2 complex, which is essential for DPOR catalysis. We make use of the individually purified DPOR subunits BchL2 and (BchNB)2 from the green sulfur bacterium C. tepidum and ChlL2 and (ChlNB)2 from the prochlorophyte Prochlorococcus marinus and from the cyanobacterium Thermosynechococcus elongatus. The individual combination of (BchNB)2 or (ChlNB)2 complexes and BchL2 or ChlL2 proteins from these organisms resulted in catalytically active chimeras of DPOR. These results enabled us to propose conserved regions of the postulated docking surface, which were subsequently verified in a mutagenesis study. To elucidate the potential evolution of the electron-transferring subunit of nitrogenase and nitrogenase-like enzymes, we also analyzed chimeric enzymes consisting of DPOR subunits (BchNB)2 or (ChlNB)2 in combination with subunits BchX2 from C. tepidum and R. denitrificans of the COR enzyme and with subunit NifH2 of nitrogenase from Azotobacter vinelandii, respectively.  相似文献   

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