Nickel-based Enzyme Systems

Of the eight known nickel enzymes, all but glyoxylase I catalyze the use and/or production of gases central to the global carbon, nitrogen, and oxygen cycles. Nickel appears to have been selected for its plasticity in coordination and redox chemistry and is able to cycle through three redox states (1+, 2+, 3+) and to catalyze reactions spanning ∼1.5 V. This minireview focuses on the catalytic mechanisms of nickel enzymes, with an emphasis on the role(s) of the metal center. The metal centers vary from mononuclear to complex metal clusters and catalyze simple hydrolytic to multistep redox reactions.Seven of the eight known nickel enzymes (1). CODH² interconverts CO and CO₂; ACS utilizes CO; the nickel ARD produces CO; hydrogenase generates/utilizes hydrogen gas; MCR generates methane; urease produces ammonia; and SOD generates O₂.

TABLE 1

Nickel-containing enzymes

Disease Mutations in the Human Mitochondrial DNA Polymerase Thumb Subdomain Impart Severe Defects in Mitochondrial DNA Replication

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 (10–12). 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 (19–21). 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 (

Mode of Action of cGMP-dependent Protein Kinase-specific Inhibitors Probed by Photoaffinity Cross-linking Mass Spectrometry

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, K_I = 0.8 μm) and a membrane translocating sequence (DT-6, YGRKKRRQRRRPP, K_I = 1.1 μm), that combined strongly inhibits PKG catalyzed phosphorylation (K_I = 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 (1–4). 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 (10–16). 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 (18–24). 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 (K_i = 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 (28–31). Using this technique, important information on conformational changes (32–35), 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 (K_I) of PKA- or PKG-specific peptide inhibitors and the PKA/PKG specificity index

Critical Factors Determining Dimerization of Human Antizyme Inhibitor

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 K_d, 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 (K_d value = 1.3 μm). Finally, a quadruple mutant, S331Y/D389Y/S277R/E332D, behaved as a dimer with a K_d 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 (1–3). 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 (8–15). They also have been associated with human diseases and a variety of cancers (16–26). 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 (29–31). 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, 32–41).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 (42–46). 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, 48–50). 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 (58–60). 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

Molecular and Biochemical Characterization of the Protein Template Controlling Biosynthesis of the Lipopeptide Lichenysin

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.

Biological Activity of Nerve Growth Factor Precursor Is Dependent upon Relative Levels of Its Receptors

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 (k_d ≈ 10⁻¹¹ m) to tropomyosin-related kinase A (TrkA) and with low affinity (k_d ≈ 10⁻⁹ m) to the common neurotrophin receptor p75^NTR (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). p75^NTR 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, p75^NTR 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 (7–9). High levels of p75^NTR 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). p75^NTR 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 (16–20). ProNGF is the predominant form of NGF in the central and peripheral nervous systems, whereas little or no mature NGF can be detected (21–24). 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 (25–28). 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     

A Review of Principal Studies on the Development and Treatment of Epithelial Ovarian Cancer in the Laying Hen Gallus gallus

Often referred to as the silent killer, ovarian cancer is the most lethal gynecologic malignancy. This disease rarely shows any physical symptoms until late stages and no known biomarkers are available for early detection. Because ovarian cancer is rarely detected early, the physiology behind the initiation, progression, treatment, and prevention of this disease remains largely unclear. Over the past 2 decades, the laying hen has emerged as a model that naturally develops epithelial ovarian cancer that is both pathologically and histologically similar to that of the human form of the disease. Different molecular signatures found in human ovarian cancer have also been identified in chicken ovarian cancer including increased CA125 and elevated E-cadherin expression, among others. Chemoprevention studies conducted in this model have shown that decreased ovulation and inflammation are associated with decreased incidence of ovarian cancer development. The purpose of this article is to review the major studies performed in laying hen model of ovarian cancer and discuss how these studies shape our current understanding of the pathophysiology, prevention and treatment of epithelial ovarian cancer.

Ovarian cancer is the leading cause of death among female gynecologic malignancies, with a 47% 5 y relative survival rate.¹⁵⁴ Early detection of the disease is necessary for decreasing the high mortality rate. However, early detection is difficult due to the lack of known specific biomarkers and clinically detectable symptoms until the tumor reaches at an advanced stage. The disease has multiple subtypes. Epithelial ovarian cancer (EOC) is the most common type of ovarian cancer, accounting for about 90% of all reported cases.^127,164 EOC is commonly subdivided into 5 histotypes: high-grade serous (HGSOC), low-grade serous, mucinous, endometroid (EC), and clear cell. The histotypes differ in terms of tumor cell morphology, severity, systemic effect, and response to treatment. Among the different subtypes, HGSOC accounts for about 70% of cases of EOC observed in women. HGSOC has a higher mitotic index and is a more aggressive form of cancer with a worse prognosis. HGSOC and low-grade serous histotypes exhibit distinctly different presentations of the disease^82,166 and demand different treatment modalities. EC (10% to 20%), mucinous (5% to 20%), and clear cell (3% to 10%) histotypes are less common forms of the disease. The subtypes of EOC also differ in terms of 5 y survival rates of patients; that is, HGSOC (20% to 35%), EC (40% to 63%), mucinous (40% to 69%), and clear cell (35% to 50%).^20,76,148Developing a representative animal model for EOC has been challenging due to the histologic and pathologic differences among different subtypes of EOC. While developing a reliable animal model is challenging due to the vast complexity and limited understanding of the origin of the disease, laying hens naturally develop EOC that is histopathologically very similar to the human form of the disease (Figure 1).¹⁵ All the different human ovarian cancer histotypes have been observed in laying hen ovarian cancer (Figure 2). In addition, the presentation of the disease in chickens is remarkably similar to the human form of the disease, with early-stage ovarian cancer in laying hens having similar precursor lesions as occur in women.¹⁵ The laying hen develops ovarian cancer spontaneously, allowing analysis of early events and investigation into the natural course of the disease, as tumors can be examined as they progress from normal to late-stage ovarian carcinoma. The gross appearance of these stages is shown in Figure 3.Open in a separate windowFigure 1.Gross pathologic presentation of chicken compared with human ovarian cancer. The remarkably similar presentation in hens (A,B) and women (C,D) at the gross anatomic level with profuse abdominal ascites and peritoneal dissemination of metastasis. A) Ascites in abdominal cavity chicken with advanced ovarian cancer (photo credit: DB Hales); (B) Chicken ovarian cancer with extensive peritoneal dissemination of metastasis (photo credit: DB Hales); (C) Distended abdomen from ascites fluid accumulation in woman with ovarian cancer (http://www.pathguy.com/bryanlee/ovca.html) (D) Human ovarian cancer with extensive peritoneal dissemination of metastasis (http://www.pathguy.com/bryanlee/ovca.html).Open in a separate windowFigure 2.Gross anatomic appearance of different stages of ovarian cancer in the chicken The progression from the normal hen ovary to late-stage metastatic ovarian cancer. (A) Normal chicken ovary showing hierarchal clutch of developing follicles and postovulatory follicle; (B) Stage 1 ovarian cancer, confined to ovary with vascularized follicles; (C) Stage 2/3 ovarian cancer, metastasis locally to peritoneal cavity with ascites; (D) Stage 4 ovarian cancer, late stage with metastasis to lung and liver with extensive ascites (photo credits: DB Hales).Open in a separate windowFigure 3.Histologic subtypes in chicken compared with human ovarian cancers. H and E staining of formalin fixed paraffin embedded tissues from hens with ovarian cancer (A through D) and women (E through G). (A) Chicken clear cell carcinoma; (B) Chicken endometrioid carcinoma; (C) Chicken mucinous adenocarcinoma; (D) Chicken serous papillary adenocarcinoma (photo credits: DB Hales). (E) Human clear cell carcinoma; (F) Human endometrioid carcinoma; (G) Human mucinous cystadenocarcinoma; (H) Human serous adenocarcinoma (https://www.womenshealthsection.com).Over the past 2 decades, the laying hen has emerged as a valuable experimental model for EOC, in addition to other in vivo models such as Patient-Derived Xenografts (PDX) and Genetically Engineered Mouse Models (GEMMs). Comparison of the hen model with other animal models has been reviewed elsewhere.⁷² Modern-day laying hens, such as the white leghorn, have been selected from their ancestor red jungle fowl⁵⁷ for decreased broodiness and persistent ovulation, resulting in approximately one egg per day, if proper nutrition and light-dark cycles are maintained. Daily rupture and consequent repair of the ovarian surface epithelia (OSE) due to the persistent ovulation promotes potential error during rapid DNA replication. This increases the probability of oncogenic mutations, ultimately leading to neoplasia.¹³⁷ Inflammation resulting from continuous ovulation also promotes the natural development of EOC.⁸¹ By the age of 2.5 to 3 y, laying hens have undergone a similar number of ovulations as a perimenopausal woman. The risk of ovarian cancer in white leghorn hens in this time (4%) is similar to the lifetime risk of ovarian cancer in women (0.35% to 8.8%).¹²⁵ By the age of 4 to 6 y, the risk of ovarian cancer in hens rises to 30% to 60%.⁵⁴ The incidence of ovarian carcinoma in the hens, however, depends on the age, genetic strain,⁸⁰ and the egg-laying frequency of the specific breed.⁵⁴ The common white leghorn hen has routinely been employed in chicken ovarian cancer studies. On average, hens are exposed to 17 h of light per day, with lights turned on at 0500 h and turned off at 2200 h. The laying hen model of EOC does present some considerable challenges. Despite its great utility for research, the model is still used mainly by agricultural poultry scientists and a small number of ovarian cancer researchers.Comprehensive and proper vivarium support is required to conduct large-scale cancer prevention studies. Only a few facilities are available for biomedical chicken research, including University of Illinois Urbana-Champaign, Cornell University, Penn State University, NC State, Auburn University, and MS State University. Another difficulty is a lack of available antibodies specific for chicken antigens. Because of the structural dissimilarities between most human proteins and murine antigens to their chicken counterparts, cross-reactivity of available antibodies is also limited. The entire chicken genome was sequenced in 2004;⁷⁸ however, the chromosomal locus of many key genes, such as p53, are still unknown. Overall, humans and chickens share about 60% of genetic commonality, whereas humans and rats share about 88% of their genes. Specific pathway-mutated strains of chickens are not yet available, limiting the ability to study key pathways in carcinogenesis and prevention of cancer using this model. Although all 5 different subtypes of ovarian cancer are present in hens, their most predominant subtype is different from women. Close to 70% of women diagnosed with ovarian cancer have serous EOC, while the predominant subtype reported in hens is endometrioid.¹⁵ However, these comparisons are complicated because observations of cancer in hens consist of both early and late stages of the disease, wherein women, most of the data is from late stage and aggressive ovarian carcinoma.The spontaneous onset of ovarian cancer and the histologic and pathologic similarities to the human form of the disease make laying hens an excellent model for continued research on EOC. To date, a large number of studies have been performed on laying hens. Here we have divided the current studies into 2 groups— (A) studies that have described the molecular presentation of EOC to be similar to that in women; (AuthorYearSignificanceKey molecular targetsCitationHaritani and colleagues.1984Investigating ovarian tumors for key gene signaturesOvalbumin 71 Rodriguez-Burford and colleagues.2001Investigating expressions of clinically important prognostic markers in cancerous hensCA125, cytokeratin AE1/AE3, pan cytokeratin, Lewis Y, CEA, Tag 72, PCNA, EGFR, erbB-2, p27, TGF{α}, Ki-67, MUC1, and MUC2 135 Giles and colleagues.2004, 2006Investigating ovarian tumors for key gene signaturesOvalbumin, PR, PCNA, Vimentin62, 63Jackson and colleagues.2007CA125 expression in hen ovarian tumorsCA125 79 Stammer and colleagues.2008SELENBP1 downregulation in hen ovarian tumorsSELENBP1 149 Hales and colleagues.2008Cyclooxygenase expressions in hen ovarian tumorsCOX1, COX2, PGE2 67 Urick and colleagues.2008-2009VEGF expression in cultured ascites cells from hen ovarian tumorsVEGF160, 161Ansenberger and colleagues.2009Elevation of E-cadherin in hen ovarian tumorsE-cad 6 Hakim and colleagues.2009Investigating oncogenic mutations in hen ovarian tumorsp53, K-ras, H-ras 66 Zhuge and colleagues.2009CYP1B1 levels in chicken ovarian tumorsCYP1B1 175 Seo and colleagues.2010Upregulation of Claudin-10 in hen ovarian tumorsClaudin-10 145 Trevino and colleagues.2010Investigating ovarian tumors for key gene signaturesOvalbumin, Pax2, SerpinB3, OVM, LTF, RD 157 Choi and colleagues.2011Upregulation of MMP-3 in hen ovarian tumor stromaMMP-3 28 Barua and colleagues.2012Upregulation of DR6 in hen ovarian tumorsDR6 16 Lee and colleagues.2012-2014Upregulation of DNA methylation in hen ovarian tumorsDNMT1, DNMT3A, DNMT3B,
SPP1, SERPINB11, SERPINB1394, 101, 103, 104Lim and colleagues.2013-2014Key genes upregulated in endometrioid hen tumorsAvBD-11, CTNNB1, Wnt4102, 11, 100Bradaric and colleagues.2013Investigating immune cells in hen ovarian tumors 23 Ma and colleagues.2014Identifying unique proteins from proteomic profilingF2 thrombin, ITIH2 106 Hales and colleagues.2014Key genes upregulated in hen ovarian tumorsPAX2, MSX2, FOXA2, EN1 68 Parada and colleagues,2017Unique ganglioside expressed in hen ovarian tumorsNeuGcGM3 124 Open in a separate windowTable 2.Ovarian cancer prevention studies using laying hen model

Mouse Models of Osteoarthritis: A Summary of Models and Outcomes Assessment

Osteoarthritis (OA) is a multidimensional health problem and a common chronic disease. It has a substantial impact on patient quality of life and is a common cause of pain and mobility issues in older adults. The functional limitations, lack of curative treatments, and cost to society all demonstrate the need for translational and clinical research. The use of OA models in mice is important for achieving a better understanding of the disease. Models with clinical relevance are needed to achieve 2 main goals: to assess the impact of the OA disease (pain and function) and to study the efficacy of potential treatments. However, few OA models include practical strategies for functional assessment of the mice. OA signs in mice incorporate complex interrelations between pain and dysfunction. The current review provides a comprehensive compilation of mouse models of OA and animal evaluations that include static and dynamic clinical assessment of the mice, merging evaluation of pain and function by using automatic and noninvasive techniques. These new techniques allow simultaneous recording of spontaneous activity from thousands of home cages and also monitor environment conditions. Technologies such as videography and computational approaches can also be used to improve pain assessment in rodents but these new tools must first be validated experimentally. An example of a new tool is the digital ventilated cage, which is an automated home-cage monitor that records spontaneous activity in the cages.

Osteoarthritis (OA) is a multidimensional health problem and a common chronic disease.³⁶ Functional limitations, the absence of curative treatments, and the considerable cost to society result in a substantial impact on quality of life.⁷⁶ Historically, OA has been described as whole joint and whole peri-articular diseases and as a systemic comorbidity.^9,111 OA consists of a disruption of articular joint cartilage homeostasis leading to a catabolic pathway characterized by chondrocyte degeneration and destruction of the extracellular matrix (ECM). Low-grade chronic systemic inflammation is also actively involved in the process.^42,92 In clinical practice, mechanical pain, often accompanied by a functional decline, is the main reason for consultations. Recommendations to patients provide guidance for OA management.^{22, 33,49,86} Evidence-based consensus has led to a variety of pharmacologic and nonpharmacologic modalities that are intended to guide health care providers in managing symptomatic patients. Animal-based research is of tremendous importance for the study of early diagnosis and treatment, which are crucial to prevent the disease progression and provide better care to patients.The purpose of animal-based OA research is 2-fold: to assess the impact of the OA disease (pain and function) and to study the efficacy of a potential treatment.^18,67 OA model species include large animals such as the horse, goat, sheep, and dog, whose size and anatomy are expected to better reflect human joint conditions. However, small animals such as guinea pig, rabbit, mouse, and rat represent 77% of the species used.^1,87 In recent years, mice have become the most commonly used model for studying OA. Mice have several advantageous characteristics: a short development and life span, easy and low-cost breeding and maintenance, easy handling, small joints that allow histologic analysis of the whole joint,³² and the availability of genetically modified lines.¹⁰⁸ Standardized housing, genetically defined strains and SPF animals reduce the genetic and interindividual acquired variability. Mice are considered the best vertebrate model in terms of monitoring and controlling environmental conditions.^7,14,15,87 Mouse skeletal maturation is reached at 10 wk, which theoretically constitutes the minimal age at which mice should be entered into an OA study.^64,87,102 However, many studies violate this limit by testing mice at 8 wk of age.Available models for OA include the following (32,111 physical activity and exercise induced OA; noninvasive mechanical loading (repetitive mild loading and single-impact injury); and surgically induced (meniscectomy models or anterior cruciate ligament transection). The specific model used would be based on the goal of the study.⁷ For example, OA pathophysiology, OA progression, and OA therapies studies could use spontaneous, genetic, surgical, or noninvasive models. In addition, pain studies could use chemical models. Lastly, post-traumatic studies would use surgical or noninvasive models; the most frequently used method is currently destabilization of the medial meniscus,³² which involves transection of the medial meniscotibial ligament, thereby destabilizing the joint and causing instability-driven OA. An important caveat for mouse models is that the mouse and human knee differ in terms of joint size, joint biomechanics, and histologic characteristics (layers, cellularity),^32,64 and joint differences could confound clinical translation.¹⁰ Table 1. Mouse models of osteoarthritis.

Natural Infection of Burkholderia pseudomallei in an Imported Pigtail Macaque (Macaca nemestrina) and Management of the Exposed Colony

Identification of the select agent Burkholderia pseudomallei in macaques imported into the United States is rare. A purpose-bred, 4.5-y-old pigtail macaque (Macaca nemestrina) imported from Southeast Asia was received from a commercial vendor at our facility in March 2012. After the initial acclimation period of 5 to 7 d, physical examination of the macaque revealed a subcutaneous abscess that surrounded the right stifle joint. The wound was treated and resolved over 3 mo. In August 2012, 2 mo after the stifle joint wound resolved, the macaque exhibited neurologic clinical signs. Postmortem microbiologic analysis revealed that the macaque was infected with B. pseudomallei. This case report describes the clinical evaluation of a B. pseudomallei-infected macaque, management and care of the potentially exposed colony of animals, and protocols established for the animal care staff that worked with the infected macaque and potentially exposed colony. This article also provides relevant information on addressing matters related to regulatory issues and risk management of potentially exposed animals and animal care staff.Abbreviations: CDC, Centers for Disease Control and Prevention; IHA, indirect hemagglutination assay; PEP, postexposure prophylacticBurkholderia pseudomallei, formerly known as Pseudomonas pseudomallei, is a gram-negative, aerobic, bipolar, motile, rod-shaped bacterium. B. pseudomallei infections (melioidosis) can be severe and even fatal in both humans and animals. This environmental saprophyte is endemic to Southeast Asia and northern Australia, but it has also been found in other tropical and subtropical areas of the world.^7,22,32,42 The bacterium is usually found in soil and water in endemic areas and is transmitted to humans and animals primarily through percutaneous inoculation, ingestion, or inhalation of a contaminated source.^{8, 22,28,32,42} Human-to-human, animal-to-animal, and animal-to-human spread are rare.^8,32 In December 2012, the National Select Agent Registry designated B. pseudomallei as a Tier 1 overlap select agent.³⁹ Organisms classified as Tier 1 agents present the highest risk of deliberate misuse, with the most significant potential for mass casualties or devastating effects to the economy, critical infrastructure, or public confidence. Select agents with this status have the potential to pose a severe threat to human and animal health or safety or the ability to be used as a biologic weapon.³⁹Melioidosis in humans can be challenging to diagnose and treat because the organism can remain latent for years and is resistant to many antibiotics.^12,37,41 B. pseudomallei can survive in phagocytic cells, a phenomenon that may be associated with latent infections.^19,38 The incubation period in naturally infected animals ranges from 1 d to many years, but symptoms typically appear 2 to 4 wk after exposure.^13,17,35,38 Disease generally presents in 1 of 2 forms: localized infection or septicemia.²² Multiple methods are used to diagnose melioidosis, including immunofluorescence, serology, and PCR analysis, but isolation of the bacteria from blood, urine, sputum, throat swabs, abscesses, skin, or tissue lesions remains the ‘gold standard.’^9,22,40,42 The prognosis varies based on presentation, time to diagnosis, initiation of appropriate antimicrobial treatment, and underlying comorbidities.^7,28,42 Currently, there is no licensed vaccine to prevent melioidosis.There are several published reports of naturally occurring melioidosis in a variety of nonhuman primates (NHP; 2,10,13,17,25,30,31,35 The first reported case of melioidosis in monkeys was recorded in 1932, and the first published case in a macaque species was in 1966.³⁰ In the United States, there have only been 7 documented cases of NHP with B. pseudomallei infection.^2,13,17 All of these cases occurred prior to the classification of B. pseudomallei as a select agent. Clinical signs in NHP range from subclinical or subacute illness to acute septicemia, localized infection, and chronic infection. NHP with melioidosis can be asymptomatic or exhibit clinical signs such as anorexia, wasting, purulent drainage, subcutaneous abscesses, and other soft tissue lesions. Lymphadenitis, lameness, osteomyelitis, paralysis and other CNS signs have also been reported.^{2,7,10,22,28,32} In comparison, human''s clinical signs range from abscesses, skin ulceration, fever, headache, joint pain, and muscle tenderness to abdominal pain, anorexia, respiratory distress, seizures, and septicemia.^7,9,21,22

Table 1.

Summary of reported cases of naturally occurring Burkholderia pseudomalleiinfections in nonhuman primates

Quantitative Proteomics by Metabolic Labeling of Model Organisms

In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life.Well before the genomics era, the foundation for our current understanding of genetics was largely established by biological research performed using model organisms. Early genetics discoveries such as the chromosome theory of heredity and bacterial conjugation were first described in the fruit fly Drosophila melanogaster (1) and the bacterium Escherichia coli (2), respectively. Apart from these organisms, most of the current knowledge of development, evolution, and genetics originates from other classical model organisms including the bakers'' yeast Saccharomyces cerevisiae, the nematode Caenorhabditis elegans, and the mouse Mus musculus. Nowadays, they hold a primary position in the analysis of biological, disease, and pharmaceutical processes in modern biology and probably claim an even more promising position in future biological research. With increasing numbers of completed genome annotations, however, the focus is also shifting somewhat from these classical model organisms toward organisms that have unique genetic properties, are economically interesting, or are more directly related to human disease such as puffer fish, rice, and Plasmodium, respectively. Consequently, the definition of a model organism has broadened over the past decade, and today model organisms are found in nearly all branches of the “tree of life,” providing extensive means to further investigate conservation or diversification of biological principles through evolution (3). This has gained momentum tremendously by the completion of genome sequencing efforts in hundreds of organisms. In relatively simple organisms (bacteria and yeast), this has allowed the systematic investigation of multiple basic biological processes conserved through evolution (e.g. apoptosis (4) and vacuolar transport (5)). Higher organisms are highly useful for the study of complex traits, which is facilitated by large collections of mutant strains (6, 7). This is of particular relevance where model systems of human physiology, either in a healthy or diseased state, are studied. Fruit flies and C. elegans, the “classical” model organisms, have been used as models for a variety of diseases (8) but also for natural processes like aging (9, 10), sleep (11, 12), and olfaction (13). Mouse and rat models have been a long-standing model for human biology (14), especially in cancer (15). Particularly the availability of strains engineered to represent human diseases has increased our understanding of pathological processes tremendously (16).So far, the focus has primarily been on genetic and genomic aspects of these processes and disorders, but with the maturation of proteomics techniques, ways to study these at the protein level in a meaningful way are coming within reach. Over the last decade, proteomics research has experienced significant advances and has evolved into an indispensable technology to investigate the proteomic composition of biological samples. Proteomics has shifted from the analysis of small sets of proteins toward the comprehensive investigation of a much larger number of proteins expressed in a cell, tissue, or organism (17). Nowadays, a typical proteomics experiment is peptide-centric and starts with the enzymatic digestion of a protein mixture followed by fractionation using one or more chromatographic steps to reduce sample complexity (18, 19) as illustrated in Fig.1. Peptides are fragmented in the mass spectrometer as they elute, and subsequent matching of fragmentation profiles against a protein database leads to peptide and protein identification. When performed at a large scale, this can be used for the identification of thousands of proteins in cells or subcellular structures (20–23). Although such qualitative approaches are fruitful in providing information on proteins present in cells or tissues, they largely ignore the dynamics of protein expression when different conditions are to be investigated. This is highly relevant because in general only the proteins that differ between biological states (e.g. healthy/diseased) are likely to be of primary interest. Because mass spectrometry is not inherently quantitative, it is beneficial to add an internal standard as a reference for the peptide of interest. For large scale experiments, often all proteins or peptides in one sample are modified with a stable isotope-coded mass label. After mixing the labeled sample with an unmodified sample, the intensity ratio between the modified peptide and the unlabeled peptide accurately reflects the change in expression level.Open in a separate windowFig. 1.Qualitative proteomics work flow. Proteins are extracted, digested, and separated by strong cation exchange. Each strong cation exchange fraction is then analyzed by nano-LC-MS/MS. Peptide fragment spectra are used in a database search to identify the peptide sequence and the corresponding protein.Various approaches have been developed for the incorporation of stable isotopes into proteins that can be divided into in vivo and in vitro methods. In the former, isotope-enriched compounds (salts or amino acids) are added to the growth media that can be metabolized by the cell and incorporated into proteins. In vitro labeling can be established using chemical derivatization of proteins or peptides after protein extraction. The choice for either approach depends on the biological system under investigation, but there are a few considerations that should be taken into account because of their impact on the experimental work flow. In Labeling methodCostStrengthsWeaknessesMetabolic labeling (in vivo)    SILAC+Incorporation at the organism level (lowest variation). Available (free) quantitation software.Not applicable to human samples. Arginine-to-proline conversion. Expensive and slow. Enzymes other than trypsin and/or Lys-N may produce non-quantifiable peptides. Auxotroph for the labeled amino acid(s).    ¹⁵N labeling+Incorporation at the organism level (lowest variation). All peptides can be used for quantitation regardless of the enzymeNot applicable to human samples. Expensive and slow. Available quantitation software. Unknown mass difference prior to identification.    ¹³C labeling+Incorporation at the organism level (lowest variation). All peptides can be used for quantitation regardless of the enzyme.Not applicable to human samples. Expensive and slow. Available quantitation software. Unknown mass difference prior to identification. Isotope distribution might hamper identification.    SMIRP+/−Incorporation at the organism level (lowest variation). All peptides can be used for quantitation regardless of the enzyme.Not applicable to human samples. Slow. Available quantitation software.    Isotope-depleted labeling+Incorporation at the organism level (lowest variation). All peptides can be used for quantitation regardless of the enzyme.Not applicable to human samples. Expensive and slow. Available quantitation software. Identification requires ECD or ETD. Quantitation at the protein level.Chemical labeling (in vitro)    ICAT+/−Applicable to any sample. Fast.Incorporation at the protein level (moderate variation). Only Cys-containing peptides can be used for quantitation.    ICPL+/−Applicable to any sample. Fast.Incorporation at the protein level (moderate variation). Only Lys-containing peptides and the protein N terminus can be used for quantitation. Trypsin cleaves C-terminal to arginine residues only.    iTRAQ+/−Applicable to any sample. Fast. Simultaneous analysis of 8 labeled samples. No increase in complexity at the MS level.Incorporation at the peptide level (high variation). Quantitation is based on 1 or a few tandem mass spectra. Requires mass spectrometers that can analyze the low m/z region.    ¹⁸O labeling−Applicable to any sample. Cheap and fast.Incorporation at the peptide level (high variation). Difficult to reach complete labeling. Available quantitation software.    Dimethyl labeling−Applicable to any sample. Cheap and fast. Automation is possible.Incorporation at the peptide level (high variation). Identification issues due to the number of variable modifications.Open in a separate windowOne major consideration for labeling in vivo (metabolic) or in vitro (chemical) critically depends on whether the biological sample in question can metabolically incorporate the isotope label. Metabolic labeling requires the addition of an isotopically enriched element (e.g. ¹³C, ¹⁵N, or ¹⁸O in salts or amino acids) to the growth media in a form that makes it available for incorporation into the entire organism, tissue, or cell. In contrast, chemical labeling occurs after protein extraction and therefore is completely independent of the source and preparation of the sample. This has the advantage that virtually any type of biological sample can be labeled, including human tissue or body fluids. Additionally, the time needed for this type of labeling is in general much shorter than when a label is incorporated metabolically where it may take weeks to in vivo label organisms or cells depending on the growth rate. This can even increase to a few months if a secondary labeling step is required such as is the case in the ¹⁵N labeling procedure of fruit flies and worms by feeding them on labeled yeast and E. coli, respectively.The great advantage of metabolic labeling becomes clear when the proteomics work flow is considered. Fig.2 gives an overview of the different positions in the experimental work flow where the internal standard can be introduced. Clearly, the best place to introduce an internal standard is by metabolically incorporating the stable isotope into living organisms or cells, thereby producing the lowest variation before any sample processing occurs (Fig. 2, left). When the internal standard is introduced further downstream in the work flow, higher levels of variation can be expected due to parallel sample processing as is the case with chemical derivatization of intact proteins (e.g. with ICAT and isotope-coded protein labeling (ICPL)¹ (24, 25)) (Fig. 2, middle) or with chemical labeling of peptides such as isobaric tag for relative and absolute quantitation (iTRAQ) and stable isotope dimethyl labeling procedures (26–28) or proteolytic digestion in ¹⁸O-labeled water (29, 30) (Fig. 2, right).Open in a separate windowFig. 2.Strategies for quantitative proteomics. Stable isotopes can be incorporated at different stages of the quantitative work flow and are indicated in black. The methods are metabolic labeling (left), protein labeling (middle), and peptide labeling (right). Relative expression levels are obtained by mass spectrometry where the signal of the unlabeled peptide is compared with that of the labeled peptide.