Stable Isotope Labeling in Zebrafish Allows in Vivo Monitoring of Cardiac Morphogenesis

Quantitative proteomics is an important tool to study biological processes, but so far it has been challenging to apply to zebrafish. Here, we describe a large scale quantitative analysis of the zebrafish proteome using a combination of stable isotope labeling and liquid chromatography-mass spectrometry (LC-MS). Proteins derived from the fully labeled fish were used as a standard to quantify changes during embryonic heart development. LC-MS-assisted analysis of the proteome of activated leukocyte cell adhesion molecule zebrafish morphants revealed a down-regulation of components of the network required for cell adhesion and maintenance of cell shape as well as secondary changes due to arrest of cellular differentiation. Quantitative proteomics in zebrafish using the stable isotope-labeling technique provides an unprecedented resource to study developmental processes in zebrafish.Over the past years, mass spectrometry-based proteomics has been widely used to analyze complex biological samples (1). Although the latest generation of MS instrumentation allows proteome-wide analysis, protein quantitation is still a challenge (2, 3). Metabolic labeling using stable isotopes has been used for almost a century. Today, the most commonly used techniques for relative protein quantification are based on ¹⁵N labeling and stable isotope labeling by amino acids in cell culture (SILAC)¹ (4, 5). SILAC was initially developed for cell culture experiments, and recent approaches extended labeling to living organisms, including bacteria (6), yeast (7), flies (8), worms (9), and rodents (10, 11). In addition, several pulsed SILAC (also known as dynamic SILAC) experiments were performed to assess protein dynamics in cell culture and living animals (12–15).The zebrafish (Danio rerio) has proved to be an important model organism to study developmental processes. It also serves as a valuable tool to investigate basic pathogenic principles of human diseases such as cardiovascular disorders and tissue regeneration (16). So far, most researchers rely on immunohistochemistry and Western blots for semi-quantitative protein analysis, an approach that is hampered by the paucity of reliable antibodies in zebrafish. Proteomics approaches that depend on two-dimensional gel approaches (17–19) have not gained wide popularity because of issues with workload, reproducibility, and sensitivity (20, 21).Another approach for protein quantitation is the chemical modification of peptides, and so far several isobaric tagging methods, including ICAT (22), iTRAQ (23), ¹⁸O (24), and dimethyl labeling (25), have been proven to be successful methods.Recently, a quantitative phosphopeptide study based on dimethyl labeling in zebrafish showed the consequences of a morpholino-based kinase knockdown (26). However, each chemical modification bears the risk of nonspecific and incomplete labeling, which complicates mass spectrometric data interpretation.Alternatively, a metabolic labeling study with stable isotopes was recently performed on adult zebrafish by the administration of a mouse diet containing [¹³C₆]lysine (Lys-6) (27). Feeding adult zebrafish with the Lys-6-containing mouse chow leads to an incorporation rate of 40%, and SILAC labeling was used to investigate protein and tissue turnover.Here, we have developed a SILAC fish diet made in-house for the complete SILAC labeling of zebrafish. We established a Lys-6-containing diet as a universal fish food for larval and adult zebrafish. The method allows accurate quantitation of large numbers of proteins, and we proved our approach by the analysis of embryonic heart development. In addition, we investigated the consequences of the morpholino-based activated leukocyte cell adhesion molecule (ALCAM) knockdown during development and identified the lipid anchor protein Paralemmin as a down-regulated protein during heart development. Our approach yielded a huge resource of protein expression data for zebrafish development and provided the basis for more refined studies depending on accurate SILAC protein quantification.     

The SILAC Fly Allows for Accurate Protein Quantification in Vivo

Stable isotope labeling by amino acids in cell culture (SILAC) is widely used to quantify protein abundance in tissue culture cells. Until now, the only multicellular organism completely labeled at the amino acid level was the laboratory mouse. The fruit fly Drosophila melanogaster is one of the most widely used small animal models in biology. Here, we show that feeding flies with SILAC-labeled yeast leads to almost complete labeling in the first filial generation. We used these “SILAC flies” to investigate sexual dimorphism of protein abundance in D. melanogaster. Quantitative proteome comparison of adult male and female flies revealed distinct biological processes specific for each sex. Using a tudor mutant that is defective for germ cell generation allowed us to differentiate between sex-specific protein expression in the germ line and somatic tissue. We identified many proteins with known sex-specific expression bias. In addition, several new proteins with a potential role in sexual dimorphism were identified. Collectively, our data show that the SILAC fly can be used to accurately quantify protein abundance in vivo. The approach is simple, fast, and cost-effective, making SILAC flies an attractive model system for the emerging field of in vivo quantitative proteomics.Mass spectrometry-based quantitative proteomics has emerged as a highly successful approach to study biological processes in health and disease (1–3). Most studies have so far been limited to in vitro systems such as cell culture models. Although tremendously useful, these models cannot appropriately reflect relevant regulatory mechanisms of multicellular eukaryotes in vivo. This is particularly relevant for complex processes involving interactions between different cell types such as differentiation and development (4).Relative changes in protein abundance are most accurately measured by comparing the natural form of a peptide with its stable isotope-labeled analog. Several different approaches enable stable isotope labeling of peptides either by chemical reactions or metabolic incorporation of the label (5, 6). Metabolic labeling has several advantages such as high labeling efficiency and intrinsically higher precision. For example, metabolically labeled samples can be combined before further processing steps so that protein quantification is not affected by differences in sample preparation. Labeling of organisms with stable isotope tracers was pioneered by Rudolf Schoenheimer 75 years ago (7, 8). Since then, several model organisms ranging from prokaryotes to mammals have been labeled metabolically (for an excellent review, see Ref. 9). For example, Caenorhabditis elegans and Drosophila melanogaster have successfully been labeled with ¹⁵N (10), and ¹⁵N-labeled flies were recently used to study maternal-to-zygotic transition (11) and seminal fluid proteins (sfps)¹ transferred at mating (12). ¹⁵N has also been used to label entire rats, particularly for quantitative brain proteomics (13, 14). Despite its usefulness, ¹⁵N labeling also has several disadvantages. Because most peptides contain dozens of nitrogen atoms, labeling with highly enriched ¹⁵N still results in only partial peptide labeling and therefore complex isotope clusters. In addition, the mass shift between the labeled (i.e. heavy) and unlabeled (i.e. light) forms of a peptide depends on the number of nitrogen atoms and therefore varies depending on the peptide sequence. This leads to an increase in the number of candidate masses that need to be considered and therefore complicates peptide identification by search algorithms. Both problems result in smaller identification rates and less accurate quantification that can partially be overcome by computational correction (15, 16).Stable isotope labeling by amino acids in cell culture (SILAC) is another metabolic labeling approach with several unique advantages (17): because the label is introduced at the amino acid level, mass spectra can easily be interpreted, and peptides can be quantified with high precision. These features have made SILAC a very popular approach for cell culture-based quantitative and functional proteomics (18). As a potential disadvantage, SILAC is generally thought to be restricted to in vitro cell culture experiments. The only SILAC experiments in the fly model were carried out using cell lines cultivated in vitro (19, 20). However, in 2005, Hayter et al. (21) demonstrated that chicken can be partially labeled at the amino acid level by feeding them with a diet containing stable isotope-labeled valine. Three years later, Krüger et al. (22) achieved essentially complete labeling of the laboratory mouse. Until now, this so-called “SILAC mouse” was the only multicellular organism that has been completely labeled with the SILAC approach, and partial labeling was recently achieved in newts (21, 23).Here, we introduce the fruit fly D. melanogaster in the SILAC zoo. We refer to these animals as SILAC flies because they are obtained by feeding flies on SILAC-labeled yeast. D. melanogaster is one of the best characterized model organisms and has been used to address many fundamental questions in biology (24). Until now, most studies in D. melanogaster have focused on genetic aspects (25). However, proteins are the key actors in most biological processes. It is therefore highly desirable to obtain quantitative information at the protein level in D. melanogaster. We demonstrate in the present study that raising fly larvae on a diet of heavy lysine-labeled yeast cells results in virtually complete heavy labeling in the first filial (F₁) generation. Furthermore, we show that the SILAC fly enables proteome-wide quantification with higher precision than a label-free method. In a series of proof-of-principle experiments, we used the SILAC fly to investigate sexually dimorphic protein expression in D. melanogaster, thus providing the first systematic comparison of male and female flies at the protein level.     

Refined Preparation and Use of Anti-diglycine Remnant (K-ε-GG) Antibody Enables Routine Quantification of 10,000s of Ubiquitination Sites in Single Proteomics Experiments

Detection of endogenous ubiquitination sites by mass spectrometry has dramatically improved with the commercialization of anti-di-glycine remnant (K-ε-GG) antibodies. Here, we describe a number of improvements to the K-ε-GG enrichment workflow, including optimized antibody and peptide input requirements, antibody cross-linking, and improved off-line fractionation prior to enrichment. This refined and practical workflow enables routine identification and quantification of ∼20,000 distinct endogenous ubiquitination sites in a single SILAC experiment using moderate amounts of protein input.The commercialization of antibodies that recognize lysine residues modified with a di-glycine remnant (K-ε-GG)¹ has significantly transformed the detection of endogenous protein ubiquitination sites by mass spectrometry (1–5). Prior to the development of these highly specific reagents, proteomics experiments were limited to identification of up to only several hundred ubiquitination sites, which severely limited the scope of global ubiquitination studies (6). Recent proteomic studies employing anti-K-ε-GG antibodies have enhanced our understanding of ubiquitin biology through the identification of thousands of ubiquitination sites and the analysis of the change in relative abundance of these sites after chemical or biological perturbation (1–3, 5, 7). Use of stable isotope labeling by amino acids in cell culture (SILAC) for quantification has enabled researchers to better understand the extent of ubiquitin regulation upon proteasome inhibition and precisely identify those protein classes, such as newly synthesized proteins or chromatin-related proteins, that see overt changes in their ubiquitination levels upon drug treatment (2, 3, 5). Emanuel et al. (1) have combined genetic and proteomics assays implementing the anti-K-ε-GG antibody to identify hundreds of known and putative Cullin-RING ligase substrates, which has clearly demonstrated the extensive role of Cullin-RING ligase ubiquitination on cellular protein regulation.Despite the successes recently achieved with the use of the anti-K-ε-GG antibody, increased sample input (up to ∼35 mg) and/or the completion of numerous experimental replicates have been necessary to achieve large numbers of K-ε-GG sites (>5,000) in a single SILAC-based experiment (1–3, 5). For example, it has been recently shown that detection of more than 20,000 unique ubiquitination sites is possible from the analysis of five different murine tissues (8). However, as the authors indicate, only a few thousands sites are detected in any single analysis of an individual tissue sample (8). It is recognized that there is need for further improvements in global ubiquitin technology to increase the depth-of-coverage attainable in quantitative proteomic experiments using moderate amounts of protein input (9). Through systematic study and optimization of key pre-analytical variables in the preparation and use of the anti-K-ε-GG antibody as well as the proteomic workflow, we have now achieved, for the first time, routine quantification of ∼20,000 nonredundant K-ε-GG sites in a single SILAC triple encoded experiment starting with 5 mg of protein per SILAC channel. This represents a 10-fold improvement over our previously published method (3).     

A Genetic Engineering Solution to the ��Arginine Conversion Problem�� in Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC)

Stable isotope labeling by amino acids in cell culture (SILAC) provides a straightforward tool for quantitation in proteomics. However, one problem associated with SILAC is the in vivo conversion of labeled arginine to other amino acids, typically proline. We found that arginine conversion in the fission yeast Schizosaccharomyces pombe occurred at extremely high levels, such that labeling cells with heavy arginine led to undesired incorporation of label into essentially all of the proline pool as well as a substantial portion of glutamate, glutamine, and lysine pools. We found that this can be prevented by deleting genes involved in arginine catabolism using methods that are highly robust yet simple to implement. Deletion of both fission yeast arginase genes or of the single ornithine transaminase gene, together with a small modification to growth medium that improves arginine uptake in mutant strains, was sufficient to abolish essentially all arginine conversion. We demonstrated the usefulness of our approach in a large scale quantitative analysis of proteins before and after cell division; both up- and down-regulated proteins, including a novel protein involved in septation, were successfully identified. This strategy for addressing the “arginine conversion problem” may be more broadly applicable to organisms amenable to genetic manipulation.Stable isotope labeling by amino acids in cell culture (SILAC)¹ (1) is one of the key methods for large scale quantitative proteomics (2, 3). In SILAC experiments, proteins are metabolically labeled by culturing cells in media containing either normal (“light”) or heavy isotope-labeled amino acids, typically lysine and arginine. Peptides derived from the light and heavy cells are thus distinguishable by mass spectrometry and can be mixed for accurate quantitation. SILAC is also possible at the whole-organism level (4).An inherent problem in SILAC is the metabolic conversion of labeled arginine to other amino acids, as this complicates quantitative analysis of peptides containing these amino acids. Arginine conversion to proline is well described in mammalian cells, although the extent of conversion varies among cell types (5). When conversion is observed, typically 10–25% of the total proline pool is found to contain label (6–11). Arginine conversion has also been reported in SILAC experiments with budding yeast Saccharomyces cerevisiae (3, 12, 13).Because more than 50% of tryptic peptides in large data sets contain proline (7), it is not practical simply to disregard proline-containing peptides during quantitation. Several methods have been proposed to either reduce arginine conversion or correct for its effects on quantitation. In some cell types, arginine conversion can be prevented by lowering the concentration of exogenous arginine (6, 14–16) or by adding exogenous proline (9). However, these methods can involve significant changes to growth media and may need to be tested for each experimental condition used. Given the importance of arginine in many metabolic pathways, careful empirical titration of exogenous arginine concentration is required to minimize negative effects on cell growth (14). In addition, low arginine medium can lead to incomplete arginine labeling, although the reasons for this are not entirely clear (7). An alternative strategy is to omit labeled arginine altogether (3, 13, 17), but this reduces the number of quantifiable peptides. Correction methods include using two different forms of labeled arginine (7) or computationally compensating for proline-containing peptides (11, 12, 18). Ultimately, none of these methods address the problem at its root, the utilization of arginine in cellular metabolism.To develop a differential proteomics work flow for the fission yeast Schizosaccharomyces pombe, we sought to adapt SILAC for use in this organism, a widely used model eukaryote with excellent classical and reverse genetics. Here we describe extremely high conversion of labeled arginine to other amino acids in fission yeast as well as a novel general solution to the problem that should be applicable to other organisms. As proof of principle, we quantitated changes in protein levels before and after cell division on a proteome-wide scale. We identified both up- and down-regulated proteins, including a novel protein involved in septation.     

A New in Vivo Cross-linking Mass Spectrometry Platform to Define Protein–Protein Interactions in Living Cells

Protein–protein interactions (PPIs) are fundamental to the structure and function of protein complexes. Resolving the physical contacts between proteins as they occur in cells is critical to uncovering the molecular details underlying various cellular activities. To advance the study of PPIs in living cells, we have developed a new in vivo cross-linking mass spectrometry platform that couples a novel membrane-permeable, enrichable, and MS-cleavable cross-linker with multistage tandem mass spectrometry. This strategy permits the effective capture, enrichment, and identification of in vivo cross-linked products from mammalian cells and thus enables the determination of protein interaction interfaces. The utility of the developed method has been demonstrated by profiling PPIs in mammalian cells at the proteome scale and the targeted protein complex level. Our work represents a general approach for studying in vivo PPIs and provides a solid foundation for future studies toward the complete mapping of PPI networks in living systems.Protein–protein interactions (PPIs)¹ play a key role in defining protein functions in biological systems. Aberrant PPIs can have drastic effects on biochemical activities essential to cell homeostasis, growth, and proliferation, and thereby lead to various human diseases (1). Consequently, PPI interfaces have been recognized as a new paradigm for drug development. Therefore, mapping PPIs and their interaction interfaces in living cells is critical not only for a comprehensive understanding of protein function and regulation, but also for describing the molecular mechanisms underlying human pathologies and identifying potential targets for better therapeutics.Several strategies exist for identifying and mapping PPIs, including yeast two-hybrid, protein microarray, and affinity purification mass spectrometry (AP-MS) (2–5). Thanks to new developments in sample preparation strategies, mass spectrometry technologies, and bioinformatics tools, AP-MS has become a powerful and preferred method for studying PPIs at the systems level (6–9). Unlike other approaches, AP-MS experiments allow the capture of protein interactions directly from their natural cellular environment, thus better retaining native protein structures and biologically relevant interactions. In addition, a broader scope of PPI networks can be obtained with greater sensitivity, accuracy, versatility, and speed. Despite the success of this very promising technique, AP-MS experiments can lead to the loss of weak/transient interactions and/or the reorganization of protein interactions during biochemical manipulation under native purification conditions. To circumvent these problems, in vivo chemical cross-linking has been successfully employed to stabilize protein interactions in native cells or tissues prior to cell lysis (10–16). The resulting covalent bonds formed between interacting partners allow affinity purification under stringent and fully denaturing conditions, consequently reducing nonspecific background while preserving stable and weak/transient interactions (12–16). Subsequent mass spectrometric analysis can reveal not only the identities of interacting proteins, but also cross-linked amino acid residues. The latter provides direct molecular evidence describing the physical contacts between and within proteins (17). This information can be used for computational modeling to establish structural topologies of proteins and protein complexes (17–22), as well as for generating experimentally derived protein interaction network topology maps (23, 24). Thus, cross-linking mass spectrometry (XL-MS) strategies represent a powerful and emergent technology that possesses unparalleled capabilities for studying PPIs.Despite their great potential, current XL-MS studies that have aimed to identify cross-linked peptides have been mostly limited to in vitro cross-linking experiments, with few successfully identifying protein interaction interfaces in living cells (24, 25). This is largely because XL-MS studies remain challenging due to the inherent difficulty in the effective MS detection and accurate identification of cross-linked peptides, as well as in unambiguous assignment of cross-linked residues. In general, cross-linked products are heterogeneous and low in abundance relative to non-cross-linked products. In addition, their MS fragmentation is too complex to be interpreted using conventional database searching tools (17, 26). It is noted that almost all of the current in vivo PPI studies utilize formaldehyde cross-linking because of its membrane permeability and fast kinetics (10–16). However, in comparison to the most commonly used amine reactive NHS ester cross-linkers, identification of formaldehyde cross-linked peptides is even more challenging because of its promiscuous nonspecific reactivity and extremely short spacer length (27). Therefore, further developments in reagents and methods are urgently needed to enable simple MS detection and effective identification of in vivo cross-linked products, and thus allow the mapping of authentic protein contact sites as established in cells, especially for protein complexes.Various efforts have been made to address the limitations of XL-MS studies, resulting in new developments in bioinformatics tools for improved data interpretation (28–32) and new designs of cross-linking reagents for enhanced MS analysis of cross-linked peptides (24, 33–39). Among these approaches, the development of new cross-linking reagents holds great promise for mapping PPIs on the systems level. One class of cross-linking reagents containing an enrichment handle have been shown to allow selective isolation of cross-linked products from complex mixtures, boosting their detectability by MS (33–35, 40–42). A second class of cross-linkers containing MS-cleavable bonds have proven to be effective in facilitating the unambiguous identification of cross-linked peptides (36–39, 43, 44), as the resulting cross-linked products can be identified based on their characteristic and simplified fragmentation behavior during MS analysis. Therefore, an ideal cross-linking reagent would possess the combined features of both classes of cross-linkers. To advance the study of in vivo PPIs, we have developed a new XL-MS platform based on a novel membrane-permeable, enrichable, and MS-cleavable cross-linker, Azide-A-DSBSO (azide-tagged, acid-cleavable disuccinimidyl bis-sulfoxide), and multistage tandem mass spectrometry (MSⁿ). This new XL-MS strategy has been successfully employed to map in vivo PPIs from mammalian cells at both the proteome scale and the targeted protein complex level.     

Defining,Comparing, and Improving iTRAQ Quantification in Mass Spectrometry Proteomics Data

The purpose of this study was to generate a basis for the decision of what protein quantities are reliable and find a way for accurate and precise protein quantification. To investigate this we have used thousands of peptide measurements to estimate variance and bias for quantification by iTRAQ (isobaric tags for relative and absolute quantification) mass spectrometry in complex human samples. A549 cell lysate was mixed in the proportions 2:2:1:1:2:2:1:1, fractionated by high resolution isoelectric focusing and liquid chromatography and analyzed by three mass spectrometry platforms; LTQ Orbitrap Velos, 4800 MALDI-TOF/TOF and 6530 Q-TOF. We have investigated how variance and bias in the iTRAQ reporter ions data are affected by common experimental variables such as sample amount, sample fractionation, fragmentation energy, and instrument platform. Based on this, we have suggested a concept for experimental design and a methodology for protein quantification. By using duplicate samples in each run, each experiment is validated based on its internal experimental variation. The duplicates are used for calculating peptide weights, unique to the experiment, which is used in the protein quantification. By weighting the peptides depending on reporter ion intensity, we can decrease the relative error in quantification at the protein level and assign a total weight to each protein that reflects the protein quantitation confidence. We also demonstrate the usability of this methodology in a cancer cell line experiment as well as in a clinical data set of lung cancer tissue samples. In conclusion, we have in this study developed a methodology for improved protein quantification in shotgun proteomics and introduced a way to assess quantification for proteins with few peptides. The experimental design and developed algorithms decreased the relative protein quantification error in the analysis of complex biological samples.Recent developments in methods and instruments for mass spectrometry enable quantitative proteomics analysis of complex samples with good coverage (1–4). Several techniques for quantification by mass spectrometry exist, both using isotopic labeling and label free methods (5, 6). Quantification by isotopic labeling can be done on precursor ion level or by quantifying isobaric label fragments in fragment spectra. Isotope-coded affinity tag (7), isobaric tags for relative and absolute quantification (iTRAQ)¹ (8), and stable isotope labeling by amino acids in cell culture (SILAC) (9) are among the most commonly used labeling methods based on stable isotopes. iTRAQ allows for simultaneous relative quantification of up to eight samples within a single run. Quantification by mass spectrometry is however a challenge, and several factors contribute to the uncertainty in the quantitative estimate; differences in labeling efficiency, protein digestion, precursor mixing, ion suppression, peak detection, data preprocessing, and data analysis (10). The quality of quantitation methods can be measured in terms of precision and accuracy. Precision is affected by random errors, that is, random fluctuations around the true value (variance). Lack of accuracy is caused by systematic errors, that is, differences between true and observed values (bias).Several studies have shown that iTRAQ labeling is associated with bias; fold changes are compressed toward one (11–14). It has been suggested that this underestimation of fold change is caused by co-eluting peptides with similar m/z values that are isolated together, creating mixed iTRAQ intensities in complex samples (14). Concerning precision, iTRAQ data has been reported to exhibit variance heterogeneity. The coefficient of variance (CV) of the signal depends on the intensity, with larger CV for low intensity peaks (11, 12, 15, 16). Measurements of iTRAQ intensities for quantification are made in the MS/MS spectra of the peptides, and thereafter combined to calculate a summarized relative protein quantity. There are several different approaches for combining the iTRAQ peptide data to compute a reliable protein ratio. Methods to improve the protein quantification by addressing the variance heterogeneity have been based on excluding low intensity peptide data (17, 18), weighting the peptide data according to intensity (18–21) or stabilizing the variance (12).Quantitative studies of complex human samples are subject to even more challenges related to large biological variation, large and unknown complexity of the human proteome and a large concentration range of proteins. This in turn results in many peptides and a large variety of peptides that can cause interference and related problems in the mass spectrometry analysis. In, for example, biomarker discovery research the goal is to measure quantitative changes or differences in protein levels between two or more clinical conditions. It is therefore crucial to achieve as accurate and precise quantitative information from the data as possible as well as to correctly estimate the limitations of the quantification. Setting adequate standards for quantitative proteomics analysis is hence essential for being able to detect relevant changes in protein abundance, select important proteins, and further use those proteins to interpret the biological and clinical meaning (10, 22). Selecting a protein as significant and taking it to further validation in other clinical material using complementary techniques is time consuming and costly (23). For successful use of iTRAQ labeling in biomarker discovery, and to avoid false discoveries, it is hence essential to assess the accuracy and precision of the methodology.A common approach to study variance and bias in mass spectrometry based protein quantification is to spike a set of standard proteins into a sample and then measure the CV and bias of the intensities of those peptides. Spike-in of proteins has the benefit of looking at a small controlled set of peptides and how they behave in the studied system. This strategy has been used in several of the previously mentioned papers that address iTRAQ quantification (11–14). However, the number of data points studied may be unlikely to represent the complexity of a real biological sample, which often contains thousands of proteins (24). In the current study, all peptides detected in a complex human cell line sample (A549) are used to get an estimate of the quantitative accuracy and precision. This experimental setup is hence more similar to a real biomarker discovery study with high complex human proteome samples. The quality of the protein quantifications is compared among several different mass spectrometers in this work; also the influence of different loaded peptide amounts and the use of different methods for sample separation are examined. Factors such as variance and bias of peptide quantification by iTRAQ are systematically evaluated in those high complex samples. Further, methods for improving the protein quantification are investigated; by filtering on the peptide level to remove low quality intensities and by weighting the peptide values to account for the higher risk of errors at low intensities (20).We have described the factors contributing to bias and variance in protein quantification by iTRAQ labeling. This has generated guidelines for how to estimate the accuracy of protein quantities, which will be an essential tool in both biomarker discovery and studies of biological systems. Based on the results, we suggest an experimental design where each labeling set (e.g., iTRAQ) includes duplicate samples, and we describe how these duplicates are used for calculating peptide weights that can be used in addressing the accuracy of protein quantities. This novel approach is shown to improve protein quantification by iTRAQ in six data sets of A431 cell line samples treated with drug and a clinical data set of lung cancer tissue samples.     

Conserved Glutamate Residues Glu-343 and Glu-519 Provide Mechanistic Insights into Cation/Nucleoside Cotransport by Human Concentrative Nucleoside Transporter hCNT3

Human concentrative nucleoside transporter 3 (hCNT3) utilizes electrochemical gradients of both Na⁺ and H⁺ to accumulate pyrimidine and purine nucleosides within cells. We have employed radioisotope flux and electrophysiological techniques in combination with site-directed mutagenesis and heterologous expression in Xenopus oocytes to identify two conserved pore-lining glutamate residues (Glu-343 and Glu-519) with essential roles in hCNT3 Na⁺/nucleoside and H⁺/nucleoside cotransport. Mutation of Glu-343 and Glu-519 to aspartate, glutamine, and cysteine severely compromised hCNT3 transport function, and changes included altered nucleoside and cation activation kinetics (all mutants), loss or impairment of H⁺ dependence (all mutants), shift in Na⁺:nucleoside stoichiometry from 2:1 to 1:1 (E519C), complete loss of catalytic activity (E519Q) and, similar to the corresponding mutant in Na⁺-specific hCNT1, uncoupled Na⁺ currents (E343Q). Consistent with close-proximity integration of cation/solute-binding sites within a common cation/permeant translocation pore, mutation of Glu-343 and Glu-519 also altered hCNT3 nucleoside transport selectivity. Both residues were accessible to the external medium and inhibited by p-chloromercuribenzene sulfonate when converted to cysteine.Physiologic nucleosides and the majority of synthetic nucleoside analogs with antineoplastic and/or antiviral activity are hydrophilic molecules that require specialized plasma membrane nucleoside transporter (NT)³ proteins for transport into or out of cells (1–4). NT-mediated transport is required for nucleoside metabolism by salvage pathways and is a critical determinant of the pharmacologic actions of nucleoside drugs (3–6). By regulating adenosine availability to purinoreceptors, NTs also modulate a diverse array of physiological processes, including neurotransmission, immune responses, platelet aggregation, renal function, and coronary vasodilation (4, 6, 7). Two structurally unrelated NT families of integral membrane proteins exist in human and other mammalian cells and tissues as follows: the SLC28 concentrative nucleoside transporter (CNT) family and the SLC29 equilibrative nucleoside transporter (ENT) family (3, 4, 6, 8, 9). ENTs are normally present in most, possibly all, cell types (4, 6, 8). CNTs, in contrast, are found predominantly in intestinal and renal epithelia and other specialized cell types, where they have important roles in absorption, secretion, distribution, and elimination of nucleosides and nucleoside drugs (1–3, 5, 6, 9).The CNT protein family in humans is represented by three members, hCNT1, hCNT2, and hCNT3. Belonging to a CNT subfamily phylogenetically distinct from hCNT1/2, hCNT3 utilizes electrochemical gradients of both Na⁺ and H⁺ to accumulate a broad range of pyrimidine and purine nucleosides and nucleoside drugs within cells (10, 11). hCNT1 and hCNT2, in contrast, are Na⁺-specific and transport pyrimidine and purine nucleosides, respectively (11–13). Together, hCNT1–3 account for the three major concentrative nucleoside transport processes of human and other mammalian cells. Nonmammalian members of the CNT protein family that have been characterized functionally include hfCNT, a second member of the CNT3 subfamily from the ancient marine prevertebrate the Pacific hagfish Eptatretus stouti (14), CeCNT3 from Caenorhabditis elegans (15), CaCNT from Candida albicans (16), and the bacterial nucleoside transporter NupC from Escherichia coli (17). hfCNT is Na⁺- but not H⁺-coupled, whereas CeCNT3, CaCNT, and NupC are exclusively H⁺-coupled. Na⁺:nucleoside coupling stoichiometries are 1:1 for hCNT1 and hCNT2 and 2:1 for hCNT3 and hfCNT3 (11, 14). H⁺:nucleoside coupling ratios for hCNT3 and CaCNT are 1:1 (11, 16).Although much progress has been made in molecular studies of ENT proteins (4, 6, 8), studies of structurally and functionally important regions and residues within the CNT protein family are still at an early stage. Topological investigations suggest that hCNT1–3 and other eukaryote CNT family members have a 13 (or possibly 15)-transmembrane helix (TM) architecture, and multiple alignments reveal strong sequence similarities within the C-terminal half of the proteins (18). Prokaryotic CNTs lack the first three TMs of their eukaryotic counterparts, and functional expression of N-terminally truncated human and rat CNT1 in Xenopus oocytes has established that these three TMs are not required for Na⁺-dependent uridine transport activity (18). Consistent with this finding, chimeric studies involving hCNT1 and hfCNT (14) and hCNT1 and hCNT3 (19) have demonstrated that residues involved in Na⁺- and H⁺-coupling reside in the C-terminal half of the protein. Present in this region of the transporter, but of unknown function, is a highly conserved (G/A)XKX₃NEFVA(Y/M/F) motif common to all eukaryote and prokaryote CNTs.By virtue of their negative charge and consequent ability to interact directly with coupling cations and/or participate in cation-induced and other protein conformational transitions, glutamate and aspartate residues play key functional and structural roles in a broad spectrum of mammalian and bacterial cation-coupled transporters (20–30). Little, however, is known about their role in CNTs. This study builds upon a recent mutagenesis study of conserved glutamate and aspartate residues in hCNT1 (31) to undertake a parallel in depth investigation of corresponding residues in hCNT3. By employing the multifunctional capability of hCNT3 as a template for these studies, this study provides novel mechanistic insights into the molecular mechanism(s) of CNT-mediated cation/nucleoside cotransport, including the role of the (G/A)XKX₃NEFVA(Y/M/F) motif.     

Identification and Quantification of Glycoproteins Using Ion-Pairing Normal-phase Liquid Chromatography and Mass Spectrometry

Glycoprotein structure determination and quantification by MS requires efficient isolation of glycopeptides from a proteolytic digest of complex protein mixtures. Here we describe that the use of acids as ion-pairing reagents in normal-phase chromatography (IP-NPLC) considerably increases the hydrophobicity differences between non-glycopeptides and glycopeptides, thereby resulting in the reproducible isolation of N-linked high mannose type and sialylated glycopeptides from the tryptic digest of a ribonuclease B and fetuin mixture. The elution order of non-glycopeptides relative to glycopeptides in IP-NPLC is predictable by their hydrophobicity values calculated using the Wimley-White water/octanol hydrophobicity scale. O-linked glycopeptides can be efficiently isolated from fetuin tryptic digests using IP-NPLC when N-glycans are first removed with PNGase. IP-NPLC recovers close to 100% of bacterial N-linked glycopeptides modified with non-sialylated heptasaccharides from tryptic digests of periplasmic protein extracts from Campylobacter jejuni 11168 and its pglD mutant. Label-free nano-flow reversed-phase LC-MS is used for quantification of differentially expressed glycopeptides from the C. jejuni wild-type and pglD mutant followed by identification of these glycoproteins using multiple stage tandem MS. This method further confirms the acetyltransferase activity of PglD and demonstrates for the first time that heptasaccharides containing monoacetylated bacillosamine are transferred to proteins in both the wild-type and mutant strains. We believe that IP-NPLC will be a useful tool for quantitative glycoproteomics.Protein glycosylation is a biologically significant and complex post-translational modification, involved in cell-cell and receptor-ligand interactions (1–4). In fact, clinical biomarkers and therapeutic targets are often glycoproteins (5–9). Comprehensive glycoprotein characterization, involving glycosylation site identification, glycan structure determination, site occupancy, and glycan isoform distribution, is a technical challenge particularly for quantitative profiling of complex protein mixtures (10–13). Both N- and O-glycans are structurally heterogeneous (i.e. a single site may have different glycans attached or be only partially occupied). Therefore, the MS¹ signals from glycopeptides originating from a glycoprotein are often weaker than from non-glycopeptides. In addition, the ionization efficiency of glycopeptides is low compared with that of non-glycopeptides and is often suppressed in the presence of non-glycopeptides (11–13). When the MS signals of glycopeptides are relatively high in simple protein digests then diagnostic sugar oxonium ion fragments produced by, for example, front-end collisional activation can be used to detect them. However, when peptides and glycopeptides co-elute, parent ion scanning is required to selectively detect the glycopeptides (14). This can be problematic in terms of sensitivity, especially for detecting glycopeptides in digests of complex protein extracts.Isolation of glycopeptides from proteolytic digests of complex protein mixtures can greatly enhance the MS signals of glycopeptides using reversed-phase LC-ESI-MS (RPLC-ESI-MS) or MALDI-MS (15–24). Hydrazide chemistry is used to isolate, identify, and quantify N-linked glycopeptides effectively, but this method involves lengthy chemical procedures and does not preserve the glycan moieties thereby losing valuable information on glycan structure and site occupancy (15–17). Capturing glycopeptides with lectins has been widely used, but restricted specificities and unspecific binding are major drawbacks of this method (18–21). Under reversed-phase LC conditions, glycopeptides from tryptic digests of gel-separated glycoproteins have been enriched using graphite powder medium (22). In this case, however, a second digestion with proteinase K is required for trimming down the peptide moieties of tryptic glycopeptides so that the glycopeptides (typically <5 amino acid residues) essentially resemble the glycans with respect to hydrophilicity for subsequent separation. Moreover, the short peptide sequences of the proteinase K digest are often inadequate for de novo sequencing of the glycopeptides.Glycopeptide enrichment under normal-phase LC (NPLC) conditions has been demonstrated using various hydrophilic media and different capture and elution conditions (23–28). NPLC allows either direct enrichment of peptides modified by various N-linked glycan structures using a ZIC®-HILIC column (23–27) or targeting sialylated glycopeptides using a titanium dioxide micro-column (28). However, NPLC is neither effective for enriching less hydrophilic glycopeptides, e.g. the five high mannose type glycopeptides modified by 7–11 monosaccharide units from a tryptic digest of ribonuclease b (RNase B), nor for enriching O-linked glycopeptides of bovine fetuin using a ZIC-HILIC column (23). The use of Sepharose medium for enriching glycopeptides yielded only modest recovery of glycopeptides (28). In addition, binding of hydrophilic non-glycopeptides with these hydrophilic media contaminates the enriched glycopeptides (23, 28).We have recently developed an ion-pairing normal-phase LC (IP-NPLC) method to enrich glycopeptides from complex tryptic digests using Sepharose medium and salts or bases as ion-pairing reagents (29). Though reasonably effective the technique still left room for significant improvement. For example, the method demonstrated relatively modest glycopeptide selectivity, providing only 16% recovery for high mannose type glycopeptides (29). Here we report on a new IP-NPLC method using acids as ion-pairing reagents and polyhydroxyethyl aspartamide (A) as the stationary phase for the effective isolation of tryptic glycopeptides. The method was developed and evaluated using a tryptic digest of RNase B and fetuin mixture. In addition, we demonstrate that O-linked glycopeptides can be effectively isolated from a fetuin tryptic digest by IP-NPLC after removal of the N-linked glycans by PNGase F.The new IP-NPLC method was used to enrich N-linked glycopeptides from the tryptic digests of protein extracts of wild-type (wt) and PglD mutant strains of Campylobacter jejuni NCTC 11168. C. jejuni has a unique N-glycosylation system that glycosylates periplasmic and inner membrane proteins containing the extended N-linked sequon, D/E-X-N-X-S/T, where X is any amino acid other than proline (30–32). The N-linked glycan of C. jejuni has been previously determined to be GalNAc-α1,4-GalNAc-α1,4-[Glcβ1,3]-GalNAc-α1,4-GalNAc-α1,4-GalNAc-α1,3-Bac-β1 (BacGalNAc₅Glc residue mass: 1406 Da), where Bac is 2,4-diacetamido-2,4,6-trideoxyglucopyranose (30). In addition, the glycan structure of C. jejuni is conserved, unlike in eukaryotic systems (30–32). IP-NPLC recovered close to 100% of the bacterial N-linked glycopeptides with virtually no contamination of non-glycopeptides. Furthermore, we demonstrate for the first time that acetylation of bacillosamine is incomplete in the wt using IP-NPLC and label-free MS.