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.     

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.     

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).     

Absolute Proteome and Phosphoproteome Dynamics during the Cell Cycle of Schizosaccharomyces pombe (Fission Yeast)

To quantify cell cycle-dependent fluctuations on a proteome-wide scale, we performed integrative analysis of the proteome and phosphoproteome during the four major phases of the cell cycle in Schizosaccharomyces pombe. In highly synchronized cells, we identified 3753 proteins and 3682 phosphorylation events and relatively quantified 65% of the data across all phases. Quantitative changes during the cell cycle were infrequent and weak in the proteome but prominent in the phosphoproteome. Protein phosphorylation peaked in mitosis, where the median phosphorylation site occupancy was 44%, about 2-fold higher than in other phases. We measured copy numbers of 3178 proteins, which together with phosphorylation site stoichiometry enabled us to estimate the absolute amount of protein-bound phosphate, as well as its change across the cell cycle. Our results indicate that 23% of the average intracellular ATP is utilized by protein kinases to phosphorylate their substrates to drive regulatory processes during cell division. Accordingly, we observe that phosphate transporters and phosphate-metabolizing enzymes are phosphorylated and therefore likely to be regulated in mitosis.Cell replication involves a complex series of highly regulated and evolutionary conserved events, called the “cell cycle.” Aberrations in the cell cycle have severe implications and can cause cancerous growth. A detailed understanding of the cell cycle and its regulation may identify additional targets for cancer therapy (1–3). The cell cycle has been the subject of previous proteomics studies. Olsen et al. (4) measured the dynamics of thousands of proteins and phosphorylation events across cell cycle phases of HeLa cells, providing insights into the underlying regulatory mechanisms and pointing to a general increase in phosphorylation site occupancy during M phase. In a targeted study, Pagliuca et al. (5) investigated interactors of cyclins E1, A2, and B1 in HeLa cells, revealing key mechanistic links between DNA replication and mitosis.Schizosaccharomyces pombe (fission yeast) is a unicellular organism, which can easily be genetically manipulated and carries many cell cycle features similar to metazoan cells. It is an important model organism to study the cell cycle and its checkpoint controls (6). Recent global proteomics studies of yeasts and their cell cycle (7–13) have mainly focused on Saccharomyces cerevisiae (budding yeast), with only a few studies of fission yeast (14, 15), although the fission yeast cell cycle may be more representative of eukaryotic cell cycles (16). However, attention of the proteomics community toward S. pombe is increasing. Recent proteomics studies covered up to 4087 S. pombe proteins (71% of the predicted proteome) and 1544 phosphoproteins in both asynchronous and synchronized cell cultures (17–22); however, a comprehensive analysis of the S. pombe cell cycle is so far missing.Here, we use high resolution mass spectrometry in combination with stable isotope labeling by amino acids in the cell culture (SILAC)¹ method, termed super-SILAC (23), and intensity-based absolute quantification (iBAQ) (24) to measure relative and absolute dynamics of the proteome and phosphoproteome during the cell cycle of fission yeast. We estimate copy numbers for 3178 S. pombe proteins, and we combine these data with calculated phosphorylation site stoichiometry to estimate the total amount of protein-bound phosphate and its dynamics across the cell cycle. Providing the global absolute dynamics and stoichiometry of proteins and their modifications will be a valuable resource for classical and systems biologists alike.     

Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC)-Based Strategy for Proteome-Wide Thermodynamic Analysis of Protein-Ligand Binding Interactions

Described here is a quantitative mass spectrometry-based proteomics method for the large-scale thermodynamic analysis of protein-ligand binding interactions. The methodology utilizes a chemical modification strategy termed, Stability of Proteins from Rates of Oxidation (SPROX), in combination with a Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) approach to compare the equilibrium folding/unfolding properties of proteins in the absence and presence of target ligands. The method, which is general with respect to ligand, measures the ligand-induced changes in protein stability associated with protein-ligand binding. The methodology is demonstrated in a proof-of-principle study in which the well-characterized protein-drug interaction between cyclosporine A (CsA) and cyclophilin A was successfully analyzed in the context of a yeast cell lysate. A control experiment was also performed to assess the method''s false positive rate of ligand discovery, which was found to be on the order of 0.4 - 3.5%. The new method was utilized to characterize the adenosine triphosphate (ATP)-interactome in Saccharomyces cerevisiae using the nonhydrolyzable ATP analog, adenylyl imidodiphosphate (AMP-PNP), and the proteins in a yeast cell lysate. The new methodology enabled the interrogation of 526 yeast proteins for interactions with ATP using 2035 peptide probes. Ultimately, 325 peptide hits from 139 different proteins were identified. Approximately 70% of the hit proteins identified in this work were not previously annotated as ATP binding proteins. However, nearly two-thirds of the newly discovered ATP interacting proteins have known interactions with other nucleotides and co-factors (e.g. NAD and GTP), DNA, and RNA based on GO-term analyses. The current work is the first proteome-wide profile of the yeast ATP-interactome, and it is the largest proteome-wide profile of any ATP-interactome generated, to date, using an energetics-based method. The data is available via ProteomeXchange with identifiers PXD000858, DOI 10.6019/PXD000858, and PXD000860.The characterization of protein-ligand interactions is important in many areas of biochemical research from fundamental studies of biological processes to understanding drug action. Currently, the most widely used methods for proteome-wide analyses of protein-ligand binding interactions are those that combine an affinity purification step with a mass spectrometry-based proteomics analysis. Such methods have provided a wealth of information about protein-protein interaction networks in different proteomes (1–4), and they have helped identify the protein targets of small molecules (5–7). However, a significant drawback to their use is the need for specially designed ligands to facilitate the affinity purification. This has prompted the development of more general methods for protein-ligand binding analyses that can be performed directly in solution and do not require derivatization and/or immobilization of the ligand. Several such methods involving the use of chromatography co-elution (8), protease susceptibility (9), and energetics-based approaches (10–15) have recently been reported.Energetics-based approaches are especially attractive for protein-ligand binding analyses because they can be both quantitative and general with respect to ligand class. Two energetics-based approaches, the stability of proteins from rates of oxidation (SPROX)¹ (10, 16, 17) and pulse proteolysis techniques (13, 18), have shown promise for protein-ligand binding analyses on the proteomic scale, but so far have been limited in their proteomic coverage. Although the pulse proteolysis technique does utilize targeted mass spectrometry-based proteomics analyses for the identification of hit proteins, the technique relies on gel-based strategies for the resolution, detection, and quantitation of potential protein targets (13, 18). This reliance on gel-based strategies for protein resolution, detection, and quantitation, ultimately limits the complexity of protein samples that can be interrogated for ligand binding. In contrast, the SPROX technique has been interfaced with conventional bottom-up shotgun proteomics platforms that exploit the capabilities of modern LC-MS/MS systems to resolve, detect, and quantify the protein components of complex biological mixtures (10, 16, 17).A key limitation to the bottom-up shotgun proteomics protocols developed for SPROX analyses, to date, is that they require the detection and quantitation of methionine-containing peptides to report on the thermodynamic stability of the proteins to which they map. Although the frequency of methionine residues in proteins is relatively low (∼2.5%) (19), the large majority of proteins have at least one methionine. Because one methionine residue can report on the global equilibrium folding/unfolding properties of the protein or protein domain to which it maps, the scope of SPROX is not fundamentally limited by the relatively low frequency of methionine residues in proteins. Rather, the protein coverage in proteome-wide SPROX experiments is limited by the practicalities associated with the comprehensive detection and quantitation of methionine-containing peptides in the bottom-up shotgun proteomics experiment.The SPROX protocol described here utilizes a stable isotope labeling with amino acids in cell culture (SILAC)-based strategy to expand the protein coverage in proteome-wide SPROX experiments by enabling any peptide (i.e. methionine-containing or not) that is identified and quantified in a bottom-up shotgun proteomics experiment to report on the stability of the protein to which it maps. As part of the work described here the capabilities of this new method for protein-ligand binding analysis (referred to hereafter as SILAC-SPROX) are demonstrated and benchmarked in two protein-ligand binding studies. In the first part of this work, the endogenous proteins in a yeast cell lysate are analyzed for binding to cyclosporine A (CsA), an immunosuppressant with well-characterized protein targets (5, 20). In the second part of this work, the endogenous proteins in a yeast cell lysate are analyzed for binding to adenylyl imidodiphosphate (AMP-PNP), a nonhydrolyzable analog of the ubiquitous enzyme co-factor, adenosine triphosphate (ATP), which has less well-characterized protein targets. In the CsA binding study, the already well-characterized tight-binding interaction between CsA and cyclophilin A (21–23) was successfully detected and quantified using the methodology. A number of known and unknown protein binding interactions of ATP were identified and quantified in the ATP-binding experiments described here. The SILAC-SPROX approach shows promise for future studies of protein-ligand interactions at the systems level (e.g. in cellular processes and disease states).     

Deep Proteomic Evaluation of Primary and Cell Line Motoneuron Disease Models Delineates Major Differences in Neuronal Characteristics

The fatal neurodegenerative disorders amyotrophic lateral sclerosis and spinal muscular atrophy are, respectively, the most common motoneuron disease and genetic cause of infant death. Various in vitro model systems have been established to investigate motoneuron disease mechanisms, in particular immortalized cell lines and primary neurons. Using quantitative mass-spectrometry-based proteomics, we compared the proteomes of primary motoneurons to motoneuron-like cell lines NSC-34 and N2a, as well as to non-neuronal control cells, at a depth of 10,000 proteins. We used this resource to evaluate the suitability of murine in vitro model systems for cell biological and biochemical analysis of motoneuron disease mechanisms. Individual protein and pathway analysis indicated substantial differences between motoneuron-like cell lines and primary motoneurons, especially for proteins involved in differentiation, cytoskeleton, and receptor signaling, whereas common metabolic pathways were more similar. The proteins associated with amyotrophic lateral sclerosis also showed distinct differences between cell lines and primary motoneurons, providing a molecular basis for understanding fundamental alterations between cell lines and neurons with respect to neuronal pathways with relevance for disease mechanisms. Our study provides a proteomics resource for motoneuron research and presents a paradigm of how mass-spectrometry-based proteomics can be used to evaluate disease model systems.Motoneurons are extremely extended neurons that mediate the control of all muscle types by the central nervous system. Therefore, diseases involving progressive motoneuron degeneration such as amyotrophic lateral sclerosis (ALS)¹ (OMIM: 105400) or spinal muscle atrophy (OMIM: 253300) are particularly devastating and generally fatal disorders. Today, ALS is believed to form a phenotypic continuum with the disease entity frontotemporal lobe degeneration (OMIM: 600274) (1, 2). About 10% of ALS cases are known to be inherited, but the vast majority are considered sporadic. The number of inherited cases might be underestimated because of incomplete family histories, non-paternity, early death of family members, or incomplete penetrance (3).Mutations in several genes have been reported for the familial form, including in Sod1 (4), Als2 (5), Setx (6), Vapb (7), Tardbp (8, 9), Fus/Tls (10, 11), Vcp (12), Pfn1 (13), and several others (reviewed in Ref. 14). The most frequent genetic cause of inherited ALS was recently shown to be a hexanucleotide repeat expansion in an intron of a gene of unknown function called C9orf72 (15–17). Based on the spectrum of known mutations, several disease mechanisms for ALS have been proposed, including dysfunction of protein folding, axonal transport, RNA splicing, and metabolism (reviewed in Refs. 14, 18, and 19). Despite intensive research, it is still unclear whether a main common molecular pathway or mechanism underlies motoneuron degeneration in ALS and frontotemporal lobe degeneration. Spinal muscle atrophy is caused by homozygous mutations or deletions in the survival of motor neuron gene (Smn1) that presumably impair the RNA metabolism through diminished functionality of the Smn1 gene product (20). Over recent decades several model systems have been established to investigate ALS (21). These include transgenic animal models such as mouse (22), drosophila (23), and zebrafish (24). In cell-based studies, primary motoneurons cultured from rodent embryos (25) or motoneuron-like cell lines are employed. Primary cells are considered to more closely mimic the in vivo situation, but they are more challenging to establish and maintain. In contrast, the degree of functional relevance of cell lines can be difficult to establish, but they can be propagated without limitation and are well suited for high-throughput analysis. In particular, the spinal cord neuron–neuroblastoma hybrid cell line NSC-34 (26) and the mouse neuroblastoma cell line N2a (27) are widely used not only to assess motoneuron function, but also to study disease mechanisms in motoneurons (28, 29).As proteins are the functional actors in cells, proteomics should be able to make important contributions to the characterization and evaluation of cellular models. In particular, by identifying and quantifying the expressed proteins and bioinformatically interpreting the results, one can obtain enough information to infer functional differences. Our laboratory has previously shown proof of concept of such an approach by comparing the expression levels of about 4,000 proteins between primary hepatocytes and a hepatoma cell line (30). Very recently, mass-spectrometry-based proteomics has achieved sufficient depth and accuracy to quantify almost the entire proteome of mammalian cell lines (31–33). Furthermore, new instrumentation and algorithms now make it possible to perform label-free quantification between multiple cellular systems and with an accuracy previously associated only with stable isotope labeling techniques (34, 35).To evaluate the suitability of motoneuron-like cell lines as cellular model systems for research on ALS and related disorders, we characterized the proteomes of two widely used cell lines, NSC-34 and N2a, and compared them with the proteomes of mouse primary motoneurons and non-neuronal control cell lines. To generate primary motoneurons, we employed a recently described culturing system that makes it possible to isolate highly enriched motoneuron populations in less than 8 h (25). We identified more than 10,000 proteins and investigated differences in quantitative levels of individual neuron-associated proteins and pathways related to motoneuron function and disease mechanisms.     

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.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

CD38/cADPR/Ca2+ Pathway Promotes Cell Proliferation and Delays Nerve Growth Factor-induced Differentiation in PC12 Cells

Intracellular Ca²⁺ mobilization plays an important role in a wide variety of cellular processes, and multiple second messengers are responsible for mediating intracellular Ca²⁺ changes. Here we explored the role of one endogenous Ca²⁺-mobilizing nucleotide, cyclic adenosine diphosphoribose (cADPR), in the proliferation and differentiation of neurosecretory PC12 cells. We found that cADPR induced Ca²⁺ release in PC12 cells and that CD38 is the main ADP-ribosyl cyclase responsible for the acetylcholine (ACh)-induced cADPR production in PC12 cells. In addition, the CD38/cADPR signaling pathway is shown to be required for the ACh-induced Ca²⁺ increase and cell proliferation. Inhibition of the pathway, on the other hand, accelerated nerve growth factor (NGF)-induced neuronal differentiation in PC12 cells. Conversely, overexpression of CD38 increased cell proliferation but delayed NGF-induced differentiation. Our data indicate that cADPR plays a dichotomic role in regulating proliferation and neuronal differentiation of PC12 cells.Mobilization of intracellular Ca²⁺ stores is involved in diverse cell functions, including fertilization, cell proliferation, and differentiation (1–4). At least three endogenous Ca²⁺-mobilizing messengers have been identified, including inositol trisphosphate (IP₃),³ nicotinic adenine acid dinucleotide phosphate (NAADP), and cyclic adenosine diphosphoribose (cADPR). Similar to IP₃, cADPR can mobilize calcium release in a wide variety of cell types and species, from protozoa to animals. The cADPR-mediated Ca²⁺ signaling has been indicated in a variety of cellular processes (5–7), from abscisic acid signaling and regulation of the circadian clock in plants, to mediating long-term synaptic depression in hippocampus.Ample evidence shows that the ryanodine receptors are the main intracellular targets for cADPR (1, 2, 8). Ryanodine receptors (RyRs) are intracellular Ca²⁺ channels widely expressed in various cells and tissues, including muscles and neurons. It is the major cellular mediator of Ca²⁺-induced Ca²⁺ release (CICR) in cells. There are three isoforms of ryanodine receptors: RyR1, RyR2, and RyR3, all of which have been implicated in the cADPR signaling (1, 2, 8). However, evidence regarding cADPR acting directly on the receptors is lacking (9). It has been suggested that accessory proteins, such as calmodulin and FK506-binding protein (FKBP), may be involved instead (10–15).cADPR is formed from nicotinamide adenine dinucleotide (NAD) by ADP-ribosyl cyclases. Six ADP-ribosyl cyclases have been identified so far: Aplysia ADP-ribosyl cyclase, three sea urchin homologues (16, 17), and two mammalian homologues, CD38 and CD157 (18). CD38 is a membrane-bound protein and the main mammalian ADP-ribosyl cyclase. As a novel multifunctional enzyme, CD38 catalyzes the synthesis and hydrolysis of both cADPR and NAADP, two structurally and functionally distinct Ca²⁺ messengers. Virtually all mammalian tissues ever examined have been shown to express CD38. CD38 knock-out mice exhibit multiple physiological defects, ranging from impaired immune responses, metabolic disturbances, to behavioral modifications (1, 6, 18).CD38 was originally identified as a lymphocyte differentiation antigen (18). Indeed, CD38/cADPR has been linked to cell differentiation (5). For example, in human HL-60 cells, CD38 expression and the consequential accumulation of cADPR play a causal role in mediating granulocytic differentiation (19). In addition, expression of CD38 in HeLa and 3T3 cells not only increased intracellular Ca²⁺ concentration but also induced cell proliferation by significantly reducing the S phase duration, leading to shortened cell doubling time (20). The ability of cADPR to increase cell proliferation has also been observed in human T cells (21), human hemopoietic progenitors (22), human peripheral blood mononuclear cells (23), human mesenchymal stem cells (24), and murine mesangial cells (25).The PC12 cell line was derived from rat adrenal medulla and has been used extensively as a neuronal model, since it exhibits many of the functions observed in primary neuronal cultures (26). Most importantly, PC12 cells can be induced by nerve growth factor (NGF) to differentiate into cells with extensive neurite outgrowths, resembling neuronal dendritic trees (26, 27). In contrast to NGF, numerous growth factors and neurotransmitters can induce the proliferation of PC12 cells instead (26). Both IP₃ receptor- and ryanodine receptor-mediated Ca²⁺ stores have been shown to be present in PC12 cells (28–31). The type 2 ryanodine receptor is expressed in PC12 cells and activation of the NO/cGMP pathway in PC12 cells results in calcium mobilization, which is mediated by cADPR and similar to that seen in sea urchin eggs (32). It has been demonstrated that NAADP, another Ca²⁺-mobilizing messenger, is also a potent neuronal differentiation inducer in PC12 cells, while IP₃ exhibits no such role (33, 34). Whether cADPR is involved in the proliferation and differentiation of PC12 cells is unknown.Here we show that activation of the CD38/cADPR/Ca²⁺ signaling is required for the ACh-induced proliferation in PC12 cells, while inhibition of the pathway accelerates NGF-induced neuronal differentiation. Our data indicate that cADPR is important in regulating cell proliferation and neuronal differentiation in PC12 cells.     

Mass Spectrometry–based Proteomic Analysis of the Matrix Microenvironment in Pluripotent Stem Cell Culture

The cellular microenvironment comprises soluble factors, support cells, and components of the extracellular matrix (ECM) that combine to regulate cellular behavior. Pluripotent stem cells utilize interactions between support cells and soluble factors in the microenvironment to assist in the maintenance of self-renewal and the process of differentiation. However, the ECM also plays a significant role in shaping the behavior of human pluripotent stem cells, including embryonic stem cells (hESCs) and induced pluripotent stem cells. Moreover, it has recently been observed that deposited factors in a hESC-conditioned matrix have the potential to contribute to the reprogramming of metastatic melanoma cells. Therefore, the ECM component of the pluripotent stem cell microenvironment necessitates further analysis.In this study we first compared the self-renewal and differentiation properties of hESCs grown on Matrigel™ pre-conditioned by hESCs to those on unconditioned Matrigel™. We determined that culture on conditioned Matrigel™ prevents differentiation when supportive growth factors are removed from the culture medium. To investigate and identify factors potentially responsible for this beneficial effect, we performed a defined SILAC MS-based proteomics screen of hESC-conditioned Matrigel™. From this proteomics screen, we identified over 80 extracellular proteins in matrix conditioned by hESCs and induced pluripotent stem cells. These included matrix-associated factors that participate in key stem cell pluripotency regulatory pathways, such as Nodal/Activin and canonical Wnt signaling. This work represents the first investigation of stem-cell-derived matrices from human pluripotent stem cells using a defined SILAC MS-based proteomics approach.The two defining characteristics of human embryonic stem cells (hESCs),¹ self-renewal and pluripotency, are maintained by a delicate balance of intracellular and extracellular signaling processes. Extracellular regulation is primarily the result of changes in the microenvironment surrounding the cells during growth in vitro or in vivo. HESCs interact with this “niche ” through support cells, extracellular matrix (ECM) components, and autocrine/paracrine signaling (reviewed in Refs. 1–3). Modulation of any of these supportive elements individually or in combination has been used extensively to alter hESC behavior (1–3).The culture of hESCs, as well as that of human induced pluripotent stem cells (hiPSCs), is conventionally performed on a layer of irradiated mouse embryonic fibroblast cells (MEFs). These MEFs are believed to promote the maintenance of hESCs and hiPSCs through the secretion of beneficial support proteins and cytokines into the soluble microenvironment. A number of proteomic studies have been conducted that examine the secretome of feeder-cell layers in an attempt to elucidate proteins and pathways essential for hESC and hiPSC survival (4–7). Alternatively, hESCs and hiPSCs can be cultured in feeder-free conditions in the absence of support cells. In feeder-free conditions, hESCs and hiPSCs are most often grown on the basement membrane matrix Matrigel™ in medium that has been previously conditioned by MEFs (MEF-CM). Matrigel™ is a gelatinous mixture that is secreted by Engelbreth-Holm-Swarm mouse sarcoma cells (8). Although recent studies have proposed that a variety of defined matrices can support the growth of hESCs and hiPSCs, few of these can maintain a wide range of stem cell lines and therefore are typically not used in place of Matrigel™. The properties of Matrigel™ that make it such an effective matrix for hESC and hiPSC culture remain poorly understood. Because of the complexity of matrices like Matrigel™, the majority of proteomic studies that examine the hESC and hiPSC microenvironment have focused on contributions from support cells and soluble extracellular factors.The ECM is typically a complex network of structural proteins and glycosaminoglycans that function to support cells through the regulation of processes such as adhesion and growth factor signaling (9). Thus, it is not surprising that the generation of a well-defined matrix capable of facilitating hESC and hiPSC self-renewal has remained difficult (10). Previous proteomic investigations of Matrigel™ and other matrices supportive of hESC maintenance in vitro have revealed the presence of numerous growth, binding, and signaling proteins (11, 12). Further examination of how hESCs and hiPSCs interact with these complex matrices would provide critical information about what role the ECM plays in the organization of processes involved in the regulation of self-renewal and pluripotency.A recent study has established the ability of hESC-derived matrix microenvironments to alter tumorigenic properties through the reprogramming of metastatic melanoma cells (13). Importantly, this effect was found to be dependent on the exposure of metastatic cells to hESC-derived conditioned Matrigel™. Culture of metastatic melanoma cells in hESC-conditioned medium did not promote the reprogramming effect. These data suggest that the proteins responsible for this effect were integrated in the matrix. With the use of immunochemical techniques, it was later found that the left-right determination (Lefty) proteins A and B that were deposited in the matrix by hESCs during conditioning were at least in part responsible for the cellular change observed in metastatic cells (14). The Lefty A and B proteins are antagonists of transforming growth factor (TGF)-β signaling that act directly on Nodal protein, a critical regulator of the stem cell phenotype (15, 16). Subsequent studies of conditioned matrix utilizing mESCs implicated the bone morphogenic protein (BMP) 4 antagonist Gremlin as a primary regulator of the observed changes in metastatic cells (17). Collectively, these studies were all biased by a targeted analysis of potential effectors of metastatic cells. A comprehensive proteomic analysis of conditioned matrix could potentially reveal other factors involved in metastatic cell reprogramming. Furthermore, proteomic examination of hESC and hiPSC conditioned matrix could expose factors important in the regulation of self-renewal and pluripotency by the microenvironment in vitro.To this end, we have analyzed both types of human pluripotent stem cells, hESCs and hiPSCs, via a mass spectrometry (MS)-based proteomics approach to identify proteins deposited during growth in feeder-free conditions in vitro on Matrigel™. To investigate the hESC- and hiPSC-derived matrix, the metabolic labeling technique known as stable isotope labeling with amino acids in cell culture (SILAC) was used (18). SILAC facilitates the identification of hESC- and hiPSC-derived proteins that would otherwise be confounded by the presence of mouse-derived protein background from Matrigel™. From the proteomic analysis of three cells lines, namely, the hESC lines H9 and CA1 and the hiPSC line BJ-1D, we identified a total of 621, 1355, and 1350 total unique proteins, respectively. This work represents the first analysis of a hESC- and hiPSC-derived conditioned matrix and resulted in the identification of at least one novel microenvironmental contributor responsible for the regulation of human pluripotent stem cells.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Dbf4-Cdc7 Phosphorylation of Mcm2 Is Required for Cell Growth

The Dbf4-Cdc7 kinase (DDK) is required for the activation of the origins of replication, and DDK phosphorylates Mcm2 in vitro. We find that budding yeast Cdc7 alone exists in solution as a weakly active multimer. Dbf4 forms a likely heterodimer with Cdc7, and this species phosphorylates Mcm2 with substantially higher specific activity. Dbf4 alone binds tightly to Mcm2, whereas Cdc7 alone binds weakly to Mcm2, suggesting that Dbf4 recruits Cdc7 to phosphorylate Mcm2. DDK phosphorylates two serine residues of Mcm2 near the N terminus of the protein, Ser-164 and Ser-170. Expression of mcm2-S170A is lethal to yeast cells that lack endogenous MCM2 (mcm2Δ); however, this lethality is rescued in cells harboring the DDK bypass mutant mcm5-bob1. We conclude that DDK phosphorylation of Mcm2 is required for cell growth.The Cdc7 protein kinase is required throughout the yeast S phase to activate origins (1, 2). The S phase cyclin-dependent kinase also activates yeast origins of replication (3–5). It has been proposed that Dbf4 activates Cdc7 kinase in S phase, and that Dbf4 interaction with Cdc7 is essential for Cdc7 kinase activity (6). However, it is not known how Dbf4-Cdc7 (DDK)² acts during S phase to trigger the initiation of DNA replication. DDK has homologs in other eukaryotic species, and the role of Cdc7 in activation of replication origins during S phase may be conserved (7–10).The Mcm2-7 complex functions with Cdc45 and GINS to unwind DNA at a replication fork (11–15). A mutation of MCM5 (mcm5-bob1) bypasses the cellular requirements for DBF4 and CDC7 (16), suggesting a critical physiologic interaction between Dbf4-Cdc7 and Mcm proteins. DDK phosphorylates Mcm2 in vitro with proteins purified from budding yeast (17, 18) or human cells (19). Furthermore, there are mutants of MCM2 that show synthetic lethality with DBF4 mutants (6, 17), suggesting a biologically relevant interaction between DBF4 and MCM2. Nevertheless, the physiologic role of DDK phosphorylation of Mcm2 is a matter of dispute. In human cells, replacement of MCM2 DDK-phosphoacceptor residues with alanines inhibits DNA replication, suggesting that Dbf4-Cdc7 phosphorylation of Mcm2 in humans is important for DNA replication (20). In contrast, mutation of putative DDK phosphorylation sites at the N terminus of Schizosaccharomyces pombe Mcm2 results in viable cells, suggesting that phosphorylation of S. pombe Mcm2 by DDK is not critical for cell growth (10).In budding yeast, Cdc7 is present at high levels in G₁ and S phase, whereas Dbf4 levels peak in S phase (18, 21, 22). Furthermore, budding yeast DDK binds to chromatin during S phase (6), and it has been shown that Dbf4 is required for Cdc7 binding to chromatin in budding yeast (23, 24), fission yeast (25), and Xenopus (9). Human and fission yeast Cdc7 are inert on their own (7, 8), but Dbf4-Cdc7 is active in phosphorylating Mcm proteins in budding yeast (6, 26), fission yeast (7), and human (8, 10). Based on these data, it has been proposed that Dbf4 activates Cdc7 kinase in S phase and that Dbf4 interaction with Cdc7 is essential for Cdc7 kinase activity (6, 9, 18, 21–24). However, a mechanistic analysis of how Dbf4 activates Cdc7 has not yet been accomplished. For example, the multimeric state of the active Dbf4-Cdc7 complex is currently disputed. A heterodimer of fission yeast Cdc7 (Hsk1) in complex with fission yeast Dbf4 (Dfp1) can phosphorylate Mcm2 (7). However, in budding yeast, oligomers of Cdc7 exist in the cell (27), and Dbf4-Cdc7 exists as oligomers of 180 and 300 kDa (27).DDK phosphorylates the N termini of human Mcm2 (19, 20, 28), human Mcm4 (10), budding yeast Mcm4 (26), and fission yeast Mcm6 (10). Although the sequences of the Mcm N termini are poorly conserved, the DDK sites identified in each study have neighboring acidic residues. The residues of budding yeast Mcm2 that are phosphorylated by DDK have not yet been identified.In this study, we find that budding yeast Cdc7 is weakly active as a multimer in phosphorylating Mcm2. However, a low molecular weight form of Dbf4-Cdc7, likely a heterodimer, has a higher specific activity for phosphorylation of Mcm2. Dbf4 or DDK, but not Cdc7, binds tightly to Mcm2, suggesting that Dbf4 recruits Cdc7 to Mcm2. DDK phosphorylates two serine residues of Mcm2, Ser-164 and Ser-170, in an acidic region of the protein. Mutation of Ser-170 is lethal to yeast cells, but this phenotype is rescued by the DDK bypass mutant mcm5-bob1. We conclude that DDK phosphorylation of Ser-170 of Mcm2 is required for budding yeast growth.     

Large-scale Top-down Proteomics of the Human Proteome: Membrane Proteins,Mitochondria, and Senescence

Top-down proteomics is emerging as a viable method for the routine identification of hundreds to thousands of proteins. In this work we report the largest top-down study to date, with the identification of 1,220 proteins from the transformed human cell line H1299 at a false discovery rate of 1%. Multiple separation strategies were utilized, including the focused isolation of mitochondria, resulting in significantly improved proteome coverage relative to previous work. In all, 347 mitochondrial proteins were identified, including ∼50% of the mitochondrial proteome below 30 kDa and over 75% of the subunits constituting the large complexes of oxidative phosphorylation. Three hundred of the identified proteins were found to be integral membrane proteins containing between 1 and 12 transmembrane helices, requiring no specific enrichment or modified LC-MS parameters. Over 5,000 proteoforms were observed, many harboring post-translational modifications, including over a dozen proteins containing lipid anchors (some previously unknown) and many others with phosphorylation and methylation modifications. Comparison between untreated and senescent H1299 cells revealed several changes to the proteome, including the hyperphosphorylation of HMGA2. This work illustrates the burgeoning ability of top-down proteomics to characterize large numbers of intact proteoforms in a high-throughput fashion.Although traditional bottom-up approaches to mass-spectrometry-based proteomics are capable of identifying thousands of protein groups from a complex mixture, proteolytic digestion can result in the loss of information pertaining to post-translational modifications and sequence variants (1, 2). The recent implementation of top-down proteomics in a high-throughput format using either Fourier transform ion cyclotron resonance (3–5) or Orbitrap instruments (6, 7) has shown an increasing scale of applicability while preserving information on combinatorial modifications and highly related sequence variants. For example, the identification of over 500 bacterial proteins helped researchers find covalent switches on cysteines (7), and over 1,000 proteins were identified from human cells (3). Such advances have driven the detection of whole protein forms, now simply called proteoforms (8), with several laboratories now seeking to tie these to specific functions in cell and disease biology (9–11).The term “proteoform” denotes a specific primary structure of an intact protein molecule that arises from a specific gene and refers to a precise combination of genetic variation, splice variants, and post-translational modifications. Whereas special attention is required in order to accomplish gene- and variant-specific identifications via the bottom-up approach, top-down proteomics routinely links proteins to specific genes without the problem of protein inference. However, the fully automated characterization of whole proteoforms still represents a significant challenge in the field. Another major challenge is to extend the top-down approach to the study of whole integral membrane proteins, whose hydrophobicity can often limit their analysis via LC-MS (5, 12–16). Though integral membrane proteins are often difficult to solubilize, the long stretches of sequence information provided from fragmentation of their transmembrane domains in the gas phase can actually aid in their identification (5, 13).In parallel to the early days of bottom-up proteomics a decade ago (17–21), in this work we brought the latest methods for top-down proteomics into combination with subcellular fractionation and cellular treatments to expand coverage of the human proteome. We utilized multiple dimensions of separation and an Orbitrap Elite mass spectrometer to achieve large-scale interrogation of intact proteins derived from H1299 cells. For this focus issue on post-translational modifications, we report this summary of findings from the largest implementation of top-down proteomics to date, which resulted in the identification of 1,220 proteins and thousands more proteoforms. We also applied the platform to H1299 cells induced into senescence by treatment with the DNA-damaging agent camptothecin.