Proteomic Profiling of Proliferating and Differentiated Neural mes-c-myc A1 Cell Line from Mouse Embryonic Mesencephalon by LC-MS Angela Chambery,*,†,‡ Luca Colucci-D’Amato,†,‡,§ Johannes P. C. Vissers,| Simona Scarpella,| James I. Langridge,| and Augusto Parente‡ Dipartimento di Scienze della Vita, Seconda Universita` di Napoli, I-81100 Caserta, Italy, Istituto di Genetica e Biofisica “A. Buzzati-Traverso”, Consiglio Nazionale delle Ricerche, 80131-Napoli, Italy, and Waters Corporation, MS Technologies Center, M22 5PP Manchester, United Kingdom Received June 19, 2008
The proteomic profiling, by means of label-free qualitative and quantitative LC-MS analysis of proliferating/undifferentiated vs nonproliferating/differentiated mes-c-myc A1 cell line (A1), has been performed. A1 cells were generated from mouse embryonic central nervous system. The study was aimed at surveying the molecular changes following neural differentiation. The results provide a list of candidate proteins with potential relevance for the transition of A1 cells from the proliferative to the differentiated status. Keywords: LC-MS • proteomic profiling • mass spectrometry • data independent scanning • neuron • differentiation
Introduction Insight into the mechanisms underlying central nervous system (CNS) differentiation and functions is typically gained by studying the properties of its constituting cell types during neural differentiation. Although in vitro studies using primary cultures obtained directly from tissues have provided useful information, cellular heterogeneity makes it difficult to dissect molecular events at a single cellular phenotype. The variety and the extreme precision of the functions over which CNS presides are assured by the fine-tuning of the communications between different types of neural cells. Neural and stem cell lines, due to their cellular homogeneity and reproducibility of results, have been instrumental to discover molecules and understand mechanisms underlying neural differentiation and function under normal and pathological conditions. Many cell types, including neural cells, may respond differently to external stimuli (i.e., growth factors, hormones, toxic molecules and drugs) depending on the status of differentiation.1-3 Mes-c-myc A1 (A1), a cell line generated from mouse embryonic mesencephalon, can be cultured under undifferentiated/proliferative or differentiated/nonproliferative conditions.4 In the presence of serum, these cells appear undifferentiated and proliferate, whereas serum withdrawal and cAMP stimulation cause cell cycle arrest and neuronal dif* To whom correspondence should be addressed. Mailing address: Dipartimento di Scienze della Vita, Seconda Universita` di Napoli, Via Vivaldi 43, I-81100 Caserta, Italy. Phone: +39 0823 274535. Fax: +39 0823 274571. E-mail:
[email protected]. † These authors contributed equally to this work. ‡ Seconda Universita` di Napoli. § Istituto di Genetica e Biofisica “A. Buzzati-Traverso”. | Waters Corporation. 10.1021/pr800454n CCC: $40.75
2009 American Chemical Society
ferentiation, ensuing neurite outgrowth, neuronal electrophysiological properties, and expression of neuronal markers.4 In such a cellular model it is possible to distinguish molecules and mechanisms related to different status of proliferation and differentiation. Moreover, no bias due to the genetic background would interfere with the study as in the case of primary cultures. Previous studies have shown that A1 cells respond differently to molecules exerting toxic or pharmacological effects according to their differentiation status.1,2 Furthermore, A1 cells express serotonin and tryptophan hydroxylase (TPH 1 and TPH 2 isoforms), its biosynthetic rate limiting enzyme, as well as the serotonin transporter.2 The latter is the main site of action of drugs widely used for the treatment of many psychiatric diseases. Therefore, A1 cells represent a valid cellular model to study the regulation of serotonergic pathway during differentiation. Transcriptomic analysis has been proven to be a powerful tool to unravel mechanisms underlying differentiation.5-7 Nevertheless, this approach often fails to provide a comprehensive understanding of molecules involved in such process, due to susceptibility of mRNA to degradation and to the discrepancy between mRNA and protein expression levels.8 Over the past few years, proteomic profiling has become a powerful tool in neuroscience studies (“neuromics”). In particular, there has been a growing interest in proteomic analysis of neural (stem) cells, focused to unravel the regulatory networks of the neuronal differentiation process. Both neural cell lines generated from mature tissues and from embryonic stem (ES) cells, including human ES,9 have been used as biological systems, reviewed in detail by Hoffrogge and coworkers.10 In addition, the embryonal carcinoma P1911 and neuroblastoma N1E-115 cell lines12 have been chosen as Journal of Proteome Research 2009, 8, 227–238 227 Published on Web 12/11/2008
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experimental models. To date, the reported results from various studies indicate or show little to no overlap, which is mainly due to the variation in cell origin, genetic modifications, and the applied culture conditions. However, cataloguing differentially expressed proteins can provide a useful overview of proteins involved in neural differentiation.13 To address this issue, proteomic profiling of mes-c-myc A1 cell line by labelfree LC-MSE for quantitative and qualitative analysis has been performed.
A1D samples (0.5 µg) were injected onto a 180 µm × 2 cm Symmetry C18 (5 µm) trap column (Waters Corporation) for preconcentration and desalting. The samples were subsequently directed from the precolumn onto a 1.7 µm BEH 75 µm × 150 mm analytical column (Waters Corporation). The sample elution was performed at a flow rate of 300 nL/min by increasing the organic solvent concentration from 1 to 40% B in 90 min, using 0.1% formic acid in water as reversed phase solvent A and 0.1% formic acid in acetonitrile as reversed phase solvent B. All analyses were conducted in triplicate.
Experimental Section
The precursor ion masses and associated fragment ion spectra of the tryptic peptides were mass measured with a hybrid quadrupole orthogonal acceleration time-of-flight Q-Tof Premier mass spectrometer (Waters Corporation, Manchester, UK) directly coupled to the chromatographic system. The timeof-flight analyzer of the mass spectrometer was externally calibrated with NaI from m/z 50 to 1990, with the data postacquisition lock mass corrected using the monoisotopic mass of the doubly charged precursor of [Glu1]-Fibrinopeptide B. The latter was delivered at 100 fmol/µL to the mass spectrometer via a NanoLockSpray interface using the auxiliary pump of a nanoACQUITY system at a flow rate of 100 nL/min. The reference sprayer was sampled every 30 s. Accurate mass data were collected in data independent mode of acquisition by alternating the energy applied to the collision cell between a low energy and elevated energy state as described previously.14 The LC-MSE scanning method combines peptide MS and multiplexed, data independent peptide fragmentation MS analysis in a single LC-MS experiment for the quantitative and qualitative characterization of a peptide mixture. Briefly, the lock mass corrected spectra are first centroided, deisotoped, and charge-state-reduced to produce a single accurately mass measured monoisotopic mass for each peptide and the associated fragment ions. The correlation of a precursor and a potential fragment ion is initially achieved by means of time alignment, followed by a further correlation process during the database search that is based on the physicochemical properties of peptides when they undergo collision induced fragmentation.
Cell Cultures. Mouse CNS immortalized A1 cell line has been obtained from mouse embryonic mesencephalon primary culture as previously described.4 A1 cells, both proliferating (i.e., undifferentiated, A1P) and differentiated cells (A1D), were produced as previously reported.4 Briefly, cells were grown in 10 cm tissue culture dishes in MEM/F12 medium (1/1, GibcoBRL, Milan, Italy), supplemented with 200 mM L-glutamine, 30% glucose, 7% NaHCO3 with the addition of 10% fetal bovine serum (FBS, Gibco-BRL) in a 5% CO2 environment at 70-80% confluence. Cells, cultured in the absence of serum and supplemented with N2 mixture (Gibco-BRL), were induced to differentiate with the addition of 1 mM dibutyryl cyclic adenosine 3′,5′-monophosphate (cAMP, Sigma, Milan, Italy). Three independent cell cultures preparations were pooled to address biological variation. Immunofluorescence Analysis. Serotonin (5-HT) immunofluorescence has been carried out as previously described2 using the HT antibody (1:2000 Sigma, Milan, Italy) and goat antirabbit, rhodamine conjugate secondary antibody diluted 1:50 (Chemicon, Milan, Italy). Control cultures were incubated in the same solution without primary antibodies and subsequently processed as above. Three culture wells were analyzed in each experiment for each experimental condition. Sample Preparation. Monolayer cultures of cell lines were harvested and, after three washes in ice-cold PBS, incubated with a solution containing trypsin (0.5 g/L) and EDTA (0.2 g/L). After centrifugation at 2000 rpm for 5 min at 4 °C in a JA14 rotor (Beckman centrifuge GS-15R; Beckman Coulter Inc., CA), cell pellets were washed three times with PBS and resuspended in 25 mM NH4HCO3/0.5% RapiGest (Waters Corporation, Milford, MA) for cell lysis and protein extraction. Samples were then sonicated into an ultrasonic bath for 10-15 min and centrifuged at 13 000 · g for 15 min at 4 °C to eliminate cellular debris. The protein concentration of collected supernatants was determined by the Bradford method, according to manufacturer’s instructions (Biorad, Milan, Italy). Proteolytic Digestions. Total protein extracts, obtained as described above, were reduced with 2.5 mM DTT at 60 °C for 30 min and carbamidomethylated with 7.5 mM iodoacetamide at room temperature in the dark for 30 min. Digestion was performed by two subsequent additions (1:100 for 16 h at 37 °C, then 1:50 for 4 h at 37 °C) of TPCK-treated trypsin (Sigma, Milan, Italy). After digestion, 0.5% TFA was added to hydrolyze RapiGest and inactivate trypsin. The samples were centrifuged at 12000 · g for 10 min, the supernatants collected and the resulting aliquots dried in a SpeedVac Vacuum concentrator (Savant Instruments, Holbrook, NY). The tryptic digests were finally resuspended in aqueous 0.1% formic acid at a final protein concentration of 1 µg/µL. LC-MS Configurations. Nanoscale LC separations of tryptic peptides for qualitative and quantitative multiplexed LC-MSE analysis were performed with a nanoACQUITY system. A1P and 228
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The spectral acquisition time in each mode was 1.5 s with a 0.1 s interscan delay. In the low energy MS mode, data were collected at constant collision energy of 4 eV. In elevated energy MS mode, the collision energy was ramped from 15 to 35 eV during each 1.5 s integration, with one complete cycle of low and elevated energy data acquired every 3.2 s. The RF applied to the quadrupole mass analyzer was adjusted such that ions from m/z 300 to 2000 were efficiently transmitted, ensuring that any ion with a mass below m/z 300, observed in the LC-MSE data, only arose from dissociations in the collision cell. Data Processing and Protein Identification. Data independent, alternate scanning LC-MSE data were processed and searched using ProteinLynx GlobalSERVER version 2.3. Protein identifications were obtained by searching a mouse speciesspecific Swiss-Prot database (release 52.1; 12,577 entries). The ion detection, data clustering and normalization of the multiplexed, data independent LC-MS data has been explained in detail in previous reports.15,16 Briefly, the lock mass corrected spectra are first centroided, deisotoped, and charge-statereduced to produce a single accurately mass measured monoisotopic mass for each peptide and the associated fragment ion. For protein quantification, the observed intensity measurements are normalized on the intensity values of peptides that
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Embryonic Mesencephalon Cell Line do not change in concentration or amount between replicate injections or on the peptides of a protein digest spike. The principle of the search algorithm for data independent, alternate scanning LC-MSE data has been recently described.17 The following search criteria were used for protein identification: peptide mass tolerance, 15 ppm; fragment ion tolerance, 30 ppm; allowed number of missed cleavage sites up to 1; fixed modification: carbamidomethyl-cysteine; variable modifications: methionine oxidation, N/Q deamidation, N-terminal acetylation. The protein identifications were based on the detection of at least 3 fragment ions per peptide and at least 2 peptides identified to a protein. Moreover, identification of the protein had to occur in at least 2 out of 3 injections of the same condition. Only protein identifications with a probability score greater than 95% are reported. The false positive rate (FPR) of the identification algorithm is typically 3 to 4% with a randomized database, appended to the original one, which is five times the size of the original utilized database. However, by using replication as a filter, the FPR is minimized, as false positive identifications have a random nature and therefore do not replicate across injections. Considering replication and including homologues identifications, the calculated FPR of identification for the A1D and the A1P samples were 0% and 0.15%, respectively. Qualitative identification results were also considered when a protein was identified in a single injection for a given condition, but occurred in all triplicate injections of the comparative condition. Quantitative analyses have been performed by data independent alternate scanning expression algorithm17 by comparing normalized peak area/intensity of each peptide in a control vs a challenged sample. Automatic-normalization was applied to the data set. Briefly, for complex samples, it is often possible to measure and correct for systematic errors taking into account slight differences in protein loading amounts without using an internal standard. The assumption is that changes in protein expression occur against a dominant background of proteins which are unaffected by the perturbation being studied. Each peptide or cluster is initially treated as an internal standard by the quantification algorithm. During this step, peptides showing real changes are naturally suppressed as it occurs for inappropriate assignments or interferences in normal quantification. After this pass, the entire data set is corrected and quantified. Quantification can be either conducted by annotating the cluster quantification list with the corresponding proteins from the database search results, or, as in the case of the present study, by solely quantifying the peptides identified to the protein. In the latter instance, a regulation likelihood can be calculated by using confidence of identification at the peptide level as a quantification weighing mechanism is specifically designed for independently acquired LC-MS data. The overall likelihood of regulation is expressed by the probability of upregulation (P > 1) value reported by the utilized quantification software. If this value is smaller than 0.05 (i.e., in between 0 and 0.05) the likelihood of down-regulation is greater than 95%. If the value is greater than 0.95 (i.e., in between 0.95 and 1) the likelihood of up-regulation is greater than 95%. The entire data set of differentially expressed proteins was further filtered by considering only those identifications from the data independent, alternate scanning LC-MS data with identified peptides that replicated two out of three technical instrument replicates. Furthermore, the significance of regulation level was determined at 30% fold change, that is, an
average relative fold change between -0.30 and 0.30 on a natural log scale, which is typically 2-3 times higher than the estimated error on the intensity measurement.17 Moreover, a likelihood of regulation higher than 95%, as reported by the quantification algorithm, was considered. Additional data analysis was performed with Decisionsite (Spotfire, Somerville, MA) and Excel (Microsoft Corporation, Redmond, WA). Gene Ontology Analysis. The classification of identified proteins was performed according to the Gene Ontology (http://www.geneontology.org/) hierarchy using the GO Terms Classifications Counter (http://www.animalgenome.org/). The sequence retrieval system (SRS) web interface of the European Bioinformatics Institute (www.ebi.ac.uk) was used for the GO annotation searches. The clustering of the GO annotation results was performed applying the GOA2GO classification method (http://www.geneontology.org/GO.slims.shtml). The gene ontology OBO file was downloaded from the gene ontology database and manually edited to obtain three separate classifications (cellular component, molecular function and biological process). The assessment of the statistical significance of protein enrichment in the differentiated (A1D) and proliferating (A1P) samples has been performed by using the WebGestalt software package developed by Bioinformatics Resource Center at Vanderbilt University (http://bioinfo.vanderbilt.edu/webgestalt) on the basis of Fisher’s exact test (P < 0.01).18 A further comparison of the differentially expressed proteins in the A1 cell line upon differentiation with the entire Mouse genome as reference set has been performed by using the hypergeometric test (P < 0.01).18 Protein Interaction Analysis. The protein interaction network has been obtained by using the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) software, available at EMBL Web site (http://www.embl-heidelberg.de/) with default settings. The interaction algorithm uses a database of known and predicted protein-protein interactions based on direct (physical) and indirect (functional) associations.19 The source interaction derives from coexpression and highthroughput experiments, homology data, database information and from previous literature knowledge. The additional genefusion, co-occurrence, and neighborhood prediction methods have not been utilized for network drawing.
Results The proteomic profiling of proliferating/undifferentiated (A1P) vs nonproliferating/differentiated (A1D) A1 cells has been performed by means of label-free qualitative and quantitative LC-MS analysis. Under conditions where A1 cell proliferation is arrested, morphological, and physiological events underlying differentiation (i.e., neurite outgrowth and neuronal electrophysiological properties4) can be observed (Figure 1). Whole-cell protein extracts under both conditions were subjected to tryptic digestion as described in the Methods section. The analytical quality of the detected accurate mass-retention time components (clusters) was evaluated for the complete data set. The analytical reproducibility was assessed by reviewing the measurement statistics of the clustering results for both investigated conditions. These include the intensity variations of the technical replicates, shown in Supplementary Figure 1, Supporting Information, for samples A1P and A1D. Under ideal conditions, the binary comparisons would yield a perfect 45-degree diagonal intersecting through zero and displaying a minimum degree of deviation throughout the detected range with little intensity Journal of Proteome Research • Vol. 8, No. 1, 2009 229
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Chambery et al. three and/or in at least two out of three injections. Furthermore, a significant number of clusters can be assigned uniquely to one of the investigated conditions. It should be noted that unique detections merely depend on the detection of a mass at a given retention time in a given condition and not in the other. Indeed, the detection dynamic range of the applied analytical method is also related to the (large) dynamic range of the studied proteome. However, to minimize the analytical measurement uncertainties, only the unique clusters detected in at least two out of three replicate injections were considered.
Figure 1. Phase-contrast photomicrographs showing A1 cells before (A) and after (B) differentiation (240×). Under undifferentiated conditions cell bodies are flat and large and no/or short neurites can be observed. Morphological changes occur upon differentiation, resulting in neurites sprouting from high refractive cell bodies. Morphological changes are paralleled by the appearance of functional and molecular features of differentiated neurons as previously reported2,4 and summarized in C.
variation. As can be seen, the resulting scatter plots are distributed along a diagonal line with hardly any intensity deviation between matched cluster components. Furthermore, the mass measurement precision, retention time reproducibility and intensity variation were also evaluated at the sample level (Supplementary Figure 2, Supporting Information). For condition A1D, the mass precision, retention time coefficient of variation (CV), and intensity CV were 2.0 ppm, 0.4%, and 3%, respectively. Similar values were obtained for the A1P sample (i.e., 2.5 ppm, 0.4%, and 3%, respectively). These assessments, typically conducted to estimate the data quality prior to conduct qualitative and quantitative analysis, further confirm the findings of previous studies reporting the highly reproducibility of intensity measurements by label-free LC-MS.17 The total number of deisotoped, charged state reduced monoisotopic masses across both conditions equalled 153 505, which could be ultimately assigned to 69 365 accurate massretention time clusters. A quantitative expression of the clustering result was obtained by comparing the peak area/intensity of the detected clusters in samples A1P and A1D. Differentially regulated peptides belonging to the same protein will share a common intensity variation distribution, thus representing the protein regulation level between the two conditions. The normalized intensities of the accurate mass-retention time clusters of sample A1D vs A1P are shown in Supplementary Figure 3, Supporting Information. As expected, while most of peptide clusters shows no expression level changes, several significantly regulated peptide clusters were detected (shown in gray in Supplementary Figure 3, Supporting Information), indicating differential protein expression. A binary comparison, although useful in providing an overview of the quality of the entire data set, does not reveal the complete experimental detail, since neither the uniquely detected components, nor the replication detail are visible. By considering replication of detected clusters at the injection level (Figure 2), it can be observed that the majority of the clusters were identified in all 230
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On the basis of the above-discussed filtering criteria, 245 proteins were qualitatively identified across both conditions. The majority of them (169), accordingly to the data analysis at the cluster level, were found to be common to both A1D and A1P conditions (Table 1S, Supporting Information). In line with the analysis of the data at the cluster level, certain proteins were uniquely identified in either the A1D (32) or the A1P (44) sample (Table 2S, Supporting Information). An overview of the differentially expressed proteins, other than a mere qualitative overview of the A1 cell proteome, was obtained by conducting a quantitative analysis experiment using a recently developed label-free LC-MS technique,15,16 which is described in more detail in the Experimental Section. The significance of the regulation level was set at 30% (1.3fold change, ( 0.30 on a natural log scale), which is typically 2-3 times higher than the estimated error on the intensity measurement. The proteins identified by this process and found to be significantly up- and down-regulated in A1P vs A1D condition, are listed in Table 1, along with their relative fold change and variance. Previous work reported the coexistence in proliferating and differentiated A1 cells4 of both neuronal and glial markers (i.e., vimentin, nestin, neuron specific enolase, peripherin and glial fibrillary acidic protein), attesting their bipotent neuronal and glial fingerprint. Nestin, although identified (data not shown), is not reported, since its identification was not compliant with the replication filtering criteria used in the present study. As expected, peripherin and gamma neuron specific enolase were revealed in both A1P and A1D cells without a significant expression change. The intermediate filament vimentin was also commonly identified with a high number of peptides, some of which are shown as an example of fragmentation data in Supplementary Figure 4, Supporting Information. In accordance with previous studies,20 a slight upregulation of vimentin in A1D vs A1P cells was observed. Similarly, glial fibrillary acidic protein (GFAP) was found to be up-regulated in A1D sample as previously reported by RT-PCR analysis.4 Qualitative and quantitative clustering of identified proteins was performed according to their cellular localization and biological processes on the basis of the Gene Ontology (GO) categories. The classification based on cellular localization of the qualitative results revealed that the cytoplasmic (43.1%), membrane (19.9%) and nuclear (19.1%) proteins represent the largest populations found in the A1 cell line (Supplementary Figure 5A, Supporting Information). The annotation of the biological processes (Supplementary Figure 5A, Supporting Information) revealed that most of the identified proteins were involved in metabolism (33.1%), transport (15.2%), nucleic acid metabolism (10.5%) and biosynthetic processes (about 10%). Furthermore, small, but representative classes of proteins that are involved in cell differentiation (3.5%) and development (4.7%) were detected.
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Figure 2. Accurate mass-retention time component replication distribution detail at the injection (technical replicate) level for the triplicate LC-MS analysis of samples A1P and A1D. The clustering mass precision and retention time tolerances are automatically determined by the detection processing software and were 2.1 ppm and 0.2%, respectively. The accurate mass-retention time clusters that were identified in all, 5 out 6 (common), or 2 out 3 (unique) technical replicates are highlighted and annotated with the number of detected clusters.
The analysis of the quantitative results revealed that most of the differentially expressed proteins are involved in neuronal differentiation, survival, metabolic processes, protein synthesis, and remodelling of the cytoskeleton. In addition, several proteins uniquely detected and/or up-regulated in A1P condition were previously associated with cell proliferation. Another category of differentially regulated proteins includes tightly regulated enzymes (i.e., aspartate aminotransferase, AAT, and glutamate dehydrogenase, GDH) directly or indirectly involved in L-glutamate and GABA neurotransmitter metabolism. In particular, as shown in Figure 3, a comparison of the GO cellular localization categories of up- and down-regulated proteins revealed a significant increase of expression of mitochondrial proteins in A1D (15.7%) vs A1P (2.6%), supporting the recent hypothesis of mitochondrial participation in neuronal differentiation.21 The main protein categories that are upregulated in A1 proliferating cells, were the nuclear ones and many proteins of the translation machinery, including ribosomal proteins and components of the translational apparatus, nucleolus and microtubule organizing center, consistently with the high rate of cell proliferation (duplication time 20 h).4 The assessment of significantly enriched categories has been performed by using the WebGestalt software package on the basis of hypergeometric test and Fisher’s exact test as described in the Experimental Section.18 The enriched proteins of the differentiated (A1D) and proliferating (A1P) samples are reported in Supplementary Figures 6 and 7 (Supporting Informa-
tion), respectively. Most of the previously discussed categories were found to be enriched within the hierarchical structure of the Directed Acyclic Graphs, including the mitochondrial, endoplasmic reticulum and endocytic vescicle proteins for the differentiated sample and proteins belonging to the nuclear compartment, ribosomal subunits and cytoskeleton for the proliferating cells. The significantly enriched GO categories under Biological Processes of differentially expressed proteins using the entire Mouse Genome as reference set are reported in Supplementary Figure 8, Supporting Information. Notably, beyond the metabolic categories, the regulation of locomotion and transferase activity, the significantly enriched functional categories in the A1 cells include the neuron differentiation and system development processes. To further analyze the mutual interactions between the differentially expressed proteins, a network map was constructed (Figure 4). The graphical view of the resulting network revealed that specific populations of differentially expressed proteins clustered on the basis of their reciprocal interactions. In particular, several proteins involved in common metabolic pathways (e.g., glycolysis: phosphoglycerate kinase 1, pyruvate kinase, glyceraldehyde-3-phosphate dehydrogenase, phosphoglycerate mutase 1, lactate dehydrogenase) were up-regulated in A1P (Figure 4, panel C). This finding is not surprising as it is widely accepted that both proliferating as well as cancer cells consume large amounts of energy, which needs a high glycolytic rate, thus requiring high amounts of glycolytic enzymes. Journal of Proteome Research • Vol. 8, No. 1, 2009 231
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Table 1. Significantly Differentially Regulated Proteins in A1P vs. A1D Condition Identified by Label-Free Quantitative LC-MSEa accession #
Q64433 P63038
Q99KI0 P48962 P51881 Q03265 P56480 P14211 P08113
P03995 P26443 P08752 P50446 Q9Z331 P08249 P67778 P27773 Q922R8 P09103 Q8VDN2
P20152 Q60932
Q9CQV8 P62259 P68510 P61982 O70456 P68254 P63101 P62908 P14206 Q9CXW4 P62830 P68033 P68134 P62737 P60710 P63260 P63268 Q7TPR4 Q9JI91 P57780 P17182 232
description
10 kDa heat shock protein mitochondrial (Hsp10) 60 kDa heat shock protein mitochondrial precursor (Hsp60) Aconitate hydratase mitochondrial precursor ADP/ATP translocase 1 ADP/ATP translocase 2 ATP synthase subunit alpha mitochondrial precursor ATP synthase subunit beta mitochondrial precursor Calreticulin precursor Endoplasmin precursor (Heat shock protein 90 kDa beta member 1) Glial fibrillary acidic protein astrocyte (GFAP) Glutamate dehydrogenase 1 mitochondrial precursor Guanine nucleotide-binding protein G(i) alpha-2 subunit Keratin type II cytoskeletal 6A Keratin type II cytoskeletal 6B Malate dehydrogenase mitochondrial precursor Prohibitin (B-cell receptor-associated protein 32) Protein disulfide-isomerase A3 precursor Protein disulfide-isomerase A6 precursor Protein disulfide-isomerase precursor Sodium/potassium-transporting ATPase alpha-1 chain precursor Vimentin Voltage-dependent anion-selective channel protein 1 (VDAC-1) 14-3-3 protein beta/alpha 14-3-3 protein epsilon 14-3-3 protein eta 14-3-3 protein gamma 14-3-3 protein sigma 14-3-3 protein theta (14-3-3 protein tau) 14-3-3 protein zeta/delta 40S ribosomal protein S3 40S ribosomal protein SA (37 kDa oncofetal antigen) 60S ribosomal protein L11 60S ribosomal protein L23 Actin alpha cardiac muscle 1 Alpha-Actin-1 Actin aortic smooth muscle Beta-Actin Gamma-Actin Actin gamma-enteric smooth muscle Alpha-actinin-1 Alpha-actinin-2 Alpha-actinin-4 Alpha-enolase (Non- neural enolase)
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e
log ratio A1P/A1D
variance
regulation
-0.85
0.056
down
-0.58
0.001
down
-0.52
0.009
down
-0.92 -0.89 -0.9
0.094 0.077 0.082
down down down
-0.83
0.047
down
-0.38 -0.51
0.054 0.011
down down
-0.31
0.092
down
-0.67
0.003
down
-0.51
0.011
down
-0.45 -0.45 -0.73
0.027 0.027 0.014
down down down
-0.98
0.135
down
-0.54
0.005
down
-0.33
0.080
down
-0.38
0.054
down
-0.64
0.001
down
-0.32 -0.81
0.086 0.039
down down
0.96 1.06 0.74 0.73 0.75 0.81
0.085 0.153 0.005 0.004 0.007 0.020
up up up up up up
0.83 0.31 0.89
0.026 0.129 0.049
up up up
0.37 0.47 0.48 0.33 0.64 0.55 0.56 0.58
0.089 0.040 0.036 0.115 0.001 0.014 0.012 0.008
up up up up up up up up
0.78 0.36 0.84 0.71
0.012 0.095 0.029 0.002
up up up up
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Embryonic Mesencephalon Cell Line Table 1. Continued accession #
P07356 P10126 P62631 P60843 P10630 P16045 P16858 Q61696 P17879 P16627 P63017 P07901 P11499 P17156 Q8BG05 O35737 P06151 P00342 P09405 P15532 Q01768 P35700 P09411 Q9DBJ1 Q9CY58 P52480 P68369 P05213 P05214 P68368 P68373 Q9JJZ2 Q7TMM9 Q9CWF2 P68372 Q9ERD7 Q9D6F9 P99024 Q922F4 P62991
description
Annexin A2 Elongation factor 1-alpha 1 Elongation factor 1-alpha 2 Eukaryotic initiation factor 4A-I Eukaryotic initiation factor 4A-II Galectin-1 Glyceraldehyde-3-phosphate dehydrogenase Heat shock 70 kDa protein 1A Heat shock 70 kDa protein 1B Heat shock 70 kDa protein 1 L Heat shock cognate 71 kDa protein Heat shock protein HSP 90-alpha Heat shock protein HSP 90-beta Heat shock-related 70 kDa protein 2 Heterogeneous nuclear ribonucleoprotein A3 Heterogeneous nuclear ribonucleoprotein H L-lactate dehydrogenase A chain L-lactate dehydrogenase C chain Nucleolin Nucleoside diphosphate kinase A (NDPK-A, nm23-M1) Nucleoside diphosphate kinase B (NDK B, nm23-M2) Peroxiredoxin-1 Phosphoglycerate kinase 1 Phosphoglycerate mutase 1 Plasminogen activator inhibitor 1 RNA-binding protein Pyruvate kinase isozymes M1/M2 Tubulin alpha-1 chain Tubulin alpha-2 chain Tubulin alpha-3/alpha-7 chain Tubulin alpha-4 chain Tubulin alpha-6 chain Tubulin alpha-8 chain Tubulin beta-2A chain Tubulin beta-2B chain Tubulin beta-2C chain Tubulin beta-3 chain Tubulin beta-4 chain Tubulin beta-5 chain Tubulin beta-6 chain Ubiquitin
e
log ratio A1P/A1D
variance
regulation
0.54 0.83 0.74 0.65 0.56 1.26 0.75
0.017 0.026 0.005 0.000 0.012 0.349 0.007
up up up up up up up
0.51 0.52 0.51 0.68
0.025 0.022 0.025 0.000
up up up up
0.79
0.015
up
0.83 0.56
0.026 0.012
up up
0.33
0.115
up
0.31
0.129
up
0.62
0.002
up
0.53
0.019
up
0.31 1.36
0.129 0.477
up up
1.17
0.251
up
0.73 0.88 1.18 0.86
0.004 0.045 0.261 0.036
up up up up
0.88
0.045
up
0.51 0.56 0.49 0.51 0.51 0.48 0.65 0.59 0.74 0.6 0.93 0.72 0.58 0.31
0.025 0.012 0.032 0.025 0.025 0.036 0.000 0.006 0.005 0.005 0.068 0.003 0.008 0.129
up up up up up up up up up up up up up up
a The number of peptides used for quantification are provided in Table 1S, Supporting Information. Data relative to differentially expressed proteins have been filtered on the basis of identification in at least two out of three replicate injections (see Table 1S, Supporting Information, for replication detail).
Another network of interacting proteins is represented by cytoskeletal proteins (Figure 4, panel D), as several differentially regulated proteins are components of microfilaments and microtubuli such as Actin, myosins and tubulins. Interestingly, in both A1P and A1D cells, two neuronal specific intermediate filaments (NF-M and NF-66) were detected. Several proteins involved in quality control, such as molecular chaperones, folding catalysts, and proteases, some of which classified as heat shock proteins (HSPs, Figure 4, panel B),
appeared differentially expressed upon differentiation. Among them, members of HSP90, HSP70, gp96 and several subunits of T-complex protein 1 were found, the latter assisting the protein folding upon ATP hydrolysis and was uniquely detected in sample A1P. Furthermore, HSP90 and HSP70 protein 4 were also found to be connected with the cluster of the members belonging to the 14-3-3 family, up-regulated in proliferating A1 cells (Figure 5, panel A). The 14-3-3 proteins are involved in a wide range of cellular functions, including the regulation Journal of Proteome Research • Vol. 8, No. 1, 2009 233
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Figure 3. Gene ontology (GO) cellular localization categories. Comparison of the GO cellular localization categories obtained for the differentially regulated proteins in the A1P (black) and A1D (gray) conditions.
Figure 4. Protein interaction network obtained for the differentially expressed proteins in A1 cell line under proliferative/differentiated status. The predicted functional links are colored on the basis of the type of evidence (see Methods and legend on the right). Some functional networks are boxed for HSPs (B), metabolic enzymes (C) and cytoskeleton proteins (D). A magnification of the 14-3-3 cluster with the indication of the relative Swiss-Prot accession numbers is reported in panel A1 (see text for discussion).
of tryptophan 5-hydroxylase,22 a key enzyme in serotonin synthesis. This result is of particular interest, since A1 cells express serotonin under both proliferation and differentiating 234
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conditions as previously demonstrated2 (Figure 5A and 5B for A1D and A1P, respectively). It is also worth noting that the distribution of serotonin immunofluorescence is highly remi-
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Figure 5. Immunofluorescence with antiserotonin antibody in A1P (A) and A1D (B) cells. Higher magnifications are shown in (C) and (D) for proliferating and differentiated A1 cells, respectively. Different magnifications scales are used to highlight the vesicular distribution of serotonin within the cells. All experiments were carried out in triplicates.
niscent of vesicular compartmentalization as shown in the high magnifications (Figure 5, panels C and D).
Discussion Mes-c-myc A1, a neural cell line obtained from mouse embryonic mesencephalon, is a valid tool for studying mechanisms at the basis of CNS differentiation, plasticity, and neurotransmission.2,4 In the present study, the proteomic profiling of proliferating/undifferentiated vs nonproliferating/ differentiated A1 cells has been performed, with the aim to survey the molecular changes following cell differentiation. Among proteins whose expression levels are affected upon A1 differentiation, there are many already known as markers of neural differentiation. In addition, other potential candidate markers for neuronal differentiation have been found. Among these, glucosidase II beta subunit (GLU2B, O08795) has been proposed as a neuronal/glial early differentiation marker in neural ST14A rat striatal progenitor cells.23 As in A1 cells, human fetal midbrain stem cells (ReNcell VM197), downregulate nucleosome assembly protein 1-like 1 (NAP1, P28656), peroxiredoxin 4 (O08807) and heterogeneous nuclear ribonucleoprotein K (P61979) following neuronal and glial cell differentiation.20 In particular, an active role in neuronal
differentiation has been reported for NAP1, uniquely detected in A1P and initially identified as histone chaperone and chromatin-assembly factor.24,25 It has been observed that the neuronal variant Nap1L2, by controlling histone acetylation, can strongly affect the transcriptional regulation during neuronal differentiation and/or survival.24 Furthermore, by ex vivo differentiation studies of Nap1L2-/- ES cells, it has been demonstrated that it regulates the kinetics of neuronal differentiation, increasing neural precursor renewal, maintenance, and apoptosis. The 60S ribosomal protein L34 (Q9D1R9) was only detected in A1D sample. Although this is a classical structural ribosomal protein, it has been also found to play a role in neuronal differentiation by interacting with cyclindependent kinase 5 (Cdk5) and its activator p35, which are involved in neurite outgrowth.26,27 Two proteins, uniquely detected in the A1D cells, belong to the family of H1 linker histone. Interestingly, the H1(0) histone (P10922) expression levels have been reported to be more closely related to the degree of differentiation than to the proliferative activity of cells (i.e., cancerous cells).28 It is well-known that both cellular statuses are characterized by extensive chromatin remodeling events. Previous studies have shown that the exchange of H1 subtype H1(0) occurs at a significant rate, resulting in its Journal of Proteome Research • Vol. 8, No. 1, 2009 235
research articles accumulation during terminal differentiation in numerous cell/ tissue systems, including terminally differentiated neurons.29-31 In rat cerebral cortex neurons, it has been found that the four H1a-d subtypes exponentially decay during postnatal development and are partially or totally replaced by H1e (P43274), the major subtype in adults, also uniquely detected in A1D sample. In the same experimental system, H1(0) accumulates in a period restricted to neuronal terminal differentiation.32 A novel inhibitor of TGF beta proteins,33 the serine protease HtrA (Q9R118) has been uniquely detected in A1D. Interestingly, it has been reported that HtrA1 could be indirectly related to the development of nervous system, by binding several TGF beta family proteins, including Bmp4, Gdf5, TGF betas, and activin.33-35 Upon A1 differentiation and cell growth arrest, changes of proteins involved in the cell cycle control have been identified. Prohibitin 1 (Phb1, P67778) and 2 (Phb2, O35129), inhibitors of proliferation by means of histone deacetylase,36 are upregulated or uniquely detected in A1D cells, respectively. In addition, prohibitins are involved in several functions including senescence, apoptosis, stabilization of mitochondrial proteins and targeting to lipid rafts.37 Furthermore, prohibitins can modulate transcription by interacting with various transcription factors, including the steroid hormone receptors and can activate Raf/MEK/ERK pathway.38 They therefore represent important candidates to gain insight into molecular mechanisms at the basis of different responses of A1P and A1D to external stimuli.1,2 Several proteins previously associated with proliferation have been identified in proliferating A1 cells. Interestingly, some proteins have been previously associated with the proliferation of adult neural stem cells (NSCs). In particular, it has been reported that galectin-1 (Gal-1, P16045) is expressed in adult NSCs and promotes their proliferation through its carbohydratebinding ability.39,40 Gal-1 also increased the proliferation and adhesion of endothelial cells and enhanced cell migration in combination with VEGF, by directly binding to neuropilin-1 (NRP1), a neuronal receptor that mediates repulsive growth cone guidance.41 Other proteins that play critical roles in cell proliferation, motility and oxidative stress response, differentially expressed in A1P vs A1D, include lactate dehydrogenase (P06151), the antioxidant peroxiredoxins (P35700 and O08807), the Rb-associated protein nucleolin (P09405), the RNA-binding proteins HuR (ELAV-like protein 1, P70372), the elongation factor 2 (P58252), the RhoC GTPase (Q62159), annexins I (P10107) and II (P07356). Several members of the heterogeneous nuclear ribonucleoproteins (hnRNPs), a large family of nucleic acid binding proteins, have been uniquely detected in the A1P. hnRNP family members are involved in many steps of mRNA maturation/turnover; some of them acting as DNAbinding proteins and transcriptional activators. The heterogeneous nuclear ribonucleoprotein K (hnRNP K, P61979) for example interacts with several signal transducers and directly regulates rates of transcription and translation.42 In our cellular model, as in other cell types, hnRNP K expression is higher in proliferating with respect to resting cells.43 In particular, hnRNP K is down-regulated also in ReNcell VM neural stem cells, upon neuronal differentiation.20 The mechanism by which hnRNP K is involved in neuronal differentiation has been proposed in mouse neuroblastoma N1E-115 cells.44 It has been demonstrated that the Hu family, a group of neuronal RNA-binding proteins required for neuronal differentiation by stabilizing p21 (CIP1) mRNA, is antagonized by hnRNP K.44 It is worth noting 236
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Chambery et al. that among the differentially regulated hnRNPs isoforms there are also hnRNP A1 (P49312) and A3 (Q8BG05) isoforms, which are associated with telomere and telomerase regulation.45-47 Telomerase are ribonucleoprotein complex preventing the shortening of telomeres, the latter being involved in the process of cell senescence. HSPs, belonging to a moonlight protein family and playing important roles in cell proliferation, differentiation, survival, stress and immune response, are differentially regulated in A1 cells.48-50 Interestingly, it has been also reported that some HSPs are differentially expressed in glial and neuronal cells, as well as in the different structures of the brain.48,51 In particular, only the heat shock protein gp96 (P08113), an endoplasmic reticulum chaperone belonging to the HSP90 family, was upregulated upon A1 differentiation. On the contrary, several HSPs, belonging to the HSP90 and HSP70 families and known to be highly expressed in proliferating mammalian cells were up-regulated in A1P. The most up-regulated proteins in A1P condition are the two nucleoside diphosphate kinases (NDPK A, P15532 and NDPK B, Q01768, encoded by Nm23 gene), enzymes involved in cell proliferation, differentiation, development, tumor progression, and metastasis.52 The biological effects of Nm23/NDPK isoforms vary according to cell types and the underlying molecular mechanisms are still unclear. In particular, Nm23/NDPK together with its interacting partner PRUNE has been reported to be involved in the processes of proliferation, differentiation and migration of neural and neuronal cells either in vitro or in selective brain areas.53-57 Furthermore, several members belonging to the 14-3-3 proteins have been commonly detected in A1 cell line and upregulated in A1P. The highly conserved acidic 14-3-3 family include seven dimeric phosphoserine-binding protein isoforms that participate to many signaling pathways,58 by interacting with over 200 target proteins. 14-3-3 proteins are involved in cell cycle/growth, differentiation, survival, apoptosis and migration.59 In particular, the 14-3-3 gamma isoform (P61982) has been found involved in the dynamics of GFAP filaments, thus contributing to the stability of the cytoskeleton.60 Furthermore, 14-3-3 protein has been also known as an activator of the tryptophan 5-hydroxylase (TPH), the rate limiting enzyme in serotonin synthesis. TPH is encoded by two genes, TPH1 and TPH2, the latter being exclusively expressed in the adult CNS and, more specifically, in median and dorsal raphe nuclei.61 Recent work reports the high affinity binding of the 14-3-3 proteins gamma, epsilon and BMH1 to the phosphorylated neural form of TPH (TPH2), resulting in the increase in enzyme stability and activity.22 Integrating these findings, a potential role is suggested for 14-3-3 proteins in consolidating and strengthening the effects of phosphorylation on TPH2, with important consequences in the regulation of serotonin function in the nervous system. Althought the study of the functional implications of the differential expression of 14-3-3 proteins was beyond the scope of the present work, the results encourage further investigation of their specific role in TPH and serotonin regulation. In nerve cells, serotonin, as well as other neurotransmitters, is stored within specific vesicular compartments. It is worth mentioning that an increase of the endosomial proteins compartment, including several Rab proteins, has been found upon A1 differentiation. The Rab family determines the endosome identity, being associated with distinct endosomal subpopulation and regulating the endosomal membrane trans-
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port. In particular, Rab11 (P62492 and P46638), increased upon A1 differentiation, has been found to play an important role in determining the regulated vs constitutive vesicles secretory pathways in neuroendocrine/neuronal cells.63 Furthermore, several cytoskeletal proteins have been also found differentially expressed upon A1 differentiation. This is not surprising since cell growth arrest and differentiation are paralleled by morphological and cell motility changes requiring a wide involvement of cytoskeleton.10,64,65 Interestingly, most proteins detected as unique or significantly up-regulated in A1D cells share a mitochondrial localization with both structural and metabolic functions. These findings reconcile well with the central role exerted by mitochondria in neurons in ATP production, calcium regulation and oxyradical metabolism. A detailed study reporting the broad up-regulation of mitochondrial proteins following neuronal differentiation of P19 carcinoma cells has been recently published.21 Accordingly, an increased level of several proteins involved in mitochondrial energy metabolism has been found (e.g., TCA cycle proteins, ATP synthetase and components of the mitochondrial respiratory complexes), chaperones and membrane carriers. In particular, two enzymes (i.e., aspartate aminotransferase, AAT (P05202) and glutamate dehydrogenase, GDH (P26443)), known to be involved in L-glutamate and GABA neurotransmitter metabolism, have been found differentially expressed in A1D. AAT and GDH have a number of key roles in astrocytes and neurons, including the metabolic pathways known as “glutamate-glutamine cycle”, connected to the synthesis of neurotransmitter L-glutamate. This amino acid is the immediate precursor of the inhibitory neurotransmitter GABA, previously reported to be up-regulated upon A1 differentiation.4,66 Therefore, GDH and AAT act together in metabolism and, in addition, AAT is also an essential component of the malate-aspartate shuttle, which is particularly important in neurons, for transferring reducing equivalents from the cytosol into mitochondria.67 In A1D cells, upregulation of GDH and malate dehydrogenase (MDH, P08249) and unique detection of AAT was observed. It is known that these three enzymes can form a functional complex.67 Remarkably, 9 out of 14 mitochondrial proteins [including HSP 10 (Q64433), HSP 60 (P63038), prohibitin 2 (O35129), MDH (P08249), phosphate carrier (Q8VEM8), VDAC 1 (Q60932)], all up-regulated in P19 cell differentiation, have been found enriched or detected as unique in A1D cells. In addition, 9 other mitochondrial proteins have been found to be up-regulated following A1 differentiation. These findings attest an enhanced mitochondrial biogenesis upon neuronal differentiation accompanied by a depression in the levels of the same enzymes involved in glycolysis [e.g., triosephosphate isomerase (P17751), glyceraldehyde 3-phosphate dehydrogenase (P16858), enolase (P17182), lactate dehydrogenase ((P06151) and (P00342)) and pyruvate kinase, (P52480)], as observed in P19 cells. It has been suggested that the transition to mitochondrial metabolism makes more efficient use of carbohydrate energy, providing more ATP to satisfy the demands of the maturing neuron. Accordingly, the mitochondrially generated ATP is made available to the cell through the up-regulation of the adenine nucleotide transporters, as observed in both P19 and A1 experimental systems.
Conclusions The proteomic profiling of proliferating/undifferentiated vs nonproliferating/differentiated A1 neural cells, performed by
qualitative and quantitative LC-MSE analysis, provides a list of candidates with potential relevance for the functional and biological features of proliferative and differentiated A1 cells. Extensive changes in biosynthesis of proteins belonging to specific cellular compartments, upon differentiation, have been observed mainly involving mitochondrial proteins. The overall increase of mitochondrial proteins in A1 cells represents the first evidence of the involvement of mitochondria in neuronal differentiation other than the highly transformed tumor-derived P19 teratocarcinoma cell line. Interestingly, enzymes and other proteins involved in neurotransmitter (e.g., GABA and serotonin) biosynthesis, stabilization, activation and/or regulated exocytose (e.g., AAT, GDH, 14-3-3, Rab11) have been found as differentially expressed in A1 cells. Finally, different neural cell lineages and/or differentiation markers, including neuronal and glial, have been found in A1 cells. These findings confirm and extend previous observations on the coexistence of both neuronal and glial properties within A1 cells.4 These features are not only typical of neural progenitors, but also of neural stem cells, which constantly express a broad range of multilineage markers.8,68,69 Collectively, these results suggest potential “stemness” properties for A1 cells. The perspectives of the present study will focus on further investigation of proteins found to be differentially expressed within the two cell populations, with the aim to better understand their implications in the A1 differentiation process.
Acknowledgment. This study was supported by funds from the Second University of Naples. A.C. thanks CNR (Italy) for a short-term mobility fellowship (program 2006). Supporting Information Available: Supplemenatry Figures 1-8 and Tables 1S and 2S. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Ianora, A.; Miralto, A.; Poulet, S. A.; Carotenuto, Y.; Buttino, I.; Romano, G.; Casotti, R.; Pohnert, G.; Wichard, T.; Colucci-D’Amato, L.; Terrazzano, G.; Smetacek, V. Nature 2004, 429 (6990), 403–7. (2) Di Lieto, A.; Leo, D.; Volpicelli, F.; di Porzio, U.; Colucci-D’Amato, L. Brain Res. 2007, 1143, 1–10. (3) Colucci-D’Amato, L.; Perrone-Capano, C.; di Porzio, U. Bioessays 2003, 25 (11), 1085–95. (4) Colucci-D’Amato, G. L.; Tino, A.; Pernas-Alonso, R.; ffrench-Mullen, J. M.; di Porzio, U. Exp. Cell Res. 1999, 252 (2), 383–91. (5) Ivanova, N. B.; Dimos, J. T.; Schaniel, C.; Hackney, J. A.; Moore, K. A.; Lemischka, I. R. Science 2002, 298 (5593), 601–4. (6) Ramalho-Santos, M.; Yoon, S.; Matsuzaki, Y.; Mulligan, R. C.; Melton, D. A. Science 2002, 298 (5593), 597–600. (7) Fortunel, N. O.; Otu, H. H.; Ng, H. H.; Chen, J.; Mu, X.; Chevassut, T.; Li, X.; Joseph, M.; Bailey, C.; Hatzfeld, J. A.; Hatzfeld, A.; Usta, F.; Vega, V. B.; Long, P. M.; Libermann, T. A.; Lim, B. Science 2003, 302 (5644), 393. and author reply 393. (8) Colucci-D’Amato, L.; di Porzio, U. Bioessays 2008, 30 (2), 135–45. (9) Baharvand, H.; Hajheidari, M.; Ashtiani, S. K.; Salekdeh, G. H. Proteomics 2006, 6 (12), 3544–9. (10) Hoffrogge, R.; Beyer, S.; Volker, U.; Uhrmacher, A. M.; Rolfs, A. Neurodegener. Dis. 2006, 3 (1-2), 112–21. (11) Inberg, A.; Bogoch, Y.; Bledi, Y.; Linial, M. Proteomics 2007, 7 (6), 910–20. (12) Oh, J. E.; Freilinger, A.; Gelpi, E.; Pollak, A.; Hengstschlager, M.; Lubec, G. Electrophoresis 2007, 28 (12), 2009–17. (13) Baharvand, H.; Fathi, A.; van Hoof, D.; Salekdeh, G. H. Stem Cells 2007, 25 (8), 1888–903. (14) Bateman, R. H.; Carruthers, R.; Hoyes, J. B.; Jones, C.; Langridge, J. I.; Millar, A.; Vissers, J. P. J. Am. Soc. Mass Spectrom. 2002, 13 (7), 792–803. (15) Silva, J. C.; Denny, R.; Dorschel, C. A.; Gorenstein, M.; Kass, I. J.; Li, G. Z.; McKenna, T.; Nold, M. J.; Richardson, K.; Young, P.; Geromanos, S. Anal. Chem. 2005, 77 (7), 2187–200. (16) Hughes, M. A.; Silva, J. C.; Geromanos, S. J.; Townsend, C. A. J. Proteome Res. 2006, 5 (1), 54–63.
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PR800454N
