Application of SILAC Labeling to Primary Bone Marrow-Derived

Article pubs.acs.org/jpr

Application of SILAC Labeling to Primary Bone Marrow-Derived Dendritic Cells Reveals Extensive GM-CSF-Dependent Arginine Metabolism Ivo Fabrik,*,† Marek Link,† Anetta Har̈ tlova,‡ Vera Dankova,†,§ Pavel Rehulka,† and Jiri Stulik† †

Institute of Molecular Pathology, Faculty of Military Health Sciences, University of Defence, Trebesska 1575, 500 01 Hradec Kralove, Czech Republic ‡ Department of Molecular Biology, Laboratory of Molecular Medicine Sweden (MIMS), Umeå University, SE-901 85 Umeå, Sweden § Department of Biochemical Studies, Faculty of Pharmacy in Hradec Kralove, Charles University in Prague, Heyrovskeho 1203, 500 05 Hradec Kralove, Czech Republic S Supporting Information *

ABSTRACT: Although dendritic cells (DCs) control the priming of the adaptive immunity response, a comprehensive description of their behavior at the protein level is missing. The introduction of the quantitative proteomic technique of metabolic labeling (SILAC) into the field of DC research would therefore be highly beneficial. To achieve this, we applied SILAC labeling to primary bone marowderived DCs (BMDCs). These cells combine both biological relevance and experimental feasibility, as their in vitro generation permits the use of 13C/15N-labeled amino acids. Interestingly, BMDCs appear to exhibit a very active arginine metabolism. Using standard cultivation conditions, ∼20% of all protein-incorporated proline was a byproduct of heavy arginine degradation. In addition, the dissipation of 15N from labeled arginine to the whole proteome was observed. The latter decreased the mass accuracy in MS and affected the natural isotopic distribution of peptides. SILAC-connected metabolic issues were shown to be enhanced by GMCSF, which is used for the differentiation of DC progenitors. Modifications of the cultivation procedure suppressed the argininerelated effects, yielding cells with a proteome labeling efficiency of ≥90%. Importantly, BMDCs generated according to the new cultivation protocol preserved their resemblance to inflammatory DCs in vivo, as evidenced by their response to LPS treatment. KEYWORDS: dendritic cells, SILAC, arginine metabolism, peptide isotopic distribution, lipopolysaccharide, quantitative proteomics, mass spectrometry

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INTRODUCTION

Of several approaches suitable for comprehensive quantitative cellular proteomics, stable isotope labeling by amino acids in cell culture (SILAC) has gained particular popularity.7,8 SILAC is based on the cultivation of two or more groups of cells in media containing differently isotopically labeled amino acids that are incorporated into the cells’ proteomes. A selected group of cells is subsequently treated and mixed with untreated control cells. The change in the protein expression is inferred from the ratio of light/heavy peptide signal intensities obtained through MS analysis. The principal advantage of SILAC lies in the minimization of quantification errors introduced by sample processing because the cells or cell lysates are mixed together immediately after the treatment, and the same conditions apply for the proteins from differently labeled cells.8 Considering the use of SILAC for DC quantitative proteomics, primary bone marow-derived DCs (BMDCs) would appear to be the most suitable cells for labeling.9−11

Dendritic cells (DCs) are considered the most efficient of the antigen presenting cells (APCs).1−3 As such, these cells represent a decision mechanism that instructs adaptive immunity effectors and provide the essential link between innate and adaptive immunity.1,4,5 At steady state, DCs reside in the peripheral organs, where they scavenge the local environment for antigens. The acquisition of antigens leads to the process of maturation, during which DCs reduce their endocytic activity, upregulate their surface expression of MHC complexes and costimulatory molecules, and start to migrate toward the local lymph node, where antigen presentation and lymphocyte priming take place. However, it is increasingly apparent that the general description of DC behavior does not encompass the whole complexity of DC biology, and we are still far from being able to understand DCs at the cellular level. In this context, more systematic approaches, such as quantitative proteomics, have proven to be invaluable tools6 with benefits that would be highly appreciated in DC research. © 2013 American Chemical Society

Received: August 15, 2013 Published: December 6, 2013 752

dx.doi.org/10.1021/pr4007798 | J. Proteome Res. 2014, 13, 752−762

Journal of Proteome Research

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Figure 1. Changes in the arginine metabolism affect the character of the LC−MS spectra. (A) Bone marrow progenitors isolated from mice were seeded into three different SILAC RPMI media. (See panel B.) The differentiation of the cells was induced by the additions of GM-CSF starting on the next day after isolation. (B) Concentrations of proline and isotopically labeled forms of arginine and lysine in SILAC media used for BMDC metabolic labeling. (C,D) Two representative peptides from tryptic digests of labeled BMDCs lysates. The top MS spectra are software-modeled (R = 40 000). The other spectra were designated according to the media formulation that was used for BMDC generation. The gray parts highlight the medium-dependent changes in the relative abundance of the isotopic peaks of the peptide signal cluster. The LC−MS spectra were summed through the elution window of the peptide.

As an in vitro model, BMDCs combine the experimental feasibility of cell lines and the biological relevance of primary cells. BMDCs are produced from isolated bone marow DC progenitors that are differentiated through cocultivation with granulocyte/macrophage colony-stimulating factor (GMCSF)9,10 or FMS-like tyrosine kinase-3 ligand (Flt3L).11−13 However, it must be stressed that SILAC was primarily designed for cell lines whose replication ensured sufficient label incorporation. In general, primary cells do not divide at a high frequency and longer labeling periods may be required.14−18 Some cells have a relatively short life span,19 and the feasibility of SILAC labeling is therefore cell-type-dependent. The length of cultivation of BMDCs differentiated by GM-CSF usually varies between 7 and 12 days,9,10 and longer periods may result in the spontaneous maturation of the cells. Moreover, amino acid metabolic activity may be a source of quantification error, as in the case of the arginine-to-proline conversion problem.20−25 The metabolism of primary cells in particular is very diverse and amino acid-specific, and this aspect should also be controlled during the SILAC experiment. To assess the suitability of metabolic labeling for DC proteomics, we applied the SILAC methodology to GM-CSFderived9,10 BMDCs. The presented results revealed the extensive metabolism of isotopically labeled arginine in these cells with the observable impact on SILAC labeling. In addition to complications connected with pronounced arginine-toproline conversion, a redistribution of 15N from the degraded amino acid into the newly synthesized proteins was observed. This caused a decrease in the isotopic mass accuracy and a distortion of the peptides’ isotopic envelopes. Although the arginine metabolism was found to be amplified by GM-CSF, we were able to suppress the metabolic effects through a modification of the contents of labeled arginine and lysine

and unlabeled proline in the SILAC medium formulation. Importantly, these changes did not affect the functional state or capabilities of BMDCs and provided sufficient label incorporation efficiency.

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MATERIAL AND METHODS

Generation of Bone Marrow DCs

BMDCs were generated according to Lutz et al.10 with minor modifications. Femoral and tibial bone marrow cells were obtained from 6- to 8-week-old female C57BL/6 mice by the protocol approved by the ethical committee of Faculty of Military Health Sciences of University of Defence (project number: 89-3/2013-3696). Approximately 1 × 107 bone marrow cells were seeded on 10 cm tissue plastic Petri dish into 10 mL of RPMI-1640 media containing 10% (v/v) fetal bovine serum (FBS) and penicillin/streptomycin and left at 37 °C in a humidified atmosphere of 5% CO2. After overnight depletion of adherent cells, suspension cells were seeded on a new dish with RPMI-1640, 10% FBS, and 5% (v/v) supernatant from Ag8653 cells transfected by cDNA of murine GM-CSF. Cells were passaged every 2−3 days. Suspension cells were harvested on the ninth day of cultivation. SILAC Labeling

For SILAC labeling, the cultivation procedure was identical to that previously described, except RPMI-1640 medium without L-lysine and L-arginine (with L-glutamine; Thermo Pierce) and containing 10% (v/v) dialyzed FBS (Sigma Aldrich) was used (Figure 1A). Isotopically labeled L-lysine [13C6] and L-arginine [13C6, 15N4] or L-arginine [13C6] (Sigma Aldrich) were added at concentrations of 0.2 and 1.1 mM for RPMI-like formulation or at 0.8 and 0.4 mM for DMEM-like formulation, respectively. Unlabeled L-proline was added to a final concentration of 2.61 753



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mM (300 mg/L). The exact formulations of all used media are provided in Figure 1B.

were eluted by 80% ACN/0.1% TFA and dried using a vacuum concentrator.

LPS Treatment and ELISA Microarray Assay

HPLC Fractionation

5 × 105 or 2 × 106 BMDCs per well were seeded into a 24-well or a 6-well plate, respectively. Cells were stimulated with 20 μg/mL E. coli 055:B5 lipopolysaccharide (LPS, Sigma Aldrich) for either 6 or 24 h. For SILAC experiments, heavy labeled BMDCs were left untreated (control cells), and unlabeled BMDCs were treated with LPS. Levels of cytokines and chemokines in medium supernatant were determined by ELISA microarray assay using Quantibody Cytokine Array (RayBiotech).

Fractionation of tryptic peptides from whole cell lysates of SILAC-labeled BMDCs treated by LPS was carried out by reversed-phase liquid chromatography on Gemini C18 3 μm, 110 Å, 2.0 × 100 mm column (Phenomenex) under high-pH mobile phase conditions using an Alliance 2695 liquid chromatograph (Waters). The mobile phases were (A) water, (B) acetonitrile (ACN), and (C) 200 mM ammonium formate of pH 10. Vacuum-dried peptides were dissolved in 80 μL of 10% C, and 20 μL of the sample (corresponding to 50 μg of undigested protein) was injected onto the column. Peptide separation was performed by a linear gradient formed by mobile phase A and mobile phase B, from 2 to 45% of mobile phase B in 43 min at a flow rate of 0.3 mL/min. Mobile phase C proportioning was 10% throughout the separation. Column temperature was kept constant at 40 °C, and the separation was monitored at 215 nm. Fractions were collected into the microcentrifuge tubes at 2 min time intervals over the sample elution window of 10−30 min and dried using a vacuum concentrator.

Flow Cytometry

BMDCs were stained by following antibodies: anti-CD11b conjugated with PE (eBioscience), anti-CD11c conjugated with PE (BD Pharmingen), anti-CD80 conjugated with PE (Beckman Coulter), anti-CD86 conjugated with PE (Beckman Coulter), and anti-I-A/I-E MHC II conjugated with biotin (Novus Biologicals), respectively. Anti-MHC II antibodies were then stained by streptavidin-conjugated FITC (Invitrogen). Cells were fixed by CellFIX buffer (BD Biosciences) and subsequently analyzed on CyAn ADP flow cytometer (Beckman Coulter). Data acquisition and interpretation were done using Summit 4.3 software (Beckman Coulter). Two-sample Student’s t test was used to assess the significance of the change in fluorescence intensity for the determination of cell surface marker upregulation.

nanoLC−MS/MS

For the determination of metabolic effects of SILAC labeling, both offline nanoLC−MALDI-TOF/TOF and online nanoLC−nESI-Q-Orbitrap systems were used for sample analysis. Samples from pulsed-SILAC experiment were analyzed by nanoLC−MALDI-TOF/TOF only. The samples for evaluation of labeling efficiency and the samples from LPS treatment of SILAC-labeled BMDCs were analyzed by nanoLC−nESI-Q-Orbitrap only. The conditions for nanoLC−MALDI-TOF/TOF analyses were as follows: Samples were dissolved in 5% ACN/0.1% TFA, and ∼2.5 μg of peptide material was injected into an Ultimate 3000 system (Dionex). Peptides were loaded on trap column (C18 PepMap100, 5 μm, 100 Å, 0.3 × 5 mm; Dionex) at flow rate 20 μL/min of 2% ACN/0.1% TFA mobile phase and after 5 min eluted and separated on capillary column (Atlantis dC18 3 μm, 100 Å, 0.1 × 150 mm; Waters). Elution was carried out by step linear gradient of mobile phase B (80% ACN/0.1% TFA) over mobile phase A (5% ACN/0.1% TFA); from 0 to 35% B in 62 min and from 35 to 50% B in 18 min at flow rate 360 nL/min. Temperature of column was kept at 30 °C, and eluent was monitored at 215 nm during the separation. For off-line MS analysis, 12 s elution fractions were collected and mixed on steel plate with MALDI matrix (α-cyano-4hydroxycinnamic acid; LaserBio Labs) by Probot automated spotting device (Dionex). The volume of each fraction was 240 nL with matrix concentration of 2.3 mg/mL. Mass spectrometric analyses were carried out on 4800 MALDI-TOF/TOF Analyzer (AB Sciex) equipped with 200 Hz Nd:YAG laser with wavelength of 355 nm. Spectra were acquired in 800−4000 m/z window in the positive ion reflectron mode. Every MS spectrum was accumulated from 1800 laser shots. MS/MS spectra were acquired using a 1 kV MS/MS reflector positive ion mode. The quality of each tandem mass spectrum was monitored on-the-fly by stop conditions criteria with a maximum of 1800 laser shots per spectrum. Criteria for selection of precursors were as follows: minimal S/N 180, minimal length of elution window through two collected fractions, and fraction-to-fraction precursor mass tolerance 150 ppm. The maximal number of selected precursors per fraction

Pulsed SILAC Experiment

BMDCs were generated according to the previously described protocol employing light RPMI-1640 medium containing 10% (v/v) dialyzed FBS and 5% (v/v) supernatant from Ag8653 cells. On day 9, suspension cells were washed and transferred into new dishes with light RPMI-1640 medium containing 10% dialyzed FBS but without Ag8653 supernatant and left for 24 h. The next day, cells were seeded into SILAC RPMI-1640 medium containing 1.1 mM Arg+10 [13C6,15N4] and 0.2 mM Lys+6 [13C6] and 10% dialyzed FBS (Figure 1B). One group of BMDCs was left untreated, and three other groups were treated by various concentrations (10, 30, and 60 ng/mL) of recombinant murine GM-CSF (BD Pharmingen) for 2 days. After the treatment, cells were processed as described later. Cell Lysis and Protein Digestion

BMDCs were harvested and washed twice with ice-cold PBS. Cells were resuspended at 3 × 106 per 1 mL of ice-cold hypotonic lysis buffer (10 mM Tris of pH 7.5 and 0.5 mM MgCl2) and lysed by glass dounce homogenizer with tight pestle, followed by sonication. For SILAC experiments with LPS-treated BMDCs, heavy-labeled and unlabeled lysates were mixed in 1:1 protein ratio. NH4HCO3 was added to lysates to a final concentration of 50 mM. Proteins were reduced with 10 mM dithiotreitol at 37 °C for 60 min and alkylated with 20 mM iodoacetamide for 30 min in the dark at room temperature. The excess of iodoacetamide was quenched by the addition of dithiotreitol to a final concentration of 20 mM, followed by the incubation for 15 min at room temperature. Proteins were digested by trypsin (Promega) at a ratio 20:1 (w/w) at 37 °C overnight. Digestion was stopped by the addition of TFA (Sigma Aldrich) to a final concentration of 0.1% (v/v). Digests were desalted on 3M Empore (4 mm/1 mL) or on Discovery DSC-18 SPE (500 mg/3 mL; both Sigma Aldrich) cartridges depending on the amount of loaded protein material. Peptides 754



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was 9. Data acquisition, precursor selection, and data procession were carried out by 4000 Series Explorer software v3.5 (AB Sciex). Online LC−MS analyses were performed on an Ultimate 3000 RSLCnano system (Dionex) coupled through Nanospray Flex ion source with Q Exactive mass spectrometer (Thermo Scientific).26 Samples were dissolved in 2% ACN/0.05% TFA, and ∼500 ng of peptide material was injected into RSLCnano system. Peptides were loaded on capillary trap column (C18 PepMap100, 3 μm, 100 Å, 0.075 × 20 mm; Dionex) by 2% ACN/0.05% TFA mobile phase at flow rate 5 μL/min for 5 min and then eluted and separated on capillary column (C18 PepMap RSLC, 2 μm, 100 Å, 0.075 × 150 mm; Dionex). Elution was carried out by step linear gradient of mobile phase B (80% ACN/0.1% FA) over mobile phase A (0.1% FA) from 4 to 34% B in 68 min and from 34 to 55% B in 21 min at flow rate 300 nL/min. The temperature of the column was 40 °C, and the eluent was monitored at 215 nm during the separation. Spraying voltage was 1.8 kV, and heated capillary temperature was 220 °C. Mass spectrometer was operated in the positive ion mode performing survey MS (range 300−1800 m/z) and datadependent MS/MS scans on the 12 most intense precursors with dynamic exclusion window of 60 s. MS scans were acquired with 70 000 resolution at 200 m/z from 1 × 106 accumulated charges (maximum fill time was 60 ms). The lock mass at m/z 445.12003 ([(C2H6SiO)6+H]+) was used for internal calibration of mass spectra. Intensity threshold for triggering MS/MS was set at 1 × 105 for ions with z ≥ 2 with 2 Da isolation window. Precursor ions were accumulated with AGC of 1 × 106 (maximum fill time was 60 ms), and normalized collisional energy for HCD fragmentation was 27 units. MS/MS spectra were acquired with 17 500 resolution (at 200 m/z).

cleavage restriction was set as protease. Mass tolerance for fragments in MS/MS was 20 ppm, taking the 10 most intensive peaks per 100 Da (with enabled possibility of cofragmented peptide identification). FDR filtering of peptides and proteins identifications were done as described in the supporting information of ref 27. In brief, only peptides filtered on the PSM level of 0.01 FDR were used for the assembly of protein groups, which were then filtered on the level of 0.01 protein FDR. The software function Match between runs was enabled with time window of 30 s for the analysis of high-pH fractionated samples. For quantification, function Re-quantify was enabled. The software Xcalibur v2.2 (Thermo Scientific) or Isotope Distribution Calculator (http://proteome.gs.washington.edu/ software/IDCalc/) was used for modeling of isotopic patterns of peptides. For evaluation of SILAC labeling efficiency, protein groups identified on at least one unique and two unique + razor peptides and quantified by at least one SILAC-doublet in each biological replicate were considered. Incorporation completeness was determined according to formula Eff (%) = [1 − (XIC Light/XICHeavy )] × 100, where XICLight or XICHeavy correspond to extracted ions chromatograms of light (insufficiently labeled) or heavy proteins, respectively. XICs of individual light/heavy forms of proteins were obtained from the summation of corresponding light or heavy peptides’ XIC. For relative protein quantification of LPS-treated BMDCs, only protein groups identified/quantified independently in all three replicates on at least one unique peptide were considered. The normalized protein ratios from each replicate were further considered, and the most significantly regulated proteins were found by ranking method,29 taking those proteins that were found in top-T/bottom-T groups in all three replicates (TTT or BBB). The false discovery rate was evaluated by nonparametric estimate as an average number of proteins in the “false” groups (TTB, TBT, TBB, BTB, BBT, and BTT).29

Protein Identification, Quantification, and Estimation of Metabolic Labeling Properties

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ProteinPilot v2.0.1 (AB Sciex) using Paragon searching algorithm and MaxQuant v1.3.0.5.27 coupled to Andromeda search engine28 was used for interpretation of MS/MS data from MALDI-TOF/TOF and nESI-Q-Orbitrap, respectively. Only Swiss-Prot database entry for Mus musculus (October 12, 2012; 24 415 sequences) was considered for the evaluation of metabolic effects and labeling efficiency. The protein sequence database for LPS-treated BMDCs proteome identification/ quantification was the reference proteome set for Mus musculus (March 25, 2013; 50 665 sequences). The contaminants file was downloaded from the MaxQuant Web page (http:// maxquant.org/downloads.htm). Both search engines used the target-decoy approach for the estimation of false-positive hits with concatenated reversed database as decoy (with swap of lysine and arginine with neighboring amino acid for MaxQuant). Parameters of ProteinPilot/Paragon search were set as follows: alkylation by iodoacetamide, digestion with trypsin, and detected protein threshold 1.3. Quantitate option was enabled with corresponding combination of labeled amino acids as SILAC sample type. For search by MaxQuant/ Andromeda, parameters were set as follows: mass tolerance for the first search 20 ppm, for the second search from recalibrated spectra 6 ppm (with individual mass error filtering enabled); maximum of 2 missed cleavages; maximal charge per peptide z = 7; minimal length of peptide 7 amino acids; carbamidomethylation (C) as fixed and oxidation (M) and acetylation (protein N-term) as variable modifications; and trypsin with no

RESULTS AND DISCUSSION

Arginine-to-Proline Conversion During SILAC Labeling of BMDCs

Light and heavy SILAC-labeled BMDCs were generated by cultivating bone marrow cells with the supernatant of Ag8653 cells transfected with cDNA of the murine GM-CSF gene instead of the addition of a recombinant colony-stimulating factor.9,10 This approach is occasionally used for the preparation of BMDCs for in vitro experiments30,31 but has not yet been used for quantitative proteomics purposes. Routinely, ∼80% of the suspension cell population was CD11c+ on the ninth day of cultivation (Supplementary Figure 1, Supporting Information), which correlates well with the original protocols for BMDC generation.9,10 For the initial SILAC experiments, isotopically labeled Arg +10 [13C6,15N4] and Lys+6 [13C6] were used at concentrations of 1.1 and 0.2 mM, respectively (denoted “Medium A” in the text and figures; Figure 1A,B), as defined by original RPMI1640 medium formulation. The whole cell lysates of labeled BMDCs were digested and subjected to both nanoLC− MALDI-TOF/TOF and nanoLC−nESI-Q-Orbitrap LC−MS/ MS analyses. The comparison of the MS spectra of peptides from Medium A-cultivated BMDCs and the theoretical peptides isotopic patterns revealed that the most dramatic difference is the presence of +6 Da satellite signal clusters in the 755



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spectra of the Medium A peptides (Figure 1C and Supplementary Figure 2, Supporting Information). As expected,22 this was due to the incorporation of Arg+10derived proline Pro+6 [13C5, 15N1] into the BMDC proteome (confirmed by MS/MS, data not shown). Interestingly, more than 20% of all protein-incorporated proline was the heavy arginine byproduct (Supplementary Figure 3, Supporting Information), which hindered the accurate estimation of the protein ratio based strictly on the unlabeled and Arg/Lyslabeled peptide signals intensities. Although several solutions to the arginine-to-proline conversion problem exist,20−25,32 we have decided to modify the medium formulation (denoted “Medium B”; Figure 1B) because RPMI-1640 contains relatively high amounts of arginine (1.1 mM). The concentrations of added Arg+10 and Lys+6 were adopted based on the DMEM medium, where these are more balanced (0.4 mM for arginine and 0.8 mM for lysine), and the amount of unlabeled proline was also significantly increased (300 mg/mL, ∼2.61 mM).22 The changes in the medium formulation suppressed the abundance of Pro+6 signal clusters of proline-containing peptides, as evidenced by the MS spectra of the lysate digests prepared from BMDCs cultivated in Medium B (Figure 1C). The XIC of the +6 Da signals of peptides containing or lacking proline in the sequence were generated and compared to quantify the improvement. There were no differences between these two peptide groups, which demonstrates the quantitative suppression of the arginine-to-proline conversion during the labeling of these cells (Supplementary Figures 3A,B, Supporting Information). Notably, alternations in the amino acids concentrations did not affect the yields or phenotype of the generated BMDCs (confirmed by flow cytometry, data not shown). Therefore, the arginine-to-proline conversion problem in BMDC SILAC labeling could be circumvented by the careful adjustment of the cultivation media formulation.

Figure 2. Incorporation of Arg+10-originating 15N into the BMDC proteome impacts the peptide isotopic cluster distribution and the isotopic mass accuracy. Overlay of software-modeled (black, R = 40 000) and three measured summed LC−MS spectra obtained for the representative peptide. (The colors of the spectrum line and of the numbers indicate the cultivation media used; see Figure 1B.) The numbers above the peaks correspond to the theoretical/measured m/z values. The overlay of the individual isotopic peaks is shown below, and the numbers correspond to the isotopic mass errors (in ppm).

Finally, the effector cells of innate immunity (including inflammatory DCs) use arginine as a nitrogen source for nitric oxide synthesis.34 Therefore, it would not be surprising if the distortion of the peptides isotopic patterns was a consequence of the isotopically labeled arginine catabolism in BMDCs. This hypothesis was confirmed by the MS analysis of the digest from BMDCs cultivated in Medium B containing unlabeled arginine instead of Arg+10, in which the isotopic envelopes of the tryptic peptides regained the theoretical distribution (data not shown). This notion, viewed from the context of arginine metabolism, led to the suspicion that the peptide isotopic distortion effect is caused by the 15N isotope of Arg+10. Indeed, the substitution of Arg+10 by Arg+6 [13C6] in the formulation of Medium B (denoted “Medium C”, Figure 1B) eliminated the isotopic distortion of peptide envelopes (Figure 1C,D, Figure 2, and Supplementary Figure 2, Supporting Information). Importantly, the peptide from the Medium C-cultivated BMDCs keeps a mass error for all of isotopic peaks below 2 ppm, together with predicted relative abundance (Figure 2). It appears that 15N is redistributed into the BMDC proteome during Arg+10 catabolism and thereby causes one or several +1 mass unit shifts in the peptide masses. Not only does this effect impact the relative abundance of the peptide isotope cluster but also the unnatural distribution of 15N in the peptide structure is the source of the observed mass errors (Figure 2). The mass difference between the +1 mass shifts caused by 15N and 13C is approximately −0.006 Da, and the resolution of 70 000 (at m/z 200), which is routinely used for Q-Orbitrap-based LC−MS shotgun proteomics,35 is sufficient for the registration of changes in the 15N/13C distribution (Figure 2). To roughly quantify the extent of 15N incorporation, we adopted the approach used for the estimation of the incorporation efficiency in 15N-based proteome labeling experiments.36,37 (For details,

Distortion of Peptide Isotopic Distribution During SILAC Labeling of BMDCs

Interestingly, a detailed inspection of the MS spectra obtained from the SILAC-labeled BMDC digest indicated another feature of the peptide signals. The relative abundance of isotopic patterns belonging to heavy peptides was distributed toward higher masses, resulting in a proportional decrease in monoisotopic peaks (Figure 1C,D and Supplementary Figure 2, Supporting Information). In addition, the high-resolution MS experiments performed on Orbitrap revealed shifts in the mass accuracy, strikingly only for the nonmonoisotopic peptide peaks (Figure 2). The mass error of the monoisotopic peak of the representative peptide was 200 000 in proteomics, new powerful approaches taking advantage of resolved isobars will certainly appear.39 Even in current shotgun proteomics, software triggering the MS/MS event or distinguishing the peptide cluster may rely on boundaries arising from the isotopic distribution of peptides populations. In this study, the Explorer software, which secured the MALDI-TOF/TOF analysis of peptides from heavy labeled BMDCs, interpreted the monoisotopic and second isotopic peaks as two distinct monoisotopic peptide peaks. This disrupted the precursor selection for MS/MS acquisition and consequently the peptide identification and the SILAC-based quantification in ProteinPilot. The MaxQuant interpretation of the data acquired on the Q-Orbitrap appeared to be unaffected by the shifts in the isotopic mass accuracy and the isotopic abundance; however, the software takes the advantage of high-resolution MS for the clustering of individual peaks into peptide isotopic envelopes and expects predictable peptide isotopic patterns for the SILAC pair detection from the MS spectra (supporting information of ref 27). It is clear that the effect of the peptides isotopic profiles distortion is highly software-dependent, and the robustness of each algorithm needs to be tested. However, on the basis of a survey of the available literature and our knowledge, we assume that the 15N incorporation of this extent would affect peptide identification rather than protein quantification. In conclusion, arginine, in addition to functioning as a proline precursor, also serves as a source of nitrogen for peptide/protein synthesis in BMDCs. The selection of 15Nlabeled arginine for SILAC labeling of BMDCs therefore causes the deterioration of the peptide isotopic distribution, which, although deeply hidden in the data, may have a significant impact on the obtained results. Origin of Extensive Arginine Catabolism in BMDCs

Although BMDCs are expected to possess an apparatus for high arginine turnover, there are no obvious reasons why the described effects would not be observed in macrophages because these cells fulfill similar functions in innate immunity. Isotopically labeled arginine was previously successfully

Figure 3. Proposed model for the metabolic degradation of isotopically labeled arginine [13C6,15N4] in primary BMDCs. 757



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individual proteins (Supplementary Figure 6, Supporting Information). The labeling completeness of the Lys-containing peptides was slightly higher (92−93%) than that of the Argcontaining peptides (84−85%; Figure 4B,C, respectively). Undoubtedly, these results were affected by the use of the 5% Ag8653 cell culture supernatant as a source of GM-CSF throughout the BMDC cultivation. The Ag8653 cells were cultivated in unmodified light RPMI-1640, and the dilution of heavy acids in Medium C may have deteriorated the incorporation efficiency. We postulate that the use of murinepurified recombinant GM-CSF instead of the supernatant would result in even higher incorporation rates. Despite this, the labeling characteristics of the presented protocol are satisfactory for SILAC-based proteome quantification and confirm the suitability of BMDCs for SILAC.

network of transamination processes. Meanwhile, deaminated ornithine provides a platform for the production of Pro+6. As a result, peptides containing proline in the sequence show clear +6 satellite clusters in the MS spectra, and virtually all of the peptides accumulate one or several 15N-labeled amino acids, explaining the mass shifts and the increase in the abundance of nonmonoisotopic peaks of the peptide isotopic cluster. Efficiency of Isotopically Labeled Amino Acids Incorporation after Cultivation Modifications

Unfortunately, deciphering GM-CSF as the important driving force of the arginine catabolism problem in the SILAC labeling of BMDCs did not indicate an easy way to circumvent the issue because GM-CSF cannot be omitted from the cultivation procedure. Several possible options still exist, for example, an approach utilizing only labeled lysine and Lys-C as the protease.32 However, on the basis of the promising MS spectra of peptides from Medium C-labeled BMDCs (Figure 1C,D, Figure 2, and Supplementary Figure 2, Supporting Information), we decided to continue with arginine and lysine labeling with subsequent trypsin digestion. The protein-labeling efficiency for BMDCs cultivated in Medium C (DMEM-like concentrations of arginine and lysine, 300 mg/L unlabeled proline, and Arg+6 instead of Arg+10, Figure 1B) was calculated from biological triplicate (Figure 4). Overall, 430

Functional Testing of BMDCs Prepared According to the Modified SILAC Protocol

The successful SILAC labeling of the BMDC proteome was possible only after modifications to the cultivation protocol. However, the decrease in the arginine concentration in the medium may have an impact on the functional state of the generated cells.46 Therefore, to test the preservation of the DC capabilities, we stimulated the BMDCs with LPS. The response of monocytic phagocytes toward this endotoxin is a wellstudied phenomenon.18,47−52 LPS is sensed by TLR-4 and triggers either the MyD88-dependent activation of NF-κB or the TRIF-dependent activation of IRF3 transcription factors, which leads to the production of proinflammatory cytokines, such as IL-12, IL-6, TNF-α, and type-I IFNs.53 In addition, LPS-activated APCs also increase their surface expression of costimulatory and MHC molecules in preparation for the antigen presentation process.54 Because GM-CSF-derived BMDCs correspond to inflammatory DCs in vivo,13,55 both innate and adaptive immunity competence should be preserved in the BMDCs prepared using the SILAC labeling protocol. First, the global change in the endotoxin-induced BMDCs protein expression was assessed in a SILAC experiment in which these cells were treated with LPS for 6 h. To avoid any heavy amino acid metabolism issues caused by BMDC activation, we used heavy labeled BMDCs as a control. (For other details, see the Materials and Methods section.) In summary, we identified and quantified a total of 1450 protein groups independently in all three replicates (Figure 5). Significantly upregulated/downregulated proteins were found through a method described in Materials and Methods,29 with the size of the top-T/bottom-T groups set to T = 100 because less than one protein was expected to be falsely assigned as regulated in the data set (on average 0.67 proteins per “false” group; see Materials and Methods). As a result, 77 proteins were found to be reproducibly regulated in the LPS-treated BMDCs (Supplementary Tables 1 and 2, Supporting Information). Of these, 52 were upregulated (FDR 0.013, green dots in Figure 5 and Supplementary Table 1, Supporting Information) and 25 were downregulated (FDR 0.027, red dots in Figure 5 and Supplementary Table 2, Supporting Information). Not surprisingly, the proinflammatory cytokines IL-1β, IL-12p40, IL-1α, TNF, and IL-6 represent a substantial part of newly expressed proteins. The increased presence of these cytokines in the medium of the LPS-treated BMDCs was confirmed by ELISA (Supplementary Table 3, Supporting Information). The activation of BMDCs may result from their direct contact with LPS, seeing increased expression of CD14.

Figure 4. Modified SILAC cultivation medium enables the metabolic labeling of BMDCs. The histograms show the efficiency and the reproducibility of SILAC labeling (Medium C, see Figure 1B) at the level of (A) the proteome, (B) the lysine-containing peptides, and (C) the arginine-containing peptides (no missed cleavages for peptide histograms). For the identification/quantification criteria and the calculation of the labeling efficiency, see Materials and Methods. The data were obtained from biological triplicates.

protein groups were independently identified in all three replicates, providing sufficient background for the estimation of the labeling state of the proteome. The efficiency of the metabolic labeling was ≥90% for the majority of the proteins (Figure 4A). Importantly, the incorporation histograms shown in Figure 4 demonstrate the high reproducibility of the labeling across replicates on the proteome level and on the level of 758



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Figure 5. Scatter-plot of LPS-regulated proteins in BMDCs. Unlabeled cells generated according to the modified cultivation procedure were treated with LPS for 6 h, and analogous heavy labeled BMDCs were used as a control. The experiment was performed in biological triplicate. The scatter-plot shows the log2 (average H/L ratio from triplicates) on the x axis and the log10 (relative standard deviation (RSD) of three measured ratios) on the y axis for quantified proteins. Overall, the expression of 77 proteins was shown to be reproducibly regulated in response to LPS. For details regarding the upregulated (52, green dots, Supplementary Table 1 in the Supporting Information) and downregulated (25, red dots, Supplementary Table 2 in the Supporting Information) proteins, see the text and Materials and Methods.

Figure 6. Upregulation of antigen-presentation cell surface markers in LPS-stimulated BMDCs. The cells were treated with PBS or LPS for 24 h, and the cell-surface expression of CD80, CD86, and MHC II was then analyzed by flow cytometry. (A) Representative histograms from the flow cytometric analysis. (B) Medians of fluorescence intensity (MFI). The data are shown as averages + SD from triplicate experiments, and the significance is evaluated by two-sample Student’s t test.

Nevertheless, the autocrine-mediated activation of BMDCs cannot be ruled out because several proteins connected with the IFN and TNF signaling pathways were also shown to be highly upregulated. In contrast, only 25 proteins were found to be downregulated after 6 h of LPS treatment, with rather small fold-changes in expression. Of these, the macrophage colonystimulating factor 1 receptor (CSF-1R) showed the most significant level of regulation. The downregulation of CSF-1R after LPS activation has been reported to be dependent on the action of the transmembrane protease TNF-converting enzyme (TACE), which cleaves the extracellular part of CSF-1R.56 This mechanism may explain the observed rapid change in CSF-1R abundance after LPS treatment. Histones appeared to also be downregulated (Supplementary Table 2, Supporting Information). However, the change in their expression is relatively small (with a maximal change of 1.67 in the log2 scale for histone H1.5; see Figure 5) with a rather high relative standard deviation (Supplementary Table 2, Supporting Information). Therefore, further validation of the acquired data would be necessary to confirm the role of these proteins in the BMDC response toward LPS. Over time, the position of activated inflammatory DCs expands from innate-like effectors to APCs during the maturation process.54 To assess the cells’ functional capabilities from this aspect, the BMDCs generated through the modified SILAC protocol were stimulated with LPS for 24 h and analyzed to determine any changes in the cell surface expression of MHC II and the costimulatory molecules CD80 and CD86 by flow cytometry. The LPS-activated BMDCs showed the upregulation of all monitored markers compared with the controls (Figure 6). Overall, the reaction of SILAC-labeled BMDCs to the activation stimulus was shown to be consistent with the current

image of the behavior of inflammatory DCs as linkers of innate and adaptive immunity. The BMDCs generated according to the introduced SILAC protocol should therefore represent a suitable model for in vitro DC quantitative proteomics.

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CONCLUSIONS In this study, we applied metabolic labeling with stable isotopes (SILAC) to primary BMDCs in search of a cell model applicable for quantitative DC proteomics. By avoiding the use of cell lines, we assume that the results obtained from primary cells will be more accurate and relevant to the in vivo situation. A primary origin, however, introduces several obstacles because the cells must be relatively long-lived to be sufficiently labeled (if they do not continuously proliferate), and the metabolism of isotopically labeled amino acids should be minimal. For shotgun proteomics, 13C- and 15N-isotopically labeled arginine and lysine are usually used. However, our first attempt to label GM-CSF-derived BMDCs with an Arg+10 [13C6, 15N4] and Lys +6 [13C6] amino acid configuration revealed the extensive metabolism of arginine, resulting in the formation of Pro+6 [13C6,15N1] and 15N-containing metabolic products, which were incorporated into the proteome during labeling. The later products caused the mass shifts and distortions in the isotopic patterns of virtually all peptides, an observation that had not been previously described. Further experiments proved that GM-CSF is the factor responsible for the unexpectedly high arginine turnover in BMDCs. It is known that the arginine-toproline conversion hampers the accurate estimation of the 759



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light/heavy peptide ratio, but the 15N-problem may have unpredictable consequences because the majority of proteomic/mass spectrometric software relies on the peptide isotopic distribution and accurate masses. This finding reveals a more general problem of SILAC experiments, and researchers should be aware of the influence that a treatment has on the metabolism of the labeled amino acids. On the basis of the available literature, we performed modifications to the cultivation procedure and were able to decrease the arginine metabolism issue to a level at which it does not pose a problem for SILAC-based proteomics of BMDCs. The efficiency of the metabolic labeling of primary BMDCs is reproducibly ≥90% for the majority of the proteome. Importantly, the necessary optimizations of the culture medium preserved the BMDCs functions. LPS treatment tests confirmed the immature state of the generated BMDCs, their ability to act in an innate-like manner in early interactions, and their adaptive immunitypriming characteristics in longer cocultivations. In summary, the described protocol for the generation of SILAC-labeled BMDCs facilitates the application of these cells as a suitable cell model for quantitative DC proteomics that offers both biological relevance and experimental feasibility.

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factor; IFN, interferon; IL, interleukin; IRF, interferon regulatory factor; LPS, lipopolysaccharide; M-CSF, macrophage colony-stimulating factor; MHC, major histocompatibility complex; MyD88, myeloid differentiation primary response gene (88); NF-κB, nuclear factor kappa-light-chain-enhancer of activated B cells; PE, phycoerythrin; TACE, TNF-converting enzyme; TLR, toll-like receptor; TNF, tumor necrosis factor; TRIF, TIR-domain-containing adapter-inducing interferon-β; SILAC, stable isotope labeling by amino acids in cell culture

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ASSOCIATED CONTENT

S Supporting Information *

Phenotypic characterization of GM-CSF-derived BMDCs. Impact of BMDC arginine metabolism on MALDI-TOF MS spectra. Effect of the arginine-to-proline conversion on heavy peptide signals during the SILAC labeling of BMDCs. Estimation of Arg+10-derived 15N incorporation rate. GMCSF-dependent induction of the arginine metabolism in BMDCs. Reproducibility of BMDC SILAC labeling by the modified cultivation protocol on the protein level. Upregulated proteins in BMDCs treated with LPS. Downregulated proteins in BMDCs treated with LPS. Concentrations of cytokines in the culture supernatant of BMDCs treated with LPS. This material is available free of charge via the Internet at http:// pubs.acs.org.

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REFERENCES

AUTHOR INFORMATION

Corresponding Author

*Tel: +420 973 255 199. Fax: +420 495 513 018. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We would like to thank Jana Balounova from Institute of Molecular Genetics of the ASCR, v. v. i. for help with preparation of the Ag8653 supernatant. The work was supported by research grants of Ministry of Education, Youth and Sports of Czech Republic 7AMB12GR038 and SV/ FVZ201107 and by a long-term organization development plan 1011.

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ABBREVIATIONS APC, antigen-presenting cell; BMDC, bone marow-derived dendritic cell; CSF-1R, macrophage colony-stimulating factor 1 receptor; DC, dendritic cell; FBS, fetal bovine serum; FITC, fluorescein isothiocyanate; Flt3L, FMS-like tyrosine kinase-3 ligand; GM-CSF, granulocyte/macrophage colony-stimulating 760



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Application of SILAC Labeling to Primary Bone Marrow-Derived

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