Metabolic labeling of plant cell cultures with K15NO3 as a tool for quantitative analysis of proteins and metabolites
© Engelsberger et al; licensee BioMed Central Ltd. 2006
Received: 14 August 2006
Accepted: 04 September 2006
Published: 04 September 2006
Strategies for robust quantitative comparison between different biological samples are of high importance in experiments that address biological questions beyond the establishment of protein lists. Here, we propose the use of 15N-KNO3 as the only nitrogen source in Arabidopsis cell cultures in order to achieve a metabolically fully labeled cell population. Proteins from such metabolically labeled culture are distinguishable from unlabeled protein populations by a characteristic mass shift that depends on the amino acid composition of the tryptic peptide analyzed. In addition, the metabolically labeled cell extracts are also suitable for comparative quantitative analysis of nitrogen-containing cellular metabolic complement. Protein extracts from unlabeled and from standardized 15N-labeled cells were combined into one sample for joined analytical processing. This has the advantage of (i) reduced experimental variability and (ii) immediate relative quantitation at the level of single extracted peptide and metabolite spectra. Together ease and accuracy of relative quantitation for profiling experiments is substantially improved. The metabolic labeling strategy has been validated by mixtures of protein extracts and metabolite extracts from the same cell cultures in known ratios of labeled to unlabeled extracts (1:1, 1:4, and 4:1). We conclude that saturating metabolic 15N-labeling provides a robust and affordable integrative strategy to answer questions in quantitative proteomics and nitrogen focused metabolomics.
Plants adjust to developmental and environmental variability with respective changes in protein abundance and enzyme activity. Thus, protein expression and metabolite pools in cells can be highly dynamic and the abundance and activity of specific proteins can vary greatly during growth and development or in response to biotic and abiotic stress. Therefore, it is of great biological interest to be able to quantitatively compare the subproteomes of different developmental stages or to quantitatively examine the dependent or independent responses of metabolic or signaling pathways under specific conditions. Thus combined analysis of metabolites and proteins may yield novel information about regulatory processes in plants .
Liquid-chromatography coupled mass spectrometry has in the recent years become a widely applied tool in quantitative proteomic approaches also in plant sciences [2–4]. Mass spectrometry is especially powerful to identify and quantitate changes in post-translational modifications, which often play important roles in protein function and regulation [5, 6]. However, quantitative comparisons between independent samples remain a challenging task. Label-free approaches termed 'protein correlation profiling' rely on the relative quantitation of ion intensities between independent LC-MS/MS runs require accurate reproducibility of retention times in combination with elaborate data analysis [7, 8]. Other label-free techniques use the number or recorded spectra for each protein as a comparative measure [9, 10].
Due to difficulties in peak assignments between independent LC-runs of complex mixtures, many quantitative proteomic strategies rely on the incorporation of stable isotopes into proteins or peptides, which are then quantitatively compared to an unlabeled control sample based on their mass spectra . Relative protein abundance can be calculated from the intensities of the labeled versus the unlabeled labeled forms of the same tryptic peptides in the same mass spectrum (for review see [12, 13]). Stable isotope labeling of protein samples can in principle be achieved by chemical modification of proteins and tryptic peptides. Initially, 18O labeling was used to differentially label peptides of protein samples during the digest with trypsin . This approach is still used today for relative comparison between two samples [4, 15]. Later, isotope coded affinity reactive tags were developed which tag specific amino acid species and allow for specific enrichment of the labeled tryptic peptides . This variety of tags has successfully been used in an number of comparative proteomic studies involving comparisons of changes in protein abundances [17–19] or characterizing changes in posttranslational modifications [20, 21]. Furthermore, stable isotope labeled synthetic peptides are being used as internal standard peptides for a variety of targeted assays involving quantitative mass spectrometry [22, 23]. However, the drawbacks of chemical labeling strategies are that only a rather small subset of tryptic peptides are being tagged and that experimental variability may be introduced during the labeling processes.
The first studies making use of metabolic labeling for protein quantitation by mass spectrometry relied on growth of bacterial or yeast cells on 15N-enriched medium [24, 25]. However, since the mass shift introduced by 15N labeling depends on the amino acid composition of each tryptic peptide, knowledge of the peptide sequence is necessary to calculate the expected mass difference to the labeled or unlabeled partner. Thus, full metabolic labeling has recently been widely replaced by labeling of only specific amino acids (SILAC), such as lysine, arginine or leucine to introduce a fixed mass shift between labeled and unlabeled peptide pairs [26–28]. SILAC works especially well with mammalian cell cultures to which essential amino acids can easily be supplied in a stable isotope labeled form and full incorporation into the proteome of the cells is ensured. In yeast, auxotrophic mutants inhibited in the synthesis of arginine or lysine have been used for full incorporation of stable isotope labeled amino acids. The SILAC approach has successfully been applied to quantitative proteomic studies of the formation of signal-dependent protein complexes , in modification-dependent protein-protein interaction screens [30, 31], and to analyses of the dynamics of signal-dependent phosphorylation events [32–34]. In plants, labeling of arginine, lysine or leucine has also been achieved using cell cultures , and an average of 70% to 80% incorporation of the metabolic label was obtained. Possibly, by using auxotrophic mutants in certain amino acid synthesis pathways, higher degrees of labeling may be feasible. In general it has to be considered that SILAC labeling is a costly exercise, especially if high concentrations of amino acids need to be supplied, such as for plant cell cultures.
Therefore, in plant biology, quantitative proteomic approaches so far mainly relied on chemical modification of proteins to study membrane lipid rafts , on 18O labeling in tryptic digests, e.g. to characterize purity of plant plasma membrane purifications , or on label-free quantitation by spectrum count as comparison between independent samples . More recently, the iTRAQ reagent can be used in studies comparing more than two samples . However, metabolic labeling strategies of whole proteomes have the advantage over chemical labeling that samples to be compared can be processed together through the complete analytical process from extraction of combined biological samples, isolation of metabolic or proteomic complements to quantitative analysis. Since biochemical techniques, such as the isolation of proteins, their fractionation and enrichment introduce much more heterogeneity than what is known from analyses of mRNA, reduction of sample variability is of great importance . Also for metabolites, comparative quantitation to date relies on the analysis of a large number of replica samples . Only recently has the use of 13C-labeling been proposed as a strategy for quantitative analysis of metabolite profiles [39, 40]. In addition N labeling in plants has been successfully applied to flux studies and tracer analysis indicating the feasibility of generating saturated N labeled metabolomes [41, 42].
In complementation to metabolic N-flux analysis, we propose the use of full 15N-labeling of plant cell cultures in comparative quantitative proteomics and metabolomic approaches as a cheaper alternative to SILAC labeling and a more robust and accurate method for quantitation compared to label-free protein correlation profiling. For the reasons noted above, 15N-labeling of intact plant has yet only been applied to analysis of proteins by NMR  or metabolic flux studies [41, 42], which do not require full incorporation of the label. In addition, the approach described here is the first example of a labeling strategy that can be robustly applied to the protein and metabolite complement of the same sample.
Results and discussion
Since first proteomic experiments involving metabolic labeling with 15N involved growth of yeast cells in 14N and 15N medium for the quantitation of phosphorylation , the technique of 15N-labeling for proteomic research had mostly remained in the field of microbiology. Exceptions are studies using 15N-labeled microorganisms as a food source for metabolically labeling Drosophila  and 15N-labeling of rats by the use of 15N-labeled algal food . In this proof-of-principle study, we use 15N-labeling to quantify protein and metabolite abundance in known mixtures of labeled and unlabeled cells.
Quantitative analysis of known mixtures of protein extracts
Proteins and the corresponding peptides identified in unlabeled protein extract (14N extract) and 15N labeled extract (15N extract) in two consecutive database searches without (14N search) and with (15N search) 15N as a fixed modification.
Overview of the intensity ratio of 14N and 15N tryptic peptide pairs and the number of proteins identified in the two database searches.
ID in 14N search
ID in 15N search
0.89 ± 0.2
5.69 ± 2.0
0.29 ± 0.1
A subset of tryptic peptides from glyceraldehyde-3-phosphate dehydrogenase C subunit (At3g04120) that were identified by mass spectrometry and subsequent database search (14N-search, see methods for details). For each peptide the expected mass difference was calculated based on the measured mass to charge ratio (MCR). Asterisks mark those peptides that have also been identified in the database search with 15N as fixed modification (15N-search, see Methods for details)
measured mass 14N
MCR 14N [Th]
calculated mass difference
calculated mass 15N
MCR 15N [Th]
Overview of the costs of SILAC labeling and full 15N-labeling for plant cell culturesa. Depending on the compounds and concentrations used in the medium, K15NO3 labeling is 7 to 12 times cheaper per liter medium.
Amount in package (g)
Cost per package (€)
Cost per g (€)
Final concentration in medium (mM)
Price per L (€)
Quantitative analysis of known mixtures of metabolic extracts
For metabolites, quantitation was based on the ion intensities of characteristic fragment ions . In total, among the nitrogen-containing compounds, 14 amino acids (ala, asp, cys, glu, gly, ile, lys, met, phe, pro, thr, trp, tyr, val) and two polyamines (spermidine, putrescine) were analyzed. We estimated an average of 91% incorporation of 15N-label into metabolites, ranging from 70% for alanine to the maximally achievable 98% for tryptophan and putrescine.
Measured ratios of 15N/14N forms of metabolite fragment peaks in 1:1 mixtures of labeled and unlabeled extracts compared to their expected values. Expected ratios were calculated based on the fragment spectra ratios in the unmixed extracts (14N-extract, 15N-extract). The difference of the measured values to the expected values is expressed as percentage of the expected value.
difference to expected (%)
The examples of different metabolite pool sizes (ala, met, glu, putrescine) in the 14N-cells compared to the 15N-cells actually reflect the true experimental situation, in which two cell extracts of unknown concentrations would be mixed in a 1:1 ratio, and those compound differing significantly from a 1:1 ratio of the ion intensities are concluded to be of different pool size in the original cells. The same experimental strategy generally also applies to proteins, and has already been successfully been used to detect proteins specifically interacting with a bait protein or peptide from background interaction partners or to describe temporal changes in protein abundance [29, 30, 32]. However, in the experiments described here, no variation between proteins was observed, since protein extracts were mixed based on total protein content, while for metabolite analysis, frozen cell material was mixed on a fresh weight basis (see Methods for details). Thus, the labeling and mixing strategy described here is well suitable for accurate detection of small changes and also ideal for screening for large deviations from an expected ratio, e.g. in presence/absence studies.
Alternative labeling strategies
A drawback of the 15N-labeling strategy for metabolomic analyses can be seen in the fact that quantitative information can only be obtained for nitrogen-containing metabolites. Thus, for quantitative information of a full metabolite profile, metabolic labeling with 13C would be a more promising strategy, as has already been proposed in an experiment using yeast cells . However, for protein analysis full 13C-labeling is not suitable: The high proportion of carbon atoms in tryptic peptides would lead to very large mass differences between labeled and unlabeled peptides making unambiguous detection of labeled and unlabeled ion pairs very difficult.
In this study we used K15NO3 to metabolically label plant cell cultures for comparative proteomic and metabolomic experiments. We demonstrate that quantitative comparison using mixtures of labeled and unlabeled cell extracts is (i) approximately 10-times less expensive per liter of cell culture compared to SILAC labeling for plants or the iTRAQ reagent and (ii) accurate at the level of single mass spectra. Data supporting quantitative statistics are generated at the level of single mass spectra for peptides and those metabolites which comprise the N-metabolome. It is (iii) the first approach describing possibilities of a joined quantitative analysis utilizing mass isotopomer ratios of proteins and metabolites from the same cell extract. Thus, we believe that metabolic 15N-labeling may be applied to a wide range of biological questions in plant science which require quantitative proteomic and metabolomic analysis.
Metabolic labeling of cell cultures
Arabidopsis cell cultures derived from leaves  were grown in JPL medium  with 19 mM potassium nitrate as the sole nitrogen source. Potassium nitrate was supplied either in normal form or in 15N-enriched form (98 atom% K15NO3, Sigma-Aldrich). Cells were subcultured every 7 days using 10% of the culture volume. The remaining cells were harvested by suction over a filter plate and frozen at -80°C.
Protein extracts and mixing
Frozen cells were ground and extracted in 50 mM TRIS-HCl pH 7.5, 1% NP-40, and a protease inhibitor mixture (Complete Tabs, Roche). Cell debris was pelleted by centrifugation and 200 μg of Protein was precipitated with TCA. Protein was resuspended in a small volume (approx. 20μL) of 6 M Urea/2 M thiourea pH8 and in-solution digested with trypsin after reduction in DTT, alkylation with iodoacetamide and dilution of the sample with 4 volumes of 50 mM NH4HCO3 was performed as described .
Mass spectrometric analysis of proteins and database search
Tryptic peptide mixtures were then desalted on STAGE tips  before LC-MS/MS analysis using nanoflow HPLC (Proxeon Biosystems, Odense, Denmark) and a linear ion trap instrument (LTQ, Thermo Electron, San Jose, CA, USA) as mass analyzer. Peptides were eluted from the analytical column (Reprosil C18, Dr. Maisch GmbH, Tübingen, Germany) by a linear gradient running from 10 % to 50 % acetonitrile in 110 minutes and sprayed directly into the LTQ mass spectrometer. Proteins were identified by tandem mass spectrometry (MS/MS) by information-dependent acquisition of fragmentation spectra of multiple-charged peptides. Additional data-dependent fragmentation (MS3) was used to confirm identity of ambiguous proteins . Fragment spectra were then searched against a non-redundant version of the Arabidopsis protein Database (TIGR6) using the Mascot algorithm (Matrix Science, UK, http://www.matrixscience.com). The following search parameters were applied: Peptide mass tolerance 800 ppm, MS/MS tolerance 0.8 Da, methionine oxidation and carbamidomethylation of cysteine were set as variable modifications. For each sample, two database searches were carried out, one without fixed modifications ('14N-search') and one with 15N-amino acids as a fixed modification ('15N-search').
Quantitative analysis of protein
Metabolite extraction and sample preparation
Metabolites were extracted from 120 mg cell material, which was shock frozen in liquid nitrogen and ground to a fine powder. Alternately different ratios of labeled and non labeled powder were combined to a final amount of 120 mg and subsequently treated as a single sample. Care was taken to keep samples frozen during manipulation. Frozen material was extracted with 360 μL methanol. Extraction temperature was 70°C. 200 μL chloroform and 400 μL water were added for partitioning polar metabolites as described . Polar extracts were dried in a vacuum concentrator over night. Derivatization was conducted with 10 μL 20 mg mL-1 methoxyamine hydrochloride/pyridine, and 17.5 μL 20 mg mL-1 N-methyl-N-(trimethylsilyl)-trifluoroacetamide. A mixture of alkanes was added for calculation of retention time indices .
Mass spectrometric analysis of metabolites
GC-MS based metabolite profiling performed according to the procedure described previously . Briefly, 1μL of sample was injected at 230°C into a GC 6890 (Agilent Technologies, Palo Alto, CA, USA) gas chromatograph mounted with a Rtx-5Sil MS capillary column, 30 m × 0.25 mm inner diameter with 0.25 μm film thickness, and a 10 m integrated guard column (Restek GmbH, Bad Homburg, Germany). The temperature program comprised 1 min at 70°C, a 9°C min-1 ramp to 350°C, and 5 min at 350°C. The transfer line to the mass-spectrometer was set to 250°C. Carrier gas was helium at a flow rate of 0.6 mL min-1 and operated at constant flow. A time-of-flight mass-spectrometer was used, Pegasus III TOF-MS system (Leco, St. Joseph, MI, USA) with the electron impact ionization source set to -70 eV and 250°C. Data acquisition was set to 20 spectra s-1 and the mass range restricted to m/z = 70–600. All other settings of the mass spectrometer were according to manufacturer's instructions. Chromatograms were acquired, deconvoluted and processed with ChromaTOF™ software (LECO, St. Joseph, MI, USA). Metabolites were identified using the GMD library (Golm Metabolome Database, http://csbdb.mpimp-golm.mpg.de/csbdb/gmd/gmd.html; [57, 58]). Mass spectral and RI comparison was performed by NIST02 (National Institute of Standards and Technology, Gaithersburg, MD, USA) mass spectral search and comparison software accepting mass spectral matches >650 on a scale of 1000 and retention time index matches ± 5.0 RI units. Mass spectra and fragmentation pattern of amino acid derivatives were interpreted as described  in order to identify 15N-labeled forms of the respective amino acids.
Quantitation of metabolites
Absolute ion currents and ratios in ion intensities of metabolites were directly derived from mass spectral fragmentation pattern exported from the ChromaTOF™ software. If available, for each metabolite, more than one fragment ion was used for quantitation . For each sample type (original cell cultures, and the three mixtures), five independent samples were analyzed and the ion intensities for each fragment ion were averaged across the five replica samples.
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