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First published online November 23, 2005; 10.1104/pp.105.071589 Plant Physiology 139:1995-2005 (2005) © 2005 American Society of Plant Biologists OPEN ACCESS ARTICLE
Metabolite Profiling of Chlamydomonas reinhardtii under Nutrient Deprivation1,[OA]Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany
A metabolite profiling technique for Chlamydomonas reinhardtii cells for multiparallel analysis of low-molecular weight polar compounds was developed. The experimental protocol was optimized to quickly inactivate enzymatic activity, achieve maximum extraction capacity, and process large sample quantities. As a result of the rapid sampling, extraction, and analysis by gas chromatography coupled to time-of-flight mass spectrometry, more than 800 analytes from a single sample could be measured, of which more than 100 could be identified. Analyte responses could be determined mostly with SEs less than 10%. Wild-type cells of C. reinhardtii strain CC-125 subjected to nitrogen-, phosphorus-, sulfur-, or iron-depleted growth conditions develop highly distinctive metabolite profiles. Individual metabolites undergo marked changes in their steady-state levels. Compared to control conditions, sulfur-depleted cells accumulated 4-hydroxyproline more than 50-fold, whereas the amount of 2-ketovaline was reduced to 2% of control levels. The contribution of each compound to the differences observed in the metabolic phenotypes is summarized in a quantitatively rigorous way by principal component analysis, which clearly discriminates the cells from different growth regimes and indicates that phosphorus-depleted conditions induce a deficiency syndrome quite different from the response to nitrogen, sulfur, or iron starvation.
With the recent completion of the Chlamydomonas reinhardtii genome project, a systems biology perspective, allowing the understanding of how the numerous components in a living system interact to comprise a functioning whole, comes into focus for this model organism, too. To this end, investigation of the world beyond mRNA abundance will be essential: Genes, proteins, and metabolites are all integrated into a seamless and dynamic network to sustain cellular functions (Kitano, 2002  ; Stelling et al., 2004).
Metabolomic analysis aims at the unbiased representation and quantitative determination of the suite of metabolites in a biological sample (Fiehn, 2002
Metabolic profiles reflect the dynamic response of the network of biochemical reactions to environmental, genetic, or developmental signals. As such, they are a valuable integrated measure of how a living system adjusts to a changing environment. This property has led to the successful application of large-scale analysis of metabolites in distinguishing between silent plant phenotypes (Weckwerth et al., 2004 Because of unsurpassed chromatographic separation power, sensitivity, and reproducibility, we have chosen gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF) to establish a method for analysis of metabolite levels of the unicellular green alga C. reinhardtii. Here, we report the detection of several hundred analytes from polar phase extracts of algal cells and the analysis of nutrient deprivation as a test case for metabolite profiling in Chlamydomonas.
A Protocol for Metabolite Analysis in Cell Cultures To obtain metabolomic data that correctly measure amount of substance and reflect the levels of intracellular metabolites, we followed a multistep procedure that conceptually can be divided into cell harvest and extraction, sample preparation for the acquisition of GC-TOF data, and processing of the analytical signal obtained. Harvest and extraction essentially comprise the injection of the cell suspension into a quenching solution to stop enzymic reactions, recovery of the cells by centrifugation, homogenization of the material, and metabolite extraction. GC-TOF samples are then prepared by further separating the crude extract into a lipophilic and a polar phase. Metabolites contained in the latter are concentrated and derivatized to increase compound volatility for separation of the complex mixture by gas chromatography. Once the samples have been measured by GC-TOF, the raw data chromatograms are processed to find analyte peaks, compare individual samples, and identify analytes by mass spectral comparison with custom mass spectral libraries of genuine compounds. The initial peak lists are filtered for false negatives, artifact peaks, and contaminants. Normalization to the amount of sample material and internal standards enables comparison and evaluation of the metabolic profiles.
Steady-state metabolite pools are the result of an equilibrium of catalyzed reactions. Environmental stimuli of any kind provoke rapid changes in metabolite concentrations, especially for intermediates that participate in reactions with high turnover rates. To generate an authentic picture of the metabolic composition of a biological system, it is therefore crucial to stop biochemical activity instantly as the material is removed from the original growth conditions for harvest. Whereas plant material can be flash-frozen in liquid nitrogen directly, the situation is different for suspension cultures. Although freezing of entire microbial cultures with subsequent analysis of the metabolite composition have been reported (Barsch et al., 2004
Taking up an approach originally suggested for rapid sampling of yeast cultures (de Koning and van Dam, 1992
To demonstrate that the quenching procedure does not compromise the integrity of the cells to an extent where significant leakage of intracellular matter into the quenching solution occurs, cells of a late log-phase culture were cultivated in TAP medium in the presence of labeled [U-14C]acetic acid as reduced carbon source. After 3 h of cultivation with the labeled substrate, cells were harvested and the culture medium containing the labeled substrate carefully removed. After equilibration of the cells for 15 min in TAP medium without labeled acetate, cells were subjected to the quenching procedure. To account for leakage due to centrifugation itself, aliquots of the equilibrated cell suspensions were centrifuged and the supernatants treated in parallel with the samples containing whole suspension aliquots. Both the walled wild-type strain CC-125 and the wall-less strain CC-400 were tested in this way (Table I).
After 3 h of growth, 19.5% and 8.7% of the entire amount of radioactivity remains with the cells of strain CC-125 and CC-400 after removal of the growth medium, washing, and equilibration in normal TAP medium, respectively. Of the incorporated radioactivity, 1.9% is found in the supernatant of CC-125 cells after quenching and immediate sedimentation of cells. Incubation of the cells in quenching solution for 30 min at –25°C prior to centrifugation increases this value to 2.4%. After centrifugation of the cell suspension and addition of the supernatant to the quenching solution, 1.3% of the activity can be found in the quenched sample. For the wall-less strain CC-400, 4.8% of the incorporated activity are found in the supernatant of the quenched sample. This value increases to 6.2% when the sample is stored for 30 min at –25°C prior to centrifugation. Addition of the supernatant of the centrifuged cell suspension to quench solution accounts for 2.0% of the activity. To ensure that the detection limit of 14C-scintillation would allow for spotting metabolite leakage exceeding 1% of the incorporated label, the amount of radioactivity added (20 kBq x mL–1 cell suspension) and the actual volume of cell suspension used for scintillation (125 µL) were chosen accordingly. These results indicate that even after prolonged handling of cells during quenching, leakage of intracellular substances is below an acceptable level. For the walled strain CC-125, this is well below 2%, whereas with the cell wall-deficient strain CC-400 leakage appears to be slightly higher. Still, also with CC-400 after 30-min suspension in methanol-water at –25°C, less than 5% of the activity taken up by the cells is lost as a result of quenching, if the activity in the supernatant of the quenched sample is corrected by the activity found in the control accounting for leakage due to mechanical stress during harvest.
Cells are collected by centrifugation at –20°C. After careful removal of the supernatant, the cell pellet is flash-frozen in liquid nitrogen, rendering it biologically inert. Prior to extraction, cells are homogenized by grinding the material under liquid nitrogen. The homogenized material is suspended at –20°C in methanol-chloroform-water (MCW) for extraction.
Composition of the extraction mixture was optimized to maximize extraction capacity, measured as the capacity to quantitatively extract chlorophyll and minimize the volume needed for extraction to concentrate extracted compounds (Fig. 1). As a result, the original extraction formulation of 10:4:4 (v/v/v) MCW, which had been used for extraction of plant material (Roessner et al., 2001
Extracts were used to prepare polar phase samples and acquire GC-TOF data as described previously (Roessner et al., 2001 ). In chromatograms of C. reinhardtii polar phase metabolite extracts, more than 800 analytes were detected routinely (Fig. 2A). Among the most prominent peaks we found Ala, pyruvate, Glu, glycerolphosphate, and adenosine 5'-monophosphate. Also, isotopically labeled sorbitol, which was introduced as an internal standard, and a number of unidentified analytes produced prominent peaks. Originating from residual culture medium, 2-amino-2-(hydroxymethyl)-1,3-propanediol (TRIS) and orthophosphate (Pi) were observed with very high detector signal intensities. The former regularly exceeded detector capacity, impeding analysis of analytes coeluting with the TRIS signal. Although reduction of TRIS peak size can be achieved by additional washes of the pelleted cells with quench solution (data not shown), we dispensed with additional washes, as this would require handling of cells for a prolonged period of time before rendering the material inert in liquid nitrogen and still yield chromatograms with a prominent TRIS peak.
GC-TOF chromatograms contain detector signal intensities for each mass-to-charge ratio (m/z) value in the chosen mass range for every spectrum acquired during the run. By mass spectral similarity and retention index comparison with custom libraries of authentic compounds, more than 100 of the detected peaks could be assigned a chemical structure, including amino acids, carbohydrates, phosphorylated intermediates, nucleotides, and organic acids. The diverse chemical nature of the compounds identified underlines the usefulness of this technique to detect metabolites in a multiparallel and unbiased manner. However, in such a complex mixture, chromatographic separation does not suffice to resolve all analytes. Instead, additional resolution and mass spectrum purification are achieved by mass spectral deconvolution. The deconvolution algorithm compares retention profiles and position of local maxima of fragment ion intensities to resolve overlapping peaks and computationally derive true mass spectra by identification of unique ions for each analyte peak (Fig. 2B). Identification of corresponding peaks from individual samples involves automatic peak finding and comparison against a reference chromatogram derived from a reference extract containing equal amounts of extract from all experimental groups involved. Peaks from individual chromatograms are assigned to the reference analytes by virtue of their mass spectral similarity and retention index match. Due to the complexity of the chromatograms, for most analytes mass spectra derived by automatic deconvolution differ from one chromatogram to the next to a certain extent. This is especially true when comparing different experimental groups that exhibit large differences in total metabolite composition. When setting rigid thresholds for mass spectrometric similarities and retention index match for peak assignment, this procedure may result in a large number of analytes not being reported from individual samples. To exclude such false negatives and ensure that missing values indeed are the consequence of the absence of any detectable analytical signal, all chromatograms in this study were corrected manually for the occurrence of false negative analytes.
To demonstrate the relevance of our approach, we decided to analyze how nutrient availability is reflected in metabolite profiles under conditions of nitrogen (N), sulfur (S), phosphorus (P), and iron (Fe) depletion, respectively. Table II shows metabolite peak area normalized to cell number and the internal standard [U-13C]sorbitol for a selection of 77 abundant primary metabolites after 24 h of nutrient starvation and for controls. Each metabolite is quantified by area integration of a characteristic fragment ion trace most suitable to distinguish the peak from local coeluting neighbor peaks. In addition, calibration curves are known to have different slopes (analytical sensitivity) for each metabolite, depending on ionization efficiency and detector response in the mass spectrometer. Therefore, to compare normalized peak areas of different peaks, metabolite-specific calibration curves have to be acquired. For the purpose of this study, comparisons are restricted to the differences of peak areas of the same metabolite in different conditions. A large number of metabolites undergo marked changes in at least one of the conditions applied. In Fe-deficient cells, the levels of succinate, threonic acid, and citrate all rise more than 2-fold, whereas the levels of Phe, Leu, Ser, Asn, Ala, and His, among other metabolites, drop to less than one-half of control levels. The increase of organic acids in roots, leaves, and xylem is a well documented response to Fe deficiency among higher plants. Specifically, the accumulation of citrate is implicated in mechanisms for Fe acquisition, formation of stable water-soluble complexes, cation/anion homeostasis, or supply of reducing power for ferric chelate reduction (for review, see Abadia et al., 2002
Apart from investigating differences in the levels of individual metabolites, factor analytic techniques can be used to quantitatively examine the sources of variation between different experimental conditions. Here, we used principal component analysis (PCA) to reduce the number of variables, classify metabolites, and obtain a multivariate measure of the variability of the metabolite profiles between different treatments and the relative homogeneity among replicate samples of each group. A data matrix of 170 metabolites, including both known compounds and unidentified analyte peaks, was manually inspected for false negatives and subsequently used for PCA. Projection of the resulting sample scores for the first and second principal components, which together account for 54% of the total sample variance, clearly separated the five experimental groups (Fig. 3), indicating a high suitability of metabolic readouts to study environmental effects in Chlamydomonas. It was apparent that the replicate analysis of samples of each individual treatment gave very similar profiles, which validates high reproducibility of the experimental procedure from cell harvest to data analysis. Distances between the groups of samples give a measure of the overall difference between the metabolite profiles of different treatments. Interestingly, score values for the first and second principal components for the –Fe, –N, and –S samples correlate. This suggests that the first two principal components, rather than explaining specific effects of adaptation to Fe, N, or S deprivation, measure parameters of the general response to nutrient deficiency with common effects in all three treatments with the most severe impact observed under S-depleted conditions. P deprivation, however, is transduced mainly as difference in score value for principal component two, suggesting that adjustment to P deficiency may share the general response developing in the other nutrient stress situations during 24-h treatment only to a limited extent. This notion is supported by the varying growth rates (controls: 1.6 doublings per day; –Fe: 1.6; –N: 0.7; –S: 0.7; and –P: 1.3) during the 24-h period of treatment. Besides cessation of growth, the regulation of photosynthetic electron transport has been characterized as a general response to adjust metabolism and sustain viability when nutrient levels fall (Grossman and Takahashi, 2001 ). While the decline of photosynthetic electron transport in N-deprived Chlamydomonas cells is due to the loss of the cytochrome b6f complex (Peltier and Schmidt, 1991), during P and S limitation cells undergo a transition of the photosynthetic apparatus to state 2, which allows them to more effectively dissipate excess absorbed excitation energy. Both conditions result in a 75% decrease of maximal O2 evolution that correlates with the reduction of electron flow through PSII, although with P deprivation a longer treatment is needed to observe the effect (Wykoff et al., 1998). The delayed response of P-deprived cells may be due to the mobilization of internal phosphate reserves. Chlamydomonas cells possess electron-dense vacuoles containing large amounts of pyrophosphate and short and long chain polyphosphate alongside with magnesium, calcium, and zinc (Ruiz et al., 2001). They presumably serve as Pi storage and buffer a critical Pi concentration in the cytoplasma, although also P-starved cells contain polyphosphate bodies of the normal size (Siderius et al., 1996) and most of the inorganic phosphate taken up by Pi-starved Chlamydomonas cells is still accumulated as polyphosphate (Hebeler et al., 1992). Therefore, it has been suggested that apart from Pi storage these organelles may serve also as internal calcium stores and may have a role in inositol-1,4,5-trisphosphate/calcium signaling (Siderius et al., 1996). The positional shift of the metabolite profiles for P-deprived cells after projection onto the plane defined by principal components 1 and 2 as compared to the other treatments may reflect the divergent alteration of metabolism due to the mobilization of internal Pi reserves and alleviation of external phosphate deficiency during the first 24 h of treatment. The contribution of individual metabolites to the differences observed is quantified via the loading of the metabolite for the respective principal component (Fig. 4). Among the group of metabolites with high absolute loading values for the first principal component are Glc-6-phosphate, Tyr, Trp, and yCR610 (high positive loadings), and glyceraldehyde-3-phosphate, Lys, and yCR535 (small negative loadings). A high positive loading value usually indicates abundance of these metabolites in samples with high score value for the corresponding principal component, whereas for small negative loading metabolite levels and score value are inversely correlated. This is confirmed for Tyr (PC1 loading = 0.098) with pool ratios increasing from 0.51 (–Fe) to 1.11 (–N) and 4.51 (–S), and for glyceraldehyde-3-phosphate (PC1 loading = –0.0829) with pool ratios decreasing from 1.22 (–Fe) to 0.98 (–N) and 0.50 (–S). TAP-cultured cells and –P cells, which are not very well discriminated by the first PC, nevertheless can be clearly separated using the linear combination of metabolite responses that constitutes the second principal component. Here, phosphoenolpyruvate, shikimate, and analyte yCR635 have among the highest loadings, whereas yCR758, N-acetyl-Orn, and maltotriose have very small loadings, indicating high discriminative power of these metabolites for TAP versus –P cultures in this set of five experimental groups.
In conclusion, metabolite profiling appears to be a well suited method to detect numerous changes of metabolite levels in response to environmental stimuli. The method introduced here will enable more refined experimental setups to detect more subtle changes in metabolite levels. This will be useful to derive specific hypotheses of how metabolic activity adjusts in response to external stimuli and also for investigation of Chlamydomonas mutants. The level of accuracy observed in this study suggests that Chlamydomonas may be highly suitable as a model for metabolomic research, especially in the context of photosynthetic processes. The possibility to control growth conditions precisely and to obtain large amounts of homogeneous sample material is a clear advantage in the attempt to study complex metabolic changes in fine-scaled gradients of conditions or with high temporal resolution.
Cell Culture Chlamydomonas reinhardtii strains CC-125 wt mt+ and CC-400 cw15 mt+ were acquired from the Chlamydomonas Genetics Center.
Strain CC-125 was cultured in TAP medium (Harris, 1989
Correlation between turbidity and cell density was verified in advance by hemocytometer cell count with an optical density (
Strains CC-125 and CC-400 were grown for 22 h from a starting density of 1 x 106 cells/mL in unlabeled TAP medium to a density of 6.8 x 106 cells/mL. Ten microliters of [U-14C]acetate (Amersham; 200 µCi mL–1) were added to 10 mL of the cell suspension, which was put back to the same culture conditions. After 3 h of incubation, cells were harvested by centrifugation for 5 min at 2,000g at 4°C. The culture supernatant was carefully removed and residual medium extracted with a pipette. Cells were gently resuspended in 10 mL of ice-cold (unlabeled) TAP medium to wash off all remaining activity from medium residuals and interstitial spaces. Resuspended cells were collected by centrifugation for 5 min at 2,000g at 4°C, and the supernatant was carefully removed. The pellet was resuspended in 10 mL of room-temperature (unlabeled) TAP and gently agitated on a shaker for 15 min in the light at room temperature to allow for equilibration of the cells after two rounds of centrifugation. Aliquots of 170 µL of the cell suspension were subjected to the quenching procedure described below. The quenched samples were prepared in six replicates: Cells of three of the samples were harvested after 3 min by centrifugation, whereas the other three were kept for 30 min at –25°C before pelleting. A total of 625 µL of the supernatant, corresponding to 125 µL of cell suspension, was used for scintillation. Measurements of the total amount of incorporated radioactivity were made by using 125 µL of the washed and equilibrated cell suspension with an addition of 500 µL of quench solution directly for scintillation. Control samples for leakage inflicted by the centrifugation itself were prepared by harvesting an aliquot of the washed and equilibrated cell suspension at 2,500g for 5 min at 4°C and subjecting the supernatant to quenching in parallel with the cell suspension. Using 10 mL of scintillation cocktail (Ready Safe; Beckman Coulter) per sample, scintillation for 14C was performed on an LS 6500 scintillation counter (Beckman Coulter).
HPLC-grade methanol and chloroform were supplied by Merck. MSTFA was supplied by Macherey-Nagel. [U-13C]Sorbitol was purchased from Isotec. All other chemicals, in the highest grade available, were supplied by Sigma-Aldrich.
At the incubation site, the cell suspension was injected into a stirred solution composed of 32.5% methanol in water supplied with 300 µM CaCl2, 400 µM MgCl2, and 7 mM KCl, which corresponds to the molarity of macro salts in standard TAP medium. The solution was prechilled at –25°C and used at a ratio of 4:1 (v/v) of quenching solution to cell suspension for rapid cooling of cells. During injection, the quenching solution was stirred for rapid dilution of injected cells. Centrifuge tubes containing the solution during harvest were cooled in an ethanol/dry ice bath to keep sample temperature below –20°C. Cells were collected by centrifugation at 2,500g for 5 min with the centrifuge and rotor precooled at –20°C. Supernatant was decanted and residual liquid carefully removed. The pellet was flash-frozen in liquid nitrogen. Throughout homogenization of the recovered material with pestle and mortar, the preparation was kept in a bath of liquid N2. Cells were extracted by adding 8.33 mL per 109 cells of MCW (10:3:1, v/v/v) prechilled at –20°C.
Further processing of the extract, including removal of particulate material, phase separation by addition of 0.4 volume parts water, centrifugation, solvent evaporation to complete dryness, and methoxyamine/trimethylsilylation derivatization, was carried out as described earlier (Roessner et al., 2001
Chromatographic files were processed with ChromaTOF software (Leco). Samples were compared to reference chromatograms containing equal amounts of extract from all experimental groups involved and peaks were reported at a signal to noise ratio of 20. Analyte spectra were searched against custom spectrum libraries and identified based on retention index and spectrum similarity match. Peak lists were checked for false negatives and artifact peaks removed. Peak area was normalized to cell number and internal standard [U-13C]sorbitol. PCA was carried out after standardization of the data using the functions provided in Matlab 6.5 (Mathworks).
We thank the Chlamydomonas Genetics Center for providing the C. reinhardtii wild-type and mutant strains. We also would like to thank Aenne Eckardt for excellent technical assistance, and Prof. Lothar Willmitzer for valuable and helpful discussions. Received September 16, 2005; returned for revision September 16, 2005; accepted October 13, 2005.
1 This work was supported by the Max Planck Society. 
2 Present address: University of California Davis Genome Center, 4321 GBSF Building, Health Sciences Drive, Davis, CA 95616. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Christian Bölling (boelling{at}mpimp-golm.mpg.de).
[OA] Open Access articles can be viewed online without a subscription. Article, publication date, and citation information can be found at www.plantphysiol.org/cgi/doi/10.1104/pp.105.071589. * Corresponding author; e-mail boelling{at}mpimp-golm.mpg.de; fax 49–(0)331–567–8250.
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= 750 nm) of one corresponding to 1.5 x 107 cells/mL. Chlorophyll a and b levels were determined spectrophotometrically (Wintermans and Demots, 1965
