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Biochemistry

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

doi: 10.3791/62061 Published: January 5, 2021
Karamat Mohammad1, Heng Jiang2, Vladimir I. Titorenko1

Abstract

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within a cell, tissue, organ, biological fluid, or organism. Metabolomics traditionally focuses on water-soluble metabolites. The water-soluble metabolome is the final product of a complex cellular network that integrates various genomic, epigenomic, transcriptomic, proteomic, and environmental factors. Hence, the metabolomic analysis directly assesses the outcome of the action for all these factors in a plethora of biological processes within various organisms. One of these organisms is the budding yeast Saccharomyces cerevisiae, a unicellular eukaryote with the fully sequenced genome. Because S. cerevisiae is amenable to comprehensive molecular analyses, it is used as a model for dissecting mechanisms underlying many biological processes within the eukaryotic cell. A versatile analytical method for the robust, sensitive, and accurate quantitative assessment of the water-soluble metabolome would provide the essential methodology for dissecting these mechanisms. Here we present a protocol for the optimized conditions of metabolic activity quenching in and water-soluble metabolite extraction from S. cerevisiae cells. The protocol also describes the use of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of the extracted water-soluble metabolites. The LC-MS/MS method of non-targeted metabolomics described here is versatile and robust. It enables the identification and quantification of more than 370 water-soluble metabolites with diverse structural, physical, and chemical properties, including different structural isomers and stereoisomeric forms of these metabolites. These metabolites include various energy carrier molecules, nucleotides, amino acids, monosaccharides, intermediates of glycolysis, and tricarboxylic cycle intermediates. The LC-MS/MS method of non-targeted metabolomics is sensitive and allows the identification and quantitation of some water-soluble metabolites at concentrations as low as 0.05 pmol/µL. The method has been successfully used for assessing water-soluble metabolomes of wild-type and mutant yeast cells cultured under different conditions.

Introduction

Water-soluble metabolites are low-molecular-weight intermediates and products of metabolism that contribute to essential cellular processes. These evolutionarily conserved processes include the conversion of nutrients into usable energy, synthesis of macromolecules, cellular growth and signaling, cell cycle control, regulation of gene expression, stress response, post-translational regulation of metabolism, maintenance of mitochondrial functionality, vesicular cellular trafficking, autophagy, cellular aging, and regulated cell death1,2,3.

Many of these essential roles of water-soluble metabolites have been discovered by studies in the budding yeast S. cerevisiae1,3,4,7,9,14,15,16,17,18,19,20,21,22. This unicellular eukaryote is a useful model organism for dissecting mechanisms through which water-soluble metabolites contribute to cellular processes due to its amenability to advanced biochemical, genetic, and molecular biological analyses23,24,25,26. Although the LC-MS/MS methods of non-targeted metabolomics have been used for studying the roles of water-soluble metabolites in budding yeast3,18,22,27, this type of analysis requires the improvement of its versatility, robustness, sensitivity, and ability to distinguish between different structural isomers and stereoisomeric forms of these metabolites.

Recent years are marked by significant advances in applying the LC-MS/MS methods of non-targeted metabolomics to the profiling of water-soluble metabolites in vivo. However, many challenges in using this methodology remain2,28,29,30,31,32,33,34,35,36. These challenges include the following. First, the intracellular concentrations of many water-soluble metabolites are below a threshold of sensitivity for the presently used methods. Second, the efficiency of metabolic activity quenching is too low, and the extent of quenching-associated cell leakage of intracellular metabolites is too high for current methods; hence, the presently used methods under-estimate the intracellular concentrations of water-soluble metabolites. Third, the existing methods cannot differentiate the structural isomers (i.e., molecules with the same chemical formula but different atomic connectivity) or stereoisomers (i.e., molecules with the same chemical formula and atomic connectivity, but with the different atomic arrangement in space) of specific metabolites; this prevents the correct annotation of certain metabolites by the presently used methods. Fourth, the existing mass spectral online databases of parent ions (MS1) and secondary ions (MS2) are incomplete; this affects the correct identification and quantitation of specific metabolites using the raw LC-MS/MS data produced with the help of the current methods. Fifth, the existing methods cannot use a single type of metabolite extraction to recover all or most classes of water-soluble metabolites. Sixth, the existing methods cannot use a single type of the LC column to separate from each other all or most classes of water-soluble metabolites.

Here, we optimized conditions for quenching of metabolic activity within S. cerevisiae cells, maintaining most of the water-soluble metabolites within these cells before extraction, and extracting most classes of water-soluble metabolites from yeast cells. We developed a versatile, robust, and sensitive method for the LC-MS/MS-based identification and quantification of more than 370 water-soluble metabolites extracted from S. cerevisiae cells. This method of non-targeted metabolomics enables to assess the intracellular concentrations of various energy carrier molecules, nucleotides, amino acids, monosaccharides, intermediates of glycolysis, and tricarboxylic cycle intermediates. The developed LC-MS/MS method permits the identification and quantification of different structural isomers and stereoisomeric forms of water-soluble metabolites with diverse structural, physical, and chemical properties.

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Protocol

1. Making and sterilizing a medium for growing yeast

  1. Make 180 mL of a complete yeast extract with bactopeptone (YP) medium. The complete YP medium contains 1% (w/v) yeast extract and 2% (w/v) bactopeptone.
  2. Distribute 180 mL of the YP medium equally into four 250 mL Erlenmeyer flasks. Each of these flasks contains 45 mL of the YP medium.
  3. Sterilize the flasks with YP medium by autoclaving at 15 psi/121 °C for 45 min.

2. Wild-type yeast strain

  1. Use the BY4742 (MATα his3Δ1 leu2Δ0 lys2Δ0 ura3Δ0) strain.

3. Growing yeast in the YP medium containing 2% glucose

  1. Sterilize a 20% (w/v) stock solution of glucose by autoclaving at 15 psi/121 °C for 45 min.
  2. Add 5 mL of the autoclaved 20% (w/v) stock solution of glucose to each of the two Erlenmeyer flasks with 45 mL of the sterilized YP medium. The final concentration glucose in the YP medium is 2% (w/v).
  3. Use a microbiological loop to inoculate yeast cells into each of the two Erlenmeyer flasks with the YP medium containing 2% glucose.
  4. Grow the yeast cells overnight at 30 °C in a rotational shaker set at 200 rpm.
  5. Take an aliquot of yeast culture. Determine the total number of yeast cells per mL of culture. Count cells using a hemocytometer.

4. Cell transfer to and cell grows in the YP medium with 2% glucose

  1. Add 5 mL of the sterilized 20% (w/v) stock solution of glucose to each of the remaining two Erlenmeyer flasks with the autoclaved YP medium. The final concentration of glucose is 2% (w/v).
  2. Transfer a volume of the overnight yeast culture in YP medium with 2% glucose that contains the total number of 5.0 x 107 cells into each of the two Erlenmeyer flasks with the YP medium containing 2% glucose. Use a sterile pipette for the cell transfer.
  3. Grow the yeast cells for at least 24 h (or more, if the experiment requires) at 30 °C in a rotational shaker set at 200 rpm.

5. Making reagents, preparing labware, and setting up equipment for cell quenching

  1. Prepare the following: 1) a quenching solution (60% high-grade (>99.9%) methanol in 155 mM ammonium bicarbonate (ABC) buffer, pH = 8.0); 2) an ice-cold ABC solution (pH = 8.0); 3) a digital thermometer capable of measuring up to -20 °C; 4) 500 mL large centrifuge bottles; 5) a pre-cooled high-speed centrifuge with a pre-cooled rotor and pre-cooled 500 mL centrifuge bottles for this rotor, all at -5 °C; 6) metabolite extraction tubes (15 mL high-speed glass centrifuge tubes with polytetrafluoroethylene lined caps); and 7) dry ice.

6. Cell quenching

  1. Use a hemocytometer to determine the number of yeast cells per mL of YP with 2% glucose culture.
  2. Transfer a volume of the culture in YP medium with 2% glucose that contains the total number of 5.0 x 108 cells into pre-cooled 500 mL centrifuge bottles.
  3. Quickly fill the centrifuge bottle containing the cells up to the volume of 200 mL with a quenching solution stored at -20 °C.
  4. Centrifuge the bottles in a high-speed centrifuge at 11,325 x g for 3 min at -5 °C.
  5. Quickly and tenderly recover the bottle from the centrifuge; gently unscrew the lid and remove the supernatant without disturbing the pellet.
  6. Quickly resuspend the cell pellet in 10 mL of ice-cold ABC buffer and transfer the suspension into a 15 mL high-speed glass centrifuge tube with a polytetrafluoroethylene-lined cap for metabolite extraction.
  7. Collect cells by centrifugation in a clinical centrifuge at 3,000 x g for 3 min at 0 °C.
  8. Quickly remove the supernatant and place the tube on dry ice to begin metabolite extraction or store the tube at -80 °C until extraction.

7. Preparation of reagents, labware and equipment for metabolite extraction

  1. Prepare the following: 1) LC-MS grade chloroform; 2) LC-MS grade methanol; 3) LC grade nano-pure water; 4) LC-MS grade (ACN); 5) glass beads (acid-washed, 425-600 µm); 6) a vortex with a foam tube holder kit with retainer; 7) 15 mL high-speed glass centrifuge tubes with polytetrafluoroethylene-lined caps; 8) MS vials; 9) dry ice; and 10) 1.5 mL tubes washed once with ethanol, once with ACN and once with nano-pure water.
    ​NOTE: Use only micropipette tips and tubes made of polypropylene that is resistant to organic solvents.

8. Metabolite extraction

  1. To the metabolites kept on dry ice or stored at -80 °C tube from step 6.7, add the following: 1) 2 mL of chloroform stored at -20 °C; 2) 1 mL of methanol stored at -20 °C; 3) 1 mL of ice-cold nano-pure water; and 4) 200 µL of 425-600 µm acid-washed glass beads.
  2. Cover and close the mouth of a tube with aluminum foil. Place tubes in a foam tube holder kit with retainer and vortex them for 30 min at medium speed (i.e., at a speed that is set at 6, with 12 being the maximum speed of a vortex) at 4 °C to facilitate metabolite extraction.
  3. Incubate the tube for 15 min on ice (NOT dry ice!) to promote protein precipitation and the separation of the upper aqueous from the lower organic phase.
  4. Centrifuge the tube in a clinical centrifuge at 3,000 x g for 10 min at 4 °C. This centrifugation step allows separating the upper aqueous phase (which contains water-soluble metabolites) from the middle layer (which contains cell debris and proteins) and from the lower organic phase (which contains mostly lipids).
  5. Use a micropipette to transfer the upper aqueous phase (400 µL) to a washed and labeled 1.5 mL tube containing 800 µL of ACN that was stored at -20 °C.
    NOTE: There will be white cloud precipitation after adding the upper aqueous phase to ACN kept at -20 °C.
  6. Centrifuge the tube with the sample in a tabletop centrifuge at 13,400 x g for 10 min at 4 °C.
    ​NOTE: The white cloud precipitation will disappear after centrifugation.
  7. Transfer 800 µL from the upper portion of a liquid in the tube to a labeled MS vial. Store the sample at 0 °C until it is analyzed by LC-MS/MS.

9. Preparation of reagents, labware, and equipment for LC

  1. Prepare the following: 1) a vortex; 2) an ultrasonic sonicator; 3) MS glass vials; 4) an LC system equipped with a binary pump, degasser, and autosampler; 5) a zwitterionic-phase chromatography column (5 µm polymer, 150 x 2.1 mm) named in Table of Materials; 6) a column heater; and 7) mobile phases, including phase A (5:95 ACN:water (v/v) with 20 mM ammonium acetate, pH = 8.0) and phase B (100% ACN).

10. Separation of extracted metabolites by LC

  1. Subject the content of the MS vial to ultrasonic sonication for 15 min.
  2. Vortex the MS vial 3x for 10 sec at room temperature (RT).
  3. Place the MS vial into the well plate.
  4. During chromatograph, maintain the column at 45 °C and a flow rate of 0.250 mL/min. Keep the sample in the well plate at 0 °C. Refer to Table 1 for the LC gradients that need to be used during chromatography.
    NOTE: A representative total ion chromatogram of water-soluble metabolites that were extracted from cells of the wild-type strain BY4742 is shown in Figure 1. The metabolites separated by LC were identified and quantified by mass spectrometric analysis that was performed in positive ionization [ESI (+)] mode, as described for step 11.

11. Mass spectrometric analysis of metabolites separated by LC

  1. Use a mass spectrometer equipped with heated electrospray ionization (HESI) for the identification and quantitation of water-soluble metabolites that were separated by LC. Use the mass spectrometer's analyzer for MS1 ions and the mass spectrometer's detector for MS2 ions. Use the settings provided in Table 2 and Table 3 for the data-dependent acquisition of MS1 and MS2 ions, respectively.
  2. Use a sample volume of 10 µL for the injection in both the ESI (+) and ESI (-) modes.

12. Identification and quantitation of different metabolites by the processing of raw data from LC-MS/MS

  1. Use the software named in Table of Materials to conduct the identification and quantitation of different water-soluble metabolites from raw LC-MS/MS files. This software uses MS1 for metabolite quantitation and MS2 for metabolite identification. The software exploits the most extensively curated mass spectral fragmentation library to annotate the metabolites using the LC-MS/MS raw data by matching MS spectra. This software also uses the exact mass of MS1 and isotope pattern match to annotate metabolites using online databases. See Figure 2 for details.
  2. Use the library of databases and spectra, which is freely available online (https://www.mzcloud.org), to search for MS2 spectra of the raw data.

13. Membrane integrity assay by propidium Iodide (PI) staining and fluorescence microscopy

  1. After cell quenching performed as described for step 6, wash the quenched cells thoroughly with 15 mL of ABC buffer to remove the quenching solution. Collect cells by centrifugation at 3,000 x g for 5 min at 0 °C.
  2. Resuspend the cell pellet in 1 mL of ABC buffer and add 0.5 mL of the PI solution (0.5 mg/mL).
  3. Vortex a tube with the sample 3x for 10 s and incubate it for 10 min in the dark and on ice.
  4. Centrifuge the tube with the sample in a tabletop centrifuge at 13,400 x g for 10 min at 4 °C.
  5. Remove the supernatant and resuspend the pellet in 1 mL of ABC buffer.
  6. Centrifuge the tube at 13,400 x g for 10 min at 4 °C and remove the supernatant. Repeat this step 2 more times to remove the PI bound to the cell surface.
  7. Resuspend the pellet in 300 µL of ABC buffer. Place 10 µL of the suspension on the surface of a microscope slide.
  8. Capture the differential interference contrast (DIC) and fluorescence microscopy images with a fluorescence microscope. Use a filter set up at the excitation and emission wavelengths of 593 nm and 636 nm (respectively).
  9. Use a software to count the total cell number (in the DIC mode) and the number of fluorescently stained cells. Also, use this software to determine the intensity of staining for individual cells.

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Representative Results

To improve a quantitative assessment of water-soluble metabolites within a yeast cell, we optimized the conditions of cell quenching for metabolite detection. Cell quenching for this purpose involves a rapid arrest of all enzymatic reactions within a cell31,33,37,38. Such an arrest of cellular metabolic activity is an essential step of any method for the quantitation of water-soluble metabolites in vivo because it prevents the under-estimation of their intracellular concentrations31,33,37,38. Cell quenching for metabolite assessment always impairs the integrity of the plasma membrane (PM) (and of the cell wall (CW), if present); this causes metabolite leakage from the cell31,33,37,38. The method employs cell quenching conditions that minimize such impairment, thereby significantly decreasing the quenching-associated cell leakage of intracellular metabolites. Indeed, most current methods for cell quenching involve the use of a certain concentration of methanol (i.e., 40% (v/v), 60% (v/v), 80% (v/v), or 100% (v/v)) at specific temperature (i.e., -20 °C, -40 °C, or -60 °C), with or without a buffer31,33,37,38. We compared the efficiency of the PM and CW impairment for one of the currently used cell quenching method (i.e., by cell treatment with 80% (v/v) methanol at -40 °C in the absence of a buffer38) to that for the modified cell quenching method (i.e., by cell treatment with 60% (v/v) methanol at -20 °C in the presence of an isotonic buffered solution of ABC at pH = 8.0). PI is a fluorescent dye that is impermeable to intact cells; it can enter the cell only if the integrity of the PM (and of the CW, if present) is impaired39. Moreover, the intensity of fluorescence emission by PI rises by 30-fold when it is bound to DNA or RNA39. Thus, a PI staining assay can be used for assessing the efficiency of quenching-associated cell leakage of intracellular metabolites because these metabolites can leak into the extracellular space only if the PM and CW of a yeast cell are damaged39. We found that the modified cell quenching method causes significantly lower damage to the PM and CW than the quenching method by cell treatment with non-buffered 80% (v/v) methanol at -40 °C (Figure 3). Indeed, almost all cells subjected to quenching using the method exhibited red fluorescence emission, which is characteristic of the yeast cells whose PM and CW are not damaged (Figure 3). In contrast, almost all cells subjected to quenching using the other method, displayed green fluorescence emission characteristic of the yeast cells whose PM and CW are significantly damaged (Figure 3). The most intense red fluorescence was converted to green fluorescence by a software to differentiate between the strong red fluorescence and mild red fluorescence emissions.

The modified cell quenching method caused significantly lower leakage of water-soluble metabolites from yeast cells than the - quenching method by cell treatment with non-buffered 80% (v/v) methanol at -40 °C. We subjected equal numbers of yeast cells to quenching using either the method (i.e., by cell treatment with 60% (v/v) methanol at -20 °C in the presence of an isotonic buffered solution of ABC at pH = 8.0; Figure 4) or the other method (i.e., by cell treatment with non-buffered 80% (v/v) methanol at -40 °C; Figure 5). The extent of quenching-associated cell leakage into the extracellular solution was assessed for specific water-soluble metabolites with the help of LC-MS/MS. The concentrations of different amino acid classes (i.e., large and small acidic, basic, neutral-nonpolar, and neutral polar amino acids) in the extracellular solution were measured before and after cell quenching. We found that the cell quenching method causes significantly lower leakage of all these amino acid classes into the extracellular solution (Figure 4) than the other method (Figure 5).

The LC-MS/MS method for a quantitative assessment of water-soluble metabolites within a yeast cell uses a single type of the column for chromatographic separation of all water-soluble metabolite classes. This column is the zwitterionic-phase column named in Table of Materials. We found that this column provides a much more efficient separation of different classes of water-soluble metabolites than the reverse-phase column named in Table of Materials (Supplemental Table 1). Indeed, the retention time (RT) shift values of water-soluble metabolite standards (i.e., NAD+, AMP, GMP, arginine, and glutamic acid) were significantly lower and the peak shapes were substantially sharper for the zwitterionic-phase column, as compared with the reverse-phase column (Supplemental Table 1). LC conditions used for chromatographic separation of all metabolites (i.e., water-soluble and water-insoluble) for the reverse-phase column are provided in Supplemental Table 2.

Another advantage of the LC-MS/MS method consists in the ability of chromatographic separation on the above zwitterionic-phase column to efficiently separate from each other different water-soluble metabolites with diverse structural, physical, and chemical properties. These water-soluble metabolites include the following metabolite classes: 1) acidic, basic, neutral polar, and non-neutral polar amino acids, including their different structural isomers (Figure 6); 2) stable and unstable nucleotides and their derivates that perform vital functions within a cell (Figure 7); and 3) various monosaccharides, including their different stereoisomeric forms (Figure 8).

Importantly, the LC-MS/MS method for a quantitative assessment of water-soluble metabolites within a yeast cell was versatile and robust. It allowed us to identify and quantify 374 water-soluble metabolites with diverse structural, physical, and chemical properties in S. cerevisiae cells that were cultured in the complete YP medium initially containing 2% glucose (Supplemental Table 3). 240 metabolites were detected in the positive ionization mode and 134 metabolites were detected in the negative ionization mode. The identities of all these water-soluble metabolites were confirmed by matching their data-dependent acquisition (DDA) MS2 fragments acquired both in the positive and negative ionization modes to the MS2 mzCloud spectral library. This online library includes the spectra of metabolite standards that differ in their MS1 and DDA MS2 parameters. To maximize the extent of matching the MS2 spectra of the sample with the online spectral library, we used different DDA MS2 parameters. These parameters are provided in Supplemental Table 4. Almost 6,000 features (putative metabolites) for the same sample were acquired with the help of the high-energy-induced-collision-dissociation (HCD) or collision-induced dissociation (CID) fragmentation method, using top 5 MS2 events, 35 collision energy values, and 10 ms activation times. After filtering the resulting files with > 95% MS2 matching and > 90% MS1 isotopic pattern matching criteria, only 162 metabolites under HCD fragmented condition and 142 metabolites under CID fragmented condition were identified. 81 out of 162 metabolites were unique to the HCD fragmentation method, whereas 42 out of 142 were unique to the CID fragmentation method (see a sheet named "T5_35E__10 ms_HCD vs CID" in Supplemental Table 4). Therefore, we concluded that the correct annotation of water-soluble metabolites with the help of the LC-MS/MS method requires the use of many different DDA MS2 parameters.

The LC-MS/MS method is also highly sensitive. It allows to identify and quantitate some water-soluble metabolites at concentrations as low as 0.05 pmol/µL (see data for phenylalanine in Table 4). This limit of quantitation varies within a wide range of concentrations for different metabolite classes (Table 4).

The MS system used here has a wide (at least two orders of magnitude) linear dynamic range for measuring the concentrations of various metabolites (Supplemental Table 5).

Figure 1
Figure 1: The total ion chromatogram (TIC) from liquid chromatography/mass spectrometry (LC-MS) data of water-soluble metabolites that were extracted from cells of the wild-type strain BY4742. The metabolites were separated by LC on the zwitterionic-phase chromatography column named in Table of Materials. The metabolites were detected by MS of parent ions (MS1) that were created using the positive electrospray ionization mode. Please click here to view a larger version of this figure.

Figure 2
Figure 2: A workflow used for the analysis of water-soluble metabolites with the help of the software named in Table of Materials. All the parameters were autocorrected by the software based on the MS raw data, except the followings: 1) "Detect Compounds" tab: set min, peak intensity 10,000; and 2) "Search ChemSpider" tab: 4 online databases were selected for the identification of metabolites, including the BioCyc, Human Metabolome Database, KEGG, and Yeast Metabolome Database. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Differential interference contrast (DIC; top row) and fluorescence (bottom row) microscopic images of yeast cells quenched either with ammonium bicarbonate (ABC) buffer (pH = 8.0; control) or with a different quenching solution. After cell quenching, equal numbers of cells were incubated with the PI solution for 10 min in the dark and on ice. The most intense red fluorescence was converted to green fluorescence by software to differentiate between the strong red fluorescence and mild red fluorescence emissions. The efficiency of damage to the PM and CW was compared for the method of cell quenching (i.e., by cell treatment with 60% (v/v) methanol at -20 °C in the presence of an isotonic buffered solution of ABC at pH = 8.0) and one of the currently used methods (i.e., by cell treatment with 80% (v/v) methanol at -40 °C in the absence of a buffer). A scale bar is shown. Please click here to view a larger version of this figure.

Figure 4
Figure 4: The leakage percentage of different amino acid classes for the method of cell quenching. 5.0 x 108 of yeast cells were subjected to quenching by the treatment with 60% (v/v) methanol at -20 °C in the presence of an isotonic buffered solution of ABC at pH = 8.0. The leakage percentage of different amino acid classes was assessed using LC-MS/MS to measure their concentrations in the extracellular solution before and after quenching. The mean values ± SD and individual data points are shown (n = 3). * p < 0.05. Please click here to view a larger version of this figure.

Figure 5
Figure 5: The leakage percentage of different amino acid classes for one of the currently used cell quenching methods. 5.0 x 108 of yeast cells were subjected to quenching by the treatment with 80% (v/v) methanol at -40 °C in the absence of a buffer. The leakage percentage of different amino acid classes was assessed using LC-MS/MS to measure their concentrations in the extracellular solution before and after quenching. The mean values ± SD and individual data points are shown (n = 3). * p < 0.05. Please click here to view a larger version of this figure.

Figure 6
Figure 6: Efficient chromatographic separation of acidic, basic, neutral polar and non-neutral polar amino acid classes, including two structural isomers (i.e., leucine and isoleucine), on the zwitterionic-phase column named in Table of Materials. All these amino acids were detected by MS/MS in the positive ionization [ESI (+)] mode. Conditions for LC on the zwitterionic-phase chromatography column are described in Table 1. Conditions for MS/MS are described in Table 2 and Table 3. All amino acid standards are bought commercially (e.g., Sigma). The retention time shifts between 3 independent chromatography runs are less than ± 10 seconds. Please click here to view a larger version of this figure.

Figure 7
Figure 7: Efficient chromatographic separation of different classes of nucleotides, including energetically unstable nucleotides (nucleoside monophosphates, nucleoside diphosphates, and nucleoside triphosphates) and electron carrier molecules (NADH and NAD+), on the zwitterionic-phase columnnamed in Table of Materials. All these nucleotides were detected by MS/MS in the positive ionization [ESI (+)] mode. Conditions for LC on the zwitterionic-phase chromatography column are described in Table 1. Conditions for MS/MS are described in Table 2 and Table 3. All nucleotide standards are bought commercially (e.g., Sigma). The retention time shifts between 3 independent chromatography runs are less than ± 10 seconds. Please click here to view a larger version of this figure.

Figure 8
Figure 8: Efficient chromatographic separation of different classes of monosaccharides, including structural isomers and stereoisomeric forms of aldo- and ketohexoses (fructose, mannose, and galactose), and aldopentoses (ribose and arabinose), on the zwitterionic-phase columnnamed in Table of Materials. All these monosaccharides were detected by MS/MS in the positive ionization [ESI (+)] mode. Conditions for LC on the zwitterionic-phase chromatography column are described in Table 1. Conditions for MS/MS are described in Table 2 and Table 3. All monosaccharide standards are bought commercially (e.g., Sigma). The retention time shifts between 3 independent chromatography runs are less than ± 10 seconds. Please click here to view a larger version of this figure.

Column type SeQuant ZIC-pHILIC 5µm polymer 150 x 2.1 mm
Solvent A LC-MS grade H2O: ACN (95:5, v/v) 20 mM Ammonium acetate
Solvent B LC-MS grade Acetonitrile (ACN) 
Pressure limit Maximum = 300 bar Minimum = 0
HPLC gradient program
Time (minutes) Flow rate (0.25 ml/min) Compositions
A% B%
0.5 0.25 5 95
26 0.25 40 60
30 0.25 70 30
31 0.25 70 30
31.1 0.4 5 95
43.9 0.4 5 95
44 0.25 5 95
45 0.25 5 95

Table 1: LC condition used for the separation of water-soluble metabolites with the help of the zwitterionic-phase columnnamed in Table of Materials. These conditions were used in all experiments described here.

Full scan mass range (Dalton) 70-900
FTMS (Orbitrap analyzer) full scan resolution 6.0 x 104
FTMS (Orbitrap analyzer) HCD resolution 7500
FTMS full scan AGC target 1.0 x 106
FTMS MSn AGC target 5.0 x 104
Ion trap (LTQ) MSn AGC target 1.0 x 104
Ion Source type Heated Electrospray Ionization
Capillary Temperature (°C) 275
Source heater Temperature (°C) 250
Sheath Gas Flow 10
Aux Gas flow 5

Table 2: The mass spectrometer settings used to analyze metabolites that were separated by LC. These conditions were used for the analysis of metabolites in all experiments described here. Abbreviations: FTMS = Fourier transform (FTMS); HCD = high-energy-induced-collision-dissociation; LTQ = linear trap quadrupole; AGC = automatic gain control, an ion population value for MS and MS/MS.

Instrument polarity Positive/Negative
Activation type CID/HCD
Min. signal required 5000
Isolation Width 2
Normalized Collision energies for CID 35, 60
Normalized Collision energies for HCD 35, 45, 55
Default charge state 1
Activation time for CID (ms) 10, 30
Activation time for HCD (ms) 10
Number of MS/MS events in CID Top 3, Top 5, Top 10
Number of MS/MS events in HCD Top 5
Number of micro scans used in both HCD and CID 1

Table 3: The mass spectrometer settings used to detect secondary ions (MS2). Abbreviations: HCD = high-energy-induced-collision-dissociation; CID = collision induced dissociation; ms = milliseconds.

Std Metabolites M.W. (g/mole) [M+H]+1 [M-H]-1 Detection mode Lowest concentration detected (pmol/µL)
glycine 75.03203 76.03931 74.02475 P 7.43E+00
tryptophan 204.08988 205.09716 203.0826 P 5.56E-02
phenylalanine 165.07898 166.08626 164.0717 P 5.14E-02
arginine 174.11168 175.11896 173.1044 P 7.14E-02
threonine* 119.05824 120.06552 118.05096 P
serine 105.04259 106.04987 104.03531 P 4.66E+00
glutamate 147.05316 148.06044 146.04588 P 4.20E-01
methionine 149.05105 150.05833 148.04377 P 1.96E+00
aspartate 133.03751 134.04479 132.03023 P 3.75E+00
valine 117.07898 118.08626 116.0717 P 1.49E+00
isoleucine 131.09463 132.10191 130.08735 P 1.84E+00
leucine 131.09463 132.10191 130.08735 P 2.26E+00
histidine 155.06948 156.07676 154.0622 P 2.53E+00
tyrosine 181.07389 182.08117 180.06661 P 8.72E-02
lysine 146.10553 147.11281 145.09825 P 1.43E-01
alanine 89.04768 90.05496 88.0404 P 1.12E+00
proline 115.06333 116.07061 114.05605 P 1.05E+00
cysteine 121.01975 122.02703 120.01247 P 8.22E-01
asparagine 132.05349 133.06077 131.04621 P 1.08E+00
glutamine 146.06914 147.07642 145.06186 P 1.92E+00
guanine 151.04941 152.05669 150.04213 P 5.47E+00
guanosine 283.09167 284.09895 282.08439 P 3.67E-01
GMP 363.058 364.06528 362.05072 P 7.17E-01
GDP 443.02434 444.03162 442.01706 P 2.57E+00
GTP 522.99067 523.99795 521.98339 P 2.27E+00
AMP 347.06309 348.07037 346.05581 P 5.25E-01
ADP 427.02942 428.0367 426.02214 P 1.32E+00
ATP 506.99575 508.00303 505.98847 P 1.77E+00
NADH 665.12478 666.13206 664.1175 P 1.47E+00
NAD+ 663.10912 664.1164 662.10184 P 3.03E+00
glucose** 180.06339 181.07067 179.05611
fructose*** 180.06339 181.07067 179.05611 N 5.67E-01
mannose*** 180.06339 181.07067 179.05611 N 1.05E+00
galactose*** 180.06339 181.07067 179.05611 N 9.00E-01
ribose*** 150.05283 151.06011 149.04555 N 1.10E+00
arabinose*** 150.05283 151.06011 149.04555 N 1.23E+00
fructose-6-phosphate*** 260.02972 261.037 259.02244 N 6.60E+00
glucose-6-phosphate*** 260.02972 261.037 259.02244 N 4.27E+00
citric acid 192.12 g 193.034279 191.019726 N 9.33E-01
malic acid 134.09 135.0288 133.014247 N 1.23E+00
pyruvic acid 88.06 89.02332 87.008768 N 2.77E+00

Table 4:The lowest concentrations of different water-soluble metabolite standards that the LC-MS/MS method can identify and quantitate. The MS1 peak area of each metabolite standard was used to estimate the lowest quantifiable concentration for this metabolite. Mean values of two independent experiments are shown. Three technical replicates were performed for each of the two independent experiments. NOTE: Threonine* can be detected but cannot be quantified due to its co-elution with homoserine, a chemical isomer of threonine. Glucose** cannot be identified because it creates multiple chromatography peaks. Metabolite standards*** can be identified and quantitated only in individual samples, but not in a mixture of metabolite standards or a biological mixture of metabolites.

Supplemental Table 1: Retention Time (RT) shift values of the same set of metabolites for the zwitterionic-phase and reverse-phase columns (see Table of Materials) after column equilibration. The table compares the retention reproducibility of the zwitterionic-phase and reverse-phase columns for a distinct set of metabolites the differ from each other in their hydrophilicity and hydrophobicity. These metabolites were identified with the help of LC-MS/MS. Note that the RT shift values of hydrophilic metabolites (i.e., NAD+, AMP, GMP, arginine, and glutamic acid) are significantly lower and the peak shapes are substantially sharper for the zwitterionic-phase column, as compared to the reverse-phase column. In contrast, the RT shift values of hydrophobic metabolites (i.e., stearic acid, lauric acid, and decanoic acid) are significantly lower and the peak shapes are substantially sharper for the reverse-phase column, as compared to the zwitterionic-phase column. Conditions for the chromatographic separation of metabolites with the help of the zwitterionic-phase and reverse-phase columns are detailed in Table 1 and Supplemental Table 2, respectively. The reported here RT shift values are based on the measurement of 20 different samples taken from different vials. The samples were analyzed after column equilibration. The metabolites in each sample were extracted from 5.0 × 108 yeast cells. RT shift values are the means of 20 different samples (n = 20). The p values derived from the unpaired t test were used to compare the two columns with the equal variance between both sample types. Please click here to download this table.

Supplemental Table 2: LC conditions for the reverse-phase 8 column named in Table of Materials and used to separate different metabolites in this study. Column properties were as follows: 150 x 2.1 mm, 5 µm polymer. Please click here to download this table.

Supplemental Table 3: A list of all 374 water-soluble metabolites recovered and annotated using the LC-MS/MS method. All metabolites were recovered from the same LC gradient run, subjected to a data-dependent acquisition (DDA) fragmentation algorithm described in Supplemental Table 4, and annotated using the software named in Table of Materials. The MS1 peak shapes of 211 metabolites (whose status in the table is indicated as a blank) were appropriate to be used for quantification, and their respective MS2 spectra had full matches with the mzCloud spectral library. MS2 spectra of 38 metabolites (whose status in the table is indicated as a d) had full matches with the online spectral library. Still, their MS1 peak shapes were not appropriate to be used for quantification. MS2 spectra of 125 metabolites (whose status in the table is indicated as an n) did not have full matches with the online spectral library. These metabolites were annotated as follows: 1) using the "Predict composition node" (which annotates metabolites based on the exact match of MS1 values, number of matched and missed isotopes, and isotope % intensity matched with that of the theoretical reference standards); 2) using the "ChemSpider node" (which annotates metabolites based on the exact match of MS1 values and similarity match score of MS2 spectra with the online spectral library); and 3) using the retention time (RT) shift values of metabolites (these values depend on the physical structure and chemical properties of metabolites). The metabolites listed in the table were found in all 3 biological replicates performed, with the RT shift values of < 0.2 min. Please click here to download this table.

Supplemental Table 4: A data-dependent acquisition (DDA) fragmentation algorithm that was used here for the annotation of water-soluble metabolites with the help of the software named in Table of Materials. Please click here to download this table.

Supplemental Table 5: A typical linear dynamic range that we observed when we measured the concentrations of different amino acids with the help of the MS system named in Table of Materials. The MS system used here has a wide (at least two orders of magnitude) linear dynamic range for measuring various metabolites' concentrations. Please click here to download this table.

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Discussion

To successfully use the protocol described here, follow the preventive measures described below. Chloroform and methanol extract various substances from laboratory plasticware. Therefore, handle them with caution. Avoid the use of plastics in steps that involve contact with any of these two organic solvents. Use borosilicate glass pipettes for these steps. Rise these pipettes with chloroform and methanol before use. Use only micropipette tips and tubes made of polypropylene that is resistant to organic solvents. During sample preparation for LC-MS/MS, eliminate all air bubbles in the glass vials before inserting them into a wellplate.

The zwitterionic-phase column used here requires extensive re-conditioning after each run to minimize the RT shift. For column re-conditioning, we recommend using a volume of the re-conditioning solution that is about 20 volumes of the column. The column needs to be re-conditioned with the initial mobile phase for 15 min at an increased flow rate of 0.4 mL/min. To avoid any damage to the column during its re-conditioning, keep the column pressure below the upper limit of pressure recommended by the manufacturer.

Of note, some mixed-separation chromatography columns that operate in the reverse-phase mode allow resolution of charged metabolites40,41. These mixed-separation columns are based on the reverse-phase column used here (see Table of Materials) and contain polar embedded groups that can separate metabolites based on charge40,41.

Here, we described an LC-MS/MS-based method of non-targeted metabolomics for the quantitative analysis of many water-soluble metabolites extracted from yeast cells. The method provides several advantages over the LC-MS/MS methods of non-targeted metabolomics currently used for this purpose. These advantages include the following. First, the method is sensitive and allows the identification and quantitation of some water-soluble metabolites at concentrations as low as 0.05 pmol/µL. The reported sensitivity of the existing LC-MS/MS methods is lower3,22,27,42. Second, the method uses a cell quenching procedure that elicits a significantly lower leakage of intracellular metabolites from the cell than that reported for the presently used procedures31,33,38. Thus, the procedure that we developed for cell quenching lowers the extent to which the currently used procedures under-estimate the intracellular concentrations of water-soluble metabolites. Third, unlike the existing LC-MS/MS methods2,31,33, the method distinguishes between different structural isomers and stereoisomeric forms of many metabolites. These metabolites include various energy carrier molecules, nucleotides, amino acids, monosaccharides, intermediates of glycolysis, and tricarboxylic cycle intermediates. Fourth, we used the method to create an extensive mass spectral database of MS1 and MS2 for the correct identification and quantitation of a wide range of specific metabolites using the raw LC-MS/MS data. In contrast, the existing mass spectral online databases of MS1 and MS2 are incomplete43,44,45. Fifth, the method uses a single type of metabolite extraction to recover water-soluble metabolites with diverse structural, physical, and chemical properties. These metabolites' diversity significantly exceeds that of alternative methods for a single-step extraction of water-soluble metabolites from yeast cells3,22,27,46. Six, unlike the existing LC-MS/MS methods3,22,47,48, the method uses a single type of the LC column to separate from each other various structural and functional classes of water-soluble metabolites. Seven, the method enables the identification and quantification of more than 370 water-soluble metabolites extracted from yeast cells. This number of identifiable and quantifiable metabolites exceeds the numbers of metabolites reported for other methods of non-targeted metabolomics in yeast3,22,27,49,50.

The method has several limitations. These limitations are as follows. The zwitterionic-phase column used for metabolite separation by LC requires extensive re-conditioning after each run. Furthermore, the method is efficient only for the non-targeted metabolomics of water-soluble, hydrophilic metabolites. Moreover, different isomeric forms of carbohydrates (including isomers of fructose, glucose, and galactose) cannot be quantified with the help of the method. This is because the zwitterionic-phase column used in the method cannot separate these carbohydrate isomers from each other when present in a mixture with other metabolites. Besides, the method cannot be exploited for identifying glucose because this carbohydrate creates multiple peaks during chromatography on the zwitterionic-phase column used in the method. Finally, threonine cannot be quantified with the help of the method due to the co-elution of this amino acid with its isomer homoserine during metabolite separation by chromatography.

We use this LC-MS/MS method to study aging-associated changes in the water-soluble metabolome of the budding yeast S. cerevisiae. We also employ this method to investigate how many aging-delaying genetic, dietary, and pharmacological interventions affect the water-soluble metabolome of yeast cells during their chronological aging. Because of its versatility, robustness, and sensitivity, the LC-MS/MS method can be successfully used for the quantitative assessment of the water-soluble metabolomes in evolutionarily distant eukaryotic organisms.

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Disclosures

The authors declare that they have no competing financial interests.

Acknowledgments

We are grateful to current and former members of the Titorenko laboratory for discussions. We acknowledge the Centre for Biological Applications of Mass Spectrometry, the Centre for Structural and Functional Genomics, and the Centre for Microscopy and Cellular Imaging (all at Concordia University) for outstanding services. This study was supported by grants from the Natural Sciences and Engineering Research Council (NSERC) of Canada (RGPIN 2014-04482 and CRDPJ 515900 - 17). K.M. was supported by the Concordia University Armand C. Archambault Fellowship and the Concordia University Dean of Arts and Sciences Award of Excellence.

Materials

Name Company Catalog Number Comments
Chemicals
Acetonitrile Fisher Scientific A9554
Ammonium acetate Fisher Scientific A11450
Ammonium bicarbonate Sigma 9830
Bactopeptone Fisher Scientific BP1420-2
Chloroform Fisher Scientific C297-4
Glucose Fisher Scientific D16-10
L-histidine Sigma H8125
L-leucine Sigma L8912
L-lysine Sigma L5501
Methanol Fisher Scientific A4564
Methanol Fisher Scientific A4564
Propidium iodide Thermo Scientific R37108
Uracil Sigma U0750
Yeast extract Fisher Scientific BP1422-2
Hardware equipment
500 ml centrifuge bottles Beckman 355664
Agilent 1100 series LC system Agilent Technologies G1312A
Beckman Coulter Centrifuge Beckman 6254249
Beckman Coulter Centrifuge Rotor Beckman JA-10
Centra CL2 clinical centrifuge Thermo Scientific 004260F
Digital thermometer Omega HH509
Foam Tube Holder Kit with Retainer Thermo Scientific 02-215-388
SeQuant ZIC-pHILIC zwitterionic-phase column (5µm polymer 150 x 2.1 mm) Sigma Milipore 150460
Thermo Orbitrap Velos MS Fisher Scientific ETD-10600
Ultrasonic sonicator Fisher Scientific 15337416
Vortex Fisher Scientific 2215365
ZORBAX Bonus-RP, 80Å, 2.1 x 150 mm, 5 µm Agilent Technologies 883725-901
Laboratory materials
2-mL Glass sample vials with Teflon lined caps Fisher Scientific 60180A-SV9-1P
Glass beads (acid-washed, 425-600 μm) Sigma-Aldrich G8772
Hemacytometer Fisher Scientific 267110
15-mL High-speed glass centrifuge tubes with Teflon lined caps PYREX 05-550
Software
Compound Discoverer 3.1 Fisher Scientific V3.1
Yeast strain
Yeast strain BY4742 Dharmacon YSC1049

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Cite this Article

Mohammad, K., Jiang, H., Titorenko, V. I. Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry. J. Vis. Exp. (167), e62061, doi:10.3791/62061 (2021).More

Mohammad, K., Jiang, H., Titorenko, V. I. Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry. J. Vis. Exp. (167), e62061, doi:10.3791/62061 (2021).

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