Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults

Summary

The goal of this protocol is to detect phenolic metabolites in plasma using a semi-targeted chromatography-mass spectrometry method.

Abstract

A group of 23 elderly persons was given functional meals (a beverage and a muffin) specially formulated for the prevention of sarcopenia (age-related loss of muscle mass). Plasma samples were taken at the beginning of the intervention and after 30 days of consuming the functional meals. A semi-targeted ultra-high-performance chromatography coupled with tandem mass (UPLC-MS/MS) analysis was carried out to identify phenolic compounds and their metabolites. Plasma proteins were precipitated with ethanol and the samples were concentrated and resuspended in the mobile phase (1:1 acetonitrile: water) before injection into the UPLC-MS/MS instrument. Separation was carried out with a C₁₈ reverse-phase column, and compounds were identified using their experimental mass, isotopic distribution, and fragment pattern. Compounds of interest were compared to those of data banks and the internal semi-targeted library. Preliminary results showed that the major metabolites identified after the intervention were phenylacetic acid, glycitin, 3-hydroxyphenylvaleric acid, and gomisin M2.

Introduction

Sarcopenia is a progressive skeletal disorder related to an accelerated loss of muscle in the elderly population. This condition increases the risk of falls and leads to limited activities of daily living. Sarcopenia is present in about 5%-10% of persons over 65 years old and about 50% of persons aged 80 years or older¹. No specific drugs have been approved for the treatment of sarcopenia, so prevention with physical activity and a well-balanced diet is important^1,2. Nutritional interventions with specially formulated foods enriched with dairy protein and essential amino acids have shown positive results in preventing sarcopenia². In other studies, authors have included vitamins and antioxidants, like vitamin E and isoflavones, in the diet, increasing the benefits for muscle gain on the waist and hips³.

Brosimum alicastrum Sw. (Ramón) is a tree that grows in the Mexican tropical regions; it has been consumed by Mayan cultures due to its high nutritional value⁴. It is a good source of protein, fiber, minerals, and phenolic antioxidants, such as chlorogenic acid⁵. Since it can be ground into powder and used in baking products or consumed in beverages, recent studies have evaluated the incorporation of Ramón seed flour (RSF) into different foods to improve their nutritional value. An RSF-supplemented cappuccino-flavored beverage was formulated, which was high in dietary fiber and had more than 6 g of protein per serving, and was highly accepted by consumers; thus, it was considered a potential alternative for meeting special dietary requirements⁶. In a follow-up study, RSF was also used to formulate a muffin and a new beverage rich in protein, dietary fiber, micronutrients, and phenolic antioxidants. The muffin and beverage were used in a dietary intervention for elderly individuals, who consumed both products twice per day for 30 days. After this period, the nutritional and sarcopenic status of the participants improved, and the total phenolic content of plasma increased⁷. However, the determination of total phenolic compounds in plasma was carried out by a spectrophotometric method, so identification of the actual phenolic compounds that were absorbed was not possible; moreover, this method is not completely specific for phenolic compounds, so some overestimation may occur⁸.

Identification and quantification of the phenolic compounds that are absorbed after consumption of foods rich in these antioxidants is a difficult task but is necessary to demonstrate the biological activity of these phytochemicals. The bioavailability of most phenolic compounds is low; less than 5% of them can be found without structural transformation in plasma. Phenolic compounds undergo several biotransformations, such as methylation, sulfonation, or glucuronidation, which are carried out by enterocytes and hepatocytes⁹. Phenolic compounds are also biotransformed by the microbiota into bacterial catabolites that may exert their beneficial effects in the body after being absorbed into the plasma¹⁰. For example, phenylacetic acid is a product of the bacterial transformation of flavonoids and oligomeric proanthocyanidins, which can inhibit up to 40% of bacteria (Escherichia coli) adhesion in the urinary tract after cranberry consumption¹¹.

The structural diversity of naturally occurring phenolic compounds, added to the diversity of their metabolites and their low bioavailability, makes their identification in plasma even more challenging. Metabolomic profiling, using spectroscopic analysis platforms like nuclear magnetic resonance (NMR) and tandem mass spectroscopy (MS/MS), is probably the best approach to achieve this goal; unfortunately, the equipment is not easily accessible, and the development of analysis protocols is still limited¹². Several studies have reported MS/MS coupled with a separation system (such as liquid chromatography) as a strategy for reducing the complexity of mass spectra in metabolomic studies. The recent introduction of ultra-high-performance liquid chromatography (UPLC) separation methods has reduced the time of analysis and increased the resolution and sensitivity compared with conventional high-performance liquid protocols, so UPLC-MS/MS systems have rapidly been widely accepted by the analytical metabolomics community¹³. In this way, some studies have investigated phenolic metabolites and detected glucuronidated derivatives from caffeic acid, quercetin, and ferulic acid, as well as sulfonated derivatives from syringic and vanillic acid in the plasma of individuals after cranberry intake¹⁴. Previous protocols have intended to find phenolic compounds and phenolic metabolites in biofluids such as plasma. These protocols were based on identification and quantification by high-performance liquid chromatography (HPLC) coupled to a UV-vis detector¹⁵. Nevertheless, such protocols require the use of authentic standards to assess absolute identification and accurate quantification. A wide range of studies have identified the most common metabolites in biofluids (sulphonated, glucuronidated, and methylated forms) by UPLC-MS and UPLC-MS/MS; however, a large part of the bacterial metabolites has not been reported due to the lack of databases that contain their complete information¹⁶. Metabolite identification is complicated by the cost and commercial availability of metabolite standards. Therefore, the best strategy may be untargeted or semi-targeted MS/MS metabolite analysis, which relies on the use of molecular feature information (m/z, monoisotopic exact mass, isotopic distribution, and fragmentation pattern) to determine the chemical identity and compares it with freely available online databases that contain polyphenol metabolites identified in biofluids after the consumption of polypolyphenol-richts¹². The most important databases used in UPLC-MS/MS studies for the identification of phenolic compounds and their metabolites are the Human Metabolome Database (HMDB), LipidBlast Library, METLIN Library, and other complementary databases, such as PubChem, ChemSpider, and Phenol Explorer¹⁷.

In the present study, a semi-targeted UPLC-MS/MS method was developed to analyze the plasma samples of the group of elderly persons involved in the RSF-containing muffin and beverage consumption study⁷. Data from different free online databases of plasma metabolites were collected and integrated into a specialized database. This database can be accessed automatically by the equipment software to identify the polyphenolic metabolites in the five plasma samples before and after the 30-day nutritional intervention. This is done to identify the main phenolic compounds, or their metabolites, that are absorbed from the specially formulated functional foods designed for the prevention of sarcopenia.

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Protocol

The plasma samples used in this protocol were collected in a previous study following all the ethical guidelines and approved by the Institutional Ethics and Bioethics Committee (CIEB-2018-1-37) from the Universidad Autónoma de Ciudad Juárez. The complete protocol for the extraction and identification of the phenolic compounds and metabolites in plasma by UPLC-MS/MS is represented in Figure 1.

Figure 1: Schematic representation of the extraction and identification of phenolic compounds and metabolites in plasma by the semi-targeted UPLC-MS/MS method. Please click here to view a larger version of this figure.

1. Sample preparation

1. Store the plasma samples at -80 °C until analysis.
2. Defrost the plasma samples at room temperature for 15 min.
   NOTE: The samples can be placed in a water bath at 37 °C to accelerate the process (5 min).
3. Place 200 µL of plasma sample in a 2 mL microtube and mix with 1,000 µL of pure ethanol. Vortex the plasma sample for 30 s.
   NOTE: Always use gloves when working with plasma samples.
4. Centrifuge the sample at 6,580 x g for 5 min. After centrifugation, collect the supernatant with a micropipette or Pasteur pipette and place it in a new microtube. Store the supernatant at 4 °C.
5. Mix the pellet from the previous step with 1,000 µL of 100% ethanol, vortex for 30 s, and then centrifuge at 6,580 x g for 5 min.
   NOTE: The pellet is strongly packed and needs to be resuspended well to ensure contact between the sample and pure ethanol. The use of a micropipette to flush the pellet with ethanol is recommended.
6. After centrifugation, collect the supernatant and mix with the supernatant previously obtained from Step 1.4. in a 2 mL microtube.
7. Remove ethanol from the sample by using pure nitrogen (99.997%) at 135 psi. Keep the needle 1 cm away from the top of the microtube to prevent sample loss and flush until the sample is dry. No heat is needed to evaporate the ethanol.
   NOTE: The nitrogen flow must be low to prevent sample loss. Once the ethanol is dried, keep the nitrogen flow for at least 5 min to ensure sample dryness. The protocol can be paused at this point; samples must be stored at -20 °C. Avoid storing the samples for more than 12 h.
8. Resuspend the dry samples in 100 µL of a mixture of acetonitrile: water at a proportion of 50:50 (v:v).
9. Filter the sample through a 0.45 µm nylon syringe membrane directly into an HPLC vial micro insert.
   NOTE: The samples in the vial can be stored at -20 °C before analysis. Store the samples for no more than 8 h. It is recommended to inject the samples into the UPLC system just after filtration.

2. UPLC-MS/MS analysis

1. Inject 3 µL of sample onto a UPLC equipped with a C₁₈ reverse-phase column (50 mm x 2.1 mm; 1.8 µm). Set the autosampler temperature at 20 °C and the column thermostat at 25 °C. Inject each sample in triplicate.
2. Use 0.1% (v:v) formic acid in water as solvent A, and 100% acetonitrile as solvent B. Set the flow rate at 0.4 mL/min and a gradient program as follows: 0-1 min 10% B, 1-4 min 30% B, 4-6 min 38% B, 6-8 min 60% B, 8-8.5 min 60% B, 8.5-9 min 10% B (Table 1).
3. Set the mass spectrometer to negative mode ionization. Use nitrogen as a drying gas at 340 °C and a flow rate of 13 L/min. Set the nebulizer pressure at 60 psi. Set the capillary voltage at 4,000 V, the fragmentor voltage at 175 V, and the Skimmer voltage at 65 V. Use collision energy at 20 V (Table 2).
4. Scan the masses between 100-1100 mass to charge ratio (m/z) and, for MS/MS, scan masses between 50-1000 m/z (Table 2). Set data acquisition to Auto MS/MS mode. Use the following reference mass: 119.036 and 966.0007.

Time (min)	Solvent A (0.1 % formic acid in HPLC water)	Solvent B (100 % acetonitrile)
0 to 1	90	10
1 to 4	70	30
4 to 6	62	38
6 to 8	40	60
8 to 8.5	40	60
8.5 to 9	90	10

Table 1: Mobile phase gradient used for the separation of phenolic compounds by UPLC.

Ionization mode	Negative
Drying gas	Nitrogen at 340 °C, flow rate 13 L/min
Nebulizer pressure	60 psi
Capillary voltage	175 V
MS scan masses	100-1100 m/z
MS/MS scan masses	50-1000 m/z

Table 2: Ionization parameters for the MS/MS analysis.

3. Database construction

1. Search for phenolic compounds, phenolic metabolites, or other compounds of interest in the scientific literature.
2. Open the database management software included in the UPLC system. Select File | New Personal Database Compound Library (PCDL) | Create New PCDL. Select the type of PCDL: LC/MS Metabolomics. Set a name for the PCDL. Then select Create.
3. In the toolbar, select PCDL and then the Allow editing option. Then click the Find compounds button.
   NOTE: Since it is a new PCDL, the table results will be empty. This will change once new compounds are added into the PCDL.
   1. Add compounds to the specialized personal database compound library by copying them from the instrument's general library. Open the instrument's existing database included in the database management software. Click the button Find compounds. In the Single search option, enter the compound search criteria to find the compound of interest.
      NOTE: Compounds can be found by name, molecular formula, exact mass, and retention time.
   2. In the compound results table, select the compound of interest. To select more than one compound, click the first compound, hold down the CTRL key, and then click each compound of interest. Then, right-click on all the highlighted compounds and select Append to PCDL.
   3. In the new window, search and select the specialized personal database file. Mark the boxes Include spectra for compounds if present and Include ion mobility info for compounds if present. Click the Append button. In the new dialog box, select Yes to check the new compounds added. Select No to keep searching for more compounds of interest.
4. If the compounds of interest are not available in the instrument's general library, add new compounds manually.
   1. Open the specialized personal database. Once opened, follow Step 3.3. Select the Edit compounds option. Click the Add new button.
   2. In the upper section of the window, complete the information for the new compound. Fill in the formula, name, IUPAC name, CAS number, Chemspider ID, and other identifiers.
   3. Use the information available in the free online libraries (Chemspider, PubChem, and Phenol Explorer) to fill in the information for the new compound of interest. Once finished, click the button Save as new to save the new compound information in the specialized personal database.
      NOTE: When adding information from free libraries, be sure to include the compound information without the presence of chloride or iodide ions. This may modify the exact mass and molecular formula of the compound of interest.
5. Repeat the process with all the compounds of interest to complete the specialized personal database.

4. Data analysis

1. Use the instrument´s qualitative manager software to identify the phenolic compounds and phenolic metabolites present in the samples.
2. Open the sample file. In the Chromatogram panel, select Define Chromatograms and extract the total ion chromatogram (TIC), the extracted ion-chromatogram of MS (EIC), and the EIC of MS/MS. Select the integrate chromatogram option.
3. In the Find Compounds panel, select Find by Formula-Options. In the new window, select Formula Source and then the Database/Library option. Find the personal database previously created and click on Open.
4. Select the Formula Matching option and set a mass match tolerance of 5 parts per million (ppm).
   NOTE: A different match tolerance of masses can be set at 10 ppm; this difference depends on the mass spectrometer used.
5. Select the Negative Ions option and select only the -H dialog box. In the Results option, mark the Extract EIC, Extract Cleaned Spectrum, Extract Raw Spectrum, and include Structure dialog boxes.
6. Select the Result Filters option. Mark Warn if score is and set the score match at 80.00%. Mark Do not match if the score is and set the score at 75.00%.
   NOTE: The match/not match scores can be changed to lower values if needed. This will reduce the accuracy of identification.
7. Click on the Find Compounds by Formula to identify compounds of interest in the sample.

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Results

The step-by-step process for the identification of phenolic metabolites through the semi-targeted UPLC-MS/MS analysis, in negative mode, of plasma samples is depicted in Figure 2. First, the total ion chromatogram (TIC) from the plasma phenolics extract (obtained after protein precipitation of the total plasma sample) was obtained through the instrument's qualitative software. Then, the extracted ion chromatogram was used, and the exact mass and fragmentation patter...

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Discussion

The identification and quantification of the bioactive phytochemicals that are absorbed after consumption of a food or food supplement are crucial for demonstrating and understanding the health benefits of these compounds and the foods containing them. In the present work, the UPLC-MS/MS method was developed, aimed only at the identification of the main phenolic compounds and their metabolites that increased in concentration in plasma after a 30-day nutritional intervention with two food products specially formulated for...

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Materials

Name	Company	Catalog Number	Comments
Acetonitrile	Tedia	Al1129-001	LC Mass spectrometry
Autosampler	Agilent Technologies	G4226A	1290 Infinity series
C18 reverse phase column	Agilent Technologies	959757-902	Zorbax Eclipse plus C18 2.1x50 mm, 1.8 μm; Rapid resolution HD
Centrifuge	Eppendorf	5452000018	Mini Spin; Rotor F-45-12-11
Column compartment with thermostat	Agilent Technologies	G1316C	1290 Infinity series
Diode Array Detector (UV-Vis)	Agilent Technologies	G4212B	1260 Infinity series
Electrospray ionnization source	Agilent Technologies	G3251B	Dual sprayer ESI source
Formic acid	J.T. Baker	0128-02	Baker reagent, ACS
Mass Hunter Data Acquisition	Agilent Technologies	G3338AA
Mass Hunter Personal Compound Datbase and Library Manager	Agilent Technologies	G3338AA
Mass Hunter Qualitative Analysis	Agilent Technologies	G3338AA
Microcentrifuge tube	Brand	BR780546	Microcentrifuge tube, 2 mL with lid
Pure ethanol	Sigma-Aldrich	E7023-1L	200 proof, for molecular biology
Q-TOF LC/MS	Agilent Technologies	G6530B	6530 Accurate Mass
Quaternary pump	Agilent Technologies	G4204A	1290 Infinity series
Syringe filter	Thermo Scientific	44514-NN	17 mm, 0.45 μm, nylon membrane
Thermostat	Agilent Technologies	G1330B	1290 Infinity series
Vial	Agilent Technologies	8010-0199	Amber, PFTE red silicone 2 mL with screw top and blue caps
Vial insert	Agilent Technologies	5183-2089	Vial insert 200 μL for 2mL standard opening, conical
Water	Tedia	WL2212-001	LC Mass spectrometry