Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry

Summary

A headspace solid-phase microextraction-gas-chromatography platform is described here for fast, reliable, and semi-automated volatile identification and quantification in ripe blackcurrant fruits. This technique can be used to increase knowledge about fruit aroma and to select cultivars with enhanced flavor for the purpose of breeding.

Abstract

There is an increasing interest in measuring volatile organic compounds (VOCs) emitted by ripe fruits for the purpose of breeding varieties or cultivars with enhanced organoleptic characteristics and thus, to increase consumer acceptance. High-throughput metabolomic platforms have been recently developed to quantify a wide range of metabolites in different plant tissues, including key compounds responsible for fruit taste and aroma quality (volatilomics). A method using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) is described here for the identification and quantification of VOCs emitted by ripe blackcurrant fruits, a berry highly appreciated for its flavor and health benefits.

Ripe fruits of blackcurrant plants (Ribes nigrum) were harvested and directly frozen in liquid nitrogen. After tissue homogenization to produce a fine powder, samples were thawed and immediately mixed with sodium chloride solution. Following centrifugation, the supernatant was transferred into a headspace glass vial containing sodium chloride. VOCs were then extracted using a solid-phase microextraction (SPME) fiber and a gas chromatograph coupled to an ion trap mass spectrometer. Volatile quantification was performed on the resulting ion chromatograms by integrating peak area, using a specific m/z ion for each VOC. Correct VOC annotation was confirmed by comparing retention times and mass spectra of pure commercial standards run under the same conditions as the samples. More than 60 VOCs were identified in ripe blackcurrant fruits grown in contrasting European locations. Among the identified VOCs, key aroma compounds, such as terpenoids and C6 volatiles, can be used as biomarkers for blackcurrant fruit quality. In addition, advantages and disadvantages of the method are discussed, including prospective improvements. Furthermore, the use of controls for batch correction and minimization of drift intensity have been emphasized.

Introduction

Flavor is an essential quality trait for any fruit, impacting consumer acceptance and thus significantly affecting marketability. Flavor perception involves a combination of the taste and olfactory systems and depends chemically on the presence and concentration of a wide range of compounds that accumulate in edible plant parts, or in case of VOCs, are emitted by the ripe fruit^1,2. While traditional breeding has focused on agronomic traits such as yield and pest resistance, fruit quality trait improvement, including flavor, has long been neglected due to the genetic complexity and the difficulty to properly phenotype these characteristics, leading to consumer discontent^3,4. Recent advances in metabolomic platforms have been successful in identifying and quantifying key compounds responsible for fruit taste and aroma^5,6,7,8. Furthermore, the combination of metabolite profiling with genomic or transcriptomic tools allows the elucidation of the genetics underlying fruit flavor, which in turn will help breeding programs develop new varieties with enhanced organoleptic characteristics^{2,4,9,10,11,12,13,14}.

Blackcurrant (Ribes nigrum) berries are highly appreciated for their flavor and nutritional properties, being widely cultivated across the temperate zones of Europe, Asia, and New Zealand¹⁵. Most of the production is processed for food products and beverages, which are very popular in the Nordic countries, mainly due to the berries' organoleptic properties. The intense color and flavor of the fruit are the result of a combination of anthocyanins, sugars, acids, and VOCs present in the ripe fruits^16,17,18. The analysis of blackcurrant volatiles goes back to the 1960s^19,20,21. More recently, several studies have focused on blackcurrant VOCs, identifying important compounds for fruit aroma perception and assessing the impact of genotype, environment, or storage and processing conditions on VOC content^{5,17,18,22,23}.

Because of its numerous advantages, the technique of choice for high-throughput volatile profiling is HS-SPME/GC-MS^24,25. A silica fiber, coated with a polymeric phase, is mounted on a syringe device, allowing the adsorption of the volatiles in the fiber until an equilibrium phase is reached. Headspace extraction protects the fiber from the nonvolatile compounds present in the matrix²⁴. SPME can successfully isolate a high number of VOCs present at highly variable concentrations (parts per billion to parts per million)²⁵. In addition, it is a solvent-free technique that requires limited sample processing. Other advantages of HS-SPME are the ease of automation and its relatively low cost.

However, its success can be limited, depending on the chemical nature of the VOCs, the extraction protocol (including time, temperature, and salt concentration), sample stability, and the availability of sufficient fruit tissue^26,27. This paper presents a protocol for blackcurrant VOCs isolated by HS-SPME and analyzed by gas chromatography coupled with an ion trap mass spectrometer. A balance between the quantity of plant material, sample stability, and duration of extraction and chromatography was achieved to be able to process high numbers of blackcurrant samples, some of them presented in this study. In particular, VOC profiles and/or chromatograms of five cultivars ('Andega', 'Ben Tron', 'Ben Gairn', 'Ben Tirran', and 'Tihope') will be presented and discussed as example data. Furthermore, the same protocol has been successfully put into practice for VOC measurement in other fruit berry species such as strawberry (Fragaria x ananassa), raspberry (Rubusidaeus), and blueberry (Vaccinium spp.).

Protocol

1. Fruit harvesting

1. Grow between 4 to 6 plants per genotype and/or treatment to ensure sufficient fruit material and variability.
2. If possible, harvest the samples on the same date; if there is not enough fruit material, pool together samples harvested on different dates.
   NOTE: It is recommended that the harvest time (morning, noon, afternoon) remains approximately identical as VOC profiles are affected by daytime/circadian rhythm^28,29,30,31.
3. Assess fruit ripening stage by visual observation³². Pool fruits from the same ripening stage, as ripening status strongly impacts VOC emission. Discard any damaged or pathogen-infected fruits.
   NOTE: To better assess fruit ripeness, texture analysis can be performed³³. In addition, counting days after flowering can be used to ensure that pooled fruits belong to a similar ripening stage.
4. Include a minimum of 10-15 fruits per biological replicate (3 to 5) for VOC analysis.
   NOTE: Here, three separate pools of 13-20 fruits (biological replicates) of 'Andega', 'Ben Tron', 'Ben Gairn', 'Ben Tirran', and 'Tihope' cultivars were harvested in two locations (Poland and Scotland) in summer 2018 and directly frozen in liquid nitrogen. Samples were then sent to the laboratory and processed as described below.
5. Once harvested, freeze all fruits immediately in liquid nitrogen, and subsequently store them at -80 °C until processing.
   ​NOTE: If possible, fruits can be directly processed after harvest. In this case, fresh fruits can be homogenized in a mixer, weighed, and directly analyzed (step 3.1 onwards). However, to prevent fruits from further postharvest degradative processes, the fresh material should be stored in a cooler (4 °C) and processed as rapidly as possible. If not properly handled, liquid nitrogen can produce cold burns and can cause asphyxiation in poorly ventilated spaces.

2. Fruit sample and reagent preparation

1. Grind the fruits into a fine powder, taking care to always keep them frozen with the help of liquid nitrogen. Use a cryogenic mill, bead mill, or a mortar and pestle for homogenization. Precool stainless grinding jars or mortar and pestle with liquid nitrogen to avoid sample thawing.
   NOTE: It is critical to homogenize samples to a fine powder to ensure proper VOC extraction.
2. Weigh 1 g of frozen material (from step 2.1.) in a 5 mL tube that is previously cooled in liquid nitrogen, and note the exact weight. Keep the material at -80 °C until processing step 3.1.
3. Include 'reference' or 'control' samples in the analysis to check technical variation, including VOC extraction and HS-SPME/GC-MS performance. For this purpose, pool together a mixture of randomly chosen fruit samples, and include at least one control sample per day for VOC analysis. In addition, use an internal standard, as described in step 2.5., to minimize the impact of intensity drift.
4. Prepare 20% (w/v) sodium chloride solution in high-performance liquid chromatography (HPLC) grade water (hereafter, referred to as NaCl solution). Dissolve NaCl with the help of a magnetic stirrer; ensure the availability of 1 mL of the solution per sample.
5. Prepare a 1 ppm solution in HPLC grade methanol of N-pentadecane (D32, 98%) from pure commercial standard (hereafter, referred to as the internal standard).
   NOTE: N-pentadecane-d32 will be used as an internal standard, and 5 µL per sample will be needed. Methanol should be manipulated under a fume hood.
6. Prepare 1 ppm solutions in HPLC grade methanol of pure commercial standards for VOC identification (see Table 1 for the list of commercial standards used in this study).
7. Prepare 10 mL screw-cap headspace vials by adding 0.5 g NaCl in each needed vial. Ensure that screw caps include a septum composed of a soft material, i.e., silicone, with a thin polytetrafluoroethylene film on the inner side, to avoid contamination.

3. Sample preparation

1. Add 1 mL of NaCl solution to the 5 mL tube containing the weighed frozen sample. Shake the tube until the sample is completely thawed and homogenized.
2. Centrifuge at 5000 × g for 5 min at room temperature.
3. Transfer the supernatant with a 1000 µL pipette tip to the NaCl-containing headspace vial. Cut the end of the tip to facilitate this process.
4. Add 5 µL of internal standard to each sample-containing headspace vial.

4. HS-SPME/GC-MS data acquisition

1. Place the closed headspace vial in a GC-MS autosampler at room temperature, for an automated HS-SPME/GC-MS run, which is described in section 4. Do not place biological replicates in successive positions in the autosampler; instead, randomly distribute them to minimize the impact of intensity drift.
   NOTE: Approximately 10-12 vials can be placed at once in the autosampler, without affecting sample stability.
2. Preincubate the headspace vials 10 min at 50 °C with agitation at 17 x g.
3. Insert an SPME device into the vial to expose the fiber to the headspace for VOC extraction for 30 min at 50 °C with agitation at 17 x g.
4. Introduce the fiber into the injection port for 1 min at 250 °C in splitless mode for volatile desorption.
5. Clean the fiber in an SPME cleaning station with nitrogen (1 bar N₂, ≥ 99.8% pure) for 5 min at 250 °C. Reuse the fiber approximately 100x.
6. Analyze VOCs with a gas chromatograph coupled to an ion trap mass spectrometer (see the Table of Materials), and perform chromatography under a constant flow of helium (He ≥ 99.9999% purity) of 1 mL/min, with a column that has dimensions of 60 m x 0.25 mm x 1 μm thickness. Use an oven temperature program that is isothermal at 40 °C for 3 min, followed by an 8 °C/min ramp to 250 °C and holding at 250 °C for 5 min. For mass spectrometry, set the transfer line and ion source temperatures to 260 °C and 230 °C, respectively. Set the ionization energy to 70 eV and the recorded mass range to m/z 35-220 at 6 scans per s.
7. Extract and analyze 1 ppm solutions of commercial standards as described above. In addition, run a mixture containing all the diluted commercial standards mixed with 300 µL NaCl solution and 900 µL HPLC grade water before sample data acquisition to check the correct calibration of the equipment. Furthermore, include a blank sample containing NaCl solution alone in every batch.

5. Analysis of GC-MS profile chromatograms: VOC identification and semi-quantification

1. Open raw GC-MS profile files with the software provided by the manufacturer. To identify compounds, compare their retention times and mass spectra and Kovats linear retention indices determined from the chromatograms of the samples with retention indices obtained from authentic standards. For each commercial standard, annotate retention time and the most abundant m/z ions. Then, select a specific m/z ion for each VOC (Table 1).
2. Automatically integrate VOC peaks based on standard retention times and chosen m/z ions of the selected GC-MS raw files. For this, provide a list for each VOC with retention time and selected m/z ion. Although the software automatically integrates peak area corresponding to the same retention time and m/z ion as provided in the sequence setup, check the correct integration of each peak and correct it manually if necessary.
3. Calculate the peak area of each VOC relative to that of the internal standard to minimize instrumental variation and intensity drift.
   NOTE: When analyzing fruit from different genotypes or growth and storage conditions, it is highly recommended to determine the VOC content relative to the fruit dry weight content to rule out dilution effects due to differences in water content.
4. For batch effect correction, normalize the VOC peak area of each sample to the corresponding peak area in the control sample analyzed in the same run.
   NOTE: A relative VOC quantification is obtained; however, for the purpose of the experiment, VOC content can be then determined relative to any sample (e.g., untreated fruits to compare the effect of storage upon VOC levels).

Results

High-throughput VOC profiling in a large set of fruit crops grown under different conditions or locations or belonging to distinct genotypes is necessary for accurate aroma phenotyping. Here, a fast and semi-automated HS-SPME/GC-MS platform for relative VOC quantification in blackcurrant cultivars is presented. VOC detection and identification were based on a library that was developed to profile berry fruit species (Table 1). A typical ripe blackcurrant fruit volatile profile (total ion chromatogram) ob...

Discussion

Breeding for fruit aroma has long been hindered by the complex genetics and biochemistry underlying the synthesis of volatile compounds and the lack of technologies for proper phenotyping. However, recent advances in metabolomic platforms, combined with genomic tools, are finally allowing the identification of the metabolites responsible for consumer preferences and to breed crops with improved flavor³. While most progress has been achieved in the model fruit, tomato^9,...

Materials

Name	Company	Catalog Number	Comments
10 mL screw top headspace vials	Thermo Scientific	10-HSV
18 mm screw cap Silicone/PTFE	Thermo Scientific	18-MSC
5 mL Tube with HDPE screw cap	VWR	216-0153
Centrifuge	Thermo Scientific	75002415
Methanol for HPLC	Merck	34860-1L-R
N-pentadecane (D32, 98%)	Cambridge Isotope Laboratories	DLM-1283-1
Sodium chloride	Merck	S9888
SPME fiber PDMS/DVB	Merck	57345-U
Stainless grinding jars for TissueLyser	Qiagen	69985
TissueLyser II	Qiagen	85300	Can be subsituted by mortar and pestle or cryogenic mill
Trace GC gas chromatograph-ITQ900 ion trap mass spectrometer	Thermo Scientific
Triplus RSH autosampler with automated SPME device	Thermo Scientific	1R77010-0450
Water for HPLC	Merck	270733-1L
Xcalibur 4.2 SP1	Thermo Scientific		software