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. 2020 Sep 18;58(8):2914–2923. doi: 10.1007/s13197-020-04793-9

Chemometric optimization of trypsin digestion method applying infrared, microwave and ultrasound energies for determination of caseins and ovalbumin in wines

Jessy Pavón-Pérez 1, Karem Henriquez-Aedo 2,3, Ricardo Salazar 4, Miguel Herrero 5, Mario Aranda 6,✉
PMCID: PMC8249656  PMID: 34294953

Abstract

Caseins and ovalbumin are frequently used as wine fining agents to remove undesirable compounds like polymeric phenols. Their presence in wines is a subject of concern because may cause adverse effects on susceptible consumers, especially when their presence is not labeled. A key step for its determination is trypsin digestion, which is considered the bottleneck of bottom-up approach workflow because usually requires several hours. To reduce this time, the objective of this work was to carry out a chemometric optimization of trypsin digestion method applying infrared, microwave and ultrasound energies to determine caseins and ovalbumin in wines. The conditions of each accelerated digestion method were optimized using a Response Surface Methodology based on central composite design. The parameters optimized were digestion time and trypsin: protein ratio. The response variable evaluated was digestion yield, which was determined through the peak area of each protein transition determined by liquid chromatography-mass spectrometry. The most effective technique was microwave followed by ultrasound and infrared. Since optimal values of microwave and ultrasound-assisted digestion were the same, the later was chosen considering sample preparation and cost. Applying the proposed approach, a reduction of ca. 140 and 240-fold on digestion time was achieved compared with optimized and non-optimized conventional methods, respectively. With this workflow, both proteins were digested in a single 3 min process allowing its detection by liquid chromatography-mass spectrometry at µg L−1 level, which is ca. 60 times lower than the current limit of 0.25 mg L−1.

Keywords: Fining agents, Mass spectrometry, Central composite design, Response surface methodology

Introduction

In winemaking process different kind of clarifying agents are used to eliminate/reduce unwanted wine compounds such as polymeric phenols and proteins responsible for haze (Dordoni et al. 2015). Caseins (milk protein) and ovalbumin (egg-white protein) are commonly utilized for fining white and red wines, respectively (Gonzalez-Neves et al. 2014). This enological practice produces that a certain amount of these allergenic proteins remains in wines, which can be a health risk for susceptible consumers, especially when their presence is unlabeled in the final product. Due to this food safety issue, the European Union through the Directive 89/2003/EC, 579/2012/EC and its latest version 2019/33/EC listed the potential food allergenic substances including both, milk and egg derivatives (European Commission 2019). This Directive makes mandatory the declaration of these proteins on wine label when the concentration in wines is superior to the analytical limit established in OIV/COMEX/502/2012 resolution (Organisation Internationale de la Vigne et du Vin (OIV) 2012). Currently, this limit is set at 0.25 mg L−1, evaluated via enzyme-linked immunosorbent assay-ELISA (Vogt et al. 2016), which is a simple and fast immunoassay (Rolland et al. 2008) but presents some drawbacks and limitations (Pavón-Pérez et al. 2019).

Other analytical approaches like two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) (Mainente et al. 2014) and liquid chromatography (LC) (Mattarozzi et al. 2014) have become suitable alternatives, because with both techniques proteins and peptides are separated, which is one of the key-step for an accurate and precise determination. 2D-PAGE is a labor-intensive technique with some limitations in detecting hydrophobic and alkaline proteins (Chambery et al. 2009). Additionally, most steps are still manual or with minimal automatization.

In this scenario, liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS) has become the most suitable technique for proteomic analysis. This hyphenated technique offers several advantages, including multi-allergen detection and unambiguous identification and characterization of food allergens (Cristina et al. 2016). Proteomic analysis can be accomplished by performing two different strategies: top-down or bottom-up. In the first one, intact proteins are analyzed without previous digestion, whereas in the second, enzymatic digestion is required before LC–MS/MS analysis, which is based on the comparison of peptides (digestion products) MS/MS spectra with protein-sequence databases (Monaci and Visconti 2009). This approach is one of the most employed strategies because the information obtained from mass spectra is much easier to interpret than those acquired by top-down approach (Chiva et al. 2014). However, in bottom-up proteomics, sample preparation is an important limitation since it requires complex and time-consuming procedures with many different steps, which must be done carefully to achieve reliable results (Rial-Otero et al. 2007). Protein digestion for LC–MS/MS analysis is mostly carried out using trypsin enzyme that cleaves exclusively basic residues of arginine and lysine, which generates peptides with an adequate mass range (7–9 amino acids) for MS analysis (Loziuk et al. 2013). Unfortunately, trypsin digestion time (12 to 24 h) is incompatible with high-throughput protein analysis being considered the bottleneck of bottom-up analysis (Reddy et al. 2010).

In this respect, several efforts have been done to reduce digestion time, for example, an enzymatic reactor with different kinds of supports was developed, e.g. magnetic particles (Li et al. 2010), polymer particles (Yuan et al. 2009) and monolithic materials (Rivera and Messersmith 2012). Other sample preparation techniques like microwave (Chen et al. 2014; Pramanik et al. 2002; Reddy et al. 2010), infrared (Wang et al. 2008) and ultrasound-assisted digestion (Guo et al. 2017) have been assayed in different types of samples due to their advantages compared with conventional methods. For example, Chen et al. (2014) used microwave-assisted (MA) digestion to determine bovine serum albumin (BSA) and proteins extracted from ginkgo nuts; Bao et al. (2009) applied infrared-assisted (IRA) digestion for in-gel proteolysis of human serum; Dominguez-Vega et al. (2010) employed ultrasound-assisted (UA) digestion to accelerate the cleavage process of soybean protein and Santos et al. (2007) using a sonoreactor achieved in 5 min a similar peptide profile than classical approach. MA digestion is capable of accelerating enzymatic cleavage by rotation of bipolar molecules inducing a perturbation of protein three-dimensional structure, which exposes some protein regions previously inaccessible for proteolytic enzyme (Chen et al. 2014; Joergensen and Thestrup 1995). Reddy et al. (2010) studied how different solvents, reaction times, enzyme to protein molar ratios, and microwave temperatures affected the digestion processes of myoglobin, lysozyme, cytochrome c, ubiquitin, ribonuclease A, α-casein, albumin and transferrin. They concluded that all these proteins could be digested into peptides within 30 min at 60 °C under microwave irradiation. IRA digestion is based on the use of radiation as a heat source, which possesses a high molecular penetration (Wang et al. 2008). UA digestion has demonstrated high efficiency in shortening processing time (Kadam et al. 2015). UA mechanism is not fully elucidated but it has been related to an increment in diffusion rates as a result of cavitation phenomenon and heating (Santos et al. 2007). Cavitation crushing produces large mechanical shearing forces resulting in a degradation of protein structure and the opening of hydrophilic groups. This structural phenomenon increases the protein solubility that facilitates the enzyme–substrate (protein) interaction (Kadam et al. 2015). UA digestion has been applied using different energy intensities through diverse types of sources, e.g. sonoreactor, ultrasonic probes and ultrasound baths (Dominguez-Vega et al. 2010; Rial-Otero et al. 2007).

Currently, there is not well-established standard protocol for trypsin cleavage; parameters such as digestion time and the enzyme to substrate ratio are highly dependent on personalized laboratory protocols. Traditional enzyme to protein ratios used for bottom-up proteomics approach range from 1:100 to 1:2.5 (Loziuk et al. 2013). Since several factors can affect trypsin activity, the most efficient approach to optimized trypsin digestion conditions is the application of chemometric tools. Mattarozzi et al. (2014) and Tolin et al. (2012) proposed sensitive LC–MS/MS methods for allergens detection in red wines, however, trypsin digestion required several hours (overnight).

The objective of this work was to carry out a chemometric optimization of trypsin digestion method applying infrared, microwave and ultrasound energies to determine caseins and ovalbumin in wines. To the best of our knowledge, this is the first report about chemometric optimization of trypsin digestion method applying these techniques for α-casein, β-casein and ovalbumin determination in wines.

Materials and methods

Reagents, standards and samples

Albumin (> 98%, CAS 9006-59-1) from chicken egg white and casein (87–94%, CAS 9000-71-9) from bovine milk, sodium dodecyl sulfate (SDS, > 99%), iodoacetamide (IAM, > 99%), 2-mercaptoethanol (98%) and DL- dithiothreitol (DTT, > 99%) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Trichloroacetic acid (TCA, > 99%), acetic acid (100%), formic acid (98–100%), citric acid, sodium hydroxide, ammonia solution (> 25%), ammonium hydrogen carbonate (NH4HCO3, 99%), absolute ethanol, acetic acid (100%), silver nitrate (AgNO3, extra pure), formaldehyde solution (37%), sequencing modified trypsin from bovine pancreas and LC-grade acetonitrile were obtained from Merck (Darmstadt, Germany). Bis-Acrylamide (> 99%), Acrylamide (> 99.9%), Tris buffer (1 mol L−1, pH 8.8 and pH 6.8), ammonium persulfate, tetramethylethylenediamine (TEMED, > 99%), were bought from Winkler (Santiago, Chile). Precision Plus Protein All Blue Prestained Protein Standards, 4 × Laemmli sample buffer were purchased from Bio-Rad (California, USA). Ultrapure water (18.2 MΩ cm) was produced by Simplicity system from Millipore (Bedford, MA, USA). Stock solutions were prepared in a 0.05 mol L−1 NH4HCO3 solution (pH 7.8) for a given concentration of 12 mg L−1 casein and ovalbumin. Pooled standard solutions were prepared by aliquot dilution from stock solution.

Sample preparation

Sample preparation was carried out following the protocol reported by Pavón-Pérez et al. (2019). Briefly, red wine samples (blank), free of allergen proteins, were spiked with 1.2 mg L−1 of each protein. After vortex-mixing, 12.5 mL of sample were centrifuged at 5433 × g for 40 min at 20 °C into Amicon (Merck) 10 kDa cut-off membrane ultrafiltration tube, previously conditioned with 10 mL of ultrapure water using a Hettich (Tuttlingen, Germany) refrigerated centrifuge. After centrifugation, proteins from 2.5 mL of retained volume were precipitated on ice for 2 h after addition of eight volumes of 15% w/v of TCA in ethanol. The mixture was then centrifuged at 8981 × g for 10 min at 4 °C and solvent residues were evaporated under a gentle flow of nitrogen without heat. The formed pellet was solubilized in 1 mL of 0.05 mol L−1 NH4HCO3, pH 7.8. Before trypsin digestion, proteins were first reduced adding 12 µL of 0.10 mol L−1 DTT followed by 5 min incubation at 95 °C, thereafter cysteine SH-groups were alkylated (irreversible) by addition of 24 µL of an aqueous solution of 0.10 mol L−1 IAM (freshly prepared), letting react protected from light for 15 min at room temperature. Enzymatic cleavage was done adding 4 µL of trypsin solution (0.5 mg mL−1, in 0.05 mol L−1 of NH4HCO3, pH 7.8) for a trypsin to protein ratio of 1:10, the reaction mixture was incubated according to the digestion method under study. Reaction was stopped adding 10 µL of aqueous solution of formic acid (0.1%v/v). All digestion products were filtered through a 13 mm PVDF syringe filter (0.22 µm) before gel electrophoresis (GE) and LC–MS/MS analysis.

Trypsin digestion conditions

UA- and IRA protein digestion procedures were carried out in Brand (Wertheim, Germany) 1.5 mL microcentrifuge tubes. Each digestion (time and trypsin to protein ratios) condition was prepared according to the experimental plan established via chemometric tool. IRA digestions were performed in a home-made IR oven following Wang et al. (2008) protocol. UA digestion experiments were performed in a BiosLab (Santiago, Chile) ultrasonic bath model SB-5200D, which provides indirect sonication with a frequency of 40 kHz with adjustable temperature. MA digestion conditions were assayed on Milestone (Sorisole (BG), Italy) Ethos UP with contact-less temperature and pressure sensors, applying a microwave power of 400 W and the lowest controlled temperature (41 °C).

Gel electrophoresis

One-dimensional SDS-PAGE was used to evaluate each digestion method following the conditions reported by Laemmli (1970) with slight modifications. Briefly, GE was carried out on a vertical chamber from Biotec (Santiago, Chile) using a Bio-Rad (Bio-Rad, Hercules, CA) PowerPac 1000 power supply set at 100 V (constant) for 120 min at room temperature. Before application onto 14% polyacrylamide gels, standards (1 mg L−1 of casein and ovalbumin in 0.05 mol L−1 of NH4HCO3, pH 7.8) were mixed at 1:4 ratio with 4 × Laemmli sample buffer (0.0625 mol L−1 Tris–HCl pH 6.8, 10% v/v glycerol, 1% lithium dodecyl sulfate (LDS), and 0.005% bromophenol blue) and heated for 4 min at 95 °C. 10 µL of this mixture were loaded onto the gel. After the electrophoretic run, gels were silver stained according to the method reported by Blum et al. (1987) with slight modifications. Briefly, gels were incubated for one hour into a fixer solution composed of ethanol: water: acetic acid (3:6:1 v/v/v); washed with ultrapure water for at least 30 min and incubated for 20 min in a silver staining solution. Gels were washed three times with ultrapure water for 10 min and then immersed into a solution composed of citric acid, formaldehyde and water for 2–3 min until the protein bands get dark stained.

Liquid chromatography – tandem mass spectrometry

Following the method proposed by Pavón-Pérez et al. (2019), LC–MS/MS analysis was performed on Shimadzu (Kyoto, Japan) Nexera X2 UHPLC system consisted of LC-30AD pump, DGU-20A5R degassing unit, SIL-30AC autosampler, CTO-20AC column oven, CBM-20A communication module, SPD-M20A diode array detector and LCMS-8030 triple quadrupole (TQ) mass spectrometer. The system was controlled by Shimadzu LabSolution 5.8 software. Peptides separation was carried out on a Phenomenex (Torrance, CA, USA) Kinetex XB Core–Shell C18 column (100 mm × 4.6 mm, id. 2.6 µm), thermostated at 35 °C, using a binary mobile phase composed of ultrapure pure water (A) and acetonitrile (B) both with 0.1% (v/v) formic acid. Gradient elution was applied at a flow rate of 0.6 mL min−1 using the following program: 0–19 min, 10–40% B; 19–20 min, 40–10% B; with 5 min for column conditioning. MS parameters were set as follows for multiple reaction monitoring (MRM) mode: ESI in positive mode using a voltage of 4.5 kV; collision energy of − 30.0 V for casein and − 40.0 V for ovalbumin; nebulizer gas (N2), 3 L min−1; desolvation gas (N2), 18 L min−1; desolvation line temperature, 250 °C; heat block temperature, 400 °C. Full scan spectra were acquired from m/z 100 to 2000. Digestion yields were determined through peptide formation, which was quantified in MRM mode. Transitions were defined according to Pavón-Pérez et al. (2019), the two most abundant and stable fragments from product ion spectrum for each peptide were chosen, one for qualitative/confirmatory and other for quantitative purposes. Peak areas of the following MRM transitions were defined as the variable response for each different digestion method: m/z 634.6 → 991.8 for α-casein, m/z 390.9 → 258.5 for β-casein and m/z 929.5 → 1116.5 for ovalbumin.

Statistical analysis

Data were studied using descriptive statistics [mean, standard deviation (SD) and relative standard deviation (RSD)]. Peptides calibrations were adjusted to a linear regression model. F-test was used to compare calibrations with and without matrix. All above tests were done with a significance level (α) of 0.05 using GraphPad (San Diego, CA, USA) Prism 6.0 software. Central composite design was prepared and analyzed employing SAS (Marlow, Buckinghamshire, England) JMP 8 statistical software. An analysis of variance (ANOVA) with a significance level of 0.05 was carried out to define which experimental factors significantly affect the model response (peak area) measured via MRM transitions. All analyses were performed at least by duplicate.

Results and discussion

Optimization of trypsin digestion conditions

As mention before, enzymatic digestion is considered the bottleneck of bottom-up analysis because enzyme cleavage usually requires ca. 12–24 h. In this scenario, the present work evaluated the use of modern techniques to reduce trypsin digestion time. The efficiency, repeatability and reliability of each assayed method were evaluated by SDS-PAGE, percentage of sequence coverage (%SQ) and peak area of each MRM transitions (α-casein 634.6 → 991.8, β-casein 390.9 → 258.5, ovalbumin 929.5 → 1116.5, Fig. 1). SDS-PAGE was carried out using a standard mixture (1 mg L−1) because red wines polyphenols may produce certain level of interference with silver staining resulting in higher background, and low bands resolution (Vogt et al. 2016). %SQ is commonly used to evaluate protein digestion efficiency (Shevchenko and Shevchenko 2001) and its value is easily obtained from database like Mascot. UA-, MA- and IRA protein digestion conditions were individually optimized applying a Response Surface Methodology based on face-centered central composite design (CCD) with two central points. This experimental design is one of the most used to optimized diverse analytical parameters due to its high efficiency regarding the number of experiments (Angulo et al. 2020; Galarce-Bustos et al. 2019). Since one of the most relevant aspects of wine allergen proteins evaluation is method's detection capability, α-casein, β-casein and ovalbumin peak areas (digestion yields) from MRM determination were defined as the critical variable (response) looking for lower detection limits. Among, the factors that could affect the critical variable, two were chosen: digestion time (X1), and enzyme to protein ratio (X2). Considering that lower or higher amounts of trypsin may cause incomplete digestion or auto-cleavage, and taking into account previous reports about traditional digestion conditions optimization (Pavón-Pérez et al. 2019), the following ranges were studied for digestion time (3.0 to 30.0 min), and enzyme to protein ratio (1:10 to 1:100), which resulted in a 10 runs experimental plan for each method (MA, UA, IRA) including two center points. All experiments were conducted in duplicate (n = 2) in randomized order to minimize the effects of uncontrolled factors using red wine samples (free of allergen) spiked with 1.2 mg L−1 of each protein.

Fig. 1.

Fig. 1

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LC–ESI–MS/MS chromatograms in MRM mode of red wine sample (blank) spiked with 1.2 mg L−1 of each protein using optimal UA digestion conditions for β-casein (a), α-casein (b), and ovalbumin (c) detection

Optimization of infrared-assisted digestion

Experimental results showed that digestion time (quadratic coefficient) affected α-casein (P = 0.0009) and β-casein (P = 0.04) yields. The determination coefficient (R2) in all cases was higher than 0.75, indicating a close relationship between the experimental data and the model. Lack of fit test for quadratic models showed P-values higher than 0.05 which is adequate in terms of model suitability (Derringer and Suich 1980). Using digestion yields from each MRM transition (Table 1) an individual optimum was defined for each response, with which a multiple response optimization was performed to establish optimal conditions for all responses (desirability conditions, Fig. 2a). The optimal IRA digestion conditions to simultaneously determine α-casein, β-casein and ovalbumin in wines were 16 min as digestion time and 1:10 enzyme to protein ratio. MRM signals intensities were very low for each transition, which can suggest deficient enzymatic digestion, but taking into account that infrared technique is highly energetic and contributes to intensify reactions a peptide decay due to excessive digestion cannot be discarded (van den Broek et al. 2013). Usually, peptides formation by tryptic digestion can follow one of three types of kinetic: (1) fast forming peptides reaching rapidly a plateau; (2) slow forming peptides never reaching a maximum and (3) rapidly forming peptides that degrade over time (Lesur et al. 2010; van den Broek et al. 2013). As can be observed in Fig. 2, IRA digestion showed a type-3 kinetic profile, with a fast peptides formation that degrade over time. The low MRM signals might be influenced by the experimental conditions, particularly the physical configuration of IR oven, which also seems to have affected the results in terms of reproducibility. MS/MS results were concordant with stained SDS-PAGE gels that showed unclear bands from digested proteins. As expected, %SQ values were only 5, 4 and 3 for α-casein, β-casein and ovalbumin, respectively.

Table 1.

Experimental runs for a central composite design for IR-assisted digestion with the corresponding responses (means) for each MRM transition (peak area)

Factors Responses (peak area, m/z)*
Time (min) Enzyme: protein ratio 634.6 → 991.8 390.9 → 258.25 929.5 → 1116.5
1 16.5 1:20 691.00 ± 1.50 2175.00 ± 4.24 47.00 ± 2.08
2 30.0 1:10 61.00 ± 0.35 335.00 ± 0.35 65.00 ± 2.70
3 3.0 1:10 152.00 ± 2.12 863.00 ± 2.88 63.00 ± 2.82
4 16.5 1:20 106.00 ± 1.70 402.00 ± 2.47 26.00 ± 3.88
5 30.0 1:100 675.00 ± 2.94 2954.00 ± 3.59 23.00 ± 2.82
6 3.0 1:20 34.00 ± 2.51 98.00 ± 2.82 28.00 ± 3.30
7 16.5 1:10 134.00 ± 2.21 679.00 ± 0.50 47.00 ± 2.98
8 3.0 1:20 848.00 ± 1.41 6319.00 ± 4.78 118.00 ± 1.41
9 30.0 1:20 29.00 ± 2.47 196.00 ± 3.53 19.00 ± 1.50
10 16.5 1:100 470.00 ± 3.18 1017.00 ± 0.35 62.00 ± 1.50
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*mean ± standard deviation (n = 2)

Fig. 2.

Fig. 2

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Response surface plots for α-casein, β-casein and ovalbumin transitions obtained with IR (a), MA (b) and UA (c) assisted trypsin digestion

Optimization of microwave-assisted digestion

MA digestion was assayed considering its capability of favoring fast protein cleavage even at very lower amount. Zhao et al. (2016) used microwave energy to accelerate enzymatic digestion of bovine serum albumin, b-lactoglobulin, and cytochrome c, reducing 15-fold the analysis time compared with traditional in-solution method (1 h vs. 15 h). In concordance with this report, our results showed also an important decrease in digestion time detailing the relation between both factors. According to results, trypsin to protein ratio affected α-casein (P = 0.005), β-casein (P = 0.02) and ovalbumin (P = 0.01) yields, while digestion time affected β-casein yield (P = 0.002). The model was validated through ANOVA, which showed R2 values of 0.90, 0.94 and 0.85 for α-casein, β-casein and ovalbumin responses, respectively. Lack of fit test for quadratic models showed P values higher than 0.05, acceptable in terms of model suitability (Derringer and Suich 1980). Individual optimum was defined for each response using the digestion yields from each MRM transition (Table 2). Desirability conditions were established applying a multiple response optimization, with which the following optimal trypsin cleavage conditions for simultaneously evaluate α-casein, β-casein, and ovalbumin in wines were defined: 3 min as digestion time and 1:10 enzyme to protein ratio. This digestion time is ca. 140-fold (99%) lower than the one (7 h) previously obtained by Pavón-Pérez et al. (2019); 3 times lower (70%) than the one (10 min) reported by Pramanik et al. (2002) for several types of proteins; and ca. twofold lower than the one published by Wu et al. (2015) for myoglobin (horse), BSA (bovine), and α- casein (bovine milk) digestions. MRM results were concordant with stained SDS-PAGE gel, which showed a large number of bands corresponding to the peptides from digested proteins. %SQ were also adequate observing values of 25, 24 and 21 for α-casein, β-casein, and ovalbumin, respectively. In Fig. 2b, it can be observed that α-casein and ovalbumin showed a type-1 kinetic profile, which is fast forming peptides reaching rapidly a plateau. In β-casein surface plot, this type of kinetic was not evidently detected due to a slight but sustained decrease of peak area values along the digestion time. Maybe the higher peptides formation from β-casein could lead to a higher peptide degradation; and/or the domain (interval) selected for this protein was not large enough. Even when the kinetic profile of β-casein was not clearly observed, the results showed an adequate peptide formation using a 3 min digestion. In general terms, MA digestion is a highly efficient technique, the elevate pressure reached increases protein denaturation and trypsin cleavage; and the heat generated, due to molecular vibrations, enhances the interaction between trypsin and proteins improving the digestion efficiency.

Table 2.

Experimental runs for a central composite design for microwave-assisted digestion with the corresponding responses (means) for each MRM transition (peak area)

Factors Responses (peak area, m/z)*
Time (min) Enzyme: protein ratio 634.6 → 991.8 390.9 → 258.25 929.5 → 1116.5
1 30.0 1:20 3252.00 ± 3.18 9245.00 ± 2.12 178.00 ± 1.41
2 3.0 1:100 2555.00 ± 2.47 10,877.00 ± 1.73 108.00 ± 1.00
3 3.0 1:20 3384.00 ± 4.24 11,218.00 ± 2.82 175.00 ± 1.50
4 30.0 1:100 1273.00 ± 1.00 9631.00 ± 2.62 110.00 ± 1.41
5 3.0 1:10 3815.00 ± 3.18 13,303.00 ± 2.38 221.00 ± 2.82
6 16.5 1:100 1391.00 ± 1.76 10,136.00 ± 1.70 145.00 ± 4.27
7 30.0 1:10 3265.00 ± 3.30 10,050.00 ± 2.06 185.00 ± 1.70
8 16.5 1:20 2985.00 ± 2.12 10,351.00 ± 2.75 171.00 ± 2.98
9 16.5 1:10 4098.00 ± 1.29 10,649.00 ± 0.50 174.00 ± 1.70
10 16.5 1:20 2690.00 ± 4.24 10,419.00 ± 0.95 166.00 ± 2.44
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*mean ± standard deviation (n = 2)

Optimization of ultrasound-assisted digestion

UA digestion has emerged as a powerful strategy for proteomics analysis because drastically reduces the time required for protein digestion (Rial-Otero et al. 2007). Dominguez-Vega et al. (2010) described a soybean protein digestion in one minute using an ultrasonic probe. This study evidenced the efficiency of this type of energy for proteins digestion. Our experimental results showed the same trend, applying UA digestion (see conditions in “Trypsin digestion conditions” Section) it was observed that trypsin to protein ratio significantly affected β-casein (P = 0.01) and ovalbumin (P = 0.03) yields, whereas digestion time significantly modified α-casein (P = 0.005) and β-casein (P = 0.002) yields. ANOVA validation showed R2 > 0.90 for all peptides transitions and non-significant lack of fit (P > 0.05), which is adequate in terms of model suitability (Derringer and Suich 1980). Based on MRM results (Table 3) each optimum was established, with which a multiple response optimization was calculated to define the optimal conditions for all responses (desirability conditions, Fig. 2c). Optimal trypsin digestion conditions to simultaneously determine α-casein, β-casein and ovalbumin in wines were 3 min as digestion time and 1:10 enzyme to protein ratio. Stained SDS-PAGE gel confirmed the peptides formation (dotted square) by comparison of digested and non-digested protein tracks (Fig. 3). Low protein concentration, at ng mL−1 level, made difficult a clear band visualization due to the lower contrast. In tracks a and d, it was possible to notice two bands between 10 and 20 kDa that could be related to m/z values observed in the mass spectra. The band observed in track d, at ~ 10 kDa could be related to the ovalbumin m/z 929.5 (10+). Same inference can be done for ~ 20 kDa band, observed in track a, which could correspond to casein m/z 634.6 (30+). %SQ values were appropriated showing values of 25, 26 and 23 for α-casein, β-casein, and ovalbumin, respectively. In Fig. 2c is observed that peptide formation using UA digestion did not follow a typical kinetic. For any fixed ratio substrate/enzyme the peak areas decrease over time. This phenomenon can be explained by fast digestion, reaching the plateau before 3 min. Therefore, the most likely type of kinetic is a rapidly forming peptides that degrade over time. Despite the lack of typical kinetic profile, the amount of peptide formed (peak area) using a 3 min digestion was suitable for α-casein, β-casein and ovalbumin detection in wines at µg L−1 level, which is ca. 60 times lower than the current limit (0.25 mg L−1).

Table 3.

Experimental runs for a central composite design for ultrasound-assisted digestion with the corresponding responses (means) for each MRM transition (peak area)

Factors Responses (peak area, m/z)*
Time (min) Enzyme: protein ratio 634.6 → 991.8 390.9 → 258.25 929.5 → 1116.5
1 30.0 1:10 233.00 ± 0.35 1350.00 ± 4.59 36.00 ± 1.06
2 3.0 1:100 760.00 ± 2.12 2823.00 ± 2.82 58.00 ± 2.47
3 3.0 1:10 1000.00 ± 3.18 9018.00 ± 0.70 105.00 ± 0.35
4 16.5 1:100 311.00 ± 11.31 1478.00 ± 5.65 167.00 ± 0.70
5 16.5 1:20 493.00 ± 1.76 2546.00 ± 7.42 94.00 ± 0.00
6 16.5 1:10 598.00 ± 2.47 2764.00 ± 0.70 51.00 ± 0.70
7 30.0 1:20 173.00 ± 8.38 877.00 ± 6.71 47.00 ± 1.06
8 3.0 1:20 845.00 ± 2.82 4604.00 ± 0.35 48.00 ± 5.31
9 30.0 1:100 173.00 ± 0.00 862.00 ± 1.06 176.00 ± 2.75
10 16.5 1:20 110.00 ± 4.94 1555.00 ± 2.12 107.00 ± 5.25
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*mean ± standard deviation (n = 2)

Fig. 3.

Fig. 3

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Stained SDS-PAGE showing the peptides obtained after ultrasound-assisted trypsin digestion of ovalbumin (a) and casein (d) compared with ovalbumin (b) and casein (c) native proteins

Conclusion

Wine industry is a very important sector of Chile’s economy in terms of productivity, exports and employment. In this sense, it is very important to reduce the risks associated with the presence of allergenic proteins in wines that could affect susceptible people. Thus, it is necessary to develop high throughput methods of analysis that ensure wines quality in terms of food safety. In this way, the reduction of trypsin digestion time contributes to solving one of the bottlenecks of bottom-up approach workflow. Further, the proposed cost-effective analytical procedure provides adequate support to establish routine analysis by mass spectrometry. An efficient determination of the optimal conditions was achieved through Response Surface Methodology based on central composite design. The optimized MA, UA and IRA protocols allowed the reduction of digestion time as well as an increase in trypsin cleavage yields. According to results obtained via MRM of marker peptides, the most effective technique was MA follow by UA and IRA. Since MA and UA showed the same optimal values (3 min and trypsin protein ratio of 1:10), UA was chosen considering the simplicity of sample preparation procedure and equipment cost. This technology allowed the reduction of protein digestion time from 7 h to 3 min (140-fold reduction) without compromising %SQ. Further, compared with non-optimized conventional digestion time, the reduction was ca. 240-fold, from 12 h to 3 min. To the best of our knowledge, this is the first report describing a chemometric optimization of trypsin digestion method applying infrared, microwave and ultrasound energies for α-casein, β-casein and ovalbumin determination in wines.

Acknowledgments

This work is part of Jessy Pavón-Pérez thesis to obtain the degree of Doctor in Science and Analytical Technology from the University of Concepcion, Chile. Authors thank to the National Commission of Scientific and Technological Research (CONICYT) of the Chilean Government for the doctoral scholarship granted. This study was funded by the National Fund for Scientific and Technological Development (FONDECYT) Project No. 1171857 and by the National Fund for Scientific and Technological Equipment (FONDEQUIP) Project No. 130209.

Footnotes

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