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The hidden “digestome”: current analytical approaches provide incomplete peptide inventories of food digests Maristella De Cicco, Gianfranco Mamone, Luigia Di Stasio, Pasquale Ferranti, Francesco Addeo, and Gianluca Picariello J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.9b02342 • Publication Date (Web): 15 May 2019 Downloaded from http://pubs.acs.org on May 18, 2019
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Journal of Agricultural and Food Chemistry
The hidden “digestome”: current analytical approaches provide incomplete peptide inventories of food digests Maristella De Cicco‡, Gianfranco Mamone‡, Luigia Di Stasio‡,#, Pasquale Ferranti#, Francesco Addeo#, Gianluca Picariello*,‡
‡Institute
of Food Sciences – National Research Council (CNR), Via Roma 64, 83100 Avellino, Italy
#Department
of Agriculture, University of Naples “Federico II”, Parco Gussone, Via Università 100,
80055 Portici (Naples), Italy
*correspondence to:
[email protected] – Tel. +39 0825 299521
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ABSTRACT 1
Analyzing an in vitro gastroduodenal digest of whey proteins by HPLC coupled to high-
2
resolution/high-sensitivity MS/MS, we sought to evaluate if state-of-art peptidomics provides
3
comprehensive peptide coverage of a food “digestomes”. A multitude of small-sized peptides derived
4
from both -lactalbumin and β-lactoglobulin as well as disulfide cross-linked hetero-oligomers
5
remained unassigned, even when the digests were compared before and after S-S reduction. The
6
precipitation with 12% trichloroacetic acid demonstrated the occurrence of large-sized polypeptides
7
that escaped the bioinformatic identification. The analysis of a HPLC-MS/MS run with different
8
proteomic search engines generated dissimilar peptide subsets, thus emphasizing the demand of
9
refined searching algorithms. Although the MS/MS fragmentation of mono-charged ions with exclusion
10
of non-peptide interfering compounds enlarged the inventory of short peptides, the overall picture of
11
the “digestome” was still incomplete. These findings rise relevant implications for the identification of
12
possible food-derived bioactive peptides or allergenic determinants.
Keywords: Food peptide digestomes, bioactive peptides, food allergens, HPLC-MS/MS, disulfide crosslinked peptides, protein digestibility, whey proteins
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INTRODUCTION 13
The research focused on discovery of food-derived bioactive peptides and assessment of their activity
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has increased exponentially over the last decades. To date, bioactive peptides have been described in
15
a very ample range of food matrices, including milk and dairy products, eggs, meat, fish, legumes and
16
cereals. Bioactive peptides are linear amino acid sequences that remain inactive as long as they are
17
encrypted in the parent protein and became active upon proteolytic release, exhibiting a wide range of
18
more or less evident effects in vivo. 1 The gastrointestinal (GI) stability of food-derived peptides is an
19
obvious requirement to exert bioactive effects, either at a systemic or at a local level.
20
Recently, the release of possible bioactive peptides from foods has been predicted with
21
bioinformatic approaches, based on known proteolytic specificity of digestive proteases, expected
22
stability of protein domains and interaction models of bioactive motifs with receptors, enzymes or
23
antibodies.2 Combinatorial models, computational advances and combined analytical workflows concur
24
to predict the formation of peptide components within complex food-derived digests.3-4 However, in
25
general in silico predictions do not mirror the in vitro or in vivo outcomes, due to the molecular and
26
structural complexity of the food matrices, process-induced modifications and inter-/intra-individual
27
variability of the human digestion physiology. Thus, the typical pipeline to discover single or panels of
28
candidate peptides able to induce a response in relevant biological systems (molecular targets, cells,
29
tissues and organisms) still firmly grounds on the peptidomic characterization of food digests obtained
30
through in vitro, ex-vivo or in vivo models. Several strategies can be used to enrich/isolate and
31
characterize specific peptides from complex digests, in order to test them in biological assays.5 The
32
most advanced methods in this sense make extensive use of mass spectrometry (MS).
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Generally, protein digestomes comprise free amino acids, small-/medium-size peptides, large
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polypeptides, also including possible disulfide-linked heterodimer/oligomers, and in some case variable
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amounts of undigested proteins. Ordinary proteomic/peptidomic workflows involve automated ion
36
selection for tandem MS (MS/MS) fragmentation (data dependent acquisition), excluding singly
37
charged species in order to limit the interference by background low-molecular weight compounds.
38
Due to the complexity of the digestomes, the eventuality of assigning hundreds-to-thousands
39
individual peptides manually is impracticable. Therefore, more than 30 different search engines have
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been developed in the last decades to identify peptides in complex proteolytic mixtures.6 Some of them
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perform spectral library searching or are capable of de novo sequencing, whereas others match
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experimentally obtained fragmentation spectra with theoretical ones generated from a protein
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sequence database.7 In all cases, the matching score from available algorithms increases proportionally
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with peptide length, thus intrinsically underrepresenting small peptides, which often comprise those
45
involved in bioactive actions. The identification of very short peptides (< 5 amino acids) could also be
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hindered by insufficient fragmentation patterns, inadequate to distinguish between several possible
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isobaric sequences.8 Thus, the untargeted identification of small-sized peptides in a food digestome can
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severely challenge the potentiality of peptidomics.9
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Several expedients have been developed to overcome these limitations, including: i) N-terminal
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derivatization;10 ii) prediction methods of hydrophobicity and retention time coupled to hydrophilic
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interaction liquid chromatography (HILIC)-MS/MS;8 iii) prediction of the released peptides and reversed
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phase UPLC-MS/MS combined to a de novo sequencing stage.11 These methods have advantages and
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disadvantages, but all introduce more or less laborious steps in the identification process and, for this
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reason, they are not routinely used yet. 4 ACS Paragon Plus Environment
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The MS detection of food-derived large-sized polypeptides in a complex digest can be
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problematic as well, due to suppression ion effects, reduced sensitivity associated with wide charge
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distribution and limited fragmentation efficiency.12 A number of structural features, such as low
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solubility, intrinsically scarce ionization efficiency, presence of post-translational modifications (e. g.
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multiple phosphorylation or glycosylation), incompleteness of the protein databases, variability of
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protein isoforms and presence of hard-to-identify disulfide cross-linked peptide heterodimers,13-14
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further limits the comprehensive characterization of a food digestome. The complexity can even
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increase when foods undergo thermal processing, due to variable protein modifications.
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The intrinsic stability to GI digestion of large domains has long been considered among the
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primary factors in the allergenicity risk assessment of food proteins.15 Many food allergens are proteins
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highly resistant to proteolytic enzymes. Likewise, the GI stability of gluten proteins have a recognized
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role in the pathological mechanisms of celiac disease.16-17 For this reason, identification of food protein
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sequences surviving GI digestion is largely used to predict possible peptide determinants of adverse
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reaction to foods. On the other hand, the correlation of digestion stability with sensitizing/eliciting
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capacity in the etiopathology of food allergy still appears controversial. There are more than a few
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examples of food allergens, such as -lactalbumin, caseins, thermally treated ovalbumin and peanut
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(Arachis hypogaea) Ara h 1,18 which are believed substantially labile and susceptible to fast digestion
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proteolysis. In effects, these proteins are broken down into small peptides within seconds or minutes
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when incubated with pepsin or downstream with duodenal and intestinal proteases/peptidases.
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Nevertheless, the survival of potentially immunogenic/allergenic large polypeptides at low abundance
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has not been adequately investigated.19-20 The minimal dose of determinants able to sensitize or elicit
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an allergic response is not known and, in principle, even very small amounts of polypeptides survived 5 ACS Paragon Plus Environment
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digestion could be responsible of an allergic response in predisposed individuals. These aspects are still
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underexplored, as stability or susceptibility to digestion of food proteins has been typically evaluated
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monitoring the disappearance of the protein bands by SDS-PAGE analysis, while only sporadically the
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peptide digests have been characterized in depth using MS-based peptidomics. Even using advanced
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techniques, the characterization of a complex “digestome” is a challenging task, which heavily depends
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on the fractionation and enrichment of specific set of components as well as on technical and
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contingent performance of MS instrumental resources.21 Notably, standard procedures for a
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comprehensive characterization of food digests do not exist yet.
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Herein, through the high resolution HPLC-MS/MS characterization of a digest of whey proteins obtained
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with a static in vitro method of simulated digestion,22 we tried to address the non-trivial question: do
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the current analytical approaches provide comprehensive peptide inventory of a food digest?
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This issue has relevant implications for both discovery of possible food-derived bioactive peptides and
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evaluation of stability/susceptibility of food proteins to digestion, in view of the allergenicity risk
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assessment. MATERIALS AND METHODS
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All chemicals were purchased from Sigma–Aldrich (St. Louis, MO, USA) and were analytical grade or
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better. HPLC-grade solvents were purchased from Carlo Erba (Milan, Italy).
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Isolation of whey proteins
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Whey proteins were chosen as a relatively simple model of food proteins. Bulk bovine milk was
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obtained from a local farm and collected soon after milking. Milk samples (50 mL) were aliquoted into
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sterile polystyrene containers. To prevent undesired proteolysis, phenylmethylsulfonyl fluoride (PMSF)
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was added to a final concentration of 1mM and milk was frozen and stored at -20 °C until use. Milk was 6 ACS Paragon Plus Environment
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centrifuged at 1500 g for 20 min at 4 °C (Labofuge 400R, Heraeus Instruments, Hanau, Germany) and
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skimmed by manual removal of the floating fat layer (twice). Casein was depleted by isoelectric
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precipitation at pH 4.6 with 10% (v/v) acetic acid and 1M sodium acetate and pelleted by centrifugation
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at 1500 g for 10 min at 4 °C. Whey proteins were purified from the supernatants dialyzing against
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deionized water, using benzoylated dialysis tubes with 3 kDa- molecular weight cut-off (Sigma).
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Afterwards, proteins were quantified with the Bradford assay (kit from Bio-Rad, Milan, Italy) and finally
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lyophilized.
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It was verified by reversed-phase high performance liquid chromatography (RP-HPLC)-UV analysis that
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whey proteins contained both the A and B of -lactoglobulin (-Lg), using the analysis conditions as in
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Ferranti et al.23
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In vitro digestion of whey protein
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In vitro simulated gastroduodenal (GD) digestion of whey proteins was performed according to Minekus
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et al.,22 skipping the oral phase. Simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) were
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prepared according to the harmonized conditions. All digestion steps were carried out in a shaking
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incubator at 37 °C and 170 rpm. Briefly, for the gastric phase, 500 mg of whey proteins was diluted with
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400 μL of SGF 1,25x. Liposomes, freshly prepared with lecithin (Sigma), were added up to 0.17 mM in
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the final solution. The pH was adjusted to 2.7 and porcine pepsin (2000 U/mL final concentration).
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Sample was incubated for 2 h at 37 °C. Pepsin hydrolysis was stopped by raising the pH to 7.0 with 1M
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sodium bicarbonate. The duodenal digestion was carried out 2 h at 37 °C after duplicating the volume
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with SIF, containing bile salts (10 mM final, based on the cholic acid) and pancreatin at 100 U/mL based
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on the trypsin activity (7 U/mg of pancreatin as TAME activity). At the end of the duodenal phase,
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peptides in a 1 mL aliquot of the digest were immediately purified with a C18 reverse-phase prepacked 7 ACS Paragon Plus Environment
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cartridges (Sep-pak, Waters, Milford, MA, USA), washing extensively with 0.1% (v/v) trifluoroacetic acid
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(TFA) and eluting with 70% acetonitrile/0.1% TFA. Peptides were vacuum dried and finally lyophilized.
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An aliquot of the peptide extract (10 µg) was suspended in 100 µL 25 mM ammonium bicarbonate/10
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mM dithiothreitol (DTT) and incubated at 55 °C for 45 min prior to LC-MS/MS analysis. The remaining
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solution of digests was aliquoted and immediately frozen and stored at -20 °C until use. A solution of
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SGF and SIF containing the respective digestive enzymes, but lacking the whey proteins, was incubated
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under the same conditions of the sample and used as the control.
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Pre-fractionation of the whey protein digests
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Several attempts of pre-fractionation of the whey protein digest were performed, including size
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exclusion chromatography using either Econopac (Bio-Rad, Hercules, CA, USA) pre-packed column
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(exclusion limit 6 kDa) or polyacrylamide spin desalting columns (Pierce-Thermo scientific), in both
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cases eluting the high molecular weight fraction with 25 mM ammonium bicarbonate pH 7.8.
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Alternatively, aliquots (1 mL) of the digests were diluted with 100% (w/v) thricloroacetic acid (TCA) up
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to 12% final TCA concentration. After 30 min in an ice cold bath, the precipitate was pelleted by
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centrifugation (3000 g, 15 min, 4 °C) and the supernatant was discarded. To remove the excess of TCA,
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the pellet was washed trice with -20 °C cold acetone and finally dried.
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SDS-PAGE analysis
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The course of digestion was monitored by SDS-PAGE electrophoresis using hand cast 15% acrilammide
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gels (Tetra cell Miniprotean system, Bio-Rad). Indicatively 20 µg of proteins, suspended in Laemmli
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buffer, were loaded onto each well of the gel. Proteins were separated at room temperature, at 100 V
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constant voltage and were visualized with G250 brilliant blue Coomassie. The gel was imaged with a
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scanner and processed using the LABScan software 3.00 (Amersham Bioscience, Uppsala, Sweden). 8 ACS Paragon Plus Environment
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RP-HPLC
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RP-HPLC analysis of whey protein digests and the relevant 12% TCA insoluble fraction was carried out
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using an HP 1100 HPLC chromatographer (Agilent, Palo Alto, CA, USA) equipped with a C18 250 x 2.0
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mm i.d., 4 µm particle diameter column (Jupiter, Phenomenex, Torrance, CA, USA). After 5 min of
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isocratic elution at 5% solvent B (0.1% TFA in acetonitrile, v/v), a 5-60% B over 60 min was applied at a
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flow rate of 0.2 mL/min. Solvent A was 0.1% TFA in water (v/v). The column was maintained in a
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thermostatic oven at 40°C. The column effluents were monitored by UV detection at λ=220 and 280
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nm. Nearly 50 µg of peptide digests were analyzed for each run. In the case of the 12% TCA insoluble
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fraction, the pellet resulting from a 1 mL aliquot of the digest was resuspended in 200 µL of 0.1% TFA
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and 50 µL was injected onto the column. Undigested whey proteins (15 µg) were separated under the
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same conditions of the digests, in order to confirm the digestion of the proteins and to check the
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possible permanence of intact protein chains.
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Nanoflow-HPLC-MS/MS
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HPLC-MS/MS analyses were performed using an Ultimate 3000 nano-flow ultra-high-performance
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liquid chromatography (Dionex/Thermo Scientific, San Jose, CA, USA) coupled to a Q-Exactive Orbitrap
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mass spectrometer (Thermo Scientific). Peptides were reconstituted in 0.1% formic acid, and nearly 2
158
µg were loaded through Acclaim PepMap 100 trap columns (75-µm i.d. x 2 cm; Thermo Scientific) using
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a FAMOS autosampler (Thermo Scientific). Peptides were separated with an EASY-Spray™ PepMap C18
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column (2 µm, 25 cm x 75 µm) with 2-µm particles and 100-Å pore size (Thermo Scientific), applying a
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2–50% gradient of B over 120 min after 5 min of isocratic elution at 2% B and a constant flow rate of
162
300 nL/min. Eluent A was 0.1% formic acid (v/v) in LC-MS-grade water, and eluent B was 0.1% formic
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acid (v/v) in acetonitrile. MS1 precursor spectra were acquired in the positive ionization mode scanning 9 ACS Paragon Plus Environment
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the 1800-350 m/z range with resolving power of 70,000 full width at half maximum (FWHM), an
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automatic gain control (AGC) target of 1x106 ions, and maximum ion injection time (IT) of 256 ms. The
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spectrometer operated in data-dependent acquisition mode while selecting up to the 10 most intense
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ions for MS/MS fragmentation and applying a 12-s dynamic exclusion. Fragmentation spectra were
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obtained at a resolving power of 17,500 FWHM. Ions with one charge or more than six were excluded
169
from the MS/MS selection.
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To improve the identification of short peptides, the HPLC-MS/MS analysis of peptide digests, both non-
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reduced and reduced with DTT, was repeated under the same chromatographic conditions, scanning
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the 1600-200 m/z range. In this case, fragmentation of mono-charged ions with intensity higher than 1
173
x 106 was also allowed, while selection of background ions was impeded with an exclusion list, which
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was prepared based on a blank HPLC-MS/MS analysis. Spectra were elaborated using the software
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Xcalibur version 3.1 (Thermo Scientific).
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Identification of peptides
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The LC-MS/MS runs were utilized for interrogating a home-built database of the 30 most abundant
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proteins of bovine milk,24 using the following search engines: i) the Protein Prospector Batch-Tag Web
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tool (http://prospector2.ucsf.edu); ii) the Andromeda tool of the MaxQuant vers. 1.6.2.10; iii) the
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Proteome Discoverer 2.1 (Thermo Scientific), relying on the SEQUEST algorithm. For the analysis with
181
the Batch-Tag Web the mgf files were generated from the LC-MS runs using the MS Convert tool of the
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open source ProteoWizard 3.0 software (http://proteowizard.sourceforge.net/). Database searching
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parameters were the following in all cases: no modification of cysteins; Met oxidation and pyroglutamic
184
acid at N-terminus Gln as variable modifications; mass tolerance value of 8 ppm for precursor ion and
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12 ppm for MS/MS fragments; no enzyme specificity for the cleavage. The LC-MS/MS analyses of the 10 ACS Paragon Plus Environment
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peptide digests reduced by DTT were processed considering the possibility that cysteins were in the
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free thiol form. Charges of precursor peptides were (+)2-5, or (+)1-5 for analysis carried out with the
188
possibility of fragmenting mono-charged ions.
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The Batch-Tag Web search engine was operated also considering the possibility of peptide cross-linking
190
through disulfide bridges.
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Identification scores were calculated by Target Decoy Peptide Spectrum Matches (PSMs) filtering,
192
working at 0.01 peptide-level false discovery rate (FDR). In the case of the Proteome Discoverer search
193
engine, identifications were validated with the Percolator tool. RESULTS AND DISCUSSION
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Monitoring the protein degradation
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The course of digestion of whey proteins was monitored by SDS-PAGE analysis (Fig. 1, panel A). In
196
agreement with previous findings,25 a significant part of β-Lg resisted the simulated gastric digestion,
197
while it was quickly degraded by simulated duodenal fluids.26 In contrast, -La and serum albumin (BSA)
198
were extensively digested already at level of the simulated gastric compartment. After a few minutes
199
of in vitro duodenal digestion no polypeptides were detected by SDS-PAGE, apart from digestive
200
enzymes. The volume of SDS-PAGE-separated digests corresponded to 20 µg of the original protein
201
content. With this protein amount, undigested proteins appeared slightly overloaded, whereas only
202
faint bands of digestive enzymes were detected after complete digestion. The SDS-PAGE analysis of
203
digests was repeated after concentration by size exclusion chromatography or by precipitation with
204
TCA (final, 12% w/w), demonstrating the presence of polypeptides with estimated molecular weight
205
4-6 and 15-16 kDa, which most likely originated from whey proteins (Fig. 1, panel B).
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This finding suggests that food proteins appearing extensively digested could actually generate low-
207
abundance large fragments, which became detectable upon concentration. At the moment it has not
208
established a minimum threshold amount for food allergens. Indeed, in principle, even scant amounts
209
of polypeptides might sensitize and/or elicit an allergic reaction in predisposed individuals. Thus, the
210
persistence of digestion stable large polypeptides, albeit at very low abundance, rises important
211
implications about the correlation between digestion stability and food allergenic potential. The
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possible presence of these protein fragments after digestion has been most often overlooked for a large
213
variety of food allergens. The definitive identification of these large polypeptides would require
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dedicated time-consuming approaches, combining electrophoretic and/or HPLC isolation and MS
215
analysis.
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HPLC analysis of whey protein digests
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As expected, the RP- HPLC analysis of gastroduodenal digests (Fig. 2B) showed the formation of a
218
multitude of peptide fragments and confirmed the complete degradation of whey proteins (Fig. 2A).
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Interestingly, the peptide profiles of Cys-non-reduced and Cys-reduced by DTT exhibited only minor
220
differences (not shown), suggesting that possible disulfide cross-linked peptides could occur at a low
221
abundance or are less detectable than the linear peptide fragments. Large polypeptide fragments were
222
selectively targeted analyzing the 12% insoluble TCA fraction in the same HPLC conditions (Fig. 2C). The
223
relevant chromatogram contained a multitude of peaks eluting at relatively high retention time, which
224
were not evidenced in the analysis of unfractionated digests, probably as a consequence of suppression
225
by dominant peptides. In line with SDS-PAGE analysis, these results suggested that the digest does
226
contain large polypeptide fragments. At least part of these large-sized polypeptides arose from whey
227
proteins rather than being impurities or hydrolysis products of digestion fluids, because they were 12 ACS Paragon Plus Environment
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substantially missing in the HPLC chromatogram of a control sample prepared with GD digestive
229
enzymes in the absence of the whey protein substrate, incubated and then fractionated under parallel
230
conditions (not shown).
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HPLC-MS/MS identification of whey protein derived peptides
232
To maximize the identification of the peptide components, we separated the whey protein digests by
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HPLC-MS/MS, with a 120 min gradient and using a high-resolution 25 cm capillary column.
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The total ion current (TIC) chromatogram (Fig. 3A) was largely dominated by the β-Lg f(125-135)
235
([M+2H)]2+ = 623.29), which was previously demonstrated to be relatively resistant to simulated GI
236
digestion,13 and by β-Lg f(149-154) ([M+H]+ = 678.34), eluting at retention time (tr) 48.62 and 61.45 min,
237
respectively.
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This latter peptide was tentatively identified only with the accurate molecular weight, because it was
239
not fragmented, as its possible doubly charged ions was out of the range of analysis (m/z 350-1800).
240
The peptide β-Lg f(42-51) (tr = 50.76), belonging to another relatively β-Lg stable domain,19,27 occurred
241
with a relatively high signal intensity as well. A multitude of lower intensity chromatographic peaks
242
contained multiple ion signals, only some of which were assigned by the available search engines.
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The manual exploration of the spectra, allowed the assignment of additional signals such as the
244
unexpected -La f(69-79), occurring as a minor component at tr = 49.4 min, which escaped the
245
recognition by search engines, because it contains two unpaired cysteine residues (sequence:
246
SSNICNISCDK). Similarly, the BSA f(414-421) and -La f(18-25) were identified by manual interpretation
247
of the spectra. The MS/MS fragmentation of these peptides with the corresponding assignment of
248
relevant signals is shown in Figure 4. The MS/MS spectra, in particular those of Figure 4B-C, contained
249
several not assigned fragments, which arose from internal and non-conventional fragmentation.8 13 ACS Paragon Plus Environment
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The under- or over-fragmentation of short peptides in data dependent acquisition-MS/MS is a well
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known drawback which complicates their identification.4,
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(MW
