Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum third-stage larvae (L3) are fish-borne nematodes that can cause human anisakidosis. Although A. simplex is a known source of allergens, knowledge about the allergic potential of P. decipiens and C. osculatum is limited. Therefore, we performed comparative proteomic profiling of A. simplex, P. decipiens, and C. osculatum L3 larvae using liquid chromatography–tandem mass spectrometry. In total, 645, 397, and 261 proteins were detected in A. simplex, P. decipiens, and C. osculatum L3 larvae, respectively. Western blot analysis confirmed the cross-reactivity of anti-A. simplex immunoglobulin (Ig)G antibodies with protein extracts from P. decipiens and C. osculatum L3 larvae. The identified proteins of the Anisakidae proteomes were characterized by label-free quantification and functional analysis, and proteins involved in many essential biological mechanisms, such as parasite survival, were identified. In the proteome of A. simplex 14, the following allergens were identified: Ani s 1, Ani s 2 (2 isomers), Ani s 3 (2 isomers), Ani s 4, Ani s 8, Ani s 9, Ani s 10, Ani s 11-like, Ani s 13, Ani s fructose 1,6-bisphosphatase, Ani s phosphatidylethanolamine-binding protein (PEPB), and Thu a 3.0101. The following 8 allergens were detected in P. decipiens: Ani s 2, Ani s 3 (2 isomers), Ani s 5, Ani s 8, Ani s 9, Ani s PEPB, and Ani s troponin. In C. osculatum 4, the following allergens were identified: Ani s 2, Ani s 5, Ani s 13, and Asc l 3. Furthermore, 28 probable allergens were predicted in A. simplex and P. decipiens, whereas in C. osculatum, 25 possible allergens were identified. Among the putative allergens, heat shock proteins were most frequently detected, followed by paramyosin, peptidyl-prolyl cis-trans isomerase, enolase, and tropomyosin. We provide a new proteomic data set that could be beneficial for the discovery of biomarkers or drug target candidates. Furthermore, our findings showed that in addition to A. simplex, P. decipiens and C. osculatum should also be considered as potential sources of allergens that could lead to IgE-mediated hypersensitivity.

Anisakidae nematodes are one of the most important food-borne parasites. Live third-stage larvae (L3) of anisakids consumed with fish or seafood dishes can cause anisakidosis. Each year, approximately 2,000 new cases of anisakidosis are found in Japan; in South Korea, 200; in Europe, 500; and in the United States, 70 (Arizono et al., 2012; Lim et al., 2015). The main etiologic agents of the disease are 2 species: Anisakis simplex and Anisakis pegreffii. Pseudoterranova spp. and Contracaecum spp. human infections have been detected less frequently. In the course of anisakidosis, live L3 larvae cause organ damage at the location of the larvae, predominantly in the gastrointestinal tract. The L3 larvae can penetrate the wall of the alimentary tract and migrate to the internal organs. In addition, allergens of A. simplex and A. pegreffii L3 larvae may cause allergic reactions in the form of urticaria, angioedema, and even life-threatening anaphylactic shock (Choi et al., 2009). Furthermore, employees of the fish processing industry have had episodes of allergic asthma (Scala et al., 2001) and conjunctivitis (Añíbarro and Seoane, 1998) induced by Anisakis allergens. Nephrotic syndrome (Meseguer et al., 2007) and arthritis (Cuende et al., 1998) associated with Anisakis allergy have also been reported. Because of the thermostability of many Anisakis allergens, immunoglobulin (Ig)E-mediated hypersensitivity reactions can also occur after the ingestion of highly processed fish products containing Anisakis allergens (Bao et al., 2015).

Many studies on various aspects of Anisakidae nematodes have been performed, and among them, investigations of the allergic properties of Anisakis are particularly important. Nonetheless, knowledge about the allergic potential of Pseudoterranova and Contracaecum is very limited. Because of the phylogenetic closeness of anisakids, we suppose that Pseudoterranova decipiens and Contracaecum osculatum could contain allergens similar to A. simplex. Moreover, for the majority of human Anisakis allergy cases, the pathogenic agent was not confirmed by genetic or morphological tests. Consequently, although other nematodes from the Anisakidae family may cause allergic reactions, these cases are attributed to Anisakis.

A powerful tool allowing large-scale identification and expression analysis of proteins as well as many allergens is liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Additionally, proteomic studies enable the identification of protein modifications not present in the deoxyribonucleic acid sequence and allow accurate determination of protein abundance (Zhang et al., 2014), in contrast to genomic or transcriptomic analyses, which are also used for high-throughput allergen detection (Gygi et al., 1999; Cho, 2007). To date, only 2 proteomic investigations have been conducted to identify the allergens of Anisakis nematodes (Arcos et al., 2014; Fæste et al., 2014). Moreover, new allergens and potential allergens of Anisakis spp. are still being discovered, and many allergens of Anisakis spp. have yet to be discovered.

Therefore, we aimed to provide more insight into Anisakidae proteomes by comparative investigation of A. simplex, P. decipiens, and C. osculatum L3 larvae using LC-MS/MS technology. Furthermore, we carried out a functional analysis of the identified proteins to further understand anisakid biology and pathogenicity. Above all, special emphasis was placed on the identification of allergens of Anisakidae parasites, and here we reported novel data concerning the allergens and predicted allergens of A. simplex, P. decipiens, and C. osculatum.

Anisakidae L3 larvae collection and identification

Anisakis simplex, P. decipiens, and C. osculatum L3 larvae were collected from marine fish and identified as previously described (Kochanowski et al., 2019). In brief, anisakid larvae were manually purified from fish tissue and extensively rinsed with sterile 0.01 M phosphate-buffered saline solution (PBS), pH 7.4. Anisakidae parasites were then identified by using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) (Zhu et al., 1998). The results of the PCR-RFLP assay were validated by Sanger sequencing of PCR products before the enzymatic digestion step. Sequences were submitted to GenBank (https://www.ncbi.nlm.nih.gov/genbank/) under accession nos. MF967307.1, MF988284.1 and MF980981.1.

Protein extraction from anisakid L3 larvae

Extracts from whole nematodes were obtained as described previously with minor modifications (Kochanowski et al., 2019). Briefly, approximately 0.5 g of A. simplex, C. osculatum, and P. decipiens L3 larvae were initially homogenized with 3 ml of sterile PBS by grinding with a mortar and pestle followed by further disintegration using a high-speed homogenizer. Afterward, to increase the protein extraction yield, parasite homogenates were sonicated in ice (10-μm amplitude for 30 sec) and incubated for 1 hr at 4 C. Finally, the lysates were clarified by centrifugation (20,000 g for 30 min at 4 C). Protein concentration was determined by measuring the absorbance at 280 nm using an ultraviolet–visible spectrophotometer (Implen, München, Germany) and adjusted to 4 mg/ml. Three independent biological replicates of each parasite extract were performed. Protein extracts were kept at −80 C for further analysis.

Generation of rabbit anti-A. simplex antisera

Rabbits were immunized by intramuscular injection of 2.0 mg of A. simplex extract mixed with Freund's complete adjuvant (Sigma, St. Louis, Missouri) according to our previously described protocol (Kochanowski et al., 2019). Preimmune serum was collected before immunization and used as a negative control.

Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and Western blot (WB) analysis

Whole parasite extracts were analyzed by 4–20% gradient SDS-PAGE (BioRad, Hercules, California) under reducing conditions (Laemmli, 1970), and gels were stained with colloidal Coomassie G-250 (PageBlue, Thermo Fisher Scientific, Rockford, Illinois). For WB analysis, parasite extracts from the 3 species were first separated by 4–20% gradient SDS-PAGE in duplicate and then transferred onto a 0.45-μm nitrocellulose membrane (BioRad, München, Germany). After the blocking step, the membrane was cut; 3 strips loaded with different Anisakidae species extracts were incubated with rabbit anti-A. simplex hyperimmune serum diluted 1:400; another 3 strips were incubated with preimmune rabbit serum. The anti-rabbit IgG antibody conjugated to horseradish peroxidase (Sigma) was used as a secondary antibody. SDS-PAGE and WB profiles were analyzed with GelAnalyzer software (ver. 2010a; http://www.gelanalyzer.com/).

Sample processing and LC-MS/MS analysis

Protein solutions were subjected to the standard procedure of tryptic digestion, during which proteins were reduced with 0.5 M (5 mM final concentration [f.c.]) tris (2-carboxyethyl) phosphine for 1 hr at 60 C; the cysteine residues were subsequently alkylated with 200 mM (10 mM f.c.) methyl methanethiosulfonate for 10 min at room temperature and finally cleaved overnight with 10 μl of 0.1 μg/μl trypsin at 37 C. A total of 20 μl of the resulting peptide mixtures was loaded onto a reversed-phase RP-18 precolumn (Waters, Milford, Massachusetts) using 0.1% (v/v) formic acid (FA) in water as a mobile phase and then transferred to a nano-high-performance liquid chromatography (nano-HPLC) RP-18 column (internal diameter 75 μm [Waters]) using a linear acetonitrile gradient of 0–35% (v/v) over 160 min in the presence of 0.1% (v/v) FA at a flow rate of 250 nl/min. The nano-HPLC column outlet was coupled directly to the ion source of a Q Exactive mass spectrometer (Thermo Electron Corp., San Jose, California) working in the regime of data-dependent MS to MS/MS switch with higher-energy collisional dissociation (HCD)-type peptide fragmentation. A blank run ensuring the absence of cross-contamination from previous samples preceded each analysis.

Data analysis

Database search and protein identification:

Raw LC-MS/MS data were processed and queried using MaxQuant software with the integrated Andromeda search engine ver. 1.6.1.0 (http://www.coxdocs.org) (Tyanova et al., 2016) against the A. simplex reference proteome (20,786 sequences; proteome ID: UP000036680) obtained from Universal Protein Resource (UniProt) (http://www.uniprot.org/) and searched against the reverse sequences from the same database as generated by MaxQuant along with 248 sequences of common contaminants. The search parameters were set as follows: trypsin was specified as the cleavage enzyme, and the maximum number of missed cleavages was set to 1. The allowed precursor mass deviation for the initial search used for mass recalibration was 20 parts per million (ppm). In the main Andromeda search, the precursor and isotope match tolerances were set to 10 ppm and 5 ppm, respectively. Fixed modification searches including oxidation of methionine and beta-methylthiolation of cysteine were performed as variable modifications. The false discovery rate (FDR) for proteins, peptides, and modification sites was fixed at 0.01. The minimum peptide length was set to 7, and requantification was enabled. Additionally, mass spectrometric data were preprocessed with Mascot Distiller software ver. 2.6 (Matrix Science, London, U.K.; http://www.matrixscience.com/distiller.html) and analyzed with the Mascot search engine server ver. 2.5 (Matrix Science; http://www.matrixscience.com/server.html) against the nonredundant National Center for Biotechnology Information protein database (http://www.ncbi.nlm.nih.gov) with a taxonomy filter for Metazoa (13,299,211 sequences in June 2017). To reduce mass errors, the peptide and fragment mass tolerance settings were established separately for individual LC-MS/MS runs after a measured mass recalibration, resulting in values of 5 ppm for the parent and 0.01 Da for fragment ions in HCD MS/MS mode. Peptide sequences were searched using trypsin specificity allowing 1 missed cleavage; the ion type was set as monoisotopic, and protein mass was set as unrestricted. Beta-methylthiolation of cysteine was used as a fixed modification, whereas oxidation of methionine was set as a variable modification. Proteins with Mascot scores ≥50 were considered significant (P < 0.05).

Scaffold software ver. 4.8.7 (Proteome Software Inc., Portland, Oregon; http://www.proteomesoftware.com/) (Searle, 2010) was used to merge search results from search engines, validate the peptide and protein identifications, and estimate the relative protein abundance. Peptide identifications were accepted at ≥95.0% probability with the Peptide Prophet algorithm (Keller et al., 2002). Protein identifications assigned by the Protein Prophet algorithm (Nesvizhskii et al., 2003) were accepted if they were established with ≥99.0% probability and if at least 1 peptide was identified in all 3 biological replicates. Proteins that contained similar peptides and that could not be differentiated on the basis of MS/MS analysis alone were grouped to satisfy the principles of parsimony. Label-free quantification of the protein amounts was conducted using total spectral count (Liu et al., 2004) and visualized in Morpheus (https://software.broadinstitute.org/morpheus/).

In silico proteome maps:

In silico proteome maps (virtual 2-dimensional [2D] protein gel electrophoresis) of A. simplex, P. decipiens, and C. osculatum were generated using JVirGel software ver. 2.0 (http://www.jvirgel.de/index.html) (Hiller et al., 2006). The same software was applied to calculate the theoretical isoelectric point (pI) and molecular weight (Mw) of detected proteins.

Protein annotation:

Homology searches, InterPro motifs searches, Gene Ontology (GO) annotation into 3 categories (molecular function, biological process, and cellular component), Clusters of Orthologous Group annotations, annex augmentation, enzyme search, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed using Blast2GO Pro software ver. 5.1.13 (https://www.blast2go.com/) (Conesa et al., 2005). Annotations obtained from the different databases were merged via Blast2GO. All of these analyses were run with default settings and thresholds.

Identification of putative allergens:

Identified proteins were evaluated for putative allergenicity by web servers using different bioinformatics approaches and databases: (1) searching against The Food Allergy Research and Resource Program AllergenOnline.org database ver. 18B (http://www.allergenonline.com/) (2,089 sequences, March 2018) using full-length FASTA alignment (e-value cut-off: 1e-05; 70% identity match); (2) scanning with the AllerTOP web server ver. 2.0 (http://www.ddg-pharmfac.net/AllerTOP/method.html) (Dimitrov et al., 2013); (3) searching in the PREAL web server (http://www.gmobl.sjtu.edu.cn/PREAL/index.php) (Wang et al., 2013) at a probability threshold of 0.7. Only predicted allergens identified with at least 2 different servers were accepted.

SDS-PAGE and WB analysis of extracts of anisakid larvae

The parasite extracts were separated by SDS-PAGE, and the displayed protein profiles are shown in Figure 1a. SDS-PAGE band patterns of A. simplex and P. decipiens extracts were similar and characterized by a large number of bands at a wide range of molecular weights (16–246 kDa), whereas the profile of the C. osculatum extract was slightly different with a smaller number of major bands.

Figure 1.

Sodium dodecyl sulfate–polyacrylamide gel electrophoresis analysis of extracts prepared from Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae (a). Western blot analysis of Anisakidae extracts immunoreacted with rabbit anti-A. simplex immunoglobulin G antibodies; densitometric analysis and molecular weight (Mw) quantification (kDa) were performed by GelAnalyzer software (b).

Figure 1.

Sodium dodecyl sulfate–polyacrylamide gel electrophoresis analysis of extracts prepared from Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae (a). Western blot analysis of Anisakidae extracts immunoreacted with rabbit anti-A. simplex immunoglobulin G antibodies; densitometric analysis and molecular weight (Mw) quantification (kDa) were performed by GelAnalyzer software (b).

Close modal

In WB, the anti-A. simplex rabbit IgG antibodies reacted with extracts from all 3 anisakids (Fig. 1b). All Anisakidae extracts had a quite similar reaction profile with a multiband pattern; however, the WB profiles of the C. osculatum and P. decipiens extracts were characterized by a reduced number or intensity of bands compared with that of the A. simplex extract.

Identification of proteins

In A. simplex, 645 proteins corresponding to 2,417 total unique peptides were detected. A total of 397 proteins of P. decipiens based on 1,111 unique peptides and 261 proteins of C. osculatum based on 621 unique peptides was detected. Furthermore, 423, 165, and 152 proteins were unique to the A. simplex, P. decipiens, and C. osculatum proteomes, respectively (see Fig. 2a). Most of the predicted Anisakidae proteins were phylogenetically related to A. simplex, Toxocara canis, and Ascaris suum. Identification was conducted with high confidence since the protein and peptide FDR in all cases was ≤0.2%.

Figure 2.

Venn diagrams of all identified proteins (a), allergens (b), and putative allergens (c) from Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum. Distribution of detected anisakid proteins based on the molecular weight (Mw) and isoelectric point (pI) values; detected allergens are displayed in red; predicted allergens are in blue (d). Color version available online.

Figure 2.

Venn diagrams of all identified proteins (a), allergens (b), and putative allergens (c) from Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum. Distribution of detected anisakid proteins based on the molecular weight (Mw) and isoelectric point (pI) values; detected allergens are displayed in red; predicted allergens are in blue (d). Color version available online.

Close modal

Virtual 2D gels showing the identified protein distributions according to theoretical Mw and pI values are presented in Figure 2d. Proteins from all 3 nematodes had an approximate Mw in the range of 2–800 kDa and pI in the range of 3–15. Nevertheless, the majority of proteins had a Mw in a narrower range of 15–100 kDa and pI in the range of 4–8.

Among all detected proteins, 51 were identified in 3 nematodes, and they are listed in Table I. Sequences of heat shock proteins (HSPs), spindle- and centrosome-associated proteins, and fructose bisphosphate aldolase were the most frequently detected shared proteins.

Table I

Shared proteins identified in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.

Shared proteins identified in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.
Shared proteins identified in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.

Relative quantification

Spectral counting analyses of MS/MS data were used to calculate the relative abundances of proteins in proteomes. This parameter is not an accurate measurement of protein concentration; nevertheless, it allows an approximate level to be estimated. The top 50 most abundant proteins of the 3 nematodes are displayed in the heat map (Fig. 3). The most highly expressed proteins of A. simplex L3 larvae were SXP/RAL-2 family protein isoform 1 (allergen Ani s 8) and enolase. Hemoglobin and disorganized muscle protein 1 were the most abundant in the P. decipiens proteome, whereas enolase proteins were the most abundant in the C. osculatum proteome. Moreover, many of the top 50 most abundant proteins were allergens or putative allergens.

Figure 3.

Heat map of the top 50 most abundant proteins of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum determined by label-free quantification mass spectrometry. The average total spectrum count of proteins identified in all 3 replicates was log2-transformed and visualized using Morpheus. Accession numbers of proteins were obtained from the National Center for Biotechnology Information nonredundant protein database (*) or UniProtKB (†). Color version available online.

Figure 3.

Heat map of the top 50 most abundant proteins of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum determined by label-free quantification mass spectrometry. The average total spectrum count of proteins identified in all 3 replicates was log2-transformed and visualized using Morpheus. Accession numbers of proteins were obtained from the National Center for Biotechnology Information nonredundant protein database (*) or UniProtKB (†). Color version available online.

Close modal

GO annotation of identified proteins

GO functional analysis was performed using Blast2GO software to assign functions and processes to the identified anisakid larvae proteins. From the analysis, GO terms were assigned for 527 proteins of A. simplex. For P. decipiens and C. osculatum, 297 and 205 proteins were assigned, respectively. For A. simplex proteins, a total of 2,442 annotations was assigned. For P. decipiens and C. osculatum proteomes, in total 1,171 and 871 annotations were assigned, respectively. Nevertheless, the structures of GO terms among the 3 proteomes were quite similar.

The most common biological process categories of Anisakidae proteins were organic substance metabolic process (15%; GO:0071704), primary metabolic process (14–15%; GO:0044238), cellular metabolic process (14%; GO:0044237), and nitrogen compound metabolic process (12–14%; GO:0006807), followed by small-molecule metabolic process (8–9%; GO:0044281) and biosynthesis process (7–8%; GO:0009058).

Concerning the GO analysis for molecular function, anisakid proteins were mainly involved in ion binding (15–17%; GO:0043167), organic cyclic compound binding (12–13%; GO:0097159), heterocyclic compound binding (12–13%; GO:1901363), small molecule binding (11–12%; GO:0036094), carbohydrate derivative binding (8–9%; GO:0097367), hydrolase activity (7–10%; GO:0016787), drug binding (7–8%; GO:0008144), and protein binding (6–9%; GO:0005515).

In terms of cellular components, the major groups were intracellular (22%; GO:0005622), intracellular part (22%; GO:0044424), intracellular organelle (15–17%; GO:0043229), nonmembrane bounded organelle (11–12%; GO:0043228), and intracellular organelle part (11%; GO:0044446). More details regarding GO analysis are shown in Figure 4 and Suppl. File S1.

Figure 4.

Gene Ontology (GO) pie chart of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae proteins assigned using Blast2GO. The identified GO terms at level 3 with the corresponding number of identified proteins and percentage distribution of sequences among GO categories are presented. Color version available online.

Figure 4.

Gene Ontology (GO) pie chart of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae proteins assigned using Blast2GO. The identified GO terms at level 3 with the corresponding number of identified proteins and percentage distribution of sequences among GO categories are presented. Color version available online.

Close modal

Identification of enzymes and metabolic pathways

Enzymes were assigned according to Enzyme Commission (EC) numbers and KEGG pathway analysis to better understand the function of the detected proteins. Potential enzymes of anisakids were mapped on the basis of the chemical reaction they catalyze. Enzyme classification revealed that hydrolases were the largest group in 3 proteomes (45–82 sequences; EC 3). Less abundant enzymes were oxidoreductases (11–48 sequences; EC 1), lyases (14–27 sequences; EC 4), transferases (16–31 sequences; EC 2), and isomerases (11–30 sequences; EC 5). Ligases (EC 6) were the smallest group of enzymes in A. simplex (10 sequences) and P. decipiens (1 sequence), whereas ligases were not detected in C. osculatum. The identified Anisakidae enzymes are listed in Table II.

Table II

Enzyme identification of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.

Enzyme identification of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.
Enzyme identification of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.

The predicted enzymes of A. simplex, P. decipiens, and C. osculatum were assigned to 70, 43, and 32 KEGG pathways, respectively. The most represented pathways of 3 proteomes were biosynthesis of antibiotics (17–73 sequences; 17–37 enzymes), purine metabolism (12–63 sequences; 5 enzymes), glycolysis/gluconeogenesis (9–41 sequences; 9–14 enzymes), citrate cycle (6–32 sequences; 6–13 enzymes), pyruvate metabolism (5–26 sequences; 5–7 enzymes), carbon fixation in photosynthetic organisms (4–21 sequences; 4–9 enzymes), carbon fixation pathways in prokaryotes (4–18 sequences; 4–12 enzymes), pentose phosphate pathway (4–17 sequences; 4–8 enzymes), fructose and mannose metabolism (3–15 sequences; 3–7 enzymes), and methane metabolism (3–18 sequences; 3–8 enzymes). The complete list of predicted pathways with the number of identified protein sequences and enzymes is shown in a heat map (Fig. 5). Suppl. File S1 shows the details of enzyme identification and KEGG pathway mapping.

Figure 5.

Heat map of predicted metabolic pathways of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum with the number of corresponding protein sequences and enzymes. Color version available online.

Figure 5.

Heat map of predicted metabolic pathways of Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum with the number of corresponding protein sequences and enzymes. Color version available online.

Close modal

Anisakid allergome

Allergen identification:

In the proteome of A. simplex 14, the following allergens were identified: Ani s 1, Ani s 2 (2 isomers), Ani s 3 (2 isomers), Ani s 4, Ani s 8, Ani s 9, Ani s 10, Ani s 11-like, Ani s 13, Ani s fructose 1,6-bisphosphatase, Ani s phosphatidylethanolamine-binding protein (PEPB), and Thu a 3.0101. Eight allergens were detected in P. decipiens: Ani s 2, Ani s 3 (2 isomers), Ani s 5, Ani s 8, Ani s 9, Ani s PEPB, and Ani s troponin. In C. osculatum 4, the following allergens were predicted: Ani s 2, Ani s 5, Ani s 13, and Asc l 3. Moreover, the following allergens were among the top 50 most abundant Anisakidae proteins: Ani s 2, Ani s 3, Ani s 8, and Ani s 13 (see Fig. 3). All allergens identified in the tested anisakids are presented in Table III and Figure 2b.

Table III

Allergens detected in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.

Allergens detected in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.
Allergens detected in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae.

Predicted allergen identification:

To increase the sensitivity and accuracy of allergen prediction, we have combined the results of 3 commonly used bioinformatics tools: AllergenOnline, AllerTop, and PREAL. The analysis predicted 28 probable allergens of A. simplex and the same number of putative allergens of P. decipiens, whereas in C. osculatum, 25 possible allergens were detected. In total, 61 unique candidate allergens were identified in the 3 Anisakidae parasites (see Fig. 2c; Table IV). Among them, sequences of HSPs were most frequently detected, followed by paramyosin, peptidyl-prolyl cis-trans isomerase, enolase, and tropomyosin. Furthermore, putative allergens such as tropomyosin, paramyosin, myosin-3, enolase, HSPs, and Caenorhabditis briggsae CBR-CYN-3 protein were the most abundant Anisakidae proteins (see Fig. 3). The 3 anisakids shared 4 putative allergens: hsp70, myosin-3, enolase, and paramyosin.

Table IV

Predicted allergens detected in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae. Homologous allergens identified by AllergenOnline and AllerTop are also presented.

Predicted allergens detected in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae. Homologous allergens identified by AllergenOnline and AllerTop are also presented.
Predicted allergens detected in Anisakis simplex, Pseudoterranova decipiens, and Contracaecum osculatum L3 larvae. Homologous allergens identified by AllergenOnline and AllerTop are also presented.
Table IV

Extended.

Extended.
Extended.

Here, we performed LC-MS/MS profiling of L3 larvae of A. simplex, P. decipiens, and Contracaecum osculatum. To date, few studies have explored the proteomes of A. simplex and P. decipiens (Arcos et al., 2014; Fæste et al., 2014; Carrera et al., 2016; Stryiński et al., 2019), whereas the proteome of C. osculatum was examined for the first time in the present survey. We predicted a higher number of A. simplex proteins (n = 645) compared with P. decipiens (n = 397) and C. osculatum (n = 261) proteins probably because the protein database for Anisakis is much larger because, in contrast to Pseudoterranova and Contracaecum, the whole genome of Anisakis was sequenced. In a previous study, 98 proteins of Anisakis spp. were identified using 2D gel-based matrix-assisted laser desorption–time-of-flight (TOF)/TOF mass spectrometry (Arcos et al., 2014), whereas 103 proteins of A. simplex were detected using a SDS-PAGE gel-based LC-MS/MS approach (Fæste et al., 2014). In the present study, more than 6 times the number of A. simplex proteins were predicted compared with the previously mentioned investigations; this result could have been caused primarily by 3 factors: (1) the available database of the whole A. simplex proteome; (2) we used a gel-free approach, which is considered to be more sensitive (Abdallah et al., 2012); (3) 2 databases of proteins and 2 search engines were used to increase the sensitivity of LC-MS/MS detection. Nonetheless, Carrera et al. (2016) identified 1,231 and 1,276 proteins in A. simplex and P. decipiens L3, respectively, using a gel-free approach. Moreover, Stryiński et al. (2019) reported 1,872 proteins of A. simplex L3. Carrera et al. (2016) and Stryiński et al. (2019) probably predicted a larger number of proteins because they used a LC-MS/MS system with better resolution and different search engines.

HSPs were found most frequently among all detected anisakid proteins. HSPs are also abundant in the proteomes of many nematodes, and these proteins are essential for parasite survival, particularly during temperature stress (Chen et al., 2014; da Silva et al., 2018). The protective activity of HSPs can be one of the main mechanisms of resistance of Anisakidae larvae to low and high temperatures, which are used to kill larvae in fish products (e.g., cold smoking, freezing in domestic freezers). Furthermore, many HSPs are known as allergens (Aki et al., 1994; Chiung et al., 2000; Movérare et al., 2000).

The functional analysis conducted in this study allowed the characterization of the proteins and proteomes of Anisakidae nematodes. We found that the main GO categories, biological process, molecular functions, and cellular component, were very similar for the 3 anisakids. KEGG analysis revealed that carbohydrate metabolism pathways were the major group among all identified pathways. Certainly, carbohydrate metabolism pathways are essential for Anisakidae larvae since carbohydrates are probably the main source of energy. Moreover, it was reported that trehalose, which is one of the major carbohydrates of A. simplex, could play a protective role in the stress response (Łopieńska-Biernat et al., 2006, 2007). Surprisingly, a high abundance of proteins putatively involved in the biosynthesis pathway of antibiotics was found. Nevertheless, antibiotic biosynthesis pathways were also reported in studies of the transcriptome (Llorens et al., 2018) and proteome (Stryiński et al., 2019) of Anisakis spp. L3 larvae. Furthermore, we found that hydrolases were the most common enzyme class of A. simplex, P. decipiens, and C. osculatum L3 larvae. Indeed, the hydrolytic activity of Anisakis spp. and Contracaecum spp. larvae were previously reported (Łopieńska-Biernat et al., 2004; Żółtowska et al., 2007). Hydrolases could play a relevant role in anisakidosis pathogenesis by allowing penetration of host tissue (Hotez et al., 1994; Bahlool et al., 2013).

To date, 22 allergens of A. simplex have been identified (see File S1), and 14 of them (Ani s 1 to Ani s 14) were approved by the World Health Organization and International Union of Immunological Societies Allergen Nomenclature Subcommittee. As mentioned before, little is known about the allergenic potential of P. decipiens and C. osculatum. Human IgE-mediated responses to P. decipiens and C. osculatum have not been tested thus far. However, it was found that infection with P. decipiens can induce an allergic reaction in mice (Ludovisi et al., 2017). Furthermore, allergens of A. simplex, such as Ani s 2, Ani s 8, and Ani s 9, were reported in P. decipiens L3 larvae (Carrera et al., 2016). Data about allergens in C. osculatum larvae are not available. However, in a previous study, we found that excretory–secretory and crude antigens from A. simplex, P. decipiens, and C. osculatum L3 larvae also react with IgG antibodies from the sera of anisakidosis patients (Kochanowski et al., 2019). Similarly, in the present study, we confirmed by Western blot the cross-reactivity of rabbit anti-A. simplex IgG antibodies with protein extracts from P. decipiens and C. osculatum L3 larvae.

In this survey, allergomes of Anisakidae L3 larvae were investigated. We found 14, 8, and 4 allergens in A. simplex, P. decipiens, and C. osculatum, respectively (see Table III). Among the identified proteins, the major allergen, Ani s 2 (Carballeda-Sangiao et al., 2016), was shared among the 3 Anisakidae nematodes. It is known that major allergens cause the IgE response in more than 50% of sanitized patients. Moreover, the following major allergens were identified in anisakid larvae: Ani s 1, Ani s 11-like, and Ani s 13 (Carballeda-Sangiao et al., 2016). Ani s 2 and Ani s 3 detected in anisakids are considered panallergens with high similarity to related muscle proteins of invertebrates (Daschner et al., 2012; Quiazon et al., 2013). Therefore, Ani s 2 and Ani s 3 could be responsible for cross-reactions with proteins of other nematodes, crustaceans, or insects and could lead to IgE-dependent hypersensitivity in allergic patients (Guarneri et al., 2007). It is worth mentioning that the detected allergens Ani s 1, Ani s 4, Ani s 5, Ani 8, Ani s 9, Ani s 10, and Ani s 11-like are resistant to high temperatures (Moneo et al., 2005; Baird et al., 2014; Carballeda-Sangiao et al., 2016). This creates a risk of allergic reactions in sensitized humans even after highly processed food contaminated with Anisakidae allergens are ingested.

Since many Anisakidae allergens have yet to be discovered, we investigated the proteomes of nematodes to identify potential allergens. Computational web servers were used to predict allergens on the basis of the similarity of sequence and physicochemical properties between known allergens and possible allergens. In total, 61 candidate allergens were found in 3 anisakid species. Possible allergens of P. decipiens and C. osculatum were identified for the first time, and potential allergens of A. simplex were detected previously in the transcriptome (Baird et al., 2016; Llorens et al., 2018) and proteome (Arcos et al., 2014; Fæste et al., 2014). The largest allergome database for Anisakis spp. was provided by Llorens et al. (2018) (AnisakisDB; http://anisakis.mncn.csic.es/public/allergome), and it contains 937 consensus transcripts from 121 different allergens. The putative allergens predicted in our study are generally consistent with the AnisakisDB allergome database (Llorens et al., 2018) and the majority of possible allergens identified by us are in this database. Putative anisakid allergens, such as sequences of HSPs, paramyosin, peptidyl-prolyl cis-trans isomerase, enolase, and tropomysin, were highly represented in our investigation and are also abundant in previously mentioned studies (Fæste et al., 2014; Baird et al., 2016; Llorens et al., 2018). Similarly, less common in this study, possible Anisakidae allergens such as alpha-tubulin, arginine kinase, cathepsin L-like cysteine proteinase, myosin-3, sigma class glutathione S-transferase, superoxide dismutase (Cu-Zn), SXP/RAL-2 family protein 2 isoform 1, thioredoxin, triosephosphate isomerase, troponin C isoform 2, and tubulin alpha-3 chain were also previously identified as putative allergens on the basis of the proteome (Fæste et al., 2014) or transcriptome (Baird et al., 2016; Llorens et al., 2018) of A. simplex. It should be noted, however, that the allergenicity of possible allergens should be confirmed by immunological investigations in future studies.

In summary, our study provides novel scientific insight from proteomic investigations of A. simplex, P. decipiens, and C. osculatum L3 larvae. LC-MS/MS analysis supported by the bioinformatics approach allowed the identification and functional analysis of anisakid proteins. For the first time, the proteomes of P. decipiens and C. osculatum L3 larvae were deeply investigated. We anticipate that our data set will be beneficial for the discovery of new Anisakidae biomarkers and drugs against anisakids. More important, anisakid allergomes were investigated to detect allergens and possible allergens. On the basis of these results we can also conclude that in addition to A. simplex, P. decipiens and C. osculatum should be considered potential sources of allergens that could lead to IgE-mediated hypersensitivity.

This research was partially supported by a grant from the National Centre for Research and Development under the Strategic Program Biostrateg (grant no. 350 BIOSTRATEG2/296211/4/NCBR/2016) and statutory funds (project no. S/261) of the National Veterinary Research Institute in Puławy, Poland.

Animal experiments were conducted in accordance with protocols approved by the Local Ethical Commission for Animal Experimentation in Lublin (license no. 66/2012).

This paper is part of M.K.'s Ph.D. dissertation (National Veterinary Research Institute, Puławy, Poland).

Abdallah,
 
C.,
Dumas-Gaudot,
 
E.
Renaut,
 
J.
and
Sergeant.
 
K.
2012
.
Gel-based and gel-free quantitative proteomics approaches at a glance
.
International Journal of Plant Genomics
:
Article 494572, 17 p
.
Aki,
 
T.,
Fujikawa,
 
A.
Wada,
 
T.
Jyo,
 
T.
Shigeta,
 
S.
Murooka,
 
Y.
Oka,
 
S.
and
Ono.
 
K.
1994
.
Cloning and expression of cDNA coding for a new allergen from the house dust mite, Dermatophagoides farinae: Homology with human heat shock cognate proteins in the heat shock protein 70 family
.
Journal of Biochemistry
115
:
435
440
.
Añíbarro,
 
B.,
and
Seoane.
 
F. J.
1998
.
Occupational conjunctivitis caused by sensitization to Anisakis simplex
.
Journal of Allergy and Clinical Immunology
102
:
331
332
.
Arcos,
 
S. C.,
Ciordia,
 
S.
Roberston,
 
L.
Zapico,
 
I.
Jiménez-Ruiz,
 
Y.
Gonzalez-Muñoz,
 
M.
Moneo,
 
I.
Carballeda-Sangiao,
 
N.
Rodriguez-Mahillo,
 
A.
Albar,
 
J. P.
et al.
2014
.
Proteomic profiling and characterization of differential allergens in the nematodes Anisakis simplex sensu stricto and A. pegreffii
.
Proteomics
14
:
1547
1568
.
Arizono,
 
N.,
Yamada,
 
M.
Tegoshi,
 
T.
and
Yoshikawa.
 
M.
2012
.
Anisakis simplex sensu stricto and Anisakis pegreffii: Biological characteristics and pathogenetic potential in human anisakiasis
.
Foodborne Pathogens and Disease
9
:
517
521
.
Bahlool,
 
Q. Z.,
Skovgaard,
 
A.
Kania,
 
P. W.
and
Buchmann.
 
K.
2013
.
Effects of excretory/secretory products from Anisakis simplex (Nematoda) on immune gene expression in rainbow trout (Oncorhynchus mykiss)
.
Fish & Shellfish Immunology
35
:
734
739
.
Baird,
 
F. J.,
Gasser,
 
R. B.
Jabbar,
 
A.
and
Lopata.
 
A. L.
2014
.
Foodborne anisakiasis and allergy
.
Molecular and Cellular Probes
28
:
167
174
.
Baird,
 
F. J.,
Su,
 
X.
Aibinu,
 
I.
Nolan,
 
M. J.
Sugiyama,
 
H.
Otranto,
 
D.
Lopata,
 
A. L.
and
Cantacessi.
 
C.
2016
.
The Anisakis transcriptome provides a resource for fundamental and applied studies on allergy-causing parasites
.
PLoS Neglected Tropical Diseases
10
:
e0004845
.
Bao,
 
M.,
Mota,
 
M.
Nachón,
 
D.
Antunes,
 
C.
Cobo,
 
F.
Garci,
 
M. E.
Pierce,
 
G. J.
and
Pascual.
 
S.
2015
.
Anisakis infection in allis shad, Alosa alosa (Linnaeus, 1758), and twaite shad, Alosa fallax (Lacépède, 1803), from Western Iberian Peninsula Rivers: Zoonotic and ecological implications
.
Parasitology Research
114
:
2143
2154
.
Carballeda-Sangiao,
 
N.,
Rodríguez-Mahillo,
 
A. I.
Careche,
 
M.
Navas,
 
A.
Caballero,
 
T.
Dominguez-Ortega,
 
J.
Jurado-Palomo,
 
J.
and
González-Muñoz.
 
M.
2016
.
Ani s 11-like protein is a pepsin- and heat-resistant major allergen of Anisakis spp. and a valuable tool for Anisakis allergy component-resolved diagnosis
.
International Archives of Allergy and Immunology
169
:
108
112
.
Carrera,
 
M.,
Gallardo,
 
J. M.
Pascual,
 
S.
González,
 
Á. F.
and
Medina.
 
I.
2016
.
Protein biomarker discovery and fast monitoring for the identification and detection of anisakids by parallel reaction monitoring (PRM) mass spectrometry
.
Journal of Proteomics
142
:
130
137
.
Chen,
 
H. Y.,
Cheng,
 
Y. S.
Grabner,
 
D. S.
Chang,
 
S. H.
and
Shih.
 
H. H.
2014
.
Effect of different temperatures on the expression of the newly characterized heat shock protein 90 (Hsp90) in L3 of Anisakis spp. isolated from Scomber australasicus
.
Veterinary Parasitology
205
:
540
550
.
Chiung,
 
Y. M.,
Lin,
 
B. L.
Yeh,
 
C. H.
and
Lin.
 
C. Y.
2000
.
Heat shock protein (hsp 70)-related epitopes are common allergenic determinants for barley and corn antigens
.
Electrophoresis
21
:
297
300
.
Cho,
 
W. C.
2007
.
Proteomics technologies and challenges
.
Genomics, Proteomics & Bioinformatics
5
:
77
85
.
Choi,
 
S. J.,
Lee,
 
J. C.
Kim,
 
M. J.
Hur,
 
G. Y.
Shin,
 
S. Y.
and
Park.
 
H. S.
2009
.
The clinical characteristics of Anisakis allergy in Korea
.
Korean Journal of Internal Medicine
24
:
160
163
.
Conesa,
 
A.,
Götz,
 
S.
García-Gómez,
 
J. M.
Terol,
 
J.
Talón,
 
M.
and
Robles.
 
M.
2005
.
Blast2GO: A universal tool for annotation, visualization and analysis in functional genomics research
.
Bioinformatics
21
:
3674
3676
.
Cuende,
 
E.,
Audicana,
 
M. T.
Garcia,
 
M.
Anda,
 
M.
Fernández Corres,
 
L.
Jimenez,
 
C.
and
Vesga.
 
J. C.
1998
.
Rheumatic manifestations in the course of anaphylaxis caused by Anisakis simplex
.
Clinical and Experimental Rheumatology
16
:
303
304
.
Daschner,
 
A.,
Cuéllar,
 
C.
and
Rodero.
 
M.
2012
.
The Anisakis allergy debate: Does an evolutionary approach help?
Trends in Parasitology
28
:
9
15
.
da Silva,
 
M. B.,
Urrego,
 
J. R. A.
Oviedo,
 
Y.
Cooper,
 
P. J.
Pacheco,
 
L. G.
Pinheiro,
 
C. S.
Ferreira,
 
F.
Briza,
 
P.
and
Alcantara-Neves.
 
N. M.
2018
.
The somatic proteins of Toxocara canis larvae and excretory–secretory products revealed by proteomics
.
Veterinary Parasitology
259
:
25
34
.
Dimitrov,
 
I.,
Flower,
 
D. R.
and
Doytchinova.
 
I.
2013
.
AllerTOP—A server for in silico prediction of allergens
.
BMC Bioinformatics
14
(Suppl. 6)
:
S4
.
Fæste,
 
C. K.,
Jonscher,
 
K. R.
Dooper,
 
M. M.
Egge-Jacobsen,
 
W.
Moen,
 
A.
Daschner,
 
A.
Egaas,
 
E.
and
Christians.
 
U.
2014
.
Characterisation of potential novel allergens in the fish parasite Anisakis simplex
.
EuPA Open Proteomics
4
:
140
155
.
Guarneri,
 
F.,
Guarneri,
 
C.
and
Benvenga.
 
S.
2007
.
Cross-reactivity of Anisakis simplex: Possible role of Ani s 2 and Ani s 3
.
International Journal of Dermatology
46
:
146
150
.
Gygi,
 
S. P.,
Rochon,
 
Y.
Franza,
 
B. R.
and
Aebersold.
 
R.
1999
.
Correlation between protein and mRNA abundance in yeast
.
Molecular and Cellular Biology
19
:
1720
1730
.
Hiller,
 
K.,
Grote,
 
A.
Maneck,
 
M.
Münch,
 
R.
and
Jahn.
 
D.
2006
.
JVirGel 2.0: Computational prediction of proteomes separated via two-dimensional gel electrophoresis under consideration of membrane and secreted proteins
.
Bioinformatics
22
:
2441
2443
.
Hotez,
 
P.,
Cappello,
 
M.
Hawdon,
 
J.
Beckers,
 
C.
and
Sakanari.
 
J.
1994
.
Hyaluronidases of the gastrointestinal invasive nematodes Ancylostoma caninum and Anisakis simplex: Possible functions in the pathogenesis of human zoonoses
.
Journal of Infectious Diseases
170
:
918
926
.
Keller,
 
A.,
Nesvizhskii,
 
A. I.
Kolker,
 
E.
and
Aebersold.
 
R.
2002
.
Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search
.
Analytical Chemistry
74
:
5383
5392
.
Kochanowski,
 
M.,
González-Muñoz,
 
M.
Gómez-Morales,
 
M. Á.
Gottstein,
 
B.
Dąbrowska,
 
J.
Różycki,
 
M.
Cencek,
 
T.
Müller,
 
N.
and
Boubaker.
 
G.
2019
.
Comparative analysis of excretory–secretory antigens of Anisakis simplex, Pseudoterranova decipiens and Contracaecum osculatum regarding their applicability for specific serodiagnosis of human anisakidosis based on IgG-ELISA
.
Experimental Parasitology
197
:
9
15
.
Laemmli,
 
U. K.
1970
.
Cleavage of structural proteins during the assembly of the head of bacteriophage T4
.
Nature
227
:
680
685
.
Lim,
 
H.,
Jung,
 
B. K.
Cho,
 
J.
Yooyen,
 
T.
Shin,
 
E. H.
and
Chai.
 
J. Y.
2015
.
Molecular diagnosis of cause of anisakiasis in humans, South Korea
.
Emerging Infectious Diseases
21
:
342
344
.
Liu,
 
H.,
Sadygov,
 
R. G.
and
Yates.
 
J. R.
2004
.
A model for random sampling and estimation of relative protein abundance in shotgun proteomics
.
Analytical Chemistry
76
:
4193
4201
.
Llorens,
 
C.,
Arcos,
 
S.
Robertson,
 
L.
Ramos,
 
R.
Futami,
 
R.
Soriano,
 
B.
Ciordia,
 
S.
Careche,
 
M.
González-Muñoz,
 
M.
Jiménez-Ruiz,
 
Y.
et al.
2018
.
Functional insights into the infective larval stage of Anisakis simplex s.s., Anisakis pegreffii and their hybrids based on gene expression patterns
.
BMC Genomics
19
:
592
.
Łopieńska-Biernat,
 
E.,
ZóŁtowska,
 
K.
and
Rokicki.
 
J.
2004
.
The activity of hydrolases of larval stages of Anisakis simplex (Nematoda)
.
Annals of Parasitology
50
:
503
507
.
Łopieńska-Biernat,
 
E.,
ZóŁtowska,
 
K.
and
Rokicki.
 
J.
2006
.
The content of carbohydrates in larval stages of Anisakis simplex (Nematoda, Anisakidae)
.
Helminthologia
43
:
125
129
.
Łopieńska-Biernat,
 
E.,
ZóŁtowska,
 
K.
and
Rokicki.
 
J.
2007
.
Trehalose catabolism enzymes in L3 and L4 larvae of Anisakis simplex
.
Journal of Parasitology
93
:
1291
1294
.
Ludovisi,
 
A.,
Di Felice,
 
G.
Carballeda-Sangiao,
 
N.
Barletta,
 
B.
Butteroni,
 
C.
Corinti,
 
S.
Marucci,
 
G.
González-Muñoz,
 
M.
Pozio,
 
E.
and
Gómez-Morales.
 
M. A.
2017
.
Allergenic activity of Pseudoterranova decipiens (Nematoda: Anisakidae) in BALB/c mice
.
Parasites & Vectors
10
:
290
.
Meseguer,
 
J.,
Navarro,
 
V.
Sánchez-Guerrero,
 
I.
Bartolomé,
 
B.
and
Negro Alvarez
 
J. M.
.
2007
.
Anisakis simplex allergy and nephrotic syndrome
.
Allergologia et Immunopathologia
35
:
216
220
.
Moneo,
 
I.,
Caballero,
 
M. L.
González-Muñoz,
 
M.
Rodríguez-Mahillo,
 
A. I.
Rodríguez-Perez,
 
R.
and
Silva.
 
A.
2005
.
Isolation of a heat-resistant allergen from the fish parasite Anisakis simplex
.
Parasitology Research
96
:
285
289
.
Movérare,
 
R.,
Elfman,
 
L.
Stålenheim,
 
G.
and
Björnsson.
 
E.
2000
.
Study of the Th1/Th2 balance, including IL-10 production, in cultures of peripheral blood mononuclear cells from birch-pollen-allergic patients
.
Allergy
55
:
171
175
.
Nesvizhskii,
 
A. I.,
Keller,
 
A.
Kolker,
 
E.
and
Aebersold.
 
R.
2003
.
A statistical model for identifying proteins by tandem mass spectrometry
.
Analytical Chemistry
75
:
4646
4658
.
Quiazon,
 
K. M. A.,
Zenke,
 
K.
and
Yoshinaga.
 
T.
2013
.
Molecular characterization and comparison of four Anisakis allergens between Anisakis simplex sensu stricto and Anisakis pegreffii from Japan
.
Molecular and Biochemical Parasitology
190
:
23
26
.
Scala,
 
E.,
Giani,
 
M.
Pirrotta,
 
L.
Guerra,
 
E. C.
Cadoni,
 
S.
Girardelli,
 
C. R.
De Pità,
 
O.
and
Puddu.
 
P.
2001
.
Occupational generalised urticaria and allergic airborne asthma due to Anisakis simplex
.
European Journal of Dermatology
11
:
249
250
.
Searle,
 
B. C.
2010
.
Scaffold: A bioinformatic tool for validating MS/MS-based proteomic studies
.
Proteomics
10
:
1265
1269
.
Stryiński,
 
R.,
Mateos,
 
J.
Pascual,
 
S.
González,
 
Á. F.
Gallardo,
 
J. M.
Łopieńska-Biernat,
 
E.
Medina,
 
I.
and
Carrera.
 
M.
2019
.
Proteome profiling of L3 and L4 Anisakis simplex development stages by TMT-based quantitative proteomics
.
Journal of Proteomics
201
:
1
11
.
Tyanova,
 
S.,
Temu,
 
T.
and
Cox.
 
J.
2016
.
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
.
Nature Protocols
11
:
2301
2319
.
Wang,
 
J.,
Zhang,
 
D.
and
Li.
 
J.
2013
.
PREAL: Prediction of allergenic protein by maximum relevance minimum redundancy (mRMR) feature selection
.
BMC Systems Biology
7
(Suppl. 5)
:
S9
.
Zhang,
 
Z.,
Wu,
 
S.
Stenoien,
 
D. L.
and
Pasa-Tolic.
 
L.
2014
.
High-throughput proteomics
.
Annual Review of Analytical Chemistry (Palo Alto California)
7
:
427
454
.
Zhu,
 
X.,
Gasser,
 
R. B.
Podolska,
 
M.
and
Chilton.
 
N. B.
1998
.
Characterisation of anisakid nematodes with zoonotic potential by nuclear ribosomal DNA sequences
.
International Journal for Parasitology
28
:
1911
1921
.
ŻóŁtowska,
 
K.,
Dmitryjuk,
 
M.
Rokicki,
 
J.
and
Łopieńska-Biernat.
 
E.
2007
.
Hydrolases of Hysterothylacium aduncum (Nematoda)
.
Annals of Parasitology
53
:
91
95
.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Supplementary data