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A Rapid and Simple LC–MS Method Using Collagen Marker Peptides for Identification of the Animal Source of Leather Yuki Kumazawa, Yuki Taga, Kenji Iwai, and Yohichi Koyama J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b02132 • Publication Date (Web): 10 Jul 2016 Downloaded from http://pubs.acs.org on July 11, 2016

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Journal of Agricultural and Food Chemistry

A Rapid and Simple LC–MS Method Using Collagen Marker Peptides for Identification of the Animal Source of Leather

Yuki Kumazawa†, Yuki Taga*,‡, Kenji Iwai†, and Yoh-ichi Koyama†,‡



Japan Institute of Leather Research, 520-11 Kuwabara, Toride, Ibaraki 302-0017, Japan



Nippi Research Institute of Biomatrix, 520-11 Kuwabara, Toride, Ibaraki 302-0017, Japan

*Corresponding author (Tel: +81-297-71-3046; Fax: +81-297-71-3041; E-mail: [email protected])

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ABSTRACT

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Identification of the animal source of leather is difficult using traditional methods, including

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microscopic observation and PCR. In the present study, a LC–MS method was developed for

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detecting interspecies differences in the amino acid sequence of type I collagen, which is a

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major component of leather, among six animals (cattle, horse, pig, sheep, goat, and deer). After

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a dechroming procedure and trypsin digestion, six tryptic peptides of type I collagen were

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monitored by LC–MS in multiple reaction monitoring mode for the animal source identification

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using the patterns of the presence or absence of the marker peptides. We analyzed commercial

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leathers from various production areas using this method, and found some leathers in which the

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commercial label disagreed with the identified animal source. Our method enabled rapid and

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simple leather certification and could be applied to other animals whether or not their collagen

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sequences are available in public databases.

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KEYWORDS: leather, collagen, mass spectrometry, species identification, scanning electron

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microscopy

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INTRODUCTION

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Leather is produced from animal skin by chemical tanning using chrome or vegetable agents.1

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The tanning process provides high mechanical strength and stability against heat and moisture

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by cross-linking of collagen, which is a major protein component in skin. Leather is widely

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used for making bags, gloves, clothes, and other products, and the global trade value of the

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leather and leather products industry is approximately $100 billion per year. Leather can be

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derived from various animals, such as cattle, pig, and goat. The animal source of the leather

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must be specified on the consumer product by the supplier. However, the animal source is

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sometimes incorrectly stated because of accidental or fraudulent substitution. In many cases, the

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animal source cannot be easily discriminated by visual analysis.

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Identification of the animal source of leather is generally performed by microscopic

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observation of characteristic morphology. Scanning electron microscopy (SEM) is used for

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identification of the animal source based on the cross-sectional fiber structure of collagen, the

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surface texture of the grain layer, and pore patterns on the leather surface, which are all

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characteristic for certain animals.2-4 However, extensive operator experience is required to

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correctly identify the animal source. Leather is produced using various finishing processes,

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including sanding to produce nubuck, embossing, and laminating, and these processes

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sometimes make the skin pores disappear. In addition, split leather lacks skin pores because the

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grain layer is removed. Without these pores on the surface, it is hard to discriminate among

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animal sources of leather, especially sheep and goat, by SEM because of their similarity of the

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cross-sectional fiber structure of collagen.

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A DNA-based approach using PCR has been increasingly used for identification of animal

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sources, especially for food samples,5, 6 and has also been applied to leather from cattle, pig,

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sheep, and goat.7-10 The major advantages of the DNA-based approach are high sensitivity and

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high taxonomic specificity. However, there are some problems with the DNA-based method for

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leather samples. First, DNA can be damaged and degraded by manufacturing treatments,

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especially the tanning process.11 Second, PCR amplifications are inhibited by co-extracted

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compounds during the DNA extraction process from leather.10, 12

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In contrast to DNA, the primary structure of protein is highly stable in the processing of

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leather. Type I collagen consists of two α1 chains and a genetically distinct α2 chain that form

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a stable triple-helical structure. It is the most abundant protein in connective tissues, including

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skin. The amino acid sequence characteristic of collagen is a repeating Gly–Xaa–Yaa sequence,

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and the X and Y positions are frequently occupied by Pro and 4-hydroxyproline (Hyp),

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respectively. Collagen has been used for identification of the animal source for various samples,

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including bone,13 clothing,14 gelatin,15 and glue,16 using mass spectrometric detection of marker

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peptides following trypsin digestion. Buckley et al.13 reported species identification of bone

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with fingerprinting analysis of 92 collagen peptide markers from 32 different mammal species

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using MALDI–TOF–MS. The collagen fingerprinting methodology enables unambiguous

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discrimination of various animal species, and recent studies using the method achieved species

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identification of ancient bone samples in which morphology- and DNA-based approaches were

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unsuccessful.17, 18 However, this method requires fractionation steps and manual confirmation

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of each peptide peak for species identification.

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Multiple reaction monitoring (MRM) on a triple quadrupole MS allows highly sensitive and

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selective detection of target analytes even without purification steps.19 We recently applied LC–

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MS analysis in MRM mode to various collagen analyses.20-25 For example, highly sensitive

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collagen type-specific quantitation (types I and III) was performed by MRM analysis of a

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tryptic digest of collagen samples and needed only 10 min per sample for data acquisition.22 In

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this study, we established a new analytical method using collagen marker peptides with

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detection by LC–MS in MRM mode to identify the animal source of leather, including cattle,

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horse, pig, sheep, goat, and deer. We designed the method to give different and species-specific

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patterns of the presence or absence of six peptide peaks for simple and unambiguous species

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identification. We first investigated the effect of dechroming using calcium hydroxide and

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sulfuric acid on trypsin digestion of leather for efficient peptide generation. The dechromed and

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trypsin-digested leathers were then submitted to MS/MS analysis for identification of marker

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peptides. Commercial leather samples from various production areas were analyzed using the

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selected marker peptides by the high-throughput LC–MS analysis.

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MATERIALS AND METHODS

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Dechroming and Trypsin Digestion of Leather Samples. Samples of commercial leathers

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labeled as cattle, horse, pig, sheep, goat, and deer, which were collected and stored in our

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laboratory, were subjected to dechroming as reported previously.26 Briefly, each leather sample

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was cut into approximately 1 × 1 mm pieces, and three or four pieces of the sample were

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shaken slowly in 10 mL of 0.25% calcium hydroxide for 0–24 h at room temperature. After

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washing several times with distilled water, the leather samples were shaken slowly in 10 mL of

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1.7% sulfuric acid for 0–4 h at room temperature. The samples were washed several times with

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distilled water and heated in distilled water at 80 °C for 30 min to denature the collagen. After

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removal of the distilled water, digestion with 50 µg of trypsin (Sigma-Aldrich, St. Louis, MO)

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was performed in 200 µL of 100 mM Tris-HCl/1 mM calcium chloride (pH 7.6) at 37 °C for 4

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h. The tryptic digest was acidified with formic acid (final 1.0%), and the supernatant was

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filtered through a 0.45 µm filter and subjected to LC–MS/MS or MRM analysis.

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Peptide Identification Using LC–MS/MS. The tryptic digest was analyzed by LC–MS/MS

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using a 3200 QTRAP (AB Sciex, Foster City, CA) mass spectrometer coupled to a 1200 Series

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HPLC system (Agilent Technologies, Palo Alto, CA). The sample solution was loaded onto an

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Ascentis Express C18 HPLC column (2.1 mm x 150 mm i.d., 2.7 µm; Supelco, Bellefonte, PA)

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at a flow rate of 200 µL/min, and separated by a binary gradient as follows: 98% solvent A

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(0.1% formic acid in water) for 5 min, linear gradient of 2–50% solvent B (100% acetonitrile)

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for 15 min, 90% solvent B for 5 min, and 98% solvent A for 5 min. The separated peptides

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were ionized and detected in positive ion mode by information–dependent acquisition, which

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involved selecting the two most intense precursor ions of the prior survey MS scan and then

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subjecting them to MS/MS fragmentation, with Analyst software 1.6.2 (AB Sciex). The MS

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scan and MS/MS acquisition were performed over m/z ranges of 400–1300 and 100–1700,

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respectively. The collision energy was automatically determined based on the mass and charge

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state of the precursor ions using rolling collision energy. ProteinPilot software 4.0 (AB Sciex)

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with the Paragon™ algorithm was used for peptide identification.27 The acquired MS/MS

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spectra were searched against a local type I collagen database, which includes type I collagen

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sequences for various animals from public databases and a previous publication.28

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MRM Analysis of Marker Peptides. Marker peptides were monitored by LC–MS in MRM

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mode. The sample solution was loaded onto an Ascentis Express C18 HPLC column (2.1 mm x

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150 mm i.d., 5 µm; Supelco) at a flow rate of 500 µL/min, and separated by a binary gradient as

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follows: 98% solvent A (0.1% formic acid in water) for 2 min, linear gradient of 2–60% solvent

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B (100% acetonitrile) for 4 min, 90% solvent B for 2 min, and 98% solvent A for 2 min. The

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MRM transitions and collision energy settings for the marker peptides are shown in Table 1.

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The threshold for the peptide detection was set to a signal-to-noise ratio of 10.

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SEM Analysis. The surfaces of the leather samples were cleaned with dimethylformamide,

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and microscopic observation of the grain surface was performed using a JCM-5700 scanning

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electron microscope (JEOL, Tokyo, Japan). Leather samples were sliced into thin layers to

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observe the cross-sectional fiber structure by SEM.

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RESULTS AND DISCUSSION

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Optimization of Dechroming Treatment. Almost no peptides were generated from chrome-

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tanned leathers by trypsin digestion following heat denaturation. Thus, we dechromed the

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leathers using an established process with calcium hydroxide and sulfuric acid.26 Peptide

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generation was investigated for one chrome-tanned cattle leather sample using three tryptic

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peptides, which were identified as marker peptides for animal source identification in the next

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experiment. No peptides were detected by trypsin digestion after dechroming of the leather

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without calcium hydroxide treatment (treatment time = 0 h) and with 1 h of sulfuric acid

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treatment (Figure 1A). Calcium hydroxide treatment dramatically increased peptide generation

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by trypsin, and maximum peptide generation was reached with a calcium hydroxide treatment

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time of 2 h. In contrast, subsequent sulfuric acid treatment did not enhance peptide generation

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(Figure 1B). Therefore, sulfuric acid treatment is not required for peptide generation from

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leather samples using trypsin. Consequently, in the subsequent experiments, we used calcium

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hydroxide treatment (2 h) without sulfuric acid treatment for all leather samples, although

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dechroming treatment was not required for vegetable-tanned leather (data not shown).

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Identification of Collagen Marker Peptides. The collagen-derived peptides generated for

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cattle, horse, pig, sheep, goat, and deer leathers after dechroming and trypsin digestion were

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identified by LC–MS/MS analysis. Various peptides were identified for type I collagen α1 and

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α2 chains. MRM transitions were set for the respective collagen-derived tryptic peptides to

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monitor the presence or absence of the peptides for the leathers from the six different animals.

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Collagen marker peptides for animal source identification were selected in accordance with the

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following concepts: (1) presence of more than three marker peptides for each animal and (2) at

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least two differences in the patterns of the presence or absence of marker peptides between each

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animal. This reduced the chance of incorrect identification of the animal source. We selected

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three marker peptides from α1(I) and three marker peptides from α2(I) in which all Pro at the Y

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position are hydroxylated to 4-Hyp (Figure 2 and Table 1). MRM transitions for the marker

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peptides (Table 1) were determined from the precursor ion (Q1) and fragmented product ions

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(Q3) in the MS/MS analysis (Figure 2).

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The patterns of the presence or absence of the six marker peptides for leather from the six

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animal sources are summarized in Table 1. The MRM chromatograms of the marker peptides

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(Figure 3) showed good peak shapes for all the marker peptides, and were easy to interpret as to

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the presence or absence of the marker peptides. We investigated the trypsin digestion conditions

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and found that most of the peptide generation was completed within 4 h of incubation at 37 °C

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(Figure S1 in the Supporting Information). MRM analysis of the marker peptides took only

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10 min per sample with separation by reverse-phase chromatography. Thus, species

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identification using this method usually can be completed within a day. Detection patterns of

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the marker peptides were different for each of the six animal sources. For example, α1(I) [316–

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327] GFOGADGVAGPK (O indicates 4-Hyp) referred to as P1 was observed for cattle, horse,

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pig, and deer leathers, and α2(I) [978–990] TGQOGAVGPAGIR (P6) was observed for pig,

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sheep, goat, and deer leathers. Buckley et al.29 enabled discrimination between sheep and goat

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bones using a 33 amino acid tryptic peptide, α2(I) [757-789], which differed between the two

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species at two positions. In addition to the above peptide, we identified the following two new

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marker peptides containing a common sequence region for discrimination between sheep and

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goat: α1(I) [733–756] GETGPAGROGEVGPOGPOGPAGEK (P2) and α1(I) [741–756]

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AGEVGPOGPOGPAGEK (P3). The Ala741Hyp substitution from P3 resulted in the missed

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cleaved P2 peptide, because the Arg-Hyp bond is resistant to trypsin.30, 31 As shown in Figure 3,

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P2 was detected for cattle, goat, and deer leathers, whereas P3 was detected only for sheep

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leather. The new marker peptides were detected at high intensities compared with the

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previously identified α2(I) [757-789] peptide by MRM detection (data not shown), probably

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because of the difference in peptide length (24 and 16 vs. 33). The selected six marker peptides

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enabled efficient and simple identification of the animal source of leather, and even allowed

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discrimination between sheep and goat leathers.

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Identification of the Animal Source for Commercial Leathers. We analyzed 75

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commercial leathers from various production areas using our method. Using the presence or

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absence of the marker peptides, all the leather samples labeled as being of cattle, horse, and pig

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origins were identified as the same (Table 2). For leather labeled as sheep, goat, and deer, some

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of the detected marker peptide patterns did not match the animal source given on the label. The

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marker peptide patterns for leather samples labeled as deer seemed to differ depending on the

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production area. For deer samples from Japan and New Zealand, the identification results

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matched the commercial labels with detection of P1, P2, P4, P5 and P6 markers. In contrast, for

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deer samples from Italy and the USA, detection of P1, P2, P4, and P6 was observed, which did

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not correspond to any of the animals in this study (Figure 4C). This could be because deer are

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classified into two subfamilies, Cervinae and Capreolinae.32 A previous study reported amino

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acid substitution(s) in α2(I) [757-789] between the Cervinae subfamily (fallow deer) and

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Capreolinae subfamily (roe deer).33 From the habitat distribution of deer,32 we assume that the

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deer leathers from Japan and New Zealand are from Cervinae and those from Italy and the USA

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are from Capreolinae. This subfamily difference in deer could explain the lack of the P5 marker

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for the deer samples from Italy and the USA. However, authenticated deer samples are needed

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to confirm this hypothesis. Almost all leather samples labeled as sheep and goat were identified

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as the same species. However, the marker peptide patterns for sheep_China-1 (P2, P4, and P6;

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Figure 4A) and goat_China-2 (P3, P4, and P6; Figure 4B) disagreed with the labeled animal

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source. The detection patterns for sheep_China-1 and goat_China-2 indicated that they were

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goat and sheep leathers, respectively.

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Microscopic Observation of Sheep and Goat Leathers. To confirm the lack of a match

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between the label and identification results for sheep_China-1 and goat_China-2, we analyzed

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these samples by SEM to observe the fiber structure, surface texture, and skin pore patterns

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(Figure 5). Sheep_Indonesia-1 and goat_Indonesia-1 were identified as sheep and goat,

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respectively, using the marker peptides (Table 2), and were used as standard samples. Collagen

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fibers ran parallel to the grain layer in both the sheep and goat standard leathers (Figure 5A and

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B). However, the surface of the goat leather was rough compared with the smooth surface of the

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sheep leather, and the skin pores were grouped in rows on the grain surface of the goat leather

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but not on the sheep leather (Figure 5E and F). In the goat_China-2 and sheep_China-1

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samples, the fiber structures were similar to those in the sheep and goat standards (Figure 5C

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and D). In addition, in the goat_China-2 sample, the smooth surface and the uniform skin pores

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were similar to the sheep standard (Figure 5G). Therefore, this sample was likely of sheep

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origin, and this result was consistent with the identification using the marker peptides. In

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contrast, the surface of the sheep_China-1 leather sample was not present, probably because the

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grain layer had been removed by splitting (Figure 5H). Consequently, we were not able to

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confirm the animal source for the sheep_China-1 sample using SEM analysis. However, our

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method using the tryptic marker peptides provided an indication of this sample’s origin.

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In the present study, LC–MS in MRM mode was used to identify the animal source of leather

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using a combination of presence or absence of six marker peptides derived from type I collagen.

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The sample preparation took approximately 7 h, including dechroming and trypsin digestion,

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and LC–MS analysis took 10 min per sample. The MS data were easily interpreted to identify

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the species from the detection patterns of the six marker peptides. Although we limited the

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target animals to cattle, horse, pig, sheep, goat, and deer, other animals could be identified

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using this method after selection of appropriate marker peptides. This strategy for animal source

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identification using the presence or absence of marker peptides could also enable identification

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of animals, such as snakes and alligators that are used for leather products, even if their type I

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collagen sequences are not available in public databases. Animal source identification by

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microscopic observation sometimes fails when the surface and fiber structure of leather are

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disrupted (Figure 5H), but the LC–MS analysis of tryptic marker peptides successfully

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identified all the 75 leather samples analyzed in this study. The developed method is robust and

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can be used for screening and routine measurements.

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ABBREVIATIONS USED

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SEM, scanning electron microscopy; Hyp, hydroxyproline; MRM, multiple reaction monitoring

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SUPPORTING INFORMATION AVAILABLE

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Figure S1: Optimization of trypsin digestion of leather. Table S1: List of identified peptides

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for cattle leathers. Table S2: List of identified peptides for horse leathers. Table S3: List of

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identified peptides for pig leathers. Table S4: List of identified peptides for sheep leathers.

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Table S5: List of identified peptides for goat leathers. Table S6: List of identified peptides for

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deer leathers. This material is available free of charge via the Internet at http://pubs.acs.org.

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Lange, V.; Picotti, P.; Domon, B.; Aebersold, R. Selected reaction monitoring for

Taga, Y.; Kusubata, M.; Ogawa-Goto, K.; Hattori, S. Development of a novel method

Taga, Y.; Kusubata, M.; Ogawa-Goto, K.; Hattori, S. Site-specific quantitative analysis

Taga, Y.; Kusubata, M.; Ogawa-Goto, K.; Hattori, S. Stable isotope-labeled collagen: a

Taga, Y.; Kusubata, M.; Ogawa-Goto, K.; Hattori, S. Highly accurate quantification of

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Taga, Y.; Kusubata, M.; Ogawa-Goto, K.; Hattori, S. Developmental stage-dependent

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regulation of prolyl 3-hydroxylation in tendon type I collagen. J. Biol. Chem. 2016, 291, 837-

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hydroxyproline (Hyp)-Gly after oral administration of a novel gelatin hydrolysate prepared

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using ginger protease. J. Agric. Food Chem. 2016, 64, 2962-70.

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from chrome leather. Sci. Rept. Fac. Agr. Kobe Univ. 1983, 15, 387-391.

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Hunter, C. L.; Nuwaysir, L. M.; Schaeffer, D. A. The Paragon Algorithm, a next generation

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search engine that uses sequence temperature values and feature probabilities to identify

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peptides from tandem mass spectra. Mol. Cell. Proteomics 2007, 6, 1638-55.

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survival and utility. Geochim. Cosmochim. Acta 2011, 75, 2007-2016.

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Distinguishing between archaeological sheep and goat bones using a single collagen peptide. J.

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Archaeol. Sci. 2010, 37, 13-20.

Taga, Y.; Kusubata, M.; Ogawa-Goto, K.; Hattori, S. Efficient absorption of X-

Itoh, K.; Nakagawa, S.; Okayama, T. Basic studies on the dechroming of shaving dust

Shilov, I. V.; Seymour, S. L.; Patel, A. A.; Loboda, A.; Tang, W. H.; Keating, S. P.;

Buckley, M.; Larkin, N.; Collins, M. Mammoth and Mastodon collagen sequences;

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Rodriguez, J.; Gupta, N.; Smith, R. D.; Pevzner, P. A. Does trypsin cut before proline?

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J.; Ge, Y.; Westphall, M. S.; Coon, J. J.; Greenspan, D. S. Comprehensive mass spectrometric

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mapping of the hydroxylated amino acid residues of the alpha1(V) collagen chain. J. Biol.

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remains from Domuztepe, South Eastern Turkey. Archaeol. Anthropol. Sci. 2011, 3, 271-280.

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Geist, V., Deer of the world: their evolution, behavior, and ecology. Stackpole Books:

Buckley, M.; Kansa, S. W. Collagen fingerprinting of archaeological bone and teeth

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FIGURE CAPTIONS

325

Figure 1. Effect of dechroming treatments on peptide generation from leather using trypsin. A

326

sample of chrome-tanned cattle leather was incubated with (A) 0.25% calcium hydroxide for

327

either 0, 0.5, 1, 2, 4, 8, or 24 h followed by incubation with 1.7% sulfuric acid for 1 h or (B)

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1.7% sulfuric acid for either 0, 0.5, 1, 2, or 4 h following incubation with 0.25% calcium

329

hydroxide for 2 h. Peptide generation was estimated using collagen marker peptides (P1, P2,

330

and P4) shown in Table 1. The data are expressed as relative intensity with (A) 24 h or (B) 0 h

331

being 100%, and represent the mean ± SD of three replicates.

332

333

Figure 2. MS/MS spectra of marker peptides for species identification of leather. (A–F)

334

MS/MS spectra of P1–P6 marker peptides were obtained from cattle, goat, sheep, sheep, pig,

335

and pig leathers. The peaks in blue and red are used for Q1 and Q3 transitions, respectively, for

336

MRM analysis of the marker peptides as summarized in Table 1.

337

338

Figure 3. MRM chromatograms of marker peptides for leather from six animal species (cattle,

339

horse, pig, sheep, goat, and deer). Detected marker peptides are indicated in bold face.

340

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Figure 4. MRM chromatograms of marker peptides in unmatched leather samples. Tryptic

342

digests of (A) sheep_China-1, (B) goat_China-2, and (C) deer_USA-1 were analyzed by LC–

343

MS in MRM mode. Detected marker peptides are indicated in bold face.

344

345

Figure 5. SEM images of (A–D) cross sections and (E–H) surfaces of leather samples.

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TABLES Table 1. List of Marker Peptides for Animal Species Identification Chain

α1(I)

α2(I)

Positiona

Marker peptide

Cattlec

Horsec

Pigc

Sheepc

Goatc

Deerc

Q1 (m/z)d

Q3 (m/z)d

zd

Collision energyd

Time (min)d

316–327

P1

GFOGADGVAGPK

+

+

+





+

544.76

643.34

2

30.0

5.3

733–756

P2

GETGPAGROGEVGPOGPOGPAGEK

+







+

+

739.35

964.98

3

25.3

5.0

741–756

P3

AGEVGPOGPOGPAGEK







+





724.85

1035.51

2

37.9

5.0

361–374

P4

GFOGSOGNIGPAGK

+

+



+

+

+

644.31

826.44

2

34.3

5.2

502–519

P5

GPOGESGAAGPAGPIGSR



+

+





+

775.87

811.44

2

40.1

5.1

978–990

P6

TGQOGAVGPAGIR





+

+

+

+

598.82

669.40

2

32.3

5.1

Sequenceb

a

The numbering of residues begins with the triple-helical portion of the chains. For example, first residue corresponds to residue 178 of Uniprot # P02453 (bovine type I

collagen α1 chain) and residue 89 of Uniprot # P02465 (bovine type I collagen α2 chain). bO indicates 4-Hyp. cThe presence and absence of marker peptides are denoted by + and −, respectively. dMRM transitions (Q1 and Q3) for the marker peptides are shown with their charge state, collision energy, and retention time.

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Table 2. Species Identified for Leathers from Various Production Areas Species on label Cattle

Horse

Pig

Sheep

Goat

Sample

P1

P2

P3

P4

P5

P6

Identified species

Japan-1, Japan-2, Japan-3

+

+



+





Cattle

China-1, China-2, China-3

+

+



+





Cattle

India-1, India-2, India-3

+

+



+





Cattle

Pakistan-1, Pakistan-2, Pakistan-3

+

+



+





Cattle

Bangladesh-1, Bangladesh-2

+

+



+





Cattle

Italy-1, Italy-2, Italy-3

+

+



+





Cattle

USA-1, USA-2, USA-3

+

+



+





Cattle

Japan-1, Japan-2

+





+

+



Horse

Mongolia-1

+





+

+



Horse

France-1

+





+

+



Horse

Poland-1, Poland-2, Poland-3

+





+

+



Horse

Japan-1, Japan-2, Japan-3

+







+

+

Pig

China-1, China-2, China-3

+







+

+

Pig

Japan-1, Japan-2, Japan-3





+

+



+

Sheep

China-1



+



+



+

Goat

China-2, China-3





+

+



+

Sheep

India-1, India-2, India-3





+

+



+

Sheep

Pakistan-1, Pakistan-2, Pakistan-3





+

+



+

Sheep

Indonesia-1, Indonesia-2





+

+



+

Sheep

Italy-1, Italy-2, Italy-3





+

+



+

Sheep

China-1, China-3



+



+



+

Goat

China-2





+

+



+

Sheep

India-1, India-2, India-3



+



+



+

Goat

Pakistan-1, Pakistan-2, Pakistan-3



+



+



+

Goat

22

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Deer

Indonesia-1, Indonesia-2, Indonesia-3



+



+



+

Goat

Italy-1



+



+



+

Goat

Japan-1, Japan-2, Japan-3

+

+



+

+

+

Deer

Italy-1, Italy-2, Italy-3

+

+



+



+

Deer?

USA-1, USA-2, USA-3

+

+



+



+

Deer?

New Zealand-1, New Zealand-2, New Zealand-3

+

+



+

+

+

Deer

23

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Fig. 1 83x85mm (300 x 300 DPI)

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Fig. 2 173x123mm (300 x 300 DPI)

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Fig. 3 173x109mm (300 x 300 DPI)

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Fig. 4 83x104mm (300 x 300 DPI)

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Fig. 5 177x67mm (300 x 300 DPI)

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Graphic for table of contents 85x44mm (300 x 300 DPI)

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