Species-specific identification of donkey-hide gelatin and its adulterants using marker peptides

Jinju Zhang; Menghua Wu; Zhiguo Ma; Ying Zhang; Hui Cao

doi:10.1371/journal.pone.0273021

. 2022 Aug 12;17(8):e0273021. doi: 10.1371/journal.pone.0273021

Species-specific identification of donkey-hide gelatin and its adulterants using marker peptides

Jinju Zhang ^1,², Menghua Wu ^1,², Zhiguo Ma ^1,², Ying Zhang ^1,^2,^*, Hui Cao ^1,^2,^*

Editor: Chun-Hua Wang³

PMCID: PMC9374224 PMID: 35960756

Abstract

Donkey-hide gelatin is an important traditional Chinese medicine made from donkey skin. Despite decades of effort, identifying the animal materials (donkeys, horses, cattle and pigs) in donkey-hide gelatin remains challenging. In our study, we aimed to identify marker peptides of donkey-hide gelatin and its adulterants and develop a liquid chromatography–tandem mass spectrometry method to identify them. Theoretical marker peptides of four animals (donkeys, horses, cattle and pigs) were predicted and verified by proteomic experiments, and 12 species-specific marker peptides from donkey-hide gelatin and its adulterants were identified. One marker peptide for each gelatin was selected to develop the liquid chromatography–tandem mass spectrometry method. The applicability of the method was evaluated by investigating homemade mixed gelatin samples and commercial donkey-hide gelatin products. Using the liquid chromatography–tandem mass spectrometry method, the addition of cattle-hide gelatin and pig-hide gelatin to donkey-hide gelatin could be detected at a level of 0.1%. Horse-hide gelatin was detected when added at a level of 0.5%. Among 18 batches of donkey-hide gelatin products, nine were identified as authentic, and eight of the remaining samples were suspected to be adulterated with horse materials. These results provide both a practical method to control the quality of donkey-hide gelatin and a good reference for quality evaluations of other medicinal materials and foods containing protein components.

Introduction

Donkey-hide gelatin (DHG), also known as Colla Corri Asini, has been used as a valuable medicine in China for thousands of years due to its effects such as nourishing the blood and enhancing physical abilities. DHG is a mixture of amino acids and high-molecular-weight polypeptides that are produced by the hydrolysis of collagens from donkey skin. However, the supply of donkey skins cannot fulfill the increasing demands for DHG due to donkey husbandry limitations. Therefore, skins from other animals, such as cattle, pigs and horses, are often used illicitly as a substitute for DHG [1]. The safety and efficiency of DHG have been tested and verified by proven historical facts, but gelatins made from other animal skins may have unpredictable and serious consequences [2–4]. For example, it has been indicated that cattle-hide gelatins (CHGs) may cause safety problems because of the risk of bovine spongiform encephalopathy and foot-and-mouth disease [5, 6]. Pig-hide gelatins (PHGs) may present religious conflicts since the use of porcine foods and drugs is forbidden for people in some Islamic countries [7]. Furthermore, traditional Chinese medicine experts believe that DHGs and horse-hide gelatins (HHGs) have opposite effects.

Since DHG was listed in the Chinese Pharmacopoeia in 1977, great efforts have been dedicated to its identification. However, it is difficult to distinguish different gelatins, especially adulterated gelatins, using traditional physicochemical analysis methods [8–10]. Some widely used analytical methods, including polymerase chain reaction (PCR) and enzyme-linked immunosorbent assays (ELISAs), have been applied to identify gelatins [11, 12]. However, the thermal processing of gelatins at high temperatures may result in poor yield or degradation of DNA. This may lead to false and unreliable results and therefore, prevents PCR from being widely implemented. ELISA methods are also limited because of the protein degradation that can be caused by severe processing treatments [13]. Therefore, establishing an effective method to identify DHG and its adulterants is urgently needed.

Previous studies have proven that collagens, especially type I collagen, are the main active components in gelatins [14, 15]. Type I collagens contain two α1 chains [α1 (I)] and one α2 chain [α2 (I)]. Theoretically, the amino acid sequences of type I collagens vary from species to species. Therefore, we hypothesized that collagens from different animals may produce marker peptides that are unique to each species after being digested by trypsin [16] that may serve as markers to identify their corresponding gelatin. However, finding marker peptides in complex samples is very challenging. Fortunately, in recent years, highly sensitive and accurate liquid chromatography–tandem mass spectrometry (LC–MS/MS) proteomic profiling has led to the fast and accurate identification of peptides [16]. To date, several methods have been reported for identifying gelatins based on clustering analysis of MS/MS data [14, 17]. Other studies have predicted potential marker peptides by analyzing part of the type I collagen sequences followed by validation of these sequences using a proteomic method [10, 17, 18]. The latter strategy is better for the identification of adulterated gelatins and deserves further research.

In our study, both α1 (I) and α2 (I) were used to predict theoretical marker peptides. The presence of the theoretical peptides in gelatins was tested by LC–MS/MS proteomic analysis. Then, based on the detected marker peptides, an LC–MS/MS method was developed. The ability to identify DHG and its adulterants using this method was also evaluated. The study presented in this thesis is a comprehensive investigation to focus specifically on the identification of gelatins using marker peptides. Moreover, the method established here plays an important role in gelatin quality control.

Materials and methods

Samples and reagents

Dithiothreitol (DTT), 3-indoleacrylic acid (IAA), formic acid (FA), and acetonitrile (ACN) were purchased from Sigma (St. Louis, MO, USA). Water was purified using a Millipore purification system (Billerica, MA, USA). Sequencing-grade trypsin was obtained from Aladdin (Shanghai, China). A BCA protein assay kit was purchased from Beyotime (Nanjing, China). The four selected marker peptides were synthesized by Chinese Peptides (purity ≥ 95%, Shanghai, China).

Standard medicine samples of DHG (121274–201703), CHG (121695–201802) and PHG (121745–201701) were purchased from the National Institutes for Food and Drug Control (NIFDC; Beijing, China). Twenty-five batches of the four different gelatins (10 DHGs, 5 CHGs, 5 PHGs and 5 HHGs) were provided by the Inner Mongolia Gen-incept Biological Medicine Technology Co. (Inner Mongolia, China). All samples from the Inner Mongolia Gen-incept Biological Medicine Technology Co. were prepared according to the processing specifications in the Chinese Pharmacopoeia 2020 edition, and the quality of every gelatin sample complied with Chinese Pharmacopeia 2020 edition requirements [19]. A total of 18 batches of commercial DHG products were purchased from several pharmacies and medicine markets. The information for all of the samples collected in our study is detailed in S1 Table. No specific permissions were required for the collected samples as none of the studies involved animal research or sacrifice.

Theoretical marker peptide prediction

To perform sequence alignment and predict theoretical marker peptides, collagen sequences, including α1 (I) and α2 (I) from donkeys, horses, cattle and pigs (accession numbers: B9VR88, B9VR89, F6SSG3, F6RTI8, P02453, P02465, A0A1S7J210, F1SFA7), were obtained from the Universal Protein Resource (UniProt, https://www.uniprot.org/). The collagen sequences from these four animal species were compared by sequence alignment using BioEdit software (version 7.0.9).

Sample preparation for proteomic analysis

Three samples (one DHG, one CHG and one PHG) collected from the NIFDC and seven samples (two DHGs, two CHGs, two PHGs and one HHG) from the Inner Mongolia Gen-incept Biological Medicine Technology Co. were used for proteomic analysis. Sample preparation was performed via modified methods from previous studies [20, 21]. Each sample was ground in a crucible with a continuous supply of liquid nitrogen to create a powder. Then, 2 ml of RIPA lysis buffer was added to 0.5 g of accurately weighed powder to extract the protein. The product was concentrated using a 10 kDa centrifugal filter. Then, a BCA protein assay kit was used to determine the protein concentration in the supernatant according to the manufacturer’s instructions. The protein sample (100 μg) was reduced using 10 mM DTT at 56°C for 3 h. Next, alkylation was performed in 50 mM IAA for 40 min at room temperature in the dark. Then, the protein was digested with 3 μg of trypsin at 37°C for 12 h. All digests were desalted using a SOLA HRP Cartridge (Thermo Fisher Scientific, USA) and dried with a vacuum freeze-dryer. The lyophilized peptides were reconstituted in 0.1% FA prepared for proteomic analysis.

Proteomic analysis

To verify the predicted theoretical marker peptides, we performed proteomic experiments using an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific, USA) equipped with an EASY-nLC 1200 HPLC system (Thermo Fisher Scientific, USA). The HPLC and mass spectrometry (MS) instruments were both controlled by Xcalibur software (Thermo Fisher Scientific, USA). For LC separation, tryptic peptides were sequentially injected onto an Acclaim PepMap 100 C18 column (100 μm × 20 mm, 5 μm, Thermo, P/N: 1645664) and an Acclaim PepMap 100 C18 column (50 μm × 150 mm, 2 μm, Thermo, P/N: 164943). The mobile phases were Buffer A (2% ACN with 0.1% FA) and Buffer B (80% ACN with 0.1% FA). The following gradient program was utilized at a flow rate of 600 nL/min: 0–14 min, 5–12% Buffer B; 14−40 min, 12–24% Buffer B; 40–53 min, 24–38% Buffer B; 53–54 min, 38–95% Buffer B; and 54−60 min, 95% Buffer B. The MS global settings were as follows: ion source type, nanospray ionization; spray voltage, 2.2 kV (positive); and capillary temperature, 270°C. The MS parameters were as follows: detector type, orbitrap; orbitrap resolution, 60000 at 400 m/z; and mass precursor m/z range, 100.0–1500.0. The MS/MS parameters were as follows: product ion scan range, starting from m/z 100; activation type, CID; min. signal needed, 1500.0; isolation width, 3.00; normalized coll. energy; 40.0; default charge state, 6; activation Q, 0.250; activation time: 30.000; MS precursor m/z range, 50.0–1500.0; and data-dependent MS/MS, up to the 15 most intense peptide ions from the preview scan in the orbitrap.

Database searching

The original MS/MS data were imported into Proteome Discoverer software (version 2.2) and searched against the UniProt Equus caballus database, UniProt Equus asinus database, UniProt Bos taurus database and UniProt Sus scrofa database. The search parameters were set as follows: mass analyzer, Orbitrap mass spectrometer; MS order, MS2; polarity mode, positive; enzyme name, trypsin (full); minimum peptide length, 6; precursor mass tolerance, 10 ppm; fragment mass tolerance, 0.02 Da; static modification, carbamidomethyl/+57.021 Da (C); and dynamic modifications (peptide terminus), oxidation/+15.995 Da (M). The MS/MS peptide data were exported from Xcalibur software and plotted with Origin Pro 8.5.0.

Sample preparation for LC–MS/MS analysis

All gelatins analyzed by the LC–MS/MS method, including the single-gelatin samples, homemade adulterated DHG samples and commercial DHG products, were prepared using a simplified procedure based on a previous study [10]. First, 0.1 g of gelatin powder was added to 50 ml of a 1% NH₄HCO₃ solution and dissolved for 30 min by ultrasound treatment. Then, 1 ml of trypsin solution (1 mg/ml in 1% NH₄HCO₃, prepared immediately when needed) and 2 ml of a 1% NH₄HCO₃ solution were added to 1 ml of the gelatin solution. The mixture was incubated at 37°C for 12 h and the digest was filtered through a 0.22 μm microporous membrane.

LC–MS/MS analysis

LC–MS/MS analysis was performed using a Shimadzu Nexera X2 UHPLC system (Shimadzu, Kyoto, Japan) and an AB Sciex Q-Trap 4500 mass spectrometer equipped with a Turbo V™ source in positive mode and an electrospray ionization (ESI) source. Chromatographic separation was carried out using a Kinetex C18 100 Å column (2.6×100×4.6 mm, Phenomenex, Torrance, CA, USA) at a temperature of 40°C. The sample injection volume was 5 μL. The mobile phase consisted of Buffer A (0.1% FA in water) and Buffer B (ACN). Gradient elution was performed as follows: 0–3 min, 10–16% Buffer B; 3–7 min, 16–50% Buffer B; 7–8 min, 50–60% Buffer B; 8–11 min, 60–90% Buffer B; 11–12 min, 90–10% Buffer B; and 12–15 min, 10% Buffer B. The flow rate was set to 0.3 ml/min. The following MS parameters were used: ion spray voltage, 4500 V; curtain gas and collision gas, 30 psi and 6 psi, respectively; ion source gas 1 and 2, 45 psi and 50 psi, respectively; and vaporizer temperature, 500°C.

The mass spectrometer was operated in multiple reaction monitoring (MRM) mode, which allowed the simultaneous detection of several marker peptides in a single run. In our study, the ions at m/z 570.4, 386.2, 641.3 and 590.8 represented the peptides LA1, MA1, NA1 and ZA1, which are unique to DHG, HHG, CHG and PHG, respectively. These ions and their fragments formed different ion transition pairs. In the LC–MS/MS MRM experiments, each marker peptide was monitored by its corresponding ion transition pair. Before sample analysis, two or more transitions were examined for each peptide using the synthesized marker peptide standards. The ion transition with the most abundant intensity was selected to monitor the peptide. In our study, we chose the ion transition pairs 570.4→698.3, 386.2→402.2, 641.3→726.4 and 590.8→894.5 to monitor the marker peptides LA1, MA1, NA1 and ZA1, respectively.

Evaluation of specificity of the LC–MS/MS method

To test the specificity of the LC–MS/MS method, single-gelatin samples and a mixed standard solution containing the four marker peptides were first analyzed. After data acquisition, extracted ion chromatograms (XICs) using the ion transition pairs were generated with Analyst 1.6 software (AB Sciex). The XIC data were exported and plotted using Origin Pro 8.5.0 software. The XICs from the gelatin samples were verified by comparing the observed retention times with those determined from the standard solution. Theoretically, the four marker peptides could be detected only in their corresponding gelatin sample. Samples with an identified marker peptide indicated that the corresponding animal skin material was present.

Evaluation of linearity, repeatability and sensitivity of the LC–MS/MS method

To evaluate the applicability of the developed method, the linearity, repeatability and sensitivity were investigated.

For the linearity tests, 10 μl of each of the four synthesized peptide standard solutions at various concentrations ranging from 0.01 μg/ml to 0.1 μg/ml were injected for LC–MS/MS analysis. Standard curves were plotted using the peak area under the XIC and the amount of sample injected. The limits of detection and quantification, defined as the peak signal with signal-to-noise ratios of 3/1 and 10/1, respectively, were determined based on the data obtained from the marker peptide standard solution injections with the lowest concentration (0.01 μg/ml).

To test the repeatability, five replicate samples of each kind of gelatin were prepared and analyzed by LC–MS/MS.

Typically, gelatin adulteration occurs when less expensive HHG, CHG or PHG are mixed into more expensive DHG. Thus, the sensitivity of a method to detect adulteration is crucial to accurately trace the gelatin source. Therefore, to evaluate the sensitivity of the method, homemade adulterated samples were prepared by mixing different amounts (0.1%, 1%, 5% and 10%) of HHG, CHG and PHG into the DHG samples. The homemade adulterated DHG samples were then analyzed to evaluate the effectiveness of this method.

Moreover, there are many different kinds of commercial DHG products on the market. During DHG processing, different excipients, such as yellow wine, crystal sugar and soybean oil, may be added [8, 11], and gelatin identification may be influenced by the excipients. Therefore, 18 batches of commercial DHG products covering a broad range of prices and divisions were collected and analyzed to test the suitability of the LC–MS/MS method and investigate the product quality.

Results

Theoretical marker peptide prediction

To predict the theoretical marker peptides of the four animal species, we carried out a sequence alignment of their type I collagens. As shown in Fig 1A, peptide ⁴⁹⁷GPTGEPGKPGDK⁵⁰⁸, which is unique to donkeys, was selected because α2 (I) of the four animals has amino acid variations at positions 499, 501, 505 and 507. Likewise, as shown in Fig 1B, the amino acids at positions 423 and 424 were different among the four species. After digestion with trypsin, peptides ⁴²²GASGPAGVR⁴³⁰ and ⁴²²GPTGPAGVR⁴³⁰, which are unique to horses and pigs, respectively, were obtained. Another marker peptide from pig α2 (I), ⁴¹²AGVMGPPGSR⁴²¹, was obtained because of the amino acid variation at position 418. In total, 52 theoretical marker peptides were found, 18 of which were derived from the α1 chain of type I collagen and 34 of which belonged to the α2 chain of type I collagen (S2 Table). Donkeys and horses had two peptides each, while cattle and pigs had 25 and 23 marker peptides, respectively. The results provided a rationale for follow-up studies; therefore, we used LC–MS/MS to verify whether the theoretical marker peptides were present in the different gelatins.

Fig 1 — (A) Peptide unique to donkeys. (B) Peptide unique to horses. The amino acid variations are highlighted in red. Theoretical marker peptides after digestion with trypsin are indicated with black boxes.

Marker peptides detected in gelatins

To determine if the theoretical marker peptides were present in the four kinds of gelatins, we conducted LC–MS/MS experiments. Both the α1 and α2 chains of type I collagen were determined with high confidence from database searches to possibly contain marker peptide sequences (S3 Table). Peptides from various other kinds of proteins were also identified (S4 Table). As shown in Table 1, according to the predicted marker peptides and the identification results, we found a total of 12 marker peptides (one for DHG, one for HHG, four for CHG and six for PHG) derived from type I collagen. All marker peptides were detected only in their corresponding gelatins and not in any other gelatin. Four marker peptides (ZA1~ZA4) were detected in the PHG for the first time. Peptides LA1 (Fig 2A) and MA1 (Fig 2B) were the only marker peptides for DHG and HHG, respectively. NA1 (Fig 2C) and ZA1 (Fig 2D) showed the highest abundance in CHG and PHG, respectively. Therefore, these four peptides were selected and synthesized as standards to further develop an LC–MS/MS MRM method.

Table 1. Marker peptides detected in different gelatins.

Number	Marker peptides	Collagen	Species	Length	Mass (Da)	Charge	Gelatin
LA1	⁴⁹⁷GPTGEPGKPGDK⁵⁰⁸	α2(I)	Donkeys	12	1139.5800	2	DHG
MA1	⁴²²GASGPAGVR⁴³⁰	α2(I)	Horses	9	770.4035	2	HHG
NA1	⁷⁸¹GEAGPSGPAGPTGAR⁷⁹⁵	α1(I)	Cattle	15	1280.6109	2	CHG
NA2	¹⁰⁶⁶GETGPAGPAGPIGPVGAR¹⁰⁸³	α1(I)	Cattle	18	1559.8056	2; 3	CHG
NA3	⁸²⁹SGETGASGPPGFVGEK⁸⁴⁴	α2(I)	Cattle	16	1475.6892	2	CHG
NA4	¹⁰⁶⁶IGQPGAVGPAGIR¹⁰⁷⁸	α2(I)	Cattle	13	1191.6724	2	CHG
ZA1	⁹⁷⁶TGQPGAVGPAGIR⁹⁸⁸	α2(I)	Pigs	13	1179.6360	2; 3	PHG
ZA2	³¹³GRPGPPGPAGAR³²⁴	α1(I)	Pigs	12	1088.5839	2; 3	PHG
ZA3	⁶²⁴QGPSGPSGER⁶³³	α1(I)	Pigs	10	970.4468	2	PHG
ZA4	⁴²²GPTGPAGVR⁴³⁰	α2(I)	Pigs	9	810.4348	2	PHG
ZA5	¹⁰⁶⁹GETGPAGPAGPVGPVGAR¹⁰⁸⁶	α1(I)	Pigs	18	1549.7900	2; 3	PHG
ZA6	⁷³⁹TGETGASGPPGFAGEK⁷⁵⁴	α2(I)	Pigs	16	1461.6736	2	PHG

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The sequence number corresponds to the actual position of the collagen sequence from the UniProt database.

α1(I) and α2(I) indicate the α1 and α2 polypeptide chains of type I collagen.

Fig 2 — Peptides (A) ⁴⁹⁷GPTGEPGKPGDK⁵⁰⁸, (B) ⁴²²GASGPAGVR⁴³⁰, (C) ⁷⁸¹GEAGPSGPAGPTGAR⁷⁹⁵ and (D) ⁹⁷⁶TGQPGAVGPAGIR⁹⁸⁸ were detected in donkey-hide, horse-hide, cattle-hide and pig-hide gelatins, respectively. The b and y ions shown in red and blue represent the prefix (N-terminal b-ion) and the suffix (C-terminal y-ion) fragments of the given peptide, respectively. X axis and Y axis represent the m/z and the intensity of the ion fragments, respectively.

Specificity of the LC–MS/MS method

To investigate the specificity of the method, four kinds of gelatins were first tested. The results showed that the four marker peptides eluted at 1.14 min, 1.24 min, 1.44 min and 3.19 min (Fig 3). Each marker peptide was detected in only the corresponding gelatin. Therefore, the identification of each kind of gelatin could be undoubtedly confirmed by the presence of the corresponding marker peptide and the absence of the other marker peptides. These results demonstrated that this method had good specificity.

Fig 3 — **(A)** Donkey-hide gelatin, **(B)** horse-hide gelatin, **(C)** cattle-hide gelatin, and (D) pig-hide gelatin. LA1, MA1, NA1 and ZA1 are the four marker peptides. All marker peptides were detected only in the corresponding gelatin.

Linearity of the synthetic marker peptides

Mixed standards of the four synthesized marker peptides at various concentrations were analyzed to test the linearity of the LC–MS/MS MRM method. The results showed that all R² values were greater than 0.99 (S1 Fig), indicating a good correlation between the peak area and amount of each marker peptide injected. In addition, the limit of detection–limit of quantification of LA1, MA1, NA1 and ZA1 were 7.14 pg– 23.56 pg, 13.62 pg– 44.95 pg, 2.46 pg– 8.12 pg and 1.85 pg– 6.11 pg, respectively.

Repeatability of the identification of the four gelatins

To confirm whether the LC–MS/MS MRM method provided reproducible detection of the marker peptides, five independent replicate experiments for each gelatin were performed. The five replicates showed small differences in retention time and peak intensity (S2 Fig), indicating that the repeatability of this method was satisfactory.

Sensitivity of the LC–MS/MS method

Homemade mixed gelatin samples were analyzed to test the ability of the method to identify adulterated DHGs. As shown in S3 Fig, when 0.1% of the three other gelatins were added, the DHG, CHG and PHG marker peptides were all easily observed. This result indicated that the addition of CHG and PHG could be detected at a level of 0.1%. HHG was accurately identified at a level of 0.5%. These results suggested that the LC–MS/MS MRM method developed in our study is sufficiently sensitive to detect animal skin materials in adulterated DHGs.

Identification of commercial DHG products

A broad range of commercial DHG products were tested to confirm the feasibility of the method for practical applications. From a total of 18 batches of products, nine were identified as authentic DHG, as only LA1 was detected (S4A Fig). However, MA1 was found in eight batches of the samples (S4B and S4D Fig). Thus, there is a strong possibility that these samples were adulterated with horse skin materials. In addition, NA1 was detected in two of the products (S4C and S4D Fig), which were suspected to be adulterated with cattle skin materials. Interestingly, ZA1 was not found in any commercial DHG products collected in our study.

Discussion

DHG is a widely used traditional Chinese medicine, but its identification has puzzled researchers for decades. In this study, we investigated whether there are marker peptides in different gelatins and whether these peptides could be used to identify gelatins. To identify the marker peptides, we performed bioinformatics analysis for their prediction followed by proteomic experiments for verification. We found 12 marker peptides in the four gelatins. Based on the detected marker peptides, we developed an LC–MS/MS method and then examined its applicability for both single and mixed gelatin samples. Our results demonstrated that the developed method had good specificity, repeatability and sensitivity.

By sequence alignment analysis, we predicted 52 theoretical marker peptides derived from the type I collagens of the four animals. A previous study [8] showed certain different theoretical marker peptides from ours. However, in contrast to this previous study, we used both the α1 (I) and α2 (I) chains of the four animals for the prediction, which may account for the different results. Our results also showed that most of the peptides were from CHG and PHG. DHG and HHG each had only two predicted peptides because donkeys are closely related to horses, so there are few amino acid variations among their collagen sequences.

After proteomic analysis verification, we found 12 marker peptides in the four kinds of gelatin. Some of the peptides were consistent with those from other relevant studies [8, 10, 17]. These findings should help us distinguish among different gelatins. In addition, four marker peptides from PHG that were detected for the first time in our study may be used as possible substitutes to identify pig materials in the future. However, 40 predicted peptides, which accounted for 77% of the total peptides, were not detected in our experiments. Previous studies [1] conducted by other researchers on the components in gelatins may explain this result. Proteins and peptides may suffer from denaturation due to the gelatin heating process. Thus, the peptides that were not detected may have been destroyed during gelatin formation.

To develop an LC–MS/MS method with good specificity, selecting marker peptides is important. The highly similar peptides produced by each of the four gelatins may disrupt the identification of the other peptides [10]. In the Chinese Pharmacopoeia 2015 edition, the peptide GPPGAAGPPGPR was used to identify DHG [19]. However, according to a previous study, the peptide GPPGAAGPPGPR is derived from type I collagen and is common to both donkeys and horses, and it can therefore be detected in both DHG and HHG [9]. Thus, in our study, we selected different marker peptides for each gelatin to establish an LC–MS/MS method. Next, we tested the specificity of the method. Our results showed that the four selected marker peptides could be clearly identified without any interference. Moreover, we examined the linearity, repeatability and sensitivity of the method, and the results demonstrated that it has good applicability for the identification of gelatins.

We collected 18 batches of commercial DHG products and used the LC–MS/MS method to identify them. Surprisingly, almost half of these samples were suspected to be adulterated with horse skin materials, revealing the current state of DHG quality control. Donkeys are more closely related to horses than to cattle or pigs. The collagen sequences between donkeys and horses are therefore very similar, making it extremely difficult to distinguish between them [1, 22]. This may explain why DHGs were particularly prone to adulteration with HHG. Notably, the LC–MS/MS method developed in our study may be useful for addressing this issue.

In conclusion, we successfully predicted and verified marker peptides in gelatins. In addition, we developed an LC–MS/MS method with good specificity, repeatability and sensitivity. These findings might help us to identify these four kinds of gelatin and their adulterants. Despite our promising results, questions remain. In recent years, DHG products made from donkey meat or bones have begun to appear on the market. These DHG products are of poor quality because of the insufficient amount of donkey skin. In the Chinese Pharmacopoeia 2020 edition, poor-quality DHG products are identified by quantitative determination of the marker peptides [23], and an insufficient amount of donkey skin may lead to a low level of marker peptides. However, marker peptides can be synthesized and added to DHG products to satisfy the detection criterion. Therefore, DHG products with an insufficient amount of donkey skin cannot be completely avoided by quantitatively measuring the amounts of marker peptides. Further studies that address these problems will be needed.

Conclusions

The purpose of this study was to identify four gelatins by LC–MS/MS using marker peptides. Herein, we successfully predicted theoretical marker peptides of four gelatins, and a total of 12 marker peptides for the four gelatins were verified by proteomic experiments. Furthermore, we developed an LC–MS/MS method for peptide marker detection, which was applicable and demonstrated good specificity and sensitivity for the identification of gelatins. These results can help us control the gelatin quality. In addition, the strategy of predicting theoretical marker peptides followed by their verification via proteomic experiments can be adapted to other medicines containing protein components, especially known proteins.

Supporting information

S1 Fig

Linearity of the LC–MS/MS MRM method for the analysis of the four marker peptides: (A) 570.4→698.3 for LA1, (B) 386.2→402.2 for MA1, (C) 641.3→726.4 for NA1, and (D) 590.8→894.5 for ZA1.

(TIF)

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S2 Fig. Repeatability evaluation of the established LC–MS/MS MRM method.

(A) Donkey-hide gelatin, (B) horse-hide gelatin, (C) cattle-hide gelatin, and (D) pig-hide gelatin. Five replicates for each gelatin sample were measured independently, and the results were reproducible.

(TIF)

Click here for additional data file.^{(1.9MB, tif)}

S3 Fig. Identification of donkey-hide gelatins adulterated with different amounts of the other three gelatins.

Donkey-hide gelatin samples were mixed with the following amounts of horse-hide gelatin, cattle-hide gelatin and pig-hide gelatin: (A) 0.1%, (B) 0.5%, (C) 5.0%, and (D) 10.0%. The addition of two of the three other gelatins could be detected at a level of 0.1% of the total weight.

(TIF)

Click here for additional data file.^{(1.4MB, tif)}

S4 Fig. Detection of commercial donkey-hide gelatin products.

(A) Identified as an authentic donkey-hide gelatin product. Samples (B), (C) and (D) were identified as counterfeit commercial donkey-hide gelatin products adulterated with horse-hide gelatin and cattle-hide gelatin.

(TIF)

Click here for additional data file.^{(1.4MB, tif)}

S1 Table. Information on the samples used in our study.

(XLSX)

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S2 Table. All predicted theoretical marker peptides of the four species.

(XLSX)

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S3 Table. Identification of proteins from the four kinds of gelatins.

(XLSX)

Click here for additional data file.^{(50.2KB, xlsx)}

S4 Table. Identification of peptides from the four kinds of gelatins.

(XLSX)

Click here for additional data file.^{(143.4KB, xlsx)}

Data Availability

All relevant data are within the article and its Supporting Information files.

Funding Statement

This work was supported by Guangdong Natural Science Foundation (No. 2020A151501577, Ying Zhang), the Open Fund of Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research (No. 2016B030301004, Hui Cao), and Cao Hui’s Expert Workstation in Yunnan Province (202005AF150011, Hui Cao). The funder of Ying Zhang and Hui Cao had contributed to the project administration, supervision, validation, draft writing and editing throughout the period of this research.

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PLoS One. doi: 10.1371/journal.pone.0273021.r001

Decision Letter 0

Chun-Hua Wang

28 Jun 2022

PONE-D-22-11303Species-specific identification of donkey-hide gelatin and its adulterants using marker peptidesPLOS ONE

Dear Dr. Zhang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewer #3: I Don't Know

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5. Review Comments to the Author

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Reviewer #1: 1.Only Standard medicine samples DHG, CHG and PHG were purchased from from the National Institutes for Food and Drug Control (NIFDC; Beijing, China), but HHG was not purchased. Please explain the reasons.

2.Can the doping amount in donkey-hide gelatin be identified according to the existing marker peptides content determination results?

3.What is the purity of the synthetic marker peptide standard?

4.Is there really enough horse hide for adulteration in donkey-hide gelatin production?Is it of practical significance to identify the adulterated horse hide in donkey-hide gelatin?

Reviewer #2: Donkey-hide gelatin is an important traditional Chinese medicine made from donkey skin. Identifying the animal materials (donkeys, horses, cattle and pigs) in donkey-hide gelatin is challenging. The goal of this study by Zhang J. et al. is to utilize liquid chromatography–tandem mass spectrometry method to identify species-specific marker peptides, and these marker peptides can be used to discriminate the ingredient from (donkeys, horses, cattle and pigs). This reviewer realizes that the results were so interesting because the marker peptides and LC–MS/MS method showed a good specificity, sensitivity and reproducibility. This method is valuable in controlling the quality of donkey-hide gelatin. My comments to co-authors are:

1. Figure 1 and the words that describe Figure 1 from theoretical marker peptide prediction section in Materials and Methods should be in Result section, and the Figure 1a should be Figure 1A.

2. In the “Evaluation of applicability of the LC–MS/MS method” section and the corresponding result section, the authors should organize the word and data to highlight the specificity, repeatability and sensitivity of the method.

3. In the legend of Figure 2, the authors should describe the Figure in details, such as, what are the meanings of b and y? different colors? X axis and Y axis.

4. In line 303, R2 should be R2.

5. In line 366 and 367, “Unlike our study, a previous study showed certain different theoretical marker peptides.” The authors should provide references for the study.

6. In line 379 and 380, “Previous studies conducted by other researchers on the components in gelatins may explain this result.” The authors should provide references for these studies.

7. In the manuscript, “in this study” should be changed as “in our study”.

8. In the manuscript, S1 Figure should be Figure S1 and S1 Table should be Table S1.

Reviewer #3: This is a well-written paper containing interesting results which merit publication. The paper presents an LC-MS/MS method for peptide marker detection, which was applicable and demonstrated good specificity and sensitivity for the identification of gelatins. It is a topic of interest to the researchers in the related areas but the manuscript needs a bit improvement (minor revision) before acceptance for publication. My detailed comments are as follows:

1. Please note that the English letters marked on the chart in the article are consistent with those marked on the chart itself, which can be in lowercase or uppercase.

2. Fig4 can also be attached to the end of the article like S3 figure.

3. The consistency between the information displayed by S3 figure and the content described in the discussion part of the article needs to be improved. （MAI exists in samples（b）、（d），instead（b）、（c）.

4. If the marker peptide was added into HHG, the proposed LC-MS/MS method can not identify the HHG. Please try to discuss this point deeply and try to draw a possible method to assistant to identify the it.

Reviewer #4: 1． There have been some research papers on identification of donkey-hide glue and its adulterants, so this paper should show the novelty of the work in the Introduction section, compared with the literature that had been reported. I do not think it is correct that the authors stated this manuscript as “one of the first investigations to focus specifically on the identification of gelatins using marker peptides”. Please add the literatures of related studies in the introduction part.

2． Dithiothreitol often was used to destroy the disulfide bond, does the collagen contain disulfide bond? Please make sure the necessity of Dithiothreitol must be used to destroy the disulfide bond?

3． From the manuscripts, 12 marker peptides for the four gelatins were verified only by proteomic experiments, it advised that the 12 marker peptides should be validated by different sources samples.

4． It is recommended that the manuscripts be professionally edited for English language before submitting your revised manuscript version.

**********

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Reviewer #1: Yes: Zou Xiaoxing

Reviewer #2: No

Reviewer #3: Yes: Yuming Dong

Reviewer #4: Yes: WEI Feng

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PLoS One. 2022 Aug 12;17(8):e0273021. doi: 10.1371/journal.pone.0273021.r002

Author response to Decision Letter 0

11 Jul 2022

Responses to comments about Journal Requirements

Comment #1: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response #1: We have carefully checked the paper to ensure that the manuscript meets PLOS ONE's style requirements.

Comment #2: Thank you for stating the following financial disclosure…Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

Response #2: This work was supported by Guangdong Natural Science Foundation (No. 2020A151501577, Ying Zhang), the Open Fund of Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research (No. 2016B030301004, Hui Cao), and Cao Hui’s Expert Workstation in Yunnan Province (202005AF150011, Hui Cao). The funder of Ying Zhang and Hui Cao had contributed to the project administration, supervision, validation, draft writing and editing throughout the period of this research. In order to make it more clearly about all author's contributions, we add the part of “Author Contributions” in the manuscript (Page 22, Line 464-475).

Comment #3: We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing…we ask that you remove the phrase that refers to these data.

Response #3: We are sorry for neglecting the requirements of data sharing. For the first section of “Data not shown”, we have removed the related data (Page 16, Line 342-344), because it is not a core part of the research. For the second section of “Data not shown”, we have added a reference to support our points (Page 20, Line 417-418).

Comment #4: Please review your reference list to ensure that it is complete and correct….

Response #4: We have reviewed the references list and made some changes according to the comments of reviewers (Page 23-27, Line 477-571).

Responds to comments from the reviewers

Reviewer #1:

Comment #1: Only Standard medicine samples DHG, CHG and PHG were purchased from the National Institutes for Food and Drug Control (NIFDC; Beijing, China), but HHG was not purchased. Please explain the reasons.

Response #1: The HHG made by horse skins cannot be used as food stuffs or medicines, although horse skins were always adulterated into donkey skins to make DHG. There is no reference substance of HHG provided by NIFDC or sold on the market. So, we used the house-made HHG samples to perform the proteomics study and build the LC-MS/MS method.

Comment #2: Can the doping amount in donkey-hide gelatin be identified according to the existing marker peptides content determination results?

Response #2: This is a really interesting question and we have also taken this possibility into account. But unfortunately, the doping amount in donkey-hide gelatin cannot be identified based on the results. We will focus on this question and try to solve this problem.

Comment #3: What is the purity of the synthetic marker peptide standard?

Response #3: The purity of the synthetic marker peptide standard is more than 95%. We have added it in the manuscript (Page 5, Line 106).

Comment #4: Is there really enough horse hide for adulteration in donkey-hide gelatin production? Is it of practical significance to identify the adulterated horse hide in donkey-hide gelatin?

Response #4: Since the donkey-hide gelatin was recorded in Chinese Pharmacopoeia (1977 edition), the great efforts have been made to push the identification of donkey-hide gelatin and other gelatins, including horse-hide gelatin. Based on the identification results of the commercial DHG products, almost half of all samples were adulterated with horse skin materials, which indicated that the identification of the adulterated horse hide in donkey-hide gelatin is of great practical significance.

Reviewer #2:

Comment #1: Figure 1 and the words that describe Figure 1 from theoretical marker peptide prediction section in Materials and Methods should be in Result section, and the Figure 1a should be Figure 1A.

Response #1: Thanks for your good comments. We have moved the Figure 1 and the words that describe Figure 1to the Results section (Page 13, Line 266-274). We have changed the Figure 1a to Figure 1A (Page 13, Line 266-284) and corrected other same mistakes.

Comment #2: In the “Evaluation of applicability of the LC–MS/MS method” section and the corresponding result section, the authors should organize the word and data to highlight the specificity, repeatability and sensitivity of the method.

Response #2: According to the comments of reviewers, we have reorganized the words and data to make it more readable (Page 11-13, Line 221-251). And we also changed the subtitle of the “Evaluation of applicability of the LC–MS/MS method” section and the corresponding results section to highlight the specificity, repeatability and sensitivity of the method (Page 11, Line 221-222; Page 11, Line 232-233; Page 15, Line 313-314; Page 17, Line 351-352).

Comment #3: In the legend of Figure 2, the authors should describe the Figure in details, such as, what are the meanings of b and y? different colors? X axis and Y axis.

Response #3: Thanks for your good comments. The MS/MS spectrum contains a complex mixture of peptide fragments. The b and y ions shown in red and blue represent the prefix (N-terminal b-ion) and the suffix (C-terminal y-ion) fragments of the given peptide, respectively. The X axis and Y axis represent the m/z and the intensity of the ion fragments, respectively. We have added this description to the legend of Figure 2 (Page 15, Line 309-312).

Comment #4: In line 303, R2 should be R2.

Response #4: We are sorry about it and have corrected this mistake (Page 16, Line 329).

Comment #5: In line 366 and 367, “Unlike our study, a previous study showed certain different theoretical marker peptides.” The authors should provide references for the study.

Response #5: We have added the corresponding references for the study (Page 19, Line 393).

Comment #6: In line 379 and 380, “Previous studies conducted by other researchers on the components in gelatins may explain this result.” The authors should provide references for these studies.

Response #6: We have added the corresponding references for the study (Page 19, Line 406).

Comment #7: In the manuscript, “in this study” should be changed as “in our study”.

Response #7: We have changed “in this study” to “in our study” in the manuscript.

Comment #8: In the manuscript, S1 Figure should be Figure S1 and S1 Table should be Table S1.

Response #8: We have changed the file naming according the PLOS ONE style templates to ensure that our manuscript meets PLOS ONE's style requirements.

Reviewer #3:

Comment #1: Please note that the English letters marked on the chart in the article are consistent with those marked on the chart itself, which can be in lowercase or uppercase.

Response #1: We are sorry about this and we have modified the letters to ensure that the letters marked on the chart in the article are consistent with those marked on the chart itself.

Comment #2: Fig4 can also be attached to the end of the article like S3 figure.

Response #2: Thanks for your good comments. We have changed the Figure 4 to Figure S3 and renumbered other figures (Page 17, Line 361). It makes the manuscript become more readable.

Comment #3: The consistency between the information displayed by S3 figure and the content described in the discussion part of the article needs to be improved. (MAI exists in samples (b), (d), instead (b), (c).

Response #3: We are so sorry about this mistake. And we have corrected this mistake (Page 18, Line 369-373).

Comment #4: If the marker peptide was added into HHG, the proposed LC-MS/MS method cannot identify the HHG. Please try to discuss this point deeply and try to draw a possible method to assistant to identify it.

Response #4: This is a really interesting question. Thank you so much for your good comments. In our study, each marker peptide for one gelatin was selected to build the LC-MS/MS method. Theoretically, the four marker peptides could only be detected in their corresponding gelatin samples. Samples with an identified marker peptide was well related to the corresponding animal skin material. That is to say, only marker peptide MA1 should be detected in HHG samples, and samples detected with multiple marker peptides were considered as adulterated samples. If marker peptides of LA1, NA1 and ZA1 are added into HHG, these marker peptides including MA1 will be detected and the samples will be considered as adulterated samples. Based on the identification results, we could not determine whether the marker peptides of LA1, NA1 and ZA1 were derived from the corresponding samples or just artificially added. To solve this problem, we have considered whether proteins which are difficult to synthesize could be used to identify different gelatins. The Parallel Reaction Monitoring (PRM) which is commonly used to quantify proteins may be used to analysis the collagens or other proteins in different gelatins. If we establish a PRM method which can specifically identify the HHG based on the protein components, the problem may be solved brilliantly.

Reviewer #4:

Comment #1: There have been some research papers on identification of donkey-hide glue and its adulterants, so this paper should show the novelty of the work in the Introduction section, compared with the literature that had been reported. I do not think it is correct that the authors stated this manuscript as “one of the first investigations to focus specifically on the identification of gelatins using marker peptides”. Please add the literatures of related studies in the introduction part.

Response #1: Thanks for your good comments. Previous studies have focus on the identification of donkey-hide gelatin using the marker peptides method. We have deleted the statement of “one of the first investigation…” and added the related studies in the introduction section (Page 4, Line 68 and 87). And in our study, we used both the α1 (I) and α2 (I) chains to predict the marker peptides of four animals. Then we verified the marker peptides and applied them to build an MRM method. Based on the methods, we also collected and tested kinds of commercial donkey-hide gelatin products. It is a comprehensive study of the identification of donkey-hide gelatin, and we believed that our study can help improve the quality control of donkey-hide gelatin.

Comment #2: Dithiothreitol often was used to destroy the disulfide bond, does the collagen contain disulfide bond? Please make sure the necessity of Dithiothreitol must be used to destroy the disulfide bond?

Response #2: Type I collagens contain two α1 chains [α1 (I)] and one α2 chain [α2 (I)], and there are disulfide bonds between chains of collagens. According to previous studies, dithiothreitol was always used during the sample’s preparation for the proteomics analysis. In our study, not only the collagens but also other kinds of proteins from four gelatins were used to the proteomics study. So, it is necessary to use dithiothreitol for samples’ preparation in our study.

Comment #3: From the manuscripts, 12 marker peptides for the four gelatins were verified only by proteomic experiments, it advised that the 12 marker peptides should be validated by different sources samples.

Response #3: Thanks for your good comments. Donkey-hide gelatin are most commonly adulterated with materials from horse, pig and cattle. However, it is also possible that donkey-hide gelatin will be adulterated with tissues from sheep, deer or other animals. According to the Introduction section in the manuscript, we find that previous studies had tried to identify the donkey-hide gelatin and other gelatin like deer-horn glue, etc. In fact, it is a really good idea to validate the 12 marker peptides using other kinds of samples in our further study. Thanks again for your good advice.

Comment #4: It is recommended that the manuscripts be professionally edited for English language before submitting your revised manuscript version.

Response #4: We are very sorry about this. The revised manuscript version has been edited for proper English language, grammar, punctuation, spelling, and overall style by one or more of the highly qualified native English-speaking editors in American Journal Experts (AJE) corporation.

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PLoS One. doi: 10.1371/journal.pone.0273021.r003

Decision Letter 1

Chun-Hua Wang

18 Jul 2022

PONE-D-22-11303R1Species-specific identification of donkey-hide gelatin and its adulterants using marker peptidesPLOS ONE

Dear Dr. Zhang,

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Reviewer #2: The authors have addressed my comments and concerns. I recommend that editors accept the submission.

Reviewer #3: The authors have answered the questions well.However, there are still some other questions to be considered.

1. If this LC-MS/MS of marker peptide is not the first investigation on DHG and its adulterants(The study presented in this thesis is a comprehensive one of the first investigations to focus specifically on the identification of gelatins using marker peptides.),what is the innovation of this LC-MS/MS?Please compare the proposed method and the published LC-MS/MS method of marker peptide on the identification of DHG.

2. Please add the method of identification of DHG of Chinsed Pharmaceopoeia 2020 version and discuss the limitations of the CHP2020 method briefly and show the proposed LC-MS/MS can be helpful to improve the CHP 2020 method in Introducation part but not in the discussion part.

3. Line113-115, … Chinese Pharmacopoeia 114 and the quality of every gelatin sample complied with Chinese Pharmacopeia 115 requirements .Please add the version of the Chinese Pharmacopoeia .for example,2020 version.

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Reviewer #3: Yes: OK

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PLoS One. 2022 Aug 12;17(8):e0273021. doi: 10.1371/journal.pone.0273021.r004

Author response to Decision Letter 1

20 Jul 2022

Responses to comments about Journal Requirements

Comment #1: Please review your reference list to ensure that it is complete and correct…and full reference for the retraction notice.

Response #1: We have carefully reviewed the references list to ensure that the references meet PLOS ONE's requirements.

Responds to comments from the reviewers

Reviewer #3:

Comment #1: If this LC-MS/MS of marker peptide is not the first investigation on DHG and its adulterants (The study presented in this thesis is a comprehensive one of the first investigations to focus specifically on the identification of gelatins using marker peptides.), what is the innovation of this LC-MS/MS? Please compare the proposed method and the published LC-MS/MS method of marker peptide on the identification of DHG.

Response #1: Thanks for your good comments. As you mentioned before, previous studies have focus on the identification of donkey-hide gelatin based on the marker peptides. So, we have deleted the statement of “one of the first investigation…”. LC-MS/MS based on proteomics experiments are commonly used on the discovery of marker peptides, meanwhile the reference protein database used to predict the theoretical marker peptides and specified search is essential for identifying peptides. After the discovery of marker peptides, it is also a challenge to build a fast, sensitive and accurate method based on the marker peptides. In our study, to obtain enough candidate marker peptides, we used both the α1 (I) and α2 (I) chains to predict the theoretical marker peptides. Although we focused on the marker peptides derived from type I collagen, we used all the reference proteins of four animals from UniProt as searched database. Our results might provide a reference to discover other marker peptides which derived from non-collagen proteins such as keratins. Using the marker peptides, we build an MRM method which allows a fast identification of four kinds of gelatins in 15 minutes with good specialty and sensitivity. We also collected and tested a variety kinds of commercial donkey-hide gelatin products which covers large brands, and the results might help us understand the real situation of the donkey-hide gelatin on the market.

Comment #2: Please add the method of identification of DHG of Chinsed Pharmacopoeia 2020 version and discuss the limitations of the CHP2020 method briefly and show the proposed LC-MS/MS can be helpful to improve the CHP 2020 method in Introducation part but not in the discussion part.

Response #2: This is an interesting question. In Chinese Pharmacopoeia 2020 edition, quantitative determination of A1 and A2 peptides derived from donkey skins are used to assess the quality of donkey-hide gelatin. The total amount of A1 and A2 should reach at least 0.15%. The donkey-hide gelatin with a low level of A1 and A2 may be considered as products with an insufficient amount of donkey skin. However, marker peptides of A1 and A2 can be synthesized and added to donkey-hide gelatin products to satisfy the detection criterion. Therefore, donkey-hide gelatin products with an insufficient amount of donkey skin cannot be completely avoided only by quantitative analysis of the amounts of marker peptides. Unfortunately, not only our current research but also other studies cannot provide a good solution to avoid the artificial addition of the marker peptides. We've been paying attention and trying to solve this problem in the future. Alternatively, it may be more appropriate to discuss this issue in the “Discussion” section. We have considered whether proteins which are difficult to synthesize could be used to identify different gelatins. The Parallel Reaction Monitoring (PRM) which is commonly used to quantify proteins may be used to analysis the collagens or other proteins in different gelatins. If we establish a PRM method which can specifically identify the donkey-hide gelatin based on the quantitative determination of protein components, the problem may be solved satisfactorily at last.

Comment #3: Line113-115, … Chinese Pharmacopoeia 114 and the quality of every gelatin sample complied with Chinese Pharmacopeia 115 requirements. Please add the version of the Chinese Pharmacopoeia. for example,2020 version.

Response #3: We have added the version of Chinese Pharmacopoeia in the manuscript (Page 6, Line 112-113).

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PLoS One. doi: 10.1371/journal.pone.0273021.r005

Decision Letter 2

Chun-Hua Wang

2 Aug 2022

Species-specific identification of donkey-hide gelatin and its adulterants using marker peptides

PONE-D-22-11303R2

Dear Dr. Zhang,

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PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0273021.r006

Acceptance letter

Chun-Hua Wang

4 Aug 2022

PONE-D-22-11303R2

Species-specific identification of donkey-hide gelatin and its adulterants using marker peptides

Dear Dr. Zhang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig

Linearity of the LC–MS/MS MRM method for the analysis of the four marker peptides: (A) 570.4→698.3 for LA1, (B) 386.2→402.2 for MA1, (C) 641.3→726.4 for NA1, and (D) 590.8→894.5 for ZA1.

(TIF)

Click here for additional data file.^{(476.9KB, tif)}

S2 Fig. Repeatability evaluation of the established LC–MS/MS MRM method.

(TIF)

Click here for additional data file.^{(1.9MB, tif)}

S3 Fig. Identification of donkey-hide gelatins adulterated with different amounts of the other three gelatins.

(TIF)

Click here for additional data file.^{(1.4MB, tif)}

S4 Fig. Detection of commercial donkey-hide gelatin products.

(TIF)

Click here for additional data file.^{(1.4MB, tif)}

S1 Table. Information on the samples used in our study.

(XLSX)

Click here for additional data file.^{(11.5KB, xlsx)}

S2 Table. All predicted theoretical marker peptides of the four species.

(XLSX)

Click here for additional data file.^{(12.5KB, xlsx)}

S3 Table. Identification of proteins from the four kinds of gelatins.

(XLSX)

Click here for additional data file.^{(50.2KB, xlsx)}

S4 Table. Identification of peptides from the four kinds of gelatins.

(XLSX)

Click here for additional data file.^{(143.4KB, xlsx)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(31.1KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(24.5KB, docx)}

Data Availability Statement

All relevant data are within the article and its Supporting Information files.

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PERMALINK

Species-specific identification of donkey-hide gelatin and its adulterants using marker peptides

Jinju Zhang

Menghua Wu

Zhiguo Ma

Ying Zhang

Hui Cao

Roles

Abstract

Introduction

Materials and methods

Samples and reagents

Theoretical marker peptide prediction

Sample preparation for proteomic analysis

Proteomic analysis

Database searching

Sample preparation for LC–MS/MS analysis

LC–MS/MS analysis

Evaluation of specificity of the LC–MS/MS method

Evaluation of linearity, repeatability and sensitivity of the LC–MS/MS method

Results

Theoretical marker peptide prediction

Fig 1. Partial sequence alignments of the type I collagen α2 chains from four different animal species.

Marker peptides detected in gelatins

Table 1. Marker peptides detected in different gelatins.

Fig 2. MS/MS spectra of marker peptides detected in the four digested gelatins.

Specificity of the LC–MS/MS method

Fig 3. Detection of marker peptides in the four kinds of gelatin by LC–MS/MS MRM.

Linearity of the synthetic marker peptides

Repeatability of the identification of the four gelatins

Sensitivity of the LC–MS/MS method

Identification of commercial DHG products

Discussion

Conclusions

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Chun-Hua Wang

Roles

Author response to Decision Letter 0

Decision Letter 1

Chun-Hua Wang

Roles

Author response to Decision Letter 1

Decision Letter 2

Chun-Hua Wang

Roles

Acceptance letter

Chun-Hua Wang

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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