Method for distinguishing and judging producing areas of muskrat muskrat based on GC-MS (Gas Chromatography-Mass Spectrometer)

Abstract

According to the method, chemical components in muskrat musk samples from different producing areas and different batches are analyzed through GC-MS, and the muskrat musk in Chongqing, Hebei, Jiangsu and Heilongjiang is distinguished and judged by establishing a fingerprint spectrum and an orthogonal-partial least square discriminant analysis model. Extracting chemical components of the muskrat muskrat and carrying out GC-MS analysis; establishing a fingerprint spectrum of the muskrat muskrat by adopting a traditional Chinese medicine chromatographic fingerprint spectrum similarity evaluation system, and performing similarity evaluation; sIMCA software is used for establishing an orthogonal-partial least square discriminant analysis model for the data, chromatographic peak data is substituted into the established model for distinguishing and judging the producing areas, the model is not over-fitted, and relevant parameters can prove the predictive capacity of the model. The method is accurate, simple and convenient, and can provide reference for the production place determination and quality evaluation of the muskrat muskrat.

Description

Technical Field

[0001] The invention relates to a method for analyzing components of muskrat, and in particular to a method for distinguishing and determining the production areas of muskrat based on GC-MS. Background Art

[0002] Muskrat musk is a milky white secretion from the glandular cysts of adult male muskrats of the hamster family. It has the effects of opening the orifices and channels, dispersing blood stasis and relieving pain. Studies have reported that both muskrat musk and musk contain compounds such as cycloalkanones, fatty acids, and steroids, and pharmacological experiments have shown that its anti-inflammatory and analgesic effects are not significantly different from those of musk. Since the production of natural musk is not enough to meet market demand, it has become one of the potential substitutes for musk in recent years. Substitutes for rare and endangered animal drugs include biological species with close genetic relationships, similar pharmacology and efficacy, artificial domestication and breeding, and artificial synthesis. Animals with similar pharmacological effects to musk include civet musk secreted by civet cats, ambergris of sperm whales, and muskrat musk. However, there is no successful case of artificial breeding of civet cats. Ambergris is more precious and rare than musk. Therefore, muskrat musk from farmed muskrats is the easiest and most convenient to obtain. Muskrat was originally distributed in ponds, swamps, lakes, rivers and other places in North America. As the most captured wild fur animal in North America in the 20th century, it is widely distributed in various countries in Asia and Europe due to biological invasion. Muskrat breeding has the advantages of low investment cost, low feeding cost and good economic benefits. my country has started to breed muskrat since the 1990s, but it is still mainly small-scale breeding. Different muskrat farms have different quality due to climate, feed composition, feeding management, etc., so its quality evaluation system needs to be further improved.

[0003] GC-MS has both the separation capability of GC and the identification function of MS, and has unique advantages in the qualitative and quantitative analysis of volatile components of traditional Chinese medicine. Traditional Chinese medicine fingerprint is an effective method for evaluating the quality of traditional Chinese medicine, identifying authenticity, distinguishing species, and quality control research. Orthogonal-partial least squares discriminant analysis is a supervised chemical pattern analysis that can better analyze the causes of sample differences and difference markers, thereby obtaining information on inter-group differences and predicting the grouping of samples.

[0004] Muskrat from different origins is distinguished and determined by GC-MS combined with fingerprint and orthogonal-partial least squares method, and differential metabolites in muskrat from different origins are found for quality evaluation, in order to provide a basis for the further development and use of muskrat. At present, there is no literature study on the use of GC-MS combined with chemometrics to analyze various chemical components in muskrat from different origins. Therefore, it is of great significance to establish a method for determining the origin of muskrat based on GC-MS. The present invention measures the chemical components of muskrat from different origins, establishes a fingerprint for similarity evaluation, and combines orthogonal-partial least squares discriminant analysis to determine the differential metabolites of muskrat from different origins, which is more clear and reasonable as an indicator for quality evaluation. The method is accurate and simple, and can provide a reference for the quality evaluation of muskrat. Summary of the invention

[0005] The technical problem solved by the present invention is to provide a method for distinguishing and determining the origin of muskrat based on GC-MS, so as to quickly find the metabolites causing the quality difference.

[0006] The method for distinguishing and determining the origin of muskrat based on GC-MS of the present invention is carried out according to the following steps:

[0007] (1) Preparation of sample solution: Accurately weigh 0.1 g of muskrat incense, add 1 mL of anhydrous ethanol, sonicate for 30 min, vortex, centrifuge, and filter through a 0.22 μm fat-soluble filter membrane to obtain the test solution. Dilute 5 times with anhydrous ethanol to obtain the sample solution.

[0008] (2) The GC-MS method was used for determination. The chromatographic and mass spectrometric conditions were as follows: the chromatographic column was a DB-17MS chromatographic column (0.25 mm × 30 m, 0.25 μm); the temperature was programmed, with an initial temperature of 120 °C and a ramp rate of 10 °C min -1 Raise to 160℃, hold for 5min, and adjust at 2℃·min -1 Raise to 190℃, maintain for 5min, and heat at 5℃·min -1 Rise to 280℃ and maintain for 25min. Injection volume 1μL, injection port temperature 250℃, split ratio 50:1. EI ion source; electron energy 70eV; scan interval 0.05s; ion source temperature 250℃; interface temperature 250℃; Q3 Scan full scan mode; mass scan range 50-600amu; solvent delay time 3.5min, acquisition time 72min.

[0009] (3) Using the analytical data obtained from GC-MS, the similarity of muskrat musk from different origins was evaluated using the Traditional Chinese Medicine Fingerprint Similarity Evaluation Software (2012 Edition), and origin 2022 was used to draw a three-dimensional fingerprint map. SIMCA14.1 software was used for orthogonal partial least squares discriminant analysis to screen differential metabolites.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] 1. The method of the present invention utilizes GC-MS to realize the identification of the chemical components of muskrat, collects GC-MS data of muskrat from different origins, more comprehensively characterizes the chemical components in muskrat from different origins, and is more accurately applied to the classification and determination of origins.

[0012] 2. The present invention is simple to operate and has high detection efficiency. It uses fingerprint spectrum and orthogonal-partial least squares discriminant analysis to quickly screen muskrat metabolites from different origins and determine the origin of muskrat. It can be widely used in the distinction and determination of the origin of traditional Chinese medicine. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 GC-MS total ion chromatogram of muskrat samples from Chongqing

[0014] Figure 2 GC-MS total ion chromatogram of muskrat samples from Jiangsu

[0015] Figure 3 GC-MS total ion chromatogram of muskrat samples from Hebei

[0016] Figure 4 GC-MS total ion chromatogram of muskrat samples from Heilongjiang

[0017] Figure 5 3D fingerprint of muskrat incense sample

[0018] Figure 6 OPLS-DA model score diagram of muskrat samples from different origins

[0019] Figure 7 VIP diagram of OPLS-DA model of muskrat samples from different origins

[0020] Figure 8 OPLS-DA model permutation test diagram of muskrat samples from different origins DETAILED DESCRIPTION

[0021] For a better understanding of the present invention, the present invention is further described in detail below in conjunction with specific examples. The following examples are only used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0022] Example 1 GC-MS determination of chemical components of muskrat musk from different origins

[0023] 1. Instruments and reagents:

[0024] Shimadzu TQ-8040 GC-MS (Shimadzu Corporation, Japan); 321LS electronic balance (Tianmei Instrument Laboratory Equipment (Shanghai) Co., Ltd.); Milli-Q water purifier (Millipore Corporation, USA); KQ2200B ultrasonic cleaner (Kunshan Ultrasonic Instrument Co., Ltd.);

[0025] 24 batches of muskrat samples from different origins were identified as muskrat secreted by the scent glands of rodents by researcher Jie Hang of Chongqing Institute of Medicinal Planting. Anhydrous ethanol was chromatographically pure (Knowles).

[0026] 2. GC-MS analysis conditions

[0027] The column injection port temperature was 250°C, split injection, split ratio was 50:1, injection volume was 1 μL; program temperature rise: initial temperature 120°C, 10°C min -1 Raise to 160℃, hold for 5min, and adjust at 2℃·min -1 Raise to 190℃, maintain for 5min, and heat at 5℃·min -1 The temperature was raised to 280°C and maintained for 25 min. The mass spectrometer used an EI ion source with an ion source temperature of 250°C, an interface temperature of 250°C, and a scanning range of 50-600 amu.

[0028] 3. Chemical composition identification

[0029] The ion peak information in the total ion current chromatogram was processed, and the chemical components of muskrat incense were qualitatively identified by comparing with the reference substance and NIST14 and NIST14s databases. The peak area was normalized to determine the relative mass fraction.

[0030] The GC-MS total ion chromatograms of muskrat samples from different origins obtained by the above method are shown in the following figure: Figure 1-4 According to the chromatogram, the retention time and mass spectrum information of 32 chromatographic peaks were obtained, and the results are shown in Table 1.

[0031]

[0032]

[0033]

[0034] Example 2 Establishment of fingerprints of muskrat incense from different origins and similarity evaluation

[0035] The Chinese medicine chromatographic fingerprint similarity evaluation system (2012 version) was used to determine the common peaks and evaluate the similarity of the muskrat fingerprints from different origins. The average method was used to generate a reference spectrum with a time window width of 0.1. After full spectrum peak matching, a reference spectrum was generated. The GC-MS fingerprints of muskrat from different origins ( Figure 5 ) and the reference spectrum similarity results showed that a total of 27 common peaks were identified, the similarity of the reference spectrum of 24 batches of samples was between 0.360-0.999, the retention time RSD was 0.03-0.14%, and the peak area RSD was 3.30-132.88%.

[0036] Example 3 Establishment of OPLS-DA model of muskrat incense from different origins

[0037] In order to identify the metabolites that cause the quality differences of muskrat from different origins, an OPLS-DA classification model was established using SIMCA software. The 27 groups of common peak areas of 24 batches of muskrat samples from different origins were modeled and classified according to the origin of muskrat. All 24 batches of samples fell within the 95% confidence interval, and the three parameters R of the evaluation model were evaluated. 2 X, R 2 Y and Q 2 They are 0.940, 0.579 and 0.510 respectively, indicating that the explanatory rate of the model's independent variables is 94.0%, the explanatory rate of the dependent variables is 57.9%, and the predictability of the model is 51.0%, all of which are greater than 0.5. Therefore, the current model has good predictive ability. Figure 6 As shown in the figure, the production areas of Chongqing, Hebei, and Heilongjiang are concentrated in three different quadrants, and the production areas of Jiangsu and Hebei are relatively close, indicating that the content of common components of muskrat incense in the two production areas is relatively close. In order to further explain the markers that lead to differences in different production areas, the variable importance projection (VIP) of the data matrix was established for analysis. The variable importance projection (VIP) > 1 was used as the screening standard, indicating that the compound explained more than 50% of the classification summary. A total of 5 markers with large contributions were screened out, such as Figure 7 As shown in the figure, from large to small, it is cholesterol>cyclotriquinone>1,2-epoxyoctadecane>cyclopentadecanone>14-methyl-8-hexadecene-1-ol>5-cyclohexadecene-1-one, indicating that these five compounds are differential metabolites that are distinguished and determined from different origins, which has an indicative effect on the subsequent drug quality evaluation. In order to prevent the model from overfitting, OPLS-DA was subjected to 200 permutation tests. Figure 8 The results show that R 2 The intercept on the Y axis is 0.0405, which is greater than Q 2 The intercept on the Y axis is -0.384, R 2 >0 and Q 2 <0, indicating that the model is not overfitting.

Claims

1. A method for distinguishing and determining the origin of muskrat based on GC-MS. It is characterized by the following steps: (1) Extract the chemical components of muskrat and conduct GC-MS analysis; (2) importing the obtained chromatographic peak data into a traditional Chinese medicine chromatographic fingerprint similarity evaluation system to establish a muskrat incense fingerprint and perform similarity evaluation; (3) The orthogonal partial least squares discriminant analysis model was established for the data using SIMCA software. The chromatographic peak data were substituted into the established model for production area differentiation and judgment. The model was not overfitted, and the relevant parameters could prove the predictive ability of the model.

2. The method for determining the origin of muskrat based on GC-MS according to claim 1, characterized in that: Step (1) is as follows: accurately weigh 0.1 g of muskrat incense, add 1 mL of anhydrous ethanol, sonicate for 30 min, vortex, centrifuge, filter through a 0.22 μm fat-soluble filter membrane to obtain a test solution, dilute 5 times with anhydrous ethanol, and perform GC-MS analysis.

3. A method for distinguishing and determining the origin of muskrat based on GC-MS according to claim 2, characterized in that: The GC-MS analysis conditions were as follows: programmed temperature increase: initial temperature 120°C, 10°C·min -1 Raise to 160℃, hold for 5min, and adjust at 2℃·min -1 Raise to 190℃, maintain for 5min, and heat at 5℃·min -1 Raise to 280℃ and maintain for 25min. Injection volume 1μL, injection port temperature 250℃, split ratio 50:

1. Use EI ion source; ion source temperature 250℃; interface temperature 250℃; Q3Scan full scan mode; mass scan range 50-600amu.

4. The method for distinguishing and determining the origin of muskrat based on GC-MS according to claim 1, characterized in that: According to the chromatographic peak data obtained after GC-MS analysis, the chemical components in muskrat were determined, and the GC-MS fingerprint of muskrat was constructed using the traditional Chinese medicine chromatographic fingerprint similarity evaluation system.

5. The method for distinguishing and determining the origin of muskrat based on GC-MS according to claim 1, characterized in that: An orthogonal-partial least squares discriminant analysis model for muskrat musk from different origins was established, and the chromatographic peak data were substituted into the established model for origin determination. The model was not overfitted, and the relevant parameters could prove the predictive ability of the model.

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