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Identification of active compounds in Ophiopogonis Radix from different geographical origins by UPLC-Q/TOF-MS combined with GC-MS approaches

  • Xiaoyu Zha , Gaowen Li , Ling Zhang , Qun Chen and Qing Xia EMAIL logo
Published/Copyright: August 12, 2022
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Open Life Sciences
From the journal Open Life Sciences Volume 17 Issue 1

Abstract

Ophiopogonis Radix, also known as Maidong in Chinese, is largely produced in the Sichuan and Zhejiang provinces: “Chuan-maidong (CMD)” and “Zhe-maidong (ZMD),” respectively. This study aimed to distinguish and evaluate the quality of CMD and ZMD. In this study, the tubers of CMD and ZMD were investigated using UPLC-Q/TOF-MS, GC-MS, and LC-MS methods, respectively. Overall, steroidal saponins, homoisoflavonoids, amino acids, and nucleosides were quickly identified. Furthermore, multivariate statistical analysis revealed that CMD and ZMD could be separated. Moreover, CMD showed higher levels of 4-aminobutanoic acid, glycine, l-proline, monoethanolamine, and serine than ZMD. Besides, the levels of chlorogenic acid, traumatic acid, cytidine, cadaverine, pyridoxine 5-phosphate, glutinone, and pelargonidin 3-O-(6-O-malonyl-β-d-glucoside) were remarkably higher in ZMD than in CMD. Furthermore, these different constituents were mainly associated with galactose metabolism; starch and sucrose metabolism; cysteine and methionine metabolism; valine, leucine, and isoleucine biosynthesis; and glycerophospholipid metabolism. In general, these results showed many differences between the bioactive chemical constituents of Ophiopogon japonicus from different production areas, where ZMD performed better in the quality assessment than CMD, and that UPLC-Q/TOF-MS, GC-MS, and LC-MS are effective methods to discriminate medicinal herbs from different production areas.

Graphical abstract

Keywords: Ophiopogonis Radix; Maidong; UPLC-Q/TOF-MS; GC-MS; LC-MS

1 Introduction

Ophiopogonis Radix (known as Maidong), the root tuber of Ophiopogon japonicus Ker-Gawl, belongs to the family Liliaceae and is the most widely used traditional Chinese medicine (TCM) in the Chinese Pharmacopoeia [1]. According to TCM theory, Maidong nourishes yin, moistens the lungs, promotes body fluid production, eases the mind, and clears away heart fires [2,3]. It has been employed to control diabetes and its complications [4], radiation pneumonitis [5], atherosclerotic coronary heart disease, and viral myocarditis [6]. Additionally, modern phytochemical studies have suggested that Maidong is rich in various biologically active compounds, including steroidal saponins, amino acids, homoisoflavonoids, polysaccharides, and nucleosides, which have beneficial immunomodulatory, anti-inflammatory, central nervous system protective, antioxidative, and anti-apoptosis effects [7–9]. Although several studies on the chemical components of Maidong have been reported, these studies were performed with a single analytical technique and are not comprehensive [10,11]. Therefore, to the best of our knowledge, there is still a lack of information on the comprehensive chemical constituents of Maidong determined by using a multidimensional assessment approach.

At present, the cultivation regions of Ophiopogonis Radix are mainly concentrated in the Sichuan (mainly Santai County) and Zhejiang provinces (mainly the city of Cixi) of China. Ophiopogonis Radix from Sichuan and Zhejiang provinces is popularly called Chuan-maidong (CMD) and Zhe-maidong (ZMD), respectively, but ZMD is generally considered superior to Ophiopogonis Radix cultivated in other provinces [10]. Currently, it is generally accepted that the quantity and pharmacological effects of tubers on Maidong in different areas are controlled by environmental conditions and endogenous factors [11]. A study by Lu et al. found that the chemical constituents of CMD and ZMD differed much from each other according to high-performance liquid chromatography-mass spectrometry (LC-MS) with multivariate statistical analysis [12]. With the structural transformation of economic development, the cultivation of ZMD has drastically decreased in Zhejiang Province in recent years. Sichuan has now become the primary place of MD production [10,12]. In addition, CMD and ZMD are difficult to distinguish based on their appearance, which has also made quality control of Maidong challenging. Considering these findings, further study of the compositional distinction between Maidong tubers grown in Sichuan and Zhejiang provinces remains limited. Differences between the chemical constituents of CMD and ZMD have been reported by using LC coupled with evaporative light scattering detection, gas chromatography (GC) coupled with MS, or LC coupled with MS [2,10,13]. Because of the complexity of chemical constituents, those studies only assessed saponins, polysaccharides, or homoisoflavonoids.

Thus, this study aimed to comprehensively characterize the bioactive constituents of CMD and ZMD from the two producing areas and investigate their metabolic pathway. In this study, CMD and ZMD tubers were collected, and the chemical information of multiple bioactive constituents was characterized by using ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS), as well as GC-MS and LC-MS methods with multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares-discriminate analysis (OPLS-DA). Furthermore, the pathways of significantly different chemical constituents were identified to reveal the potential biological events occurring between CMD and ZMD. Therefore, the results of this study might provide a guide for a comprehensive evaluation and quality control, as well as a study on the mechanism of Ophiopogonis Radix.

2 Materials and methods

2.1 Chemicals and reagents

Ultrapure water was prepared by a Milli-Q system (Milford, MA, USA). Acetonitrile and methanol (HPLC grade) were produced by Merck (Darmstadt, Germany). Bis(trimethylsilyl)trifluoroacetamide was obtained from CNW Technologies (Shanghai, China). dl-o-Chlorophenylalanine was purchased from GL Biochem (Shanghai) Ltd (Shanghai, China). All the other chemicals and solvents were of analytical grade (purity (S98%) for GC/LC use.

2.2 Plant materials

CMD and ZMD at the same growth stage were collected from the market as mature plants in the cities of Cixi (Zhejiang, China) and Mianyang (Sichuan, China) in May 2020, respectively, including six batches of ZMD and six batches of CMD samples. All the samples were authenticated by Professor Qing Xia, Ningbo College of Health & Science, Ningbo, Zhejiang, China.

2.3 Sample preparation for UPLC-Q/TOF-MS analysis

The aim of the present study was to thoroughly evaluate the polysaccharides and saponins of CMD and ZMD in water extract solutions. Briefly, the dried tubers of CMD and ZMD were ground and passed through a standard 60-mesh filter. The obtained powder (3.0 g) was accurately weighed into a conical flask, immersed in 200 mL of distilled water for 30 min, and boiled for 90 min. Then, the liquid extract obtained was concentrated to 10 g by using rotating evaporation (JC-ZF-1L, Qingdao Juchuang Times Environmental Protection Technology Co., Ltd, China). The obtained liquid extract was dissolved in methanol at a weight ratio of 1:1 and centrifuged at a speed of 14,000 rpm for 20 min before UPLC-Q/TOF-MS analysis.

2.4 Sample preparation for GC-MS analysis

Additionally, approximately 50 mg of the dried tubers of CMD and ZMD were used for the extraction procedure. Briefly, CMD and ZMD were mixed with 800 μL of methanol containing an internal standard (2.8 mg/mL dl-o-Chlorophenylalanine). Then, all samples were ground to a fine powder using a grinding mill operated at 65 Hz for 120 s. The samples were ultrasonicated at 4 kHz in an ice bath for 30 min and then centrifuged at 12,000 rpm at 4°C for 10 min. Subsequently, 200 μL of the supernatant was evaporated to dryness at room temperature. After that, the samples were derivatized by shaking with 30 μL of methoxyamine hydrochloride (20 mg/mL) in pyridine for 90 min at 37°C. The samples were then trimethylsilylated by adding 30 μL of bis(trimethylsilyl)trifluoroacetamide and incubated for 1 h at 70°C. After the reaction was complete, the samples were incubated for 1 h at room temperature. Finally, 200 μL of the supernatant was transferred to a vial for GC-MS analysis. The mix of all extract solutions was used as a control sample (QC).

2.5 Sample preparation for LC-MS analysis

Furthermore, approximately 50 mg of the dried tubers of CMD and ZMD were applied for the extraction procedure. Briefly, CMD and ZMD were extracted with 800 μL of methanol containing dl-o-Chlorophenylalanine (2.8 mg/mL) to investigate flavonoids. All samples were ground to a fine powder using a grinding mill operated at 65 Hz for 120 s. The samples were ultrasonicated at 40 kHz in an ice bath for 30 min and then centrifuged at 12,000 rpm at 4°C for 15 min. After that, 200 μL of the supernatant was transferred to a vial for LC-MS analysis. The mix of all extract solutions was used as QC.

2.6 UPLC-Q/TOF-MS analysis and MS conditions

UPLC-Q/TOF-MS analysis was performed on a Waters ACQUITY UPLC I-Class PLUS system (Waters Corporation, Milford, MA, USA) coupled with hybrid quadrupole time-of-flight tandem mass spectrometer (SCIEX X-500R, SCIEX, Framingham, MA, USA) equipped with TurboIonSpray sources and a Turbo ion spray interface. Briefly, chromatographic separation was performed on a Waters UPLC BEH C18 column (100 mm × 2.1 mm, 1.7 µm particle size) at 40°C with a flow rate of 0.3 mL/min, and the injection volume was 3 μL. The mobile phase was composed of 0.1% ammonium formate in acetonitrile (A) and 0.1% formic acid aqueous solution (B) and introduced under the following gradient conditions: 0–12 min, 99% A–50% A; 12–14.5 min, 50–15% A; 14.5–15 min, 15–1% A; 15–18 min, 1% A; 18–18.1 min, 1% B–99% A; and 18.1–21 min, 99% A. TOF MS was performed using a Turbo Ion Spray ion source and ESI positive (+) and negative (−) ion scanning modes. The MS analysis conditions were as follows: source temperature: 600°C; nebulizing gas (N2): 55 psi; drying gas (N2): 45 psi; curtain gas (CUR): 35 psi; IonSpray Voltage Floating: 5,500 V/−4,500 V; TOF MS scan m/z range: 100–1,500 Da; TOF-MS/MS scan m/z range: 25–1,500 Da; TOF MS scan accumulation time: 0.25 s/spectra; and product ion scan accumulation time: 0.035 s/spectra. MS uses information-dependent acquisition and high sensitivity mode.

2.7 GC-MS analysis

An Agilent 6890A/5973C GC-MS system and a DB-5MS fused-silica capillary column (30 m × 0.25 mm × 0.25 μm, Agilent J&W Scientific, USA) were used for analysis. The injector temperature was 280°C. The temperature program used was as follows: the column temperature was held at 70°C for 2 min, increased by 10°C  to 200°C, increased by 5°C  to 280°C and held there for 6 min. The ion source and quadrupole rod temperatures were 230 and 150°C, respectively. The column effluent was fully scanned in the mass range of 50–550 m/z. The data were subjected to feature extraction and preprocessed with the XCMS package in R software (version 4.0.5, https://www.r-project.org/) and then normalized and edited into a two-dimensional data matrix by Excel 2010 software; data included the retention time (RT), the mass-to-charge ratio, observations (samples), and peak intensity.

2.8 LC-MS analysis

LC-MS was performed using an ACQUITYTM UPLC-QTOF platform (Waters, Wexford, Ireland) with a Waters ACQUITY UPLC HSS T3 column (2.1 mm × 100 mm, 1.8 μm). The mobile phases consisted of 0.1% aqueous formic acid (v/v) (A) and acetonitrile (B), and were introduced under the following gradient elution conditions: 0% B at 0–1 min, 0–20% B at 1–2 min, 20–50% B at 2–12 min, 50–95% B at 12–15 min, and 95–100% B at 15–20 min. The flow rate was set at 0.35 mL/min, and the column temperature was maintained at 40°C. The injection volume was 6 μL. The electrospray ionization source was set in both ESI (+) and ESI (–) ionization modes. The parameters were set as follows: source and desolvation temperatures: 120 and 350°C, respectively; desolvation gas (N2) flow: 600 L/h; capillary voltages: 1.4 kV for ESI (+) and 1.3 kV for ESI (–); sampling cone: 40 V for ESI (+) and 23 V for ESI (–); cone gas (N2) flow: 50 L/h; collision energy: 10–40 V; ion energy: 1 V; scan time: 0.03 s; and interscan time: 0.02 s. The mass range scanned was 50–1,500 m/z. MS data were collected with MassLynx 4.1 software.

2.9 Data analysis

For UPLC-Q/TOF-MS analysis, the data were processed using SCIEX OS software with multiple confidence criteria, including quality accuracy, RT, isotopes, and matching use of compound libraries. In this study, the TCM MS/MS Library, which contains secondary data for more than 1,500 Chinese herbal medicines, was used to identify the target constituents based on the first-order accurate mass number, isotope distribution ratio, and MS/MS of the compounds. For GC-MS analysis, a total of 1,060 features were collected in this experiment, and the data were imported into SIMCA-P (version 13.0, Umetrics AB, Sweden) software for PCA and OPLS-DA. For LC-MS analysis, the data were first transformed to CDF files by CDFbridge and input into the XCMS package in R software and then normalized and edited into a two-dimensional data matrix by Excel 2007 software. A total of 1,712 features in ESI (+) ionization mode and 1,138 features in ESI (–) ionization mode were collected in this experiment, and the data were imported into SIMCA-P software to perform PCA and OPLS-DA.

3 Results

3.1 UPLC/Q-TOF MS analysis of chemical constituents of CMD and ZMD

By using UPLC/Q-TOF MS analysis, CMD and ZMD could be analyzed within 21 min and exhibited some major peaks in the total ion chromatography, as shown in Figures 1 and 2, respectively. According to the TCM MS/MS Library in SCIEX OS software, the chemical constituents were identified qualitatively. As a result, a total of 26 chemical constituents of CMD were identified in positive ion mode and 33 chemical constituents of CMD were identified in negative ion mode in UPLC/Q-TOF MS analysis. Furthermore, a total of 33 chemical constituents of ZMD were identified in positive ion mode and 39 chemical constituents of ZMD were identified in negative ion mode in UPLC/Q-TOF MS analysis. Most of these chemical constituents were steroidal saponins, amino acids, homoisoflavonoids, polysaccharides, and nucleosides. Additionally, our UPLC/Q-TOF MS analysis revealed that the dried tubers of both CMD and ZMD contained methylophiopogonanone A, methylophiopogonanone B, methylophiopogonone A, ophiopogonin D, ophiopogonin D′, ophiopogonanone C, ophiopogonanone E, and ruscogenin. Detailed information on the identified chemical constituents is listed in Tables 1–4. Also, the MS fragmentation pathways for different chemical constituents of CMD and ZMD in positive ion mode or negative ion mode are shown in Tables S1 and S2, respectively.

Figure 1 Total ion chromatogram of CMD obtained by UPLC/Q-TOF MS analysis in (a) positive ion mode and (b) negative ion mode.
Figure 1

Total ion chromatogram of CMD obtained by UPLC/Q-TOF MS analysis in (a) positive ion mode and (b) negative ion mode.

Figure 2 Total ion chromatogram of ZMD obtained by UPLC/Q-TOF MS analysis in (a) positive ion mode and (b) negative ion mode.
Figure 2

Total ion chromatogram of ZMD obtained by UPLC/Q-TOF MS analysis in (a) positive ion mode and (b) negative ion mode.

Table 1

Putative identification of CMD in positive ion mode

No. Component name Area RT Formula Precursor mass Found at mass Mass error (ppm)
1 l(+)-Arginine 7,402,000 1.14 C6H14N4O2 175.119 175.1187 −1.5
2 Trigonelline 253,900 1.21 C7H7NO2 138.055 138.0551 1
3 Proline 433,800 1.24 C5H9NO2 116.071 116.0707 0.4
4 Glutamic acid 187,400 1.3 C5H9NO4 148.06 148.0606 0.8
5 Betaine 140,700 1.37 C5H11NO2 118.086 118.0863 0.6
6 Nicotinic acid 155,300 1.71 C6H5NO2 124.039 124.0394 0.9
7 Nicotinamide 235,400 1.79 C6H6N2O 123.055 123.0554 0.9
8 Adenosine 2,131,000 2.36 C10H13N5O4 268.104 268.1038 −0.9
9 Cordycepin 43,090 2.42 C10H13N5O3 252.109 252.1093 0.8
10 Guanosine 207,900 2.46 C10H13N5O5 284.099 284.0992 0.7
11 Phenylalanine 1,719,000 3.17 C9H11NO2 166.086 166.0863 0.3
12 Cinnamic acid 48,090 3.18 C9H8O2 149.06 149.0598 0.6
13 4-Hydroxybenzoic acid 12,960 4.73 C7H6O3 139.039 139.039 0.4
14 Esculetin 23,820 5.13 C9H6O4 179.034 179.034 0.6
15 Hyperin 4,621 6.5 C21H20O12 465.103 465.1034 1.4
16 Syringaldehyde 3,442 6.56 C9H10O4 183.065 183.065 −1.1
17 Luteoloside 2,638 6.67 C21H20O11 449.108 449.1091 2.8
18 Isoferulic acid 3,834 6.74 C10H10O4 195.065 195.0652 0.1
19 Narirutin 2,831 7.08 C27H32O14 581.186 581.1873 1.4
20 Neohesperidin 4,766 7.5 C28H34O15 611.197 611.1977 1.1
21 Tiliroside 4,904 8.91 C30H26O13 595.145 595.145 0.7
22 Calycosin-7-O-glucoside 6,176 9.42 C22H22O10 447.129 447.1284 −0.4
23 Nobiletin 31,320 12.77 C21H22O8 403.139 403.1388 0.1
24 Ophiopogonin D′ 877,800 14.83 C44H70O16 855.474 855.4731 −0.6
25 Ruscogenin 178,800 14.85 C27H42O4 431.316 431.3154 −0.5
26 Ophiopogonanone C 3,902 15.06 C20H20O6 357.133 357.134 1.9
Table 2

Putative identification of CMD in negative ion mode

No. Component name Area RT Formula Precursor mass Found at mass Mass error (ppm)
1 Histidine 17,540 1.09 C6H9N3O2 154.062 154.0621 −0.7
2 l(+)-Arginine 165,100 1.1 C6H14N4O2 173.104 173.1044 0.2
3 Glutamic acid 57,600 1.14 C5H9NO4 146.046 146.046 0.6
4 d-(+)-Mannose 786,300 1.22 C6H12O6 179.056 179.0562 0.4
5 l-Malic acid 3,632,000 1.38 C4H6O5 133.014 133.0144 0.9
6 Citric acid 9,523,000 1.9 C6H8O7 191.02 191.0198 0.3
7 Succinic acid 58,120 2.29 C4H6O4 117.019 117.0193 0
8 Leucine 473,700 2.47 C6H13NO2 130.087 130.0873 0
9 Guanosine 335,800 2.47 C10H13N5O5 282.084 282.0844 0.1
10 Gallic acid 10,950 2.65 C7H6O5 169.014 169.0142 −0.3
11 Phenylalanine 592,600 3.18 C9H11NO2 164.072 164.0717 −0.1
12 Vanillic acid 119,600 3.37 C8H8O4 167.035 167.035 0.2
13 l-Tryptophan 383,500 4.16 C11H12N2O2 203.083 203.0827 0.7
14 4-Hydroxybenzoic acid 36,400 4.63 C7H6O3 137.024 137.0245 0.9
15 4-O-caffeoyl quinic acid 21,560 4.8 C16H18O9 353.088 353.0881 0.8
16 Esculetin 151,700 5.13 C9H6O4 177.019 177.0195 0.8
17 Caffeic acid 154,600 5.21 C9H8O4 179.035 179.0351 0.6
18 Shikimic acid 548,900 5.49 C7H10O5 173.046 173.0454 −0.9
19 Ellagic acid 28,660 6.35 C14H6O8 300.999 300.999 0.1
20 Hyperin 34,590 6.51 C21H20O12 463.088 463.0875 −1.4
21 Narirutin 8,615 7.08 C27H32O14 579.172 579.1718 −0.3
22 Neohesperidin 16,980 7.5 C28H34O15 609.182 609.1827 0.4
23 Tiliroside 16,580 8.92 C30H26O13 593.13 593.1292 −1.4
24 Calycosin-7-o-glucoside 4,825 9.43 C22H22O10 491.119 491.1188 −1.4
25 Gracillin 14,970 10.78 C45H72O17 929.475 929.473 −2.3
26 Liriope muscari baily saponins C 165,000 13.46 C44H70O17 869.454 869.4514 −3
27 Methylophiopogonone A 386,000 14.71 C19H16O6 339.087 339.0864 −2.9
28 Ophiopogonin D 3,242,000 14.83 C44H70O16 899.465 899.4623 −2.6
29 Methylophiopogonanone B 2,266,000 14.99 C19H20O5 327.124 327.1228 −3
30 Liriopesides B 181,500 15.12 C39H62O12 767.422 767.4199 −3.1
31 Gingerglycolipid B 5,459 15.2 C33H58O14 723.381 723.3788 −2.8
32 Corosolic acid 3,440 15.55 C30H48O4 471.348 471.3459 −4.4
33 Ophiopogonanone C 75,350 15.72 C19H16O7 355.082 355.0814 −2.7
Table 3

Putative identification of ZMD in positive ion mode

No. Component name Area RT Formula Precursor mass Found at mass Mass error (ppm)
1 l(+)-Arginine 4,301,000 1.11 C6H14N4O2 175.119 175.1189 −0.5
2 Trigonelline 207,100 1.2 C7H7NO2 138.055 138.0551 1.2
3 Proline 2,757,000 1.22 C5H9NO2 116.071 116.0706 0
4 Nicotinic acid 56,410 1.72 C6H5NO2 124.039 124.0395 1.6
5 Nicotinamide 208,200 1.8 C6H6N2O 123.055 123.0553 0.4
6 Adenosine 926,700 2.35 C10H13N5O4 268.104 268.104 −0.2
7 Cordycepin 41,280 2.42 C10H13N5O3 252.109 252.1096 1.9
8 Isoleucine 280,500 2.46 C6H13NO2 132.102 132.1019 −0.2
9 Guanosine 90,750 2.47 C10H13N5O5 284.099 284.0995 1.9
10 Phenylalanine 285,000 3.17 C9H11NO2 166.086 166.0863 0.4
11 Chlorogenic acid 57,310 4.64 C16H18O9 355.102 355.1031 2
12 4-Hydroxybenzoic acid 14,360 4.73 C7H6O3 139.039 139.0391 0.9
13 Daphnetin 124,300 5.13 C9H6O4 179.034 179.0339 −0.1
14 Esculetin 124,300 5.13 C9H6O4 179.034 179.0339 −0.1
15 Rutin 71,010 6.3 C27H30O16 611.161 611.1621 2.3
16 Hyperin 297,200 6.5 C21H20O12 465.103 465.1034 1.4
17 Isoscopoletin 42,290 6.69 C10H8O4 193.05 193.0498 1.6
18 Isoferulic acid 2,997 6.74 C10H10O4 195.065 195.0657 2.4
19 Luteoloside 1,829 6.96 C21H20O11 449.108 449.1097 4.1
20 Narirutin 15,920 7.08 C27H32O14 581.186 581.1875 1.8
21 Luteolin 107,100 7.14 C15H10O6 287.055 287.0553 1
22 Genistein 31,520 7.38 C21H20O10 433.113 433.1134 1
23 Hesperidin 55,530 7.48 C28H34O15 611.197 611.1975 0.7
24 Pratensein-7-O-glucoside 4,385 7.7 C22H22O11 463.123 463.1243 1.8
25 Tiliroside 190,600 8.91 C30H26O13 595.145 595.1444 −0.4
26 Calycosin-7-O-glucoside 42,280 9.42 C22H22O10 447.129 447.1293 1.5
27 Farrerol 249,800 10.35 C17H16O5 301.107 301.1068 −0.8
28 Patchouli alcohol 611,500 12.24 C15H24 205.195 205.1949 −0.7
29 Nobiletin 99,200 12.77 C21H22O8 403.139 403.1389 0.3
30 Diosgenin 38,270 14.75 C27H42O3 415.321 415.3208 0.2
31 Ruscogenin 6,144 14.83 C27H42O4 431.316 431.3175 4.4
32 Ophiopogonanone C 41,460 15.1 C20H20O6 357.133 357.1333 0
33 Liriopesides B 256,700 15.11 C39H62O12 723.431 723.4309 −0.7
Table 4

Putative identification of ZMD in negative ion mode

No. Component name Area RT Formula Precursor mass Found at mass Mass error (ppm)
1 Histidine 11,660 1.08 C6H9N3O2 154.062 154.0622 −0.1
2 Arginine 165,500 1.09 C6H14N4O2 173.104 173.1044 0.1
3 d-(+)-Mannose 376,700 1.19 C6H12O6 179.056 179.056 −0.8
4 l-Malic acid 2,191,000 1.35 C4H6O5 133.014 133.0143 0.2
5 Fungitetraose 329,200 1.79 C24H42O21 665.215 665.2146 0
6 Citric acid 7,804,000 1.94 C6H8O7 191.02 191.0196 −0.5
7 Succinic acid 21,110 2.31 C4H6O4 117.019 117.0192 −0.9
8 Adenine 10,630 2.37 C5H5N5 134.047 134.0473 0.3
9 Guanosine 115,800 2.48 C10H13N5O5 282.084 282.0845 0.3
10 Gallic acid 54,280 2.66 C7H6O5 169.014 169.0142 0
11 Phenylalanine 70,380 3.19 C9H11NO2 164.072 164.0718 0.8
12 Vanillic acid 228,400 3.37 C8H8O4 167.035 167.035 0.3
13 Hydroxytyrosol 11690 3.69 C8H10O3 153.056 153.0559 1
14 l-Tryptophan 250,300 4.16 C11H12N2O2 203.083 203.0826 0.1
15 Salidroside 31,980 4.17 C14H20O7 299.114 299.1138 0.7
16 4-Hydroxybenzoic acid 92,120 4.63 C7H6O3 137.024 137.0244 0.1
17 4-O-caffeoyl quinic acid 264,700 4.8 C16H18O9 353.088 353.0879 0.1
18 Esculetin 430,000 5.14 C9H6O4 177.019 177.0193 −0.3
19 Caffeic acid 309,100 5.21 C9H8O4 179.035 179.0348 −0.8
20 Eleutheroside E 14,750 5.88 C34H46O18 787.267 787.2658 −1
21 Rutin 202,800 6.3 C27H30O16 609.146 609.1456 −0.9
22 Hyperin 2,004,000 6.51 C21H20O12 463.088 463.0879 −0.7
23 Astragalin 12,120 6.96 C21H20O11 447.093 447.0931 −0.4
24 Specnuezhenide 872,500 7.04 C31H42O17 685.235 685.2342 −1
25 Narirutin 43,210 7.08 C27H32O14 579.172 579.1709 −1.8
26 Dicaffeoylquinic acid 34,110 7.49 C25H24O12 515.119 515.1189 −1.2
27 Hesperidin 161,500 7.49 C28H34O15 609.182 609.1816 −1.5
28 Quercetin 16,350 9.1 C15H10O7 301.035 301.035 −1.3
29 Calycosin-7-o-glucoside 20,440 9.43 C22H22O10 491.119 491.1178 −3.5
30 Apigenin 6,976 10.1 C15H10O5 269.046 269.0448 −2.9
31 Butylparaben 2,508 13.24 C11H14O3 193.087 193.0869 −0.7
32 Liriope muscari baily saponins C 5,340 13.53 C44H70O17 869.454 869.4516 −2.8
33 Asiatic acid 31,510 14.06 C30H48O5 487.343 487.3414 −3
34 Methylophiopogonone A 264,600 14.71 C19H16O6 339.087 339.0865 −2.7
35 Ophiopogonin D 47,450 14.83 C44H70O16 899.465 899.463 −1.7
36 Gingerglycolipid B 5,698 15.21 C33H58O14 723.381 723.3777 −4.3
37 Corosolic acid 13,550 15.55 C30H48O4 471.348 471.3464 −3.3
38 Ophiopogonanone C 201,100 15.72 C19H16O7 355.082 355.0815 −2.2
39 Oleanolic acid 20,510 16.77 C30H48O3 455.353 455.3524 −1.4

3.2 GC-MS analysis of chemical constituents of CMD and ZMD

The total ion chromatograms of CMD and ZMD are shown in Figure 3. PCA and OPLS-DA were used to realize the CMD and ZMD clusters. In addition, the PCA score plot exhibited a relatively tight clustering of the QC samples, which confirmed the reliability of the MS data. As shown in Figure 4a, the CMD and ZMD groups were clearly separated in the PCA score plot (R 2 X = 0.864, Q 2 = 0.651) with four PCs. Meanwhile, an OPLS-DA model was established (R 2 X = 0.912, R 2 Y = 0.998, and Q 2 = 0.936) and showed clear discrimination between CMD and ZMD groups (Figure 4b). A heatmap plot was generated to further characterize the significant differences. Variables with variable importance in the projection (VIP) values larger than 1 were considered to be potential chemical constituents, and 17 chemical constituents were selected (Figure 4c and Table S3).

Figure 3 GC-MS chromatographs of CMD extract (a) and ZMD extract (b).
Figure 3

GC-MS chromatographs of CMD extract (a) and ZMD extract (b).

Figure 4 Multivariate statistical analysis of CMD and ZMD samples using GC-MS analysis: (a) PCA score plots for CMD, ZMD, and QC samples, (b) OPLS-DA score plots for CMD and ZMD, and (c) heatmap plot for the different chemical constituents of CMD and ZMD.
Figure 4

Multivariate statistical analysis of CMD and ZMD samples using GC-MS analysis: (a) PCA score plots for CMD, ZMD, and QC samples, (b) OPLS-DA score plots for CMD and ZMD, and (c) heatmap plot for the different chemical constituents of CMD and ZMD.

3.3 Pathway enrichment of different chemical constituents in GC-MS analysis

To explore the roles of different chemical constituents based on GC-MS analysis, the different chemical constituents were imported into MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/), a comprehensive platform dedicated to metabolomics data analysis via a user-friendly, web-based interface [14]. The impact value threshold was set to 0.1, and pathways with an impact value greater than the threshold were considered potential target pathways. As shown in Table 5, the therapeutic effect of CMD and ZMD was probably associated with galactose metabolism; starch and sucrose metabolism; cyanoamino acid metabolism; methane metabolism; aminoacyl-tRNA biosynthesis; glycine, serine, and threonine metabolism; arginine and proline metabolism; amino sugar and nucleotide sugar metabolism; sulfur metabolism; and glycerolipid metabolism (Table 5).

Table 5

Pathways of significantly different chemical constituents in GC-MS analysis

No. Pathway name Metabolite KEGG ID
1 Galactose metabolism Glycerol C00116
d-Galactose C00124
d-Glucose C00031
Sucrose C00089
2 Starch and sucrose metabolism Trehalose C01083
beta-d-Fructose C02336
d-Glucose C00031
Sucrose C00089
3 Cyanoamino acid metabolism Glycine C00037
l-Serine C00065
4 Methane metabolism Glycine C00037
l-Serine C00065
5 Aminoacyl-tRNA biosynthesis Glycine C00037
l-Serine C00065
l-Proline C00148
6 Glycine, serine, and threonine metabolism l-Serine C00065
Glycine C00037
7 Arginine and proline metabolism Gamma-aminobutyric acid C00334
l-Proline C00148
8 Amino sugar and nucleotide sugar metabolism d-Galactose C00124
beta-d-Fructose C02336
9 Sulfur metabolism l-Serine C00065
10 Glycerolipid metabolism Glycerol C00116
11 Sphingolipid metabolism l-Serine C00065
12 Nitrogen metabolism Glycine C00037
13 Glyoxylate and dicarboxylate metabolism l-Malic acid C00149
14 Butanoate metabolism Gamma-aminobutyric acid C00334
15 Citrate cycle (TCA cycle) l-Malic acid C00149
16 Carbon fixation in photosynthetic organisms l-Malic acid C00149
17 Pyruvate metabolism l-Malic acid C00149
18 Alanine, aspartate, and glutamate metabolism Gamma-aminobutyric acid C00334
19 Glycerophospholipid metabolism Ethanolamine C00189
20 Glutathione metabolism Glycine C00037
21 Cysteine and methionine metabolism l-Serine C00065

3.4 LC-MS analysis of chemical constituents of CMD and ZMD

The CMD and ZMD extracts were also analyzed by LC-MS in both positive and negative ion modes. The base peak chromatograms of LC-MS are shown in Figure 5a and b. As shown in Figure 6a, the CMD and ZMD groups were also clearly separated in the PCA score plot (R 2 X = 0.59, Q 2 = 0.303) with three PCs. Then, the OPLS-DA model was established (R 2 X = 0.658, R 2 Y = 1, and Q 2 = 0.892) in positive ion mode (Figure 6c). And, an OPLS-DA model was established (R 2 X = 0.763, R 2 Y = 1, and Q 2 = 0.93) in negative ion mode (Figure 6d), and both showed clear discrimination of the CMD and ZMD groups in negative ion mode (R 2 X = 0.63, Q 2 = 0.279; Figure 6b) with three PCs. Furthermore, we found 25 differences in the chemical constituents of CMD and ZMD in positive ion mode (Figure 7a and Table S4) and a total of 17 differences in the chemical constituents of CMD and ZMD in negative ion mode (Figure 7b and Table S5).

Figure 5 Base peak chromatograms of CMD and ZMD obtained by LC-MS in positive mode (a) and negative mode (b).
Figure 5

Base peak chromatograms of CMD and ZMD obtained by LC-MS in positive mode (a) and negative mode (b).

Figure 6 PCA and OPLS-DA score plots of CMD and ZMD samples in (a and c) positive ion mode and (b and d) negative ion mode.
Figure 6

PCA and OPLS-DA score plots of CMD and ZMD samples in (a and c) positive ion mode and (b and d) negative ion mode.

Figure 7 Heatmap plot for the different chemical constituents between CMD and ZMD using LC-MS analysis in (a) positive ion mode and (b) negative ion mode.
Figure 7

Heatmap plot for the different chemical constituents between CMD and ZMD using LC-MS analysis in (a) positive ion mode and (b) negative ion mode.

3.5 Pathway enrichment of different chemical constituents in LC-MS analysis

Similarly, metabolic pathways of different chemical constituents were analyzed in LC-MS analysis using the integrated web-based tool MetaboAnalyst. In our study, the 25 different chemical constituents between CMD and ZMD in the positive ion mode were mainly associated with tropane, piperidine, and pyridine alkaloid biosynthesis; sulfur metabolism; stilbenoid, diarylheptanoid, and gingerol biosynthesis; and cysteine and methionine metabolism (Table 6). Moreover, the 17 differences in the chemical constituents of CMD and ZMD in the negative ion mode were related to valine, leucine, and isoleucine biosynthesis; diterpenoid biosynthesis; pantothenate and CoA biosynthesis; flavonoid biosynthesis; glycolysis or gluconeogenesis; carbon fixation in photosynthetic organisms; and glycerophospholipid metabolism (Table 7). These data suggested that there were many differences between CMD and ZMD. Additionally, CMD and ZMD likely act to nourish yin through all three signaling pathways.

Table 6

Pathways of significantly different chemical constituents (ESI+)

No. Pathway name Metabolite KEGG ID
1 Tropane, piperidine, and pyridine alkaloid biosynthesis Cadaverine C01672
2 Sulfur metabolism l-Cysteine C00097
3 Stilbenoid, diarylheptanoid, and gingerol biosynthesis Chlorogenic acid C00852
4 Cysteine and methionine metabolism l-Cysteine C00097
l-Cystathionine C02291
5 Glycerophospholipid metabolism Phosphatidate C00416
2-Lysophosphatidylcholine C04230
6 Phenylpropanoid biosynthesis Chlorogenic acid C00852
7 Diterpenoid biosynthesis Gibberellin A53 C06094
8 Arginine and proline metabolism l-Arginine C00062
9 Thiamine metabolism l-Cysteine C00097
10 Aminoacyl-tRNA biosynthesis l-Arginine C00062
l-Cysteine C00097
11 Flavonoid biosynthesis Taxifolin C01617
Chlorogenic acid C00852
12 Purine metabolism 5-Hydroxyisourate C11821
13 Glutathione metabolism l-Cysteine C00097
Cadaverine C01672
Glutathione C00051
14 Glycerolipid metabolism Phosphatidate C00416
15 Pyrimidine metabolism Cytidine C00475
Thymidine C00214
16 Ubiquinone and other terpenoid-quinone biosynthesis Alpha-tocopherol C02477
17 Vitamin B6 metabolism Pyridoxal 5′-phosphate C00018
Pyridoxine 5′-phosphate C00627
Table 7

Pathways of significantly different chemical constituents (ESI−)

No. Pathway name Metabolite KEGG ID
1 Valine, leucine, and isoleucine biosynthesis Pyruvic acid C00022
2 Butanoate metabolism Pyruvic acid C00022
3 Pyruvate metabolism Pyruvic acid C00022
4 Diterpenoid biosynthesis Gibberellin A53 C06094
5 Pantothenate and CoA biosynthesis Pyruvic acid C00022
6 Flavonoid biosynthesis Quercetin C00389
7 Glycolysis or gluconeogenesis Pyruvic acid C00022
8 Carbon fixation in photosynthetic organisms Pyruvic acid C00022
9 Glycerophospholipid metabolism 2-Lysophosphatidylcholine C04230
Phosphatidylcholine C00157
10 Alanine, aspartate, and glutamate metabolism Pyruvic acid C00022
11 Citrate cycle (TCA cycle) Pyruvic acid C00022
12 C5-branched dibasic acid metabolism Pyruvic acid C00022
13 Terpenoid backbone biosynthesis Pyruvic acid C00022
Geranyl-PP C00341
14 Flavone and flavonol biosynthesis Quercetin C00389
15 Glycine, serine, and threonine metabolism Pyruvic acid C00022
16 Monoterpenoid biosynthesis Geranyl-PP C00341
17 Taurine and hypotaurine metabolism Taurine C00245
18 Cysteine and methionine metabolism Pyruvic acid C00022

4 Discussion

The tubers of Ophiopogonis Radix (Maidong in Chinese) are an important Chinese herb and functional health food. However, the quality of CMD and ZMD remains to be distinguished and evaluated. In this respect, UPLC-Q/TOF-MS provides accurate structural information about bioactive compounds for the identification of TCM [15]. In addition, metabolomics provides new insights into understanding global metabolic changes and the multiple related biochemical pathways of altered metabolites [16,17]. GC-MS and LC-MS have become two of the most commonly used high-throughput technologies in metabolomics research due to their high sensitivity and favorable reproducibility [16,18,19]. Due to the complexity of chemical components in MD, it is difficult for traditional methods to thoroughly isolate trace ingredients with a single method. Therefore, multiple analytical platforms are needed.

In this study, efficient and reliable methods based on UPLC-Q/TOF-MS, GC-MS, and LC-MS analyses were used to identify the bioactive chemical constituents in CMD and ZMD. For UPLC-Q/TOF-MS analysis, UPLC-Q/TOF-MS technology has greatly improved the speed of analysis and detection in plants [20]. Overall, a total of 59 and 72 chemical constituents were quickly identified in CMD and ZMD, respectively, including steroidal saponins, homoisoflavonoids, amino acids, and nucleosides. Among them, isoleucine, chlorogenic acid, daphnetin, rutin, isoscopoletin, luteolin, genistein, hesperidin, pratense-7-O-glucoside, farrerol, patchouli alcohol, diosgenin, arginine, fungitetraose, adenine, hydroxytyrosol, salidroside, eleutheroside E, astragalin, specnuezhenide, dicaffeoylquinic acid, quercetin, apigenin, butylparaben, asiatic acid, and oleanolic acid existed only in ZMD, while glutamic acid, betaine, cinnamic acid, syringaldehyde, neohesperidin, leucine, shikimic acid, ellagic acid, gracillin, and methylophiopogonanone B existed only in CMD. In general, these results showed that there were many differences between the bioactive chemical constituents of Ophiopogonis Radix from different production areas.

Metabolomics can help to assess the physiological state of an organism in diverse biochemical events [21]. Previously, Lyu et al. reported that O. japonicas from Zhejiang and Sichuan can clearly be separated by using UPLC/Q-TOF MS-based metabolome analysis where CMD showed higher level steroidal saponins, and ZMD had higher contents of homoisoflavonoids specifically [20]. Similarly,i this study, for GC-MS and LC-MS-based metabolome analyses, the PCA results showed that the CMD and ZMD samples were divided into two clusters and indicated that metabolite profiling by GC-MS and LC-MS also contributes to discriminating CMD and ZMD samples from different geographical origins. Moreover, the OPL-DA and VIP values revealed that the bioactive chemical constituents in CMD and ZMD were significantly different. Among them, 4-aminobutanoic acid, glycine, l-proline, monoethanolamine, and serine showed higher levels in CMD according to the results of GC-MS analysis. In addition, the contents of chlorogenic acid, traumatic acid, cytidine, cadaverine, pyridoxine 5-phosphate, glutinone, and pelargonidin 3-O-(6-O-malonyl-β-d-glucoside) were remarkably higher than those in CMD. Moreover, these different constituents were mainly associated with multiple metabolic pathways, such as galactose metabolism; starch and sucrose metabolism; cysteine and methionine metabolism; valine, leucine, and isoleucine biosynthesis; and glycerophospholipid metabolism. Significantly, galactose is crucial for human metabolism, with an established role in energy delivery and the galactosylation of complex molecules [22]. Additionally, sucrose plays a central role in the control of carbon flux in the biosynthesis of different storage reserves [23]. Xu et al. showed that methionine restriction, a dietary regimen that protects against metabolic diseases and aging, represses cancer growth and improves cancer therapy [24]. Interestingly, leucine and isoleucine reduced body weight and white adipose tissue weight by regulating lipid metabolism-related genes in high-fat diet-induced obese mice [25]. Overall, the bioactive chemical constituents in CMD and ZMD are involved in diverse metabolic pathways with different pharmacological effects. However, there are some limitations to this study. The number of samples is too small to be representative for multivariate statistical analysis. The sample size should be expanded for further study. In further research, we will focus on the molecular mechanisms of different chemical constituents in Maidong, which are critical for developing Maidong for pharmacology and clinical uses.

5 Conclusion

In summary, UPLC-Q/TOF-MS, GC-MS, and LC-MS analyses combined with multivariate statistical analysis could provide basic information for the discrimination and quality evaluation of Ophiopogonis Radix from two different production areas. These findings suggested that the ZMD samples showed higher levels of one type of bioactive chemical constituent than the CMD samples, demonstrating that the geographical area influenced the accumulation of bioactive constituents. This study also lays foundations for future studies on the quantitative analysis of the 12 bioactive chemical constituents between CMD and ZMD and their relevant metabolic pathways, which will contribute to increasing the understanding of the pharmacodynamic effects and improve the development of Ophiopogonis Radix in TCM.

# These authors contributed equally to this work.

Acknowledgments

This study was completed in the Ningbo College of Health Science. We would like to thank the teachers at this college for their guidance.

  1. Funding information: This work was financially supported by the National Natural Science Foundations of Ningbo (No. 2019C50082 and No. 202002N3172) and the “2025” Major Science and Technology Project of Ningbo (No. 2019B10008).

  2. Author contributions: G.W.L. and Q.X. conceived and supervised the study; G.W.L. designed the experiments; G.W.L., X.Y.Z., Q.C., and L.Z. performed the experiments; G.W.L. and L.Z. analyzed the data and wrote the manuscript. All authors reviewed the results and approved the final version of the manuscript.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Received: 2021-12-15
Revised: 2022-04-12
Accepted: 2022-05-09
Published Online: 2022-08-12

© 2022 Xiaoyu Zha et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  85. Continuous renal replacement therapy combined with double filtration plasmapheresis in the treatment of severe lupus complicated by serious bacterial infections in children: A case report
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  87. Preclinical immunogenicity assessment of a cell-based inactivated whole-virion H5N1 influenza vaccine
  88. One case of iodine-125 therapy – A new minimally invasive treatment of intrahepatic cholangiocarcinoma
  89. S1P promotes corneal trigeminal neuron differentiation and corneal nerve repair via upregulating nerve growth factor expression in a mouse model
  90. Early cancer detection by a targeted methylation assay of circulating tumor DNA in plasma
  91. Calcifying nanoparticles initiate the calcification process of mesenchymal stem cells in vitro through the activation of the TGF-β1/Smad signaling pathway and promote the decay of echinococcosis
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  93. N6-Methyladenosine-related alternative splicing events play a role in bladder cancer
  94. Characterization of the structural, oxidative, and immunological features of testis tissue from Zucker diabetic fatty rats
  95. Effects of glucose and osmotic pressure on the proliferation and cell cycle of human chorionic trophoblast cells
  96. Investigation of genotype diversity of 7,804 norovirus sequences in humans and animals of China
  97. Characteristics and karyotype analysis of a patient with turner syndrome complicated with multiple-site tumors: A case report
  98. Aggravated renal fibrosis is positively associated with the activation of HMGB1-TLR2/4 signaling in STZ-induced diabetic mice
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  100. SRPX2 attenuated oxygen–glucose deprivation and reperfusion-induced injury in cardiomyocytes via alleviating endoplasmic reticulum stress-induced apoptosis through targeting PI3K/Akt/mTOR axis
  101. Aquaporin-8 overexpression is involved in vascular structure and function changes in placentas of gestational diabetes mellitus patients
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  103. Effects of growth hormone on lipid metabolism and sexual development in pubertal obese male rats
  104. Cloning and identification of the CTLA-4IgV gene and functional application of vaccine in Xinjiang sheep
  105. Antitumor activity of RUNX3: Upregulation of E-cadherin and downregulation of the epithelial–mesenchymal transition in clear-cell renal cell carcinoma
  106. PHF8 promotes osteogenic differentiation of BMSCs in old rat with osteoporosis by regulating Wnt/β-catenin pathway
  107. A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis
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  109. A novel association between Bmi-1 protein expression and the SUVmax obtained by 18F-FDG PET/CT in patients with gastric adenocarcinoma
  110. The role of erythrocytes and erythroid progenitor cells in tumors
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  113. Silencing TLR4 using an ultrasound-targeted microbubble destruction-based shRNA system reduces ischemia-induced seizures in hyperglycemic rats
  114. Plant Sciences
  115. Seasonal succession of bacterial communities in cultured Caulerpa lentillifera detected by high-throughput sequencing
  116. Cloning and prokaryotic expression of WRKY48 from Caragana intermedia
  117. Novel Brassica hybrids with different resistance to Leptosphaeria maculans reveal unbalanced rDNA signal patterns
  118. Application of exogenous auxin and gibberellin regulates the bolting of lettuce (Lactuca sativa L.)
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  121. Alleviative effects of magnetic Fe3O4 nanoparticles on the physiological toxicity of 3-nitrophenol to rice (Oryza sativa L.) seedlings
  122. Selection and functional identification of Dof genes expressed in response to nitrogen in Populus simonii × Populus nigra
  123. Study on pecan seed germination influenced by seed endocarp
  124. Identification of active compounds in Ophiopogonis Radix from different geographical origins by UPLC-Q/TOF-MS combined with GC-MS approaches
  125. The entire chloroplast genome sequence of Asparagus cochinchinensis and genetic comparison to Asparagus species
  126. Genome-wide identification of MAPK family genes and their response to abiotic stresses in tea plant (Camellia sinensis)
  127. Selection and validation of reference genes for RT-qPCR analysis of different organs at various development stages in Caragana intermedia
  128. Cloning and expression analysis of SERK1 gene in Diospyros lotus
  129. Integrated metabolomic and transcriptomic profiling revealed coping mechanisms of the edible and medicinal homologous plant Plantago asiatica L. cadmium resistance
  130. A missense variant in NCF1 is associated with susceptibility to unexplained recurrent spontaneous abortion
  131. Assessment of drought tolerance indices in faba bean genotypes under different irrigation regimes
  132. The entire chloroplast genome sequence of Asparagus setaceus (Kunth) Jessop: Genome structure, gene composition, and phylogenetic analysis in Asparagaceae
  133. Food Science
  134. Dietary food additive monosodium glutamate with or without high-lipid diet induces spleen anomaly: A mechanistic approach on rat model
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  136. Potential of honey against the onset of autoimmune diabetes and its associated nephropathy, pancreatitis, and retinopathy in type 1 diabetic animal model
  137. FTO gene expression in diet-induced obesity is downregulated by Solanum fruit supplementation
  138. Physical activity enhances fecal lactobacilli in rats chronically drinking sweetened cola beverage
  139. Supercritical CO2 extraction, chemical composition, and antioxidant effects of Coreopsis tinctoria Nutt. oleoresin
  140. Functional constituents of plant-based foods boost immunity against acute and chronic disorders
  141. Effect of selenium and methods of protein extraction on the proteomic profile of Saccharomyces yeast
  142. Microbial diversity of milk ghee in southern Gansu and its effect on the formation of ghee flavor compounds
  143. Ecology and Environmental Sciences
  144. Effects of heavy metals on bacterial community surrounding Bijiashan mining area located in northwest China
  145. Microorganism community composition analysis coupling with 15N tracer experiments reveals the nitrification rate and N2O emissions in low pH soils in Southern China
  146. Genetic diversity and population structure of Cinnamomum balansae Lecomte inferred by microsatellites
  147. Preliminary screening of microplastic contamination in different marine fish species of Taif market, Saudi Arabia
  148. Plant volatile organic compounds attractive to Lygus pratensis
  149. Effects of organic materials on soil bacterial community structure in long-term continuous cropping of tomato in greenhouse
  150. Effects of soil treated fungicide fluopimomide on tomato (Solanum lycopersicum L.) disease control and plant growth
  151. Prevalence of Yersinia pestis among rodents captured in a semi-arid tropical ecosystem of south-western Zimbabwe
  152. Effects of irrigation and nitrogen fertilization on mitigating salt-induced Na+ toxicity and sustaining sea rice growth
  153. Bioengineering and Biotechnology
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  155. Development of alkaline phosphatase-scFv and its use for one-step enzyme-linked immunosorbent assay for His-tagged protein detection
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  158. Effects of chemical-based fertilizer replacement with biochar-based fertilizer on albic soil nutrient content and maize yield
  159. Genome-wide identification and expression analysis of CPP-like gene family in Triticum aestivum L. under different hormone and stress conditions
  160. Agronomic and economic performance of mung bean (Vigna radiata L.) varieties in response to rates of blended NPS fertilizer in Kindo Koysha district, Southern Ethiopia
  161. Influence of furrow irrigation regime on the yield and water consumption indicators of winter wheat based on a multi-level fuzzy comprehensive evaluation
  162. Discovery of exercise-related genes and pathway analysis based on comparative genomes of Mongolian originated Abaga and Wushen horse
  163. Lessons from integrated seasonal forecast-crop modelling in Africa: A systematic review
  164. Evolution trend of soil fertility in tobacco-planting area of Chenzhou, Hunan Province, China
  165. Animal Sciences
  166. Morphological and molecular characterization of Tatera indica Hardwicke 1807 (Rodentia: Muridae) from Pothwar, Pakistan
  167. Research on meat quality of Qianhua Mutton Merino sheep and Small-tail Han sheep
  168. SI: A Scientific Memoir
  169. Suggestions on leading an academic research laboratory group
  170. My scientific genealogy and the Toronto ACDC Laboratory, 1988–2022
  171. Erratum
  172. Erratum to “Changes of immune cells in patients with hepatocellular carcinoma treated by radiofrequency ablation and hepatectomy, a pilot study”
  173. Erratum to “A two-microRNA signature predicts the progression of male thyroid cancer”
  174. Retraction
  175. Retraction of “Lidocaine has antitumor effect on hepatocellular carcinoma via the circ_DYNC1H1/miR-520a-3p/USP14 axis”
https://doi.org/10.1515/biol-2022-0096
Keywords for this article
Ophiopogonis Radix; Maidong; UPLC-Q/TOF-MS; GC-MS; LC-MS
Creative Commons
BY 4.0

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  123. Study on pecan seed germination influenced by seed endocarp
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  125. The entire chloroplast genome sequence of Asparagus cochinchinensis and genetic comparison to Asparagus species
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  132. The entire chloroplast genome sequence of Asparagus setaceus (Kunth) Jessop: Genome structure, gene composition, and phylogenetic analysis in Asparagaceae
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  134. Dietary food additive monosodium glutamate with or without high-lipid diet induces spleen anomaly: A mechanistic approach on rat model
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  139. Supercritical CO2 extraction, chemical composition, and antioxidant effects of Coreopsis tinctoria Nutt. oleoresin
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  142. Microbial diversity of milk ghee in southern Gansu and its effect on the formation of ghee flavor compounds
  143. Ecology and Environmental Sciences
  144. Effects of heavy metals on bacterial community surrounding Bijiashan mining area located in northwest China
  145. Microorganism community composition analysis coupling with 15N tracer experiments reveals the nitrification rate and N2O emissions in low pH soils in Southern China
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  147. Preliminary screening of microplastic contamination in different marine fish species of Taif market, Saudi Arabia
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  153. Bioengineering and Biotechnology
  154. Poly-l-lysine-caused cell adhesion induces pyroptosis in THP-1 monocytes
  155. Development of alkaline phosphatase-scFv and its use for one-step enzyme-linked immunosorbent assay for His-tagged protein detection
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  160. Agronomic and economic performance of mung bean (Vigna radiata L.) varieties in response to rates of blended NPS fertilizer in Kindo Koysha district, Southern Ethiopia
  161. Influence of furrow irrigation regime on the yield and water consumption indicators of winter wheat based on a multi-level fuzzy comprehensive evaluation
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  168. SI: A Scientific Memoir
  169. Suggestions on leading an academic research laboratory group
  170. My scientific genealogy and the Toronto ACDC Laboratory, 1988–2022
  171. Erratum
  172. Erratum to “Changes of immune cells in patients with hepatocellular carcinoma treated by radiofrequency ablation and hepatectomy, a pilot study”
  173. Erratum to “A two-microRNA signature predicts the progression of male thyroid cancer”
  174. Retraction
  175. Retraction of “Lidocaine has antitumor effect on hepatocellular carcinoma via the circ_DYNC1H1/miR-520a-3p/USP14 axis”
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