马鲛鱼抗氧化肽的纳流液相色谱法分离与筛选

doi:10.3724/SP.J.1123.2020.04019

摘要/Abstract

摘要：

在海洋天然产物中,马鲛鱼是一种重要的高活性抗氧化肽生物源,具有极高的加工附加值。由于鱼体组织的复杂性,活性抗氧化肽成分的提取和筛选对样品制备和分离技术提出了挑战。使用不同蛋白酶对鱼体组织进行酶解时,所获得的活性肽结构及功能活性会有显著的差别。为了获得高活性的抗氧化肽,该研究分别考察了风味蛋白酶、胰蛋白酶、酸性蛋白酶、中性蛋白酶、碱性蛋白酶5种蛋白酶的酶解效果。以二苯代苦味肼基自由基(DPPH·)、羟自由基(·OH)清除率和水解度(DH)为指标,筛选最优水解酶。结果表明,胰蛋白酶酶解液清除DPPH·和·OH能力最强,清除率分别达到88.93%±0.82%和53.09%±0.73%。在单因素试验的基础上,以DPPH·清除率为响应值,以加酶量、酶解温度和时间为函数,进行了三因素三水平响应面试验,获得水解度23.66%、DPPH·清除率93.78%以及·OH清除率62.59%的最优制备条件。纳流液相色谱具有低样品量、低溶剂消耗和高效等优势。为筛选出适合于马鲛鱼内脏抗氧化肽分离分析的固定相,该研究使用1∶1000分流比的纳流液相平台,分别使用反相C18柱(15 cm×100 μm, 5 μm, 30 nm)和强阳离子交换柱(15 cm×100 μm, 5 μm, 100 nm)进行分离,收集、冻干并评测了各组分的抗氧化能力。结果表明,强阳离子交换固定相更适合于马鲛鱼内脏抗氧化肽的分离纯化,并筛选出1个强活性抗氧化肽组分。该组分DPPH·清除力的半抑制浓度(IC₅₀)为0.672±0.051 mg/mL,与纯化前相比提高了13.6倍。该研究报道了纳流液相色谱在海洋天然产物源抗氧化肽分离分析中的应用,并证明了其在活性抗氧化肽成分筛选中的有效性和良好的应用前景。

关键词: 纳流液相色谱, 抗氧化肽, 马鲛鱼, 海洋天然产物

Abstract:

As a rich source of high activity antioxidant peptides, Scomberomorus niphonius is a key marine natural product with a high processing value. Due to the high complexity of fish tissues, high recovery extraction and high efficiency screening of the active antioxidant peptide species have become the major challenges for the research and development of preparation and separation techniques. Due to the high specificity of hydrolytic enzymes, when different types of enzymes are used for the hydrolysis of fish tissues, the resultant active peptides may have significant differences in chemical structures, biological functions, and physical activities. In this study, in order to obtain antioxidant peptides with high activity and functionality, defatted visceral powder of Scomberomorus niphonius was used as a raw material for sample preparation. Five hydrolytic enzymes (flavor protease, trypsin, acid protease, neutral protease, and alkaline protease) were selected and investigated for their hydrolyzing efficiencies in visceral solutions of Scomberomorus niphonius, according to their optimum hydrolyzing conditions. The diphenyl bitter hydrazine radical (DPPH·) scavenging rate, hydroxyl radical (·OH) scavenging rate, and degree of hydrolysis (DH) were adopted as indicators for hydrolytic enzyme selection and optimization. The data suggested that, among all the hydrolytic enzymes investigated, trypsin presented the best scavenging capabilities for both DPPH· and ·OH species, with scavenging rates of 88.93%±0.82% for DPPH· and 53.09%±0.73% for ·OH, respectively. Based on the single-factor test results, the DPPH· scavenging rate was further utilized as an indicator and was found to depend on the hydrolytic enzyme quantity, hydrolyzation temperature, and hydrolyzation time. According to the Box-Behnken center composed experimental design, a triple factor and triple level response surface method was adopted for further optimization of antioxidant peptide preparation from Scomberomorus niphonius viscera. The preparation method was systematically optimized, and as a result, a degree of hydrolysis of 23.66%, DPPH· scavenging rate of 93.78%, and ·OH scavenging rate of 62.59% were achieved. High performance nano flow liquid chromatography is a new generation micro scale liquid phase separation technique that has the advantages of low sample requirement, low solvent consumption, and high efficiency. In this study, we applied this method to marine natural product purification. In order to screen the most suitable chromatographic stationary phase for the separation and analysis of active antioxidant peptides from Scomberomorus niphonius viscera, a nano flow reversed-phase C18 column (15 cm×100 μm, 5 μm, 30 nm) and a strong cation exchange column (15 cm×100 μm, 5 μm, 100 nm) were investigated. A nano flow high performance liquid chromatography platform with a 1∶1000 splitting ratio was adopted for this study. Using the enzyme-hydrolyzed solution from Scomberomorus niphonius viscera as the sample, following filtration, the antioxidant peptides were separated, collected, freeze-dried, and finally tested for their antioxidant capability. The results showed that the strong cation exchange phase was more suitable for antioxidant peptide isolation and purification from Scomberomorus niphonius viscera, and an antioxidant peptide component with high activity was successfully screened. During the activity test, the 50% inhibition concentration (IC₅₀) value of the DPPH· scavenging capability of this peptide was 0.672±0.051 mg/mL, which was 13.6 times higher than the activity value before the peptide species was purified. The current study for the first time reports the application of high performance nano flow liquid chromatography in the purification and analysis of antioxidant peptides from a marine natural product source and also demonstrates the effectiveness and future prospect of the use of nano flow ion exchange chromatography for high performance separation and high efficiency screening of antioxidant peptides.

Key words: nano flow liquid chromatography, antioxidant peptides, Scomberomorus niphonius, marine natural product

中图分类号:

O658

薛雅茹, 郭睿, 张博. 马鲛鱼抗氧化肽的纳流液相色谱法分离与筛选[J]. 色谱, 2020, 38(12): 1431-1439.

XUE Yaru, GUO Rui, ZHANG Bo. Separation and screening of antioxidant peptides from Scomberomorus niphonius based on nano flow liquid chromatography[J]. Chinese Journal of Chromatography, 2020, 38(12): 1431-1439.

图/表 12

表 1 蛋白酶的水解条件

Table 1 Hydrolysis conditions of various proteases

Type of enzyme	Enzyme activity/(u/g)	Temperature/ ℃	pH	Time/ h
Flavor protease	15000	50	7	8
Trypsin	250000^*	37	7	8
Acid protease	800000	50	3	8
Neutral protease	200000	50	7	8
Alkaline protease	200000	50	8	8

表 2 响应面分析试验的因素和水平

Table 2 Factors and levels of response surface analysis

Level	Factors
Level	A(Addition of enzyme/%)	B(Hydrolysis temperature/ ℃)	C(Hydrolysis time/h)
-1	0.2	35	2.0
0	0.4	40	2.5
1	0.6	45	3.0

图 1 不同蛋白酶对酶解液水解度、DPPH·清除率和·OH清除率的影响(n=3)

Fig. 1 Effect of various proteases on degree of hydrolysis, DPPH· and ·OH scavenging ability (n=3)

表 4 回归方程模型的方差分析

Table 4 Analysis of variance for regression equation model

Source	Sum of squares	df	Mean square	F value	p-value (Prob>F)	Significance
Model	220.21	9	24.47	77.59	<0.0001	**
A	9.22	1	9.22	29.25	0.001	**
B	8	1	8	25.37	0.0015	**
C	2.11	1	2.11	6.7	0.0361	*
AB	4.35	1	4.35	13.79	0.0075	**
AC	1.04	1	1.04	3.3	0.1122
BC	14.18	1	14.18	44.95	0.0003	**
A²	59.65	1	59.65	189.17	<0.0001
B²	84.94	1	84.94	269.36	<0.0001
C²	19.45	1	19.45	61.66	0.0001
Residual	2.21	7	0.32
Lack of fit	1.27	3	0.42	1.79	0.2879
Pure error	0.94	4	0.24
Cor total	222.41	16

表 3 Box-Behnken试验设计及结果

Table 3 Design and results of Box-Behnken test

Test	A	B	C	Y(DPPH· scavenging ability/%)
1	0.2	35	2.5	84.73
2	0.6	35	2.5	85.16
3	0.2	45	2.5	88.91
4	0.6	45	2.5	85.17
5	0.2	40	2	88.94
6	0.6	40	2	87.32
7	0.2	40	3	90.37
8	0.6	40	3	86.71
9	0.4	35	2	83.95
10	0.4	45	2	89.62
11	0.4	35	3	89.36
12	0.4	45	3	87.50
13	0.4	40	2.5	94.04
14	0.4	40	2.5	93.71
15	0.4	40	2.5	94.51
16	0.4	40	2.5	94.03
17	0.4	40	2.5	94.95

图 2 加酶量和酶解温度对DPPH·清除率交互影响的响应面和等高线

Fig. 2 Surface and contour plots of influence for the addition of enzyme and hydrolysis temperature against DPPH· scavenging ability

图 3 加酶量和酶解时间对DPPH·清除率交互影响的响应面和等高线

Fig. 3 Surface and contour plots of influence for the addition of enzyme and hydrolysis time against DPPH· scavenging ability

图 4 酶解温度和酶解时间对DPPH·清除率交互影响的响应面和等高线

Fig. 4 Surface and contour plots of influence for hydrolysis temperature and hydrolysis time against DPPH· scavenging ability

图 5 C18柱分离APS的高效纳流液相色谱图

Fig. 5 nano-HPLC chromatogram of APS using C18 column Mobile phase: 60% ACN; flow rate: 0.6 mL/min; split ratio: 1∶1000; chromatographic column: C18, 15 cm×100 μm, 5 μm, 30 nm.

图 6 SCX固定相分离APS的高效纳流液相色谱图

Fig. 6 Nano-HPLC chromatogram of APS using SCX stationary phase Mobile phase: 60% ACN; flow rate: 0.6 mL/min; split ratio: 1∶1000; chromatographic column: SCX, 15 cm×100 μm, 5 μm, 100 nm.

图 7 C18固定相分离后各组分的DPPH·清除力

Fig. 7 DPPH· scavenging activity of fractions obtained on C18 column The letters indicate significant difference at 0.05 level (data=mean±standard, n=3).

图 8 SCX柱分离后各组分的DPPH·清除力

Fig. 8 DPPH· scavenging activity of fractions obtained on SCX column The letters indicate significant difference at 0.05 level (data=mean±standard, n=3).

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