厚朴中1株高产厚朴酚与和厚朴酚菌株的分离鉴定及其“发汗”工艺优化

doi:10.13560/j.cnki.biotech.bull.1985.2025-0422

摘要/Abstract

摘要：

目的为明确厚朴“发汗”过程中微生物群落与厚朴品质的相关性，探究关键微生物对厚朴中厚朴酚及和厚朴酚积累的影响机制。方法采用传统培养分离技术结合高效液相色谱分析方法，系统分离和筛选厚朴“发汗”过程中的关键功能菌株。通过分子生物学技术对目标菌株进行鉴定，并构建系统发育树分析其进化地位和亲缘关系。采用单因素试验结合Box-Behnken响应面法对菌株HP3“发汗”工艺参数进行优化。结果从“发汗”厚朴样本中分离纯化出48株菌，经筛选发现有9株能够显著提升厚朴酚与和厚朴酚产量的菌株，其中HP3菌株效果最佳，经鉴定HP3菌株为贝莱斯芽胞杆菌（Bacillus velezensis）；对HP3菌株的“发汗”工艺参数优化发现，其最佳“发汗”工艺参数为发汗温度31.84 ℃、发汗时间1.9 d、水煮时间6.37 min、干燥温度80 ℃，在此条件下，厚朴酚与和厚朴酚总量高达5.149%，较未“发汗”样品提升62.67%。结论从厚朴“发汗”过程中分离鉴定出一株菌株HP3，该菌株可显著提高厚朴“发汗”过程中厚朴酚与和厚朴酚的总含量。此外，通过响应面优化试验确定了菌株HP3的最佳“发汗”工艺条件。研究揭示了厚朴“发汗”过程中与品质密切相关的细菌类群，为厚朴药材的微生物资源开发提供了重要依据。

关键词: 厚朴, 分离鉴定, 厚朴酚, 和厚朴酚, “发汗”

Abstract:

Objective To clarify the correlation between the microbial colonies and the quality of Magnolia officinalis during the process of “sweating”, and to investigate the regulatory mechanisms of key microbial species on the biosynthesis and accumulation of magnolol and honokiol in M. officinalis. Method Traditional culture separation and HPLC were systematically employed to isolate and screen functionally critical microbial strains during the “sweating” process of M. officinalis. The target strains were identified using molecular biological techniques, and phylogenetic trees were constructed to analyze their evolutionary status and genetic relationships. The process parameters of “sweating” of strain HP3 were optimized by using single-factor experiments combined with the Box-Behnken response surface method. Result Forty-eight strains were isolated and purified from the “sweating” M. officinalis samples. Subsequent screening revealed 9 strains that significantly increased the production of magnolol and honokiol. Among these, strain HP3 presented the most pronounced efficacy and was identified as Bacillus velezensis. The optimization of the “sweating” process parameters for strain HP3 revealed the following optimal conditions: Sweating temperature 31.84 ℃, sweating time 1.9 d, boiling time 6.37 min and drying temperature 80 ℃. Under these conditions, the total amount of magnolol and honokiol was as high as 5.149%, an increase of 62.67% compared with the non-sweated samples. Conclusion A strain HP3 was isolated and identified from the “sweating” process of M. officinalis, which demonstrated remarkable capability in enhancing the total content of magnolol and honokiol. Furthermore, the optimal sweating process parameters for strain HP3 were determined through response surface optimization experiments. The study has revealed the bacterial communities closely related to the quality of M. officinalis during its “sweating” process, providing an important basis for the development of microbial resources of M. officinalis medicinal materials.

Key words: Magnolia officinalis, isolation and identification, magnolol, honokiol, “sweating”

张茹, 李一鸣, 张桐溪, 孙占斌, 任清, 潘寒姁. 厚朴中1株高产厚朴酚与和厚朴酚菌株的分离鉴定及其“发汗”工艺优化[J]. 生物技术通报, 2025, 41(8): 322-334.

ZHANG Ru, LI Yi-ming, ZHANG Tong-xi, SUN Zhan-bin, REN Qing, PAN Han-xu. Isolation and Identification of a High-yielding Magnolol and Honokiol Strain from Magnolia officinalis and Optimization of the “Sweating” Process[J]. Biotechnology Bulletin, 2025, 41(8): 322-334.

图/表 15

参考文献 35

[1]	Chen YH, Huang PH, Lin FY, et al. Magnolol: a multifunctional compound isolated from the Chinese medicinal plant Magnolia officinalis [J]. Eur J Integr Med, 2011, 3(4): e317-e324.
[2]	Kim H, Lim CY, Chung MS. Magnolia officinalis and its honokiol and magnolol constituents inhibit human norovirus surrogates [J]. Foodborne Pathog Dis, 2021, 18(1): 24-30.
[3]	国家药典委员会. 中华人民共和国药典-三部: 2020年版 [M]. 北京: 中国医药科技出版社, 2020.
	National Pharmacopoeia Commission. People's republic of China (PRC) pharmacopoeia-part III: 2020 edition [M]. Beijing: China Medical Science Press, 2020.
[4]	贾音, 任晨曦, 夏悠楠, 等. 厚朴酚的药理作用研究现状 [J]. 生物化工, 2023, 9(3): 170-174.
	Jia Y, Ren CX, Xia YN, et al. Research status of pharmacological action of magnolol [J]. Biol Chem Eng, 2023, 9(3): 170-174.
[5]	王颖, 陈文强, 邓百万, 等. 厚朴酚与和厚朴酚的药理作用及提取合成研究进展 [J]. 陕西理工大学学报: 自然科学版, 2018, 34(2): 58-64, 78.
	Wang Y, Chen WQ, Deng BW, et al. Advances in pharmacological effects, extraction and synthesis of magnolol and honokiol [J]. J Shaanxi Univ Technol Nat Sci Ed, 2018, 34(2): 58-64, 78.
[6]	Sarrica A, Kirika N, Romeo M, et al. Safety and toxicology of magnolol and honokiol [J]. Planta Med, 2018, 84(16): 1151-1164.
[7]	Xu JW, Xu H. Magnolol: chemistry and biology [J]. Ind Crops Prod, 2023, 205: 117493.
[8]	Sciacca C, Cardullo N, Pulvirenti L, et al. Evaluation of honokiol, magnolol and of a library of new nitrogenated neolignans as pancreatic lipase inhibitors [J]. Bioorg Chem, 2023, 134: 106455.
[9]	Yuan Y, Zhou XC, Wang YY, et al. Cardiovascular modulating effects of magnolol and honokiol, two polyphenolic compounds from traditional Chinese medicine-Magnolia officinalis [J]. Curr Drug Targets, 2020, 21(6): 559-572.
[10]	Ranaware AM, Banik K, Deshpande V, et al. Magnolol: a neolignan from the Magnolia family for the prevention and treatment of cancer [J]. Int J Mol Sci, 2018, 19(8): 2362.
[11]	Yu CP, Li PY, Chen SY, et al. Magnolol and honokiol inhibited the function and expression of BCRP with mechanism exploration [J]. Molecules, 2021, 26(23): 7390.
[12]	Lovecká P, Svobodová A, Macůrková A, et al. Decorative Magnolia plants: a comparison of the content of their biologically active components showing antimicrobial effects [J]. Plants, 2020, 9(7): 879.
[13]	Stefanache A, Ignat M, Peptu C, et al. Development of a prolonged-release drug delivery system with magnolol loaded in amino-functionalized mesoporous silica [J]. Appl Sci, 2017, 7(3): 237.
[14]	Konoshima T, Kozuka M, Tokuda H, et al. Studies on inhibitors of skin tumor promotion, IX. Neolignans from Magnolia officinalis [J]. J Nat Prod, 1991, 54(3): 816-822.
[15]	Wang LQ, Wang D, Yuan SZ, et al. Transcriptomic insights into the antifungal effects of magnolol on the growth and mycotoxin production of Alternaria alternata [J]. Toxins, 2020, 12(10): 665.
[16]	Cai XY, Jiang XQ, Zhao M, et al. Identification of the target protein and molecular mechanism of honokiol in anti-inflammatory action [J]. Phytomedicine, 2023, 109: 154617.
[17]	Lü JL, Zhao J, Duan JN, et al. Quality evaluation of Angelica sinensis by simultaneous determination of ten compounds using LC-PDA [J]. Chromatographia, 2009, 70(3): 455-465.
[18]	李亚霏, 杜伟锋, 姜东京, 等. 续断产地加工“发汗” 前后总皂苷及常春藤皂苷元的含量测定 [J]. 甘肃中医药大学学报, 2016, 33(2): 51-54.
	Li YF, Du WF, Jiang DJ, et al. Content determination of total saponins and hederagenin in Radix dipsaci before and after processing [J]. J Gansu Univ Chin Med, 2016, 33(2): 51-54.
[19]	刘畅, 王潇, 刘芳, 等. “发汗” 前后厚朴质量标志物的预测分析 [J]. 中国中药杂志, 2021, 46(11): 2686-2690.
	Liu C, Wang X, Liu F, et al. Q-marker prediction of Magnoliae Officinalis Cortex before and after “sweating” [J]. China J Chin Mater Med, 2021, 46(11): 2686-2690.
[20]	陈佩东, 薛露, 严辉, 等. 厚朴“发汗” 工艺的研究 [J]. 中成药, 2015, 37(11): 2469-2472.
	Chen PD, Xue L, Yan H, et al. “Fahan” technology of Magnolia officinalis [J]. Chin Tradit Pat Med, 2015, 37(11): 2469-2472.
[21]	刘芳, 卫莹芳, 胡慧玲. 厚朴“发汗”的研究现状与思考 [J]. 实用医院临床杂志, 2013, 10(3): 191-192.
	Liu F, Wei YF, Hu HL. Research states and thinking on sweating process for Magnolia officinalis [J]. Pract J Clin Med, 2013, 10(3): 191-192.
[22]	杨红兵, 詹亚华, 陈科力, 等. 发汗与去皮对厚朴中酚类成分含量的影响 [J]. 中药材, 2007, 30(1): 22-23.
	Yang HB, Zhan YH, Chen KL, et al. Effects of sweating and peeling on the content of phenolic compounds in Magnolia officinalis [J]. J Chin Med Mater, 2007, 30(1): 22-23.
[23]	余盛贤, 张春霞, 陈承瑜, 等. “发汗” 对厚朴质量的影响 [J]. 中国中药杂志, 2010, 35(14): 1831-1835.
	Yu SX, Zhang CX, Chen CY, et al. Effects of primary processing on quality of cortex Magnolia officinalis [J]. China J Chin Mater Med, 2010, 35(14): 1831-1835.
[24]	刘畅, 王潇, 刘芳, 等. 基于多指标质量差异关键属性优化厚朴产地加工“发汗”工艺 [J]. 中草药, 2021, 52(3): 677-684.
	Liu C, Wang X, Liu F, et al. Optimization of “sweating” process in producing area for Magnoliae Officinalis Cortex based on multi-index determinant attributes of quality difference [J]. Chin Tradit Herb Drugs, 2021, 52(3): 677-684.
[25]	朱林峰, 张媛, 冯紫薇, 等. “发汗”对厚朴药材质量影响的研究及其工艺的建立 [J]. 中国现代中药, 2019, 21(11): 1551-1556, 1563.
	Zhu LF, Zhang Y, Feng ZW, et al. Effect of primary processing method “Sweating” on quality of cortex magnoliae officinals [J]. Mod Chin Med, 2019, 21(11): 1551-1556, 1563.
[26]	Wu Q, Wei D, Dong LL, et al. Variation in the microbial community contributes to the improvement of the main active compounds of Magnolia officinalis Rehd. et Wils in the process of sweating [J]. Chin Med, 2019, 14: 45.
[27]	朱兴龙, 卢丽洁, 吴清华, 等. 基于成分变化研究厚朴“发汗”过程中颜色与酶促反应的关系 [J]. 中国中药杂志, 2022, 47(5): 1262-1272.
	Zhu XL, Lu LJ, Wu QH, et al. Composition changes reveal relationship between color and enzymaticreaction of Magnoliae Officinalis Cortex during “sweating” process [J]. China J Chin Mater Med, 2022, 47(5): 1262-1272.
[28]	李玉平, 严春兰, 骆进程, 等. 中药厚朴发汗过程中微生物群落结构及特征的分析 [J]. 云南中医中药杂志, 2022, 43(7):78-84.
	Li YP, Yan CL, Luo JC, et al. Analysis of the Microbial Community structure and Characteristics during the Sweating Process of the Traditional Chinese medicine Magnolia Officinalis [J]. Yunnan Journal of Traditional Chinese Medicine and Materia Medica, 2022, 43(7):78-84.
[29]	张佳旭, 黄成凤, 朱兴龙, 等. 基于CRITIC结合Box-Behnken响应面法的厚朴产地趁鲜加工与炮制一体化工艺研究 [J]. 中草药, 2023, 54(17): 5560-5567.
	Zhang JX, Huang CF, Zhu XL, et al. Research on integration of fresh processing and processing process of Magnolia officinalis origin based on CRITIC combined with Box-Behnken responsesurface method [J]. Chin Tradit Herb Drugs, 2023, 54(17): 5560-5567.
[30]	陈茹, 陈成, 杨兴鑫, 等. 中药“发汗”炮制法的现代研究进展 [J]. 中草药, 2018, 49(2): 489-493.
	Chen R, Chen C, Yang XX, et al. Modern research progress of Chinese materia Medica diaphoretic processing method [J]. Chin Tradit Herb Drugs, 2018, 49(2): 489-493.
[31]	王晓宇, 张松林, 王颖, 等. 基于高通量测序中江丹参“发汗”过程中优势微生物群落与主要药效成分相关性研究 [J]. 中草药, 2024, 55(2): 420-433.
	Wang XY, Zhang SL, Wang Y, et al. Correlation between dominant microbial communities and major medicinal compositions in Salvia miltiorrhiza from Zhongjiang processed by “sweating” based on high-throughput sequencing [J]. Chin Tradit Herb Drugs, 2024, 55(2): 420-433.
[32]	周旭香, 田家瑛, 陈漂洋, 等. 基于“饮片-标准汤剂-药效”探讨“发汗”对茯苓质量的影响 [J]. 中草药, 2025, 56(7): 2330-2343.
	Zhou XX, Tian JY, Chen PY, et al. Exploring effect of “sweating” on quality of Poria based on “decoction piecestandard decoction-efficacy” [J]. Chin Tradit Herb Drugs, 2025, 56(7): 2330-2343.
[33]	魏担, 吴清华, 刘钰萍, 等. 基于高通量测序研究厚朴“发汗” 过程中微生物群落多样性及其特征 [J]. 中国中药杂志, 2019, 44(24): 5405-5412.
	Wei D, Wu QH, Liu YP, et al. Microbial community diversity and its characteristics in Magnolia Officinalis Cortex “sweating” process based on high-throughput sequencing [J]. China J Chin Mater Med, 2019, 44(24): 5405-5412.
[34]	Shi XD, Yang LS, Gao JH, et al. Deep sequencing of Magnoliae officinalis reveals upstream genes related to the lignan biosynthetic pathway [J]. J For Res, 2017, 28(4): 671-681.
[35]	Yang Y, Li ZH, Zong H, et al. Identification and validation of magnolol biosynthesis genes in Magnolia officinalis [J]. Molecules, 2024, 29(3): 587.

属 Genus	筛选培养基 Screening medium	稀释梯度 Dilution gradient	数量 Number
Bordetella（鲍特氏菌属）	TSA	10^-3	1
Alcaligenes（产碱杆菌属）	TSA/BHI	10^-4/10^-5	4
Brevundimonas（短波单胞菌属）	TSA/BHI	10^-4/10^-5	3
Brucella（布鲁氏菌属）	TSA	10^-4	1
Stenotrophomonas（黄单胞菌属）	NA/TSA/BHI/R₂A	10^-4/10^-5	5
Acinetobacter（不动杆菌属）	NA/TSA/BHI/R₂A	10^-4/10^-5	4
Pseudomonas（假单胞菌属）	NA/BHI	10^-4	3
Enterobacter（肠杆菌属）	R₂A	10^-4	1
Klebsiella（克雷伯氏菌属）	R₂A	10^-4/10^-5/10^-6	4
Leclercia（勒克氏菌属）	NA	10^-4	1
Curtobacterium（短小杆菌属）	NA/TSA	10^-4/10^-5	3
Georgenia（乔治菌属）	NA/TSA/BHI	10^-3/10^-4/10^-5	5
Brevibacterium（短杆菌属）	NA/TSA/BHI	10^-3/10^-4/10^-5	4
Streptomyces（链霉菌属）	TSA	10^-4	1
Chryseobacterium（金黄杆菌属）	NA	10^-4	1
Staphylococcus（葡萄球菌属）	NA	10^-4	1
Lysinibacillus（赖氨酸芽胞杆菌属）	NA/TSA	10^-4	2
Sporosarcina（八叠球菌属）	TSA	10^-4	1
Oceanobacillus（大洋芽胞杆菌属）	TSA	10^-5	1
Bacillus（芽胞杆菌属）	TSA/BHI	10^-3	2

属 Genus	筛选培养基 Screening medium	稀释梯度 Dilution gradient	数量 Number
Bordetella（鲍特氏菌属）	TSA	10^-3	1
Alcaligenes（产碱杆菌属）	TSA/BHI	10^-4/10^-5	4
Brevundimonas（短波单胞菌属）	TSA/BHI	10^-4/10^-5	3
Brucella（布鲁氏菌属）	TSA	10^-4	1
Stenotrophomonas（黄单胞菌属）	NA/TSA/BHI/R₂A	10^-4/10^-5	5
Acinetobacter（不动杆菌属）	NA/TSA/BHI/R₂A	10^-4/10^-5	4
Pseudomonas（假单胞菌属）	NA/BHI	10^-4	3
Enterobacter（肠杆菌属）	R₂A	10^-4	1
Klebsiella（克雷伯氏菌属）	R₂A	10^-4/10^-5/10^-6	4
Leclercia（勒克氏菌属）	NA	10^-4	1
Curtobacterium（短小杆菌属）	NA/TSA	10^-4/10^-5	3
Georgenia（乔治菌属）	NA/TSA/BHI	10^-3/10^-4/10^-5	5
Brevibacterium（短杆菌属）	NA/TSA/BHI	10^-3/10^-4/10^-5	4
Streptomyces（链霉菌属）	TSA	10^-4	1
Chryseobacterium（金黄杆菌属）	NA	10^-4	1
Staphylococcus（葡萄球菌属）	NA	10^-4	1
Lysinibacillus（赖氨酸芽胞杆菌属）	NA/TSA	10^-4	2
Sporosarcina（八叠球菌属）	TSA	10^-4	1
Oceanobacillus（大洋芽胞杆菌属）	TSA	10^-5	1
Bacillus（芽胞杆菌属）	TSA/BHI	10^-3	2

来源 Source	离差平方和 Sum of squared	自由度 Freedom	均方 Mean	F值 F value	P值 P value	显著性 Significance
模型 Model	9.55	14	0.682 4	5.39	0.002 9	Significant
A	0.655 5	1	0.655 5	5.17	0.042 1	Significant
B	0.922 5	1	0.922 5	7.28	0.019 4	Significant
C	1.16	1	1.160	9.12	0.010 7	Significant
D	0.307 2	1	0.307 2	2.42	0.145 5
AB	0.032 1	1	0.032 1	0.253 6	0.623 7
AC	0.002 5	1	0.002 5	0.019 7	0.890 6
AD	0.072 1	1	0.072 1	0.568 7	0.465 3
BC	0.126 9	1	0.126 9	1.00	0.336 7
BD	0.359 4	1	0.359 4	2.84	0.118 0
CD	0.828 3	1	0.828 3	6.54	0.025 2	Significant
A²	3.19	1	3.190	25.13	0.000 3	Significant
B²	3.51	1	3.510	27.67	0.000 2	Significant
C²	0.899 5	1	0.899 5	7.10	0.020 6	Significant
D²	0.312 9	1	0.312 9	2.47	0.142 1
残差 Residual	1.52	12	0.126 7
失拟项 Lack of fit	1.17	10	0.117 1	0.670 2	0.729 0	Non-significant
纯误差 Pure error	0.349 5	2	0.174 8
总和 Total sum	11.07	26
R²=0.862 7

来源 Source	离差平方和 Sum of squared	自由度 Freedom	均方 Mean	F值 F value	P值 P value	显著性 Significance
模型 Model	9.55	14	0.682 4	5.39	0.002 9	Significant
A	0.655 5	1	0.655 5	5.17	0.042 1	Significant
B	0.922 5	1	0.922 5	7.28	0.019 4	Significant
C	1.16	1	1.160	9.12	0.010 7	Significant
D	0.307 2	1	0.307 2	2.42	0.145 5
AB	0.032 1	1	0.032 1	0.253 6	0.623 7
AC	0.002 5	1	0.002 5	0.019 7	0.890 6
AD	0.072 1	1	0.072 1	0.568 7	0.465 3
BC	0.126 9	1	0.126 9	1.00	0.336 7
BD	0.359 4	1	0.359 4	2.84	0.118 0
CD	0.828 3	1	0.828 3	6.54	0.025 2	Significant
A²	3.19	1	3.190	25.13	0.000 3	Significant
B²	3.51	1	3.510	27.67	0.000 2	Significant
C²	0.899 5	1	0.899 5	7.10	0.020 6	Significant
D²	0.312 9	1	0.312 9	2.47	0.142 1
残差 Residual	1.52	12	0.126 7
失拟项 Lack of fit	1.17	10	0.117 1	0.670 2	0.729 0	Non-significant
纯误差 Pure error	0.349 5	2	0.174 8
总和 Total sum	11.07	26
R²=0.862 7