Article(id=1308840428888228159, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308840287129141340, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2025-1144, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1758729600000, receivedDateStr=2025-09-25, revisedDate=1767628800000, revisedDateStr=2026-01-06, acceptedDate=null, acceptedDateStr=null, onlineDate=1789981475326, onlineDateStr=2026-09-21, pubDate=1775923200000, pubDateStr=2026-04-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789981475326, onlineIssueDateStr=2026-09-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789981475326, creator=13701087609, updateTime=1789981475326, updator=13701087609, issue=Issue{id=1308840287129141340, tenantId=1146029695717560320, journalId=1189982191388893191, year='2026', volume='61', issue='4', pageStart='1001', pageEnd='1434', issueExtLink='null', onlineDate='null', pubDate='1775923200000', pubDateStr='2026-04-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789981441528, creator='13701087609', updateTime=1789984228828, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308851977992368434, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308840287129141340, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308851977992368435, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308840287129141340, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1408, endPage=1417, ext={EN=ArticleExt(id=1308840429085360448, articleId=1308840428888228159, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Correlation between secondary metabolite accumulation and rhizosphere soil microenvironment of turmeric from major production areas of Sichuan province via non-targeted metabolomics and metagenomics, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

The rhizosphere soil microenvironment critically influences secondary metabolite accumulation in medicinal rhizomatous plants. To compare the effects of the rhizosphere soil microenvironment in major production areas of Sichuan province on the accumulation of secondary metabolites in turmeric, we collected turmeric from Qianwei, Shuangliu, and Xingwen production areas in Sichuan province as research subjects. UPLC-Q-TOF-MS-based metabolomics was employed to analyze the composition of metabolites. And the high-throughput sequencing platform was utilized to analyze the rhizosphere soil microbial community structure. Then correlation analyses were performed between the metabolites, microbial community, and physicochemical factors. The results indicated that the metabolite profiles of turmeric from different production areas are relatively similar. The most abundant secondary metabolites in plants include ketones, aldehydes, esters, terpenoids, flavonoids, and polyphenols. Polyphenols, terpenoids, and some curcuminoids were significantly higher in turmeric from Shuangliu region than in samples from Qianwei and Xingwen. Significant differences were observed in rhizosphere soil physicochemical properties, including pH, organic matter, total nitrogen, available phosphorus, available potassium, manganese, magnesium, calcium, copper, and selenium among the different regions. At the phylum level, Proteobacteria and Acidobacteria were the dominant bacterial phyla across all three regions, while considerable variations existed at the genus level. In turmeric, correlation analysis revealed that bisdemethoxycurcumin correlated positively with pH, manganese, magnesium, and calcium. ar-Turmerone correlated positively with organic matter and available phosphorus. And tetrahydrocurcumin correlated positively with Rhodanobacter and Sphingomonas. In summary, secondary metabolites differed between turmeric from different regions. These metabolites exhibited correlations with both the physicochemical properties of the rhizosphere soil and the associated microbial communities. These findings provide a scientific basis for cultivation base selection and ecosystem-based cultivation practices.

, authors=Wei-wei TIAN1, Li LIU2, An-qi ZENG1, Ping CHEN1, Qian-hua YUE1, Dong-mei YU2, Xue CHEN2, Hua HUA2, *, Jun-ning ZHAO2, 3, *, authorsList=Wei-wei TIAN, Li LIU, An-qi ZENG, Ping CHEN, Qian-hua YUE, Dong-mei YU, Xue CHEN, Hua HUA, Jun-ning ZHAO, authorCompany=null, correspAuthors=Hua HUA, Jun-ning ZHAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2026 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308840431866184013, articleId=1308840428888228159, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于非靶向代谢组学和宏基因组学探究四川主产区姜黄次生代谢产物累积差异-根际土壤微环境变化相关性, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

根际土壤微环境对根茎类药材的次生代谢产物积累尤为重要。为比较四川主产区根际土壤微环境对姜黄次生代谢产物积累的影响, 以四川犍为、双流、兴文产区的姜黄为研究对象, 采用UPLC-Q-TOF-MS代谢组学技术检测其代谢产物种类及含量, 运用高通量测序技术分析根际土壤微生物群落结构, 并对代谢产物和微生物群落、理化因子进行相关性分析。结果表明, 不同产区姜黄代谢产物种类较为接近, 酮、醛、酯类, 萜类, 黄酮和多酚是含量最丰富的次级代谢产物; 双流产区姜黄中多酚和萜类物质显著高于犍为和兴文, 部分姜黄素类成分差异显著。不同产区根际土壤pH、有机质、全氮、有效磷、速效钾、锰、镁、钙、铜、硒等理化因子具有显著性差异; 3个产区的优势菌群在门水平上均为变形菌门和酸杆菌门, 属水平差异较大。相关性分析结果表明, 姜黄的双去甲氧基姜黄素与pH、锰、镁、钙显著正相关, 芳姜黄酮与有机质、有效磷显著正相关, 四氢姜黄素与Rhodanobacter、Sphingomonas显著正相关。综上所述, 不同产区姜黄次生代谢产物存在差异, 根际土壤理化因子、微生物群落与次级代谢产物均有一定的相关性, 可为后期种植基地选择、生态种植等提供科学依据。

, authors=田韦韦1, 刘俐2, 曾安琪1, 陈平1, 岳倩华1, 余东梅2, 陈雪2, 华桦2, *, 赵军宁2, 3, *, authorsList=田韦韦, 刘俐, 曾安琪, 陈平, 岳倩华, 余东梅, 陈雪, 华桦, 赵军宁, authorCompany=null, correspAuthors=华桦, 赵军宁, authorNote=

作者贡献:

田韦韦负责实验设计、样本采集、数据分析、图表制作和论文撰写; 刘俐和曾安琪协助样本采集和论文撰写; 陈平和岳倩华参与数据分析; 余东梅和陈雪参与图表制作; 赵军宁和华桦指导论文撰写及修改。

, correspAuthorsNote=
华桦, E-mail:
赵军宁, E-mail:
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A: QWJH vs SLJH KEGG enrichment plot; B: QWJH vs XWJH KEGG enrichment plot; C: SLJH vs XWJH KEGG enrichment plot, figureFileSmall=YprrTlfHo6DClB71v6VRgg==, figureFileBig=Y+YPxq2utxU25H52fiTG5Q==, tableContent=null), ArticleFig(id=1308840437973090711, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1308840428888228159, language=EN, label=null, caption=null, figureFileSmall=q660OQ7lBKLj2jVCmB7ZtA==, figureFileBig=UoFHlQqIloi6gLSHsQT46w==, tableContent=null), ArticleFig(id=1308840438048588184, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1308840428888228159, language=CN, label=Fig.4, caption=Soil physicochemical properties of turmeric in major production areas of Sichuan. A: pH; B: Organic matter; C: Total nitrogen; D: Available phosphorus; E: Available potassium; F: Manganese; G: Magnesium; H: Calcium; I: Copper; J: Selenium. n = 3, x ± s. **P < 0.01, ***P < 0.001, figureFileSmall=q660OQ7lBKLj2jVCmB7ZtA==, figureFileBig=UoFHlQqIloi6gLSHsQT46w==, tableContent=null), ArticleFig(id=1308840438119891353, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1308840428888228159, language=EN, label=null, caption=null, figureFileSmall=4amyqg9xFackoMj1JmJcqw==, figureFileBig=J5kdfh4FTRTJ+uGR1iCApg==, tableContent=null), ArticleFig(id=1308840438191194522, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1308840428888228159, language=CN, label=Fig.5, caption=Analysis of soil metagenomes of turmeric in major production areas of Sichuan. 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基于非靶向代谢组学和宏基因组学探究四川主产区姜黄次生代谢产物累积差异-根际土壤微环境变化相关性
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田韦韦 1 , 刘俐 2 , 曾安琪 1 , 陈平 1 , 岳倩华 1 , 余东梅 2 , 陈雪 2 , 华桦 2, * , 赵军宁 2, 3, *
药学学报 | 研究论文 2026,61(4): 1408-1417
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药学学报 |研究论文 2026 , 61 (4) : 1408 -1417
基于非靶向代谢组学和宏基因组学探究四川主产区姜黄次生代谢产物累积差异-根际土壤微环境变化相关性
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田韦韦1, 刘俐2, 曾安琪1, 陈平1, 岳倩华1, 余东梅2, 陈雪2, 华桦2, * , 赵军宁2, 3, *
作者信息
  • 1四川省中医药科学院, 中医药转化医学四川省重点实验室, 四川 成都 610041
  • 2四川省中医药转化医学中心, 国家中医药管理局中药质量生物学评价重点研究室, 中医药转化医学四川省重点实验室, 四川 成都 610041
  • 3国家纳米科学中心, 中国科学院纳米生物效应与安全性实验室, 北京 100190
通讯作者:
华桦, E-mail:
赵军宁, E-mail:
作者简介:

作者贡献:

田韦韦负责实验设计、样本采集、数据分析、图表制作和论文撰写; 刘俐和曾安琪协助样本采集和论文撰写; 陈平和岳倩华参与数据分析; 余东梅和陈雪参与图表制作; 赵军宁和华桦指导论文撰写及修改。

Correlation between secondary metabolite accumulation and rhizosphere soil microenvironment of turmeric from major production areas of Sichuan province via non-targeted metabolomics and metagenomics
Wei-wei TIAN1, Li LIU2, An-qi ZENG1, Ping CHEN1, Qian-hua YUE1, Dong-mei YU2, Xue CHEN2, Hua HUA2, * , Jun-ning ZHAO2, 3, *
Affiliations
  • 1Sichuan Academy of Chinese Medical Sciences, Translational Chinese Medicine Key Laboratory of Sichuan Province, Chengdu 610041, China
  • 2Biological Evaluation of TCM Quality of the State Administration of Traditional Chinese Medicine, Translational Chinese Medicine Key Laboratory of Sichuan Province, Sichuan Institute for Translational Chinese Medicine, Chengdu 610041, China
  • 3Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Chinese Academy of Sciences, National Center for Nanoscience and Technology, Beijing 100190, China
出版时间: 2026-04-12 doi: 10.16438/j.0513-4870.2025-1144
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根际土壤微环境对根茎类药材的次生代谢产物积累尤为重要。为比较四川主产区根际土壤微环境对姜黄次生代谢产物积累的影响, 以四川犍为、双流、兴文产区的姜黄为研究对象, 采用UPLC-Q-TOF-MS代谢组学技术检测其代谢产物种类及含量, 运用高通量测序技术分析根际土壤微生物群落结构, 并对代谢产物和微生物群落、理化因子进行相关性分析。结果表明, 不同产区姜黄代谢产物种类较为接近, 酮、醛、酯类, 萜类, 黄酮和多酚是含量最丰富的次级代谢产物; 双流产区姜黄中多酚和萜类物质显著高于犍为和兴文, 部分姜黄素类成分差异显著。不同产区根际土壤pH、有机质、全氮、有效磷、速效钾、锰、镁、钙、铜、硒等理化因子具有显著性差异; 3个产区的优势菌群在门水平上均为变形菌门和酸杆菌门, 属水平差异较大。相关性分析结果表明, 姜黄的双去甲氧基姜黄素与pH、锰、镁、钙显著正相关, 芳姜黄酮与有机质、有效磷显著正相关, 四氢姜黄素与Rhodanobacter、Sphingomonas显著正相关。综上所述, 不同产区姜黄次生代谢产物存在差异, 根际土壤理化因子、微生物群落与次级代谢产物均有一定的相关性, 可为后期种植基地选择、生态种植等提供科学依据。

姜黄  /  四川主产区  /  非靶向代谢组学  /  理化因子  /  微生物群落  /  相关性

The rhizosphere soil microenvironment critically influences secondary metabolite accumulation in medicinal rhizomatous plants. To compare the effects of the rhizosphere soil microenvironment in major production areas of Sichuan province on the accumulation of secondary metabolites in turmeric, we collected turmeric from Qianwei, Shuangliu, and Xingwen production areas in Sichuan province as research subjects. UPLC-Q-TOF-MS-based metabolomics was employed to analyze the composition of metabolites. And the high-throughput sequencing platform was utilized to analyze the rhizosphere soil microbial community structure. Then correlation analyses were performed between the metabolites, microbial community, and physicochemical factors. The results indicated that the metabolite profiles of turmeric from different production areas are relatively similar. The most abundant secondary metabolites in plants include ketones, aldehydes, esters, terpenoids, flavonoids, and polyphenols. Polyphenols, terpenoids, and some curcuminoids were significantly higher in turmeric from Shuangliu region than in samples from Qianwei and Xingwen. Significant differences were observed in rhizosphere soil physicochemical properties, including pH, organic matter, total nitrogen, available phosphorus, available potassium, manganese, magnesium, calcium, copper, and selenium among the different regions. At the phylum level, Proteobacteria and Acidobacteria were the dominant bacterial phyla across all three regions, while considerable variations existed at the genus level. In turmeric, correlation analysis revealed that bisdemethoxycurcumin correlated positively with pH, manganese, magnesium, and calcium. ar-Turmerone correlated positively with organic matter and available phosphorus. And tetrahydrocurcumin correlated positively with Rhodanobacter and Sphingomonas. In summary, secondary metabolites differed between turmeric from different regions. These metabolites exhibited correlations with both the physicochemical properties of the rhizosphere soil and the associated microbial communities. These findings provide a scientific basis for cultivation base selection and ecosystem-based cultivation practices.

turmeric  /  major production areas of Sichuan province  /  non-targeted metabolomics  /  physicochemical factor  /  microbial community  /  correlation
田韦韦, 刘俐, 曾安琪, 陈平, 岳倩华, 余东梅, 陈雪, 华桦, 赵军宁. 基于非靶向代谢组学和宏基因组学探究四川主产区姜黄次生代谢产物累积差异-根际土壤微环境变化相关性. 药学学报, 2026 , 61 (4) : 1408 -1417 . DOI: 10.16438/j.0513-4870.2025-1144
Wei-wei TIAN, Li LIU, An-qi ZENG, Ping CHEN, Qian-hua YUE, Dong-mei YU, Xue CHEN, Hua HUA, Jun-ning ZHAO. Correlation between secondary metabolite accumulation and rhizosphere soil microenvironment of turmeric from major production areas of Sichuan province via non-targeted metabolomics and metagenomics[J]. Acta Pharmaceutica Sinica, 2026 , 61 (4) : 1408 -1417 . DOI: 10.16438/j.0513-4870.2025-1144
姜黄(Curcuma longa L.)为姜科姜黄属多年生草本植物, 以其干燥根茎和干燥块根入药, 其中干燥根茎为药材“姜黄”, 干燥块根为药材“黄丝郁金”[1]。《图经本草》曰: “姜黄, 旧不载所出州郡, 今江、广、蜀川多有之”, 《本草乘雅半偈》言: “原从大秦国, 及西戎来, 今蜀地、广南、江西州郡亦有, 不及蜀中者佳”, 表明四川自古以来便是姜黄的道地产区。四川省乐山市犍为县为姜黄道地产区, 也是其主产区, 年产量占全国姜黄总量的60%左右, 被列入国际标准《ISO 9299: 2024 Traditional Chinese medicine-Curcuma longa rhizome》质量检测标样的重要基地[2]。此外, 四川省成都市金马河、羊马河流域的双流、崇州地区以及四川省宜宾市兴文县亦为姜黄产区。根据《中华人民共和国药典》2020年版一部, 姜黄以干燥根茎入药, 具有破血行气、通经止痛的功效, 用于胸胁刺痛、胸痹心痛、痛经经闭、癥痕、风湿肩臂疼痛、跌扑肿痛[3]。现代研究表明, 姜黄素类物质和萜类物质是姜黄的主要活性成分, 在其品质评价和临床疗效中起着重要作用[4, 5]。
在长期用药实践中, 历代医药学家很早就意识到土地对药材品质的影响。《神农本草经》谓: “土地所出, 真伪陈新, 并各有法”, 《新修本草》称: “离其本土, 则质同而效异”, 《备急千金要方》云: “古之医者……用药必依土地, 所以治十得九”, 《本草衍义》记载: “凡用药必择土地所宜者, 则药力具, 用之有据”。姜黄的药用部位集中在地下部, 其根际与土壤之间发生着极其复杂的相互作用。目前, 有关土壤与姜黄品质的相关性分析主要侧重于土壤理化因子等方面[6-9]。根际土壤微生物被誉为植物的第二套基因组, 在促进矿质元素吸收、植株生长发育、次生代谢物合成、生物及非生物胁迫等发挥重要作用[10-12]。近年来, 广陈皮[13]、人参[14]、铁皮石斛[15]、党参[16]、甘草[17]、天麻[18]等中药材在土壤微生物与药效成分相关性研究等方面取得了巨大的进展。然而, 根际土壤微生物与姜黄药效成分的相关性研究仍不清楚。基于此, 本实验以四川主产区(犍为、双流、兴文)姜黄为研究对象, 采用代谢组学技术分析四川主产区代谢成分及代谢途径差异, 同时测定药材根际土壤微生物群落结构、理化性质, 通过皮尔逊相关性分析探究代谢成分与根际土壤微生物群落、理化因子的相关性, 对姜黄配方施肥、种植规划及品质提升等具有重要意义。
仪器与试剂   Waters Acquity Ⅰ-Class PLUS超高效液相色谱串联Waters Xevo G2-XS QTOF高分辨质谱仪、色谱柱(Acquity UPLC HSS T3, 100 mm × 2.1 mm, 1.8 μm, 美国Waters公司); 酸度计(奥豪斯公司); K1100全自动凯氏定氮仪和I3紫外分光光度计(济南海能仪器有限公司); 火焰光度计(FP640, 上海悦丰仪器仪表有限公司); 原子荧光光度计(AFS-10B, 北京吉天仪器有限公司); 电感耦合等离子体发射光谱仪(Avio 200, 珀金埃尔默仪器有限公司); Qsep-400 [光鼎生物科技(江苏)有限公司]; Illumina Novassq 6000 (美国Illumina公司); 甲醇、乙腈(LC-MS级)购自德国Merck公司。
样品及其来源   本研究样品于2025年02月13日采集于四川省姜黄主产区, 分别为双流区种植基地(103°57′32″E, 28°59′21″N)、犍为县种植基地(104°9′49″E, 29°8′34″N)和兴文县种植基地(103°48′50″E, 30°32′33″N), 均为一年生样品。每个种植基地随机采挖9株长势均匀的姜黄植株, 轻轻抖动除去附着在根系周围的土壤及杂质, 随机将3株姜黄植株的根际土壤混匀作为一个样品, 每个种植基地各有3个样品, 部分装入无菌冷冻管后立即放入液氮速冻, 部分带回实验室晾干, 3个种植基地的姜黄土壤样本分别记为SL (双流区)、QW (犍为县)、XW (兴文县)。使用PBS/RNase-free水将姜黄植株的根茎冲洗干净, 再用吸水纸吸干样品表面水分, 随机将3株姜黄植株的根茎混匀作为一个样品, 每个种植基地各有3个样品, 装入无菌冷冻管后立即放入液氮速冻, 3个种植基地的姜黄根茎样本分别记为SLJH (双流区)、QWJH (犍为县)、XWJH (兴文县)。
非靶向代谢组学检测   称取50 mg样品, 加入1 000 μL提取液(甲醇-乙腈-水, 2∶2∶1), 再加入20 μL内标, 涡旋混匀30 s, 随后向样品中加入钢珠, 45 Hz研磨处理4 min, 冰水浴超声5 min, -20 ℃静置1 h后将样品离心(12 000 r·min-1, 15 min), 吸取上清液保存于进样瓶中, 用于分析。色谱柱Waters UPLC HSS T3 (100 mm × 2.1 mm, 1.8 μm), 流动相为0.1%甲酸水溶液(A), 乙腈(B), 洗脱梯度: 0~1 min, 1% B; 1~8 min, 1%~99% B; 8~10 min, 99% B; 10~10.1 min, 99%~1% B; 10.1~12 min, 1% B。流速500 μL·min-1, 柱温40 ℃, 进样体积1 μL。检测平台为Waters Acquity Ⅰ-Class PLUS超高效液相色谱串联Waters Xevo G2-XS QTOF高分辨质谱仪。代谢物数据采集使用Xcalibur 4.0.27软件, 物质鉴定使用OSI-SMMS (version 1.0)软件, 再利用KEGG数据库、HMDB数据库和LIPID MAPS数据库进行代谢物功能注释。利用主成分分析(principal component analysis, PCA)和正交偏最小二乘法(orthogonal projections to latent structures-discriminant analysis, OPLS-DA)判别分析了解各组样本之间的总体代谢差异和组内样本之间的变异度大小。差异代谢物的筛选标准为变量重要性投影(variable importance projection, VIP) ≥ 1, 以及差异倍数(fold change, FC) ≥ 2或≤ 0.5, 且P < 0.05, 再通过KEGG数据库分析富集通路。
土壤理化指标检测   土壤pH值用酸度计进行检测[19]; 有机质含量测定采用重铬酸钾容量法-稀释热法, 由消耗的重铬酸钾量按氧化校正系数计算出有机碳量, 再乘以常数1.724, 即为土壤有机质含量[20]; 全氮的测定运用自动定氮仪法, 通过高锰酸钾将样品中的亚硝态氮氧化为硝态氮后, 再用还原铁粉将全部硝态氮还原, 在加速剂的参与下, 用浓硫酸消煮, 经过高温分解反应, 将各种含氮化合物转化为铵态氮, 碱化后蒸馏出来的氨用硼酸溶液吸收, 用硫酸(盐酸)标准溶液滴定, 即得土壤全氮含量[21]; 有效磷含量测定利用紫外-可见分光光度计法, 通过氟化铵-盐酸溶液浸提酸性土壤中有效磷, 碳酸氢钠溶液浸提中性和石灰性土壤中有效磷, 所提取出的磷以钼锑抗比色法测定, 计算得出土壤样品中的有效磷含量[22]; 速效钾含量测定采用乙酸铵浸提-火焰光度计法, 利用中性乙酸铵溶液浸提, 再通过火焰光度计测定[23]; Mn2+、Cu2+、Ca2+、Mg2+金属元素的测定采用电感耦合等离子体发射光谱法, 上述土壤金属元素浸出液经酸消解后, 进入等离子体发射光谱仪的雾化器中被雾化, 由氩载气带入等离子体火炬中, 目标元素在离子体火炬中被气化、电离、激发并辐射出特征谱线, 特征光谱强度与待测金属元素的含量在一定范围内成正比[24]; Se4+的测定利用微波消解原子荧光法, 土壤样品经微波消解后试液进入原子荧光光度计, 在硼氢化钾溶液还原作用下, 生成硒化氢气体, 在氩氢火焰中形成基态原子, 在元素灯(硒)发射光的激发下产生原子荧光, 原子荧光强度与试液中元素含量成正比[25]。
土壤微生物宏基因组测序   采取十六烷基三甲基溴化铵法提取姜黄植株根际土壤微生物DNA, 提取后进行完整性、浓度和纯度评估, 评估合格后进行文库构建, 建库要求: 总量≥ 0.1 μg, 完整性主要弥散带在5 kb以上, 下面无明显杂质。将评估合格的DNA进行文库构建, 包括DNA酶切打断及末端修复、连接产物纯化、PCR扩增、PCR产物片段筛选等, 再通过Qsep-400进行文库质检, 质检合格后使用Illumina平台进行上机测序。将测序所得的原始数据去除接头和低质量的序列, 得到Clean Reads, 使用软件MEGAHIT进行宏基因组组装、去冗余, 得到Unigene, 使用DIAMOND软件将得到的Unigene与NR、Swissprot、Pfam、eggNOG、GO、KEGG、CARD、CAZy等数据库比对, 获得Unigene的注释信息, 随后进行物种多样性和功能多样性分析, 包括丰度组成、α多样性分析、β多样性分析、差异分析等。
数据处理   实验结果以x ± s表示, 采用SPSS 21.0单因素方差分析法(One-way ANOVA)对实验数据统计分析, 假定方差齐性用LSD, 未假定方差齐性则用Tamhane's T2。P < 0.05表示有统计学差异。使用Origin和Adobe Illustrator软件作图。
基于LC-QTOF平台对四川主产区姜黄初级代谢产物和次级代谢产物进行检测, 共检测和定量了5 147个已注释的代谢产物, 包括2 115个初级代谢产物, 2 333个次级代谢产物和699个其他类代谢产物。次级代谢产物包括34个苯丙素, 190个多酚, 221个黄酮, 54个醌类, 70个木脂素, 142个生物碱, 518个萜类, 915个酮、醛、酯类, 116个香豆素和73个甾体(图1A)。结果表明, 酮、醛、酯类, 萜类, 黄酮和多酚是姜黄含量最丰富的次级代谢产物, 其中, 多酚和萜类是姜黄的主要药效物质。
PCA分析揭示组间代谢产物的整体差异和组内差异[26]。主成分1 (principal component analysis 1, PC1)解释了总方差的26.96%, 主成分2 (principal component analysis 2, PC2)解释了总方差的24.90%, 主成分3 (principal component analysis 3, PC3)解释了总方差的14.98%。PCA分析结果显示(图1B), QWJH、SLJH和XWJH组间分离, 组内生物学重复聚到一起, 表明三组样品中的代谢物特征明显不同。另外, QWJH和SLJH在PC1和PC2上的分布比XWJH更接近, 提示QWJH和SLJH组的代谢产物含量更为相似。
OPLS-DA是判定差异代谢产物的重要方法[27]。本实验利用该方法对3个产区的姜黄分别进行总体分析及两两配对比较, 以VIP > 1, P < 0.05, FC ≥ 2或FC ≤ 0.5为标准筛选显著差异代谢产物。差异代谢产物结果如图2所示。QWJH vs SLJH组中, 共筛选到272个差异代谢产物, 207个代谢产物上调表达, 65个代谢产物下调表达; QWJH vs XWJH组中, 共筛选到326个差异代谢产物, 181个代谢产物上调表达, 145个代谢产物下调表达; SLJH vs XWJH组中, 共筛选到462个差异代谢产物, 129个代谢产物上调表达, 333个代谢产物下调表达。综上, 四川不同产区共有33个差异表达的多酚类物质和68个差异表达的萜类物质, 其中, QWJH的双去甲氧基姜黄素显著高于XWJH, 与SLJH差异不显著。SLJH的部分多酚类物质和萜类物质含量显著高于QWJH和XWJH。
为进一步探究四川不同产区姜黄代谢产物的差异, 通过KEGG对差异代谢物进行关键代谢通路富集。主要KEGG通路如图3所示。QWJH vs SLJH组中, 显著富集的代谢途径与“黄酮和黄酮醇的生物合成”、“二萜生物合成”、“半胱氨酸和甲硫氨酸代谢”、“三羧酸循环”、“乙醛酸和二羧酸代谢”、“ABC转运”等通路相关; QWJH vs XWJH组中, 显著富集的代谢途径与“甜菜碱生物合成”、“甘露糖型O-聚糖生物合成”、“克拉维酸生物合成”、“磷酸转移酶系统”等通路相关; SLJH vs XWJH组中, 显著富集的代谢途径与“硫辛酸代谢”、“多环芳烃降解”等通路相关。
测定结果如图4所示, 3个产区的根际土壤理化性质有较大差异, 各指标均有显著性差异。其中土壤pH范围在4.76~7.81, 除XW的土壤偏酸性以外, QW和SL均偏碱性; 有机质质量分数为11.00~28.00 g·kg-1, SL最高, QW最低; 全氮质量分数为1.00~1.65 g·kg-1, XW最高, QW最低; 有效磷质量分数为7.34~79.28 mg·kg-1, SL最高, QW最低; 速效钾质量分数为87.73~382.27 mg·kg-1, XW最高, SL最低; 锰、镁、钙质量分数分别为65.20~735.17、918.59~11 974.25、151.76~18 724.57 mg·kg-1, 均为QW最高, XW最低; 铜质量分数为22.20~39.16 mg·kg-1, SL最高, XW最低; 硒质量分数为0.21~0.70 mg·kg-1, XW最高, QW最低。在3个产区中, QW的锰、镁和钙含量较其他产区显著偏高, SL的有机质、有效磷和铜含量较其他产区显著偏高, XW的全氮、速效钾和硒含量较其他产区显著偏高(图4)。
Alpha多样性指数可反映土壤微生物群落的丰富度和多样性, 包括Chao1、Shannon、pielou_evenness等多种指标。四川不同产区土壤微生物群落丰富度指数(Chao1指数)呈现出兴文 > 双流 > 犍为, 且兴文显著高于其他产区(图5A)。微生物群落多样性指数(Shannon指数)从高到低依次为兴文 > 双流 > 犍为, 各产区无显著性差异(图5B)。微生物群落中相对物种丰富度(pielou_evenness指数)表现出双流 > 兴文 > 犍为, 各产区无显著性差异(图5C)。
根据物种注释结果, 四川不同产区土壤微生物相对丰度最高的10个门类分别为变形菌门(Proteobacteria)、酸杆菌门(Acidobacteria)、放线菌门(Actinobacteria)、厚壁菌门(Firmicutes)、绿弯菌门(Chloroflexi)、Candidatus_Rokubacteria、拟杆菌门(Bacteroidetes)、衣原体门(Chlamydiae)、硝化螺旋菌门(Nitrospirae)和奇古菌门(Thaumarchaeota), 3个产区土壤优势菌群均为变形菌门和酸杆菌门(图5D)。属水平分析结果表明, 3个产区优势属差异较大。各产区菌群丰度占比前5的分别为, 犍为的溶杆菌属(Lysobacter)、芽孢杆菌属(Bacillus)、衣原体属(Chlamydia)、Paucibacter和慢生根瘤菌属(Bradyrhizobium); 双流的硝化螺旋菌属(Nitrospira)、极单胞菌属(Polaromonas)、溶杆菌属(Lysobacter)、慢生根瘤菌属(Bradyrhizobium)和链霉素属(Streptomyces); 兴文的纤线杆菌属(Ktedonobacter)、链霉素属(Streptomyces)、罗河杆菌属(Rhodanobacter)、慢生根瘤菌属(Bradyrhizobium)和马杜拉放线菌属(Actinomadura) (图5E)。
对10种土壤理化指标, 属水平丰富排名前20的微生物, 6种姜黄代表性多酚类物质和萜类物质(姜黄素、去甲氧基姜黄素、双去甲氧基姜黄素、四氢姜黄素、芳姜黄酮和姜烯)进行相关性分析。以P < 0.05, 相关系数≥ 0.8或相关系数≤ -0.8为标准。Mantel分析结果表明(图6), 双去甲氧基姜黄素与pH、锰、镁、钙显著正相关, 与全氮、硒、纤线杆菌属、Thermogemmatispora、Actinospica (丛生放线菌属)、Dictyobacter、Ktedonosporobacter显著负相关; 四氢姜黄素与罗河杆菌属、Sphingomonas (鞘氨醇单胞菌属)显著正相关; 芳姜黄酮与有机质、有效磷显著正相关, 与Thermogemmatispora显著负相关。
根据美国植物委员会发布的2023年草药市场报告, 姜黄成为天然零售市场中最畅销的草本补充剂成分, 在药品、食品、化妆品等领域均具有广阔的应有前景。其化学成分复杂多样, 主要药效成分包括多酚、萜类等物质, 药理作用广泛且疗效显著。本实验运用LC-QTOF非靶向代谢组学方法对犍为、双流和兴文产区的姜黄代谢产物进行整体分析。姜黄中共鉴定出190个多酚和518个萜类物质, 其中多酚类以姜黄素、去甲氧基姜黄素、四氢姜黄素、双去甲氧基姜黄素等为主, 萜类以二萜、倍半萜为主。犍为产区的双去甲氧基姜黄素显著高于兴文, 但与双流差异不显著; 双流产区的部分多酚和萜类物质含量显著高于犍为和兴文。
已有研究表明, 不同土壤理化因子的含量对八爪金龙[28]、白及[29]、云当归[30]、草果[31]、西洋参[32]、多花黄精[33]、新疆紫草等药材中主要药效成分的代谢和积累均有影响。吴萍等[6]研究发现, 土壤pH值与姜黄产量成正相关关系, 偏碱性的土壤有利于提高姜黄产量。本研究发现, 犍为和双流产区偏碱性的土壤有利于姜黄素类成分的积累。吴萍等[6]研究还发现, 土壤有机质与姜黄挥发油含量密切相关, 有机质含量越高, 则姜黄挥发油越高。本实验结果显示, 姜黄的芳姜黄酮含量与有机质、有效磷显著正相关, 表明有机质、有效磷可能有利于姜黄芳姜黄酮等萜类物质的代谢积累, 提示在姜黄的生态种植或大田栽培中, 适当增施有机肥、磷肥, 可能会提高芳姜黄酮等药效成分的含量, 进而提升药材的品质。微量元素对药材生长发育至关重要, 且与药效成分累积密切相关[34]。肖春萍等[35]研究表明叶面喷施微量元素肥料有利于苍术药材的生长及其有效成分的积累。魏彦宏等[36]研究提示叶面喷施铜、锌离子微量元素肥料有利于提高甜菜单根重、产量、含糖率及产糖量。本研究结果表明, 姜黄的主要药效成分与锰、镁、钙等微量元素显著正相关, 提示可以喷施锰、镁、钙等微量元素肥料, 以促进药效成分累积。
根际微生物通过参与养分循环、调节土壤微环境等影响药材品质[37]。已有研究报道, 细菌中的变形菌门、酸杆菌门是药用植物微生物组中普遍存在的微生物类群[38]。本实验结果显示, 四川3个产区土壤的优势菌群均为变形菌门和酸杆菌门。曹麟等[39]研究表明T3复合菌剂可通过招募罗河杆菌属、Novosphingobium (新鞘氨醇菌属)等有益微生物, 改善绞股蓝根际微生物群落, 显著提高绞股蓝药效成分含量及产量。研究[40, 41]报道甘肃主产区黄芪根系土壤丰度最高的细菌属为鞘氨醇单胞菌属, 且其能够提高植物抗逆性。本研究结果表明, 姜黄的四氢姜黄素含量与罗河杆菌属、鞘氨醇单胞菌属显著正相关, 提示这些菌群的相对丰度可能会影响姜黄药材主要药效成分的代谢和积累。后续将从姜黄种植土壤中分离筛选罗河杆菌属、鞘氨醇单胞菌属等, 开展盆栽实验, 进一步验证这些菌群对姜黄次生代谢产物合成的影响。针对姜黄产量、病虫害、次生代谢产物合成等要素, 开发高效功能性微生物菌肥, 以减少化肥和农药的使用, 实现姜黄的高质高产。

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doi: 10.16438/j.0513-4870.2025-1144
  • 接收时间:2025-09-25
  • 首发时间:2026-09-21
  • 出版时间:2026-04-12
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  • 收稿日期:2025-09-25
  • 修回日期:2026-01-06
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    1四川省中医药科学院, 中医药转化医学四川省重点实验室, 四川 成都 610041
    2四川省中医药转化医学中心, 国家中医药管理局中药质量生物学评价重点研究室, 中医药转化医学四川省重点实验室, 四川 成都 610041
    3国家纳米科学中心, 中国科学院纳米生物效应与安全性实验室, 北京 100190

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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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