Article(id=1320889434556453228, tenantId=1146029695717560320, journalId=1260987677001138203, issueId=1320889172802515656, articleNumber=null, orderNo=null, doi=10.13386/j.issn1002-0306.2025010011, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736092800000, receivedDateStr=2025-01-06, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792854182137, onlineDateStr=2026-10-24, pubDate=1768406400000, pubDateStr=2026-01-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792854182137, onlineIssueDateStr=2026-10-24, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792854182137, creator=13701087609, updateTime=1792854182137, updator=13701087609, issue=Issue{id=1320889172802515656, tenantId=1146029695717560320, journalId=1260987677001138203, year='2026', volume='47', issue='2', pageStart='1', pageEnd='514', issueExtLink='null', onlineDate='null', pubDate='1768406400000', pubDateStr='2026-01-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792854119730, creator='13701087609', updateTime=1792854119730, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=199, endPage=208, ext={EN=ArticleExt(id=1320889434774557037, articleId=1320889434556453228, tenantId=1146029695717560320, journalId=1260987677001138203, language=EN, title=Discrimination and Identification of Urea-degrading Bacteria in the Fermented Grains of Chinese Nong-xiang Baijiu, columnId=1261336275769016441, journalTitle=Science and Technology of Food Industry, columnName=Bioengineering, runingTitle=null, highlight=null, articleAbstract=

Urea was the main precursor substance of the carcinogenic ethyl carbamate in the production of Baijiu. In this study, urea-degrading microbiota was revealed in the fermented grains from different fermentation cellars of the same brewing enterprise, by Illumina NovaSeq high-throughput sequencing combined with bioinformatics and the correlation analysis between the microbiota and urea. The results showed that the urea content of six fermented grains ranged from 60.89 to 73.29 mg/kg, and significant negative relations between urea content and Brevibacterium (rho=−0.7591), Streptococcus (rho=−0.7969), Veillonella (rho=−0.8522), and Pseudomonas (rho=−0.8023) were observed by pearson correlation analysis. Furthermore, the function of bacterial microbiota in these fermented grains was mainly reflected in Metabolism, which occupied relative abundance of 80.59% by PICRUSt2 analysis. Notably, the relative abundances of carbohydrate metabolism and amino acid metabolism associated with urea degradation and urea cycle were 15.95% and 14.70%, respectively. Meanwhile, above four genera were positively correlated with urease (EC: 3.5.1.5), and the key enzymes including argininosuccinate synthetase (EC: 6.3.4.5), argininosuccinate lyase (EC: 4.3.2.1), and ornithine transcarbamylase (EC: 2.1.3.3) related to the urea cycle were negatively correlated with these genera by pearson correlation analysis, which showed potential of these genera for urea degradation. Based on this, a strain capable of effectively degrading urea was isolated from the fermented grains, and preliminarily identified as Brevibacterium linens by molecular biology, and the preserved strain has been registered in the China Typical Culture Repository. Taken together, unveiling the urea-degrading bacteria in fermented grains could provide a theoretical foundation for urea and ethyl carbamate reduction in Baijiu fermentation by bioaugmentation.

, authors=Jiahui WANG1, Yanqing WANG1, Xiaohan LI1, Jingyi BIAN1, Fei XIE2, Jian ZHOU1, Guiqiang HE1, *, authorsList=Jiahui WANG, Yanqing WANG, Xiaohan LI, Jingyi BIAN, Fei XIE, Jian ZHOU, Guiqiang HE, authorCompany=null, correspAuthors=Guiqiang HE, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2026 Science and Technology of Food Industry. 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=1320889436682965376, articleId=1320889434556453228, tenantId=1146029695717560320, journalId=1260987677001138203, language=CN, title=浓香型酒醅中尿素降解菌的辨析及鉴定, columnId=1261336277547401341, journalTitle=食品工业科技, columnName=生物工程, runingTitle=null, highlight=null, articleAbstract=

尿素是白酒生产中致癌物氨基甲酸乙酯的主要前体物质,本研究基于Illumina NovaSeq高通量测序并结合生物信息学以及菌群与尿素的关联性分析,从同一酒企不同窖池发酵的浓香型酒醅中辨析潜在的尿素降解菌群。结果表明,6个不同发酵酒醅中尿素含量为60.89~73.29 mg/kg;皮尔森相关分析表明,尿素含量与短杆菌属Brevibacterium(相关系数rho=−0.7591)、链球菌属Streptococcus(rho=−0.7969)、韦荣氏球菌属Veillonella(rho=−0.8522)和假单胞菌属Pseudomonas(rho=−0.8023)存在显著的负相关性。通过PICRUSt2功能预测在KEGG数据库对比,表明该酒醅细菌菌群功能主要体现在代谢(Metabolism)通路上,丰度占比80.59%;其中,涉及尿素代谢和尿素循环相关的碳水化合物代谢和氨基酸代谢的相对丰度分别为15.95%和14.70%。由皮尔森相关分析结果可知,上述菌属与尿素代谢相关的脲酶(EC:3.5.1.5)呈正相关,而与尿素循环相关的关键酶包括精氨酸琥珀酸合酶(EC:6.3.4.5)、精氨酸琥珀酸裂解酶(EC:4.3.2.1)和鸟氨基甲酰转移酶(EC:2.1.3.3)等呈负相关,表明这些菌属具有降解尿素的潜在能力。在此基础上,从酒醅中筛选出了一株有效降解尿素的菌株,经分子生物学鉴定,初步判定该菌株为亚麻短杆菌(Brevibacterium linens),并已于中国典型培养物保藏中心登记保藏。综上所述,通过辨析和鉴定酒醅中的尿素降解菌,为后续生物强化应用降低白酒中的尿素和氨基甲酸乙酯提供可借鉴的理论依据。

, authors=王嘉慧1, 王严庆1, 李晓韩1, 边靖贻1, 谢菲2, 周建1, 何桂强1, *, authorsList=王嘉慧, 王严庆, 李晓韩, 边靖贻, 谢菲, 周建, 何桂强, authorCompany=null, correspAuthors=何桂强, authorNote=

王嘉慧(1999−),女,硕士研究生,研究方向:食品加工与安全,E-mail:

, correspAuthorsNote=
何桂强(1990−),男,博士,副教授,研究方向:食品微生物学,E-mail:。
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王嘉慧(1999−),女,硕士研究生,研究方向:食品加工与安全,E-mail:

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王嘉慧(1999−),女,硕士研究生,研究方向:食品加工与安全,E-mail:

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Applied and Environmental Microbiology, 2017, 83(17): e01258−17., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1320889436892680577, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, xref=1, ext=[AuthorCompanyExt(id=1320889436905263490, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, companyId=1320889436892680577, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Southwest University of Science and Technology, School of Life Science and Engineering, Mianyang 621010, China), AuthorCompanyExt(id=1320889436926235011, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, companyId=1320889436892680577, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1西南科技大学生命科学与工程学院,四川绵阳 621010)]), AuthorCompany(id=1320889436989149572, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, xref=2, ext=[AuthorCompanyExt(id=1320889436993343877, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, companyId=1320889436989149572, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Forgood Distillery Co., Ltd., Mianyang 621010, China), AuthorCompanyExt(id=1320889437001732486, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, companyId=1320889436989149572, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2四川省绵阳市丰谷酒业有限责任公司,四川绵阳 621010)])], figs=[ArticleFig(id=1320889441070207412, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, language=EN, label=Fig.1, caption=Analysis of physicochemical indicators and significant differences in fermented grains from different workshops, figureFileSmall=FUl5xVG4HqefRsuXEgrUpg==, figureFileBig=EL1ueC8kJRshqWzK31Ruqg==, tableContent=null), ArticleFig(id=1320889441162482101, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, language=CN, label=图1, caption=不同车间酒醅的理化指标及显著性差异分析

注:不同字母表示理化指标的差异显著(P<0.05)。

, figureFileSmall=FUl5xVG4HqefRsuXEgrUpg==, figureFileBig=EL1ueC8kJRshqWzK31Ruqg==, tableContent=null), ArticleFig(id=1320889441347031478, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, language=EN, label=Fig.2, caption=OTU Veen diagram of fermented grains from different workshops, figureFileSmall=o9GSF+z1LiOHItaUrvQJmg==, figureFileBig=9JiB8xcrrAtho/EvCrIMCA==, tableContent=null), ArticleFig(id=1320889441414140343, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, language=CN, label=图2, caption=不同车间酒醅的OTU韦恩图, figureFileSmall=o9GSF+z1LiOHItaUrvQJmg==, figureFileBig=9JiB8xcrrAtho/EvCrIMCA==, tableContent=null), ArticleFig(id=1320889443079279032, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, language=EN, label=Fig.3, caption=α-Diversity indices of bacterial communities in different fermented grains, figureFileSmall=c2hZV6ms3ZLEXHz9DSPoIA==, figureFileBig=AUGcp/OzzatRjom7W2Th4w==, tableContent=null), ArticleFig(id=1320889443163165113, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320889434556453228, language=CN, label=图3, caption=不同车间酒醅中细菌群落α-多样性指数

注:图柱上不同字母表示细菌群落α-多样性指数的差异显著(P<0.05)。

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浓香型酒醅中尿素降解菌的辨析及鉴定
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王嘉慧 1 , 王严庆 1 , 李晓韩 1 , 边靖贻 1 , 谢菲 2 , 周建 1 , 何桂强 1, *
食品工业科技 | 生物工程 2026,47(2): 199-208
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食品工业科技 |生物工程 2026 , 47 (2) : 199 -208
浓香型酒醅中尿素降解菌的辨析及鉴定
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王嘉慧1 , 王严庆1, 李晓韩1, 边靖贻1, 谢菲2, 周建1, 何桂强1, *
作者信息
  • 1西南科技大学生命科学与工程学院,四川绵阳 621010
  • 2四川省绵阳市丰谷酒业有限责任公司,四川绵阳 621010
通讯作者:
何桂强(1990−),男,博士,副教授,研究方向:食品微生物学,E-mail:。
作者简介:

王嘉慧(1999−),女,硕士研究生,研究方向:食品加工与安全,E-mail:

Discrimination and Identification of Urea-degrading Bacteria in the Fermented Grains of Chinese Nong-xiang Baijiu
Jiahui WANG1 , Yanqing WANG1, Xiaohan LI1, Jingyi BIAN1, Fei XIE2, Jian ZHOU1, Guiqiang HE1, *
Affiliations
  • 1Southwest University of Science and Technology, School of Life Science and Engineering, Mianyang 621010, China
  • 2Forgood Distillery Co., Ltd., Mianyang 621010, China
出版时间: 2026-01-15 doi: 10.13386/j.issn1002-0306.2025010011
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尿素是白酒生产中致癌物氨基甲酸乙酯的主要前体物质,本研究基于Illumina NovaSeq高通量测序并结合生物信息学以及菌群与尿素的关联性分析,从同一酒企不同窖池发酵的浓香型酒醅中辨析潜在的尿素降解菌群。结果表明,6个不同发酵酒醅中尿素含量为60.89~73.29 mg/kg;皮尔森相关分析表明,尿素含量与短杆菌属Brevibacterium(相关系数rho=−0.7591)、链球菌属Streptococcus(rho=−0.7969)、韦荣氏球菌属Veillonella(rho=−0.8522)和假单胞菌属Pseudomonas(rho=−0.8023)存在显著的负相关性。通过PICRUSt2功能预测在KEGG数据库对比,表明该酒醅细菌菌群功能主要体现在代谢(Metabolism)通路上,丰度占比80.59%;其中,涉及尿素代谢和尿素循环相关的碳水化合物代谢和氨基酸代谢的相对丰度分别为15.95%和14.70%。由皮尔森相关分析结果可知,上述菌属与尿素代谢相关的脲酶(EC:3.5.1.5)呈正相关,而与尿素循环相关的关键酶包括精氨酸琥珀酸合酶(EC:6.3.4.5)、精氨酸琥珀酸裂解酶(EC:4.3.2.1)和鸟氨基甲酰转移酶(EC:2.1.3.3)等呈负相关,表明这些菌属具有降解尿素的潜在能力。在此基础上,从酒醅中筛选出了一株有效降解尿素的菌株,经分子生物学鉴定,初步判定该菌株为亚麻短杆菌(Brevibacterium linens),并已于中国典型培养物保藏中心登记保藏。综上所述,通过辨析和鉴定酒醅中的尿素降解菌,为后续生物强化应用降低白酒中的尿素和氨基甲酸乙酯提供可借鉴的理论依据。

浓香型白酒  /  尿素降解菌  /  脲酶  /  短杆菌属  /  白酒安全

Urea was the main precursor substance of the carcinogenic ethyl carbamate in the production of Baijiu. In this study, urea-degrading microbiota was revealed in the fermented grains from different fermentation cellars of the same brewing enterprise, by Illumina NovaSeq high-throughput sequencing combined with bioinformatics and the correlation analysis between the microbiota and urea. The results showed that the urea content of six fermented grains ranged from 60.89 to 73.29 mg/kg, and significant negative relations between urea content and Brevibacterium (rho=−0.7591), Streptococcus (rho=−0.7969), Veillonella (rho=−0.8522), and Pseudomonas (rho=−0.8023) were observed by pearson correlation analysis. Furthermore, the function of bacterial microbiota in these fermented grains was mainly reflected in Metabolism, which occupied relative abundance of 80.59% by PICRUSt2 analysis. Notably, the relative abundances of carbohydrate metabolism and amino acid metabolism associated with urea degradation and urea cycle were 15.95% and 14.70%, respectively. Meanwhile, above four genera were positively correlated with urease (EC: 3.5.1.5), and the key enzymes including argininosuccinate synthetase (EC: 6.3.4.5), argininosuccinate lyase (EC: 4.3.2.1), and ornithine transcarbamylase (EC: 2.1.3.3) related to the urea cycle were negatively correlated with these genera by pearson correlation analysis, which showed potential of these genera for urea degradation. Based on this, a strain capable of effectively degrading urea was isolated from the fermented grains, and preliminarily identified as Brevibacterium linens by molecular biology, and the preserved strain has been registered in the China Typical Culture Repository. Taken together, unveiling the urea-degrading bacteria in fermented grains could provide a theoretical foundation for urea and ethyl carbamate reduction in Baijiu fermentation by bioaugmentation.

Nong-xiang Baijiu  /  urea-degrading bacteria  /  urease  /  Brevibacterium  /  Baijiu safety
王嘉慧, 王严庆, 李晓韩, 边靖贻, 谢菲, 周建, 何桂强. 浓香型酒醅中尿素降解菌的辨析及鉴定. 食品工业科技, 2026 , 47 (2) : 199 -208 . DOI: 10.13386/j.issn1002-0306.2025010011
Jiahui WANG, Yanqing WANG, Xiaohan LI, Jingyi BIAN, Fei XIE, Jian ZHOU, Guiqiang HE. Discrimination and Identification of Urea-degrading Bacteria in the Fermented Grains of Chinese Nong-xiang Baijiu[J]. Science and Technology of Food Industry, 2026 , 47 (2) : 199 -208 . DOI: 10.13386/j.issn1002-0306.2025010011
“民以食为天、食以安为先”,保障食品安全是建设健康中国、增进人民福祉的重要内容。固态发酵白酒作为我国传统发酵食品,具有鲜明的民族特色和产业优势,消费面广量大,在我国食品行业中占有重要地位。保障白酒品质安全既是关系国计民生的大事,也是传承民族精髓和弘扬民族文化的重要举措。固态发酵白酒由于生产工艺复杂独特,加工方式传统,危害物多元,容易造成其安全风险可能高发等突出问题[1]。例如,白酒在酿造发酵过程中会生成有害副产物,主要包括氨基甲酸乙酯(Ethyl Carbamate,EC)、氰化物、甲醇和生物胺等[2]。白酒生产中相关危害副产物难以完全规避,核心在于先摸清其发酵生成机理,再针对性采取措施,最大限度降低这类副产物的形成。这些危害物是无法完全避免的,只能在了解其发酵生成机理的基础上尽量减少白酒生产过程中相关副产物的形成。其中,EC是一种天然产生于发酵食品,尤其是饮料酒中的一种2A类致癌物[3]。
目前,控制EC的途径和方法主要分为4类,分别是:优选发酵原料、筛选优良菌株、改善酿造工艺以及外源添加酸性脲酶。例如,通过选育低产尿素酵母菌,并对其基因进行改造以降低其精氨酸酶活性,达到阻断精氨酸代谢生成尿素的途径,从而减少EC的形成[4]。吴晨岑等[5]则通过研究二次蒸馏对EC的去除率,结果表明,壶式蒸馏的EC相对去除率高达92.76%,并且采用适当的掐头去尾方法能够获得EC浓度较原酒低的二次蒸馏酒。然而,传统固态发酵白酒正是因为独特的生产工艺才赋予了产品典型的风格,在不改变酿造工艺、不影响酒体感官和不降低白酒产量的前提下降低EC含量,是白酒行业面临的共同难题。此外,EC具有很好的稳定性,在白酒中一旦形成便很难被去除,尽管在强酸强碱条件下可以将其去除,但通过这种化学方式消减 EC具有一定的难度且对白酒风味和品质有较大影响[6]。
基于此,目前对白酒中EC的消减策略研究主要集中在其前体物质。EC主要通过尿素、氰化物、瓜氨酸、焦碳酸二乙酯和氨甲酰磷酸5种前体物质形成。其中,白酒中EC的主要形成途径是尿素乙醇途径和氰化物乙醇途径。具体反应过程为:在酸性环境下,随着温度的升高,尿素与乙醇反应生成EC的速率会逐渐加快;当反应温度在60~100 ℃范围,尿素会被分解为氰酸盐和异氰酸盐,这两种物质均可与乙醇反应生成EC;当温度过高时,尿素会被分解为氢氰酸和氨气,之后再与乙醇反应生成EC[7]。由此可见,尿素含量的多少对EC的形成有显著的影响。白酒发酵过程中EC和尿素的产生和消除主要取决于相关微生物的代谢和相互作用;因此,辨析和尿素降解相关的功能菌群是控制白酒生产过程中EC含量的必要基础。
综上所述,本研究以浓香型酒醅作为研究对象,采用Illumina-NovaSeq高通量测序技术结合生物信息学手段,揭示不同发酵窖池中酒醅的细菌群落结构和组成;进一步通过关联性分析和PICRUSt2功能预测,辨析酒醅中与尿素降解相关的微生物菌群以及潜在的降解途径;在此基础上,筛选并鉴定相关的尿素降解菌株及其降解性能分析。研究结果为后续生物强化应用降低白酒中的尿素和EC提供可借鉴的理论依据。
酒醅样品 来源于中国四川某浓香型白酒企业。随机从不同生产车间挑取6个窖池,发酵结束后分别从每个窖池的上层、中层和底层位置取200 g酒醅混合均匀作为一个样品,转移到无菌聚乙烯袋中,然后立即用液氮速冻置于−80 ℃冰箱保存。6个酒醅样品分别依据窖池编号,依次命名为:FG06、FG08、FG11、FG15、FG24和FG27;酒醅群落DNA提取试剂盒OMEGA Soil DNA Kit (D5635-02) 美国Bio-Tek公司;琼脂糖凝胶试剂(75510-019)和电泳缓冲液(AM9870)、荧光定量染料Quant-iT PicoGreen dsDNA Assay Kit (P7589) 美国Invitrogen公司;DNA Marker (DL2000) 美国Takara公司;Q5 DNA高保真聚合酶Q5® High-Fidelity DNA Polymerase (M0491L) 纽英伦生物技术(北京)有限公司;总酸、乙醇、氨基酸等所用到的化学试剂 均为分析纯,购自于成都市科隆化学品有限公司;LB发酵培养基:酵母浸粉5 g/L,蛋白胨10 g/L,氯化钠10 g/L,充分溶解混匀后于 121 ℃高压灭菌 20 min;固体培养基则在此基础上添加琼脂至20 g/L;筛选培养基:酵母浸粉5 g/L,蛋白胨10 g/L,氯化钠10 g/L,尿素3 g/L,溴甲酚紫6 mg/L,充分溶解混匀后于121 ℃高压灭菌20 min。
S1000TM Thermal Cycler聚合酶链式反应仪 美国Bio-Rad公司;DYY-6C电泳仪 北京六一生物科技有限公司;NanoDrop NC2000紫外可见分光光度仪 美国Thermo Fisher Scientific公司;BG-gdsAUTO (130) 凝胶成像仪 北京百晶生物技术有限公司;BSA223S-CW电子天平 德国Sartorius公司;LDZX-75KB全自动灭菌锅 上海申安医疗器械厂;SW-CJ-2FD超净工作台 浙江苏净净化设备有限公司;HWS-250恒温培养箱 上海新苗实验仪器有限公司;GL-20G-II离心机 上海安亭科学仪器厂。
酒醅中水分和总酸参照标准方法T/CBJ 004-2018《固态发酵酒醅通用分析方法》进行测定分析[8],分别采用热风干燥质量恒定法和酸碱电位滴定法。酒醅中乙醇的测定方法使用重铬酸钾比色法依据文献[9]进行操作测定。涉及尿素循环及代谢相关的精氨酸、瓜氨酸以及尿素含量的测定依据李拥军等[10]报道的方法进行。
采用试剂盒OMEGA Soil DNA Kit (D5635-02) 提取酒醅样品的总细菌群落DNA,然后以0.8%琼脂糖凝胶电泳进行分子大小判断后对DNA进行定量检测。16S rRNA V3-V4区域PCR扩增选用引物为338F (5’-ACTCCTACGGGAGGCAGCA-3’) 和806R (5’-GGACTACHVGGGTWTCTAAT-3’),扩增程序根据先前的操作方法进行[11]。PCR扩增产物进行2%琼脂糖凝胶电泳,切取目的片段然后用Axygen凝胶回收试剂盒回收目的片段。利用Quant-iT PicoGreen dsDNA Assay Kit对PCR产物在Microplate reader (Bio-Tek,FLx800) 上进行定量,然后按照每个样品所需的数据量进行混样。
利用Illumina公司的TruSeq Nano DNA LT Library Prep Kit进行建库,从构建的文库中取1 μL样品在Agilent Bioanalyzer机器上用Agilent High Sensitivity DNA Kit对文库做2100质检,合格的文库应该有单一的峰且无接头。利用Quant-iT PicoGreen dsDNA Assay Kit在Promega Quanti Fluor上对文库进行定量,合格的文库计算后浓度应在2 nmol/L以上。对合格的文库在Illumina NovaSeq机器上利用NovaSeq 6000 SP Reagent Kit (500 cycles) 进行2×250 bp的双端测序。
使用QIIME2 2019.4版本,并根据官方教程(https://docs.qiime2.org/2019.4/tutorials/)进行修改并对微生物组生物学信息进行分析。原始序列使用QIIME pipeline进行处理,根据文献[12]描述的方法去除一些低质量序列。使用UCLUST把高质量序列依据97%相似度聚成不同的操作分类单元(OTU)[13]。采用核糖体数据库对OTU代表序列进行物种分类注释[14],并分别在各个分类水平统计样本的群落组成。
称取上述1.1中尿素含量最低的FG08酒醅5.0 g,放入装有95 mL无菌生理盐水的250 mL锥形瓶中,30 ℃恒温振荡培养24 h。取活化培养液100 μL涂布于LB发酵固体培养基中,30 ℃恒温倒置培养72 h。待菌落长出后,挑取不同形态的单菌落进行分离纯化并接种于筛选培养基,30 ℃恒温振荡培养96 h,初步筛选可使培养基颜色由黄变紫的菌株。接着,将初筛菌株分别接种到LB发酵培养基中,30 ℃恒温振荡培养24 h后,检测脲酶活性,选取酶活较高的菌株作为目标菌株。脲酶活性检测方法如下:取30 mL发酵液离心5 min(4 ℃,8000 r/min)收集菌体,经磷酸盐缓冲液(pH7.0,20 mmol/L)洗涤后重悬。将重悬液置于冰浴中超声破碎5 s间歇2 s,40 W破碎30 min。将细胞破碎重悬液离心5 min(4 ℃,10000 r/min)收集上清液即为粗酶液。其中,脲酶活性检测采用Berthelot reaction比色法[15]。
离心收集培养好的细菌菌体,按照OMEGA细菌基因组提取试剂盒的说明方法提取基因组DNA,用27F和1492R引物进行PCR扩增。扩增程序:95 ℃预变性3 min;95 ℃变性30 s,55 ℃退火30 s,72 ℃延伸1 min,30个循环;72 ℃延伸10 min。扩增好的PCR产物进行琼脂糖凝胶电泳(2 µL样品+6 µL溴酚蓝),300 V电压下跑胶12 min,获取鉴定胶图;将获取16S rDNA序列后送往北京擎科生物科技有限公司成都分公司进行双向测序,测序结果在NCBI数据库中比对,利用MEGA11软件构建系统发育树。
使用IBM SPSS Statistics 27软件对酒醅理化指标数据进行显著性分析,采用单因素ANOVA分析的Duncan检验法(P<0.05,n=3)。利用 QIIME 软件对测序数据进行分析,每个样本设置3次生物学重复,在门、纲、目、科、属、种等不同分类水平上,通过R语言(ggplot2 包)采用柱状图/堆叠柱状图形式绘制物种分类图;同时基于OTU(操作分类单元)水平,利用QIIME软件内置算法计算每个样本的Chao1、Shannon和Simpson等α-多样性指数,所有实验及分析均独立重复3次以确保结果可靠性。利用IBM SPSS Statistics 27软件计算了酒醅中微生物群落、理化指标以及功能酶活性之间的皮尔森相关系数(rho),以量化它们之间的线性相关程度。基于独立OTU使用Bray-Curtis加权算法进行非度量多维尺度分析(Non-metric multidimensional scaling,NMDS)[16]。PICRUSt2(Phylogenetic Investigation of Communities by Reconstruction of Unobserved States)预测代谢通路及组间功能差异分析,主要依据细菌16S rRNA基因测序结果来预测菌群的代谢功能[17]。
酒醅理化性质的分析主要包括水分、酸度以及酒精含量等指标,这些指标会受酒醅微生物群落组成及其代谢差异的影响,因此理化指标可以在一定程度上反映发酵过程的情况。在酒醅发酵过程中,酿造菌群的互作及其代谢必然会产生多种酸类物质,同时也伴随乙醇的生成,所以总酸与酒精含量的变化趋势大致相同[18−19]。如图1所示,在发酵结束后,不同车间酒醅的水分、酸度以及乙醇含量均在正常范围内波动;其中,FG27窖池酒醅中的总酸和乙醇含量均较高,这其实主要与产酸菌的丰度大小有关系[20]。水分的变化也是影响白酒发酵的一个重要因素:水分不足会影响微生物的生长发酵,降低出酒率;水分过多则会导致微生物生长旺盛,使酒醅高度酸化,从而影响原酒酒质[21]。本研究6个不同窖池的酒醅水分在62.08%~68.86%的范围波动(图1A)。水分的含量除了受入窖水分的影响,还与酿造菌群的呼吸作用有关,微生物通过代谢原料中的淀粉、蛋白质等大分子物质并逐步形成醇、醛、酸、酯等小分子物质,同时伴随一定量的水形成。
此外,还分析比较了6个窖池酒醅中与尿素循环和代谢相关的尿素、精氨酸和瓜氨酸的含量,结果如图1D~图1F所示。尿素含量位于60.89~73.29 mg/kg之间,其中FG06酒醅尿素含量最高;同时,精氨酸作为合成尿素的重要前体物质,在这些酒醅中与尿素含量关系整体趋于一致。有文献报道,精氨酸可以促进酿酒酵母生长,随着精氨酸含量增加,酿酒酵母尿素产量也随之增加[22]。瓜氨酸主要来自于酿酒原料本身以及乳酸菌通过精氨酸脱亚胺酶(Arginine deiminase,ADI)途径降解精氨酸产生[23],其中FG08酒醅中瓜氨酸含量最高。
通过高通量测序和序列质量控制,6个酒醅样品共得到1883904条有效序列,每个样品平均包含 104661条序列,通过归类共得到28588个 OTU,结果如图2所示。所有样品共有的OTU数量为744个,仅占总数量的2.60%,这也表明6个车间酒醅样品的细菌群落结构存在显著差异。分析各酒醅样本的OTU数量分布,发现其介于3545(FG27)至6179(FG08)之间。由此可知,每个样本的测序深度足够,所得序列能够全面反映酒醅细菌群落的结构组成,可用于后续分析。
车间酒醅样本的coverage(覆盖率)在 0.98±0.01之间(图3B),基本涵盖了样品中的微生物种类,证明测序结果能够完整反映酒醅样品微生物物种的组成信息。Chao1指数主要代表样本中物种丰度,其数值越大,表明样本中包含的物种总数越多。Shannon 和Simpson指数则代表了物种的多样性,数值越大,样本的物种多样性也就越高。在6个车间酒醅样品中,Chao1指数在1877.12(FG27)~4903.10(FG08)之间(图3A),这与OTU数量结果(图2)相吻合。Shannon和Simpson指数同样呈现这个现象(图3C~图3D),表明FG08酒醅样品的物种更为丰富且其多样性更高,而FG27酒醅则反之。
基于门和属水平对6个窖池酒醅中的细菌群落结构进行分析(图4),相对丰度大于1%的共有优势菌门有7个,包括厚壁菌门(Firmicutes)、变形菌门(Proteobacteria)、放线菌门(Actinobacteriota)、酸杆菌门(Acidobacteriota)、芽单胞菌门(Gemmatimonadota)、拟杆菌门(Bacteroidota)和绿弯菌门(Chloroflexi)。其中,Firmicutes占据绝对优势(33.78%~79.89%),这与诸多研究结果一致,表明了浓香型白酒发酵酒醅的共性特征[24−26]。基于属水平上的共有优势菌属有乳杆菌属(Lactobacillus)、链球菌属(Streptococcus)、韦荣球菌属(Veillonella)和芽单胞菌属(Gemmatimonas);其中Lactobacillus占据绝对优势,相对丰度为18.83%~72.14%。
发酵结束后,酿造微生态系统内酸度和乙醇浓度升高,氧气含量减少,大部分微生物无法耐受高酸度、高乙醇浓度以及低氧等不利条件而衰亡,来自于大曲和窖泥的乳酸菌逐渐成为优势菌种。乳酸菌的主要产物是乳酸,能够减少白酒中的刺激感且能增加酒体的醇厚感,对白酒风味的形成有重要影响[27]。本研究结果可以初步推测酒醅中乳酸的形成主要由Lactobacillus代谢产生,且主要在发酵后期形成。FG08和FG15窖池酒醅中Lactobacillus的相对丰度与其它酒醅相比较低,分别为32.32%±13.31%和26.92%±7.08%(图4B);结合前文酒醅理化性质分析,这两个酒醅的尿素和精氨酸含量也更低(图1D~图1E),这可能是尿素降解菌群与其他酿造微生物复杂代谢及相互作用的结果。值得关注的是,FG08和FG15酒醅中Streptococcus的相对丰度分别达到了3.64%和3.81%,ZOTTA等[28]通过筛选获得了一株产酸性脲酶的嗜热链球菌(Streptococcus thermophilus),且该脲酶在低pH和高乙醇浓度下具有较强的活性。因此,FG08和FG15酒醅中高丰度的Streptococcus可能也是导致尿素含量相对较少的原因之一。又如仇钰莹等[29]从浓香型酒醅中分离出了具有高精氨酸利用能力和高瓜氨酸积累特性的菌株,包括葡萄球菌、芽孢杆菌、足球菌及乳球菌,且这些微生物均属于Firmicutes。FG06和FG11酒醅中Firmicutes的相对丰度较高,有可能通过利用精氨酸直接导致尿素和瓜氨酸含量高于其他酒醅样品。
使用基于OTU水平Bary-Curtis距离算法进行NMDS分析酒醅细菌群落的β-多样性(图5)。分析结果表明,在NMDS中胁强指数stress值小于0.1,表明此分析结果能良好地代表数据的真实分布。其中,FG08窖池和FG15窖池酒醅样品在NMDS图中距离更为接近说明两者间群落构成差异较小,结合前期细菌群落组成以及α-多样性分析结果,表明两酒醅样品的群落结构更为相似。但由于浓香型白酒传统固态酿造工艺较为复杂,不同位置的群落结构可能存在一定的差异,所以酒醅样品组内及组间的细菌群落组成同样具有差异性。
为判定酒醅中与尿素降解相关的微生物菌群,从样品、细菌属以及理化指标三者进行关联分析。利用冗余分析(Redundancy Analysis,RDA)考察酒醅样品和尿素、瓜氨酸、精氨酸以及乙醇的关联性,结果如图6A所示。图中分布解释率为95.22%,说明酒醅理化指标与样品中细菌群落结构的分布有显著的相关性。由图6A可知,尿素含量与酒醅FG06和FG24中的细菌群落组成呈显著的正相关性。接着,分析皮尔森相关系数,绘制了主要优势细菌属和尿素以及其他理化指标的关联网络图(图6B)。由图可知,乙醇、水分和尿素及精氨酸与Lactobacillus呈正相关,但与其他的大部分细菌属呈显著负相关,这可能是由于绝大部分Lactobacillus具有极强的环境适应性,在发酵糖类时产生大量乳酸而抑制了其他微生物和杂菌的生长,在白酒酿造过程中能够形成风味前体物质,其代谢产物也可成为其他酿酒微生物生长繁殖的碳源[30]。而在这些细菌属中,如链球菌属Streptococcus(相关系数rho=−0.7969)、韦荣氏球菌属Veillonella(rho=−0.8522)、短杆菌属Brevibacterium(rho=−0.7591)和假单胞菌属Pseudomonas(rho=−0.8023)都与尿素含量存在显著的负相关性,说明这些细菌属在降解尿素上可能都具有一定潜在能力。早在1961年,VALENTINE等[31]在《自然》期刊上就报道了通过提取Streptococcus allantoicus的胞内物可以实现尿素的磷酸盐依赖性降解,ZOTTA等[28]也分离鉴定了一株高产酸性脲酶而降解尿素的嗜热链球菌(Streptococcus thermophilus)。在白酒酿造生态系统中报道的尿素降解菌主要集中在芽孢杆菌属(Bacillus),包括地衣芽孢杆菌(Bacillus licheniformis)和解淀粉芽孢杆菌(Bacillus amyloliquefaciens)[15,32]。在降解尿素上可能具有一定潜力的微生物属Veillonella、Brevibacterium和Pseudomonas却鲜有报道,后续研究在酿酒功能微生物资源的挖掘以及代谢功能的证实方面可以进一步深入。
通过PICRUSt2方法将酒醅细菌的16S rRNA基因序列在KEGG数据库中进行菌群代谢功能预测,结果如图7所示。在KEGG数据库的6大通路包括代谢(Metabolism)、遗传信息处理(Genetic Information Processing)、环境信息处理(Environmental Information Processing)、细胞过程(Cellular Processes)、生物系统(Organismal Systems)和人类疾病(Human Diseases)中,酒醅细菌群落在Metabolism通路中占比丰度最多(80.59%),其中碳水化合物代谢(15.95%)、氨基酸代谢(14.70%)以及辅因子和维生素代谢是菌群主要的代谢方式(图7A和图7B)。其原因主要体现在白酒酿造过程中,微生物可以利用原料中大量的碳水化合物作为底物而代谢产生醇、醛、酸、酯类等白酒风味物质[17]。其中FG08和FG15酒醅中碳水化合物代谢、氨基酸代谢以及辅因子和维生素代谢的相对丰度明显高于其他酒醅。
通过KEGG直系同源基因簇(KEGG orthologous groups,KO)注释可以获得更详细的代谢功能信息,KO是KEGG数据中最小的分类,它对应代谢通路上各个具体的代谢反应。对6种酒醅中相对丰度总量排名前24的KO进行聚类分析并绘制相对丰度热图,结果如图7C所示。从图7C可知,6种酒醅共18个样本除各窖池聚为一类外,FG24和FG27、FG06和FG11、FG08和FG15在代谢功能上更为接近,但不同酒醅存在显著差异。注释到排名前24的KO多数是氨基酸代谢相关的酶,如异柠檬酸脱氢酶(KO00030)和γ-丁基甜菜碱双加氧酶(KO00471)等,以及碳水化合物代谢相关的果胶酯酶(KO01051)和6-磷酸果糖-2-激酶(KO00900)等,这也证实了酒醅细菌主要是通过碳水化合物代谢和氨基酸代谢来产生浓香型白酒主要的风味物质。
为了进一步判定酒醅中与尿素降解相关的微生物,通过PICRUSt2标记基因序列预测尿素降解和尿素循环途径相关功能酶及其丰度信息,绘制气泡关联图,结果如图8所示。尿素的生物合成途径主要为尿素循环,与精氨酸的生物合成密切相关;尿素降解则主要依靠微生物代谢产生脲酶将尿素降解为CO2和NH3。由皮尔森相关分析结果可知,Streptococcus、Veillonella、Brevibacterium和Pseudomonas与尿素代谢相关的脲酶(EC:3.5.1.5)呈正相关,而这些菌属与尿素循环相关的关键酶包括精氨酸琥珀酸合酶(EC:6.3.4.5)、精氨酸琥珀酸裂解酶(EC:4.3.2.1)和鸟氨基甲酰转移酶(EC:2.1.3.3)等呈负相关,表明这些菌属具有降解尿素的潜在能力。其中,Brevibacterium在FG08酒醅中占有1.33%的丰度,相比于其他酒醅更高,有利于后续的分离筛选。
通过活化酒醅菌悬液涂布于LB固体发酵培养基筛选出菌落形态不一的菌株,其中共筛选出有效菌株18株。将上述菌株接种于筛选培养基30 ℃培养72 h,其中有3株菌株可以分解尿素产生NH3使培养基颜色由黄变紫。进一步将这3株菌株进行发酵,测定其脲酶的活力。由图9A可知,菌株W2、W5和W7胞内脲酶活力分别为0.41、0.39和0.034 U/mL。因此,选取菌株W2和W5进行后续测序鉴定。将扩增好的PCR产物进行琼脂糖凝胶电泳,结果如图9B所示,在1500 bp左右有明显条带,条带大小与16S rDNA特征一致。将PCR产物进行测序后进一步拼接,拼接好的序列在NCBI数据库中用BLAST程序进行序列比对分析,通过MEGA11构建系统发育树,结果如图9C所示。菌株W2和W5均同亚麻短杆菌(Brevibacterium linens)聚为一簇,说明同源性最高。因菌株W2和W5同属,选择脲酶活性更高的W2作为目标菌株。该亚麻短杆菌命名为Brevibacterium linens W2,已于2024年7月18日在中国典型培养物保藏中心登记保藏,保藏号为CCTCC NO:M20241598。结合前文Brevibacterium丰度与尿素含量呈负相关且与脲酶呈正相关,表明亚麻短杆菌(B. linens W2)具有降解尿素的能力,符合前期相关性结果分析。
本研究基于高通量测序及生物信息学从不同窖池发酵的浓香型酒醅中辨析潜在的尿素降解菌群。短杆菌属Brevibacterium、链球菌属Streptococcus、韦荣氏球菌属Veillonella和假单胞菌属Pseudomonas与尿素含量存在显著的负相关性,而与降解尿素的脲酶呈正相关性。在此基础上,从酒醅中筛选出了一株有效降解尿素的菌株,经分子生物学鉴定,初步判定该菌株为亚麻短杆菌,并已于中国典型培养物保藏中心登记保藏。综上所述,通过辨析和鉴定酒醅中的尿素降解菌,为后续生物强化应用降低白酒中的尿素和氨基甲酸乙酯提供可借鉴的理论依据。

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2026年第47卷第2期
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doi: 10.13386/j.issn1002-0306.2025010011
  • 接收时间:2025-01-06
  • 首发时间:2026-10-24
  • 出版时间:2026-01-15
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  • 收稿日期:2025-01-06
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    1西南科技大学生命科学与工程学院,四川绵阳 621010
    2四川省绵阳市丰谷酒业有限责任公司,四川绵阳 621010

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何桂强(1990−),男,博士,副教授,研究方向:食品微生物学,E-mail:。
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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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