Article(id=1297571034408968781, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1297570992835023717, articleNumber=null, orderNo=null, doi=10.13343/j.cnki.wsxb.20260127, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1770652800000, receivedDateStr=2026-02-10, revisedDate=null, revisedDateStr=null, acceptedDate=1776009600000, acceptedDateStr=2026-04-13, onlineDate=1787294642306, onlineDateStr=2026-08-21, pubDate=1785772800000, pubDateStr=2026-08-04, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1787294642306, onlineIssueDateStr=2026-08-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1787294642306, creator=13701087609, updateTime=1787294642306, updator=13701087609, issue=Issue{id=1297570992835023717, tenantId=1146029695717560320, journalId=1192105938417971205, year='2026', volume='66', issue='8', pageStart='3681', pageEnd='4288', issueExtLink='null', onlineDate='null', pubDate='1785772800000', pubDateStr='2026-08-04', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1787294632395, creator='13701087609', updateTime=1787294931551, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1297572247670124783, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1297570992835023717, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1297572247670124784, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1297570992835023717, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3926, endPage=3952, ext={EN=ArticleExt(id=1297571034627072590, articleId=1297571034408968781, tenantId=1146029695717560320, journalId=1192105938417971205, language=EN, title=Comparison of gut microbiome and metabolome characteristics in preterm and full-term infants under different feeding modes, columnId=1192149543992045670, journalTitle=Acta Microbiologica Sinica, columnName=Research Article, runingTitle=null, highlight=null, articleAbstract=

Early life is a critical window for the establishment of the infant gut microbiome and the shaping of its metabolic functions, and gestational age and feeding mode are considered key determinants of this process. [Objective] To compare the fecal gut microbiome and metabolome between preterm and full-term infants under breastfeeding and non-breastfeeding conditions, thus exploring the effects of feeding mode and gestational age on early-life gut microbial ecology and metabolic features. [Methods] Infants were assigned into four groups: breastfeeding preterm infants (BPI), non-breastfeeding preterm infants (NBPI), breastfeeding full-term infants (BTI), and non-breastfeeding full-term infants (NBTI), with 10 infants per group. The 16S rRNA gene sequencing and untargeted metabolomics analysis were performed. Alpha/beta diversity analyses, differential abundance testing, and linear discriminant analysis effect size (LEfSe) were performed to identify key microbial taxa. Partial least squares-discriminant analysis (PLS-DA), volcano plots, and KEGG pathway enrichment were employed to determine differential metabolites and functional pathways, followed by microbiome-metabolite association network analysis. [Results] The 16S rRNA gene sequencing showed that the gut microbiome in the BTI group was dominated by Actinomycetota, Bifidobacterium (45.98%), and Bifidobacterium breve, forming a typical “breastfeeding-type” structure. The BPI group showed enrichment of Pseudomonadota and Streptococcus, with attenuated dominance of Bifidobacterium. Among non-breastfed infants, the NBTI group was dominated by Enterococcus (59.20%), whereas the NBPI group showed a fluctuating gut microbiome. Untargeted metabolomics further revealed functional differences consistent with these compositional patterns. KEGG enrichment indicated that differential metabolites were mainly involved in amino acid metabolism, lipid metabolism, bile acid-related pathways, and carbohydrate digestion and absorption. At the level of key metabolites, the BPI group showed significant enrichment of metabolites related to antioxidant and immune support, such as glutathione and vitamin D sulfate conjugates; the BTI group enriched long-chain polyunsaturated fatty acids and indole-derived metabolites; and non-breastfeeding groups generally exhibited accumulation of fermentable carbohydrates and specific bile acid derivatives. Correlation analysis confirmed a strong positive association between Bifidobacterium and indole-related metabolite outputs in breastfeeding groups, whereas microbiome–metabolite networks were looser in non-breastfeeding groups. [Conclusion] Both gestational age and feeding mode are related to differences in the early gut microbiome structure and related metabolic characteristics of infants, with the association between feeding mode and metabolic profile differences being more prominent. Gestational age may affect the establishment pattern of dominant microbial taxa in the context of breastfeeding. As a pioneering exploratory study, this study preliminarily reveals the specificity of gut microbiome structure and functional metabolism in different populations of infants, providing a basis for subsequent prospective cohort validation, mechanism research, and early nutritional intervention optimization.

, authors=Jiaqi YIN1, Shuang WANG2, Jiaqi LIU1, Lina DING1, Jing ZOU1, Junwen LIU1, Yao JIN1, Ping LI1, Qing GU1, Jiarun HAN1, authorsList=Jiaqi YIN, Shuang WANG, Jiaqi LIU, Lina DING, Jing ZOU, Junwen LIU, Yao JIN, Ping LI, Qing GU, Jiarun HAN, authorCompany=null, correspAuthors=Qing GU, Jiarun HAN, authorNote=

These authors contributed equally to this work.

, correspAuthorsNote=
E-mail: HAN Jiarun, ;
GU Qing,
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生命早期是婴儿肠道微生态建立与代谢功能塑形的关键窗口期,胎龄与喂养方式被认为是影响该过程的核心决定因素。 【目的】 比较早产与足月婴儿在母乳与非母乳喂养条件下粪便肠道微生物组及代谢组的差异,解析不同喂养方式与胎龄对婴儿早期肠道微生态及代谢特征的影响。 【方法】 将受试婴儿分为早产母乳喂养(breastfeeding preterm infants, BPI)、早产非母乳喂养(non-breastfeeding preterm infants, NBPI)、足月母乳喂养(breastfeeding full-term infants, BTI)、足月非母乳喂养(non-breastfeeding full-term infants, NBTI) 4组,每组10例,进行16S rRNA基因肠道微生物组测序及非靶向代谢组学分析。采用α/β多样性分析、差异丰度分析与线性判别分析效应大小(linear discriminant analysis effect size, LEfSe)筛选关键肠道微生物菌群;通过偏最小二乘判别分析(partial least squares-discriminant analysis, PLS-DA)、火山图与KEGG通路富集分析鉴定差异代谢物与功能通路,并构建微生物-代谢物关联网络。 【结果】 16S rRNA测序结果显示,BTI组以放线菌门(Actinomycetota)、双歧杆菌属(Bifidobacterium)、短双歧杆菌(Bifidobacterium breve)为特征性优势菌(双歧杆菌属占比45.98%),形成典型的“母乳型”结构;BPI组则以假单胞菌门(Pseudomonadota)与链球菌属(Streptococcus)富集为特征,双歧杆菌优势减弱。非母乳喂养组中,NBTI组以肠球菌属(Enterococcus)为优势属(59.20%),NBPI组菌群结构波动较大。非靶向代谢组学进一步揭示了与上述菌群结构对应的功能差异。KEGG通路富集表明差异主要集中于氨基酸代谢、脂质代谢、胆汁酸相关通路及碳水化合物消化吸收等通路。关键代谢物层面,BPI组中谷胱甘肽、维生素D硫酸酯等与抗氧化和免疫支持相关的代谢物显著富集,BTI组富集长链多不饱和脂肪酸与吲哚类代谢物,非母乳喂养组普遍积累可发酵碳水化合物及特定胆汁酸衍生物。相关性分析表明,母乳喂养组中双歧杆菌与吲哚类代谢物水平呈强正相关,而非母乳喂养组的菌群-代谢物关联网络更为松散。 【结论】 胎龄与喂养方式均与婴儿早期肠道菌群结构及代谢特征差异相关,其中喂养方式与代谢谱差异的关联更为突出,胎龄可能影响母乳喂养背景下优势菌群的建立模式。本研究作为一项先导性探索,初步揭示了不同群体婴儿肠道菌群结构与功能代谢的特异性,为后续前瞻性队列验证、机制研究及早期营养干预优化提供了依据。

, authors=殷家琪1, 王爽2, 刘嘉琦1, 丁丽娜1, 邹静1, 刘骏文1, 金瑶1, 郦萍1, 顾青1, 韩佳润1, authorsList=殷家琪, 王爽, 刘嘉琦, 丁丽娜, 邹静, 刘骏文, 金瑶, 郦萍, 顾青, 韩佳润, authorCompany=null, correspAuthors=顾青, 韩佳润, authorNote=

作者贡献声明

殷家琪:方案设计、实验操作、初稿写作;王爽:样本采集、方案设计;刘嘉琦:协助实验操作、稿件修改;丁丽娜:方法论、数据收集和处理;邹静:软件程序,数据收集与监管;刘骏文:提供材料,协助实验操作;金瑶:协助实验操作;郦萍:论文润色修改;顾青:提供技术支持;韩佳润:研究构思和设计、监督指导、经费支持。

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Nature Reviews Immunology, 2024, 24(11): 798-809., articleTitle=How bile acids and the microbiota interact to shape host immunity, refAbstract=null)], funds=[Fund(id=1297571041904190138, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, awardId=32402117, language=EN, fundingSource=National Natural Science Foundation of China(32402117), fundOrder=null, country=null), Fund(id=1297571041988076219, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, awardId=32402117, language=CN, fundingSource=国家自然科学基金(32402117), fundOrder=null, country=null), Fund(id=1297571042059379388, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, awardId=YESS20240737, language=EN, fundingSource=Young Elite Scientists Sponsorship Program by CAST(YESS20240737), fundOrder=null, country=null), Fund(id=1297571042130682557, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, awardId=YESS20240737, language=CN, fundingSource=中国科协青年人才托举工程(YESS20240737), fundOrder=null, country=null), Fund(id=1297571042206180030, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, awardId=ZJSKXQT201508, language=EN, fundingSource=Zhejiang Association for Science and Technology Youth Talent Support Project(ZJSKXQT201508), fundOrder=null, country=null), Fund(id=1297571042290066111, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, awardId=ZJSKXQT201508, language=CN, fundingSource=浙江省科协青年人才托举工程(ZJSKXQT201508), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1297571036833276514, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, xref=1., ext=[AuthorCompanyExt(id=1297571036837470819, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, companyId=1297571036833276514, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.Zhejiang Key Laboratory of Food Microbiology and Nutritional Health, School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang, China), AuthorCompanyExt(id=1297571036850053732, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, companyId=1297571036833276514, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.浙江工商大学 食品与生物工程学院,全省食品微生物与营养健康重点实验室,浙江 杭州)]), AuthorCompany(id=1297571036917162597, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, xref=2., ext=[AuthorCompanyExt(id=1297571036925551206, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, companyId=1297571036917162597, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.Shenyang Woman’s and Children’s Hospital, Shenyang, Liaoning, China), AuthorCompanyExt(id=1297571036933939815, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, companyId=1297571036917162597, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.沈阳市妇婴医院,辽宁 沈阳)])], figs=[ArticleFig(id=1297571040297771686, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 1, caption=Flow chart of the study cohort. Based on gestational age at birth and feeding pattern, participants were divided into four groups: breastfeeding preterm infants (BPI) (29-36 weeks), non-breastfeeding preterm infants (NBPI) (29-36 weeks), breastfeeding full-term infants (BTI) (37-42 weeks), and non-breastfeeding full-term infants (NBTI) (37-42 weeks). Fresh fecal samples from newborns were collected for subsequent microbiome and metabolome analysis., figureFileSmall=g3rbYuxKTeO6k1cUiX5zQg==, figureFileBig=Qt+oIAgGSM53NJ396NrnjQ==, tableContent=null), ArticleFig(id=1297571040360686247, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图1, caption=本研究队列流程图, figureFileSmall=g3rbYuxKTeO6k1cUiX5zQg==, figureFileBig=Qt+oIAgGSM53NJ396NrnjQ==, tableContent=null), ArticleFig(id=1297571040536847016, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 2, caption=Inter-group comparison of gut microbiota diversity in infants. A-F: Represent the Venn diagram, beta diversity, ACE index, Chao1 index, Simpson index, and Shannon index, respectively. The significance marker is * (P<0.05)., figureFileSmall=OSvGCdTPK0HE3doraGra5w==, figureFileBig=sBx829pA212rSzfbMDxniw==, tableContent=null), ArticleFig(id=1297571040591372969, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图2, caption=婴儿肠道微生物多样性的组间比较, figureFileSmall=OSvGCdTPK0HE3doraGra5w==, figureFileBig=sBx829pA212rSzfbMDxniw==, tableContent=null), ArticleFig(id=1297571040662676138, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 3, caption=Inter-group comparison of infant gut microbiota structure. A: Composition of bacterial populations in fecal samples at the phylum level; B: Composition of bacterial populations in fecal samples at the genus level; C: Comparison of relative abundance of Bifidobacterium across four groups; D: Comparison of relative abundance of Lactobacillus across four groups; E: Comparison of relative abundance of Streptococcus across four groups; F: Comparison of relative abundance of Enterococcus across four groups. Non parametric tests were used for inter-group comparison of relative abundance at the same level, with significance marked as **P<0.01, ***P<0.001, ****P<0.000 5., figureFileSmall=W39rxrDtPquYlhJYqEvbJg==, figureFileBig=yIi8xM93nhI30rFbTGtLLw==, tableContent=null), ArticleFig(id=1297571040746562219, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图3, caption=婴儿肠道微生物群落结构的组间比较, figureFileSmall=W39rxrDtPquYlhJYqEvbJg==, figureFileBig=yIi8xM93nhI30rFbTGtLLw==, tableContent=null), ArticleFig(id=1297571040834642604, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 4, caption=Comparative analysis of significant differences in species within the intestinal microbial communities of infants. A: LEfSe phylogenetic tree [Different colors indicate taxa significantly enriched in the corresponding group (red: BPI; green: BTI; blue: NBTI), representing the taxonomic levels from phylum to species, from the inside out]; B: Bar graph of LDA effect sizes for LEfSe differential microbiota, showing the key taxa significantly enriched in each group and their discriminatory power (LDA>4.0, P<0.05)., figureFileSmall=wsm06x2rVR3TOZhe0P0bfg==, figureFileBig=FIe4yk9WLJpcACo52csqSA==, tableContent=null), ArticleFig(id=1297571040905945773, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图4, caption=婴儿肠道微生物群落物种显著差异比较分析, figureFileSmall=wsm06x2rVR3TOZhe0P0bfg==, figureFileBig=FIe4yk9WLJpcACo52csqSA==, tableContent=null), ArticleFig(id=1297571040989831854, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 5, caption=Metabolite pathways and classification annotations. A: KEGG pathway annotations; B: HMDB classification annotations; C: LIPID MAPS classification annotations., figureFileSmall=eRWnsUmMzvf/cKPcAfxdyA==, figureFileBig=xRp967QFAu2Rb2eDjSaGXQ==, tableContent=null), ArticleFig(id=1297571041052746415, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图5, caption=代谢物通路及分类注释, figureFileSmall=eRWnsUmMzvf/cKPcAfxdyA==, figureFileBig=xRp967QFAu2Rb2eDjSaGXQ==, tableContent=null), ArticleFig(id=1297571041124049584, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 6, caption=Metabolomics PLS-DA and permutation test plot. A, C, E, G: PLS-DA score plot; B, D, F, H: permutation test results., figureFileSmall=iseJhauNMk+qjFTwTHzl2Q==, figureFileBig=wbicUKYpZQKUGcBWazOTBg==, tableContent=null), ArticleFig(id=1297571041199547057, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图6, caption=代谢组学PLS-DA与置换检验图, figureFileSmall=iseJhauNMk+qjFTwTHzl2Q==, figureFileBig=wbicUKYpZQKUGcBWazOTBg==, tableContent=null), ArticleFig(id=1297571041266655922, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 7, caption=Differential metabolite volcano plots (A, C, E, G) and differential metabolite KEGG pathway enrichment bubble plots (B, D, F, H). The plots show the distribution of differential metabolites for NBPI vs. BPI, NBTI vs. BTI, BTI vs. BPI, and NBTI vs. NBPI, respectively., figureFileSmall=MjyeEfgoiN7HqimRAv6D2A==, figureFileBig=i6nNMkmQWVXxEw+rHz5wcg==, tableContent=null), ArticleFig(id=1297571041333764787, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图7, caption=差异代谢物火山图(ACEG)及差异代谢物KEGG通路富集气泡图(BDFH), figureFileSmall=MjyeEfgoiN7HqimRAv6D2A==, figureFileBig=i6nNMkmQWVXxEw+rHz5wcg==, tableContent=null), ArticleFig(id=1297571041409262260, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 8, caption=Differential metabolite matchstick plots. A: BPI vs. NBPI; B: BTI vs. NBTI; C: BTI vs. BPI; D: NBTI vs. NBPI. E-X: Bar graphs of key differential metabolites. In the matchstick plot, the color of the dots represents the up/down regulation, with blue indicating downregulation and red indicating upregulation; the length of the stick represents the magnitude of log2 fold change; and the size of the dot represents the magnitude of VIP value. The significance markers are *P<0.05, **P<0.01, ***P<0.001, ****P<0.000 5., figureFileSmall=9waOOE6SpDV7eLnevm/DkA==, figureFileBig=NTXDRCeDUCjEIvQ0l6tELg==, tableContent=null), ArticleFig(id=1297571041472176821, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图8, caption=差异代谢物火柴杆图, figureFileSmall=9waOOE6SpDV7eLnevm/DkA==, figureFileBig=NTXDRCeDUCjEIvQ0l6tELg==, tableContent=null), ArticleFig(id=1297571041560257206, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Figure 9, caption=Heatmaps of microbial-differential metabolite correlation analysis across different groups. A: BPI; B: NBPI; C: BTI; D: NBTI. The P-value was adjusted for FDR using the Benjamini-Hochberg method, and a correlation of *P<0.05 was considered significant., figureFileSmall=/JVSARhd3lGus5nXLeFjMQ==, figureFileBig=O6L2ry1RfLmRBwkmkkE9Gw==, tableContent=null), ArticleFig(id=1297571041635754679, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=CN, label=图9, caption=不同组别间微生物-差异代谢物相关性分析热图, figureFileSmall=/JVSARhd3lGus5nXLeFjMQ==, figureFileBig=O6L2ry1RfLmRBwkmkkE9Gw==, tableContent=null), ArticleFig(id=1297571041698669240, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1297571034408968781, language=EN, label=Table 1, caption=

Mass spectrometry conditions

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ProjectParameters
Auxiliary airflow rate/psi13
Sheath gas flow rate/psi50
Capillary temperature/℃325
Auxiliary gas heating temperature/℃425
Positive mode ion spray voltage/V3 500
Negative mode ion spray voltage/V-3 500
Normalized collision energy/VCyclic collision energy (20-40-60 V)
Primary MS resolution60 000
Secondary MS resolution7 500
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质谱条件

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ProjectParameters
Auxiliary airflow rate/psi13
Sheath gas flow rate/psi50
Capillary temperature/℃325
Auxiliary gas heating temperature/℃425
Positive mode ion spray voltage/V3 500
Negative mode ion spray voltage/V-3 500
Normalized collision energy/VCyclic collision energy (20-40-60 V)
Primary MS resolution60 000
Secondary MS resolution7 500
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早产与足月婴儿不同喂养方式下的肠道微生物组及代谢组特征比较
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殷家琪 1 , 王爽 2 , 刘嘉琦 1 , 丁丽娜 1 , 邹静 1 , 刘骏文 1 , 金瑶 1 , 郦萍 1 , 顾青 1 , 韩佳润 1
微生物学报 | 研究报告 2026,66(8): 3926-3952
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微生物学报 |研究报告 2026 , 66 (8) : 3926 -3952
早产与足月婴儿不同喂养方式下的肠道微生物组及代谢组特征比较
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殷家琪1, 王爽2, 刘嘉琦1, 丁丽娜1, 邹静1, 刘骏文1, 金瑶1, 郦萍1, 顾青1 , 韩佳润1
作者信息
  • 1.浙江工商大学 食品与生物工程学院,全省食品微生物与营养健康重点实验室,浙江 杭州
  • 2.沈阳市妇婴医院,辽宁 沈阳
通讯作者:
顾青, 韩佳润
作者简介:

作者贡献声明

殷家琪:方案设计、实验操作、初稿写作;王爽:样本采集、方案设计;刘嘉琦:协助实验操作、稿件修改;丁丽娜:方法论、数据收集和处理;邹静:软件程序,数据收集与监管;刘骏文:提供材料,协助实验操作;金瑶:协助实验操作;郦萍:论文润色修改;顾青:提供技术支持;韩佳润:研究构思和设计、监督指导、经费支持。

Comparison of gut microbiome and metabolome characteristics in preterm and full-term infants under different feeding modes
Jiaqi YIN1, Shuang WANG2, Jiaqi LIU1, Lina DING1, Jing ZOU1, Junwen LIU1, Yao JIN1, Ping LI1, Qing GU1 , Jiarun HAN1
Affiliations
  • 1.Zhejiang Key Laboratory of Food Microbiology and Nutritional Health, School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang, China
  • 2.Shenyang Woman’s and Children’s Hospital, Shenyang, Liaoning, China
  • Corresponding Author:
    E-mail: HAN Jiarun, ;
出版时间: 2026-08-04 doi: 10.13343/j.cnki.wsxb.20260127
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生命早期是婴儿肠道微生态建立与代谢功能塑形的关键窗口期,胎龄与喂养方式被认为是影响该过程的核心决定因素。 【目的】 比较早产与足月婴儿在母乳与非母乳喂养条件下粪便肠道微生物组及代谢组的差异,解析不同喂养方式与胎龄对婴儿早期肠道微生态及代谢特征的影响。 【方法】 将受试婴儿分为早产母乳喂养(breastfeeding preterm infants, BPI)、早产非母乳喂养(non-breastfeeding preterm infants, NBPI)、足月母乳喂养(breastfeeding full-term infants, BTI)、足月非母乳喂养(non-breastfeeding full-term infants, NBTI) 4组,每组10例,进行16S rRNA基因肠道微生物组测序及非靶向代谢组学分析。采用α/β多样性分析、差异丰度分析与线性判别分析效应大小(linear discriminant analysis effect size, LEfSe)筛选关键肠道微生物菌群;通过偏最小二乘判别分析(partial least squares-discriminant analysis, PLS-DA)、火山图与KEGG通路富集分析鉴定差异代谢物与功能通路,并构建微生物-代谢物关联网络。 【结果】 16S rRNA测序结果显示,BTI组以放线菌门(Actinomycetota)、双歧杆菌属(Bifidobacterium)、短双歧杆菌(Bifidobacterium breve)为特征性优势菌(双歧杆菌属占比45.98%),形成典型的“母乳型”结构;BPI组则以假单胞菌门(Pseudomonadota)与链球菌属(Streptococcus)富集为特征,双歧杆菌优势减弱。非母乳喂养组中,NBTI组以肠球菌属(Enterococcus)为优势属(59.20%),NBPI组菌群结构波动较大。非靶向代谢组学进一步揭示了与上述菌群结构对应的功能差异。KEGG通路富集表明差异主要集中于氨基酸代谢、脂质代谢、胆汁酸相关通路及碳水化合物消化吸收等通路。关键代谢物层面,BPI组中谷胱甘肽、维生素D硫酸酯等与抗氧化和免疫支持相关的代谢物显著富集,BTI组富集长链多不饱和脂肪酸与吲哚类代谢物,非母乳喂养组普遍积累可发酵碳水化合物及特定胆汁酸衍生物。相关性分析表明,母乳喂养组中双歧杆菌与吲哚类代谢物水平呈强正相关,而非母乳喂养组的菌群-代谢物关联网络更为松散。 【结论】 胎龄与喂养方式均与婴儿早期肠道菌群结构及代谢特征差异相关,其中喂养方式与代谢谱差异的关联更为突出,胎龄可能影响母乳喂养背景下优势菌群的建立模式。本研究作为一项先导性探索,初步揭示了不同群体婴儿肠道菌群结构与功能代谢的特异性,为后续前瞻性队列验证、机制研究及早期营养干预优化提供了依据。

胎龄  /  喂养方式  /  婴儿  /  肠道微生物组  /  代谢组  /  菌群-代谢关联

Early life is a critical window for the establishment of the infant gut microbiome and the shaping of its metabolic functions, and gestational age and feeding mode are considered key determinants of this process. [Objective] To compare the fecal gut microbiome and metabolome between preterm and full-term infants under breastfeeding and non-breastfeeding conditions, thus exploring the effects of feeding mode and gestational age on early-life gut microbial ecology and metabolic features. [Methods] Infants were assigned into four groups: breastfeeding preterm infants (BPI), non-breastfeeding preterm infants (NBPI), breastfeeding full-term infants (BTI), and non-breastfeeding full-term infants (NBTI), with 10 infants per group. The 16S rRNA gene sequencing and untargeted metabolomics analysis were performed. Alpha/beta diversity analyses, differential abundance testing, and linear discriminant analysis effect size (LEfSe) were performed to identify key microbial taxa. Partial least squares-discriminant analysis (PLS-DA), volcano plots, and KEGG pathway enrichment were employed to determine differential metabolites and functional pathways, followed by microbiome-metabolite association network analysis. [Results] The 16S rRNA gene sequencing showed that the gut microbiome in the BTI group was dominated by Actinomycetota, Bifidobacterium (45.98%), and Bifidobacterium breve, forming a typical “breastfeeding-type” structure. The BPI group showed enrichment of Pseudomonadota and Streptococcus, with attenuated dominance of Bifidobacterium. Among non-breastfed infants, the NBTI group was dominated by Enterococcus (59.20%), whereas the NBPI group showed a fluctuating gut microbiome. Untargeted metabolomics further revealed functional differences consistent with these compositional patterns. KEGG enrichment indicated that differential metabolites were mainly involved in amino acid metabolism, lipid metabolism, bile acid-related pathways, and carbohydrate digestion and absorption. At the level of key metabolites, the BPI group showed significant enrichment of metabolites related to antioxidant and immune support, such as glutathione and vitamin D sulfate conjugates; the BTI group enriched long-chain polyunsaturated fatty acids and indole-derived metabolites; and non-breastfeeding groups generally exhibited accumulation of fermentable carbohydrates and specific bile acid derivatives. Correlation analysis confirmed a strong positive association between Bifidobacterium and indole-related metabolite outputs in breastfeeding groups, whereas microbiome–metabolite networks were looser in non-breastfeeding groups. [Conclusion] Both gestational age and feeding mode are related to differences in the early gut microbiome structure and related metabolic characteristics of infants, with the association between feeding mode and metabolic profile differences being more prominent. Gestational age may affect the establishment pattern of dominant microbial taxa in the context of breastfeeding. As a pioneering exploratory study, this study preliminarily reveals the specificity of gut microbiome structure and functional metabolism in different populations of infants, providing a basis for subsequent prospective cohort validation, mechanism research, and early nutritional intervention optimization.

gestational age  /  feeding mode  /  infant  /  gut microbiome  /  metabolome  /  microbiome-metabolome association
殷家琪, 王爽, 刘嘉琦, 丁丽娜, 邹静, 刘骏文, 金瑶, 郦萍, 顾青, 韩佳润. 早产与足月婴儿不同喂养方式下的肠道微生物组及代谢组特征比较. 微生物学报, 2026 , 66 (8) : 3926 -3952 . DOI: 10.13343/j.cnki.wsxb.20260127
Jiaqi YIN, Shuang WANG, Jiaqi LIU, Lina DING, Jing ZOU, Junwen LIU, Yao JIN, Ping LI, Qing GU, Jiarun HAN. Comparison of gut microbiome and metabolome characteristics in preterm and full-term infants under different feeding modes[J]. Acta Microbiologica Sinica, 2026 , 66 (8) : 3926 -3952 . DOI: 10.13343/j.cnki.wsxb.20260127
人体肠道微生态在生命早期经历快速建立与动态演替,这一过程与宿主营养代谢、免疫成熟及后续健康结局密切相关[1-2]。然而,肠道微生态并非一成不变,而是随年龄呈现阶段性、有序的发育过程[3]。婴儿肠道菌群的定殖始于出生即刻,初期菌群构成主要源于分娩过程中的直接暴露(如母体阴道、皮肤、羊水、胎盘等处的微生物),随后宿主生理环境与营养底物共同对定殖菌群进行筛选与重塑[4]。在健康婴儿肠道中,最初数周以需氧菌(如大肠杆菌、葡萄球菌)和兼性厌氧菌(如肠杆菌、肠球菌和链球菌等)为主[5];随着肠道内氧含量下降及营养结构变化,专性厌氧菌(如拟杆菌属、双歧杆菌属及梭状芽孢杆菌属)逐渐增殖并开始定殖[6-7]。Stewart等[8]研究表明,婴儿肠道菌群一直处于动态、非随机的变化过程,菌群发育可分为发育期(3-14个月,以双歧杆菌为优势属)、过渡期(15-30个月)与稳定期(≥31个月,芽孢杆菌门占主导,细菌多样性增高)共3个阶段。传统观点认为,婴儿在2岁左右可形成类似于成人的、稳定的肠道菌群结构[9],但近期纵向研究表明,其完全成熟可能耗时更久,且速度与轨迹存在显著的个体差异[10]。因此,生命早期被认为是人体肠道微生态系统建立与演替的关键“窗口期”,其定殖轨迹不仅反映肠道生态的初始装配过程,也可能影响后续代谢和免疫稳态[11-12]
在影响婴儿肠道微生态的诸多因素中,胎龄被证实是塑造婴儿早期肠道微生态结构与功能的核心决定因素[13-15]。近年来,国内外围绕“胎龄-喂养-微生态-疾病风险”的研究持续升温,尤其关注早产儿因生理不成熟与医疗暴露带来的微生态脆弱性及其临床结局的关联。胎龄不满37周即被判定为早产。与足月儿相比,早产儿由于肠道屏障和免疫功能发育不成熟,同时可能伴随新生儿重症监护室(neonatal intensive care unit, NICU)环境暴露、鼻胃喂养、肠内营养启动延迟以及广谱抗生素使用等干预,常表现出菌群定殖延迟、微生物多样性降低、双歧杆菌优势不足、假单胞菌门升高及个体差异增大等典型特征[16-17]。Sadeghpour等[18]研究发现,早产儿的肠道微生态失调与坏死性小肠结肠炎、晚发型败血症等严重并发症风险升高密切相关,且并非由单一病原体驱动,而是由多种机会致病菌的群落失衡与宿主炎症易感共同促发。此外,早产状态不仅影响菌群组成,还可能伴随代谢功能特征的改变,表现为与脂质代谢相关的基因丰度升高,而与能量代谢、辅因子合成相关的基因丰度降低[19]
除胎龄之外,喂养方式是造成婴儿肠道菌群差异的另一关键要素。足月、自然分娩且母乳喂养的婴儿常被视为肠道菌群健康发育的“参照模式”,其菌群通常以双歧杆菌属(Bifidobacterium)与拟杆菌属(Bacteroides)等有益菌占优势,并随月龄增长逐步走向多样化[20]。母乳除提供营养外,还含有母乳低聚糖(human milk oligosaccharides, HMOs)、分泌型IgA (secretory immunoglobulin A, sIgA)、乳铁蛋白及免疫球蛋白等多种生物活性因子,可通过“选择性底物+免疫调节”共同塑造婴儿肠道生态位[21]。其中,HMOs被认为是母乳塑造菌群的关键分子之一,可促进具有HMO利用能力的特定双歧杆菌(如B. longum subsp. infantis)定殖并增强其代谢活性,从而影响乳酸、乙酸等发酵产物生成及肠道免疫稳态[22]。相比之下,配方奶虽在宏量营养上趋近母乳,但其碳水来源和配方结构差异可使婴儿肠道菌群更趋“成人化”,表现为梭菌属(Clostridium)、链球菌属(Streptococcus)等相对丰度升高,并伴随蛋白质发酵相关代谢路径增强[23-24]
值得注意的是,近年研究热点已从婴儿“菌群组成”逐步转向“代谢功能”。多组学整合策略使群落结构、代谢通路、免疫表型和临床结局之间的联系得以系统揭示。肠道微生物可通过发酵膳食成分或转化宿主来源底物产生短链脂肪酸、胆汁酸、氨基酸衍生物等多类代谢物,这些小分子不仅反映菌群功能状态,也可参与微生物-宿主互作。研究表明,乙酸、丁酸等短链脂肪酸既是肠上皮能量底物,也可通过G蛋白偶联受体(G protein-coupled receptors, GPCRs)信号或抑制组蛋白去乙酰化酶(histone deacetylase, HDAC)活性调节炎症反应与屏障功能[25]。尽管婴儿肠道微生物组研究进展显著,但目前多集中于单因素比较且以16S rRNA基因扩增子测序揭示菌群结构特征为主,缺乏在同一队列框架下将胎龄与喂养方式进行交叉组合并整合代谢组信息开展系统比较的横断面研究。因此,针对“胎龄×喂养方式”组合条件下婴儿早期肠道微生态结构及其相关代谢特征是否存在差异仍缺乏较为完整的群体层面证据。基于此,本研究选取临床特征明确的早产与足月婴儿队列,根据不同的喂养方式(纯母乳喂养、非母乳喂养)进行分组,采用高通量测序技术联合非靶向代谢组学技术,同步解析4组粪便微生物群落结构特征及代谢产物谱系,并通过菌群-代谢物关联网络筛选关键差异微生物及特征代谢标志物,旨在阐明胎龄差异背景下不同喂养方式如何差异化地塑造婴儿肠道微生态系统及其代谢功能网络,为优化早产儿的临床营养支持策略、促进其肠道微生态健康成熟提供科学依据和理论支撑。
选取2025年4月至2025年10月期间在沈阳市妇婴医院新生儿病房就诊的孕晚期健康孕妇,母亲纳入及排除标准如下。纳入标准:(1) 20-35岁;(2) 身体健康;(3) 不吸烟、不酗酒;(4) 本市居住3年及以上。排除标准:(1) 肠炎;(2) 1型/2型糖尿病、高血压;(3) 感染性疾病(肺结核、病毒性肝炎、梅毒和HIV感染);(4) 精神疾病及记忆障碍;(5) 肿瘤、肝肾衰竭等重大疾病;(6) 母体围产期存在系统性抗生素暴露。
采用横断面队列研究,为减少分娩方式对新生儿早期肠道菌群定殖的影响,本研究纳入的4组婴儿均为阴道分娩。依据出生时的胎龄和喂养方式,将婴儿分为以下4组(每组10例):早产母乳喂养组(breastfeeding preterm infants, BPI) (29-36周)、早产非母乳喂养组(non-breastfeeding preterm infants, NBPI) (29-36周)、足月母乳喂养组(breastfeeding full-term infants, BTI) (37-42周)和足月非母乳喂养组(non-breastfeeding full-term infants, NBTI) (37-42周)。本研究中“非母乳喂养“定义为纯配方奶喂养,不包括混合喂养个体。新生儿纳入标准:法定监护人均提供知情同意书。排除标准:(1) 存在严重先天性畸形或出生缺陷;(2) 合并明确感染性疾病或其他严重器质性疾病;(3) 出生后接受系统性抗生素治疗。本研究流程图见图1。鉴于本研究样本量较小,且部分围产期资料未纳入多变量统计模型,本研究现阶段主要强调不同胎龄与喂养方式相关的群体差异特征,而未对其作严格的独立因果推断。
采用统一的粪便样本采集流程。本研究中所有采集的样本均限定为婴儿出生后第3-7天的过渡期粪便。婴儿排便后尽快收集纸尿裤上的新鲜粪便,使用一次性无菌采便勺取样并转移至预先标记编号的无菌采便管中,每份样本取样量不少于2勺。采样过程中避免粪便与尿液混合,以减少外源污染及样本稀释风险。采集完成后立即旋紧管盖,记录样本编号、采集日期、受试者分组信息(BPI、NBPI、BTI、NBTI)及当次喂养情况等基本信息。样本采集后立即送至实验室,置于-80 ℃冰箱保存,待后续DNA提取与代谢组学检测。
取粪便样本约200 mg,使用QIAamp PowerFecal Pro DNA Kit (Qiagen公司)试剂盒提取总基因组DNA。随后使用NanoDrop One超微量分光光度计(ThermoFisher Scientific公司)评估提取的DNA浓度与纯度,并在1%琼脂糖凝胶上进行验证。以提取的DNA为模板,使用细菌通用引物338F (5′-ACTCCTACGGGAGGC AGCAG-3′)和806R (5′-GGACTACHVGGGTWT CTAAT-3′)对16S rRNA基因V3-V4高变区进行PCR扩增。PCR反应由北京诺禾致源科技股份有限公司完成。PCR反应体系(20 μL):5×Trans Start Fast Pfu Buffer 4 µL,dNTPs (2.5 mmol/L) 2 µL,上、下游引物(5 µmol/L)各0.8 µL,Trans Start Fast Pfu DNA聚合酶(2.5 U/μL) 0.4 μL,DNA模板0.5 µL,ddH2O 11.5 µL。PCR反应条件:95 ℃预变性5 min;95 ℃变性30 s,58 ℃退火30 s,72 ℃延伸1 min,共32个循环;72 ℃终延伸10 min。所得PCR产物经2%琼脂糖凝胶电泳确认条带大小与特异性后,采用GeneJET Gel Extraction Kit (ThermoFisher Scientific公司)凝胶提取试剂盒纯化。随后使用NEB Next® UltraTM DNA Library Prep Kit for Illumina根据制造商说明构建测序文库,并在Illumina HiSeq 2500 PE250平台上进行双端测序。16S rRNA基因测序分析委托北京诺禾致源科技股份有限公司完成。
Illumina平台获得的双端原始序列数据首先在QIIME 2中进行质控与预处理,包括去除低质量碱基、截取引物/接头序列以及过滤含N碱基或异常长度序列。随后采用DADA2插件对双端序列进行去噪、纠错、嵌合体去除与序列拼接,获得高质量的扩增子序列变体(amplicon sequence variants, ASVs),并生成ASV特征表。物种注释基于SILVA 138/16S参考数据库,对ASV代表序列进行分类学赋值,并将ASV丰度与样本编号进行关联,用于下游群落结构分析。α多样性采用ACE、Chao1、Shannon、Simpson指数等指标评估群落丰富度与均匀度;β多样性基于Bray-Curtis距离矩阵进行计算,并通过PCoA等排序方法展示样本间差异。组间差异菌群鉴定采用线性判别分析效应大小(linear discriminant analysis effect size, LEfSe),筛选阈值设定为线性判别分析值(linear discriminant analysis, LDA)>4.0且P<0.05,以识别能够区分不同组别的关键分类单元。
取-80 ℃保存的婴儿粪便样本置于冰上解冻,充分混匀后称取50 mg于1.5 mL离心管中,加入400 μL提取液(水:甲醇=1:4,含终浓度0.02 mg/mL的L-2-氯苯丙氨酸)和研磨珠,用于代谢物提取。粪便样本在组织研磨仪(50 Hz)中-10 ℃低温研磨6 min,研磨结束后置于超声水浴中超声萃取30 min (40 kHz、5 ℃)。随后将样本置于-20 ℃静置30 min,4 ℃、13 000×g离心15 min,收集上清液作为待测样本。
采用LC-MS/MS开展非靶向代谢组学检测。分离条件如下:流动相A为乙腈(含0.1%甲酸):水=1:19;流动相B为乙腈(含0.1%甲酸):水:异丙醇=19:2:19 (体积比)。色谱柱温度设定为40 ℃,流速0.4 mL/min,进样量3 μL。质谱采用电喷雾离子源(electrospray ionization, ESI)在正、负离子模式下采集数据,具体参数见表1
质谱原始数据首先使用ProteoWizard转换为mzXML格式,随后采用XCMS进行峰提取、峰对齐与保留时间校正。对样本内提取的总峰面积进行校正,并过滤各组样本中缺失率>50%的峰以获得高质量的代谢特征矩阵。代谢物鉴定通过检索诺禾致源数据库获得代谢物注释信息,并在此基础上开展后续统计分析与功能解释。
采用主成分分析(principal component analysis, PCA)评估整体分布及QC稳定性,并结合偏最小二乘判别分析(partial least squares-discriminant analysis, PLS-DA)筛选不同组别的差异代谢特征。差异代谢物筛选综合考虑PLS-DA的变量投影重要度(variable importance in the projection, VIP)、差异倍数(fold change, FC)与显著性水平(P-value):设定阈值为VIP>1.0、|log2 FC|>1且P<0.05。筛选得到的差异代谢物进一步用于HMDB/KEGG代谢通路等功能分析,以解释其潜在生物学意义。
为揭示肠道菌群变化与代谢表型之间的潜在联系,选取组间差异显著的菌群与关键代谢物进行Spearman相关性分析。考虑到相关性分析涉及多重并行检验,采用Benjamini-Hochberg方法对所得P值进行假发现率(false discovery rate, FDR)校正,并以校正后的q值评估统计学显著性。
实验数据以平均值±标准差(mean±SD)表示,采用GraphPad Prism 9、IBM SPSS Statistics 26等软件进行统计分析和相关性分析。α多样性指数采用两因素方差分析(two-way ANOVA)进行组间交互作用分析评估显著性;β多样性分析采用置换多元方差分析(permutational multivariate analysis of variance, PERMANOVA)评估组间群落结构差异;使用Benjamini-Hochberg方法对Spearman相关性检验所得P值进行FDR校正,其中P<0.05或q<0.05被视为差异具有统计学意义。所有实验均设置10个生物学重复。
生命早期肠道微生态处于快速装配与演替阶段,群落多样性既受先到优势影响,也高度依赖营养底物与宿主发育状态[26]。基于ASV水平的Venn图分析显示(图2A),4组样本存在一定的核心菌群,78个ASV在4组中均被检出。同时,各组也呈现明显的组特异性定殖特征,其中BPI组特异性ASV数量最高(1 100个),明显高于BTI组(36个)、NBPI组(13个)和NBTI组(51个),提示早产母乳喂养组的个体差异与群落异质性更为突出,这可能与早产儿肠道屏障及免疫功能未成熟有关。同时,不同个体在住院环境暴露、营养支持策略及其他围产期因素方面的差异也可能进一步放大其菌群定殖轨迹的异质性[16]。β多样性PCoA结果显示,PCoA1与PCoA2分别解释了35.81%与19.71%的群落差异。4组样本的群落结构在二维空间中存在一定的分离趋势,但仍有明显重叠,表明胎龄与喂养方式对菌群结构具有一定的影响,但组间差异并非完全由单一因素驱动,个体差异仍较为显著(图2B)。
在α多样性方面,ACE与Chao1指数在4组间整体差异不大,但BPI组的Chao1指数总体偏高且离散度较大,推测该组物种丰富度在个体间波动更明显(图2C2D)。此外,Simpson指数和Shannon指数在组间出现显著差异,其中BPI组Simpson指数高于NBPI组,但Shannon指数相反,NBTI组略高于BTI组,说明无论是足月还是早产儿,非母乳喂养婴儿的肠道微生物多样性和丰富度均高于母乳喂养组(图2E-2F)。然而值得注意的是,在婴儿早期,更高的微生物多样性并不代表更健康。研究指出,母乳中的HMOs等活性成分会选择性促进双歧杆菌等优势菌的扩增,使群落呈现更明显的优势菌主导,从而降低Shannon等均匀度指标。这种低多样性但优势益生菌主导的状态在生命早期常被视为母乳喂养的典型微生态特征[27-28]。因此,本研究中BPI和BTI组多样性和丰富度偏低可能反映母乳喂养促使特定类群占优或菌群成熟延迟,还需要结合微生物群落组成进一步分析。
在门及属水平的相对丰度分析显示,4组菌群组成存在明显差异(图3)。在门水平(图3A)上,4组样本均以变形菌门(Proteobacteria)、假单胞菌门(Pseudomonadota)与放线菌门(Actinomycetota)为主,但其相对丰度分布存在差异。BPI组假单胞菌门占比最高,说明早产母乳喂养婴儿肠道中以兼性厌氧菌及条件致病菌相关类群为主的特征更为突出。BTI组放线菌门占比最高,与足月母乳喂养婴儿肠道菌群常见的“放线菌门-双歧杆菌属”为优势的模式一致。此外,NBTI组芽孢杆菌门的比例显著高于其他组,提示足月非母乳喂养婴儿的肠道菌群更偏向芽孢杆菌门主导的模式。
在属水平(图3B)上,4组样本的优势菌属分化更为明显。BTI组以双歧杆菌属(Bifidobacterium)为最主要优势属(45.98%),且显著高于其他3组(P<0.000 5) (图3C),表明足月母乳喂养对双歧杆菌定殖具有最强促进作用,这也与既往研究报道的母乳喂养婴儿菌群模式一致[27]。已有研究表明,母乳中的HMOs等活性成分可作为选择性底物,促进具有HMO利用能力的双歧杆菌扩增,从而形成以“Actinobacteriota/Bifidobacterium”为优势的典型母乳型生态格局[29]。同时,BTI和BPI组乳杆菌属(Lactobacillus)的相对丰度(0.92%和0.50%)显著高于NBTI和NBPI组(0.05%和0.28%) (图3D),这可能也与母乳喂养促进酸化环境、促进益生菌肠道定殖并抑制部分致病菌定殖的机制相关[30]。值得注意的是,尽管同为母乳喂养,BPI组并未表现出与BTI组相当的双歧杆菌优势,反而呈现更高的链球菌属(Streptococcus)相对丰度(18.72%) (图3E)。这表明“胎龄”可能影响母乳喂养的微生态效益。早产儿由于肠道屏障和免疫功能发育尚不成熟,且可能伴随住院环境暴露、营养支持差异及围产期医疗干预等因素,其菌群定殖更易偏向兼性厌氧菌相关“未成熟型”结构[17]。多项研究指出,早产儿肠道中假单胞菌门(尤其肠杆菌科)的富集常与肠道炎症易感性及坏死性小肠结肠炎风险增加相关,是菌群失调的典型标志之一[18]。因此,BPI组较高水平的PseudomonadotaStreptococcus可能反映了早产背景下肠道生态位不稳定、定殖轨迹更易受外部因素干扰。此外,NBTI组表现出肠球菌属(Enterococcus)的显著优势(59.20%) (图3F)。这一结果与既往关于配方奶喂养婴儿中Enterococcus丰度升高的报道[31]一致。作为生命早期常见的兼性厌氧定殖菌,EnterococcusStreptococcus的相对富集既可代表早期定殖阶段延长或群落成熟延迟,也可能反映在特定营养结构下某些菌群的过度增殖。由于部分菌株具有机会致病潜力,因此相关结果仍需结合婴儿临床背景谨慎解读。
对婴儿粪便样品进行微生物区系的划分是分析微生物在发酵过程中变化规律的基础。基于此,本研究进一步通过LEfSe对4组样本具有显著差异的群落进行筛选,旨在识别与胎龄和喂养方式显著相关的特征性微生物类群。相应的节点表明细菌群显著富集,分类水平如图4所示。在本研究设定的筛选阈值下,仅BPI、BTI和NBTI三组检出了达到显著富集标准的代表性标志菌群,而NBPI组未检出满足筛选阈值的特征分类单元(图4)。BTI组显著富集放线菌门及双歧杆菌谱系(包括p_Actinobacteriota、c_Actinomycetota、o_Bifidobacteriales、f_Bifidobacteriaceae、g_Bifidobacterium),并在物种层面富集Bifidobacterium breve。NBTI组显著富集g_Enterococcus及f_Enterococcaceae,而BPI组则富集f_Burkholderiaceae与g_Cupriavidus。上述差异特征的LDA评分整体较高(>4),表明其对不同组别具有较好的区分能力,可作为不同胎龄与喂养方式背景下菌群结构差异的潜在生物标志物。在本研究中,BTI组呈现由“门-种”层面的双歧杆菌相关谱系连续富集,说明足月母乳喂养更易建立结构一致性强、系统发育连续的双歧杆菌生态位[32]。相较之下,BPI组富集到f_Burkholderiaceae,这表明即便在母乳喂养条件下,早产儿仍可能因肠道屏障与免疫发育不足而呈现不稳定的定殖轨迹[33]。此外,NBTI组以g_Enterococcus相关分类单元富集为主要特征,提示非母乳喂养背景下菌群组成模式与母乳喂养组存在明显差异。总体来看,LEfSe结果证实了不同胎龄与喂养方式组合条件下婴儿肠道菌群具有不同的特征性富集模式。母乳喂养在足月儿中更容易建立以双歧杆菌为核心的母乳型生态,而早产儿中这一特征相对减弱。非母乳喂养条件下,群落可能更偏向芽孢杆菌门及肠球菌属等类群。这些差异菌群可为后续结合代谢组数据解析不同组别的菌群结构与代谢特征关联模式提供候选标志物。
为了解婴儿粪便代谢物的整体功能特征与化学类别,本研究分别基于KEGG、HMDB和LIPID MAPS数据库对鉴定到的代谢物进行注释与分类。KEGG功能注释结果显示(图5A),本研究鉴定到的代谢物可映射至多个通路层级,其中以代谢(metabolism)相关通路最为突出,主要涵盖全局代谢概览(global and overview maps)、碳水化合物代谢(carbohydrate metabolism)、氨基酸代谢(amino acid metabolism)、脂质代谢(lipid metabolism)以及辅因子与维生素代谢(metabolism of cofactors and vitamins)等。同时也可注释到环境信息处理(environmental information processing)、遗传信息加工(genetic information processing)、生物体系统(organismal systems)及人类疾病(human diseases)等相关通路,表明婴儿粪便代谢特征主要与脂质、氨基酸和碳水化合物等基础代谢过程相关。HMDB化学分类表明(图5B),鉴定到的代谢物主要分布于12个大类,其中脂类及脂样分子(lipids and lipid-like molecules)与有机酸及其衍生物(organic acids and derivatives)所占比例最高,其次为有机杂环化合物(organoheterocyclic compounds)、有机含氧化合物(organic oxygen compounds)等。这种由“脂类+有机酸”主导的粪便代谢物谱系符合生命早期营养与微生物生态的基本特征。已有研究表明,婴儿粪便中的脂质特征可能与母乳/配方乳的脂质供给、脂肪酸吸收及胆汁酸介导的消化过程有关[34-35],而有机酸及其衍生物则可能同时反映宿主代谢状态与肠道微生物对底物的发酵转化[36]。LIPID MAPS注释结果进一步显示(图5C),婴儿粪便脂质以脂肪酰类(fatty acyls)为主,其中脂肪酸及缀合物(fatty acids and conjugates, FA01)数量最多。此外,固醇脂类(sterol lipids)中以类固醇缀合物(steroid conjugates, ST05)与胆汁酸及衍生物(bile acids and derivatives, ST04)较为突出,并检出一定数量的甘油磷脂(glycerophospholipids)相关亚类。这些结果表明,婴儿粪便脂质特征主要集中于脂肪酸、胆汁酸/固醇及膜磷脂相关分子。研究表明,脂肪酸链长与不饱和度是决定小肠对膳食脂肪酸吸收效率的重要因素,其差异可反映脂类供给与吸收效率的变化[37];胆汁酸谱变化则可能与肠道菌群的胆汁酸转化能力、肠道屏障与炎症状态密切相关[38];而甘油磷脂类变化通常与膜脂代谢及炎症相关脂质信号前体有关[39]。因此,这些注释结果可为后续比较4组样本之间的差异代谢物及其与差异菌群间的关联模式提供功能背景和候选方向。
基于多变量统计模型观察到4组样本间代谢谱呈现可区分的整体差异。如图6所示,在4组粪便两两比较中,样本在得分图上均出现不同程度的分离。在相同胎龄下(NBPI vs. BPI、NBTI vs. BTI),不同喂养方式组之间表现出较明显的代谢谱分离趋势,PC1轴解释了约19.67%和11.49%的变异,且模型拟合优度(R2Y)较高,说明喂养方式可能与代谢特征差异密切相关。在相同喂养方式下(BTI vs. BPI, NBTI vs. NBPI),尤其是非母乳喂养组(NBTI vs. NBPI)的PC1解释方差相对较低(11.47%),提示胎龄的影响在非母乳喂养条件下可能相对减弱,或与其他因素的交互作用更为复杂。与此同时,在对应的置换检验结果中,各比较组的Q2截距均为负值(约-0.50--0.72),提示模型不存在明显过拟合,具有一定稳健性。
在单变量差异筛选与通路富集层面,火山图显示NBPI vs. BPI组共筛得差异代谢物104个(上调33个、下调71个),提示在早产背景下,喂养方式改变可引起较明显的代谢谱重塑(图7A)。KEGG通路显示,这些差异代谢物主要涉及氨基酸代谢相关通路(如半胱氨酸和蛋氨酸代谢、支链氨基酸生物合成)、甾醇/脂质相关通路(如类固醇生物合成、不饱和脂肪酸生物合成)及维生素消化吸收等(图7B)。在NBTI vs. BTI组中,共筛得差异代谢物76个(上调46个、下调30个) (图7C),其富集通路主要集中在代谢通路和不饱和脂肪酸生物合成通路,并伴随氨基糖与核苷酸糖代谢、碳水化合物消化吸收、半乳糖代谢等途径(图7D),表明在足月背景下,喂养方式可能对脂质与碳水化合物代谢轴的影响更为集中。研究表明,早期喂养方式(母乳、配方乳或混合喂养)可显著改变婴儿粪便代谢谱及其功能通路分布[40-41],其中母乳喂养可通过促进特定双歧杆菌增殖,推动芳香族氨基酸向芳香族乳酸(如吲哚乳酸)等微生物衍生代谢物转化,从而在色氨酸代谢通路上产生显著的功能差异[32]。此外,在相同母乳喂养背景下(BTI vs. BPI)观察到88个差异代谢物(上调60个、下调28个)(图7E),且富集通路主要涉及色氨酸代谢、甘油酯代谢、淀粉和蔗糖代谢及乙醛酸和二羧酸代谢(图7F),表明胎龄差异可能与氨基酸及脂质相关代谢特征变化有关[32]。在相同非母乳喂养背景下(NBTI vs. NBPI),共检测到79个差异代谢物(上调40个、下调39个) (图7G),其富集通路以碳水化合物消化吸收、亚油酸代谢、胆汁酸代谢及不饱和脂肪酸生物合成等为主(图7H),表明即便在非母乳喂养方式下,胎龄差异仍可通过“脂质吸收-胆汁酸循环-微生物改造”这一功能轴产生影响。Davis等[42]研究表明,婴儿早期胆汁酸谱与喂养方式密切相关。母乳喂养可能与特定胆汁酸形式(如硫酸化胆汁酸)相关,而配方乳喂养更易出现微生物转化后的次级胆汁酸特征,且胆汁酸与某些特定菌群(如Clostridia)显著相关。McCloskey等[43]基于脐带血脂质组学分析发现,胎龄与多类脂质分子谱呈显著关联,表明妊娠后期的代谢成熟过程会系统性重塑脂质组成,从而导致早产与足月儿在脂质代谢表型上存在差异。综上所述,胎龄与喂养方式均与婴儿代谢谱差异相关,涉及的通路主要集中于氨基酸代谢(尤其色氨酸相关)、脂质代谢、胆汁酸代谢及碳水化合物代谢等,上述结果为后续差异代谢物的筛选及进一步分析其与菌群特征之间的关联提供方向。
根据各组比较筛选得到的差异代谢物,对其FC值进行以2为底的对数转换(log₂FC),并按照log2 FC值进行排序,各取上下调前20的代谢物以火柴杆图展示,同时选取变化幅度较大的代表性代谢物以柱状图展示其组间丰度差异,结果如图8所示。在早产儿粪便中(BPI vs. NBPI),BPI组相对NBPI组显著升高的代谢物主要集中在谷胱甘肽、2-酮丁酸、全顺式-7,10,13,16,19-二十二碳五烯酸(all-cis-7,10,13,16,19-docosapentaenoic acid, DPA)、25-羟基维生素D3 3-硫酸酯以及7-脱氢胆固醇等(图8A8E-8I)。研究表明,早产儿普遍处于更高氧化应激风险与更脆弱的免疫发育状态,这通常与早产相关多种不良结局密切相关[44]。谷胱甘肽作为核心的内源性抗氧化剂,其水平升高可能与母乳相关底物输入、宿主代谢状态及肠道环境差异有关[45]。结合2-酮丁酸作为含硫氨基酸代谢与转硫途径中的重要中间体、可间接影响谷胱甘肽合成底物供给这一特点,表明母乳喂养可能通过提供前体底物或调节菌群代谢,促进早产儿发育过程中肠道抗氧化系统的建立与维持[46]。25-羟基维生素D3 3-硫酸酯是新生儿可检测的重要维生素D结合/转运形式之一,在循环中占据相当比例[47]。母乳中不仅存在游离维生素D相关代谢物,还可检测到硫酸化维生素D代谢物,且其水平受母体维生素D状态影响[48]。因此,BPI组25-羟基维生素D3 3-硫酸酯的升高可能与母乳来源输入及机体维生素D相关代谢状态有关,从而在粪便或循环中表现为更高水平。同时,7-脱氢胆固醇作为胆固醇和维生素D合成的重要前体,其水平升高可能暗示甾醇合成通路更为活跃,表明母乳喂养可能与早产儿体内更高的维生素D生物利用度及甾醇代谢需求相关。此外,长链多不饱和脂肪酸DPA的升高以及4-羟基巴豆酸等脂质衍生物的变化表明母乳喂养下脂质相关代谢特征存在差异,其来源可能同时涉及喂养底物组成及体内代谢过程[49]
在足月儿粪便中(BTI vs. NBTI),BTI组表现出更高水平的ω-3/ω-6长链多不饱和脂肪酸(如二十碳五烯酸和二十四碳四烯酸)及吲哚类代谢物(如吲哚乳酸、吲哚丁酸) (图8B8J-8M),呈现出典型的母乳脂质输入+母乳促进的双歧杆菌功能输出特征。已有研究表明,与母乳喂养相关的双歧杆菌可在婴儿肠道产生芳香族乳酸(如吲哚乳酸),并可通过AhR等途径影响免疫反应[32]。因此,BTI组中吲哚类代谢物的升高提示母乳促进的优势菌群与芳香族代谢特征之间可能存在一定关联,这与图3的结果一致。NBTI组则主要以更高水平的可发酵碳水化合物或寡糖相关分子(如1-蔗果三糖、麦芽三糖、麦芽五糖、棉子糖)为特征(图8N-8Q),表明配方乳所提供的碳水底物并不一定能够被所有婴儿肠道菌群以相同效率利用,尤其在早产或菌群定殖尚未充分成熟的背景下,喂养底物组成与菌群利用能力之间可能存在一定程度的不匹配[40]。因此,对于配方乳中寡糖或益生元类添加策略,未来需要更多结合婴儿早期菌群定殖状态及其底物利用能力进行优化。
进一步在相同喂养方式下比较胎龄差异发现,母乳喂养条件下(BTI vs. BPI),BTI组中吲哚丁酸、9,10-二羟基硬脂酸和N-硬脂酰脯氨酸的含量显著高于BPI组,而2′-岩藻糖基乳糖则相反(图8C8R-8U)。研究表明,母乳寡糖HMOs (如2′-岩藻糖基乳糖)可在婴儿粪便中检出,其排出水平可能与肠道菌群利用程度、宿主吸收状态及肠道转运过程等因素相关[50]。在同为母乳喂养条件下,BPI组中2′-岩藻糖基乳糖水平更高可能提示早产儿对其利用能力较弱或肠道端排出比例更高。同时,BTI组更高的9,10-二羟基硬脂酸及N-脂酰氨基酸样分子表明足月婴儿在脂质转化及微生物相关代谢特征方面可能存在与早产儿不同的群体差异,这一点也与既往关于早产儿肠道代谢谱随发育与喂养而动态变化的报道一致[51]。此外,在非母乳喂养条件下(NBTI vs. NBPI),NBTI组相对NBPI组升高的关键代谢物包括3-脱氢胆酸、乙基亚麻酸酯、甲基亚麻酸酯等,而共轭亚油酸(conjugated linoleic acid, CLA)在NBPI组中更高(图8D8V-8X),表明非母乳条件下足月与早产儿在胆汁酸衍生物及脂肪酸酯化与转化方面存在差异,这些差异可能与胎龄相关的脂质消化吸收能力、胆汁酸代谢状态及肠道菌群相关转化过程有关。早产儿肠道菌群更易处于未成熟的波动状态,胆汁酸去结合、氧化还原与进一步转化能力也可能与足月儿存在差异,最终表现为3-脱氢胆酸等代谢物的组间分化[52]。胆汁酸除参与脂质吸收外,也是重要信号分子,可通过FXR/TGR5等受体介导的通路影响胆汁酸稳态、肠道屏障及免疫炎症反应,因此其谱系变化可能具有一定的屏障-免疫相关意义[38]。此外,NBPI组CLA显著高于NBTI组,一方面反映早产儿在非母乳喂养时脂肪酸消化吸收效率较低,使更多CLA在肠腔端残留并随粪便排出;另一方面也可能与早产儿更易出现将亚油酸转化为CLA的菌群功能有关,从而提高了肠道内源性CLA的生成[53]。上述结果提示,胎龄与喂养方式均与婴儿肠道相关代谢特征差异有关,其表现可能涉及底物输入、宿主代谢状态及肠道微生态共同作用下的综合代谢表型。
采用Spearman相关分析评估各组内关键差异菌属与关键代谢物之间的潜在关联,并在多重检验校正后绘制相关性热图(图9)。总体来看,不同组别均呈现“菌群-代谢物”协同变动,但网络紧密度与主导模块存在明显差异。在BPI组中(图9A),网络以正相关为主,其中Bifidobacterium与谷胱甘肽、25-羟基维生素D3-3-硫酸酯、4-羟基巴豆酸、N2-半乳糖醛酸基-L-赖氨酸等呈显著正相关,与2-酮丁酸、DPA、7-脱氢胆固醇等呈显著负相关;Lactobacillus主要与4-羟基巴豆酸和7-脱氢胆固醇呈显著正相关;Enterococcus与DPA和2-酮丁酸呈显著正相关,提示在早产母乳喂养背景下,抗氧化、甾醇及脂质相关代谢特征可能与多类菌群变化存在关联。相较之下,NBPI组相关矩阵整体较为分散(图9B)。其中,EnterococcusEscherichia-ShigellaStreptococcus等机会致病或医院暴露常见菌属与CLA、3-脱氢胆酸呈显著负相关,但Escherichia-ShigellaStaphylococcusLactobacillus与乙基亚麻酸酯和甲基亚麻酸酯呈显著正相关。另外,Bifidobacterium与寡糖及脂质衍生物(如麦芽三糖、7-脱氢胆固醇、乙基亚麻酸酯、甲基亚麻酸酯)之间也呈现明显的正相关,这一特征可能与既往关于早产儿肠道微生态个体差异更大、波动更大的研究结论相符。在BTI组中,Bifidobacterium与吲哚乳酸、吲哚丁酸等吲哚类代谢物呈正相关,并与母乳底物相关分子如2′-岩藻糖基乳糖呈协同趋势(图9C),提示足月母乳喂养状态下,双歧杆菌优势生态位可能与芳香族代谢物输出之间存在一定联系。在NBTI组中(图9D),1-蔗果三糖、麦芽三糖、麦芽五糖、棉子糖等可发酵碳水/寡糖相关分子与部分菌属(如EnterococcusStreptococcusLactococcus)之间也呈一定的正相关趋势,同时胆汁酸衍生物3-脱氢胆酸与脂肪酸酯化分子(乙基亚麻酸酯和甲基亚麻酸酯)也与特定菌属(EnterococcusRothiaStaphylococcus)呈现正相关,表明非母乳喂养下未被完全消化吸收的膳食成分及其后续的微生物发酵与转化过程可能对粪便代谢谱具有一定的塑造作用。
母乳喂养组(BTI)中Bifidobacterium与吲哚乳酸、吲哚丁酸等芳香族吲哚衍生物呈稳定正向相关趋势,这与既往关于母乳相关双歧杆菌可能参与芳香族乳酸生成并通过AhR等通路参与免疫调控的报道一致[32]。同时,2′-岩藻糖基乳糖在粪便中的检出与排出水平可能与菌群利用程度相关,表明母乳底物供给与菌群代谢利用之间存在一定联系。相对地,非母乳喂养组(尤其NBTI)中可发酵碳水/寡糖相关分子与EnterococcusStreptococcusLactococcus等菌属之间聚类增强,表明配方乳相关碳水摄入或利用效率差异可能影响粪便端底物残留特征。考虑到部分配方奶中可能含有益生元寡糖等功能性成分,不同产品之间的底物组成差异可能影响粪便端可检测到的碳水/寡糖相关分子及其后续微生物利用模式[54],因此非母乳喂养下代谢谱可能在一定程度上反映摄入、消化及微生物利用之间的差异。NBPI与NBTI组中胆汁酸衍生物与脂肪酸酯化分子与特定菌属StaphylococcusEnterococcusRothiaLactobacillus之间也观察到一定的相关趋势,提示“脂质吸收-胆汁酸循环-微生物改造”轴有可能是连接胎龄差异与代谢特征变化的重要候选通路[55]。此外,早产母乳组(BPI)中谷胱甘肽及2-酮丁酸与Enterococcus等多菌属相关,提示母乳背景下前体底物供给与微生物代谢变化可能共同参与早产儿肠道抗氧化相关代谢特征的形成。需要强调的是,相关性分析仅能反映统计学层面的共变关系,而不能证明因果联系。结合本研究样本量较小及16S rRNA基因测序在功能层面分辨率有限的特点,本研究中菌群-代谢物相关结果更适合作为后续宏基因组学、靶向代谢组学及功能验证研究的候选线索。
本研究作为一项先导性的横断面多组学关联研究,在统一2×2分组框架下对不同胎龄与喂养方式组合条件下婴儿肠道菌群与代谢特征进行了初步比较。在肠道菌群方面,足月母乳喂养(BTI)更易建立以放线菌门-双歧杆菌谱系为核心的“母乳型”菌群特征,群落结构一致性强;而早产状态显著改变这一模式,早产母乳喂养(BPI)组双歧杆菌优势减弱,假单胞菌门与链球菌属水平升高。非母乳喂养则促进了不同的优势类群,足月组(NBTI)以肠球菌属为主,早产组(NBPI)则呈现更高的异质性。通过LEfSe筛选的BifidobacteriumEnterococcusStreptococcus等可作为不同组别的潜在系统发育标志物。代谢组学结果表明,4组样本代谢谱具有一定区分度,且在相同胎龄比较中差异更集中,相关差异代谢物主要涉及色氨酸代谢、脂质/甾醇代谢、不饱和脂肪酸生物合成、胆汁酸代谢及碳水化合物消化吸收等通路。在关键代谢物层面,早产母乳喂养组(BPI)关联更高的谷胱甘肽、维生素D代谢物及DPA水平,提示其可能与抗氧化防御、免疫调节及神经发育相关过程存在关联;足月母乳喂养组(BTI)则与吲哚乳酸、吲哚丁酸等双歧杆菌衍生代谢物的富集密切相关。非母乳喂养组(NBTI及NBPI)的代谢特征则突出表现为肠道中可发酵碳水化合物残留以及胆汁酸/脂肪酸酯化形式的差异,提示喂养底物组成、宿主消化吸收及肠道相关转化过程可能共同参与其代谢特征形成。相关性分析进一步表明,母乳喂养组形成了以Bifidobacterium为核心,并与吲哚衍生物等有益代谢物紧密协同的菌群-代谢物关联模式;而非母乳喂养组则更多表现为可发酵碳水/寡糖及胆汁酸相关分子与特定菌属之间的关联特征。
综合来看,胎龄与喂养方式共同决定婴儿早期肠道微生态的结构-功能耦联模式,其中胎龄可能影响喂养方式对肠道微生态的塑造模式。基于此,早产儿营养支持策略应在倡导母乳喂养这一临床共识的基础上,进一步关注与早期菌群利用能力相匹配的功能性底物(2′-岩藻糖基乳糖、吲哚乳酸、吲哚丁酸)强化及促进优势菌(BifidobacteriumLactobacillus)定殖的微生态干预方向。需要指出的是,尽管本研究中非母乳喂养组均为纯配方奶喂养,但不同个体所使用的配方奶品牌及成分并不完全一致,且未对母乳和配方奶本身进行代谢组检测,因此当前结果尚难严格区分饮食直接残留与微生物代谢来源。同时,本研究属于横断面多组学关联分析,样本量相对有限,且部分可能影响婴儿肠道微生态的围产期临床资料尚未纳入多变量统计校正。因此,本研究所揭示的差异更适合解释为与胎龄及喂养方式相关的群体特征,而非严格意义上的独立因果效应。未来仍需在更大样本量、临床资料更完整的前瞻性队列中结合混杂因素校正、纵向随访、宏基因组学及靶向代谢组学验证,进一步确认关键菌群与代谢物的因果关系与可重复性,并探索其干预潜力,以期为优化早产儿营养支持与微生态干预策略提供依据。
  • 国家自然科学基金(32402117)
  • 中国科协青年人才托举工程(YESS20240737)
  • 浙江省科协青年人才托举工程(ZJSKXQT201508)
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2026年第66卷第8期
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doi: 10.13343/j.cnki.wsxb.20260127
  • 接收时间:2026-02-10
  • 首发时间:2026-08-21
  • 出版时间:2026-08-04
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  • 收稿日期:2026-02-10
  • 录用日期:2026-04-13
基金
National Natural Science Foundation of China(32402117)
国家自然科学基金(32402117)
Young Elite Scientists Sponsorship Program by CAST(YESS20240737)
中国科协青年人才托举工程(YESS20240737)
Zhejiang Association for Science and Technology Youth Talent Support Project(ZJSKXQT201508)
浙江省科协青年人才托举工程(ZJSKXQT201508)
作者信息
    1.浙江工商大学 食品与生物工程学院,全省食品微生物与营养健康重点实验室,浙江 杭州
    2.沈阳市妇婴医院,辽宁 沈阳

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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