Article(id=1246845539468333780, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246845538742719188, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-4193.2019.12.015, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1544544000000, receivedDateStr=2018-12-12, revisedDate=1561046400000, revisedDateStr=2019-06-21, acceptedDate=null, acceptedDateStr=null, onlineDate=1775200741878, onlineDateStr=2026-04-03, pubDate=1577203200000, pubDateStr=2019-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775200741878, onlineIssueDateStr=2026-04-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775200741878, creator=13701087609, updateTime=1775200741878, updator=13701087609, issue=Issue{id=1246845538742719188, tenantId=1146029695717560320, journalId=1149651085930835976, year='2019', volume='41', issue='12', pageStart='1', pageEnd='176', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1775200741706, creator=13701087609, updateTime=1775200890782, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1246846164105060671, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246845538742719188, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1246846164105060672, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246845538742719188, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=156, endPage=171, ext={EN=ArticleExt(id=1246845539820655320, articleId=1246845539468333780, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Distribution characteristics and influencing factors of bacterioplankton community with offshore distance variation in the surface seawater of Bohai Bay, columnId=1243954927383462170, journalTitle=Haiyang Xuebao, columnName=Marine Biology, runingTitle=null, highlight=null, articleAbstract=

In order to study the impact of coastal pollution in Bohai Bay on the microecology of sea areas with different distances from the shore, the bacterioplankton community compositions (BCCs) in surface seawater samples from 6 stations with different offshore distances along the coastal region of Bohai Bay were analyzed through high throughput sequencing technology, and the main factors affecting the variation of BCCs were explored by combining environmental and spatial factors in this region. The results showed that there was gradient change of environmental factor in the studied region, such as the contents of nitrogen nutrients were higher in the nearshore station than those in the offshore station. Although there was no significant difference tested for the alpha diversity among different sites, the diversity indexes were still relatively higher in the nearshore stations. The bacterioplankton community compositions were significantly varied with the change of offshore distances. Members of Gammaproteobacteria and Bacteroidetes were mainly enriched in nearshore stations which were closely related with the contents of nitrogen nutrients, members of Cyanobacteria were mainly enriched in offshore stations, which were closely related to ammonia nitrogen, transparency and conductivity. The variance partitioning analysis showed that PCNM variables purely contributed most (38.1%) to the variation of community structure, indicating that there may be environmental variables with spatial structure within the research scope that had not yet been measured may affect the spatial distribution of the bacterioplankton community. Meanwhile, the results of functional prediction indicated that the eutrophication, hydrocarbon pollution and other environmental conditions in the nearshore station may contribute to the change of BCCs. This study explored the variation of offshore-distance-varied BCC in the coastal region of Bohai Bay from environmental and spatial impact, which may provide reference for the study and protection of marine environment in Bohai Bay.

, correspAuthors=Zhiyong Huang, authorNote=null, correspAuthorsNote=null, copyrightStatement=Haiyang Xuebao, 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, authorCompany=null, fund=null, authors=null, authorsList=Wei Zhao, Jingjing Wang, Song Xu, Qingqing Li, Rong Yang, Xiaoxia Zhang, Zhiyong Huang), CN=ArticleExt(id=1246845541292856073, articleId=1246845539468333780, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=渤海湾表层海水中浮游细菌群落随离岸距离的分布特征及其影响因素, columnId=1243954927517679901, journalTitle=海洋学报, columnName=海洋生物, runingTitle=null, highlight=null, articleAbstract=

为研究渤海湾近岸污染对远近岸海域微生态的影响,利用高通量测序技术,对渤海湾不同离岸距离的6个站位采集表层海水,进行浮游细菌群落结构分析,结合环境、空间因素探究影响其变化的主要因素。结果表明:研究区域存在环境因子的梯度变化,如氮营养盐在近岸高于远岸;细菌α-多样性在不同站位间差异不显著,但仍显示在近岸相对较高;细菌群落结构随离岸距离变化显著,γ-变形菌和拟杆菌在近岸显著富集,且与氮营养盐的含量有关;蓝细菌在远岸显著富集,且与氨氮、透明度、电导率有关;邻体矩阵主坐标单独解释部分对群落结构变异的贡献率最大(38.1%),说明可能存在尚未测量但具有空间结构的环境变量影响群落空间分布;结合功能预测的结果推测近岸区域的富营养与烃类污染等可能影响群落变化。本文从环境和空间影响两方面探讨了渤海湾不同离岸距离的海域浮游细菌群落结构变化,为研究渤海湾海洋生态及环境保护提供一定的参考。

, correspAuthors=黄志勇, authorNote=null, correspAuthorsNote=
*黄志勇,研究员,主要从事环境微生物生态学研究。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2023, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=oC1gWtZu28j/rHzLHw14og==, magXml=r3NHU+dH2njjIhir9Z20QQ==, pdfUrl=null, pdf=dsWdezYX2eafGrGBBjG/Pw==, pdfFileSize=10249640, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=Pgfo84yayayHXPqEWhwutA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=+NbqzDLJRWgu39upA5AkVA==, mapNumber=null, authorCompany=null, fund=null, authors=

赵维(1988—),女,河北省沧州市人,助理研究员,主要从事海洋环境微生物多样性研究。E-mail:

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赵维(1988—),女,河北省沧州市人,助理研究员,主要从事海洋环境微生物多样性研究。E-mail:

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Ecosphere, 2016, 7(12): e016179., articleTitle=null, refAbstract=null)], funds=[Fund(id=1254506334590792517, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, awardId=null, language=CN, fundingSource=天津市科技计划项目(18ZXSZSF00100,18YFZCNC01180,16YFXTSY00580);国家自然科学基金项目(3150020230);中国科学院战略生物资源计划(KFJ-BRP-009)。, fundOrder=null, country=null)], companyList=[AuthorCompany(id=1254506318228812363, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, xref=1, ext=[AuthorCompanyExt(id=1254506318233006668, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, companyId=1254506318228812363, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Tianjin Key Laboratory for Industrial Biological Systems and Bioprocessing Engineering, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China), AuthorCompanyExt(id=1254506318253978188, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, companyId=1254506318228812363, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 中国科学院天津工业生物技术研究所 天津市工业生物系统与过程工程重点实验室,天津 300308)])], figs=[ArticleFig(id=1254506328936870650, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 1, caption=Sampling sites in the Bohai Bay, figureFileSmall=sjLmS5wHVdRMk2pVI/UOFA==, figureFileBig=g3zwc14nHgSGRtpMAgUvNg==, tableContent=null), ArticleFig(id=1254506329129808639, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图1, caption=渤海湾取样点, figureFileSmall=sjLmS5wHVdRMk2pVI/UOFA==, figureFileBig=g3zwc14nHgSGRtpMAgUvNg==, tableContent=null), ArticleFig(id=1254506329381466883, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 2, caption=Clustering analysis of environmental factors based on the nutrient contents and histogram of bacterial community composition at each site, figureFileSmall=zIgwxdpg9HMIUDjSHGLT6w==, figureFileBig=ZyoNLjTIby+hEFD2NxSslg==, tableContent=null), ArticleFig(id=1254506329658290952, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图2, caption=基于营养盐类含量变化的环境因子聚类分析与各站位群落组成柱状图, figureFileSmall=zIgwxdpg9HMIUDjSHGLT6w==, figureFileBig=ZyoNLjTIby+hEFD2NxSslg==, tableContent=null), ArticleFig(id=1254506329763148555, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 3, caption=Principal coordinates analysis (PCoA) plot derived from the Jaccard (a) and Bray-Curtis (b) distance among seawater samples based on the occurrences and abundances of Operational Taxonomic Units (OTUs), figureFileSmall=1FL9yFSZgp3AiuXAe3ukyA==, figureFileBig=adrXdVmnyqNU0Rw87tIU6w==, tableContent=null), ArticleFig(id=1254506329872200464, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图3, caption=基于Jaccard距离(a)和Bray-Curtis距离(b)的OTU水平的群落聚类分析, figureFileSmall=1FL9yFSZgp3AiuXAe3ukyA==, figureFileBig=adrXdVmnyqNU0Rw87tIU6w==, tableContent=null), ArticleFig(id=1254506330010612499, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 4, caption=Least discriminant analysis (LDA) effect size taxonomic cladogram comparing all samples categorized by three bacterial groups

Significantly discriminant taxon nodes are colored and branch areas are shaded according to the highest ranked group for that taxon. If the taxon is not significantly differentially represented among sample groups, the corresponding node is colored yellow

, figureFileSmall=OiOY5Atm47nBWYxjELLDqg==, figureFileBig=YJkh1Hsg3tnNZjLBFQjQzw==, tableContent=null), ArticleFig(id=1254506330216133400, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图4, caption=基于LDA分析的3组间差异微生物展示图

具有显著差异的分类单元节点被着以不同颜色,该分类单元的最高等级对应的分支区域也着以相同颜色。如果分类单元在组间没有显著差异,则相应节点为黄色

, figureFileSmall=OiOY5Atm47nBWYxjELLDqg==, figureFileBig=YJkh1Hsg3tnNZjLBFQjQzw==, tableContent=null), ArticleFig(id=1254506330492957466, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 5, caption=Heat map demonstrate correlations between highly abundant discriminant taxa of three groups and seawater environmental parameters

Value of the heat map bar represents the Pearson correlation coefficient (r ), and the asterisk represents the significance of the relationship with * 0.05 and ** 0.001

, figureFileSmall=Xer+8EoXjcC9BSFPZr7wNw==, figureFileBig=8FkSvEByHzFnTgszzxJbUQ==, tableContent=null), ArticleFig(id=1254506330874639133, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图5, caption=差异物种和环境因子的相关性分析

热图代表各差异物种和环境因子的Pearson相关性系数,星号代表显著性:* 0.05,** 0.001

, figureFileSmall=Xer+8EoXjcC9BSFPZr7wNw==, figureFileBig=8FkSvEByHzFnTgszzxJbUQ==, tableContent=null), ArticleFig(id=1254506331063382819, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 6, caption=Variation partitioning of bacterial communities

Hellinger transformed OTU matrix was used as responsible variable by the water environmental factors (Env., top left and the spatial factors including linear trend (Trend, top right) and PCNM variables (bottom). Forward selection procedures were used to select the best subset of environmental, trend and PCNM variables explaining community variation respectively (n = 6)

, figureFileSmall=nFsDKYesUWXQumFTzD7gOA==, figureFileBig=C3I4CAZVrCS2RE1hUnXKgQ==, tableContent=null), ArticleFig(id=1254506331239543592, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图6, caption=群落结构变异因素分析

基于Hellinger转化的OTU数据,通过海水环境因子(左上)、地理因素包括线性趋势(右上)和邻体矩阵主坐标(下)来对群落结构进行变异分解分析。每一个解释部分都经过前向选择选出最适模型的环境因子子集、线性趋势变量子集和邻体矩阵主坐标子集(n=6)

, figureFileSmall=nFsDKYesUWXQumFTzD7gOA==, figureFileBig=C3I4CAZVrCS2RE1hUnXKgQ==, tableContent=null), ArticleFig(id=1254506331361178410, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Fig. 7, caption=PCoA plot based on function prediction through FAPROTAX, figureFileSmall=oJqmwDsmKEycYT/gh6Kzrg==, figureFileBig=ZIL8Dnv2Oj3jzpp1sxqGUw==, tableContent=null), ArticleFig(id=1254506331524756269, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=图7, caption=基于FAPROTAX功能预测的结果进行的主坐标分析, figureFileSmall=oJqmwDsmKEycYT/gh6Kzrg==, figureFileBig=ZIL8Dnv2Oj3jzpp1sxqGUw==, tableContent=null), ArticleFig(id=1254506331751248688, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Table 1, caption=

Environment and seawater properties of sampling sites

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 TJ13 TJ14 TJ16 TJ17 TJ23 TJ27
经度 118.093 6°E 118.884 1°E 117.766 9°E 118.488 6°E 117.742 2°E 117.727 3°E
纬度 38.673 9°N 38.659 1°N 38.670 1°N 38.634 8°N 38.667°N 38.671 4°N
离岸距离/km 44.0 113.1 16.0 79.0 14.0 12.0
风向 NE NE NW NE NW NW
风速/m·s−1 1.0 3.0 2.7 4.0 2.0 0.8
水深/m 12.8 22.0 5.0 8.5 4.0 3.9
气压/kPa 1 012 1 012 1 012 1 011 1 012 1 012
气温/℃ 26.4 24 28.2 23.4 28.3 30.4
水温/℃ 26.9 24.0 27.0 23.5 27.0 28.4
湿度/% 63.6 76.9 62.9 68.4 30.4 56.3
透明度/cm 100 300 200 200 200 170
盐度 23.5 29.5 29.6 29.5 29.5 29.4
溶解氧含量/mg·L–1 7.51 6.70 6.51 6.88 5.79 6.85
pH 8.18 8.10 8.12 8.06 8.12 8.15
电导率/mS·cm–1 45.1 45.6 45.4 45.6 45.3 45.2
化学需氧量/mg·L –1 0.64 1.13 1.05 0.56 1.35 1.60
亚硝酸盐/mg·L –1 0.030 0.006 0.134 0.016 0.108 0.106
硝酸盐/mg·L –1 0.114 0.127 0.318 0.103 0.402 0.356
氨氮/mg·L –1 0.011 0.133 0.009 0.043 0.019 0.064
无机氮/mg·L –1 0.155 0.266 0.461 0.162 0.529 0.526
活性硅酸盐/mg·L –1 0.768 0.890 0.712 0.712 0.812 1.010
活性磷酸盐/mg·L –1 0.004 0.003 0.007 0.004 0.016 0.005
), ArticleFig(id=1254506333332501298, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=表1, caption=

取样站位的环境特征与海水理化性质

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 TJ13 TJ14 TJ16 TJ17 TJ23 TJ27
经度 118.093 6°E 118.884 1°E 117.766 9°E 118.488 6°E 117.742 2°E 117.727 3°E
纬度 38.673 9°N 38.659 1°N 38.670 1°N 38.634 8°N 38.667°N 38.671 4°N
离岸距离/km 44.0 113.1 16.0 79.0 14.0 12.0
风向 NE NE NW NE NW NW
风速/m·s−1 1.0 3.0 2.7 4.0 2.0 0.8
水深/m 12.8 22.0 5.0 8.5 4.0 3.9
气压/kPa 1 012 1 012 1 012 1 011 1 012 1 012
气温/℃ 26.4 24 28.2 23.4 28.3 30.4
水温/℃ 26.9 24.0 27.0 23.5 27.0 28.4
湿度/% 63.6 76.9 62.9 68.4 30.4 56.3
透明度/cm 100 300 200 200 200 170
盐度 23.5 29.5 29.6 29.5 29.5 29.4
溶解氧含量/mg·L–1 7.51 6.70 6.51 6.88 5.79 6.85
pH 8.18 8.10 8.12 8.06 8.12 8.15
电导率/mS·cm–1 45.1 45.6 45.4 45.6 45.3 45.2
化学需氧量/mg·L –1 0.64 1.13 1.05 0.56 1.35 1.60
亚硝酸盐/mg·L –1 0.030 0.006 0.134 0.016 0.108 0.106
硝酸盐/mg·L –1 0.114 0.127 0.318 0.103 0.402 0.356
氨氮/mg·L –1 0.011 0.133 0.009 0.043 0.019 0.064
无机氮/mg·L –1 0.155 0.266 0.461 0.162 0.529 0.526
活性硅酸盐/mg·L –1 0.768 0.890 0.712 0.712 0.812 1.010
活性磷酸盐/mg·L –1 0.004 0.003 0.007 0.004 0.016 0.005
), ArticleFig(id=1254506333563188022, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Table 2, caption=

Analysis of microbial diversity index of the six sea water samples

, figureFileSmall=null, figureFileBig=null, tableContent=
样品号 OTU 丰度 谱系多样性值 Shannon值
TJ13 628.80 ± 13.30 63.19 ± 2.23 4.83 ± 0.11
TJ14 603.05 ± 27.05 64.57 ± 1.49 4.92 ± 0.05
TJ16 718.30 ± 60.28 69.92 ± 3.73 5.09 ± 0.02
TJ17 827.85 ± 92.55 72.22 ± 2.34 5.43 ± 0.43
TJ23 836.73 ± 125.36 79.48 ± 8.22 5.78 ± 0.28
TJ27 639.23 ± 46.51 63.89 ± 4.82 5.06 ± 0.09
), ArticleFig(id=1254506333949063993, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=表2, caption=

海水样品的微生物多样性指数分布

, figureFileSmall=null, figureFileBig=null, tableContent=
样品号 OTU 丰度 谱系多样性值 Shannon值
TJ13 628.80 ± 13.30 63.19 ± 2.23 4.83 ± 0.11
TJ14 603.05 ± 27.05 64.57 ± 1.49 4.92 ± 0.05
TJ16 718.30 ± 60.28 69.92 ± 3.73 5.09 ± 0.02
TJ17 827.85 ± 92.55 72.22 ± 2.34 5.43 ± 0.43
TJ23 836.73 ± 125.36 79.48 ± 8.22 5.78 ± 0.28
TJ27 639.23 ± 46.51 63.89 ± 4.82 5.06 ± 0.09
), ArticleFig(id=1254506334062310205, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=EN, label=Table 3, caption=

Difference analysis of relative functional group abundance between different groups of stations

, figureFileSmall=null, figureFileBig=null, tableContent=
功能组 第1组/% 第2组/% 第3组/%
甲烷营养 0.01±0.02 0.01±0.01 0±0
甲醇氧化 0.55±0.13 0.61±0.06 0.51±0.18
甲基营养 0.57±0.12 0.62±0.06 0.51±0.18
好氧氨氧化 0±0 0.01±0.01 0.01±0.02
有氧亚硝酸盐氧化 0.04±0.02a 0.09±0.03b 0.09±0.04ab
硝化作用 0.05±0.02a 0.1±0.02b 0.1±0.06ab
硫酸盐呼吸 0.01±0.01 0.01±0.01 0.01±0.01
硫化物呼吸 0.01±0.01 0.01±0.01 0.01±0.01
硝化反硝化作用 0.14±0.06 0.22±0.09 0.1±0
亚硝酸盐脱氮作用 0.14±0.06 0.22±0.09 0.1±0
一氧化二氮反硝化作用 0.14±0.06 0.22±0.09 0.1±0
反硝化作用 0.14±0.06 0.22±0.09 0.1±0
Chitinolysis 0.02±0.01 0.01±0.01 0±0
暗氢氧化反应 0.02±0.01a 0±0b 0±0b
固氮作用 0.01±0.01 0.01±0.01 0±0
亚硝酸盐呼吸 0.14±0.06 0.22±0.09 0.1±0
溶纤作用 0.01±0.01 0.01±0.01 0±0
暗硫氧化反应 0.02±0.01 0.29±0.34 0.03±0.01
暗硫化合物氧化反应 0.16±0.16 0.35±0.41 0.03±0.01
锰氧化作用 0.01±0 0.01±0.01 0.01±0.01
发酵作用 2.97±2.23 0.91±0.56 1.46±0.19
有氧化能异养 29.71±4.4a 17.26±3.3ab 10.88±2.97b
人类病原体 0.04±0.02 0.06±0.05 0.05±0.01
人类肠道 0±0 0±0 0.01±0.01
哺乳动物肠道 0±0 0±0 0.01±0.01
动物寄生虫或共生体 0.45±0.15 0.41±0.44 0.27±0.05
芳烃降解 0.76±0.35 0.6±0.65 0.14±0.08
芳香族化合物降解 0.84±0.36 0.68±0.62 0.22±0.07
烃降解 0.83±0.38 0.63±0.68 0.14±0.09
铁呼吸 0.03±0.02 0.04±0.05 0.03±0.01
硝酸盐呼吸 0.15±0.06 0.23±0.09 0.11±0
硝酸盐还原作用 2.92±2.16 1.52±0.18 1.34±0.34
氮呼吸 0.15±0.06 0.23±0.09 0.11±0
细胞内寄生虫 0.85±0.27 2.01±1.16 1.52±0.3
捕食和寄生 0.62±0.37a 0.09±0.05b 0.1±0ab
蓝藻细菌 1.77±0.47ab 0.3±0.29b 29.29±10.27a
非产氧光自养型硫氧化 0.14±0.06 0.22±0.08 0.11±0.01
非产氧光能自养 0.14±0.06 0.22±0.08 0.11±0.01
产氧光能自养 1.77±0.47ab 0.3±0.29b 29.29±10.27a
光能自养 1.9±0.51ab 0.53±0.34b 29.4±10.26a
光能异养 0.14±0.06 0.22±0.09 0.1±0
光营养 1.91±0.51ab 0.53±0.35b 29.4±10.26a
尿素分解 0.1±0.06 0.14±0.11 0.26±0.17
化能异养 30.37±4.33a 17.91±3.36ab 11.43±3.2b
), ArticleFig(id=1254506334221693760, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246845539468333780, language=CN, label=表3, caption=

群落功能在不同组别站位间的相对丰度差异分析

, figureFileSmall=null, figureFileBig=null, tableContent=
功能组 第1组/% 第2组/% 第3组/%
甲烷营养 0.01±0.02 0.01±0.01 0±0
甲醇氧化 0.55±0.13 0.61±0.06 0.51±0.18
甲基营养 0.57±0.12 0.62±0.06 0.51±0.18
好氧氨氧化 0±0 0.01±0.01 0.01±0.02
有氧亚硝酸盐氧化 0.04±0.02a 0.09±0.03b 0.09±0.04ab
硝化作用 0.05±0.02a 0.1±0.02b 0.1±0.06ab
硫酸盐呼吸 0.01±0.01 0.01±0.01 0.01±0.01
硫化物呼吸 0.01±0.01 0.01±0.01 0.01±0.01
硝化反硝化作用 0.14±0.06 0.22±0.09 0.1±0
亚硝酸盐脱氮作用 0.14±0.06 0.22±0.09 0.1±0
一氧化二氮反硝化作用 0.14±0.06 0.22±0.09 0.1±0
反硝化作用 0.14±0.06 0.22±0.09 0.1±0
Chitinolysis 0.02±0.01 0.01±0.01 0±0
暗氢氧化反应 0.02±0.01a 0±0b 0±0b
固氮作用 0.01±0.01 0.01±0.01 0±0
亚硝酸盐呼吸 0.14±0.06 0.22±0.09 0.1±0
溶纤作用 0.01±0.01 0.01±0.01 0±0
暗硫氧化反应 0.02±0.01 0.29±0.34 0.03±0.01
暗硫化合物氧化反应 0.16±0.16 0.35±0.41 0.03±0.01
锰氧化作用 0.01±0 0.01±0.01 0.01±0.01
发酵作用 2.97±2.23 0.91±0.56 1.46±0.19
有氧化能异养 29.71±4.4a 17.26±3.3ab 10.88±2.97b
人类病原体 0.04±0.02 0.06±0.05 0.05±0.01
人类肠道 0±0 0±0 0.01±0.01
哺乳动物肠道 0±0 0±0 0.01±0.01
动物寄生虫或共生体 0.45±0.15 0.41±0.44 0.27±0.05
芳烃降解 0.76±0.35 0.6±0.65 0.14±0.08
芳香族化合物降解 0.84±0.36 0.68±0.62 0.22±0.07
烃降解 0.83±0.38 0.63±0.68 0.14±0.09
铁呼吸 0.03±0.02 0.04±0.05 0.03±0.01
硝酸盐呼吸 0.15±0.06 0.23±0.09 0.11±0
硝酸盐还原作用 2.92±2.16 1.52±0.18 1.34±0.34
氮呼吸 0.15±0.06 0.23±0.09 0.11±0
细胞内寄生虫 0.85±0.27 2.01±1.16 1.52±0.3
捕食和寄生 0.62±0.37a 0.09±0.05b 0.1±0ab
蓝藻细菌 1.77±0.47ab 0.3±0.29b 29.29±10.27a
非产氧光自养型硫氧化 0.14±0.06 0.22±0.08 0.11±0.01
非产氧光能自养 0.14±0.06 0.22±0.08 0.11±0.01
产氧光能自养 1.77±0.47ab 0.3±0.29b 29.29±10.27a
光能自养 1.9±0.51ab 0.53±0.34b 29.4±10.26a
光能异养 0.14±0.06 0.22±0.09 0.1±0
光营养 1.91±0.51ab 0.53±0.35b 29.4±10.26a
尿素分解 0.1±0.06 0.14±0.11 0.26±0.17
化能异养 30.37±4.33a 17.91±3.36ab 11.43±3.2b
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渤海湾表层海水中浮游细菌群落随离岸距离的分布特征及其影响因素
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赵维 1 , 王敬敬 1 , 徐松 1 , 李晴晴 1 , 杨榕 1 , 张小霞 1 , 黄志勇 1, *
海洋学报 | 海洋生物 2019,41(12): 156-171
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海洋学报 | 海洋生物 2019, 41(12): 156-171
渤海湾表层海水中浮游细菌群落随离岸距离的分布特征及其影响因素
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赵维1 , 王敬敬1, 徐松1, 李晴晴1, 杨榕1, 张小霞1, 黄志勇1, *
作者信息
  • 1 中国科学院天津工业生物技术研究所 天津市工业生物系统与过程工程重点实验室,天津 300308
  • 赵维(1988—),女,河北省沧州市人,助理研究员,主要从事海洋环境微生物多样性研究。E-mail:

通讯作者:

*黄志勇,研究员,主要从事环境微生物生态学研究。E-mail:
Distribution characteristics and influencing factors of bacterioplankton community with offshore distance variation in the surface seawater of Bohai Bay
Wei Zhao1 , Jingjing Wang1, Song Xu1, Qingqing Li1, Rong Yang1, Xiaoxia Zhang1, Zhiyong Huang1, *
Affiliations
  • 1 Tianjin Key Laboratory for Industrial Biological Systems and Bioprocessing Engineering, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
出版时间: 2019-12-25 doi: 10.3969/j.issn.0253-4193.2019.12.015
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为研究渤海湾近岸污染对远近岸海域微生态的影响,利用高通量测序技术,对渤海湾不同离岸距离的6个站位采集表层海水,进行浮游细菌群落结构分析,结合环境、空间因素探究影响其变化的主要因素。结果表明:研究区域存在环境因子的梯度变化,如氮营养盐在近岸高于远岸;细菌α-多样性在不同站位间差异不显著,但仍显示在近岸相对较高;细菌群落结构随离岸距离变化显著,γ-变形菌和拟杆菌在近岸显著富集,且与氮营养盐的含量有关;蓝细菌在远岸显著富集,且与氨氮、透明度、电导率有关;邻体矩阵主坐标单独解释部分对群落结构变异的贡献率最大(38.1%),说明可能存在尚未测量但具有空间结构的环境变量影响群落空间分布;结合功能预测的结果推测近岸区域的富营养与烃类污染等可能影响群落变化。本文从环境和空间影响两方面探讨了渤海湾不同离岸距离的海域浮游细菌群落结构变化,为研究渤海湾海洋生态及环境保护提供一定的参考。

渤海湾  /  浮游细菌群落结构  /  地理分布  /  功能预测  /  邻体矩阵主坐标

In order to study the impact of coastal pollution in Bohai Bay on the microecology of sea areas with different distances from the shore, the bacterioplankton community compositions (BCCs) in surface seawater samples from 6 stations with different offshore distances along the coastal region of Bohai Bay were analyzed through high throughput sequencing technology, and the main factors affecting the variation of BCCs were explored by combining environmental and spatial factors in this region. The results showed that there was gradient change of environmental factor in the studied region, such as the contents of nitrogen nutrients were higher in the nearshore station than those in the offshore station. Although there was no significant difference tested for the alpha diversity among different sites, the diversity indexes were still relatively higher in the nearshore stations. The bacterioplankton community compositions were significantly varied with the change of offshore distances. Members of Gammaproteobacteria and Bacteroidetes were mainly enriched in nearshore stations which were closely related with the contents of nitrogen nutrients, members of Cyanobacteria were mainly enriched in offshore stations, which were closely related to ammonia nitrogen, transparency and conductivity. The variance partitioning analysis showed that PCNM variables purely contributed most (38.1%) to the variation of community structure, indicating that there may be environmental variables with spatial structure within the research scope that had not yet been measured may affect the spatial distribution of the bacterioplankton community. Meanwhile, the results of functional prediction indicated that the eutrophication, hydrocarbon pollution and other environmental conditions in the nearshore station may contribute to the change of BCCs. This study explored the variation of offshore-distance-varied BCC in the coastal region of Bohai Bay from environmental and spatial impact, which may provide reference for the study and protection of marine environment in Bohai Bay.

Bohai Bay  /  bacterioplankton community composition  /  geographic distribution  /  function prediction  /  PCNM
赵维, 王敬敬, 徐松, 李晴晴, 杨榕, 张小霞, 黄志勇. 渤海湾表层海水中浮游细菌群落随离岸距离的分布特征及其影响因素. 海洋学报, 2019 , 41 (12) : 156 -171 . DOI: 10.3969/j.issn.0253-4193.2019.12.015
Wei Zhao, Jingjing Wang, Song Xu, Qingqing Li, Rong Yang, Xiaoxia Zhang, Zhiyong Huang. Distribution characteristics and influencing factors of bacterioplankton community with offshore distance variation in the surface seawater of Bohai Bay[J]. Haiyang Xuebao, 2019 , 41 (12) : 156 -171 . DOI: 10.3969/j.issn.0253-4193.2019.12.015
渤海湾位于渤海西部,是我国九大海湾之一,周围集中了海洋化工、港口、滩涂养殖和盐业等多种经济活动,是开发利用海洋资源比较活跃的地区之一[1]。随着城市化进程的加快和临港工业的发展,陆源排海污染物不断增加,倾废、船舶以及海水养殖等对海域生态环境造成巨大压力[1]。排海污水主要包括耗氧有机物、无机氮、无机磷和油类等,严重超标的污染物加之渤海湾为半封闭港湾、与外海交换能力差的特征,导致渤海湾海洋环境质量急剧恶化。微生物作为一类多样性最高的生命形式,在地球化学循环(碳循环,氮循环,硫循环,磷循环和金属循环等)中承担着重要的生态功能,复杂的群落结构、功能、相互作用及其动态变化对环境生态功能的维持有重要意义。海洋微生物群落的结构组成和特性在一定程度上反映了海洋生态系统的环境状况[2]。深入研究渤海湾微生物群落结构与分布特征对认识和预测渤海湾海洋生态功能极为重要[3]。已有的关于渤海湾微生物多样性的调查研究主要集中在对浮游细菌数量变化及与环境因子的关系等方面[4-5],而对海洋细菌群落结构和功能多样性变化及其受环境和空间因素的影响则少有报道。近年来,越来越多的海洋生态学家开始关注自然环境中空间距离和环境因子在微生物群落结构形成和维持中的作用。在具体的研究中,空间距离代表历史因素、扩散限制等;环境因素代表当代气候、物理、化学的环境变化[6],这两者被认为是驱动当前微生物多样性差异的主要因素[7-10]。目前,国内相关的研究主要集中在东海、南海近岸海域,如Xiong等[11]报道了东海沉积物中的细菌群落存在地理分布特征且与氮污染梯度有关系,发现空间距离对细菌群落变化的影响要高于环境因子;同时,Wang等[12]对东海沿岸浙江省区跨越8个海岸带的表层海水中浮游细菌群落结构变化规律的研究表明,环境和地理因素共同影响部分对该区域浮游细菌群落结构的变化解释度最高。Zhang等[13]对南海沿海海域400~500 km范围内的总菌群和活性菌群多样性的分析表明在研究区域内细菌群落存在的地理分布特征是环境和距离衰减共同作用的结果,其中环境因子与群落组成的关系相较于地理距离与群落组成的关系更加紧密。这些研究均显示在近岸海洋环境中,微生物群落的地理分布规律均分别受空间因素和环境因素的影响,但是针对半封闭港湾的相关研究尚未见报道。
针对渤海湾而言,其地理水文环境与上述海域相比有其独特性,渤海湾是一种浅滩淤泥质海湾,海底地形自岸向海倾斜,沿岸受人类活动影响较大,半封闭港湾的特征决定了其与外海交换能力差,沿岸各类污染加剧了渤海湾的生态负担。已有的关于渤海湾微生物生态学研究更加关注浮游细菌丰度和沉积物中细菌群落的变化,如赵海萍等[14]基于浮游细菌的丰度变化对渤海湾浮游细菌分布特征进行研究,为了解渤海湾浮游细菌的生态环境状况提供了有力的数据支持;另外,刘鹏远等[15]对渤海湾表层沉积物中细菌群落结构的研究较为全面的探讨了海洋环境因素与沉积物微生物群落构成、分布与多样性的联系,其重点关注环境因子对表层沉积物群落的影响。目前,对空间因素同环境因素在渤海湾浮游细菌群落变化中的影响作用研究还较为匮乏。为进一步研究渤海湾近岸环境污染对渤海湾近岸及远岸的海洋微生物生态产生的影响,本文试图探究渤海湾湾区内从近岸到远岸接近渤海中央浅海盆地的区域内,随离岸距离的变化,浮游细菌群落的结构和组成变化,通过对营养盐等污染物含量和群落的变化进行相关研究,来回答近岸污染对渤海湾沿岸由近及远的海洋环境微生态的影响程度,并通过方差分解分析地理空间因素和环境因素对该区域细菌群落变化的贡献,进一步基于群落结构预测该区域微生物功能的空间变化特征,为深入了解微生物群落在渤海湾海洋环境中的生态功能提供参考。
2014年8月中旬,采集了渤海湾38.671 4°~38.659 1°N,117.727 3°~118.884 1°E范围内6个站位(图1)的海水样品,站位划分为3个小区域:近岸站位(TJ16、TJ23、TJ27);中间站位(TJ13、TJ17);远岸站位(TJ14)。每个站点的地理坐标见表1。对每个站位采集1.5 L的表层海水(0.5 m)样品。随船记录环境参数(水温、湿度、盐度、电导率、溶解氧等环境参数)。采集的水样于采样船上,每个样品取500 mL用经灭菌处理的100 μm孔径的尼龙布预过滤后用0.2 μm孔径的聚碳酸酯膜(Millipore,USA)过滤,置于预先灭菌容器中存于冰盒,4 h内运回实验室储存于−80℃冰箱以待后续检测分析。剩余水样用于海水水质测定。每个站位采集3个重复。
pH、盐度、电导率和溶解氧(DO)利用探头测定(Multi 3420,WTW,Germany),其余理化性质的测定均参照标准方法(GB 17378.4—2007)。活性磷酸盐含量使用钼蓝比色法测定,氨氮含量使用苯酚次氯酸盐法测定,活性硅酸盐含量使用硅钼蓝比色法测定,亚硝酸盐含量使用对氨基苯磺酰胺法测定,硝酸盐含量则使用Cd-Cu柱还原成亚硝酸盐后按照亚硝酸盐含量测定法测定。可溶性总无机氮含量则是通过将氨氮,硝酸盐氮和亚硝酸盐氮含量相加获得。海水中的化学需氧量(COD)使用碱性高锰酸钾法测定。
利用MoBio强力水样DNA提取试剂盒(MO BIO,USA)对海水样品进行微生物总DNA提取。利用16S rRNA基因V4区引物:F515(5′–GTG CCA GCM GCC GCG GTA A– 3′)和R806(5′– GGA CTA CHV GGG TWT CTAAT– 3′)[16]进行目的片段扩增。扩增子样品测序前的准备工作参照Illumina公司 《16S宏基因组测序文库制备-为Illumina MiSeq系统制备16S核糖体RNA基因扩增子》 使用说明书进行。扩增后产物利用Illumina Miseq测序仪进行高通量测序。测序样品的原始数据已上传至中国科学院北京基因组研究所大数据中心建立的组学原始数据归档库中,获取编号为CRA000481,访问网址:http://bigd.big.ac.cn/gsa。
测序产生的双端序列使用FLASH软件进行拼接,参数默认[17]。拼接后序列使用QIIME软件进行数据过滤[18],过滤标准:(1)删除长度小于200 bp和大于450 bp的序列;(2)筛选质量大于20(即准确度99%)的序列;(3)最少有连序75%的碱基质量高于20。过滤后的序列,利用USEARCH检测嵌合体,并使用filter_fasta.py命令将其去除[19]。然后基于条形码信息对样本序列进行分配[18]。利用Uclust[19]对优质序列按相似度0.97进行聚类,并将其分配给可操作分类单元(Operational Taxonomic Unit,OTU)。选取每个OTU中丰度最高的序列作为代表序列。代表序列基于Greengenes数据库[20]进行分类,使用PyNAST[21]基于Greengenes数据库进行BLAST比对。清除被分类到叶绿体、线粒体、古生菌、真核生物或未知序列的序列以及单序列。为了保持数据的一致性,对高通量测序数据进行抽平处理,每个样本随机选择3 000条序列子集(对应样本的最小测序量)来计算样本之间的多样性、群落组成和群落距离。
根据取样点的地理坐标计算各个站位的离岸距离,对各站位营养盐含量(主要是COD、无机氮、氨氮、硝态氮、亚硝态氮、活性磷酸盐、活性硅酸盐)基于Gower距离进行Cluster聚类分析;利用Kruskal-Wallis秩和检验对各站位间的细菌多样性、优势物种组成差异进行检验;基于Jaccard和Bray-Curtis算法,对各样本OTU组成数据进行主坐标分析(Principle coordinate analysis,PCoA)。
基于取样点坐标,利用趋势面分析(trend surface analysis,Trend)和邻体矩阵主坐标(principal coordinates of neighbour matrices,PCNM)分析模拟各种可能的空间结构。趋势面分析是利用数学曲面模拟地理系统要素在空间上的分布及变化趋势,该方法较为粗放,主要是对数据进行除趋势处理[22];PCNM分析是基于空间坐标位置,模拟出一系列不同尺度上具有空间自相关的特征值,作为空间变量来解释不同机制引起的群落结构变化[6, 23]。PCNM分析首先构建样点之间的欧式距离矩阵,削减距离矩阵规模,只保留一定规模的邻体之间的距离。其次,计算削减距离矩阵的主坐标分析,并保留具有正空间相关的特征向量[6]。最后使用保留的特征向量作为空间变量,运用于多元数据分析当中。PCNM分析可以获得很多比取样间隔更宽尺度的正交空间变量,可以对任何类型的空间结构(规则取样、不规则取样)进行建模[6]。显著的PCNM变量可以被定义为宽尺度、中尺度和微尺度变量,一般是任意设定,需要指出的是,随着PCNM轴的增加,其所代表的空间尺度逐渐减小[23],但目前尚没有统一的方法将PCNM变量定义为宽尺度、中尺度和微尺度变量。对于宽尺度和中尺度PCNM变量可以认为是模拟的尚未测量但存在空间结构的微生境变量;微尺度PCNM变量大部分情况是模拟由群落动态产生的局部空间结构,可能与中性生物学过程有关,通常与环境变量没有关系[6]
变差分解分析(Rariance Partitioning Analysis,VPA)可以用于评估环境变量与所有尺度的空间变量对响应变量的解释程度[6]。变差分解的目的是量化各种不同因素单独或共同解释响应变量变差的比例,其中,线性趋势可以视为产生变差的一部分来源。线性趋势可以发生在响应变量,也可以发生在解释变量,在进行变差分解之前,需要检验线性趋势的显著性,如果趋势显著,变差分解过程应考虑线性趋势的影响[6]。结合以上,以环境参数作为环境数据源,浮游细菌群落组成作为生物数据源,基于趋势面分析和PCNM分析模拟的空间结构作为空间因子数据源,构成环境因子、空间因子与物种组成矩阵,利用VPA分析环境变量和空间变量对浮游细菌群落分布的单独解释量和共同解释量。在进行上述分析之前,对原始环境数据进行对数变换,对物种数据通过海林格变换(Hellinger transform)进行中心变换。在模型构建过程中,分别对环境变量(Env)、Trend和PCNM变量进行前向选择,即根据R 2准则,如果在保留的变量基础上获得的校正R 2已经等于或者稍大于全模型的校正R 2,则停止选择[6]
基于线性判别分析流程(linear discriminant analysis(LDA)effect size pipeline,LEfSe)[24]确定每组的显著差异分类单元,该流程可在网址:http://huttenhower.sph.harvard.edu/galaxy/获取。取LDA score = 2.0(α = 0.05)的阈值作为判别标准,选择one-against-all作为比对方式,对组间相对丰度差异显著的分类单元进行识别。基于皮尔逊相关系数衡量各变量与差异分类单元之间的关系。利用FAPROTAX工具对微生物群落功能进行预测[25],基于Bray-Curtis算法对群落功能进行主坐标分析,并基于主坐标分析的聚类结果进行各组别群落功能的差异分析(Kruskal-Wallis秩和检验)。
结合环境参数(表1),可以看到取样站位的水深是远岸站位最深,中间站位次之,近岸站位最浅。此外,物理环境参数,气压、电导率、盐度的变化随离岸距离变化不大,温度(水温和气温)在远岸站位较低、近岸站位较高,湿度和透明度在远岸站位较大,近岸站位较小;化学环境参数,总无机氮、亚硝酸盐和硝酸盐含量在远岸站位较低,近岸站位较高,氨氮含量则在TJ14站位含量最高,其次是TJ27、TJ17,然后是TJ23、TJ13、TJ16,氨氮含量的变化并未随离岸距离的增大而减小;活性硅酸盐和活性磷酸盐含量在近岸站位和远岸站位相差不大;DO含量在远岸站位相对高于近岸站位;COD含量则整体上近岸站位高于远岸站位,但是在远岸站位中,TJ14的COD含量明显高于中间站位(TJ13、TJ17)。基于主要营养盐,如硝酸盐、亚硝酸盐、氨氮、无机氮、活性磷酸盐、活性硅酸盐、COD在各个站位海水样品中的含量,进行聚类分析,结果显示6个站位聚成3组,TJ14站位单独一组,TJ13与TJ17站位聚成一组,TJ16、TJ23与TJ27站位聚成一组(图2)。主要营养盐含量的聚类结果,与站位距离具有较高的一致性,该结果表明在本文的研究范围内,渤海湾的海水水质随离岸距离呈现出梯度变化的趋势。
6个站位共测序18个样品,其中TJ13、TJ14和TJ17站位的各一个重复由于序列数偏低未计入后续的统计中,其余共计15个样品分别抽取3 000条序列进行细菌多样性分析,稀释曲线均基本趋于平缓,说明测序趋于饱和,取样基本合理,能够较为真实的反映样品中的微生物群落。微生物多样性指数比如OTU丰度、谱系多样性(Phylogenetic Diversity,PD)、香农指数(Shannon)可以用来估算样品中微生物的多样性及物种多度,Shannon值越大代表群落多样性越高,PD值越大代表群落的系统发育多样性也越高,OTU 丰度越大代表群落物种数量越多。由于在分析的6个站位中,有3个站位的样品只保留了2个有效重复,因此使用Kruskal-Wallis秩和检验进行各站位间生物多样性的差异比较分析,结果显示,3类多样性指数在各个站位间的差异均不显著,因此无法进行多重比较。但是,根据各站位多样性指数的平均值和标准差(表2)可以看出,近岸站位(TJ23、TJ27、TJ16)的生物多样性指数较高,远岸站位(TJ14)以及中间站位(TJ13)的生物多样性指数较低,其中,OTU 丰度和Shannon值在TJ17站位较高,PD值在TJ27站位较低。将这3种细菌多样性指数与环境参数进行Pearson相关性分析,结果显示只有PD与DO(r = −0.822,p < 0.05)和活性磷酸盐(r = 0.845,p < 0.05)具有显著相关性。
基于以上15个样品在各个站位的物种组成情况进行统计,共计获得44个门(变形菌门以纲水平分类),计算各个物种在各站位间的相对丰度平均值,按相对丰度比例排序,排名前10的门累计丰度在各个站位均超过了90%,其余记为其他(图2)。排名前10的物种分别属于α-变形菌(Alphaproteobacteria,p < 0.05)、γ-变形菌(Gammaproteobacteria,p < 0.05)、拟杆菌(Bacteroidetes,p = 0.079)、放线菌(Actinobacteria,p = 0.057)、δ-变形菌(Deltaproteobacteria,p < 0.05)、浮霉菌(Planctomycetes,p = 0.05)、疣微菌(Verrucomicrobia,p = 0.09)、蓝细菌(Cyanobacteria,p < 0.05)、β-变形菌(Betaproteobacteria,p = 0.232)、酸杆菌(Acidobacteria,p = 0.298)、其他(others,p = 0.132),在门水平上基于非参检验(Kruskal-Wallis秩和检验)发现α-变形菌、γ-变形菌、δ-变形菌、蓝细菌在各个站位间所占比例存在显著性差异。其中,最为明显的是TJ14站位,蓝细菌(Cyanobacteria)的比例(29%)显著高于其他站位,进一步在属水平上的分析发现,在TJ14站位中检出含量最多的蓝细菌为聚球藻属(Synechococcus,19%),在其他站位该物种含量均较低(<3%)。在OTU水平上的PCoA结果显示(图3),无论是基于OTU种类变化的Jaccard距离(ANOSIM,R= 0.799 7,p = 0.001)还是基于OTU种类与丰度变化的Bray-Curtis距离(ANOSIM,R= 0.799 7,p = 0.001),6个站位的样品均显著地分成了3组:TJ14一组,TJ13和TJ17一组,TJ16、TJ23和TJ27一组,这与按照取样距离进行的分组一致,说明,微生物群落组成沿渤海湾离岸距离变化有显著的差异。
基于LEfSe分析,对上述3个区域的细菌群落相对丰度在各个水平上的差异进行分析。其中,第1组代表近岸站位(TJ16、TJ23、TJ27);第2组代表中间站位(TJ13和TJ17);第3组代表远岸站位(TJ14)。在LDA值设为2(α = 0.05)时,共找出107个差异分类单元,其中属于第1组的差异分类单元有47种,属于第2组的差异分类单元有23种,属于第3组的差异分类单元有37种。差异分析结果包含了门、纲、目、科、属5个水平的差异物种信息,并以树图的形式展示差异分类单元的系统发育关系。为进一步提高不同组别差异物种辨识度,将LDA值设为3.5,其结果如图4所示,其中来自近岸站位(第1组)的差异微生物主要包括:γ-变形菌纲(Gammaproteobacteria)以及γ-变形菌纲的交替单胞菌目(Alteromonadales)、OM60科、海洋螺菌目(Oceanospirillales)、海洋螺菌科(Oceanospirillaceae)、弧菌目(Vibrionales)、假交替单胞菌科(Pseudoalteromonadaceae)、假交替单胞菌属(Pseudoalteromonas),拟杆菌门(Bacteroidetes)以及拟杆菌门的黄杆菌纲(Flavobateriia)黄杆菌目(Flavobacteriales)、Cryomorphaceae、Fluviicola,α-变形菌纲的Anaerospora、鞘脂单胞菌目(Sphingomonadales),δ-变形菌纲的蛭弧菌目(Bdellovibrionales)、噬菌弧菌科(Bacteriovoracaceae);来自中间站位(第2组)的差异微生物主要有α-变形菌纲(Alphaproteobacteria)以及α-变形菌纲的根瘤菌目(Rhizobiales)、叶杆菌科(Phyllobacteriaceae)、红杆菌目(Rhodobacterales)、红杆菌科(Rhodobacteraceae),拟杆菌门的Kordia、黄杆菌科(Flavobacteriaceae),γ-变形菌纲的军团菌目(Legionellales),疣微菌门(Verrucomicrobia),疣微菌门的丰佑菌纲(Opitutae)、紫红球目(Puniceicoccales)紫红球菌科(Puniceicoccaceae)、Coraliomargarita;来自远岸站位(第3组)的差异微生物主要有蓝细菌门(Cyanobacteria),集聚球藻亚纲(Synechococca) 聚球藻科(Synechococcaceae)、聚球藻目(Synechoccales)聚球藻属(Synechoccophycideae),浮霉菌门(Planctomycetes)、OM190科、agg27、Phycisphaerae、Phycisphaerales、浮霉菌纲(Planctomycetia)和Pirellulaceae,Pirellulales, α-变形菌纲的远洋杆菌科(Pelagibacteraceae)。立克次氏体目(Richettisales), δ-变形菌纲(Deltaproteobaterica)以及δ-变形菌纲的BP19目和γ-变形菌纲的着色菌目(Chromatiales)
将以LDA值设为2时得到的107个差异分类单元在各个站位的相对丰度与各环境因子进行相关性分析,结果显示(图5):近岸站位的差异物种主要与亚硝酸盐、硝酸盐、无机氮、活性磷酸盐、COD呈正相关,与湿度、DO呈负相关;而远岸站位的差异物种则主要与经度、离岸距离、水深、透明度、氨氮以及电导率呈正相关,与温度、亚硝态氮以及硝态氮呈负相关;中间站位则与盐度、COD、透明度呈负相关。
为了更好地评估空间因子和海水环境因子对浮游细菌群落结构变化的影响,我们基于Env、Trend、PCNM变量进行了VPA分析。进行VPA分析之前,先对各部分变量进行前向选择:Env包括离岸距离、水深、气压、气温、水温、湿度、透明度、盐度、溶氧、pH、电导率、化学需氧量、亚硝酸盐、硝酸盐、氨氮、无机氮、活性硅酸盐、活性磷酸盐,经前向选择后最终留下的环境因子是水深;Trend包括经度和纬度,经前向选择后保留下的地理因子是经度;PCNM分析后具有正空间相关的特征向量有2组,经前向选择后保留下一组显著PCNM特征向量(TJ13: 47.210 01,TJ14: −44.961 97,TJ16: −11.923 40,TJ17: 34.872 62,TJ23: −12.441 77,TJ27: −12.755 50)。基于前向选择后的各变量因子进行变差分解,结果显示(图6),Env单独解释部分并不具有显著性,Trend单独解释部分也不具有显著性,只有PCNM变量的单独解释部分具有显著性,解释了38.1%的群落变异。尽管环境因子和线性趋势单独解释部分并不显著,但是二者的共同解释量为16.1%,而PCNM和环境因子的共同解释量仅为4.6%。在整体分析中,有5.1%的群落变异是未被解释的。
利用FAPROTAX功能预测工具,基于属水平的BIOM文件对各站位的群落功能进行预测,结果有34.75%的属水平分类单元能够预测到功能信息,共预测到44类功能(表3),基于不同功能在各个站位的相对丰度进行的PCoA结果(图7)显示3个组别的站位能够明显分开,但是近岸站位的TJ16与中间站位混在一起。为进一步查看近岸站位与远岸站位的群落在功能上的差异,将TJ14的两个重复作为一组(第3组),中间站位TJ13和TJ17的各两个重复作为一组(第2组),近岸站位(除TJ16)作为一组(第1组),计算各类功能在距岸边不同距离的站位中的丰度差异。差异分析结果显示(表3),与有氧亚硝酸盐氧化作用、硝化作用、暗条件下的氢氧化、捕食与寄生、蓝细菌(cyanobacteria)、有氧光能自养、光能自养、光合营养、化能异养、好氧化能异养相关的功能在远近岸站位间均有显著性差异。其中与有氧亚硝酸盐氧化作用、硝化作用、蓝细菌、有氧光能自养、光能自养和光合营养相关的功能在远岸站位和中间站位均高于近岸站位;与化能异养、好氧化能异养相关的功能在近岸站位和中间站位均高于远岸站位;与暗条件下的氢氧化、捕食与寄生相关的功能在近岸站位均高于中间站位和远岸站位。此外,在近岸站位中,与芳香烃降解、芳香类化合物降解、烃降解、动物寄生或共生、胞内寄生相关的功能其相对丰度要高于中间站位和远岸站位,但是不具有统计意义上的显著性。
其中,有氧亚硝酸盐氧化作用和硝化作用的贡献者来自于硝化螺旋菌门(Nitrospirae)和硝化刺菌属(Nitrospina);有氧光能自养和光能自养功能的贡献者主要来自于蓝细菌门(Cyanobacteria);化能异养和耗氧化能异养功能的贡献者主要来自酸杆菌门(Acidobacteria)、放线菌门(Actinobacteria)、拟杆菌门(Bacteroidetes)、厚壁菌门(Firmicutes)、α-变形菌纲(Alphaproteobacteria)、β-变形菌纲(Betaproteobacteria)、γ-变形菌纲(Gammaproteobacteria)和疣微菌门(Verrucomicrobia);暗条件下的氢氧化功能的贡献者主要来自于副球菌属(Paracoccus)和噬氢菌属(Hydrogenophaga);捕食与寄生功能的贡献者主要来自噬菌弧菌属(Bacteriovorax)和蛭弧菌属(Bdellovibrio);芳香烃降解和芳香族化合物降解功能的贡献者主要来自红球菌属(Rhodococcus)和类诺卡氏属(Nocardioides)以及海神单胞属菌(Neptunomonas)和不动杆菌属(Acinetobacter);烃降解功能的贡献者主要来自红球菌属(Rhodococcus)、甲基孢囊菌科(Methylocystaceae)、海杆菌属(Marinobacter)、甲基暖菌属(Methylocaldum)、甲基单胞菌属(Methylomonas)、盐单胞菌属(Halomonas)和海神单胞菌Neptunomonas
从总体上看,在研究区域范围内渤海湾主要的优势浮游细菌种类与全球范围内的海洋浮游细菌种类组成[26]较为一致,主要由α-变形菌、γ-变形菌、拟杆菌、放线菌、浮霉菌、疣微菌、蓝细菌、β-变形菌等优势物种组成。但是,在研究范围内,不同站位间的浮游细菌群落组成存在明显的差异。其中,在近岸站位,γ-变形菌和拟杆菌占据较高的相对丰度,而在远岸站位蓝细菌的相对丰度较高。这种变化趋势与其他海域的相关研究大体一致,如Wang等[12]对东海近海微生物群落地理分布模式的研究结果也显示在近岸区(杭州湾)γ-变形菌为优势物种,而远海区(远海岛屿等)则是蓝细菌为优势物种;Bernhard等[27]对太平洋沿岸蒂拉穆克湾(Tillamook Bay)(俄勒冈州西北海岸)微生物群落的变化进行追踪,发现随环境梯度变化(如盐度、硅酸盐)浮游细菌群落组成有显著且可以预测的变化趋势,α-变形菌、蓝细菌主要出现在海洋样品中且随盐度降低而减少,而γ-变形菌、β-变形菌和拟杆菌则主要出现在近淡水区。在本研究中γ-变形菌和拟杆菌同样表现出在近岸相对丰度较高的现象,其中,γ-变形菌是最常被报道出现在沿海环境的微生物,比如,在地中海[28]、北大西洋[29]、南大西洋[30]均有报道,有的研究者甚至将γ-变形菌的局部峰值与营养源建立联系来推测点源污染可能来自的废水处理厂[31]。在本文中,来自γ-变形菌的微生物与硝酸盐、活性磷酸盐均具有显著的正相关性,这说明γ-变形菌纲在近岸的聚集并非是随机的,而是与无机盐的浓度紧密相关。另外,拟杆菌在近岸的相对高丰度主要来自纤维粘菌纲(Cytophagia)和黄杆菌纲(Flavobacteriia),其中,黄杆菌纲(Flavobacteriia)在本研究中与硝酸盐、亚硝酸盐、总无机氮呈极显著正相关,这种微生物常被报道易于与颗粒产生附着[32],与高含量营养物质存在相关性[26],与浮游植物繁殖密切相关,存在于藻际微环境中[33],这可能与渤海湾近岸营养物质丰富、各种人类活动扰动海水造成悬浮物含量较高有关。除此之外,在近岸站位中还检测到蛭弧菌目(Bdellovibrionales)、噬菌弧菌科(Bacteriovoracaceae)、噬菌弧菌属(Bacteriovorax)的富集,这导致功能预测结果中近岸站位与捕食和寄生相关的功能相对偏高。噬菌弧菌属(Bacteriovorax)对环境的适应性较为广泛,能在较短时间内裂解弧菌及其他常见病原菌,可以有效地控制水体中的氨氮、亚硝酸盐、硫化物等有毒有害物质[34],这种微生物在近岸站位具有较高的相对丰度反映出近岸站位的环境状况较差。在远岸站位中,与近岸站位物种相对丰度差异最为明显的是蓝细菌,蓝细菌在远岸站位(TJ14)明显高于近岸站位和中间站位。蓝细菌是海洋初级生产力的主要来源,在世界上绝大多数的温带和热带海区都存在,其中主要包括聚球藻(Synechococcus)和原绿球藻(Prochlorococcus[35],在本研究中Synechococcus为优势属,Synechococcus和其他蓝细菌一样能够进行光合作用,其生长与分布的主要影响因素包括pH、碳氮磷源等[36]。大部分Synechococcus能利用硝酸盐和氨作为生长所需的唯一氮源。在本案中,蓝细菌门中主要是Synechococcus显示出与氨氮显著的正相关性,但是与硝态氮、亚硝态氮和总无机氮以及活性磷酸盐含量之间没有显著相关性,这可能与TJ14站位的高氨氮含量有关,在He等[37]关于渤海海域秦皇岛近岸海区微生物群落分布规律的研究中,也发现蓝细菌的分布与氨氮含量密切相关,韩哲一[38]对聚球藻生长与海区再生氮的定量关系研究表明,聚球藻对氨氮的利用率要高于硝态氮,而远岸站位(TJ14)的氨氮含量在所监测的几个站位中是最高的。此外,尽管如此,影响蓝藻种类和分布的因素十分复杂,除了营养盐还包括水动力学、TOC等[39],有必要在该区域的后续调查中进行深入系统的研究。需要指出的是,在进行样品细菌群落组成统计分析之前,我们针对测序后的序列进行了去Chloroplast处理,在进行去Chloroplast之前,近岸站位(TJ16和TJ23)的Chloroplast相对比例分别占到15%和10%,其中主要包含Stramenopiles物种。去Chloroplast之后,保证样品只保留细菌种类,在TJ14站位中检出含量最多的蓝细菌为聚球藻属(Synechococcus,19%),在其他站位该物种含量均较低(<3%)。虽然代表远岸的站位只有一个,但是针对该站位样品进行的两次有效重复测定结果均显示归类到Synechococcus的序列所占比例较高,这与一些其他近海区域的研究结果是一致的[40-43]。当然,一些研究也指出,除了空间变化,Synechococcus的分布还存在季节变化,且随时间的变化其空间分布也会发生变化[36, 44],说明海水环境中影响蓝细菌分布的因素较为复杂,在以后的调查中,需加强对渤海湾蓝细菌分布及其种属变化受环境及季节影响的研究。本文基于高通量测序分析浮游细菌的相对丰度,重点在于关注不同站点间细菌群落组成的相对变化,一般来说,序列丰度可以可靠地测量微生物群落的相对变化,这在分析微生物群落的研究中是可信的[45]。因此,以上研究主要基于各站位间物种组成的相对变化进行比较分析,后续研究中需进一步加强对优势物种的定量分析,以进行站位间不同物种的绝对定量比较。
本研究中的6个站位取样点代表渤海湾从近岸到远岸的距离梯度。对6个站位的细菌α-多样性分析,虽然并未显示出统计学上的显著差异,但是除了TJ17站位,整体上仍然是近岸站位的细菌多样性高于远岸站位,这与位光山[46]关于黄河入海口渤海湾和胶州湾交汇处近岸水体中微生物多样性的变化规律报道是一致的,同时,也与其他海湾区如瓜纳巴拉海湾[47]、那不勒斯湾[43]的研究结果一致。近岸海域受陆源污染物及人类活动的影响较大,营养物质含量较丰富,微生物多样性也相对较高,但是由于受洋流等不确定性因素的影响,离岸站位也会出现相对较高的细菌多样性指数。从浮游细菌群落β-多样性变化的角度分析,微生物群落结构在远岸站位、中间站位和近岸站位明显分开,说明,在渤海湾这样的半封闭港湾内,随离岸距离的变化存在不同的微生物群落结构。进一步基于VPA分析环境因素和空间因素对浮游细菌群落结构变化的影响,发现PCNM变量单独解释部分对群落变异的贡献达38.1%,可以认为在研究区域内可能存在尚未测量但存在空间结构的微生境变量影响了群落的空间分布,当然也不排除过去历史事件在浮游细菌群落结构留下的痕迹[48]。在VPA分析中,Env和Trend单独解释部分,虽然并未显著解释群落变异,但实际上在分别利用Env(variance = 0.175,p = 0.034)、Trend(variance = 0.073,p = 0.034)与群落结构进行回归分析(marginal test)时,两者对于群落变异的解释都是显著的,同时,二者共同解释部分达16.1%,其中,环境因子经前向选择后保留下来的显著影响因子为水深,而由于渤海湾本身海底地形由岸向海倾斜,水深变化实际上在一定程度上代表的是离岸距离变化,因此,可认为这16.1%的群落变异仍可归咎于地理距离变化,即在所研究范围内,空间因子对群落结构变异具有主要的影响。该研究结果与其他关于近岸海区的报道有所不同,Wang等[12]对东海沿海跨越8个区域(约200 km)的浮游细菌地理分布研究结果显示PCNM变量单独解释部分(9.4%)比Env(4.74%)、Trend(0.56%)都要高,且Env和PCNM共同解释部分占到了49.7%,说明存在典型的“诱导空间变差” [49-50],即微生境变量空间变化引起响应变量即浮游细菌群落的分布产生类似的空间结构。在本研究中,环境因子诸如DO、pH、盐度、氮营养盐等广泛被报道对海洋环境微生物群落结构具有重要影响的参数,未检测到对群落结构变异的显著性影响,但是诸如硝酸盐、亚硝酸盐、无机氮、氨氮等指标与群落中有剧烈变化的关键物种有显著的相关性,尤其是与硝化作用、有氧亚硝酸盐氧化相关的类群在近岸站位明显低于远岸站位和中间站位,这说明,近岸站位微生物的氮同化作用较低,远岸站位的氮同化作用较高,海洋中氮营养盐的输入可能会引起与氮代谢相关的群落与功能的变化。除了已监测的环境因子,也可能存在其他未被测定的环境因子对群落结构有影响。基于物种组成进行的功能预测结果显示与芳香烃、芳香类化合物、烃类降解相关的功能在近岸偏高,说明未被测量的芳香类、烃类化合物可能也对群落变化有一定的贡献,这可能与渤海湾沿岸各大港口汇集的运输船只造成的石油泄漏有关,尽管海神单胞菌属Neptunomonas等与石油烃代谢相关的物种在各类站位间的差异并不显著,但是在近岸站位的相对丰度依然高于远岸站位,这在一定程度上可反映该区域的有机烃类物质含量变化[51]。除此之外,虽然渤海湾为半封闭港湾,但是由于风力、降水等原因该区域也会存在海流与水团运动,尽管我们测定了取样站位采样时的风向和风速,这些在近岸站位和远岸站位也存在明显的差异,但是由于微生物群落结构的变化对于环境的响应具有一定的滞后性[52],我们暂时尚无法评价该部分因素对群落结构的变化起到多大的作用,但是这些不确定性因素也可能会导致细菌群落结构的变化,在今后有必要加强对该方向的关注。
综上所述,本研究采用高通量测序技术研究在渤海湾近岸海域表层海水浮游细菌群落结构的变化规律,结果显示渤海湾近岸海域沿离岸距离变化存在明显变化的细菌群落结构。浮游细菌群落的α-多样性在不同站位间的差异不显著,但OTU richness、PD、Shannon仍显示近岸较高。随离岸距离的不同,近岸站位、中间站位和远岸站位存在特异富集的微生物类群,近岸站位显著富集的类群主要来自γ-变形菌纲(Gammaproteobacteria)、拟杆菌门(Bacteroidetes)和δ-变形菌纲(Deltaproteobacteria);中间站位显著富集的类群主要来自α-变形菌纲(Alphaproteobacteria)、γ-变形菌纲的军团菌目(Legionellales)和疣微菌门(Verrucomicrobia);远岸站位显著富集的类群主要来自蓝细菌门(Cyanobacteria)、浮霉菌门(Planctomycetes)和α-变形菌纲的远洋杆菌科(Pelagibacteraceae)。近岸站位的富集类群与海水中无机氮、硝酸盐、亚硝酸盐含量紧密相关,远岸站位的富集类群与海水中氨氮含量、透明度、电导率紧密相关。研究范围内的浮游细菌群落结构变异主要被PCNM变量所解释,说明可能存在尚未测量但具有空间结构的环境变量影响群落的空间分布。功能预测显示近岸站位与芳香族化合物、烃类物质降解、捕食和寄生、化能异养相关的功能类群相对高于远岸站位,揭示近岸站位的富营养与烃类污染等环境状况相较于远岸存在差异。本研究揭示渤海湾近岸环境因子和空间因子对海水中浮游细菌群落的影响,为了解渤海湾微生物生态与环境保护提供一定的参考。
  • 天津市科技计划项目(18ZXSZSF00100,18YFZCNC01180,16YFXTSY00580);国家自然科学基金项目(3150020230);中国科学院战略生物资源计划(KFJ-BRP-009)。
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2019年第41卷第12期
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doi: 10.3969/j.issn.0253-4193.2019.12.015
  • 接收时间:2018-12-12
  • 首发时间:2026-04-03
  • 出版时间:2019-12-25
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  • 收稿日期:2018-12-12
  • 修回日期:2019-06-21
基金
天津市科技计划项目(18ZXSZSF00100,18YFZCNC01180,16YFXTSY00580);国家自然科学基金项目(3150020230);中国科学院战略生物资源计划(KFJ-BRP-009)。
作者信息
    1 中国科学院天津工业生物技术研究所 天津市工业生物系统与过程工程重点实验室,天津 300308

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*黄志勇,研究员,主要从事环境微生物生态学研究。E-mail:
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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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