我国黄、东海典型海域微生物群落结构及其与环境变化的关系
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摘要
海洋微生物具有丰度高、分布广的特点，同时可以产生许多特殊的活性物质。它们在能量传递和多种重要生源要素的生物地球化学循环中起到重要的作用，一直以来都是海洋生态学研究中的热点。本文应用测序、分子生物学方法和培养手段对我国黄、东海典型海域微生物的群落结构和特殊种类做了相应研究。
利用PCR-DGGE方法，结合克隆、测序技术对黄海中部海域细菌群落结构的周年变化进行研究。结果显示，研究海域中主要存在8个细菌类群，分别是Alphaproteobacteria、Gammaproteobacteria、Deltaproteobacteria、Cyanobacteria、Actinobacteria、Flavobacteria、Bacilli和SAR406类群。其中Alphaproteobacteria是群落组成中绝对的优势类群，另外，各月份中一直存在的类群还有Gammaproteobacteria、Flavobacteria、Bacilli及SAR406类群。DGGE图谱上条带的多少可以表征多样性的高低，在时间尺度上，9月份多样性最高（25条条带），10月份多样性最低（19条）。依据条带有无的聚类分析显示，调查海区的细菌群落结构存在周年变化，在1-5月中，每个月份各个水层的群落结构相似，可以按月份聚类，并最终聚成一枝；6-11月中，不同月份、水层的样品群落结构复杂，聚类相互交叉。水文环境（温度和盐度）的变化可能是影响细菌群落结构变化和聚类的主要原因，黄海冷水团的产生、鼎盛和衰退，对6-11月样品的聚类产生明显影响，特别是8月份处在黄海冷水团的鼎盛时期，细菌群落结构最为特殊，聚类自成一枝。
使用罗氏454高通量测序技术在东海选取一个断面（2011年5月）进行细菌群落结构的研究。5个站位共17个海水样品和5个表层沉积物样品获得16SrDNA V1-V3区优化序列149067条，平均长度454nt。细菌多样性丰富（Shannon指数平均为5.38），且沉积物样品（平均7.65）高于海水样品（平均4.71）。经与SILVA数据库对比，确定22个门，34个纲，74个目，146个科及333个属的细菌分类信息，其中有十余个门的细菌在以往同海域的研究中未见报道。另外，各分类阶元中都存在一些不能确定具体分类的信息，其含量变化在海水样品中为1.52-59.96%，沉积物样品中为8.07-71.61%，从“门”到“属”有增加趋势。纲水平上，海水群落组成以Alphaproteobacteria、Gammaproteobacteria、Deltaproteobacteria和Flavobacteria等为优势，沉积物中以Gammaproteobacteria、Deltaproteobacteria和Phycisphaerae为优势。对比海水样品的聚类和水团划分结果显示，细菌群落结构可能受到东海水团和其它因素的共同影响，黑潮表层水和中层水中的样品分别按水团的划分相聚在一起，长江冲淡水和黑潮次表层水中的一些聚类结果可能受到叶绿素荧光值的影响，另有一些因素的综合作用也可能影响细菌的群落结构。
上述东海海域的古菌群落结构同样使用罗氏454高通量测序技术进行研究，共获得16S rDNA V3-V5区的优化序列196018条，其中海水样品171653条，平均长度495nt，沉积物样品24365条，平均长度511nt。古菌多样性丰富（Shannon指数平均为4.79），且沉积物样品（平均6.25）高于海水样品（平均4.36）。经与SILVA数据库对比，确定2个门，13个纲，10个目，21个科及25个属的分类信息，各分类阶元均存在不能确定分类的信息，含量在海水样品中为0.04-85.25%，沉积物中为1.40-86.95%，从“门”到“属”有增加趋势。纲水平上，海水样品群落组成以Marine Group I和Thermoplasmata为优势，沉积物中的优势类群还有Halobacteria、Group C3及Marine Benthic Group B。不同海水样品的物种丰富度与水团划分的比较显示，丰富度指数由高到低的排序为黑潮次表层水（Chao1平均2751）、黑潮中层水（2432）、黑潮表层水（2259）、长江冲淡水（2131）、东海陆架混合水（1843）。东海海域的细菌、古菌在属的水平上均存在较高比例无准确分类的信息，提示东海蕴含着很高的未知微生物资源。
胶州湾是一个半封闭海湾，受人类活动的影响明显，通过监测胶州湾大肠菌群丰度的长期变化，不仅能在时间和空间尺度上对特定类群的细菌进行研究，也可以使用大肠菌群丰度作为指标对环境变化进行评价。采用最大可能数计数法对表层海水中大肠菌群丰度进行连续9年（108个月）的监测，发现其丰度的周年变化明显，夏秋季呈上升趋势，冬、春两季呈下降趋势，一年中最高丰度（9月，（2.18±1.93）×10~4个·L~(-1)）与最低丰度（4月，（1.05±0.71）×10~4个·L~(-1)）相差约2.1倍。大肠菌群的丰度分布具有明显的区域性特征，河口区（（5.20±2.35）×10~4个·L~(-1)）最高，湾内区最低（（0.41±0.08）×10~4个·L~(-1)），差异近13倍。使用SPSS软件对大肠菌群的平均丰度与环境因子进行两两相关性分析，结果表明大肠菌群丰度变化与胶州湾表层海水中的总氮、溶解有机碳、叶绿素a浓度、盐度以及青岛市的废水排放量均显著相关。表层海水中大肠菌群丰度自2005年至2009年持续下降，作为环境评价的指标，说明胶州湾环境质量在5年内一直有所好转，也显示河口区和湾口区环境污染状况较为严重，应作为今后环保工作的重点。
对黄、东海典型海区微生物群落结构和特殊种类的研究，有助于了解微生物和环境变化间的关系并全面认识海洋生态系统。通过本文中的实验，也为深入开展我国黄、东海海洋微生物研究奠定了基础。
Marine microorganisms have the characteristics of high abundance and widedistribution. The microorganisms can produce many active substances and playimportant roles either in the energy flows or in the material circulations. Study onmarine microorganisms is a hotspot in marine ecology. In this article, the microbialcommunity structure and special bacteria in typical areas of the Yellow Sea and EastChina Sea were studied by sequencing, molecular biological methods and culture.
In order to study the annual variation of bacterial community structure in thecentral Yellow Sea, PCR-DGGE, clone and sequencing methods were employed.There were eight main classes of bacteria in the sampling area, includingAlphaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Cyanobacteria,Actinobacteria, Flavobacteria, Bacilli and SAR406cluster. Alphaproteobacteria wasthe dominant class in the central Yellow Sea, Gammaproteobacteria, Flavobacteriaand Bacilli were also the common classes in different months. Quantity of bands inDGGE profiles showed the diversity of different samples. In this study, diversity washighest in September with25bands while October was the lowst with19bands. Thecluster analysis which based on the presence and absence of each band showed anannual variation of bacterial community structure. Structures of different layers’samples in different months were alike and could be clustered together duringJannuary to May, while the structures were much more complex in June to Novenber.The hydrogeological environments (temperature and salinity) might influence thecommunity structure most. For example, the Yellow Sea Cold Water Mass influencedthe bacterial community structure in June to Novenber significantly, especially inAugust, which samples could be clustered in an independent branch.
Bacterial community structures in one section of the East China Sea in May2011 were studied by Roche454pyrosequencing technology.17seawater samples and5sediment samples were collected in5stations. Totally,149067optimized reads withthe average length of454nt in V1-V3regions of the16S rDNA were obtained. Thediversity was high (the average of Shannon indices was5.38), and the sedimentsamples (7.65) were higher than seawater ones (4.71). In all,22phyla,34classes,74orders,146families, and333genera were identified by comparing against the SILVAdatabase. More than10phyla were reported in the East China Sea for the first time.There was some unclassified information in each taxonomic category with theproportions increased from “phylum” to “genus”. The unclassified information washigher in sediment samples (8.07-71.61%) than in seawater samples (1.52-59.96%).Alphaproteobacteria, Gammaproteobacteria, Deltaproteobacteria; and Flavobacteriawere some dominant classes in seawater samples while Gammaproteobacteria,Deltaproteobacteria, and Phycisphaerae were dominant in sediment. Comparation ofclustering and partition of water masses showed that bacterial diversity andcommunity structure might be affected by the water masses in the East China Seaand other factors. The samples in Kuroshio surface water (KSW) and intermediatewater (KIW) were clustered together, samples in Changjiang diluted water (CDW)and Kuroshio subsurface water (KSSW) might be influenced by chlorophyllfluorescence. There were also some comprehensive factors which could influencethe bacterial community structure.
Archael community structure in the same area in the ECS were studied also byRoche454pyrosequencing technology and obtained196018optimized reads inV3-V5regions of16S rDNA.171653optimized reads were detected with theaverage length of495nt in seawater samples while sediment samples contained24365optimized reads with the average length of511nt. The diversity was high (theaverage of Shannon indices was4.79), and the sediment samples (6.25) were higherthan seawater ones (4.36). Totally,2phyla,13classes,10orders,21families, and25genera were identified by comparing against the SILVA database. Unclassifiedinformation in each taxonomic category with the proportions increased from“phylum” to “genus”. The unclassified information in sediment (1.40-86.95%) was more than it in seawater (0.04-85.25%). Marine Group I and Thermoplasmata weredominant in seawater while Marine Group I, Thermoplasmata Halobacteria, GroupC3and Marine Benthic Group B were dominant in sediment. The comparation ofrichness indices and partition of water masses showed that the indices from high tolow were samples in KSSW (average Chao1indices was2751), KIW (2432), KSW(2259), CDW (2131) and shelf mixing water (SMW,1843). The high proportions ofunclassified information in bacterial and archaeal studies indicated that the ECScontained a lot of unknown microbial resources.
Jiaozhou Bay is a semi-enclosed bay and can be affected by human activitiessignificantly. The abundance of coliform bacteria is an indicator of environmentalquanlity. We can either obtain the results on the temporal and spatial scales orappraise the environment by monitoring the abundance. The MPN method wasemployed to study the abundance of coliform bacteria in Jiaozhou Bay. A9-year(108months) monitoring result showed clear annual variations. The abundance ofcoliform bacteria increased in summer and autumn and reduced in winter and spring.The maximum (in Semptember,(2.18±1.93)×10~4·L~(-1)) was about2.1times of theminimum (in April,(1.05±0.71)×10~4·L~(-1)) on an annual basis. The abundance ofcoliform bacteria in the surface seawater in Jiaozhou Bay was different in4marinedivisions (the estuary area, the inner bay area, the outer bay area and the bay moutharea). It’s highest in estuary area ((5.20±2.35)×10~4·L~(-1)) and lowest in inner bay area((0.41±0.08)×10~4·L~(-1)), the highest value was about13times of the lowest one.Correlation analysis between the abundance of the coliform bacteria and theenvironmental factors showed that the abundance was significantly corre-lated withsewage discharged in Qingdao, salinity, concentration of total nitrogen, dissolvedorganic carbon, and chlorophyll-a in the Jiaozhou Bay. Analysis on the interannualvariations showed that the abundance of coliform bacteria declined from2005to2009, suggesting that the environmental quality of Jiaozhou Bay had been improved.The pollutin was much more serious in the estuary area and bay mouth area whichindicated those areas should be paid more attention on environmental protection inthe future.
The researches on microbial community structure and special bacteria in typicalareas of the Yellow Sea and East China Sea helpe people to better understand therelationship between environmental changes and microorganisms. It can also layfoundation for researches on microorganisms in the Yellow Sea and East China Sea.
利用PCR-DGGE方法，结合克隆、测序技术对黄海中部海域细菌群落结构的周年变化进行研究。结果显示，研究海域中主要存在8个细菌类群，分别是Alphaproteobacteria、Gammaproteobacteria、Deltaproteobacteria、Cyanobacteria、Actinobacteria、Flavobacteria、Bacilli和SAR406类群。其中Alphaproteobacteria是群落组成中绝对的优势类群，另外，各月份中一直存在的类群还有Gammaproteobacteria、Flavobacteria、Bacilli及SAR406类群。DGGE图谱上条带的多少可以表征多样性的高低，在时间尺度上，9月份多样性最高（25条条带），10月份多样性最低（19条）。依据条带有无的聚类分析显示，调查海区的细菌群落结构存在周年变化，在1-5月中，每个月份各个水层的群落结构相似，可以按月份聚类，并最终聚成一枝；6-11月中，不同月份、水层的样品群落结构复杂，聚类相互交叉。水文环境（温度和盐度）的变化可能是影响细菌群落结构变化和聚类的主要原因，黄海冷水团的产生、鼎盛和衰退，对6-11月样品的聚类产生明显影响，特别是8月份处在黄海冷水团的鼎盛时期，细菌群落结构最为特殊，聚类自成一枝。
使用罗氏454高通量测序技术在东海选取一个断面（2011年5月）进行细菌群落结构的研究。5个站位共17个海水样品和5个表层沉积物样品获得16SrDNA V1-V3区优化序列149067条，平均长度454nt。细菌多样性丰富（Shannon指数平均为5.38），且沉积物样品（平均7.65）高于海水样品（平均4.71）。经与SILVA数据库对比，确定22个门，34个纲，74个目，146个科及333个属的细菌分类信息，其中有十余个门的细菌在以往同海域的研究中未见报道。另外，各分类阶元中都存在一些不能确定具体分类的信息，其含量变化在海水样品中为1.52-59.96%，沉积物样品中为8.07-71.61%，从“门”到“属”有增加趋势。纲水平上，海水群落组成以Alphaproteobacteria、Gammaproteobacteria、Deltaproteobacteria和Flavobacteria等为优势，沉积物中以Gammaproteobacteria、Deltaproteobacteria和Phycisphaerae为优势。对比海水样品的聚类和水团划分结果显示，细菌群落结构可能受到东海水团和其它因素的共同影响，黑潮表层水和中层水中的样品分别按水团的划分相聚在一起，长江冲淡水和黑潮次表层水中的一些聚类结果可能受到叶绿素荧光值的影响，另有一些因素的综合作用也可能影响细菌的群落结构。
上述东海海域的古菌群落结构同样使用罗氏454高通量测序技术进行研究，共获得16S rDNA V3-V5区的优化序列196018条，其中海水样品171653条，平均长度495nt，沉积物样品24365条，平均长度511nt。古菌多样性丰富（Shannon指数平均为4.79），且沉积物样品（平均6.25）高于海水样品（平均4.36）。经与SILVA数据库对比，确定2个门，13个纲，10个目，21个科及25个属的分类信息，各分类阶元均存在不能确定分类的信息，含量在海水样品中为0.04-85.25%，沉积物中为1.40-86.95%，从“门”到“属”有增加趋势。纲水平上，海水样品群落组成以Marine Group I和Thermoplasmata为优势，沉积物中的优势类群还有Halobacteria、Group C3及Marine Benthic Group B。不同海水样品的物种丰富度与水团划分的比较显示，丰富度指数由高到低的排序为黑潮次表层水（Chao1平均2751）、黑潮中层水（2432）、黑潮表层水（2259）、长江冲淡水（2131）、东海陆架混合水（1843）。东海海域的细菌、古菌在属的水平上均存在较高比例无准确分类的信息，提示东海蕴含着很高的未知微生物资源。
胶州湾是一个半封闭海湾，受人类活动的影响明显，通过监测胶州湾大肠菌群丰度的长期变化，不仅能在时间和空间尺度上对特定类群的细菌进行研究，也可以使用大肠菌群丰度作为指标对环境变化进行评价。采用最大可能数计数法对表层海水中大肠菌群丰度进行连续9年（108个月）的监测，发现其丰度的周年变化明显，夏秋季呈上升趋势，冬、春两季呈下降趋势，一年中最高丰度（9月，（2.18±1.93）×10~4个·L~(-1)）与最低丰度（4月，（1.05±0.71）×10~4个·L~(-1)）相差约2.1倍。大肠菌群的丰度分布具有明显的区域性特征，河口区（（5.20±2.35）×10~4个·L~(-1)）最高，湾内区最低（（0.41±0.08）×10~4个·L~(-1)），差异近13倍。使用SPSS软件对大肠菌群的平均丰度与环境因子进行两两相关性分析，结果表明大肠菌群丰度变化与胶州湾表层海水中的总氮、溶解有机碳、叶绿素a浓度、盐度以及青岛市的废水排放量均显著相关。表层海水中大肠菌群丰度自2005年至2009年持续下降，作为环境评价的指标，说明胶州湾环境质量在5年内一直有所好转，也显示河口区和湾口区环境污染状况较为严重，应作为今后环保工作的重点。
对黄、东海典型海区微生物群落结构和特殊种类的研究，有助于了解微生物和环境变化间的关系并全面认识海洋生态系统。通过本文中的实验，也为深入开展我国黄、东海海洋微生物研究奠定了基础。
Marine microorganisms have the characteristics of high abundance and widedistribution. The microorganisms can produce many active substances and playimportant roles either in the energy flows or in the material circulations. Study onmarine microorganisms is a hotspot in marine ecology. In this article, the microbialcommunity structure and special bacteria in typical areas of the Yellow Sea and EastChina Sea were studied by sequencing, molecular biological methods and culture.
In order to study the annual variation of bacterial community structure in thecentral Yellow Sea, PCR-DGGE, clone and sequencing methods were employed.There were eight main classes of bacteria in the sampling area, includingAlphaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Cyanobacteria,Actinobacteria, Flavobacteria, Bacilli and SAR406cluster. Alphaproteobacteria wasthe dominant class in the central Yellow Sea, Gammaproteobacteria, Flavobacteriaand Bacilli were also the common classes in different months. Quantity of bands inDGGE profiles showed the diversity of different samples. In this study, diversity washighest in September with25bands while October was the lowst with19bands. Thecluster analysis which based on the presence and absence of each band showed anannual variation of bacterial community structure. Structures of different layers’samples in different months were alike and could be clustered together duringJannuary to May, while the structures were much more complex in June to Novenber.The hydrogeological environments (temperature and salinity) might influence thecommunity structure most. For example, the Yellow Sea Cold Water Mass influencedthe bacterial community structure in June to Novenber significantly, especially inAugust, which samples could be clustered in an independent branch.
Bacterial community structures in one section of the East China Sea in May2011 were studied by Roche454pyrosequencing technology.17seawater samples and5sediment samples were collected in5stations. Totally,149067optimized reads withthe average length of454nt in V1-V3regions of the16S rDNA were obtained. Thediversity was high (the average of Shannon indices was5.38), and the sedimentsamples (7.65) were higher than seawater ones (4.71). In all,22phyla,34classes,74orders,146families, and333genera were identified by comparing against the SILVAdatabase. More than10phyla were reported in the East China Sea for the first time.There was some unclassified information in each taxonomic category with theproportions increased from “phylum” to “genus”. The unclassified information washigher in sediment samples (8.07-71.61%) than in seawater samples (1.52-59.96%).Alphaproteobacteria, Gammaproteobacteria, Deltaproteobacteria; and Flavobacteriawere some dominant classes in seawater samples while Gammaproteobacteria,Deltaproteobacteria, and Phycisphaerae were dominant in sediment. Comparation ofclustering and partition of water masses showed that bacterial diversity andcommunity structure might be affected by the water masses in the East China Seaand other factors. The samples in Kuroshio surface water (KSW) and intermediatewater (KIW) were clustered together, samples in Changjiang diluted water (CDW)and Kuroshio subsurface water (KSSW) might be influenced by chlorophyllfluorescence. There were also some comprehensive factors which could influencethe bacterial community structure.
Archael community structure in the same area in the ECS were studied also byRoche454pyrosequencing technology and obtained196018optimized reads inV3-V5regions of16S rDNA.171653optimized reads were detected with theaverage length of495nt in seawater samples while sediment samples contained24365optimized reads with the average length of511nt. The diversity was high (theaverage of Shannon indices was4.79), and the sediment samples (6.25) were higherthan seawater ones (4.36). Totally,2phyla,13classes,10orders,21families, and25genera were identified by comparing against the SILVA database. Unclassifiedinformation in each taxonomic category with the proportions increased from“phylum” to “genus”. The unclassified information in sediment (1.40-86.95%) was more than it in seawater (0.04-85.25%). Marine Group I and Thermoplasmata weredominant in seawater while Marine Group I, Thermoplasmata Halobacteria, GroupC3and Marine Benthic Group B were dominant in sediment. The comparation ofrichness indices and partition of water masses showed that the indices from high tolow were samples in KSSW (average Chao1indices was2751), KIW (2432), KSW(2259), CDW (2131) and shelf mixing water (SMW,1843). The high proportions ofunclassified information in bacterial and archaeal studies indicated that the ECScontained a lot of unknown microbial resources.
Jiaozhou Bay is a semi-enclosed bay and can be affected by human activitiessignificantly. The abundance of coliform bacteria is an indicator of environmentalquanlity. We can either obtain the results on the temporal and spatial scales orappraise the environment by monitoring the abundance. The MPN method wasemployed to study the abundance of coliform bacteria in Jiaozhou Bay. A9-year(108months) monitoring result showed clear annual variations. The abundance ofcoliform bacteria increased in summer and autumn and reduced in winter and spring.The maximum (in Semptember,(2.18±1.93)×10~4·L~(-1)) was about2.1times of theminimum (in April,(1.05±0.71)×10~4·L~(-1)) on an annual basis. The abundance ofcoliform bacteria in the surface seawater in Jiaozhou Bay was different in4marinedivisions (the estuary area, the inner bay area, the outer bay area and the bay moutharea). It’s highest in estuary area ((5.20±2.35)×10~4·L~(-1)) and lowest in inner bay area((0.41±0.08)×10~4·L~(-1)), the highest value was about13times of the lowest one.Correlation analysis between the abundance of the coliform bacteria and theenvironmental factors showed that the abundance was significantly corre-lated withsewage discharged in Qingdao, salinity, concentration of total nitrogen, dissolvedorganic carbon, and chlorophyll-a in the Jiaozhou Bay. Analysis on the interannualvariations showed that the abundance of coliform bacteria declined from2005to2009, suggesting that the environmental quality of Jiaozhou Bay had been improved.The pollutin was much more serious in the estuary area and bay mouth area whichindicated those areas should be paid more attention on environmental protection inthe future.
The researches on microbial community structure and special bacteria in typicalareas of the Yellow Sea and East China Sea helpe people to better understand therelationship between environmental changes and microorganisms. It can also layfoundation for researches on microorganisms in the Yellow Sea and East China Sea.
引文
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