文献类型：期刊文献

中文题名：南海深海底层水和沉积物的细菌群落特征及其环境影响因子

英文题名：Bacterial Community Characteristics and Environmental Impact Factors of Deep-sea Bottom Water and Sediments in South China Sea

作者：黄柳鑫[1];侯庆华[1];曲学鹏[1];孔德明[1]

机构：[1]广东海洋大学海洋与气象学院/广东省近海海洋变化与灾害预警重点实验室,广东湛江524088

年份：2024

卷号：44

期号：6

起止页码：59

中文期刊名：广东海洋大学学报

外文期刊名：Journal of Guangdong Ocean University

收录：北大核心2023、、CSCD_E2023_2024、北大核心、CSCD

基金：国家重点研发计划(2018YFA0605601);广东海洋大学科研启动经费资助项目(060302032101)。

语种：中文

中文关键词：南海;深海;细菌;16S rRNA扩增子测序;环境因子

外文关键词：South China Sea;deep sea;bacteria;16S rRNA amplicon sequencing;environmental factor

中文摘要：【目的】探索南海深海底层细菌群落结构及其环境影响因子,为南海生态环境监测提供基础数据资料。【方法】利用16S rRNA高通量测序技术和统计学分析[如α多样性分析、β多样性分析和随机森林模型(Random forest analvsis,RF)分析等],结合溶解氧质量浓度、硝酸盐和磷酸盐浓度、温度、盐度、水深参数,对南海北部、东部和西部的6个深海水体及沉积物样本进行综合分析。【结果】细菌群落包括42个门、100个纲、249个目、357个科、542个属和998个种,其中变形菌门(相对丰度占比60.22%)、绿弯菌门(相对丰度占比7.44%)和放线菌门(相对丰度占比6.87%)等为主要优势门类,而γ-变形菌纲(相对丰度占比47.82%)、α-变形菌纲(相对丰度占比22.57%)和酸微菌纲(相对丰度占比5.86%)为优势亚纲。通过距离冗余分析(Distance-based redundancy analysis,db-RDA),发现底层硝酸盐浓度和温度与沉积物细菌群落多样性显著正相关(P<0.05)。随机森林模型分析指出,海洋芽孢杆菌(Bacillus aquimaris)、威尼斯不动杆菌(Acinetobacter venetianus)、阿氏芽孢杆菌(Bacillus aryabhattai)、油田水海杆菌(Marinobacter salsuginis)、噬甲基硝化还原菌(Methylophaga nitratireducenticrescens)、新疆假单胞菌(Pseudomonas xinjiangensis)、硒酸芽孢杆菌(Bacillus selenatarsenatis)、嗜碱盐单胞菌(Halomonas alkaliphila)、球孢囊菌(Sphaerisporangium)、马来西亚芽孢杆菌(Jeotgalibacillus malaysiensis)等是最重要的10种细菌。Spearman相关性分析表明,马来西亚芽孢杆菌丰度与底层磷酸盐浓度呈负相关关系(P<0.05),与底层盐度、底层溶解氧质量浓度和底层硝酸盐浓度呈正相关关系(P<0.05)。【结论】南海深海水体的深度、底层温度、底层盐度、底层溶解氧质量浓度及底层硝酸盐浓度等因素均会影响细菌群落多样性和丰度。其中,沉积物细菌多样性分别与底层盐度和硝酸盐浓度呈正相关关系,底层水细菌多样性与温度呈正相关关系。马来西亚芽孢杆菌的丰度分别与底层磷酸盐浓度、盐度、溶解氧质量浓度及硝酸盐浓度相关,可作为深海环境监测的有效指示种。

外文摘要：【Objective】To explore the bacterial community structure and its environmental influencing factors in the deep-sea floor of South China Sea,and to provide fundamental data for ecological environment monitoring in the region.【Method】The composition of bacterial communities in the deep-sea floor of South China Sea was analyzed using 16S rRNA high-throughput sequencing technology.Through statistical analyses,includingαdiversity,βdiversity,and random forest model analysis,consideringenvironmental parameters such as dissolved oxygen,nitrate,phosphate,temperature,salinity,and water depth,six deep-sea water and sediment samples from the northern,eastern,and western regions of South China Sea were comprehensively analyzed.【Result】The results showed that bacterial communities comprising 42 phyla,100 classes,249 orders,357 families,542 genera,and 998 species.The dominant phyla are Proteobacteria(relative abundance proportion 60.22%),Chloroflexi(relative abundance proportion 7.44%),and Actinobacteria(relative abundance proportion 6.87%),while the dominant subclasses are Gamma-proteobacteria(relative abundance proportion 47.82%),Alpha-proteobacteria(relative abundance proportion 22.57%),and Acidimicrobiia(relative abundance proportion 5.86%).It was found that nitrate and bottom temperature have positive correlation with bacterial community diversity in sediments through distance-based redundancy analysis(db-RDA)(P<0.05).Random forest analvsis(RF)analysis showed that Bacillus aquimaris,Acinetobacter venetianus,Bacillus aryabhattai,Marinobacter salsuginis,Methylophaga nitratireducenticrescens,Pseudomonas xinjiangensis,Bacillus selenatarsenatis,Halomonas alkaliphila,Sphaerisporangium,and Jeotgalibacillus malaysiensis were the most important 10 bacteria.Spearman correlation analysis revealed that the abundance of J.malaysiensis was negatively correlated with phosphate concentration in the bottom layer(P<0.05)and positively correlated with salinity,dissolved oxygen,and nitrate concentrations in the bottom layer(P<0.05).【Conclusions】The depth,bottom temperature,bottom salinity,bottom dissolved oxygen,and bottom nitrate concentration all could influence bacterial diversity and abundance.The bacterial diversity of sediments is positively correlated with bottom salinity and nitrate concentration.The bacterial diversity in bottom water is positively correlated with temperature.The abundance of J.malaysiensis is associated with bottom phosphate concentration,salinity,dissolved oxygen concentration,and nitrate concentration,making it an effective indicator for deep-sea environmental monitoring.