基于16S rRNA基因高通量绝对定量解析黄河入海口淡水与海水水体细菌群落特征
作者:
基金项目:

国家重点研发计划(2023YFC3709004);国家自然科学基金(U22A20615)


Characterization of bacterial communities in freshwater and seawater of the Yellow River estuary by 16S rRNA gene high-throughput absolute abundance quantification
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [53]
  • |
  • 相似文献
  • | | |
  • 文章评论
    摘要:

    【目的】 黄河入海口地处河流-陆地-海洋的交汇地带,是淡水水体与海水水体相互作用的混合区域,也是多样化和生产力较强的河口生态系统。本研究以黄河入海口为研究对象,探究其淡水与海水水体细菌群落特征。【方法】 采用高通量绝对定量技术,获得细菌群落绝对丰度信息,在此基础上比较分析2种水体细菌群落优势物种组成、α和β多样性、网络共现模式、构建机制及潜在功能,并探究优势物种与水体环境因子的相关性。【结果】 淡水水体细菌的绝对拷贝数为2.61×106 copies/mL,是海水的1.8倍。2种水体共同优势菌门为放线菌门、假单胞菌门、蓝细菌门和拟杆菌门等,其各自绝对丰度有明显差异。淡水中放线菌门数量最高,约等于海水中所有优势菌门数量之和,而海水中假单胞菌门数量最高。淡水水体细菌群落α多样性高于海水,2种水体细菌群落结构存在较明显的差异,主要源于各自优势物种丰度的差异。淡水水体细菌共现网络较海水更复杂和稳定,随机性过程主导2种水体细菌群落构建机制。2种水体细菌群落功能结构存在差异,但拥有共性功能。新陈代谢是2种水体细菌群落丰度最高的功能,其在淡水中的相对丰度显著高于海水。5种环境因子[pH、氧化还原电位(oxidation-reduction potential, ORP)、电导率(electrical conductivity, EC)、总有机碳(total organic carbon, TOC)和总氮(total nitrogen, TN)]与水体优势物种分别具有不同程度的相关性。除EC外的4种环境因子间均存在共线性关系,与pH、TOC和TN呈正相关关系的优势菌属均与ORP呈负相关,反之亦然。放线菌门和假单胞菌门分别与pH呈正相关和负相关关系。【结论】 黄河入海口淡水和海水水体细菌群落特征存在较大差异,主要体现在细菌数量、多样性、功能结构和共现网络上,但2种水体具有相似的优势物种组成和群落构建机制。本研究结果可为黄河入海口水体微生物生态学研究及开发利用微生物资源提供数据支持。

    Abstract:

    [Objective] The Yellow River estuary located at the confluence of the Yellow River, land, and ocean is an area with mixed freshwater and seawater and a diverse and productive estuary ecosystem. This study aims to characterize the bacterial communities in freshwater and seawater of the Yellow River estuary. [Methods] High-throughput absolute abundance quantification was adopted to measure the absolute abundance of bacterial communities. The dominant taxa, α and β diversity, co-occurrence network, assembly mechanisms, and potential functions were compared between the bacterial communities in freshwater and seawater. The correlations between dominant taxa and environmental factors were explored. [Results] The absolute abundance of bacteria in freshwater was 2.61×106 copies/mL, which was 1.8 times of that in seawater. The common dominant phyla in freshwater and seawater were Actinomycetota, Pseudomonadota, Cyanobacteriota, and Bacteroidota, with significant differences in absolute abundance. The abundance of Actinomycetota ranked first in freshwater, which was approximately equal to the sum of all dominant phyla in seawater. The abundance of Pseudomonadota was the highest in seawater. The alpha diversity of bacteria in freshwater was higher than that in seawater. There were significant differences in the bacterial community structure between freshwater and seawater, mainly due to the differences in the abundance of the dominant taxa. The bacterial co-occurrence network in freshwater was more complex and stable than that in seawater, and stochastic processes dominated the bacterial community assembly in both freshwater and seawater. The bacterial communities in freshwater and seawater presented different functions, while they shared some common functions. Metabolism was the most abundant function, with higher relative abundance in freshwater than in seawater. Five environmental factors ((pH, oxidation-reduction potential (ORP), electrical conductivity (EC), total organic carbon (TOC), and total nitrogen (TN)) correlated with the dominant bacterial taxa to different extent. There were collinear relationships among the four environmental factors except EC. The dominant genera showing positive correlations with pH, TOC and TN were all negatively correlated with ORP, and vice versa. Actinomycetota and Pseudomonadota were positively and negatively correlated with pH, respectively. [Conclusion] The bacterial communities showed great differences between freshwater and seawater in the Yellow River estuary. The differences were mainly reflected in the abundance, diversity, functional structure, and co-occurrence network. The bacterial communities in freshwater and seawater had similar dominant taxa and assembly mechanisms. The results provide data support for studying the microbial ecology and exploiting microbial resources in the Yellow River estuary.

    参考文献
    [1] ZHANG HX, ZHENG SL, DING JW, WANG OM, LIU FH. Spatial variation in bacterial community in natural wetland-river-sea ecosystems[J]. Journal of Basic Microbiology, 2017, 57(6): 536-546.
    [2] HOU CY, YI YJ, SONG J, ZHOU Y. Effect of water-sediment regulation operation on sediment grain size and nutrient content in the lower Yellow River[J]. Journal of Cleaner Production, 2021, 279: 123533.
    [3] 封永辉, 张人铭, 时春明, 李林, 马燕武. 参与水体循环的微生物群落研究[J]. 安徽农业科学, 2016, 44(1): 132-134. FENG YH, ZHANG RM, SHI CM, LI L, MA YW. Study of microbial community participating in water cycle[J]. Journal of Anhui Agricultural Sciences, 2016, 44(1): 132-134(in Chinese).
    [4] CHAO CX, WANG LG, LI Y, YAN ZW, LIU HM, YU D, LIU CH. Response of sediment and water microbial communities to submerged vegetations restoration in a shallow eutrophic lake[J]. Science of the Total Environment, 2021, 801: 149701.
    [5] CHI ZF, ZHU YH, LI H, WU HT, YAN BX. Unraveling bacterial community structure and function and their links with natural salinity gradient in the Yellow River Delta[J]. Science of the Total Environment, 2021, 773: 145673.
    [6] YANG C, LV DT, JIANG SY, LIN H, SUN JQ, LI KJ, SUN J. Soil salinity regulation of soil microbial carbon metabolic function in the Yellow River Delta, China[J]. Science of the Total Environment, 2021, 790: 148258.
    [7] WEI GS, LI MC, LI FG, LI H, GAO Z. Distinct distribution patterns of prokaryotes between sediment and water in the Yellow River estuary[J]. Applied Microbiology and Biotechnology, 2016, 100(22): 9683-9697.
    [8] 位光山, 张嘉炜, 李明聪, 高峥. 黄河入海口水体细菌群落多样性及分布特征[J]. 生物技术通报, 2017, 33(10): 199-208. WEI GS, ZHANG JW, LI MC, GAO Z. The diversity and distribution pattern of bacterial community in the water of Yellow River Estuary[J]. Biotechnology Bulletin, 2017, 33(10): 199-208(in Chinese).
    [9] YIN XB, WANG WT, WANG AH, HE MC, LIN CY, OUYANG W, LIU XT. Microbial community structure and metabolic potential in the coastal sediments around the Yellow River Estuary[J]. Science of the Total Environment, 2022, 816: 151582.
    [10] MAGHINI DG, DVORAK M, DAHLEN A, ROOS M, DOYLE B, KUERSTEN S, BHATT AS. Quantifying bias introduced by sample collection in relative and absolute microbiome measurements[J]. Nature Biotechnology, 2024, 42(2): 328-338.
    [11] PROPS R, KERCKHOF FM, RUBBENS P, de VRIEZE J, HERNANDEZ SANABRIA E, WAEGEMAN W, MONSIEURS P, HAMMES F, BOON N. Absolute quantification of microbial taxon abundances[J]. The ISME Journal, 2017, 11(2): 584-587.
    [12] 张紫薇, 陈召莹, 张甜娜, 周石磊, 崔建升, 罗晓. 基于高通量绝对定量测序解析岗南水库微生物群落的时空分布特征及关键驱动因素[J]. 环境科学学报, 2022, 42(2): 224-239. ZHANG ZW, CHEN ZY, ZHANG TN, ZHOU SL, CUI JS, LUO X. Spatiotemporal characteristics and key driving factors of microbial community evolution based on high-throughput absolute quantification sequencing in the Gangnan Reservoir[J]. Acta Scientiae Circumstantiae, 2022, 42(2): 224-239(in Chinese).
    [13] TKACZ A, HORTALA M, POOLE PS. Absolute quantitation of microbiota abundance in environmental samples[J]. Microbiome, 2018, 6(1): 110.
    [14] TOURLOUSSE DM, YOSHIIKE S, OHASHI A, MATSUKURA S, NODA N, SEKIGUCHI Y. Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing[J]. Nucleic Acids Research, 2017, 45(4): e23.
    [15] 中华人民共和国环境保护部. 水质样品的保存和管理技术规定: HJ 493—2009[S]. 北京: 中国环境科学出版社, 2009. Ministry of Ecology and Environment of the People’s Republic of China. Water Quality—Technical Regulation of the Preservation and Handling of Samples: HJ 493—2009[S]. Beijing: China Environmental Science Press, 2009(in Chinese).
    [16] LIU CS, ZHAO DF, MA WJ, GUO YD, WANG AJ, WANG QL, LEE DJ. Denitrifying sulfide removal process on high-salinity wastewaters in the presence of Halomonas sp[J]. Applied Microbiology and Biotechnology, 2016, 100(3): 1421-1426.
    [17] EDGAR RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads[J]. Nature Methods, 2013, 10(10): 996-998.
    [18] STACKEBRANDT E, GOEBEL BM. Taxonomic note: a place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology[J]. International Journal of Systematic and Evolutionary Microbiology, 1994, 44(4): 846-849.
    [19] STODDARD SF, SMITH BJ, HEIN R, ROLLER BRK, SCHMIDT TM. rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and Archaea and a new foundation for future development[J]. Nucleic Acids Research, 2015, 43(Database issue): D593-D598.
    [20] WANG Q, GARRITY GM, TIEDJE JM, COLE JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[J]. Applied and Environmental Microbiology, 2007, 73(16): 5261-5267.
    [21] DOUGLAS GM, MAFFEI VJ, ZANEVELD JR, YURGEL SN, BROWN JR, TAYLOR CM, HUTTENHOWER C, LANGILLE MGI. PICRUSt2 for prediction of metagenome functions[J]. Nature Biotechnology, 2020, 38(6): 685-688.
    [22] ZENG J, JIAO CC, ZHAO DY, XU HM, HUANG R, CAO XY, YU ZB, WU QL. Patterns and assembly processes of planktonic and sedimentary bacterial community differ along a trophic gradient in freshwater lakes[J]. Ecological Indicators, 2019, 106: 105491.
    [23] JIAO CC, ZHAO DY, ZENG J, GUO L, YU ZB. Disentangling the seasonal co-occurrence patterns and ecological stochasticity of planktonic and benthic bacterial communities within multiple lakes[J]. Science of the Total Environment, 2020, 740: 140010.
    [24] BARBERÁN A, BATES ST, CASAMAYOR EO, FIERER N. Using network analysis to explore co-occurrence patterns in soil microbial communities[J]. The ISME Journal, 2012, 6(2): 343-351.
    [25] YI YJ, LIN CQ, WANG WJ, SONG J. Habitat and seasonal variations in bacterial community structure and diversity in sediments of a Shallow lake[J]. Ecological Indicators, 2021, 120: 106959.
    [26] XIAO GF, CHENG XJ, ZHU DT, LI ZF, FENG LJ, PENG XM, LU ZY, XIE J. Exploring the mechanism of a novel recirculating aquaculture system based on water quality parameters and bacterial communities[J]. Environmental Science and Pollution Research International, 2023, 30(12): 34760-34774.
    [27] 程豹, 望雪, 徐雅倩, 杨正健, 刘德富, 马骏. 澜沧江流域浮游细菌群落结构特征及驱动因子分析[J]. 环境科学, 2018, 39(8): 3649-3659. CHENG B, WANG X, XU YQ, YANG ZJ, LIU DF, MA J. Bacterioplankton community structure in the Lancang River Basin and the analysis of its driving environmental factors[J]. Environmental Science, 2018, 39(8): 3649-3659(in Chinese).
    [28] KIRCHMAN DL, COTTREL MT, DiTULLIO GR. Shaping of bacterial community composition and diversity by phytoplankton and salinity in the Delaware Estuary, USA[J]. Aquatic Microbial Ecology, 2017, 78(2): 93-106.
    [29] CAMPBELL BJ, KIRCHMAN DL. Bacterial diversity, community structure and potential growth rates along an estuarine salinity gradient[J]. The ISME Journal, 2013, 7(1): 210-220.
    [30] LU J, ZHANG YX, WU J, WANG JH. Nitrogen removal in recirculating aquaculture water with high dissolved oxygen conditions using the simultaneous partial nitrification, anammox and denitrification system[J]. Bioresource Technology, 2020, 305: 123037.
    [31] LIU WS, QIU KY, XIE YZ, HUANG YY, WANG RX, LI HC, MENG WF, HE Y, LI YY, LI HQ, ZHAO PB, YANG Y. High-throughput absolute quantification sequencing reveals that a combination of leguminous shrubs is effective in driving soil bacterial diversity during the process of desertification reversal[J]. Microbial Ecology, 2023, 86(2): 1145-1163.
    [32] JIANG SQ, YU YN, GAO RW, WANG H, ZHANG J, LI R, LONG XH, SHEN QR, CHEN W, CAI F. High-throughput absolute quantification sequencing reveals the effect of different fertilizer applications on bacterial community in a tomato cultivated coastal saline soil[J]. Science of the Total Environment, 2019, 687: 601-609.
    [33] 浦滇, 石明, 周雪孟, 张仲富, 蓝增全. 基于高通量绝对定量对不同树龄茶树土壤细菌群落多样性的研究[J]. 西南农业学报, 2022, 35(1): 186-193. PU D, SHI M, ZHOU XM, ZHANG ZF, LAN ZQ. Soil bacterial community diversity of tea plants with different ages based on high-throughput absolute quantification[J]. Southwest China Journal of Agricultural Sciences, 2022, 35(1): 186-193(in Chinese).
    [34] HAN Y, ZHANG M, CHEN XF, ZHAI WD, TAN EH, TANG K. Transcriptomic evidences for microbial carbon and nitrogen cycles in the deoxygenated seawaters of Bohai Sea[J]. Environment International, 2022, 158: 106889.
    [35] 薛银刚, 蒋聪, 耿金菊, 谢文理, 张皓, 陈心一. 基于qPCR和16S rDNA高通量测序研究蓝藻暴发期间太湖竺山湾水体浮游细菌群落[J]. 环境监控与预警, 2017, 9(3): 19-23. XUE YG, JIANG C, GENG JJ, XIE WL, ZHANG H, CHEN XY. Profiles of bacterioplankton based on qPCR and 16S rDNA high-throughput sequencing during a heavy cyanobacterial bloom in Zhushan bay, Taihu lake[J]. Environmental Monitoring and Forewarning, 2017, 9(3): 19-23(in Chinese).
    [36] YANG ZB, WANG J, SHANG CC, YANG SM, HAO Y, TANG XX, XIAO H. Spatial and temporal changes in bacterial community structure in adjacent waters of Dagu River estuary of Jiaozhou Bay (China) revealed by high-throughput sequencing[J]. Regional Studies in Marine Science, 2022, 52: 102302.
    [37] 杨勇, 李昆太. 放线菌资源及其活性物质研究概述[J]. 生物灾害科学, 2019, 42(1): 7-14. YANG Y, LI KT. The overview of actinomycetes resources and its active substances[J]. Biological Disaster Science, 2019, 42(1): 7-14(in Chinese).
    [38] 杨阳, 李海亮, 马凯丽, 汪钰欣, 牛世全. 放线菌及其代谢产物研究进展: 基于CiteSpace可视化分析[J]. 微生物学报, 2022, 62(10): 3825-3843. YANG Y, LI HL, MA KL, WANG YX, NIU SQ. Actinomycetes and their metabolites: visual analysis based on CiteSpace[J]. Acta Microbiologica Sinica, 2022, 62(10): 3825-3843(in Chinese).
    [39] 彭飞, 周彦锋, 王晨赫, 张希昭, 罗宇婷, 唐雪梅, 周依帆, 王东伟. 2019年春季淮河中下游水体微生物的空间异质性[J]. 大连海洋大学学报, 2022, 37(5): 830-840. PENG F, ZHOU YF, WANG CH, ZHANG XZ, LUO YT, TANG XM, ZHOU YF, WANG DW. Spatial differences in water microorganisms in middle and lower reaches of the Huaihe River in spring 2019[J]. Journal of Dalian Ocean University, 2022, 37(5): 830-840(in Chinese).
    [40] ZHANG Q, ZHANG ZY, LU T, YU YT, PENUELAS J, ZHU YG, QIAN HF. Gammaproteobacteria, a core taxon in the guts of soil fauna, are potential responders to environmental concentrations of soil pollutants[J]. Microbiome, 2021, 9(1): 196.
    [41] 杨艳, 王浩, 李凯航, 李贝贝, 张琦, 王子权, 金一, 何晓青. 长江三峡上游水域细菌群落结构与功能预测[J]. 微生物学报, 2022, 62(4): 1401-1415. YANG Y, WANG H, LI KH, LI BB, ZHANG Q, WANG ZQ, JIN Y, HE XQ. Community structure and function predication of bacterial communities in the upper reaches of the Three Gorges of the Yangtze River[J]. Acta Microbiologica Sinica, 2022, 62(4): 1401-1415(in Chinese).
    [42] 迪拉热·海米提, 樊永红, 王伟楠, 喻文丽, 艾海白尔·卡斯木. 盐穗木叶片及根际土壤微生物群落高通量分析[J]. 新疆农业科学, 2021, 58(4): 731-740. DILARE HAIMITI, FAN YH, WANG WN, YU WL, AIHAIBAIER KASIMU. Analysis of microbial communities in leaves and rhizosphere soil of Halostachys capsica by high-throughput sequencing[J]. Xinjiang Agricultural Sciences, 2021, 58(4): 731-740(in Chinese).
    [43] 顾颖, 伏光辉, 姚永琪, 梁宝贵, 叶仁智, 王超, 卢璐, 孙苗苗. 海州湾细菌群落结构多样性及环境因子分析[J]. 生命科学研究, 2023, 27(6): 512-520, 527. GU Y, FU GH, YAO YQ, LIANG BG, YE RZ, WANG C, LU L, SUN MM. Diversity of bacterial community structure and environmental factors in Haizhou bay[J]. Life Science Research, 2023, 27(6): 512-520, 527(in Chinese).
    [44] 梁川, 周利, 邓洁, 俞姗姗, 杨艳芳, 陈勤凤, 张平究. 渔业养殖对水体和沉积物细菌群落结构及分子生态网络特征的影响[J]. 环境科学学报, 2024, 44(5): 228-242. LIANG C, ZHOU L, DENG J, YU SS, YANG YF, CHEN QF, ZHANG PJ. Effects of fish farming on bacterial community structure and molecular ecological network in water and sediment[J]. Acta Scientiae Circumstantiae, 2024, 44(5): 228-242(in Chinese).
    [45] MA J, LU YQ, CHEN F, LI XX, XIAO D, WANG H. Molecular ecological network complexity drives stand resilience of soil bacteria to mining disturbances among typical damaged ecosystems in China[J]. Microorganisms, 2020, 8(3): 433.
    [46] YUAN MM, GUO X, WU LW, ZHANG Y, XIAO NJ, NING DL, SHI Z, ZHOU XS, WU LY, YANG YF, TIEDJE JM, ZHOU JZ. Climate warming enhances microbial network complexity and stability[J]. Nature Climate Change, 2021, 11: 343-348.
    [47] WU BB, WANG P, DEVLIN AT, CHEN L, XIA Y, ZHANG H, NIE MH, DING MJ. Spatial and temporal distribution of bacterioplankton molecular ecological networks in the Yuan River under different human activity intensity[J]. Microorganisms, 2021, 9(7): 1532.
    [48] ZENG J, LIN YQ, ZHAO DY, HUANG R, XU HM, JIAO CC. Seasonality overwhelms aquacultural activity in determining the composition and assembly of the bacterial community in Lake Taihu, China[J]. Science of the Total Environment, 2019, 683: 427-435.
    [49] TAO MM, LI WB, ZHOU XH, LI YN, SONG HY, WU F. Effects of microplastics on the structure and function of bacterial communities in sediments of a freshwater lake[J]. Chemosphere, 2024, 356: 141880.
    [50] HUANG Y, ZHAO YR, WANG J, ZHANG MJ, JIA WQ, QIN X. LDPE microplastic films alter microbial community composition and enzymatic activities in soil[J]. Environmental Pollution, 2019, 254: 112983.
    [51] CHANG CN, MA YS, LO CW. Application of oxidation–reduction potential as a controlling parameter in waste activated sludge hydrolysis[J]. Chemical Engineering Journal, 2002, 90(3): 273-281.
    [52] MEI Y, LU Y, YE ZP, XU DM, PAN H, WANG JD. Impacts of operating parameters on oxidation- reduction potential and COD removal during the electrochemical removal of 2-chlorophenol[J]. Desalination and Water Treatment, 2019, 140: 199-206.
    [53] OUYANG L, CHEN HR, LIU XY, WONG MH, XU FF, YANG XW, XU W, ZENG QH, WANG WM, LI SF. Characteristics of spatial and seasonal bacterial community structures in a river under anthropogenic disturbances[J]. Environmental Pollution, 2020, 264: 114818.
    相似文献
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

鲍文秀,陈明,张闻,汤佳豪,李瑜婷,古鹏,卢媛. 基于16S rRNA基因高通量绝对定量解析黄河入海口淡水与海水水体细菌群落特征[J]. 微生物学报, 2024, 64(11): 4338-4357

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2024-06-01
  • 在线发布日期: 2024-10-30
  • 出版日期: 2024-11-04
文章二维码