微生物学报  2021, Vol. 61 Issue (6): 1474-1487   DOI: 10.13343/j.cnki.wsxb.20200791.
http://dx.doi.org/10.13343/j.cnki.wsxb.20200791
中国科学院微生物研究所,中国微生物学会,中国菌物学会
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文章信息

王鹏, 吴莹, 刘素美, 王晓娜, 戴金龙, 叶祁. 2021
Wang Peng, Wu Ying, Liu Sumei, Wang Xiaona, Dai Jinlong, Ye Qi. 2021
长江口外低氧区及其邻近海域表层沉积物反硝化微生物多样性和分布特征
Diversity and distribution of denitrifying microorganisms in the surface sediments of the hypoxic zone near the Changjiang Estuary and its offshore
微生物学报, 61(6): 1474-1487
Acta Microbiologica Sinica, 61(6): 1474-1487

文章历史

收稿日期:2020-12-24
修回日期:2021-03-12
网络出版日期:2021-03-26
长江口外低氧区及其邻近海域表层沉积物反硝化微生物多样性和分布特征
王鹏1 , 吴莹1 , 刘素美2,3 , 王晓娜1 , 戴金龙1 , 叶祁1     
1. 华东师范大学河口海岸学国家重点实验室, 上海 200241;
2. 中国海洋大学海洋化学理论与工程技术教育部重点实验室, 山东 青岛 266100;
3. 青岛海洋科学与技术试点国家实验室, 海洋生态与环境科学功能实验室, 山东 青岛 266237
摘要[目的] 微生物参与的反硝化是河口区氮损失的主要途径。[方法] 本研究采用Illumina MiSeq测序方法,研究了长江口外低氧区及其邻近海域表层沉积物中nirS型和nirK型反硝化微生物群落的多样性和分布特征。[结果] 样品共检测到346个nirS Operational Taxonomic Units和267个nirK Operational Taxonomic Units,根据采样地的环境特征及nirS型和nirK型反硝化微生物群落聚类分析结果将所有Operational Taxonomic Units划分为低氧区、南部区域及外部深水区,其中外部深水区的样品nirS功能基因的多样性最高。各实验样地优势Operational Taxonomic Units在系统进化关系上可分为多个不同的簇。此次发现的所有优势Operational Taxonomic Units均属于未被培养的菌群,其中部分Operational Taxonomic Units还是首次被发现。此外还发现nirS功能基因对低氧区的环境适应性更好。[结论] 我们的研究结果表明广泛存在的反硝化微生物在河口沉积物的氮循环中发挥重要作用。
关键词长江口    低氧区    nirS    nirK    
Diversity and distribution of denitrifying microorganisms in the surface sediments of the hypoxic zone near the Changjiang Estuary and its offshore
Wang Peng1 , Wu Ying1 , Liu Sumei2,3 , Wang Xiaona1 , Dai Jinlong1 , Ye Qi1     
1. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China;
2. The Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao 266100, Shandong Province, China;
3. Laboratory of Marine Ecology and Environmental Science, Pilot National Laboratory for Marine Science and Technology(Qingdao), Qingdao 266237, Shandong Province, China
Abstract: [Objective] Microbial denitrification is the essential process to transform nitrate into nitrogen gas in estuarine environment. [Methods] In the present study, we investigated the diversity and distribution of the nirS-type and nirK-type denitrifying microbial communities in the surface sediments of the hypoxic zone near the Changjiang Estuary and in the East China Sea by Illumina MiSeq sequencing approach. [Results] A total of 346 nirS-type and 267 nirK-type Operational Taxonomic Units were detected. Environmental characteristics of sampling site and cluster analysis of nirS and nirK divided all Operational Taxonomic Units into hypoxic, southern and deep-water groups, and the samples from the deep-water group had the highest diversity of nirS functional genes. Furthermore, the dominant Operational Taxonomic Units phylogenetically formed several clusters, representing by Operational Taxonomic Units from distinct groups. All the dominant Operational Taxonomic Units were uncultured and some of them were first retrieved. Likewise, nirS gene was more adaptable to the hypoxic condition. [Conclusion] Our results indicate that widespread denitrifying microorganisms play a critical role in nitrogen cycle in the estuarine sediments.
Keywords: Changjiang Estuary    hypoxic zone    nirS    nirK    

河口区氮循环主要包括固氮、硝化、反硝化、厌氧氨氧化及硝酸盐异化还原成铵(Dissimilatory nitrate reduction to ammonium,DNRA)等过程[1]。这些循环主要是由微生物推动的,反硝化作为氮循环的途径之一是河口氮损失的主要途径。反硝化过程既可以用于支持某些微生物的呼吸[2-3],也可缓解河口富营养化程度,因此研究微生物参与的反硝化对河口环境具有重要意义[4-5]。微生物体内编码与反硝化作用相关的关键酶的基因称之为功能基因[6]。反硝化作用最常见的功能基因是编码异化亚硝酸盐还原酶的基因nirS (编码细胞色素- cd1酶)和nirK (编码含铜酶),它是将NO2-催化转化为气态产物的第一步,即亚硝酸盐(NO2-)转化为一氧化氮(NO)。这两种基因有不同的进化史,但执行着相同的功能[7],这两种功能基因是区分反硝化和其他硝酸盐还原过程的关键步骤[8]。对功能基因的检测可以帮助我们更直观、深入地了解参与生物地球化学循环的微生物的群落结构及其影响因素。

长江是世界第三长河,每年流经河口地区向东海输送大量的氮营养盐[9]。近几十年来,随着长江流域人口激增和工农业的迅猛发展,由渔业、农业生产、工业和生活废水排污等人文活动造成水生态系统中的氮污染已成为了长江口及邻近海域严重的环境问题[10]。2000-2017年,长江口淡水端溶解无机氮(Dissolved inorganic nitrogen,DIN)浓度在110-143 μmol/L (125±11 μmol/L)波动;溶解无机磷(Dissolved inorganic phosphorus,DIP)浓度在1.09-1.75 μmol/L变化,近10年波动较小[11],N/P值已高达100,含氮营养盐已显著过量。比如每年春夏季,过量的营养盐导致长江口地区的富营养化,进而引起藻华和低氧的发生[12-13]。由微生物介导的氮清除过程是目前近海氮循环的研究热点,在以往对长江口反硝化微生物的研究中,nirS功能基因在沉积物和水体中的群落结构、分布和其环境影响因素已被报道[14-15]。基于长江口到东海海域反硝化nosZ功能基因的菌群组成和分布分析,通过qPCR对反硝化和厌氧氨氧化微生物丰度进行比较,发现反硝化是河口地区的主要氮清除过程,随着营养盐和有机物浓度的降低,厌氧氨氧化在开阔海洋海域更为重要[16]

水体中溶解氧(Dissolved oxygen,DO)对海洋生态系统非常重要[17]。溶解氧值低于2 mg/L的水体通常称为低氧水体[18]。目前长江口已成为世界低氧海域的一个典型区域,而富营养化是引起长江口外低氧事件频发的重要原因[19]。自20世纪50年代以来,一系列研究记录了长江口低氧现象的发生[12, 20-23],低氧区的位置每年存在差异[24]。长江口外低氧区中心位于123°E 31°N附近,近年来有北移的趋势[12]。2013年夏季在长江口外发现3个低氧亚区,部分区域是新观测到的[23]。微生物对溶解氧的消耗在低氧和缺氧的发展形成中起着重要作用,比如,应用Illumina MiSeq测序平台对2013年8月正在发生低氧的长江口外低氧区和邻近海域表层沉积物16S rRNA V4-V5高可变区高通量测序,发现在严重层化的区域中,好氧拟杆菌和浮霉菌降解有机物并消耗大量氧气的过程是造成低氧区的原因之一[23]

在低氧条件下,以硝酸盐为电子受体的反硝化过程是沉积物的重要氮去除途径[3, 25]。目前对长江口外低氧区和邻近海域微生物生态研究主要集中在细菌和古菌多样性分析[23, 26-27],但是缺乏针对反硝化微生物菌群结构和分布特征的研究。为此,本研究选取长江口夏季的低氧区及其邻近海域的表层沉积物样品,对其中的反硝化功能基因nirSnirK进行高通量测序,探究:(1) 两种功能基因的群落结构差异,(2) 两种功能基因群落分布特征。研究结果将丰富对长江口外低氧区nirSnirK功能基因的多样性及其分布特征的认识。

1 材料和方法 1.1 样品采集、前处理及保存

2013年8月,在R/V东方红2号上使用箱式采泥器采集了7个站位的表层沉积物(0-3 cm)进行反硝化功能基因的测序分析,沉积物样品在船上以-20 ℃的温度冷冻保存,并使用冰盒运输至实验室,在实验室以-80 ℃的温度冷冻保存直至提取DNA。底层海水样品由Niskin采样器采集,底层水中溶解有机碳(Dissolved organic carbon,DOC)样品在采集后立即用0.45 μm的尼龙滤头过滤、底层水NO3-样品在采集后立即用0.4 μm的聚碳酸酯膜过滤,均放置在-20 ℃冷冻保存直至分析。

1.2 样品数据获取

温度和盐度等数据使用CTD (Sea-Bird 11plus,Sea-Bird Electronics,Bellevue,WS,USA)获取;DO数据由溶氧仪测得,并使用Winkler的方法进行校正;实验室使用TOC分析仪(Shimadzu TOC-L CPH,Japan)测量DOC样品;称取5 g左右未研磨沉积物进行粒度分析,通过激光粒度仪(LS-100Q)测试得到数据,NO3-样品采用德国Seal Analytical生产的AH_A3型连续流动分析仪测定,使用Cd-Cu还原法和重氮偶氮法,550 nm波长测定[28]

1.3 沉积物总DNA提取、PCR和Illumina MiSeq测序

使用MoBio PowerSoil (MOBIO Laboratories,Carlsbad,CA,USA)试剂盒,每个样品称取0.5-1.0 g沉积物,按说明书提取沉积物总DNA,用NanoDrop ND2000 (Thermo Fisher Scientific, Wilmington,DE,USA)分光光度法测定其浓度和纯度,利用1%琼脂糖凝胶电泳检测DNA提取质量于-80 ℃冷冻保存。样品总DNA由上海美吉生物公司应用Illumina MiSeq测序仪对nirSnirK基因进行测序,采用引物cd3aF (5′-GTS AACGTSAAGGARACSGG-3′)和R3cd (5′-GASTT CGGRTGSGTCTTGA-3′)对nirS基因进行扩增[29],采用引物nirK1aCu (5′-ATCATGGTSCTGCCGCG-3′)和nirKR3Cu (5′-GCCTCGATCAG(A/G)TTGTG GTT-3′)对nirK基因进行扩增[30]。20 μL的反应体系包含:使用ABI GeneAmp 9700 PCR System一式三份进行PCR扩增,总体积为20 μL PCR反应混合物,其中包含5×FastPfu缓冲液(4 μL)、2.5 mmol/L dNTPs (2 μL)、5 μmol/L正向引物(0.8 μL)、5 μmol/L反向引物(0.8 μL)、FastPfu聚合酶(0.4 μL)、BSA (0.2 μL)、模板DNA (2 μL)、灭菌超纯水(9.8 μL);10×缓冲液(2 μL)、2.5 mmol/L dNTPs (2 μL)、5 μmol/L正向引物(0.8 μL)、5 μmol/L反向引物(0.8 μL)、rTaq聚合酶(0.2 μL)、BSA (0.2 μL)、模板DNA (10 ng)、灭菌超纯水(14 μL)。在95 ℃下进行3 min的热循环(nirSnirK),在95 ℃下进行40个循环,持续0.5 min,在55 ℃下进行0.5 min,在72 ℃下进行1 min,最后延伸到72 ℃下进行10 min通过凝胶电泳和纯化鉴定所有PCR产物[31]

原始测序序列使用Trimmomatic软件质控,使用FLASH软件进行拼接:设置50 bp的窗口,如果窗口内的平均质量值低于20,从窗口前端位置截去该碱基后端所有序列,之后再去除质控后长度低于50 bp的序列;根据重叠碱基overlap将两端序列进行拼接,拼接时overlap之间的最大错配率为0.2,长度需大于10 bp。去除无法拼接的序列。根据序列首尾两端的barcode和引物将序列拆分至每个样本,barcode需精确匹配,引物允许2个碱基的错配,去除存在模糊碱基的序列。使用UPARSE软件(version 7.1 http://drive5.com/uparse/),根据88%的相似度对序列进行Operational Taxonomic Units (OTU)聚类[31],并在聚类的过程中去除单序列和嵌合体,使用FunGene Pipeline (http://fungene.cme.msu.edu/FunGenePipeline/)对每条序列进行物种分类注释[32],比对fgr/nirS和fgr/nirK数据库,设置比对阈值为70%。

1.4 数据分析

利用美吉生物云平台分析样品的Alpha多样性指数,包括Chao、Ace、Shannon和Coverage (www.majorbio.com)。使用QIIME软件生成加权的UniFrac距离进行层次聚类分析,并使用R语言进行绘图。选取样品中主要的OTU序列作为代表序列,将其与NCBI数据库中的同源氨基酸序列进行对比,将相似性最高的已知同源氨基酸序列选取为参考序列,导入MEGAX软件以邻接法绘制进化树。使用OriginPro 2019b绘制主要OTU相对丰度heatmap图。使用SPSS Statistics 17.0分析nirSnirK主要OTU与DO和DOC之间的相关性。

1.5 数据提交

基因序列提交至NCBI GenBank数据库,序列号为:PRJNA660324。

2 结果和分析 2.1 沉积物理化性质

根据采样站位水深、底层水的溶氧值、温度、盐度、DOC、硝酸盐浓度和沉积物粒径等理化性质以及其经纬度将样地分为3个区域。(1) 低氧区(Hypoxic area):位于长江口外,包括H_A2、H_A3、H_A5三个站位,其底层水的溶解氧值介于1.3- 1.5 mg/L。此区域水深较浅、温度较高、受冲淡水影响,盐度较低,DOC浓度较高,另外低氧区的沉积物平均粒径相对较大;(2) 南部区域(Southern area):位于低氧区南部,包括S_C3和S_E2两个站位,其溶解氧值分别为3.4 mg/L和4.7 mg/L,沉积物平均粒径很小。南部区域主要受台湾暖流影响,越靠近冲淡水区域,DO及温度与低氧区越接近;(3) 外部深水区(Deep water area):位于低氧区和南部区域东侧,靠近外海,包括D_A8和D_C10两个站位,其溶解氧值最高,分别为4.7 mg/L和4.8 mg/L,水深均大于100 m。7个研究的站位的硝酸盐浓度介于10.1至17.6 μmol/L之间(表 1)。

表 1. 采样站位的经纬度及理化性质 Table 1. Longitudes, latitudes and physicochemical characteristics of sampling stations
Sample ID GPS Location (E/N) Depth/m DO/(mg/L) T/℃ S/PSU Mean grain size/μm DOC/ (μmol/L) NO3-/ (μmol/L)
H_A2 122.64
31.66
32.0 1.5 21.0 33.4 159.1 49.0 16.8
H_A3 122.98
31.69
35.0 1.3 21.7 33.2 197.4 62.0 16.8
H_A5 124.25
31.94
38.0 1.4 21.3 31.8 104.8 82.0 13.0
S_C3 122.82
30.59
38.0 3.4 19.4 34.4 18.7 56.0 10.1
S_E2 122.09
28.05
58.0 4.7 17.7 34.4 13.2 51.0 12.0
D_A8 127.02
118.0 4.7 15.4 34.5 319.2 52.0 13.6
D_C10 126.84
215.0 4.8 12.2 34.4 81.1 40.0 17.6
DO: dissolved oxygen; S: salinity; DOC: dissolved organic carbon; NO3-: nitrate.

2.2 nirSnirK多样性指数分析

七个沉积物样本测序,按最小样本序列数抽平后共获得了72289条nirS有效序列,平均每个样本10327条;74284条nirK有效序列,平均每个样本10612条。在88%相似度下共获得346条nirS OTU及267条nirK OTU。其中H_A2有nirS OTU 98个,nirK OTU 79个;H_A3有nirS OTU 88个,nirK OTU 60个;H_A5有nirS OTU 112个,nirK OTU 64个;S_C3有nirS OTU 116个,nirK OTU 78个;S_E2有nirS OTU 150个,nirK OTU 126个;D_A8有nirS OTU 199个,nirK OTU 96个;D_C10有nirS OTU 202个,nirK OTU 79个。nirS基因在低氧区域的H_A2、H_A3、H_A5站位上,Chao指数和ACE指数(用于估算样本群落中所含OTU数目的指数,两指数越高均代表丰富度越高)在3个区域中最低;外部深水区的D_A8和D_C10则相反,Chao指数和ACE指数最高,Shannon指数(用于估算群落多样性的指数,Shannon值越大,说明群落多样性越高)也最高。nirK基因在低氧区域H_A3、H_A5和nirS具有相似的趋势,但二者整体上也有区别,nirS基因Chao指数和ACE指数最高的站位为D_A8和D_C10,即外部深水区;nirK基因Chao指数和ACE指数最高的站位为S_C3和S_E2,即南部区域。这说明同为反硝化功能基因,但各自也存在生态位的不同分布(表 2)。

表 2. nirSnirK基因多样性指数 Table 2. Diversity indices of nirS gene and nirK gene
Sample ID Diversity indices of nirS gene Diversity indices of nirK gene
Observed OTUs Coverage/% Chao ACE Shannon Observed OTUs Coverage/% Chao ACE Shannon
H_A2 98 99.9 114.0 118.1 2.6 79 99.8 115.6 112.1 2.0
H_A3 88 99.9 136.5 120.6 2.6 60 99.9 68.7 69.5 1.4
H_A5 112 99.8 133.1 131.4 3.1 64 99.9 75.6 79.5 1.4
S_C3 116 99.9 142.0 149.2 2.6 78 99.9 122.1 111.8 1.8
S_E2 150 99.8 183.6 184.5 3.1 126 99.9 132.2 134.1 2.8
D_A8 199 99.9 208.5 208.0 4.2 96 99.9 98.2 99.6 2.5
D_C10 202 99.8 219.8 221.5 3.9 79 99.9 84.6 83.6 2.5

2.3 nirSnirK的聚类分析

通过聚类分析结果可以看出,nirS功能基因有明显的3个大分支分别对应低氧区、南部区域及外部深水区,nirK功能基因整体可分为两大支,在低氧区和外部深水区具有较好的区分度,南部区域较为接近低氧区但也可区分(图 1)。样品的OTU分布与样地划分有较好的一致性。

图 1 nirSnirK功能基因聚类分析图 Figure 1 Hierarchical clustering trees of nirS and nirK on the OTU level. A: hierarchical clustering tree of nirS; B: hierarchical clustering tree of nirK.

2.4 nirSnirK的群落结构及其相对丰度

由于对所有OTU分析不易发现其主要特征,而其优势OTU受到的干扰则较小,因此对其主要

OTU相对丰度(每个站位相对丰度处于前三位的OTU,nirS平均覆盖范围超过55%,nirK平均覆盖范围超过80%)进行分析更能体现该区域的分布特征(图 2)。由图 2可以看出,nirS功能基因相对丰度在3个区域均有着明显不同,外部深水区优势OTU相对丰度最低,区域内部则较为相似;nirK功能基因在S_C3站位与低氧区域较为相似,这一点在图 1中也能体现出来,低氧区域(H_A2、H_A3、H_A5)与外部深水区(D_A8、D_C10)区别较大。nirS功能基因主要OTU相对丰度比nirK要低,OTU分布更为分散,在低氧区优势更明显。

图 2 nirSnirK功能基因主要OTU比例 Figure 2 Proportions of nirS and nirK main OTUs. A: proportion of nirS main OTUs; B: proportion of nirK main OTUs.

在区域水平上,中国长江口低氧区和外部深水区表层沉积物中优势OTU差别很大(图 2),OTU144 S (2.9%-7.7%)、OTU41 S (4.3%-16.0%)、OTU100 K (11.7%-16%)、OTU97 K (19.0%-19.2%)在外部深水区相对丰度较高,而在低氧区很少甚至没有;OTU349 S (8.1%-20.7%)、OTU320 S (12.6%-18.9%)、OTU14 S (6.7%-15.0%)、OTU24 K (3.4%-15.2%)、OTU15 K (44.9%-68.7%)在低氧区相对丰度较高,而在外部深水区很少甚至没有。

基于两种功能基因的主要OTU编码氨基酸序列的系统发育分析,发现nirS型OTU272 S和OTU31 S及nirK型OTU95 K与NCBI数据库中已知序列的同源性较低,其相似度均小于88%,这3个为本研究新检测到的反硝化细菌。根据其进化关系,nirS整体可分为2个簇,Cluster S1:Cluster S1A包含低氧区和南部区域主要OTU (相对丰度在该区域处于前三或所有区域中相对丰度最高)、Cluster S1B为外部深水区主要OTU、Cluster S1C为外部深水区主要OTU、Cluster S1D包含低氧区和南部区域主要OTU;Cluster S2:Cluster S2A为低氧区主要OTU、Cluster S2B包含低氧区和南部区域主要OTU。nirK整体可分为3个簇,Cluster K1:Cluster K1A为外部深水区主要OTU、Cluster K1B为低氧区主要OTU;Cluster K2:Cluster K2A为外部深水区主要OTU、Cluster K2B包含低氧区和南部区域主要OTU;Cluster K3:Cluster K3包含低氧区、南部区域和外部深水区主要OTU (图 2图 3)。

图 3 nirSnirK功能基因编码的氨基酸序列系统发育树 Figure 3 Neighbor-joining phylogenic trees constructed by amino acid sequences translated from the nirS and Ralstouia eutropha nirK genes. A: neighbor-joining phylogenic tree constructed by amino acid sequences translated from the nirS gene; B: neighbor-joining phylogenic tree constructed by amino acid sequences translated from the nirK gene. Phylogenic trees showing the phylogenetic relationships of the deduced nirS and nirK protein sequences translated from the clone sequences of the nirS and nirK genes obtained in this study and their closely related sequences from the GenBank database; the numbers following OTUs represent different OTUs; GenBank accession numbers are shown in the brackets; the scale bar indicates the expected number of change per homologous position; bootstrap values of (1000 replicates) > 50% are shown; the SoxB amino acid sequence from Thioalkalivibrio versutus was used as outgroup for nirS; the nirK amino acid sequence from Nitrosospira multiformis was used as outgroup for nirK.

在本研究区域,除新发现的OTU外,优势OTU所代表的nirSnirK功能基因氨基酸序列相似性为97%-100%,全部来自于细菌,样品分布广泛,在中国长江口、黄海、黄河口、象山、闽江和南海等区域及墨西哥湾和美国旧金山湾,该类功能基因OTU均有发现;在不同样品类型(如水样,OTU15 K)中也有发现(表 3)。

表 3. nirSnirK功能基因主要OTU和其在NCBI比对到的最近序列列表 Table 3. The main OTUs and their closest relatives retrieved from NCBI GenBank of nirS and nirK genes
OTU ID Closest relative Accession number Identity/% Sample source Taxonomy Reference
nirS OTU280 S S33b-29 MF421059 100.0 Changjiang Estuary, China D-bacteria NCBI
OTU320 S S-P6-6 KU995595 100.0 Coastal Wetlands, China D-bacteria [33]
OTU41 S nirS-704-C9_Meng1 HQ666726 100.0 South China Sea, China D-bacteria NCBI
OTU144 S S33b-11 MF421073 100.0 Changjiang Estuary, China D-bacteria NCBI
OTU256 S nirS-Summer WSK38_475|1 KM892216 100.0 Changjiang Estuary, China P-proteobacteria [15]
OTU278 S nirS-Winter LC81_389|3 KM892131 100.0 Changjiang Estuary, China D-bacteria [15]
OTU14 S J5_62 JX941943 100.0 Minjiang, China D-bacteria NCBI
OTU13 S J5_40 JX941923 100.0 Minjiang, China P-proteobacteria NCBI
OTU349 S mx7nir_g07 DQ451281 100.0 Gulf of Mexico C-betaproteobacteria [25]
nirK
OTU100 K SF04-BF21-B07 GQ454176 98.0 San Francisco Bay, USA D-bacteria [34]
OTU97 K ECS01_16 KP750758 98.0 Huanghai Sea and Donghai Sea, China P-proteobacteria NCBI
OTU177 K ECS03_2 KP750732 100.0 Huanghai Sea and Donghai Sea, China P-proteobacteria NCBI
OTU26 K ECS03_8 KP750736 100.0 Huanghai Sea and Donghai Sea, China P-proteobacteria NCBI
OTU15 K YRE-KC29 KF143995 100.0 Yellow River Estuary, China D-bacteria [35]
OTU220 K ECS01_28 KP750766 100.0 Huanghai Sea and Donghai Sea, China D-bacteria NCBI
OTU187 K SYS01_10 KP750698 99.0 Huanghai Sea and Donghai Sea, China D-bacteria NCBI
OTU24 K bXSB33 KX510718 97.0 Xiangshan Landfill, China D-bacteria NCBI
These OTUs were selected within the top three abundant reads from a single sample and/or from multiple samples. D: domain; P: phylum; C: class.

2.5 氮、碳循环功能耦合

氮循环与碳循环之间往往存在耦合关系,部分执行反硝化功能的微生物可以进行自养[36]。为此分析了nirSnirK优势OTU与DO和DOC之间的相关性,探究本研究区域内反硝化与碳循环之间的功能耦合(表 4)。两种功能基因基本反映出一个相同的趋势,即OTU与DO的相关性和OTU与DOC的相关性相反。比如nirS OTU14 S、OTU320 S、OTU349 S和nirK OTU15 K、OTU24 K与DO值呈显著负相关,与DOC含量呈正相关,暗示其可能具有自养功能。其中nirS OTU349 S是低氧区站位最优势的菌群,在H_A3和H_A5站位分别达到了20.7%和16.2%;nirKOTU15 K是低氧区站位最优势的菌群,在H_A2、H_A3和H_A5站位分别达到了44.9%、65.0%和68.7%,说明在低氧区沉积物中微生物的反硝化可能是新有机物的重要来源。

表 4. nirSnirK主要OTU与DO和DOC之间的相关性 Table 4. The correlations of dominant OTUs for nirS and nirK genes with DOC and DO concentrations
OTU ID nirS Pearson correlation OTU ID nirK Pearson correlation
DO/(mg/L) DOC/(μmol/L) DO/(mg/L) DOC/(μmol/L)
OTU278 S -0.09 -0.12 OTU15 K -0.90** 0.73
OTU14 S -0.88** 0.25 OTU24 K -0.81* 0.12
OTU320 S -0.97** 0.61 OTU177 K -0.59 -0.07
OTU349 S -0.85* 0.64 OTU26 K 0.24 -0.17
OTU13 S -0.67 0.29 OTU95 K 0.50 -0.39
OTU256 S -0.39 0.85* OTU97 K 0.66 -0.53
OTU41 S 0.66 -0.62 OTU100 K 0.76* -0.63
OTU272 S 0.79* -0.65 OTU220 K 0.24 -0.16
OTU144 S 0.62 -0.59 OTU187 K 0.45 -0.28
OTU280 S 0.12 0.15
OTU31 S -0.15 0.31
*: significant difference; P < 0.05; **: P < 0.01.

3 讨论

通常认为,如果物种之间的16S rRNA序列相似性<97%,即为不同物种[37]。由于在特定的进化压力下,编码不同蛋白质的基因会发生变异,97%的阈值并不完全适用于编码蛋白质的功能基因[31]。95%相似性常用于基于建立nirSnirK克隆库的反硝化微生物OTU聚类[38],随着第二代测序技术广泛应用于功能基因研究中,如何在精简OTU数目的情况下准确保留生态信息是分析高通量数据时面临的重要挑战。Bowen等[31]应用赤池信息量准则,即Akaike information criterion (AIC)对聚类nirS基因OTU不同临界值的网络结构复杂性进行评估,发现在盐沼沉积物的nirS型反硝化微生物多样性研究中,88%是既获得最精简OTU数目,又能捕捉生态系统复杂性的最佳OTU聚类阈值。Lee和Francis[7]分别用88%和95% OTU聚类阈值,比较了美国旧金山湾沉积物nirS型和nirK型反硝化微生物的alpha和beta多样性指数,发现两者区别不大。更重要的是,两种聚类阈值的分析并不影响反硝化微生物群落组成和环境因素的相关性分析结果。在本研究中,我们选用88%阈值对Miseq高通量测序获得的nirSnirK序列进行OTU聚类和后续分析。

三个区域中,低氧区主要受冲淡水影响携带了大量有机物,同时存在上升流带来的营养盐和富营养化导致藻华频发产生大量海源有机物,异养微生物在利用有机物的过程中消耗大量的溶解氧,而夏季长江口水体分层阻碍了表底层水的溶解氧的交换,当耗氧超过补给时,形成低氧[12, 23-24];南部区域主要受中国台湾暖流影响,盐度和DO更高,其与低氧区都受沿岸影响较大但又有所差别[39];外部深水区远离中国长江口,水深最深、盐度和DO最高。由于三个区域受影响因素存在较大差异,因而也对功能基因的分布产生了不同的影响。nirS基因在低氧区域的Chao指数和ACE指数低于其余区域较明显,且三站位指数接近,OTU数目也最少,可能适应低氧区生活的物种较少,致使nirS基因多样性指数较低,但优势物种更明显。外部深水区则相反,Chao指数和ACE指数高,Shannon指数也高于其他区域,证明外部深水区域中nirS基因多样性较高。nirK基因在部分站位(H_A3、H_A5等)和nirS具有相似的趋势,可能原因为二者同为反硝化功能基因,受到环境影响相似,但二者也有区别(D_A8、D_C10等),可能是因为两种功能基因所对应的OTU有各自的生态位分布。

在低氧区和非低氧区,OTU相对丰度差别较大,由于外部深水区DO含量最高,与其他区域差别尤为显著,结合图 2对比,外部深水区主要OTU相对丰度之和在nirS中均不足40%,在D_A8站位不足20%,低氧区主要OTU相对丰度之和接近其2倍,具有很大差别;在nirK中外部深水区主要OTU相对丰度之和略低于低氧区域,可能是因为nirK在环境中分布更广泛的缘故。图 2可以看出各区域主要OTU的相对丰度与所有站位主要OTU相对丰度分布有较大差异,因此推断造成该差异的主要原因很可能是因为环境不同造成物种的不同,在阿拉伯海东南部季节性缺氧区的研究中也得到了类似的结果[3]。根据NCBI对比分析发现,虽然我们采集地在中国长江口,但在中国黄海、黄河口、象山、闽江和南海等区域及墨西哥湾、美国旧金山湾,该类功能基因OTU均有发现[15, 25, 33-35],这些功能基因广泛存在于各个位置,又有未知序列,这对未来研究是一个机会也是挑战,其很可能参与了其他生物地化过程(硫氧化、碳固定等)。在图 3的Cluster K3中,三个区域优势OTU均聚集在了一起,且有未知的新序列,它们之间的亲缘关系或值得进一步研究。

通过对nirSnirK优势OTU与DO和DOC之间的相关性分析,发现低氧区沉积物反硝化微生物可能通过自养过程向底层水释放新的有机物,是除了陆源有机物和富营养化引起的初级生产产生的海源有机物外另一类重要的可利用有机物。化能自养微生物的暗碳固定可以通过现场生产的有机物质支撑食物网而不受光合作用的影响[40]。在前期研究中发现在低氧区沉积物样品中,有约5.9%的序列与瓦登海沉积物中未被培养的Gamma-变形菌纲的硫氧化自养菌16S rRNA序列相似[23, 41],这类未被培养的Gamma-变形菌属于新命名的Woeseiaceae/JTB255科,参与二氧化碳固定、硫氧化、不完全反硝化等代谢途径[42],因其多样性的代谢功能使之有很强的环境适应能力,在全球沉积物中广泛存在[43]。本研究为进一步研究低氧区未被培养的反硝化微生物在碳、氮、硫的耦合过程提供了新的证据。一般认为在DO含量低时会有利于反硝化,但多样性指数分析显示在非低氧区域反硝化物种更为丰富,原因可能为这两种功能基因对应的物种在氧含量低的区域与执行其他地化过程(如厌氧氨氧化、DNRA等)的物种竞争了反应底物[4, 16, 44]。此外,有研究表明,nirK功能基因比nirS有更广泛的栖息地[45-46],其系统发育分析中的地域差异不如nirS显著,也体现了其分布相比nirS更广泛,其选择性或将更强。两种功能基因在低氧区的分布均与DO呈现负相关,DO对nirS功能基因负相关影响更多,在低氧区nirS功能基因优势OTU分布更集中,或可表明nirS功能基因对低氧环境适应性更好。

4 结论

反硝化微生物在中国长江口外低氧区域及其邻近海域广泛存在,其中低氧区nirS功能基因适应性更强但微生物多样性低,可能存在其他地化过程(如厌氧氨氧化、DNRA等)的物种对反应底物的竞争。低氧区的反硝化微生物也很有可能同时执行着碳固定的功能。此项研究检测到的反硝化微生物多为未被培养的菌种,在未来的研究中,可以结合宏基因分箱和传统分离技术探究这些新型反硝化微生物在生物地球化学循环中的作用和环境效应。

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