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酸性矿山废水(AMD)是含硫的矿物在氧气和水共同作用下,经风化、淋溶和微生物共同作用而形成[1].酸性矿山废水具有 低pH 值,高电导率,硫酸盐和重金属浓度高的特点[2],这对大多数生物来说都是难以生存的极端环境[3-5],然而这种极端环境胁迫下的独特生境却孕育着大量的微生物。大部分酸性矿山废水未经处理便直接排放到自然环境中,该环境下的微生物可以反过来影响外界水环境,微生物与水体的密切联系使得酸性废水水体生态修复成为可能.贵州省煤矿矿山规模偏小,分布面广,导致废水排放分散、持久,对山区水环境的污染相当严重[6].因此研究酸性矿山废水影响下环境中微生物群落结构特征及其与环境因子的关系具有重要意义.
微生物在水生生态系统中起着重要作用,其中浮游细菌扮演着多重角色(分解者、转化者、储存者和生产者)[7],与自然界中的碳、氮、磷、硫和微量元素铁等循环关系密切[8],在自然环境的自净过程中占有重要地位,是控制水生生态过程的关键因子,微生物食物网的关键组成部分[9].目前,越来越多的研究开始关注水体中的浮游细菌及其与环境因子之间的关系.研究者在国内外对不同纬度、不同大小的湖、库水体细菌群落结构组成开展了大量的研究工作[10-15],但主要集中在中性或碱性水库,对酸性水库细菌群落结构组成的研究鲜见报道. 目前在国际上,美国、西班牙、英国和法国等几个国家对AMD微生物多样性的研究得最广泛、最深入,其中最典型的两个研究样地为美国的IronMountain和西班牙的Tinto River. 然而,这些研究主要是基于湖库或者河流单一水生态系统的浮游细菌群落的调查,而对湖库及流域细菌群落结构和多样性的系统性调查研究还较为不足.浮游细菌与环境因子之间的关系较为复杂, 但在高通量测序技术的支撑下,能更加真实地揭示原位环境中微生物群落的复杂性和多样性[16],该方法摆脱了传统分离培养方法不能完整反映生态系统全部信息的束缚,逐渐成为各类环境中微生物群落结构和多样性研究的常用手段.
基于此,本研究选取贵州省兴仁市受矿区污染的青树子和马家屯水库及其入库流域作为研究区域,该区属亚热带温和湿润季风气候区,年均降水量约为1400 mm,年均气温为22.1 ℃.青树子水库(E:105°13'53.1'',N:25°23'12.7'',H:1371.8 m)及其入库流域,马家屯水库(E:105°08′35.3″,N:25°22′36.3″,H:1434 m)及其入库流域,它们的空间距离相对较近,地质背景条件相对一致(图1),特别是有含煤地层(P3l)的出露.该地区目前有一定规模的煤矿开采活动,矿山排出的酸性废水使得流域及水库水体产生不同程度的酸化.从上游到下游再从水库表层至底层进行系统采样,从水平空间再到垂向空间,调查不同污染梯度水体中细菌群落多样性的差异,使用MiSeq测序技术分析16S rDNA的丰度和多样性,并结合水质理化因子分析和主成分分析(PCA)对引起细菌群落结构和多样性变化的主要胁迫因子进行甄别,探讨了酸性废水影响下水库及入库流域水体中细菌群落结构特征及其影响因素,拓展了对酸性矿山废水污染环境中细菌群落多样性的了解.
酸性矿山排水影响下水库及其入库流域水体细菌多样性与环境因子的关系
Relationship between bacterial diversity and environmental factors in reservoirs and their inflow basins under the influence of acid mine drainage
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摘要: 为了解酸性矿山废水排水处沿流域至水库底层水体细菌群落结构的沿程变化,探索其环境影响因素.采用高通量测序技术并结合主成分分析(principal component analysis,PCA)方法,对2019年9月采集受酸性矿山废水(acid mine drainage,AMD)影响的12个水样进行研究.结果表明,入库流域水样中细菌群落多样性变化趋势不明显,从表层至底层细菌多样性不断升高.在门水平上受AMD影响的细菌主要由变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes,0.21%—12.96%)、厚壁菌门(Firmicutes,0.15%—14.48%)和放线菌门(Actinobacteria,0.06%—4.64%)构成。其中,变形菌门中的α-变形菌纲(Alphaproteobacteria,2.42%—61.99%)、β-变形菌纲(Betaproteobacteria,1.29%—63.53%)和γ-变形菌纲(Gammaproteobacteria,6.41%—63.09%)为优势菌类.从不同空间位置浮游细菌群落组成来看,不动杆菌属(Acinetobacter)在受AMD影响流域上游至水库底层水样中均占较大比例,为2.13%—57.84%,假单胞菌属(Pseudomonas,3.86%—12.29%)、铁细菌属(Ferrovum,0.97%—13.21%)和拟杆菌属(Bacteroides,0.01%—5.02%)是上游水样中的优势菌属,噬氢菌属(Hydrogenophaga,0—5.94%)、盖氏铁柄杆菌属(Gallionella,1.45%—11.91%)和新鞘氨醇杆菌(Novosphingobium,0—5.34%)是中游占比较大的菌属,红细菌属(Rhodobacter,12.73%—57.52%)是下游水样和水库水样中的优势细菌.造成AMD影响下不同位点处水体浮游细菌群落组成差异的环境因子各不相同,入库流域水体细菌群落主要受
${\rm{NH}}_4^+ $ -N、总磷(TP)和${\rm{SO}}_4^{2-}$ 影响,Mg2+和As3+也与入库流域水体中细菌多样性存在一定相关关系,水库水体中细菌群落主要受水温(T)影响.研究结果将有助于为酸性矿山废水微生物资源及生态环境的研究提供理论依据.Abstract: To understand the changes in bacterial community structure along the watershed to the bottom of the reservoir at the acid mine drainage and to explore the environmental impact factors. Twelve water samples affected by acid mine drainage (AMD) were collected in September 2019 using high-throughput sequencing technology and principal component analysis (PCA). The results showed that the trend of bacterial community diversity in the water samples from the inlet basin was not obvious, and the bacterial diversity increased from the surface to the bottom layer. The bacteria affected by AMD at the phylum level were mainly Proteobacteria, Bacteroidetes (0.21%—12.96%), Firmicutes (0.15%—14.48%), and Actinobacteria( 0.06%—4.64%). Of these, the phylum Alphaproteobacteria (2.42%—61.99%), the phylum Betaproteobacteria (1.29%—63.53%) and the phylum Gammaproteobacteria (6.41%—63.09%) were the dominant bacterial groups. In terms of the composition of the planktonic bacterial community at different spatial locations, Acinetobacter(2.13%—57.84%), Pseudomonas(3.86%—12.29%), Ferrobacter(0.97%—13.21%), and Bacteroides (0.01%—5.02%) were the most abundant species in the water samples from the upstream to the bottom of the reservoirs affected by AMD. Pseudomonas (3.86%—12.29%), Ferrovum (0.97%—13.21%) and Bacteroides (0.01%—5.02%) were the dominant genera in the upstream water samples, Hydrogenophaga (0—5.94%), Gallionella (1.45%—11.91%) and Novosphingobium(0—5.34%) were the dominant genera in the midstream, and Rhodobacter(12.73%—57.52%) were the dominant bacteria in the downstream water samples and in the reservoir water samples. The environmental factors leading to the difference in the composition of the planktonic bacterial community at different sites under the influence of AMD are different,${\rm{NH}}_4^+$ -N, total phosphorus (TP) and${\rm{SO}}_4^{2-} $ were the main factors affecting the bacterial community in the inflow basin. Mg2+ and As3+ also had a certain correlation with the bacterial diversity in the inflow basin, and bacterial community in reservoir water is mainly affected by water temperature (T). The results of the study will help to provide a theoretical basis for the study of the microbial resources and ecological environment of acid mine wastewater.-
Key words:
- acid mine drainage /
- bacterial diversity /
- environmental factors /
- watershed /
- reservoir /
- high-throughput sequencing
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表 1 各水库水体主要理化参数
Table 1. Physicochemical parameters of the reservoir water
pH EC/
(μS·cm−1)Eh/
mVDO/
(mg·L−1)T/
℃ -N/${\rm{NH}}_4^+ $
(mg·L−1)TN/
(mg·L−1)TP/
(mg·L−1)DOC/
(mg·L−1) /${\rm{SO}}_4^{2-} $
(mg·L−1)QSZ-1 3.51 1271.00 460.70 7.44 20.40 0.98 1.80 4.88 2.48 1065.65 QSZ-2 3.74 1106.00 404.50 7.24 21.20 0.86 1.51 5.86 1.13 960.02 QSZ-3 4.02 909.00 382.40 7.19 22.30 0.85 1.54 1.61 1.06 1022.80 QSZS 4.78 598.00 328.80 7.11 23.80 0.07 0.87 0.02 0.69 543.27 QSZM 4.60 580.00 325.10 7.03 23.40 0.13 1.02 0.02 1.00 555.40 QSZB 4.75 557.00 261.50 6.79 23.10 0.59 1.02 0.03 1.38 364.87 MJT-1 3.82 1638.00 417.20 7.14 21.40 0.85 2.11 0.03 1.27 1570.19 MJT-2 6.73 1421.00 -7.10 7.04 21.30 1.06 2.90 0.08 1.39 1112.73 MJT-3 6.56 1132.00 28.60 6.75 24.80 0.93 1.97 0.03 2.24 1042.56 MJTS 6.13 1177.00 174.70 6.84 23.00 0.57 1.02 0.02 0.87 718.66 MJTM 5.70 1211.00 243.30 6.33 22.30 0.35 1.09 0.01 1.04 812.42 MJTB 4.24 1301.00 353.80 5.36 21.80 0.95 5.14 0.04 0.94 832.39 TFe/
(mg·L−1)Mn2+/
(μg·L−1)K+/
(mg·L−1)Na+/
(mg·L−1)Mg2+/
(mg·L−1)Cu2+/
(μg·L−1)Zn2+/
(μg·L−1)Pb2+/
(μg·L−1)As3+/
(μg·L−1)Cr2+/
(μg·L−1)QSZ-1 4.88 3.61 2.98 18.18 62.19 34.11 166.02 43.59 0.63 1.41 QSZ-2 5.86 2.15 3.40 34.24 38.16 21.26 202.32 34.27 0.58 1.58 QSZ-3 1.61 1.70 3.13 27.50 31.02 27.29 286.32 44.85 0.26 2.15 QSZS 0.07 1.12 2.47 15.04 17.28 23.07 415.91 25.93 0.22 1.89 QSZM 0.08 1.16 3.04 15.78 16.65 6.06 77.93 9.19 0.15 0.60 QSZB 1.26 1.13 3.12 15.52 15.78 12.61 110.82 31.65 0.54 0.44 MJT-1 5.10 6.56 4.61 9.50 66.72 43.39 239.20 80.70 5.35 1.84 MJT-2 5.16 3.29 3.34 56.44 61.02 18.69 196.73 83.18 0.59 1.94 MJT-3 1.23 1.46 3.33 59.08 46.71 22.08 119.97 44.81 0.20 1.03 MJTS 0.1 1.83 4.40 69.24 41.16 8.24 88.59 67.66 0.14 0.65 MJTM 0.07 1.89 4.60 69.80 43.80 7.01 74.90 12.67 0.07 0.83 MJTB 0.09 2.06 3.45 75.92 46.44 22.16 107.76 57.23 0.40 16.11 表 2 水样浮游细菌多样性统计
Table 2. Diversity statistics of planktonic bacteria in water samples
样品编号
Sample序列数
ReadsOTUs
OUT numbersShannon指数
Shannon indexACE指数
ACE indexChao1指数
Chao1 indexCoverage 指数
Coverage indexSimpson指数
Simpson indexQSZ-1 75559 4646 5.25 7323.34 6842.28 0.97 0.04 QSZ-2 83521 4580 3.36 7783.59 6938.25 0.97 0.18 QSZ-3 110769 6439 4.42 10697.98 9660.64 0.97 0.10 QSZS 97569 1266 1.85 3038.80 2118.58 0.99 0.35 QSZM 86442 1581 2.03 3479.42 2452.01 0.99 0.36 QSZB 64947 4743 5.55 6974.32 6426.88 0.97 0.05 MJT-1 83538 5000 5.21 6871.02 6298.86 0.98 0.03 MJT-2 61293 6444 6.56 9651.25 8682.00 0.96 0.01 MJT-3 85407 2311 2.67 4234.92 3799.55 0.99 0.17 MJTS 95221 2234 2.64 5055.19 3582.34 0.99 0.15 MJTM 90072 3372 3.11 6062.15 5366.32 0.98 0.16 MJTB 82878 3139 4.46 5826.37 4539.25 0.98 0.08 -
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