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安全清洁的饮用水与人群健康息息相关,也是我国当前经济社会发展中的重大民生问题之一[1]。饮用水处理工艺经过百余年的发展,特别是消毒工艺的应用,为消除伤寒、霍乱等介水传播疾病做出了重大贡献。但随着检测技术的不断发展,耐氯性条件致病菌在饮用水系统中被不断检出[2-3]。有研究[4]显示,人类仍有50%的疾病与饮用水中病原微生物有关。因此,探究饮用水处理工艺中细菌群落的时空分布与动态变化,对病原微生物控制技术的开发,进而保障人群健康具有重要意义。
高通量测序因其准确性高、成本低等优点,在供水系统微生物群落解析中应用广泛。目前,已有利用该技术对常规处理工艺[5]、臭氧-生物活性炭深度处理工艺[6]、炭砂滤池处理工艺[7]等工艺过程中细菌群落多样性进行解析的很多案例。但是,针对超滤工艺及其组合净水工艺过程中细菌群落变化的研究却鲜见报道[8]。
本研究以我国南方某基于活性炭-超滤深度处理工艺的自来水厂为采样地,采用NovaSeq6000高通量测序技术对夏季和冬季各工艺单元出水和活性炭生物膜的细菌群落进行解析,以探究细菌群落在工艺过程中的分布与变化规律;并了解主要条件致病菌属的组成,以期为全面保障饮用水安全提供参考。
活性炭-超滤深度处理工艺中细菌群落时空分布及动态变化规律
Spatiotemporal distribution and dynamic variation of bacterial communities in granular activated carbon-ultrafiltration advanced treatment process
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摘要: 利用NovaSeq6000高通量测序技术对夏季和冬季我国南方某采用活性炭-超滤深度处理工艺自来水厂工艺过程中的细菌群落进行解析,以探究该工艺过程中细菌群落的分布和变化规律。结果表明,出厂水浊度、菌落总数等水质指标均符合国标GB 5749-2006的要求。混凝沉淀、超滤和消毒对细菌群落多样性起到去除作用,且夏季去除率明显高于冬季;夏季和冬季优势菌门均为变形菌门(Proteobacteria)、放线菌门(Actinobacteria)等,但在属水平上细菌群落组成存在明显差异。此外,检测到的条件致病菌属主要包括分支杆菌属(Mycobacterium)和假单胞菌属(Pseudomonas),其在核心微生物中合计占比为5.56%。活性炭-超滤深度处理工艺过程中细菌群落具有明显的时空变化规律。
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关键词:
- 饮用水 /
- 活性炭-超滤深度处理工艺 /
- 细菌群落 /
- 时空分布 /
- 动态变化
Abstract: The bacterial communities in a granular activated GAC-UF advanced treatment process drinking water plant in the south of China were analyzed using NovaSeq6000 high throughput sequencing technology in summer and winter, in order to gain insight into the distribution and variation of those bacterial communities in this process. The results showed that the water quality indicators such as turbidity and total plate count in finished water all met the standards for drinking water quality GB 5749-2006. The bacterial community diversities were removed by the coagulation sedimentation, UF and disinfection, and the removal rates in summer were significantly higher than those in winter. The dominant phyla in both summer and winter were Proteobacteria, Actinobacteria, etc., but significant differences in bacterial community composition were found at the genus level. Additionally, Mycobacterium and Pseudomonas were the main potential pathogenic genera, and their total proportion in core microorganisms was 5.56%. In a word, the results provided evidence of distinct spatiotemporal variation of bacterial communities in the GAC-UF advanced treatment process, and contributed to microbiological safety assurance of drinking water. -
表 1 GAC-UF深度处理工艺过程中水质参数变化
Table 1. Variations of water characteristics in GAC-UF advanced treatment process
样品名称 pH 水温/
℃浊度/
NTU溶解氧/
(mg·L−1)总磷/
(mg·L−1)氨氮/
(mg·L−1)UV254/
cm−1TOC/
(mg·L−1)CODMn/
(mg·L−1)BDOC/
(mg·L−1)菌落总数/
(CFU·mL−1)HPC/
(CFU·mL−1)S.RW 7.87 28.2 11.30 7.96 0.206 0.123 0.034 7 4.68 3.06 0.75 260 620 S.CSE 8.84 28.3 1.62 8.24 1.490 0 0.038 3 2.95 2.85 0.65 112 98 S.GACFE 7.84 28.2 0.61 7.78 0.532 0 0.025 4 2.40 2.48 0.45 21 64 S.UFE 7.82 28.4 0.11 8.65 0.107 0 0.023 6 1.25 1.79 0.23 3 0 S.FW 7.88 28.3 0.10 8.62 0.100 0 0.023 0 1.28 1.70 0.19 1 2 W.RW 7.31 17.2 2.94 9.29 0.124 0.210 0.028 6 2.78 2.50 0.52 150 8800 W.CSE 8.19 17.3 0.63 9.58 0.105 0 0.019 0 2.68 2.30 0.43 68 5700 W.GACFE 7.30 17.2 0.39 9.05 0.122 0 0.015 0 2.16 1.80 0.32 42 1850 W.UFE 7.60 17.4 0.04 9.92 0.137 0 0.011 1 1.76 1.30 0.15 0 370 W.FW 7.65 17.3 0.07 9.93 0.097 0 0.010 9 1.65 1.10 0.13 0 323 表 2 各样品OTUs数目和α多样性指数
Table 2. OTUs numbers and alpha diversity indexes of each sample
样品名称 OTUs α多样性指数 Shannon Simpson Chao1 ACE Good’s coverage S.RW 1 695 7.319 0.984 1 876.506 1 956.042 0.985 S.CSE 1 411 3.095 0.588 1 506.975 1 550.896 0.991 S.GACFE 2 435 8.219 0.990 2 370.500 2 409.806 0.988 S.UFE 1 676 5.940 0.958 1 689.852 1 721.605 0.988 S.FW 881 4.415 0.718 866.174 875.634 0.995 S.GACB 1 896 6.468 0.928 1 858.297 1 898.854 0.993 W.RW 2 060 7.388 0.984 1 916.576 2 035.472 0.985 W.CSE 1 537 6.289 0.974 1 589.256 1 651.141 0.986 W.GACFE 2 490 8.834 0.991 2 497.889 2 517.366 0.982 W.UFE 1 330 7.297 0.976 1 382.941 1 548.965 0.990 W.FW 1 183 5.831 0.941 1 225.567 1 311.826 0.987 W.GACB 2 278 8.511 0.981 2 131.875 2 227.622 0.984 注:Shannon和Simpson为菌群多样性指数,Chao1和ACE为菌群丰度指数。 -
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