从三个污水处理厂(WWTP)研究了富集的微生物群落及其代谢功能,这是CWWTP(焦化废水),MWWTP1(生活污水),和MWWTP2(含有上述CWWTP的各种工业WWTP的混合废水与生活废水和废水)。三个污水处理厂和每个污水处理厂中的反应单元之间的污染物类型和浓度不同。CWWTP比MWWTPs具有更高的TCN和苯酚浓度,然而,在MWWTP2中未发现苯酚,但在其厌氧单元中发现了0.72mg/LTCN。RDA结果显示COD,TN,TP,TCN,NO3--N,和苯酚是影响微生物群落的主要因素(P<0.05)。CPCoA证实了由污染物类型和浓度驱动的微生物群落差异(65.1%的方差,P=0.006)。它们为微生物提供了不同的生长环境和生态位,在每个污水处理厂塑造独特的细菌群落,如:硫杆菌,Tepidiphus,Soehngenia,CWWTP中的焦耳杆菌;Acidovorax,黄杆菌,MWWTP1中的Gp4;和中根瘤菌,Terriphomum,Shinella,MWWTP2中的示波氯。组间比较分析表明,这些独特的细菌在WWTP之间表现出统计学上的显着差异(P<0.01),它们分别是每个污水处理厂的生物标志物。细菌的共现和共排除模式表明,每个污水处理厂中的大多数优势细菌分别被分配到不同的模块中,这些微生物在每个模块中都有更密切的正相关关系。与功能轮廓预测一致,CWWTP中的外源生物的生物降解和代谢高于其他WWTP(3.86%)。不同的功能细菌通过氧化还原酶代谢特定的异源生物,异构酶,裂解酶,转移酶,脱羧酶,羟化酶,和水解酶在每个单位或WWTP。这些结果为以下观点提供了证据:污染物类型和浓度对活性污泥中的微生物产生选择压力。塑造独特的微生物群落结构和功能。
Enriched microbial communities and their metabolic function were investigated from the three wastewater treatment plants (WWTPs), which were CWWTP (coking wastewater), MWWTP1 (domestic wastewater), and MWWTP2 (mixed wastewater with domestic wastewater and effluent from various industrial WWTPs that contained the mentioned CWWTP). Pollutant types and concentrations differed among the three WWTPs and the reaction units in each WWTP. CWWTP had a higher TCN and phenol concentrations than the MWWTPs, however, in MWWTP2 no phenol was discovered but 0.72 mg/L TCN was found in its anaerobic unit. RDA results revealed that COD, TN, TP, TCN, NO3--N, and phenol were the main factors influencing the microbial communities (P < 0.05). CPCoA confirmed the microbial community difference driven by pollutant types and concentrations (65.1% of variance, P = 0.006). They provided diverse growth environments and ecological niches for microorganisms, shaping unique bacterial community in each WWTP, as: Thiobacillus, Tepidiphilus, Soehngenia, Diaphorobacter in CWWTP; Saccharibacteria, Acidovorax, Flavobacterium, Gp4 in MWWTP1; and Mesorhizobium, Terrimicrobium, Shinella, Oscillochloris in MWWTP2. Group comparative was analyzed and indicated that these unique bacteria exhibited statistically significant difference (P < 0.01) among the WWTPs, and they were the biomarkers in each WWTP respectively. Co-occurrence and coexclusion patterns of bacteria revealed that the most of dominant bacteria in each WWTP were assigned to different modules respectively, and these microorganisms had a closer positive relationship in each module. Consistent with the functional profile prediction, xenobiotics biodegradation and metabolism were higher in CWWTP (3.86%) than other WWTPs. The distinct functional bacteria metabolized particular xenobiotics via oxidoreductases, isomerases, lyases, transferases, decarboxylase, hydroxylase, and hydrolase in each unit or WWTP. These results provided the evidences to support the idea that the pollutant types and concentration put selection stress on microorganisms in the activated sludge, shaping the distinct microbial community structure and function.