初始pH对厌氧环境下污泥中抗生素抗性基因行为特征的影响

污水处理厂产生大量的剩余污泥中含有丰富的抗性基因,给环境带来了潜在风险。以城市污水处理厂的剩余污泥为研究对象,在不同初始p H(对照组、初始p H=3、5、7、9、11)下观察厌氧条件下,8种抗生素浓度以及四环素类抗性基因(tet A、tet G、tet L、tet M、tet O、tet Q、tet W、tet X)、磺胺类抗性基因(sul I、sul II)和Ⅰ类整合子(int I 1)的行为特征。研究结果显示,初始p H对抗生素的降解影响较小,污泥中总抗生素的平均去除率为42%。对照组及初始p H为3、5、7、9、11下的总四环素类抗性基因分别削减0.65 log、0.96 log、0.75 log、0.62 log、0.86 log和0.98 log。不同四环素类抗性基因表现相似,在初始p H=3和初始p H=11下部分抗性基因削减较多,特别是tet A、tet G、tet L、tet O和tet X。2种磺胺类抗性基因均无削减,浓度平均上升0.18log。相关性分析显示,总抗性基因与TN、NH3-N、TP、SCOD(溶解性COD)均存在显著相关性(P0.05)。上述研究结果为污泥厌氧消化中抗生素抗性基因减量条件提供参考依据。     

围生期毒死蜱暴露致子代8周雄鼠睾丸组织的氧化损伤

毒死蜱是目前全世界使用和销售量最大的有机磷杀虫剂之一。为探讨围生期毒死蜱暴露致8周雄性子鼠睾丸组织的氧化损伤,选择健康Wistar妊娠母鼠于妊娠期(gestation days,GD)第6天至子鼠出生后(postnatal days,PND)21天通过灌胃染毒0、0.75、1.35和2.70 mg·kg~(-1)剂量的毒死蜱,待雄性子鼠8周龄取左侧睾丸实施组织病理学检查,右侧睾丸用以检测丙二醛(maleic dialdehyde,MDA)的含量和谷胱甘肽S转移酶(glutathione S transferases,GST)、谷胱甘肽过氧化物酶(glutathione peroxidase,GSH-Px)、总超氧化物歧化酶(total superoxide dismutase,T-SOD)的活力。结果表明,与对照组比较,随着染毒剂量的增加子鼠体重和睾丸、附睾脏器系数有下降的趋势(P0.05);而MDA呈升高趋势(P0.05)。各组T-SOD和1.35、2.70 mg·kg~(-1)剂量组GSH-Px活力的下降及2.70 mg·kg~(-1)剂量组GST活力的升高均有统计学意义(P0.05)。睾丸组织病理学检查结果可见2.70mg·kg~(-1)剂量组睾丸组织有明显的损伤,管腔中精液量减少,生精细胞脱落增多。上述研究结果提示母鼠于围生期暴露于毒死蜱,可通过氧化损伤诱导子代雄性大鼠睾丸的毒性作用。     

检测细胞DNA断裂损伤效应的彗星实验法的改良

为了解决彗星实验过程中常出现的脱胶、细胞核分离操作繁琐、重复性低等问题,对彗星实验方法进行了改良,初步建立了彗星实验的快速操作流程。结果显示,通过对载玻片进行预处理,可确保凝胶悬挂均匀;采用改良机械法分离的细胞核浓度适中;以0.5%(w/v)涂层琼脂糖作为基层、以1.5%(w/v)低熔点包埋琼脂糖作为叠加层的"双层凝胶法",辅以"推片法"铺胶,操作便捷且不发生脱胶现象;细胞核膜经裂解处理后再进行电泳和荧光观察,彗星图像清晰,杂质少。应用改良后的彗星实验方法,操作简便,耗时更短,实验效果良好,可快速检测出细胞DNA损伤效应。     

全氟辛烷磺酸(PFOS)和多壁碳纳米管(MWCNTs)复合对斑马鱼外周血红细胞DNA的损伤

为了评价全氟辛烷磺酸(PFOS)和多壁碳纳米管(MWCNTs)对水环境及鱼类的影响,以斑马鱼为模式生物,研究了PFOS和MWCNTs复合对斑马鱼外周血红细胞的DNA损伤。将成年斑马鱼暴露于PFOS(0.2、0.4、0.8、1.6 mg·L-1)、MWCNTs(50 mg·L-1)、PFOS+MWCNTs(0.2+50、0.4+50、0.8+50、1.6+50 mg·L-1)和对照溶液中30 d后,断尾取血进行微核试验和彗星试验。结果表明:PFOS和MWCNTs均可造成斑马鱼外周血红细胞的DNA损伤。1.6 mg·L-1PFOS处理组的微核率、Olive尾矩及尾长分别为(36.3±0.25)‰、(87.91±14.90)μm和(250.49±34.71)μm。PFOS与MWCNTs复合后,斑马鱼外周血红细胞的DNA损伤效应明显降低。复合处理组斑马鱼外周血红细胞的微核率、Olive尾矩及尾长均低于PFOS单独处理相。1.6 mg·L-1复合处理组的微核率、Olive尾矩及尾长比PFOS单独处理组分别降低了24.7%、68.9%、52.4%。因此,在实验浓度范围内,MWCNTs可以降低PFOS对斑马鱼外周血红细胞的DNA损伤。     

烧结机共处置危险废物过程中重金属Pb、Zn的挥发特性

利用化学试剂PbCl2、ZnCl2来模拟危险废物,研究了烧结机共处置危险废物过程中Pb、Zn的挥发特性.首先选取PbCl2、ZnCl2两种化合物的纯化学试剂分别进行了热重分析实验,然后对掺有一定比例PbCl2、ZnCl2的烧结矿原料进行煅烧,采集分析煅烧烟气和煅烧所得烧结矿中Pb和Zn的总量.实验结果表明,在刚开始煅烧的一段时间内,Pb、Zn两种重金属挥发特性相似,均是随着时间的增加以及温度的升高而挥发率逐渐上升,而当煅烧超过一定时间后,其挥发和固化反应会达到平衡,当煅烧的温度为1200℃时,Pb和Zn的挥发率分别为97.13%和65.04%.运用化学反应动力学理论对Pb、Zn两种重金属在烧结机共处置过程中的挥发规律进行动力学模拟,模拟结果表明,PbCl2中Pb挥发的动力学方程可表示为α=f(T,t)=1-exp[-7.90exp(-5595/T)t];而ZnCl2中的Zn为α=f(T,t)=1-exp[-0.534exp(-3210/T)t].     

Enhanced bio-decolorization of 1-amino-4-bromoanthraquinone-2-sulfonic acid by Sphingomonas xenophaga with nutrient amendment

Bacterial decolorization of anthraquinone dye intermediates is a slow process under aerobic conditions. To speed up the process, in the present study, effects of various nutrients on 1-amino-4-bromoanthraquinone-2-sulfonic acid (ABAS) decolorization by Sphingomonas xenophaga QYY were investigated. The results showed that peptone, yeast extract and casamino acid amendments promoted ABAS bio-decolorization. In particular, the addition of peptone and casamino acids could improve the decolorization activity of strain QYY. Further experiments showed that L-proline had a more significant accelerating effect on ABAS decolorization compared with other amino acids. L-Proline not only supported cell growth, but also significantly increased the decolorization activity of strain QYY. Membrane proteins of strain QYY exhibited ABAS decolorization activities in the presence of L-proline or reduced nicotinamide adenine dinucleotide, while this behavior was not observed in the presence of other amino acids. Moreover, the positive correlation between L-proline concentration and the decolorization activity of membrane proteins was observed, indicating that L-proline plays an important role in ABAS decolorization. The above findings provide us not only a novel insight into bacterial ABAS decolorization, but also an L-proline-supplemented bioaugmentation strategy for enhancing ABAS bio-decolorization.     

Molecular diversity of arbuscular mycorrhizal fungi at a large-scale antimony mining area in southern China

Arbuscular mycorrhizal fungi (AMF) have great potential for assisting heavy metal hyperaccumulators in the remediation of contaminated soils. However, little information is available about the community composition of AMF under natural conditions in soils contaminated by antimony (Sb). The objective of this study was to investigate the characteristics of AMF molecular diversity, and to explore the effects of Sb content and soil properties on the AMF community structure in an Sb mining area. Four Sb mine spoils and one adjacent reference area were selected from around the Xikuangshan mine in southern China. The association of AMF molecular diversity and community composition with the rhizosphere soils of the dominant plant species was studied by Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis (PCR-DGGE). Results from all five studied sites showed that the diversity of AMF decreased with increasing Sb concentration. Principal component analysis (PCA) indicated that the AMF community structure was markedly different among these groups. Further redundancy analysis (RDA) showed that Sb contaminationwas the dominating factor influencing the AMF community structure in the Sb mine area. However, the multivariate analysis showed that, apart from the soil Sb content, extractable nitrogen content and organic matter content also attributed to AMF sequence distribution type. Some AMF sequences were only found in the highly contaminated area and these might be ideal candidates for improving phytoremediation efficiency in Sb mining regions. Gene sequencing analysis revealed that most species were affiliated with Glomus, suggesting that Glomus was the dominant AMF genus in the studied Sb mining area.     

Microcystis aeruginosa/Pseudomonas pseudoalcaligenes interaction effects on off-flavors in algae/bacteria co-culture system under different temperatures

We conducted an experiment to study the interaction effects of Microcystis aeruginosa and Pseudomonas pseudoalcaligenes on off-flavors in an algae/bacteria co-culture system at three temperatures (24, 28 and 32°C). Gas chromatography–mass spectrometry was applied to measure off-flavor compounds dimethyl sulfide (DMS), dimethyl trisulfide (DMTS), 2-methylisoborneol, geosmin (GEO) and β-cyclocitral. During the lag phase of co-cultured M. aeruginosa (first 15 days), P. pseudoalcaligenes significantly increased the production of DMS, DMTS and β-cyclocitral at all three temperatures. In the exponential phase of co-cultured M. aeruginosa (after 15 days), M. aeruginosa became the main factor on off-flavors in the co-culture system, and β-cyclocitral turned to the highest off-flavor compound. These results also indicated that DMS, DMTS and β-cyclocitral were the main off-flavor compounds in our M. aeruginosa/P. pseudoalcaligenes co-culture system. Univariate analysis was applied to investigate the effects of M. aeruginosa and P. pseudoalcaligenes on the production of off-flavors. The results demonstrated that both M. aeruginosa and P. pseudoalcaligenes could increase the production of DMS and DMTS, while β-cyclocitral was mainly determined by M. aeruginosa. Our results also provide some insights into understanding the relationship between cyanobacteria and heterotrophic bacteria.     

Microcystis aeruginosa/Pseudomonas pseudoalcaligenes interaction effects on off-flavors in algae/bacteria co-culture system under different temperatures

We conducted an experiment to study the interaction effects of Microcystis aeruginosa and Pseudomonas pseudoalcaligenes on off-flavors in an algae/bacteria co-culture system at three temperatures(24, 28 and 32℃). Gas chromatography–mass spectrometry was applied to measure off-flavor compounds dimethyl sulfide(DMS), dimethyl trisulfide(DMTS),2-methylisoborneol, geosmin(GEO) and β-cyclocitral. During the lag phase of co-cultured M. aeruginosa(first 15 days), P. pseudoalcaligenes significantly increased the production of DMS, DMTS and β-cyclocitral at all three temperatures. In the exponential phase of co-cultured M. aeruginosa(after 15 days), M. aeruginosa became the main factor on off-flavors in the co-culture system, and β-cyclocitral turned to the highest off-flavor compound. These results also indicated that DMS, DMTS and β-cyclocitral were the main off-flavor compounds in our M. aeruginosa/P. pseudoalcaligenes co-culture system. Univariate analysis was applied to investigate the effects of M. aeruginosa and P. pseudoalcaligenes on the production of off-flavors. The results demonstrated that both M. aeruginosa and P. pseudoalcaligenes could increase the production of DMS and DMTS, while β-cyclocitral was mainly determined by M. aeruginosa. Our results also provide some insights into understanding the relationship between cyanobacteria and heterotrophic bacteria.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.