环境污染控制过程高灵敏生物传感技术研究及其检测体系构建
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摘要
在环境污染控制过程中,污染物的降解大多是通过微生物的相互协同作用完成的,对污染物及参与降解过程的微生物的种群分布、功能活性和代谢产物变化等进行快速、灵敏的追踪、监测与时空分辨,是研究污染物降解过程的重要途径。生物传感技术是一种对待测物实现快速、实时、在线分析检测的新兴技术,它利用生物识别作用对待测的物质进行分析测定,与传统的分析方法相比,具有高灵敏度、高专一性、快速测定、简便易携、适用于复杂体系的实时、在线测定等优点,为环境污染物及其降解过程涉及到的各种生物组分或代谢产物的分析检测提供了一个新的技术平台。系统地构建环境污染控制过程中生物传感技术检测体系,为环境污染控制工作提供及时、准确的生物信息,对于解决环境科学与工程领域的实时、在线监测技术难题,最终实现自动化控制,推动环境检测技术大跨度发展具有重要意义。
本文研制了一系列生物传感检测方法,用于环境中痕量污染物及其降解产物等的高灵敏检测,并以堆肥环境体系为例,建立起了一套基于生物传感技术的检测环境复杂系统中的污染物及参与其降解过程的生物酶、微生物种群、功能基因和代谢产物动态变化的新方法体系,克服了传统的分析检测方法在环境污染控制过程实时在线检测等方面的局限性,有利于深入了解整个垃圾堆肥处理过程的微生物学机理,高效指导微生物接种和堆肥工艺革新。论文工作从整体上分为四个部分:
第一部分为环境中痕量有毒有害污染物及降解产物的高灵敏生物传感检测技术研究。通过采用二茂铁掺杂电聚合和伴刀豆蛋白A自组装等技术将酶固定在电极表面,构建了抑制型葡萄糖氧化酶传感器和抑制型辣根过氧化物酶传感器,分别用于检测土壤样品中的痕量Cr(VI)和Hg(II)与湘江水中的苯肼,具有灵敏度高、抑制可逆、稳定性和选择性好等优点,获得的Cr(VI)和Hg(II)的检测下限均为0.49μg L~(-1),苯肼的检测下限为1.7×10~(-6) M,并运用酶传感器实验数据,推导出了辣根过氧化物酶对H_2O_2、对苯二酚的催化反应以及苯肼对该反应的抑制作用的动力学模型,进行了模型拟合与参数估计;将有机氯农药毒莠定与牛血清蛋白交联制备人工抗原,并注射入新西兰大白兔体内提纯出抗体,研制了一种基于壳聚糖/纳米金复合膜的电化学免疫传感器,用于检测稻米、莴苣和稻田水中的痕量毒莠定,该免疫膜具有很好的选择性,灵敏度高,可批量制作、一次性使用,检测下限为5 ng mL~(-1) ;利用酚类物质普遍具有的还原性,研制了一种传感晶片,以固定在玻片表面的金纳米颗粒为晶种,运用在酚还原作用下金纳米颗粒催化增长的原理和吸收光谱变化规律,用于好氧发酵液等复杂体系中酚浓度检测,检测下限为7×10-6 M,该方法操作简便,成本低,灵敏度高;还利用漆酶催化邻苯二酚氧化还原反应和磁性颗粒分离技术,研制了一种基于磁性纳米颗粒固定技术的漆酶传感器,可用于检测堆肥复杂系统中的浓度低至7.5×10~(-7) M的痕量邻苯二酚。
第二部分着重开展基于生物传感技术的堆肥系统微生物降解酶活性及生物表面活性剂的跟踪监测。堆肥系统中多种酶的活性是检测堆肥腐熟度的重要指标,本文利用电极表面固定化纳米金原位扩增对还原型烟酰胺腺嘌呤二核苷酸(NADH)氧化的生物电催化活性,研制了一种新型NADH电化学传感器,响应迅速,灵敏度高,能够在酸性缓冲液中检测浓度低至2.5×10~(-7) M的NADH,3个月内保持检测结果精确;利用在NADH还原作用下Au/Ag核壳型纳米颗粒催化增长的原理和吸收光谱变化规律,研制了一种NADH光学纳米生物传感晶片,检测下限为1.56×10~(-5) M;利用木素过氧化物酶(LiP)和锰过氧化物酶(MnP)催化底物的氧化还原反应,研制了一种快速同步检测堆肥中木质素降解酶活的电化学酶传感器,检测样品LiP活性范围为8.14~29.79 U L~(-1) ,MnP活性范围为0.085~1.37 U L~(-1) ,该方法能够排除堆肥浸出液中浊度和光干扰物质的干扰,较传统的分光光度法更加快速、灵敏和精确,是堆肥系统中快速、低成本的堆肥腐熟度检测技术;堆肥常见微生物铜绿假单胞菌发酵代谢产生的鼠李糖脂是一种可改善堆肥微环境的生物表面活性剂,本文制备了二鼠李糖脂人工抗原和抗体,研制了一种基于3,3’-二氨基联苯胺(DAB)显色的二鼠李糖脂酶联免疫试纸,可用于肉眼检测浓度低至0.05 mg L~(-1)的二鼠李糖脂,该方法简便、快速,可重复性良好。
第三部分着重开展基于基因传感技术的堆肥系统微生物种群动态和功能基因的跟踪监测。堆肥中某些高效降解污染物的微生物具有相应的功能基因,LiP是真菌降解木质素的一种关键酶,设计合成了黄孢原毛平格菌lip基因探针,研制了一种夹心式杂交识别lip基因的酶联电流型DNA传感器,结合聚合酶链式反应(PCR)和限制性酶切技术,成功检测了黄孢原毛平格菌的基因组DNA提取样品中的lip基因,检测下限为0.03 nM,该DNA传感器能够有效识别相同长度的错配核酸链样品;纤维二糖水解酶(CBH)是纤维素降解的一种关键酶,设计合成了瑞氏木霉cbh2基因探针,运用纳米金原位扩增技术制备了一种金/硅/铁三层复合型核壳磁性纳米颗粒,研制成竞争式杂交识别cbh2基因的电化学纳米DNA传感器,检测下限达到10-13 M;还将羧基化的多壁碳纳米管-多聚(3,4-乙烯二氧噻吩)复合膜沉积在电极表面,制备了cbh2基因传感器,优化实验参数,进行了扫描电镜(SEM)和电化学表征;细菌的16S rDNA/rRNA基因序列具有高度的保守性,可用于种属特异性鉴定,研制了一种基于分子信标荧光分析的铜绿假单胞菌16S rRNA体外定量检测方法,用于检测总RNA提取样品中的16S rRNA,杂交反应需时约30 min,该方法具有高度的特异性,不受核酸交叉污染,检测前不需要对细菌总RNA进行分离和纯化。
第四部分为复杂环境体系污染物及降解性能定量检测的数据解析。由于环境样品组成复杂,干扰物质较多,多种待测组分可能同时存在,给分析监测带来很大的不确定性,本文利用人工神经网络(ANNs)解析信号的优良性能,将人工神经网络和电化学酶传感技术相结合,用于黄孢原毛平革菌接种堆肥中木质素降解酶活性电化学检测及漆酶传感器检测邻苯二酚的定量分析,与线性回归模型相比,该方法更加精确、灵敏、稳健;土壤阳离子交换量(CEC)是土壤保留阳离子营养物质和缓冲污染物能力的重要指标,本文还构建了一种基于径向基函数神经网络的土壤传递函数,用于定量分析不同地区、不同土层的土壤CEC,该复合神经网络模型在大规模数据拟合中具有优越性。
In environmental pollution control, the degradation of contaminants are carried out by the cooperation of microbes, and it is an important approach for studying the contaminant degradation process to rapidly and sensitively trace, monitor and indentify the contaminants and the microbial community population, functional activities, variety of metabolites, and etc. in their degradation. Biosensing technology is a new approach for rapid, real-time and on-line detection of analytes based on biometric identification, which has the advantages of high sensitivity, specificity, rapidity, portability and capacity for real-time and on-line detection in complex system in comparison with conventional analytical methods, and provides a new technical platform for the analysis and measurement of contaminants and various biological components or metabolites in relative degradation. It is very significant for the development of environmental detection technology to systematically construct a detection system of biosensing technology in environmental pollution control, to provide timely and accurate biological information for pollution control process, and to solve the real-time and on-line monitoring problems in environmental science and engineering study, and to ultimately realize automation.
This dissertation developed a series of biosensing detection methods, for highly sensitive detection of trace contaminants and their degradation metabolites in the environment, and took the composting system for example to construct a set of novel methods based on biosensing technology for the detection of contaminants and the dynamic changing of relative enzymes, microbial community population, functional genes and metabolites in complex environment, which overcame the limitation of conventional analytical methods applied in environmental pollution control in the aspects of real-time and on-line detection, and etc., and favored the thorogh investigation of the microbial mechanism in waste composting process and efficient instruction of the microbial inoculation and composting technique renovation. This dissertation is composed of four sections.
The first section describes the research on highly sensitive biosensing detection technology for trace hazardous contaminants and their metabolites in the environment. The enzymes were immobilized on the electrodes through ferrocene-doped electropolymerization, self-assembly by concanavalin A, and other techniques to develop an inhibition-based glucose oxidase sensor and an inhibition-based horseradish peroxidase sensor, for the detection of trace Cr(VI) and Hg(II) in soil, and the detection of phenylhydrazine in Xiangjiang River, respectively, which obtained high sensitivity, reversibility, stability and selectivity. Both of the lower detection limits for Cr(VI) and Hg(II) were 0.49μg L~(-1), and that for phenylhydrazine was 1.7×10~(-6) M. The experimental data obtained by enzyme sensors were used to deduce the kinetic models of the catalysis of H_2O_2 and hydroquinone by horseradish peroxidase and the inhibition by phenylhydrazine, and to carry out the model simulation and parameter estimation. Picloram, a kind of organo-chlorinated pesticide, was conjugated with bovine serum albumin as an artificial antigen which was injected into New Zealand white rabbits to obtain purified antibody. An electrochemical immonosensor based on chitosan/gold nanoparticles (Au NPs) composite membrane was developed for the detection of trace picloram in rice, lettuce, and paddy field water. The immunomenbrane has good selectivity, high sensitivity, disposability, and good reproducibility for fabrication in batch. The lower detection limit was 5 ng mL~(-1). A sensoring chip was developed based on the ubiquitous reductivity of phenols, which utilized the Au NPs immobilized on the glass slide as the seeds to catalyze the enlargement of Au NPs by the phenol reduction, and then the phenol concentration could be detected through absorption spectroscopy change. The lower detection limit was 7×10~(-6) M. This method was convenient, low-cost, and highly sensitive. A laccase sensor based on magnetic nanoparticles-laccase conjugates was developed utilizing laccase-catalyzed redox of catechol and the magnetic separation, which was used to detect trace catechol in complex composting system with the concentration as low as 7.5×10~(-7) M.
The second section describes the trace of microbial degrading enzyme activities and biosurfactants in composting system using biosensing technology. Some enzyme activities in composting system are important maturity indexes. An electrochemical dihydronicotinamide adenine dinucleotide (NADH) sensor based on the catalytic growth of Au NPs on electrode was developed with fast response and high sensitivity, which could detect NADH in acidic buffers with the concentration as low as 2.5×10~(-7) M, and maintained the accuracy in 3 months. A sensoring chip was developed based on the catalytic growth of Au/Ag core/shell nanoparticles by NADH reduction, and then NADH concentration could be detected through absorption spectroscopy change with the lower detection limit of 1.56×10-5 M. An electrochemical enzyme sensor for rapid and simultaneous detection of the lignin-degrading peroxidase activities was developed based on the substrate redox catalyzed by lignin peroxidase (LiP) and manganese peroxidase (MnP). LiP and MnP activities could be detected in the range of 8.14~29.79 U L~(-1) and 0.085~1.37 U L~(-1) , respectively. This assay is more rapid, sensitive and precise than conventional spectrophotometric assays, free from interference of turbidity and UV- and visible-light-absorbing substances in compost extract. Rhamnolipid, a biosurfactant secreted by the common bacteria in compost, Pseudomonas aeruginose, in fermentation metabolism, can improve the microenvironment in compost. The artificial antigen and antibody of rhamnolipid were fabricated, and a chromogenic enzyme-linked immuno test paper for dirhamnolipid based on 3,3′-diaminobenzidine (DAB) was developed, which could detect dirhamnolipid with the concentration as low as 0.05 mg L~(-1) by unaided eye. This method was convenient, fast, and reproducible.
The third section focuses on the trace of microbial community dynamics and the functional genes in composting system based on genosensing technology. Some high- efficiency contaminant degrading microbes contain relative functional genes. LiP is a key enzyme in lignin degradation by fungi. The gene probes for lip in Phanerochaete chrysosporium was designed and synthesized, and an enzyme-linked electrochemical DNA sensor based on the sandwich hybridization recognition of lip was developed. This sensor, combined with polymerase chain reaction (PCR) and restriction enzyme digestion, succeeded in measuring lip gene fragments from Phanerochaete chrysosporium genome extraction samples with the lower detection limit of 0.03 nM. It could discriminate satisfactorily against mismatched nucleic acid samples of similar lengths. Cellobiohydrolase (CBH) is a key enzyme in cellulose degradation. The gene probes for cbh2 in Trichoderma reesei was designed and synthesized, and magnetic Au/Si/Fe core/shell nanoparticles were fabricated by catalytic growth of Au NPs on the surface. An electrochemical nano DNA sensor based on the competitive hybridization recognition of cbh2 was developed, with the lower detection limit of 10-13 M. Another cbh2 genosensor was developed by the deposition of multi-walled carbon nanotubes-poly(1-ethyl-(3-dimethyllaminopropyl)carbodiimide hydrochloride) complex membrane on electrode surface. The experimental parameters were optimized, and the genosensor was characterized by scanning electron microscopy (SEM) and electrochemistry. The 16S rDNA/rRNA sequences of bacteria are highly conservative, and can be used for species identification. An in vitro 16S rRNA quantification method for Pseudomonas aeruginose based on molecular beacon was developed for the detection of 16S rRNA from total RNA isolation samples. The hybridization reaction required 30 min, and the method had high specificity, free from cross-pollution by nucleic acid, and required no isolation or purification procedures for bacteria total RNA.
The fourth section focused on the data resolution of quantification of contaminants and relative degradation capabilities in complex environment system. The complex components in real environmental samples, various interferents, and coexistence of multiple analytes take uncertainty to environmental analysis. Due to the good performance of artificial neural networks (ANNs) in signal resolution, this dissertation combined ANNs with electrochemical enzyme biosensing technology in the electrochemical detection of the lignin-degrading peroxidase activities in Phanerochaete chrysosporium inoculated compost, and the quantitive analysis of catechol by laccase sensor. These methods were more accurate, sensitive and robust than linear regression models. Cation exchange capacity (CEC) is an important index of the soil buffering capacity to maintain cationic nutrients and pollutants against leaching to the subsurface layers. A pedotransfer function based on radial basis function neural networks (RBFN) was developed and applied into the estimation of CEC different regions and different horizons, from soil physico-chemical properties, which showed superiority in large scale data simulation.
本文研制了一系列生物传感检测方法,用于环境中痕量污染物及其降解产物等的高灵敏检测,并以堆肥环境体系为例,建立起了一套基于生物传感技术的检测环境复杂系统中的污染物及参与其降解过程的生物酶、微生物种群、功能基因和代谢产物动态变化的新方法体系,克服了传统的分析检测方法在环境污染控制过程实时在线检测等方面的局限性,有利于深入了解整个垃圾堆肥处理过程的微生物学机理,高效指导微生物接种和堆肥工艺革新。论文工作从整体上分为四个部分:
第一部分为环境中痕量有毒有害污染物及降解产物的高灵敏生物传感检测技术研究。通过采用二茂铁掺杂电聚合和伴刀豆蛋白A自组装等技术将酶固定在电极表面,构建了抑制型葡萄糖氧化酶传感器和抑制型辣根过氧化物酶传感器,分别用于检测土壤样品中的痕量Cr(VI)和Hg(II)与湘江水中的苯肼,具有灵敏度高、抑制可逆、稳定性和选择性好等优点,获得的Cr(VI)和Hg(II)的检测下限均为0.49μg L~(-1),苯肼的检测下限为1.7×10~(-6) M,并运用酶传感器实验数据,推导出了辣根过氧化物酶对H_2O_2、对苯二酚的催化反应以及苯肼对该反应的抑制作用的动力学模型,进行了模型拟合与参数估计;将有机氯农药毒莠定与牛血清蛋白交联制备人工抗原,并注射入新西兰大白兔体内提纯出抗体,研制了一种基于壳聚糖/纳米金复合膜的电化学免疫传感器,用于检测稻米、莴苣和稻田水中的痕量毒莠定,该免疫膜具有很好的选择性,灵敏度高,可批量制作、一次性使用,检测下限为5 ng mL~(-1) ;利用酚类物质普遍具有的还原性,研制了一种传感晶片,以固定在玻片表面的金纳米颗粒为晶种,运用在酚还原作用下金纳米颗粒催化增长的原理和吸收光谱变化规律,用于好氧发酵液等复杂体系中酚浓度检测,检测下限为7×10-6 M,该方法操作简便,成本低,灵敏度高;还利用漆酶催化邻苯二酚氧化还原反应和磁性颗粒分离技术,研制了一种基于磁性纳米颗粒固定技术的漆酶传感器,可用于检测堆肥复杂系统中的浓度低至7.5×10~(-7) M的痕量邻苯二酚。
第二部分着重开展基于生物传感技术的堆肥系统微生物降解酶活性及生物表面活性剂的跟踪监测。堆肥系统中多种酶的活性是检测堆肥腐熟度的重要指标,本文利用电极表面固定化纳米金原位扩增对还原型烟酰胺腺嘌呤二核苷酸(NADH)氧化的生物电催化活性,研制了一种新型NADH电化学传感器,响应迅速,灵敏度高,能够在酸性缓冲液中检测浓度低至2.5×10~(-7) M的NADH,3个月内保持检测结果精确;利用在NADH还原作用下Au/Ag核壳型纳米颗粒催化增长的原理和吸收光谱变化规律,研制了一种NADH光学纳米生物传感晶片,检测下限为1.56×10~(-5) M;利用木素过氧化物酶(LiP)和锰过氧化物酶(MnP)催化底物的氧化还原反应,研制了一种快速同步检测堆肥中木质素降解酶活的电化学酶传感器,检测样品LiP活性范围为8.14~29.79 U L~(-1) ,MnP活性范围为0.085~1.37 U L~(-1) ,该方法能够排除堆肥浸出液中浊度和光干扰物质的干扰,较传统的分光光度法更加快速、灵敏和精确,是堆肥系统中快速、低成本的堆肥腐熟度检测技术;堆肥常见微生物铜绿假单胞菌发酵代谢产生的鼠李糖脂是一种可改善堆肥微环境的生物表面活性剂,本文制备了二鼠李糖脂人工抗原和抗体,研制了一种基于3,3’-二氨基联苯胺(DAB)显色的二鼠李糖脂酶联免疫试纸,可用于肉眼检测浓度低至0.05 mg L~(-1)的二鼠李糖脂,该方法简便、快速,可重复性良好。
第三部分着重开展基于基因传感技术的堆肥系统微生物种群动态和功能基因的跟踪监测。堆肥中某些高效降解污染物的微生物具有相应的功能基因,LiP是真菌降解木质素的一种关键酶,设计合成了黄孢原毛平格菌lip基因探针,研制了一种夹心式杂交识别lip基因的酶联电流型DNA传感器,结合聚合酶链式反应(PCR)和限制性酶切技术,成功检测了黄孢原毛平格菌的基因组DNA提取样品中的lip基因,检测下限为0.03 nM,该DNA传感器能够有效识别相同长度的错配核酸链样品;纤维二糖水解酶(CBH)是纤维素降解的一种关键酶,设计合成了瑞氏木霉cbh2基因探针,运用纳米金原位扩增技术制备了一种金/硅/铁三层复合型核壳磁性纳米颗粒,研制成竞争式杂交识别cbh2基因的电化学纳米DNA传感器,检测下限达到10-13 M;还将羧基化的多壁碳纳米管-多聚(3,4-乙烯二氧噻吩)复合膜沉积在电极表面,制备了cbh2基因传感器,优化实验参数,进行了扫描电镜(SEM)和电化学表征;细菌的16S rDNA/rRNA基因序列具有高度的保守性,可用于种属特异性鉴定,研制了一种基于分子信标荧光分析的铜绿假单胞菌16S rRNA体外定量检测方法,用于检测总RNA提取样品中的16S rRNA,杂交反应需时约30 min,该方法具有高度的特异性,不受核酸交叉污染,检测前不需要对细菌总RNA进行分离和纯化。
第四部分为复杂环境体系污染物及降解性能定量检测的数据解析。由于环境样品组成复杂,干扰物质较多,多种待测组分可能同时存在,给分析监测带来很大的不确定性,本文利用人工神经网络(ANNs)解析信号的优良性能,将人工神经网络和电化学酶传感技术相结合,用于黄孢原毛平革菌接种堆肥中木质素降解酶活性电化学检测及漆酶传感器检测邻苯二酚的定量分析,与线性回归模型相比,该方法更加精确、灵敏、稳健;土壤阳离子交换量(CEC)是土壤保留阳离子营养物质和缓冲污染物能力的重要指标,本文还构建了一种基于径向基函数神经网络的土壤传递函数,用于定量分析不同地区、不同土层的土壤CEC,该复合神经网络模型在大规模数据拟合中具有优越性。
In environmental pollution control, the degradation of contaminants are carried out by the cooperation of microbes, and it is an important approach for studying the contaminant degradation process to rapidly and sensitively trace, monitor and indentify the contaminants and the microbial community population, functional activities, variety of metabolites, and etc. in their degradation. Biosensing technology is a new approach for rapid, real-time and on-line detection of analytes based on biometric identification, which has the advantages of high sensitivity, specificity, rapidity, portability and capacity for real-time and on-line detection in complex system in comparison with conventional analytical methods, and provides a new technical platform for the analysis and measurement of contaminants and various biological components or metabolites in relative degradation. It is very significant for the development of environmental detection technology to systematically construct a detection system of biosensing technology in environmental pollution control, to provide timely and accurate biological information for pollution control process, and to solve the real-time and on-line monitoring problems in environmental science and engineering study, and to ultimately realize automation.
This dissertation developed a series of biosensing detection methods, for highly sensitive detection of trace contaminants and their degradation metabolites in the environment, and took the composting system for example to construct a set of novel methods based on biosensing technology for the detection of contaminants and the dynamic changing of relative enzymes, microbial community population, functional genes and metabolites in complex environment, which overcame the limitation of conventional analytical methods applied in environmental pollution control in the aspects of real-time and on-line detection, and etc., and favored the thorogh investigation of the microbial mechanism in waste composting process and efficient instruction of the microbial inoculation and composting technique renovation. This dissertation is composed of four sections.
The first section describes the research on highly sensitive biosensing detection technology for trace hazardous contaminants and their metabolites in the environment. The enzymes were immobilized on the electrodes through ferrocene-doped electropolymerization, self-assembly by concanavalin A, and other techniques to develop an inhibition-based glucose oxidase sensor and an inhibition-based horseradish peroxidase sensor, for the detection of trace Cr(VI) and Hg(II) in soil, and the detection of phenylhydrazine in Xiangjiang River, respectively, which obtained high sensitivity, reversibility, stability and selectivity. Both of the lower detection limits for Cr(VI) and Hg(II) were 0.49μg L~(-1), and that for phenylhydrazine was 1.7×10~(-6) M. The experimental data obtained by enzyme sensors were used to deduce the kinetic models of the catalysis of H_2O_2 and hydroquinone by horseradish peroxidase and the inhibition by phenylhydrazine, and to carry out the model simulation and parameter estimation. Picloram, a kind of organo-chlorinated pesticide, was conjugated with bovine serum albumin as an artificial antigen which was injected into New Zealand white rabbits to obtain purified antibody. An electrochemical immonosensor based on chitosan/gold nanoparticles (Au NPs) composite membrane was developed for the detection of trace picloram in rice, lettuce, and paddy field water. The immunomenbrane has good selectivity, high sensitivity, disposability, and good reproducibility for fabrication in batch. The lower detection limit was 5 ng mL~(-1). A sensoring chip was developed based on the ubiquitous reductivity of phenols, which utilized the Au NPs immobilized on the glass slide as the seeds to catalyze the enlargement of Au NPs by the phenol reduction, and then the phenol concentration could be detected through absorption spectroscopy change. The lower detection limit was 7×10~(-6) M. This method was convenient, low-cost, and highly sensitive. A laccase sensor based on magnetic nanoparticles-laccase conjugates was developed utilizing laccase-catalyzed redox of catechol and the magnetic separation, which was used to detect trace catechol in complex composting system with the concentration as low as 7.5×10~(-7) M.
The second section describes the trace of microbial degrading enzyme activities and biosurfactants in composting system using biosensing technology. Some enzyme activities in composting system are important maturity indexes. An electrochemical dihydronicotinamide adenine dinucleotide (NADH) sensor based on the catalytic growth of Au NPs on electrode was developed with fast response and high sensitivity, which could detect NADH in acidic buffers with the concentration as low as 2.5×10~(-7) M, and maintained the accuracy in 3 months. A sensoring chip was developed based on the catalytic growth of Au/Ag core/shell nanoparticles by NADH reduction, and then NADH concentration could be detected through absorption spectroscopy change with the lower detection limit of 1.56×10-5 M. An electrochemical enzyme sensor for rapid and simultaneous detection of the lignin-degrading peroxidase activities was developed based on the substrate redox catalyzed by lignin peroxidase (LiP) and manganese peroxidase (MnP). LiP and MnP activities could be detected in the range of 8.14~29.79 U L~(-1) and 0.085~1.37 U L~(-1) , respectively. This assay is more rapid, sensitive and precise than conventional spectrophotometric assays, free from interference of turbidity and UV- and visible-light-absorbing substances in compost extract. Rhamnolipid, a biosurfactant secreted by the common bacteria in compost, Pseudomonas aeruginose, in fermentation metabolism, can improve the microenvironment in compost. The artificial antigen and antibody of rhamnolipid were fabricated, and a chromogenic enzyme-linked immuno test paper for dirhamnolipid based on 3,3′-diaminobenzidine (DAB) was developed, which could detect dirhamnolipid with the concentration as low as 0.05 mg L~(-1) by unaided eye. This method was convenient, fast, and reproducible.
The third section focuses on the trace of microbial community dynamics and the functional genes in composting system based on genosensing technology. Some high- efficiency contaminant degrading microbes contain relative functional genes. LiP is a key enzyme in lignin degradation by fungi. The gene probes for lip in Phanerochaete chrysosporium was designed and synthesized, and an enzyme-linked electrochemical DNA sensor based on the sandwich hybridization recognition of lip was developed. This sensor, combined with polymerase chain reaction (PCR) and restriction enzyme digestion, succeeded in measuring lip gene fragments from Phanerochaete chrysosporium genome extraction samples with the lower detection limit of 0.03 nM. It could discriminate satisfactorily against mismatched nucleic acid samples of similar lengths. Cellobiohydrolase (CBH) is a key enzyme in cellulose degradation. The gene probes for cbh2 in Trichoderma reesei was designed and synthesized, and magnetic Au/Si/Fe core/shell nanoparticles were fabricated by catalytic growth of Au NPs on the surface. An electrochemical nano DNA sensor based on the competitive hybridization recognition of cbh2 was developed, with the lower detection limit of 10-13 M. Another cbh2 genosensor was developed by the deposition of multi-walled carbon nanotubes-poly(1-ethyl-(3-dimethyllaminopropyl)carbodiimide hydrochloride) complex membrane on electrode surface. The experimental parameters were optimized, and the genosensor was characterized by scanning electron microscopy (SEM) and electrochemistry. The 16S rDNA/rRNA sequences of bacteria are highly conservative, and can be used for species identification. An in vitro 16S rRNA quantification method for Pseudomonas aeruginose based on molecular beacon was developed for the detection of 16S rRNA from total RNA isolation samples. The hybridization reaction required 30 min, and the method had high specificity, free from cross-pollution by nucleic acid, and required no isolation or purification procedures for bacteria total RNA.
The fourth section focused on the data resolution of quantification of contaminants and relative degradation capabilities in complex environment system. The complex components in real environmental samples, various interferents, and coexistence of multiple analytes take uncertainty to environmental analysis. Due to the good performance of artificial neural networks (ANNs) in signal resolution, this dissertation combined ANNs with electrochemical enzyme biosensing technology in the electrochemical detection of the lignin-degrading peroxidase activities in Phanerochaete chrysosporium inoculated compost, and the quantitive analysis of catechol by laccase sensor. These methods were more accurate, sensitive and robust than linear regression models. Cation exchange capacity (CEC) is an important index of the soil buffering capacity to maintain cationic nutrients and pollutants against leaching to the subsurface layers. A pedotransfer function based on radial basis function neural networks (RBFN) was developed and applied into the estimation of CEC different regions and different horizons, from soil physico-chemical properties, which showed superiority in large scale data simulation.
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