rep-PCR基因指纹图微生物源追踪方法建立的研究

[目的]建立重复序列聚合酶链反应(rep-PCR)微生物源追踪方法,应用于淮河流域某水库的粪便污染来源追踪.[方法]采集已知来源的人和动物粪便标本以及水样标本,分离并确认指示菌大肠杆菌,以BOXA1R为引物进行PCR扩增;用Bionumerics 4.0软件对rep-PCR基因指纹图进行判别分析和多元方差分析并计算各源种类的正确归类率.[结果]2分类、4分类和10分类的正确归类率分别为:85.60%、79.20%和70.98%.判别分析和多元方差分析结果显示rep-PCR基因指纹图能将已知源不同来源指示菌区分开.水样中主要粪便污染来源为猪、鸡和人.[结论]建立的rep-PCR微生物源追踪方法能较好地区分水体中指示菌的不同来源,该方法的建立为查找水体中粪便污染来源以及水体治理提供了新技术.     

水库水非点源粪便污染微生物源追踪法鉴定

目的应用细菌基因组重复序列PCR技术(rep-PCR)微生物源追踪方法对江苏省盱眙县桂五水库中粪便污染来源进行追踪。方法分别采集不同季节水库周边已知来源粪便标本,分离大肠埃希菌作为指示菌,建立已知污染源指示菌rep-PCR特征指纹库,用基因聚类分析软件计算平均正确归类率,进行判别分析和多元方差分析;同期采集水库水样,分离并确认指示菌,进行rep-PCR扩增,与已知污染源数据库进行对比,判断水样中指示菌污染来源。结果将已知源数据库分为2,3,4,5和9类时,平均正确归类率分别为89.19%,77.58%,76.69%,75.25%和70.92%;已知源数据库可区分指示菌的不同来源。对534株水库水样指示菌微生物源追踪结果显示,人、鸡、鸭、鹅、狗、猪、牛、羊和野生动物各占26.49%,14.74%,7.77%,5.78%,3.98%,7.97%,10.96%,8.76%和8.57%。结论桂五水库粪便污染来源种类繁多,其中人、鸡和牛为主要污染源;该方法为查找水体粪便污染来源及污染整改效果评估提供了新技术。     

应用不同微生物源追踪方法追踪水库中粪便污染来源

目的:用两种不同的微生物源追踪(Microbial source tracking,MST)方法对江苏省盱眙县桂五水库粪便污染来源进行追踪。方法:于春、夏、秋、冬4季分别采集水库周边已知来源粪便标本,分离大肠埃希菌并作为指示菌,分别建立已知源指示菌细菌基因组重复序列PCR(repetitive Extragenic Palindromic-Polymerase chain reaction,rep-PCR)特征指纹库和已知源指示菌抗生素敏感性(Antibiotic Resistance Analysis,ARA)数据库,并分别用统计分析及试验设计软件(JMP7.0软件)和基因聚类分析软件(Bionumerics 4.0软件)计算平均正确归类率(Average Rate of Correct Classification,ARCC),以检验各自的宿主来源区分效果。同期采集水样,膜过滤法分离并确认指示菌,分别进行rep-PCR扩增和ARA试验,并分别与已知源指示菌rep-PCR特征指纹库和ARA数据库进行统计学比对,判断桂五水库中粪便污染来源。结果:将已知源指示菌rep-PCR特征指纹库和ARA数据库分别分为2、...     

抗生素敏感性微生物源追踪方法建立

目的 建立抗生素敏感性微生物源追踪方法,以分析淮河流域某水库粪便污染来源.方法 采集水库周边已知来源粪便标本,分离指示菌,接种至含抗生素的培养基,筛选能区分不同来源指示菌的抗生素浓度,用YMP7.0软件进行判别分析检验效果.同时采集水样进行粪便污染来源追踪.结果 筛选的不同抗生素及其浓度能将已知来源指示菌正确归类率分别为93.05%(2分类)、85.75%(3分类)和78.53%(9分类).100株指示菌中有58株来自家畜,25株来自家禽,11株来自狗,4株来自人,2株来自野生动物.水样标本中主要的粪便污染来源为猪、牛、鸡,分别占水样分离指示菌总数的36%,17%和15%.结论 所筛选的抗生素浓度均能较好地区分指示菌的不同来源,该方法的建立可以为查找水体粪便污染来源以及水体治理提供参考与帮助.     

微生物源追踪技术在不同污染水体中的应用评价

目的建立南京秦淮河上游中山河和淮河流域桂五水库的微生物源追踪抗生素敏感性分析（antibiotic resistance analysis,ARA）数据库,追踪水体中的污染来源,探讨该方法在不同水体中追踪微生物污染源的应用价值。方法采集目标水体周边自然村中人、家畜、家禽等的粪便标本及生活和工业污水排放口直接排放的污水,分离并确认指示菌,建立已知源微生物源追踪数据库。按计划采集未知源水样,分离指示菌并使用JMP7．0软件进行污染源追踪及效果评价。结果秦淮河上游中山河水体污染源主要为工业及生活污水和狗的粪便污染。淮河流域桂五水库环境水污染源则主要为人和羊的粪便污染。结论微生物源追踪方法不仅可以应用于原生态水体,而且可以应用于受生活、工业双重污染水体的微生物污染源追踪,均能取得较好的效果。     

微生物源追踪技术在不同污染水体中的应用评价

目的建立南京秦淮河上游中山河和淮河流域桂五水库的微生物源追踪抗生素敏感性分析(antibiotic resistance analysis,ARA)数据库,追踪水体中的污染来源,探讨该方法在不同水体中追踪微生物污染源的应用价值。方法采集目标水体周边自然村中人、家畜、家禽等的粪便标本及生活和工业污水排放口直接排放的污水,分离并确认指示菌,建立已知源微生物源追踪数据库。按计划采集未知源水样,分离指示菌并使用J MP7.0软件进行污染源追踪及效果评价。结果秦淮河上游中山河水体污染源主要为工业及生活污水和狗的粪便污染。淮河流域桂五水库环境水污染源则主要为人和羊的粪便污染。结论微生物源追踪方法不仅可以应用于原生态水体,而且可以应用于受生活、工业双重污染水体的微生物污染源追踪,均能取得较好的效果。     

太湖水域微囊藻类毒素污染状况调查

目的：了解无锡太湖水域不同水体微囊藻类毒素(MC)污染现状。方法：用酶联免疫吸附(ELISA)法检测无锡太湖水域不同水样中MC含量。结果：7种水体中有6种检出MC，检出率为85．1％；20l份水样中，MC阳性58份，阳性率28．9％。阳性水样中MC含量均值为1437．8pg/L。所有阳性水样中以太湖水阳性率最高，为l00．0％。结论：无锡太湖水域MC污染严重，常规水处理不能将毒素完全去除，对人群健康己构成一定威胁。     

三氯化铁-聚偏氟乙烯膜滤器富集噬菌体方法的建立和评价

目的建立和评价基于三氯化铁-聚偏氟乙烯(FeCl3-PVDF)膜滤器富集自然水体中噬菌体的方法。方法基于絮凝浓缩原理, 利用铁离子絮凝结合膜过滤器建立从水样中回收噬菌体的方法。利用琼脂双层法测定噬菌体滴度、噬菌体荧光染色观察和实时荧光PCR反应等方法检测噬菌体的回收效率。采集不同来源的水体标本进行模拟实验评价富集效果, 同时以医院排出污水作为实际水样, 利用临床常见的耐药菌作为宿主指示菌, 进一步分析FeCl3-PVDF膜滤器富集方法对自然实际水样中噬菌体的富集效果。结果建立了铁离子浓度50 mg/L, 采用PVDF膜滤器富集自然水体中噬菌体的方法。该方法对噬菌体的回收率为93%～100%;在多功能显微镜下观察发现富集后水样的噬菌体明显增多, 酶标仪测定富集后水样荧光值约为富集前的13倍;对医院外排水实际水样浓缩处理后, 浓缩组和未浓缩组噬菌体的分离阳性率分别为23%和4%, 浓缩组荧光值为未浓缩组的2～24倍。结论 FeCl3-PVDF膜滤器方法可简便、高效快速地富集不同水体样本中噬菌体。     

引滦水源隐孢子虫和f2噬菌体消长规律研究

目的 探讨天津引滦水源原虫与病毒污染现状和消长规律。方法 根据引滦河道的排污、与其他水体交叉及其倒虹闸的分布情况确定采样监测点。分别用隐孢子虫和f2噬菌体表示水体受原虫和病毒污染的情况，水样通过浓集分离装置使隐孢子虫和f2噬菌体得到浓集，隐孢子虫经过固定、洗脱、悬浮和洗涤、染色，镜检计数；f2噬菌体滤液中加入Ecoli 285寄主菌液，恒温培养，观察计数。结果 各采样点隐孢子虫和f2噬菌体点次检出率分别为57．7％和63，9％，分别集中在春夏季和秋季。f2噬菌体在中上游较高，于桥水库和下游较低。结论 引滦水源已受原虫和病毒的污染。建议将引滦河道中极易受到污染的自然河道和明渠段改为暗渠输水方式，并加强引滦河道沿岸工农业和生活污染来源的监控。     

副溶弧菌染色体DNA指纹图及其质粒图谱研究

对不同来源，不同血清型的７１株副溶血弧菌染色体ＤＮＡ指纹图及其质粒图谱进行了分析研究。结果表明：不同血清型，不同来源菌株的ＤＮＡ指纹图有显著的不同，相同血清型而来源不同的菌株其ＤＮＡ指纹图亦有区别，来自同一起暴发的同一克隆菌株的ＤＮＡ指纹图则极为相似，而且该ＤＮＡ指纹图具有极好的稳定性和精确性。质粒分析显示，其检出率为８７．３２％，且图谱呈多样性，但未发现质粒分布与血清型及来源的相关性。     

Assessment of statistical methods used in library-based approaches to microbial source tracking

Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.     

Population dynamics and genetic variability of Escherichia coli in a mixed land-use watershed

Better understanding of Escherichia coli population dynamics and genetic variability in the secondary habitat is essential to improve fecal contamination monitoring and contamination pathway characterization. In this study, water samples were collected monthly over a one-year period at eight locations in the Catoma Creek watershed, a mixed land-use watershed in Central Alabama. E. coli concentrations varied from 17 to 12,650 CFU/100 ml and were well correlated with stream flow rates. Repetitive sequence-based PCR DNA fingerprinting was used to generate 271 unique DNA fingerprint patterns from 502 E. coli isolated from water samples. Cluster analysis showed an overall similarity of 32.8% across all DNA fingerprints. Multivariate analysis of variance (MANOVA) showed that E. coli genotypes had a tendency to cluster according to season and stream flow rather than sampling sites. MANOVA of a subset of data within a given season and flow rate, however, revealed some geographical differentiation between urban and rural sampling sites. The results indicate that genetic diversity of E. coli populations was not only high in the secondary habitat but also varied with season, flow conditions and, to a lesser extent, sampling location. To our knowledge, this is the first report relating E. coli genotype to stream flow.     

Phenotypic library-based microbial source tracking methods: efficacy in the California collaborative study

As part of a larger microbial source tracking (MST) study, several laboratories used library-based, phenotypic subtyping techniques to analyse fecal samples from known sources (human, sewage, cattle, dogs and gulls) and blinded water samples that were contaminated with the fecal sources. The methods used included antibiotic resistance analysis (ARA) of fecal streptococci, enterococci, fecal coliforms and E. coli; multiple antibiotic resistance (MAR) and Kirby-Bauer antibiotic susceptibility testing of E. coli; and carbon source utilization for fecal streptococci and E. coli. Libraries comprising phenotypic patterns of indicator bacteria isolated from known fecal sources were used to predict the sources of isolates from water samples that had been seeded with fecal material from the same sources as those used to create the libraries. The accuracy of fecal source identification in the water samples was assessed both with and without a cut-off termed the minimum detectable percentage (MDP). The libraries (approximately 300 isolates) were not large enough to avoid the artefact of source-independent grouping, but some important conclusions could still be drawn. Use of a MDP decreased the percentage of false-positive source identifications, and had little effect on the high percentage of true-positives in the most accurate libraries. In general, the methods were more prone to false-positive than to false-negative errors. The most accurate method, with a true-positive rate of 100% and a false-positive rate of 39% when analysed with a MDP, was ARA of fecal streptococci. The internal accuracy of the libraries did not correlate with the accuracy of source prediction in water samples, showing that one should not rely solely on parameters such as the average rate of correct classification of a library to indicate its predictive capabilities.     

Determining the source of fecal contamination in recreational waters

Public health departments bear the responsibility for investigating recreational water-associated disease outbreaks. Tracking the source of the disease is often problematic, however, because routine monitoring of recreational waters (for bacterial counts) is not source specific. The intent of the project reported here was to monitor Escherichia coli levels in a small recreational lake in Iowa and to determine their source. The authors monitored water samples for E. coli and used phenotypic methods to analyze multiple samples of lake water, well water, and known fecal sources. Moderate to high levels of E. coli were found in lake water samples from the swimming area throughout the summer. The highest levels of E. coli were found after rainfall events in both lake water samples and samples taken from monitoring wells. Phenotypic analyses indicated that likely sources of E. coli in the lake included both human and wildlife (goose) fecal material. The authors also found that the phenotype used to characterize E. coli isolated from geese frequenting this lake could not be used to characterize E. coli isolated from geese in a neighboring watershed. Identifying the source of fecal material will help authorities implement the proper preventive measures to avoid fecal contamination of the lake in the future.     

Molecular Detection and Identification of Zoonotic Microsporidia Spore in Fecal Samples of Some Animals with Close-Contact to Human

Background: Microsporidia species are obligatory intracellular agents that can infect all major animal groups including mammals, birds, fishes and insects. Whereas worldwide human infection reports are increasing, the cognition of sources of infection particularly zoonotic transmission could be helpful. We aimed to detect zoonotic microsporidia spore in fecal samples from some animals with close – contact to human. Methods: Overall, 142 fecal samples were collected from animals with closed-contact to human, during 2012-2013. Trichrome – blue staining were performed and DNA was then extracted from samples, identified positive, microscopically. Nested PCR was also carried out with primers targeting SSU rRNA gene and PCR products were sequenced. Results: From 142 stool samples, microsporidia spores have been observed microscopically in 15 (10.56%) samples. En. cuniculi was found in the faces of 3 (15%) small white mice and 1 (10%) laboratory rabbits(totally 2.81%). Moreover, E. bieneusi was detected in 3 (10%) samples of sheep, 2 (5.12%) cattle, 1 (10%) rabbit, 3 (11.53%) cats and 2 (11.76%) ownership dogs (totally 7.74%). Phylogenetic analysis showed interesting data. This is the first study in Iran, which identified E. bieneusi and En. Cuniculi in fecal samples of laboratory animals with close – contact to human as well as domesticated animal and analyzed them in phylogenetic tree. Conclusion: E. bieneusi is the most prevalent microsporidia species in animals. Our results can also alert us about potentially zoonotic transmission of microsporidiosis.Key Words: Laboratory animals, Enterocytozoon bieneusi, Encephalitozoon cuniculi, Zoonotic transmission     

Use of viral pathogens and indicators to differentiate between human and non-human fecal contamination in a microbial source tracking comparison study

Assays for the detection and typing of adenoviruses, enteroviruses and F+ specific coliphages were performed on samples created as part of a national microbial source tracking methods comparison study. The samples were created blind to the researchers, and were inoculated with a variety of types of fecal contamination source (human, sewage, dog, seagull and cow) and mixtures of sources. Viral tracer and pathogen assays demonstrated a general ability to discriminate human from non-human fecal contamination. For example, samples inoculated with sewage were correctly identified as containing human fecal contamination because they contained human adenovirus or human enterovirus. In samples containing fecal material from individual humans, human pathogen analysis yielded negative results probably because the stool samples were taken from healthy individuals. False positive rates for the virus-based methods (0-8%) were among the lowest observed during the methods comparison study. It is suggested that virus-based source tracking methods are useful for identification of sewage contamination, and that these methods may also be useful as an indication of the public health risk associated with viral pathogens. Overall, virus-based source tracking methods are an important approach to include in the microbial source tracking 'toolbox'.     

LGT模型鼠血清及其癌组织提取液中蛋白质指纹比较研究

目的 分析比较LGT模型鼠血清与其肿瘤组织中危重患者预警（LGT-Lost Goodwill Target）蛋白指纹的表达特征.方法 取4～5周龄雌性小鼠1只,接种S180肿瘤细胞悬液（02 ml/只）,建立小鼠S180肉瘤动物模型.肿瘤细胞株S180以腹水瘤形式在昆明（KM）小鼠体内传代,传代后第8天,无菌条件下抽取腹水并以生理盐水稀释,调整细胞密度 2×107/ml,制成肿瘤悬液,置于冰浴备用.将制备好的肿瘤细胞悬液以每只02 ml于昆明小鼠（10只）右腋下的皮下接种造模.建立小鼠S180肉瘤动物模型.随机分为造模组（A组,5只）及对照组（B组,5只）,肿瘤长至05 cm大小时,开始给予造模组（A组）腹腔注射顺铂52 mg/kg,连用4 d;同天给予空白对照组（B组）腹腔注射等计量生理盐水,连用4 d.于造模结束后第3天两组小鼠全部摘眼球取血,分离血清进SELDI 检测,解剖造模组小鼠,分别取瘤组织、瘤旁组织及正常组织各1 g,匀浆,抽取上清液行SELDI检查.并利用Biomarker Wizard 软件对各组血清及瘤组织、瘤旁组织及正常组织匀浆液的蛋白质组指纹图谱进行比较分析.结果 （1）A组血清LGT蛋白质组指纹阳性,B组血清LGT蛋白质指纹阴性.造模成功,A组可行进一步分析.（2）A组血清与癌组织液LGT相关蛋白质指纹图谱：有8个蛋白质差异有统计学意义（P〈005）.其m/z分别为1993、2009、2028、2217、2502、8696、9940、10145.（3）A组血清与癌旁组织液LGT相关蛋白质指纹图谱：有7个蛋白质差异有统计学意义（P〈005）.其m/z分别为1077、1211、1994、2009、2030、2081、11 817.（4）A组血清与正常组织液LGT相关蛋白质指纹图谱：有5个蛋白质差异有统计学意义（P〈005）.其m/z分别为1004、1994、2010、2030、2217.结论 本结论认为造成肿瘤恶化而导致死亡发生的因素极有可能不单独在肿瘤本身,而在于周围环境.各个部位所表达的蛋白质指纹也不一致,可以是因各组织蛋白质代谢不同所致.但其与LGT的关系有待进一步研究.