Heterotrophic plate count monitoring of treated drinking water in the UK: a useful operational tool

Sartory, D. P.

doi:10.1016/j.ijfoodmicro.2003.08.006

Cited by 63 publications

(36 citation statements)

References 7 publications

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“…However, 2, 3, 5 and 7-day HPCs can be used as an indicator of unexpected "change" in general water quality, that may trigger more detailed investigations [17]. According to Sartory [18]: "The number of bacteria enumerated at 20-22˝C provides some indication of (1) the amount of food substance available for bacterial nutrition and (2) the amount of soil, dust and other extraneous material that had gained access to the water. The HPC at 37˝C affords more information relating to potentially dangerous pollution, as the organisms developing at this temperature are chiefly those of soil, sewage, or intestinal origin.…”

Section: Hypotheses On Factors Influencing Microbial Water Quality Datamentioning

confidence: 99%

Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps

et al. 2016

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Understanding and managing water quality in drinking water distribution system is essential for public health and wellbeing, but is challenging due to the number and complexity of interacting physical, chemical and biological processes occurring within vast, deteriorating pipe networks. In this paper we explore the application of Self Organising Map techniques to derive such understanding from international data sets, demonstrating how multivariate, non-linear techniques can be used to identify relationships that are not discernible using univariate and/or linear analysis methods for drinking water quality. The paper reports on how various microbial parameters correlated with modelled water ages and were influenced by water temperatures in three drinking water distribution systems.

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Section: Hypotheses On Factors Influencing Microbial Water Quality Datamentioning

confidence: 99%

Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps

et al. 2016

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“…In general, heterotrophic plate counts (HPC) are used to assess the overall bacterial quality of drinking water (32). However, the majority of bacterial cells in natural communities are either nonculturable by current cultivation methods or are present in a viablebut-nonculturable state (24,39).…”

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confidence: 99%

Composition and Dynamics of Bacterial Communities of a Drinking Water Supply System as Assessed by RNA- and DNA-Based 16S rRNA Gene Fingerprinting

Eichler

Christen

Höltje

et al. 2006

Appl Environ Microbiol

188

174

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Bacterial community dynamics of a whole drinking water supply system (DWSS) were studied from source to tap. Raw water for this DWSS is provided by two reservoirs with different water characteristics in the Harz mountains of Northern Germany. Samples were taken after different steps of treatment of raw water (i.e., flocculation, sand filtration, and chlorination) and at different points along the supply system to the tap. RNA and DNA were extracted from the sampled water. The 16S rRNA or its genes were partially amplified by reverse transcription-PCR or PCR and analyzed by single-strand conformation polymorphism community fingerprints. The bacterial community structures of the raw water samples from the two reservoirs were very different, but no major changes of these structures occurred after flocculation and sand filtration. Chlorination of the processed raw water strongly affected bacterial community structure, as reflected by the RNA-based fingerprints. This effect was less pronounced for the DNA-based fingerprints. After chlorination, the bacterial community remained rather constant from the storage containers to the tap. Furthermore, the community structure of the tap water did not change substantially for several months. Community composition was assessed by sequencing of abundant bands and phylogenetic analysis of the sequences obtained. The taxonomic compositions of the bacterial communities from both reservoirs were very different at the species level due to their different limnologies. On the other hand, major taxonomic groups, well known to occur in freshwater, such as Alphaproteobacteria, Betaproteobacteria, and Bacteroidetes, were found in both reservoirs. Significant differences in the detection of the major groups were observed between DNA-based and RNA-based fingerprints irrespective of the reservoir. Chlorination of the drinking water seemed to promote growth of nitrifying bacteria. Detailed analysis of the community dynamics of the whole DWSS revealed a significant influence of both source waters on the overall composition of the drinking water microflora and demonstrated the relevance of the raw water microflora for the drinking water microflora provided to the end user.

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“…하지만, 종속영양세균수가 수 질의 변동을 반영하는 조작적 수단(operational tool)이 됨은 다 양한 연구에서 지속적으로 확인된다 (Sartory, 2004) 종속영양세균수를 레지오넬라균 오염도 지표로 사용함에 있 어 고려될 수 있는 단점은 종속영양세균수가 개별 조사별로 다 양한 방법으로 측정된다는 점이다 (Reasoner, 2004). 배지의 종 류, 배양온도, 배양시간, 접종방법 등에서 여러 가지 선택가능성 이 있기 때문이다.…”

Section: 주로 폐렴과 폰티악증 증상으로 발병하는 레지오넬라증은unclassified

Meta-Analysis of Risk Factors for Contamination of Environmental Waters by Legionella

Zo¹

2013

The Korean Journal of Microbiology

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To identify risk factors for Legionella contamination, water quality variables routinely measured in examination of natural and city waters were meta-analyzed for significance of correlation to Legionella incidences. For evaluation of abundance of Escherichia coli as a risk factor, which is currently used as an indicator of Legionella contamination in an official guideline in Korea, odds ratio (OR) of above-cutoff total coliform counts for Legionella presence/absence was used as the effect size in the meta-analysis. The OR was estimated as 1.05 (0.36-3.12, 95% CI), and the probability of having identical odds reached 0.92. Also, ORs from individual studies showed significant heterogeneity (P=0.008), which contributed to 63% of total variance of the ORs. In the case of heterotrophic plate count (HPC), the OR for Legionella presence/absence was 2.72 (2.04-3.63) with highly significant deviation from identical odds (P<0.0001). ORs from different studies were seemingly homogeneous (Qdf=8=12.7, P=0.12). Turbidity and concentrations of chlorine, iron ion and cupper ion were other routine variables that could be considered as risk factors. However, statistical measures from different studies were not uniform enough to develop an appropriate effect size while the number of studies reporting the variables was also small (3-5). In conclusion, HPC appeared to be appropriate as indicator of Legionella contamination, rather than fecal bacteria contamination. HPC may imply abundance of habitats (amoebas and biofilms) of Legionella in water. This result warrants further studies for standardizing protocols and cutoff values to infer Legionella risks from HPC.

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Heterotrophic plate count monitoring of treated drinking water in the UK: a useful operational tool

Cited by 63 publications

References 7 publications

Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps

Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps

Composition and Dynamics of Bacterial Communities of a Drinking Water Supply System as Assessed by RNA- and DNA-Based 16S rRNA Gene Fingerprinting

Meta-Analysis of Risk Factors for Contamination of Environmental Waters by Legionella

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