Microbiome identification in bulk water and biofilms in drinking water networks Culture-dependent methods, routinely used by water utilities to assess the microbiological quality

LIST OF ABBREVIATIONS

2 LITERATURE REVIEW

2.4 BIOFILMS IN DRINKING WATER DISTRIBUTION NETWORKS

2.4.2 Microbiome identification in bulk water and biofilms in drinking water networks Culture-dependent methods, routinely used by water utilities to assess the microbiological quality

of drinking water, present shortcomings such as underestimation of the amount and diversity of the microbial community (Theron and Cloete, 2000). Heterotrophic bacterial counts only represent a limited fraction of the whole microbial community (Douterelo et al., 2014a; Ren et al., 2015), when used to estimate bacterial loads in water samples. Moreover only less than 5% of the biomass is present in the water phase and 95% is living in the biofilm phase (Flemming et al., 2002). Current drinking water quality standards rely on culture-dependent techniques to quantify specific pathogenic organisms (e.g., E. coli, Enterococci, Coliform bacteria) (UK Parliament, 2000;

Ministerio de la Protección Social and Ministerio de Ambiente Vivienda y Desarrollo Territorial, 2007) and heterotrophic bacteria in bulk water. Then, biofilms are only explored for research purposes and, to date, they have not been included in routine operative and regulatory plans by drinking water operators and agencies, respectively.

Chapter 2. Literature review 26

Disinfection by-product formation from biofilm chlorination in drinking water pipes Carolina Montoya Pachongo. School of Civil Engineerin

Recently, water microbiology research is focused on developing and applying culture-independent practices in order to improve the diagnostic of microbiological quality of water. Therefore, molecular analysis is being used for studying the microbial community in bulk water and biofilms. According to Douterelo et al. (2014a), studying microorganisms in a DWDN allows improving knowledge about how abundant they are, which types of microorganisms are present, how their activities shape the environment or influence other organisms, including any possible effects on human health, and how the environment influences the structure and functions of the microorganisms present.

Douterelo et al. (2014a) also described the classification of microbiological techniques used to study microbial communities according to their purpose and nature: culture-based methods, microscopy, polymerase chain reaction (PCR), molecular techniques, and quantification of metabolism by-products. In particular, molecular techniques include cloning and sequencing, metagenomics, and next generation sequencing. The molecular techniques are applied to study the microbial community composition and involve the extraction of nucleic acid, followed by PCR amplification of “marker genes” to obtain taxonomic information. The most commonly used marker gene in microbiological research is the ribosomal RNA (rRNA) gene, 16S rRNA for prokaryotes and 18S rRNA for eukaryotes (Douterelo et al., 2014a).

According to Douterelo et al. (2014a), cloning and sequencing is the conventional and more widespread genomic approach used when detailed and accurate phylogenetic information from environmental samples is required. After DNA extraction and amplification of the rRNA gene with suitable primers, clone libraries using sequencing vectors must be constructed (Rondon et al., 2000). Selected clones are then sequenced (Sangerbased) (Sanger et al., 1977) and the nucleotide sequence of the rRNA gene retrieved, allowing estimates of the microbial diversity in the samples by comparison with sequences available in databases (e.g., GenBank, EMBL and Silva). The generation of DNA clone libraries followed by sequencing has being extensively applied in drinking water microbiology. The need to analyse the extensive amount of data related to sequence reads from environmental samples led to the development of the bioinformatics field, which involves software and analysis tools (Douterelo et al., 2014a).

Understanding of microorganisms in DWDNs has been developed by sampling water and biofilms.

In relation to water sampling, guidelines from environmental and regulatory agencies exist for sampling methods and interpretation of results of traditional and well-known laboratory parameters.

For instance, there are several International Organization for Standardization (ISO) standards for detection and enumeration of faecal indicator organisms in water, which are listed in WHO (2017).

The environmental agency of the United States has designed a guide for sampling biological contaminants in bulk water (USEPA, 2016b). In the European territory, the standard ISO 19458 is

Chapter 2. Literature review 27

Disinfection by-product formation from biofilm chlorination in drinking water pipes

recommended for compliance samples for microbiological parameters (European Union, 2015).

Locally, the UK Environment Agency also offers guidelines for sampling drinking water to test microbiological parameters (Environment Agency, 2010).

However, if molecular analysis and/or proteomics/metabolomics-based approaches are desired, there is not enough guidance about the minimal representative sampling volume required to capture the complete microbiome in a DWDN. Therefore, comparisons are difficult to make. In relation to biofilm sampling, two approaches have been used to study biofilms in DWDNs such as scrapping attached biofilm from cut-out pipes or directly from devices inserted into the pipes. Both methods can be used for sampling in real-scale or laboratory DWDNs (Douterelo et al., 2014a).

Pipe cut-out sampling are labour-intensive, then it is common to take advantage of the leakage repairs or pipe replacement activities to collect pipe samples. Due to the random nature of leakages location, the arbitrary selection of sampling points according to the scope of the study is limited.

Therefore, the sampling campaign may last several months in order to cope with all the selected criteria. Otherwise, the study must be based on few variables in order to find the balance time-scope. On the other hand, excavation and cutting processes often lead to concerns with contamination and representative sampling and preservation of the physical integrity of the sample (Douterelo et al., 2014a). The use of devices, commonly coupons, that can be deployed repeatedly either within a pilot-scale test facility or in an operational DWDN, allows the study of biofilm dynamics over time in relation to changing abiotic and biotic factors in situ. According to Douterelo et al. (2014a), commonly the main limitation of some of these devices is that they distort hydraulic conditions in pipes and, in most cases, shear stress and turbulence regimes are different from those expected in real pipes, artificially influencing the way biofilms develop.

Recent studies applying molecular analysis in DWDNs supplied by surface water, either simulated or real-scale DWDNs, are summarized in Table 2-2. These studies were developed mainly in temperate-climate areas; with water treated by different treatment processes, including chlorine and chloramines as disinfectants. Samples were collected from several pipe materials such as polyvinyl chloride (PVC), HDPE, ductile and cast iron, cement, copper. Pipe material was the variable more frequently tested among these studies. Results reported in every investigation found Proteobacteria as the predominant phylum in biofilm and bulk water samples. Particularly, research in USA indicates that other phyla also dominating include Cyanobacteria and Actinobacteria (Holinger et al., 2014; Kelly et al., 2014). By comparison, bacterial class, family and genera exhibit more variety of the microbial communities in the studied samples.

Chapter 2. Literature review 28

Disinfection by-product formation from biofilm chlorination in drinking water pipes Carolina Montoya Pachongo. School of Civil Engineering

Table 2-2. Summary of bacterial composition in DWDNs supplied by surface water sources Reference

and study country

Type of

system Water treatment Sampling point

Composition of bacterial communities in pipelines (dominant communities and relative abundance -RA-)

Phyla Class Genera

Tap Water Proteobacteria

(27-41%)

HDPE NS Proteobacteria

Gammaproteobacteria (6-87%) Betaproteobacteria (4-60 %)

Pseudomonas (20-65%)

Water Alphaproteobacteria (59-88 %)

Methylocistis

SFILT, chlorination Tap Cold

water NS NS Proteobacteria

Chapter 2. Literature review 29

Disinfection by-product formation from biofilm chlorination in drinking water pipes

Reference and study country

Type of

system Water treatment Sampling point

Composition of bacterial communities in pipelines (dominant communities and relative abundance -RA-)

Phyla Class Genera

buildings Water NS NS Cyanobacteria

Actinobacteria

disinfection Pipelines Biofilm Ductile iron 40-45 Proteobacteria

Actinobacteria Gammaproteobacteria

28 months Proteobacteria Alphaproteobacteria NS Sun et al.

Pipelines Biofilm CI ≈ 20 Proteobacteria (40-60%)

Chapter 2. Literature review 30

Disinfection by-product formation from biofilm chlorination in drinking water pipes Carolina Montoya Pachongo. School of Civil Engineering

Reference and study country

Type of

system Water treatment Sampling point

Composition of bacterial communities in pipelines (dominant communities and relative abundance -RA-)

Phyla Class Genera

pipelines Biofilm Cement, iron

and PVC Biofilm age:

steal and PVC NS Proteobacteria

(58.6%) Gammaproteobacteria (34.0%) NS

Lührig et al.

plastic 4-10 Proteobacteria

(45-87 %) Alphaproteobacteria (70-85 %) NS Pipelines Cast iron 45-103 Proteobacteria

(58-86 %)

Gammaproteobacteria (60-65%) Betaproteobacteria (35%)

Alphaproteobacteria (35 %) NS

Mahapatra

Chapter 2. Literature review 31

Disinfection by-product formation from biofilm chlorination in drinking water pipes

Reference and study country

Type of

system Water treatment Sampling point

Composition of bacterial communities in pipelines (dominant communities and relative abundance -RA-)

Phyla Class Genera

PVC 11-13 Proteobacteria (71-99%)

Polycarbonate Biofilm age:

3-18

Faucets Water NS NS Proteobacteria

(> 98%) Betaproteobacteria (92.2%) Alphaproteobacteria (76.6%)

Chapter 2. Literature review 32

Disinfection by-product formation from biofilm chlorination in drinking water pipes Carolina Montoya Pachongo. School of Civil Engineering

Reference and study country

Type of

system Water treatment Sampling point

Type of sample

Pipe material

Pipe age (Years) / Biofilm

age

Composition of bacterial communities in pipelines (dominant communities and relative abundance -RA-)

Phyla Class Genera

Ductile iron Gammaproteobacteria (47.95%)

Actinobacteria (13.88%) Betaproteobacteria (11.95%)

Enhydrobacter (33.84%)

Propionibacterium (8.08%)

Acinetobacter (5.59%) SS

Betaproteobacteria (27.53%) Flavobacteria (25.15%) Verrumicrobiae (13.4%) Cytophagia (12.04%)

Flavobacterium (24.76%)

Arcicella (12.03%) Acidovorax (8.98%) Water -- -- Proteobacteria Betaproteobacteria (95.5%) Methylophilus

(95.41%)

Chapter 2. Literature review 33

Disinfection by-product formation from biofilm chlorination in drinking water pipes

In document Disinfection by-product formation from biofilm chlorination in drinking water pipes (Page 49-57)