| Literature DB >> 35478887 |
Wei Zhou1,2, Weiying Li1,2, Jiping Chen1, Yu Zhou1, Zhongqing Wei3, Longcong Gong4.
Abstract
The prevalence of microorganisms in full-scale water supply systems raises concerns about their pathogenicity and threats to public health. Clean tap water is essential for public health safety. The conditions of the water treatment process from the source water to tap water, including source water quality, water treatment processes, the drinking water distribution system (DWDS), and building water supply systems (BWSSs) in buildings, greatly influence the bacterial community in tap water. Given the importance of drinking water biosafety, the study of microbial diversity from source water to tap water is essential. With the development of molecular biology methods and bioinformatics in recent years, sequencing technology has been applied to study bacterial communities in full-scale water supply systems. In this paper, changes in the bacterial community and the influence of each treatment stage on microbial diversity in full-scale water supply systems are classified and analyzed. Microbial traceability analysis and control are discussed, and suggestions for future drinking water biosafety research and its prospects are proposed. This journal is © The Royal Society of Chemistry.Entities:
Year: 2021 PMID: 35478887 PMCID: PMC9037190 DOI: 10.1039/d1ra03680g
Source DB: PubMed Journal: RSC Adv ISSN: 2046-2069 Impact factor: 4.036
Comparison of four generation sequencing technologies
| First-generation sequencing technology | Next-generation sequencing technology | Third-generation sequencing technology | Fourth-generation sequencing technology | |
|---|---|---|---|---|
| Characteristics | Dideoxy chain termination method | Sequencing by synthesis | Single-molecule sequencing | Nanopore sequencing |
| Read length | ∼1000 bp | 50–300 bp | 8–12 kb | ∼100 kb |
| Throughput | Low | High | High | High |
| Instrument time | Long | Short | Short | Short |
| Relative cost | High | Relatively low | Low | Low |
| Advantage | Long read length and high accuracy | High throughput, accuracy, speed, and output | Long read length, high throughput, and high speed | Long read length, high throughput, low cost, high speed, simpleness on sample preparation and analysis |
| Disadvantage | Low throughput and long instrument time | Short read length | Relatively low accuracy | Relatively low accuracy |
| Represented platforms | ABI | Illumina | Pacbio | Nanopore |
Fig. 1Timeline and comparison of commercial HTS instruments and costs since 2003. (A plot of commercial release dates versus machine output per run are shown. For MinION, output from an 18 hour run was used; for MGISEQ-17, output from a one-day run was used. Different dot colours indicate different companies.).
Fig. 2The annual increasing number of publications with the topics of “water & bacterial community” and “drinking water & bacterial community” in Web of Science (as of July 1st, 2021).
The microbial diversity of water sources analyzed by sequencing technology
| Factors | Impacts on drinking water microbiome | Ref. |
|---|---|---|
| Biological effects | ✓ Different water sources have different microbial community compositions, resulting in different bacterial communities in the final tap water |
|
| ✓ The dominant microbial composition may be similar in different water sources, but the abundances may vary | ||
| Chemical and physical effects | ✓ Temperature, seasonality seasonal, pH, electrolyte type, salinity, dissolved particles, dissolved oxygen (DO), C/N ratio, total nitrogen (TN), total phosphorus (TP), and COD have been verified to influence the composition of the microbial community in drinking water |
|
| ✓ | ||
| ✓ The bacterial diversity was positively correlated with CODMn, turbidity, and pH | ||
| ✓ The bacterial diversity in water source was higher in wet season than in dry season | ||
| Organics effects | ✓ Organic nutrients (such as assimilable organic carbon) or DBPs precursors of organic matter have positive effect on the bacteria proliferation |
|
| ✓ Some pharmaceutical and personal care products (such as antibiotics, and environmental endocrine disruptor) have negative effect on the bacterial diversity, however, they may pose a great threat to drinking water safety | ||
| Unconventional water sources effects | ✓ The presence of one or more fecal indicators, and potential bacterial and protozoan pathogens were detected in rainwater, giving suggestion to that it may not be suitable for drinking |
|
| ✓ Disinfection was recommended whenever possible |
Fig. 3Influencing factors of microbial diversity in drinking water sources and their effects on drinking water biosafety.
Drinking water treatment processes effects on its microbiome
| Treatment processes | Impacts on drinking water microbiome | Ref. |
|---|---|---|
| Coagulation and sedimentation | ✓ Early studies suggested that they have minimal influence on the microbial community |
|
| ✓ With the develop of analytical approach, the results show that they are important for the removal of bacteria in source water | ||
| ✓ The removal of microorganisms from source water by coagulation and clarification mostly refers to microorganisms that are easily adsorbed on suspended particles and colloids | ||
| Filtration | ✓ Filtration is the key step shaping downstream microbiota through removing incoming particles and seeding outflow with microorganisms sloughed from filters |
|
| ✓ The filtration process can significantly reduce suspended substances such as bacteria and viruses, further affecting the microbial diversity | ||
| ✓ Various biological processes can occur in filters | ||
| O3–BAC | ✓ Ozonation increased taxonomic diversity but decreased functional diversity of the bacterial communities in the BAC filters |
|
| ✓ With the removal of organic matters in DWTP, the leakage of bacteria which could be have been seeding of distribution system, becomes an important issue in this unit | ||
| ✓ The influent water quality, oxidative pretreatment, empty bed contact time, and backwashing frequency can affect the redox environment of the system, influencing the microbial diversity of the effluent | ||
| ✓ O3–BAC effect on assimilable organic carbon (AOC) removal in three DWTPs and AOC increased after O3 treatment, and BAC could remove most AOC from water, which may be attributed to the microbial community differences | ||
| Disinfection | ✓ Different disinfection type and dosage might result in different bacterial populations |
|
| ✓ Generally, after disinfection, alpha- and beta- | ||
| ✓ Although disinfection process could inactivate most bacteria, there are still some chlorine-resistant bacteria existed in finished water, leading to the formation of biofilms in drinking water distribution systems and thus affecting the biosafety of residential water | ||
| ✓ The molecular mechanism of chlorine resistance is attributed to glutathione synthesis | ||
| ✓ Much attentions have been paid on the new approached of disinfection |
Fig. 4Influence of each unit in DWTP on microbial community.
Fig. 5Factors affecting microbiome composition in DWDS.
Pipe materials effects on drinking water microbial diversity
| Materials | Impacts on biofilms bacterial community | Ref. |
|---|---|---|
| PVC and cast ion | ✓ Hyphomicrobia was the most dominant bacteria identified in the PVC |
|
| ✓ Corrosion associated bacteria was the most dominant bacteria identified cast-iron biofilms | ||
| ✓ Bacterial colonization on the material surfaces was selective | ||
| HDPE, PEX and PVC | ✓ Coupon material did not have a significant impact on biomass levels or composition of the biofilm communities in the chloraminated reactors |
|
| ✓ The biological diversity of different metal pipes was significantly different due to the metal precipitation problem | ||
| ✓ A higher biological diversity was observed in biofilms on metallic material than that on plastic materials | ||
| ✓ The most extensive biofilm was found in pipes of HDPE material | ||
| ✓ The most numerous quantities of bacterial was found in pipes of PEX surface | ||
| EPDM and PEX | ✓ The biofilm populations on EPDM were higher than those on PEX |
|
| Copper | ✓ Copper could significantly reduce the microbial diversity downstream |
|
| ✓ Effect of copper surface on | ||
| ✓ Copper could inactivate | ||
| UPVC and copper | ✓ Significant differences between bacterial and eukaryotic member in biofilm on UPVC and Cu |
|
| Epoxying iron, PVC, and cement | ✓ Free chlorine was most stable in the presence of PVC while chloramine was most stable in the presence of cement |
|
| ✓ The influence of pipe material became apparent at water ages corresponding to low disinfectant residual | ||
| ✓ Each target microbe appeared to display a distinct response to disinfectant type, pipe materials, water age, and their interactions | ||
| EPDM and PEX | ✓ Total cell counts and HPC values were highest on EPDM followed by the plastic materials and copper |
|
| ✓ | ||
| ✓ Copper biofilms were colonized only by | ||
| Copper and PEX | ✓ Pipe material seemed to affect mycobacteria occurrence, and bacterial communities with MWT in copper but not in PEX pipes |
|
| Plastic and stainless steel | ✓ The microbiome of biofilms formed on stainless steel and plastics was quite different |
|
| ✓ Metallic materials facilitate the formation of higher diversity biofilms | ||
| Copper (CU), chlorinated poly vinyl chloride (CP), polybutylene (PB), polyethylene (PE), stainless steel (SS), steel coated with zinc (ST) | ✓ Steel pipes (SS and ST) had the highest biofilm formation potential (BFP) and CU showed the lowest BFP |
|
| ✓ The BFP of CP in drinking water and mixed water were comparable to those of CU | ||
| ✓ PB and PE showed relatively high BFP |