Skip to main content
Download PDF

What is the effect on antibiotic resistant genes of chlorine disinfection in drinking water supply systems? A systematic review protocol

Environmental Evidence volume 11, Article number: 11 (2022) Cite this article

Abstract

Background

Antibiotic-resistant bacteria (ARB) usually enter water sources in different ways, such as via municipal and hospital wastewaters. Because conventional technologies used to treat water inefficient in removing these contaminants (especially antibiotic-resistant genes; ARGs), these contaminants easily enter drinking water distribution networks and pose serious threats to consumers’ health. This study’s main purpose is to systematically investigate the effect of chlorine disinfection on ARGs in drinking water supply systems. This study could play an important role in elucidating the effect of chlorine disinfection on ARGs.

Methods

The systematic review outlining this protocol will be performed according to the Collaboration for Environmental Evidence (CEE) guidelines. The main question is, “what is the effect of chlorine disinfection on ARGs in drinking water supply systems?” For this purpose, the articles will be considered, in which chlorine’s effect on ARGs is investigated. The search includes electronic resources, grey literature, and related websites. Electronic resources include Scopus, PubMed, Embase, Web of Science Core Collection, and Science Direct. After the final search, the obtained articles will be collected in the reference management software (Endnote X8). Upon removing the duplicate articles, the first stage of article screening will be performed based on the title and abstract the articles. In the second stage, the articles obtained from the first screening stage will be screened based on the full text of the articles based on the eligibility criteria. Then, two members of the expert team extract the data. To assess the validity of the articles, bias sources will be determined by an expert team. Biases will be defined according to the criteria designed by Bilotta et al. Finally, a narrative synthesis will be performed for the extracted data; if appropriate data are available, quantitative analysis will also be performed.

Background

Antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs) are among the emerging contaminants in water and recently too much attention is paid to these contaminants globally [1, 2]. The widespread use of antibiotics in medicine, livestock breeding, aquaculture and industry have caused the ARB proliferation and release [3, 4]. According to the Centers for Disease Control and Prevention (CDC), in the United States, at least 2 million people are infected with resistant bacteria every year and about 23,000 of these patients lose their lives [5]. According to a review study conducted in 2016, antibiotic resistance caused 700,000 deaths worldwide. Moreover, it is estimated the deaths could reach 10 million by 2050 [6]. In addition, the damage caused by antibiotic resistance to the world economy could reach 100 billion US dollars by 2050 [7,8,9]. According to World Health Organization (WHO), if immediate action is not taken to combat antibiotic resistance, humans will face deadly infections in the "post-antibiotic era" that can take decades to cure [10]. ARBs enters water sources through municipal wastewater, hospital wastewater, municipal waste, agricultural waste, manure used as fertilizer on agricultural lands, runoff and even the effluent of some industrial treatment plants [11, 12]. After discharge, these contaminants enter surface water and, sometimes, groundwater. Because conventional technologies used for water treatment cannot efficiently remove these contaminants (especially ARGs) [13, 14], and thus, they may easily enter the drinking water distribution networks and turn into a serious threat to consumer health. Some studies have shown that ARBs and ARGs are present in bottled water, wells, rivers, lakes and various sources of drinking water [8]. ARBs and ARGs have also been recorded in drinking water treatment plants and drinking water distribution networks [10, 15]. Genes are transmitted between the bacteria in natural environments and engineering systems such as water and wastewater treatment plants [16]. Water supply systems can act as a suitable reservoir for transferring ARBs and ARGs from the aquatic environment to humans [17]. The main concern is that ARGs (which by themselves pose a little risk) can be easily passed through the water treatment system and transmit resistance to bacteria in the distribution network, including pathogenic bacteria. In this way, they pose serious threats (such as death, deadly and, sometimes, long-term infections) to human health. This expansion of potential bacterial resistance can be accomplished through horizontal transfer of genes (HGT), plasmids, transposons and integrons among different bacterial species [8, 18,19,20,21]. In large cities, drinking water is often supplied from surface water resources close to the city after proper and strict treatment processes [22]. The water treatment plant uses various processes such as flocculation, sedimentation, filtration and disinfection to improve water quality. Among these processes, disinfection is the most important process for controlling microorganisms that reach the point of consumption from the treatment plant [23]. Chlorine is used as a disinfectant in drinking water supply systems in many countries due to its cost-effectiveness and simplicity of use [24]. It plays an important role not only in killing bacteria, but also in stabilizing the microbial conditions of water in the distribution network [25, 26]. Recent findings show that chlorine may increase the number of ARGs in drinking water [25, 27, 28]. Depending on the concentration of chlorine in the water, bacteria use different strategies to resist and transmit ARGs [17, 29]. In some studies, the frequency of mobile genetic elements (MGEs), including integrons and plasmids, increases after chlorination, which accelerates ARG transfer [20, 25, 30]. The results of some studies show that chlorination increases ARGs [22, 25, 28], while the results of some other studies indicate a decrease in ARGs after chlorination [31,32,33,34]. Therefore, there is debate among researchers and scientists about the effect of disinfectants, especially chlorine, on ARBs and ARGs. Since we did not find any systematic reviews in literature in this field. According to the overview we have done in this area, several review studies have investigated the effect of the chlorination process on ARGs in municipal and hospital wastewater [35,36,37,38,39,40]. Some reviews have investigated the impact of disinfectants on ARGs in biofilms [41]; others have studied the effect of chlorine on intracellular ARGs [42]; furthermore, others have examined the effectiveness of various treatment technologies and processes in removing ARGs from different aquatic environments [43,44,45,46]. Nevertheless, no systematic review article has explicitly investigated the effect of chlorine on ARGs in drinking water supply systems; however, there are several reviews in a similar field that have examined the presence, dissemination and removal of ARG in raw and drinking water. In addition to chlorine, these articles have investigated other processes such as ozone, UV, ultraviolet light and, sometimes, biological activated carbon (BAC) [8, 17, 44, 47, 48]. Because these reviews are not "systematic" and have considered various treatment processes, the effect of chlorine on ARGs has not been studied in details. Thus, the present review can play an important role in elucidating the role of chlorine disinfection on the removal of ARGs. No organization, institution, or individual will be engaged in designing and conducting this study except the authors. Therefore, this study does not have stakeholder engagement.

Objective of the review

The main purpose of the present work is to investigate systematically the effect of chlorine disinfection (the most widely used disinfection in water supply systems) on ARGs of drinking water supply systems. It is not clear exactly what type of effect chlorine can have on ARGs. Herein, this review explains the effect of chlorine and its compounds on ARGs in drinking water supply systems. It can indicate which ARGs are most present in disinfected (chlorinated) drinking water. It also shows at what dosages chlorine is the most effective in terms of limiting and inactivating ARGs.

Primary question

“What is the effect of chlorine disinfection in drinking water supply systems on ARGs?” The question includes the following components: Population: Drinking water supply systems such as springs, wells, treatment plants and drinking water distribution networks; Intervention/exposure: Chlorine and chlorine compounds are added to drinking water as a disinfectant; Comparator: The presence of ARGs pre/post chlorination comparison; Outcome: The abundance and presence of ARGs after drinking water chlorination.

Secondary questions

  1. 1.

    What ARGs are the most commonly present after chlorination?

  2. 2.

    What are the maximum and minimum effects of chlorine dosages on ARGs?

  3. 3.

    What is the optimal chlorine contact time for inactivating or limiting ARGs?

Methods

This protocol, along with the systematic review outlined, will be performed according to the Collaboration for Environmental Evidence (CEE) guidelines for systematic review and evidence synthesis in environmental management [49], and will be reported according to ROSES reporting standards for systematic review evidence syntheses (see Additional file 1) [50]. This systematic review protocol has been registered in the PROSPERO database (Registration Number: CRD4202124307).

Searching for articles

In this study, for the scoping exercise, the articles investigating the effects of chlorine on ARGs were considered. At first, a pre-search was performed to determine the approximate number of articles in this field. The articles obtained in this stage were reviewed quantitatively and qualitatively. Also, search terms were identified. After consultation and discussion with the team members, the search strings were revised. High-sensitivity search strategies were designed to identify most of the evidence in this field. The expert team developed a search strategy for each database based on PICO/PECO framework. In the next stage, the search will be based on the published reviews on the topic and suggestions from expert team members in at least four areas, including electronic databases, grey literature, related websites and contact with the authors. The electronic databases included are Scopus, PubMed, Embase, Web of Science Core Collection and Science Direct. We will use Boolean operators to combine search terms and substrings. The 'OR' operator will be used to combine synonym terms that increase search sensitivity. The 'AND' operator will be used to combine the components of a research question (PICO/PECO framework); this will limit the search and increase the search accuracy for retrieving the related articles. It is usually not recommended to use the 'NOT' operator because it may cause the loss of some of the related articles, but to limit a large number of irrelevant articles and specificity of the topic, the 'NOT' operator will be used in this case. Asterisk (*) will be used to include the different search term characters. Finally, if not accessible by the usual retrieval of articles, authors will be directly contacted to request the full texts of their publications [51, 52].

Language

The primary search was conducted in Persian and English. However, due to the lack of related studies in Persian, the final search will be limited to English and we will not have a time limit.

Estimating the comprehensiveness of the search

To evaluate the performance of the search strategy, a test list (see Additional file 2) of 15 articles was collected from primary search, experts and previous reviews according to the method used by Livoreil et al. [51]. At first, our search strategy could not retrieve the test listing articles; we changed the search strategy again until it retrieved all the test listing articles. Our search strategy was able to find all the test list articles. In addition, we reviewed references to the relevant articles obtained in the search based on the existing search strategy. Most of the relevant articles were found in the references in our search strategy, which confirmed the proper functioning of our search strategy.

Publication databases

Search terms will be searched in Scopus based on “TITLE-ABS-KEY”, PubMed based on “MeSH”, Embase based on “EMTREE”, Web of Science Core Collection based on “Topic” and Science Direct based on “Title, abstract or author-specified keywords”. Search strings will be used to search the following five databases (see Additional file 3).

Example of a search string in PubMed:

("Drinking Water"[Mesh] OR "Fresh Water"[Mesh] OR "Water"[Mesh]) OR "Water Resources" [Mesh] OR "Water Supply"[Mesh] OR "supply and distribution" [Subheading] OR "Water Purification"[Mesh] OR "Water Quality"[Mesh] OR "Water Wells"[Mesh] OR "Groundwater"[Mesh] OR "Water Pollution"[Mesh]) AND ("Disinfection"[Mesh] OR "Disinfectants"[Mesh] OR "Chlorine"[Mesh] OR "Halogenation"[Mesh]) AND ("Drug Resistance, Multiple, Bacterial"[Mesh] OR "Drug Resistance, Microbial"[Mesh] OR "Drug Resistance, Bacterial"[Mesh] OR "Anti-Bacterial Agents"[Mesh]) NOT "Waste Water"[Mesh] NOT "Sewage"[Mesh].

Internet searches

Internet search will be done in Google Scholar. We will search Google Scholar using the Publish or Perish software. The search will be done based on a simplified search string (see Additional file 4) then the results of the first 1000 hits will be downloaded.

Specialist searches

Searching for the systematic study will not be limited to electronic databases. Also, it will be done to minimize the bias caused by publishing separate searches in grey literature and websites. In this context, our search will be limited to the keywords “drinking water”, “drinking water treatment plant”, “water supply”, “tap water”, “distribution system”, chlorine*, disinfect*, “antimicrobial resistance”, “antibiotic resistance”, “antibiotic resistant”. These keywords will be used in most searches for grey literature, but are not the same for all the sources and vary according to the source. Searching in grey literature will be done in the following databases and websites [51] (see Additional file 5).

  • ProQuest Dissertations and Theses Global;

  • Open grey literature in Europe;

  • World Alliance against Antibiotic Resistance;

  • Center for Antibiotic Resistance Research;

  • Centers for Disease Control and Prevention;

  • European Committee on Antimicrobial Susceptibility Testing;

  • Open Access Theses and Dissertations (OATD);

  • Food and Agriculture Organization of the United Nations (FAO);

  • British Library for Development Studies (BDLS);

  • British Library e-theses online service;

  • Directory of Open Access Journals; and

  • Bielefeld Academic Search Engine.

Supplementary searches

For supplementary searches, citation chasing will be used to identify the potentially relevant studies. If not accessible by the usual retrieval of articles, authors will be directly contacted to request the full texts of their publications.

Search updating

Evidence is constantly evolving. New studies are always likely to be undertaken and published. Therefore, if necessary, a search strategy update for all the resources will be performed before the final analysis. The searches will be updated before publication if this systematic review takes more than a year.

Article screening and study eligibility criteria

Screening process

After the final search, the articles will be collected in the reference management software (Endnote X8). After removing the duplicate articles, screening will be done in two stages (according to Fig. 1). The first screening stage will be based on the title and abstract of the articles. In the second stage and upon full text retrieval, the relevant items will be screened based on the full text criteria. The full text of articles that are not found will be obtained by contacting the authors. For three levels, two team members will perform the screening. In the case of disagreement between the two reviewers, the third reviewer will give the final opinion. All the team members will review articles that have been excluded at the full-text screening level. The project manager will double-check all the excluded articles to verify that no relevant articles are inappropriately excluded [53, 54]. For the procedural independence, we followed the method proposed by Ebrahimi et al. [55]. Systematic reviewers (who have also authored articles to be considered within the review) will not participate in decisions regarding inclusion or study validity assessment of their own work. The reasons for excluding the articles in the screening process (full text) should be reviewed by all the team members and will provide a list of full text articles excluded with reasons for their exclusion.

Fig. 1
figure 1

Decision tree for inclusion and exclusion of studies

Full size image

Eligibility criteria

Eligibility criteria are described in Table 1. Before screening all the articles (pre-screening), 10% of the articles (minimum 50) randomly will be screened by two reviewers, and Kappa tests will be calculated as a part of consistency checking and to assure consistency among reviewers. The Kappa score of ≤ 0.6 would indicate lack of consistency among reviewers. Eligibility criteria will be clarified and the consistency check will be repeated until the Kappa score is 0.6 or more [52, 56]. According to the eligibility criteria, books will be excluded because they have longer editing and publishing time than most of the books are not available through electronic search and need a manual search, which is very time-consuming and, sometimes, out of reach.

Table 1 Eligibility criteria
Full size table

Study validity assessment

The team manager will check again all the articles excluded from the screening process before evaluating the validity of the articles. To evaluate the validity of studies and the internal validity of each included study, sources of bias will be determined by an expert team according to the criteria designed by Bilotta et al. [57, 58] and the criteria defined by Schindler et al. [59]. Table 2 includes the bias assessment framework of the articles. The bias areas include: (1) selection and performance, (2) measurement of outcome, (3) publication and (4) other biases. The score range for each article will be in the range of 0–100. Articles will be classified into three categories with low, medium and high bias. Articles with a score of higher than 67 will be placed in the low bias article class, articles with a score of 33–67 will be placed in the class with moderate bias, and articles with a score below 33 will be placed in the high bias class (see Additional file 6). Articles in category with high bias will be excluded from the quantitative synthesis.

Table 2 Bias assessment framework of included articles
Full size table

External validity to determine the generalizability will be assessed using the eligibility criteria in the section above. We will consider for external validity: population (drinking water treatment plant/distribution network/tank/transmission line/tap water), disinfection (chlorine and its compounds), study scale (pilot/field) and presentation of results (absolute versus relative abundance) as well as global susceptibility to bias (low external validity if definitively low internal validity). The critical appraisal could be used to qualify conclusions (i.e., weight studies in the synthesis) if we find a large variance in biases among studies. To assess accuracy in validity assessment, the validity assessment will be conducted on a random sample (at least 20% of the articles) by two reviewers. Disagreements will be resolved after discussion, with the opinion of the third reviewer. Finally, all the included articles will be controlled and confirmed by the team.

Data coding and extraction strategy

We will extract raw data from appraised full texts. The extracted data will be recorded on a pre-configured Excel spreadsheet (see Additional file 7). In accordance with the pre-designed form author, year of publication, location of study, sample size, type of study (bench, pilot or full scale), laboratory method, type of ARGs, concentration of ARGs, removal rate of ARGs, type of ARBs, type of antibiotic, type and dosage of used disinfectant, type of water such as springs, wells, surface water, groundwater, properties of water such as temperature, pH, DO, total organic carbon (TOC), nitrate and phosphorus as well as existence or absence of biofilm (in the form of existence) will be extracted from the full text of the articles. In the case of incomplete data, the authors of the article will be contacted and the complete data will be obtained. To reduce bias in data reporting and ensure all data are extracted correctly, data extraction will be performed by two team members (at least for 10% of the articles). Moreover, in case of disagreement, the article will be reviewed by the rest of the team [54,55,56].

Potential effect modifiers/reasons for heterogeneity

Potential effect modifiers will be identified and recorded from the included articles.

In this study, several factors may cause heterogeneity:

  • Type of drinking water source (such as springs, wells, surface water, groundwater, water treatment systems, and drinking water distribution network);

  • Properties and characteristics of the drinking water sources (physical, chemical, and biological quality);

  • Study design (pilot or field);

  • Type of chlorine compounds and dosage of chlorine;

  • Monitoring duration;

  • Sample size or number of samples;

  • Laboratory methods for detection and measuring ARGs [such as PCR, qPCR, HT-qPCR or high-throughput sequencing (HTS)];

  • Type of ARGs; and

  • Study location.

The list (potential effect modifiers) will be reviewed and completed by the expert team after consultation (if necessary).

Data synthesis and presentation

Narrative synthesis will be done for all the included articles. The results will be summarized in the tables and figures, and will be accompanied by an interpretation and discussion. Quantitative data analysis will be done for those articles that meet the requirements for quantitative synthesis. ARGs and chlorine doses will be presented based on the mean and standard deviation. Studies with different methods of measuring ARGs concentrations will be analyzed separately. If the studies have sufficient and similar data, meta-analysis (using random-effects models) can be used to analyze the data. Studies with incomplete or missing data will not be included in the meta-analysis. If heterogeneity exists, meta-regression analyses or Cochrane’s Q test will be done depending on the study process to assess between-study heterogeneity. The I2 test statistic can be used to measure the extent of this heterogeneity. A funnel plot comparing the study effect size with the standard error may be used to check the publication bias.

Availability of data and materials

Not applicable.

References

  1. Bitton G. Wastewater microbiology. Hoboken: Wiley; 2005.

    Google Scholar 

  2. Dimavičienė B. Lithuanian and translated young adult literature in the contemporary Lithuanian literary system as conditioned by historical factors: an analysis using polysystem theory. 2016.

  3. Bai X, Ma X, Xu F, Li J, Zhang H, Xiao X. The drinking water treatment process as a potential source of affecting the bacterial antibiotic resistance. Sci Total Environ. 2015;533:24–31.

    CAS  Google Scholar 

  4. He H, Zhou P, Shimabuku KK, Fang X, Li S, Lee Y, et al. Degradation and deactivation of bacterial antibiotic resistance genes during exposure to free chlorine, monochloramine, chlorine dioxide, ozone, ultraviolet light, and hydroxyl radical. Environ Sci Technol. 2019;53(4):2013–26.

    CAS  Google Scholar 

  5. Li R, Jay JA, Stenstrom MK. Fate of antibiotic resistance genes and antibiotic-resistant bacteria in water resource recovery facilities. Water Environ Res. 2019;91(1):5–20.

    CAS  Google Scholar 

  6. Liu S-S, Qu H-M, Yang D, Hu H, Liu W-L, Qiu Z-G, et al. Chlorine disinfection increases both intracellular and extracellular antibiotic resistance genes in a full-scale wastewater treatment plant. Water Res. 2018;136:131–6.

    Google Scholar 

  7. Wang R-N, Zhang Y, Cao Z-H, Wang X-Y, Ma B, Wu W-B, et al. Occurrence of super antibiotic resistance genes in the downstream of the Yangtze River in China: prevalence and antibiotic resistance profiles. Sci Total Environ. 2019;651:1946–57.

    CAS  Google Scholar 

  8. Sanganyado E, Gwenzi W. Antibiotic resistance in drinking water systems: occurrence, removal, and human health risks. Sci Total Environ. 2019;669:785–97.

    CAS  Google Scholar 

  9. Giannakis S, Lett T-TM, Entenza JM, Pulgarin C. Solar photo-Fenton disinfection of 11 antibiotic-resistant bacteria (ARB) and elimination of representative AR genes. Evidence that antibiotic resistance does not imply resistance to oxidative treatment. Water Res. 2018;143:334–45.

    CAS  Google Scholar 

  10. Sullivan BA, Vance CC, Gentry TJ, Karthikeyan R. Effects of chlorination and ultraviolet light on environmental tetracycline-resistant bacteria and tet (W) in water. J Environ Chem Eng. 2017;5(1):777–84.

    CAS  Google Scholar 

  11. Laroche E, Pawlak B, Berthe T, Skurnik D, Petit F. Occurrence of antibiotic resistance and class 1, 2 and 3 integrons in Escherichia coli isolated from a densely populated estuary (Seine, France). FEMS Microbiol Ecol. 2009;68(1):118–30.

    CAS  Google Scholar 

  12. Mantilla-Calderon D, Plewa MJ, Michoud G, Fodelianakis S, Daffonchio D, Hong P-Y. Water disinfection byproducts increase natural transformation rates of environmental DNA in Acinetobacter baylyi ADP1. Environ Sci Technol. 2019;53(11):6520–8.

    CAS  Google Scholar 

  13. Destiani R, Templeton M. Chlorination and ultraviolet disinfection of antibiotic-resistant bacteria and antibiotic resistance genes in drinking water. AIMS Environ Sci. 2019;6(3):222–41.

    CAS  Google Scholar 

  14. Zhang M, Wang L, Xu M, Zhou H, Wang S, Wang Y, et al. Selective antibiotic resistance genes in multiphase samples during biofilm growth in a simulated drinking water distribution system: occurrence, correlation and low-pressure ultraviolet removal. Sci Total Environ. 2019;649:146–55.

    CAS  Google Scholar 

  15. Miranda AC, Lepretti M, Rizzo L, Caputo I, Vaiano V, Sacco O, et al. Surface water disinfection by chlorination and advanced oxidation processes: inactivation of an antibiotic resistant E. coli strain and cytotoxicity evaluation. Sci Total Environ. 2016;554:1–6.

    Google Scholar 

  16. Luo Y, Mao D, Rysz M, Zhou Q, Zhang H, Xu L, et al. Trends in antibiotic resistance genes occurrence in the Haihe River, China. Environ Sci Technol. 2010;44(19):7220–5.

    Google Scholar 

  17. Tan Q, Li W, Zhang J, Zhou W, Chen J, Li Y, et al. Presence, dissemination and removal of antibiotic resistant bacteria and antibiotic resistance genes in urban drinking water system: a review. Front Environ Sci Eng. 2019;13(3):1–15.

    CAS  Google Scholar 

  18. Guo X, Li J, Yang F, Yang J, Yin D. Prevalence of sulfonamide and tetracycline resistance genes in drinking water treatment plants in the Yangtze River Delta, China. Sci Total Environ. 2014;493:626–31.

    CAS  Google Scholar 

  19. Zhang M, Chen S, Yu X, Vikesland P, Pruden A. Degradation of extracellular genomic, plasmid DNA and specific antibiotic resistance genes by chlorination. Front Environ Sci Eng. 2019;13(3):1–12.

    Google Scholar 

  20. Zhang J, Li W, Chen J, Wang F, Qi W, Li Y, et al. Effect of hydraulic conditions on the prevalence of antibiotic resistance in water supply systems. Chemosphere. 2019;235:354–64.

    CAS  Google Scholar 

  21. Yoon Y, Dodd MC, Lee Y. Elimination of transforming activity and gene degradation during UV and UV/H 2 O 2 treatment of plasmid-encoded antibiotic resistance genes. Environ Sci Water Res Technol. 2018;4(9):1239–51.

    CAS  Google Scholar 

  22. Xu L, Ouyang W, Qian Y, Su C, Su J, Chen H. High-throughput profiling of antibiotic resistance genes in drinking water treatment plants and distribution systems. Environ Pollut. 2016;213:119–26.

    CAS  Google Scholar 

  23. Khan S, Beattie TK, Knapp CW. Relationship between antibiotic-and disinfectant-resistance profiles in bacteria harvested from tap water. Chemosphere. 2016;152:132–41.

    CAS  Google Scholar 

  24. Zhang H, Chang F, Shi P, Ye L, Zhou Q, Pan Y, et al. Antibiotic resistome alteration by different disinfection strategies in a full-scale drinking water treatment plant deciphered by metagenomic assembly. Environ Sci Technol. 2019;53(4):2141–50.

    CAS  Google Scholar 

  25. Shi P, Jia S, Zhang X-X, Zhang T, Cheng S, Li A. Metagenomic insights into chlorination effects on microbial antibiotic resistance in drinking water. Water Res. 2013;47(1):111–20.

    CAS  Google Scholar 

  26. Ding W, Jin W, Cao S, Zhou X, Wang C, Jiang Q, et al. Ozone disinfection of chlorine-resistant bacteria in drinking water. Water Res. 2019;160:339–49.

    CAS  Google Scholar 

  27. Huang J-J, Hu H-Y, Wu Y-H, Wei B, Lu Y. Effect of chlorination and ultraviolet disinfection on tetA-mediated tetracycline resistance of Escherichia coli. Chemosphere. 2013;90(8):2247–53.

    CAS  Google Scholar 

  28. Jia S, Shi P, Hu Q, Li B, Zhang T, Zhang X-X. Bacterial community shift drives antibiotic resistance promotion during drinking water chlorination. Environ Sci Technol. 2015;49(20):12271–9.

    CAS  Google Scholar 

  29. Guo M-T, Yuan Q-B, Yang J. Distinguishing effects of ultraviolet exposure and chlorination on the horizontal transfer of antibiotic resistance genes in municipal wastewater. Environ Sci Technol. 2015;49(9):5771–8.

    CAS  Google Scholar 

  30. Munir M, Wong K, Xagoraraki I. Release of antibiotic resistant bacteria and genes in the effluent and biosolids of five wastewater utilities in Michigan. Water Res. 2011;45(2):681–93.

    CAS  Google Scholar 

  31. Bertelli C, Courtois S, Rosikiewicz M, Piriou P, Aeby S, Robert S, et al. Reduced chlorine in drinking water distribution systems impacts bacterial biodiversity in biofilms. Front Microbiol. 2018;9:2520.

    Google Scholar 

  32. Hao H, Shi D-Y, Yang D, Yang Z-W, Qiu Z-G, Liu W-L, et al. Profiling of intracellular and extracellular antibiotic resistance genes in tap water. J Hazard Mater. 2019;365:340–5.

    CAS  Google Scholar 

  33. Zhang T, Hu Y, Jiang L, Yao S, Lin K, Zhou Y, et al. Removal of antibiotic resistance genes and control of horizontal transfer risk by UV, chlorination and UV/chlorination treatments of drinking water. Chem Eng J. 2019;358:589–97.

    CAS  Google Scholar 

  34. Stange C, Sidhu J, Toze S, Tiehm A. Comparative removal of antibiotic resistance genes during chlorination, ozonation, and UV treatment. Int J Hyg Environ Health. 2019;222(3):541–8.

    CAS  Google Scholar 

  35. Triggiano F, Calia C, Diella G, Montagna MT, De Giglio O, Caggiano G. The role of urban wastewater in the environmental transmission of antimicrobial resistance: the current situation in Italy (2010–2019). Microorganisms. 2020;8(10):1–12.

    Google Scholar 

  36. Wang J, Chu L, Wojnárovits L, Takács E. Occurrence and fate of antibiotics, antibiotic resistant genes (ARGs) and antibiotic resistant bacteria (ARB) in municipal wastewater treatment plant: an overview. Sci Total Environ. 2020. https://doi.org/10.1016/j.scitotenv.2020.140997.

    Article  Google Scholar 

  37. Rizzo L, Manaia C, Merlin C, Schwartz T, Dagot C, Ploy M, et al. Urban wastewater treatment plants as hotspots for antibiotic resistant bacteria and genes spread into the environment: a review. Sci Total Environ. 2013;447:345–60.

    CAS  Google Scholar 

  38. Hassoun-Kheir N, Stabholtz Y, Kreft J-U, De La Cruz R, Romalde JL, Nesme J, et al. Comparison of antibiotic-resistant bacteria and antibiotic resistance genes abundance in hospital and community wastewater: a systematic review. Sci Total Environ. 2020. https://doi.org/10.1016/j.scitotenv.2020.140804.

    Article  Google Scholar 

  39. Manaia CM, Macedo G, Fatta-Kassinos D, Nunes OC. Antibiotic resistance in urban aquatic environments: can it be controlled? Appl Microbiol Biotechnol. 2016;100(4):1543–57.

    CAS  Google Scholar 

  40. Dodd MC. Potential impacts of disinfection processes on elimination and deactivation of antibiotic resistance genes during water and wastewater treatment. J Environ Monit. 2012;14(7):1754–71.

    CAS  Google Scholar 

  41. Zhang J, Li W, Chen J, Qi W, Wang F, Zhou Y. Impact of biofilm formation and detachment on the transmission of bacterial antibiotic resistance in drinking water distribution systems. Chemosphere. 2018;203:368–80.

    CAS  Google Scholar 

  42. Zarei-Baygi A, Smith AL. Intracellular versus extracellular antibiotic resistance genes in the environment: prevalence, horizontal transfer, and mitigation strategies. Bioresour Technol. 2021. https://doi.org/10.1016/j.biortech.2020.124181.

    Article  Google Scholar 

  43. Li S, Zhang C, Li F, Hua T, Zhou Q, Ho S-H. Technologies towards antibiotic resistance genes (ARGs) removal from aquatic environment: a critical review. J Hazard Mater. 2021. https://doi.org/10.1016/j.jhazmat.2021.125148.

    Article  Google Scholar 

  44. Sharma VK, Johnson N, Cizmas L, McDonald TJ, Kim H. A review of the influence of treatment strategies on antibiotic resistant bacteria and antibiotic resistance genes. Chemosphere. 2016;150:702–14.

    CAS  Google Scholar 

  45. Herraiz-Carboné M, Cotillas S, Lacasa E, de Baranda CS, Riquelme E, Cañizares P, et al. A review on disinfection technologies for controlling the antibiotic resistance spread. Sci Total Environ. 2021. https://doi.org/10.1016/j.scitotenv.2021.149150.

    Article  Google Scholar 

  46. Zhang G, Li W, Chen S, Zhou W, Chen J. Problems of conventional disinfection and new sterilization methods for antibiotic resistance control. Chemosphere. 2020. https://doi.org/10.1016/j.chemosphere.2020.126831.

    Article  Google Scholar 

  47. Zhang T, Lv K, Lu Q, Wang L, Liu X. Removal of antibiotic-resistant genes during drinking water treatment: a review. J Environ Sci. 2021;104:415–29.

    Google Scholar 

  48. Wan K, Lin W, Zhu S, Zhang S, Yu X. Biofiltration and disinfection codetermine the bacterial antibiotic resistome in drinking water: a review and meta-analysis. Front Environ Sci Eng. 2020. https://doi.org/10.1007/s11783-019-1189-1.

    Article  Google Scholar 

  49. Petrokofsky G. Guidelines and standards for evidence synthesis in environmental management: version 5.0. 2018.

  50. Haddaway N, Macura B, Whaley P, Pullin A. ROSES for systematic review protocols. Version 1.0. 2017.

  51. Livoreil B, Glanville J, Haddaway NR, Bayliss H, Bethel A, de Lachapelle FF, et al. Systematic searching for environmental evidence using multiple tools and sources. Environ Evid. 2017;6(1):1–14.

    Google Scholar 

  52. Stanton IC, Bethel A, Leonard AF, Gaze WH, Garside R. What is the research evidence for antibiotic resistance exposure and transmission to humans from the environment? A systematic map protocol. Environ Evid. 2020;9:1–8.

    Google Scholar 

  53. Goulas A, Belhadi D, Descamps A, Andremont A, Benoit P, Courtois S, et al. How effective are strategies to control the dissemination of antibiotic resistance in the environment? A systematic review. Environ Evid. 2020;9(1):1–32.

    Google Scholar 

  54. Rodríguez-Molina D, Mang P, Schmitt H, Chifiriuc MC, Radon K, Wengenroth L. Do wastewater treatment plants increase antibiotic resistant bacteria or genes in the environment? Protocol for a systematic review. Syst Rev. 2019;8(1):1–8.

    Google Scholar 

  55. Ebrahimi SM, Reyhani RD, Asghari-JafarAbadi M, Fathifar Z. Diversity of antibiotics in hospital and municipal wastewaters and receiving water bodies and removal efficiency by treatment processes: a systematic review protocol. Environ Evid. 2020;9(1):1–9.

    Google Scholar 

  56. Goulas A, Livoreil B, Grall N, Benoit P, Couderc-Obert C, Dagot C, et al. What are the effective solutions to control the dissemination of antibiotic resistance in the environment? A systematic review protocol. Environ Evid. 2018;7(1):1–9.

    Google Scholar 

  57. Bilotta GS, Milner AM, Boyd IL. Quality assessment tools for evidence from environmental science. Environ Evid. 2014;3(1):1–14.

    Google Scholar 

  58. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011. https://doi.org/10.1136/bmj.d5928.

    Article  Google Scholar 

  59. Schindler S, Bayliss HR, Essl F, Rabitsch W, Follak S, Pullin AS. Effectiveness of management interventions for control of invasive common ragweed Ambrosia artemisiifolia: a systematic review protocol. Environ Evid. 2016;5(1):1–10.

    Google Scholar 

Download references

Acknowledgements

This work is part of the MSPH thesis of the first author. The authors wish to thank the financial support from the Department of Environmental Engineering of the School of Public Health Tehran University of Medical Sciences (TUMS) (Project No. 98-01-27-39639)

Funding

Tehran University of Medical Sciences, through its Research Vice-Chancellor, funded the systematic review protocol described here. This study is related to thesis number IR.TUMS.SPH.REC.1399.297, Tehran University of Medical Sciences, Tehran, Iran. Tehran University of Medical Sciences supports this protocol (as a part of a Master’s thesis) and the forthcoming review.

Author information

Authors and Affiliations

  1. Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

    Esfandiar Ghordouei Milan, Amir Hossein Mahvi, Ramin Nabizadeh & Mahmood Alimohammadi

  2. Center for Solid Waste Research (CSWR), Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran

    Amir Hossein Mahvi

  3. Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran

    Ramin Nabizadeh & Mahmood Alimohammadi

  4. Center for Water Quality Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran

    Mahmood Alimohammadi

  5. Health Equity Research Center (HERC), Tehran University of Medical Sciences, Tehran, Iran

    Mahmood Alimohammadi

Authors
  1. Esfandiar Ghordouei Milan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amir Hossein Mahvi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramin Nabizadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mahmood Alimohammadi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The authors of the present protocol declare that they have cooperated in the formulation of the question, ideas and writing of the protocol. EGM: describing literature research method, study screening, data extraction, evidence evaluation, content drafting and approval and statistical analysis (if applicable); AHM: systematic review methods consultation, content review and approval; RN: microbiology consultation, statistical consultation, systematic review methods consultation, content review and approval; MA: study screening, data extraction, evidence evaluation, content review and approval. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mahmood Alimohammadi.

Ethics declarations

Ethics approval and consent to participate

This study is related to the thesis with ethics number IR.TUMS.SPH.REC.1399.297, Tehran University of Medical Sciences, Tehran, Iran.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

ROSES form for the systematic review protocol.

Additional file 2.

Test list (benchmark articles).

Additional file 3.

Search strings for electronic database.

Additional file 4.

Search strings in Google Scholar.

Additional file 5.

Search strings for grey literature and academic.

Additional file 6.

Study validity assessment.

Additional file 7.

Data coding and extraction strategy.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghordouei Milan, E., Mahvi, A.H., Nabizadeh, R. et al. What is the effect on antibiotic resistant genes of chlorine disinfection in drinking water supply systems? A systematic review protocol. Environ Evid 11, 11 (2022). https://doi.org/10.1186/s13750-022-00266-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13750-022-00266-y

Keywords

  • Antibiotic-resistant bacteria (ARB)
  • Antibiotic-resistant genes (ARGs)
  • Drinking water
  • Water supply
  • Drinking water treatment plant
  • Chlorination
  • Disinfection

Environmental Evidence

ISSN: 2047-2382