Antibiotics in Drinking Water in Shanghai and Their Contribution to

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Antibiotics in drinking water in Shanghai and its contribution to antibiotic exposure of school children Hexing Wang, Na Wang, Bin Wang, Qi Zhao, Hong Fang, Chaowei Fu, Chuanxi Tang, Feng Jiang, Ying Zhou, Yue Chen, and Qingwu Jiang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b05749 • Publication Date (Web): 05 Feb 2016 Downloaded from http://pubs.acs.org on February 7, 2016

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Environmental Science & Technology

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Antibiotics in drinking water in Shanghai and its contribution to

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antibiotic exposure of school children

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Hexing Wang1†, Na Wang1†, Bin Wang1, Qi Zhao1, Hong Fang2, Chaowei Fu1,

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Chuanxi Tang3, Feng Jiang1, Ying Zhou1*, Yue Chen4, Qingwu Jiang1

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1

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Health, Fudan University, Shanghai 200032, China

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2

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Shanghai 201101, China

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3

Key Laboratory of Public Health Safety of Ministry of Education, School of Public

Minhang District Center for Disease Control and Prevention, Minhang District,

Changning District Center for Disease Control and Prevention, Changning District,

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Shanghai 200051, China

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4

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Medicine, University of Ottawa, Ottawa, Ontario K1H8M5, Canada.

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†These authors contributed equally to this work.

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*Corresponding author: Ying Zhou, [email protected]; Tel. and Fax: 086 021

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54237565; Address: NO 130, Dongan Road, Xuhui District, Shanghai City 200032,

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China.

School of Epidemiology, Public Health and Preventive Medicine, Faculty of

17 18 19 20 21 22 1

ACS Paragon Plus Environment


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Abstract A variety of antibiotics have been found in aquatic environment, but antibiotics

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in drinking water and its contribution to antibiotic exposure in human are not well

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explored. For this, representative drinking water samples and 530 urines of school

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children were selected in Shanghai and 21 common antibiotics (five macrolides, two

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β-lactams, three tetracyclines, four fluoquinolones, four sulfonamides, and three

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phenicols) were measured in water samples and urines by isotope dilution

30

two-dimensional ultra-performance liquid chromatography coupled with

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high-resolution quadrupole time-of-flight mass spectrometry. Drinking water

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included 46 terminal tap water samples from different spots in the distribution

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system of the city, 45 bottled water samples from 14 common brands, and eight

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barreled water samples of different brands. Of 21 antibiotics, only florfenicol and

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thiamphenicol were found in tap water with the median concentrations of

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0.0089ng/mL and 0.0064ng/mL, respectively; only florfenicol was found in three

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bottled water samples from a same brand with the concentrations ranging from

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0.00060ng/mL to 0.0010ng/mL; no antibiotics were found in barreled water. In

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contrast, besides florfenicol and thiamphenicol, additional 17 antibiotics were

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detected in urines, and the total daily exposure doses and detection frequencies of

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florfenicol and thiamphenicol based on urines were significantly and substantially

42

higher than their predicted daily exposure doses and detection frequencies from

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drinking water by Monte Carlo Simulation. These data indicated that drinking water

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was contaminated by some antibiotics in Shanghai, but played a limited role in

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antibiotic exposure of children. 2


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INTRODUCTION Antibiotics have been extensively used to prevent or treat bacterial infections

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in human and veterinary medicine and to promote growth in animal husbandry and

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aquaculture for nearly one hundred years 1. Because a considerable proportion of

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antibiotics used in human and animal would be excreted in urine and faeces as

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unchanged and active species 2, and wastewater treatment plants (WWTPs),

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hospitals, and livestock farms do not always have enough capacity of removing

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antibiotics in their effluent, sludge, or manure, antibiotics have contaminated

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aquatic environment 3. Due to their potential threats to aquatic ecological

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environment and human health, antibiotics have been thought as one group of

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emerging environment contaminants 4. Of more concern is that the adverse

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consequence of antibiotics in aquatic environment is likely to be far-reaching

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beyond bacterial resistance 5. Antibiotic exposure from aquatic environment might

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result in a systematic effect on human body physiology by gut microbiota, which

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has been linked to many diseases related to immune and metabolism 6. Given that

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there are more than 100 antibiotics used in human and animal 7-9 and nearly 70

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antibiotics have been found in surface water and sediment 3,10, the concern of

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antibiotics in drinking water as potential exposure source is arising. In previous

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studies, however, only a few categories of antibiotics were investigated in drinking

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water 11,12, and their contribution to overall exposure of human to antibiotics from

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various sources is not well explored.

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Shanghai is the largest Chinese city located in the estuary of the Yangtze River 3



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in East China with a relatively high economical development level. Due to its dense

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population and intensive livestock breeding industry, Shanghai was expected to have

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a high antibiotic contamination level in aquatic environment 13. A previous study

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measured 18 antibiotics in urines from more than 1000 children living in East China

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and found that children carried a heavy antibiotic body burden, but the role of

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antibiotics from drinking water in human antibiotic exposure remain unclear 14. In

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this study, we investigated 21 antibiotics in drinking water and in urines from school

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children in Shanghai by isotope dilution two-dimensional ultra-performance liquid

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chromatography coupled with high-resolution quadrupole time-of-flight mass

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spectrometry (UPLC-Q/TOF MS), estimated antibiotic exposure based on drinking

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water and urine, and made an assessment for antibiotic contamination in drinking

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water and its contribution to overall antibiotic exposure in children.

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MATERIALS AND METHODS

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Collection of tap, bottled, and barreled water

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Given that the existing 14 subway lines in Shanghai can almost cover the entire

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city, a sampling method based on the stations along subway lines was employed. To

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collect representative terminal tap water samples of Shanghai, besides two sampling

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sites respectively set at two end stations of each subway line, a suitable number of

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other sampling sites were evenly distributed in the stations between two ends of each

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subway line. The details of subway network map were provided in the official

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website of Shanghai Metro 15. A total of 46 sampling sites were set along all the 14

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subway lines and the collection was performed in June 2015. 4


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There are two main water sources for tap water in Shanghai: the Qingcaosha

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reservoir in the Yangtze estuary and the upper reach of the Huangpu River 16. The

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former is on the north side and the latter is on the south side of Shanghai City. It was

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inferred that the tap water in the north part of Shanghai mainly originates from

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Qingcaosha reservoir and the tap water in the south part of the city mainly originates

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from the upper reach of Huangpu River, and the tap water in the middle part of the

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city may be a mixture from the two water sources. Based on the subway network

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map, two virtual lines were drawn to evenly divide the city into three parts of north,

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middle, and south, in which tap water had different water sources, and 15, 16, and 15

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of 46 selected sampling sites were located in the north, middle, and south parts of the

100 101

city, respectively. One liter of terminal tap water was collected at each sampling site. Water

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samples were collected in glass bottles previously cleaned by pure water and acetone.

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To avoid possible contamination during water sampling, the water taps were turned

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on completely to release water for at least 5 minutes and the glass bottles were

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cleaned at least five times by tap water before the formal water collection. After tap

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water samples were collected in glass bottles, about 50mg of ascorbic acid was

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immediately added to quench the residual chlorine in tap water to prevent the

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antibiotics from degrading 17. Tap water sampling was performed by five technicians

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in two consecutive days and each technician carried one water field blank to monitor

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possible interferences during entire sampling process.

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Forty-five bottled water samples from 14 different brands were conveniently 5



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purchased from super markets in Shanghai and at least three bottles were collected

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for each brand. Eight barreled water samples of different brands were purchased

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from commercial agents in Shanghai. One 25 L barrel of water was collected for

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each brand. All water samples were kept in an air conditioned room set at 20℃ and

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were analyzed within one week.

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Analysis of antibiotics in drinking water

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A total of 21 common antibiotics were selected from six categories, including

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five macrolides (azithromycin, clarithromycin, erythromycin, roxithromycin, and

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tylosin), two β-lactams (cefaclor and ampicillin), three tetracyclines

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(chlortetracycline, tetracycline, and oxytetracycline), four fluoquinolones

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(ciprofloxacin, ofloxacin, enrofloxacin, and norfloxacin), four sulfonamides

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(sulfamethazine, sulfamethoxazole, sulfadiazine, and trimethoprim), and three

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phenicols (chloramphenicol, florfenicol, and thiamphenicol). Among them,

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azithromycin, clarithromycin, roxithromycin, cefaclor, and chloramphenicol are only

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used as human antibiotics; tylosin, chlortetracycline, enrofloxacin, and florfenicol

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are only used as veterinary antibiotics; erythromycin and ampicillin are preferred as

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human antibiotics; rest ten antibiotics are preferred as veterinary antibiotics.

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A method based on the isotope dilution two-dimensional UPLC-Q/TOF MS

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was used to measure 21 antibiotics in drinking water. The sample pretreatment

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followed an analytical method described previously 17. Briefly, 2ml of 2.5g/L

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Na2EDTA and 13 stable isotope labeled internal standards were added to each 500

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ml tap water sample, and then was adjusted to pH 3 and extracted using 200 mg 6


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HLB solid phase extraction cartridges. When analyzed by two-dimensional

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UPLC-Q/TOF MS, 21 antibiotics were divided into two groups: one group was

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consisted of three phenicols and another group was consisted of remaining 18

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antibiotics. Antibiotics in the former group were analyzed in negative ion mode and

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those in the latter group were analyzed in positive ion mode. The interbatch

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recoveries of three phenicols varied between 81.7% and 103.7% with the interbatch

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relative standard deviations ranging from 4.2% to 5.9%. The interbatch recoveries of

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18 antibiotics varied between 83.6% and 109.6% with the interbatch relative

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standard deviations ranging from 8.2% to 12.8%. Details of analytical method were

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provided in Supporting Information.

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Predication of antibiotic exposure from drinking water

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Daily exposure dose. Using concentrations of antibiotics in drinking water,

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daily drinking water consumption, and body weight, the daily exposure dose from

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drinking water was estimated in children. The calculation formula was as follows:

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Ed =

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Cd: antibiotic concentration in drinking water, ng/mL; Vd: daily drinking water

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consumption, mL/day; Mb: body weight, kg). After the probability distributions of

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antibiotic concentrations in drinking water, body weight, and daily consumption

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volume of drinking water were obtained, the probability distribution of daily

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exposure doses of antibiotics from drinking water was predicted by 10000 times of

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Monte Carlo Simulation using the @Risk software (version 6.1.1, Palisade

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Corporation). The probability distributions of body weight (kg) were defined as the

Cd × Vd (Ed: estimated daily exposure dose from drinking water, µg/kg/day; M b ×1000

7



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Weibull distribution with a scale of 1.8485 and a shape of 19.985 for boys and the

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Weibull distribution with a scale of 1.7948 and a shape of 17.186 for girls by the

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@Risk software. The probability distributions of daily consumption volume of

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drinking water were set as the normal distribution with a mean of 773 and a standard

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deviation of 19 for boys and the normal distribution with a mean of 622 and a

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standard deviation of 16 for girls according to a study conducted in 1454 children

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aged 8-17 years in Shanghai 18.

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Detection frequency. Based on concentrations of antibiotics in tap water, daily

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drinking water consumption, body weight, daily urine output by body weight,

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urinary concentrations of antibiotics from drinking water was estimated. The

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calculation formula was as follows: Cu =

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concentration in subjects, ng/mL; Cd, Vd, and Mb were same as mentioned above; Vu:

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daily urine output by body weight, ml/ kg/day; P: antibiotic excretion proportion in

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urine as unchanged and glucuronide-conjugated species (Table S1)). Because the

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experimental excretion proportions of tylosin, enrofloxacin, and florfenicol in urine

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was unavailable in human, urinary excretion proportion from pigs was used here 13.

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After the probability distributions of antibiotic concentrations in drinking water,

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body weight, daily consumption volume of drinking water, and daily urine output by

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body weight were obtained, the probability distribution of urinary antibiotic

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concentrations from drinking water was predicted by 10000 times of Monte Carlo

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Simulation to obtain its probability distribution using the @Risk software. The

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probability distribution of daily urine output by body weight (ml/ kg/day) was set as

Cd × Vd × P (Cu: estimated urinary M b × Vu

8


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the normal distribution with a mean of 22.2 and a standard deviation of 2.0 19.

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Detection frequency of urinary antibiotics from drinking water in children was

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defined as the proportion of predicted urinary concentrations greater than their limits

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of detection (LODs) among all predicted urinary concentrations.

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Predication of total antibiotic exposure in children

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Selection of school children. To better represent children in Shanghai, two

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elementary schools were respectively selected in the urban and suburban parts of the

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city in 2013 14. The urban school is located in the middle of the city and the suburban

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school is located in the south part of the city. After three or four classes were

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randomly selected from each of third, fourth, and fifth grades in each school, a total

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of 530 Han children aged 8-11 years were included in this study. Of them, 222 came

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from the urban school and 308 came from the suburban school; 274 were boys and

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256 were girls; 530 children provided first morning urines and 518 children

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participated in routine physical examination. The study was reviewed and approved

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by the Institutional Review Board of Fudan University.

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Analysis of antibiotics in urines. Total urinary concentrations (free and

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conjugated) of 21 antibiotics were determined by the isotope dilution

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two-dimensional UPLC-Q/TOF MS, based on an analytical method modified from

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that previously established in our lab 20. Except for three phenicols, the analysis of

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18 antibiotics and creatinine in urine were described previously 14. For three

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phenicols, the analytical method was briefly provided as follows: after an aliquot

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(1.0 mL) of urine was spiked with isotope-labelled chloramphenicol and hydrolyzed 9



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by β-glucuronidase, the mixture was purified by solid-phase extraction and analyzed

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by two-dimensional UPLC-Q/TOF MS in negative ion mode. The interbatch

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recoveries of three phenicols varied between 86.1% and 110.2% with the interbatch

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relative standard deviations ranging from 3.8% to 9.3%. Details of analytical method

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for three phenicols were provided in Supporting Information. Total daily exposure dose. The total daily exposure dose was calculated using

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the following formula frequently used in previous daily intake evaluation studies 21,22:

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Eu =

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antibiotic concentration, µg/L (equivalent to ng/mL); Cc: urinary creatinine

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concentration, mmol/L; Mc: daily output of urinary creatinine, mmol/day; Mb and P

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were same as mentioned above). Daily output of urine creatinine was predicted by a

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height-based regression equation based on a population of 454 healthy children aged

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3-18 years: Mc=0.0102×Hb-0.6854 with a determination coefficient of 0.87 and a

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p-value less than 0.0001 (Hb: standing height, cm) 23.

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Statistical analysis

Ca × M c 1 (Eu: estimated daily exposure dose, µg/kg/day; Ca: urinary × Cc × M b P

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Given that there was lack of specific individual and population-based data on

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daily consumption amount of tap, bottled, and barreled water in Chinese children,

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the concentrations and probability distributions of antibiotics with the highest

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contamination level among tap, bottled, or barreled water was assumed as those in

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drinking water to avoid possible underestimation of exposure level from drinking

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water. To check the validity of prediction by Monte Carlo Simulation, average daily

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dose and urinary concentration based on average body weight (35.7kg for girls and 10


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38.0 kg for boys), average daily drinking water consumption (773 mL/day for boys

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and 622 mL/day for girls), average antibiotic concentration in drinking water, and

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average daily urine output by body weight (22.2 ml/ kg/day) were compared with

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those predicted by Monte Carlo Simulation. In terms of exposure dose and urinary

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detection frequency, antibiotic exposure predicted from drinking water by Monte

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Carlo Simulation was compared with those based on urine to explore the role of

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antibiotics from drinking water in total antibiotic exposure. Analysis of variance was

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used to test for antibiotic concentration differences in tap water samples by their

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geographic locations in north, middle, and south parts of the city. Rank and

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chi-square test were used to test for the differences of concentration distributions and

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detection frequencies of urinary antibiotics between the urban and suburban schools,

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respectively. All statistical analyses were performed using the statistical software

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packages SPSS (version 17; SPSS, Inc., Chicago, IL, USA). A p-Value < 0.05 was

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considered statistically significant.

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RESULTS

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Of 21 antibiotics, only two phenicols (florfenicol and thiamphenicol) were

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detected in tap water samples with the median concentrations of 0.0089ng/mL and

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0.0064ng/mL, respectively (Table 1); only florfenicol was found in three bottled

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water samples from a same brand with the concentrations of 0.00060ng/mL,

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0.00076ng/mL, and 0.0010ng/mL, respectively; No antibiotics were detected in

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barreled water samples. Three phenicols (florfenicol, thiamphenicol, and

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chloramphenicol) were found in urines with a varying detection frequencies from 11



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6.0% to 34.2% and chloramphenicol showed a higher concentration than other two

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phenicols (Table 1). Besides florfenicol and thiamphenicol, additional 17 of 19

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antibiotics, except for roxithromycin and tylosin, were found in urines with the

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different detection frequencies from 0.4% (tetracycline) to 25.7% (sulfamethazine)

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(Table S2).

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Because the contamination level of florfenicol and thiamphenicol in tap water

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was higher than that in bottled or barreled water, their concentrations and probability

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distributions in tap water were assumed as those in drinking water. By the @Risk

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software, the probability distributions of florfenicol concentration in tap water were

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defined as the Gumbel distribution with a location of 8.0492 and a scale of 4.3112

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and those of thiamphenicol were defined as the Gumbel distribution with a location

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of 5.6133 and a scale of 3.2585. Figure 1 shows the probability distributions of daily

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exposure doses and urinary concentrations of florfenicol and thiamphenicol

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predicted from drinking water by Monte Carlo Simulation. The predicted urinary

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detection frequencies were 9.5% in boys and 5.8% in girls for florfenicol and 1.4%

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in boys and 0.6% in girls for thiamphenicol. The selected percentiles of predicted

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daily exposure doses and urinary concentrations were respectively listed in Tables

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S3 and S4. The averages of predicted daily exposure doses of florfenicol were

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0.00022 µg/kg/day in boys and 0.00019 µg/kg/day in girls and those of

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thiamphenicol were 0.00016 µg/kg/day in boys and 0.00014 µg/kg/day in girls. The

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averages of predicted urinary concentrations of florfenicol were 0.0056 ng/ml in

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boys and 0.0049 ng/ml in girls and those of thiamphenicol were 0.0034 ng/ml in 12


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boys and 0.0030 ng/ml in girls. These values were similar to those based on average

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values of body weight, daily drinking water consumption, concentrations of two

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phenicols in drinking water, or daily urine output by body weight (Table S5).

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The daily exposure doses and urinary detection frequencies of florfenicol and

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thiamphenicol based on urine were compared with those predicted from drinking

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water and the exposure level of florfenicol based on urine showed a higher level than

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that of thiamphenicol (Table 2). The detection frequencies of two phenicols based on

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urine were 3 to 11 times higher than those predicted from drinking water. The

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selected percentiles of daily exposure doses based on urine were 260 to 680 times

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higher than those from drinking water for florfenicol, and were 4 to 45 times for

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thiamphenicol. Besides two phenicols, the daily exposure doses of other 19

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antibiotics were also estimated (Table S6). The estimated daily exposure dose varied

278

greatly by antibiotics and some extremes exceeded 1mg/kg/day for some human

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antibiotics. Figure 2 shows that at least one antibiotic was found in 78.3% of

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children. Of them, 56.4% of children had a sum of estimated daily exposure doses of

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21 antibiotics less than 1.0µg/kg/day, 10.3% between 1.0µg/kg/day and

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10.0µg/kg/day, and 11.6% greater than 10µg/kg/day.

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Moreover, the concentrations of florfenicol and thiamphenicol in tap water were

284

similar among in the south, middle, and north parts of Shanghai (Table 3). Urinary

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concentrations and detection frequencies of thiamphenicol in children living in the

286

suburb located in the south part of Shanghai were found to be lower than those of

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children living in the downtown in the middle part of the city, but this phenomenon 13



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did not exist for florfenicol (Figure 3).

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DISCUSSION

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In this study, by screening 21 common antibiotics in representative drinking

291

water samples using two-dimensional UPLC-Q/TOF MS, two phenicols (florfenicol

292

and thiamphenicol) were detected in tap water, florfenicol was detected in some

293

bottled water, and no antibiotics were detected in barreled water. To our knowledge,

294

this study is the first time to comprehensively screen antibiotics in bottled and

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barreled water. In contrast, besides florfenicol and thiamphenicol, additional 17

296

antibiotics were detected in urines with varying detection frequencies and the

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predicted daily exposure of florfenicol and thiamphenicol from drinking water by

298

Monte Carlo Simulation were significantly lower than those based on urines. The

299

average values of daily exposure dose and urinary concentration for two phenicols

300

predicted by Monte Carlo Simulation were well matched with those based on

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average value of each variable. These findings indicated that drinking water was

302

contaminated by some antibiotics in Shanghai, but played a limited role in total

303

antibiotic exposure in children.

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Sources of antibiotics in drinking water

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Generally, the primary antibiotic source in aquatic environment is from the

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excretion of antibiotics used in animals and human as unchanged or conjugated

307

species in urine or faeces 13. Direct discarding during the use or production of

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antibiotics is another possible pathway 24. Antibiotics in aquatic environment have to

309

survive a series of drinking water treatment processes before residue in drinking 14


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water. Water treatment processing includes conventional techniques, such as

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coagulation, sedimentation, filtration, and chlorine disinfection, and relatively

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advanced techniques, such as reverse osmosis, ozone disinfection, and activated

313

carbon sorption. The removal efficiencies of these treatment techniques have been

314

tested for some antibiotics 25-27. In general, the conventional water treatment

315

techniques, except for chlorine disinfection, did not efficiently remove antibiotics,

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but the advanced techniques did, such as for amoxicillin, tetracycline,

317

oxytetracycline, sulfamethoxazole, sulfamethazine, trimethoprim, and erythromycin

318

26,27

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these technologies.

320

. However, there were no reports about the removing efficiency of phenicols by

A variety of antibiotics have been detected in the surface water of Yangtze

321

estuary and Huangpu River, which are the primary water sources of tap water in

322

Shanghai 28,29. Among them, phenicols, sulfonamides, trimethoprim, and macrolides

323

were frequently detected, followed by tetracyclines and fluoquinolones 29. However,

324

only two phenicols (florfenicol and thiamphenicol) were found in terminal tap water

325

in Shanghai in our study and their concentration ranges were comparable to those

326

reported for the surface water of Shanghai (0.91-110ng/L for florfenicol and

327

0.45-89.5ng/L for thiamphenicol) 29. Florfenicol was also found in some bottled

328

water produced from other water sources outside Shanghai in China. Besides

329

conventional water treatment techniques, some advanced techniques, such as ozone

330

disinfection and activated carbon filtration, have been introduced in water plants in

331

Shanghai. These results suggest that water treatment processing in Shanghai can 15



332

efficiently remove most antibiotic residues in source water, but not phenicols in the

333

basis of current advanced techniques used.

334

Drinking water and other possible sources of antibiotic exposures in children

335

Of 21 selected antibiotics, only florfenicol and thiamphenicol were detected in

336

drinking water. Their level of antibiotic contamination was higher in tap water than

337

that in bottled or barreled water. In the estimation of daily exposure dose from

338

drinking water, using tap water measurements could result in an overestimation of

339

true daily exposure dose of florfenicol and thiamphenicol from drinking water.

340

However, their predicted daily exposure dose and detection frequency were still

341

significantly and substantially lower than those based on the urine levels. Furthermore,

342

the concentrations of florfenicol and thiamphenicol in tap water were also found not

343

to change with those in urines by sampling sites. These data collectively indicated that

344

drinking water was not an important source of antibiotic exposure in children.

345

Generally, there are three sources for exposure of children to antibiotics: direct

346

utilization, drinking water, and food. After drinking water was ruled out as a primary

347

antibiotic exposure source, the primary exposure sources were inferred to be direct

348

utilization and/or contaminated food. Antibiotics can be divided into two groups

349

based on their application objects: one group is only used or preferred in animal and

350

another group is only used or preferred in human. The exposure sources of children

351

to antibiotics might depend on their applications: mainly via contaminated food for

352

antibiotics only used or preferred in animal and mainly via direct utilization for

353

antibiotics only used or preferred in human. Moreover, given that antibiotics only 16


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used or preferred in animal are used to prevent or treat diseases or as growth

355

promoters in breeding industry 30, their primary exposure source was likely to be

356

meat foods, such as derived from livestock, poultry, and aquaculture.

357

Comparative analysis

358

Only a few studies reported the contamination of antibiotics in tap water, which

359

partially supported our results 12,31. Leung et al found 11 common antibiotics in tap

360

waters from 13 cities in China, such as thiamphenicol, sulfamethoxazole,

361

sulfamethazine, azithromycin, trimethoprim, tylosin, and dimetridazole 31. Of them,

362

thiamphenicol were detected in tap water of Hangzhou in Zhejiang Province and

363

Nanjing in Jiangsu Province, and sulfamethoxazole, sulfamethazine, and

364

dimetridazole were detected in Shanghai. Some antibiotics were also found in tap

365

water in the USA and some countries in Europe and Asia, such as sulfamethoxazole,

366

sulfadiazine, trimethoprim, and azithromycin 11,32,33. The detection of antibiotics

367

might be related to antibiotic contamination extent in source water, water treatment

368

techniques, and/or sampling seasons 30,34.

369

However, there have been no reports about florfenicol contamination in tap water.

370

Several studies reported its contamination of surface water in other areas than

371

Shanghai in China 35-37, but few in other countries. For example, florfenicol were

372

detected in Jiulong River in Fujian Province 37, the reservoirs in North China 36, and

373

some river and pond waters in Jiangsu Province 35. Given that phenicols might not be

374

efficiently removed by current water treatment techniques and water treatment

375

processes were similar among water plants in China, it might be common for 17



376

florfenicol contamination in tap water in China.

377

Total antibiotic exposure and its implications for future studies

378

The sum of daily exposure dose of all 21 antibiotics showed that more than half

379

of children were exposed to antibiotics around 1.0 µg/kg/day level. Compared to the

380

dose level around or above mg/kg/day level resulting from their application, this can

381

be defined as a low-dose level. The risk factors related to antibiotic exposure are

382

relatively stable in a certain period, such as antibiotic use in human and veterinary

383

medicine, occurrence of infectious diseases, dietary habits, and antibiotic

384

contamination extent of aquatic environment and food, and therefore, a long-term

385

exposure to low-dose antibiotics was inferred to be the primary exposure mode in

386

children. The occurrence of low-dose antibiotics in children’s bodies could originate

387

from the exposure to low-level residues of antibiotics in food, or the metabolic

388

gradients of exposure to high-level antibiotics, such as from antibiotic use.

389

It is noteworthy that current studies about potential health hazards of antibiotics

390

are based on antibiotic use or relevant high-dose exposure at the mg/kg/day level and

391

most focused on short-term effects of high-dose antibiotic exposures 38, except that

392

bacteria resistance has only been investigated under a sub-lethal concentration of

393

antibiotics 39. Besides bacteria resistance, however, possible health consequences of

394

antibiotic exposure also include direct side effects, such as the effects on growth and

395

hematopoietic function of children 40,41, and health outcomes related to human

396

microbiome, such as psoriasis, inflammatory bowel disease (IBD), asthma, diabetes,

397

obesity, cardiovascular disease, and colorectal cancer 5,6. Because the significant 18


Page 18 of 34

Page 19 of 34


398

difference exists between two kinds of exposure modes, i.e. short-term exposure to

399

high-dose antibiotics and long-term exposure to low-dose antibiotics, more studies

400

are needed to clarify the effects of latter exposure mode on human health.

401

Strengths and limitations of the study

402

This study comprehensively assessed the antibiotic contamination of drinking

403

water in Shanghai by sampling representative terminal tap, bottled, and barreled

404

water. In the prediction of antibiotic exposure in children from drinking water, the

405

Monte Carlo Simulation considering the probability distributions of variables

406

provided more accurate estimates, compared to conventional estimation method

407

based only on mean or median. Moreover, total antibiotic exposure in children was

408

accurately estimated by the biomonitoring data of urinary antibiotics and daily

409

urinary creatine output, a key variable of estimating total antibiotic exposure, was

410

predicted for each child by their body heights, which could reduce the estimation

411

uncertainty, compared to the sex- and age-specific cutoff values as used in other

412

studies 21,22.

413

There were several limitations when interpreting the results. Firstly, the

414

assumption of antibiotic contamination level in tap water as that in drinking water

415

and the unconsidered effects of some cooking processes on degradation of antibiotics,

416

such as boiling, would overestimate the true daily antibiotic exposure dose from

417

drinking water, but this further enhanced the inference that drinking water played a

418

limited role in total antibiotic exposure in children. Secondly, in this estimation of

419

total antibiotic exposure based on urine, the ratio of antibiotic urine excretion rate to 19



420

urinary creatinine rate was assumed to be constant during a day, but antibiotic urine

421

excretion rate might be fluctuant during a day due to discontinuous antibiotic

422

exposure and their rapid metabolism rate 42, and then daily variation might exist in

423

the ratio. Thirdly, the urinary excretion proportion of low-dose antibiotics was also

424

assumed to be equal to that of high-dose antibiotics in the estimation of total

425

antibiotic exposure, but the excretion proportions of some antibiotic in urine were

426

dose-dependent 43,44. Due to a lack of pharmacokinetic data for low-dose antibiotic

427

exposure, a proportion of antibiotic excretion in urine based on the pharmacokinetics

428

at high-dose antibiotic exposure was used identically.

429

ACKNOWLEDGMENTS

430

This work was supported by Research Initiation Funds for New Teacher of

431

Fudan University (No. JJF201204), Natural Science Foundation of China (No.

432

81373089), 985 Innovation Platform Project for Superiority Subject of Ministry of

433

Education of China (No. EZF201001), and Scientific Research Foundation for

434

Health Field, National Health and Family Planning Commission of China (No.

435

201202012).

436

SUPPORTING INFORMATION AVAILABLE

437

Additional text and six tables provided details of analytical method of

438

antibiotics in drinking water and urine, urinary excretion proportions of 21

439

antibiotics as unchanged and glucuronide-conjugated species, predicted daily

440

exposure doses and urinary concentrations of florfenicol and thiamphenicol from

441

drinking water, urinary detection frequencies and concentrations of 18 antibiotics in 20


Page 20 of 34

Page 21 of 34


442

school children, urinary concentrations and daily exposure doses of two phenicols

443

based on average values of each variable, and daily exposure dose estimates of 21

444

antibiotics based on urines. This information is available free of charge via the

445

Internet at http://pubs.acs.org.

446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 21



464 465 466 467 468 469 470 471 472 473 474 475 476

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572 573

26


doses. Antimicrob.

Page 27 of 34


574

Figure caption:

575

Figure 1. Probability distribution of predicted daily exposure dose (DED) (A1, A2,

576

B1, and B2) and urinary concentrations (C1, C2, D1, and D2) of florfenicol and

577

thiamphenicol from drinking water by Monte Carlo Simulation (n=10000) (In A1,

578

A2, B1, and B2, red section of top bar indicates the 99th percentile of predicted daily

579

exposure doses; In C1, C2, D1, and D2, red fragmentation of top bar indicates

580

proportion of predicted urinary concentrations greater than limits of detection (LODs)

581

among all predicted urinary concentrations; Both LODs of two phenicols are 0.01

582

ng/mL).

583

Figure 2. Frequency distribution of sum of daily exposure dose estimates of all

584

antibiotics (n=518).

585

Figure 3. Comparison of urinary concentration (a) and detection frequency (b) of

586

florfenicol and thiamphenicol in children from between the downtown (n=222) and

587

suburb (n=308) of Shanghai (The difference of urinary concentration and detection

588

frequency were analyzed by rank sum test and Chi square test, respectively; *:

589

p-Value＜0.001 ).

27



590

591 592 593 594 595 596 597 598 599 600 601 602 603 604

Table 1. Detection frequency and concentration (ng/mL) of phenicols in tap water and urines. Antibiotics Tap water (n=46) Urine (n=530) a n (%) Average Median (min-max) n (%) a Percentiles 50th 70th Florfenicol 46 (100) 0.011 0.0089 (0.00082-0.024) 181 (34.2) 0.05 Chloramphenicol 0 120 (22.6) Thiamphenicol 46 (100) 0.0076 0.0064 (0.00084-0.023) 32 (6.0) a , Positive detection (detection frequency, %); -: Less than LOD.

28


Page 28 of 34

Max 75th 0.06 -

95th 0.33 0.56 0.02

99th 2.74 32.98 0.06

67.71 157.38 0.88

Page 29 of 34

605

606 607


Table 2. Comparison of antibiotic exposure between predicted from drinking water by Monte Carlo Simulation and based on urine. Antibiotics sex Predicted exposure from drinking water (n=10000) Total exposure based on urine (n=518) a b n(%) Percentiles Max n(%) c Percentiles b Max 50th 75th 95th 99th 50th 75th 95th 99th Florfenicol Boy 950(9.5) 0.00046 0.00064 0.0013 95(35.8) 0.039 0.12 0.26 0.38 Girl 580(5.8) 0.00040 0.00056 0.0013 80(31.6) 0.031 0.16 0.38 0.40 Thiamphenicol Boy 140(1.4) 0.00048 0.0012 15(5.7) 0.00044 0.0022 0.0050 Girl 60(0.6) 0.0008 17(6.7) 0.0013 0.023 0.036 a b c , Predicted positive detection (predicted detection frequency, %); , Selected percentiles of daily exposure dose (µg/kg/day); , Actual positive detection (actual detection frequency, %); -: Less than LOD.

29



608 609

610

Table 3. Concentrations of two phenicols in tap waters by their geographic locations in north, middle, and south parts of Shanghai. Location Florfenicol Thiamphenicol North (n=15) 0.011±0.0059 a 0.0081±0.0044 Middle (n=16) 0.011±0.0055 0.0084±0.0053 South (n=15) 0.0096±0.0049 0.0061±0.0036 p-Value b 0.726 0.324 a , Mean±SD (ng/mL) ; b, Analysis of variance

30


Page 30 of 34

Page 31 of 34


Figure 1. Probability distribution of predicted daily exposure dose (DED) (A1, A2, B1, and B2) and urinary concentrations (C1, C2, D1, and D2) of florfenicol and thiamphenicol from drinking water by Monte Carlo Simulation (n=10000) (In A1, A2, B1, and B2, red section of top bar indicates the 99th percentile of predicted daily exposure doses; In C1, C2, D1, and D2, red fragmentation of top bar indicates proportion of predicted urinary concentrations greater than limits of detection (LODs) among all predicted urinary concentrations; Both LODs of two phenicols are 0.01 ng/mL). 179x243mm (300 x 300 DPI)



Figure 2. Frequency distribution of sum of daily exposure dose estimates of all antibiotics (n=518). 82x80mm (300 x 300 DPI)


Page 32 of 34

Page 33 of 34


Figure 3. Comparison of urinary concentration (a) and detection frequency (b) of florfenicol and thiamphenicol in children from between the downtown (n=222) and suburb (n=308) of Shanghai (The difference of urinary concentration and detection frequency were analyzed by rank sum test and Chi square test, respectively; *: p-Value＜0.001 ). 106x133mm (300 x 300 DPI)



TOC ART 85x39mm (300 x 300 DPI)


Page 34 of 34

Antibiotics in Drinking Water in Shanghai and Their Contribution to

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