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Ecotoxicology and Human Environmental Health
Chronic Exposure to an Environmentally Relevant Triclosan Concentration Induces Persistent Triclosan Resistance but Reversible Antibiotic Tolerance in Escherichia coli Mingzhu Li, Yuning He, Jing Sun, Jing Li, Junhong Bai, and Chengdong Zhang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b06763 • Publication Date (Web): 21 Feb 2019 Downloaded from http://pubs.acs.org on February 21, 2019
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Chronic Exposure to an Environmentally Relevant Triclosan Concentration
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Induces Persistent Triclosan Resistance but Reversible Antibiotic Tolerance
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in Escherichia coli
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Mingzhu Li, 1 Yuning He, 1 Jing Sun, 1 Jing Li, 1 Junhong Bai,2 Chengdong Zhang 2, *
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1
College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
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2
School of Environment, Beijing Normal University, Beijing 100875, China
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Manuscript prepared for Environmental Science & Technology
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* Corresponding author: (Phone/fax) 86-10-58802029.
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E-mail address:
[email protected].
19 20 21 22 23
Postal address: School of Environment Beijing Normal University No. 19, XinJieKouWai St., HaiDian District, Beijing, P. R. China 100875
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ABSTRACT The major concern regarding the biocide triclosan (TCS) stems from its potential
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coselection for antibiotic resistance. However, environmental impacts are often
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investigated using high concentrations and acute exposure, while predicted releases are
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typified by chronic low concentrations. Moreover, little information is available
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regarding the reversibility of TCS and derived antibiotic resistance with diminishing TCS
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usage. Here, the model Gram-negative bacterium Escherichia coli was exposed to 0.01
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mg/L TCS continuously for more than 100 generations. The adapted cells gained
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considerable resistance to TCS as indicated by a significant increase in the minimal
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inhibitory concentration (MIC50) from 0.034 to 0.581 mg/L. This adaptive evolution was
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attributed to overexpression and mutation of target genes (i.e., fabI) as evidenced by
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transcriptomic and genomic analyses. However, only mild tolerance to various antibiotics
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was observed, possibly due to reduced membrane permeability and biofilm formation.
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After TCS exposure ceased, the adapted cells showed persistent resistance to TCS due to
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inheritable genetic mutations, whereas their antibiotic tolerance declined over time. Our
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results suggest that extensive use of TCS may promote the evolution and persistence of
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TCS-resistant bacterial pathogens. Quantitative definition of the conditions under which
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TCS selects for multidrug resistance in the environment is crucially needed.
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INTRODUCTION Triclosan [TCS; 5-chloro-2-(2,4-dichlorophenoxy)phenol] is widely used in
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personal care products (e.g., toothpaste, soap and body wash) as an antimicrobial agent 1.
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TCS is used in large quantities on a global scale, resulting in high residual levels in water.
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For example, its concentration ranges from 2 × 10-7 to 4.78 × 10-4 mg/L in surface water,
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and it can be detected in amounts as high as 8.62 × 10-2 mg/L and 5.37 × 10-3 mg/L,
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respectively, in wastewater influent and effluent 2. In particular, most TCS preferentially
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adsorbs onto carbon and lipid-rich sludge 3, 4. Therefore, the levels of TCS in digested
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sewage sludge were reported to be as high as 133 mg/kg dry weight, with a mean
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concentration of approximately 16 ± 65 mg/kg dry weight (± standard deviation (SD)) 1, 5.
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Given the massive amount of TCS released into the environment, the
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microorganisms living in contaminated environments may have evolved certain
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mechanisms to tolerate/resist this biocide. For example, pathogenic bacteria, such as
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Salmonella enterica 6, 7, Escherichia coli 8, 9 and Pseudomonas aeruginosa 10, 11, are
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currently less susceptible to TCS than they were in the past. The mechanisms of TCS
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resistance include target gene mutation 12, target gene overexpression 13, induction of
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efflux pumps 14, reduced membrane permeability 15, and TCS transformation or
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degradation 16. However, the typical concentrations of TCS used for these evolutionary
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studies have ranged from 0.195 mg/L to 2.05 ×103 mg/L 17-20, which are much higher
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than realistic environmental concentrations. The incubation times studied have generally
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varied between 24 h and 20 days, which is a short period of time compared to years of
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exposure in the environment. Moreover, beginning in September 2017, the FDA
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prohibited the sale of "consumer antiseptic washes" containing TCS. Information 4 ACS Paragon Plus Environment
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regarding whether TCS resistance would decrease or disappear in response to suddenly
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reduced concentrations is lacking.
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TCS and its derivatives are considered a group of endocrine disruptors 1, 5, and an
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emerging toxic outcome of concern is the potential link between TCS exposure and
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coselection on antibiotic resistance. For instance, at a concentration of 0.2 mg/L, TCS
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induces multidrug resistance in wild-type E. coli after 30 days of exposure 21. In this
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study, TCS exposure-induced mutants demonstrated greater than 6-fold increases in the
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MIC90 (the minimum inhibitory concentration that kills 90% of bacteria) against three
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beta-lactam antibiotics, including ampicillin, cephalexin and amoxicillin. The
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mechanisms that confer cross-resistance to antibiotics are induction of a multidrug efflux
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pump and decreased influx or membrane permeability 16. Nevertheless, whether TCS can
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directly trigger antibiotic resistance at environmentally relevant concentrations remains
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under debate. Determining whether the antibiotic resistance associated with TCS
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resistance will be reversible after the sudden decline in consumer usage is equally
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important.
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The goals of this project were (1) to determine whether prolonged exposure of the
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model bacterium E. coli to an environmentally relevant concentration of TCS can trigger
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TCS resistance and examine the associated mechanism and its hereditary stability, and
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(2) to experimentally investigate cross-resistance/tolerance to antibiotics and the
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reversibility of such cross-resistance/tolerance. The results indicated that chronic TCS
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exposure may be linked to a significant increase in TCS resistance accompanied by a
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moderate rise in drug tolerance. Once the stressor was removed, TCS resistance lasted
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more than 20 generations, whereas stress-induced antibiotic tolerance eventually
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disappeared. Our study reveals that implementing environmental emission limits for TCS
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would be an effective strategy to prevent preferential selection for antimicrobial
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resistance.
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MATERIALS AND METHODS Strains and the evolution experiment. TCS (purity ≥ 99%) and dimethyl
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sulfoxide (DMSO) were purchased from Sigma-Aldrich, USA. TCS stock solution (100
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mg/L) was prepared in DMSO. To prepare 0.01-mg/L TCS solution, 5 μL of stock
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solution was added to 50 mL of Luria-Bertani (LB) medium 22, 23. Silicide glassware was
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used throughout the experiment to prevent TCS adsorption. Escherichia coli K-12 strain
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MP1 was obtained from the Agricultural Culture Collection of China (ACCC, Beijing).
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E. coli was incubated in LB medium containing 0.01 mg/L TCS at 37°C under
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continuous shaking (160 rpm). Every 24 h, 1 mL of bacterial suspension was transferred
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to fresh medium containing the same amount of TCS. The process was repeated for 100
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subculture cycles, and the TCS-adapted strain was termed ETCS (adapted cells). The
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selected concentration of 0.01 mg/L in this study represents various degrees of
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contamination in receiving waters, e.g., hotspots in surface water 21, the medians in
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wastewater influent 24 and high residual levels in effluent 25.
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Bacterial growth and MIC50 determination. Cells (both wild-type E. coli and
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ETCS) were collected via centrifugation at 8000 ×g for 10 min at 4°C, washed with saline
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(0.9% NaCl) three times (to remove residual TCS and metabolites), and then resuspended
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in saline to achieve a concentration of 107-108 CFU/mL. One milliliter of cell suspension
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was inoculated into 49 mL of sterilized LB medium in the presence or absence of 0.02
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mg/L TCS, and the optical density was measured at 600 nm (OD600) with a UV-Vis
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spectrophotometer (Cary 100 UV-Vis, Agilent Technologies, USA) over 12 h. The MIC50
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was determined as the concentration of TCS that inhibited 50% of bacterial growth after
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12 h of incubation.
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Ribonucleic acid (RNA) preparation, library construction and quantitative
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real-time polymerase chain reaction (qRT-PCR) validation. Detailed descriptions of
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RNA isolation, RNA sequencing, reverse transcription, and qRT-PCR can be found in the
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Supporting Information (SI). The primers used for PCR were designed by Sangon
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Biotech (Shanghai, China) and are listed in Table S1. RNA-sequencing data analysis. Clean reads were mapped to the Escherichia coli
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K-12 MG1655 genome assembly using TopHat software 26. Fragments per kilobase of
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exon model per million mapped reads (FPKMs) values for each gene and differentially
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expressed genes (DEGs) were analyzed with Cufflinks v2.2.1. The DEGs between the
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two samples were identified by considering both fold changes (log2FC > 1) and p-values
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(p < 0.005). Hierarchical clustering analysis was performed using the FPKMs of DEGs of
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E. coli, E. coli + TCS (wild-type cells exposed to 0.02 mg/L TCS) and ETCS + TCS
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(adapted cells exposed to 0.02 mg/L TCS).
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Deoxyribonucleic acid (DNA) extraction, whole-genome sequencing and data
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processing. Genomic DNA was extracted using the FastDNATM SPIN Kit for Soil (MP,
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USA). The Nextera XT DNA Sample Preparation Kit (Illumina, USA) was used to
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prepare a whole-genome sequencing library, which was sequenced by Allwegene
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BioTech Co. using a MiSeq instrument (Illumina). Two biological replicates were
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performed in each group. Escherichia coli K-12 MG1655 (NCBI reference sequence
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NC000913.3) was used as the reference genome sequence. Further details are given in the
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SI.
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Determination of the fatty acid composition of bacterial membranes. Fatty acids in bacterial membranes were extracted using the method reported by Yang et al. 27
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with some modifications. Fatty acid methyl ester was measured by gas chromatography
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(7890A, Agilent Technologies) analysis on a device equipped with a flame ionization
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detector and a capillary column HP-5 (30 m, 0.32 mm, 0.25 μm, Agilent Technologies);
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see the SI for detailed descriptions. All treatments were performed in triplicate, and the
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data are displayed as the means ± SD.
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Biofilm characterization by confocal laser scanning microscopy. Cells were
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grown statically in the presence of 0.02 mg/L TCS for 24 h. Biofilms on the bottoms of
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culture dishes were stained with the LIVE/DEAD BacLight Bacterial Viability Kit
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(L13152, ThermoFisher Scientific Inc.) 28 and were visualized by confocal laser scanning
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microscopy (Zeiss, LSM880 with Airyscan, Germany). See the SI for details.
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Antibiotic sensitivity tests. The MIC50 values to various antibiotics (i.e., penicillin,
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kanamycin, gentamicin and ciprofloxacin) were determined as the concentration of the
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corresponding antibiotic that inhibited 50% of bacterial growth (wild-type E. coli.).
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Antibiotic sensitivity was measured by evaluating survival following antibiotic exposure.
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Wild-type E. coli and ETCS were collected at the exponential phase of growth, and 1-mL
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aliquots of cell suspension were added to 49 mL of sterilized LB medium containing 1 ×
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MIC50, 2 × MIC50, and 4 × MIC50 concentrations of the corresponding antibiotics and
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incubated at 37°C for 12 h. The optical density was measured at 600 nm (OD600). Each
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strain was tested in triplicate, and sterilized LB medium was used as a blank control.
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Reversibility of TCS resistance and antibiotic tolerance. The reversibility of
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resistance/tolerance to TCS and antibiotics in adapted ETCS was determined by
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subculturing in TCS-free medium. Briefly, after 100 subcultures, ETCS species were
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collected, washed and re-suspended in saline. One milliliter of microbial suspension was
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inoculated into 49 mL of fresh LB medium without TCS, followed by 24 h of incubation.
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The process was repeated for 20 additional cycles, and changes in the MIC50 to TCS was
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monitored. Alterations in antibiotic tolerance were also evaluated every 5 subcultures by
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monitoring the OD600 after 12 h of incubation in the presence of 25 mg/L penicillin. After
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TCS exposure was ceased, the biofilm formation of ETCS was visualized by confocal laser
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scanning microscopy.
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Statistical analysis. At least three replicates were run per treatment. All data were
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expressed as the means ± SD, and statistical differences were determined by an
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independent t test or one-way analysis of variance (ANOVA). A p-value less than 0.05
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(*) or 0.01 (**) indicated a significant difference.
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RESULTS AND DISCUSSION
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Development of TCS resistance. Following exposure to 0.01 mg/L TCS for more
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than 100 generations (> 100 days), E. coli developed high resistance to TCS as indicated
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by the loss of growth inhibition at 0.02 mg/L TCS (Figure 1a) and marked augmentation
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of the MIC50 from the original 0.033 mg/L to 0.562 mg/L (Figure 1b). The observed
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resistance degree may not be as pronounced as that reported previously 8, 18, 19, which was
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possibly due to the fluctuating culture conditions (e.g., the TCS concentration, exposure
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time, and bacterial strain) under different treatments. In particular, we did not select the
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potential mutant strain for this purpose. Instead, the susceptibility of the overall
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population was assessed; thus, the tolerance profile can be maintained undisturbed.
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Meanwhile, we did not observe any obvious morphological changes in the bacteria after
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chronic exposure (Figure S1).
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In general, the resistance evolution model presumes a trade-off between resistance
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and fitness costs in the adapted populations in the absence of pollutant 29. However, no
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detrimental effect on fitness was observed in the adapted population (as indicated by no
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growth reduction in the adapted cells in the absence of TCS, as shown in Figure 1a),
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indicating that the major resistance mechanism was related to alteration of specific target
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genes rather than stress-induced global physiological changes. Thus, the molecular
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mechanisms responsible for TCS resistance were determined by transcriptional analysis.
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Illumina sequencing data of the tested samples are shown in Table S2 and Table S3. The
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fold changes of the DEGs are displayed in the SI (Excel file 1). The transcriptomic data
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were selectively validated via qRT-PCR analysis (Figure 2a). Upon exposure to 0.02
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mg/L TCS, the total number of DEGs in adapted cells was notably lower than that in
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wild-type cells using E. coli alone as a biotic control (Figure 2b). The response pattern of
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the adapted cells was grouped together with that of the untreated wild-type cells and was
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distinct from the acute response in wild-type cells (Figure 2c). Collectively, the TCS
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resistance mechanism was mostly attributed to alterations of target genes.
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Chronic exposure to TCS triggers differential expression and mutation of
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target genes. We focused on modifications of target gene expression in adapted cells.
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TCS targets enoyl-acyl carrier protein reductases, blocking bacterial type II fatty acid
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synthesis 30. Reportedly, fabI, which catalyzes the final step in each fatty acid elongation
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cycle, is an important target of TCS 31. Kyoto Encyclopedia of Genes and Genomes
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(KEGG) analysis verified that fatty acid-related pathways (i.e., synthesis, metabolism,
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and degradation) were differentially enriched in adapted cells relative to wild-type E. coli
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upon TCS exposure (Figure 3a). The KEGG enrichment analysis of DEGs between ETCS
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and E. coli is displayed in the SI (Excel file 2). A summarized sketch of the key genes
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involved in fatty acid synthesis in Figure 3b (quantified via qRT-PCR analysis) shows
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differential expression levels of selected genes that are influenced by chronic TCS
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exposure. Among them, fabI was significantly upregulated (log2 FC > 2.8), corroborating
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the overexpression of target genes (Figure 3b and Figure 2a). Overexpression of fabI in
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TCS-resistant bacteria has been previously observed for Staphylococcus aureus 32, 33 and
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E. coli 8, 34.
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Moreover, to reveal the genetic changes involved in TCS resistance, we conducted
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whole-genome sequencing on ETCS and wild-type E. coli. TCS inhibits bacterial fatty acid
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synthesis by binding enoyl reductase; therefore, missense mutations in target genes may
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reduce TCS efficacy by altering the structures of the target proteins, i.e., fabI, fabB, fabD
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and fabZ (Figure 4). Mutation in fabI after TCS exposure was also reported for S. aureus
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following ten passages with a gradient of TCS exposure concentrations 17 and for E. coli
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with exposure to 0.2 mg/L TCS for 30 days 21. Notably, in different studies, the mutation
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patterns may not be identical even for the same target gene due to dissimilar evolutionary
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mechanisms. Other mechanisms conferring multidrug resistance, such as changes in the
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outer membrane and biofilm formation, may also actively participate in TCS resistance
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and are discussed below.
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TCS treatment induces mild multi-antibiotic tolerance. TCS is generally
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thought to induce coselection for antibiotic resistance; thus, we tested the susceptibility of
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TCS-resistant bacteria to various types of antibiotics (i.e., beta-lactam, aminoglycoside,
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and quinolone compounds). TCS-resistant cells showed decreased susceptibility to
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antibiotics, i.e., penicillin, gentamicin, kanamycin, and ciprofloxacin, to various extents
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(Figure 5). However, the tolerance degree was not specifically relevant to any class of
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antibiotic (i.e., beta-lactam, aminoglycoside, and quinolone). The increases in antibiotic
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cross-tolerance were less strong than those previously reported for TCS-resistant bacteria
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18, 20, 21.
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of wild-type E. coli (Figure S2). In studies performed on E. coli and P. aeruginosa, the
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MIC50 to chloramphenicol and tetracycline increased 10-fold following TCS exposure 16.
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This discrepancy was attributed to the low dose of TCS utilized in our study (0.01 mg/L);
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at this concentration, TCS did not trigger significant reactive oxygen species (ROS)
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generation or cell growth inhibition (Figure S3). Thus, antibiotic-resistant mutations via
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the ROS stress response system 35 were less effective, which can be verified by the
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unaltered mutation frequency 36 (data not shown, see the SI for the mutagenesis assay).
For example, the MIC50 of penicillin for ETCS was only 1.76-fold greater than that
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Alteration of the membrane structure and biofilm formation were responsible
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for antibiotic tolerance. Fatty acids are important components of the phospholipids that
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form the phospholipid bilayers out of which cell membranes are constructed. Thus,
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interference with fatty acid synthesis by TCS results in alterations in the membrane
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structure (Table 1) that diminish antibiotic uptake. The ratio of saturated to unsaturated
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fatty acids rose from 0.64 ± 0.05 to 0.74 ± 0.04 (p < 0.05), indicating a decrease in
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membrane permeability. Similar fatty acid compositional changes in the cell membrane
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have been observed in E. coli, Bacillus subtilis and other bacteria subjected to various
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environmental stresses, e.g., nanoparticles 37, 38 and environmental pollutants 39.
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However, the degree of alteration in the relative proportions of fatty acids in this study
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may not be as high as that reported in acute toxicity tests 37, 38. One possible explanation
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is that alteration of the membrane structure is an adaptive strategy adopted in evolved
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bacteria rather than an acute detrimental effect. Inhibition of membrane activity (i.e.,
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intercalation into the bacterial cell membrane) due to acute TCS exposure has been
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described previously 40, 41. However, this may be the first report of a protective response
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from cells via alteration of the membrane structure with chronic TCS exposure.
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Interestingly, TCS exposure induced notable biofilm formation in adapted cells, as
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shown in Figure 6. Sublethal concentrations of chemicals (e.g., biocidal, antibiotic, and
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quorum-sensing molecules) can promote biofilm development, which is an adaptive
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strategy of bacteria to cope with various environmental stimuli 42, 43. Biofilm-associated
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cells show low susceptibility to TCS due to limited diffusion 15, which may also be an
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important mechanism underlying the observed antibiotic tolerance.
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Meanwhile, efflux is another common resistance strategy, and exposure to TCS has
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been reported to effectively upregulate efflux pump genes in a few studies 19, 44. E. coli
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harbors a large number of efflux pumps with a wide spectrum of substrates, and the most
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relevant efflux pump for multidrug transporters is acrAB-tolC (the resistance nodulation
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and cell division (RND) efflux pump) 45. However, we did not detect significant
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upregulation of the acrAB-tolC pump based on our transcriptomic analysis. In contrast,
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the pathway encoding ATP Binding Cassette (ABC) transporters (another type of efflux
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pump) was enriched in adaptive cells according to the KEGG analysis (Figure 3a). The
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enhanced expression of the ABC transporter-coding genes cysPU, ydcVTUS and gltI was
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validated by qRT-PCR analysis (Figure 2a). Since only a few members of this family
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have been identified as multidrug exporters in prokaryotes 46, we tentatively infer that the
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contribution of the induction of efflux pumps to antibiotic tolerance in this study is
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limited. Collectively, at environmentally relevant concentrations, TCS appears to affect
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only the target genes and may not induce overall oxidative stress, thus avoiding triggering
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overexpression of a specific efflux pump.
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Persistent TCS resistance and reversible antibiotic tolerance. Whether reduced
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TCS use will influence the evolved resistant strains to regain TCS susceptibility and lose
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their derived antibiotic resistance/tolerance traits over time is still unclear. The MIC50 of
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ETCS to TCS decreased slightly after stopping exposure for 20 generations (Figure 7a) but
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was still greater than 16-fold higher than that of wild-type E. coli. The hereditary stability
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assay suggested the ETCS can stably transfer resistance to their offspring. This effect was
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attributed to inheritable resistance via genetic mutations at target sites because
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transcriptional regulation alone (i.e., overexpression of target genes in response to stress)
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cannot induce transgenerational inheritance of acquired traits 47, 48.
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However, the tolerance of ETCS towards penicillin dropped markedly as a function
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of time, and after 20 generations, the evolved tolerance approached the wild-type level
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(Figure 7b). Simultaneously, the level of biofilm formation returned to normal (similar to
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that of wild-type E. coli) (Figure 7c), which further strengthened our conclusion that
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antibiotic tolerance was largely attributed to biofilm formation. Little information is
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currently available regarding the reversibility of TCS exposure-induced antibiotic
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resistance in adapted bacteria and related mechanisms. Some sporadic data suggest that
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most antibiotic resistance mechanisms are associated with a fitness cost, and that the
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magnitude of the fitness cost determines the stability of resistance 49. Accordingly, the
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lack of fitness cost in the current study implies that at the 0.01-mg/L concentration, TCS
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triggered antibiotic tolerance mostly via functional adjustments (i.e., alteration of
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membrane permeability and biofilm formation), which were unstable and not heritable.
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Notably, the environmental concentration of TCS will drop gradually (not sharply) due to
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continuous usage in other products, and how the attenuation effect influences the
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dissipation of antibiotic resistance is of interest.
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ENVIRONMENTAL IMPLICATIONS
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This study demonstrated that chronic exposure of E. coli to an environmentally
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relevant TCS dose induced transgenerational TCS resistance but non-heritable multidrug
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tolerance. This work reveals that reduced release of TCS may be an efficient approach to
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mitigate the propagation of antibiotic resistance. Future studies are needed to determine
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the threshold concentration of TCS and the breakthrough time point that trigger
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pathogenic evolution. Identifying the behavior of horizontal gene transfer (another means
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of acquiring antibiotic resistance) in the presence of low-dose TCS is equally important.
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This information will be critical for accurate quantitative predictions regarding the impact
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of TCS on the emergence and spread of resistant bacteria in the environment.
313 314
Supporting Information Availability: Supporting information is available free of charge
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on the Internet at…
316
The detailed procedures for RNA preparation and library construction,
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transcriptomic analysis, qRT-PCR validation, DNA extraction, whole-genome
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sequencing and data processing, preparation of membrane samples for fatty acid
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composition determination, transmission electron microscopy analysis of bacterial
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morphology, measurement of intracellular ROS and the mutagenesis assay are described.
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The primers used in the qRT-PCR analysis and their target classification are provided
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(Table S1); Sequencing and assembly statistics for the transcriptomic data (Table S2);
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The distributions of genes at differentially expressed levels (Table S3); Summary of the
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total numbers of differentially expressed genes in ETCS + TCS compared to those of E.
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coli + TCS (Excel file 1); KEGG enrichment analysis of differentially expressed genes
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between ETCS and E. coli (upregulated) (Excel file 2); TEM images showing no obvious
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morphological change in adapted ETCS compared with wild-type E. coli (Figure S1);
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MIC50 determination of E. coli and ETCS towards penicillin (Figure S2); No obvious
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adverse effect of 0.01 mg/L TCS on bacterial growth and intracellular ROS production
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(Figure S3).
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Acknowledgments. This project was supported by the National Natural Science
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Foundation of China (Grant 21777077). Partial support was also provided by the
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Fundamental Research Funds for the Central Universities and the Interdiscipline
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Research Funds of Beijing Normal University.
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Notes― The authors declare no competing financial interests.
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(b)
0.8
E. coli E. coli + 0.02 mg/L TCS ETCS ETCS + 0.02 mg/L TCS
0.6
OD600
Percentage of OD600 (Relative to E. coli alone)
(a)
0.4 0.2 0.0 0
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E. coli ETCS
100 80 60
MIC50 = 0.033 mg/L
40 20
MIC50 = 0.562 mg/L
0 0.0 0.04 0.08 0.12 0.2 0.4 0.6 0.8 1.0 1.2
12
Time (h)
TCS concentration (mg/L)
Figure 1. ETCS developed considerable resistance to TCS. a) Growth curves of E. coli and ETCS in the presence or absence of 0.02 mg/L TCS; b) The MIC50 of E. coli and ETCS towards TCS. Cells were incubated in LB medium containing various concentrations of TCS for 12 h. The MIC50 values were calculated by fitting the data using the fourparameter logistic curve in Sigma Plot v10.0. Error bars, which are smaller than the symbols in some cases, represent the SD of triplicate experiments.
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Log2 fold change
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RNA-seq data qRT-PCR data
qRT-PCR data
(a)
8 6
R2 = 0.8483 4
3
2
2
4
4
6
10
8
RNA-seq data
2 0 atoB
fabI
atoA
atoE
Fatty acid metabolism
torC
torD
Quorum sensing
gadB
gmr
ydcV
ydcT
Two-component system
Gene name
(b)
ydcS
ydcU
cysP
cysU
ABC transporters
(c) 1
E. coli + TCS
0.5
ETCS + TCS
0 -0.5 -1
869
161
128
E. coli + TCS ETCS+ TCS E. coli
496 497 498 499 500 501 502 503 504 505 506 507
Figure 2. Transcriptomic analysis revealed different response patterns of E. coli and ETCS upon exposure to 0.02 mg/TCS for 5 h. (a) Validation of RNA sequencing data via qRTPCR analysis of selected genes. The inset shows the correlation analysis between RNAseq and qRT-PCR results from the same RNA samples. The Spearman correlation coefficient expresses the strength of the relationship between the RNA-seq and qRT-PCR variables. (b) Venn diagram comparing the number and overlap of DEGs in E. coli and ETCS in response to 0.02 mg/L TCS. (c) Dendrogram and unsupervised hierarchical clustering heat map (using Euclidean distance) of gene expression based on the log ratio FPKM data. Untreated E. coli was used as a biotic control. The qRT-PCR results of three biological replicates are shown as the mean values ± SD. RNA sequencing analysis was performed using two biological replicates.
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509 510 511 512 513 514 515 516
Figure 3. Functional enrichment analysis shows that pathways related to fatty acids are significantly impacted by TCS exposure. (a) KEGG enrichment analysis of DEGs (upregulated) in ETCS compared with E. coli based on transcriptomic sequencing data. (b) Quantification of DEGs relevant to fatty acid synthesis in ETCS compared with that in E. coli via qRT-PCR analysis. For both transcriptomic and qRT-PCR analyses, wild-type E. coli and adapted ETCS were exposed to 0.02 mg/L TCS in LB medium for 5 h, and E. coli alone was used as a biotic control.
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(b)
(a)
fabD fabI
ETCS1 ETCS2 fabB
fabZ
Gene Changes Site Annotation fabD T → G 84115 F275V fabD C → T 84165 T291T fabI G → A 312262 N227N fabI A → C 312376 A189A fabI A → G 312478 N155N fabI T → C 312520 L141L fabI A → G 312616 T109T fabI T → C 312738 T69A fabB G → T 277083 T384T fabB A → G 277407 G276G fabB G → A 277440 D265D fabB C → A 277893 V114V fabB A → G 277899 F112F fabZ A → G 21509 F101F fabZ G → A 21530 A94A
517 518 519 520 521 522 523 524 525
Figure 4. The whole-genome sequencing analysis showing genetic mutations in target sites. (a) Genetic mutations annotated for adapted ETCS. Sequencing coverage for each clone (two biological replicates, ETCS1 and ETCS2, under 0.01-mg/L TCS exposure for 100 subcultures) is plotted according to color on concentric tracks. Each genetic change related to fatty acid synthesis, represented by colored dots, is marked at the appropriate genomic position. The outer circle represents the 4.8-Mb E. coli reference genome. (b) Table showing the list of corresponding gene mutations and annotations in ETCS according to Fig. 4a.
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100
60
Growth inhibition (% of E. coli alone) 528 529 530 531 532 533 534 535
**
40 20 1 × MIC50 2 × MIC50
Penicillin
120 100
E. coli ETCS
(d) *
**
60
*
40 20 1 × MIC50 2 × MIC50
120
Gentamicin
**
80
*
60 40 20
1 × MIC50 2 × MIC50
4 × MIC50
Kanamycin
120
E. coli ETCS
100
*
80
**
60 40 20 0
4 × MIC50
E. coli ETCS
100
0
4 × MIC50
80
0
527
**
80
0
(c)
(b) E. coli ETCS
Growth inhibition (% of E. coli alone)
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Growth inhibition (% of E. coli alone)
Growth inhibition (% of E. coli alone)
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1 × MIC50 2 × MIC50
4 × MIC50
Ciprofloxacin
Figure 5. TCS-resistant bacteria (ETCS) exhibit less susceptibility to various types of antibiotics compared to E. coli. The inhibition rate of bacterial growth in the presence of various concentrations of (a) penicillin; (b) kanamycin; (c) gentamicin and (d) ciprofloxacin are shown. Bacteria were exposed to various concentrations of antibiotics at 37 °C for 12 h in LB medium. The MIC50 refers to the antibiotic concentration that inhibits 50% of wild-type E. coli growth. All experiments were performed at least in triplicate, and the results are expressed as the mean values ± SD. * and ** denote p < 0.05 and p < 0.01 compared to E. coli under the same treatment, respectively.
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PI
Merge
ETCS
E. coli
SYTO 9
537 538 539 540 541
Figure 6. Confocal laser scanning microscopy images comparing biofilm formation by E. coli and ETCS. E. coli and ETCS were exposed to 0.02 mg/L TCS in LB medium at 37 ºC for 24 h. Live cells were stained with SYTO 9 dye (green), and dead cells were stained with propidium iodide (PI) (red). The scale bar in each image is 20 μm.
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(b)
25
Stop TCS exposure
20
**
**
4 2 E. coli
50
100
Generation
SYTO 9
60
40 30
**
20
**
**
10 0
120
Stop TCS exposure
50
E. coli 100 105 110 115 120
Generation
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Merge
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ETCS
after stopping exposure
(c)
**
15
Growth inhibition (% of E. coli alone)
Fold change of MIC50 (Relative to E. coli)
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544 545 546 547 548 549 550 551 552
Figure 7. ETCS exhibits irreversible TCS resistance and reversible penicillin tolerance after stopping TCS exposure. (a) Fold changes in the MIC50 to TCS; (b) changes in susceptibility to 25 mg/L penicillin; and (c) changes in biofilm formation via confocal laser scanning microscopy following subculture for an additional 20 passages without TCS exposure. The scale bar is 20 μm. After stopping exposure to TCS for the indicated number of generations, the bacteria were incubated with serial dilutions of TCS or 25 mg/L penicillin for 12 h in LB medium. All experiments were performed at least in triplicate, and the results are expressed as the mean values ± SD. ** denotes p < 0.01 relative to the MIC50 of E. coli and the inhibition rate of 25 mg/L penicillin for E. coli.
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Table 1. Fatty acid profiles of the cell membranes in E. coli and ETCS. % of total fatty acids E. coli ETCS C6:0 3.028 ± 0.58 2.57 ± 0.36 C8:0 1.78 ± 0.27 1.46 ± 0.21 a C10:0 ND 1.09 ± 0.35 C11:0 7.67 ± 0.95 7.36 ± 1.19 C13:0 4.32 ± 0.43 3.94 ± 0.52 C14:1 4.06 ± 0.3 4.89 ± 0.3 C15:1 ND 0.73 ± 0.63 C15:0 4.31 ± 0.4 9.53 ± 1.09 C16:1 42.07 ± 1.05 40.07 ± 0.56 C16:0 3.43 ± 0.47 4.53 ± 0.18 C18:2 15.08 ± 1.41 11.90 ± 0.97 C18:0 14.24 ± 1.01 11.91 ± 1.96 b SFA 38.79 ± 2.18 42.41 ± 1.63 c UFA 61.21 ± 2.18 57.59 ± 1.63 SFA/UFA 0.64 ± 0.05 0.74 ± 0.04 The value is the average of three replicates ± SD. a Not detected. b Saturated fatty acids. c Unsaturated fatty acids. Fatty acids
555 556 557 558 559 560 561
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