Potential impact factors on the enhancement of antibiotic resistance in a lake environment

With a long history as effective treatments for bacterial infections, antibiotics have more recently been considered emerging environmental pollutants that have caused remarkable concern regarding antimicrobial resistance (AMR). Infectious bacteria have become resistant to their respective antimicrobial agents, which implicates morbidity and mortality rates as well as increased treatment costs. Therefore, AMR has become a global health concern that the WHO lists as one of the highest priority threats to human health of the century. Massive deaths attributed to AMR are expected to reach 10 million deaths annually by 2050 (O'Neill 2014). Moreover, AMR will impact the global economy, as close to 24 million people could fall into extreme poverty if no action is taken to combat the prevalence of antibiotic resistance.

WWTPs represent the main pathway for the release of antibiotics into the water environment. The presence of antibiotics in WWTPs, likely derived from households, slaughter houses, and partially from hospital effluents, was globally reported (Aydin et al. 2019; Kairigo et al. 2020). After ingesting antibiotics to treat bacterial infections, only a fraction of the antimicrobial agent is metabolized and up to 90% of the un-metabolized portion is excreted through the urine and faeces (Gao et al. 2012). These excreted antimicrobial agents are most likely to end up in sewerage systems or water environments and degrade water quality.

Besides antibiotics, other emerging pollutants such as polyaromatic hydrocarbon (PAH), polychlorinated biphenyls (PCB), per- and polyfluoroalkyl substances (PFAS) in wastewater treatment plants have created favorable conditions that promote widespread antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) (Barancheshme & Munir 2018; Rodgers et al. 2019). In a lab-scale conventional activated sludge process, exposure to antibiotics induced higher resistance in the susceptible E. coli isolates tested, especially in the simulated aeration tank (Sulfikar et al. 2018). Antibiotics, ARB, and ARGs were frequently detectable throughout treatment steps and even in the final effluent, which indicated the low removal efficiency in the WWTPs (Ben et al. 2017; Lee et al. 2017).

The water environment is recognized as the ideal settling reservoir of AMR, as it receives contaminated water from anthropogenic activities, including from WWTPs, which may pose a severe risk to downstream applications (Rodriguez-Mozaz et al. 2015; Panagopoulos & Haralambous 2020). The abundance of antibiotics in the water environment has been frequently detected (Kümmerer 2009). Bacteria can acquire higher resistance after adapting to antibiotic-contaminated environments (Sulfikar et al. 2018). The sublethal concentration of antibiotic residues has been increasingly recognized as an important selective pressure that promotes AMR in the water environment (Gullberg et al. 2011). However, our understanding of its contribution is still limited. For instance, the environmental factors and the conditions of the water environment that drive AMR development still need further studies. In general, temperature, exposure time, and availability of carbon source conditions influence the growth of bacteria. It is unclear whether combining these factors with sublethal concentrations of antibiotics affects resistance induction. Therefore, we investigated the effect of temperature, exposure time, and carbon source under sublethal norfloxacin concentrations on the induction of resistance in Escherichia coli (E. coli). The determination of these factors is key to understanding the prevalence of antibiotic-resistant bacteria in the water environment and may help to prevent the development of antibiotic resistance.

Faecal indicator bacteria, E. coli, were isolated from water samples obtained from Kahokugata Lake, located in Ishikawa Prefecture, Japan. This catchment receives water from six rivers impacted by the treated effluent from the surrounding livestock industry and agriculture facilities such as pig farms, slaughterhouses, and food processing factories. Between June 2014 and May 2015, water samples were collected in sterilized 1 L bottles at six sampling points: Unoke River (Unoke River Bridge, A), Toubu drain channel (Konan Bridge, B), the estuary of Morimoto River (C), the center of Kahokugata Lake (D), an area near Uchinada Outlet (E), and a river near the outlet of treated wastewater from a slaughtering factory (F), as shown in Figure 1.

After arriving in the laboratory, the water samples were diluted as necessary by 10-fold dilution in triplicate, using 0.85% saline water. Each diluted or undiluted water sample was filtered through sterile φ0.45 μm membrane filters (ADVANTEC, Toyo Roshi Kaisha, Ltd). E. coli were cultivated by placing each membrane filter on Chromocult coliform agar ES (Merck KGaA, Darmstadt, Germany) and incubated at 37 °C for 22 hours. After cultivation, up to twenty blue colonies were isolated from each sampling point. Each colony was propagated in PERLCORE Trypto-Soy (TS) Broth liquid medium (Eiken Chemicals, Tokyo, Japan) for 16–18 hours at 37 °C.

The culture of each E. coli isolate was examined for susceptibility to norfloxacin using the Kirby-Bauer disk diffusion method. Bacteria cultures were spread on susceptibility test agar containing antibiotic KB disks (Eiken Chemical Co., Ltd). Following overnight incubation at 37 °C, we measured the inhibitory zone to determine the susceptibility to norfloxacin according to the CLSI standard (CLSI 2014). Subsequently, sixteen E. coli isolates were randomly selected for the resistance induction experiment.

Lake water was sampled twice from point D of Kahokugata Lake (Figure 1) in December 2016 and October 2017. The water samples were collected using sterilized bottles and stored in an icebox during transportation to the laboratory. Upon arrival, the lake water for the resistance induction experiment was first autoclaved at 121 °C for 20 minutes and stored at 4 °C for later use. On the other hand, for the physicochemical and antibiotic concentration analysis (Tables 1 and 2), the samples were immediately filtered with a φ0.45 μm membrane filter (ADVANTEC, Toyo Roshi Kaisha, Ltd). The total organic carbon (TOC), total inorganic carbon (IC), and total nitrogen (TN) concentrations were measured using a TOC-L CSN analyzer (SHIMADZU, Japan). The ions were analyzed by ion chromatography CBM-20A (SHIMADZU, Japan) (Table 1). Quinolone antibiotics in the lake water were extracted using SPE-HLB cartridges (Waters, Milford, USA) as described in EPA Method 1694 of PPCPs. The antibiotics bound in the cartridge were eluted using 12 mL of HPLC-grade methanol and reduced to 10 mL under a gentle stream of nitrogen at 50 °C. After that 5 mL of the extract was further re-concentrated under a gentle stream of nitrogen at 50 °C until near dryness. The concentrated extracts were redissolved in 2 mL of acetonitrile:water (5:95), containing 0.1% formic acid, and centrifuged. The supernatant was collected for LC-MS/MS analysis. The antibiotic concentrations were quantitatively analyzed using one-point calibration in LC-MS/MS (U3000 and TSQ Quantum Discovery Max, Thermo Fisher Scientific, San Jose, USA) (Table 2).

We tested three parameters: temperature, exposure time, and carbon sources (i.e. TS broth [TOC ∼ 9 mg/L] and Kahokugata Lake water [TOC ∼ 2–4 mg/L]), under sublethal concentrations of norfloxacin, to examine the induction of antibiotic resistance in the isolated E. coli. In the first experiment, resistance induction was assessed by incubating each of the sixteen strains at different temperatures and exposure times in a series of sublethal norfloxacin concentrations (1,000, 100, 10, 1, and 0 ng/L prepared in TS Broth in 96-well sterile plates). In detail, frozen stocks of each of the sixteen strains were propagated in TS broth at 37 °C for 18 hours. The fresh culture was then added to the prepared norfloxacin-TS broth to reach 2% (v/v) in a total volume of 200 μL. The incubation temperatures were 5, 25, and 37 °C for 18 hours and five days. In the second experiment, we used the lake water instead of the TS broth with the same serially diluted concentrations of norfloxacin as in the first experiment. The same incubation temperatures and lengths of time were applied, as in the first experiment (Table 3).

Each strain's minimum inhibitory concentration (MIC) was determined before and after the induction experiments. The norfloxacin was diluted with the TS broth (Wako Pure Chemicals, Mie, Japan) in a series of two-fold concentrations into 96-well sterile microplates. The concentration ranges were 32–0.03125 μg/mL, and 0 μg/mL as a control. An overnight inoculum was made by incubating the pre-thawed frozen stock of each strain in TS broth at 37 °C for 18 hours. We added the inoculum to the microplate to a final concentration of 2% (v/v) of 200 μL. Next, the microplates were incubated at 37 °C for 18 hours. The lowest concentrations that inhibited the visible growth of inoculated bacteria were observed visually and by measuring the optical density at 405 nm using a microplate reader (Bio-Rad, Model 680). The E. coli were considered resistant at a MIC of >16 μg/mL, intermediate at a MIC between 8 and 16 μg/mL, and sensitive at a MIC of <8 μg/mL, following (CLSI 2014).

Of the sixteen randomly selected strains for the resistance induction experiment, three strains had the original MIC of 32 μg/L, A14–A16, as shown in Figure 2. Therefore, the following discussion is based on the thirteen susceptible and intermediate strains.

Figure 3 shows the relative MIC changes to sublethal norfloxacin of E. coli at different temperatures. Generally, the higher the temperature, the more strains were induced. At 37 °C, the induced strains had increased higher resistance compared to those grown at lower temperatures.

Our results demonstrate that temperature is a critical parameter affecting the development of resistance in E. coli at low antibiotic concentrations, in this case, norfloxacin. Bacteria grown at high temperatures were more tolerant to antibiotics than those at low temperatures, resulting in greater resistance. Under variable temperatures during the incubation period, different modifications in bacterial cell composition could account for this developed resistance. Temperature is an important factor for bacterial growth and modifying bacterial cell compositions, functions, and processes (Ratkowsky et al. 1982). E. coli adjust their membrane lipid composition to maintain the ideal physical state of cells by changing the relative abundance of saturated and unsaturated fatty acids in response to various growth temperatures (Cronan & Vagelos 1972). At lower temperatures, bacterial cells may contain a more significant proportion of unsaturated fatty acids, which increases membrane fluidity, hence the term, homeoviscous adaptation (Sinensky 1974). On the contrary, bacterial cells grown at higher temperatures increase saturated fatty acids, decreasing membrane permeability. These changes can increase cellular resistance to physical and chemical stresses. E. coli grown at higher temperatures (42 °C and 37 °C) had higher resistance against heat stress than the ones grown at lower temperatures (30 °C, 20 °C, and 10 °C) (Cebrián et al. 2008). In this context, the alteration of physical characteristics in E. coli under various growth temperatures may also affect the development of resistance to stress. The norfloxacin uptake into E. coli cells may be reduced due to the corresponding decrease of membrane permeability under high growth temperature.

Despite cell alteration under different growth temperatures, the effect of antibiotic concentration on resistance induction might also be as significant. At 37 °C, more strains were induced when incubated in norfloxacin up to 100 ng/L. A fewer number of isolates were induced at 1,000 ng/L. Our results also suggest that even at 1 ng/L of norfloxacin, the induction of antibiotic resistance may occur.

In the high carbon (TOC = 9 mg/L) exposure, we found that for strains incubated at 37 °C, longer exposure times resulted in a greater MIC fold change. The 5-day incubation increased the MIC by 4.7 ± 0.2-fold compared to 2.2 ± 1.2 for the 18-hour incubation. There were no differences in MIC fold changes or the number of strains induced for strains incubated at lower temperatures and those in low carbon concentration (Figure 3).

Bacteria may become stressed when they are exposed to challenging conditions. Environmental factors such as temperature, total organic carbon, and sublethal concentrations of antibiotics can be considered stressors when their characteristics are not favorable for bacterial growth. After exposure to the stressor, E. coli cells might respond by producing enzymes and important metabolites or synthesizing RNA essential to repair the injured cells. Due to stress, the damaged cells likely take longer to repair themselves relative to actively growing cells. The subpopulation that survives during stress conditions could perceive and possibly shape its response to a subsequent stressful environmental event. Our results suggest that longer exposure time was likely favorable for cell growth under stress conditions than shorter exposure time, which increased MIC fold changes.

E. coli strains grown under high carbon conditions were more likely to develop antibiotic resistance than those in low carbon conditions. The MIC fold changes were generally increased under the high carbon condition as the temperature and exposure time increased (Figures 3 and 4). A different pattern was observed for strains incubated under low carbon concentration (2–4 mg/L). For the same temperature condition, the number of strains induced was fewer (at 25 °C) or exhibited lower MIC fold changes (at 37 °C). These differences were not observed at 5 °C.

These results demonstrated that carbon conditions affected antibiotic resistance development in bacteria, but it was dependent on the specific growth temperature. Bacterial resistance could increase under low carbon conditions but the bacteria did not thrive as much as in high carbon conditions. The development of induction was possibly due to several different mechanisms. However, in this challenging growth condition, less compatible cells may die and lyse, which then may be utilized as a nutrient supply for the living cells. In a monoculture of small and large E. coli cells under deficient nutrient supply, the death rate of large E. coli cells was higher than the small cells at the stationary phase (Rozen et al. 2009). After the starvation period extension, the growth rate and the total density of the small cells increased, which was explained as the cannibalization of the lysed large cells (Dubos 1939). Cell lysis may occur in sensitive cells due to injury at the beginning of antibiotic exposure or under the event of autolysis. In this context, antibiotics possibly play a critical role in promoting the cells' survival.

The occurrence of resistance under poor nutrient conditions or during the stationary phase may also be attributed to bacterial physiological changes during adaptation to the environmental stress conditions (Jishage et al. 1996). The induction of stress-response genes may result from the expression of the rpoS gene, which has been generally identified as a regulator for bacterial growth (O'Neal et al. 1994). As a result, a much higher level of rpoS expression was detected under low as opposed to high nutrient conditions in wild-type E. coli. In addition, the rpoS gene has also been associated with tolerance to antibiotics in P. aeruginosa during the stationary phase or heat shock (Murakami et al. 2005). Our study found that 2–4 mg/L carbon concentration triggered antibiotic resistance in this simulated lake environment. Further studies are needed to explore this observation.

Our results suggest that induction of antibiotic resistance may occur in surface water contaminated with wastewater that contains high organic carbon and antibiotic residues. The abundance of antibiotic residues presented up to several hundred ng/L in the aquatic environment in Asian countries (Shimizu et al. 2013). These concentrations could cause selective pressure to accelerate antibiotic resistance. The resistance level may depend on the local temperature and the pollution level. Higher levels of resistant E. coli were detected in (the more polluted) tropical rivers of India than in Sri Lanka (Kumar et al. 2019). In another study of the Chaophraya River, the increasing antibiotic resistance of E. coli was suggested to be dependent on anthropogenic activities of the main location rather than transmission from upstream (Honda et al. 2016).

Organic substances may serve as nutrients for bacterial growth and may promote the development of antibiotic resistance at high to very low concentrations. These results were relevant to the findings of Lin et al., in which the wild-type and rifampin-resistant strains of E. coli mutated at broad nutrient concentrations of 2–2,000 mg/L, although a higher growth density was observed at the higher nutrient concentrations (Lin et al. 2018). We suggest that higher organic carbon contamination may cause more severe antibiotic resistance in the aquatic environment. Interestingly, antibiotic resistance induction occurred even at the low TOC concentrations (2–4 mg/L). In this context, the available resources in the freshwater environment may promote the development of antibiotic resistance. The average total organic carbon concentration in 8,300 lakes in 68 countries was 5.578 mg/L (Chen et al. 2015).

This study allows us to make a more explicit assumption about the prevalence of antibiotic resistance that is often reported in LMIC (Low-Middle Income Countries) (e.g. Suzuki & Hoa 2012; Azad et al. 2019), which is not only caused by misused or overuse of antibiotics in animal farms. It might also be due to a lack of wastewater treatment facilities. Only 28% of wastewater is treated before it is discharged to other sources (Lipponen & Nikiforova 2017). Direct discharge of the untreated sewage containing emerging contaminants from various anthropogenic activities will cause adverse effects on the aquatic environment (Du et al. 2015). Consequently, antibiotic resistance has been reported globally (García-Galán et al. 2011; Kumar et al. 2019).

Moreover, antibiotic-resistant bacteria potentially may spread from aquatic organisms through food chains to humans (Kovalakova et al. 2020). Therefore, it is essential to install and improve the performance of wastewater treatment facilities to minimize discharging organic pollutants, antibiotics, ARB, and ARG-containing wastewater into aquatic environments. Also, it is critical to collect and treat stormwater using combined sewage flow treatment. Another strategy strictly controls wastewater discharges by developing a national quality standard related to emerging antibiotic resistance (effluents and drinking water standards).

Our findings show that organic wastewater contamination in the lake environment is a possible cause of the enhancement of antibiotic resistance, even under sublethal concentrations of antibiotics. Longer exposure time will increase the chance of resistance induction. Our results also suggest that enhancement of antibiotic resistance in lakes is more likely to occur in the tropics than in temperate climates, especially since lakes in the tropics have a relatively uniform temperature over the year compared to lakes in temperate regions. It is imperative to pay more attention to lakes located in agricultural or urban catchments. Management of the catchment area should include preventing agricultural runoff or municipal wastewater from flowing directly into the lakes, for example, creating a series of constructed wetlands or developing proper wastewater treatment facilities to treat the wastewater. One of the impacts of climate change is more frequent extreme high precipitation events that will increase carbon, other nutrients, and pollutant influx from the catchment area. Still, these events will decrease lake water residence time. Further studies are needed to evaluate how these events influence the occurrence or the spread of antibiotic resistance in the water environment.

This study was supported by JST MIRAI Program (Grant No. JPMJMI18DC) and JSPS KAKENHI Grant-in-Aid (Grant No. 26281037, 26289180, 19H02272, 21H03617).

Data cannot be made publicly available; readers should contact the corresponding author for details.