Next Article in Journal
Green Supply Chain Management Practices’ Impact on Operational Performance with the Mediation of Technological Innovation
Previous Article in Journal
Adaptive Retrofit for Adaptive Reuse: Converting an Industrial Chimney into a Ventilation Duct to Improve Internal Comfort in a Historic Environment
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 14
Issue 6
10.3390/su14063358
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Enrofloxacin on Nutrient Removal by a Floating Treatment Wetland Planted with Iris pseudacorus: Response and Resilience of Rhizosphere Microbial Communities

by
Naven Ramdat
1,
Zi-Jing Wang
2,
Jung-Chen Huang
2,*,
Yikun Wang
1,
Azharuddin Chachar
1,
Chuanqi Zhou
1 and
Zhiping Wang
1
1
School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2
Department of Environmental Engineering, National Cheng Kung University, Tainan City 701, Taiwan
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(6), 3358; https://doi.org/10.3390/su14063358
Submission received: 22 February 2022 / Revised: 10 March 2022 / Accepted: 11 March 2022 / Published: 13 March 2022
(This article belongs to the Section Sustainable Water Management)
Browse Figures
Versions Notes

Abstract

:
Constructed wetlands (CWs), including floating treatment wetlands (FTWs), possess great potential for treating excessive nutrients in surface waters, where, however, the ubiquitous presence of antibiotics, e.g., enrofloxacin (ENR), is threatening the performance of CWs. In developing a more efficient and resilient system, we explored the responses of the FTW to ENR, using tank 1, repeatedly exposed to ENR, and tank 2 as control. Plant growth and nutrient uptake were remarkably enhanced in tank 1, and similar phosphorus removal rates (86~89% of the total added P) were obtained for both tanks over the experimental period. Contrarily, ENR apparently inhibited N removal by tank 1 (35.1%), compared to 40.4% for tank 2. As ENR rapidly decreased by an average of 71.6% within a week after each addition, tank 1 took only 4 weeks to adapt and return to a similar state compared to that of tank 2. This might be because of the recovery of microbial communities, particularly denitrifying and antibiotic-resistance genes containing bacteria, such as Actinobacteria, Patescibacteria, Acidovorax and Pseudomonas. After three ENR exposures over six weeks, no significant differences in the nutrient removal and microbial communities were found between both tanks, suggesting the great resilience of the FTW to ENR.

1. Introduction

Eutrophication is characterized by the uncontrollable growth of phytoplankton and plants in aquatic environments due to excessive nutrients, particularly phosphorus (P) and nitrogen (N). The presence of excessive nutrients is caused by anthropogenic activities, including agriculture, industry and sewage disposal [1], as well as the inadequate treatment of wastewater [2]. Eutrophication further leads to the depletion of aquatic wildlife and deterioration of water quality across the world [3].
Among all the treatment approaches, constructed wetlands (CWs) have the lowest construction and operation costs for contaminant removal [4,5]. In addition to the uptake by plants in CWs, N is mainly removed through microbially-mediated nitrification and denitrification processes, while P is mainly removed through adsorption to substrates [6], as well as microbial transformation and chemical precipitation [7,8,9]. As an innovative variant of CWs, floating treatment wetlands (FTWs) have also been widely utilized for their better performance, greater flexibility in applications and even lower costs [10,11,12]. With roots as the filter substrate, rhizospheric microorganisms play a crucial role in the removal of contaminants by the FTW [13,14]. However, microbial activity, composition and diversity in terrestrial and aquatic environments have been seriously affected in the presence of antibiotics [15,16] usually used by humans in clinical therapy to annihilate or prevent the growth of bacteria or as prophylaxes and growth promotors in animal husbandry [17]. Approximately 30–90% of antibiotics are reportedly unmetabolized and released into the environment through urine and feces as either the original compound or its metabolite [18,19,20], ending up in the aquatic environment receiving the untreated wastewater or agricultural runoff [20,21].
In treating the contaminated water, therefore, the presence of antibiotics is threatening the performance of CWs, particularly through changes in the microbial activities and compositions in the CW [22,23]. Although numerous studies have been conducted regarding the removal of antibiotics by CWs and their influence on the nutrient removal capacity and microbial composition of CWs [5,18,24], few studies have focused on the recovery of CWs after exposure to antibiotics. Moreover, to the best of our knowledge, no study has been found to specifically investigate the impact of antibiotics on the microbial community in the rhizosphere of the FTW and its resilience to repeated exposures to antibiotics. Weber et al. [25] briefly mentioned the recovery time of the microbial community in a wetland mesocosm after treating antibiotic-contaminated wastewater. However, this research focused more on the acute exposure, while the antibiotic exposure was more chronic in the current study.
Therefore, the overall goal of our research is to develop a more resilient and resistant FTW system against antibiotics in the wastewater. To this end, the current study was carried out under hydroponic conditions using two FTW mesocosms planted with Iris pseudacorus and intermittently receiving synthesized water containing enrofloxacin (ENR), a fluoroquinolone (FQ) antibiotic frequently used in the livestock industry [24,26] and commonly found in different environmental matrices [27]. We hypothesized that the influence of ENR on the FTW would weaken over repeated exposures, with new microbial communities more resistant to ENR in the rhizosphere. Our objectives were to (1) explore the effects of ENR on the growth and uptake of P and N by I. pseudacorus; (2) evaluate the P and N removal efficiencies of the FTW during and after exposure to ENR; (3) determine the capacity of the FTW to remove ENR; (4) monitor the changes in the microbial community in the rhizosphere of I. pseudacorus repeatedly exposed to ENR. The results of this research will be applied to develop hypotheses for subsequent testing in pilot FTWs under field conditions.

2. Materials and Methods

2.1. Experimental Design and Setup

Two FTW mesocosms, tank 1 and tank 2 (control), were made from two HDPE cylinder tanks (965 mm height × 509 mm bottom diameter × 390 mm top diameter) with a volume of 160 L (Figure S6).
The outlet of each tank was connected to a bucket containing a submersible pump creating recirculation. The system was operated for six weeks, which were divided into 3 cycles, as each cycle consisted of 2 phases: a treatment phase (1 week) and a recovery phase (1 week). In the beginning of the treatment phase, ENR antibiotic was only added to tank 1, while synthetic water was supplied for both tanks. During the recovery phase, both tanks only received synthetic water without ENR. At the end of each phase, the synthetic water of both tanks was replaced with new synthetic water for the next phase.
The synthetic wastewater was prepared based on the nutrient levels of secondary effluents of WTPs: the concentrations of NO3-N, NH4-N and TP were set at 11, 3 and 0.5 mg/L, respectively [10]. Both mesocosms contained only media without any substrate, as I. pseudacorus, collected from the botanical garden of the Shanghai Jiao Tong University (SJTU), was grown in 1/20 Hoagland solution for 1 month for acclimation before the test. I. pseudacorus is a plant species that is usually detected in natural wetlands in tropical and subtropical regions [28]. It has also been reported to be one of the species commonly utilized in constructed wetlands [28,29]. I. pseudacorus has been referred to as a hardy plant by a previous study, saying that it remained active during winter compared to Typha orientalis. It also had a higher radical oxygen loss (ROL), contributing to a higher richness estimator for aerobic microorganisms, subsequently leading to a higher nitrogen removal [30]. Its influence on the microbial community was also demonstrated by its higher release of dissolved organic carbon (DOC) compared to Phragmites australis and Juncus effusus [29].
The mesocosm experiments were carried out in an environment-controlled greenhouse, with 19/10 °C day/night temperatures at SJTU from November to December 2020.

2.2. Sampling and Analysis

2.2.1. Water Sampling and Analysis

Water samples were collected 3 times during each phase of each cycle and filtered through 0.45 μm pore size membrane filters. The TN/TOC analyzer (Multi N/C 3100, Analytik Jena, Germany) was utilized to determine total nitrogen (TN). Ammonium (NH4+), nitrite (NO2−), nitrate (NO3−) and total phosphorus (TP) were analyzed according to the standard method [31] by using ultraviolet spectrophotometer (UV-1800, Shimadzu, Japan). The water quality was monitored in situ for the pH, dissolved oxygen (DO) and temperature before sampling, using a multiparameter water quality instrument (ProPlus, YSI, Yellow Springs, OH, USA). Water samples for ENR were measured by high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS-MS), after pre-treatment by solid phase extraction (SPE). All chemicals utilized were analytical grade reagents purchased from Sigma-Aldrich (Shanghai, China).

2.2.2. Plant Tissue Sampling and Analysis

At the end of the experiment, plant samples were collected and divided into shoots and roots. Approximately 1/3 of the shoots were stored at −20 °C for determination of chlorophyll content, and the rest were oven dried for 48 h at 60 °C for N and P analyses using inductively coupled plasma emission spectrometer (iCAP7600, Waltham, MA, USA). The chlorophyll content in the fresh shoots was analyzed according to Gogoi et al. [32] (see Supplementary Materials SI 2.2.2.1).

2.2.3. Microbial Sampling and Analysis

Roots were sampled in triplicate from tank 1 and tank 2 at the beginning and end of the experiment. The microbial biofilms were washed from the samples and stored at −80 °C before being sent to Majorbio Bio Pharm Technology Co. Ltd. (Shanghai, China) for microbial analysis (see Supplementary Materials SI 2.2.3.1). The free online platform of Majorbio I-Sanger Cloud Platform (www.i-sanger.com, accessed on 29 January 2021) was utilized for the analysis of the microbial data, including the Analysis of Similarity (ANOSIM).

2.3. Statistical Analysis

The removal efficiencies and microbial data in the current study were presented as mean ± standard error (SE). The microbial data were analyzed by one-way analysis of variance (ANOVA) at a 95% confidence interval (a = 0.05), followed by Tukey’s multiple comparison test using SPSS Statistics 17.0 (IBM, New York, NY, USA). The results were considered statistically significant at p < 0.05. The Greengenes reference database (http://greengenes.secondgenome.com/, accessed on 29 January 2021) was used to classify taxonomic sequences down to the phylum and genus levels at an 80% confidence threshold, and was conducted by the vegan package of R. In addition, the alpha–beta diversity and richness of total bacterial 16S rRNA in the rhizosphere of both mesocosms were analyzed, such as Chao1, Shannon, Simpson, Student’s t-test bar plot, one-way ANOVA bar plot, principal coordinate analysis (PCoA) and redundancy analysis (RDA).

3. Results

3.1. Effects of Enrofloxacin on Iris Pseudacorus

Although P and N are considered pollutants in this research, they are the macro-nutrients required for the growth of wetland plants. Therefore, we monitored the N and P concentrations and dry weight of plant tissues in each mesocosm to evaluate the impacts of ENR on the nutrient uptake by wetland plants.
The results suggest the greater TP was observed in plant tissues, particularly roots, of tank 1 than tank 2: the TP in the roots of tank 1 (6.76 mg/g) was nearly twice as much as that of tank 2 (3.46 mg/g), while a slightly greater value was observed in the shoots of tank 1 (2.77 mg/g) than that for tank 2 (2.59 mg/g) (Figure 1a). Similarly, for TN, a substantially greater value of 46.06 mg/g was also obtained for the roots of tank 1, compared to only 34.07 mg/g for tank 2 (Figure 1b). However, the shoots of tank 1 showed a slightly lower value of 21.74 mg/g than that of tank 2 (24.08 mg/g). At the end of the experiment, tank 1 had a substantially higher dry weight of both shoots and roots than tank 2 (Figure 1c).
It was observed that the chlorophyll levels were affected as there were relatively higher concentrations of chlorophyll a and b in the shoots of the ENR-exposed plant of tank 1 (1.51 and 0.59 mg/g, respectively), compared to 1.37 and 0.54 mg/g, respectively, for tank 2 (Figure 1d), which is also considered to be evidence of the stress caused by ENR.

3.2. Effects of Enrofloxacin on Nutrient Removal

To investigate the effects of antibiotics on the nutrient removal efficiency of the FTW system, comparisons were made for nutrient levels between ENR-treated tank 1 and ENR-free tank 2 during the three cycles.
As shown in Figure 2a, TP was consistently lower in tank 1 than tank 2, particularly during the recovery phase of each cycle, over the whole experimental period. Consequently, greater average removal rates of TP (89.47 ± 3.95%) were obtained for tank 1, compared to 86.20 ± 3.94% for tank 2 (Figure 2b); however, both tank 1 and tank 2 reached the maximum values of 97.60 and 92.40%, respectively, at the end of the experiment.
In contrast to the trend observed for TP, Figure 2c shows TN concentrations tended to be lower in tank 2 than tank 1, particularly during the treatment phase of each cycle, over the six-week period, while average TN removal efficiencies were 35.11 ± 6.63 and 40.38 ± 8.54% for tank 1 and tank 2, respectively, for each phase. Noteworthy is the increase in TN removal efficiency for tank 1 (65.79%) and tank 2 (81.14%) during the second week, which was not observed for TP (Figure 2d).
As ENR was seemingly more influential on the removal of N than P, we further investigated changes in ammonium (NH4+), nitrite (NO2−) and nitrate (NO3−) concentrations over the experimental period to evaluate the effects of ENR on N cycling in the FTW (Figure 3). Figure 3b shows both tanks acted similarly, with or without ENR, to efficiently remove NH4+, by up to 100% during the sixth week. Although NO3- was not removed as fast by both tanks as NH4+, greater rates were generally obtained for tank 2 (47.61 ± 10.20%) than tank 1 (33.82 ± 7.68%) (Figure 3d). Even though both tanks achieved similar NH4+ removal rates, tank 1 appeared to have much lower NO2− levels (Figure 3e). Noteworthy is the lower concentration or greater removal rates for NO3− in tank 1 during the second week, which did not occur for NH4+ and NO2−. Finally, by combining the data of total dry biomass and tissue N concentrations of the plants in each tank, a considerably greater total N content in plant tissues was obtained for tank 1 (7254.9 mg) than that for tank 2 (4068.6 mg) (Table S2).

3.3. Removal of Enrofloxacin

In addition to being affected by ENR, we further evaluated tank 1, as an FTW system, for its capacity to remove or degrade ENR supplied at 100 µg/L during the treatment phase of each of three cycles.
The ENR concentration exhibited a similar profile in each cycle: the value rapidly decreased by up to 45% within 24 h, followed by a relatively slow decline in the next five days (Figure S2). The average removal of ENR was 71.58 ± 2.54%, with the maximum value of 77. 81% obtained in the first cycle, compared to approximately 68% for the next two cycles.

3.4. Microbial Community Richness, Diversity and Composition

As bacteria are a critical indicator of the impact of ENR on the performance and the resilience of the FTW after exposure, an evaluation was conducted in terms of the richness, diversity and community compositions in the current study.
Serving as a filter substrate, the roots of each tank were sampled at the beginning and end of the experiment to investigate the microbial diversity and community composition in both tanks via high-throughput sequencing analyses. Table S4 demonstrates the operational taxonomic unit (OTU) numbers, Coverage, Simpson, Chao1, Ace, Shannon and Simpson indices of the root samples, while the minimal coverage was 0.99, indicating the experimental results were credible. All the OTU numbers and indices followed the same pattern: almost all the initial values of tank 1 were significantly greater (p < 0.001) than those of tank 2, although both of them had been grown under the same conditions for more than one month before the test. However, all the values of tank 1 substantially or significantly (p < 0.01) decreased over six weeks, while slight increases in the values were observed for tank 2. At the end of the experiment, no significant differences in the OTU numbers and indices were found between two tanks.
To see if functional bacteria in the rhizosphere were impacted by ENR, the microbial community compositions of root samples were analyzed at the phylum and genus levels (Figure 4). In Figure 4a, the Circos diagram illustrates the proportions and distributions of the top 10 dominant phyla in the root samples, among which Proteobacteria was most dominant, followed by Actinobacteria and Patescibacteria. Our results show the relative abundance of Proteobacteria significantly (p < 0.01) (Figure S3) decreased from 62.6 to 23.9% for tank 1 (Figure S4) over six weeks, compared to only a gentle drop from 76.4 to 51.8% for tank 2 (Figure S4). Contrary to Proteobacteria, the proportions of Actinobacteria significantly (p < 0.05) (Figure S3) increased from 25.4 to 55.4% for tank 1 (Figure S4) during the experiment, as a profound increase from 18.0 to 29.8% was found for tank 2 (Figure S4). Similar to Actinobacteria, Patescibacteria that initially comprised a neglectable proportion of <0.3% for both tanks (Figure S4) became the third dominant phylum after six weeks, accounting for 13.2 and 5.6% for tanks 1 and 2 (Figure S4), respectively.
The microbial analysis at the genus level (Figure 4b) shows Enterobacter, from the phylum Proteobacteria, and Microbacterium, from the phylum Actinobacteria, were the two most abundant genera for both tanks before testing, accounting for a major proportion of 39–63%. However, Paenarthrobacter, within the phylum Actinobacteria, initially comprised only a minor proportion (<2%) for both tanks but increased significantly (p < 0.001) in tank 1 (45.5%) and in tank 2 (22.3%), with p < 0.01 at the end of experiment (Figure S3). Similarly, TM7A, belonging to the phylum Patescibacteria, and Pseudomonas, in the phylum Proteobacteria, became relatively dominant over six weeks for tank 1 (12.9%) and tank 2 (22.5%), respectively.
To understand bacterial evolution over the experimental period, two PCoA analyses based on Bray–Curtis distance were conducted at the genus level (Figure 5). The PCoA (Figure 5a) and the one-way ANOVA bar plot (Figure S5) were performed for the initial and final samples of both tanks.
The PCoA for the initial and final samples from both tanks clearly shows the bacterial assemblage of the initial samples from both tanks could be grouped together, while the final samples could be divided into two groups (Figure 5a). The second PCoA carried out for the final samples shows a difference in the assemblage, though not significant, between tanks 1 and 2 (Figure 5b).
In order to better understand the relationship between the microbial community in the root samples and the environmental variables, such as DO, pH and temperature, a redundancy (RDA) analysis was executed (Figure 5c) as the magnitude of each environmental variable was represented by the length of the arrow [33]. The results show none of the variables had an outstanding impact on the microbial community when compared with one another. Based on the angles of the arrows, the correlation between the genera and the environmental factors was derived [33], showing temperature and pH had a positive correlation with the initial samples of tank 2, while DO was positively related to the final samples of tank 1.

3.5. Relative Abundance (%) of Significant Functional Groups Associated with N and P Removal

The relative abundances of the functional groups related to N removal were calculated (Table S5) and expressed in a heatmap after normalization according to z-scores (Figure 6a). Among all the detected genera in the root samples from both tanks, only two genera were linked to nitrification: Ellin6067 was related to the AOB (ammonia oxidizing bacteria), oxidizing ammonium into nitrite [34,35], while Nitrospira was associated with the NOB (nitrite oxidizing bacteria), responsible for the conversion of nitrite to nitrate [36,37]. The relative abundances of two nitrifying genera were less than 0.01% (Table S5) in the samples, collected either before or after the test, for both tanks.
The relative abundance of denitrification-related genera decreased from 19.0% in the beginning to 9.9% at the end of the test for tank 1, compared to a substantial increase from 8.3 to 28.7% for tank 2 (Table S5). Among all the denitrifying genera, Acidovorax were most dominant in the initial samples of both tanks and remained relatively abundant in tank 1 in the end. However, the most abundant genus in both tank 1 (5.0%) and, particularly, tank 2 (22.9%) at the end of the test was Pseudomonas (Table S5).
In addition to bacteria related to N removal, Pseudomonas was also found to be the most abundant genus for both tanks along with the other four genera related to phosphorous removal as presented in Table S6 and Figure 6b. Among the other genera, the least abundant was Acinetobacter that was only present in the initial samples of tank 1. The other genera were Candidatus Accumulibacter, Microlunatus and Dechloromonas.

4. Discussion

4.1. Plant Growth and Photosynthetic Pigment

As previously mentioned, ENR apparently affected the metabolism of I. pseudacorus. Previous studies claimed that antibiotics could either have a stimulating effect on plants at low concentrations or an inhibiting impact at high levels, known as the biphasic effect [38]. However, this would depend on the type of antibiotic or plant [39]. Batchelder [40] suggested wheat and corn absorbed more nutrients upon exposure to chlortetracycline or oxytetracycline, while an adverse effect was observed on the yield and nutrient uptake by pinto beans. The current study suggests ENR might have induced stress on the plant, triggering defense responses, including elevated production of reactive oxygen species (ROS) as suggested by Das and Roychoudhury [41], signaling an increase in growth, which is subsequently facilitated by increased nutrient uptake. Therefore, the greater nutrient levels and dry weight of the ENR-exposed plant tissues, particularly roots, of tank 1 could be attributed to the accumulation of ENR in tissues (not measured during the investigation), as indicated by Chowdhury et al. [42] for the ENR-exposed roots of red cabbage, and by L. Liu et al. [19] for ciprofloxacin-treated Phragmites Australis. Verhagen et al. [43] claimed certain bacteria could compete with the plant roots for the available nutrients. Therefore, the presence of ENR might have suppressed these bacteria, allowing the root to take up more nutrients for growth.
Furthermore, it has been reported that pharmaceuticals, particularly ENR, could cause phytotoxicity to plants, leading to alterations in the photosynthetic pigments of the plant [44,45], while Liu et al. [19] suggested veterinary antibiotics would affect the chlorophyl levels of Phragmites Australis. This is in accordance with our results which show an increase in chlorophyl a and b for I. pseudacorus in tank 1 treated with ENR.

4.2. N and P Elimination in the Presence of Enrofloxacin

The results of the current research are similar to those reported by Lu et al. [46] claiming TP removal rates were obviously elevated for the hydroponic systems planted with Iris pseudacorus exposed to FQ antibiotic levofloxacin at below 0.3 µg/L; however, inhibitory effects on TP removal were observed at levels above 1 µg/L, with a similar value of 86.98% obtained at the same antibiotic concentration (100 µg/L) applied in the current study. Meanwhile, compared with ENR-free tank 2, the greater TP removal from water might indicate a higher plant uptake of TP in ENR-treated tank 1, which can be confirmed by the higher TP in plant tissues and better development of roots and shoots in tank 1. As a result, TP removal could be further enhanced due to the greater root system of tank 1, providing more surface area for P adsorption as the main removal mechanism for TP [6,47]. Overall, the capacity of I. pseudacorus to remove TP from water was profoundly promoted in the presence of ENR.
The lower removal rates of N in tank 1 during the treatment phase could be due to the inhibitory effects of ENR on microbial activities that played a major role in N removal [48,49], which is verified by the comparison of microbial communities between both tanks in Section 4.4. Even though TN concentrations remained lower in tank 1, even without ENR during the recovery phase, the differences between both tanks were smaller than those during the treatment phase, suggesting the microbial communities previously impacted by ENR were recovering. However, the ENR impact on tank 1 apparently wore off over three cycles, leading to the similar removal rate to that of tank 2 at the end of the experiment, even though the medium was renewed with fresh ENR for tank 1 at the beginning of each cycle. The results suggest it might take 4 weeks for an FTW to adapt to ENR, after which the N removal performance of the system could quickly recover in a week once ENR has been removed, reflecting the great resilience of the microbial communities as suggested in our hypothesis. This result is similar to that of Weber et al. [25] claiming the microbial community in the wetland system exposed to ciprofloxacin could recover after a 2–5 week period after the 5-day exposure. It is noteworthy that the experiment conducted by Weber et al. [25] can be viewed as an acute exposure, while in the current experiment the exposure was more chronic. Moreover, the above-mentioned study investigated a constructed wetland containing substrates at temperatures of approximately 24–28 °C. Meanwhile, the TN removal rates obtained in the current study were lower than the 54.24% reported by Zheng et al. [50] using a different antibiotic, i.e., sulfamethoxazole, possibly because the current investigation was carried out at lower temperatures, averaging approximately 18 °C during weeks 1–3 and 12 °C during weeks 4–6 (Figure S1) [51]. Nevertheless, relatively higher temperatures (up to 25 °C) during the second week seemed to boost microbial activities, leading to an obvious increase in TN removal efficiency. However, the TP removal efficiency did not increase correspondingly, suggesting phosphorous removal was more dependent on adsorption, while N was removed mainly through a microbially-meditated process in the FTW that was subject to temperature variations.
Since the media provided for both tanks did not contain NO2− initially, its presence could be due to either the oxidation of NH4+ or the reduction in NO3−. NO2− has been considered less usable by organisms and relatively unstable in the environment as it could be rapidly further oxidized into NO3−, a form preferred by plants [52]. Both processes performed by nitrifying bacteria are known as nitrification, as denitrification is a microbially facilitated process where NO3− is reduced to nitrogen gas or nitrous oxide under anaerobic conditions. As ENR is meant to destroy or slow down the growth of bacteria, the nitrification and denitrification processes were highly likely to be hindered in tank 1 [49]. In this regard, the oxidation of ammonium to nitrite could have been impeded, leading to higher NH4+ levels in ENR-treated tank 1. Surprisingly, both tanks showed similar NH4+ removal rates, possibly because the greater uptake of NH4+ by the plant occurred in tank 1, while more NH4+ of tank 2 was converted to nitrite, leading to a remarkable increase in NO2− in tank 2 compared to much lower NO2− levels in tank 1. Similarly, the oxidation of nitrite to nitrate could have been inhibited by ENR in tank 1 as well, while the process continued to proceed smoothly in tank 2, with more of NO2− converted to NO3−. However, contrary to expectation, NO3− concentrations of tank 2 were lower than those of tank 1, possibly due to a net N loss through denitrification as suggested by previous research [53]. Moreover, during the second week, lower concentrations or greater removal rates of NO3− obtained in tank 1 might be due to the increased microbial activities at higher temperatures; however, no such corresponding changes were observed for NH4+ and NO2−, indicating ENR had a greater impact on nitrifying bacteria, or denitrifying bacteria were more resilient after ENR exposure. Nonetheless, all the impacted microbial processes seemed to be restored in tank 1 during the sixth week, possibly because of the recovery or adaption of microbial communities after ENR exposure, resulting in the similar ammonium, nitrite and nitrate concentrations for both tanks towards the end of the experiment.
The findings of the combined data of the total dry biomass and the tissue N concentrations suggests I. pseudacorus might have played a relatively bigger role than microbes in N removal for ENR-treated tank 1, while the greater total N loss from the medium of tank 2 might be due to plant uptake as well as intact microbial activities, particularly associated with denitrification under low oxygen conditions (Table S3).

4.3. Enrofloxacin Degradation

An ENR concentration of 100 μg/L was applied for each treatment phase for the previous research, considered to be the most suitable value used for the assessment of CWs [24,54] and the highest concentration found in effluents of wastewaters [24,26]. Moreover, Berglund et al. [22] suggested antibiotic concentrations at these levels of μg/L would be environmentally relevant concentrations, which would elucidate and accurately assess the risks of environmental contamination by means of antibiotics. In the environment, antibiotics degrade through diverse processes including evaporation, biodegradation and sorption [55]. Meanwhile, there is an optimal hydrophobicity value for antibiotics to be taken up by plants according to Liu et al. [19]. If the compound is too either hydrophilic or lipophilic, the plant uptake might be limited, which is the case for highly lipophilic ENR.
FQ’s are regarded as being immobile in soil due to their hydrophobicity [56], while Conkle et al. [57] suggested the most efficient way to eliminate FQ’s in CW’s was through sorption to solid materials. Among all the FQ’s, ENR is considered the most lipophilic compound regarding the FQ antibiotics with a carbon-normalized sorption coefficient (Koc) of 15,800 L kg−1 [56]. As the plant uptake of antibiotics depends on their hydrophobicity values, the absorption of the compound, either hydrophilic or lipophilic, by plants will be restricted [19], suggesting the role played by plants in ENR removal could be neglected. Therefore, Carvalho et al. [54] claimed adsorption was the major mechanism for ENR removal, as various substrate types had been applied by earlier researchers to reduce ENR by more than 85% [24,26,54]. Although the removal rates obtained in the current study are relatively lower than those of some of the above-mentioned studies, this could be due to the root system of the FTW that functioned as a filter substrate for ENR sorption being not well developed and covering less than half (about 0.038 m3) of tank 1.
As well as plants, bacteria, such as Proteobacteria and Bacteroidetes, have been found to biodegrade ENR [58], which might have also contributed to ENR removal. As microbial activities are subject to temperature changes [59], the higher temperature (19.80 °C) might have contributed to greater ENR removal rates during the first cycle, with lower rates obtained for the following cycles at temperatures of 12–15 °C.

4.4. Effect of Enrofloxacin on Microbial Communities

The results suggest the decreased richness and diversity of tank 1 might be due to limited microbial activities by ENR in the rhizosphere, while microbes continued to expand and diversify in ENR-free tank 2 over six weeks. Because non-invasive sampling was performed during the experiment, the instant impact after ENR addition could only be verified based on the decrease in microbially-mediated N removal by tank 1. However, the similar richness and diversity estimators observed for both tanks at the end of the experiment suggest that the microbial communities of tank 1 took about 4 weeks to adapt to ENR. This reclamation is based on the resumption of the N cycling, which could be verified by the similar removal rates of both tanks obtained during the final (sixth) week.
The resilience of tank 1 after ENR exposure might be partly attributed to plants that could emit a broad range of organic exudates, such as enzymes, amino acids and organic acids for microorganisms in the rhizosphere, as observed in previous CW studies [36,60,61]. Tong et al. [5] and Fernandes et al. [26] reported no significant changes in microbial communities in the planted system 12 weeks after antibiotic exposure, compared to obvious changes in bacterial richness and diversity in the unplanted system, indicating a crucial role played by plants in the recovery of the antibiotic-exposed treatment system. Since the FTW tested in the current study is considered a typical rhizosphere treatment system using plant roots as a filter substrate, our results suggest rhizospheric bacteria and plant roots working together might offer a greater potential than other systems to buffer the impact of ENR or even other antibiotics.
Similarly to the current research, Proteobacteria has been reportedly dominant in CWs in previous studies [33,60], mainly composed of organisms able to perform heterotrophic denitrification [62]. The decrease in Proteobacteria corresponds to the fate of rhizospheric Proteobacteria in the presence of FQ and other unknown antibiotics as described by previous reports [13,23,63]. The decreased abundance of Proteobacteria indicates denitrification had been profoundly prohibited in tank 1 over the experimental period, during which time the process might continue normally in tank 2 as discussed in Section 4.2. Actinobacteria, the second most dominant phylum, was also one of the dominating phyla reported by previous studies [24,33]. Its increase in the presence of antibiotics has also been recorded by Santos et al. [24] for a CW exposed to ENR, and by Lu et al. [46] for a hydroponic system planted with levofloxacin-treated Iris pseudacorus. The phenomenon might be because Actinobacteria carry antibiotic resistance genes (ARGs) to develop major defense mechanisms through b-lactamase, MFS transporter, methyltransferase, acetyltransferase, ABC transport, etc. [5,64]. Thus, ENR might have suppressed most of the bacteria in tank 1, except for Actinobacteria that might have grown better with less competition. Moreover, Patescibacteria as a potential carrier of ARGs that have been reportedly found in the activated sludge [34,65], might have also taken advantage of the inhibiting effect of ENR on other bacteria during the experiment.
The first PCoA suggests that the microbial communities of both tanks were initially similar but differed from each other over the experimental period, while the second PCoA showed consistency with the richness and diversity indices for both tanks at the end of the experiment. The results above confirm that ENR did have an effect on the bacterial communities in tank 1. However, these bacterial communities displayed resilience by returning to a similar state to that of tank 2 (control) after ENR exposure.
Finally, the RDA analysis suggests that the changes in the microbial communities during the experiment were mainly due to the impact of ENR rather than a specific environmental factor in tank 1 or tank 2. It also proposes that the differences in OUT and diversity estimators between the initial sample of both tanks, as mentioned above, might be caused by the influence of the temperature and pH on the microbial community structure in the initial samples of tank 2. While the recovery of the microbial community in tank 1 might have been more dependent on the DO levels.
The low relative abundance of nitrifying bacteria present could possibly be due to low DO levels frequently found in the mesocosms, suggesting nitrification might play a relatively small role in N cycling or removal in the FTW. However, the genera related to denitrification was well represented, confirming the reducing conditions, and, due to low DO levels, were prevailing in both tanks during the experiment. Hence, the finding indicates the denitrification process was obviously suppressed in tank 1 in the presence of ENR, but improved in tank 2 over the experimental period, which supports the claim that the lower nitrate levels in tank 2 were likely due to greater denitrification rates instead of plant uptake. However, the abundances of those genera in tank 1 in the end were similar to the initial values for tank 2, indicating denitrification still remained at baseline levels six weeks after ENR exposure, indicating the resilience of tank 1.
The dominance of Acidovorax might be due to its ARGs as suggested by Feng et al. [66] who found that Acidovorax was one of the dominant genera in a denitrification reactor under oxytetracycline stress, while Pseudomonas might be dominant because it not only contains ARGs [67], but also belongs to the phylum Proteobacteria that can reportedly degrade ENR as mentioned in Section 4.2 [58]. Moreover, Rezakhani et al. [68] reported that Pseudomonas played a prominent role in the enhancement of plant uptake of phosphorous; however, the phosphorous content and concentration in the plant was lower in tank 2 than tank 1 (Table S2), even though Pseudomonas was most abundant in tank 2 during the experiment, suggesting the major role of the plant was to provide a root system for phosphorous adsorption instead of absorption, while Acinetobacter is known for simultaneously removing N and P by utilization of nitrate as an electron acceptor [69]. Candidatus Accumulibacter and Microlunatus that remove P through accumulation were apparently not affected by ENR [70,71,72,73], while Dechloromonas, a polyphosphate-accumulating organism (PAO), was absent from the ENR-treated tank 1 [74].
However, since the relative abundance of the latter four genera was low, their impact on P removal might be negligible.

5. Conclusions

Given the ubiquitous presence of antibiotics in surface waters, the present study examined the impact of repeated exposures to ENR on the performance of an FTW system in nutrient removal. The results show phosphorous removal was not affected by ENR, possibly because it was mainly through adsorption to the plant roots of the system. However, ENR apparently inhibited N removal, mostly through changes in functional bacteria related to nitrification and, particularly, denitrification. Even so, the system took only 4 weeks to adapt and return to a nearly normal state, possibly due to the recovery of microbial communities, particularly denitrifying bacteria that contained ARGs. In addition, the microbial resilience might have been facilitated by the root excretion of the plant, whose growth and nutrient uptake were profoundly enhanced at exposure to ENR. Further investigation should be carried out to verify the capacity of plants to buffer or even remove antibiotics. Meanwhile, the system should be further tested with more complex wastewater containing multiple antibiotics to determine key factors that can improve the performance and resilience. Overall, the study provides a critical insight into the response and resilience of the FTW system to ENR. On a large scale, the system might need to be operated intermittently when treating antibiotics-containing wastewater, to allow the regeneration of the microbial community and, subsequently, prevent deterioration of the system to ensure high quality effluents.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su14063358/s1, Figure S1: Average temperature per week during the entire experiment. Figure S2: Changes of ENR removal during the different cycles (a) and the relation between ENR removal efficiency and temperature (b). Figure S3: Student’s t-test bar plot on phylum level (a, b) and genus level (c, d) for the initial and final sample of tanks 1 and 2. *: p < 0.05; **: p < 0.01; ***: p < 0.001. Figure S4: Community analysis pie plot on phylum level: Initial sample of Tank 1 (a) and Tank 2 (c); Final sample of Tank 1 (b) and Tank 2(d). Figure S5: One-way ANOVA bar plot for the initial and final samples of both tanks. *: p < 0.05; **: p < 0.01; ***: p < 0.001. Figure S6: Schematic diagram of the experimental setup; Table S1: PCR primer sequences and reaction conditions. Table S2: Total content and concentration of N and P in plant tissue. Table S3: Average dissolved oxygen levels during the experimental period. Table S4: Richness and diversity estimation of total bacterial 16S rRNA gene in Rhizosphere from pyrosequencing analysis. Table S5: Relative abundance (%) of genera related to nitrogen removal. Table S6: Relative abundance (%) of genera related to Biological Phosphorus removal.

Author Contributions

Conceptualization, N.R. and J.-C.H.; funding acquisition, J.-C.H.; investigation, N.R., Z.-J.W., Y.W., A.C. and C.Z.; methodology, N.R., Z.-J.W., J.-C.H., Y.W., A.C. and C.Z.; resources, J.-C.H. and Z.W.; supervision, J.-C.H. and Z.W.; visualization, N.R.; writing—original draft, N.R.; writing—review and editing, J.-C.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We thank the laboratory staff of the Analysis Centre of the School of Environmental Science and Engineering for their technical assistance on ENR analysis.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Li, J.; Yang, X.; Wang, Z.; Shan, Y.; Zheng, Z. Comparison of four aquatic plant treatment systems for nutrient removal from eutrophied water. Bioresour. Technol. 2015, 179, 1–7. [Google Scholar] [CrossRef]
  2. González, J.E.; Roldán, G. Eutrophication and Phytoplankton: Some Generalities from Lakes and Reservoirs of the Americas. In Microalgae—From Physiology to Application; Vítová, M., Ed.; IntechOpen: London, UK, 2020; ISBN 978-1-83880-035-2. [Google Scholar]
  3. Lin, Z.; Wang, Y.; Huang, W.; Wang, J.; Chen, L.; Zhou, J.; He, Q. Single-stage denitrifying phosphorus removal biofilter utilizing intracellular carbon source for advanced nutrient removal and phosphorus recovery. Bioresour. Technol. 2019, 277, 27–36. [Google Scholar] [CrossRef]
  4. Li, X.; Li, Y.; Lv, D.; Li, Y.; Wu, J. Nitrogen and phosphorus removal performance and bacterial communities in a multi-stage surface flow constructed wetland treating rural domestic sewage. Sci. Total Environ. 2020, 709, 136235. [Google Scholar] [CrossRef]
  5. Tong, X.; Wang, X.; He, X.; Xu, K.; Mao, F. Effects of ofloxacin on nitrogen removal and microbial community structure in constructed wetland. Sci. Total Environ. 2019, 656, 503–511. [Google Scholar] [CrossRef]
  6. Liang, Y.; Zhu, H.; Bañuelos, G.; Yan, B.; Shutes, B.; Cheng, X.; Chen, X. Removal of nutrients in saline wastewater using constructed wetlands: Plant species, influent loads and salinity levels as influencing factors. Chemosphere 2017, 187, 52–61. [Google Scholar] [CrossRef]
  7. Eveborn, D.; Kong, D.; Gustafsson, J.P. Wastewater treatment by soil infiltration: Long-term phosphorus removal. J. Contam. Hydrol. 2012, 140–141, 24–33. [Google Scholar] [CrossRef]
  8. Maucieri, C.; Salvato, M.; Borin, M. Vegetation contribution on phosphorus removal in constructed wetlands. Ecol. Eng. 2020, 152, 105853. [Google Scholar] [CrossRef]
  9. Su, C.; Zhu, X.; Shi, X.; Xie, Y.; Fang, Y.; Zhou, X.; Huang, Z.; Lin, X.; Chen, M. Removal efficiency and pathways of phosphorus from wastewater in a modified constructed rapid infiltration system. J. Clean. Prod. 2020, 267, 122063. [Google Scholar] [CrossRef]
  10. Gao, L.; Zhou, W.; Huang, J.; He, S.; Yan, Y.; Zhu, W.; Wu, S.; Zhang, X. Nitrogen removal by the enhanced floating treatment wetlands from the secondary effluent. Bioresour. Technol. 2017, 234, 243–252. [Google Scholar] [CrossRef]
  11. Yu, B.; Huang, J.-C.; Zhou, C.; He, S.; Zhou, W. Selenium removal by clam shells and gravels amended with cattail and reed litter. Sci. Total Environ. 2020, 742, 140661. [Google Scholar] [CrossRef]
  12. Zhao, Q.; Huang, J.-C.; He, S.; Zhou, W. Enhancement of a constructed wetland water treatment system for selenium removal. Sci. Total Environ. 2020, 714, 136741. [Google Scholar] [CrossRef]
  13. Huang, X.; Xiong, W.; Liu, W.; Guo, X. Effect of reclaimed water effluent on bacterial community structure in the Typha angustifolia L. rhizosphere soil of urbanized riverside wetland, China. J. Environ. Sci. 2017, 55, 58–68. [Google Scholar] [CrossRef]
  14. Saumya, S. Construction and evaluation of prototype subsurface flow wetland planted with Heliconia angusta for the treatment of synthetic greywater. J. Clean. Prod. 2015, 91, 235–240. [Google Scholar] [CrossRef]
  15. Chen, J.; Liu, Y.-S.; Su, H.-C.; Ying, G.-G.; Liu, F.; Liu, S.-S.; He, L.-Y.; Chen, Z.-F.; Yang, Y.-Q.; Chen, F.-R. Removal of antibiotics and antibiotic resistance genes in rural wastewater by an integrated constructed wetland. Environ. Sci. Pollut. Res. 2015, 22, 1794–1803. [Google Scholar] [CrossRef]
  16. He, Y.; Zhang, L.; Jiang, L.; Wagner, T.; Sutton, N.B.; Ji, R.; Langenhoff, A.A.M. Improving removal of antibiotics in constructed wetland treatment systems based on key design and operational parameters: A review. J. Hazard. Mater. 2021, 407, 124386. [Google Scholar] [CrossRef]
  17. Yuan, Y.; Yang, B.; Wang, H.; Lai, X.; Li, F.; Salam, M.M.A.; Pan, F.; Zhao, Y. The simultaneous antibiotics and nitrogen removal in vertical flow constructed wetlands: Effects of substrates and responses of microbial functions. Bioresour. Technol. 2020, 310, 123419. [Google Scholar] [CrossRef]
  18. Chen, J.; Wei, X.-D.; Liu, Y.-S.; Ying, G.-G.; Liu, S.-S.; He, L.-Y.; Su, H.-C.; Hu, L.-X.; Chen, F.-R.; Yang, Y.-Q. Removal of antibiotics and antibiotic resistance genes from domestic sewage by constructed wetlands: Optimization of wetland substrates and hydraulic loading. Sci. Total Environ. 2016, 565, 240–248. [Google Scholar] [CrossRef]
  19. Liu, L.; Liu, Y.-H.; Liu, C.-X.; Wang, Z.; Dong, J.; Zhu, G.-F.; Huang, X. Potential effect and accumulation of veterinary antibiotics in Phragmites australis under hydroponic conditions. Ecol. Eng. 2013, 53, 138–143. [Google Scholar] [CrossRef]
  20. Tran, N.H.; Hoang, L.; Nghiem, L.D.; Nguyen, N.M.H.; Ngo, H.H.; Guo, W.; Trinh, Q.T.; Mai, N.H.; Chen, H.; Nguyen, D.D.; et al. Occurrence and risk assessment of multiple classes of antibiotics in urban canals and lakes in Hanoi, Vietnam. Sci. Total Environ. 2019, 692, 157–174. [Google Scholar] [CrossRef]
  21. Liu, X.-H.; Guo, X.; Liu, Y.; Lu, S.; Xi, B.; Zhang, J.; Wang, Z.; Bi, B. A review on removing antibiotics and antibiotic resistance genes from wastewater by constructed wetlands: Performance and microbial response. Environ. Pollut. 2019, 254, 112996. [Google Scholar] [CrossRef]
  22. Berglund, B.; Khan, G.A.; Weisner, S.E.; Ehde, P.M.; Fick, J.; Lindgren, P.-E. Efficient removal of antibiotics in surface-flow constructed wetlands, with no observed impact on antibiotic resistance genes. Sci. Total Environ. 2014, 476–477, 29–37. [Google Scholar] [CrossRef]
  23. Li, X.; Lu, S.; Liu, S.; Zheng, Q.; Shen, P.; Wang, X. Shifts of bacterial community and molecular ecological network at the presence of fluoroquinolones in a constructed wetland system. Sci. Total Environ. 2020, 708, 135156. [Google Scholar] [CrossRef]
  24. Santos, F.; de Almeida, C.M.R.; Ribeiro, I.; Ferreira, A.C.; Mucha, A.P. Removal of veterinary antibiotics in constructed wetland microcosms—Response of bacterial communities. Ecotoxicol. Environ. Saf. 2019, 169, 894–901. [Google Scholar] [CrossRef] [PubMed]
  25. Weber, K.P.; Mitzel, M.R.; Slawson, R.M.; Legge, R.L. Effect of ciprofloxacin on microbiological development in wetland mesocosms. Water Res. 2011, 45, 3185–3196. [Google Scholar] [CrossRef] [PubMed]
  26. Fernandes, J.P.; Almeida, C.M.R.; Pereira, A.C.; Ribeiro, I.L.; Reis, I.; Carvalho, P.; Basto, M.C.P.; Mucha, A.P. Microbial community dynamics associated with veterinary antibiotics removal in constructed wetlands microcosms. Bioresour. Technol. 2015, 182, 26–33. [Google Scholar] [CrossRef]
  27. Sayen, S.; Rocha, C.; Silva, C.; Vulliet, E.; Guillon, E.; Almeida, C.M.R. Enrofloxacin and copper plant uptake by Phragmites australis from a liquid digestate: Single versus combined application. Sci. Total Environ. 2019, 664, 188–202. [Google Scholar] [CrossRef]
  28. Li, L.; Yang, Y.; Tam, N.F.-Y.; Yang, L.; Mei, X.-Q.; Yang, F.-J. Growth characteristics of six wetland plants and their influences on domestic wastewater treatment efficiency. Ecol. Eng. 2013, 60, 382–392. [Google Scholar] [CrossRef]
  29. Zhai, X.; Piwpuan, N.; Arias, C.A.; Headley, T.; Brix, H. Can root exudates from emergent wetland plants fuel denitrification in subsurface flow constructed wetland systems? Ecol. Eng. 2013, 61, 555–563. [Google Scholar] [CrossRef]
  30. Wang, P.; Zhang, H.; Zuo, J.; Zhao, D.; Zou, X.; Zhu, Z.; Jeelani, N.; Leng, X.; An, S. A Hardy Plant Facilitates Nitrogen Removal via Microbial Communities in Subsurface Flow Constructed Wetlands in Winter. Sci. Rep. 2016, 6, 33600. [Google Scholar] [CrossRef] [Green Version]
  31. American Public Health Association (APHA). Standard Methods For the Examination of Water and Wastewater, 23rd ed.; American Public Health Association: Washington, DC, USA, 2005. [Google Scholar]
  32. Gogoi, M.; Basumatary, M.; Institutional Biotech Hub, Science College, Kokrajhar, BTC, Assam, India. Estimation of the Chlorophyll Concentration in Seven Citrus Species of Kokrajhar District, BTAD, Assam, India. Trop. Plant Res. 2018, 5, 83–87. [Google Scholar] [CrossRef]
  33. Sun, S.; Liu, J.; Zhang, M.; He, S. Simultaneous improving nitrogen removal and decreasing greenhouse gas emission with biofilm carriers addition in ecological floating bed. Bioresour. Technol. 2019, 292, 121944. [Google Scholar] [CrossRef] [PubMed]
  34. Chen, Y.; Shao, Z.; Kong, Z.; Gu, L.; Fang, J.; Chai, H. Study of pyrite based autotrophic denitrification system for low-carbon source stormwater treatment. J. Water Process Eng. 2020, 37, 101414. [Google Scholar] [CrossRef]
  35. Lezcano, M.Á.; Velazquez, D.; Quesada, A.; El-Shehawy, R. Diversity and temporal shifts of the bacterial community associated with a toxic cyanobacterial bloom: An interplay between microcystin producers and degraders. Water Res. 2017, 125, 52–61. [Google Scholar] [CrossRef] [PubMed]
  36. Chen, D.; Gu, X.; Zhu, W.; He, S.; Wu, F.; Huang, J.; Zhou, W. Denitrification- and anammox-dominant simultaneous nitrification, anammox and denitrification (SNAD) process in subsurface flow constructed wetlands. Bioresour. Technol. 2019, 271, 298–305. [Google Scholar] [CrossRef] [PubMed]
  37. Sun, S.; Liu, J.; Zhang, M.; He, S. Thiosulfate-driven autotrophic and mixotrophic denitrification processes for secondary effluent treatment: Reducing sulfate production and nitrous oxide emission. Bioresour. Technol. 2020, 300, 122651. [Google Scholar] [CrossRef] [PubMed]
  38. Pan, M.; Chu, L.M. Fate of antibiotics in soil and their uptake by edible crops. Sci. Total Environ. 2017, 599–600, 500–512. [Google Scholar] [CrossRef] [PubMed]
  39. Liu, F.; Ying, G.-G.; Tao, R.; Zhao, J.-L.; Yang, J.-F.; Zhao, L.-F. Effects of six selected antibiotics on plant growth and soil microbial and enzymatic activities. Environ. Pollut. 2009, 157, 1636–1642. [Google Scholar] [CrossRef] [PubMed]
  40. Batchelder, A.R. Chlortetracycline and Oxytetracycline Effects on Plant Growth and Development in Soil Systems. J. Environ. Qual. 1982, 11, 675–678. [Google Scholar] [CrossRef]
  41. Das, K.; Roychoudhury, A. Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants. Front. Environ. Sci. 2014, 2, 53. [Google Scholar] [CrossRef] [Green Version]
  42. Chowdhury, F.; Langenkämper, G.; Grote, M. Studies on uptake and distribution of antibiotics in red cabbage. J. Verbr. Lebensm. 2016, 11, 61–69. [Google Scholar] [CrossRef]
  43. Verhagen, F.J.M.; Laanbroek, H.J.; Woldendorp, J.W. Competition for ammonium between plant roots and nitrifying and heterotrophic bacteria and the effects of protozoan grazing. Plant Soil 1995, 170, 241–250. [Google Scholar] [CrossRef] [Green Version]
  44. Carvalho, P.N.; Basto, M.C.P.; Almeida, C.M.R. Potential of Phragmites australis for the removal of veterinary pharmaceuticals from aquatic media. Bioresour. Technol. 2012, 116, 497–501. [Google Scholar] [CrossRef] [PubMed]
  45. Dordio, A.V.; Duarte, C.; Barreiros, M.; Carvalho, A.J.P.; Pinto, A.P.; da Costa, C.T. Toxicity and removal efficiency of pharmaceutical metabolite clofibric acid by Typha spp.—Potential use for phytoremediation? Bioresour. Technol. 2009, 100, 1156–1161. [Google Scholar] [CrossRef] [PubMed]
  46. Lu, H.; Wang, T.; Lu, S.; Liu, H.; Wang, H.; Li, C.; Liu, X.; Guo, X.; Zhao, X.; Liu, F. Performance and bacterial community dynamics of hydroponically grown Iris pseudacorus L. during the treatment of antibiotic-enriched wastewater at low/normal temperature. Ecotoxicol. Environ. Saf. 2021, 213, 111997. [Google Scholar] [CrossRef] [PubMed]
  47. Wang, Q.; Ding, J.; Xie, H.; Hao, D.; Du, Y.; Zhao, C.; Xu, F.; Kong, Q.; Wang, B. Phosphorus removal performance of microbial-enhanced constructed wetlands that treat saline wastewater. J. Clean. Prod. 2021, 288, 125119. [Google Scholar] [CrossRef]
  48. Gonzalez-Martinez, A.; Rodriguez-Sanchez, A.; Martinez-Toledo, M.V.; Garcia-Ruiz, M.-J.; Hontoria, E.; Osorio-Robles, F.; Gonzalez–Lopez, J. Effect of ciprofloxacin antibiotic on the partial-nitritation process and bacterial community structure of a submerged biofilter. Sci. Total Environ. 2014, 476–477, 276–287. [Google Scholar] [CrossRef] [PubMed]
  49. Hou, L.; Yin, G.; Liu, M.; Zhou, J.; Zheng, Y.; Gao, J.; Zong, H.; Yang, Y.; Gao, L.; Tong, C. Effects of Sulfamethazine on Denitrification and the Associated N2O Release in Estuarine and Coastal Sediments. Environ. Sci. Technol. 2015, 49, 326–333. [Google Scholar] [CrossRef] [PubMed]
  50. Zheng, Y.; Liu, Y.; Qu, M.; Hao, M.; Yang, D.; Yang, Q.; Wang, X.C.; Dzakpasu, M. Fate of an antibiotic and its effects on nitrogen transformation functional bacteria in integrated vertical flow constructed wetlands. Chem. Eng. J. 2021, 417, 129272. [Google Scholar] [CrossRef]
  51. Shan, A.; Wang, W.; Kang, K.J.; Hou, D.; Luo, J.; Wang, G.; Pan, M.; Feng, Y.; He, Z.; Yang, X. The Removal of Antibiotics in Relation to a Microbial Community in an Integrated Constructed Wetland for Tail Water Decontamination. Wetlands 2020, 40, 993–1004. [Google Scholar] [CrossRef]
  52. Hachiya, T.; Sakakibara, H. Interactions between nitrate and ammonium in their uptake, allocation, assimilation, and signaling in plants. EXBOTJ 2016, 68, erw449. [Google Scholar] [CrossRef] [PubMed]
  53. Gao, L.; Zhou, W.; Wu, S.; He, S.; Huang, J.; Zhang, X. Nitrogen removal by thiosulfate-driven denitrification and plant uptake in enhanced floating treatment wetland. Sci. Total Environ. 2018, 621, 1550–1558. [Google Scholar] [CrossRef] [PubMed]
  54. Carvalho, P.N.; Araújo, J.L.D.S.; Mucha, A.P.; Basto, M.C.P.; Almeida, C.M.R. Potential of constructed wetlands microcosms for the removal of veterinary pharmaceuticals from livestock wastewater. Bioresour. Technol. 2013, 134, 412–416. [Google Scholar] [CrossRef] [PubMed]
  55. Roose-Amsaleg, C.; Laverman, A.M. Do antibiotics have environmental side-effects? Impact of synthetic antibiotics on biogeochemical processes. Environ. Sci. Pollut. Res. 2016, 23, 4000–4012. [Google Scholar] [CrossRef] [PubMed]
  56. Picó, Y.; Andreu, V. Fluoroquinolones in soil—risks and challenges. Anal. Bioanal. Chem. 2007, 387, 1287–1299. [Google Scholar] [CrossRef] [PubMed]
  57. Conkle, J.L.; Lattao, C.; White, J.R.; Cook, R.L. Competitive sorption and desorption behavior for three fluoroquinolone antibiotics in a wastewater treatment wetland soil. Chemosphere 2010, 80, 1353–1359. [Google Scholar] [CrossRef] [PubMed]
  58. Santos, F.; Mucha, A.P.; Alexandrino, D.A.M.; Almeida, C.M.R.; Carvalho, M.F. Biodegradation of enrofloxacin by microbial consortia obtained from rhizosediments of two estuarine plants. J. Environ. Manag. 2019, 231, 1145–1153. [Google Scholar] [CrossRef] [PubMed]
  59. Dixon, M.J.R.; Loh, J.; Davidson, N.C.; Beltrame, C.; Freeman, R.; Walpole, M. Tracking global change in ecosystem area: The Wetland Extent Trends index. Biol. Conserv. 2016, 193, 27–35. [Google Scholar] [CrossRef]
  60. Yan, Q.; Min, J.; Yu, Y.; Zhu, Z.; Feng, G. Microbial community response during the treatment of pharmaceutically active compounds (PhACs) in constructed wetland mesocosms. Chemosphere 2017, 186, 823–831. [Google Scholar] [CrossRef] [PubMed]
  61. Zhang, M.; Huang, J.-C.; Sun, S.; Ur Rehman, M.M.; He, S.; Zhou, W. Impact of functional microbes on nitrogen removal in artificial tidal wetlands in the Yangtze River estuary: Evidence from molecular and stable isotopic analyses. J. Clean. Prod. 2021, 287, 125077. [Google Scholar] [CrossRef]
  62. Cao, S.; Du, R.; Peng, Y.; Li, B.; Wang, S. Novel two stage partial denitrification (PD)-Anammox process for tertiary nitrogen removal from low carbon/nitrogen (C/N) municipal sewage. Chem. Eng. J. 2019, 362, 107–115. [Google Scholar] [CrossRef]
  63. Xiong, W.; Sun, Y.; Ding, X.; Zhang, Y.; Zhong, X.; Liang, W.; Zeng, Z. Responses of plasmid-mediated quinolone resistance genes and bacterial taxa to (fluoro)quinolones-containing manure in arable soil. Chemosphere 2015, 119, 473–478. [Google Scholar] [CrossRef] [PubMed]
  64. Forsberg, K.J.; Patel, S.; Gibson, M.K.; Lauber, C.L.; Knight, R.; Fierer, N.; Dantas, G. Bacterial phylogeny structures soil resistomes across habitats. Nature 2014, 509, 612–616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Gu, X.; Zhai, H.; Cheng, S. Fate of antibiotics and antibiotic resistance genes in home water purification systems. Water Res. 2021, 190, 116762. [Google Scholar] [CrossRef] [PubMed]
  66. Feng, L.; Yang, J.; Yu, H.; Lan, Z.; Ye, X.; Yang, G.; Yang, Q.; Zhou, J. Response of denitrifying community, denitrification genes and antibiotic resistance genes to oxytetracycline stress in polycaprolactone supported solid-phase denitrification reactor. Bioresour. Technol. 2020, 308, 123274. [Google Scholar] [CrossRef] [PubMed]
  67. Meng, L.; Liu, H.; Lan, T.; Dong, L.; Hu, H.; Zhao, S.; Zhang, Y.; Zheng, N.; Wang, J. Antibiotic Resistance Patterns of Pseudomonas spp. Isolated From Raw Milk Revealed by Whole Genome Sequencing. Front. Microbiol. 2020, 11, 1005. [Google Scholar] [CrossRef] [PubMed]
  68. Rezakhani, L.; Motesharezadeh, B.; Tehrani, M.M.; Etesami, H.; Mirseyed Hosseini, H. Phosphate–solubilizing bacteria and silicon synergistically augment phosphorus (P) uptake by wheat (Triticum aestivum L.) plant fertilized with soluble or insoluble P source. Ecotoxicol. Environ. Saf. 2019, 173, 504–513. [Google Scholar] [CrossRef] [PubMed]
  69. Wang, X.; Zhu, M.; Li, N.; Du, S.; Yang, J.; Li, Y. Effects of CeO2 nanoparticles on bacterial community and molecular ecological network in activated sludge system. Environ. Pollut. 2018, 238, 516–523. [Google Scholar] [CrossRef] [PubMed]
  70. He, S.; Gall, D.L.; McMahon, K.D. “Candidatus Accumulibacter” Population Structure in Enhanced Biological Phosphorus Removal Sludges as Revealed by Polyphosphate Kinase Genes. Appl. Environ. Microbiol. 2007, 73, 5865–5874. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Mino, T.; van Loosdrecht, M.C.M.; Heijnen, J.J. Microbiology and biochemistry of the enhanced biological phosphate removal process. Water Res. 1998, 32, 3193–3207. [Google Scholar] [CrossRef]
  72. Peterson, S.B.; Warnecke, F.; Madejska, J.; McMahon, K.D.; Hugenholtz, P. Environmental distribution and population biology of Candidatus Accumulibacter, a primary agent of biological phosphorus removal: Environmental Distribution of Accumulibacter. Environ. Microbiol. 2008, 10, 2692–2703. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Wagner, M.; Loy, A.; Nogueira, R.; Purkhold, U.; Lee, N. Microbial community composition and function in wastewater treatment plants. Antonie van Leeuwenhoek 2002, 81, 665–680. [Google Scholar] [CrossRef] [PubMed]
  74. Wang, B.; Zeng, W.; Fan, Z.; Wang, C.; Meng, Q.; Peng, Y. Effects of polyaluminium chloride addition on community structures of polyphosphate and glycogen accumulating organisms in biological phosphorus removal (BPR) systems. Bioresour. Technol. 2020, 297, 122431. [Google Scholar] [CrossRef] [PubMed]
Sustainability 14 03358 g001 550
Figure 1. Uptake of P (a) and N (b) by the shoots and roots; the dry weight (c) and chlorophyll content (d) of the plants in tank 1 treated with ENR and tank 2.
Figure 1. Uptake of P (a) and N (b) by the shoots and roots; the dry weight (c) and chlorophyll content (d) of the plants in tank 1 treated with ENR and tank 2.
Sustainability 14 03358 g001
Sustainability 14 03358 g002 550
Figure 2. Nutrient concentrations during the experimental period: TP (a), TN (c); removal efficiencies: TP (b) and TN (d). Treatment phase: ENR was added in the beginning to only tank 1. Recovery phase: neither tank 1 nor 2 received ENR.
Figure 2. Nutrient concentrations during the experimental period: TP (a), TN (c); removal efficiencies: TP (b) and TN (d). Treatment phase: ENR was added in the beginning to only tank 1. Recovery phase: neither tank 1 nor 2 received ENR.
Sustainability 14 03358 g002
Sustainability 14 03358 g003 550
Figure 3. Nutrient concentration during the experimental period: NH4+ (a), NO3− (c), NO2− (e) removal efficiencies: NH4+ (b) and NO3− (d). Treatment phase: ENR was added in the beginning to only tank 1. Recovery phase: neither tank 1 nor 2 received ENR.
Figure 3. Nutrient concentration during the experimental period: NH4+ (a), NO3− (c), NO2− (e) removal efficiencies: NH4+ (b) and NO3− (d). Treatment phase: ENR was added in the beginning to only tank 1. Recovery phase: neither tank 1 nor 2 received ENR.
Sustainability 14 03358 g003
Sustainability 14 03358 g004 550
Figure 4. Bacterial Community Composition Analysis: Circos diagram on phylum level (a) and Community barplot at genus level (b).
Figure 4. Bacterial Community Composition Analysis: Circos diagram on phylum level (a) and Community barplot at genus level (b).
Sustainability 14 03358 g004
Sustainability 14 03358 g005a 550Sustainability 14 03358 g005b 550
Figure 5. Analysis of initial and final samples of both tanks (genus level): PCoA analysis (a); analysis of the final samples (genus level): PCoA analysis (b); RDA analysis on OTU level (c).
Figure 5. Analysis of initial and final samples of both tanks (genus level): PCoA analysis (a); analysis of the final samples (genus level): PCoA analysis (b); RDA analysis on OTU level (c).
Sustainability 14 03358 g005aSustainability 14 03358 g005b
Sustainability 14 03358 g006 550
Figure 6. Heatmap showing the abundance of the functional genera related to N (a) and P (b) removal. Heatmap is color-coded based on row z-scores.
Figure 6. Heatmap showing the abundance of the functional genera related to N (a) and P (b) removal. Heatmap is color-coded based on row z-scores.
Sustainability 14 03358 g006
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ramdat, N.; Wang, Z.-J.; Huang, J.-C.; Wang, Y.; Chachar, A.; Zhou, C.; Wang, Z. Effects of Enrofloxacin on Nutrient Removal by a Floating Treatment Wetland Planted with Iris pseudacorus: Response and Resilience of Rhizosphere Microbial Communities. Sustainability 2022, 14, 3358. https://doi.org/10.3390/su14063358

AMA Style

Ramdat N, Wang Z-J, Huang J-C, Wang Y, Chachar A, Zhou C, Wang Z. Effects of Enrofloxacin on Nutrient Removal by a Floating Treatment Wetland Planted with Iris pseudacorus: Response and Resilience of Rhizosphere Microbial Communities. Sustainability. 2022; 14(6):3358. https://doi.org/10.3390/su14063358

Chicago/Turabian Style

Ramdat, Naven, Zi-Jing Wang, Jung-Chen Huang, Yikun Wang, Azharuddin Chachar, Chuanqi Zhou, and Zhiping Wang. 2022. "Effects of Enrofloxacin on Nutrient Removal by a Floating Treatment Wetland Planted with Iris pseudacorus: Response and Resilience of Rhizosphere Microbial Communities" Sustainability 14, no. 6: 3358. https://doi.org/10.3390/su14063358

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop