Effect of Sequencing Batch Reactor Operation on Presence and Concentration of Tetracycline-Resistant Organisms Sungpyo Kim1, Diana S. Aga2, James N. Jensen3, A. Scott Weber3*
ABSTRACT: The effect of sequencing batch reactor operation on presence and concentration of tetracycline-resistant organisms was studied as a function of organic loading rate (OLR) and solids retention time (SRT), with and without supplemented influent tetracycline. These effects were evaluated using bacterial counts, bacterial production, system growth rate, and percent resistance. These evaluation parameters were applied to both intermediate resistant and resistant heterotrophs, enterics, and lactose fermenters. Tetracycline intermediate resistant and resistant bacteria are defined as the survival of colonies on agar with 5 and 20 mg/L tetracycline, respectively. Based on these studies, increases in influent tetracycline concentration and OLR resulted in amplification of tetracycline resistance. Decreases in SRT also resulted in amplification of tetracycline resistance. Water Environ. Res., 79, 2287 (2007). KEYWORDS: tetracycline intermediate resistance, tetracycline resistance, sequencing batch activated sludge, tetracycline, organic loading rate, growth rate. doi:10.2175/106143007X184087
Introduction Antibiotic-resistant organisms are those that have developed some mechanism to protect themselves from antibiotics (Madigan et al., 1997). Over the past several decades, a rapid emergence of antibiotic resistance in pathogens has been observed, and the number of microorganisms resistant to antibiotics has increased (Madigan et al., 1997; Pillai et al., 2001). Many public health professionals believe that antibiotic-resistant pathogens are becoming a major public health threat (Guardabassi and Dalsgaard, 2002; Pillai et al., 2001). Significant numbers of excreted antibioticresistant organisms survive in wastewater and reach wastewater treatment plants, as documented by Guardabassi and Dalsgaard (2002), Iwane et al. (2001), and Reinthaler et al. (2003). As municipal wastewater is the major source of antibiotic-resistant organisms excreted to the environment by humans, researchers have been interested in the role that biological wastewater processes play in the fate of antibiotic-resistant microorganisms (Guardabassi and Dalsgaard, 2002). This flux of antibiotic-resistant bacteria may 1 Department of Earth and Environmental Engineering, Columbia University, New York. 2 Department of Chemistry, The State University of New York at Buffalo, New York. 3 Department of Civil, Structural, and Environmental Engineering, The State University of New York at Buffalo, New York.
* Department of Civil, Structural, and Environmental Engineering, 212 Ketter Hall, The State University of New York at Buffalo, Buffalo NY 14260, USA, e-mail:
[email protected]. October 2007
amplify in a biological treatment process by vertical growth (microbial growth) and/or horizontal growth (antibiotic gene transfer). Several studies have shown that the environmental conditions in wastewater treatment plants may enhance the likelihood of antibiotic-resistant gene transfer (Mach and Grimes, 1982; Pote´ et al., 2003). The results of previous studies on this subject have been mixed. Conclusions from some studies have suggested that treatment plants raise antibiotic resistance, because an increased portion of antibiotic resistance, normalized by total target organisms, was observed (Anderson, 1993; Bell et al., 1983; Grabow et al., 1973; Mezrioui and Baleux, 1994). Other researchers have shown the opposite result (Kish and Lampky, 1983; Walter and Vennes, 1985). These conflicting results may be the result of differences in the treatment plants and/or their operation (Bell et al., 1983; Guardabassi et al., 2002; Iwane et al., 2001; Mezrioui and Baleux, 1994) or differences in the materials and methods used for the assessment of antimicrobial resistance (i.e., type of medium and definition of breakpoint value) (Guardabassi et al., 2002). For many years, tetracycline has been used widely in human therapy and livestock, because of its low toxicity and broadspectrum activity (Klajn, 2001). Historically, the tetracycline group has been the second most used antibiotic after penicillins in the world (Col and O’Connor, 1987). The broad-spectrum activity of tetracycline affects a broad range of bacteria species, thereby potentially increasing the opportunity to develop resistance in diverse populations (Steinman et al., 2003), such as those found in activated sludge treatment processes. There has been significant documentation of tetracycline resistance (Bell, 1978; Guardabassi and Dalsgaard, 2002; Mach and Grimes, 1982), which appears correlated to antibiotic use. In addition, tetracycline is present in wastewater (Karthikeyan and Meyer, 2006; Kim et al., 2005) and is suspected as an inducer for increasing tetracycline gene transfer between bacteria (Salyers et al., 1995). Therefore, tetracycline is a strong candidate for studying the fate of antibiotic resistance as a function of activated sludge process operation. The objective of this study was to quantify the effect of sequencing batch reactor (SBR) operation on the presence and concentration of tetracycline-resistant organisms. The following three operational factors were tested: (1) influent tetracycline concentration, (2) volumetric organic loading rate (OLR), and (3) solids retention time (SRT). These factors were chosen because of suggestions in the literature on their positive effect on antibiotic resistance. For example, a number of researchers have reported higher numbers of antibiotic-resistant bacteria in hospital wastewater than 2287
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Figure 1—Schematic diagram of SBRs experimental setup used in study.
domestic wastewater (Fountaine and Hoadley, 1976; Guardabassi et al., 1998; Walter and Vennes, 1985), which may result from the selective pressure from higher concentrations of antibiotics in hospital wastewater compared with domestic wastewater (Guardabassi et al., 1998). Variation in substrate concentration, substrate flux, and growth rate as controlled by feed pattern OLR and SRT also are known to be important in horizontal and vertical growth (Ehlers, 1997; Muela et al., 1994). Methods and Materials Study Design. Sequencing batch reactors, which are known for their operational flexibility, were selected for this study. Four 5-L cylindrical reactors (13.7-cm internal diameter) were constructed of clear Plexiglass with a working volume of 4 L. Liquid agitation of the SBR contents was achieved through a direct-drive stirrer (Fisher Scientific Company, Pittsburgh, Pennsylvania). Aeration in all reactors was supplied by humidified compressed air from the laboratory main supply. To increase oxygen transfer efficiency, the air was delivered through Pyrex glass-fritted diffusers (model no. 39533 12C, Corningt, Corning, New York). The Town of Amherst Wastewater Treatment Plant No. 16 (Amherst, New York) primary clarifier effluent was used as the influent source. Preliminary studies showed that influent wastewater could be stored for up to 5 days without significant degradation (Kim, 2005). Accordingly, wastewater was collected twice weekly (Tuesday and Friday) and stored at 48C in a refrigerator for later use.
The initial biomass inocula for all SBRs were obtained from the Amherst, New York, stage 1 aeration basins. To evaluate the effect of influent tetracycline concentration, two SBRs (labeled B type) received domestic wastewater that contained background concentrations of tetracycline only. Background concentrations of tetracycline in the influent used were measured 27 times during the study and were consistently below 1 lg/L, which is in good agreement with the literature (Karthikeyan and Meyer, 2006). Actual measured values were 0.2 6 0.1 (n 5 9), 0.4 6 0.1 (n 5 7), and 0.4 6 0.3 (n 5 11) during phases 1, 2, and 3, respectively. The other two SBRs received the same wastewater augmented with 250 lg/L tetracycline (labeled A type). The augmented tetracycline concentration used mimics concentrations found in agricultural and fish farm wastewater (Mellon et al., 2001). Each subset of two SBRs (based on the influent tetracycline concentration) was further subdivided by the rate of influent addition. In one SBR, influent was added over a 2-minute period simulating a pulse load, called ‘‘slug.’’ The other SBR had influent added slowly and continuously over the appropriate feed cycle time and were considered to more closely mimic a continuously fed reactor, called ‘‘cont.’’ Figure 1 is the schematic diagram of SBR system. The initial motivation for using different feed patterns was to address the effect of transient substrate concentrations on tetracycline resistance. Operation. Changes in volumetric OLR were achieved by alteration of influent volumetric wastewater flux. Changes in system
Table 1—SBR operational periods, operational conditions, and cycle times during Phases 1, 2, and 3. Operating time in a cycle
Feed
Phase
Acclimation Period (days)
Sampling Period (days)
OLR (kg TCOD/m3/d)
SRT* (days)
Slug
1 2 3
49 18 21
60 51 51
0.18 0.77 0.82
10 10 3
Cont
1 2 3
49 18 21
60 51 51
0.18 0.77 0.82
10 10 3
Fill (min)
React (min)
Settle (min)
Decant (min)
Total (hours)
Cycles/day
2 2 2
598 298 298
90 45 45
30 15 15
12 6 6
2 4 4
600 300 300
600 300 300
90 45 45
30 15 15
12 6 6
2 4 4
* solids retention time 2288
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Table 2—Average concentrations of water quality parameters measured during Phases 1, 2, and 3. Effluent Concentrations Phase
Reactor
1
Cont Cont Slug Slug Cont Cont Slug Slug Cont Cont Slug Slug
2
3
A B A B A B A B A B A B
pH 7.12 7.05 7.27 7.38 6.92 6.86 7.26 7.16 7.22 7.16 7.26 7.26
6 6 6 6 6 6 6 6 6 6 6 6
Dissolved oxygen (mg/L)
0.30* 0.28 0.18 0.16 0.27 0.29 0.34 0.31 0.20 0.22 0.21 0.34
4.6 4.6 4.9 4.8 4.0 4.2 4.4 4.1 5.0 5.1 5.7 5.5
6 6 6 6 6 6 6 6 6 6 6 6
0.6 0.3 0.3 0.3 0.3 0.1 0.2 0.1 0.2 0.2 0.3 0.4
MLSS (mg/L) 699 669 812 790 1,892 1,994 1,798 1,871 1,001 1,003 1,281 1,314
6 6 6 6 6 6 6 6 6 6 6 6
FCOD (mg/L)
97 119 116 64 233 215 175 168 173 207 255 307
25 26 28 25 32 35 35 30 36 46 28 27
6 13 6 12 6 13 6 18 66 6 10 6 23 6 11 68 68 611 67
TSS (mg/L) 12.4 9.5 13.3 6.6 14.5 13.2 9.8 6.1 14.2 22.4 21.4 19.6
6 6 6 6 6 6 6 6 6 6 6 6
7.5 4.5 7.3 5.8 6.2 5.1 4.4 3.5 4.5 7.9 9.0 4.4
Tetracycline (lg/L) 35.4 0.3 33.9 0.2 47.3 0.2 37.2 0.1 62.5 0.1 53.9 0.2
611.4 6 0.2 6 21.8 6 0.1 6 18.5 6 0.2 6 13.6 6 0.1 6 29.0 6 0.1 6 17.7 6 0.1
* Average 6 standard deviation.
growth rate were achieved by altering the SRT of the reactors and were independent of OLR. Using this approach, the OLRs in phases 1, 2, and 3 were 0.18, 0.77, and 0.82 kg total chemical oxygen demand (TCOD)/m3 d, respectively. In phases 1, 2, and 3, SRTs, calculated using a mass balance on total suspended solids, were 10, 10, and 3 days, respectively. Typical OLRs reported for full-scale facilities (Metcalf and Eddy, 2003) range from a low of 0.1 kg fiveday biochemical oxygen demand (BOD5)/m3 d for extended aeration to as high as 0.7, 1.0, and 1.6 kg BOD5/m3 d for conventional, step feed, and completely mixed activated sludge, respectively. Adjusting for the differences between the COD and BOD5, volumetric OLRs applied in the current work are consistent with the upper and lower ranges applied in practice. The same is true for the SRT values selected in this study. Accordingly, in phase 1, SBRs were operated under low growth and low OLRs. In phase 2, SBRs were operated under low growth and high OLRs. In phase 3, SBRs were operated under high growth and high OLRs. Throughout each phase, SBR operation consisted of the following four periods in each cycle: fill, react, settle, and decant. Table 1 presents the length of each period for each experimental phase. As reported in Table 1, each phase consisted of acclimation and sampling periods. The minimum sampling period was 51 days. Daily maintenance of the SBRs included monitoring all flowrates, cleaning of influent and effluent lines, and brushing the interior of all SBRs to minimize attached growth. All reactors were brushed/ scraped every day to remove attached microorganisms. The operating temperature of all SBRs was maintained at room temperature, which ranged from 22 to 268C during the study.
Sampling and Analytical Techniques. Water Quality Parameters. During the study, the SBR mixed liquor was sampled twice per week for pH, total and volatile suspended solids (TSS/VSS), and dissolved oxygen. Mixed liquor sampling consisted of a 100-mL grab sample collected from each reactor at the end of the react cycle. A 200-mL aliquot, collected twice per week from the 24-hour composite SBR effluent, was sampled for effluent total and filtered COD (TCOD/FCOD), TSS/VSS, and effluent tetracycline. Mixed liquor pH was measured using an Orion pH meter (EA940, Orion, San Diego, California) using Standard Method 4500-H1 B (APHA et al., 1998). For each sample, duplicate analyses were run and averaged. Mixed liquor dissolved oxygen concentrations in each reactor were measured frequently during aeration (fill and react) periods using a Yellow Springs Instrument Model 54A dissolved oxygen meter (YSI Incorporated, Yellow Springs, Ohio). During these periods, the dissolved oxygen concentration was maintained above 2 mg/L at all times. Mixed liquor and effluent TSS and VSS concentrations were measured using Standard Methods 2540D and 2540E (APHA et al., 1998). Effluent TCOD and FCOD concentrations were measured using Standard Methods 5220C (APHA et al., 1998). Commercially available tetracycline ELISA kits (R-Biopharm GnbH, Darmstadt, Germany) were used for the detection of tetracycline concentration in feed wastewater and effluents of reactors. The details of the ELISA method have been described previously (Kim et al., 2005). Tetracycline-Resistant Bacteria. A number of earlier studies have used lactose fermenters, including Escherichia coli (E. coli), to quantify antibiotic resistance based on the assumption that there is a higher chance that this organism has been previously exposed to
Table 3—Average concentration of tetracycline resistant organisms in the study influent wastewater. Heterotrophic (105 CFU/mL) Phase 1 2 3
Total enteric (103 CFU/mL)
Lactose-fermenting (103 CFU/mL)
Sample size (n)
Intermediate resistant
Resistant
Intermediate resistant
Resistant
Intermediate resistant
Resistant
13 10 13
4.4 6 1.4* 6.4 6 1.3 8.2 6 3.3
1.7 6 0.5 1.3 6 0.2 2.0 6 0.6
3.3 6 1.5 6.3 6 2.1 9.9 6 6.0
0.6 6 0.2 1.5 6 0.4 1.8 6 0.9
1.4 6 0.7 3.3 6 1.2 4.5 6 2.5
0.4 6 0.2 1.2 6 0.3 1.2 6 0..5
* Average 6 standard deviation. October 2007
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Table 4—Summary of evaluation parameter average values calculated for each organism group and phase. X (bacterial concentration, CFU/mL)
Phase 1
Bacteria Heterotrophic
Total enteric
Lactose-fermenting
2
Heterotrophic
Total enteric
Lactose-fermenting
3
Heterotrophic
Total enteric
Lactose-fermenting
Conditions Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont Slug Cont
Sample Intermediate size (n) resistanta
A
12 12 12 12 12 12 12 12 12 12 12 12 10 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 11 11 11 11
B A B A B A B A B A B A B A B A B
VdX/dt (bacterial production, CFU/d)
Resistantb
0.43 0.29 0.27 0.20 0.24 0.50 0.15 0.28 0.07 0.14 0.06 0.13 1.43 2.24 0.83 0.92 1.15 1.39 0.42 0.55 0.21 0.33 0.15 0.24 4.20 1.99 1.09 0.63 3.39 2.55 1.49 0.93 0.98 0.57 0.36 0.31
lnet (net specific growth, d21)
P.R. (percentage of resistance, %)
Intermediate Intermediate Intermediate resistantc Resistantd resistant Resistant resistant Resistant
1.17 0.89 1.24 1.07 0.47 0.78 0.41 0.83 0.12 0.34 0.12 0.49 4.75 5.38 2.53 2.89 3.84 2.36 1.29 1.38 0.76 0.97 0.60 0.67 17.00 6.29 6.10 2.49 5.66 3.05 3.11 2.12 2.41 1.25 1.20 0.96
1.68 1.24 1.32 0.82 1.19 2.17 0.65 1.27 0.29 0.60 0.21 0.49 5.30 8.57 3.11 3.35 4.35 5.16 1.58 2.14 0.80 1.30 0.56 0.97 46.57 24.51 12.09 7.28 38.49 31.90 16.49 11.49 11.10 7.30 4.05 3.84
0.48 0.37 0.52 0.42 0.21 0.37 0.17 0.31 0.05 0.14 0.05 0.17 1.72 1.98 0.93 1.08 1.44 0.91 0.49 0.59 0.31 0.40 0.23 0.31 18.73 7.63 6.69 2.86 6.65 4.05 3.59 2.67 2.83 1.66 1.34 1.22
20.08 20.05 20.07 20.16 22.73 20.88 24.67 23.01 25.19 21.21 28.46 21.28 20.10 20.01 20.25 20.16 21.95 21.62 26.49 24.00 29.83 25.37 210.02 26.48 0.16 0.10 20.04 20.22 20.65 21.40 22.47 23.51 21.68 23.26 29.90 24.51
6.77 6.21 4.55 3.90 2.42 3.29 1.91 1.65 2.96 4.76 3.31 3.71 7.86 11.38 4.80 5.67 6.56 4.08 1.48 1.81 3.83 4.55 2.88 3.27 14.76 13.61 5.41 5.06 5.19 6.44 2.31 2.29 5.56 5.11 1.97 2.18
20.03 20.03 20.02 20.02 22.16 20.89 24.47 20.90 25.93 21.66 211.59 21.33 20.02 0.00 20.08 20.07 21.25 22.28 24.56 23.63 29.07 24.91 28.20 26.21 0.19 0.13 0.10 20.47 20.98 22.60 25.27 22.94 22.59 23.99 212.11 24.06
1.94 1.76 2.06 2.10 0.50 0.51 0.58 0.58 0.58 1.13 0.78 1.60 2.47 2.62 1.59 1.84 2.55 0.70 0.47 0.46 1.45 1.51 1.15 1.03 6.08 4.52 2.97 1.84 0.94 0.82 0.57 0.50 1.26 1.13 0.57 0.67
a
Heterotrophic bacteria in 107CFU/mL, total enteric bacteria in 104 CFU/mL, lactose-fermenting bacteria in 104 CFU/mL. Heterotrophic bacteria in 106 CFU/mL, total enteric bacteria in 103 CFU/mL, lactose-fermenting bacteria in 103 CFU/mL. c Heterotrophic bacteria in 109 CFU/d, total enteric bacteria in 106 CFU/d, lactose-fermenting bacteria in 106 CFU/d. d Heterotrophic bacteria in 109 CFU/d, total enteric bacteria in 106 CFU/d, lactose-fermenting bBacteria in 106 CFU/d. b
the antibiotic (Grabow et al., 1973; Koditschek and Guyre, 1974; Mach and Grimes, 1982; Mezrioui and Baleux, 1994; Reinthaler et al., 2003). The major drawback of using indicator bacteria for evaluating antibiotic resistance is that there is no microorganism
that fully represents the total microbial population. To compensate for this drawback, both heterotrophic and enteric bacteria also were quantified in this study, to evaluate the effect of the study variables on tetracycline resistance.
Table 5—Sample results for bacterial concentration comparisons: heterotrophic intermediate resistant and resistant bacteria in Phase 1. Wilcoxson Rank Sum Test Bacteria Intermediate resistant
Resistant
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Conditions
Bacterial concentration (CFU/mL) (average 6 standard deviation) 7
7
Range
Score
Results
Cont Cont Slug Slug
A B A B
0.29 0.20 0.43 0.27
3 3 3 3
10 107 107 107
6 6 6 6
0.11 0.06 0.19 0.09
3 3 3 3
10 107 107 107
52 to 117
131.5
A.B
52 to 117
132
A.B
Cont Cont Slug Slug
A B A B
0.89 1.07 1.17 1.24
3 3 3 3
107 107 107 107
6 6 6 6
0.22 0.22 0.42 0.23
3 3 3 3
107 107 107 107
52 to 117
4
A,B
52 to 117
61.5
A5B
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Figure 2—Summary of tetracycline effect on tetracycline intermediate resistant heterotrophic, total enteric, and lactosefermenting bacteria (A 5 tetracycline augmented, and B 5 background tetracycline) (X 5 bacterial concentration, VdX/dt 5 bacterial production, lnet 5 net specific growth rate, and P.R. 5 percentage of resistance).
Figure 3—Summary of tetracycline effect on tetracycline-resistant heterotrophic, total enteric, and lactose-fermenting bacteria (A 5 tetracycline augmented, and B 5 background tetracycline) (X 5 bacterial concentration, VdX/dt 5 bacterial production, lnet: net specific growth rate, and P.R.5 percentage of resistance). October 2007
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Figure 4—Summary of volumetric OLR effect on tetracycline intermediate resistant (left) and resistant (right) bacteria in group A (tetracycline-augmented SBRs) (X 5 bacterial concentration, VdX/dt 5 bacterial production, lnet 5 net specific growth rate, and P.R.: percentage of resistance).
Tetracycline-resistant heterotrophs, total enterics, and lactose fermenters in the SBR influent, biomass, effluent, and wasting were monitored twice weekly using a spread plate method, as outlined in Standard Method 9215C (APHA et al., 1998). The survival of colonies on agar with 5 mg/L tetracycline were defined as intermediate tetracycline-resistant bacteria, and colonies surviving on 20 mg/L tetracycline were considered as tetracycline-resistant bacteria, based on recommendations by the National Antimicrobial Resistance Monitoring System (2001). Cultures also were plated with no tetracycline, for control purposes. Before plating, each biomass sample was blended for 3 minutes to homogenize the culture, while influent and effluent samples were blended for 2 and 1 minutes, respectively (Kim, 2005). Heterotrophic bacteria were analyzed on R2A agar, and enterics and lactose fermenters were cultured on MacConkey agar (Difco Laboratories, 1998). Lactose fermenters were differentiated from total enterics by their pink to brick-red color. Colonies were enumerated with a Quebec Darkfield colony counter (Reichert, New York) equipped with a counting pen having audible and digital output. For each sample, duplicate plate counts were conducted, and the average was used for statistical analysis. Following common practice in environmental engineering, results are measured and reported as colony-forming units per milliliter (CFU/mL). Attempts to determine the number of bacteria represented by each CFU cultured were not conducted as part of this work. 2292
Analysis of Antibiotic Resistance. The following four techniques were used to evaluate the effect of influent tetracycline, volumetric OLR, and SRT on tetracycline-resistant bacteria: (1) tetracycline-resistant bacterial concentrations in the SBR biomass; (2) production of tetracycline-resistant bacteria, as measured by a combination of effluent efflux and intentional solids wasting; (3) net specific growth rates, as determined by an SBR population balance; and (4) percentage of resistance, as determined by normalizing resistant concentrations to total concentrations. The net specific growth rates were calculated in this study using a population balance for the sampled SBR, as shown in eq 1. V
dX ¼ Qin Xin Qe Xe þ lnet XV Qw X dt
ð1Þ
Where lnet 5 net specific growth rate for tetracycline-resistant bacteria (days21), X 5 tetracycline-resistant bacterial concentrations in SBR mixed liquor (CFU/mL), Xin 5 influent tetracycline-resistant bacterial concentrations (CFU/mL), Xe 5 effluent tetracycline-resistant bacterial concentrations (CFU/mL), Qin 5 daily influent wastewater flowrate (L/d), Water Environment Research, Volume 79, Number 11
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Figure 5—Summary of volumetric OLR effect on tetracycline intermediate resistant (left) and resistant (right) bacteria in group B (background tetracycline SBRs) (X 5 bacterial concentration, VdX/dt 5 bacterial production, lnet 5 net specific growth rate, and P.R. 5 percentage of resistance).
Qw 5 daily wasted volume (L/d), Qe 5 daily effluent volume (L/d) 5 Qin 2 Qw, and V 5 reactor volume (L). With the exception of dX/dt and lnet, all parameters in eq 1 were measured directly. The term dX/dt was calculated by measuring the difference in bacterial counts between contiguous sampling dates. Once dX/dt was known, lnet was calculated directly using eq 1. This approach provided multiple values of lnet for each phase, enabling statistical comparisons. Results and Discussion Sequencing Batch Reactor Performance. Data collected to monitor SBR performance with respect to conventional parameters are presented in Table 2. All conventional monitored parameters, including pH, dissolved oxygen, mixed liquor suspended solids (MLSS), effluent TSS, and FCOD, are typical of a well-operated activated sludge process, with little differences noted between phases. Tetracycline concentrations were different between phases and reflected differences in influent loading and operation. These tetracycline data have been presented and discussed earlier (Kim et al., 2005). Analysis of Tetracycline Resistance. Influent. Influent tetracycline intermediate resistant and resistant bacteria were measured October 2007
throughout the study. The number of samples, average, and standard deviations for total, intermediate resistant, and resistant heterotrophic, total enteric, and lactose fermenters are presented in Table 3. Cultured bacteria numbers showed similar ranges with the investigated bacterial counts, which were previously reported (Guardabassi and Dalsgaard, 2002). For each organism group and degree of resistance, influent concentrations typically appear to increase with the phase or study duration. Statistical analysis of these data was conducted using a t-test, with 95% confidence limit. Based on the results of this analysis, the appearance of increasing influent tetracycline resistance during the study was not statistically significant. General Overview and Analysis Approach. Bacterial counts (X), bacterial production (VdX/dt), net specific growth rate (lnet), and percentage of resistance (P.R.) were used to assess the effect of SBR operation on antibiotic resistance. Average values for these parameters with sample number and standard deviations are presented in Table 4. Because data were not normally distributed, the Wilcoxson ranksum test was adopted for antibiotic-resistant data statistical analysis in the study. To illustrate how the research hypothesis was tested, intermediate resistant and resistant heterotrophic bacterial concentrations measured in phase 1 are presented in Table 5 for SBRs augmented with 250 lg/L tetracycline (SBRs A) and SBRs 2293
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Figure 6—Summary of SRT effect on tetracycline intermediate resistant (left) and resistant (right) bacteria in group A (tetracycline-augmented SBRs) (X 5 bacterial concentration, VdX/dt 5 bacterial production, lnet 5 net specific growth rate, and P.R. 5 percentage of resistance).
receiving background tetracycline (SBRs B). In the Wilcoxson rank-sum test, the statistics are evaluated by the critical score range. If a compared group’s statistical analysis result (score) is higher or lower than the critical score range, the median of one group is significantly shifted into right (or left) between compared groups, suggesting that tetracycline intermediate resistant and/or resistant bacterial concentrations in tetracycline-fed SBRs are significantly higher (or lower) than that of non-tetracycline-fed SBRs. If the score falls within the range, they are not significantly different. For the statistical testing conducted, the null hypothesis was that ‘‘the medians of the two groups are the same’’. The alternative hypothesis, ‘‘the median of one group is significantly shifted into right (or left) between compared groups,’’ was chosen when the scored value was higher (or lower) than the score ranges, which were calculated at a significance level of 0.05. As shown in Table 5, SBRs with augmented tetracycline concentrations had higher intermediate resistant bacterial counts than their background tetracycline concentration counterparts (A . B). For resistant heterotrophs, there was no difference in the slug fed pair (A 5 B), while the continuously fed SBR receiving background influent tetracycline concentrations had higher counts than its 250 lg/L counterpart (B . A). To evaluate the data trends, 2294
the percent frequencies of A . B and A , B were then plotted as bar charts (Figure 2) for each phase. Because no consistent differences in tetracycline resistance were noted between the two feed patterns used, these data were combined in all statistical testing. Antibiotic Effect. Using the analysis approach presented above, bar chart plots were generated to describe the acceptance of the hypothesis testing based on the Wilcoxson rank sum analysis in each phase using X, VdX/dt, lnet, and P.R. As shown in Figures 2 and 3, the positive effect of influent tetracycline on the selection of tetracycline-resistant bacteria was dependent on factors such as the degree of tetracycline resistance, microbial species, and operating conditions. In Figure 2, tetracycline intermediate resistant heterotrophs and tetracycline intermediate resistant total enterics showed more positive response to influent tetracycline (A . B) when compared with tetracycline intermediate resistant lactose fermenters. The positive effect of influent tetracycline on tetracycline intermediate resistance was increased with increased OLR (compare phases 1 and 2) and with increased SRT (compare phases 2 and 3). This positive effect was observed for all organism groups evaluated. In Figure 3, the positive effect of increased influent tetracycline on tetracycline resistance also was more significant under increased OLR (phase 2) and SRT (phase 3) compared with phase 1. The Water Environment Research, Volume 79, Number 11
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Figure 7—Summary of SRT effect on tetracycline intermediate resistant (left) and resistant (right) bacteria in group B (background tetracycline SBRs) (X 5 bacterial concentration, VdX/dt 5 bacterial production, lnet 5 net specific growth rate, and P.R. 5 percentage of resistance). response between intermediate resistant (Figure 2) and resistant bacteria (Figure 3) was fairly similar for all conditions and bacterial types. Organic Loading Rate. To address the effect of OLR, the X, VdX/dt, lnet, and P.R. were statistically compared between phases 1 and 2. These comparisons are presented in Figure 4 for tetracyclineaugmented reactors and in Figure 5 for background tetracycline concentrations. For both intermediate resistant and resistant populations, X and VdX/dt were higher under the higher OLRs of phase 2, as expected (i.e., P2 . P1). Increased OLR also had a generally positive effect on the percent resistance. Interestingly, while all were negative, higher net specific growth rates of intermediate resistant and resistant bacteria were more frequently observed for the low organic loading conditions of phase 1, except for heterotrophs. Although the data are not presented here, this last observation is strongly supported by the measured influent and effluent fluxes of resistant organisms. For example, the intermediate resistant and resistant total enteric and lactose-fermenting bacteria influx in phase 2 ranged from 6 to 9 times that of phase 1, simply because of increased influent hydraulic loading. However, the phase 2 SBR efflux of these populations, which includes those in the effluent mass and wastage, only ranged from 2 to 5 times that of phase 1. These differences in influent and effluent fluxes of intermediate resistant and resistant total enteric and lactoseOctober 2007
fermenting bacteria suggests higher decay rates for these populations in phase 2. Solids Retention Time. To address the effect of SRT, performance of the populations were statistically compared between phases 2 and 3. These comparisons for X, VdX/dt, lnet, and P.R. are presented in Figure 6 (tetracycline-augmented SBRs) and Figure 7 (background tetracycline SBRs), respectively. Although included in this comparison, the population number comparisons (X) between phases are not thought to be a good indicator for estimating the tetracycline resistance, because wasting amounts were significantly different. In spite of the higher wasting rates of phase 3, however, X in phase 3 was higher than in phase 2, in many cases. The VdX/dt values of the tetracycline-resistant population, the more appropriate indicator between phases, were always higher in phase 3 than in phase 2. Accordingly, higher growth rate conditions resulted in higher tetracycline-resistant bacterial production. In addition, the higher growth rate conditions applied in phase 3 increased the net specific growth rates of intermediate resistant and resistant organisms for all three organism types. Comparing Figures 6 and 7, increased growth rate had a more positive effect on the selection of heterotrophic and lactosefermenting resistance at the higher tetracycline concentrations. Several researchers have demonstrated the importance of microbial growth rates for plasmid transfer frequencies (Ehlers, 1997; Levin 2295
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et al., 1979). Levin et al. (1979) reported that the fastest rate of R-plasmid conjugation is thought to occur during high growth rate, which would be consistent with the conditions applied in phase 3. Ehlers (1997) suggests that a strong positive relationship between increased growth rate and conjugation processes exists, because both require replication of DNA, and the fastest rate of conjugation is thought to occur during the exponential growth phase. Support for this conjecture is found by the increase in percentages of intermediate resistant and resistant heterotrophic and total enteric bacteria under increased-growth-rate conditions. However, the lowgrowth-rate conditions of phase 2 favored biomass percentages of lactose-fermenting bacteria. Organism Type. In general, the extent and/or degree of heterotrophic population response were different than the response of total and lactose-fermenting enterics. The likely reason for this different response is that heterotrophic populations represent a broad range of species, many of which are selected by the constraints imposed on SBR operation. Thus, it makes sense that these species respond more favorably to the conditions applied. Enterics and lactose-fermenting bacteria are discharged directly to the sewer system by the population served and are not favored by typical environmental and/or operational conditions used in wastewater treatment operations (Guardabassi et al., 2002). Thus, it is not surprising that these tetracycline-resistant populations always have lower net growth rates than that of the tetracycline-resistant heterotrophic population. This result also suggests that the choice of E. coli or enteric bacteria as an indicator organism to evaluate the fate of antibiotic resistance bacteria in biological wastewater treatment plant is not ideal. Conclusions Based on the results of this research, the following conclusions were developed: Increases in influent tetracycline increased both intermediate tetracycline resistance and tetracycline resistance under increased OLRs and decreased SRTs; Increases in volumetric OLR applied to SBRs resulted in increased intermediate and tetracycline resistance, for both background and augmented tetracycline SBRs; Decreases in SBR SRT resulted in increased intermediate and tetracycline resistance, for both background and augmented tetracycline SBRs; and Under all experimental conditions, the response of hetertrophs in general was different than the response of enterics and lactose fermenters.
Credits The authors thank the Town of Amherst Wastewater Treatment Plant No. 16 (Amherst, New York) for assistance in completing this work. Submitted for publication May 9, 2006; revised manuscript submitted December 27, 2006; accepted for publication January 23, 2007. The deadline to submit Discussions of this paper is January 15, 2008. References American Public Health Association; American Water Works Association; Water Environment Federation (1998) Standard Methods for the 2296
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