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Effect of organic carbon on ammonia oxidizing bacteria in a mixed culture
Bioresource Technology 101 (2010) 6454–6460
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Effect of organic carbon on ammonia oxidizing bacteria in a mixed culture LeeAnn Racz, Tania Datta, Ramesh Goel * Department of Civil and Environmental Engineering, University of Utah, Suite 104, 122 S. Central Campus Drive, Salt Lake City, UT 84112-0610, USA
a r t i c l e
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Article history: Received 3 December 2009 Received in revised form 1 March 2010 Accepted 11 March 2010 Available online 3 April 2010 Keywords: Nitrification Monod kinetics Microbial ecology Cloning and sequencing Fluorescent in situ hybridization
a b s t r a c t This study examined the effect of organic carbon (peptone vs. glucose) on two sequencing batch reactors performing simultaneous carbon oxidation and nitrification. Although each reactor had similar COD oxidation kinetics (0.029 and 0.036 mg COD mg VSS1 h1), the Monod nitrification kinetics for the peptonefed reactor (lm = 2.72 h1, Ks = 17.8 mg N L1) were faster than for the glucose-fed reactor (lm = 0.868 h1, Ks = 26.5 mg L1). The overall bacterial communities were profiled by 16S rRNA cloning and sequencing and revealed homology with a greater variety of bacteria from the peptone-fed reactor than the glucose-fed reactor. In addition, amoA cloning and sequencing, terminal restriction fragment length polymorphism, and fluorescent in situ hybridization experiments indicated greater AOB diversity and abundance in the peptone-fed reactor. This research provides evidence that the organic carbon source affects the make-up of the heterotroph community as well as AOB in mixed cultures. Published by Elsevier Ltd.
1. Introduction The activated sludge process is widely used around the globe to treat municipal wastewater. This treatment technique is mature, and its engineering and microbiology are well understood. Our firm understanding of the activated sludge process enables us to configure treatment plants to remove organic pollutants, nitrogenous compounds and phosphorus from municipal wastewater. While there are many contaminants removed from municipal wastewater, ammonia nitrogen (NH3–N) is of particular concern as their release to surface waters is directly related to eutrophication, a mechanism through which surface waters undergo excess algae growth. Nitrification is a two-step process which biologically removes NH3–N in the activated sludge processes. Ammonia oxidizing bacteria (AOB) oxidize NH3–N to nitrite nitrogen (NO2–N) in the first step. In the second step, nitrite oxidizing bacteria (NOB) oxidize NO2–N to nitrate nitrogen (NO3–N). Even though AOB require inorganic carbon for growth, AOB are quite diverse among wastewater treatment plants. For instance, Wagner et al. (1998) reported a strong presence of Nitrosococcus mobilis, which phylogenetically belongs to the genus Nitrosomonas (Koops and Pommering-Röser, 2001), when studying an industrial wastewater treatment plant with high ammonia concentrations. Conversely, Hiorns et al. (1995) noted a prevalence of AOB related to Nitrosospira in activated sludge systems. Dionisi et al. (2002) similarly concluded the dominant AOB in their activated sludge system was Nitrosomonas oligotropha. Other studies reported that * Corresponding author. Tel.: +1 315 801 5816110; fax: +1 315 801 585 5477. E-mail address: [email protected] (R. Goel). 0960-8524/$ - see front matter Published by Elsevier Ltd. doi:10.1016/j.biortech.2010.03.058
Nitrosospira-related AOB were seldom detected in wastewater treatment plants and Nitrosomonas AOB were most common (Mobarry et al., 1996; Purkhold et al., 2000). Park and Noguera (2004) explained that the type of wastewater as well as operational parameters influence AOB community profiles. AOB commonly coexist with heterotrophs in full-scale activated sludge systems. Temperature (Ducey et al., 2010), solid retention time (Duan et al., 2009), high carbon-to-nitrogen (C/N) ratios and salinity (Rene et al., 2008), low dissolved oxygen concentrations (Rongsayamanont et al., 2010), and inhibitory compounds (Gotvajn and Zagorc-Koncˇan, 2009) affect AOB communities and metabolism. Several researchers have also studied the interaction between nitrifying and heterotrophic bacteria. Jones and Hood (1980) observed that Nitrosomonas spp. increased ammonium oxidation by 150% when grown in the presence of heterotrophs. More recently, Michaud et al. (2006) examined the effect of particulate organic carbon on heterotrophic bacterial populations and nitrification efficiency in biological filters. Also, Okabe et al. (2005) confirmed that in complex multispecies biofilms, including nitrifying communities, exchange of substrates among different phylogenetic groups is the most important ecophysiological interaction. Wittebolle et al. (2009) reported that the source of inoculum will affect the AOB community profile but not necessarily the nitrification functionality. Wastewater treatment plants have combined carbon oxidation and nitrification in the same reactor since the 1970s, although heterotrophs compete with nitrifying bacteria for oxygen and space, particularly in biofilms (Nogueira et al., 2002). Heterotrophs gain their energy primarily from organic carbon sources. On the other hand, nitrifying bacteria are autotrophic organisms which grow on inorganic carbon. The composition of inorganic
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carbon, which primarily exists in form of carbonates and bicarbonates in municipal wastewaters, does not change much. However, variations in organic carbon composition in municipal wastewater lead to wide variations in heterotrophic microbial ecology, both in time and space. We point out that the ecologies of AOB, and possibly NOB, differ despite the fact that these organisms primarily feed on inorganic carbon sources. Therefore, it is possible that there is some symbiotic relationship between heterotrophs and AOB although both of these feed on different carbon sources. The objective of this research was to evaluate the effect of organic carbon sources on the AOB community. Two identical sequencing batch reactors with nitrifying activated sludge were fed with two different carbon sources: one with peptone and sodium acetate and the other with glucose and sodium acetate. Our earlier work (Racz et al., 2010) used molecular fingerprinting techniques to characterize the microbial ecologies of the two reactors. In that research, automatic ribosomal intergenic spacer analysis (ARISA) indicated a more diverse overall bacterial community in the peptone-fed reactor than the glucose-fed reactor. This research, however, provides a fine-scale profile of the heterotroph and AOB microbial ecologies in the two reactors using cloning and sequencing. Furthermore, this study includes examination of the performance kinetics which revealed additional differences between the two reactors. To the best of our knowledge, no other studies have examined the effect of organic carbon sources, and in turn a heterotrophic population, on an AOB community. We hypothesize that in a mixed culture of heterotrophs and AOB, the more complex the organic carbon source will lead to a more diverse heterotrophic and, in turn, the more diverse the AOB community.
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ganic carbon with amino acids, an important source of carbon, nitrogen and energy for heterotrophic bacteria in aquatic environments (Ouverney and Fuhrman, 2000). Therefore, peptone was added as well. Feed A contained (per liter) 44.6 g NaHCO3 and the composition of feed B was (per liter) 6 g peptone, 1.25 g sodium acetate, 2.26 g NH4Cl, 6.86 g MgCl26H2O, 1.72 g CaCl22H2O, 0.6675 g KH2PO4 and 20 mL of a trace element solution. The trace element solution, adapted from Hesselmann et al. (1999), consisted of the following per liter of deionized water: 5.46 g citric acid, 4.0 g hippuric acid, 0.72 g Na3NTA2H2O, 0.3 g Na3EDTA4H2O, 3.0 g FeCl36H2O, 0.5 g H3BO3, 0.3 g ZnSO47H2O, 0.24 g MnCl24H2O, 0.14 g CuSO45H2O, 0.06 g KI, 0.06 g Na2MoO42H2O, 0.06 g CoCl26H2O, 0.06 g NiCl26H2O and 0.06 g Na2WO42H2O. To evaluate the effect of carbon source on the microbial community, a second sequencing batch reactor was initiated with the mixed liquor from the first reactor which was fed with peptone and acetate. The operation of this second reactor was identical to the first one except that the peptone in the feed was gradually replaced with glucose over a period of three weeks as an effort to change the organic carbon source in the feed. Glucose was chosen as it is a simple sugar and, like peptone, is easily metabolizable. The final concentration of glucose in feed B was 5.38 g L1, which maintained a constant COD concentration in the reactor influent. Since peptone contains organic nitrogen in the form of amino acids and peptides, another experiment was conducted to determine the contribution of NH3–N from hydrolyzed peptone. In this experiment, peptone was dissolved in filtered (0.2 lm) effluent from the peptone-fed reactor proportional to the amount fed to the SBR. Concentrations of NH3–N, NO3–N, and NO2–N were measured at the beginning and after 24 h of the effluent being placed on an orbital shaker.
2. Methods 2.2. DNA extraction, PCR, TRFLP, cloning and sequencing 2.1. Reactor operation The reactors were operated as described previously (Racz et al., 2010). Specifically, an initial 2.0 L sequencing batch reactor was operated to achieve simultaneous COD and nitrification removals. The reactor was operated on a 12 h cycle (total two cycles per day) consisting of two stages. The first stage was an 11.5 h aerobic period that started with the rapid addition of the synthetic wastewater and air. During this stage, the mixed liquor was maintained at 4–5 mg L1 DO concentration by purging air using an aquarium pump. The second stage consisted of 30 min of settling and decanting. The pH in the reactors was maintained at 7.2 ± 0.3 by adding acid or base using a pH controller (Cole-Parmer Instrument Company, Vernon Hills, Illinois). All pumps associated with the reactor system were automated using electronic timers (Cole-Palmer). The reactor was seeded with mixed liquor from a local wastewater treatment plant. A total volume of 670 ml was decanted at the end of the settling period in each cycle and substituted with the synthetic wastewater at the beginning of the next cycle, providing a hydraulic retention time of 36 h. The solid retention time in the reactor was maintained at 20 days by wasting the mixed liquor from the reactor on daily basis. To simulate the desired strength of synthetic wastewater, two pre-autoclaved concentrated solutions (feed A and B) were mixed with the deionized water directly in the reactor reservoir. During the feeding step, the reactors received 624 ml of deionized water, 8 ml of feed A and 38 ml of feed B. Municipal wastewater contains a complex mixture of organic compounds, including volatile fatty acids. Since polysaccharide and protein fermentation forms acetate, a common substrate in wastewater treatment systems (Kindaichi et al., 2004) which is readily metabolizable by heterotrophs (Tam et al., 1992), sodium acetate was added to simulate the volatile fatty acids present in municipal wastewater. Peptone is a complex source of or-
Genomic DNA was extracted from biomass samples collected from the reactors using a soil DNA extraction kit (MoBio Labs, Solana Beach, CA). TRFLP was performed using the modified protocol developed by Park and Noguera (2004). Briefly, labeled forward (amoA-1F) and reverse (amoA-2R) primers were used to amplify the amoA gene (Park and Noguera, 2004). The forward primer was labeled with the fluorophore HEX, and the reverse primer was labeled with 6FAM. Amplification was done on a master gradient thermocycler (Eppendorf) with the following temperature cycle: denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 1 min, annealing at 56 °C for 1.5 min, and elongation at 72 °C for 1.5 min, with polishing steps at 60 °C for 1.5 min and 72 °C for 10 min. PCR products were run on 1% agarose gel for 40 min against a standard DNA Ladder (Promega) to verify the length. The products were then purified from the gel using the QIAQuick PCR purification kit (Qiagen Inc., Valencia, CA). The purified PCR products were digested with TaqI restriction endonuclease (MBI Fermentas, Hanover, MD). Aliquots (2 lL) of digested PCR products were mixed with 1 lL of ROX-labeled GENEFLOt 625 internal length standard (CHIMERx, Milwaukee, WI) and 20 lL of formamide. Samples were processed through an Applied Biosystems 3130xl Genetic Analyzer capillary electrophoresis instrument (Applied Biosystems, Foster City, CA) at the University of Utah Core Facility and analyzed using the GeneMapper software (Applied Biosystems, Foster City, CA) version 2.6. The resulting fragment lengths were compared with known fragment lengths of AOB to identify presence of specific AOB (Park and Noguera, 2004; Park et al., 2002; Horz et al., 2000). To obtain the information on all ammonia oxidizers at a finer scale using cloning and sequencing, the amoA gene fragment was amplified using the same protocol that was used in TRFLP except
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Table 1 Probes used for FISH. Target organism Most bacteria
Probe name EUB338
Betaproteobacterial AOB
Nso1225
Nitrosomonas oligotropha
Nmo218
Nitrosomonas europaea
Nse1472
Sequence 0
5 -GCT GCC TCC CGT AGG AGT30 50 -CGC CAT TGT ATT ACG TGT GA-30 50 -CGG CCG CTC CAA AAG CAT-30 50 -ACC CCA GTC ATG ACC CC-30
Formamide (%)
Reference
0–50
Amann et al. (1990b) Mobarry et al. (1996) Gieseke et al. (2001) Juretschko et al. (1998)
35
35
50
Concentrations of NH3–N, NO3–N, NO 2 , and COD in the influent and effluent were periodically measured using Hach methods 10,031, 10,020, 8153, and 8000, respectively. Total suspended solids (TSS) and volatile suspended solids (VSS) were measured using standard methods (APHA, AWWA, WEF, 1998). All measurements were made in duplicate. Monod kinetics parameters for nitrification were estimated using the substrate depletion method described by Shuler and Kargi (2002). The Monod equation is expressed as:
80
(a)
100 NH3-N
60
NO2-N
80
NO3-N Total N COD
40
60
40 20
COD concentration (mg/L)
FISH was performed as detailed in Manz et al. (1992). Biomass from both reactors was washed twice in PBS and fixed in 4% (v/ v) paraformaldehyde solution as described previously (Amann et al., 1990a; Coskuner et al., 2005). Following fixation, the cells were washed again and resuspended in 1 mL of hybridization buffer and 37.5 lL of probe solution (12.5 lM). Table 1 lists the probes used and the corresponding target organisms. All probes were labeled with Cy5. The biomass was allowed to hybridize at 46 °C for 12–16 h at which time the biomass was washed in wash buffer and washed twice again in PBS. The biomass was resuspended in 1 mL PBS with 0.5% TWEEN 20 at 4 °C. The cells were quantified
2.4. Other analytical methods
20
0
0 0
80
2
4
6 Time (hours)
8
(b)
10
NH3-N NO2-N NO3-N Total N COD
60
100
80
60 40 40 20
COD concentration (mg/L)
2.3. Fluorescent in situ hybridization (FISH)
on a CANTO II flow cytometry instrument. Percentages of each target organism were calculated relative to all bacteria (EUB338), and percentages of N. oligotropha (Nmo218) and Nitrosomonas europaea (Nse1472) were calculated relative to all Betaproteobacterial AOB (Nso1225). Negative controls were obtained by quantifying unlabeled biomass. FISH was similarly performed on slides. However, Nse1472 was labeled with Cy5 and Nmo218 was labeled with Cy3. As Nse1472 required a higher stringency (50% formamide) than Nmo218 (35% formamide), Nse1472 was hybridized first. Following hybridization with both probes, the samples were stained with 40 ,60 -diamidino2-phenylindole (DAPI) (1 lg ml1) for 5 min in the dark to visualize all cells. The slides were then washed with 4 °C DI water and allowed to air dry. The cells were viewed using a fluorescence microscope (Olympus BX51) equipped with a halogen lamp and camera (Olympus DP71).
N concentration (mg/L)
that the primers were not labeled. Cloning and sequencing was similarly performed to profile the overall microbial community by amplifying the 16S rRNA fragment. The 16S rRNA fragment was targeted using the primers 8f (50 -AGAGTTTGATCMTGGCTCAG-30 ) and 1492r (50 -GGYTACCTTGTTACGACTT-30 ) and the following temperature cycle: initial denaturation at 94 °C for 3 min, followed by 30 cycles of denaturation at 94 °C for 1 min, annealing at 55 °C for 45 s, and elongation at 72 °C for 2 min, with a final elongation at 72 °C for 2 min. PCR products were run on 1% agarose gel for 40 min against a standard DNA Ladder (Promega) to verify the length and then purified. For cloning, the purified PCR products were ligated to a pCRÒ4-TOPOÒ (Invitrogen, CA) kanamycin resistant vector or plasmids, and the recombinant plasmid was then transformed to chemically competent Escherichia coli cells. After allowing a transformation time of 60 min, the cells were spread on a growth media containing agar, LB broth and 50 lg mL1 kanamycin in order to grow colonies. Distinct clones from the LB plate containing kanamycin were selectively picked and were subjected to further screening for appropriate inserts by growing them in the same LB growth medium containing 50 lg mL1 kanamycin. Plasmid DNA was extracted using the Wizard Plus Miniprep DNA purification system (Promega, WI). To verify the presence of inserts in the purified plasmids, extracted plasmid DNA were run on 1% agarose gel. To conduct sequencing, 1 ll of the plasmid DNA was used as template for cycle sequencing using a Big Dye sequencing kit (Applied Biosystems, Foster City, CA) and using the forward primer (amoA1f or 8f) on an ABI PRISM 377 automated DNA sequencer (Applied Biosystems, USA). The ClustalX software (Thompson et al., 1997) version 1.81 was used to align sequences of the recovered clones with other published sequences. PhyML 3.0 (Guindon and Gascuel, 2003) was used to construct phylogenetic trees using the maximum likelihood method, and bootstrap values were based on 100 trials. TreeView software (Page 1996) version 1.6.6 was used to view the phylogenetic trees.
N concentration (mg/L)
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20
0
0 0
2
4
6 Time (hours)
8
10
Fig. 1. Performance kinetics of (a) peptone-fed reactor 1 and (b) glucose-fed reactor 2.
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l¼
lm S Ks þ S
where l is the specific growth rate, lm is the maximum specific growth rate, S is the substrate concentration, and Ks is the saturation constant equal to the concentration of the substrate when l = ½ lm.
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3. Results and discussion 3.1. Reactor performance Fig. 1 illustrates the COD oxidation and nitrification kinetics for both reactors over a typical cycle. The values presented are the aver-
Fig. 2. (a) TRFLP plot for reactor 1 prior to feed transition. (b) TRFLP plot for reactor 2, day 2 after feed transition. (c) TRFLP plot for reactor 2, 13 days after feed transition (d) TRFLP plot for reactor 2, 134 days after feed transition. The black and grey peaks indicate forward and reverse terminal fragments, respectively. Reproduced with permission from Water Science and Technology (Racz et al., 2010) with permission from the copyright holders, IWA Publishing.
Fig. 3. Phylogenetic tree for the amoA gene in reactors 1 and 2. The clones within each shaded box share at least 99% homology with each other.
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ages of duplicate measurements. Similar reactor performances were observed during the operation of both reactors as depicted in Fig. 1. Each reactor had similar first-order COD oxidation kinetics, with the degradation rate constants of 0.029 and 0.036 mg COD mg VSS1 h1 for reactors 1 and 2, respectively. These results align with Duan et al. (2009) in which a mixed culture operating at various solids retention times resulted in different heterotrophic communities but similar COD oxidation performances. However, the nitrification kinetics for reactor 1 were considerably faster than for reactor 2. The maximum growth rate coefficient (lm) for reactor 1 was 2.72 h1, whereas it was only 0.868 h1 for reactor 2. The half-saturation coefficient (Ks) was 17.8 mg N L1 for reactor 1 and 26.4 mg N L1 for reactor 2. These values are comparable with other nitrifying cultures (Chandran et al., 2008; van Haandel and van der Lubbe, 2007). Although the nitrification kinetics for each reactor were markedly different, the effluent NH3–N concentrations from each reactor at the end of each cycle were similar. The average concentrations of NH3–N and COD in the effluents from both reactors over a period of 83 days were 0.531 ± 1.48 mg L1 and 3.83 ± 4.76 mg L1, respectively. These effluent concentrations equated to 98.1 ± 1.84% COD and 97.3 ± 6.69% NH3–N removals in reactor 1 and 99.1 ± 1.29% COD and 99.4 ± 0.76% NH3–N removals in reactor 2. NO2–N was not present in the effluent from both reactors, thus indicating the completion of second stage of nitrification. The NO3–N concentration in the effluent from the glucose-fed reactor 2 was 26.5 mg L1, which was nearly equivalent to the influent NH3–N concentration in reactor. However, the average NO3–N in the effluent of the peptone-fed reactor 1 was 72.2 ± 6.57 mg L1. In the separate experiment in which peptone was dissolved in the effluent of the peptone-fed reactor, we observed an increase of ammonia but no increase of nitrate or nitrite. Since there are limited pathways of nitrate production through metabolic pathways other than through nitrification, the increased NO3–N in the peptone-fed reactor can be attributed to oxidation of organic nitrogen to inorganic ammonia which led to more nitrate production by nitrifiers. The average TSS and VSS concentrations in reactor 1 were 2707 ± 309 and 2484 ± 429 mg L1, respectively and the corresponding concentrations in reactor 2 were 1830 ± 184 and 1597 ± 157 mg L1, respectively.
PCR amplification and lack of adequate controls (Park and Noguera, 2004).
18 Reactor 1 Reactor 2
16 Percentage of bacteria in reactor
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14 12 10 8 6 4 2 0
Nse1472 Nso1225 Nmo218 (Betaproteobacterial AOB) (N. oligotropha) (N. europaea)
Fig. 4. Percentages of AOB relative to all bacteria in each reactor.
3.2. Response of AOB community against changes in organic carbon source 3.2.1. TRFLP TRFLP was performed on the mixed liquor from reactor 1 when it was at steady state and the same procedure was performed on reactor 2 during the transition period when peptone was slowly replaced by glucose in the reactor 2. The profiles are shown in Fig. 2. Panel (a) in Fig. 2 shows the TRFLP profile for reactor 1 at steady state. According to the TRFLP profiles, the main AOB present in reactor 1 were represented by fragments 48/441, 48/206, 354/ 135, 219/135 and 219/270. Likewise, the AOB population in reactor 2 at steady state (after 134 days) was represented by fragments 354/135, 219/135 and 219/270, which were the same as some of the terminal fragments in reactor 1. In addition, a new terminal fragment with size 441/57 was also noticed in the reactor 2. The terminal fragments 219/135 and 219/270 mostly represent N. europaea lineage (Park and Noguera, 2004). Fragment length 48/ 441 is characteristic of the N. oligotropha lineage. Using results from Park and Noguera (2004), we find that the other two remaining fragment lengths (48/206, 354/135) may belong to different strains within N. oligotropha lineage. The TRFLP results suggest that N. europaea was abundant in the peptone-fed reactor whereas a new lineage of the genus Nitrosomonas with terminal fragment length of 419/57 along with N. europaea dominated the glucosefed reactor. However, we note that the TRFLP tool alone is not quantitative, as quantification is hampered by inherent biases in
Fig. 5. FISH image of biomass from (a) reactor 1 and (b) reactor 2. All cells were stained in DAPI (blue), N. oligotropha (Nmo218, Cy3) is colored magenta and N. europaea (Nse1472, Cy5) is colored green.
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3.2.2. Identification of AOBs using cloning and sequencing To obtain a finer scale resolution in AOB community present in both reactors, amoA gene based cloning and sequencing was performed on the genomic DNA obtained from both reactors. The phylogenetic comparison of recovered amoA sequences from both reactors and other relevant sequences from publicly available databases is depicted in Fig. 3. Forty-eight clones were recovered from each reactor and were divided into operational taxonomic units (OTUs) based on 99% or more sequence homology among them. Most of the clones (30 out of 40) from the peptone-fed reactor 1 were closely associated with an uncultured Nitrosomonadaceae bacterium in the N. oligotropha lineage. This uncultured bacterium was recovered from the rhizosphere of a laboratory-scale planted fixed-bed reactor which simulated a constructed wetland system undergoing a diurnal redox potential variation (Nikolausz et al., 2008). The bacteria in the rhizosphere of such a constructed wetland receive amino acids, sugars, and organic acids through the roots. Therefore, there is an active environment with complex substrates for the bacterial community. Peptone, which was the primary feed to reactor 1, is also a complex organic substrate. Hence, it is entirely justifiable that most of AOB clones recovered from reactor 1 showed similarity with the uncultured Nitrosomonadaceae bacterium recovered from the constructed wetland rhizosphere. Most of the clones form the glucose-fed reactor 2 had more than 99% sequence similarity with another uncultured bacterium recovered from a laboratory-scale reactor operated under low dissolved oxygen conditions (Park and Noguera, 2004) in the N. oligotropha lineage. Five AOB clones from each reactor had greater than 99% homology with a clone identified as uncultured bacterium clone Marshall-77 W (NCBI Accession number AY356431, Park and
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Noguera, 2004). This clone was identified in a study examining the effect of dissolved oxygen on AOBs (Park and Noguera, 2004), and was classified as belonging to the N. europaea lineage (81.4% homology). TRFLP analysis on the peptone-fed reactor showed that although ammonia oxidizers most closely related to N. oligotropha lineage were also present, AOB related to N. europaea were abundant in this reactor. However, most of the clones form this reactor matched an uncultured Nitrosomonadaceae bacterium in the N. oligotropha lineage. This shows that TRFLP analysis underestimated the presence of N. oligotropha lineage in the peptone-fed reactor. Nevertheless, quantification with FISH identified the relative abundance of AOB in the reactors. 3.2.3. FISH Percentages of all Betaproteobacterial AOB, N. oligotropha and N. europaea were quantified using flow cytometry assisted FISH relative to the percentages of all bacteria as illustrated in Fig. 4. In the peptone-fed reactor 1, 16.1% of all bacteria were Betaproteobacterial AOB, 13.7% were N. oligotropha, and 2.12% were N. europaea. In the glucose-fed reactor 2, 3.58% of all bacteria were Betaproteobacterial AOB, 3.37% were N. oligotropha, and 0.41% were N. europaea. These results agree with the cloning and sequencing results in that nearly all of the AOB were N. oligotropha in both reactors. While both reactors contained some amount of N. europaea, the relative proportion of this species was greater in the peptone-fed reactor than in the glucose-fed reactor. In addition, the greater proportion of AOB in reactor 1 than reactor 2 provides a possible explanation as to the faster nitrification kinetics in reactor 1 when compared with reactor 2. Fig. 5 provides FISH images of each reactor’s biomass on slides hybridized with Nmo218 (N. oligotropha) and Nse1472 (N. euro-
Fig. 6. Phylogenetic tree for the 16S rRNA gene in reactors 1 and 2. The clones within each shaded box share at least 99% homology with each other.
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paea) and stained with DAPI. This image supports the flow cytometry results in that in each reactor N. oligotropha was abundant while there was scant N. europaea. The images also illustrate the greater percentage of AOB in reactor 1 than reactor 2. 3.3. Ecology of heterotrophic bacteria The phylogram presented in Fig. 6 shows the distribution of clones retrieved from the peptone-fed and glucose-fed reactors along with other sequences taken from other studies. Clones from the peptone-fed reactor were mostly represented by Betaproteobacteria, Acidobacteria, Sphingobacteria crenotrichaceae and Sphingobacteria saprospiraceae families. On the other hand, clones from the glucose-fed reactor were mostly represented by Alphaproteobacteria, Sphingobacteria flexibacteraceae and S. saprospiraceae families. Although both reactors shared some common bacterial ecology, different bacterial ecologies were also noticed in both reactors. For example, S. saprospiraceae was the most abundant family in the peptone-fed reactor based on the cloning results, yet this particular bacterial population was completely absent in the glucose-fed reactor. 4. Conclusions This study provides insight for heterotrophic bacteria and AOB interactions. The reactor receiving peptone had more diverse overall bacterial and AOB communities than the glucose-fed reactor. Although both reactors received the same inorganic carbon and shared similar species of AOB, the organic carbon source affected the composition of the bacterial strains. FISH experiments revealed that the peptone-fed reactor also had a greater proportion of AOB than the glucose-fed reactor. This increased proportion of AOB helps to explain the faster nitrification kinetics in the peptonefed reactor than the glucose-fed reactor, although both reactors shared similar COD oxidation kinetics. References Amann, R.I., Krumholz, L., Stahl, D.A., 1990a. Fluorescentoligonucleotide probing of whole cells for determinative, phylogenetic, and environmental studies in microbiology. J. Bacteriol. 172, 762–770. Amann, R.I., Binder, B.J., Olson, R.J., Chisholm, S.W., Devereux, R., Stahl, D.A., 1990b. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56, 1919– 1925. American Public Health Association, American Water Works Association, Water Environment Federation, 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. Chandran, K., Hu, Z., Smets, B.F., 2008. A critical comparison of extant batch respirometric and substrate depletion assays for estimation of nitrification biokinetics. Biotechnol. Bioeng. 101, 62–72. Coskuner, G., Ballinger, S.J., Davenport, R.J., Pickering, R.L., Solera, R.R., Head, I.M., Curtis, T.P., 2005. Agreement between theory and measurement in the quantification of ammonia oxidizing bacteria. Appl. Environ. Microbiol. 71, 6325–6334. Dionisi, H.M., Layton, A.C., Harms, G., Gregory, I.R., Robinson, K.G., Sayler, G.S., 2002. Quantification of Nitrosomonas oligotropha-like ammonia-oxidizing bacteria and Nitrosospira spp. from full-scale wastewater treatment plants by competitive PCR. Appl. Environ. Microbiol. 68, 245–253. Duan, L., Moreno-Andrade, I., Huang, C., Xia, S., Hermanowicz, S.W., 2009. Effects of short solids retention time on microbial community in a membrane bioreactor. Bioresour. Technol. 100, 3489–3496. Ducey, T.F., Vanotti, M.B., Shriner, A.D., Szogi, A.A., Ellison, A.Q., 2010. Characterization of a microbial community capable of nitrification at cold temperature. Bioresour. Technol. 101, 491–500. Gieseke, A., Purkhold, U., Wagner, M., Amann, R., Schramm, A., 2001. Community structure and activity dynamics of nitrifying bacteria in a phosphate-removing biofilm. Appl. Environ. Microbiol. 67, 1351–1362. Gotvajn, A.Zˇ., Zagorc-Koncˇan, J., 2009. Identification of inhibitory effects of industrial effluents on nitrification. Water Sci. Technol. 59, 797–803.
Guindon, S., Gascuel, O., 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52, 696–704. Hesselmann, R.P.X., Werlen, C., Hahn, D., van der Meer, J.R., Zehnder, A.J.B., 1999. Enrichment, phylogenetic analysis and detection of a bacterium that performs enhanced biological phosphate removal in activated sludge. Syst. Appl. Microbiol. 22, 454. Hiorns, W.D., Hastings, R.C., Head, I.M., McCarthy, A.J., Saunders, J.R., Pickup, R.W., Hall, G.H., 1995. Amplification of 16S ribosomal RNA genes of autotrophic ammonia-oxidizing bacteria demonstrates the ubiquity of nitrosospiras in the environment. Microbiology 141, 2793–2800. Horz, H.-P., Rotthauwe, J.-H., Lukow, T., Liesack, W., 2000. Identification of major subgroups of ammonia-oxidizing bacteria in environmental samples by T-RFLP analysis of amoA PCR products. J. Microbiol. Methods 39, 197–204. Jones, R.D., Hood, M.A., 1980. Interaction between an ammonium-oxidizer, Nitrosomonas sp., and two heterotrophic bacteria, Nocardia atlantica and Pseudomonas sp.: a note. Microbiol. Ecol. 6, 271–275. Juretschko, S., Timmermann, G., Schmid, M., Schleifer, K.-H., Pommerening-Röser, A., Koops, H.-P., Wagner, M., 1998. Combined molecular and conventional analyses of nitrifying bacterium diversity in activated sludge: Nitrosococcus mobilis and Nitrospira-like bacteria as dominant populations. Appl. Environ. Microbiol. 64, 3042–3051. Kindaichi, T., Ito, T., Okabe, S., 2004. Ecophysiological interaction between nitrifying bacteria and heterotrophic bacteria in autotrophic nitrifying biofilms as determined by microautoradiography-fluorescence in situ hybridization. Appl. Environ. Microbiol. 70, 1641–1650. Koops, H.-P., Pommering-Röser, A., 2001. Distribution and ecophysiology of the nitrifying bacteria emphasizing cultured species. FEMS Microbiol. Ecol. 37, 1–9. Manz, W., Amann, R., Ludwig, W., Wagner, M., Schleifer, K.-H., 1992. Phylogenetic oligonucleotide probes for the major subclasses of Proteobacteria: problems and solutions. Syst. Appl. Microbiol. 15, 593–600. Michaud, L., Blancheton, J.P., Bruni, V., Piedrahita, R., 2006. Effect of particulate organic carbon on heterotrophic bacterial populations and nitrification efficiency in biological filters. Aquaculture Eng. 34, 224–233. Mobarry, B.K., Wagner, M., Urbain, V., Rittmann, B.E., Stahl, D.A., 1996. Phylogenetic probes for analyzing abundance and spatial organization of nitrifying bacteria. Appl. Environ. Microbiol. 62, 2156–2162. Nikolausz, M., Kappelmeyer, U., Székely, A., Rusznyák, A., Márialigeti, K., Kästner, M., 2008. Diurnal redox fluctuation and microbial activity in the rhizosphere of wetland plants. Eur. J. Soil Biol. 44, 324–333. Nogueira, R., Melo, L.F., Purkhold, U., Wuertz, S., Wagner, M., 2002. Nitrifying and heterotrophic population dynamics in biofilm reactor: effects of hydraulic retention time and presence of organic carbon. Water Res. 36, 469–481. Okabe, S., Kindaichi, T., Ito, T., 2005. Fate of 14C-labeled microbial products derived from nitrifying bacteria in autotrophic nitrifying biofilms. Appl. Environ. Microbiol. 71, 3987–3994. Ouverney, C.C., Fuhrman, J.A., 2000. Marine planktonic archaea take up amino acids. Appl. Environ. Microbiol. 69, 3626–3635. Park, H.-D., Noguera, D.R., 2004. Evaluating the effect of dissolved oxygen on ammonia-oxidizing bacterial communities in activated sludge. Water Res. 38, 3275–3286. Park, H.-D., Regan, J.M., Noguera, D.R., 2002. Molecular analysis of ammoniaoxidizing bacterial populations in aerated-anoxic Orbal processes. Water Sci. Technol. 46, 273–280. Purkhold, U., Pommerening-Röser, A., Juretschko, S., Schmid, M.C., Koops, H.-P., Wagner, M., 2000. Phylogeny of all recognized species of ammonia oxidizers based on comparative 16S rRNA and amoA sequence analysis: implications for molecular diversity surveys. Appl. Environ. Microbiol. 66, 5368–5382. Racz, L., Datta, T., Goel, R.K., 2010. Organic carbon effect on nitrifying bacteria in a mixed culture. Water Sci. Technol., in press. Rene, E.R., Kim, S.J., Park, H.S., 2008. Effect of COD/N ratio and salinity on the performance of sequencing batch reactors. Bioresour. Technol. 99, 839–846. Rongsayamanont, C., Limpiyakorn, T., Law, B., Khan, E., 2010. Relationship between respirometric activity and community of entrapped nitrifying bacteria: implications for partial nitrification. Enzyme Microb. Technol. 46, 229–236. Shuler, M.L., Kargi, F., 2002. Bioprocess Engineering: Basic Concepts, second ed. Prentice Hall, New Jersey. Tam, N.F.Y., Wong, Y.S., Leung, G., 1992. Effect of exogenous carbon sources on removal of inorganic nutrient by the nitrification-denitrification process. Water Res. 26, 1229–1236. Thompson, J.D., Gibson, T.J., Plewniak, F., Jeanmougin, F., Higgins, D.G., 1997. The ClustalX windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 25, 4876–4882. van Haandel, A., van der Lubbe, J., 2007. Handbook Biological Waste Water Treatment: Design and Optimization of Activated Sludge Systems. Quist Publishing, Leidschendam, The Netherlands. Wagner, M., Noguera, D.R., Juretschko, S., Rath, G., Koops, H.-P., Schleifer, K.-H., 1998. Combining fluorescent in situ hybridization (FISH) with cultivation and mathematical modeling to study population structure and function of ammonia-oxidizing bacteria in activated sludge. Water Sci. Technol. 37, 441– 449. Wittebolle, L., Verstraete, W., Boon, N., 2009. The inoculum effect on the ammoniaoxidizing bacterial communities in parallel sequential batch reactors. Water Res. 43, 4149–4158.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Effect of organic carbon on ammonia oxidizing bacteria in a mixed culture LeeAnn Racz, Tania Datta, Ramesh Goel * Department of Civil and Environmental Engineering, University of Utah, Suite 104, 122 S. Central Campus Drive, Salt Lake City, UT 84112-0610, USA
a r t i c l e
i n f o
Article history: Received 3 December 2009 Received in revised form 1 March 2010 Accepted 11 March 2010 Available online 3 April 2010 Keywords: Nitrification Monod kinetics Microbial ecology Cloning and sequencing Fluorescent in situ hybridization
a b s t r a c t This study examined the effect of organic carbon (peptone vs. glucose) on two sequencing batch reactors performing simultaneous carbon oxidation and nitrification. Although each reactor had similar COD oxidation kinetics (0.029 and 0.036 mg COD mg VSS1 h1), the Monod nitrification kinetics for the peptonefed reactor (lm = 2.72 h1, Ks = 17.8 mg N L1) were faster than for the glucose-fed reactor (lm = 0.868 h1, Ks = 26.5 mg L1). The overall bacterial communities were profiled by 16S rRNA cloning and sequencing and revealed homology with a greater variety of bacteria from the peptone-fed reactor than the glucose-fed reactor. In addition, amoA cloning and sequencing, terminal restriction fragment length polymorphism, and fluorescent in situ hybridization experiments indicated greater AOB diversity and abundance in the peptone-fed reactor. This research provides evidence that the organic carbon source affects the make-up of the heterotroph community as well as AOB in mixed cultures. Published by Elsevier Ltd.
1. Introduction The activated sludge process is widely used around the globe to treat municipal wastewater. This treatment technique is mature, and its engineering and microbiology are well understood. Our firm understanding of the activated sludge process enables us to configure treatment plants to remove organic pollutants, nitrogenous compounds and phosphorus from municipal wastewater. While there are many contaminants removed from municipal wastewater, ammonia nitrogen (NH3–N) is of particular concern as their release to surface waters is directly related to eutrophication, a mechanism through which surface waters undergo excess algae growth. Nitrification is a two-step process which biologically removes NH3–N in the activated sludge processes. Ammonia oxidizing bacteria (AOB) oxidize NH3–N to nitrite nitrogen (NO2–N) in the first step. In the second step, nitrite oxidizing bacteria (NOB) oxidize NO2–N to nitrate nitrogen (NO3–N). Even though AOB require inorganic carbon for growth, AOB are quite diverse among wastewater treatment plants. For instance, Wagner et al. (1998) reported a strong presence of Nitrosococcus mobilis, which phylogenetically belongs to the genus Nitrosomonas (Koops and Pommering-Röser, 2001), when studying an industrial wastewater treatment plant with high ammonia concentrations. Conversely, Hiorns et al. (1995) noted a prevalence of AOB related to Nitrosospira in activated sludge systems. Dionisi et al. (2002) similarly concluded the dominant AOB in their activated sludge system was Nitrosomonas oligotropha. Other studies reported that * Corresponding author. Tel.: +1 315 801 5816110; fax: +1 315 801 585 5477. E-mail address: [email protected] (R. Goel). 0960-8524/$ - see front matter Published by Elsevier Ltd. doi:10.1016/j.biortech.2010.03.058
Nitrosospira-related AOB were seldom detected in wastewater treatment plants and Nitrosomonas AOB were most common (Mobarry et al., 1996; Purkhold et al., 2000). Park and Noguera (2004) explained that the type of wastewater as well as operational parameters influence AOB community profiles. AOB commonly coexist with heterotrophs in full-scale activated sludge systems. Temperature (Ducey et al., 2010), solid retention time (Duan et al., 2009), high carbon-to-nitrogen (C/N) ratios and salinity (Rene et al., 2008), low dissolved oxygen concentrations (Rongsayamanont et al., 2010), and inhibitory compounds (Gotvajn and Zagorc-Koncˇan, 2009) affect AOB communities and metabolism. Several researchers have also studied the interaction between nitrifying and heterotrophic bacteria. Jones and Hood (1980) observed that Nitrosomonas spp. increased ammonium oxidation by 150% when grown in the presence of heterotrophs. More recently, Michaud et al. (2006) examined the effect of particulate organic carbon on heterotrophic bacterial populations and nitrification efficiency in biological filters. Also, Okabe et al. (2005) confirmed that in complex multispecies biofilms, including nitrifying communities, exchange of substrates among different phylogenetic groups is the most important ecophysiological interaction. Wittebolle et al. (2009) reported that the source of inoculum will affect the AOB community profile but not necessarily the nitrification functionality. Wastewater treatment plants have combined carbon oxidation and nitrification in the same reactor since the 1970s, although heterotrophs compete with nitrifying bacteria for oxygen and space, particularly in biofilms (Nogueira et al., 2002). Heterotrophs gain their energy primarily from organic carbon sources. On the other hand, nitrifying bacteria are autotrophic organisms which grow on inorganic carbon. The composition of inorganic
L. Racz et al. / Bioresource Technology 101 (2010) 6454–6460
carbon, which primarily exists in form of carbonates and bicarbonates in municipal wastewaters, does not change much. However, variations in organic carbon composition in municipal wastewater lead to wide variations in heterotrophic microbial ecology, both in time and space. We point out that the ecologies of AOB, and possibly NOB, differ despite the fact that these organisms primarily feed on inorganic carbon sources. Therefore, it is possible that there is some symbiotic relationship between heterotrophs and AOB although both of these feed on different carbon sources. The objective of this research was to evaluate the effect of organic carbon sources on the AOB community. Two identical sequencing batch reactors with nitrifying activated sludge were fed with two different carbon sources: one with peptone and sodium acetate and the other with glucose and sodium acetate. Our earlier work (Racz et al., 2010) used molecular fingerprinting techniques to characterize the microbial ecologies of the two reactors. In that research, automatic ribosomal intergenic spacer analysis (ARISA) indicated a more diverse overall bacterial community in the peptone-fed reactor than the glucose-fed reactor. This research, however, provides a fine-scale profile of the heterotroph and AOB microbial ecologies in the two reactors using cloning and sequencing. Furthermore, this study includes examination of the performance kinetics which revealed additional differences between the two reactors. To the best of our knowledge, no other studies have examined the effect of organic carbon sources, and in turn a heterotrophic population, on an AOB community. We hypothesize that in a mixed culture of heterotrophs and AOB, the more complex the organic carbon source will lead to a more diverse heterotrophic and, in turn, the more diverse the AOB community.
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ganic carbon with amino acids, an important source of carbon, nitrogen and energy for heterotrophic bacteria in aquatic environments (Ouverney and Fuhrman, 2000). Therefore, peptone was added as well. Feed A contained (per liter) 44.6 g NaHCO3 and the composition of feed B was (per liter) 6 g peptone, 1.25 g sodium acetate, 2.26 g NH4Cl, 6.86 g MgCl26H2O, 1.72 g CaCl22H2O, 0.6675 g KH2PO4 and 20 mL of a trace element solution. The trace element solution, adapted from Hesselmann et al. (1999), consisted of the following per liter of deionized water: 5.46 g citric acid, 4.0 g hippuric acid, 0.72 g Na3NTA2H2O, 0.3 g Na3EDTA4H2O, 3.0 g FeCl36H2O, 0.5 g H3BO3, 0.3 g ZnSO47H2O, 0.24 g MnCl24H2O, 0.14 g CuSO45H2O, 0.06 g KI, 0.06 g Na2MoO42H2O, 0.06 g CoCl26H2O, 0.06 g NiCl26H2O and 0.06 g Na2WO42H2O. To evaluate the effect of carbon source on the microbial community, a second sequencing batch reactor was initiated with the mixed liquor from the first reactor which was fed with peptone and acetate. The operation of this second reactor was identical to the first one except that the peptone in the feed was gradually replaced with glucose over a period of three weeks as an effort to change the organic carbon source in the feed. Glucose was chosen as it is a simple sugar and, like peptone, is easily metabolizable. The final concentration of glucose in feed B was 5.38 g L1, which maintained a constant COD concentration in the reactor influent. Since peptone contains organic nitrogen in the form of amino acids and peptides, another experiment was conducted to determine the contribution of NH3–N from hydrolyzed peptone. In this experiment, peptone was dissolved in filtered (0.2 lm) effluent from the peptone-fed reactor proportional to the amount fed to the SBR. Concentrations of NH3–N, NO3–N, and NO2–N were measured at the beginning and after 24 h of the effluent being placed on an orbital shaker.
2. Methods 2.2. DNA extraction, PCR, TRFLP, cloning and sequencing 2.1. Reactor operation The reactors were operated as described previously (Racz et al., 2010). Specifically, an initial 2.0 L sequencing batch reactor was operated to achieve simultaneous COD and nitrification removals. The reactor was operated on a 12 h cycle (total two cycles per day) consisting of two stages. The first stage was an 11.5 h aerobic period that started with the rapid addition of the synthetic wastewater and air. During this stage, the mixed liquor was maintained at 4–5 mg L1 DO concentration by purging air using an aquarium pump. The second stage consisted of 30 min of settling and decanting. The pH in the reactors was maintained at 7.2 ± 0.3 by adding acid or base using a pH controller (Cole-Parmer Instrument Company, Vernon Hills, Illinois). All pumps associated with the reactor system were automated using electronic timers (Cole-Palmer). The reactor was seeded with mixed liquor from a local wastewater treatment plant. A total volume of 670 ml was decanted at the end of the settling period in each cycle and substituted with the synthetic wastewater at the beginning of the next cycle, providing a hydraulic retention time of 36 h. The solid retention time in the reactor was maintained at 20 days by wasting the mixed liquor from the reactor on daily basis. To simulate the desired strength of synthetic wastewater, two pre-autoclaved concentrated solutions (feed A and B) were mixed with the deionized water directly in the reactor reservoir. During the feeding step, the reactors received 624 ml of deionized water, 8 ml of feed A and 38 ml of feed B. Municipal wastewater contains a complex mixture of organic compounds, including volatile fatty acids. Since polysaccharide and protein fermentation forms acetate, a common substrate in wastewater treatment systems (Kindaichi et al., 2004) which is readily metabolizable by heterotrophs (Tam et al., 1992), sodium acetate was added to simulate the volatile fatty acids present in municipal wastewater. Peptone is a complex source of or-
Genomic DNA was extracted from biomass samples collected from the reactors using a soil DNA extraction kit (MoBio Labs, Solana Beach, CA). TRFLP was performed using the modified protocol developed by Park and Noguera (2004). Briefly, labeled forward (amoA-1F) and reverse (amoA-2R) primers were used to amplify the amoA gene (Park and Noguera, 2004). The forward primer was labeled with the fluorophore HEX, and the reverse primer was labeled with 6FAM. Amplification was done on a master gradient thermocycler (Eppendorf) with the following temperature cycle: denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 1 min, annealing at 56 °C for 1.5 min, and elongation at 72 °C for 1.5 min, with polishing steps at 60 °C for 1.5 min and 72 °C for 10 min. PCR products were run on 1% agarose gel for 40 min against a standard DNA Ladder (Promega) to verify the length. The products were then purified from the gel using the QIAQuick PCR purification kit (Qiagen Inc., Valencia, CA). The purified PCR products were digested with TaqI restriction endonuclease (MBI Fermentas, Hanover, MD). Aliquots (2 lL) of digested PCR products were mixed with 1 lL of ROX-labeled GENEFLOt 625 internal length standard (CHIMERx, Milwaukee, WI) and 20 lL of formamide. Samples were processed through an Applied Biosystems 3130xl Genetic Analyzer capillary electrophoresis instrument (Applied Biosystems, Foster City, CA) at the University of Utah Core Facility and analyzed using the GeneMapper software (Applied Biosystems, Foster City, CA) version 2.6. The resulting fragment lengths were compared with known fragment lengths of AOB to identify presence of specific AOB (Park and Noguera, 2004; Park et al., 2002; Horz et al., 2000). To obtain the information on all ammonia oxidizers at a finer scale using cloning and sequencing, the amoA gene fragment was amplified using the same protocol that was used in TRFLP except
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Table 1 Probes used for FISH. Target organism Most bacteria
Probe name EUB338
Betaproteobacterial AOB
Nso1225
Nitrosomonas oligotropha
Nmo218
Nitrosomonas europaea
Nse1472
Sequence 0
5 -GCT GCC TCC CGT AGG AGT30 50 -CGC CAT TGT ATT ACG TGT GA-30 50 -CGG CCG CTC CAA AAG CAT-30 50 -ACC CCA GTC ATG ACC CC-30
Formamide (%)
Reference
0–50
Amann et al. (1990b) Mobarry et al. (1996) Gieseke et al. (2001) Juretschko et al. (1998)
35
35
50
Concentrations of NH3–N, NO3–N, NO 2 , and COD in the influent and effluent were periodically measured using Hach methods 10,031, 10,020, 8153, and 8000, respectively. Total suspended solids (TSS) and volatile suspended solids (VSS) were measured using standard methods (APHA, AWWA, WEF, 1998). All measurements were made in duplicate. Monod kinetics parameters for nitrification were estimated using the substrate depletion method described by Shuler and Kargi (2002). The Monod equation is expressed as:
80
(a)
100 NH3-N
60
NO2-N
80
NO3-N Total N COD
40
60
40 20
COD concentration (mg/L)
FISH was performed as detailed in Manz et al. (1992). Biomass from both reactors was washed twice in PBS and fixed in 4% (v/ v) paraformaldehyde solution as described previously (Amann et al., 1990a; Coskuner et al., 2005). Following fixation, the cells were washed again and resuspended in 1 mL of hybridization buffer and 37.5 lL of probe solution (12.5 lM). Table 1 lists the probes used and the corresponding target organisms. All probes were labeled with Cy5. The biomass was allowed to hybridize at 46 °C for 12–16 h at which time the biomass was washed in wash buffer and washed twice again in PBS. The biomass was resuspended in 1 mL PBS with 0.5% TWEEN 20 at 4 °C. The cells were quantified
2.4. Other analytical methods
20
0
0 0
80
2
4
6 Time (hours)
8
(b)
10
NH3-N NO2-N NO3-N Total N COD
60
100
80
60 40 40 20
COD concentration (mg/L)
2.3. Fluorescent in situ hybridization (FISH)
on a CANTO II flow cytometry instrument. Percentages of each target organism were calculated relative to all bacteria (EUB338), and percentages of N. oligotropha (Nmo218) and Nitrosomonas europaea (Nse1472) were calculated relative to all Betaproteobacterial AOB (Nso1225). Negative controls were obtained by quantifying unlabeled biomass. FISH was similarly performed on slides. However, Nse1472 was labeled with Cy5 and Nmo218 was labeled with Cy3. As Nse1472 required a higher stringency (50% formamide) than Nmo218 (35% formamide), Nse1472 was hybridized first. Following hybridization with both probes, the samples were stained with 40 ,60 -diamidino2-phenylindole (DAPI) (1 lg ml1) for 5 min in the dark to visualize all cells. The slides were then washed with 4 °C DI water and allowed to air dry. The cells were viewed using a fluorescence microscope (Olympus BX51) equipped with a halogen lamp and camera (Olympus DP71).
N concentration (mg/L)
that the primers were not labeled. Cloning and sequencing was similarly performed to profile the overall microbial community by amplifying the 16S rRNA fragment. The 16S rRNA fragment was targeted using the primers 8f (50 -AGAGTTTGATCMTGGCTCAG-30 ) and 1492r (50 -GGYTACCTTGTTACGACTT-30 ) and the following temperature cycle: initial denaturation at 94 °C for 3 min, followed by 30 cycles of denaturation at 94 °C for 1 min, annealing at 55 °C for 45 s, and elongation at 72 °C for 2 min, with a final elongation at 72 °C for 2 min. PCR products were run on 1% agarose gel for 40 min against a standard DNA Ladder (Promega) to verify the length and then purified. For cloning, the purified PCR products were ligated to a pCRÒ4-TOPOÒ (Invitrogen, CA) kanamycin resistant vector or plasmids, and the recombinant plasmid was then transformed to chemically competent Escherichia coli cells. After allowing a transformation time of 60 min, the cells were spread on a growth media containing agar, LB broth and 50 lg mL1 kanamycin in order to grow colonies. Distinct clones from the LB plate containing kanamycin were selectively picked and were subjected to further screening for appropriate inserts by growing them in the same LB growth medium containing 50 lg mL1 kanamycin. Plasmid DNA was extracted using the Wizard Plus Miniprep DNA purification system (Promega, WI). To verify the presence of inserts in the purified plasmids, extracted plasmid DNA were run on 1% agarose gel. To conduct sequencing, 1 ll of the plasmid DNA was used as template for cycle sequencing using a Big Dye sequencing kit (Applied Biosystems, Foster City, CA) and using the forward primer (amoA1f or 8f) on an ABI PRISM 377 automated DNA sequencer (Applied Biosystems, USA). The ClustalX software (Thompson et al., 1997) version 1.81 was used to align sequences of the recovered clones with other published sequences. PhyML 3.0 (Guindon and Gascuel, 2003) was used to construct phylogenetic trees using the maximum likelihood method, and bootstrap values were based on 100 trials. TreeView software (Page 1996) version 1.6.6 was used to view the phylogenetic trees.
N concentration (mg/L)
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20
0
0 0
2
4
6 Time (hours)
8
10
Fig. 1. Performance kinetics of (a) peptone-fed reactor 1 and (b) glucose-fed reactor 2.
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l¼
lm S Ks þ S
where l is the specific growth rate, lm is the maximum specific growth rate, S is the substrate concentration, and Ks is the saturation constant equal to the concentration of the substrate when l = ½ lm.
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3. Results and discussion 3.1. Reactor performance Fig. 1 illustrates the COD oxidation and nitrification kinetics for both reactors over a typical cycle. The values presented are the aver-
Fig. 2. (a) TRFLP plot for reactor 1 prior to feed transition. (b) TRFLP plot for reactor 2, day 2 after feed transition. (c) TRFLP plot for reactor 2, 13 days after feed transition (d) TRFLP plot for reactor 2, 134 days after feed transition. The black and grey peaks indicate forward and reverse terminal fragments, respectively. Reproduced with permission from Water Science and Technology (Racz et al., 2010) with permission from the copyright holders, IWA Publishing.
Fig. 3. Phylogenetic tree for the amoA gene in reactors 1 and 2. The clones within each shaded box share at least 99% homology with each other.
L. Racz et al. / Bioresource Technology 101 (2010) 6454–6460
ages of duplicate measurements. Similar reactor performances were observed during the operation of both reactors as depicted in Fig. 1. Each reactor had similar first-order COD oxidation kinetics, with the degradation rate constants of 0.029 and 0.036 mg COD mg VSS1 h1 for reactors 1 and 2, respectively. These results align with Duan et al. (2009) in which a mixed culture operating at various solids retention times resulted in different heterotrophic communities but similar COD oxidation performances. However, the nitrification kinetics for reactor 1 were considerably faster than for reactor 2. The maximum growth rate coefficient (lm) for reactor 1 was 2.72 h1, whereas it was only 0.868 h1 for reactor 2. The half-saturation coefficient (Ks) was 17.8 mg N L1 for reactor 1 and 26.4 mg N L1 for reactor 2. These values are comparable with other nitrifying cultures (Chandran et al., 2008; van Haandel and van der Lubbe, 2007). Although the nitrification kinetics for each reactor were markedly different, the effluent NH3–N concentrations from each reactor at the end of each cycle were similar. The average concentrations of NH3–N and COD in the effluents from both reactors over a period of 83 days were 0.531 ± 1.48 mg L1 and 3.83 ± 4.76 mg L1, respectively. These effluent concentrations equated to 98.1 ± 1.84% COD and 97.3 ± 6.69% NH3–N removals in reactor 1 and 99.1 ± 1.29% COD and 99.4 ± 0.76% NH3–N removals in reactor 2. NO2–N was not present in the effluent from both reactors, thus indicating the completion of second stage of nitrification. The NO3–N concentration in the effluent from the glucose-fed reactor 2 was 26.5 mg L1, which was nearly equivalent to the influent NH3–N concentration in reactor. However, the average NO3–N in the effluent of the peptone-fed reactor 1 was 72.2 ± 6.57 mg L1. In the separate experiment in which peptone was dissolved in the effluent of the peptone-fed reactor, we observed an increase of ammonia but no increase of nitrate or nitrite. Since there are limited pathways of nitrate production through metabolic pathways other than through nitrification, the increased NO3–N in the peptone-fed reactor can be attributed to oxidation of organic nitrogen to inorganic ammonia which led to more nitrate production by nitrifiers. The average TSS and VSS concentrations in reactor 1 were 2707 ± 309 and 2484 ± 429 mg L1, respectively and the corresponding concentrations in reactor 2 were 1830 ± 184 and 1597 ± 157 mg L1, respectively.
PCR amplification and lack of adequate controls (Park and Noguera, 2004).
18 Reactor 1 Reactor 2
16 Percentage of bacteria in reactor
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14 12 10 8 6 4 2 0
Nse1472 Nso1225 Nmo218 (Betaproteobacterial AOB) (N. oligotropha) (N. europaea)
Fig. 4. Percentages of AOB relative to all bacteria in each reactor.
3.2. Response of AOB community against changes in organic carbon source 3.2.1. TRFLP TRFLP was performed on the mixed liquor from reactor 1 when it was at steady state and the same procedure was performed on reactor 2 during the transition period when peptone was slowly replaced by glucose in the reactor 2. The profiles are shown in Fig. 2. Panel (a) in Fig. 2 shows the TRFLP profile for reactor 1 at steady state. According to the TRFLP profiles, the main AOB present in reactor 1 were represented by fragments 48/441, 48/206, 354/ 135, 219/135 and 219/270. Likewise, the AOB population in reactor 2 at steady state (after 134 days) was represented by fragments 354/135, 219/135 and 219/270, which were the same as some of the terminal fragments in reactor 1. In addition, a new terminal fragment with size 441/57 was also noticed in the reactor 2. The terminal fragments 219/135 and 219/270 mostly represent N. europaea lineage (Park and Noguera, 2004). Fragment length 48/ 441 is characteristic of the N. oligotropha lineage. Using results from Park and Noguera (2004), we find that the other two remaining fragment lengths (48/206, 354/135) may belong to different strains within N. oligotropha lineage. The TRFLP results suggest that N. europaea was abundant in the peptone-fed reactor whereas a new lineage of the genus Nitrosomonas with terminal fragment length of 419/57 along with N. europaea dominated the glucosefed reactor. However, we note that the TRFLP tool alone is not quantitative, as quantification is hampered by inherent biases in
Fig. 5. FISH image of biomass from (a) reactor 1 and (b) reactor 2. All cells were stained in DAPI (blue), N. oligotropha (Nmo218, Cy3) is colored magenta and N. europaea (Nse1472, Cy5) is colored green.
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3.2.2. Identification of AOBs using cloning and sequencing To obtain a finer scale resolution in AOB community present in both reactors, amoA gene based cloning and sequencing was performed on the genomic DNA obtained from both reactors. The phylogenetic comparison of recovered amoA sequences from both reactors and other relevant sequences from publicly available databases is depicted in Fig. 3. Forty-eight clones were recovered from each reactor and were divided into operational taxonomic units (OTUs) based on 99% or more sequence homology among them. Most of the clones (30 out of 40) from the peptone-fed reactor 1 were closely associated with an uncultured Nitrosomonadaceae bacterium in the N. oligotropha lineage. This uncultured bacterium was recovered from the rhizosphere of a laboratory-scale planted fixed-bed reactor which simulated a constructed wetland system undergoing a diurnal redox potential variation (Nikolausz et al., 2008). The bacteria in the rhizosphere of such a constructed wetland receive amino acids, sugars, and organic acids through the roots. Therefore, there is an active environment with complex substrates for the bacterial community. Peptone, which was the primary feed to reactor 1, is also a complex organic substrate. Hence, it is entirely justifiable that most of AOB clones recovered from reactor 1 showed similarity with the uncultured Nitrosomonadaceae bacterium recovered from the constructed wetland rhizosphere. Most of the clones form the glucose-fed reactor 2 had more than 99% sequence similarity with another uncultured bacterium recovered from a laboratory-scale reactor operated under low dissolved oxygen conditions (Park and Noguera, 2004) in the N. oligotropha lineage. Five AOB clones from each reactor had greater than 99% homology with a clone identified as uncultured bacterium clone Marshall-77 W (NCBI Accession number AY356431, Park and
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Noguera, 2004). This clone was identified in a study examining the effect of dissolved oxygen on AOBs (Park and Noguera, 2004), and was classified as belonging to the N. europaea lineage (81.4% homology). TRFLP analysis on the peptone-fed reactor showed that although ammonia oxidizers most closely related to N. oligotropha lineage were also present, AOB related to N. europaea were abundant in this reactor. However, most of the clones form this reactor matched an uncultured Nitrosomonadaceae bacterium in the N. oligotropha lineage. This shows that TRFLP analysis underestimated the presence of N. oligotropha lineage in the peptone-fed reactor. Nevertheless, quantification with FISH identified the relative abundance of AOB in the reactors. 3.2.3. FISH Percentages of all Betaproteobacterial AOB, N. oligotropha and N. europaea were quantified using flow cytometry assisted FISH relative to the percentages of all bacteria as illustrated in Fig. 4. In the peptone-fed reactor 1, 16.1% of all bacteria were Betaproteobacterial AOB, 13.7% were N. oligotropha, and 2.12% were N. europaea. In the glucose-fed reactor 2, 3.58% of all bacteria were Betaproteobacterial AOB, 3.37% were N. oligotropha, and 0.41% were N. europaea. These results agree with the cloning and sequencing results in that nearly all of the AOB were N. oligotropha in both reactors. While both reactors contained some amount of N. europaea, the relative proportion of this species was greater in the peptone-fed reactor than in the glucose-fed reactor. In addition, the greater proportion of AOB in reactor 1 than reactor 2 provides a possible explanation as to the faster nitrification kinetics in reactor 1 when compared with reactor 2. Fig. 5 provides FISH images of each reactor’s biomass on slides hybridized with Nmo218 (N. oligotropha) and Nse1472 (N. euro-
Fig. 6. Phylogenetic tree for the 16S rRNA gene in reactors 1 and 2. The clones within each shaded box share at least 99% homology with each other.
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paea) and stained with DAPI. This image supports the flow cytometry results in that in each reactor N. oligotropha was abundant while there was scant N. europaea. The images also illustrate the greater percentage of AOB in reactor 1 than reactor 2. 3.3. Ecology of heterotrophic bacteria The phylogram presented in Fig. 6 shows the distribution of clones retrieved from the peptone-fed and glucose-fed reactors along with other sequences taken from other studies. Clones from the peptone-fed reactor were mostly represented by Betaproteobacteria, Acidobacteria, Sphingobacteria crenotrichaceae and Sphingobacteria saprospiraceae families. On the other hand, clones from the glucose-fed reactor were mostly represented by Alphaproteobacteria, Sphingobacteria flexibacteraceae and S. saprospiraceae families. Although both reactors shared some common bacterial ecology, different bacterial ecologies were also noticed in both reactors. For example, S. saprospiraceae was the most abundant family in the peptone-fed reactor based on the cloning results, yet this particular bacterial population was completely absent in the glucose-fed reactor. 4. Conclusions This study provides insight for heterotrophic bacteria and AOB interactions. The reactor receiving peptone had more diverse overall bacterial and AOB communities than the glucose-fed reactor. Although both reactors received the same inorganic carbon and shared similar species of AOB, the organic carbon source affected the composition of the bacterial strains. FISH experiments revealed that the peptone-fed reactor also had a greater proportion of AOB than the glucose-fed reactor. This increased proportion of AOB helps to explain the faster nitrification kinetics in the peptonefed reactor than the glucose-fed reactor, although both reactors shared similar COD oxidation kinetics. References Amann, R.I., Krumholz, L., Stahl, D.A., 1990a. Fluorescentoligonucleotide probing of whole cells for determinative, phylogenetic, and environmental studies in microbiology. J. Bacteriol. 172, 762–770. Amann, R.I., Binder, B.J., Olson, R.J., Chisholm, S.W., Devereux, R., Stahl, D.A., 1990b. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56, 1919– 1925. American Public Health Association, American Water Works Association, Water Environment Federation, 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. Chandran, K., Hu, Z., Smets, B.F., 2008. A critical comparison of extant batch respirometric and substrate depletion assays for estimation of nitrification biokinetics. Biotechnol. Bioeng. 101, 62–72. Coskuner, G., Ballinger, S.J., Davenport, R.J., Pickering, R.L., Solera, R.R., Head, I.M., Curtis, T.P., 2005. Agreement between theory and measurement in the quantification of ammonia oxidizing bacteria. Appl. Environ. Microbiol. 71, 6325–6334. Dionisi, H.M., Layton, A.C., Harms, G., Gregory, I.R., Robinson, K.G., Sayler, G.S., 2002. Quantification of Nitrosomonas oligotropha-like ammonia-oxidizing bacteria and Nitrosospira spp. from full-scale wastewater treatment plants by competitive PCR. Appl. Environ. Microbiol. 68, 245–253. Duan, L., Moreno-Andrade, I., Huang, C., Xia, S., Hermanowicz, S.W., 2009. Effects of short solids retention time on microbial community in a membrane bioreactor. Bioresour. Technol. 100, 3489–3496. Ducey, T.F., Vanotti, M.B., Shriner, A.D., Szogi, A.A., Ellison, A.Q., 2010. Characterization of a microbial community capable of nitrification at cold temperature. Bioresour. Technol. 101, 491–500. Gieseke, A., Purkhold, U., Wagner, M., Amann, R., Schramm, A., 2001. Community structure and activity dynamics of nitrifying bacteria in a phosphate-removing biofilm. Appl. Environ. Microbiol. 67, 1351–1362. Gotvajn, A.Zˇ., Zagorc-Koncˇan, J., 2009. Identification of inhibitory effects of industrial effluents on nitrification. Water Sci. Technol. 59, 797–803.
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