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Characterization of the microbial community of moving-bed
biofilm reactors operated under different COD/N ratio
J. P. Bassin*,**, B. Abbas*, R. Kleerebezem*, G. Muyzer*, A.S. Rosado***, M.C.M. van Loosdrecht* and
M. Dezotti**
* Delft University of Technology, Department of Biotechnology, Julianalaan 67, 2628 BC, Delft, The Netherlands
(E-mail: [email protected]; [email protected]; [email protected])
** Federal University of Rio de Janeiro, Chemical Engineering Program, Rio de Janeiro, Brazil (E-mail:
[email protected])
*** Federal University of Rio de Janeiro, Institute of Microbiology Prof. Paulo de Goés, Rio de Janeiro, Brazil (Email: [email protected])
Abstract
The goal of this research study was to investigate the effect of different wastewater composition in
the microbial diversity of three moving-bed biofilm reactors, which were operated either in
continuous or sequencing-batch mode. A comparison between the results obtained with different
molecular techniques is pointed out. The performance of each system in terms of nitrification
efficiency was linked to the microbial community analysis. Nitrifying bacteria population was
observed to be enhanced at low influent COD/N ratios as well at increasing nitrogen load.
Nitrospira was the dominant nitrite oxidizers in an autotrophic system, whereas Nitrobacter
dominated in reactors fed with organic matter.
Keywords
Microbial diversity, nitrification, COD/N, MBBR, PCR-DGGE, FISH.
INTRODUCTION
Chemolithoautotrophic nitrifying bacteria are substantially susceptible to inhibition by a wide range
of organic compounds (Pagga et al., 2006), high salinity concentrations (Moussa et al., 1996; Bassin
et al., 2011a), heavy metals (Hu et al., 2002) and also by high concentrations of ammonium and
nitrite (Anthonisen et al., 1976). One of the most critical parameters influencing the nitrifying
bacteria activity is the chemical oxygen demand/nitrogen (COD/N) ratio (Hanaki et al., 1990;
Cheng and Chen, 1994). High COD concentrations favour the development of heterotrophs, which
presents higher growth and biomass yields than autotrophic nitrifying bacteria and outcompete them
for oxygen and nutrients (Figueroa and Silverstein, 1992). As a consequence, the nitrification
efficiency tends to decrease considerably.
Due to the higher sensitivity of nitrifying bacteria to environmental conditions compared to
heterotrophs, they can be easily washed out from the conventional systems with dispersed biomass
when process instability occurs. This is especially relevant in full-scale wastewater treatment plants,
in which the operational conditions (wastewater composition, organic and nitrogen loading rate, pH,
temperature, dissolved oxygen concentration and sludge retention time) can be rather unstable. The
development of biofilm process opened new possibilities for the wastewater treatment sector.
Biofilm processes offer several advantages compared to the conventional systems such as less space
requirement and easy biosolid-liquid separation. Moving-bed biofilm systems are one of the
growing biofilm technologies applied for wastewater treatment. This process relies on the
attachment of biomass into plastic carriers, which allows retaining a significant amount of sludge in
the reactor and makes the design and the control of effluent clarification much easier (Ødegaard et
al., 2006). Several studies report the use of MBBR for the treatment of different wastewaters in labscale (Yu et al., 2007; Bassin et al., 2011a), pilot-scale (Shin et al., 2006) and full-scale (Johnson et
al., 2000) systems. However, few studies regarding the microbial community in moving-bed
systems are reported in literature (Tal et al., 2003). Moreover, they do not compare the microbial
population of different moving-bed biofilm systems submitted to different operating conditions,
such as diverse COD/N ratios, ammonium influent concentrations and feeding regimes (continuous
or sequencing-batch). Moreover, no complete characterization of microbial community (both
heterotrophic and autotrophic bacteria) is reported in the aforementioned studies. Therefore, the
goal of this study was to investigate the impact of different wastewater composition in the microbial
community of three moving-bed biofilm reactors, operated either continuously or in sequencingbatch regime. The comparison between the results observed with different techniques is pointed out.
The findings of this study provide an important insight about the relation between operating
conditions and microbial community composition in moving-bed systems.
MATERIALS AND METHODS
Experimental set-up and operating conditions
Three laboratory scale moving-bed biofilm reactors (MBBR) were operated in parallel. Two
reactors of 5L (R1 and R2) were operated continuously, while the other (7L-volume) was operated
in sequencing-batch regime (R3). Table 1 summarizes the experimental runs for all the reactors.
Table 1. Experimental conditions of the R1, R2 and R3 over the whole experiment.
System
MBBR1
(continuous
reactor)
MBBR2
(continuous
reactor)
SBBR
(sequencingbatch reactor)
Experimental
run
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Influent
COD
(mg/L)
0
0
0
0
0
400
200
100
0
400
400
200
0
0
0
Influent
NH4-N
(mg/L)
90 - 100
140 - 170
180 - 200
180 - 200
180 - 200
100 - 200
100 - 200
100 - 200
100 - 200
150 - 200
150 - 200
150 - 200
290 - 300
550 - 650
1200 - 1300
HRTa or
Cycle
timeb (h)
48a
48a
48a
36a
24a
24a
24a
24a
24a
56a/48b
28a/24b
28a/24b
28a/24b
28a/24b
28a/24b
Time of
operation (days)
103 (60)c
32
31
32
28
63 (30)c
26
21
23
39 (20)c
24
16
33
53
26
a
Hydraulic residence time: Continuous reactors (MBBR1 and MBBR2)
Cycle time: Sequencing batch reactor (SBBR)
c Start-up period for biofilm development during Run 1 (R1), Run 6 (R2) and Run 10 (R3)
b
A programmable logic controller (PLC) connected to a computer for data acquisition was used to
control the actuation of pumps and valves of R3, whose cycle time was either 48 or 24 h,
comprising the following phases: 3 min feeding, 47 h and 54 min aeration (for the 48h-cycle) or 23
h and 54 min aeration (for the 24h-cycle) and 3 min effluent withdrawal. No settling phase was
needed since the biomass was attached to the plastic carriers. All the reactors were filled with
plastic carriers (AMB®), which provided a specific area for biofilm growth of 500 m2/m3. The
amount of support material corresponded to a volume fraction of 40% (Vsupport/Vreactor). Porous
diffusers made of polypropylene were placed in the bottom of the reactors to provide both good
oxygen transfer into the liquid phase and proper circulation of the plastic carriers. The dissolved
oxygen (DO) concentration was kept around 6.5 – 7.0 mg/L for the continuously operated systems.
For the sequencing-batch biofilm reactor, DO varied along the operational cycle and according to
the experimental run from 2.0 to 7.0 mgO2/L. Temperature was kept at 24  3°C and pH was
maintained between 6.5 and 7.5 for all reactors by adding either 1M NaOH or 1M HCl. The reactors
were fed with synthetic medium which was prepared using inorganic (Campos et al., 1999) and
organic components (Holler and Trosch, 2001). Depending on the reactor and on the experimental
run, the medium composition was varied in order to obtain the desired influent COD and
ammonium concentrations. A trace elements solution (Vishniac and Santer, 1957) was added in a
proportion of 0.5 mL per liter of medium. R1 was inoculated with activated sludge from a lab-scale
sequencing-batch reactor running in autotrophic conditions for 2 months. During the whole
experimental period, R1 was only fed with a synthetic medium containing only inorganic
components. R2 was fed with synthetic medium containing both inorganic and organic components
and was inoculated with activated sludge from a municipal wastewater treatment plant (ETIG, Rio
de Janeiro, Brazil). The SBBR was inoculated with biomass that was detached from the carrier
materials of R1 and R2.
DNA extraction and PCR amplification
DNA was extracted from the samples collected in all MBBR systems in the end of each operational
run. Extraction was performed using the FastDNA® SPIN Kit (Qbiogene, Carlsbad, CA, USA),
following the manufacture’s recommendations. Around 10 ng of genomic DNA was used as
template for PCR amplification of the 16S rRNA gene, which was performed with universal
primers for the domain bacteria: BAC341F (containing a 40-bp GC-clamp) and BAC907RM
(M=A/C) (Schäefer and Muyzer, 2001). For amplification of the gene encoding ammonia
monooxygenase of ammonia-oxidizing bacteria (amoA gene), the primer set amoA-1F-GC and
amoA-2R (Hornek et al., 2006) was used. The thermal profiles for amplification of both genes can
be found elsewhere (Bassin et al., 2011b). PCR products of 16S rRNA and amoA genes were
quantified in a 1% (w/v) agarose gel.
Denaturing Gradient Gel Electrophoresis (DGGE)
DGGE was carried out in the Bio-Rad DCode System (Bio-Rad, Richmond, USA). Electrophoresis
was run in 1 mm thick gels, containing either 6% or 8% polyacrylamide for 16S RNA and amoA
genes PCR products, respectively. The denaturing gradients of the gels varied from 20 – 70% for
16S RNA fragments and from 10 – 50% for amoA fragments (100% denaturants is defined as 7 M
urea and 40% (v/v) deionized formamide). The DGGE procedure and image capture can be found
elsewhere (Bassin et al., 2011b).
Band isolation, sequencing and identification of microorganisms
Individual bands from DGGE gels of both 16S RNA and amoA genes were excised using sterile
razor blades, eluted in 1× Tris-HCl buffer and stored overnight at 4°C. The same PCR programs as
described previously were followed for the DNA re-amplification with non-GC-clamped primers, in
which a volume of 1 μL of the DNA eluted from the DGGE band was used as template. DNA
sequencing analysis was carried out by the commercial company Macrogen (South Korea). The
obtained 16S rRNA and amoA genes sequences were compared to sequences stored in GenBank
using
the
Basic
Local
Alignment
Search
Tool
(BLAST)
algorithm
(http://www.ncbi.nlm.nih.gov/blast). In a further step, the sequences were imported into the ARB
software (http://www.arb-home.de), aligned by using the ARB automatic aligner. The alignment
was further verified and corrected manually. Phylogenetic trees were generated by performing
neighbour-joining algorithm.
Fluorescent in situ hybridization (FISH)
Biomass samples removed from the carrier materials were collected in the end of each operational
phase for all reactors. Sample preparation, probes used, hybridization and visualization in
epifluorescence microscope can be seen elsewhere (Bassin et al., 2011b).
Analytical measurements
Ammonium, chemical oxygen demand (COD), total suspended solids (TSS) and volatile suspended
solids (VSS) were measured as proposed by Standard Methods (Apha, 1995). Nitrate and nitrite
were analysed by using an ion chromatography (Dionex ICS 90) and by an analytical kit (Hach
Co.), respectively.
RESULTS AND DISCUSSION
Long-term operation of the reactors: nitrification performance
R1 was always operated under autotrophic conditions, i.e., no organic carbon was added to the
synthetic medium. During the operation of R1, ammonium removal was kept around 100% in most
of the operation (Table 2). Since nitrification was the main process taking place in the biofilm,
nitrate was formed close to stoichiometric proportion the ammonium oxidized.
As indicated in Table 2, the lowest average ammonium removal efficiency in R2 was obtained in
run 6, when influent COD was the highest (400 mg/L). Nevertheless, the ammonium removal
efficiency achieved in the end of this respective phase was close to 100%. In the subsequent runs of
this reactor, ammonium was completed nitrified.
In R3, ammonium removal was always maintained above 95% from runs 10 to 13. However,
ammonium removal decreased to 60% when ammonium concentration was increased from 300 to
600 mgN/L in run 14. Further acclimation of biomass allowed recovering full ammonium removal.
Table 2. Ammonium removal and nitrogen conservation obtained in all experimental runs of R1, R2 and R3.
Reactor
R1
R2
R3
Experimental run
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Ammonium removal (%)
93
94
92
96
94
76
98
98
99
98
96
99
99
93
Microbial diversity through PCR-DGGE analysis of 16S rRNA fragments
The microbial community composition in the MBBR systems was accessed by PCR-DGGE
analysis. Figure 1 shows the DGGE fingerprints obtained in all experimental runs of R1, R2 and
R3. In total, 41 dominant bands were excised from the gel and sequenced. Some bands appearing at
the same height of the gel but retrieved in different reactors showed identical sequencing results.
Figure 2 illustrates a phylogenetic tree based on partial sequences of the 16S rRNA gene. The
microorganisms found belonged to several phylum, such as Proteobacteria (α-, ß- and γ-subclass),
Bacteroidetes, Chloroflexi, Firmicutes and Actinobacteria.
Figure 1. DGGE banding profile of microbial community of the moving-bed biofilm reactors along all the experimental
runs. The sequenced bands are numbered from up to down for each rector. Bands whose number is underlined already
appeared in a previous run (representing other reactor). The bands corresponding to ammonium-oxidizing bacteria
(AOB) are printed in red and the bands corresponding to nitrite-oxidizing bacteria (NOB) are printed in green.
Figure 2. Neighbour-joining tree of the sequences retrieved from the 16S rRNA gene DGGE analysis. Sequences
determined in this work are printed in bold. The bar indicates 10% sequence difference. The sequence of
Nitrosopumilus maritimus (Archaea) was used as an outgroup, but was pruned from the tree.
Characterization of microbial community in R1. In R1, most of the bands retrieved in run 1 were
also detected over the whole reactor operation (runs 1 - 5). Several nitrifying bacteria were found.
AOB were detected in band 11 (high sequence similarity Nitrosomonas marina) and band 27
(closely related to Nitrosomonas aestuarii). NOB were detected in bands 23 and 24, both belonging
to the Nitrospiraceae family and showing high similarity with Candidatus Nitrospira defluvii.
Although R1 was fed only with autotrophic medium without any organic carbon source, several
bands representing heterotrophic bacteria were retrieved from the DGGE gel: bands 1-10
(Bacteroidetes), Band 12 (Cyanobacteria), Bands 13, 14, 17 (Firmicutes), Band 15 (Chlorobiales),
Band 16 (γ-proteobacteria), Band 19, 21 and 22 (Actinobacteria), Bands 18 and 20 (ßproteobacteria). These organisms could possibly have grown on soluble products from nitrifying
bacteria. Chemolithoautotrophic nitrifiers fix and reduce inorganic carbon (e.g. CO2) for cell
synthesis (Brock and Madigan 1991), produce and release soluble organic products into solution
from substrate metabolism and decaying biomass (Rittman et al. 1994). Therefore, these bacteria
also interact with the exchange of organic materials. The coexistence of heterotrophic and
autotrophic autotrophs in a nitrifying biofilm fed synthetic media containing only with inorganic
components was also reported by Okabe et al. (1999). Active nitrifying bacteria were reported to
produce a continuous flow of organic substrates for the heterotrophs (Rittmann and Brunner, 1984).
Other works demonstrated the capability of Nitrobacter sp. and Nitrosomonas europaea to produce
soluble organic products that can be used by heterotrophic organisms. In the work carried out by
Moussa et al. (2005), it was shown that that the influent COD is responsible for around 40% of the
total formed heterotrophic biomass and biomass decay is related to 60% of the biomass produced.
These authors also mentioned that heterotrophic biomass can be sustained even at low input COD
(5 – 10 mg/L). Such low values of COD can be indirectly introduced to the system by the air used
for aeration or by organic impurities present in the feeding medium.
Focusing the analysis on the nitrifying bacteria, it was observed that the intensity of the bands
corresponding to AOB and NOB population tended to increase in the long-term operation of the
system. Apparently, the long exposition of the biomass to autotrophic conditions favoured the
development of nitrifying population. The enhancement of nitrifiers could also be related to the
higher growth yield of these organisms at increasing nitrogen loads applied to R1. The intensity of
band 11 (Nitrosomonas marina) appeared to increase from runs 1 and 5. The same trend was
observed for bands 24 (Candidatus Nitrospira defluvii) and 27 (Nitrosomonas aestuarii). Band 23
(also closely related to Candidatus Nitrospira defluvii) showed a high and invariable intensity
during the whole experiment, representing one of the main dominant bands of the bacterial
community fingerprint.
Characterization of microbial community in R2. The microbial community of R2 is quite different
from that of R1. First of all, R2 was inoculated with sludge collected in a municipal wastewater
treatment, whereas the inoculum of R1 consisted of biomass from a nitrifying lab-scale sequencingbatch reactor. Furthermore, the shifts in microbial population along run 6 – 9 are more pronounced
that that observed during operation of R1, probably as a response to the gradual decrease in influent
COD. Several of bands corresponding to the R2 microbial community profile (e.g., bands 1, 5, 6, 7,
8 , 10, 14, 19, 20, 22, 23, 24 and 27) were the same as those retrieved in the profile of R1. However,
new bands representing both heterotrophic and autotrophic nitrifying bacteria appeared in R2. The
new bands corresponding to the heterotrophic community were bands 28 (Bacteroidetes), 33–35 (ßproteobacteria) and 36 (α-proteobacteria). Autotrophic nitrifying bacteria were found in bands 29,
30 and 31 (closely related to Nitrosomonas aestuarii), and in band 32 (high sequence similarity with
Nitrobacter winogradskyi).
Regarding the changes in the population of nitrifying bacteria in R2, what is interesting to remark is
the enrichment for nitrifiers occurred when the organic load was reduced, fact evidenced by the
increase in the band intensity relative to both AOB and NOB. This is in line with the higher
ammonium removal efficiency at lower COD (Table 2). Both bands 23 and 24 (Candidatus
Nitrospira defluvii) had their intensity increased as influent COD was gradually decreased from run
6 to 9. The same trend is valid for bands 29–31 (Nitrosomonas aestuarii). The intensity of band 32
(Nitrobacter winogradskyi) remained practically the same over runs 6 – 9.
Characterization of microbial community in R3. The inoculation of R3 with biomass from the other
reactors (R1 and R2) implicated that bands retrieved in runs 10-14 of that reactor was similar to the
other systems: bands 1, 2, 6, 8, 10, 12, 13, 19, 21, 29, 30, 31, 35, 37, 38 and 40. Few bands are
exclusive of R3: bands 37, 38, 39, 40 and 41. From those, band 37 (Bacteroidetes) and bands 40-41
(ß-proteobacteria) are heterotrophs. Bands 38 and 39 are autotrophic NOB, closely related to
Nitrobacter winogradskyi.
Regarding the changes in the nitrifying bacterial community, a similar trend observed in R2 was
noticed in R3, in which the intensity of the bands representing AOB and NOB increased as the
organic load was reduced. In turn, higher ammonium uptake rates were observed in the cycle tests
(data not shown) as influent COD was decreased from Runs 10 – 14. The intensity of band 27 and
bands 29–31 (closely related to Nitrosomonas aestuarii) increased as the organic matter content in
the influent was reduced. The same occurred for band 39 (Nitrobacter winogradskyi).
Ammonium-oxidizing bacteria diversity through PCR-DGGE analysis of amoA fragments
In order to have a deeper insight into the ammonium-oxidizing bacteria (AOB) dynamics during the
operation of the three moving-bed biofilm reactors, DGGE analysis on PCR-amplified amoA gene
was performed (Figure 3). The results of the amoA gene-based DGGE were compared to the 16S
rRNA gene-based DGGE. Sufficient sequence information from DGGE bands was obtained for
phylogenetic analysis of AOB community. In total, 51 bands from all reactors were selected,
excised and sequenced in order to reveal the identity of the microorganisms involved. The
phylogenetic affiliation of the dominant bands were analysed and depicted in a phylogenetic tree,
shown in Figure 4. All microorganisms belonged to the Nitrosomonas group, which fits with the
results found with the 16S rRNA gene.
Since R1 was inoculated with biomass from an enriched nitrifying culture and was always run
under autotrophic conditions, the AOB diversity of this reactor was higher than in other reactors fed
with organic material (R2 and R3). A total of 30 bands were retrieved from run 1 to 5. Bands 1-4, 6,
19 and 29 showed high sequence similarity with Nitrosomonas nitrosa. Bands 5, 25 and 27 were
closely related both to Nitrosomonas communis and Nitrosomonas nitrosa. Bands 8, 9, 10 and 12
showed high similarity with Nitrosomonas europaea. Bands 28 and 30 were closely related to
Nitrosomonas eutropha and bands 11, 14-18, 20-24 and 26 showed high sequence similarity both
with Nitrosomonas eutropha and Nitrosomonas europaea. In general, the increase of nitrogen
loading rate from run 1 to run 5 was accompanied with the increase of intensity of several bands
(bands 1, 2, 5, 6, 7, 8, 21, 22, 23, 26, 27, 28 and 30). Band 24 remained stable and dominant over
the whole operation of R1.
In R2, several bands corresponding to the same microorganisms as those of R1 were detected:
bands 15, 24 and 25. However, the banding pattern is quite different from that obtained in R1.
Bands 31 and 39-42 presented similar sequence of that of Nitrosomonas europaea, bands 32-38 and
band 43 were similar to both Nitrosomonas europaea and Nitrosomonas eutropha. As COD was
gradually reduced from Runs 6 to 9, several bands appeared (bands 25, 31 and 39) and others had
their intensity increased (bands 40 and 41). In the same way as in R1, band 24 was dominant over
the whole operation of R2.
In the reactor operated on a sequencing-batch mode (R3), the number of bands representing AOB
community was lower than in the R1 and R2. This means that the operation in sequencing batch
regime of R3 did not favour a high diversity of AOB. Only bands 23 and 24 were identical as those
obtained in the bacterial community profile of the last two reactors. Bands 44-45 and bands 46-50
were similar to both Nitrosomonas eutropha and Nitrosomonas europaea. Band 51 showed high
sequence similarity to Nitrosomonas eutropha. The AOB community structure in R3 did not vary so
much. Most of the bands were already retrieved in Run 10. In this particular reactor, bands 24 also
corresponded to a dominant band, appearing along Runs 10-14. Some bands disappeared as
nitrogen loading rate was increased (bands 44, 45 and 51) and others remained quite stable (bands
23, 48, 49 and 50). It is likely that the starvation period in some experimental runs, in which
ammonium was depleted much before the end of the cycle, were detrimental to some AOB which
could not withstand long periods without availability of substrate.
Figure 3. DGGE banding patterns showing the ammonia-oxidizing bacteria (AOB) composition over the experimental
phases. The sequenced bands are numbered from up to down for each rector. Bands whose number is underlined already
appeared in a previous run (representing other reactor).
Figure 4. Maximum likelihood phylogeny of bacterial amoA sequences from DNA retrieved from the DGGE gel. The
bar indicates 10% sequence difference. The sequence of Nitrosococcus halophilus was used as an outgroup, but was
pruned from the tree.
Diversity of nitrifying bacteria in the moving-bed systems assessed by FISH
The diversity and evolution of nitrifying bacteria (AOB and NOB) community was assessed by
FISH analysis. The results obtained from FISH were compared to those obtained from PCR-DGGEbased methods in order to validate them. According to FISH analysis, bacteria of Nitrosomonas
genus were the only AOB in R2 and R3. This is in accordance with the DGGE results from both
16S rRNA and amoA genes, which also showed that all AOB belonged to the Nitrosomonas group
in all systems. Although bacteria belonging to Nitrosomonas were also dominant in R1, as shown
by PCR-DGGE approach, few cells of Nitrosococcus mobilis were also detected in this autotrophic
reactor. This specific genus was not detected in the PCR-DGGE analysis.
In relation to the NOB community structure, Nitrospira was the dominant nitrite oxidizer in R1. No
cells of Nitrobacter were detected in this reactor, in particular. This is in line with the results
obtained in the DGGE analysis using 16S rRNA specific primers, which also showed that
Nitrospira was the only NOB detected in the biofilm of R1 (bands 23 and 24 of the 16S rRNA
DGGE gel). The fact that Nitrobacter was not found in the autotrophic reactor but only in the
heterotrophic reactors may indicate that this group could not survive without external organic
carbon source. As pointed in our recent research (Winkler et al., 2012), we hypothesized that
Nitrobacter could have grown mixotrophically by using organic compounds in an aerobic granular
sludge system. This may explain the absence of this particular genus in R1. Further research is
needed to evaluate in details the different distribution of NOB according the organic content.
In R2, both Nitrobacter and Nitrospira were detected by FISH analysis, also in accordance with the
corresponding DGGE analysis of each reactor. Nitrobacter was the dominant NOB in R3,
confirming the 16S rRNA DGGE results, which showed that bands 38 and 39 presented high
similar similarity with bacteria belonging to this particular genus. Nitrospira was hardly detected in
the R3 biofilm.
CONCLUSIONS
The microbial community of moving-bed biofilm reactors was evaluated by PCR-DGGE on 16S
rRNA and amoA genes. We observed that nitrifying bacteria was selected as influent COD was
decreased in the heterotrophic reactors. In the autotrophic system, the intensity of the bands
corresponding to AOB and NOB population tended to increase in the long-term operation of the
system. The results obtained with PCR-DGGE-based methods were validated by FISH analysis.
Nitrospira was the dominant NOB in the autotrophic system whereas Nitrobacter dominated the
heterotrophic systems.
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