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Applied and Environmental Microbiology, December 1998, p. 4877-4882, Vol. 64, No. 12
0099-2240/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
Assessment of Changes in Microbial Community Structure during
Operation of an Ammonia Biofilter with Molecular Tools
Y.
Sakano and
L.
Kerkhof*
Department of Environmental Sciences and
Institute of Marine and Coastal Sciences, Cook College, Rutgers,
The State University of New Jersey, New Brunswick, New Jersey
08903-0231
Received 10 June 1998/Accepted 14 September 1998
 |
ABSTRACT |
Biofiltration has been used for two decades to remove odors and
various volatile organic and inorganic compounds in contaminated off-gas streams. Although biofiltration is widely practiced, there have
been few studies of the bacteria responsible for the removal of air
contaminants in biofilters. In this study, molecular techniques were
used to identify bacteria in a laboratory-scale ammonia biofilter. Both
16S rRNA and ammonia monooxygenase (amoA) genes were used to characterize the heterotrophic and ammonia-oxidizing
bacteria collected from the biofilter during a 102-day experiment. The overall diversity of the heterotrophic microbial population appeared to
decrease by 38% at the end of the experiment. The community structure of the heterotrophic population also shifted from
predominantly members of two subdivisions of the
Proteobacteria (the beta and gamma subdivisions) to
members of one subdivision (the gamma subdivision). An overall decrease
in the diversity of ammonia monooxygenase genes was not observed.
However, a shift from groups dominated by organisms containing
Nitrosomonas-like and Nitrosospira-like amoA genes to groups dominated by organisms containing only
Nitrosospira-like amoA genes was observed. In
addition, a new amoA gene was discovered. This new gene is
the first freshwater amoA gene that is closely affiliated
with Nitrosococcus oceanus and the particulate methane monooxygenase gene from the methane oxidizers belonging to the gamma
subdivision of the Proteobacteria.
 |
INTRODUCTION |
Biofiltration is a technique which
removes toxic compounds (organic and inorganic compounds), odors, and
volatile organic compounds from contaminated air. Since the 1920s,
odorous compounds (e.g., H2S) have been removed by
biofilters at a variety of wastewater treatment plants.
Biofilters have also been used at solid waste processing plants
and food processing plants for several decades (10,
31). In Europe, biofilters have been used to remove volatile organic compounds and odorous compounds since the late 1970s. Currently, there is a growing interest in the applications of biofiltration techniques in a variety of other settings (4).
Reactor designs, filter materials, and other factors involved in
biofilter function (e.g., moisture content, temperature, pH,
O2 concentration, salt concentration) have been
investigated (10, 24, 26). However, it has been suggested
that monitoring microbial populations is a way to optimize biofilter
performance (31), and studies on microbial ecology in
bioreactors are needed (26, 29). Recently, molecular
techniques have been used to study microbial populations in a
wastewater-activated sludge reactor (25), a
wastewater-trickling filter reactor (19), a
toluene-degrading biofilter (13), and a phenol-degrading
batch reactor (20). Unfortunately, these studies focused on
single samples from the bioreactors, and little is known about
population changes in microbial communities through time.
In this study, we characterized microbial community structure in
a laboratory-scale ammonia biofilter under development at Rutgers
University. This biofilter was designed to remove ammonia through the
process of nitrification (i.e., microbial oxidation of
ammonia to nitrate). Small-subunit rRNA genes were used to track communities of heterotrophic bacteria at three times during a
102-day experiment in the NH3 biofilter. In addition,
the ammonia monooxygenase gene (amoA) was used
as the target gene to identify microorganisms that were
responsible for ammonia removal. (All ammonia-oxidizing bacteria bear
the amoA gene, which catalyzes the first step in the
nitrification pathway.) Large decreases in heterotrophic bacterial
diversity during operation of the filter were observed, shifts in
the community structure of both heterotrophic and ammonia-oxidizing
bacteria were documented, and a novel amoA gene
closely related to the Nitrosococcus oceanus gene was
discovered during this study. In the future, studies such as the one
described here will be crucial for characterization of microbial
communities, for biofilter optimization, and for development of
reliability measures for biofilters in other applications.
 |
MATERIALS AND METHODS |
Sampling.
Samples were collected from an ammonia biofilter
under development at New Jersey-NASA-Sponsored Center of Research and
Training (NSCORT). Briefly, perlite (an inert silica matrix) was
inoculated with nitrifying activated sludge and leaf compost to create
a biofilter having a biomass concentration of 0.5 to 1 g of
biomass/kg (dry weight) of perlite. An airstream containing 20 ppm of
ammonium and 500 to 600 ppm of CO2 was applied to the
biofilter. Composite samples (150 g) were collected at the beginning of
the experiment (day 0) and on days 15, 21, 28, 35, and 102. The samples
were stored frozen (
20°C) until they were processed in the
laboratory. The system removed between 70 and 100% of the nitrogen
during the course of the experiment (7a). The microbial
populations in the day 0, 15, and 102 samples were assayed with
molecular tools as described below.
DNA extraction and purification.
DNA was extracted by using
a modified phenol-chloroform procedure (8). A total of
2.4 g of biofilter matrix was used for extraction. The contents of
eight tubes containing 300 mg of perlite from a single time point were
crushed, and the contents of each tube were suspended in 300 µl of
buffer (cold 50 mM glucose-10 mM EDTA-25 mM Tris [pH 8.0]). The
samples were frozen rapidly in liquid nitrogen and thawed at 37°C
four times. One hundred microliters of a lysozyme solution (10 mg/ml)
was added to each sample, and the preparation was incubated at room
temperature for 5 min on a rotator. Fifty microliters of a 50% sodium
dodecyl sulfate solution was added to lyse the cells. The lysate was
extracted twice with 800 µl of a phenol-chloroform-isoamyl alcohol
mixture (25:24:1). The nucleic acids were precipitated by adding 50 µl of 3.0 M sodium acetate, 2 µl of glycogen (20 mg/ml), and 1 ml of 100% ethanol. The DNA was pelleted by centrifugation
(16,000 × g) at 4°C for 20 min. The eight nucleic
acid pellets were sequentially resuspended in 500 µl (total volume)
of 1× TE (10 mM Tris [pH 7.5], 1 mM EDTA) by adding the 1× TE to
the first tube, letting the pellet dissolve, and transferring the
entire contents to the next tube. The concentrated extract was then
purified by cesium chloride ultracentrifugation (30). The
concentration and size of the extracted DNA were determined by 1%
(wt/vol) agarose gel electrophoresis in 1× TAE (40 mM Tris, 5 mM
sodium acetate, 1 mM EDTA [pH 7.8]).
PCR amplification. (i) 16S rRNA genes.
Hot-start PCR
amplification was performed with a model 2400 DNA thermal cycler
(Perkin-Elmer, Foster City, Calif.) by using eubacterial primers 27F
(5' cua cua cua cua AAG GAG GTG WTC CAR CC 3') and 1525R (5' cau cau
cau cau AGA GTT TGA TCC TGG CTC 3') (9) bearing a
uracil-rich end for cloning (see below). Less than 10 ng of template
DNA, 15 pM primer, and 1 to 2 U of Taq polymerase were used
for each reaction. The amplification program was as follows: one cycle
consisting of 94°C for 5 min, followed by 30 cycles consisting of
94°C for 0.5 min, 55°C for 0.5 min, and 72°C for 1.5 min and a
final extension step consisting of 72°C for 10 min.
(ii) Ammonia monooxygenase (amoA) genes.
Two
primers, primers A189 (5' cau cau cau cau GGN GAC TGG GAC TTC TGG 3')
and A682 (5' cua cua cua cua GAA SGC NGA GAA GAA SGC 3'), were used to
detect ammonia oxidizers (7). The reaction conditions were
the same as those described above. The amplification program was as
follows: one cycle consisting of 94°C for 5 min, followed by 28 cycles consisting of 94°C for 0.5 min, 56°C for 0.5 min, and 72°C
for 1 min and a final extension step consisting of 72°C for 7 min.
Cloning.
The amplified 16S rRNA and amoA genes
were purified with a Geneclean kit (Bio 101, La Jolla, Calif.) by
following the manufacturer's instructions. The PCR products (22 cycles) were ligated by using the CLONEAMP pAMP1 system (Life
Technologies, Gaithersburg, Md.) as recommended by the manufacturer and
were transformed into high-efficiency competent cells (Promega,
Madison, Wis.) at a DNA concentration of <6 ng
template
1. Unique clones were identified by
HaeIII (Promega) restriction digestion. Plasmid DNA from
transformants that produced unique restriction patterns were repurified
by using a FlexiPrep kit (Pharmacia, Piscataway, N.J.) for sequencing.
Sequence analysis.
DNA sequences were determined by using a
model ABI 373A automated sequencer (Perkin-Elmer/ABI, Foster City,
Calif.). Primary sequences were analyzed by using the Auto Assembler
and SeqNavigator ABI software programs, as well as BLASTN
(2). For the 16S rRNA clonal libraries, a neighbor-joining
tree with the Jukes-Cantor correction was reconstructed with the
Genetic Data Environment (21) (data not shown). Similarity
ranks for small-subunit rRNA clones were examined by using the
Ribosomal Database Project method (11). For the
amoA gene clonal libraries, a maximum-likelihood tree was
reconstructed (100 replicates bootstraps) by using the fastDNAml
program, and a distance similarity matrix for nucleotides and amino
acids was constructed by using the neighbor-joining distance method in
the Genetic Data Environment (21). The accession numbers of
the gene sequences used in this study are as follows: Nitrosomonas europaea, L08050; Nitrosomonas
eutropha, U51630; Nitrosospira multiformis, U89833;
Nitrosospira sp., X90821; Nitrosospira sp. strain
N39-19, AF006692; Nitrosospira briensis, U76553;
Nitrosospira tenuis, U76552; Nitrosococcus
oceanus, U96611; Methylococcus capsulatus,
U94337; Methylobacter albus, U31654;
Methylomonas methanica, U31653; Methylosinus trichosporium, U31650; and Methylocystis parvus,
U31651.
Clone designations.
The biofilter amoA gene
clones were designated as follows: BAXY, where X is the day(s) on which
the sample(s) was obtained (A, day 0; B, day 15; C, day 102; D, days 0, 15, and 102) and Y is the isolate number. The biofilter heterotrophic
(16S rRNA) gene clones were designated as follows: BHXY, where X is the
day(s) on which the sample(s) was obtained (A, day 0; B, day 15; C, day 102; D, days 0, 15, and 102) and Y is the isolate number.
Nucleotide sequence accession numbers.
The nucleotide
sequences determined in this study have been deposited in the GenBank
database. The accession numbers for the amoA gene sequences
are AF070983 through AF070987, and the accession numbers for the 16S
rRNA gene sequences are AF090535 through AF090553.
 |
RESULTS |
Purification of genomic DNA from the perlite matrix yielded 50 to
150 ng of DNA per 2.4 g of perlite mixture (data not shown). This
DNA was used to amplify the 16S rRNA and amoA genes as
described above. Strong amplification of 16S rRNA genes was observed
with the day 0, 15, and 102 samples (data not shown) suggesting that there was little or no inhibition of PCR by DNA extracts at these times. No amplification was observed with the day 28 sample for some
reason, and this sample was not analyzed further. For the samples that
were successfully amplified, between 150 and 1,000 colonies were
obtained from each clonal library by using an aliquot of the PCR
mixture. The frequencies of unique clones in the libraries were used to
estimate the microbial diversity in the system (a rarefaction curve was
obtained by restriction enzyme analysis) (Fig.
1). A clear shift in microbial diversity
was observed from day 0 to day 102, and roughly 38% of the unique
clones disappeared during this time.

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FIG. 1.
Rarefaction curves plotting the number of unique 16S
rRNA clones versus the number of individual 16S rRNA clones as
determined by restriction enzyme digestion. The clonal libraries
obtained on day 0 ( ), day 15 ( ), and day 102 ( ) were
examined.
|
|
In order to determine whether the individual members of the
heterotrophic community also changed, we performed a sequence analysis of the cloned 16S rRNA genes. Table
1 shows the results of similarity
searches performed by using the Ribosomal Datbase Project
(11) for the heterotrophic population. This sequence analysis revealed that there was some duplication (99% identity) of
the various restriction fragment length polymorphism patterns in
the clonal libraries, and the clones were assumed to represent different copies of the rRNA operons within a single genome.
Therefore, the data in Table 1 differ from the total number of
unique clones shown in Fig. 1 (i.e., 13 clones were obtained from the
day 0 sample, 9 clones were obtained from the day 15 sample, and 8 clones were obtained from the day 102 sample).
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TABLE 1.
Comparison of sequences in 16S rRNA clonal libraries
obtained on days 0, 15, and 102 to sequences in the Ribosomal
Database Project database and changes in community structure over time
|
|
The phylogenetic tree reconstruction results confirmed the positions of
all of the 16S rRNA clones in their respective phyla with
Sab values (data not shown). The heterotrophic
community was comprised mostly of members of
Proteobacteria phyla along with six representatives loosely
affiliated with the gram-positive phyla or the Isosphaera
group. In the proteobacterial group, a shift from predominantly members
of the
and
subdivisions at day 0 to members of the
subdivision at day 102 occurred. Only the following three members of
the heterotrophic community were found throughout the study: clone
BHD21 (
subdivision), clone BHD15 (
subdivision), and clone
BHD3 (affiliation unknown). The remaining small rRNA clones
were observed only at one or two times.
There were no known nitrifiers in the 16S rRNA gene library. Therefore,
we amplified a portion of the amoA gene (7)
to monitor the nitrifying population during the 102-day
experiment. An analysis of the amoA clonal libraries in
which rarefaction curves were used did not reveal a change in the
diversity of the nitrifying populations over time (data not
shown). However, a reconstructed phylogenetic tree of amoA
sequences revealed that there were major shifts in the clonal
amoA gene population structure during the study (Fig.
2). Only one sequence (clone BAD34) was found throughout the study. This clone was most similar to
amoA genes recovered from Nitrosospira species.
The following two additional amoA sequences affiliated with
the Nitrosomonas europaea clade were found on day 0: clone
BAA7 (identified as Nitrosomonas europaea) and clone BAA8.
Within 2 weeks, Nitrosomonas-like amoA genes were no longer detected, and the ammonia-oxidizing population appeared to be
composed of bacteria with amoA genes most similar to those of Nitrosospira species; a new clone (clone BAB33) was
detected that was not present in the day 0 library. By the end of the
experiment, an additional Nitrosospira-like amoA
gene (clone BAC5) was detected, as was a new amoA gene
(clone BAC6) that exhibited 68% identity to the Nitrosococcus
oceanus gene. The BAC6 gene sequence was also similar to
particulate methane monooxygenase (pmoA) gene sequences.

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FIG. 2.
Consensus phylogenetic tree based on ammonia
monooxygenase genes as determined by the maximum-likelihood method and
100 iterations (483-bp alignment). The numbers at the nodes are the
percentages of bootstrap trees within similar topologies; only values
greater than 50% are shown. Biofilter clones BAB33, BAC5, BAD34, BAC6,
and BAA8 were obtained in this study.
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|
Table 2 is a distance similarity matrix
in which the nucleotide and predicted amino acid sequences of the
amoA genes identified in this study are compared. The levels
of nucleotide similarity and amino acid similarity obtained in this
study ranged from 23 to 95% and from 44 to 98%, respectively. An
alignment of the amino acids in parts of the amoA- and
pmoA-encoded proteins is presented in Fig.
3. A total of 39 of 161 amino acid
residues were conserved in all sequences. The number of conserved
residues increased to 52 when just amoA proteins were
compared.
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TABLE 2.
Distance-similarity matrix for 480 bp of amoA
and pmoA nucleotides and 160 predicted amino acids encoded
by amoA and pmoA
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|

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FIG. 3.
Partial alignment of the predicted amino acids encoded
by amoA (ammonia-oxidizing bacteria) and pmoA
(methane-oxidizing bacteria). The residues conserved in all sequences
are highlighted. The conserved amoA residues are enclosed in
shaded boxes. Abbreviations: Nmeur, Nitrosomonas europaea;
Nmeut, Nitrosomonas eutropha; Nsmul, Nitrosospira
multiformis; Nssp., Nitrosospira sp.; NsN39,
Nitrosospira sp. strain N39-19; Nsbri, Nitrosospira
briensis; Nsten, Nitrosospira tenuis; Ncoce,
Nitrosococcus oceanus; Mcap, Methylococcus
capsulatus; Malu, Methylobacter albus; Mmet,
Methylomonas methanica; Mtri, Methylosinus
trichosporium; Mpar, Methylocystis parvus; A8, clone
BAA8; B33, clone BAB33; D34, clone BAD34; C5, clone BAC5; C6, clone
BAC6.
|
|
 |
DISCUSSION |
Bioreactors are increasing in popularity as a means of remediating
waste streams. However, little is known about the bacterial population
structure of biofilters since most research treats the biofilter system
as a "black box." Furthermore, much of the microbiological research
done previously involved culturing isolates, and many bacteria in
complex systems are now widely believed to be as yet unculturable
(3, 23, 28). In this study, the population structure and
dynamics of an ammonia biofilter were examined with molecular tools. A
large (38%) decrease in heterotrophic diversity and significant
changes in the microbial community were observed by the end of the
experiment. In addition, our preliminary molecular profiling analysis
in which 16S rRNA genes were used did not detect known nitrifying
bacteria. In previous research on nitrifiers in Antarctic lakes workers
found that they were not able to directly amplify 16S rRNA genes from
nitrifiers without a two-stage enrichment procedure for nitrifier rRNA
genes (27).
To circumvent this problem, we targeted the ammonia oxidizers by
amplifying the ammonia monooxygenase (amoA) genes (7, 17). Although changes in amoA gene diversity were
not observed over time, structural shifts in the amoA
gene population analogous to the changes observed in the heterotrophic
populations occurred. Four of the five amoA gene sequences
detected in our biofilter were novel. One amoA sequence
(clone BAC6) is the first amoA gene sequence recovered from
a freshwater system that is closely affiliated with the
amoA gene of a member of the
Proteobacteria.
The maximum-likelihood tree and distance similarity matrix demonstrated
that the amoA genes of clone BAC6 and Nitrosococcus
oceanus are more closely related to the pmoA genes of
methane oxidizers than to amoA genes of the other ammonia
oxidizers. At present, we do not know the phylogenetic affiliation of
the nitrifier bearing the novel amoA gene. Furthermore, our
data support the concept that many of the model organisms traditionally
used to study nitrogen cycling may not be the indigenous bacteria
important in any particular system (18).
One possible explanation for the results which we obtained is that the
differences which we measured with the molecular tools were the result
of methodological artifacts. However, we believe that this explanation
is unlikely. Although the 16S rRNA gene characterization method for
identifying bacteria is becoming routine in many labs, potential biases
in the traditional clone and sequence approach do exist. In particular,
DNA extraction procedures can miss entire groups that are difficult to
lyse, such as gram-positive organisms. In addition, large amounts of
template DNA, high cycle numbers during PCR amplification, and large
amounts of transforming DNA are used to maximize the number of colonies
obtained during cloning. However, this strategy may confound attempts
at analysis due to PCR (1, 5, 16, 22) or cloning
biases resulting from the asymptotic transformation of
Escherichia coli at DNA masses of >10 ng
(6).
Therefore, we took steps in our study to minimize the biases
inherent in the traditional approach. The extraction procedure which we used has been shown to quantitatively recover nucleic acids
from easily lysed bacteria, such as Pseudomonas stutzeri Zobell (8), and can successfully isolate DNA from organisms that are more difficult to lyse, such as gram-positive bacteria from
marine sediment systems (15). As for PCR and cloning
artifacts, in most previous studies the researchers utilized high
template concentrations (>200 ng of template) and high numbers of
cycles (>28 cycles) for the PCR. In this study, we used minimal
template concentrations (<10 ng of genomic DNA), lower numbers of
cycles (20 to 25 cycles), and low amounts of transforming DNA (<6 ng) to create our clonal libraries. In addition, all amplification reactions and cloning of the different samples were performed at the
same time with the same reaction mixtures.
In conclusion, further work is needed to understand the
relationship between biofilter performance and microbial community dynamics. Currently, the influence of microbial diversity and the
influence of shifts in community structure, if any, on the rates of
ammonia conversion in the biofilters which we used are unclear.
However, the molecular methods described in this study can shed light
on the ecology of the unculturable organisms and their population
changes within our bioreactor over time. An understanding of microbial
populations in biofilters is important since biodiversity may play a
major role in enhancing bioreactor predictability and reliability
(12, 14). Finally, microbial profiling may provide an early
warning system that can be used to predict degradation of the
biological components far sooner than loss of function.
 |
ACKNOWLEDGMENTS |
This research was supported in part by funds from Rutgers University.
We thank the Waste Processing Team of NJ-NSCORT at Rutgers University
for providing samples and analytical data. We also thank David Scala
and Mary Voytek for assistance in sequencing and data analyses. We are
also indebted to anonymous reviewers and Jerome Kukor; their comments
significantly improved the manuscript.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Institute of
Marine and Coastal Sciences, Rutgers, The State University of New
Jersey, 71 Dudley Rd., New Brunswick, NJ 08901-8521. Phone: (732)
932-6555, ext. 335. Fax: (732) 932-6520. E-mail:
kerkhof{at}ahab.rutgers.edu.
 |
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