Microbial Community Structure of Activated Sludge As
Investigated With DGGE
Division of Applied & Environmental Microbiology, Enviro Technology Limited, Industrial Waste Water Research Laboratory, India
Shah MP, Division of Applied & Environmental Microbiology, Enviro Technology Limited, Industrial Waste Water Research
Laboratory, India, E-mail:
Received: 14 October, 2016; Accepted: 21 November, 2016; Published: 24 November, 2016
Microbial activity and structure of the bacterial community
of activated sludge reactors, which treated industrial wastewater,
were studied. Microbial communities, including ammonia oxidizing
bacteria, Eubacterium and actinomycete communities were studied
in two different systems with the polymerase chain electrophoresis
gradient denaturing gel reaction using amplified gene fragments,
16S rRNA of bacteria. Both systems, which used an anoxic-aerobic
process and anaerobic-anoxic-aerobic process, respectively,
received the same industrial wastewater, operating under the same
conditions and showed similar processing performance. Oxidizing
bacterial communities of ammonia from two systems showed almost
identical structures corresponding to ammonia removal, while the
actinomycete bacterial community showed obvious differences.
FISH results showed that the ammonia-oxidizing bacterial cells in
the anaerobic-anoxic-aerobic system increased by 3.8 ± 0.2% of the
total bacterial population, while those in the anoxic-aerobic system
represented 1.7 ± 0.2%. Thus, the existence of an anaerobic-anoxic
environment in the anaerobic-aerobic system resulted in a marked
increase in biodiversity.
Keywords: Industrial waste water; 16S rRNA; Anoxic; Anaerobic;
The growth of the world population, the development of
various industries, and the use of fertilizers and pesticides
in modern agriculture has overloaded not only the water
resources but also the atmosphere and the soil with pollutants
. The degradation of the environment due to the discharge of
polluting wastewater from industrial sources is a real problem
in a number of countries. This situation is even not as good as
in developing countries like India where little or no treatment is
carried out before the discharge . Moter and Gobel developed
the first activated sludge system for purification of wastewater
in Manchester . However, the role of microbial consortia in
this process is still not completely understood. Culture-based
techniques were found to be too selective to give a comprehensive
and authentic picture of the entire microbial community as it
has been estimated that the majority (over 99%) of bacteria in
nature cannot be cultivated by using traditional techniques .
Activated sludge is a very thorny system, comprised of a variety of populations including heterotrophic and autotrophic bacteria,
fungi and protozoa . The relationship between the microbial
composition and the treatment performance of activated sludge
processes has long attracted the attention of microbial ecologists
and environmental engineers, as this information might be useful
for the proper design and operation of biological wastewater
treatment systems. Protozoa have been studied and utilized
as an important indicator for judging process performance
and effluent quality since the 1970s, because these large sized
microorganisms can be directly observed and identified under
a microscope . The development of DNA-based techniques
has revolutionized the ability to characterize and identify the
diversity and taxonomy of environmental organisms in a wide
variety of niches [7,8], such as food , soil , water  and
the human body . A major advantage of this approach is that
it allows monitoring, exposure and investigation of the genetic
targets of interest directly from environmental samples, lacking
the additional steps of cultivation and recovery [13,14], which
are known to be inefficient in recuperating symbiotic, facultative, stationary, slow growing, pH sensitive and various other
fastidious microorganisms [15,16]. In spite of its attractiveness,
many molecular studies applied to soil and water have indicated
that the choice of processing method and the design of extraction
protocols may affect the degree of lysis of the microorganisms
present in the sample (and hence the recovery of their template
DNA) , the integrity and size of DNA obtained  and the
extent of co-extraction of both organic and inorganic impurities
which may interfere with PCR amplification . These factors
may also affect the usefulness and applicability of the DNA for
further molecular analysis  and drastically affect the recovery
of molecular diversity, leading to mistakes in the interpretation
of the true diversity and taxa present [21,22]. Despite the
knowledge that microbial communities evolving in wastewater
treatment plants contribute on handling processes, there are
only a few reports concerning the study of bacterial communities
. Until now, studies were carried out using mainly traditional
microbiological schemes. The emergence of molecular techniques
allowed the conquering of the problems associated with culturedependent
methods that lead to an underestimation of the true
diversity. Molecular methods such as 16S rDNA clone libraries
, ribosomal intergenic spacer analyses , 16S-restriction fragment length polymorphism , repetitive extragenic
palindrome polymerase chain reaction  and Fluorescent
In Situ Hybridization [FISH) [27) have already been applied to
the study of wastewater-associated microbial communities.
The combination of PCR amplification of 16S rRNA genes with
Denaturing Gradient Gel Electrophoresis [DGGE] analysis has
also provided a useful means to directly characterize bacterial
populations within many samples. Polymerase chain reaction
–denaturing gradient gel electrophoresis has been successfully
used in many fields of microbial ecology to assess the diversity
of microbial communities and to determine the community
dynamics in response to environmental variations. Studies
concerning bacterial diversity in waste waters using a DGGE based
approach have been performed for reactor systems  and
activated sludge , revealing the presence of highly complex
bacterial communities. However, petty work has been done in
order to apply this methodology to assess the bacterial diversity
in industrial wastewater where the organic matter degradation
takes place. In the present study, microbial communities of two
different systems, an anoxic-anaerobic-aerobic process and an
anoxic-aerobic process, respectively, receiving identical sewage
and having similar treatment performance, were determined
using group- specific PCR-DGGE and subsequent sequence
analysis of rRNA genes. The community diversity of eubacteria
and ammonia oxidizing bacteria, were investigated in the two
systems to evaluate the effects of different designs on microbial
populations. FISH was used for the determination of the ratio of
ammonia oxidizing bacteria in each system with a probe.
Materials & Methods
DNA Isolation from samples of activated sludge
Activated sludge samples were collected from the biological
system of the industrial treatment plant, pelleted by centrifugation
(5000 x g, 10 min, 4°C) and stored at -45°C until isolation of DNA.
Total genomic DNA was extracted from 0.3 g of activated sludge
samples according to the mechanical method . The samples
were washed three times with 1 x PBS buffer and disrupted with
bead beating in lysis buffer [Tris-HCl 100 mM, 100 mM EDTA,
1.5 M NaCl; pH = 8.0). The samples were incubated 20 minutes at
1400 revolutions per minute and 200 ul of 10% SDS was added.
After 30 minutes incubation at 65°C the samples were centrifuged
twice at 13,000 rpm and placed on spin filters. DNA fixed on the
filter was washed twice with a solution A1. The amount of DNA
was measured spectrophotometrically, using qubit and stored at
-20°C until PCR amplification.
Water temperature and dissolved oxygen were determined
in situ with a WTW model 330i/ SET and a model WTW OXI 96,
respectively. Influent characteristics, namely the biochemical
oxygen demand, chemical oxygen demand, suspended solids and
pH were determined by standard methods  and portrayed in
Analysis of microbial community diversity by means
of 16S rRNA using PCR-DGGE
The DNA of the bulk community was extracted from 1.0
mL of sludge using a Fast DNA Spin Kit for Soil. The extracted DNA was then subjected to PCR touchdown, using primers 341F
and 534R . The primer 341F contained a 44 bp GC clamp.
Amplification was performed in a thermal cycler. PCR products
were separated using a code-D and 1 mm thick polyacrylamide
gel system containing 8% (w/ v) acrylamide-bisacrylamide
(37.5:1), TAE IX buffer, and a denaturing gradient of 30% to 70%
(v/ v). Electrophoresis was performed in TAE buffer at 60°C and
constant voltage for 14 hours. Gels were stained with 1:10 000 (v/
v) SYBR Green I and photographed using Gel Doc 2000 equipped
with MULTIANALYST software. The central parts of DGGE bands
were excised with a razor blade and soaked overnight in purified
water. A portion of this (10 ul) was then removed and reamplified
as described above. The re-amplified DNA fragments from the
DGGE bands were sequenced directly or cloned into the pGEM-T
Easy vector system prior to sequencing. The sequences were
checked for possible chimeras using CHIMERA_CHECK program
on the website of ribosomal database project. To determine
the phylogenetic position of microorganisms detected in DGGE, the sequences of 16S rRNA genes analyzed were compared
with databases of sequences available via BLAST search.
The band patterns and intensities of the scanner gels were
analyzed using Gel Compar software. After applying subtraction
drive working capital, an analysis of each channel, acquiring
densitometric curves was carried out by the software. A DNA
band was identified if the tape represented more than 1.0% of
the total intensity channel. A matrix was then constructed using
this information, and has been used to calculate a set of digital
values to describe the diversity of bacterial communities. As a
parameter to the structural diversity of the microbial community,
the Shannon index  of overall diversity, H, was calculated
with the following formula: H = -ΣPi • ln (Pi) wherein Pi is the
probability that major bands in a track: H was calculated on the
basis of the bands on the gel lanes, using the intensities of the
bands after the peak heights in the densitometric curve. The
probability of material, Pi, Pi was calculated as = ni/ N, where ni
is the height of the peak i, and N is the sum of all peak heights in the densitometric curve. For the analysis of ammonia-oxidizing
bacteria and activated sludge actinomycete populations, a nested
PCR technique was used to increase the sensitivity . In the
first round, 1 μL of the extracted DNA was added to Mastermix
PCR and different primers were used, each with their own
corresponding PCR protocol. During the second round of PCR,
1 μL amplified product in the first round was added to 49 ul of
PCR mixture and then reamplified using their own protocol and
corresponding PCR primers shown in Table 2.
Table 1: Influent and effluent characteristics
CODCr (mg/ l)
BOD (mg/ l)
450 - 800
250 - 400
35.6 – 47.5
52 - 68
49.0 – 62.0
5.2 – 6.6
38.6 - 48.8
12.4 - 18.6
11.0 – 25.0
38 - 44
36.0 – 41.0
0.6 – 3.8
32.4 - 40.2
10.12 - 14.84
8.6 – 17.8
9.4 - 18.2
33.6 – 38.5
5.3 – 5.9
Sequence Analysis of denaturing gradient gel
The denaturing electrophoresis gel gradient profiles were
analyzed with the fingerprint software database TM diversity.
On the basis of the presence  or absence (0) of individual
bands in each lane, a binary matrix was constructed. Binary
data representing the banding patterns were used to generate a
Dice pair wise distance matrix. A dendrogram was obtained by
unweighted pair group analysis of the mean of the cluster means.
The distance matrix was also used for the construction of a multiscale
diagram scaling, on a two dimensional plane with artificial
x- and y-axis where each denaturing gradient electrophoresis
gel fingerprint is placed at a certain time, so that similar samples
are represented together. Clustering analysis and MDS were
performed using the software Primer 5 . Denaturing gradient
electrophoresis gel patterns were also examined using two
indices to field many aspects of microbial diversity. The Shannon-
Weaver index of diversity, H  and the index of equitability, E
 were calculated for each sample as follows:
Where, ni is the intensity of the relative area of each band
electrophoresis denaturing gradient gel, S is the number of bands
in denaturing gradient electrophoresis gel and N is the sum of
all surfaces of all bands in a given sample . The statistical
significance of the variance in the index was assessed by a twoway
analysis of variance. A canonical correspondence analysis
was used to determine the multiple relationships between each
variant denaturing gradient gel electrophoresis banding patterns
and environmental parameters. The analysis was performed
using CANOCO for Windows Version 4.5  and its significance
was evaluated by the Monte Carlo test with 1000 permutations.
The Gas Chromatograph - Mass Spectrometry (GC-MS)
analysis was performed by a MP5890GC/ MS. Chromatography
was conditioned as follows: SE- 54 capillary column (25 m ×
0.32 mm); the column temperature was maintained at 40°C for
2 minutes, then heated to 250°C, with an increment of 3 ~ 5 °
C/ min and held at 250°C for 30 min. Mass conditions were as
follow: temperature of the MS ion source was 250°C; the voltage
multiplier is 2400 V; the electron energy is 70 eV.
Fluorescence in situ hybridization analysis
Prior to hybridization, the samples were dispersed into single
cells by sonication, and then treated immediately and fixed in 4%
paraformaldehyde for 3 hours at 4°C. After that, the biomass was
washed with phosphate buffered saline (pH 7.4) and stored at a
1:1 ratio of phosphate buffered saline and 100% ethanol at 0° -
20°C. All Hybridizations were performed at 46°C for 120 min as
described by Manz, et al. (1992). The oligonucleotide probes of
the 16S rRNA target - and the stringency used in this study are
listed in Table 3.
After hybridization, the slides were mounted with Citifluor prevent money laundering and examined with an epi-fluorescence
microscope Axio skop 2. All processing and image analysis were
performed with the standard software provided by Zeiss. Three
probes are listed in Table 3.
Sampling in the industrial wastewater treatment plant was
done from two biological systems of aeration tanks. Influent
physical and chemical characteristics during the sampling
period are shown in Figure 1. Parameters such as biochemical
oxygen demand, chemical oxygen demand and total suspended
solids showed a high variation with pronounced peaks. The pH
ranged from 6.7 to 7.6. Water temperature and DO concentration
values registered in both systems were also rather unstable,
with temperatures ranging from 11.3 to 29.7 °C and DO varying
between 0.10 and 3.14 mg/ l (Figure 1).
Bacterial community analysis using 16S rRNA gene
To follow the evolution of the microbial community during
operation of the reactor, 16S rRNA PCR amplified gene fragments
were analyzed using DGGE (Figure 2). DGGE profiles show
changes in the microbial population due to progressive reductions
in HRT. The average band number per lane in each reactor used
for diversity analysis was 19.7 (from 17 to 22) Al, 18.8 (from 15
to 22) in the A- II and 19.7 (from 17-22) in AI + II. The number
and thickness of the bands observed in the DGGE profiles provide
an estimate of species richness. The Shannon diversity index, H,
from the DGGE band pattern of each sample was calculated to
Table 2: PCR Primers used in this study
Table 3: Analysis of wastewater components
and ketone acids
determine the diversity of the microbial community. Figure 3
shows changes in the Shannon diversity index H, occurring at the
same time than changes in HRT. After HRT reduction of 48 to 24
h, the values of H in A-I and A-II increased slightly (2.80 and 2.63,
respectively). At HRT 12 h, microbial diversity recovered slightly
in A-I. The final reduction of HRT decreased to 6 h H for the three
reactors. 16S rRNA gene sequences of 28 major groups (9 to A-I
bands, 10 bands to A-II and A-9 bands I + II). Most of the sequences
were found to be clustered in the Proteobacteria (17 bands) and
Bacteroidetes (6 bands). The other band sequences were found
to be clustered in the Actinobacteria (2 strips), phylum TM7 (2
bands) and Acidobacteria (1 band). In the Proteobacteria, most
sequences were combined in the β-Proteobacteria, in particular
in the control Burkholderiales (10 bands). In A-I, bands F4,
F5 and F7 were present in all periods of operation and have
become widespread as HRT has been reduced. F1, F2, F3 made
minor bands, but was observed in almost all periods. F6 became
widespread on days 40 and 46 (6 pm HRT).
In A-II, the profile does not change significantly during days
15-30 (HRT of 24 h and 12 h) or days (40-50 HRT of 6 hours).
Major groups, including Z3, Z4 and Z8, who were present during
long periods (HRT of 24 h and 48 h) persisted, but became minor
after 30 days (HRT 12 h). Z6, Z7 and Z9 have become large
groups after 40 days (HRT) 6 h of operation. In A-I + II, Group N4,
which is a minor component of the community during the first
period, gradually became dominant after the operation of the
Figure 1: Waste water treatment systems operations conditions & performance
(a) BOD (), COD (♦), TSS (▲), pH (∗) in raw water ; (b)
temperature (▲ ), Dissolved oxygen ()
Figure 2: Denaturing gradient gel electrophoresis profiles of 16S rRNA
gene of bacterial communities.
Figure 3: Change of Shannon index values throughout reactor operation
(: A-I ; □ A II; □ :A-I-II ) Shannon index values (H) were calculated
on the basis of the number and intensity of bands on the gel tracks. HRT
is indicated in parenthesis.
reactor supported (with decreasing HRT). N1, N2, N5, N6 and N9
became dominant between days 15 and 40. Finally, days 40-50,
new groups such as N7 and N8 became dominant. Only a limited
number of bands with greater than 98% similarity with each
other were recovered from sludge from all three aeration tanks.
One contained F3, Z2, and N2, which are associated with Zoogloea,
and the other contained F6, Z6, and N5, which are associated with
Acidovorax. Sludge A-I and A-II had two sequences in common:
F2 and Z1, which were associated with Microbacterium, and the
other contained F9 and Z10, which were associated with the TM7
branch. These results demonstrate that the bacterial community
is significantly different between the reactors, depending on the
type of cyanide used.
Analysis of samples in different places of the aeration tank
was performed. Total ion chromatograms are shown in Figure
4. It showed that the type and amount of organic matter in
wastewater have a decreasing trend in the flow direction. A-I +
II, the areas of ICT crest of the wave were almost the same. This
demonstrates that the disposal capacities in the last three organic
compartments were extremely limited and most organics were
removed in A-I and A-II. Further analysis of the types and relative amounts of the organic phases are illustrated in Table 3. It was
shown that there were seven major types of organic matter in
the influent. The number of organic matter in the influent was
112 and increased to 185 after the influent mixed with the return
sludge in A-I. Then the number fell by 113 and 48, but rose again to
116 in the secondary settling tank. The number of organic matter
in the secondary settling tank was close to that of the tributary.
Thus, along the direction of flow of water, types of organic
materials initially increased and then gradually decreased, and
finally increased sharply. The sudden increase in substances was
mainly those refractory organic as alcoholic aldehyde, ketone
acid, hydrocarbons and halogenated hydrocarbons. It was
deduced that these refractory organics were initially adsorbed
by the activated sludge in an aeration condition. And in anoxic
conditions of the secondary settling tank, the activity of aerobic
bacteria and Zoogloea significantly reduced.
In this investigation, several probes were used for the analysis
of ammonia oxidizing bacteria in both systems. Probes β-AO233,
Nsp436 and Nmo254 were respectively used for the detection
of bacteria belonging to Nitrosospira cluster, and the cluster
Nitrosomonas halophilic and halo tolerant, and total ammonia
oxidizing bacteria (Table 4). It was found that in both systems,
the genus Nitrosomonas shows about 1.8 % (the system A2O)
and 1.6% (AO system) respectively. The Nitrosospira proportions
in the two systems were 2.2% (the system A2O) and 1.2% (AO
system), respectively. Hybridizations with Nmo254 probe
showed that the total number of ammonia oxidizing bacteria
in the system represented A2O average 3.6 ± 0.2% of the total
bacterial population while the AO system was only 1.9 ± 0.2%.
This study was undertaken to promote our knowledge of
Figure 4: Chromatogram of (a) Influent (b) A-I (c) A-II (d) A-I+II
Table 4: Oligonucleotide Probes used in this study
Sequence (59 - 39)
All b-subgroup ammonia oxidizers
All Nitrosospira spp.
All Nitrosomonas spp.
how microbial communities in wastewater are important in
governing the settlement patterns of the bacterial community. An
excellent strategy to assess these patterns is ensured by bacterial
inoculation experiments. Microbial communities, obtained by
activated sleds, are added to the pre-sterilized effluent selected
and the implementation of certain community structures is
compared. This study provides data that support an analysis of
the foundations of the creation of the bacterial community. The
study of the composition, structure and dynamics of microbial
communities in aerated lagoons is essential to understand
and ensure the proper functioning of the treatment system, a
valuable tool for improving the design of aerated ponds. Since the
ecological function of microorganisms depended on its community
structure, operational performance and degrading treatment
system efficiency could be reflected by changes in the microbial
community structure. Each agency has its inherent niche and
optimal substrates, and the microbial community would adjust its
structure in response to the changing environment. Whereas little
information is available on microbial communities that inhabit
these ecosystems, the approach based on PCR-DGGE, which was
applied here, has shown to be effective in obtaining new data on
the structure and dynamics of these communities. In addition, the
constant changes in DO concentration, the dramatic reduction
of biodegradability and recycling of sludge also contributed to the constant changes in environmental conditions, which led to
repetitive structural changes in bacterial community. As shown
in Table 1, both systems show nearly identical performance in
the removal of chemical oxygen demand, biochemical oxygen
demand and suspended solids, while the anoxic-aerobic system
had a slightly higher removal of ammonia and the anaerobicanoxic-
aerobic system had a higher phosphate removal.
Although wastewater systems received identical, despite
fairly similar constitutions, operating conditions, and treatment
performance, both systems have shown quite different structures
of microbial communities, except for ammonia oxidizing bacteria.
It is interesting to note that the anoxic-aerobic-anaerobic
system had far richer compositions of bacterial populations,
actinomycetes and yeast. The richest community structures of
these populations have been clearly linked to the creation of
the anaerobic compartment. Most species that increased in the
anoxic-anaerobic-aerobic system are perhaps those that tend
to thrive in anaerobic environments. Temperature, DO and pH
were the parameters that have shown to exert more influence on
DGGE profiles. Yuz, et al.  previously reported temperature
and DO as decisive parameters that affect community structure.
Gilbride and colleagues  also found a significant correlation
between the temperature and the structure of the bacterial
Figure 4: Chromatogram of (a) Influent (b) A-I (c) A-II (d) A-I+II communities of the activated sludge, as well as other influential parameters, such as COD and BOD, which showed no significant
correlation. Table 1 indicates that the AO system has almost
no phosphate removal capability. The A2O system, on the
other hand, had shrinkage in TP of about 50%, which can be
attributed to the possible accumulation of ODP. The results of
bacterial DGGE bands sequencing indicated that the dominant
population that appear only in the A2O system belongs to the
gamma Proteobacteria. Gamma proteobacteria are related to the
elimination of phosphates . To stabilize the structure of the
bacterial community and the purification efficiency for industrial
wastewater process A/ O, the following strategies can be
considered: (a) to strengthen the pre-treatment units to reduce
the fluctuation of the waste water and avoiding shock loads
to the activated sludge system; (b) transforming the original
O3 compartment in the anoxic tank and packed compartment
A/ S with the immobilized carriers in different places. Thus,
after most of the organic materials responsible for the aerobic
bacteria are depleted, anaerobic bacteria and facultative bacteria
could become dominant for the degradation of pollutants by the
alteration of the oxygen concentration. The relatively low removal
of TP in the A2O system, on the other hand, might be related to
the relatively high residual nitrate from the anoxic compartment.
By this biodegradation step by step, the diversity of the microbial population and the stability of the community structure would
be improved. The nitrate concentration of the mixed liquor in the
anoxic compartment was as high as 12.4 mg / L, which could be
used as sufficient electron acceptors for the denitrifying bacteria
that use organic substrates. Activated sludge actinomycetes have
recently become the research focus because they are believed to
play an important role in sludge bulking and foaming in activated
sludge plants . Competition between PAO and denitrifying
bacteria for organic compounds could be the main reason
for the weak removal of TP . Microorganisms in different
biological compartments would view its unique functions and the
removal efficiency of pollutants will be improved. The average
of the two IVR systems was 150 l / g (A2O) and 100 l/ g (AO)
respectively. Aside from these negative roles, actinomycetes are
active in the decomposition of organic matter. The diversity of
actinomycetes in both systems suggests that some actinomycetes
could also play an important role in the elimination of the
organic substances. Further investigation, however, is needed
to draw a final conclusion. High temperatures and low DO levels
with the presence of microorganisms previously associated with anaerobic ecosystems found in this study, may explain the
reduced efficacy of treatment. We hypothesize that the increase
of the temperature and the depletion of DO levels create anoxic
micro niches, promoting the growth of anaerobic bacteria, such
as sulfate-reducing bacteria . Among the four populations
analyzed, only ammonia oxidizing bacterial communities
have demonstrated a clear similarity (77.5%) between the
two processes, suggesting that the introduction of anaerobic
compartment has not changed the wealth of AOB populations
significantly. However, when analyzing the DGGE data from
complex environmental samples through several related to DNA
extraction and purification methods , the relative efficiency
of gene amplification  or the PCR inhibition due to the
presence of humic acids and heavy metals , or the impact of artifact bands due to excessive cycles of amplification should be
taken into account. Nevertheless, analysis of bands DGGE profiles
focuses on the numerical analysis of ability to be applied to the
results obtained by molecular techniques. However, as shown
by the results of FISH analysis, the proportion of the total AOB
bacterial numbers in the two systems was very different [3.6
± 0.2% for the system A2O and 1.9 ± 0.2% for the AO system).
Obviously, the A2O system had many more cells than AOB in
the AO system. A previous study  demonstrated that sludge
retention time mainly influenced the total AOBs in activated
sludge systems. But in this study, the two systems had similar
SRT and MLSS. Further studies are necessary in order to explain
this phenomenon completely.
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