Accepted Manuscript

Biodiversity and Succession of Microbial Community in a Multi-habitat Mem-brane Bioreactor

Bing Tang, Zi Zhang, Xuan Chen, Liying Bin, Shaosong Huang, Fenglian Fu,Huiwen Yang, Cuiqun Chen

PII: S0960-8524(14)00666-XDOI: http://dx.doi.org/10.1016/j.biortech.2014.05.007Reference: BITE 13415

To appear in: Bioresource Technology

Received Date: 18 February 2014Revised Date: 26 April 2014Accepted Date: 2 May 2014

Please cite this article as: Tang, B., Zhang, Z., Chen, X., Bin, L., Huang, S., Fu, F., Yang, H., Chen, C., Biodiversityand Succession of Microbial Community in a Multi-habitat Membrane Bioreactor, Bioresource Technology (2014),doi: http://dx.doi.org/10.1016/j.biortech.2014.05.007

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Essential Title Page Information

Biodiversity and Succession of Microbial Community in a Multi-

habitat Membrane Bioreactor

Bing Tang a, *

, Zi Zhang a, Xuan Chen

a, Liying Bin

a, Shaosong Huang

a, Fenglian Fu

a,

Huiwen Yang a, Cuiqun Chen

a

a School of Environmental Science and Engineering, Guangdong University of Technology,

Guangzhou, 510006, P. R. China

* Corresponding author. Tel. : +86 20 39322295; Fax: +86 20 38457257

E-mail address: renytang@163.com (B. Tang)

1

Abstract: The present study focused on establishing a multi-habitat membrane bioreactor,

as well as exploring its biodiversity and succession of microbial communities. In a long-

term operational period (100 days), the dissolved oxygen level of a local zone within the

bioreactor decreased consistently from the original oxic state to the final anaerobic state,

which led to a continuous succession of the microbial community in the bioreactor. The

results revealed that the biodiversity of the microbial community in different zones

simultaneously increased, with a similar microbial composition in their final successional

stage. The results also indicated that the dominant species during the whole operation were

distributed among 6 major phyla. At the initial operational stages, the dominant species in

the anoxic-anaerobic and the oxic zones exhibited distinguished difference, whereas at the

final operational stage, both zones presented nearly the same dominant microbial species

and a rather similar structure in their microbial communities.

Keywords: Multi-habitat; Membrane bioreactor; Microbial community; Biodiversity;

Succession;

1. Introduction

In wastewater treatment plants (WWTPs) or other bioreactors, sufficient and stable

biomass is a vital factor, which is largely responsible for the quality of the effluent. The

biomass in bioreactors contains many microorganisms, generally forming explicit microbial

communities, and their composition and structure in geographically distributed bioreactors

are highly consistent (Xia et al., 2010). In this regard, a bioreactor (or a WWTP) can be

regarded as an artificial microbial ecosystem, through which mass and energy may be

transferred from the primary to the last trophic level. In terms of microbial ecosystem, a

common viewpoint that has been widely accepted is that if the biodiversity of an ecosystem

2

is higher, then greater stability will be achieved (Enger & Smith, 2012), and thus, effective

and rapid transfer of mass and energy in the system will be accomplished (Ye et al., 2012).

The biodiversity of an ecosystem is closely related to the habitats of the organisms, which

totally depend on the environmental conditions. Therefore, multi-environmental conditions

are favorable for increasing the biodiversity of an ecosystem, which can further improve the

stability of an ecosystem to resist external disturbance. Development of multi-

environmental conditions in artificial ecosystems, such as a WWTP or bioreactors for

treating wastewater, is of primary importance for guaranteeing high quality of effluents

when treating complex pollutants.

The membrane bioreactor (MBR) has been a hotspot in the field of wastewater

treatment and water reuse over the past decade, due to its advantages of combining the cost-

effectiveness of a conventional activated sludge (CAS) process and separation efficiency of

membrane filtration. Previous investigations have confirmed that the advantages of an

MBR for purifying both domestic and industrial wastewater are very obvious in several

aspects, including less excess sludge production, relatively small space requirement,

reduced footprint, and superior effluent quality (Mutamim et al., 2013; Kraume & Drews,

2010; Le-Clech, 2010). The predominant merit of an MBR is the total retention of the

microorganisms by the membrane module, which enables separation of sludge retention

time (SRT) from hydraulic retention time (HRT), making it possible to operate the

bioreactor with very high biomass. This advantage is especially beneficial to the survival

and growth of the microorganisms with long generation cycles, which can greatly improve

the biodiversity of a bioreactor.

3

For optimizing the performance of an MBR, researchers have tried to configure a

combined MBR system to create more complex microbial communities for the convenience

of treating hard-biodegraded pollutants (Qiu et al., 2013; Xia et al., 2012; Yang et al., 2012).

The most frequently used configuration is the arrangement of sequential or alternating

anoxic–oxic (A/O) zone in the reactor (Fernandes et al., 2013; Fu et al., 2009; Mcllroy et al.,

2011). Miura et al. (2007) revealed the relationship between community stability and

reactor performance by comparing a pilot-scale conventional MBR with a hybrid MBR

combined with pre-coagulation/sedimentation process, and found that the configurations of

a system heavily influenced the bacterial community. The A/O-MBR system built by Tan

& Ng (2008) was a bi-chamber pre-denitrification submerged MBR separated by a baffle

plate, the mixed liquor was pumped to circulate between the anoxic and the oxic zones for

achieving nitrification-denitrification of the N-containing substances. The alternate A/O

condition in space was the essential requirement for total N removal, and suitable mixed

liquor recycle ratio and aeration rate were the two controlling factors. On the other hand, Fu

et al. (2009) established a modified A/O-MBR without any circulation, in which

phosphorus (P)-accumulating organisms accumulated, leading to the simultaneous removal

of C, N and P. Li et al. (2010) developed a lab-scale MBR, with an anoxic and an oxic zone

in a single reactor by mounting an air diffuser in the middle of a vertical device. The mixed

liquor was pumped from the oxic to the anoxic zone by a recycle pump. The special

configuration of the reactor and the accumulated biomass within it ultimately led to the

formation of a vertical oxygen gradient, which was responsible for the realization of

nitrification-denitrification.

4

Currently, a consensus has been reached in terms of the relationship between the

microbial community structure and its function; i.e., the microbial community composition

is very important with respect to the way in which the ecosystem functions (Fuhrman,

2009), and also, it is an important factor affecting the operational properties of an MBR

(Teksoy Başaran et al., 2012). In an aqueous environment, the concentration of DO is

generally a limiting factor determining the state of the environment, namely, oxic, anoxic,

or anaerobic environment. The value of dissolved oxygen (DO) entirely determines the

survival state and activity of different species of microorganisms by influencing their

habitats. Such a principle has been widely employed in the traditional bio-techniques, such

as an A/O or anaerobic–anoxic–oxic (A2/O) process, for treating organic pollutants and

nutrients (N and P). Numerous engineering experiences and related scientific investigations

have confirmed that only the complex microbial communities (or microbial ecosystem),

and not the single species of microorganism, can realize the effective degradation of

complex organic pollutants or transformation of N- and P-containing compounds (Han et

al., 2012; Wagner & Loy, 2002). Such a fact greatly emphasizes the importance of

establishing a multi-environment in a single MBR for maintaining a diversified and

complex microbial ecosystem.

It must be noted that all the above-mentioned studies on MBRs had mainly focused on

creating diversified operational conditions by forming alternating aerobic or anaerobic

conditions in a time sequence or space distribution, and that most of them had actually

configured relatively independent aerobic and anaerobic chambers, and recycled the

biomass between them with an external circulating pump. From an ecological viewpoint,

multi-habitat is a pivotal guarantee for the biodiversity of an ecosystem. Such a perspective

5

can be logically transferred for the optimization of the performance of an MBR; in other

words, the formation of a multi-habitat in a single MBR may bring about a novel effect on

the biodiversity and succession of the microbial community. Thus, in the present study, we

proposed that a multi-habitat may be formed in a single MBR by internal circulation and

accumulated biomass. To evaluate the hypothesis, a lab-scale MBR with internal

circulation was designed and set up, whose microbial communities at different zones and

stages were analyzed by using modern molecular biological technique to understand its

biodiversity and successional characteristics.

2. Materials and Methods

2.1 Experimental configuration

An MBR with an effective working volume of 36 L was established by configuring

two half chambers – one chamber, with about one-third of the total working volume, served

as the oxic (“O”) zone and the other acted as the anoxic-anaerobic (“A”) zone. In the “O”

zone, an air diffuser was fixed below the membrane module (hydrophilic PVDF hollow

membrane with a pore size of 0.22 µm and surface area of 0.5 m2) to blow air bubbles for

providing DO and push the mixed liquor upward. In the middle of the “A” zone, a rotator,

connected to a torque sensor, was mounted to provide a mixing condition and drive the

mixed liquor downward. A baffle plate with deflector was set vertically between the “O”

and “A” zones. With the upward and downward flow on two sides and the guidance of the

deflector, an internal hydraulic circulation was formed to impel circulating of the mixed

liquor between the “O” and “A” zones without the need for an external circulating pump.

With the stream guidance of the deflector and under a suitable hydrodynamic condition, an

6

internal circulation for recycling the biomass inside the bioreactor could be steadily

sustained. The complete retention of the microorganisms by the membrane module

accelerated the accumulation of biomass, and increasingly improved oxygen consumption

in the half chamber without aeration, thus creating a multi-habitat in the bioreactor, which

led to diversified and successional microbial communities. The schematic diagram of the

MBR is shown in Fig. 1. The multi-habitat MBR with internal circulation was operated for

100 days, the activated sludge in the bioreactor was sampled at different time interval to

analyze the microbial composition. The daily concentration of MLSS was determined by

averaging the values obtained for both “O” and “A” zones at the same time every day. The

DO concentrations in both “O” and “A” zones were automatically and simultaneously

measured by the DO probes every 10 s, and the daily DO concentration of each zone was

the average value of the corresponding DO concentrations measured on the same day

(0:00–24:00).

2.2 Operating conditions

About 36 L activated sludge, obtained directly from the aeration tank of a local

WWTP (Lijiao municipal wastewater treatment plant, located in Haizhu district,

Guangzhou, China), was put into the used bioreactor as inoculated sludge. The inoculation

concentration was controlled at about 4000 mg/L MLSS as the concentration in the original

aeration tank. The influent was synthetic wastewater obtained by mixing tap water with

concentrated nutrient solution. The concentrated nutrient solution, with the ratio of COD: N:

P at 100: 5: 1, was prepared by dissolving chemically pure glucose (375 mg/L, 562.5 mg/L,

750 mg/L), urea (42.3 mg/L, 63.4 mg/L, 84.6 mg/L) and KH2PO4 (17.6 mg/L, 26.3 mg/L,

35.1 mg/L) in tap water; other nutrients included: 160 mg/L of NaHCO3, 132 mg/L of

7

MgSO4, 12 mg/L of MnSO4⋅H2O, 8 mg/L of CaCl2, and 0.6 mg/L of FeSO4⋅7H2O. The

influent concentrations of COD were controlled at 400 mg/L from 1st to 46

th day, 600 mg/L

from 47th

to 66th day, and 800 mg/L from 67

th to 100

th day, respectively. Under a steady

flow and with a relatively constant quality, the influent from two high water tanks with an

overflow weir was injected into the bioreactor from the bottom of the “A” zone, and a

peristaltic pump connected to the membrane module was used to pump out the effluents

(controlled by a time-relay, 8 min filtration and 2 min pause). To evaluate the influence of

biomass proliferation on the bioreactor performance, no sludge was discharged, except

sampling for analysis during the operating period. The water level in the bioreactor, the

water level in the supply tank, and the water flow from the water supply tank were

automatically controlled by a programmable logic controller, and the operational conditions

are summarized in Table 1.

2.3 Analytical Methods

CODCr, NH4+-N, NO2

−-N, NO3

−-N, TP, TN and MLSS were all measured according to

the standard methods (APHA et al., 2005). The values of DO were automatically measured

and stored every 10 s in a computer by using two DO detectors (JPSJ-605F, INESA, China)

installed in the “O” and “A” zones, respectively. The values of pH were measured by a pH

meter (pH2-S, INESA, China).

2.4 Microbial community Analysis

To analyze the structure and evaluate the succession of the microbial community in

the bioreactor during the operational period, mixed liquor samples were taken

simultaneously from the same position of the “O” and “A” zones after operating for 1, 10,

8

30, 50, 70, and 90 days, respectively. The samples obtained on the first day were the

inoculated sludge, which represented the original community in the bioreactor, and were

labeled as “S.” Other samples represented the microbial community of different

successional stages, which were marked as stage-1, stage-2, stage-3, stage-4, and stage-5,

respectively, and were labeled with the corresponding number; e.g., the samples taken from

the “O” and “A” zones on the 10th day represented the stage-1 microbial community, which

were labeled as “O1” and “A1,” respectively, and so forth. The samples collected from

different zones at various stages were analyzed by PCR-DGGE, and the dominant species

identified on the DGGE bands were chosen for sequence analysis with 16 S rDNA clone

libraries.

2.5 DNA extraction and PCR amplification

DNA was extracted using an E.Z.N.A.TM

Soil DNA Kit (Omega, Bio-Tek, Norcross,

GA, USA) according to the manufacturer’s instructions. For DGGE analysis, 16 S rRNA

gene fragments were amplified from the extracted total DNA obtained from the samples

with 2×PCR MasterMix (Genebase, China) by using the primer set 357f-GC (5´-GC-clamp-

CCTACGGGAGGCAGCAG-3´) and 518r (5´-ATTACCGCGGCTGCTGG-3´). A 40-bp

GC-clamp (CGCCCGCCGCGCGC-GGCGGGCGGGGCGGGGGCACGGGGGG) was

attached to the 5´-end of the forward primer (357f-GC). PCR amplification was performed

in a 50-µL reaction mixture containing 25 µL of 2×PCR MasterMix, 2 µL of each primer

(10 µM), and 1 µL of the template DNA. PCR was carried out in a thermocycler (PTC-100,

Bio-Rad, USA) under the following conditions: initial denaturation at 94°C for 5 min,

followed by 30 cycles of denaturation at 94°C for 30 s, primer annealing at 56°C for 30 s,

9

and primer extension at 72°C for 1 min. A final extension step was carried out at 72°C for

10 min prior to cooling at 10°C. The PCR products were electrophoresed on a 1.2%

(wt./vol.) agarose gel.

2.6 DGGE analysis

The PCR-amplified DNA fragments were separated on polyacrylamide gels (8%,

37.5:1 acrylamide-bisacrylamide) in 0.5×TAE buffer (20 mM Tris-acetate, 10 mM sodium

acetate, and 0.5 mM Na2EDTA; pH 7.4) using a denaturing gradient ranging from 35 to

60% (100% denaturant contained 7 M urea and 40% (v/v) formamide), as described by

Miura et al. (2007). Using 100 ng of the PCR products, DGGE was performed with a

DCodeTM

Universal Mutation Detection System (Bio-Rad, Hercules, CA, USA).

Electrophoresis was initially carried out at 60°C for 20 min at 100 V, and then, for 12.5 h at

80 V. Subsequently, the gel was soaked for 15 min in SYBR Green I (1:10000, Probe,

China), and then visualized with a gel imaging system (UVP, Upland, CA, USA).

2.7 Cloning and sequencing

The targeted bands chosen for sequence analysis were carefully excised from the

DGGE gel with a sterile scalpel. For each selected band, only the middle portion of the

band was excised. Then, the slices were placed in 1.5 mL of sterilized screw-cap

polypropylene tubes, and 40 µL of TE buffer was added to it. The DNA was allowed to

passively diffuse into water at 4°C overnight (Liu et al., 2007). Then, 3 µL of the eluate

was used as template DNA for PCR carried out with the primers and conditions described

earlier (see Section 2.5) for all sludge samples. The PCR products were purified with a

SanPrep Column PCR Product Purification Kit (Sangon, Biotech Co., Ltd., Shanghai,

China), and 5 µL of each PCR product was subjected to agarose gel electrophoresis to

10

check product recovery and estimate product concentration. Furthermore, 5 µL of each

reaction mixture were also subjected to DGGE analysis to confirm the melting behavior of

the recovered band. The remaining PCR products (40 µL) were subjected to sequence

analysis (Sangon Biotech Co., Ltd., Shanghai, China). For nucleotide sequence analysis,

the bands on the DGGE gel were excised, amplified, cloned, and sequenced for identifying

the dominant species. Each unknown sequence was submitted to the Basic Alignment

Search Tool (BLAST) search and verified by comparing with the known sequences in the

National Center for Biotechnology Information (NCBI) database. The phylogenetic tree

based on the 16 S rDNA nucleotide sequences was generated by using MEGA4.1 software

(Kumar et al., 2008).

2.8 Calculation of similarity and diversity indexes

To understand and evaluate the structure and succession of the microbial community

in the “O” and “A” zones of the bioreactor, characteristic parameters such as similarity and

diversity indexes were calculated from the DGGE band profiles. To evaluate the structural

similarity between the microbial communities at different stages, Dice index (Cs) of

similarity, as defined by Eq. (1), was used to quantify the pair-wise community similarity,

as described by LaPara et al. (2002).

)(2

yx

cs SS

SC

+= (1)

where Cs is the Dice index, Sx and Sy are the total numbers of DGGE bands in lane x and

lane y, respectively. Sc is the number of common bands between lane x and lane y. The

values of Cs ranged from 0 to 1, representing no common band and totally identical band

patterns, respectively.

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The biodiversity of the microbial community (species richness) in the bioreactor at

different stages was quantitatively determined by the Shannon-Wiener diversity index (H´)

(Eichner et al., 1999), as defined by Eq. (2):

)log('N

nN

nH ii ⋅−= ∑ (2)

where H ´ is the Shannon-Wiener diversity index, ni is the number of a detected

microorganism (i) to the total communities, N is the total number of microbial species in

the samples.

2.9 Analysis of the successional route of the community

Nonmetric multidimensional scaling (NMDS) analysis is a commonly used tool to

compare the similarity and dissimilarity between two complex systems. By plotting the

NMDS analysis results in time series, a visualized description of the succession of an

ecosystem with the increasing operation time could be obtained. The presence and absence

of DGGE bands in the “A” and “O” zones at the same stage were used to generate a binary

data set. By using this approach, a distance matrix could be obtained to construct a NMDS

map, in which the dotted point represents the community structure of the zone at a given

stage of the bioreactor. The distance between two points indicates the similarity of the

communities, and the connecting lines between the points of the same zone, i.e., “A” or

“O” zone, can be used to visualize the successional route of the community in the

bioreactor.

12

3 Results and discussion

3.1 Biomass Proliferation and formation of multi-habitat in the bioreactor

According to the presented methods, the concentration of MLSS in the bioreactor and

the DO values in both the “A” and “O” zones were measured every day. The results of

biomass proliferation and variation in DO level are shown in Fig. 2.

With complete biomass retention by the membrane module, the biomass gradually

proliferated with time. As shown in Fig. 2, the whole operational period could be

approximately divided into three phases according to the increasing rate of biomass

proliferation. The first phase was from the first day to the 20th day; in this period, the

biomass concentration increased very slowly, indicating that the microorganisms were

adapting to the new environment and that the bioreactor was in the start-up stage with the

differences in the DO level between the “O” and “A” zones ranging from 1.06 to 1.33 mg/L.

The second phase was from the 21st to 80

th day; in this period, the biomass proliferated very

quickly, which led to the obvious decline in the DO values in the “A” zone and increased

difference in the DO level between the “A” and “O” zones. Furthermore, after operating for

more than 50 days, the DO value in the “A” zone decreased to less than 0.2 mg/L. From the

81st day, the third phase commenced, during which the growth of the biomass slowed down,

with more than 13000 mg/L MLSS in the bioreactor, and the DO values in the “O” zone

still remained above 3.1 mg/L. These experimental results demonstrated that the established

bioreactor, with complete retention of the sludge by the membrane module, could

accumulate a considerably higher concentration of biomass than a CAS bioreactor. Large

quantity of DO was consumed in the “A” zone of the bioreactor, which disrupted the

balance between aeration and oxygen consumption in this zone, thus creating a multi-

13

habitat in a single bioreactor. Due to its diversified habitat, this bioreactor was called the

multi-habitat membrane (MHMBR).

3.2 General performance of the MHMBR

For evaluating the general performance of the MHMBR, several conventional water

quality indices, including CODCr, NH4+-N, TN, and TP, were chosen as evaluation

parameters, and their removal efficiency was calculated by considering the difference in the

corresponding index at the inlet and outlet of the bioreactor. The results of the average

removal efficiency of the MHMBR are summarized in Table 2 according to the respective

operational phases.

The removal efficiency of each quality index was its arithmetic average value of the

corresponding operational phase determined based on the daily measurement. The COD

removal was quite steady, with the average removal efficiency over 95% in all the phases.

The removal of NH4+-N and TN presented the same tendency of increase with the extension

of operation time, exhibiting an enhanced effect on removing N-containing pollutants. For

there was no excess sludge discharged during the whole operational period, the P-

containing substances gradually accumulated in the MHMBR, and in the last operational

phase, more and more TP was released in the “A” zone, which obviously lowered the TP

removal efficiency.

3.3 Similarity and its evolution of the microbial communities in the bioreactor

The performance of the MHMBR clearly indicated that a multi-habitat was formed

inside the experimental bioreactor, which was developed primarily because of the

imbalance between the aeration and oxygen consumption caused by the proliferation of

biomass. For further understanding of the similarity and its evolution of the microbial

14

communities in different zones and at various stages of the bioreactor, DGGE method was

used first to detect the species in both “O” and “A” zones, then, the similarity index

between the two inhibits defined by Eq. (1), was quantitatively calculated, with its results

processed by a software (Quantity One 4.6.2, Bio-Rad, USA) to obtain a visual description

of the similarity in the microbial communities. All of the results are shown in Fig. 3.

Fig. 3(a) shows the DGGE fingerprint patterns, in which each band stands for a

microorganism species, and higher gray level denotes greater richness of the corresponding

species. Fig. 3(b) shows the quantitative calculation result in the microbial communities of

the bioreactor. The similarity index was only 0.29–0.34 in the microbial communities

between the inoculated sludge and other operating stages in the MHMBR, which indicated

that the microbial community in the inoculated sludge (S) was very different from that of

the other sludge samples. The inoculated sludge was obtained from a local WWTP, whose

operational conditions were quite different from those of the lab-scale bioreactor; thus, the

microbial community in the reactor markedly changed after 10 days of operation. At stage-

1, the difference in the DO values between the “A” and “O” zones was only about 1.0 mg/L,

which indicated that the “A” and “O” zones were still in a similar aerobic state, thus

resulting in moderate similarity (0.61) in their community structures. After 30 days of

operation of the bioreactor, i.e., stage-2, the DO value decreased to less than 1.0 mg/L in

the “A” zone, whereas it was still more than 3.5 mg/L in the “O” zone. As a result, at this

stage, the microbial communities in the two zones showed a marked difference. However,

at stage-2, the microbial communities in the “A” zone exhibited a moderate similarity (0.5)

with those observed at stage-1 in both “A” and “O” zones, which implied certain continuity

in the community structure among them. At stage-3, after operation of the bioreactor for 50

15

days, the DO values declined to less than 0.20 mg/L in the “A” zone. A higher value (0.81)

of the similarity index at this stage indicated the same tendency of the variation in the

microbial communities between “A” and “O” zones. After stage-3, the similarity index

increased from 0.86 (stage-4) to 0.95 (stage-5), which further confirmed the approaching

trend of the microbial communities between “A” and “O” zones with the increasing

operation time.

3.4 Diversity analysis

The difference in the microbial communities in the “A” and “O” zones at various

stages showed obvious variation. For quantitative evaluation of the biodiversity in different

zones and at various stages of the bioreactor, Shannon-Wiener diversity index (H´) was

used. All the indices (H´) were calculated using Eq. (2) based on the number and relative

intensity of the bands on the gel strip, and the results are shown in Fig. 4.

From the primary community (inoculated sludge) to the last stage (stage-5), the

microbial community diversity in different zones of the bioreactor generally presented an

increasing tendency. At the initial three stages, the values of H´ in the “A” zone increased

relatively faster than those in the “O” zone. At stage-4, H´ slightly decreased in both “A”

and “O” zones, when compared with stage-3, the values in “A” and “O” zones were

gradually closer to each other. At stage-5, the biodiversity in both “A” and “O” zones was

exactly the same and was higher than that observed at stage-4, which indicated that the

microorganisms got totally adapted to the alternate anaerobic–aerobic conditions and

formed a mature and diversified community.

16

3.5 Succession of the microbial community

As the proliferation of biomass, the dominant species in both “A” and “O” zones were

gradually changed, which led to the succession of the corresponding microbial community.

For the purpose of visualizing the succession of the microbial communities in both “A” and

“O” zones, a NMDS analysis was used here with the results shown in Fig. 5.

In the experimental bioreactor, a continuous succession of the microbial community

occurred from the primary community to stage-5. The inoculated sludge (S) represented the

original community, and its structure was the same in both “A” and “O” zones. After

operating for 10 days (stage-1), the microbial communities in the “A” and “O” zones

presented an obvious variation, and were different from those of the inoculated sludge,

indicating that succession started with the growth of the biomass. At stage-2, the value of a

key limiting factor (DO) reached its turning point in the “A” zone, i.e., the DO value

declined to less than 1.0 mg/L. The large variation in the DO value in the “A” zone had a

great influence on the succession of the microbial community, leading to an obvious

difference in the structure between the “A” and “O” zones. From stage-3 to stage-5, the

biomass in the bioreactor continuously increased, resulting in a constant decrease in the DO

value to less than 0.1 mg/L in the “A” zone, which in turn, caused the microbial community

to reach a successional state in both “A” and “O” zones. Nevertheless, an interesting

phenomenon also occurred in these stages – the microbial communities in the “A” and “O”

zones gradually tended to exhibit a similar structure along with the successional process.

3.6 Cloning library

The established phylogenetic tree shown in Fig. 6 reveals the dominant species

observed in the MHMBR.

17

In this study, a total of 19 different bands of samples from different zones at different

stages were picked from the DGGE gels. The results showed that the dominant species

were distributed among 6 main phyla: Proteobacteria (nine species), Bacteroidetes (four

species), Chloroflexi (two species), Actinobacteria (one species), Firmicutes (one species),

and Acidobacteria (one species). In addition, an uncultured bacterial clone was also

detected among the 19 bands. Obviously, the predominant species was Proteobacteria,

which comprised Alpha-, Beta-, and Gammaproteobacteria, and a similar finding was also

reported by Wan et al. (2011).

The performance of a bioreactor is totally dependent on the dominant species and the

so-composed microbial community. As shown in Fig. 6, Proteobacteria was frequently

detected during the whole operational period. The sequence of band 22, which was detected

at all stages, was grouped into Alphaproteobacteria. Members of Alphaproteobacteria are

known for their ability to degrade chlorophenol and dichlorophenoxy acetic acid,

metabolize thiophene-2-carboxylate of phenanthrene- and S-containing substrates, and are

polycyclic aromatic and xenobiotic degraders (Rani et al., 2008). The sequences of bands 3,

14, 15, and 16 were grouped into Betaproteobacteria, and were related to Methylibium sp.,

Sphaerotilus sp., Leptothrix sp., and Sphaerotilus natans, respectively. Among them,

Methylibium sp. has been reported to play an important role in N compound removal (Iasur-

Kruh et al., 2010), this is also an important reason of achieving a high efficiency of

removing N compound in the presented bioreactor. Furthermore, Leptothrix sp. and

Sphaerotilus sp. are filamentous bacteria, whose appearance generally indicates the sludge

bulking phenomenon in a CAS system. However, in the present experiments, no obvious

sludge bulking phenomenon was observed, which demonstrated the capability of a

18

MHMBR to control sludge bulking. Wagner & Loy (2002), Xia et al. (2012) and Yan et al.

(2009) reported that Betaproteobacteria represented the most abundant group in activated

sludge, and Snaidr et al. (1997) found that Betaproteobacteria was the main group in the

aeration basin of a municipal sewage plant; thus, these findings suggest the importance of

this group in wastewater treatment. In the present study, the sequences of bands 8, 9, 18,

and 19 showed high similarity to Cellvibrio sp., uncultured Gammaproteobacterium,

Thiothrix eikelboomii, and Ewingella sp., respectively, all of which belong to

Gammaproteobacteria and are known for their degradation properties. Cellvibrio sp. is an

aerobic bacterium, and was only detected in the inoculated sludge and became weak or

invisible at other stages. T. eikelboomii has been reported to play a role in the

biodegradation of S-containing compounds. Nakamurella multipartite, corresponding to the

sequence of band 1, belongs to Actinobacteria, and was detected from stage-3 to stage-5.

Actinobacteria are well known for their secondary metabolite product – actinomycin. The

sequence of band 11 was grouped into Firmicutes and affiliated to Bacillus funiculus. B.

funiculus is a strict or facultative aerobic bacterium, and was only detected at stage-1,

which was consistent with the fact that during the start-up of the operation, the DO

concentration in both “A” and “O” zones still remained at a higher level. The sequences of

bands 6 and 12 belonged to Chloroflexi. Strains of Chloroflexi are obligate or facultative

photosynthetic filamentous bacteria, and most of them can not only survive under anaerobic

conditions, but also under aerobic conditions. The sequence of band 17 was affiliated to

uncultured Acidobacterium. Acidobacteria is generally considered to dominate the

phosphate-removing sludge population (Jeon et al., 2003), and its ability of phosphate

removal is also confirmed by the experimental results. In addition, the sequences of bands

19

5, 13, 20, and 21, which were detected in the late stage of operation, belonged to

Bacteroidetes. Among them, band 13 showed high similarity to uncultured Cloacibacterium

sp. Rani et al. (2008) reported that Bacteroidetes mainly degrades polycyclic aromatic

hydrocarbons and refractory biomacromolecules. Some strains of Bacteroidetes have also

been observed in other wastewater treatment bioreactors (Qiu et al., 2013; Wan et al.,

2011). These results and related analyses confirmed that the multi-habitat formed in the

bioreactor provided suitable conditions for the survival of many useful species, suggesting

its prospective application in purifying refractory organic pollutants.

4 Conclusions

This study presented a lab-scale investigation of a MHMBR, which was developed

with internal circulation and accumulated biomass. The formed multi-habitat provided

suitable conditions for various microorganisms. The proliferation of biomass in the

MHMBR directly led to continuous successions with similar tendency in different zones

and at various stages. The results of PCR-DGGE and 16 S rDNA clone library confirmed

that the bioreactor comprised diverse microbial species, and that the dominant species

included bacteria that are very useful in wastewater treatment. These results implied that

MHMBR could be a high-efficiency bioreactor to remove N-containing substances and

complex organic pollutants.

Acknowledgements

This research is funded by the National Natural Science Foundation of China (No.

51178120). The authors also want to thank Prof. Chaohai Wei and Prof. Yuan Ren from

South China University of Technology for their kind help in technical support.

20

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24

Figure Captions

Figure 1. Schematic diagram of the experimental configuration.

Figure 2. Biomass proliferation and variation of DO in the bioreactor. (“A”: anoxic-

anaerobic zone; “O”: oxic zone).

Figure 3. Comparison of bacterial 16S rDNA gene community fingerprints in “A” and “O”

zones of the MHMBR. (a: DGGE fingerprint patterns; b. the corresponding dendrogram,

the scale bar indicates the percentage similarity at the nodes).

Figure 4. Biodiversity in the bioreactor at different zones and stages.

Figure 5. NMDS map showing the succession in the community structures at different

zones and stages.

Figure 6. Phylogenetic distance tree representing the affiliation of the 16 S rDNA clone

sequences retrieved from the samples at different zones and stages.

25

Figure 1.

26

Figure 2.

0 10 20 30 40 50 60 70 80 90 1000.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5Phase IIIPhase IIPhase I

DO

(m

g/L

)

Time (day)

DO value in "A" zone

DO value in "O" zone

The time points to increase

the influent concentration

4000

6000

8000

10000

12000

14000

ML

SS

(m

g/L

)

MLSS

27

Figure 3.

(a) (b)

28

Figure 4.

0 1 2 3 4 52.45

2.50

2.55

2.60

2.65

2.70

2.75

2.80

2.85

Shan

no

n-W

ien

er d

ivers

ity I

nd

ex

Stage

A zone

O zone

Inoculated sludge

29

Figure 5.

-2 0 2-2

0

2

Dim

en

sio

n 2

Dimension 1

S

A1

O1

A2

O2

A3

O3

A4O4

A5

O5

30

Figure 6.

Band 8

Cellvibro sp. (GQ324994)

Band 9

Uncultured gamma proteobacterium (HQ691968)

Band 18

Thiothrix eikelboomii (NR024758)

Band 19

Ewingella sp. (GU944495)

Gamma Proteobacteria

Band 22

Uncultured alpha proteobacterium (KF411728)Alpha Proteobacteria

Band 3

Methylibium sp. (JX402638)

Band 15

Uncultured Leptothrix sp. (JF808730)

Band 14

Sphaerotilus sp. (FM886883)

Band 16

Sphaerotilus natans (AB680432)

Beta Proteobacteria

Proteobacteria

Band 1

Nakamurella multipartita (NR074442)Actinobacteriaphy

Band 4

Uncultured bacterium clone (AY675970)

Band 11

Bacillus funiculus (HE610879)Firmicutes

Band 6

Uncultured Chloroflexi (AB638624)

Band 12

Uncultured Chloroflexi bacterium (AB810232)

Chloroflexi

Band 17

Uncultured Acidobacteria bacterium (JQ795231)Acidobacteria

Band 5

Uncultured Bacteroidetes bacterium (AB611225)

Band 20

Uncultured Bacteroidetes bacterium (FJ828418)

Band 13

Uncultured Cloacibacterium sp. (KC006353)

Band 21

Uncultured Bacteroidetes bacterium (GU074133)

Bacteroidetes

100

100

100

100

100

100

100

100

99

99

98

98

98

94

98

90

81

65

96

93

92

86

80

64

49

27

55

32

26

65

40

50

66

78

96

0.02

31

Table 1 Operating conditions

Parameter Value Parameter Value

Operating time (d) 100 HRT (h) 3.6

Temperature (0C) * 26.5 (23.1-32.0) SRT (d) 100

pH * 7.5 (7.1-8.0) Flux (LMH, L/m2 h) 21.7

Aeration rate (L/min) 1.0 Rotate speed (rmp) 65

*: Numbers are means (minimum and maximum values)

32

Table 2 Average removal efficiency of the MHMBR at different phases (%)

Quality index Phase I (1st - 20

th day) Phase II (21

st - 80

th day) Phase III (81

st - 100

th day)

CODCr 95.2 96.4 96.8

NH4+-N 80.3 84.8 89.8

TN 78.5 80.2 85.5

TP 67.1 63.3 56.9

33

Graphical Abstract

0 10 20 30 40 50 60 70 80 90 1000.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5Phase IIIPhase IIPhase I

D

O (

mg/L

)

Time (day)

DO value in "A" zone

DO value in "O" zone

4000

6000

8000

10000

12000

14000

ML

SS

(m

g/L

)

MLSS

Proliferation of biomass → Viration of DO values → Succession of microbial communities

34

� A combined membrane bioreactor without an external recycling pump was presented.

� A multi-habitat was successfully established in a single membrane bioreactor.

� The microbial community and its succession in the bioreactor were revealed.

� The biodiversity increased along with the succession of the microbial community.

� Dominant species during the operation were mainly distributed among 6 major phyla.