Effects of salinity on nitrification efficiency and bacterial community structure in a nitrifying osmotic membrane bioreactor

Accepted Manuscript Title: Effects of salinity on nitrification efficiency and bacterial community structure in a nitrifying osmotic membrane bioreactor Authors: Dawoon Jeong, Kyungjin Cho, Chang-Ha Lee, Seockheon Lee, Hyokwan Bae PII: DOI: Reference:

S1359-5113(18)30521-X https://doi.org/10.1016/j.procbio.2018.08.008 PRBI 11419

To appear in:

Process Biochemistry

Received date: Revised date: Accepted date:

9-4-2018 27-7-2018 2-8-2018

Please cite this article as: Jeong D, Cho K, Lee C-Ha, Lee S, Bae H, Effects of salinity on nitrification efficiency and bacterial community structure in a nitrifying osmotic membrane bioreactor, Process Biochemistry (2018), https://doi.org/10.1016/j.procbio.2018.08.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Effects of salinity on nitrification efficiency and bacterial community structure in a nitrifying osmotic membrane bioreactor

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Graduate School of Water Resources, Sungkyunkwan University (SKKU), 2066,

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Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do 16419, Republic of Korea b

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Dawoon Jeonga, c, Kyungjin Chob, Chang-Ha Leec, Seockheon Leeb, *, Hyokwan Baed, *

Center for Water Resource Cycle Research, Korea Institute of Science and Technology,

39-1 Hawolgok-Dong, Seongbuk-Gu, Seoul 136-791, Republic of Korea

Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-

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Department of Civil and Environmental Engineering, Pusan National University, 63

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ro, Seodaemun-Gu, Seoul 120-749, Republic of Korea

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Busandeahak-ro, Geumjeong-Gu, Busan 46241, Republic of Korea

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Hyokwan Bae

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*Corresponding authors; contributed equally to this work.

Tel.: +82-51-510-2392, Fax.: +82-51-514-9574

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E-mail address: [email protected] and

Seockheon Lee

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Tel.: +82-2-958-5829, Fax.: +82-2-958-5839 E-mail address: [email protected]

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Graphical abstract

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Bacterial population dynamics were studied in an osmotic membrane bioreactor. Ammonia, alkalinity, and salinity caused changes in the bacterial community. Increased salinity led to NOB activity inhibition at 17.3 g-TDS/L. AOB were more tolerant than NOB to the high ammonia-loading rate and salinity. Nitrosomonas eutropha was dominant at high ammonia and salt concentrations.

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Highlights

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Abstract

The objective of this study was to evaluate the effects of salt accumulation on nitrifying bacterial communities in a nitrifying bioreactor combined with forward 2

osmosis. The conversion of nitrite to nitrate was inhibited at a total dissolved solids concentration of 17.3 g/L, whereas conversion of ammonia to nitrite was inhibited at a higher concentration (52.8 g-TDS/L). The gene copies of ammonia-oxidizing bacteria (AOB) were more abundant than those of nitrite-oxidizing bacteria (NOB) throughout

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the entire operating period of 225 days. Among NOB, the number of copies of Nitrobacter spp. were 100 to 1000 times higher than those of Nitrospira spp. A total of

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140 operational taxonomic units were identified using 454 pyrosequencing. The relative abundances of autotrophic AOB and NOB accounted for 34.1–57.8% during 225 days. Dominance of Nitrosomonas eutropha was stable as a salt-tolerant AOB, but the

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representative NOB, Nitrobacter winogradskyi, showed salt-sensitive variations in their

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relative abundance. Nonmetric multidimensional scaling and hierarchical clustering

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analysis clearly illustrated the shift in bacterial community due to external conditions,

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i.e., ammonia loading rate, alkalinity availability, and salinity. Heterotrophic bacteria contributed to changes in overall bacterial community structure in the nitrifying OMBR

Keywords

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despite the absence of carbon sources in the influent.

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Bacterial community dynamics, 454 pyrosequencing, Osmotic membrane bioreactor,

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Salt inhibition, Nitrification

1. Introduction

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Membrane bioreactors (MBRs) involve membrane separation processes, such as microfiltration (MF) or ultrafiltration (UF), coupled with conventional activated sludge systems. High biomass concentration in MBRs enhances biodegradation in biological processes. However, micro-pollutants of low molecular weight cannot be removed using

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MBRs by MF or UF due to limitations of the membrane pore size. The presence of micro-pollutants in treated wastewater not only diminishes water quality but also

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introduces risks to the ecosystem. In addition, the deposition of organic and inorganic

matter on the membrane (i.e., membrane fouling) causes deterioration of MBR performance such as water flux reduction. These problems increase operational and

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maintenance costs.

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To overcome these limitations, osmotic membrane bioreactors (OMBRs) that

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integrate forward osmosis (FO) and a biological process have been developed. Because

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FO is driven by the osmotic pressure difference between the feed and draw sides, it has a low fouling potential and low energy consumption. In addition, high-quality water

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production is achievable due to the non-porous properties of FO membranes and the

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associated removal of micro-pollutants [1, 2]. However, the high rejection rates of FO membranes often result in the accumulation of dissolved solids [3, 4]. Also, reverse salt

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flux (RSF) from the draw solution increases salt concentration in the OMBR [3-5]. In previous study, the concentration of total dissolved solids (TDS) in the OMBR reached 55 g/L for simulated wastewater [6]. In general, saline environments are unfavorable for

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bacterial activities. For example, osmotic pressure enhanced by the high salt concentration leads to cell plasmolysis, resulting in a loss of bacterial activity [7]. Besides, high salt concentrations decrease the dissolved oxygen (DO) concentrations in a bioreactor owing to lowered oxygen solubility According to the previous report, DO 4

concentration is assumed to be reduced by 20% at 20°C, when the salt concentration increases from 0 to 40 g/L [8]. To mitigate the salt accumulation problem in OMBRs, several studies have been focused on the development of draw solution and hybrid system [9, 10]. For example, the use of mixture of MgCl2 and Triton X-114 as draw

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solution resulted in a lower RSF (2.03 g/m2-h) compared with the use of MgCl2 (9.02 g/m2-h) due to adsorption of Triton X-114 [9]. A hybrid OMBR-electrodialysis system

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was effective to alleviate the salinity build-up in OMBR [10].

Nitrification is the sequential biological oxidation of ammonia to nitrate via nitrite by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). This process

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is necessary for biological removal of nitrogen at wastewater treatment plants (WWTPs).

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Nitrification efficiency is dependent on external environmental factors such as

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temperature, pH, DO, salt concentration, and the presence of inhibitory compounds [11,

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12]. In particular, high salt concentrations produced by food, leather, and petroleum industries have negative effects on the bioactivity, bacterial community structure, and

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settling properties of nitrifying bacteria and therefore cause failure of nitrification

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processes [11, 13, 14]. Although almost WWTPs were operated under continuous flow conditions, salt inhibitory effects on bacterial activity were tested in batch mode with

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NaCl-spiking experiments [11, 15, 16]. The toxicity tests using NaCl-spiking in batch mode cannot effectively predict bacterial activity at a WWTP because of the discrepancy in the duration of exposure to toxic compounds between batch and

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continuous modes. For instance, ammonia oxidation inhibitions were 100% and <10% for continuous mode and batch mode at 0.005 mM of Cu2+, respectively [17]. Therefore, the systematic and continuous investigation of the salt accumulation effects on the nitrifying bacterial activity and respective bacterial community is necessary to provide 5

details on nitrifying bioreactor performance and bacterial composition in continuous system. Another key factor is the gradual adaptation of bacteria to high salt concentrations; this approach improves nitrification efficiency [18, 19]. Recently, bacterial population dynamics and nitrification performance under conditions of

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increased salinity were monitored at a low salinity of 18 mS/cm (or a salt concentration of approximately 10 g/L) [3]. Nevertheless, a more delicate analysis in a wide range of

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salinity levels is necessary to understand the nitrification of saline wastewater, which generally contains high salt concentrations of 30–50 g/L (3–5% NaCl).

Information about the functioning of bacterial communities in response to salt

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concentrations is beneficial for improving systems of biological saline wastewater

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treatment and may lead to a more comprehensive understanding of the dynamics of

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bacterial community activities under high-salt conditions. Polymerase chain reaction

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(PCR) with denaturing gradient gel electrophoresis (DGGE) has been used to study bacterial community structure and composition at increased salt concentrations [3, 15,

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20]. However, PCR-DGGE provides incomplete information regarding bacterial

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community structure due to weak band intensity. On the contrary, high-throughput sequencing allows for detection of even minor bacterial groups by generating large

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numbers of sequences. For example, more than 7000 of 16S rRNA sequence reads were retrieved from the activated sludge, which were classified to more than about 1000

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operational taxonomic units (OTUs) [21]. The aim of this study was to investigate the bacterial activity and community

structure in an OMBR. An OMBR consists of a moving bed bioreactor (MBBR) and FO. FO gradually increases the salinity in the MBBR by dewatering. Real-time quantitative polymerase chain reaction (qPCR) was applied to quantify the AOB and NOB, 6

including Nitrobacter spp. (NTB) and Nitrospira spp. (NTS) during the entire operating period of the OMBR (225 days). Bacterial community structures under different operating conditions were compared using 454 pyrosequencing to identify representative

OTUs

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different

operating

conditions.

Nonmetric

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multidimensional scaling (NMDS) was applied to visualize bacterial community structures based on these OTUs. This research improves the understanding of the

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population dynamics of nitrifying bacteria under gradually increasing salinity.

2. Materials and Methods

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2.1. Reactor configuration

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The configuration of a system combining a nitrifying bioreactor and FO has been

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described in another paper [22]. The working volume of this nitrifying bioreactor is 3.5 L. The nitrifying inoculum with 1783.7 ± 16.3 mg-volatile suspended solids (VSS)/L

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was entrapped in poly(vinyl alcohol) (PVA)/alginate gel beads [22]. The PVA/alginate gel beads (diameter 5.98 ± 0.21 mm) were packed at a ratio of 50% (v/v) into the

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nitrifying bioreactor. The DO concentration was maintained at >8.0 mg/L throughout

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the operating period by supplying DO with an aerator at 8 L/min. The bioreactor was fed with synthetic ammonia-rich wastewater (Table S1). Hydraulic retention time (HRT) ranged from 12 to 24 h. The HCO3-C/NH4+-N ratio was utilized as a control parameter

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for partial oxidation of ammonia (i.e., 2 NH4+ → NH4+ + NO2). The bioreactor was covered with aluminum foil to avoid exposure to light. FO was implemented using an active layer–feed water (AL-FW) orientation, in which the active layer of the membrane faces the feed solution, while the support layer 7

faces the draw solution. The flow rates of both feed and draw sides were 1 L/min at ambient temperature. A cellulose triacetate (Hydration Technologies Inc., Albany, OR) membrane was utilized with membrane area of 40.32, 60.48, 80.64, and 100.80 cm2. Draw solutions consisting of 1, 2, or 3 M MgCl2 were applied to gradually increase the

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osmotic driving force against salt accumulation in the nitrifying bioreactor. Replenishment of fresh draw solutions and membrane cleaning were conducted every 2

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days. Membrane cleaning was carried out by air scouring at 5 L/min for 15 min. Detailed operating conditions of the combined system are summarized in Table 1.

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2.2. Analytical methods

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The concentrations of NH4+-N and NO3-N were measured using Kjeldahl nitrogen

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analysis equipment (Kjeltec 1035, Sweden) and NitraVer X Nitrate kits (Hach, USA), respectively. The NO2-N concentration was determined by standard methods [23]. VSS

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and TDS were also measured by standard methods for water and wastewater monitoring [23]. The electrical conductivity of the nitrifying bioreactor was monitored using a

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conductivity meter (Hach, USA).

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The AOB and NOB activities were estimated via calculation of ammonia and nitrite conversion rates: the ammonia loading or conversion rate was multiplied by the proportion of nitrogen components in the effluent from the nitrifying bioreactor, which

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are described in Eqs. 1 and 2, respectively: 𝑘𝑔−𝑁

Ammonia conversion rate (ACR) (𝑚3 −𝑑) =

(𝑁𝑂2− −𝑁)𝐸𝑓𝑓. +(𝑁𝑂3− −𝑁)𝐸𝑓𝑓. + (𝑁𝐻4 −𝑁)𝐸𝑓𝑓. +(𝑁𝑂2− −𝑁)𝐸𝑓𝑓. +(𝑁𝑂3− −𝑁)𝐸𝑓𝑓.

ammonia loading rate × (Eq. 1)

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𝑘𝑔−𝑁

Nitrite conversion rate (NCR) (𝑚3 −𝑑) = 𝐴𝐶𝑅 ×

(𝑁𝑂3− −𝑁)𝐸𝑓𝑓. − (𝑁𝑂2 −𝑁)𝐸𝑓𝑓. +(𝑁𝑂3− −𝑁)𝐸𝑓𝑓.

(Eq. 2)

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2.3. DNA sampling and extraction Randomly picked, PVA/alginate gel bead samples less than 1 mm in size were cut by

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sterilized scissors from the nitrifying bioreactor on Days 1, 27, 83, 93, 106, 113, 128, 147, 152, 167, 195, and 225 (12 samples in total) for DNA extraction. The DNA was extracted using a Power Soil TM DNA Kit (Mo Bio Laboratories, USA). DNA extraction

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was duplicated to minimize analytical errors, and DNA was stored at 80 °C before

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analysis. Detailed descriptions of the selected samples are shown in Table S2.

2.4. Quantification of the nitrifying bacteria

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For quantification of the AOB and NOB including NTB and NTS, qPCRs were run

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in a 20 μL reaction mixture containing 1 μL of a DNA template and 10 μL of TaqMan® Fast Advanced Master Mix (Applied Biosystems, USA) in triplicate. Information on the

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primers, probes, concentrations, and PCR thermal conditions is provided in Table S3 [24-26]. For the AOB quantification, primers CTO 189fA/B and CTO 189fC were used in a 2:1 ratio [24]. All the samples were prepared in 8-strip tubes (Agilent Technologies,

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USA), which were sealed with optical cap strips (Agilent Technologies, USA). The amplification reactions were conducted on an AriaMX Real-Time PCR System (Agilent Technologies, USA) and analyzed by AriaMX 1.0 software (Agilent Technologies, USA). Ten-fold serially diluted standard plasmid DNA samples were prepared to 9

construct standard curves. After each qPCR, concentrations of the 16S rRNA genes were calculated by determining threshold cycles by means of standard DNA concentrations, which were 2.1 × 108, 1.4 × 108, and 2.6 × 107 copies/μL for AOB, NTB, and NTS, respectively. The amplification efficiency (E) values were calculated using the

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equation E = (101/slope)  1. In this study, E values were 100.5% (AOB), 83.8% (NTB),

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and 99.0% (NTS), and all R2 values were above 0.99.

2.5. 454 pyrosequencing

Libraries were constructed at Macrogen Ltd. (Seoul, Korea) on a Genome Sequencer

27F

(5-GAGTTTGATCMTGGCTCAG-3)

and

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(5-

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primers

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FLX plus (454 Life Sciences, USA) according to standard protocols. The 16S universal

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WTTACCGCGGCTGCTGG-3) were used for amplification of the 16S rRNA genes

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targeting the V1–V3 regions. A FastStart High Fidelity PCR System (Roche, USA) was

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used for the PCR under the following conditions: 94 °C for 3 min followed by 35 cycles of 94 °C for 15 s, 55 °C for 45 s, and 72 °C for 1 min; and a final elongation step at

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72 °C for 8 min. After the PCR, the products were purified using AMPure beads (Beckman Coulter, USA). Raw sequences have been deposited into the NCBI Sequence

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Read Archive (SRA) with accession Nos. SRX3410160–SRX3410171.

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2.6. Processing of DNA sequences and statistical data analysis The raw sequences were processed to obtain high-quality sequences as previously

described in previous research [27]. Community richness estimator of Chao1 and diversity estimators of Shannon, and Good’s coverage were generated based on the trimmed sequences. Taxonomic classification down to the phylum, class, order, family, 10

genus, and species levels was assigned using the Silva rRNA database ver. 111. NMDS ordination was performed based on all OTUs in the PC-ORD software ver. 5 (MJM Software, Gleneden Beach, OR, USA); this analysis explains an overall distribution of the bacterial community structure. The Sørenson (Bray-Curtis) distance was applied to

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the NMDS ordination. A heatmap analysis was carried out based on the OTUs with relative abundances >5% using gplots in R-Studio ver. 3.3.1. Redundancy analysis

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(RDA) was applied to observe which operational parameters significantly affected the

change in core genera using the CANOCO 4.5 software (Plant Research International, The Netherlands). In this study, the OTUs with relative abundances >5% were used as

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dependent variables, and operational parameters (ammonia loading rate, salinity, and

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alkalinity) were used as independent variables.

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3. Results

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3.1. Ammonia and nitrite oxidation in the OMBR AOB and NOB activities were monitored for 225 days (Fig. 1a). Although the ACR

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and NCR fluctuated during Stage I, a stable full nitrification was finally achieved at

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2.47 kg-N/m3-d with an ACR and NCR of more than 2.42 kg-N/m3-d with an alkalinity of HCO3-C/NH4+-N = 2 (Fig. 1a). The fluctuation was attributed to the late adaption of nitrifying activity to an increased ammonia loading rate (ALR). At Stage II, partial

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nitrification was achieved by controlling the alkalinity (HCO3-C/NH4+-N = 1). The insufficient alkalinity resulted in a lower pH by limiting the buffering capacity against acidification via ammonia oxidation [28, 29]. Indeed, a pH reduction from 8.4 to 5.0 was observed immediately after the reduction in alkalinity (Table 1). Both the ACR and 11

NCR were steadily maintained at about 1.29 kg-N/m3-d, i.e., ammonia and nitrite oxidation efficiencies of 52%, for 60 days. During Stages III-IX, the salt concentrations in the nitrifying bioreactor increased from 13.6 to 52.8 g-TDS/L by expanding the FO membrane area and increasing the

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draw solution concentration (Fig. 1a and Table 1). NOB activity was continually suppressed to an NCR between 3.6 × 102 and 2.7 × 101 kg-N/m3-d during an increase

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in salt concentration from 17.3 to 52.8 g-TDS/L. In contrast, AOB activity decreased to

an ACR of 0.08 kg-N/m3-d at even higher concentration of 52.8 g-TDS/L. These results reveal that AOB are more tolerant than NOB to high salt concentrations. At Stage X, the

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ALR gradually increased up to 0.25 kg-N/m3-d according to the nitrifying bacteria

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activity without FO integration (Fig. 1b). In this condition, AOB showed better recovery

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3.2. Quantification by qPCR

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than NOB after inhibition.

To quantify the AOB and NOB, the 16S rRNA gene copy numbers throughout the

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entire operating period were analyzed as shown in Fig. 2. During the enrichment period

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of Stages I and II, the number of copies of AOB and NTB subsequently increased from 5.1 × 107 to 8.3 × 109 and from 3.3 × 107 to 3.1 × 109 copies/g-bead, respectively. In comparison, within the NOB groups, the number of copies of NTS was maintained at

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less than 3.8 × 106 copies/g-bead, which is 100 to 1000 times lower than that of NTB for Stages I and II. During the FO integration period, the 16S rRNA gene copy numbers of the nitrifying bacteria did not significantly change, even though the NCR sharply decreased during Stages III–VIII. In addition, a small reduction in 16S rRNA gene copy 12

numbers was observed for AOB, NTB, and NTS at Stages IX and X. This result indicates that an immobilization technique using PVA/alginate was effective in preventing the loss of nitrifying bacteria under the influence of external unfavorable

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conditions.

3.3. An overview of changes in the bacterial community

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High-throughput sequencing was conducted to characterize the bacterial community composition at elevated salt concentrations and better understand bacterial community dynamics. After filtering out low-quality sequences, a total of 75,399 qualified

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sequences and 140 OTUs were obtained. The average sequence length was 316 bp.

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An overview of the obtained NMDS results based on these 140 OTUs is shown in

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Fig. 3a to illustrate the changes in bacterial community structure. The NMDS data

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revealed that bacterial community composition was clearly classified into four groups in accordance with the operating conditions of the OMBR: Group 1, sampled on Day 1,

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consisted of the nitrifying inoculum. Group 2, sampled on Day 27, was sampled during

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full nitrification. Group 3, consisting of samples from Days 83 and 93, was collected under conditions of insufficient inorganic carbon for partial ammonia conversion. The

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ALR and alkalinity differentiated the bacterial community composition between Groups 2 and 3. Group 4 consisted of the other samples from Days 106, 113, 128, 147,

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152, 167, 195, and 225, which were exposed to high salt concentrations. A hierarchical clustering dendrogram is shown in Fig. 3b. This result facilitates

comparison for the bacterial community structure among these four groups in detail. As shown, Node 1 for Groups 1 and 2 can be distinguished from Node 2 for Groups 3 and 4. This observation implies that the ALR can significantly affect bacterial community 13

structure. In Group 4, the sample from Day 225, during an activity recovery period, was classified into a different branch than the samples obtained during the FO dewatering period.

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3.4. The change in bacterial community structure The bacterial community was monitored by pyrosequencing at different ALR,

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alkalinity, and salt concentration to examine responses to OMBR operating conditions.

At the phylum level, a total of 12 phyla are represented in Fig. 4a. Proteobacteria were

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dominant during the entire period, followed by Bacteroidetes and Actinobacteria. The

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relative dominance of Proteobacteria ranged from 46.2% to 71.1% during the entire

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operating period. In particular, Proteobacteria showed the highest relative abundance

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in the Day 1 sample because the nitrifying bacteria in the inoculum were already affiliated with Proteobacteria [30]. The relative abundance of Bacteroidetes steadily

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increased from 9.0% to 41.8% between Days 27 and 83, respectively, and then the population was maintained at more than 36.8% during the period of elevated salinity.

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The relative abundance of Actinobacteria increased from 0.1% to 6.7% until a salt

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concentration of 13.6 g-TDS/L was reached. After Day 93, they showed a tendency to decrease in number under the conditions of increased salinity. Their abundance increased again when the salt concentration decreased to 3.2 g-TDS/L on Day 225.

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Minor groups of Chloroflexi and Ignavibacteriae were found in the Day 1 sample, with relative abundances of 7.7% and 9.9%, respectively. Their relative abundances sharply decreased as the ALR and salt concentration increased. At the class level, 26 classes were classified (Fig. 4b). α-proteobacteria (5.7–24.3%), 14

β-proteobacteria (30.6–54.4%), Cytophagia (0.9–30.6%), and Flavobacteriia (4.8– 35.6%) were dominant. In particular, β-proteobacteria were the most prevalent and accounted for 60.8–89.6% of the Proteobacteria phylum abundance throughout the entire operating period. The relative abundances of α-proteobacteria significantly

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decreased from 24.3% and 12.1% between Stages II and III. In terms of classes belonging to the Bacteroidetes phylum, the relative abundance of Cytophagia rapidly

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increased from 0.9% to 30.6% for 93 days (50–2500 mg-NH4+-N/L and salt concentration <13.6 g-TDS/L). In contrast, their relative abundance decreased, and

then was maintained at less than 15.8% under salt concentrations of more than 20.8 g-

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TDS/L. For Flavobacteriia, the relative abundance rapidly increased with the

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increasing salt concentration up to 29.7 g-TDS/L, and then it slightly decreased at salt

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concentrations above 29.7 g-TDS/L. In addition, Sphingobacteriia were very sensitive

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to the salinity, as shown by their significant decrease in relative abundance during FO

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utilization.

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3.5. Identification of nitrifying bacteria and core genera

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Only fourteen OTUs were affiliated with nitrifying bacteria among all 140 OTUs (Table S4). Twelve AOB OTUs were assigned to N. eutropha, N. europaea, N. communis, and N. stercoris. Only two NOB OTUs were detected: Nitrobacter

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winogradskyi and Nitrolancea hollandica. The sum of the relative abundances of the 14 AOB and NOB OTUs from each sample was 34.1–57.8% (Table S4). Well-known AOB, including N. eutropha and N. europaea, showed different characteristics in this study. N. eutropha was the dominant nitrifying bacterium during the whole operating period, 15

accounting for 22.6–44.1% whereas N. europaea and N. communis disappeared after Day 1 (Table S4). As for NOB, the relative abundance of Nitrobacter winogradskyi was higher than that of Nitrolancea hollandica throughout the entire operating period (Table S4). In

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particular, the relative abundance of Nitrobacter winogradskyi increased from 3.3% to 15.5% at increased ALRs. However, the relative abundance of Nitrobacter winogradskyi

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decreased by half immediately after FO integration (13.6 g-TDS/L), which led to a significant reduction in α-proteobacteria. Subsequently, the relative abundance

remained at similar levels during the FO dewatering process. As soon as the activity

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recovery occurred in Stage X, the relative abundance of Nitrobacter winogradskyi

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increased to more than double that of the Day 195 sample. Nitrolancea hollandica

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belonging to the Chloroflexi phylum disappeared after Day 1.

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Fig. 5 shows thirteen core OTUs with >5% of relative abundance, which accounted for 72.7–96.2% in total 140 OTUs. Only three OTUs (OTUs 2, 4, and 16) were

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identified as nitrifying bacteria among thirteen core OTUs. Increase in the relative

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abundances of OTUs 1 and 5 coincided with the increasing salt concentration during Stages III–IX (Fig. 5). This observation was consistent with RDA result in this study

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that they significantly had positive correlation with salinity (Fig. 6). On the contrary, OTUs 6, 8, and 11 were vulnerable to the high salinity because they disappeared immediately after FO integration, i.e., Day 93, (Fig. 5). This was also supported by

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RDA result that OTUs 8, 11 showed negative correlation with the increase in salinity (Fig. 6). OTUs 3, 7, and 10 were positively correlated with ALR in RDA result. Indeed, the relative abundances of OTUs 3, 7 and 10 in high ALR (Stages II–IX, 2.5 kg-N/m3-d) were higher than that of low ALR (Stage I, <2.5 kg-N/m3-d) in Fig. 5. 16

4. Discussion The bacterial activities and community structure in an OMBR treated high-ammonia wastewater were investigated in this study. Our results showed that NOB are more

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sensitive than AOB to high salt concentrations. This is consistent with a previous study showing that AOB can survive at 0–40 g-NaCl/L while NOB can tolerate 0–10 g-

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NaCl/L [11]. Thus, the salt sensitive property of NOB can be used to selectively inhibit

NOB activity. This is beneficial for providing efficient nitrogen removal because a

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partial nitritation (PN) process, i.e., oxidation of ammonia only to nitrite, can be used as

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an anaerobic ammonium oxidation (ANAMMOX) pretreatment to remove ammonia

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from wastewater. ANAMMOX bacteria oxidize ammonia to nitrogen gas using nitrite as

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an electron accepter under anoxic conditions [31]. A bacterial group is phylogenetically similar to salt tolerant ANAMMOX bacteria; Scalindua genus, which has a stable

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nitrogen removal efficiency of 85% at 0.6 kg/m3-d of nitrogen loading rate (NLR) under the salt concentrations of 0-50 g/L [32]. Due to the characteristics of ANAMMOX

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bacteria, the OMBR-ANAMMOX hybrid system would be a cost-effective nitrogen

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removal process. In a previous study, the optimal operational parameters for selective NOB inhibition were reported, such as low DO concentration, low sludge retention time (SRT), high concentrations of free ammonia (FA) and free nitrous acid (FNA), and

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temperatures above 25 °C [33]. These operational parameters are dependent on the type of feed wastewaters, reactor configurations, and environmental conditions [34-36]. In addition to these parameters, the OMBR system in this study is an alternative method to provide a stable PN process using the difference in threshold salt concentrations 17

between NOB and AOB. Based on the qPCR results, concentrations of the AOB 16S rRNA gene were higher than that of NOB gene during the entire operating period. This could be because AOB have a shorter doubling time, i.e., 7–8 h and 10–13 h for AOB and NOB, respectively

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[37]. Kinetic parameters also affected the NOB composition, including NTB and NTS. NTB are r-strategists, which dominate in a resource-abundant environment. However,

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NTS have a slow K-strategist growth rate when resources are limited [38]. In this study, the sufficient supply of nitrite produced by the high ACR caused the predominance of NTB during Stages I and II. This result is consistent with previous research, which

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showed that NTS (50% ± 5%) are more prevalent than NTB (6% ± 1%) at a nitrite

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concentration of 200 mg/L, whereas NTB (59% ± 4%) dominate over NTS (6% ± 1%)

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at a 500 mg/L nitrite concentration [39]. However, qPCR results did not correspond to

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the nitrifying bacteria activity during Stages III–VIII. In this study, viable and nonviable cells were not distinguished by qPCR, which amplifies DNA of both live and dead cells.

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Therefore, it is necessary to observe bacterial activity at the mRNA transcription level

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for the functional genes of ammonia monooxygenase (amoA) and nitrite reductases (nirK and nirS) according to OMBR operating conditions. The presence of NTS was

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confirmed by qPCR but NTS were not detected in the 454 pyrosequencing. There were two reasons for this observation: 1) a deletion of OTUs related to NTS during Silva data processing because of their short sequence reads, 2) a mismatch of only one or two

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nucleotide bases in the non-targeted 16S rRNA. We hypothesized that the bacterial community structure is affected by the continuous

mode of salt introduction to the system, which was confirmed by 454 pyrosequencing and statistical analysis. The 454 pyrosequencing and statistical analysis results showed 18

that bacterial community structures were significantly affected by operational conditions, such as ALR, alkalinity, and salinity. In terms of bacterial diversity, favorable operating conditions for nitrification, such as low salinity and sufficient alkalinity, increased bacterial diversity. This was supported by the number of OTUs,

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Chao1 and Shannon estimators (Table S5). The highest bacterial diversity was observed as a maximum of OTUs and highest Chao1 and Shannon indexes on Day 27 (Stage I).

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On the contrary, unfavorable operating conditions, such as high salinity and insufficient

alkalinity, decreased the number of OTUs, Chao1 and Shannon estimators (Table S5). However, our results were inconsistent with previous studies, which have indicated that

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adequate dynamics of the bacterial community structure are critical factors for process

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stability because more diversity would provide flexibility in adapting to changes in

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operating conditions [40-42]. Therefore, it is considered that high nitrogen removal rate

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is not always associated with an increase in bacteria diversity. In this aspect, the relationship between bacterial diversity and bioreactor performance should be

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investigated in terms of maximal nitrogen removal rate and resilience to unfavorable

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conditions.

In this study, N. eutropha was more dominant than N. europaea during the entire

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operating period. The difference in the abundance of N. eutropha and N. europaea may be attributed to ammonia tolerance. Indeed, N. eutropha has high tolerance to ammonia, with a maximum level of 8400 mg-NH4+-N/L, whereas the maximum level for N.

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europaea is 5600 mg-NH4+-N/L at pH 8 [43]. Therefore, using enriched N. eutropha holds promise for treating saline wastewater with high ammonia concentrations without a system failure. For the NOB, the dominance of Nitrobacter winogradskyi is due to differences in nitrite tolerance between Nitrobacter spp. and Nitrolancea hollandica, 19

which are >2030 mg-NO2-N/L and <1050 mg-NO2-N/L, respectively [44]. In previous studies, Nitrobacter winogradskyi has been found as a common nitrite-oxidizing species in various types of MBRs, such as a conventional MBR, a moving bed MBR, and an anoxic/oxic MBR [45]. Although a low activity, less than 11% NCR, was observed at

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Stages III to IX (Fig. 1a), the high abundance of Nitrobacter winogradskyi was due to the entrapment technology; using PVA/alginate gel beads protects bacterial community

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from wash-out.

Proteobacteria and Bacteroidetes are common members of freshwater and marine environments [46]. In this study, Proteobacteria and Bacteroidetes dominated over a

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wide range in salt concentrations. This finding is consistent with previous research

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indicating that bacterial communities are dominant to the same level at salinity levels of

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0, 20, and 32 g/L [16]. For Proteobacteria, increases in N. eutropha resulted in the

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dominance of β-proteobacteria under increased salt concentrations, whereas decreases in Nitrobacter winogradskyi led to a substantial decrease in α-proteobacteria due to

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their different threshold salt concentration. This finding differs from the 454

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pyrosequencing results on activated sludge from a sewage treatment plant at approximately 11.0 g/L of salinity [47], where α-proteobacteria were the dominant class

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within Proteobacteria. For the Bacteroidetes in this study, Flexibacter sp. led a slight reduction in the relative abundance of Cytophagia under the increased salt concentration. In comparison, an increase in the relative abundance of Myroides sp. belonging to

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Flavobacteriia contributed to the continued dominance of Bacteroidetes. Previously, Bacteroidetes had been reported to dominate with increasing salt concentration in a submerged fixed-bed bioreactor system for treating urban wastewater [48]. In the previous study, the composition of Bacteroidetes was composed of Flavobacteriia and 20

Bacteroidia at 44.1 g-NaCl/L [48], which is different from our result. The apparent differences in bacterial composition could be due to compositional differences in the feed wastewater, including salt contents and reactor configurations. Although carbon source was not supplied in the influent, several heterotrophic bacteria; Myroides sp.,

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Flexibacter sp., Comamonas sp., Flavobacterium sp., and Ignavibacterium sp. (corresponding to OTUs 1, 3, 5, 7, 8, and 9), were detected in the OMBR. The carbon

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source of the heterotrophs for growth were probably from biopolymers released from autotrophic nitrifying bacteria. This was supported by the presence of dissolved organic

carbon (DOC) in the OMBR, which was confirmed in the previous study [22].

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Especially, OTUs 5 and 7 identified as Comamonas sp. had positive correlation with

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increasing salinity and ALR, which might play a key role for the nitrogen removal in the

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OMBR system because Comamonas sp. were found to be a core bacterium in

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heterotrophic nitrification–aerobic denitrification [49, 50]. The relative abundances of S. macrogoltabida (OTU 6) and Flavobacterium sp. (OTU 8) in the OMBR were depleted

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immediately after FO integration. Inhibition of nitrite oxidation (nitrite to nitrate) by the

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elevated salinity might result in great decrease in their relative abundances because S. macrogoltabida and Flavobacterium sp. are known to use nitrate as the electron

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acceptor for their growth [51, 52]. Therefore, it is concluded that the heterotrophic bacteria contributed to changes in overall bacterial community structure in the nitrifying

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OMBR despite the absence of carbon sources in the influent.

5. Conclusion The bacterial activities and community structure in an OMBR treating high-ammonia 21

wastewater were investigated in this study. NOB are found to be more sensitive than AOB to the conditions of both high ALR and high salt concentration. After the inhibition period, the activity recovery period for AOB is shorter than that for NOB. The response of bacterial community structure to an increased ALR and salinity was

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monitored by 454 pyrosequencing and statistical analysis. Proteobacteria are identified as the dominant phylum, followed by Bacteroidetes and Actinobacteria throughout the

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entire operating period. N. eutropha and Nitrobacter winogradskyi are the major species

related to nitrification among all 140 OTUs. Nonetheless, the detection of Nitrobacter winogradskyi is inconsistent with NCR performance because of the entrapment effect of

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PVA/alginate gel beads. For the heterotrophs, Comamonas sp. are found to play a key

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role for the nitrogen removal in the OMBR. The ALR, alkalinity, and salt concentration

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are responsible for changes in the bacterial community structure in the OMBR system.

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Conflict of interest

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Compliance with ethical standards

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The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any research conducted with human participants or animals

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by any of the authors.

Acknowledgments This research was financially supported by the Korean Ministry of Environment as an 22

‘‘Eco-Innovation Program (Environmental Research Laboratory)” (414-111-011) and the Korea Institute of Science and Technology (KIST) as an “Institutional Research

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Program” (2E27080).

23

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Figure captions Fig. 1. a The dependence of ammonia- and nitrite-oxidizing efficiency on salt concentrations throughout the entire operating period. b AOB and NOB activity recovery during Stage X (days 195–225).

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Fig. 2. The 16S rRNA gene copy numbers of AOB and NOB (classified as NTB and NTS) throughout the entire operating period.

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Fig. 3. A statistical ordination plot based on 140 OTU sequences, a NMDS (stress value = 0.00823, instability value = 0.00001), and b a hierarchical clustering dendrogram.

Node 1 discriminates between Group 1 and Group 2. Node 2 discriminates between

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Group 3 and Group 4.

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Fig. 4. Taxonomic classification of bacterial sequences retrieved from 12 samples, a at

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the phylum level and b at the class level.

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Fig. 5. A heatmap of the relative abundance and distribution based on representative OTUs. The OTU above 5% relative abundance in at least one of the samples was used

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as a threshold to generate the heatmap, i.e., to delete meaningless OTUs.

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Fig. 6. RDA showing correlations between operational parameters (red arrows) and core

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OTUs (blue arrows). P value of the RDA model was significant (p <0.05).

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Fig. 1. a The dependence of ammonia- and nitrite-oxidizing efficiency on salt concentrations throughout the entire operating period. b AOB and NOB activity recovery during Stage X (days 195–225). 32

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Fig. 2. The 16S rRNA gene copy numbers of AOB and NOB (classified as NTB and

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Fig. 3. A statistical ordination plot based on 140 OTU sequences, a NMDS (stress value = 0.00823, instability value = 0.00001), and b a hierarchical clustering dendrogram. Node 1 discriminates between Group 1 and Group 2. Node 2 discriminates between Group 3 and Group 4. 34

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Fig. 4. Taxonomic classification of bacterial sequences retrieved from 12 samples, a at

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Fig. 5. A heatmap of the relative abundance and distribution based on representative OTUs. The OTU above 5% relative abundance in at least one of the samples was used

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ALR

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Salinity

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Alkalinity

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Fig. 6. RDA showing correlations between operational parameters (red arrows) and core

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OTUs (blue arrows). P value of the RDA model was significant (p <0.05).

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Table captions Table 1. Operating conditions of the nitrifying osmotic membrane bioreactor.

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Inf. MgCl2 Volume – + HCO3 - Salt Operation NH4 Conc. of C/NH4+- Conc. Conductivity Membrane Stage time N pH for draw draw N (g(mS/cm) area (cm2) (Days) Conc. solution solution ratio TDS/L) (mg/L) (M) (L) I 1–32 502 0.4–2.0 14.8–24.8 7.5– 2500 8.4 II 33–92 2500 1 2.0–2.3 25.8–26.6 5.0– 5.7 III 93–107 2500 1 13.6– 25.4–34.0 6.0– 40.32 1.0 2 20.8 6.9 IV 107–119 2500 1 20.6– 34.0–38.7 6.0– 40.32 2.0 2 23.8 6.9 V 119–133 2500 1 22.8– 37.0–39.0 6.0– 60.48 1.0 3 25.0 6.9 VI 133–147 2500 1 24.6– 38.2–48.5 6.0– 60.48 2.0 3 29.7 6.9 VII 147–161 2500 1 28.9– 42.3–54.9 6.0– 60.48 3.0 3 35.7 6.9 VIII 161–177 2500 1 21.8– 34.2–51.2 5.7– 80.64 3.0 4 37.3 6.8 IX 177–195 2500 1 21.4– 31.8–66.4 7.0– 100.80 3.0 5 52.8 9.3 X 195–225 50-250 2 0.8–3.2 6.8– 8.0

39