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Comparative pyrosequencing analysis of bacterial community change in biofilm formed on seawater reverse osmosis membrane a

b

a

c

d

In S. Kim , Jinwook Lee , Sung-Jo Kim , Hye-Weon Yu & Am Jang a

School of Environmental Science and Engineering, Gwangju Institute of Science and Technology, 261 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, Republic of Korea b

Monitoring and Analysis Division, Wonju Regional Environmental Office, 171 Dangu-ro, Wonju-Si, Gangwon-do, 220-947, Republic of Korea c

Department of Soil, Water and Environmental Science, College of Agriculture and Life Sciences, University of Arizona, Tucson, Arizona d

Department of Civil and Environmental Engineering, Sungkyunkwan University, Jangan-gu, Suwon, Gyeonggi-do 440-746, Republic of Korea Accepted author version posted online: 20 Jun 2013.Published online: 20 Aug 2013.

To cite this article: In S. Kim, Jinwook Lee, Sung-Jo Kim, Hye-Weon Yu & Am Jang (2014) Comparative pyrosequencing analysis of bacterial community change in biofilm formed on seawater reverse osmosis membrane, Environmental Technology, 35:2, 125-136, DOI: 10.1080/09593330.2013.817445 To link to this article: http://dx.doi.org/10.1080/09593330.2013.817445

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Environmental Technology, 2014 Vol. 35, No. 2, 125–136, http://dx.doi.org/10.1080/09593330.2013.817445

Comparative pyrosequencing analysis of bacterial community change in biofilm formed on seawater reverse osmosis membrane In S. Kima , Jinwook Leeb , Sung-Jo Kima , Hye-Weon Yuc and Am Jangd∗ a School

of Environmental Science and Engineering, Gwangju Institute of Science and Technology, 261 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, Republic of Korea; b Monitoring and Analysis Division, Wonju Regional Environmental Office, 171 Dangu-ro, Wonju-Si, Gangwon-do, 220-947, Republic of Korea; c Department of Soil, Water and Environmental Science, College of Agriculture and Life Sciences, University of Arizona, Tucson, Arizona; d Department of Civil and Environmental Engineering, Sungkyunkwan University, Jangan-gu, Suwon, Gyeonggi-do 440-746, Republic of Korea

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(Received 8 December 2012; final version received 10 May 2013) The change in bacterial community structure induced by bacterial competition and succession was investigated during seawater reverse osmosis (SWRO) in order to elucidate a possible link between the bacterial consortium on SWRO membranes and biofouling. To date, there has been no definitive characterization of the microbial diversity in SWRO in terms of distinguishing time-dependent changes in the richness or abundance of bacterial species. For bacterial succession within biofilms on the membrane surface, SWRO using a cross-flow filtration membrane test unit was operated for 5 and 100 h, respectively. As results of the pyrosequencing analysis, bacterial communities differed considerably among seawater and the 5 and 100 h samples. From a total of 33,876 pyrosequences (using a 95% sequence similarity), there were less than 1% of shared species, confirming the influence of the operational time factor and lack of similarity of these communities. During SWRO operation, the abundance of Pseudomonas stutzeri BBSPN3 (GU594474) belonging to gamma-Proteobacteria suggest that biofouling of SWRO membrane might be driven by the dominant influence of a specific species. In addition, among the bacterial competition of five bacterial species (Pseudomonas aeruginosa, Bacillus sp., Rhodobacter sp., Flavobacterium sp., and Mycobacterium sp.) competing for bacterial colonization on the SWRO membrane surfaces, it was exhibited that Bacillus sp. was the most dominant. The dominant influences of Pseudomonas sp. and Bacillus sp. on biofouling during actual SWRO is decisive depending on higher removal efficiency of the seawater pretreatment. Keywords: Bacillus; biofouling; pyrosequencing; Pseudomonas; seawater reverse osmosis

1. Introduction A number ofstudies have demonstrated that biofouling has strong negative impacts on all membrane filtration systems: it can cause flux decline, shorten the lifetime of the system, and require frequent cleanings and a high energy demand.[1,2] In general, the biofouling development in seawater reverse osmosis (SWRO) systems is associated with the uncontrollable biological growth which may act like biofilms. It is accepted that succession in a bacterial community is led by biotic and physical variables. For instance, bacterial interactions tend to modify their habitat and influence the stability, function, and structure of microbial communities within biofilms.[3] In addition, external environmental variables such as pretreatment variability, pH, pressure, and temperature appear to affect the biofilm development. However, most fouling experiments using labscale reverse osmosis (RO) membrane test unit have been carried out using model foulants (i.e. Pseudomonas sp., alginate) or under more alleviated conditions (300 psi/30 h, 800 psi/35 h, 580 psi/20 h, 170–200 psi/50 h) than those of actual SWRO.[4–8] Furthermore, typical investigations into the composition of microbial communities in SWRO ∗ Corresponding

author. Email: [email protected]

© 2013 Taylor & Francis

processes have focused on the diagnosis of biofouling rather than on how biofouling can be controlled.[9,10] Identification of mechanisms on bacterial adhesion and biofilm formation on RO membrane using the designated microorganisms (i.e. Pseudomonas sp., Mycobacterium sp., Spingomonas sp.) has been reported but cases considering SWRO are very less.[4,11,12] Finally, regardless of many applications of pyrosequencing, there has been no attempt to apply pyrosequencing to analyse the bacterial community change on RO membrane for seawater desalination.[13,14] Therefore, a comprehensive understanding of temporal changes in bacterial community structure and its connection with the process performance of SWRO must be more fully explored. In this study, therefore, we investigated the hypothesis that the SWRO performance is affected by changes in the bacterial community structure. As bacterial cells become more (or less) abundant with biofilm growth, a higher richness of bacterial species or increased activities of predominant biofilm bacteria can account for an increase in extracellular polymeric substances (EPS) production. In order to issue a feasible connection between bacterial

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community change and biofouling, the impact of operational time on change in the community structure on RO membranes and the bacterial colonization during the initial stages of biofilm formation was examined.

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2. Materials and methods 2.1. Characteristics of seawater Seawater was sampled from the intake (longitude 35◦ 13 32N; latitude 129◦ 14 37N) of a SWRO plant. Water samples were taken from 7 m below sea level, and had the following chemical characteristics: 36,420 (±345) mg/L total dissolved solids, 3.4 (±0.3) mg/L total suspended solids, 51.06 (±0.63) mS/cm conductivity, 0.814 (±0.21) nephelometry turbidity unit, 6.03 (±1.9) × 105 cells/mL, and pH 8.03(±0.03) (n = 3). It should be noted that bacterial cell densities in the collected samples were not relatively high compared with other studies; for example, bacterial cells in the northern Gulf of Mexico ranged from 0.4 × 106 cells/mL offshore to 1.0 × 106 cells/mL inshore.[15] For the experiment, the seawater sample was filtered using a 0.2 μm-pore mixed cellulose ester membrane (A020A025A, Advantec, Japan) and pretreated seawater was used as the feed solution in order to make a biofilm using both a lab-scale cross-flow filtration membrane test unit and Centers for Disease Control and Prevention (CDC) biofilm reactor. 2.2.

Biofilm formation on RO membrane using a cross-flow filtration membrane test unit

Prior to performing biofilm formation experiments, a labscale cross-flow filtration membrane test unit (part no. 1142819, GE Osmonics, USA) was disinfected with 0.5% sodium hypochlorite, 5 mM ethylenediaminetetraacetate, 2 mM sodium dodecyl sulphate, 95% ethanol, and deionized (DI) water.[4] After disinfection of the RO test unit, a flat-sheet polyamide RO membrane having an effective area of 140 cm2 was placed in the unit and then rinsed several times with DI water at 20◦ C and 400 psi. A Sepa CF high foulant spacer (part no. 1142819, GE Osmonics) was inserted in the membrane cell. A polyamide RO membrane was obtained from a company in South Korea. The membrane has 99.65% salt rejection at 5200 gallons per day and 86% boron rejection at 32,000 ppm NaCl, 800 psi, 25◦ C, 5 ppm boron, and pH 8; the RO membrane was equilibrated with a 0.2 μm-pore filtered sea salt (40 g/L, Sigma) solution for about 1 h. The biofilm formation experiment was initiated by adding 9 L of 0.2 μm-pore membrane-filtered seawater to a 10 L feed storage tank. The test unit with the RO membrane insert was operated at 702 (±2) psi pressure, 20◦ C, and a 1 L/min cross-flow velocity. Both permeate and retentate were recirculated into the feed storage tank. In order to make time-dependently different biofilm on the RO membrane surface, operational times of 5 and 100 h, respectively,

were applied. As a control, the feed solution of 0.2 μm-pore size-filtered artificial sea salt solution was circulated for 5 h. Note that the flux decline was determined from the measurement of water flux at each permeate sampling time; for conductivity and pH measurements, feed, permeate, and retentate were also sampled at the end of each operational time. Conductivity measurements (EC-40N, ISTEK, Korea) were used to determine salt passage through the RO membrane. After operation, the RO membrane was immediately removed from the test unit and immersed into 30–40 mL DI water. Finally, sonication was applied to extract the foulant deposits that had formed on the membrane surface. Microorganisms in the 1 L seawater sample and in the 10 mL samples extracted from the RO membranes after 5 and 100 h of operation were collected by centrifugation. Microorganism amount of 1 L seawater was comparable with that from RO membranes after 5 and 100 h operations. The total bacterial counts of seawater in the 5 and 100 h samples were measured using 4 -6-diamidino-2phenylindole (DAPI) staining of bacterial cells under confocal laser scanning microscope (CLSM; LSM5, Zeiss, Germany), and the viability of the total counts was determined using a LIVE/DEAD BacLight Staining Kit (L-7012, Molecular Probes, USA); the staining procedure followed instructions provided by the manufacturer. Each 1 μL of SYTO 9 and propidium iodide (PI) was combined and then mixed in 1 mL of the sample solution. The mixture was subsequently incubated in the dark for 15 min and observed under CLSM. About 10 images of the same size were randomly taken using Pascal software (Laser Scanning Microscope LSM5 Pascal version 3.2 SP2, Zeiss, Germany) and then analysed using I-solution software (iMTechnology, Korea) to calculate the number of green or red-coloured cells. Application of the two different dyes resulted in green fluorescence for total cells (live and dead) and red fluorescence for dead cells, due to the presence of SYTO 9 and PI, respectively. For EPS extraction, 10 mL aliquots of seawater from the 5 and 100 h samples were sequentially treated with 0.06 mL of formaldehyde (36.5%) at 4◦ C for 1 and 4 mL of 1 N NaOH 4◦ C for 3 h.[16] Treated samples were then filtered through a 0.2 μm-pore size membrane (A020A025A, Advantec, Japan) in order to remove the bacteria cells. The filtered solution was subsequently used to examine the EPS protein and EPS hexose; the EPS protein was measured using a micro-bicinchoninic acid protein assay kit (Cat no. 23235, Thermo Scientific Pierce, USA) [17] and EPS hexose was analysed using the modified phenol-sulphuric acid method with glucose standards. Procedures of DNA isolation and 16S rRNA gene amplification were carried out for the pyrosequencing analysis. For DNA extraction, a phenol/chloroform extraction and ethanol precipitation were applied followed by bead beating (0.1 mm zirconia/silica beads, Biospec Products, USA). Primers 27F (GAGTTTGATCMTGGCTCAG) and

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Environmental Technology 518R (WTTACCGCGGCTGCTGG) were used to amplify bacterial 16S rRNA gene fragments of seawater and the 5 and 100 h samples. The polymerase chain reaction (PCR) of each sample was undertaken separately. Three different tag sequences were bar-coded to the end of each amplified PCR product for identification. Note that 454 bar code sequences are not shown here. The thermocycling conditions included an initial denaturation step at 94◦ C for 10 min followed by 30 cycles at 94◦ C for 30 s, 55◦ C for 30 s, and 72◦ C for 30 s, with a final extension step at 72◦ C for 5 min. After purifying the PCR products, all products were mixed to obtain the total 16S rRNA gene sequences of seawater and the 5 and 100 h samples, in a single sequencing reaction run. The mixed sample was run on a 454 Life Science Genome Sequencer (FLX, Roche, USA) for pyrosequencing; the sequencing was carried out according to the manufacturer’s instructions. Obtained sequences were subjected to a similarity-based search using the BLAST program (http://www.ncbi.nlm. nih.gov/BLAST/). Before the analysis of pyrosequencing results, low quality, short sequences, and primer sequence were trimmed. The software Mothur [18] was then employed to calculate the number of operational taxonomic units at different cutoffs, draw rarefaction curves, and determine the shared species between samples; note that the rarefaction curve is the number of observed species as a function of the number of samples. The rarefaction curves were subsequently used to estimate the bacterial diversity of seawater in the 5 and 100 h samples. 2.3.

Biofilm formation on RO membrane using an CDC biofilm reactor Bacillus sp. (Firmicutes phylum, KCTC 3872), Pseudomonas aeruginosa (gamma-Proteobacteria subphylum, KCTC 1636), Rhodobacter sp. (alpha-Proteobacteria subphylum, KCTC 12595), Flavobacterium sp. (Bacteroidetes phylum, KCTC 22204), and Mycobacterium sp. (Actinobacteria phylum, KCTC 1466) were obtained from the Biological Resource Centre of the Korea Research Institute of Bioscience and Biotechnology. Bacterial cells were harvested by centrifugation at 12,000 rpm for 3 min, washed three times in 1 × PBS, and resuspended in 1 × PBS to achieve a density of 1 × 108 cells m/L. Bacterial counts were then examined using a CLSM after DAPI staining. As a method to analyse bacteria competition of five strains for colonization on RO membrane, potentialities of restriction fragment length polymorphism (RFLP), realtime PCR and 16S rRNA gene sequencing were examined, respectively. Finally, gene cloning and 16S rRNA gene sequencing were applied in this study. The same RO membrane used for cross-flow filtration membrane test unit was used in this test. For the biofilm formation, RO membranes were cut into 5 × 5 mm2 and attached to polycarbonate coupons using double-sided

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adhesive tape to make only active layer of RO membrane exposed. The coupons with RO membranes were then individually placed in the coupon holder of an annular biofilm reactor (Biosurface Technologies, USA); three coupons per sampling for triplicate measurements were positioned at the top, middle, and bottom of the coupon holder. A sterile reactor was filled with 350 mL of 0.2 μm-filtered sterile seawater containing 0.5% Luria-Bertani broth, and was inoculated with 1 × 108 cells of each microbial strain. The reactor was operated in batch mode with an inner magnetic stirrer for 24 h at 25◦ C and 135 rpm, with sampling of removable RO membranes undertaken at 4, 10, and 24 h. The three pieces of RO membrane obtained at each sampling were immediately immersed in separate 1 × PBS for triplicate measurements. After 24 h operation, another series of three RO membranes were treated with 0.1% NaOH solution for 1 h at room temperature as a cleaner to observe the removal efficiency of biofilm on the membrane surface.[19] Note that all RO membranes sampled at 4, 10, 24, and 24 h with NaOH treatment were stirred and sonicated in 1 mL of 1 × PBS to extract bacteria that had adhered to and grown on the membrane surface. The number of bacteria accumulated in each sample was measured by CLSM after DAPI staining. DNA was isolated from bacterial cells collected from the RO membrane by stirring and sonication. For DNA extraction, a phenol/chloroform extraction and ethanol precipitation were applied followed by bead beating (0.1 mm zirconia/silica beads, Biospec Products, USA). Here, the extracted DNA concentration was measured as 104–210 ng/μL with some impurities since the purity ratio (A260/A280) was less than 1.8. A universal bacterial primer set, 27F and 518R, was used to amplify the 16S rRNA gene from the isolated DNA. The PCR mixture included a PCR premix (AccuPower™ PCR premix kit, K-2010, Bioneer, Korea), 20 pmol of each primer, and 100 ng of the template DNA. Sterile DI water was then added to the mixture, for a final volume of 20 μL. The thermocycling conditions included an initial denaturation step at 94◦ C for 10 min followed by 30 cycles at 94◦ C for 30 s, 55◦ C for 30 s, and 72◦ C for 30 s, with a final extension step at 72◦ C for 5 min. Next, 2 μL aliquots of the total reaction volume were analysed using a gel electrophoresis with 1% (wt/vol) agarose in a Trisacetate-EDTA buffer and stained with ethidium bromide (0.5 mg/L). Bands were then visualized using a Ultraviolet illuminator. Following this visualization, the PCR products were purified to the manufacturer’s guidelines using an AccuPrep™ PCR Purification Kit (Bioneer, Korea), and the purified products were inserted to a pGEM® -T Easy vector (RC001, RBC Bioscience, Taiwan) and the cloning vector was transformed into Escherichia coli DH5α competent cells (RBC Bioscience, Taiwan). Successful recombinant colonies were subsequently screened using a blue/white colour phenotype, and the plasmid DNA of each individual white colony was finally isolated using a plasmid

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purification kit (NucleoGen Inc., Korea), and PCR with a 27F/518R primer set was performed again to amplify the 16S rRNA fragments in the plasmid clones. All amplified 16S rRNA gene inserts were then sequenced using an ABI Prism® BigDye™ Terminator Cycle Sequencing Ready Reaction Kit (Applied Biosystems, USA) and an automatic DNA sequencer (Model 3700, Applied Biosystems, USA); the forward primer 27F was used for sequencing the 16S rRNA gene inserts. Finally, for identification, the partial 16S rRNA gene sequences were compared with the full sequences available in the GeneBank database via a BLAST search.

5h 1.0 Relative permeate flux

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0.8 100 h 0.7

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Time (h)

3. Results and discussion 3.1. Analysis of 5 and 100 h RO membranes Two different cases using a cross-flow RO membrane test unit were performed to induce time-dependent biofilms. One case was terminated at 5 h and another at 100 h (Figure 1). The permeate flux gradually decreased. The flux percentage decreased 9.8% at 5 h and 37% at the end of 100 h. Continuous flux decline from 1.0 to 0.63 was explained by microfiltration pretreatment we only applied, while feed water quality is flexible depending on the pretreatment process.[20] The values (5 and 100 h) studied are representative for practice. First, initial bacterial attachment on surfaces occurs in minutes to hours. After adhesion, over a period of up to several weeks should be elapsed to allow for bacterial colonization and biofilm formation.[21] Second, cleaning RO membrane is recommended when the normalized permeate flux is reduced by 10%.[22] Furthermore, high pressure RO membrane application (> 700 psi) was practically difficult in lab-scale experiments while maintaining its performance over several weeks.[4–8] As a control experiment, artificial sea salt solution was fed into the system and was operated for 5 h. We used a sea salt solution containing neither organic or bio-organic substances but which still had a conductivity of around 51 mS/cm, similar to that of the feed solution used in the 5 and 100 h experiments. During the initial 5 h cross-flow filtration, the 5 and 100 h experiments showed similar trends of permeate flux, whereas there was a small decrease in the control experiment. This result suggests that the flux decline was induced by organic or biological substances present in the feed solution. No significant changes in salt passage (3.2– 4%) or pH (7.6–8.2) were observed at the end of either experiment. Two pieces of the RO membranes removed from the 5 and 100 h experiments were subsequently sonicated to collect either organic or biological substances that had become stacked on the membrane surface. Measurements of biomass accumulation on the 5 and 100 h RO membranes are summarized in Table 1. Accumulation of bacteria through the production of EPS increased during the biofilm development.

Figure 1. Permeate flux decline of two cases (5 and 100 h) using a cross-flow RO membrane test unit. No significant changes in the values of salt passage or pH were observed between two. Table 1. Quantification of bacteria and EPS within biofilms on RO membranes obtained from 5 and 100 h operational times. 5h Total count (DAPI staining) (n = 10) Dead/live (SYTO 9, PI staining) (n = 10) EPS protein (mg 140 cm−2 ) (n = 3) EPS hexose (mg 140 cm−2 ) (n = 3)

100 h

2.71(±0.31) × 107 9.85(±3.45) × 108 84%/16% (±10%) 68%/32% (±15%) 12.48 (±0.05)

19.69 (±2.40)

9.93 (±2.18)

13.80 (±3.13)

CLSM observations via DAPI staining for enumerating the total count indicated that there were 2.71(±0.31) × 107 cells in the 5 h sample and 9.85(±3.45) × 108 cells in the 100 h sample. As total counts varied between 105 and 106 cells/cm2 in foulant layer in all elements of a real RO train, the values measured in this study is quite comparable with practice.[23] The per cent of viable cells in the 5 h sample was 16(±10)% and the 100 h sample revealed a viability of 32(±15)%. More than one log number of bacteria increased and the viability also showed a stronger increase with extended operational time, which means that bacteria adhered to and actively grew on the RO membrane in a time-dependent manner. Measurements of EPS protein and EPS hexose also showed larger amount of biological matters in the 100 h sample. Here, 12.48(±0.05) mg/140 cm2 RO membrane and 9.93(±2.18) mg/140 cm2 of EPS proteins and EPS hexose, respectively, were observed in 5 h sample, whereas 19.69(±2.40) mg/140 cm2 and 13.80(±3.13) mg/140 cm2 were found in 100 h sample (Table 1). Small quantities

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Environmental Technology of EPS DNA (0.14 mg/140 cm2 for the 5 h sample and 0.13 mg/140 cm2 for the 100 h sample) indicated that the bacterial cells were not significantly lysed during the extraction process. Total organic matter in foulant layer was equivalent to 14.7–19.6 mg/140 cm2 membrane area and the proportions of protein and hexose as a percentage of organic matter were 40–80% and 3(±1)%, respectively. Relatively higher protein and hexose values measured in this study were explained by mitigated pretreatment condition. Microfiltration of seawater, a single step of pretreatment applied in this study, made dramatically high flux decline compared with practice. Typically, 30–50% of total organic matters are composed of dried weight of the fouling layer, and about 90% organic matters indicates a severe case of biofouling.[23,24] The results in the table were induced from EPS extraction with formaldehyde and NaOH treatment. When EPS extraction was performed using only sonication (without formaldehyde or NaOH treatment), EPS contents were comparable with the above. 0.15 mg/140 cm2 and 0.18 mg/140 cm2 of EPS proteins and EPS hexose were observed in the 5 h sample, while 0.69 mg/140 cm2 and 2.38 mg/140 cm2 were found in the 100 h sample. Thus, it became clear that the growth of bacterial cells and the increased activity with extended operational time also led to increased EPS. From now on, biofouling propensity was mainly monitored and determined by the measurement of biomass accumulation (the amount of bacteria and EPS). However, it could not be an enough solution because numerous different bacteria participate in the biofilm development

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on RO membranes.[25] Further information about bacterial community and correlation between bacteria species change and EPS production are significantly required for accurate diagnosis of biofouling. Therefore, application of pyrosequencing to biofouling would be the better solution compared with the current monitoring techniques. 3.2. Bacterial diversity of seawater intake The bacterial diversity of the seawater intake, generated from 16S rRNA gene cloning, bacterial isolates, and pyrosequencing, is summarized in Table 2. Note that the data for 16S rRNA gene cloning and isolates were obtained from our previous studies.[26] When the gene cloning and the isolation of bacteria were compared, quite different results appeared. Not only the bacteria were identified, but also the abundance of species described a low correlation among the data sets of three methods due to the low cultivability of microorganisms and high diversity. The most dominant bacterial groups were alphaProteobacteria (53.8%) in the clone library, Firmicute (34.43%) in the isolation method, and gammaProteobacteria (50.75%) in the pyrosequencing method; Roseobacter spp., Marinobacter spp., Pseudomonas spp., and the Bacteriodetes phylum were observed fairly evenly in methods applied. However, Phaeobacter spp., Pseudoalteromonas spp., the Firmicute phylum, and the Sctinobacteria phylum were found in isolated samples but not in cloning libraries. In contrast, bacteria such as Sulfitobacter spp. were identified in cloning samples but not in isolated

Table 2. Bacterial diversity of seawater intake and comparison of 16S rRNA gene sequences from clone library, isolation, and pyrosequencing. Abundance (%)

Alpha-proteobacteria Rhodobacteraceae bacterium Roseobacter spp. Sulfitobacter spp. Phaeobacter spp. Antarcticicola litoralis Others Beta-Proteobacteria Gamma-Proteobacteria Cycloclasticus spp. Colwellia spp. Spongiibacter spp. Pseudoalteromonas spp. Marinobacter spp. Pseudomonas spp. Others Delta-Proteobacteria Firmicutes Bacteroidetes Actinobacteria Unknown Total number of clones, isolates, and pyrosequencing tags

Clone library

Isolation

Pyrosequencing

12.09 7.69 5.49 – – 28.57 –

– 11.48 – 4.92 – 4.92 3.28

0.95 0.94 3.56 0.30 1.17 20.44 0.18

– – – – 1.10 1.10 – – – 29.67 – 14.29 91

– – – 14.75 1.64 3.28 6.56 – 34.43 1.64 13.11 – 61

7.70 4.07 3.58 0.14 0.16 0.03 35.07 0.15 – 1.47 0.29 19.81 9921

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samples. Nevertheless, when the results of pyrosequencing were compared with the bacterial identification obtained by 16S rRNA gene cloning and bacterial isolation, a number of shared bacterial community properties were revealed, except for the Firmicute phylum. Similarly, in a polyphasic approach to investigate the microbial community structure of RO membrane, Low G + C (Bacillus/Chlorstridium) group were present in isolation but not observed in a clone library and fluorescence in situ hybridization (FISH).[27] Ten genera not given in Table 2 (Loktanella, Rhodovulum, Pseudoruegeria, Thalassobilus, Sagittula, Sphingopyxis, Erythrobacter, Jannaschia, Rhizobium, and Sphingobium) correspond to relatively low abundant gamma-Proteobacteria, less than 0.20% of 9921 pyrosequences. Similarly, Neptunomonas, Moraxellaceae, Glaciecola, Shewanella, Oceanospirillaceae bacterium, Psychrobacter, Alcanivorax, Thiohalomonas, Serratia, Microbulbifer, and Cellvibrio genera comprise a very small proportion of gamma-Proteobacteria. Such results describe the complex bacterial diversity and dynamic circulation of organic matter in the seawater habitat. Biofouling potential of seawater intake in RO desalination processes has been studied while focusing on biofilm formation.[28] Since the change of bacterial species association can cause the increase on biofilm resistance to chemical and mechanical treatments, further research on microbial community in SWRO process are significantly needed.[29] However, it is not easy to trace the occurrence and prevalence of biofouling bacteria from seawater intake to a RO unit in practice. 3.3.

Influence of operational time factor on bacterial community structure of RO membrane The structures of the bacteria community of the 5 and 100 h samples were analysed using pyrosequencing methods and compared with that of the seawater sample. It was assumed that the source of bacteria that attach to and form biofilms on the membrane surface originate from the seawater intake of the desalination process. For these experiments, the seawater intake was filtered through 0.2 μm pore-sized membrane to remove microorganisms larger than 0.2 μm, before addition into the feed solution of a lab-scale RO membrane test unit. However, the passage of some bacteria might occur and have a chance to adhere to the surface of the RO membrane. Note that the intent of both the 5 and 100 h operations was to investigate the development process of the structure and diversity of bacterial communities according to varied operational times. A comparison of the results from pyrosequencing is described in Figure 2. Sampling or tag numbers generated from pyrosequencing was 9921 in the seawater sample, 11,713 in the 5 h sample, and 12,242 in the 100 h sample. Community composition was not variable. There are no significant differences between bacterial communities from three samples (p > 0.05). The most abundant bacterial

Seawater

Actinobacteria 0.3%

Bacteriodetes 1.5%

Unknown 19.8% Alpha 34.9% Gamma 64.7%

Firmicutes 0.0%

Proteobacteria 78.4%

n = 9,921

5h Actinobacteria 0.2% Bacteriodetes 0.1%

Unknown 9.5%

Alpha 4.5%

Firmicutes 0.1%

Gamma 95.5% Proteobacteria 90.1% n = 11,713

100 h Actinobacteria 0.0% Bacteriodetes 0.0%

Unknown 5.8%

Alpha 0.4%

Firmicutes 0.0%

Gamma 99.6% Proteobacteria 94.2%

n = 12,242

Figure 2. Composition and percentage of bacterial pyrosequences of seawater and the 5 and 100 h samples. Only comparable bacterial groups among the three samples are shown. Subgroups of Proteobacteria were separately examined in the sector of Proteobacteria.

group was Proteobacteria. It comprised 78.4% of the seawater sample, 90.1% of the 5 h sample, and 94.2% of the 100 h sample. Only Proteobacteria displayed a composition increase; other minor groups such as Actinobacteria, Bacteriodetes, Firmicute, and unknown bacteria diminished in the 5 h sample, while some groups were not undetectable in the 100 h sample. When Proteobacteria

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Environmental Technology was categorized into alpha, beta, gamma, and delta subdivisions, the gamma subdivision accounted for 64.7% of total Proteobacteria, alpha was 34.9%, and others were 0.4% in the seawater sample. Interestingly, the gamma composition showed a continual increase as the operation time was extended; gamma was 95.5% in the 5 h sample and 99.6% in the 100 h sample. Thus, it was determined that the gamma subdivision was the main Proteobacteria composing the biofilm on the RO membrane. The percentage of total gamma-Proteobacteria in abundance increased considerably among samples, as shown in Figure 2. Even so, not all members belonging to gamma-Proteobacteria increased. As a result of the in-depth investigation of the percentage of representative gamma-Proteobacteria, those decreasing and increasing in abundance are summarized in Table 3. The total number of pyrosequencing tags representing gamma-Proteobacteria was 64.7% in the seawater sample, 95.5% in the 5 h sample, and 99.6% in the 100 h sample. Cycloclasticus sp. Phe42 (GQ345342) accounted for 14.60% of the total gamma-Proteobacteria in the seawater sample. In the same manner, Colwellia sp. BSw20968 (GU166136), Spongiibacter sp. JAM-GA14 (AB526337), and Pseudoalteromonas sp. B149 (FN295744) comprised 4.84%, 7.00%, and 0.13%, respectively, of the seawater sample. The composition of these four bacterial strains showed decrease as time increased, as they decreased significantly in abundance percentages in the 5 h sample and were zero in the 100 h sample. Note, however, that there were several bacterial strains that significantly increased

Table 3. Abundance (%) of representative gammaProteobacteria present in seawater and the 5 and 100 h samples. Gamma-Proteobacteria Cycloclasticus sp. Phe42 (GQ345342) Colwellia sp. BSw20968 (GU166136) Spongiibacter sp. JAMGA14 (AB526337) Pseudoalteromonas sp. B149 (FN295744) Marinobacter sp. YKS2 (AB504895) Pseudomonas stutzeri BBSPN3 (GU594474) Pseudidiomarina sp. KYW314 (FJ768737) Others Total number of pyrosequencing tags

Seawater

5 h 100 h

↓

14.60

0.08

0.00

↓

4.84

0.63

0.00

↓

7.00

0.03

0.00

↓

0.13

0.00

0.00

↑

0.00

0.03

5.66

↑

0.00

33.89

26.44

↑

0.00

0.00

8.40

73.42 5032

65.35 10,078

59.50 11,486

Abundance (%) of each gamma-Proteobacteria in the seawater sample was compared with that for the 5 and 100 h samples. Relative increase or decrease is shown as ↑ or ↓, respectively.

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in proportion during operation. Representatives of these strains include: Marinobacter sp. YKS2 (AB504895), Pseudomonas stutzeri BBSPN3 (GU594474), and Pseudidiomarina sp. KYW314 (FJ768737). Marinobacter sp. YKS2 and Pseudidiomarina sp. KYW314 displayed very low abundance levels of less than 1% in the seawater and 5 h samples, though a greater percentage (5.66% and 8.40%, respectively) was observed in the 100 h sample. Similarly, Pseudomonas stutzeri BBSPN3 comprised 0.03% in the seawater sample but changed to around 30% in abundance in the 5 and 100 h samples. It was subsequently posited that Pseudomonas stutzeri BBSPN3 attached and grew faster than any other bacteria on the RO membrane. Considering that their abundance in seawater was very low (0.03%), a higher occupation (about 30%) of Pseudomonas stutzeri on the RO membranes indicated that existence of Pseudomonas sp. passing through a 0.2 μm-pore filter actively contributed to the biofilm formation. Past studies to investigate the bacterial community in RO membrane processes using clone libraries, RFLP and FISH methods showed the most predominance of alphaProteobacteria.[30] Different microbial structures were supported by different feed water properties and pretreatment designs. Also, microbial succession led by different microenvironments on the membrane surface changed the microbial structure and even suggested that the dominant bacteria in mature biofilms were not the result of a feed water origin.[9]

3.4. Rarefaction curve analysis Biofilms developed on RO membranes, after filtration through a 0.2 μm-pore filter, collected at different times (5 and 100 h) had different bacterial community structures. This finding implies that the structure of the bacterial population within biofilms varies over the course of RO operation. Figure 3 presents the rarefaction curves for pyrosequences of seawater, as well as the 5 and 100 h samples. The rarefaction curve was obtained by the number of species as a function of the number of pyrosequencing tags. It is necessary for estimating the richness of bacterial species. Here, a cluster distance value of 0.05 was used to define species, which means that the species were determined at a 95% genetic similarity level. Three different shapes of a given rarefaction curve revealed the species richness for a given number of sampled individuals. The curve of the seawater sample had a steeper slope compared with the 5 and 100 h samples, indicating that a large fraction of the species diversity still remains to be investigated. However, the curves of the 5 and 100 h samples became flatter to the right, thereby implying that their species richness was relatively lower than that of seawater (Figure 3(a)). In this study, we observed detectable changes of bacterial species richness over a range of samples,

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Figure 3. (a) Rarefaction curves for pyrosequences of seawater and the 5 and 100 h samples and (b) the number of species observed and the richness estimates. Species were defined at the 5% difference level (cluster distance of 0.05).

though this richness continually decreased during operation (Figure 3(b)). The species richness of seawater was the highest and that of the 100 h sample was the lowest. In the seawater sample, the number of observed species was 645 and the estimate of total species richness was 1257 for a total of 9921 pyrosequences analysed based on the Mothur software. The observed numbers of the 5 and 100 h samples were 171 and 76, respectively; estimation of the species richness was 229 and 150 for the 5 and 100 h sample, respectively. In comparison with the richness number of the seawater sample, 73.5% losses for the 5 h sample and 88.2% losses for the 100 h sample were calculated. The considerable drop in species richness between seawater and the 5 h sample was caused by 0.2 μm-pore membrane filtration. Furthermore, it was observed that the longer the operation time, the lower species richness becomes. In other words, bacterial competition reduced the bacterial diversity in biofilms on the RO membranes, which would ultimately reach a uniform bacterial composition pattern.

3.5.

Bacterial colonization for the biofilm development on RO membrane When the equal amount of P. aeruginosa, Bacillus sp., Rhodobacter sp., Flavobacterium sp., and Mycobacterium sp. were supplied for biofilm formation on an RO membrane, Bacillus sp. was found to grow the fastest even though its adhesion was the lowest among the bacteria present during the initial phase of the biofilm formation (Figure 4). These bacteria were selected to promote biofouling potentially as they are commonly found on membrane surfaces.[31,32] Bacteria diversity in seawater intake revealed by isolation, clone library, and pyrosequencing (Table 2) also led to the selection of these five strains. Pseudomonas strains have been frequently studied as primary biofouling microorganisms in the RO process for wastewater treatment.[33,34] Bacillus sp. strains or its relatives are also arising as the problematic bacteria since they have been commonly observed in different community structures of biofilms on RO/NF membranes

Environmental Technology 1e+7

1e+6

1e+5

1e+4

4h (b) 100

10 h

24 h

24 h, NaOH

Bacillus sp.

80 Bacterial composition (%)

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Number of cells in RO membrane coupon

(a)

133

Pseudomonas 60 aeruginosa

40 Rhodobacter sp. 20 Others 0 4h

10 h

24 h

24 h, NaOH

Figure 4. (a) Number of total bacterial cells in biofilms extracted from RO membrane coupons (5 × 5 mm2 ) sampled at different times and (b) bacterial composition of five strains (Bacillus sp., P. aeruginosa, Rhodobacter sp. and others) within the biofilms.

used for water treatment.[9,27] Higher hydrophobicity of Bacillus sp. enhanced more cell adhesion on RO membrane.[35] Rhodobacter species were found to be abundantly present in clone libraries of biofouled RO membrane which was sampled from the full-scale RO process in our previous study.[32] However, no other reports exist of dedicated biofouling initiated by Rhodobacter species. Rhodobacter sp., alpha-Proteobacteria genus, possesses an extensive range of metabolic capabilities. Cultureindependent approaches show the most dominance of the alpha-Proteobacteria in seawater while members of the gamma-Proteobacteria are most common when culture methods are used.[36] Flavobacterium sp. belonging to Bacteroidetes phylum is a genus of non-motile and rodshaped bacteria. However, members of the Cytophaga and Flavobacteria genera, such as Flavobacterium sp.

exhibit forms of gliding motility occurs when bacteria are in contact with a solid surface.[36] Several investigators have explored the combined species of biofouling bacteria (i.e. Pseudomonas putida, Sphingomonas sp., Rhodopseudomonas sp., Dermacoccus sp., Microbacterium sp.) to identify the important mechanisms for biofilm formation. Pang and Ridgway examined cell adhesion competition between Mycobacterium and E. coli on RO membrane, but comparison on bacterial colonization of these five emergent species has not been found.[37,38] The total number of cells was less than 1 × 103 in the 4 h sample and 5.3(±2.2) × 104 cells in the 10 h sample. From the 10 h sample, the total cells increased significantly and reached 2.2(±0.3) × 106 cells in the 24 h sample. However, the NaOH treatment decreased the total cells to 1.2(±0.5) × 106 cells (Figure 4(a)).

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To analyse the bacterial composition, four clone libraries potentially containing mixed 16S rRNA gene fragments of the five bacterial species were prepared from the biofilms sampled at 4, 10, and 24, and after the NaOH treatment. The results are shown in Figure 4(b); a total of 38 clones from each library were analysed. Before the clone library analysis, alternative methods such as RFLP and quantitative PCR were examined. However, patterns generated by the RFLP analysis indicated that there were DNA fragments of the similar size, which were actually different sequence so they made differentiation of each strain difficult. Also, the selection of the strain specific primer sets in an effort to perform quantitative PCR was not easy in the mixed bacterial strains. The bacterial composition was then calculated from the number of individual clones divided by the number of total clones. At 4 h, P. aeruginosa adhered to RO membrane predominantly, Rhodobacter sp. ranked second, and Bacillus sp. showed the least composition among the three bacterial groups. However, the composition of Bacillus sp. markedly increased at 10 h and had the highest at 24 h and NaOH treatment. The predominance of P. aeruginosa at the initial phase of biofilm formation, which was 59% at 4 h, significantly decreased to 11% at 10 h due to the comparable occupation of Bacillus sp., though the composition rate of P. aeruginosa recovered to 34% at 24 h; the proportion of Rhodobacter sp. steadily declined. From these results, P. aeruginosa was initially found to adhere to RO membrane, but the presence of even low amounts of Bacillus sp. competed effectively with other bacteria. Furthermore, in the NaOH treatment sample, the proportion of Bacillus sp. increased to 69%, while other bacteria showed a comparable drop. Considering that almost half of the total cells were removed by the NaOH treatment, the increased percentage of Bacillus sp. in bacterial composition indicated that it also had a high level of resistance against chemical disinfection. Hence, Bacillus sp. was regarded as being very competitive in terms of biofilm formation. However, when real seawater passing through a 0.2 μm-pore-sized filter was used for biofilm formation on an RO membrane via a cross-flow test unit, a very small faction of Firmicute phylum (0.1%) was revealed in the 5 h sample, with none present in the 100 h sample. Such results can be explained by the observation that a 99.9% rejection of Bacillus sp. isolates (size = 0.5–7 μm, median = 3.73 μm) occurred through the microfiltration membrane (pore size = 0.1 μm) compared with about 97% rejection of Pseudomonas sp. (size = 0.5–2 μm, median = 1.49 μm).[26] Indeed, microfiltration reduces the biofouling potential by limiting the number of bacteria entering the system, though leak-out has been previously hypothesized in attempts to determine the overall fouling potential of a filtrate.[39] Another possibility is that bacteria could become small due to starvation, thereby allowing it to pass through a microfilter.[40] Therefore, if a comparable amount of Bacillus species are present in the microfiltration permeate due to the reasons

mentioned above, they could have a major role of membrane biofouling. In terms of bacterial colonization for the biofilm development on the RO membrane measured in this study, the attachment of P. aeruginosa was rated higher, but the coexistence of Bacillus sp. and P. aeruginosa promoted their competitive ability for the biofilm formation. To this end, it has been generally accepted that bacterial species dominance varies from facility to facility depending on sitespecific conditions such as feed water quality, temperature, location, and processes.[31] Accordingly, we suggest that the main parameter influencing bacterial populations within biofilms on RO membranes is the availability of bacteria that escapes the membrane pretreatment. 4.

Conclusions

Some further considerations about microbial community structure of biofilm associated with RO membrane biofouling in the seawater desalination process are as follows. First, bacterial richness on the RO membranes steadily decreased during operation and the distribution of specific species became more abundant; the species might originate from the permeate generated during the pretreatment process of seawater intake. The types of bacteria surviving after membrane pretreatment could be an important variable for composing bacteria populations in biofilm, those which ultimately induce significant biofouling in SWRO. As such, it is important to monitor microbial properties before and after the pretreatment process. Second, Pseudomonas and Bacillus competed effectively with other bacteria during the biofilm formation, though Bacillus was more easily controlled using micro/ultrafiltration compared with Pseudomonas. Pseudomonas, which survived the membrane pretreatment, was the fastest-growing bacteria dominating bacterial populations in the biofilms on RO membranes. For this reason, effective control of Bacillus and Pseudomonas needs to be further examined. Since the pyrosequencing analysis targeting fouling layers present on membranes in full-scale RO installations was not carried out, no further conclusion could be drawn between bacterial community change and how to control biofouling. However, the pyrosequencing analysis based on two measurements (5 and 100 h) in a lab-scale experiment provided better insights on bacterial colonization and succession. Finally, since the operational parameters [9,41,42] as well as various physicochemical parameters related to the water treatment system including dissolved oxygen concentration [43] and organic concentration [44] could also affect the microbial community evolution and biofouling, the determination of primary parameters for biofouling should be studied for each water treatment processes. Acknowledgements This research was supported by a grant (07SeaHeroA01-01) from the Plant Technology Advancement Program funded by the Min-

Environmental Technology istry of Land, Transport, and Maritime Affairs of the Korean government. [18]

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