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Biofouling of reverse-osmosis membranes under different shear rates during tertiary wastewater desalination: Microbial community composition Ashraf Al Ashhab, Osnat Gillor*, Moshe Herzberg* Zuckerberg Institute for Water Research, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben-Gurion 84990, Israel

article info

abstract

Article history:

We investigated the influence of feed-water shear rate during reverse-osmosis (RO) desalina-

Received 22 March 2014

tion on biofouling with respect to microbial community composition developed on the mem-

Received in revised form

brane surface. The RO membrane biofilm's microbial community profile was elucidated during

4 September 2014

desalination of tertiary wastewater effluent in a flat-sheet lab-scale system operated under high

Accepted 6 September 2014

(555.6 s1), medium (370.4 s1), or low (185.2 s1) shear rates, corresponding to average velocities

Available online 17 September 2014

of 27.8, 18.5, and 9.3 cm s1, respectively. Bacterial diversity was highest when medium shear was applied (ShannoneWeaver diversity index H' ¼ 4.30 ± 0.04) compared to RO-membrane

Keywords:

biofilm developed under lower and higher shear rates (H0 ¼ 3.80 ± 0.26 and H0 ¼ 3.42 ± 0.38,

Biofouling

respectively). At the medium shear rate, RO-membrane biofilms were dominated by Betapro-

Reverse osmosis

teobacteria, whereas under lower and higher shear rates, the biofilms were dominated by

Municipal wastewater

Alpha- and Gamma- Proteobacteria, and the latter biofilms also contained Deltaproteobacteria.

Biofilm

Bacterial abundance on the RO membrane was higher at low and medium shear rates compared

Shear rate

to the high shear rate: 8.97  108 ± 1.03  103, 4.70  108 ± 1.70  103 and 5.72  106 ± 2.09  103

Microbial community composition

copy number per cm2, respectively. Interestingly, at the high shear rate, the RO-membrane biofilm's bacterial community consisted mainly of populations known to excrete high amounts of extracellular polymeric substances. Our results suggest that the RO-membrane biofilm's community composition, structure and abundance differ in accordance with applied shear rate. These results shed new light on the biofouling phenomenon and are important for further development of antibiofouling strategies for RO membranes. © 2014 Elsevier Ltd. All rights reserved.

1.

Introduction

There is a growing need to develop advanced treatment processes for the reclamation of municipal wastewater as a

potential water source using various technologies. Reverseosmosis (RO) desalination is becoming widely used for the reclamation of tertiary treated wastewater (TWW), resulting in water of very high quality (Pearce, 2008; Radjenovic et al.,

Abbreviations: BEOP, biofilm enhanced osmotic pressure; CP, concentration polarization; EPS, extracellular polymeric substances; OTU, operational taxonomic unit; RO, reverse osmosis; S0 , richness estimator, Chao1; H0 , ShannoneWeaver diversity index; TWW, tertiary wastewater; UF, ultrafiltration. * Corresponding authors. Tel.: þ972 8 6563520, þ972 8 6596986; fax: þ972 8 6563503. E-mail addresses: [email protected] (A. Al Ashhab), [email protected] (O. Gillor), [email protected] (M. Herzberg). http://dx.doi.org/10.1016/j.watres.2014.09.007 0043-1354/© 2014 Elsevier Ltd. All rights reserved.

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2008). RO desalination is efficient, but suffers from a major technical drawback e membrane fouling during the process (Baker and Dudley, 1998) e consisting of biofilm formation on the membrane beyond the threshold of economical operation of the system, termed biofouling. Biofouling is caused by the deposition, attachment and proliferation of microorganisms on the RO membrane surface, forming a biofilm structure. This layer creates additional resistance to water flow and prevents effective mixing in the feed solution adjacent to the membrane surface (Flemming and Schaule, 1988; Pang et al., 2005); this enhances concentration polarization (CP) of nutrients on the membrane surface, in turn facilitating faster biofilm growth (Herzberg and Elimelech, 2007a, 2007b). Increasing the feed's linear flow velocity adjacent to membrane surface has been proposed as a means of reducing the biofouling layer (Melo and Bott, 1997; Vrouwenveder et al., 2009). Moreover, the flow regime has also been found to shape biofilm morphology: elevated shear rates result in a more compact biofilm structure, whereas a thick and fluffy biofilm is produced when the shear rate is reduced (Vrouwenvelder et al., 2010). Consequently, further studies showed easier removal of biofilms as the shear rate was reduced during biofilm formation (Vrouwenvelder et al., 2011). Despite these effects on biofilm morphology and structure, the effect of cross-flow velocity on the bacterial composition of the ROmembrane biofilm has never been elucidated. RO wastewater-desalination plants apply a spectrum of shear rates during the RO process, resulting in associated effects on biofouling and its consequences. A previous study by our group showed that elevated shear rate induces fouling and selects for a more adhesive layers of extracellular polymeric substances (EPS) during the desalination of tertiary effluents (Ying et al., 2013). These results obviously depend on the concentration of the organic compounds, serving as direct foulants as well as nutrients for microbial growth on the membrane (Ying et al., 2014). Recent studies that investigated biofilms on RO membranes desalinating tertiary TWW indicated the supremacy of Alpha- and Beta- Proteobacteria (Ayache et al., 2013; Ivnitsky et al., 2007). Other studies pointed the supremacy of Alphaand Gama- Proteobacteria over Betaproteobacteria in tertiary TWW (Pang and Liu, 2007; Chen et al., 2004). Al Ashhab et al. (2014) showed that Proteobacteria dominate 72% of an RO membrane biofilm with Betaproteobacteria relative abundance exceeding Alpha- and Gama- Proteobacteria. The discrepancy in the relative abundance of the subclasses of Proteobacteria may be related to the operational conditions, such as shear rate, water chemistry or membrane surface properties (Habimana et al., 2014). Alternatively, such differences could be due to the techniques used to analyze the bacterial community composition; most of the studies mentioned above were restricted as the bacteria community coverage was very limited (depicted by clone libraries) and deep sequencing was not used resulting in partial and thus contradicting results (Mardis, 2008). Here, we used next generation sequencing to evaluate bacterial abundance, diversity and community composition in RO-membrane biofouling layers developed under different hydrodynamic shear rates. We hypothesized that different

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shear rates, within the spectrum of those commonly applied in desalination processes (Glueckstern et al., 2008), would significantly affect the RO-membrane biofilm and create a different microenvironment that would mediate selection for different bacterial communities.

2.

Materials and methods

2.1.

RO-membrane unit operation

A laboratory-scale RO unit was fed with TWW effluents from ultrafiltration (UF) permeate of a hybrid growth membrane bioreactor as reported previously (Ying et al., 2013). A commercial thin-film composite RO membrane, ESPA-1 (Hydranautics, Oceanside, CA, USA), was used as a model membrane and placed in a rectangular (7.7 length  2.6 width  0.3 height cm) flow cell without using spacer for the biofouling experiments, the RO system flow diagram was reported in our previous publication (Al Ashhab et al., 2014). The RO membrane was compacted with deionized water for 12 h under a constant pressure of 15 bar with different cross flow velocities corresponding to the different experiments (see below). The RO unit was operated continuously till the permeate flux decreased to 60% of its initial permeate flux value (46.1 L m2 h1) under a constant pressure of 10 bars and under different average cross-flow velocities of 27.8, 18.5, and 9.3 cm s1 by changing the feed flow rate between 25, 50 and 75 L h1 that was associated with different shear rate values of 555.6 s1 (high), 370.4 s1 (medium) and 185.2 s1 (low), respectively, calculated according to Vanoyan et al. (2010). Biofouling experiments were performed in three separate replicates for each shear-rate condition (Figs. S1eS3). Upon the end of each experiment, the RO system was cleaned with 0.1% Sodium hypochlorite for 1 h and rinsed twice with deionized water. Then, the RO system was cleaned with 0.5 mM EDTA pH 11.5 for 4 h and rinsed twice with the deionized water prior to the next use.

2.2.

Sampling

2.2.1.

TWW (RO feed water)

RO feed water (100 L) were collected in four sterile 25 L plastic containers at the beginning, first week, second week and the end of each experiment. The RO feed water were combined and concentrated to approximately 100 mL using a disposable UF F200NR filter (Fresenius Medical, Bad Homburg, Germany), and stored at 4  C until DNA extraction, within 24 h (Al Ashhab et al., 2014).

2.2.2.

Fouled RO membrane

At the end of each experiment, 0.5 cm2 of the fouled RO membrane was collected and stored at 80  C for DNA extraction.

2.3.

Chemical analyses

Samples from both RO permeate and feed water were collected at all stages of each experiment. The experiments were conducted continuously until the flux decline reached

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60% of the original flux (Fig. 1) and major parameters, i.e., permeate flow rate (measured in mL s1), salt rejection (calculated according to Eq. (1)), dissolved organic carbon and pH were monitored daily. DOC was analyzed using Teledyne Tekmar Apollo 9000 TOC analyzer (Mason, OH): Triplicates of the feed water and permeate samples were filtered (0.22 mm) prior to the DOC analysis. Salt rejection ¼ 100 

1

Conductivitypermeate Conductivityfeed

! (1)

A low level of dissolved organic carbon rejection (~80%) was observed for the RO membrane, possibly due to organic contaminants in the tubing in addition to low limit of the dissolved organic carbon detection in the permeate solution. The dissolved oxygen concentration in the feed reservoir of the RO unit varied from 5.0 to 5.9 mg L1 pH varied between 6.5 and 7.4. In addition, permeate and feed water were sampled twice a week and analyzed for anion and cation composition,   3 2 including NHþ 4 , NO2 , NO3 , PO4 , SO4 , and total P using standard methods (American Public Health Association, 1998), and Naþ, Kþ, Ca2þ, Mg2þ and Cl using inductively coupled plasmaoptical emission spectrometry (ICP-OES).

2.4.

Microbial analyses

2.4.1.

DNA extraction

Total nucleic acids were extracted from a 0.5-cm2 piece of the biofouled RO membrane and from 100 mL of concentrated feed water (Angel et al., 2011). The extracted total nucleic acids (100 mL) were incubated at 37  C for 30 min with 1 mL RNase and then the mixture was cleaned using MoBioPowerSoil™ DNA Isolation Kit (Bioneer, Seoul, S. Korea) according to the manufacturer's protocol.

2.4.2.

Real-time PCR

Real-time quantitative PCR (qPCR) was used to amplify rRNAencoding genes using primer pair 341F and 519R (Table S1).

Samples were run in triplicate in 25 mL reaction mix containing: 12 mL DyNAmo Flash SYBR Green mix (Finnzyme, Espoo, Finland), 6 mL of 200 nM of the primers, 2 mL of 10e20 ng mL1 templates, and 5 mL molecular-grade water. The reaction was performed in a real-time PCR machine (Thermo Hybaid Sprint, Ashford, UK) under the following conditions: activation at 96  C for 5 s, and 40 cycles of 95  C for 10 s, 58  C for 15 s, 72  C for 20 s. The number of DNA fragments in each sample, reflecting bacterial abundance, was estimated based on calibrated fragment numbers amplified from a known number of Escherichia coli genomes as previously described (Bachar et al., 2010).

2.4.3.

2.4.4.

Sequence analysis

Screening for high-quality sequences, alignment, chimera detection and PCR noise removal were performed with the Mothur software package (Schloss et al., 2009). Sequences with a minimum length of 100 bases and an average quality score of 25 were retained prior to sequence alignment. All sequences were aligned based on the SILVA bacterial reference alignment (http://www.arb-silva.de/), and screened for those with less than 50 bp matched alignment. After alignment, sequences were screened for possible chimeras and these were removed from the dataset using the chimera.slayer algorithm implemented in Mothur. PCR noise was removed by Single Linkage Preclustering, as described previously (Huse et al., 2007).

2.4.5. Operational taxonomic unit (OTU) richness and diversity estimates Bacterial ShannoneWeaver diversity index (H') (http://ww. mothur.org/wiki/Shannon) and species richness estimator Chao1 (S) (http://www.mothur.org/wiki/Chao) were calculated in Mothur based on an OTU distance matrix constructed with the classify.otu command in Mothur. Different OTUs were assigned to sequences with an evolutionary distance of at least 0.03 (or less than 97% 16S rRNA gene sequence similarity) with the dist.seqs and average neighbor cluster command in Mothur.

2.4.6.

Fig. 1 e Permeate flux decline at constant transmembrane pressure (10 bars) and temperature (25 ± 0.2  C). The initial permeate flux was 46.1 L m¡2 h¡1. Cross-flow velocity was 9.3 cm s¡1 (185.2 s¡1), 18.5 cm s¡1 (370.4 s¡1) and 27.8 cm s¡1 (556 s¡1) for low, medium and high shear rates, respectively.

PCR amplification and sequencing

Extracted DNA (50 ng) was sent to the Research and Testing Laboratory (Lubbock, TX, USA) for sequencing of bacterial 16S rRNA-encoding genes based on tag-encoded FLX amplicon pyrosequencing (Dowd et al., 2008) to examine the bacterial populations in the RO matrices.

Assessment of community composition

Bacterial sequences were classified using the classify.seqs command in Mothur, based on the SILVA reference taxonomic file (http://www.mothur.org/wiki/Silva_reference_files). Each taxonomic group was identified down to the family level, and relative abundance was set as the number of sequences affiliated with that taxonomic level divided by the total number of sequences per sample.

2.5.

Statistical analysis

The differences between the bacterial communities in the ROmembrane biofilm samples and RO feed water were tested

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Table 1 e Characteristics of tertiary effluents and RO permeate in the fouling experiments. Analyses were performed in triplicate and the mean ± SD is reported for all experimental points. UF permeate (mg L1)

Component

DOC (mg L1) NH 4 (as N) Cl NO 2 (as N) NO 3 (as N) PO3 4 (as P) SO2 4 (as S) Naþ Kþ Ca2þ Mg2þ Total P Conductivity

RO permeate (mg L1)

Low shear

Medium shear

High shear

Low shear

Medium shear

High shear

Low shear

Medium shear

High shear

~5e6 5.1 ± 0.9 90.0 ± 5.8 0.5 ± 0.2 146.2 ± 24.6 3.9 ± 0.5 69.5 ± 12.6 80.2 ± 12.4 12.9 ± 5.2 45.2 ± 4.1 11.8 ± 2.1 5.4 ± 3.1 669.6 ± 32.1

~5e6 6.2 ± 1.2 95.1 ± 10.3 0.3 ± 0.1 153.0 ± 40.1 3.6 ± 0.6 72.3 ± 22.3 83.3 ± 22.9 14.1 ± 4.9 50.1 ± 5.6 12.1 ± 3.8 6.3 ± 0.4 632.3 ± 26.3

~5e6 6.4 ± 0.9 96.5 ± 7.3 0.2 ± 0.1 155.6 ± 27.5 3.2 ± 6.4 68.6 ± 18.5 77.8 ± 14.3 12.5 ± 5.0 51.8 ± 6.4 13.2 ± 3.2 5.9 ± 0.3 710.2 ± 29.0

~1e1.5 0.6 ± 0.2 1.2 ± 0.6 0.0 ± 0.0 13.2 ± 1.2 0.5 ± 0.0 2.0 ± 0.1 7.8 ± 1.8 1.5 ± 1.6 0.9 ± 0.2 0.2 ± 0.1 0.1 ± 0.2 32.9 ± 10.3

~1e1.5 1.1 ± 0.3 5.8 ± 0.9 0.0 ± 0.0 15.2 ± 1.8 0.1 ± 0.0 2.2 ± 0.4 8.0 ± 2.3 2.4 ± 1.2 1.2 ± 0.2 0.4 ± 0.2 0.2 ± 0.2 35.5 ± 12.0

~1e1.5 1.0 ± 0.3 2.5 ± 0.5 0.0.±0.0 14.6 ± 2.0 0.2 ± 0.0 1.5 ± 0.2 6.8 ± 1.4 1.9 ± 0.9 1.0 ± 0.1 0.3 ± 0.1 0.1 ± 0.2 37.5 ± 5.9

~80 87.5 98.7 99.8 91.0 91.7 97.2 90.2 88.1 98.1 98.2 97.7 95.1

~80 82.0 94.0 99.0 90.0 99.0 97.0 90.0 83.0 98.0 97.0 95.0 94.0

~80 84.3 97.4 97.9 90.6 96.4 97.8 91.2 85.1 98.0 97.4 95.7 94.7

using pair-wise analysis of similarity (ANOSIM) based on BrayeCurtis distance matrixes at the class level using R statistical computing (http://www.r-project.org/). Nonmetric multidimensional scaling (NMDS) was performed based on the same distance matrix to generate a cluster analysis using PC-ORD (McCune and Mefford, 1999).

2.6.

Percent rejection (%)

Accession numbers

Sequences found in this study were submitted to the MGRAST system (http://metagenomics.anl.gov/) under accession numbers (4553012.3).

3.

Results

3.1.

Chemical analysis and patterns of flux decline

Table 1 shows the chemical analyses of the RO feed water and permeate. Rejection of the different ionic species by the RO membrane varied between 82.0 ± 5.8% and 99.1 ± 0.6%, while total salt rejection throughout the experiments was 93.3 ± 5.9%. pH values of the feed water and permeate for all experiments varied between 6.5 and 7.4. Fig. 1 shows the normalized permeate flux decline at different shear rates from three representative experiments (all replicates are presented in the supplementary information, Figs. S1eS3). In the first stage of fouling (the first 2 days of RO unit operation), the medium shear resulted in the highest fouling rate (based on the rate of permeate-flux decline) compared to low and high shear-rate conditions. During the second stage of fouling, from day 2 onward, at low shear, 60% flux decline was observed after 13.5 ± 0.7 days, whereas at high and medium shear, 60% flux decline was observed after 15.6 ± 0.1 and 19.6 ± 1.5 days, respectively. To assure that permeate flux decline is only affected by shear rate conditions, rather than variability in the composition of the organic fraction in the RO feed water, the RO feed water was analyzed using liquid chromatographyeorganic carbon detectioneorganic nitrogen detection (LCeOCDeOND) in our previous study (Ying

et al., 2014), in which the percentage of different fractions (biopolymers, proteins, humic substances, building blocks, low molecular weight neutral compounds) did not change significantly with time (Ying et al., 2014). Hence, the MBR system was operated under very stable conditions for at least six months prior to the beginning of this study and the same treated TWW, i.e., UF permeate of the MBR, was injected as feed water to the RO fouling experiments. Another evidence for the robust quality of the RO feed wastewater, are the reproducible permeate flux decline profiles for each of the shear rate conditions (Figs. S1eS3), in which the fouling propensity of the RO membrane is exclusively dependent on the shear rate applied. For all the three fouling experiments operated at different shear rates, ATR-FTIR spectra was acquired (Supplementary information, Fig. S4) and a typical spectra of conditioned RO membrane with organics originated from the treated TWW was observed, similar to previous publications (Ying et al., 2013, 2014). Significant adsorption can be seen in the supplementary information (Fig. S4), where both nucleic acids and polysaccharides give rise to the broad complex band centered at 1041 cm1 as well as bands region located at 1700e1500 cm1, probably attributed to proteins. These spectra correspond to the protein content in treated TWW (Supplementary information, Table S2). The amide I band originates from C]O stretching vibration of peptide groups in proteins, whereas the amide II band includes NH bending and CeN stretching vibration. Broader and more distinct bands indicative for proteins and polysaccharides were also observed for the second biofouling stage, in our previous publications (Ying et al., 2013 and Ying et al., 2014). Succession of membrane fouling followed by biofilm growth was studied previously by Khan et al. (2013) showing similar initiation of RO biofouling by adsorption of humic acids in seawater desalination.

3.2.

Microbial analysis

A total of 18,188 high-quality bacterial 16S rRNA-encoding gene sequences were recovered in this sampling effort, with an average of 2021 ± 1174 sequences per dataset (Table S3). The rarefaction curve (Fig. S5) showed some leveling off,

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indicating that the libraries were representative of the biofilm and the estimations of microbial diversity are likely to be accurate. Pairwise analysis of similarity on the distance matrix for the bacterial classes' diversity showed significant differences among the bacterial communities of the RO-membrane biofilms developed under different shear rates (P < 0.001). Further analysis using NMDS generated different clusters based on different bacterial community similarities (Kruskal, 1964; Kenkel and Orloci, 1986). The analysis showed separate clustering of the bacterial communities in the RO feed water and RO membrane. Biofilms that developed under different shear rates also clustered separately (Fig. 2).

3.3. Effect of different shear rates on bacterial abundance and diversity in RO-membrane biofilms 3.3.1.

Bacterial abundance at different shear rates

Bacterial abundance in biofilms developed under low, medium and high shear rates were different and the highest abundance was detected in the biofilm developed under low shear rate, followed by the biofilms developed under medium and high shear rates, respectively (Fig. 3).

3.3.2.

Fig. 3 e Bacterial abundance in RO-membrane biofilm developed under low, medium, and high shear rates. Yaxis indicates the average log10 16S rRNA-encoding gene copy number cm¡2 of three replicates.

Bacterial diversity estimates under different shear rates

To better understand the bacterial diversity in the biofilm that developed on the RO membrane under different shear rates, we evaluated the communities' abundance and evenness of species distribution using H' and the communities' occurrence and richness using S (Magurran, 1988). Similar diversity of the RO-membrane biofilm bacterial communities was found under low (H0 ¼ 3.80 ± 0.26), medium (H0 ¼ 4.30 ± 0.04) and high (H0 ¼ 3.42 ± 0.38) shear rates. In contrast, species richness was higher under the medium shear rate (S ¼ 536 ± 21) than under low (S ¼ 350 ± 13) or high (S ¼ 365 ± 5) shear rates.

gene sequences for each of the bacterial communities developed under the different shear rates. The RO-membrane biofilms developed under low, medium and high shear rates supported bacterial communities composed mainly of Proteobacteria (74.8 ± 7.0%, 71.5 ± 8.3% and 81.5 ± 4.0%, respectively), with some Bacteroidetes (16.1 ± 2.9%, 16.6 ± 5.8% and 12.2 ± 1.9%, respectively), whereas the relative abundance of the Actinobacteria (5.8 ± 2.2%, 8.4 ± 3.4% and 2.7 ± 1.6%, respectively) and Acidobacteria (3.2 ± 1.3%, 3.5 ± 2.3% and 3.7 ± 1.4%, respectively) was lower (Fig. 4).

3.3.3. Bacterial community composition in RO-membrane biofilm developed under different shear rates

3.3.3.1. RO-membrane biofilm developed under low shear rate.

To characterize the dominant bacterial phyla, we classified the OTUs taxonomically based on their 16S rRNA-encoding

Fig. 2 e Clustering analysis of bacterial classes in ROmembrane biofilms developed under low (L), medium (M) and high (H) shear rates and in the water (W) feeding the RO unit. Axes 1 and 2 explain 80% and 17%, respectively, of the variability in the data. The numbers (1, 2 and 3) stand for the first, second and third independent replicates of each experiment.

The RO-membrane biofilm developed under low shear rate was dominated by alpha- and gama- Proteobacteria (50.8 ± 9.8% and 14.4 ± 5.1%, respectively), followed by the Betaproteobacteria (9.5 ± 4.2%); Deltaproteobacteria was found at less than 1% (Fig. 5A). The main orders within alphaproteobacteria were Sphingomonadales (23.8 ± 3.8%) and Rhizobiales (21.3 ± 4.5%). More than 95% of the Sphingomonadales members belonged to the family Sphingomonadaceae, whereas the Rhizobiales members belonged to the families Bradyrhizobiaceae, Hyphomicrobiaceae, Methylocystaceae and Rhizobiaceae in similar abundance. The Gamaproteobacteria were mainly constituted of the orders Pseudomonadales (7.1 ± 1.7%), Legionellales (4.2 ± 1.6%) and Xanthomonadales (3 ± 1.7%), with members belonging to the families Pseudomonadaceae, Legionellaceae and Xanthomonadaceae, respectively.

3.3.3.2. RO-membrane biofilm developed under medium shear rate. RO-membrane biofilms developed under medium shear rate were dominated by the subclasses Alpha- and Beta- Proteobacteria (25.7 ± 1.5%, and 26.2 ± 2.3%, respectively), followed by the Gamaproteobacteria (18.7 ± 3.6%); Deltaproteobacteria accounted for less than 1% (Fig. 5B). The main order within the

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biofilm, the Bacteroidetes, was composed mainly of members of the class Sphingobacteria (14.8 ± 3.1%).

3.3.3.3. RO-membrane biofilm developed under high shear rate.

Fig. 4 e Phylum distribution of the bacterial biofilm community developed on the RO membrane at low, medium and high shear rates. All numbers indicate percentages of the total sequences.

Betaproteobacteria was Burkholderiales (26.1 ± 4.2%), whose members belonged mostly to the family Comamonadaceae. The Alphaproteobacteria were mainly made up of the orders Rhizobiales (9.8 ± 1.8%) and Sphingomonadales (9.7 ± 2.8%), while the Gamaproteobacteria were dominated by the orders Pseudomonadales (7.4 ± 1.2%) and Xanthomonadales (4.3 ± 2.1%). The second-most abundant phylum on the RO-membrane

RO-membrane biofilms developed under high shear rate were dominated by Alpha-, Beta-, Gamma- and Delta- Proteobacteria (39.6 ± 5.4%, 11.3 ± 3.4%, 17.7 ± 2.1% and 12.9 ± 3.6%, respectively) (Fig. 5C). The main orders within Alphaproteobacteria were Sphingomonadales (17.9 ± 6.3%) and Rhizobiales (15.1 ± 4.5%); most of the Sphingomonadales members belonged to the family Sphingomonadaceae, while Rhizobiales members belonged to the families Bradyrhizobiaceae, Phyllobacteriaceae and Methylocystaceae in similar abundance. The Betaproteobacteria consisted mainly of the order Burkholderiales (9.1 ± 2.2%) dominated by the family Comamonadaceae. The Deltaproteobacteria were dominated by the order Myxococcales and the family Cystobacterineae, while Gamaproteobacteria consisted of the order Xanthomonadales dominated by the family Xanthomonadaceae.

4.

Discussion

Different shear rates significantly changed the biofouling rate of the RO membrane (Fig. 1). In this section, the different effects of shear rates on organic fouling (first stage, Fig. 1) and biofilm growth (second stage, Fig. 1) on the RO membrane will be discussed. Organic fouling usually dominates the

Fig. 5 e Deep sequencing and taxonomic analyses elucidating the phylum, subphylum and order distribution of the bacterial biofilm community developed on the RO membrane at low (A), medium (B) and high (C) shear rates. All numbers indicate relative abundanceof the total sequences.

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Table 2 e General effects of shear rate on organic fouling (1st stage) and biofouling (2nd stage) during the desalination of treated TWW. Shear rate, s1 (average velocity, cm s1)

CP effect

Organic loading effect

1st Stage: Actual fouling rate and possible reasons

2nd Stage: Actual fouling rate and possible reasons

High:555.6 (27.8) Medium:370.4 (18.5)

Decrease

Increase

Medium fouling e highest organic loading but lowest CP Lowest fouling e combination of CP and organic loading

Low:185.2 (9.3)

Increase

Decrease

Lowest fouling e lowest CP Highest fouling e combination of CP and organic loading Medium fouling e lowest organic loading but highest CP

beginning of TWW-desalination experiments. Such fouling results from the adsorption of dissolved organic matter from the UF permeate onto the RO-membrane surface (Ying et al., 2013). We previously showed (Ying et al., 2013) that biofilm growth on the RO membrane occurs after the drastic decrease in permeate flux during the first days of operation, as seen here (Fig. 1). Changing shear rates can affect the adsorption of organics (Ying et al., 2013) to, and growth of sessile communities on the RO-membrane surface. Adsorption of organics is known to increase at higher shear rates (Welty et al., 2009) due to the thinner hydrodynamic boundary layer and shorter distance for diffusive mass transfer of solutes to the surface that will eventually become organic adsorbate (foulant). However, in the case of RO membrane, rejected solutes adjacent to the RO membrane are polarized, with the highest concentration near the membrane surface. High shear rates will reduce the concentration of the polarized solute near the membrane surface and may reduce adsorption of organics to the membrane, if such adsorption is concentrationdependent. On the other hand, organic loading rate, induced at high shear rate, will enhance organic fouling if (i) the adsorption of organics to the membrane is instantaneous, (ii) the adsorption process is not reduced at lower solute concentration (due to smaller CP at higher shear rate), and (iii) membrane surface area does not limit adsorption. In addition to these foulant loading and CP effects on adsorption (Fig. 1, first stage), shear can also influence the rate of biofilm growth (i.e., the later stages of membrane fouling, Fig. 1, second stage) in two ways: (i) when the biofilm is nutritionally limited, increased shear rate will reduce CP and may limit microbial growth; on the other hand, (ii) elevating shear will increase the organic loading rate on the membrane surface and associated biofilm. If the growth of the biofilm is limited by the concentration of the organics (common to oligotrophic environments such as UF permeate), and mass transfer of nutrients to the biofilm is not limited (good mixing in the RO channel), then elevated shear will likely reduce biofilm growth due to reduced nutrient concentration. If the growth of the biofilm is not limited by (i) the concentration of organic compounds and (ii) mass transfer (good mixing in the RO channel), increasing organic loading rate (and shear rate) into the RO channel will likely enhance biofilm growth. . Table 2 summarizes the effects of shear rate on organic fouling and biofouling schematically in the context of the experiments conducted in this study. In the first stage of the fouling process, fouling rate was highest at medium shear rate and lowest at the high shear rate (Fig. 1). The increase in shear rate reduces CP such that lower concentrations of organics are adsorbed to the membrane surface. On the other hand, at low

Highest fouling e highest CP (nutritional effect)

shear rate, CP is higher but is probably not sufficient to provide the membrane with organics as the organic loading rate to the RO membrane is reduced, limiting the organic fouling rate. The highest fouling rate observed at the medium shear rate is probably due to the combination of sufficiently high CP and sufficient organic loading rate to the membrane surface. We attempted to link between permeate flux decline and foulant loading on the membrane at the first fouling stage. Hence, the total organic carbon dissolved from the fouled membranes provide similar trend of fouling rate shown in Fig. 1during the first fouling stage (Supplementary information Table S2). Interestingly, the total amount of accumulated polysaccharides and proteins during the first fouling stage did not follow the trend of permeate flux decline of the different fouling experiments, probably due to the majority humic acids present in the treated TWW, which abolish membrane swelling and reduce membrane permeability as shown in our previous publication (Ying et al., 2014). The second biofouling stage is dominated by microbial biofilm growth. Thus, effects of biofilm growth, translated to permeate-flux decline, are observed at the second biofouling stage (Fig. 1). As already mentioned, the decrease in shear rate increases the CP of nutrients that, in this case, will enhance biofilm growth on the membrane surface (Herzberg and Elimelech, 2007a; Herzberg et al., 2010). Thus, at low shear rate, the elevated CP enhances the second stage of biofouling. On the other hand, at the highest shear rate, when CP is reduced, the biofouling rate slows (Fig. 1) and biomass is at its lowest level (Fig. 3). The increased organic loading rate (due to higher flow rate through the RO channel) is counteracted by the reduced CP, resulting in decreased biofouling. The lowest biofouling rate observed in the second stage of biofilm growth was under medium shear rate (Fig. 1). Since fouled membranes were collected when similar flux decline of 60% was observed for all the three experiments (and not after similar experimental period), the final amount of accumulated biomass (Fig. 3) on the biofilm is not indicative to the rate of biofilm growth. The relatively high biomass content observed at the end of the medium shear experiment, where the lowest fouling rate was observed can be attributed to the different biofilm structure, which can affect biofilm enhanced osmotic pressure (BEOP) phenomenon as well as hydraulic resistance induced by the presence of EPS. Interestingly, EPS amount as well as the ratio between polysaccharide to protein content (Supplementary Material, Table S2) did not follow the rate of permeate flux decline but in contrast, the 16s gene copy numbers (Fig. 3) corroborate with the assumption of faster cell growth at higher CP. Clearly, in RO systems not only EPS dictate fouling rate. Reduced

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membrane performance is strongly influenced by bacterial cells, which contribute to the BEOP phenomenon (Herzberg and Elimelech, 2007a). Still, all biofouling experiments, in this study, stopped after achieving similar permeate flux (~40% of the initial) and therefore, variations in the biofilm volume, cell content (16s gene copy), and EPS content (mainly polysaccharides and proteins) can be related to physical selection for the adherence of the microbial community and their EPS to the membrane at elevated shear rate. Confocal laser scanning microscopy (CLSM) observations may also provide rough information on the effect of shear rate on biofilm structure, which may provide more insight on membrane performance. Though, our attempts to relate between CLSM analysis and permeate flux decline did not reveal any correlation between biofilm volume and permeate flux (Ying et al., 2013). It is known that biofilm properties including density, extent of its interaction with the membrane and porosity, are all play major role in the extent of deterioration in membrane performance. These biofilm characteristics are known to affect BEOP phenomenon as well as hydraulic resistance (Herzberg et al., 2009) and general biofilm volume determination will not necessarily correspond to permeate flux. While the above discussion provides plausible explanations for the changes in fouling behavior, i.e. effects of shear rate on permeate-flux decline, other parameters that were not checked in this study might affect biofouling. These could include selection for EPS compounds that provide high adherence to the surface at elevated shear rates (Ying et al., 2013), inducing the formation of a strong and cohesive biofilm matrix that is difficult to remove (Vrouwenvelder et al., 2011). High shear rate may contribute to the selection for ‘sticky’ bacteria that attach well to the membrane surface via enhanced secretion of EPS, causing faster permeate-flux decline (Ying et al., 2013) and a more stable biofouling layer. Hence, the bacterial community at high shear rate was dominated by Xanthomonadales, which possess enhanced € rsch et al., 2005) and show signifattachment capabilities (Ho icantly higher attachment than other bacteria in mixed culture (Elvers et al., 1998). The bacterial communities developed under low, medium and high shear were significantly different (P < 0.001) and clustered separately (Fig. 2). The bacterial communities in the feed water were similar, and differed from the bacterial communities on the membrane biofilms (Fig. 2), supporting our previous findings (Al Ashhab et al., 2014). The biofilm developed under medium shear was more diverse than those formed under low and high shear rate (Table S4). Higher diversity may indicate a more stable ecological community (Briones and Raskin, 2003), which has been shown to promote resistance to perturbation and stress (Girvan et al., 2005). The high diversity of the RO-membrane biofilm developing under medium shear might explain the reported resistance to cleaning attempts and resilience to repeated perturbations (Timke et al., 2005). The lower abundance of Alphaproteobacteria and high abundance of Betaproteobacteria in biofilms developed under medium shear rate compared to low and high shear rates may reflect higher biofilm stability under medium shear rate (Fig. 5A and B). It has been suggested that Betaproteobacteria are secondary colonizers that replace the primary colonizers € rsch et al., 2005; Pang and Liu, i.e., the Alphaproteobacteria (Ho

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2007; Bereschenko et al., 2010), and play an important role in biofilm maturation. In fact, the dominant order, Burkholderiales, belongs to the Comamonadaceae, which have been found to take part in denitrification processes (Mechichi et al., 2003; Wu et al., 2012) and is essential to biofilm development (Pang and Liu, 2007). Most of the Alphaproteobacteria belonged to the classes Rhizobiales and Sphingomonadales, previously reported as primary colonizers of RO membranes (Pang and Liu, 2007; Bereschenko et al., 2010). Biofilms that developed under high shear rate showed a different bacterial composition, with Deltaproteobacteria forming 12.9 ± 3.6% of the total bacterial abundance (Fig. 5C), unlike the biofilm developed under medium shear rate where Deltaproteobacteria formed only about 1% of the total bacterial community (Fig. 5B), and that developed under low shear rate where Deltaproteobacteria were absent (Fig. 5A). The Deltaproteobacteria were dominated by the order Myxococcales, known as “slime bacteria”, which can develop special mechanisms of attachment termed focal adhesion by excretion of polysaccharides involved in cell attachment (Mignot et al., 2007). This trait might be important for biofilm growing under high shear conditions. Under high shear rate we found the Gamaproteobacteria to be slightly more abundant (22.7 ± 2.1%) than under low or medium shear rates (14.4 ± 5.1% and 18.7 ± 3.6%, respectively). The Gamaproteobacteria all belonged to the family Xanthomonadaceae, which has been found to attach well by applying surface structures that are anchored in the bacterial outer membrane, including polysaccharidic and proteinaceous structures such as type IV pili (Mhedbi-Hajri et al., 2011).

5.

Conclusions

Feed-water velocity (shear rate), organic loading rate (nutrients), and organic foulant concentrations can be used to control the biofouling of RO membranes used to treat municipal effluents. Different shear rates resulted in the growth of different biofilms with different biomass, as well as different biofouling behavior (permeate flux). These individual effects of shear rate and its intrinsic variable, organic loading rate, were isolated by providing the RO membrane with similar feed water (similar water chemistry as well as microbial communities) and surface. Operation of RO membranes at high shear rate resulted in a lower cell content, as evident from the lower 16s gene copy, but with tolerated bacteria of higher EPS secretion and anchoring mechanisms to the membrane surface, which likely form more stable biofilms.

Acknowledgments This study was supported by the USAID Middle East Regional Cooperation (MERC) Program, project number M29-048, and by the joint BMBF-MOST German-Israeli Research Program, project number WT0902. We also acknowledge Amer Sweity and Bihter Bayramoglu for their help and support.

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Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.watres.2014.09.007.

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Biofouling of reverse-osmosis membranes under different shear rates during tertiary wastewater desalination: microbial community composition.

We investigated the influence of feed-water shear rate during reverse-osmosis (RO) desalination on biofouling with respect to microbial community comp...
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