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International Biodeterioration & Biodegradation 88 (2014) 125e133

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International Biodeterioration & Biodegradation

journal homepage: www.elsevier .com/locate/ ibiod

Treatment of cosmetic industry wastewater by submerged membranebioreactor with consideration of microbial community dynamics

Inès Friha, Fatma Karray, Firas Feki, Lobna Jlaiel, Sami Sayadi*

Laboratoire des Bioprocédés Environnementaux, Pôle d’Excellence Régional AUF, Centre de Biotechnologie de Sfax, BP: «1177», 3018 Sfax, Tunisia

a r t i c l e i n f o

Article history:Received 29 August 2013Received in revised form22 December 2013Accepted 22 December 2013Available online 11 January 2014

Keywords:Membrane bioreactorWastewater treatmentGCeMS analysisPCR-DGGE

Abbreviations: AS, anionic surfactant; BOD, biolochemical oxygen demand; DGGE, denaturing gradielectrical conductivity; EPS, extracellular polysacchatography coupled with mass spectroscopy; HRT, hydmembrane bioreactor; MLSS, mixed liquor suspendedrate; PCR, polymerase chain reaction; SC, sludgeretention time; TSS, total suspended solids; TMP, trultrafiltration; WWTP, wastewater treatment plant.* Corresponding author. Tel.: þ216 74 871 816; fax

E-mail address: sami.sayadi@cbs.rnrt.tn (S. Sayadi

0964-8305/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.ibiod.2013.12.015

a b s t r a c t

A pilot scale aerobic submerged membrane bioreactor (MBR) for treating cosmetic wastewater wasoperated for 205 days. During the operation, increasing organic loading rates (OLR) were applied in theMBR. The effects of the applied OLR (from 0.25 to 2 g COD l-1 d-1) were evaluated regarding chemicaloxygen demand (COD) and anionic surfactant (AS) removal efficiencies. At an optimal volumetric OLR of1.52 g COD l-1 d-1, the MBR achieved the highest COD and AS removal efficiencies (83.73% and 98.13%,respectively). The influence of the OLR on filtration performance was assessed, including GC/MS analysisof raw and treated wastewater. The denaturing gradient gel electrophoresis (DGGE) analysis was used tomonitor the dynamics of the bacterial communities inside the bioreactor. Major bands of DGGE patternsof sludge samples were further sequenced. Phylogenetic analysis indicated that the majority of the se-quences obtained were affiliated with a-Proteobacteria, Actinobacteria and Fimicutes.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Industrial wastewater is one of the important sources of waterpollution. With the rapid development of various industries, hugeamounts of fresh water are used as raw material, means of pro-duction and for cooling purposes. Consequently, many kinds of rawmaterial, intermediate products and wastes are found in thewastewater at the end of the industrial process. This requires thatthe treatment process must be designed specifically for theparticular type of the produced effluent in order to allow the reuseof the reclaimed water for industrial applications.

Cosmetic wastewaters are characterized by relatively high CODvalues, total suspended solids (TSS), fats, oils and detergents.Various kinds of treatment processes have been used to treat thesewastes mostly by coagulation/flocculation (Meiners, 1994), ultra-filtration (Huisman, 2004), advanced oxidation (Bautista et al.,

gical oxygen demand; COD,ent gel electrophoresis; EC,rides; GCeMS, gas chroma-raulic retention time; MBR,solids; OLR, organic loadingconcentration; SRT, sludge

ans-membrane pressure; UF,

: þ216 74 871 818.).

All rights reserved.

2007) and catalytic wet peroxide oxidation processes (Bautistaet al., 2010).

The application of some biological processes has been also re-ported. Yet it turns out that the main difficulties for biologicaltreatment of cosmetic wastewaters derive from the presence ofdetergents, surfactants, hormones, cosmetics and pharmaceuticalcompounds (Stackelberg et al., 2004). Many studies denounced thatsurfactants, especially at higher concentrations, can significantlydeteriorate biological treatment processes. Such concentrationsexpose the system to a sludge foaming risk (Petrovic and Barcelo,2004).

Thus, in order to meet the more stringent regulations con-cerning industrial wastewaters, advanced treatment technologiesfor a more efficient treatment of these effluents are required.

MBR processes are considered as promising technology forwastewater treatment and represent an advancement over theconventional activated sludge process. They combine biologicaldegradation and membrane filtration in a single-step, compactprocess and allow more flexibility in the application of differentmodifications to fine tune biological performance (Hai andYamamoto, 2011). The biological process converts dissolvedorganic matter into suspended biomass, reducing membranefouling and allowing increase in recovery. While the membranesintroduced in the bioreactors not only replace the settling unit forsolideliquid separation but also form an absolute barrier to solidsand bacteria and retain them in the process tank (Hai andYamamoto, 2011). Both aerobic and anaerobic biological treat-ment methods have been extensively used to treat domestic and

Table 1Physicochemical characteristics of Henkel Alki raw wastewater.

Characteristics Max Min Mean SD*

pH 6.08 4.93 5.51 0.52TKN (mg l�1) 144 85 107.37 24.96EC (mS cm�1) 2.89 2.43 2.61 0.17Anionic surfactant (g l�1) 5.65 2.70 3.31 1.15TSS (g l�1) 3.74 0.6 2.34 1.36Soluble COD (g l�1) 16.66 9.34 13.57 3.15BOD5 (g l�1) 1.7 1 1.62 0.23Ions and heavy metals (mg l�1)Calcium (Ca) 81.95 45.95 63.95 15.33Potassium (K) 165.99 75.99 108.24 30.96Sodium (Na) 501 151 263.5 124.16Magnesium (Mg) 353 83 178 95.22Cupper (Cu) e e e e

Zinc (Zn) 2.11 0.268 1.15 0.63Lead (Pb) e e e e

Nickel (Ni) e e e e

Chrome (Cr) 1.48 1.24 1.35 0.09Cadmium (Cd) e e

* SD: Standard deviation.

Fig. 1. Schematic diagram of the experimental set-up.

I. Friha et al. / International Biodeterioration & Biodegradation 88 (2014) 125e133126

industrial wastewater (Visvanathan et al., 2000). Admittedly, thistechnology has several advantages such as high treated waterquality, low sludge production, small foot print, robustness andflexibility for future expansion. They are particularly attractive fortreatment of recalcitrant wastewater where long sludge retentiontimes (SRT) are applied facilitating the efficient removal of slowlybiodegradable pollutants. However, membrane fouling is a majordrawback of this technology (Guo et al., 2012), requiring moreenergy for backwashing and making the system less efficient.

A number of studies have been conducted to elucidate the effectof various factors on membrane fouling. These factors can be clas-sified into two main groups, namely operation- and sludge-relatedfactors. Operation-related factors, such as operation flux (Le-Clechet al., 2006), solids retention time (SRT) (Ahmed et al., 2007) anddissolved oxygen concentration (Psoch and Schiewer, 2006).Sludge-related factors include sludge viscosity (Meng et al., 2006)and extracellular polymeric substances (EPS) (Johir et al., 2012).

Several practices have been proposed to minimize foulingfocusing mainly on physical parameters. These include altering theaeration rate, hydraulic retention time (HRT), sludge retention time(SRT) and organic loading rates. In a fixed volume of reactor, theincrease of imposed flux decreases the hydraulic retention time(HRT). The HRT affects not only the treatment efficiency of MBRs(Ren et al., 2004, 2005), but also the characteristics of the biomassinMBRs (Yoon et al., 2004). Meng et al. (2007) reported that a lowerHRT reduced COD removal, biomass activity and dissolved oxygenconcentration. Thus, a shorter HRT while having an advantage of asmaller foot print, has the disadvantage of increased membranefouling due to the larger amounts of EPS produced.

In this paper, a long-term performance of an aerobic submergedMBR to treat cosmetic wastewater was investigated. This studyfocused on two physical parameters i) imposed flux and ii) organicloading and how they influenceMBR treatment efficiency (COD andanionic surfactants removals) and their effect on the membranefouling. In addition to COD and surfactant analysis, the studiestargeted the evolution of the contents of the MBR and permeate atdifferent times by means of GC/MS analysis. The analysis of speciescomposition variation in MBR was also monitored using PCR andDGGE techniques.

2. Materials and methods

2.1. Cosmetic wastewater characteristics

Wastewater samples were collected from Henkel Alki industry.This factory discharges around 10 m3 per day of wastewater. Thewastewater produced is treated in an external cross flow mem-brane (Koch) bioreactor. The characteristics and the averagecomposition of raw wastewaters were given in Table 1.

2.2. Experimental setup and reactor operation

The schematic experimental setup is shown in Fig. 1. The aerobicMBR made of polypropylene (PP) (38 cm in diameter, 63 cm inheight, with an operating level of 58 cm) was coupled to a sub-merged cross-flow ultrafiltration (UF) flat sheet membrane module(Microdyn-Nadir GmbH, Germany) with a total effective filtrationarea of 0.39 m2, a cut-off of 150 kDa and an operating trans-membrane pressure (TMP) ranging between 70 and 350 mbar. Themembrane module is equipped with an air diffuser located underthe latter module to prevent or reduce membrane fouling and tomaintain an aerobic environment for the normal growth of acti-vated sludge. A sludge drainwas placed at the bottomof the reactor.

The seed sludge was obtained from an industrial standardactivated sludge plant treating cosmetic wastewater (Henkel Alki

industry, Sfax, Tunisia). The MBR unit was inoculated with aerobicsludge of the mentioned industrial facility at an inoculation ratio of20%. The starting mixed liquor suspended solids (MLSS) concen-trationwas 2.65 g l-1 and the aerationwas controlled andmeasuredwith an air flow meter setting the air flow between 1 and 2 m3 h-1.The temperature of the reactor varied from 15 to 29 �C.

During the experimental procedure, the plant was continuouslyfed with pre-settled cosmetic wastewater through a peristalticpump (Minipuls 3 Gilson Model 312, France) synchronized topermeate suction. The permeate was withdrawn intermittentlythrough a second peristaltic pump (Watson-Marlow 505U, Fal-mouth, Cornwall TR11 4RU, England). A pressure gauge (S-Wika EN837-1, Germany) was mounted between the membrane and thepermeate pump to monitor the TMP.

The system was operated with a constant starting volumetricloading rate (VLR), defined as the amount of COD fed per litre ofreactor volume and per day. The average starting VLR of0.25� 0.02 g COD l-1 d-1 was obtained keeping a constant permeateflux and diluting the rawwastewater with tap water, when needed.The MBR was operated at a preset flow rate corresponding to afixed HRT. The average starting HRT was about 3.5 days and wasdecreased stepwise to 2 and 1 days during the experiment. Addi-tionally, no sludge was intentionally removed from the reactorexcept for sample withdrawn for suspended solids and other bio-logical and chemical/physical measurements.

The normal cleaning procedure of the membrane module wasjet rinsing of the flat sheets with tap water after extracting themodule from the bioreactor. This procedure was performed whenthe TMP approached 600 mbar. The membranes were chemically

Fig. 2. COD removal efficiency in accordance with the increase of the OLR: InfluentCOD (C), Permeate COD (:), HRT (▬), OLR (B).

I. Friha et al. / International Biodeterioration & Biodegradation 88 (2014) 125e133 127

cleaned (soaking 3 h in bleach (3%) followed by a cleaning cycle of2 h with citric acid (1%)) if the positive effect of rinsing tended tolast too short.

2.3. Sampling

During 205 days, samples were collected every second day ascorresponding samples from the MBR-influent, the bioreactor itselfand MBR-effluent. All samples were stored at 4 �C until analysis.COD, AS, pH-value, Electrical conductivity (EC), temperature andMBR sludge concentration (SC) were measured regularly.

2.4. Analytical methods

pH and the EC were determined using a pH meter model Istek-NeoMet and a conductivimetermodel CONSORT C 831, respectively.

Hyamine colorimetric method was used for estimating the ASconcentrations.

Soluble COD was estimated as described by Knechtel (1978).BOD5 was determined by the manometric method with a

respirometer (BSB-controller Model 620 T (WTW)).Total Kjeldahl nitrogen content was determined as described by

Kjeldahl (1883).MLSS, Total Suspended Solids (TSS) were measured as the

Standard Methods for examination of water and wastewater(APHA, 1992).

2.5. GCeMS analysis

Samples (20 ml) were extracted with chloroform (20 ml). Theorganic fraction was evaporated to dryness, redissolved in equal vol-ume of chloroform and then analyzed by GCeMS. GCeMS was per-formed with a HewelettePackard model 6890N chromatographapparatus equippedwith a capillary HewelettePackard HP-5 column.The carrier gas was helium used at a flow rate of 1 ml min�1. Thetemperaturewasfirstsetat70 �C for2minandwas increased to230 �Cat 20 �Cmin�1, then to 300 �C at 40 �Cmin�1 and finally set at 300 �Cfor 10 min. The control of the GCeMS system and the data peak pro-cessing were carried out by means of the MSDCHEM Software (onlycompounds having peak area percentage over 90% were selected).

2.6. PCR-DGGE Analysis

Five sludge samples were collected from the bioreactor atdifferent days of the operational system (day 0 (T0), day 14 (T1), day36 (T2), day 102 (T3) and day 162 (T4)). All samples were centri-fuged at 10.000 g for 5 min. The supernatant was removed and thepellets were stored at�20 �C. DNA extraction and purification fromsludge samples were performed using the EZ-10 Spin Column SoilDNA Mini-Preps Kit (BIO BASIC INC.) according to the manufac-turer’s instructions. DNA was amplified with primers 341F (50-CCTACGGGAGGCAGCAG-30) (Muyzer et al., 1995) and 518R (50-ATTACCGCGGCTGCTGG-30) (Muyzer et al., 1993) spanning the V3hypervariable region of the rRNA 16S. A GC-clamp (50-CGCCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCG-30) wasattached to the 50-end of primer 341F (Muyzer et al., 1993). PCRamplification was performed in a total volume of 50 ml mixturescontaining 2 mM MgCl2, 0.2 mM of each dNTP, 0.2 mM of eachprimer, 0.1 mg/ml BSA, 50 ng DNA template and 2.5 U of Top-TaqDNA polymerase (BIORON) with the reaction buffer supplied bythe manufacturer. The PCR was performed using a touchdownannealing protocol with initial denaturation at 95 �C for 5 min,denaturation at 94 �C for 45 s, and a touchdown primer annealingfrom 65 to 55 �C for 45 s (annealing temperature decreased 1 �C foreach second cycle to a final temperature of 55 �C), annealing at

55 �C for 45 s for the next 14 cycles and then a primer extension at72 �C for 45 s. The final extension step was done at 72 �C for 10 min.DGGE analyses were performed with the method of Muyzer et al.(1993) using a DCode multiple system (BioRad) with thefollowing conditions. Polyacrylamide gels (8%) (Acrylamide: bisa-crylamide, 37.5:1) were prepared using denaturing gradientsranging from 40% to 70% (100% denaturant was 7 M urea and 40%deionized formamide) to separate the PCR products obtained byamplification with primers 341F-GC and 518R. Electrophoresis wascarried out in 1 � TAE (Trise acetate 0.04 M, EDTA 0.002 M, pH 8.5)buffer at 60 �C and at a constant voltage of 150 V for 6 h. The gel wasincubated in an ethidium bromide solution for 25 min and thenrinsed with distilled water for 5 min and photographed under UVtransillumination.

2.7. Sequences analysis

The more intense bands detected in DGGE patterns indicative ofthe most abundant populations of each sample, were excised fromthe gel, eluted overnight in 35 mL of MilliQ water and reamplified byPCR using the 341F and 518R primers. PCR products were purifiedand sequenced by society Biotools-Tunisia. The primers used forsequencing were the same used for amplification. Sequence simi-larity searches were performed using the online sequence analysisresources “BLAST” (Altschul et al., 1997) and “Seqmatch” (Ribo-somal Database project II; Release 10) (Cole et al., 2009). Multiplealignments were generated with the MUSCLE program (Edgar,2004) and phylogenetic tree was constructed with MEGA pro-gram version 4 (Tamura et al., 2007) on the basis of evolutionarydistances that were calculated by the Neighbor-Joining method(Saitou and Nei,1987) withMaximumComposite Likelihoodmodel.Bootstrap resampling analysis (Felsenstein, 1985) was performedfor 100 replicates to estimate degrees of confidence in tree topol-ogies. DGGE fingerprints were compared using Gel Compar II(Applied Maths, Belgium). The similarity among profiles wascalculated using the Pearson correlation coefficient for DGGE pro-files. Dendrograms were obtained by Unweighted Pair groupMethod using Arithmetic averages (UPGMA).

2.8. Nucleotide sequence accession number

The DGGE band sequences in this study were deposited inGenBank under accession numbers KC593532eKC593546.

3. Results and discussion

3.1. COD removal performance

The changes of substrate concentration expressed as solubleCOD are shown in Fig. 2. The average operating conditions and theremoval efficiencies of the MBR are summarized in Table 2. During

Table 2Average operating conditions and removal efficiencies of the MBR.

Time (days) Stage OLR (g COD l-1 d-1) COD removal efficiency (%) Anionic surfactant removal efficiency (%)

0e20 Acclimatation 0.25 � 0.02 79.49 � 7.72 94.52 � 3.1921e25 I 0.53 � 0.03 69.66 � 3.17 94.65 � 1.7126e30 II 0.73 � 0.11 83.20 � 6.67 95.64 � 0.4731e42 III 1.05 � 0.18 86.25 � 2.33 96.47 � 1.0643e52 IV 1.52 � 0.11 83.73 � 5.81 98.13 � 0.0953e97 V 1.71 � 0.23 74.92 � 7.27 97.95 � 1.1298e143 VI 1.97 � 0.15 67.80 � 7.59 93.46 � 2.67144e154 VII 1.67 � 0.06 67.96 � 4.85 94.52 � 0.21155e185 VIII 1.49 � 0.09 84.02 � 4.22 95.89 � 1.60186e205 IX 1.34 � 0.04 84.99 � 3.75 96.67 � 0.00

I. Friha et al. / International Biodeterioration & Biodegradation 88 (2014) 125e133128

the first 42 days, the OLR was increased progressively to 1 gCOD l�1 d�1 (Fig. 2), the COD removal efficiency reached 86.25%(Table 2). Between days 43 and 143, increasing OLR (1.5e1.9 gCOD l�1 d�1) decreased the COD removal from 83.7 to 67.8%(Table 2) which could be attributed to the accumulation of nonbiodegradable organic substances inside the bioreactor revealed bythe increase of the COD of the reactor (3.46 g l�1) and consequentlycaused fouling. To allow a better biodegradation inside the biore-actor, the OLR was decreased to 1.34 g COD l�1 d�1 at day 186. Animprovement in COD removal in the MBR system was observed(84.9%) and low COD permeate was found (0.17 g l�1).

3.2. Sludge concentration

During the start-up, the biomass showed a very slow growthand it barely reached 3 g l�1. After two months of running system,the biomass concentration increased to 6.17 g l�1. However, whencompared to the conventional process, the biomass concentrationinside the MBR was lower. It is difficult to explain why the MLSSstabilized at a so low value when no sludge was discharged. Thelargest possibility might reside in the composition of the cosmeticwastewater, which contains a variety of bactericidal substancesfrom shampoo, body soap or other cleaning agents.

Since the increase in the OLR, the MLSS declined to 3.52 g l�1

after 4 months of continuous treatment. This decline is due to theaccumulation of non biodegradable organic compounds inside thebioreactor. Such compounds, when working at high OLR exertedtoxic effects on the biomass due to their high concentrations.

3.3. Surfactant removal performance

The changes of substrate concentration expressed as AS con-centration are described in Fig. 3. The changes of AS substrateconcentrations were related to the operational OLR, the rawwastewater AS content. During the first 60 days steady state

Fig. 3. Variation of anionic surfactant concentration of influent, effluent and reactorsupernatant: Inf (influent) (C), Eff (effluent) (:), R (reactor) supernatant (,).

permeate surfactant concentration was observed (12.29 mg l�1)showing that theMBR could provide a consistently high AS removal(99.26%). However, owing to the reduction of the HRT, the surfac-tant removal rate decreased to an average of 93.46% (Table 2). Arelative increase in surfactants in permeate was observed(60 mg l�1) following the change in HRT which decreased to30.72 mg l�1 at the end of the operational period. Huang et al.(2000) reported that the extension of the contact time of the mi-crobial system with the organic pollutants is an important factorfacilitating efficient removal of slowly biodegradable pollutants andthus upgrading the effluent quality. During the last operationalperiods, the anionic surfactant removal efficiency of the systemstabilized at 96% at an HRT of 28.8e33.6 h and COD loading rates of1.34e1.49 g COD l�1 d�1 (Table 2).

3.4. Long term membrane filtration performance

The data of the membrane permeability, the TMP and the fluxare presented in Figs. 4e5 for the four stages of MBR operation. TheTMP was adopted as an indicator for membrane fouling since thefiltration flux was fixed for different MBR stages. During the start-up, the filtration flux was gradually increased from 2 to4 l h�1m�2. When the consortia became more adapted, the filtra-tion flux was greatly increased to 6 l h�1m�2 due to the reduction ofthe HRT. Therefore, the TMP pressure increased as a consequence ofthe increase in both filtration flux and MLSS. Regarding membranepermeability, one should note the reduction of membrane perme-ability in all four phases compared to the initial permeability (243 lh-1 m-2 bar-1). The membrane filtration performance remainsessentially steady under low flux value (J ¼ 2 l h-1 m-2) (stage a).However, when increasing the flux to 3 l h-1 m-2 (stage b) themembrane performance is overall inferior but practically no foulingseems to occur. During the third stage (stage c), the membranefouling was clearly intensive (Fig. 5) necessitating the chemicalcleaning of the membrane modules two times in a period ofapproximately 80 days. At the same time, high organic content is

Fig. 4. Membrane permeability data during MBR operation; arrows indicate chemicalcleanings.

Fig. 5. Trans-membrane pressure and flux evolution.

I. Friha et al. / International Biodeterioration & Biodegradation 88 (2014) 125e133 129

measured in the MBR supernatant with a mean COD value ofapprox. 3 g l-1; Barker and Stuckey (1999) reported that bacteriatend to excrete more soluble microbial products in response tovarious environmental stresses. Specifically, during the unsteadystate of stage c, when the OLR was increased, the biomass has moreavailable substrate per unit of volume and time; these conditionsprobably favor the production of more soluble microbial products

Table 3GCeMS identified compounds evolution in feed, reactor and permeate according to thei

Time (months) 2

Compound RT*(min) % Area

F* R* P*

Sabinene 4.317 25.93 6.23 e

Limonene 4.832 3.71 1.53 e

Beta.Ocimene Y 4.981 3.69 1.52 e

Linalool L 5.490 9.27 3.07 e

4-Terpineol 6.194 4.19 1.38 e

5-Dodecene 8.250 e e e

Cyclooctane 8.265 e e e

1-Tetradecanol 9.478 e e e

Cyclododecane 9.484 e

Lauryl ethoxylate 9.730 3.35 e e

N-(2-Hydroxyethyl)-Lauramide 9.793Alpha. Hexylcynnamic Aldehyde 9.970 e e e

Isopropyl Myristate 10.256 e e e

Cyclotetradecane 10.540 0.48 e e

Cyclohexadecane 10.554 e e e

1-Octadecene 11.372 1.27 e e

N-(2-hydroxyethyl)dodecanamide 11.504 e e e

Hexadecanoic acid, butyl ester 11.693 1.91 e e

Tricosane 12.025 0.42 1.16 e

2-Tetradecyloxyethanol 12.036 e e e

Octadecanoic acid, butyl ester 12.299 1.65 1.61 0Tetracosane 12.322 0.59 3.20 4Pentacosane 12.637 1.06 6.83 73-(4-Nitrophenyl)propiolic acid 12.843 2.27 e e

Hexacosane 12.969 1.30 9.53 10Heptacosane 13.329 1.38 11.69 10Octacosane 13.735 1.16 13.46 9Nonacosane 14.193 0.79 9.12 7Triacontane 14.742 0.58 1.13 5Docosane 14.754 e 5.32 e

Eicosane 15.400 e e e

*RT: Retention Time; F: Feed; R: Reactor; P: Permeate.

which in turn may affect both the effluent quality and the mem-brane filtration performance (Patsios and Karabelas, 2011). Whendecreasing the OLR (stages d-e, Fig. 4), the membrane filtrationperformance remains essentially steady for almost three monthswithout any chemical cleaning (day 109e205). Though this steadyfiltrationwas achieved under a rather lowOLR value, a concomitantimprovement in membrane performance could be identified. The

r retention time at 2, 4 and 6 months of MBR operation.

4 6

% Area % Area

F* R* P F* R* P*

e e e e e e

e e e e e e

e e e e e e

e e e e e e

e e e e e e

23.06 e e e e e

e e e 20.83 e e

9.31 e e e e e

4.10 e e

e e e e e e

2.281.22 e e e e e

2.34 e e e e e

2.66 e e e e e

e e e 4.30 e e

0.54 e e 1.90 e e

e e e 8.71 e e

5.52 e e e e e

1 e e e e e

e e e 1.11 e e

.33 4.19 e e e e

.14 0.88 3.79 4.42 e e e

.33 e 9.31 10.04 e 12.67 e

e e e 2.75 e e

.09 1.68 12.27 12.25 e 14.32 e

.44 1.50 14.76 14.58 e 18.09 6.47

.99 e 13.38 13.42 e 16.83 8.79

.11 e 10.94 10.63 e 14.69 5.82

.18 e 8.52 7.26 e e e

1.75 e e e e e

e 6.01 5.09 e 10.80 e

I. Friha et al. / International Biodeterioration & Biodegradation 88 (2014) 125e133130

organic content of the MBR supernatant decreases within the twolast stages from 2 to 0.95 at days 161 and 205, respectively.

Fig. 6. DGGE profile of PCR-amplified V3 region fragments of 16S rDNA gene obtainedfrom five samples (Lane T0: 0 day, lane T1: 14 days, lane T2: 36 days, lane T3: 102 daysand lane T4: 162 days) collected from the bioreactor sludge. The positions of the mostisolated and sequenced dominant bands are indicated by the letters (A, B, C, D, E, F, G,H, I, J, K, L, M, N and O).

3.5. GC/MS characterization of influent, reactor and effluent

The composition of the cosmetic wastewater, the reactor su-pernatant and the resulting effluents were analyzed by GCeMS attwo, four and six months of MBR operation. Table 3 shows a fairlycomplex composition of the cosmetic wastewater consisting of :monoterpens (sabinene, limonene, ocimene, linalol, terpineol);normal alpha olefins (1-octadecene, 5-dodecene); fatty acid esters(palmitic acid butyl ester, butyl stereate, isopropyle myristate);fatty alcohols (myristyl alcohol). Moreover, GCeMS analysis of feedextracts allowed the identification of surfactants such as laurylethoxylate, N-(2-hydroxyethyl)-lauramide and N-(2-hydrox-yethyl)-dodecanamide and n-alkanes of different chain length (n-octacosane, n-docosane, n-tricosane).

The challenge was to assess the efficiency of the MBR treatmentin removing the identified compounds. The GCeMS analysis of theresulting effluents (Table 3) showed the complete removal ofcompounds having retention times below 12 min namely sabinene,limonene, ocimene, linalol, octadecene, dodecene and even theidentified surfactants. One may suggest that these compounds arehighly biodegradable by the biomass. However, the other com-pounds having retention time over 12 min (tetracosane, pentaco-sane, hexacosane, etc.), corresponding to long chain n-alkanes,seem to be slightly biodegradable as they are found in permeatesbut at lower concentrations. Additional interesting observationscan be made by comparing effluents profiles obtained at four andsix months. The MBR showed a very good biodegradability after 6months of continuous treatment, the adapted aerobic bacteria wasable to completely degrade a wide range of terpens, olefins, fattyacids esters andmore particularly surfactants after 180 days of MBRoperation.

Fig. 7. Dendrogram obtained from clustering analysis of DGGE banding profiles andscoring bands as present or absent, using the gel compar II software. Scale indicatespercent similarity. Bands that have been taken into account for comparison areindicated.

3.6. Diversity of the MBR microbial community as revealed by PCR-DGGE analysis

The changes in bacterial diversity during the cosmetic waste-water treatment process were monitored and analyzed by PCR andDGGE techniques. The DGGE profiles of all bacterial communities in16S rDNA V3 region revealed a small number of distinguishablebands per sample, reflecting a relatively simple and specificstructure of bacterial community in each sample (Fig. 6). Clearchanges within the community structure were occurred during theprocess. Bands B, D, F, K, L and Mwere present at the start-up of theprocess (sample T0) while band L disappeared at the end of theexperiment (samples T3 and T4). Bands B, D, K and F initially foundat T0 disappeared after 14 days (at sample T1) of MBR operationwhereas band K reappeared at sample T2 and remained visiblethereafter. Band M increased in intensity and become one of themajor bands during the process (Band N, Fig. 6). Two commonbands (Band I and O, Fig. 6) were shared by all profiles. Three novelbands (J, H and E, Fig. 6) appeared in sample T1 and disappearedafter 36 days of treatment (not detected at sample T2). Bands G andC appeared only the last four months (April to July) while band Aappeared at sample T1 and remained visible thereafter. These dif-ferences indicated that some variance of bacterial communitycompositions existed during the treatment period. The clusteranalysis of DGGE band pattern of the different samples (T0, T1, T2,T3 and T4) is represented in Fig. 7. Within each cluster, the per-centages of similarity were higher than 50% for most samples.These results confirmed the variation of the bacterial communitystructure during the treatment period.

The prominent DGGE bands were excised and sequenced inorder to identify the predominantly present bacterial populations.

Phylogenetic analyses based on the bacterial 16S rDNA se-quences were performed. The majority of the bacterial 16S rDNAsequences were grouped with members of alpha-Proteobacteriawhich is classified into 3 bacterial orders including, Rhizobiales,Caulobacterales and Rhodospirillales except one sequence whichwas classified into unclassified Alphaproteobacteria. Two se-quences were related to members of the Actinobacteria and onesequence was clustered with the Fimicutes (Fig. 8).

Within the Rhizobiales order, Band H (Fig. 6) presented highsimilarity (99%) with Bradyrhizobium liaoningense and Bradyrhi-zobium japonicum. Band J (Fig. 6) sequence was related to Methyl-opila capsulate (facultative methylotrophic bacterium; Doroninaet al., 1998) and Blastochloris sulfoviridis (96% of similarity).Various physiological groups of bacteria were found in sewagesludge including facultative methylotrophic bacteria. Durska(2007) isolated methylotrophic bacteria belonging to facultativemethylotrophs from sewage sludge derived from mechanical andbiological sewage treatment plants. The obtained results indicated

Fig. 8. Phylogenetic tree based on partial 16S rRNA gene sequencing. The bold names correspond to the sequence types isolated from the DGGE analysis, while the other sequencesused in the analysis were obtained from the GenBank. The scale bar represents the substitution per nucleotide position. Haloferax denitrificans was used as outgroup.

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that methylotrophic bacteria were found to possess proteolyticproperties and were able to hydrolyse urea. Further it wasdemonstrated that methylotrophs take part in the transformationof nitrogen compounds. Some of them can utilize glutaminic andaspartic acids (McDonald et al., 2001), as well as methyl- dimethyl-and trimethylamines (Urakami et al., 1993). Furthermore, methyl-otrophic bacteria are also characterized by the ability for fixingatmospheric nitrogen in symbiosis with legumes (Sy et al., 2001;Jourand et al., 2004). Band L (Fig. 6) exhibited 97% of sequencesimilarity with Microvirga flocculans and Chelatococcus asacchar-ovorans. Band I (Fig. 6) was closely related to Rhizobium/

Agrobacterium (98% of similarity). Some members of the genusRhizobium and Bradyrhizobium have been reported as nitrogenfixing symbiotic bacteria. However, other non symbiotic Rhizobiumspecies were isolated from bioreactors. Bradyrhizobium is one of themost dominant bacterial species responsible for biofouling inwaterpurification membrane processes due to their ability to secreteextracellular polysaccharides (EPS) (Skorupska et al., 2006).

Within the Alphaproteobacteria, Band K (Fig. 6) was affiliated toDevosia spp (99% of similarity). Bands M, N and O (Fig. 6) wereclosely related to the genus Phenylobacterium (Caulobacteraceae).Phenylobacterium mobile DSM1986T is able to degrade LAS (Linear

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Alkylbenzene Sulphonate), a worldwide used anionic surfactantconsidered as a high-priority pollutant (Ke et al., 2003). Within theRhodospirillales order, Band C and G (Fig. 6) were affiliated toElstera litoralis strain (99% of similarity), previously isolated fromalgae-dominated biofilms (Rahalkar et al., 2012). Band D (Fig. 6)was found to belong to unclassified Rhodospirillales bacterialclones and was identified as coral-associated microorganisms. Theclosest species to band D sequence is Insolitispirillum peregrinum(Rhodospirillaceae) (95% of similarity). Band B (Fig. 6) was affiliatedto Geminicoccus roseus strain (98% of similarity), an aerobic pho-totrophic unclassified Alphaproteobacterium isolated from a ma-rine aquaculture biofilter (Foesel et al., 2007). Sequences of bands Eand F were clearly affiliated to Actinobacteria and closely related toMycobacterium spp (Band E, Fig. 6) andMicrobacterium spp (Band F,Fig. 6), with sequence similarity of 99% and 97%, respectively.Dudley and Christopher (1999) have earlier identified the relevanceof the genus Microbacterium as the major biofouling populationsrecovered from full-scale RO installations. However, Bakir et al.(2008), later, described this genus as a cosmetic product contami-nant. Further bacterial isolates (Band A, Fig. 6) were groupedwithinthe Firmicutes phylum, and were closely related to Anaerotruncuscolihominis (92% of similarity) and uncultured bacterium clones(99% of similarity).

These results illustrate a diversified spectrum of the bacteriacommunity present in the bioreactor. The majority of the bacterial16S rDNA sequences identified were affiliated with Alpha-proteobacteria. Alpha-Proteobacteria and Actinobacteria identi-fied microorganisms has been reported as major membranebiofouling communities. While Rhizobium and Bradyrhizobiumgenera were found to be responsible for nitrogen fixation. Suchmicrobial community structure was greatly influenced by changesin feed wastewater characteristics, process parameters and oper-ating conditions (OLR and HRT).

4. Conclusions

This study clearly outlines the performance of the SMBR systemin treating cosmetic wastewater. The SMBR treatment managed toremove 98.13% of AS and 83.73% of COD at OLR of 1.5 g COD l-1 d-1

and HRT of 27 h. Higher organic loading have strong effect onmembrane fouling and the MBR removal efficiency.

The PCR-DGGE method provided insights regarding the struc-tures and dynamics over six months of bacterial communities ofthe bioreactor. The results indicated that bacterial communitystructures changed obviously during the treatment period andmost of the identified bacterial sequences belonged either to sur-factant degrading microorganisms or biofouling communities inmembrane separation systems.

Acknowledgments

The research leading to these results has received funding fromthe European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n� 246039 for the project BioNexGen“Development of the next generation membrane bioreactor sys-tem”, (2010e2014).

The authors would like to thank Mrs Particia Bonin (Mediter-ranean Institute of Oceanography, Marseille, France) for performingthe Dendogram cluster analysis.

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