Metaproteomic Analysis of Biocake Proteins To Understand

SYSU-HKUST Research Center for Innovative Environmental Technology, School of Environmental Science and Engineering, Sun Yat-sen University, ...
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Metaproteomic Analysis of Biocake Proteins To Understand Membrane Fouling in a Submerged Membrane Bioreactor Zhongbo Zhou,†,‡ Fangang Meng,*,†,‡ Xiang He,†,‡ So-Ryong Chae,§ Yujia An,†,‡ and Xiaoshan Jia†,‡ †

SYSU-HKUST Research Center for Innovative Environmental Technology, School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510275, P.R. China ‡ Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou 510275, P.R. China § Department of Biomedical, Chemical, and Environmental Engineering, University of Cincinnati, 701 Engineering Research Center, Cincinnati, Ohio 45221-0012, United States S Supporting Information *

ABSTRACT: Metaproteomic analyses, including two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) separation and matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF)/TOF mass spectrometer (MS) detection, were used to trace and identify biocake proteins on membranes in a bench-scale submerged membrane bioreactor (MBR). 2D-PAGE images showed that proteins in the biocake (S3) at a low transmembrane pressure (TMP) level (i.e., before the TMP jump) had larger gray intensities in the pH 5.5−7.0 region regardless of the membrane flux, similar to soluble microbial product (SMP) proteins. However, the biocake (S2 and S4) at a high TMP level (i.e., after the TMP jump) had many more proteins in the pH range of 4.0−5.5, similar to extracellular polymeric substance (EPS) proteins. Such similarities between biocake proteins and SMP or EPS proteins can be useful for tracing the sources of proteins resulting in membrane fouling. In total, 183 differentially abundant protein spots were marked in the three biocakes (S2, S3, and S4). However, only 32 protein spots co-occurred in the 2D gels of the three biocakes, indicating that membrane fluxes and TMP evolution levels had significant effects on the abundance of biocake proteins. On the basis of the MS and MS/MS data, 23 of 71 protein spots were successfully identified. Of the 23 proteins, outer membrane proteins (Omp) were a major contributor (60.87%). These Omps were mainly from potential surface colonizers such as Aeromonas, Enterobacter, Pseudomonas, and Thauera. Generally, the metaproteomic analysis is a useful alternative to trace the sources and compositions of biocake proteins on the levels of molecules and bacteria species that can provide new insight into membrane fouling.



pressure (TMP) evolutions.24,25 Large-size polysaccharides have been reported to be a typical foulant.26,27 Kimura et al.28 revealed the structures and sources of polysaccharides in a pilot MBR using a matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF)/TOF mass spectrometer (MS). Meanwhile, Huang et al.29 found that Proteobacteria and Bacteroidetes were the main species in the biocake. Although the efforts mentioned above have provided some evidence that reveals the development and mechanism of membrane fouling, proteins (one type of potential foulant) have received relatively less attention in the literature. Particularly, the information covering the correlations between proteins and bacterial species in the biocake is sparse. An indepth understanding of proteins is crucial for the implementa-

INTRODUCTION Membrane bioreactors (MBRs) are increasingly employed in diverse fields such as municipal/industrial wastewater treatment,1,2 trace contaminants removal,3,4 and resource/energy recovery.5,6 However, the main obstacle for the sustainable operation of MBRs is membrane fouling.7,8 Microbial flocs and biomacromolecules in activated sludge-mixed liquor can be rejected and adhere onto the membranes in the form of biocake,9,10 which is the primary concern of membrane fouling.11,12 The compositions and properties of the biocake are highly complex and variable, depending on the membrane operation mode (i.e., relaxation/backwash/continuous),13,14 aeration intensity,15 and membrane flux.16−18 Moreover, temporal variation can worsen with compaction of the biocake19 and with microbial metabolism.20 Hence, further investigations of the biocake are required to understand the development of membrane fouling. Membrane foulants in the biocake mainly consist of biomacromolecules and microorganisms.21−23 Their amounts and properties show good correlations with the transmembrane © 2014 American Chemical Society

Received: Revised: Accepted: Published: 1068

September 13, 2014 December 17, 2014 December 17, 2014 December 17, 2014 DOI: 10.1021/es504489r Environ. Sci. Technol. 2015, 49, 1068−1077

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8.7 12.5 20 5817 ± 379

a

“Nr” indicates that the TMP data were not recorded. bS1, S2, S3, S4, and S5 denote Sample 1, Sample 2, Sample 3, Sample 4, and Sample 5 of the biocake on membranes, respectively. cStages A1−A8: TMP evolution cycle of membrane module A. Stages B1−B3: TMP evolution cycle of membrane module B. Stages A1−A3, B1, and A6−A8: Entire fouling processes were recorded with the membrane flux of 26.1, 8.7, and 34.8, respectively. Therefore, the TMP turning point (i.e., TMP jump) could be estimated. Stages A4 and B2: Early fouling process was recorded with the membrane flux of 26.1 (A4) and 8.7 (B2), respectively. In Stage A4 and B2, the biocake samples were taken at the TMP turning point. Stage A5: Membrane was operated to maintain a constant HRT without recording the TMP data. Stage B3: Module B was submerged in the membrane tank to maintain the identical hydraulic conditions without sucking.

34.8

12.5 20 5817 ± 379

140.8−174.4 Nra 0 148.9−158.5 0.019 140.8−148.9 0.019 80.0−140.8 0(S1)b 0−80.0 0.021(S2)b 94.3−140.8 Nra 72.3−94.3 0.0075(S3) 47.0−72.3 0.023(S4)b 26.1 0−31.2 0.025 days of operation (d) final TMP stage (MPa) membrane flux (L/(m2 h)) HRT (h) SRT (d) MLVSS (mg/L)

31.2−47.0 0.024

Module A

Stage A4 Module A

Stage A3 Stage A2 Stage A1 variablec

Table 1. Experimental Stages and Operating Conditions of MBR

MATERIALS AND METHODS Operating Conditions of Submerged MBR. A benchscale MBR with an effective volume of 50 L was employed for the treatment of synthetic wastewater. The MBR included firstanoxic aerobic, second-anoxic anaerobic tanks, and a membrane tank. Detailed information about the reactor is available in the literature.39 In brief, two identical flat sheet membrane modules (i.e., Modules A and B) (PVDF, 0.1 μm, Sinap Corp., Shanghai, China) with a total surface area of 0.23 m2 (i.e., 0.115 m2 each) were immersed in the membrane tank. The critical flux of the membrane was measured to be approximately 17.4 L/(m2 h) (LMH). To investigate the effects of the membrane flux on the TMP evolution and compositions of the biocake, Modules A and B were operated at three different fluxes: 8.7, 26.1, and 34.8 LMH. On the basis of the imposed flux of the two modules, the entire operation was divided into two periods (Table 1). In Period I, Modules A and B were continuously sucked by a peristaltic pump to reach the stable membrane flux levels of 26.1 and 8.7 LMH, respectively. For Module A, in the first three stages (Stage A1−A3), the TMP reached a higher level (approximately 0.020 MPa). Therefore, the entire fouling process, including the TMP jump, could be observed repeatedly. In Stage A4, the operation of Module A was terminated before the occurrence of the TMP jump to collect and analyze the biocake sample at the early fouling level. In Stage A5, the Module A was operated without recording the TMP data to maintain a constant hydraulic retention time (HRT = 12.5 h) in the reactor. For Module B, only one entire fouling process was recorded (Stage B1, 0−80 d) because of its

Period I (0−141 d)

Stage A5



158.5−174.4 0.019(S5)b

Module B

Stage A8 Stage B2 Stage B1

Module B

Stage A6

Period II (141−175 d)

Stage A7

tion of fouling control strategies, such as the use of enzymatic quorum quenching.30 Recently, metaproteomic analysis has been applied to detect microbial functional proteins because this method can provide novel insights into metabolic and physiological activities in mixed microbial cultures (e.g., sludge, biofilm, and soil bacteria).31−33 For instance, the functional proteins related to the formation of biofilms and microbial flocs were identified through an EPS metaproteomic analysis.34−36 According to a 2D-PAGE analysis of proteins on fouled membranes, two outer membrane proteins (OprF and OprD) from the Pseudomonas genus were found to play important roles in membrane fouling.37 Moreover, a chaperonin and outer membrane protein 32 (Omp32) were also detected on fouled membranes.38 Clearly, the metaproteomic analysis can successfully identify membrane fouling caused by proteins. Nevertheless, the flux- or TMP-dependence of proteins in the biocake have not been completely revealed. Moreover, the sources and compositions of proteins in the biocake have yet to be ascertained. This type of research can support earlier findings and improve our understanding of the relationships among membrane fouling processes, biocake proteins, and related bacteria species. In this study, therefore, a bench-scale submerged MBR with two identical flat sheet membrane modules was operated under different membrane fluxes. The biocakes that formed at different TMP evolution stages were collected, and the compositions of the biocakes were analyzed. Moreover, the proteins in the biocake were extracted, purified, and then separated by 2D-PAGE. By comparing the 2D-PAGE images with each other, differentially abundant proteins were analyzed, selected, and then identified using the MALDI-TOF/TOF MS. Finally, the proteins and bacteria species that cause fouling and are implicated in the formation of the biocake were revealed.

Stage B3

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DOI: 10.1021/es504489r Environ. Sci. Technol. 2015, 49, 1068−1077

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Therefore, only S2, S3, S4, SMP, and EPS were used for the 2D-PAGE analysis. Despite inability to run the 2D-PAGE analysis for S1 and S5, the analyses of S2, S3, and S4 were still sufficient to reveal the effects of membrane flux (S2 vs S4) and TMP jump (S3 vs S4) on biocake proteins. The purified proteins of each sample (120 μg for each silver staining gel and 1200 μg for each Coomassie brilliant blue G250 staining gel) were loaded onto a 24 cm immobilized pH gradient (IPG) strip (pH 4−7, GE Biosciences, U.S.A.) with 1% dithiothreitol (DTT), 1% IPG buffer, 1% bromophenol blue (BPB), and a rehydration buffer overnight (10−12 h). Next, isoelectric focusing for the first-dimension separation of proteins was performed at 300 V for 0.5 h, at 700 V for 0.5 h, at 1500 V for 1.5 h, and at 9000 V for 7 h. Afterward, SDS-PAGE was performed for the second-dimension electrophoresis using 5% acrylamide stacking and 10% acrylamide separating gel. The stacking gel was operated at 2 W for 45 min and the separating gel at 17 W for 4.5 h until the bromophenol blue reached the bottom of the gel. A series of different standard molecular weight protein markers ranging from 17 to 170 kDa (Promega, Madison, WI, U.S.A.) was used in the 2D-PAGE for size standardization. After the electrophoresis step, the gels were stained with silver nitrate and Coomassie brilliant blue G-250 and were then scanned on a UMAX Powerlook 1100. A duplicate 2D-PAGE map (Supplementary file-2, Supporting Information) of each sample was simultaneously created to check the reproducibility of this method on the basis of the matching of spots between replicas of the identical samples. All 2D-PAGE images analysis was conducted on Image Master 2D platinum software 5.0 (GE Healthcare, Bio-Sciences, Uppsala, Sweden). The matched protein spots were marked with green (Supplementary file-3, Supporting Information). To obtain information on differentially abundant proteins between two biocake samples, the gray intensities of matched spots (i.e., spot %volume shown in Supplementary file-4, Supporting Information) were calculated and then compared by setting parameters such as smooth, saliency, and min area.42,43 In this current study, a lower fold-change threshold of 1.5 (the ratio of spot % volume between two samples) was considered to avoid omitting some important protein spots. Digestion and Identification of Proteins. According to the analysis of the differentially abundant proteins among the biocake samples, notable protein spots were excised manually from the Coomassie brilliant blue G-250 stained gels for protein digestion. The digestion method of proteins in the gel was similar to that in previous reports.44,45 The detailed procedures are described in Supplementary file-1 of the Supporting Information. All MS and MS/MS spectra were recorded by an Autoflex speed MALDI-TOF/TOF mass spectrometer (Bruker Daltonics Inc.) under the following conditions: The UV laser was operated at a wavelength of 355 nm with a 200 Hz repetition rate and an accelerated voltage of 20 kV, and the detected mass range was 700−3200 Da. Autoflex speed delivers mass accuracy ≤2 ppm and maximum resolving power >26000 in reflection mode. In addition, trypsin autodigestion peaks were used for internal calibration. Flexanalysis version 3.0 (Bruker Daltonics) was used to process all the MS data. The processed MS and MS/MS data were then integrated and uploaded into the MASCOT search engine (V2.3, Matrix Science, London, U.K.) using Biotools 3.1 (Bruker Daltonics). The peptide was matched, and the protein was identified (Supplementary file-5, Supporting Information) in the NCBInr database on the basis of the following

much longer operating time. In Stage B2 (80−140.8 d), to reveal protein compositions in the early fouling level, the biocake samples were taken at the TMP turning point or before the TMP jump. In Period II, the membrane fluxes of Modules A and B were set at 34.8 and 0 LMH, respectively. Under the higher membrane flux, the entire TMP evolution from 0 to 0.019 MPa of Module A was also observed in three replicates (Stage A6−A8). As the TMP jump occurred rapidly, the biocake collection was not conducted. Although Module B did not work, it was still submerged in the membrane tank to maintain the identical hydraulic conditions (Stage B3). Over the two periods, the total permeate rate of the two modules was ca. 4 L/ h. The TMP data of the two modules was individually recorded by a vacuum pressure gauge. The membrane module was cleaned completely to recovery its permeability after each operating stage. The sludge retention time (SRT) of the reactor was maintained at 20 d. During the steady operation, the mixed liquor volatile suspended solid (MLVSS) concentration of the membrane tank was maintained at 5817 ± 379 mg/L. NaHCO3 was added into the mixed liquor to maintain the pH between 7.0 and 7.5. The MBR was operated in an air conditioned room to maintain the temperature in the range of 22−25 °C. Sampling of Biocake. Biocake samples of Modules A and B with respective membrane flux levels of 26.1 (Sample 3, S3) and 8.7 LMH (Sample 1, S1) were taken at low-fouling stages (TMP = 0.0075 and 0 MPa) to investigate the compositions of the biocake before the TMP jump. In addition, when the TMP increased to approximately 0.020 MPa, biocake samples (Samples 2, 4 and 5; S2, S4, and S5, resepctively) were also collected to reveal the effect of different membrane fluxes on the compositions of the biocake after the TMP jump. The fouled membrane modules were taken out of the reactor and flushed with high-pressure water to remove the biocake, after which the bulk solutions were collected. Afterward, the flushed membranes were soaked in a NaOCl (0.3%) solution for 12 h and then in a 0.1 mol/L H3PO4 solution for 1 h to remove the residual foulants completely. The pure water permeability of the membranes after each step was measured to calculate the hydraulic residence according to Darcy’s Law. The bulk solutions of the biocake were mixed gently using magnetic stirrers to disperse the agglomerated sludge flocs and gel-like organic matter for approximately 2−4 h at 4 °C and were then filtered through 0.45 μm membranes to obtain the supernatant. Subsequently, a tangential flow filtration system (Cogent, Millipore Corporation, U.S.A.) with a Pellicon PVDF cassette filter (1 kDa) was used to concentrate the supernatant and remove salts from these samples. Additionally, SMP and EPS in the mixed liquor of the reactor were extracted at regular intervals (i.e., 1−2 weeks), and the SMP/EPS solutions were then pretreated using the identical method described above. 2D-PAGE. First, the proteins in the samples were extracted and purified. The related protocol was mainly based on previous reports40,41 with minor modifications, and its details are described in Supplementary file-1 of the Supporting Information. Afterward, the purified and dried protein pellets were dissolved in 200 μL of a rehydration buffer by sonication (80 w, 0.8 s on/0.8 s off, 8 times) and then centrifuged at 12,000 r/min for 20 min at 4 °C to obtain the supernatant. Prior to the 2D-PAGE analysis, the amount of protein in the supernatant was measured by the Bradford assay to check whether the biocake samples had a sufficient amount of proteins. Unexpectedly, the amounts of proteins in S1 and S5 were insufficient for the Coomassie blue staining gels tests. 1070

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Environmental Science & Technology parameters: (1) taxonomy of all entries followed by the Bacteria or Fungi database, which could minimize the risk of missing some of the mass spectra for matches in the entire database and maximum the probability of significant matching in the Bacteria and Fungi databases,44,45 (2) trypsin of the digestion enzyme, (3) up to one missed cleavage site, (4) parent ion mass tolerance at 50 ppm, (5) MS/MS mass tolerance at 0.5 Da for fragmented ions, and (6) carbamidomethyl modification of cysteine as a fixed modification and oxidation of methionine as a variable modification. A successful identification of proteins depended on the probability score (>73) and significant level (p < 0.05) (Supplementary file-5, Supporting Information). Analysis. Before the metaproteomic analysis, the total amounts of polysaccharides and proteins in each biocake sample were quantified by the Dubois46 and Lowry47 methods, respectively. The influence of nitrate and nitrite on polysaccharide measurements was corrected by the method of Drews.48 Concentrations of ammonium, nitrite, nitrate, total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), and VSS were measured according to APHA standard methods.49 The extraction methods for SMP and EPS can be found in the literature.50



RESULTS AND DISCUSSION Performance of Submerged MBR. Over the entire operation, the average removal efficiency levels of COD, NH4+−N, TN, and TP were as high as approximately 95%, 100%, 85%, and 89%, respectively. More details are available in the literature.39 Figure 1a presents the different TMP evolution profiles at different membrane fluxes. A higher flux resulted in a faster rise in the TMP, notably for the membrane at 34.8 LMH. By contrast, the membrane at the low flux of 8.7 LMH showed a negligible fouling rate of approximately two months. These results are consistent with previous studies,17,20,29 which indicated that the TMP increase strongly depends on the imposed flux. More significantly, the TMP evolution profiles at 8.7 and 26.1 LMH showed a turning point, dividing the membrane fouling processes into two phases. The first phase had a long-term gradual TMP rise, whereas the second phase showed a short-term sudden TMP rise. This indicated that different membrane fouling mechanisms functioned before and after this turning point. As shown in Figure 1b, the biocake resistance (Rcake) was a major portion of the total resistance. Particularly, Rcake at the flux level of 8.7 LMH (S2) accounted for 94% of the total filtration resistance when the TMP reached 0.025 MPa. Moreover, the Rcake values of these highly fouled membranes (S2, S4, and S5) increased significantly as the flux decreased. These values were 8.73, 2.47, and 0.83 × 1012 m−1, respectively. However, the membranes at low TMP levels (S1 and S3) retained a good permeability despite the fact that their Rcake accounted for a large percentage of the total filtration resistance. Hence, it can be predicted that biocake at different imposed fluxes and TMP levels will have various characteristics and compositions. Effects of Flux and TMP on Compositions of Biocake. Amounts of VSS, polysaccharides, and proteins in the biocake varied considerably with different fluxes and fouling stages (Table S1, Supplementary file-1, Supporting Information). Among these components, VSS appeared at the highest levels in all of the biocake samples, in agreement with the high proportion of Rcake in the total resistance. Specifically, the VSS accounted for 60−90% of all foulants in the biocake on the

Figure 1. (a) TMP profiles of membranes under different membrane fluxes and fouling levels and (b) hydraulic resistance distributions of membranes at different sampling points. Sample 1 was collected before the TMP jump at an operating flux of 8.7 LMH after a long-term operation. Samples 2, 4, and 5 were taken after the TMP jump for the three fluxes of 8.7, 26.1, and 34.8 LMH, respectively. Sample 3 was collected before the TMP jump at an operating flux of 26.1 LMH.

highly fouled membranes. Nevertheless, membrane fouling cannot solely be attributable to biomass deposition on the membranes. First, the occurrence of the turning point in the TMP evolution is the most important with regard to the membrane fouling process; once the turning point occurs, the TMP will jump suddenly and biomass will be accumulated in the biocake. Notably, regarding the membranes at the fluxes of 8.7 and 26.1 LMH, the VSS in the biocake increased sharply from 31.3 (S1) and 8.70 g/m2 (S3) at a low TMP level to 255.13 (S2) and 66.96 g/m2 (S4) at a high TMP level. More importantly, this process occurred in a very short period that only accounted for 15−25% of the overall operation time. Therefore, the compositions and characteristics of the biocake before the TMP jump are of great significance when attempting to understand the development of membrane fouling. Second, a higher portion of biomass in the biocake does not indicate poor membrane permeability, which in contrast can potentially act as a dynamic membrane for better filtration performance.51,52 In comparison with biomass or sludge flocs, biomacromolecules such as proteins and polysaccharides have adverse effects on membrane permeability because of their large molecular size and strong adhesion/gelling propensity. 53 Comparable amounts of proteins relative to the amounts of polysaccharides were observed in the S1, S3, and S4 biocake samples. However, 1071

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Figure 2. 2D-PAGE images of proteins in S2 (a), S3 (c), S4 (b or d), SMP (e), and EPS (f). In the 2-DE analysis, spots for detectable proteins were distributed on 24 cm 2D-gels (pH 4−7) loaded with 120 μg of total protein/gel. The spots were visualized by silver staining. “S2:S4” represents the abundance of proteins that increased in sample 2 (S2) compared with sample 4 (S4). “S4:S2” represents the abundance of proteins that increased in Sample 4 compared with Sample 2. The differentially abundant proteins are marked with green numbers on the basis of 1.5-fold gray intensity changes of the spots between two compared samples.

ing Information), indicating that the proteins were extracted with high purity and were separated efficiently. As shown in Figure 2, most of the protein spots in the biocake samples appeared with an isoelectric point in the acidic region (pH 4.0− 5.5). Particularly, the biocake formed at high TMP levels (S4 and S2) had many more spots in the acidic region compared with that formed at a low TMP level (S3) (Figure 2a, c, and d). However, the biocake protein spots in S3 had greater gray intensities in the pH 5.5−7.0 region than those in S2 and S4 (Figure 2a and c). Additionally, most of the protein spots in the EPS were distributed in the pH range of 4.0 to 5.5 (Figure 2f), whereas the proteins spots in the SMP had greater gray intensities in the range of pH 5.5 to 7.0 (Figure 2e). On the basis of the protein spot distribution of the biocake and SMP/ EPS, we can assume that SMP-proteins are likely a major contributor to the proteins in the biocake formed before the TMP jump (S3), whereas EPS−proteins abundance in the biocake increased significantly after the TMP jump (S2 and S4). Because the biocake of S3 had less biomass (8.70 g/m2) and thus yielded less EPS; the high-intensity protein spots in the pH 5.5−7.0 range may originate from the SMP of the mixed liquor. In comparison, the biocake samples at high TMP levels (S2 and S4) contained considerable amounts of biomass (255.13 and 66.96 g/m2), which likely had a greater potential to

the S2 and S5 biocake samples clearly contained more polysaccharides than proteins, which is likely because of the yield and/or deposition of polysaccharides during the processes of the TMP jump and biomass accumulation.20 Hwang et al.20 reported that the increased amount of polysaccharides along the depth of the biocake mainly arose for two reasons: (1) cake compaction at a high flux and (2) cell endogenous decay/dead at a low flux. The variation in the membrane rejection efficiency because of the thick and compacted cake may be another reason for the biomacromolecule accumulation. Surprisingly, proteins in the biocake did not accumulate much, unlike biomass and polysaccharides during the TMP jump. Before and after the TMP jump, the amounts of the proteins did not change significantly. Therefore, the roles of proteins in the biocake are often ignored, and their functions during the TMP jump have remained unclear. 2D-PAGE Images of Biocake Proteins. To obtain detailed information about differences in the abundance of proteins, we applied 2D-PAGE to analyze the biocake proteins formed under different imposed fluxes and TMP levels. Proteins in the SMP and EPS were also analyzed to trace the potential origins of biocake proteins. Highly reproduced spots were observed between the parallel gels of each sample with ignorable background staining (Supplementary file-2, Support1072

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Table 2. Identification and Functional Classification of Differentially Abundant Proteins in Different Biocakes According to MALDI-TOF/TOF MS biocake samplec

coverage of peptidesd

scoree

species

2*,4

11% (2)

135

Thauera sp. MZ1T

structural molecule activity

Betaproteobacteria

2*,3**,4

8% (2)

113

porin activity

Gammaproteobacteria

Omp38 protein precursor outer membrane porin, OprD family protein outer membrane protein A

2*,3 2

44% (9) 15% (6)

196 123

porin activity porin activity

Gammaproteobacteria Gammaproteobacteria

2

15% (3)

98

porin activity

Gammaproteobacteria

MltA-interacting MipA family protein protein srpI

2*,3,4**

79% (17)

533

Aeromonas hydrophila ATCC 7966 Aeromonas veronii Pseudomonas mandelii JR-1 Cronobacter turicensis z3032 Thauera sp. MZ1T

_

Betaproteobacteria

2**,3,4*

33% (8)

230

putative metal binding site

Alphaproteobacteria

2,4*

14% (12)

356

proteins transporting

Betaproteobacteria

2,3*,4**

90% (9)

91

_

Gammaproteobacteria

gi|401675410

outer membrane autotransporter barrel domain-containing protein Hypothetical protein EC34870_2515, partial outer membrane protein

2,3**,4*

11% (3)

167

porin activity

Gammaproteobacteria

B49

gi|422318484

elongation factor Tu, partial

2,3**,4*

20% (8)

273

Betaproteobacteria

B57

gi|59711111

4

22% (5)

173

Vibrio fischeri ES114

E31

gi|26986791

deoxyribose-phosphate aldolase porin

3,4*

27% (12)

442

D02

gi|395761455

stress protein

3*,4

43%(7)

250

D11

gi|421497572

2,3**,4*

25% (8)

363

D12

gi|354722840

major outer membrane protein OmpAI outer membrane protein A

3*,4

21%(7)

269

D21

gi|30793638

Omp48 protein precursor

2*,3**,4

34%(11)

229

Pseudomonas putida KT2440 Janthinobacterium sp. PAMC 25724 Aeromonas media WS Enterobacter mori LMG 25706 Aeromonas veronii

GTP binding; GTPase activity; translation elongation factor activity lyase; deoxyribose-phosphate aldolase activity porin activity

F12

gi|401675410

outer membrane protein

2,3**,4*

40% (10)

379

F25

gi|421498148

sucrose porin

2*,3**,4

25% (10)

163

F26

gi|334705392

2, 3*

41% (22)

334

F28

gi|293977799

2,3**,4*

9% (4)

129

A03 F21

gi|76445989 gi|356512586

type I secretion outer membrane protein, TolC translation elongation factor EF-1A/EF-Tu serum albumin LETM1 and EF-hand domain-containing protein 1, mitochondrial-like

2 2,3**,4*

14% (5) 20% (10)

137 86

spot IDa

gene IDb

A02

gi|217970295

A12

gi|117620259

A18 A32

gi|31088942 gi|407363407

C01

gi|260597356

B14

gi|237654518

B06

gi|338737005

E07

gi|217970394

B09

gi|425097935

B24

protein name hypothetical protein Tmz1t_1881 outer membrane protein

Hyphomicrobium MC1 Thauera sp. MZ1T

Escherichia coli 3.4870 Enterobacter sp. SST3 Achromobacter xylosoxidans C54

Enterobacter sp. SST3 Aeromonas media WS Aeromonas caviae Ae398 Candidatus Sulcia muelleri DMIN Bos indicus Glycine max

function

taxon

Gammaproteobacteria Gammaproteobacteria

_

Betaproteobacteria

porin activity

Gammaproteobacteria

porin activity

Gammaproteobacteria

maltodextrin/maltose transporting porin activity porin activity

Gammaproteobacteria Gammaproteobacteria

porin activity

Gammaproteobacteria

porin activity

Gammaproteobacteria

protein synthesis

Bacteroidetes

transport calcium ion binding

Eukaryota Eukaryota

a

Protein spot ID refers to green numbers in Figure 2. bGene ID is the MASCOT result of MALDI-TOF/TOF searched from the NCBInr database. “**” represents the highest gray intensity. “*” denotes the second highest gray intensity. Absence of “*” denotes the lowest gray intensity. d Coverage (%) is the number of amino acids spanned by the assigned peptides divided by the sequence length. eProtein scores based on combined MS and MS/MS spectra were from the MALDI-TOF/TOF identification process. The proteins that had a statistically significant protein score of more than 73 (significant level, p < 0.05) were considered to have been successfully identified. c

release and produce EPS, thus leading to the finding that many more protein spots appeared in the pH range of 4.0−5.5. However, the large amount of biomass in the biocake induced the biodegradation of the deposited SMP such that the gray intensity level of the protein spots could be reduced in the pH range of 5.5−7.0. On the basis of the biodegradation kinetics of membrane foulants and SMP/EPS, we found that EPS was the major contributor to the proteins in the biocake on highly fouled membranes (after the TMP jump).50 Differentially Abundant Proteins in Biocake. As shown in Figure 2, four comparison groups (S2:S4/S4:S2 and S4:S3/

S3:S4) were considered with the 1.5-fold gray intensity change for spots between two compared 2D-PAGE images. According to this analysis, 183 protein spots were marked in green (Supplementary file-3, Supporting Information). The gray intensities of these spots are shown in Supplementary file-4 of the Supporting Information. Of them, only 32 protein spots co-occurred in the 2D-PAGE images of three different samples (S2, S3, and S4) with distinct gray intensities. This indicates that membrane fluxes and TMP evolution levels had significant effects on the abundance of proteins (e.g., amounts and gray intensities of spots) in the biocake. Under the identical high 1073

DOI: 10.1021/es504489r Environ. Sci. Technol. 2015, 49, 1068−1077

Article

Environmental Science & Technology

Figure 3. Relative gray intensity levels of biocake proteins identified from potential colonizers (Aeromonas, Enterobacter, and Pseudomonas) in S3 and S4 (before and after the TMP jump) and the exopolysaccharide producer (Thauera sp. MZ1T) in S2 and S4 (thick biocake). The values besides the spots in each graph denote the intensity levels of the protein spots.

TMP level (approximately 0.020 MPa), 141 differentially abundant proteins were noted between S2 and S4, including 86 significantly increased-abundance protein spots and 55 significantly decreased-abundance protein spots as the membrane flux increased from 8.7 (S2) to 26.1 LMH (S4). Of the increased-abundance protein spots, 61 protein spots were newly induced in S4 and were not found in S2, indicating that a higher flux could enhance more types of proteins to attach onto the membranes. Among the decreased-abundance proteins, 35 protein spots in S2 completely disappeared in S4. Under the identical membrane flux (26.1 LMH), a total of 108 protein spots were observed to change dynamically between S3 (before the TMP jump) and S4 (after the TMP jump), specifically 60 significantly increased-abundance protein spots and 48 significantly decreased-abundance protein spots. Among them, 26 protein spots newly appeared, whereas 22 protein spots disappeared after the TMP jump. In addition, specific protein spots that only exist in one given sample were noted, as marked by the red star icons (Figure S1a, b, and c, Supplementary file-1, Supporting Information). Notably, 21 specific protein spots were found in S2, a much higher number compared with those in S3 (4 spots) and S4 (10 spots). Moreover, these specific proteins were mainly distributed in the pH range of 4.0−5.5, indicating that they most likely originated from the EPS proteins yielded by the newly deposited bacteria after the TMP jump. Again, as S3 contained less biomass in the biocake, the proteins may stem mainly from the rejection of the SMP proteins, thus resulting in S3 only having four specific protein spots. Hence, the increased number of specific proteins spots in the biocake could be a signal of biomass accumulation on membranes, which could be crucial for understanding the development of membrane fouling. Identification and Fouling Propensity of Biocake Proteins. In total, 71 protein spots were selected and then digested for the MS analysis. The MS spectra and MS/MS fragmentation of peptides are listed in Supplementary files-5 of the Supporting Information. Among the analyzed protein spots, only 23 spots were successfully identified. Such a low

identification proportion of proteins was most likely attributable to three reasons: (i) inaccuracy excision process of spots leading to useless MS data, (ii) complexity of proteins from the activated sludge system, and (iii) incomplete genome information on wastewater treatment microbes.41,44,45,54 Kuhn et al.41 also attributed the low protein identification rate (25%) to missing genomic sequences when they searched against the NCBInr database with nanoHPLC-nanoESI-MS/MS data. Detailed information about the 23 successfully identified proteins and their functions are listed in Table 2. Of the 23 proteins, over half (60.87%) originated from the outer membrane of the cell, with roles in porin activity. Porins are normally recognized as a type of special channel through which numerous small molecules (