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Predation influences the structure of biofilm developed on ultrafiltration membranes
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Predation influences the structure of biofilm developed on ultrafiltration membranes Nicolas Derlon a,*, Maryna Peter-Varbanets a, Andreas Scheidegger a, Wouter Pronk a, Eberhard Morgenroth a,b a b
Eawag, Swiss Federal Institute of Aquatic Science and Technology, U¨berlandstrasse 133, P.O Box 611, CH-8600 Du¨bendorf, Switzerland Institute of Environmental Engineering, ETH Zu¨rich, 8093 Zu¨rich, Switzerland
article info
abstract
Article history:
This study investigates the impact of predation by eukaryotes on the development of
Received 15 July 2011
specific biofilm structures in gravity-driven dead-end ultrafiltration systems. Filtration
Received in revised form
systems were operated under ultra-low pressure conditions (65 mbar) without the control
14 March 2012
of biofilm formation. Three different levels of predation were evaluated: (1) inhibition of
Accepted 15 March 2012
eukaryotic organisms, (2) addition of cultured protozoa (Tetrahymena pyriformis), and (3) no
Available online 2 April 2012
modification of microbial community as a control. The system performance was evaluated based on permeate flux and structures of the biofilm. It was found that predation had
Keywords:
a significant influence on both the total amount and also the structure of the biofilm. An
Ultrafiltration
open and heterogeneous structure developed in systems with predation whereas a flat,
Predation
compact, and thick structure that homogeneously covered the membrane surface devel-
Biofilm structure
oped in absence of predation. Permeate flux was correlated with the structure of the bio-
Permeate flux
film with increased fluxes for smaller membrane coverage. Permeate fluxes in the presence
Optical Coherence
or absence of the predators was 10 and 5 L m2 h1, respectively. It was concluded that
Tomography (OCT)
eukaryotic predation is a key factor influencing the performance of gravity-driven ultra-
Confocal Laser Scanning
filtration systems. ª 2012 Elsevier Ltd. All rights reserved.
Microscopy (CLSM) Gravity-driven membrane (GDM) filtration
1.
Introduction
Biofouling reduces the water flux in membrane filtration systems and significant efforts are directed towards preventing or reducing biofilm formation on the surface of membrane. For example, in membrane bioreactors for wastewater treatment, biofilm formation is controlled by coarse bubble aeration resulting in increased shear stress at the membrane surface and by chemical cleaning (Le-Clech et al., 2006). In drinking water systems, membrane modules are regularly back flushed and cleaned with hypochlorite multiple times per week. In nanofiltration and reverse
osmosis, intensive pre-treatment is used. Practical experience, however, demonstrates that biofilm formation cannot be prevented. Removal of biofilms requires significant amounts of energy and chemicals, which significantly increases costs of operation of membrane systems. Thus, a different approach for the operation of membrane systems has to be investigated, avoiding extensive cleaning and flushing operations. A different strategy was proposed by Peter-Varbanets et al. (2010) where biofilm formation on the membrane is tolerated and the focus was on maximizing the permeability of the biofilm. In their study ultrafiltration (UF) systems were
* Corresponding author. Tel.: þ41 44 823 5378. E-mail address: [email protected] (N. Derlon). 0043-1354/$ e see front matter ª 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2012.03.031
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operated without any cross-flow and without membrane cleaning. Under these conditions a highly permeable biofilm is formed that allows for long-term (months) operation of the system without cleaning or backwashing. The formation of this heterogeneous biofilm resulted from biological processes and was not observed when biological activity was reduced (by cold temperature) or inhibited (by addition of sodium azide) (Peter-Varbanets et al., 2010). However, the nature of these processes (e.g., bacterial growth, predation) as well as their impacts on the system performances were not clearly identified. The current study evaluates the influence of predation on structure and permeability of biofilms formed during dead-end ultrafiltration. A range of physical and biological factors influences biofilm structure. Local biofilm growth is limited by substrate availability and biofilm growth is balanced by external forces resulting in biofilm detachment (van Loosdrecht et al., 1995). In systems where the availability of substrate is mass transport limited bacteria that are closer to the bulk phase have a competitive advantage resulting in low-density heterogeneous structures (Picioreanu et al., 1998). High detachment forces, however, can balance this phenomenon. As a result, heterogeneous structures develop under low shear conditions and/or high surface loading rate (Picioreanu et al., 2001). These conceptual and numerical modelling studies assume that the development of biofilm structure can solely be explained by local availability of substrate and physical forces. This approach explains in many cases the biofilm structures that are experimentally observed in industrial systems such as wastewater treatment plants. In the case of biofilms grown at a very low substrate concentrations (e.g., stream biofilms) factors such as quorum sensing or eukaryotic predation have been shown to be dominant factors determining biofilm structure (Bo¨hme et al., 2009). Recent studies performed in the field of stream biofilms indeed reported that predation by eukaryotes significantly impacts the morphology of biofilms (Bo¨hme et al., 2009; Weitere et al., 2005). Predators can indeed reduce the biomass concentration and alter its morphology due to grazing (Weitere et al., 2005), motility (Jackson, 1990), or sloughing induced by raptorial feeders (Fenchel and Finlay, 1986). The enhanced formation of micro-colonies and the resulting channel network yields a rougher biofilm surface compared with ungrazed biofilm (Bo¨hme et al., 2009). If predation significantly influence biofilm structure and overall amount of biofilm then predation may be relevant factor influencing the performance of membrane filtration systems e especially in systems operated without cross-flow that provide very suitable conditions for the larger eukaryotic organisms to develop. The objectives of this study were (1) to identify the influence of predation on the overall amount and the structure of biofilm during ultra-low pressure UF and (2) to correlate the biofilm formation with membrane performance (quantified as water flux or specific resistance). We hypothesized that eukaryotic predation increases biofilm heterogeneity and that increased biofilm heterogeneity in turn results in an increased water flux. To evaluate this hypothesis, three gravity-driven UF systems were operated in parallel with (1) inhibition of eukaryotic organisms, (2) addition of cultured protozoa (Tetrahymena pyriformis), and (3) no modification as a control. Long-term (up to
three months) dead-end filtration experiments were performed monitoring total amount and spatial distribution of the biofilm in combination with the permeate flux.
2.
Materials and methods
2.1.
Experimental setup and operating conditions
2.1.1.
Experimental setup
Three experimental lines each composed of five parallel membrane modules were operated as shown on Fig. 1. Feed water was pumped to a completely mixed tank that is controlled to 20 C and connected to a storage tank. The storage tank was placed at a height corresponding to a pressure of 65 mbar applied at the surface of the membrane. The level of water in the water tank was kept constant using an overflow. The tank was connected to the membrane modules using silicon tubes (Saint-Gobain, Bompass, France). Permeate of every module was collected in a separate plastic bottle and quantified gravimetrically in daily intervals. Water was withdrawn continuously from a creek (Chriesbach, Du¨bendorf, Switzerland) and used as feed water. Total organic carbon (TOC) and dissolved organic carbon (DOC) of the feed water were measured twice per week as described in Section 2.5.
2.1.2.
Membrane
Polyethersulfone membrane (PBHK, Biomax Millipore, Billerica, MA, USA) with a nominal cutoff of 100 kDa was used in this study (mean pore size of approximately 10 nm). To remove conservation agents the new membranes were stored for 24 h in deionized water. The deionized water was renewed several times during this period. Membranes were then placed in filtration modules that consisted of standard polycarbonate filter holders of 48 mm inner diameter (Whatman, Maidstone,
Fig. 1 e Scheme of one experimental line including: the water bath with temperature controlled to 20 C, the storage tank, the filtration modules containing the polyethersulfone membrane (100 kDa) and the bottles for permeate collection.
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Kent, UK). The filtration modules were operated continuously without flushing or cleaning.
2.1.3.
Predation levels and operating conditions
Three different predation levels were applied in three experimental lines operated in parallel. One line was operated with inhibition of eukaryotes (Low Predation, Low-P). Eukaryote inhibition was achieved by continuous addition of cycloheximide, an antibiotic specific to eukaryotic organisms. A second line was operated without control of predators (Natural Predation, Nat.-P). A third line was inoculated with an exogenous source of protozoa (T. pyriformis) (High Predation, HighP). The details of Cycloheximide and T. pyriformis addition are presented in parts 2.2 and 2.3, respectively. Two experimental runs were performed to identify the impact of predation on the biofilm structure and in turn on the system performances. Experiment 1 was operated for a period of four weeks where inhibition of eukaryotes and addition of T. pyriformis was done at the beginning of the experimental run and the water temperature was controlled at 20 C throughout the entire experiment. Experiment 2 was performed in two phases where during the first two months all systems were first conditioned without inhibition of eukaryotes and addition of T. pyriformis and the systems were operated with creek water without temperature control (approximately 7 C). After this conditioning phase the systems were exposed to the different treatments and the water temperature was controlled to 20 C. For experiment 2 the end of the conditioning phase is defined as the start of the experiment.
2.2.
Inhibition of predation
Cycloheximide solution at a concentration of 3.5 g L1 was injected in the five Low-P modules using a syringe-pump. The flow rate (approximately 30 mL d1) was adjusted based on the observed filtration flux to reach a stable concentration of 100 mg L1 in the permeate.
2.3.
Enhancement of the predation
The ciliate T. pyriformis (1630/1W, Culture Collection of Algae and Protozoa, Dunbeg, UK) was used in the High-P case. T. pyriformis was grown anexically in PPY (Proteose Peptone Yeast extract) medium. PPY medium is composed of proteose peptone (20.0 g L1) and yeast extract (2.5 g L1) added to 1 L of Evian water (E´vian-les-Bains, France). The medium was autoclaved at 15 psi for 15 min. 50 mL of two weeks old culture were was centrifuged at 4500g for a period of 10 min to remove the supernatant and then resuspended in Evian water. This step was once repeated before injecting the culture directly into the silicon tubes connecting the water tank with the filtration modules. Viability of the protozoa after centrifugation and before inoculation was controlled by direct microscopic observations.
2.4.
Eukaryote abundance
Fluorescent In Situ Hybridization (FISH) was used to qualitatively evaluate the abundance of eukaryote organisms. A
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eukaryote specific FISH probe was used: EUK1209 (50 - GGG CAT CAC AGA CCT G -30 ) (Amann et al., 1990). First, entire membranes were sampled and fixed with formaldehyde solution (2.5%), and then cut into subsections of around 0.25 cm2. Subsections were then placed in microtubes filled with a hybridization buffer (750 mM NaCl, 100 mM TriseHCl [pH 7.8], 5 mM EDTA, 0.1% sodium dodecyl sulphate). FISH probes were then added to reach a final concentration of 250 ng mL1. Hybridization was performed for a period of 4 h at 45 C. The membrane subsections were then placed in microtubes containing Evian water filtered at 0.45 mm to stop the hybridization process. Organisms were observed with a Confocal Laser Scanning Microscope (CLSM) (Leica SP5, Wetzlar, Germany) using 20 or 63 glycerol immersion Leica objectives. Numerical Apertures (NA) were 0.7 and 1.3 for the 20 and 63 lenses, respectively. Direct microscopic observations of the eukaryote abundance were in addition performed in parallel of the FISH analysis. For this purpose, the biofilms developed on the membrane subsections were scratched with the help of a scalpel and resuspended in filtered Evian water. A stereomicroscope (Leica M205, Wetzlar, Germany) was used.
2.5.
Chemical analysis
The accumulated mass of the biofilm (g C m2) was measured through the measurement of the Total Organic Carbon (TOC). Membranes were sampled and the entire biofilms detached by flushing 100 mL of nanopure water with the help of a sterile syringe. Since biofilms were flushed with significant amounts of nanopure water, the Dissolved Organic Carbon was insignificant and thus the TOC was equal to the particulate organic matter. The TOC concentration of the samples was measured using an automatic total organic carbon analyser (TOC-V, Shimadzu, Japan). Before determination, the unfiltered samples were homogenized with a mixer (Polytron PT 3100, Kinematica, Bohemia (NY), USA) (2 min with 15,000 rpm), a magnetic stirrer was added, and the sample was then closed using parafilm. Homogenization during injection ensured measurement is performed on a representative sample (avoiding sedimentation during injection into the TOC analyser). The analyser was calibrated with a stock solution composed of sodium nitrate (6.068 g L1), potassium hydrophtalate (2.126 g L1), and orthophosphoric acid (85%, 2 mL L1) dissolved in carbon-free water.
2.6.
Biofilm characterization
2.6.1.
Micro-scale characterization (CLSM)
The micro-scale structure of the biofilm (morphology, thickness) was characterized by CLSM. First, membranes were sampled and fixed with formaldehyde solution (2.5%), washed twice with filtered Evian water and cut in sections of around 0.25 cm2. Then, biofilm samples were stained, incubated in the dark (4 h, 20 C) and washed again. SYBR Gold nucleic acid gel stain (1000 fold diluted stock solution, Invitrogen, Basel, Switzerland) was used to detect all microorganisms. Concanavalin A (50 fold diluted stock solution, Invitrogen, Basel, Switzerland) was used to stain the a-D -mannose and a-Dglucose groups of biopolymers. These stains were applied on
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the same membrane subsections. Dehydration of the samples was then performed and consisted of six immersion steps of 20 min each in glycerol/water solutions with an increasing gradient (40, 60, 80, 90, 95 and 100%). The fluorescence of SYBR Gold was detected by excitation at 488 nm and emission at 495e540 nm. Concanavalin A was detected with an excitation at 514 nm and emission at 550e620 nm. The reflection from surfaces impermeable for light was detected at the wavelength of 633 nm using CLSM reflective mode. Ten side-view images and five z-stacks were recorded for each environment at weekly intervals. The position of the objectives was randomly changed in the x and y directions when recording side-view images and z-stacks to avoid subjective impact of the user and thus to record representative data. Biofilm morphologies were evaluated throughout the analysis of these images. No quantification of CLSM images (e.g. biovolume, biofilm thickness) was performed.
Where Yt is the quantitative variable that is considered (mean biofilm thickness or relative roughness coefficient), b1 is the slope of the Nat.-P case, b2 is the difference in slope of the Nat.-P and Low-P and b3 the difference in slope between Nat.-P and High-P. I(Low-P) and I(High-P) are the indicator variables (equal to 0 or 1 depending of the data set that is considered). Ttest and P-value calculations were then performed to statistically distinguish the different slopes that were calculated.
2.6.2.
2.6.3.
Optical Coherence Tomography (OCT)
Optical Coherence Tomography (OCT) (model 930 nm Spectral Domain, Thorlabs GmbH, Dachau, Germany) with a central light source wavelength of 930 nm was used to investigate the meso-scale structure of the biofilm. The use of long wavelength light allows to penetrate up to a depth of 2.7 mm with axial and lateral resolutions of 4.4 mm and 15 mm, respectively. For the image acquisition filtration modules were opened and carefully placed on the OCT stage. OCT images were recorded keeping the samples immersed in a thin layer of permeate. Around 20 A-Scans (i.e., XZ plane pictures) of either 5 1 mm, 5 0.5 mm, or 3 0.5 mm (depending of the biofilm thickness) were acquired at different time intervals and for each filtration modules. Image analysis software developed under Matlab (MathWorks, Natick, US) was used to analyse OCT image. Image analysis consisted of the following steps: (1) detecting the membraneebiofilm interface (grey-scale gradient analysis); (2) binarizing the image (automatic thresholding); (3) calculating physical properties of the biofilm: mean biofilm thickness (z in mm), absolute (Ra in mm) and relative roughness ðR0a Þ coefficients. These parameters were calculated according the following equations: z¼
N 1X zi n i¼1
N 1X ðjzi zjÞ Ra ¼ n i¼1
R0a ¼
N 1X jzi zj z n i¼1
(1)
relative roughness coefficient. The linear least square function of R (R Development Core Team, 2011) version 2.13.0 was used to fit the model. This approach consisted in comparing the slope of the change in the mean biofilm thickness or relative roughness to the slope of natural predation (Nat.-P). First-order equations with qualitative variables were used for this analysis Eq. (4): Yt ¼ b0 þ b1 $t þ b2 $IðLow PÞ$t þ b3 $IðHigh PÞ$t þ εt
(3)
where N is the number of thickness measurements, zi is the local biofilm thickness (mm), and z is the mean biofilm thickness (mm). Linear regression analysis was performed to statistically evaluate the effect of the level of predation on the biofilm physical structure in terms of mean biofilm thickness and
Top view biofilm pictures
Top views of the biofilms developed on the membranes were recorded using an Olympus C-7070 digital camera (Olympus, Le Mont-sur-Lausanne, Switzerland). The meso-scale characterization of biofilms consisted in measuring the membrane coverage as the fraction of the membrane surface that is covered by biofilms. Top view pictures were treated using ImageJ (http://rsb.info.nih.gov/ij/). First, the images were converted into 8-bits pictures. A threshold was then manually adjusted and applied to obtain binary images. The value of threshold was determined in order to distinguish the relevant structure, i.e., the biofilm and the uncovered membrane. The effective surface of membrane was finally selected to calculate the membrane coverage.
2.7.
Flux and hydraulic resistance
2.7.1.
Filtration flux
The permeate flux was calculated by measuring the mass of water collected in each bottle and dividing the results by the filtration period and by the membrane area. The mass of permeate was weighed daily using a scale (Ohaus Adventure Pro, Pine Brook (NJ), USA).
2.7.2.
Hydraulic resistances
The total resistance of the fouled membrane was calculated according to the Darcy’s law: J¼
(2)
(4)
DP m$Rtotal
(5)
Where DP (Pa) is the transmembrane pressure (65 mbars in this study), m is the viscosity (Pa s) of the filterate, Rtotal is the total resistance (m1), and J is the filtration flux (m s1). The total resistance Rtotal can be represented as the sum of individual resistances: Rtotal ¼ Rmembrane þ Rbiofilm þ Rirreversible
(6)
Where Rmembrane is resistance of the pristine membrane, Rbiofilm is resistance of the biofilm, and Rirreversible is resistance caused by the irreversible fouling. Two membranes per line were sampled to estimate Rbiofilm. First, the biofilm was
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detached from the membrane surface by flushing with 100 mL of deionized water using a syringe. Membranes were then returned to filtration modules and the flux of the flushed membrane was determined by filtering nanopure water. It is assumed that the after flushing the resistance is the sum of Rirreversible and Rmembrane. Based on the resistances measured of the fouled membrane, the resistance after flushing, and the resistance of the virgin membrane the different resistances in Eq. (6) can be calculated. The biofilm resistance (Rbiofilm) can be correlated to the thickness of a homogeneous biofilm layer (H ) following the CarmaneKozeny equation: Rbiofilm ¼
75$ð1 εÞ2 $H 2$ε3 $a2
(7)
Where ε (dimensionless) is the biofilm porosity, a (m) is the characteristic radius of the particles forming the cake layer, and H (m) corresponds to the thickness of the biofilm (Katsoufidou et al., 2005). During dead-end filtration all retained material is deposited on the membrane, causing an increase of biofilm thickness. According to Eq. (3), the resistance of the biofilm is defined by its thickness of the layer and structural parameters.
3.
Results
The abundance of eukaryotic organisms was evaluated after staining with FISH probes and imaging with CLSM (Fig. 2) after one week of operation under the different predation levels, in experiment 1. Clear differences in terms of eukaryote abundance were observed between the different treatments (Low-P, Nat.-P, and High-P) after one week of growth. In the Low-P case eukaryotes were either absent or very rarely observed (Fig. 2a). On the contrary, many eukaryotes were observed in the Nat.-P (Fig. 2b) and High-P cases (Fig. 2c). Based on staining with FISH probes and qualitative comparison of images the eukaryote organism abundance was greater in the High-P case that had been inoculated with T. pyriformis, compared to the Nat.-P case. These qualitative observations suggest that both predation inhibition in the Low-P case and the protozoa inoculation in the High-P resulted in significantly different
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conditions compared to the control (Nat.-P). These results were in addition confirmed by direct microscopic observations performed in experiment 1 and 2 after several weeks of operation that revealed the presence of numerous eukaryotes in both the Nat.- and High-P cases.
3.1. Impact of predation on the development of the biofilm In Fig. 3 top view pictures (Fig. 3 aec, gei) and CLSM pictures (Fig. 3 def, jel) of the biofilms after two weeks and one month under different predation conditions (experiment 1) are presented. Comparing the structure of the biofilms after two weeks of operation (Fig. 3, columns 1 and 2) only a small influence of the level of predation can be observed. For the cases with predation (Nat.-P and High-P) the biofilms had a thickness of around 25 mm while the biofilm for the case without predation (Low-P) was slightly thicker (40e50 mm). For all cases the biofilms covered the entire membrane surface but the biofilm structure was more heterogeneous with an increasing predation level. In absence of predation the biofilm surface was rather smooth whereas heterogeneities, i.e., peaks and valleys were observed in presence of predation. After two weeks of operation, biofilms developed in the Nat.and High-P cases are not homogeneous but characterized by a varying thickness and showing mounds of biofilm, especially in the case of High-P (Fig. 3 bec). No clear distinction was, however, visible between the Nat.-P and High-P levels at a large scale (e.g. membrane coverage). After 4 weeks of operation these differences in biofilm structure become even clearer. In the Low-P case a compact biofilm thicker than 50 mm covered homogeneously the entire surface of the membrane based on the CLSM observations (Fig. 3 gej). The membrane coverage did not change between day 15 and day 30 and the membrane remained almost fully covered. Low surface heterogeneity was observed for this biofilm, due to loosely attached particulate matter, which probably accumulated on top of the biofilm during filtration. Inorganic particulate matter was identified by the reflection signal of the CLSM. Thus, areas with high particle density can be identified by the shadowing effect occurring underneath of these areas. In the Nat.-P and High-P cases, heterogeneous and open structures were observed. Between days 14 and 28 the
Fig. 2 e Eukaryote abundance based on CLSM pictures of the biofilm developed after one week of growth under (a) Low-P, (b) Nat.-P and (c) High-P conditions (experiment 1). A red signal (Red-EUK1209 FISH probe) indicates the presence of eukaryote organisms. Grey colour is related to the reflected signal of the solid surface. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 3 e Top view and CLSM images of an optical cross-section of biofilms developed after two weeks and one month of growth (experiment 1) under different levels of predation: Low-P (first row), Nat.-P (second row), and High-P (third row). Images are presented for the biofilm developed after two weeks (columns 1 and 2) and after four weeks (columns 3 and 4). The following colours are used in the CLSM images: Green [ SYBR Gold (all bacterial cells), red [ Concanavalin A (presence of a-D-mannose and a-D-glucose groups of biopolymers), purple [ reflected signal (the membrane). The white arrows in def and jel indicate the position of the membrane surface. CLSM pictures def were record using the 633 objective (NA: 1.3). The red square shown in figures gei corresponds to a view field of 750 mm 3 750 mm indicating the location imaged using CLSM with the 203 objective (NA: 0.7). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
membrane coverage decreased significantly in both cases (Fig. 3 b, c, h, i). After 30 days the biofilm was composed of a thin basal layer with large and locally thick biomass mounds, as can be observed both visually and by CLSM images. The thickness of the basal layer ranged from several microns to around 25 mm (Fig. 3 k and l). CLSM images also revealed the existence of cavities in some structures developed in presence of predators (images not shown). This open and heterogeneous structure was slightly more pronounced in the case of a High-P than in the Nat.-P case. Due to the thick biofilms observed after one month of growth, different objective lenses were used to capture the entire structures in the z-direction. 63 and 20 objectives were used after two weeks and after one month, respectively. The lower NA of the 20 lens is associated with a lower resolution and in turns a lower image quality. This explains the differences between CLSM pictures captured after two weeks and after one month. The change in the meso-scale biofilm structure was monitored using OCT (Fig. 4). OCT images confirmed observations with CLSM on micro-scale. As shown in Fig. 4, OCT results confirmed that the surface heterogeneity of biofilms
increased with an increasing level of predation. Image analysis was applied to quantify OCT images and monitor the change in the biofilm structure (Fig. 5). During the first month of biofilm development, similar mean biofilm thicknesses ranging from 50 to 80 mm were monitored regardless of the level of predation. Then biofilms cultivated in presence of predation became thicker than biofilms developed in absence of predation: mean biofilm thicknesses measured for each filtration modules was ranging from 150 to 200 mm and from 80 to 120 mm in presence and absence of predation, respectively. Predation had even a greater impact on the relative biofilm roughness (Fig. 5). In absence of predation (Low-P) the relative roughness coefficient remained constant over three months at 0.25. In presence of predation (Nat.-P and High-P cases), this coefficient varied between 0.5 and 0.75 indicating that some parts of the biofilms were locally very thin or very thick. In addition, it is important to notice that the variability in flux and structure between these parallel modules was pronounced in the case of predation (Nat.- and High-P). This is likely due to random natural inoculation of protists. In absence of predation the variability between modules was insignificant.
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Fig. 4 e Typical OCT images of biofilms developed after one month under (A) Low-P, (B) Nat.-P and (C) High-P conditions.
Additional physical properties of the different biofilm structures (morphology, accumulated mass, average membrane coverage) are summarized in Table 1. The main differences were observed between the structures developed in absence of predation (Low-P) compared to structures developed in presence of predation (Nat.-P and High-P). In addition to the morphological differences described in section 3.2, the mass of the biofilm accumulated at the surface of the membranes (g C m2) was also influenced by predation. TOC concentration measured in the High-P case was 30% lower than the one measured in the Nat.-P case. No clear distinction was done between the concentration measured in the Lowand Nat.-P cases. In addition, the average membrane coverage decreases with an increasing predation level. In presence of predators the average membrane coverage was decreased by 10%. An accurate determination of the membrane coverage was possible thanks to the good contrast between the biofilm and the uncovered membrane. Statistical analysis was performed to evaluate the influence of the predation level on the change in the mean biofilm thickness and in the relative roughness coefficient (Table 2).
Slopes of the change in the mean biofilm thickness and in the relative roughness coefficient were different for the three different levels of predation. P-values calculated for mean biofilm thicknesses and relative roughness coefficients, however, indicated that the slope for High-P is statistically not different from the slope of Nat.-P. The biofilms with predation (Nat.-P and High-P) were statistically different from the biofilms developed without predation (Low-P case) indicating that the biofilm structure formation is mainly determined by the presence or absence of predators in the system.
3.2. Impact of predation on permeate flux and on hydraulic resistances of the biofilm The average flux measured during experiment 1 and 2 are shown in Fig. 6. According to the data shown in Fig. 6, a relation exists between the predation level and the average flux. Flux monitored in the systems with predators was around two times higher than flux measured in absence of predation. Indeed, a stable flux of 5 L m2 h1 was measured in both experiment 1 and 2 for the Low-P condition. In the Nat.-P case,
1
400
Low-P
Nat.-P
300
High-P
200 100 0
0
50
100
Time (d)
150
Relative roughness coefficient (%)
Mean biofilm thickness ( µm)
Low-P
Nat.-P
0,75
High-P
0,5 0,25 0
0
50 100 Time (d)
150
Fig. 5 e Change in the mean biofilm thickness and in the relative roughness coefficient of the biofilms developed under the three grazing conditions (experiment 2). Physical properties were calculated by image analysis from OCT images.
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Table 1 e Physical properties of the different types of biofilm structure developed in experiment 2. Case
Low-P
Nat.-P
High-P
Treatment
Cycloheximide
No treatment
Biofilm morphology
Flat structure without significant heterogeneities 3.9 0.6
Open and heterogeneous with biomass mounds 4.5 0.1
One-time inoculation with T. Pyriformis Open and heterogeneous with large biomass mounds 2.9 0.8
97 1
89 7
87 1
Accumulated mass of biofilm after one month (g C m2) Average membrane coverage (%)
a constant but higher flux of 9 L m2 h1 was measured. The average flux monitored in the High-P case evolved differently: after two weeks, this flux was lower than the flux measured in the Nat.-P case (15% and 27% lower than Nat.-P case in experiment 1 and 2, respectively). Then, this flux gradually increased and at the end of the experiment the flux for the High-P case was 17% and 20% higher than the flux of the Nat.-P in experiments 1 and 2, respectively. These different fluxes measured correspond to different hydraulic resistances of the biofilm. For example in experiment 2 and after one month of development, the resistance of the biofilm (Rbiofilm) in the case of a Low-P was 4.1 1012 m1, which corresponds to 95% of Rtotal. The resistances of the biofilm in the Nat.-P and High-P cases were 2.1 1012 m1 and 2.0 1012 m1, respectively (which corresponded to more than 95% of Rtotal). Resistances measured in experiment 1 after one month of operation were in the same order of magnitude.
3.3. Relationship between the flux and the coverage of the membrane by biofilm Significant differences in the structure of the biofilms and in coverage of the membrane surface by the biofilm were observed for different experimental durations and different predation levels (Fig. 3 aec and gei). A correlation between the membrane coverage and flux at end of experiment 2 is provided in Fig. 7 for the different predation levels. The extent
Table 2 e Results of the statistical analysis of the influence of the predation level on the change in the mean biofilm thickness and on the relative roughness coefficient. b1 is the slope of the Nat-P case, b2 is the difference in slope of the Nat-P and Low-P and b3 the difference in slope between Nat-P and High-P. Estimate
Standard error
T-test
P-value
Statistical analysis of the mean biofilm thickness data 55.2 14.7 3.7 b0 (Intercept) 1.38 0.26 5.4 b1 0.64 0.22 2.9 b2 (Low-P) 0.31 0.22 1.4 b3 (High-P)
0.0005 2.5e06 0.005 0.17
Statistical analysis of the relative roughness coefficient 0.2107 0.0424 4.96 b0 (Intercept) 0.0048 0.0007 6.599 b1 0.0048 0.0006 7.878 b2 (Low-P) 0.0006 0.0007 0.900 b3 (High-P)
1.20e05 5.47e08 8.30e10 0.373
of membrane coverage was determined from photographs using quantitative image analysis. Two clusters of data are highlighted in Fig. 7 indicating the presence (Nat.- and High-P cases) or absence (Low-P case) of predators in the system. In the case of Low-P, the biofilm homogeneously covered the entire surface of the membrane resulting in an observed membrane coverage larger than 95%. This almost complete coverage of the membrane was associated with fluxes smaller than 5 L m2 h1. No spreading of the data points was observed in this case. In the case of Nat.-P, a heterogeneous biofilm was formed resulting in a partial coverage ranging from 87% to 94%. This reduced observed membrane coverage resulted in fluxes of around 10 L m2 h1 according data recorded during experiment 1 and 2. A slightly lower coverage of the membrane was observed for the High-P case. In this case, membrane coverage was observed with the highest average flux, i.e., a flux higher than 10 L m2 h1. Thus, it can be concluded that lower membrane coverage is related to higher fluxes with an increasing level of predation.
4.
Discussion
4.1.
How does predation impact the biofilm structure?
Compact and flat biofilms that covered the entire membrane surface (see schematic representation in Fig. 8a) developed in absence of predation (Low-P case) whereas open and heterogeneous structures composed of a thin basal layer plus biomass mounds were observed in presence of predation (Nat.-P and High-P) (Fig. 8b). Formation of different biofilm structures was thus governed by the presence/absence of predation. The presence/absence of predation can explain the observed differences in biofilm structures in two ways: an indirect and a direct way. The indirect influence of predation results from predators triggering a reaction of the bacterial population. The formation of micro-colonies is promoted when bacterial biofilms are developed in presence of eukaryotes (Bo¨hme et al., 2009), presumably induced by quorum sensing mechanisms in the bacterial biofilm (Matz et al., 2004). Predation stimulates the production of exo-polymeric substances (e.g. alginate) and bacteria tend to aggregate in dense and disparate structures. In such structures like the biomass mounds, the bacteria are better protected from predation. The development of micro-colonies triggered by the presence of predators during the early stages of biofilm
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Fig. 6 e Average flux measured in (a) Experiment 1 and in (b) Experiment 2 under different predation levels. Bars indicate the standard errors (n [ 5).
growth potentially explains the heterogeneous structure observed at the meso-scale. The direct influence results from predators actively shaping an existing structure. The presence of cavities in the biofilm structure could be explained by the activity of raptorial feeders such as amoeba (Jackson and Jones, 1991). Also, the motility of predators like worms or nematodes can create channel networks, which result in a higher porosity of the structure. Bo¨hme et al. (2009) reported porosity values from 1.5 to 1.8 times higher in presence of protozoa. Predation also reduces significantly the amount of biomass and thus its volume. The amount of biomass on the membrane surface was 30% less in the High-P case than in the Low-P case but similar mean biofilm thicknesses were measured, which suggests that biofilm densities were different. A reduction of 70 and 39% of the biomass concentration was reported in the case of Pseudomonas aeruginosa biofilms of a non-toxic alginate overproducing strain and of a wild-type strain toxic to protozoa, respectively (Weitere et al., 2005), confirming the influence of predators on the biomass volume. In the present study, T. pyriformis that were added in the High-P, were presumably outcompeted by other protists and Metazoa that were naturally present in the creek river water. Competition between T. pyriformis. and other protists could explain that
biofilm structures developed in the Nat.-P and High-P cases were statistically not different. It is expected that continuous addition of Protozoa or Metazoa can reduce the membrane coverage to an even larger extent. Also, the use of a raptorial feeder (i.e., amoeba) or of worms that grazes only on attached biomass should be more effective than the use of ciliates such as T. pyriformis in the current study. More likely, operating the GDM systems in a way that “natural” predation is enhanced would have a greater effect than modifying the protistan ecology by adding an exogenous species. Finally, all these mechanisms yield rougher and more open structures compared with the ungrazed biofilms. In absence of predation, the biofilms developed at the surface of membranes are formed by accumulation of particulate matter, physico-chemical interactions and bacterial activity. It could be shown that these processes still cause stabilization of flux. However without predation, they lead to the development of flat and compact structures. In systems operated with cross-flow like in drinking water distribution pipes, the development of flat structures is usually explained by high shear stress conditions and low loading (van Loosdrecht et al., 1995). In addition to growth and detachment processes, predation contributes significantly to the development of biofilm structures. Therefore, we suggest that predation should be more considered when questions related to biofilm structure are addressed. From a process-engineering point of view, a crucial issue is however to understand to what extent an open and heterogeneous structure impacts the hydraulic resistances and thus the filtration process.
4.2. How does an open and heterogeneous structure enhance the filtration flux?
Fig. 7 e Flux (L mL2 hL1) versus the membrane coverage (%) measured at the end of experiment 2. Two clusters of data are identified depending of the presence or absence of predators in the system.
The use of optical methods such as CLSM or Optical Coherence Tomography has revealed the porous and heterogeneous structure of biofilms. Mass transfer is directly influenced by biofilm morphology. For homogeneous biofilm developed on impermeable substratum and under cross-flow conditions, mass transfer is governed by diffusion and results in a gradient of concentrations over biofilm depth. For heterogeneous biofilms developed on impermeable substratum, substrate diffuses only in the top of the peaks and not in the
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Fig. 8 e Schematic representation of the two distinct structures developed: (a) Compact and flat structure developed in absence of predation, (b) Open and heterogeneous structure developed in presence of predation. In both cases there is a basal layer but in the case of predation this basal layer is much thinner compared to the homogeneous layer in a system without predation.
valleys (Eberl et al., 2000; Picioreanu et al., 2000). In this case convection can contribute to mass transfer in pores but does not necessarily enhance significantly to the overall mass transfer from the bulk liquid to the biofilms matrix. Mass transfer in the case of heterogeneous biofilm structures developed on permeable substratum, like in our study, is not reported in the literature. According to the CarmaneKozeny equation (Eq. (6)), the hydraulic resistance of a biofilm is proportional to its thickness. The hydraulic resistance of biofilms developed in presence of predation was heterogeneously distributed over the surface of the membrane, due to the spatial variation of the biofilms thickness. In addition, the hydraulic resistance of the thick mounds can be expected to be significantly higher than the hydraulic resistance of the basal layer on which they developed. It can be postulated that the water does not penetrate these thick biomass mounds but only follows their surface. Then, it is likely that water passes through the membrane where only a very thin biofilm is present, i.e., in the valleys between the mounds. According to this hypothesis mass transfer would be governed by advection in the valleys and by diffusion in the peaks. This suggests that biofilm growth should be higher in the valleys than in the peaks and should lead to a decrease of the biofilm roughness. However relative roughness coefficient was increasing over time indicating that predation helps to maintain large biofilm heterogeneities. This result reinforces the idea that predation is a crucial process in the case of biofilm developed without cross-flow on permeable substratum. Also, CarmaneKozeny equation applies for systems with homogeneous and packed bed-like biofilm structures. In our study the presence of predation resulted in an increasing mean biofilm thickness but not in an increase of the hydraulic resistance. Correlating the hydraulic resistance to the mean biofilm thickness is thus not correct in the case of biofilms that are heterogeneous at the meso-scale. In our study the filtration performances are governed by the biofilm structure (coverage and surface heterogeneities) and not only by the mean biofilm thickness. A more accurate prediction of the permeate flux requires considering biofilm heterogeneities in the X and Y directions (e.g. the biofilm roughness, i.e., the change in the local biofilm thickness). Further investigations are however required to characterize the flow distribution in
the case of heterogeneous biofilms structures. Evaluation of the flow distribution can be performed experimentally and numerically using fluorescent micro-beads or computational fluid dynamics, respectively.
4.3.
Relevance for decentralized water treatment
Dead-end ultrafiltration operated without control of the biofilm formation and at very low hydrostatic pressure (kwon as Gravity-Driven Membrane (GDM) filtration) represents a relevant alternative for the decentralized production of drinking water in developing and transition countries (see http://www. eawag.ch/membranefilter). In these countries, centralized systems are relevant for the production of drinking water in densely populated zones but not in rural areas. For the production of high-quality drinking water in rural zones, decentralized systems such as GDM systems need to be developed. In these areas, surface waters (river water, pond water, etc) are usually used for the production of drinking water. It can be assumed that the microbial ecology of the surface waters influences the biofilm structure and in turn the performance of the GDM systems. An improved control of grazing in GDM could eventually lead to an optimization of the permeability in such systems and contribute to a broader application of membrane technology for decentralized use. In conventional membrane systems operated with control of the biofilm and at high pressure, the effect of predation on biofilm structure and filtration performance is negligible compared to biofilm control strategies (e.g., chlorination and high shear).
5.
Conclusions
(i) Predation by eukaryotic microorganisms influences the structure of the biofilm developing on the ultrafiltration membrane. (ii) Heterogeneous biofilm structures characterized by a reduced membrane coverage and a thin basal layer developed in presence of predation. Flat and compact structures that homogeneously cover the membrane surface are developed in absence of predation. Addition of exogenous protists did not result in a change in the biofilm structure.
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(iii) The presence of predation resulted in an increased permeate flux. Permeate flux of around 10 L m2 h1 was monitored in presence of eukaryotes compared to the flux of around 5 L m2 h1 monitored in absence of predation. (iv) The meso-scale heterogeneities of biofilm influence its hydraulic resistance. A more open structure (lower coverage by thick biomass mounds and thinner basal layer) resulted in an increased permeate flux.
references
Amann, R.I., Binder, B.J., Olson, R.J., Chisholm, S.W., Devereux, R., Stahl, D.A., 1990. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Applied and Environmental Microbiology 56 (6), 1919e1925. Bo¨hme, A., Risse-Buhl, U., Ku¨sel, K., 2009. Protists with different feeding modes change biofilm morphology. FEMS Microbiology Ecology 69 (2), 158e169. Eberl, H.J., Picioreanu, C., Heijnen, J.J., van Loosdrecht, M.C.M., 2000. A three-dimensional numerical study on the correlation of spatial structure, hydrodynamic conditions, and mass transfer and conversion in biofilms. Chemical Engineering Science 55 (24), 6209e6222. Fenchel, T., Finlay, B.J., 1986. Photobehavior of the Ciliated protozoan Loxodes - Taxic, Transient, and Kinetic Responses in the presence and absence of Oxygen. Journal of Protozoology 33 (2), 139e145. Jackson, G.J., 1990. Parasitic protozoa and worms relevant to the United-States. Food Technology 44 (5), 106. Jackson, G.J., Jones, E.B.G., 1991. Interactions within biofilms: the disruption of biofilm structure by protozoa. Kiel Meeresforsch (Sonderh) 8, 264e268.
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Katsoufidou, K., Yiantsios, S.G., Karabelas, A.J., 2005. A study of ultrafiltration membrane fouling by humic acids and flux recovery by backwashing: experiments and modeling. Journal of Membrane Science 266 (1e2), 40e50. Le-Clech, P., Chen, V., Fane, T.A.G., 2006. Fouling in membrane bioreactors used in wastewater treatment. Journal of Membrane Science 284 (1e2), 17e53. Matz, C., Bergfeld, T., Rice, S.A., Kjelleberg, S., 2004. Microcolonies, quorum sensing and cytotoxicity determine the survival of Pseudomonas aeruginosa biofilms exposed to protozoan grazing. Environmental Microbiology 6, 218e226. Peter-Varbanets, M., Hammes, F., Vital, M., Pronk, W., 2010. Stabilization of flux during dead-end ultra-low pressure ultrafiltration. Water Research 44 (12), 3607e3616. Picioreanu, C., van Loosdrecht, M.C.M., Heijnen, J.J., 1998. A new combined differential discrete cellular automaton approach for biofilm modellingdApplication for growth in gel beads. Biotechnology and Bioengineering 58, 101e116. Picioreanu, C., van Loosdrecht, M.C.M., Heijnen, J.J., 2000. Effect of diffusive and convective substrate transport on biofilm structure formation: a two-dimensional modeling study. Biotechnology and Bioengineering 69 (5), 504e515. Picioreanu, C., van Loosdrecht, M.C.M., Heijnen, J.J., 2001. Twodimensional model of biofilm detachment caused by internal stress from liquid flow. Biotechnology and Bioengineering 72 (2), 205e218. R Development Core Team, 2011. R: A Language and Environment for Statistical Computing. Austria, Vienna [online]. http:// www.R-project.org/. van Loosdrecht, M.C.M., Eikelboom, D., Gjaltema, A., Mulder, A., Ti jhuis, L., Heijnen, J.J., 1995. Biofilm structures. Water Science and Technology 32, 35e43. Weitere, M., Bergfeld, T., Rice, S.A., Matz, C., Kjelleberg, S., 2005. Grazing resistance of Pseudomonas aeruginosa biofilms depends on type of protective mechanism, developmental stage and protozoan feeding mode. Environmental Microbiology 7 (10), 1593e1601.
Available online at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Predation influences the structure of biofilm developed on ultrafiltration membranes Nicolas Derlon a,*, Maryna Peter-Varbanets a, Andreas Scheidegger a, Wouter Pronk a, Eberhard Morgenroth a,b a b
Eawag, Swiss Federal Institute of Aquatic Science and Technology, U¨berlandstrasse 133, P.O Box 611, CH-8600 Du¨bendorf, Switzerland Institute of Environmental Engineering, ETH Zu¨rich, 8093 Zu¨rich, Switzerland
article info
abstract
Article history:
This study investigates the impact of predation by eukaryotes on the development of
Received 15 July 2011
specific biofilm structures in gravity-driven dead-end ultrafiltration systems. Filtration
Received in revised form
systems were operated under ultra-low pressure conditions (65 mbar) without the control
14 March 2012
of biofilm formation. Three different levels of predation were evaluated: (1) inhibition of
Accepted 15 March 2012
eukaryotic organisms, (2) addition of cultured protozoa (Tetrahymena pyriformis), and (3) no
Available online 2 April 2012
modification of microbial community as a control. The system performance was evaluated based on permeate flux and structures of the biofilm. It was found that predation had
Keywords:
a significant influence on both the total amount and also the structure of the biofilm. An
Ultrafiltration
open and heterogeneous structure developed in systems with predation whereas a flat,
Predation
compact, and thick structure that homogeneously covered the membrane surface devel-
Biofilm structure
oped in absence of predation. Permeate flux was correlated with the structure of the bio-
Permeate flux
film with increased fluxes for smaller membrane coverage. Permeate fluxes in the presence
Optical Coherence
or absence of the predators was 10 and 5 L m2 h1, respectively. It was concluded that
Tomography (OCT)
eukaryotic predation is a key factor influencing the performance of gravity-driven ultra-
Confocal Laser Scanning
filtration systems. ª 2012 Elsevier Ltd. All rights reserved.
Microscopy (CLSM) Gravity-driven membrane (GDM) filtration
1.
Introduction
Biofouling reduces the water flux in membrane filtration systems and significant efforts are directed towards preventing or reducing biofilm formation on the surface of membrane. For example, in membrane bioreactors for wastewater treatment, biofilm formation is controlled by coarse bubble aeration resulting in increased shear stress at the membrane surface and by chemical cleaning (Le-Clech et al., 2006). In drinking water systems, membrane modules are regularly back flushed and cleaned with hypochlorite multiple times per week. In nanofiltration and reverse
osmosis, intensive pre-treatment is used. Practical experience, however, demonstrates that biofilm formation cannot be prevented. Removal of biofilms requires significant amounts of energy and chemicals, which significantly increases costs of operation of membrane systems. Thus, a different approach for the operation of membrane systems has to be investigated, avoiding extensive cleaning and flushing operations. A different strategy was proposed by Peter-Varbanets et al. (2010) where biofilm formation on the membrane is tolerated and the focus was on maximizing the permeability of the biofilm. In their study ultrafiltration (UF) systems were
* Corresponding author. Tel.: þ41 44 823 5378. E-mail address: [email protected] (N. Derlon). 0043-1354/$ e see front matter ª 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2012.03.031
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operated without any cross-flow and without membrane cleaning. Under these conditions a highly permeable biofilm is formed that allows for long-term (months) operation of the system without cleaning or backwashing. The formation of this heterogeneous biofilm resulted from biological processes and was not observed when biological activity was reduced (by cold temperature) or inhibited (by addition of sodium azide) (Peter-Varbanets et al., 2010). However, the nature of these processes (e.g., bacterial growth, predation) as well as their impacts on the system performances were not clearly identified. The current study evaluates the influence of predation on structure and permeability of biofilms formed during dead-end ultrafiltration. A range of physical and biological factors influences biofilm structure. Local biofilm growth is limited by substrate availability and biofilm growth is balanced by external forces resulting in biofilm detachment (van Loosdrecht et al., 1995). In systems where the availability of substrate is mass transport limited bacteria that are closer to the bulk phase have a competitive advantage resulting in low-density heterogeneous structures (Picioreanu et al., 1998). High detachment forces, however, can balance this phenomenon. As a result, heterogeneous structures develop under low shear conditions and/or high surface loading rate (Picioreanu et al., 2001). These conceptual and numerical modelling studies assume that the development of biofilm structure can solely be explained by local availability of substrate and physical forces. This approach explains in many cases the biofilm structures that are experimentally observed in industrial systems such as wastewater treatment plants. In the case of biofilms grown at a very low substrate concentrations (e.g., stream biofilms) factors such as quorum sensing or eukaryotic predation have been shown to be dominant factors determining biofilm structure (Bo¨hme et al., 2009). Recent studies performed in the field of stream biofilms indeed reported that predation by eukaryotes significantly impacts the morphology of biofilms (Bo¨hme et al., 2009; Weitere et al., 2005). Predators can indeed reduce the biomass concentration and alter its morphology due to grazing (Weitere et al., 2005), motility (Jackson, 1990), or sloughing induced by raptorial feeders (Fenchel and Finlay, 1986). The enhanced formation of micro-colonies and the resulting channel network yields a rougher biofilm surface compared with ungrazed biofilm (Bo¨hme et al., 2009). If predation significantly influence biofilm structure and overall amount of biofilm then predation may be relevant factor influencing the performance of membrane filtration systems e especially in systems operated without cross-flow that provide very suitable conditions for the larger eukaryotic organisms to develop. The objectives of this study were (1) to identify the influence of predation on the overall amount and the structure of biofilm during ultra-low pressure UF and (2) to correlate the biofilm formation with membrane performance (quantified as water flux or specific resistance). We hypothesized that eukaryotic predation increases biofilm heterogeneity and that increased biofilm heterogeneity in turn results in an increased water flux. To evaluate this hypothesis, three gravity-driven UF systems were operated in parallel with (1) inhibition of eukaryotic organisms, (2) addition of cultured protozoa (Tetrahymena pyriformis), and (3) no modification as a control. Long-term (up to
three months) dead-end filtration experiments were performed monitoring total amount and spatial distribution of the biofilm in combination with the permeate flux.
2.
Materials and methods
2.1.
Experimental setup and operating conditions
2.1.1.
Experimental setup
Three experimental lines each composed of five parallel membrane modules were operated as shown on Fig. 1. Feed water was pumped to a completely mixed tank that is controlled to 20 C and connected to a storage tank. The storage tank was placed at a height corresponding to a pressure of 65 mbar applied at the surface of the membrane. The level of water in the water tank was kept constant using an overflow. The tank was connected to the membrane modules using silicon tubes (Saint-Gobain, Bompass, France). Permeate of every module was collected in a separate plastic bottle and quantified gravimetrically in daily intervals. Water was withdrawn continuously from a creek (Chriesbach, Du¨bendorf, Switzerland) and used as feed water. Total organic carbon (TOC) and dissolved organic carbon (DOC) of the feed water were measured twice per week as described in Section 2.5.
2.1.2.
Membrane
Polyethersulfone membrane (PBHK, Biomax Millipore, Billerica, MA, USA) with a nominal cutoff of 100 kDa was used in this study (mean pore size of approximately 10 nm). To remove conservation agents the new membranes were stored for 24 h in deionized water. The deionized water was renewed several times during this period. Membranes were then placed in filtration modules that consisted of standard polycarbonate filter holders of 48 mm inner diameter (Whatman, Maidstone,
Fig. 1 e Scheme of one experimental line including: the water bath with temperature controlled to 20 C, the storage tank, the filtration modules containing the polyethersulfone membrane (100 kDa) and the bottles for permeate collection.
w a t e r r e s e a r c h 4 6 ( 2 0 1 2 ) 3 3 2 3 e3 3 3 3
Kent, UK). The filtration modules were operated continuously without flushing or cleaning.
2.1.3.
Predation levels and operating conditions
Three different predation levels were applied in three experimental lines operated in parallel. One line was operated with inhibition of eukaryotes (Low Predation, Low-P). Eukaryote inhibition was achieved by continuous addition of cycloheximide, an antibiotic specific to eukaryotic organisms. A second line was operated without control of predators (Natural Predation, Nat.-P). A third line was inoculated with an exogenous source of protozoa (T. pyriformis) (High Predation, HighP). The details of Cycloheximide and T. pyriformis addition are presented in parts 2.2 and 2.3, respectively. Two experimental runs were performed to identify the impact of predation on the biofilm structure and in turn on the system performances. Experiment 1 was operated for a period of four weeks where inhibition of eukaryotes and addition of T. pyriformis was done at the beginning of the experimental run and the water temperature was controlled at 20 C throughout the entire experiment. Experiment 2 was performed in two phases where during the first two months all systems were first conditioned without inhibition of eukaryotes and addition of T. pyriformis and the systems were operated with creek water without temperature control (approximately 7 C). After this conditioning phase the systems were exposed to the different treatments and the water temperature was controlled to 20 C. For experiment 2 the end of the conditioning phase is defined as the start of the experiment.
2.2.
Inhibition of predation
Cycloheximide solution at a concentration of 3.5 g L1 was injected in the five Low-P modules using a syringe-pump. The flow rate (approximately 30 mL d1) was adjusted based on the observed filtration flux to reach a stable concentration of 100 mg L1 in the permeate.
2.3.
Enhancement of the predation
The ciliate T. pyriformis (1630/1W, Culture Collection of Algae and Protozoa, Dunbeg, UK) was used in the High-P case. T. pyriformis was grown anexically in PPY (Proteose Peptone Yeast extract) medium. PPY medium is composed of proteose peptone (20.0 g L1) and yeast extract (2.5 g L1) added to 1 L of Evian water (E´vian-les-Bains, France). The medium was autoclaved at 15 psi for 15 min. 50 mL of two weeks old culture were was centrifuged at 4500g for a period of 10 min to remove the supernatant and then resuspended in Evian water. This step was once repeated before injecting the culture directly into the silicon tubes connecting the water tank with the filtration modules. Viability of the protozoa after centrifugation and before inoculation was controlled by direct microscopic observations.
2.4.
Eukaryote abundance
Fluorescent In Situ Hybridization (FISH) was used to qualitatively evaluate the abundance of eukaryote organisms. A
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eukaryote specific FISH probe was used: EUK1209 (50 - GGG CAT CAC AGA CCT G -30 ) (Amann et al., 1990). First, entire membranes were sampled and fixed with formaldehyde solution (2.5%), and then cut into subsections of around 0.25 cm2. Subsections were then placed in microtubes filled with a hybridization buffer (750 mM NaCl, 100 mM TriseHCl [pH 7.8], 5 mM EDTA, 0.1% sodium dodecyl sulphate). FISH probes were then added to reach a final concentration of 250 ng mL1. Hybridization was performed for a period of 4 h at 45 C. The membrane subsections were then placed in microtubes containing Evian water filtered at 0.45 mm to stop the hybridization process. Organisms were observed with a Confocal Laser Scanning Microscope (CLSM) (Leica SP5, Wetzlar, Germany) using 20 or 63 glycerol immersion Leica objectives. Numerical Apertures (NA) were 0.7 and 1.3 for the 20 and 63 lenses, respectively. Direct microscopic observations of the eukaryote abundance were in addition performed in parallel of the FISH analysis. For this purpose, the biofilms developed on the membrane subsections were scratched with the help of a scalpel and resuspended in filtered Evian water. A stereomicroscope (Leica M205, Wetzlar, Germany) was used.
2.5.
Chemical analysis
The accumulated mass of the biofilm (g C m2) was measured through the measurement of the Total Organic Carbon (TOC). Membranes were sampled and the entire biofilms detached by flushing 100 mL of nanopure water with the help of a sterile syringe. Since biofilms were flushed with significant amounts of nanopure water, the Dissolved Organic Carbon was insignificant and thus the TOC was equal to the particulate organic matter. The TOC concentration of the samples was measured using an automatic total organic carbon analyser (TOC-V, Shimadzu, Japan). Before determination, the unfiltered samples were homogenized with a mixer (Polytron PT 3100, Kinematica, Bohemia (NY), USA) (2 min with 15,000 rpm), a magnetic stirrer was added, and the sample was then closed using parafilm. Homogenization during injection ensured measurement is performed on a representative sample (avoiding sedimentation during injection into the TOC analyser). The analyser was calibrated with a stock solution composed of sodium nitrate (6.068 g L1), potassium hydrophtalate (2.126 g L1), and orthophosphoric acid (85%, 2 mL L1) dissolved in carbon-free water.
2.6.
Biofilm characterization
2.6.1.
Micro-scale characterization (CLSM)
The micro-scale structure of the biofilm (morphology, thickness) was characterized by CLSM. First, membranes were sampled and fixed with formaldehyde solution (2.5%), washed twice with filtered Evian water and cut in sections of around 0.25 cm2. Then, biofilm samples were stained, incubated in the dark (4 h, 20 C) and washed again. SYBR Gold nucleic acid gel stain (1000 fold diluted stock solution, Invitrogen, Basel, Switzerland) was used to detect all microorganisms. Concanavalin A (50 fold diluted stock solution, Invitrogen, Basel, Switzerland) was used to stain the a-D -mannose and a-Dglucose groups of biopolymers. These stains were applied on
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the same membrane subsections. Dehydration of the samples was then performed and consisted of six immersion steps of 20 min each in glycerol/water solutions with an increasing gradient (40, 60, 80, 90, 95 and 100%). The fluorescence of SYBR Gold was detected by excitation at 488 nm and emission at 495e540 nm. Concanavalin A was detected with an excitation at 514 nm and emission at 550e620 nm. The reflection from surfaces impermeable for light was detected at the wavelength of 633 nm using CLSM reflective mode. Ten side-view images and five z-stacks were recorded for each environment at weekly intervals. The position of the objectives was randomly changed in the x and y directions when recording side-view images and z-stacks to avoid subjective impact of the user and thus to record representative data. Biofilm morphologies were evaluated throughout the analysis of these images. No quantification of CLSM images (e.g. biovolume, biofilm thickness) was performed.
Where Yt is the quantitative variable that is considered (mean biofilm thickness or relative roughness coefficient), b1 is the slope of the Nat.-P case, b2 is the difference in slope of the Nat.-P and Low-P and b3 the difference in slope between Nat.-P and High-P. I(Low-P) and I(High-P) are the indicator variables (equal to 0 or 1 depending of the data set that is considered). Ttest and P-value calculations were then performed to statistically distinguish the different slopes that were calculated.
2.6.2.
2.6.3.
Optical Coherence Tomography (OCT)
Optical Coherence Tomography (OCT) (model 930 nm Spectral Domain, Thorlabs GmbH, Dachau, Germany) with a central light source wavelength of 930 nm was used to investigate the meso-scale structure of the biofilm. The use of long wavelength light allows to penetrate up to a depth of 2.7 mm with axial and lateral resolutions of 4.4 mm and 15 mm, respectively. For the image acquisition filtration modules were opened and carefully placed on the OCT stage. OCT images were recorded keeping the samples immersed in a thin layer of permeate. Around 20 A-Scans (i.e., XZ plane pictures) of either 5 1 mm, 5 0.5 mm, or 3 0.5 mm (depending of the biofilm thickness) were acquired at different time intervals and for each filtration modules. Image analysis software developed under Matlab (MathWorks, Natick, US) was used to analyse OCT image. Image analysis consisted of the following steps: (1) detecting the membraneebiofilm interface (grey-scale gradient analysis); (2) binarizing the image (automatic thresholding); (3) calculating physical properties of the biofilm: mean biofilm thickness (z in mm), absolute (Ra in mm) and relative roughness ðR0a Þ coefficients. These parameters were calculated according the following equations: z¼
N 1X zi n i¼1
N 1X ðjzi zjÞ Ra ¼ n i¼1
R0a ¼
N 1X jzi zj z n i¼1
(1)
relative roughness coefficient. The linear least square function of R (R Development Core Team, 2011) version 2.13.0 was used to fit the model. This approach consisted in comparing the slope of the change in the mean biofilm thickness or relative roughness to the slope of natural predation (Nat.-P). First-order equations with qualitative variables were used for this analysis Eq. (4): Yt ¼ b0 þ b1 $t þ b2 $IðLow PÞ$t þ b3 $IðHigh PÞ$t þ εt
(3)
where N is the number of thickness measurements, zi is the local biofilm thickness (mm), and z is the mean biofilm thickness (mm). Linear regression analysis was performed to statistically evaluate the effect of the level of predation on the biofilm physical structure in terms of mean biofilm thickness and
Top view biofilm pictures
Top views of the biofilms developed on the membranes were recorded using an Olympus C-7070 digital camera (Olympus, Le Mont-sur-Lausanne, Switzerland). The meso-scale characterization of biofilms consisted in measuring the membrane coverage as the fraction of the membrane surface that is covered by biofilms. Top view pictures were treated using ImageJ (http://rsb.info.nih.gov/ij/). First, the images were converted into 8-bits pictures. A threshold was then manually adjusted and applied to obtain binary images. The value of threshold was determined in order to distinguish the relevant structure, i.e., the biofilm and the uncovered membrane. The effective surface of membrane was finally selected to calculate the membrane coverage.
2.7.
Flux and hydraulic resistance
2.7.1.
Filtration flux
The permeate flux was calculated by measuring the mass of water collected in each bottle and dividing the results by the filtration period and by the membrane area. The mass of permeate was weighed daily using a scale (Ohaus Adventure Pro, Pine Brook (NJ), USA).
2.7.2.
Hydraulic resistances
The total resistance of the fouled membrane was calculated according to the Darcy’s law: J¼
(2)
(4)
DP m$Rtotal
(5)
Where DP (Pa) is the transmembrane pressure (65 mbars in this study), m is the viscosity (Pa s) of the filterate, Rtotal is the total resistance (m1), and J is the filtration flux (m s1). The total resistance Rtotal can be represented as the sum of individual resistances: Rtotal ¼ Rmembrane þ Rbiofilm þ Rirreversible
(6)
Where Rmembrane is resistance of the pristine membrane, Rbiofilm is resistance of the biofilm, and Rirreversible is resistance caused by the irreversible fouling. Two membranes per line were sampled to estimate Rbiofilm. First, the biofilm was
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detached from the membrane surface by flushing with 100 mL of deionized water using a syringe. Membranes were then returned to filtration modules and the flux of the flushed membrane was determined by filtering nanopure water. It is assumed that the after flushing the resistance is the sum of Rirreversible and Rmembrane. Based on the resistances measured of the fouled membrane, the resistance after flushing, and the resistance of the virgin membrane the different resistances in Eq. (6) can be calculated. The biofilm resistance (Rbiofilm) can be correlated to the thickness of a homogeneous biofilm layer (H ) following the CarmaneKozeny equation: Rbiofilm ¼
75$ð1 εÞ2 $H 2$ε3 $a2
(7)
Where ε (dimensionless) is the biofilm porosity, a (m) is the characteristic radius of the particles forming the cake layer, and H (m) corresponds to the thickness of the biofilm (Katsoufidou et al., 2005). During dead-end filtration all retained material is deposited on the membrane, causing an increase of biofilm thickness. According to Eq. (3), the resistance of the biofilm is defined by its thickness of the layer and structural parameters.
3.
Results
The abundance of eukaryotic organisms was evaluated after staining with FISH probes and imaging with CLSM (Fig. 2) after one week of operation under the different predation levels, in experiment 1. Clear differences in terms of eukaryote abundance were observed between the different treatments (Low-P, Nat.-P, and High-P) after one week of growth. In the Low-P case eukaryotes were either absent or very rarely observed (Fig. 2a). On the contrary, many eukaryotes were observed in the Nat.-P (Fig. 2b) and High-P cases (Fig. 2c). Based on staining with FISH probes and qualitative comparison of images the eukaryote organism abundance was greater in the High-P case that had been inoculated with T. pyriformis, compared to the Nat.-P case. These qualitative observations suggest that both predation inhibition in the Low-P case and the protozoa inoculation in the High-P resulted in significantly different
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conditions compared to the control (Nat.-P). These results were in addition confirmed by direct microscopic observations performed in experiment 1 and 2 after several weeks of operation that revealed the presence of numerous eukaryotes in both the Nat.- and High-P cases.
3.1. Impact of predation on the development of the biofilm In Fig. 3 top view pictures (Fig. 3 aec, gei) and CLSM pictures (Fig. 3 def, jel) of the biofilms after two weeks and one month under different predation conditions (experiment 1) are presented. Comparing the structure of the biofilms after two weeks of operation (Fig. 3, columns 1 and 2) only a small influence of the level of predation can be observed. For the cases with predation (Nat.-P and High-P) the biofilms had a thickness of around 25 mm while the biofilm for the case without predation (Low-P) was slightly thicker (40e50 mm). For all cases the biofilms covered the entire membrane surface but the biofilm structure was more heterogeneous with an increasing predation level. In absence of predation the biofilm surface was rather smooth whereas heterogeneities, i.e., peaks and valleys were observed in presence of predation. After two weeks of operation, biofilms developed in the Nat.and High-P cases are not homogeneous but characterized by a varying thickness and showing mounds of biofilm, especially in the case of High-P (Fig. 3 bec). No clear distinction was, however, visible between the Nat.-P and High-P levels at a large scale (e.g. membrane coverage). After 4 weeks of operation these differences in biofilm structure become even clearer. In the Low-P case a compact biofilm thicker than 50 mm covered homogeneously the entire surface of the membrane based on the CLSM observations (Fig. 3 gej). The membrane coverage did not change between day 15 and day 30 and the membrane remained almost fully covered. Low surface heterogeneity was observed for this biofilm, due to loosely attached particulate matter, which probably accumulated on top of the biofilm during filtration. Inorganic particulate matter was identified by the reflection signal of the CLSM. Thus, areas with high particle density can be identified by the shadowing effect occurring underneath of these areas. In the Nat.-P and High-P cases, heterogeneous and open structures were observed. Between days 14 and 28 the
Fig. 2 e Eukaryote abundance based on CLSM pictures of the biofilm developed after one week of growth under (a) Low-P, (b) Nat.-P and (c) High-P conditions (experiment 1). A red signal (Red-EUK1209 FISH probe) indicates the presence of eukaryote organisms. Grey colour is related to the reflected signal of the solid surface. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 3 e Top view and CLSM images of an optical cross-section of biofilms developed after two weeks and one month of growth (experiment 1) under different levels of predation: Low-P (first row), Nat.-P (second row), and High-P (third row). Images are presented for the biofilm developed after two weeks (columns 1 and 2) and after four weeks (columns 3 and 4). The following colours are used in the CLSM images: Green [ SYBR Gold (all bacterial cells), red [ Concanavalin A (presence of a-D-mannose and a-D-glucose groups of biopolymers), purple [ reflected signal (the membrane). The white arrows in def and jel indicate the position of the membrane surface. CLSM pictures def were record using the 633 objective (NA: 1.3). The red square shown in figures gei corresponds to a view field of 750 mm 3 750 mm indicating the location imaged using CLSM with the 203 objective (NA: 0.7). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
membrane coverage decreased significantly in both cases (Fig. 3 b, c, h, i). After 30 days the biofilm was composed of a thin basal layer with large and locally thick biomass mounds, as can be observed both visually and by CLSM images. The thickness of the basal layer ranged from several microns to around 25 mm (Fig. 3 k and l). CLSM images also revealed the existence of cavities in some structures developed in presence of predators (images not shown). This open and heterogeneous structure was slightly more pronounced in the case of a High-P than in the Nat.-P case. Due to the thick biofilms observed after one month of growth, different objective lenses were used to capture the entire structures in the z-direction. 63 and 20 objectives were used after two weeks and after one month, respectively. The lower NA of the 20 lens is associated with a lower resolution and in turns a lower image quality. This explains the differences between CLSM pictures captured after two weeks and after one month. The change in the meso-scale biofilm structure was monitored using OCT (Fig. 4). OCT images confirmed observations with CLSM on micro-scale. As shown in Fig. 4, OCT results confirmed that the surface heterogeneity of biofilms
increased with an increasing level of predation. Image analysis was applied to quantify OCT images and monitor the change in the biofilm structure (Fig. 5). During the first month of biofilm development, similar mean biofilm thicknesses ranging from 50 to 80 mm were monitored regardless of the level of predation. Then biofilms cultivated in presence of predation became thicker than biofilms developed in absence of predation: mean biofilm thicknesses measured for each filtration modules was ranging from 150 to 200 mm and from 80 to 120 mm in presence and absence of predation, respectively. Predation had even a greater impact on the relative biofilm roughness (Fig. 5). In absence of predation (Low-P) the relative roughness coefficient remained constant over three months at 0.25. In presence of predation (Nat.-P and High-P cases), this coefficient varied between 0.5 and 0.75 indicating that some parts of the biofilms were locally very thin or very thick. In addition, it is important to notice that the variability in flux and structure between these parallel modules was pronounced in the case of predation (Nat.- and High-P). This is likely due to random natural inoculation of protists. In absence of predation the variability between modules was insignificant.
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Fig. 4 e Typical OCT images of biofilms developed after one month under (A) Low-P, (B) Nat.-P and (C) High-P conditions.
Additional physical properties of the different biofilm structures (morphology, accumulated mass, average membrane coverage) are summarized in Table 1. The main differences were observed between the structures developed in absence of predation (Low-P) compared to structures developed in presence of predation (Nat.-P and High-P). In addition to the morphological differences described in section 3.2, the mass of the biofilm accumulated at the surface of the membranes (g C m2) was also influenced by predation. TOC concentration measured in the High-P case was 30% lower than the one measured in the Nat.-P case. No clear distinction was done between the concentration measured in the Lowand Nat.-P cases. In addition, the average membrane coverage decreases with an increasing predation level. In presence of predators the average membrane coverage was decreased by 10%. An accurate determination of the membrane coverage was possible thanks to the good contrast between the biofilm and the uncovered membrane. Statistical analysis was performed to evaluate the influence of the predation level on the change in the mean biofilm thickness and in the relative roughness coefficient (Table 2).
Slopes of the change in the mean biofilm thickness and in the relative roughness coefficient were different for the three different levels of predation. P-values calculated for mean biofilm thicknesses and relative roughness coefficients, however, indicated that the slope for High-P is statistically not different from the slope of Nat.-P. The biofilms with predation (Nat.-P and High-P) were statistically different from the biofilms developed without predation (Low-P case) indicating that the biofilm structure formation is mainly determined by the presence or absence of predators in the system.
3.2. Impact of predation on permeate flux and on hydraulic resistances of the biofilm The average flux measured during experiment 1 and 2 are shown in Fig. 6. According to the data shown in Fig. 6, a relation exists between the predation level and the average flux. Flux monitored in the systems with predators was around two times higher than flux measured in absence of predation. Indeed, a stable flux of 5 L m2 h1 was measured in both experiment 1 and 2 for the Low-P condition. In the Nat.-P case,
1
400
Low-P
Nat.-P
300
High-P
200 100 0
0
50
100
Time (d)
150
Relative roughness coefficient (%)
Mean biofilm thickness ( µm)
Low-P
Nat.-P
0,75
High-P
0,5 0,25 0
0
50 100 Time (d)
150
Fig. 5 e Change in the mean biofilm thickness and in the relative roughness coefficient of the biofilms developed under the three grazing conditions (experiment 2). Physical properties were calculated by image analysis from OCT images.
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Table 1 e Physical properties of the different types of biofilm structure developed in experiment 2. Case
Low-P
Nat.-P
High-P
Treatment
Cycloheximide
No treatment
Biofilm morphology
Flat structure without significant heterogeneities 3.9 0.6
Open and heterogeneous with biomass mounds 4.5 0.1
One-time inoculation with T. Pyriformis Open and heterogeneous with large biomass mounds 2.9 0.8
97 1
89 7
87 1
Accumulated mass of biofilm after one month (g C m2) Average membrane coverage (%)
a constant but higher flux of 9 L m2 h1 was measured. The average flux monitored in the High-P case evolved differently: after two weeks, this flux was lower than the flux measured in the Nat.-P case (15% and 27% lower than Nat.-P case in experiment 1 and 2, respectively). Then, this flux gradually increased and at the end of the experiment the flux for the High-P case was 17% and 20% higher than the flux of the Nat.-P in experiments 1 and 2, respectively. These different fluxes measured correspond to different hydraulic resistances of the biofilm. For example in experiment 2 and after one month of development, the resistance of the biofilm (Rbiofilm) in the case of a Low-P was 4.1 1012 m1, which corresponds to 95% of Rtotal. The resistances of the biofilm in the Nat.-P and High-P cases were 2.1 1012 m1 and 2.0 1012 m1, respectively (which corresponded to more than 95% of Rtotal). Resistances measured in experiment 1 after one month of operation were in the same order of magnitude.
3.3. Relationship between the flux and the coverage of the membrane by biofilm Significant differences in the structure of the biofilms and in coverage of the membrane surface by the biofilm were observed for different experimental durations and different predation levels (Fig. 3 aec and gei). A correlation between the membrane coverage and flux at end of experiment 2 is provided in Fig. 7 for the different predation levels. The extent
Table 2 e Results of the statistical analysis of the influence of the predation level on the change in the mean biofilm thickness and on the relative roughness coefficient. b1 is the slope of the Nat-P case, b2 is the difference in slope of the Nat-P and Low-P and b3 the difference in slope between Nat-P and High-P. Estimate
Standard error
T-test
P-value
Statistical analysis of the mean biofilm thickness data 55.2 14.7 3.7 b0 (Intercept) 1.38 0.26 5.4 b1 0.64 0.22 2.9 b2 (Low-P) 0.31 0.22 1.4 b3 (High-P)
0.0005 2.5e06 0.005 0.17
Statistical analysis of the relative roughness coefficient 0.2107 0.0424 4.96 b0 (Intercept) 0.0048 0.0007 6.599 b1 0.0048 0.0006 7.878 b2 (Low-P) 0.0006 0.0007 0.900 b3 (High-P)
1.20e05 5.47e08 8.30e10 0.373
of membrane coverage was determined from photographs using quantitative image analysis. Two clusters of data are highlighted in Fig. 7 indicating the presence (Nat.- and High-P cases) or absence (Low-P case) of predators in the system. In the case of Low-P, the biofilm homogeneously covered the entire surface of the membrane resulting in an observed membrane coverage larger than 95%. This almost complete coverage of the membrane was associated with fluxes smaller than 5 L m2 h1. No spreading of the data points was observed in this case. In the case of Nat.-P, a heterogeneous biofilm was formed resulting in a partial coverage ranging from 87% to 94%. This reduced observed membrane coverage resulted in fluxes of around 10 L m2 h1 according data recorded during experiment 1 and 2. A slightly lower coverage of the membrane was observed for the High-P case. In this case, membrane coverage was observed with the highest average flux, i.e., a flux higher than 10 L m2 h1. Thus, it can be concluded that lower membrane coverage is related to higher fluxes with an increasing level of predation.
4.
Discussion
4.1.
How does predation impact the biofilm structure?
Compact and flat biofilms that covered the entire membrane surface (see schematic representation in Fig. 8a) developed in absence of predation (Low-P case) whereas open and heterogeneous structures composed of a thin basal layer plus biomass mounds were observed in presence of predation (Nat.-P and High-P) (Fig. 8b). Formation of different biofilm structures was thus governed by the presence/absence of predation. The presence/absence of predation can explain the observed differences in biofilm structures in two ways: an indirect and a direct way. The indirect influence of predation results from predators triggering a reaction of the bacterial population. The formation of micro-colonies is promoted when bacterial biofilms are developed in presence of eukaryotes (Bo¨hme et al., 2009), presumably induced by quorum sensing mechanisms in the bacterial biofilm (Matz et al., 2004). Predation stimulates the production of exo-polymeric substances (e.g. alginate) and bacteria tend to aggregate in dense and disparate structures. In such structures like the biomass mounds, the bacteria are better protected from predation. The development of micro-colonies triggered by the presence of predators during the early stages of biofilm
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Fig. 6 e Average flux measured in (a) Experiment 1 and in (b) Experiment 2 under different predation levels. Bars indicate the standard errors (n [ 5).
growth potentially explains the heterogeneous structure observed at the meso-scale. The direct influence results from predators actively shaping an existing structure. The presence of cavities in the biofilm structure could be explained by the activity of raptorial feeders such as amoeba (Jackson and Jones, 1991). Also, the motility of predators like worms or nematodes can create channel networks, which result in a higher porosity of the structure. Bo¨hme et al. (2009) reported porosity values from 1.5 to 1.8 times higher in presence of protozoa. Predation also reduces significantly the amount of biomass and thus its volume. The amount of biomass on the membrane surface was 30% less in the High-P case than in the Low-P case but similar mean biofilm thicknesses were measured, which suggests that biofilm densities were different. A reduction of 70 and 39% of the biomass concentration was reported in the case of Pseudomonas aeruginosa biofilms of a non-toxic alginate overproducing strain and of a wild-type strain toxic to protozoa, respectively (Weitere et al., 2005), confirming the influence of predators on the biomass volume. In the present study, T. pyriformis that were added in the High-P, were presumably outcompeted by other protists and Metazoa that were naturally present in the creek river water. Competition between T. pyriformis. and other protists could explain that
biofilm structures developed in the Nat.-P and High-P cases were statistically not different. It is expected that continuous addition of Protozoa or Metazoa can reduce the membrane coverage to an even larger extent. Also, the use of a raptorial feeder (i.e., amoeba) or of worms that grazes only on attached biomass should be more effective than the use of ciliates such as T. pyriformis in the current study. More likely, operating the GDM systems in a way that “natural” predation is enhanced would have a greater effect than modifying the protistan ecology by adding an exogenous species. Finally, all these mechanisms yield rougher and more open structures compared with the ungrazed biofilms. In absence of predation, the biofilms developed at the surface of membranes are formed by accumulation of particulate matter, physico-chemical interactions and bacterial activity. It could be shown that these processes still cause stabilization of flux. However without predation, they lead to the development of flat and compact structures. In systems operated with cross-flow like in drinking water distribution pipes, the development of flat structures is usually explained by high shear stress conditions and low loading (van Loosdrecht et al., 1995). In addition to growth and detachment processes, predation contributes significantly to the development of biofilm structures. Therefore, we suggest that predation should be more considered when questions related to biofilm structure are addressed. From a process-engineering point of view, a crucial issue is however to understand to what extent an open and heterogeneous structure impacts the hydraulic resistances and thus the filtration process.
4.2. How does an open and heterogeneous structure enhance the filtration flux?
Fig. 7 e Flux (L mL2 hL1) versus the membrane coverage (%) measured at the end of experiment 2. Two clusters of data are identified depending of the presence or absence of predators in the system.
The use of optical methods such as CLSM or Optical Coherence Tomography has revealed the porous and heterogeneous structure of biofilms. Mass transfer is directly influenced by biofilm morphology. For homogeneous biofilm developed on impermeable substratum and under cross-flow conditions, mass transfer is governed by diffusion and results in a gradient of concentrations over biofilm depth. For heterogeneous biofilms developed on impermeable substratum, substrate diffuses only in the top of the peaks and not in the
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Fig. 8 e Schematic representation of the two distinct structures developed: (a) Compact and flat structure developed in absence of predation, (b) Open and heterogeneous structure developed in presence of predation. In both cases there is a basal layer but in the case of predation this basal layer is much thinner compared to the homogeneous layer in a system without predation.
valleys (Eberl et al., 2000; Picioreanu et al., 2000). In this case convection can contribute to mass transfer in pores but does not necessarily enhance significantly to the overall mass transfer from the bulk liquid to the biofilms matrix. Mass transfer in the case of heterogeneous biofilm structures developed on permeable substratum, like in our study, is not reported in the literature. According to the CarmaneKozeny equation (Eq. (6)), the hydraulic resistance of a biofilm is proportional to its thickness. The hydraulic resistance of biofilms developed in presence of predation was heterogeneously distributed over the surface of the membrane, due to the spatial variation of the biofilms thickness. In addition, the hydraulic resistance of the thick mounds can be expected to be significantly higher than the hydraulic resistance of the basal layer on which they developed. It can be postulated that the water does not penetrate these thick biomass mounds but only follows their surface. Then, it is likely that water passes through the membrane where only a very thin biofilm is present, i.e., in the valleys between the mounds. According to this hypothesis mass transfer would be governed by advection in the valleys and by diffusion in the peaks. This suggests that biofilm growth should be higher in the valleys than in the peaks and should lead to a decrease of the biofilm roughness. However relative roughness coefficient was increasing over time indicating that predation helps to maintain large biofilm heterogeneities. This result reinforces the idea that predation is a crucial process in the case of biofilm developed without cross-flow on permeable substratum. Also, CarmaneKozeny equation applies for systems with homogeneous and packed bed-like biofilm structures. In our study the presence of predation resulted in an increasing mean biofilm thickness but not in an increase of the hydraulic resistance. Correlating the hydraulic resistance to the mean biofilm thickness is thus not correct in the case of biofilms that are heterogeneous at the meso-scale. In our study the filtration performances are governed by the biofilm structure (coverage and surface heterogeneities) and not only by the mean biofilm thickness. A more accurate prediction of the permeate flux requires considering biofilm heterogeneities in the X and Y directions (e.g. the biofilm roughness, i.e., the change in the local biofilm thickness). Further investigations are however required to characterize the flow distribution in
the case of heterogeneous biofilms structures. Evaluation of the flow distribution can be performed experimentally and numerically using fluorescent micro-beads or computational fluid dynamics, respectively.
4.3.
Relevance for decentralized water treatment
Dead-end ultrafiltration operated without control of the biofilm formation and at very low hydrostatic pressure (kwon as Gravity-Driven Membrane (GDM) filtration) represents a relevant alternative for the decentralized production of drinking water in developing and transition countries (see http://www. eawag.ch/membranefilter). In these countries, centralized systems are relevant for the production of drinking water in densely populated zones but not in rural areas. For the production of high-quality drinking water in rural zones, decentralized systems such as GDM systems need to be developed. In these areas, surface waters (river water, pond water, etc) are usually used for the production of drinking water. It can be assumed that the microbial ecology of the surface waters influences the biofilm structure and in turn the performance of the GDM systems. An improved control of grazing in GDM could eventually lead to an optimization of the permeability in such systems and contribute to a broader application of membrane technology for decentralized use. In conventional membrane systems operated with control of the biofilm and at high pressure, the effect of predation on biofilm structure and filtration performance is negligible compared to biofilm control strategies (e.g., chlorination and high shear).
5.
Conclusions
(i) Predation by eukaryotic microorganisms influences the structure of the biofilm developing on the ultrafiltration membrane. (ii) Heterogeneous biofilm structures characterized by a reduced membrane coverage and a thin basal layer developed in presence of predation. Flat and compact structures that homogeneously cover the membrane surface are developed in absence of predation. Addition of exogenous protists did not result in a change in the biofilm structure.
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(iii) The presence of predation resulted in an increased permeate flux. Permeate flux of around 10 L m2 h1 was monitored in presence of eukaryotes compared to the flux of around 5 L m2 h1 monitored in absence of predation. (iv) The meso-scale heterogeneities of biofilm influence its hydraulic resistance. A more open structure (lower coverage by thick biomass mounds and thinner basal layer) resulted in an increased permeate flux.
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