The function of a toluene-degrading bacterial community in a waste gas trickling filter

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Pergamon

Wal Sci Tech Vol 39. No.7. pp. 131-137. 1999 .

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1999'AWQ

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THE FUNCTION OF A TOLUENE• DEGRADING BACTERIAL COMMUNITY IN A WASTE GAS TRICKLING FILTER Anne R. Pedersen* and Erik Arvin Department ofEnvironmental Science and Engineering. The Technical University of Denmark. Building 1/5. DK·280a Lyngby, Denmark

ABSTRACT The function of a community of toluene-degrading bacteria in a biofilm system was investigated with regard to growth and toluene degradallon 10 order to mvestigale substrate mteracllons 10 the commumty. This was done by the combinahon of experimental observations usmg a specdic oligonucleotide 16S ribosomal RNA probe targeting the toluene·degrading species Pseudomonas pUlido, and by compuler simulations (AQUASIM) of the biofilm growth based on a food web model. Biofilrns were taken from a lab·scale trickling filter for treatment of toluene.polluted all. The blOfilrn growth and the aCllvl1y of P. pUlido, a representahve of the toluene-degradmg species In the biofilm which have been descnbed previously (Pedersen el of., 1997) were SlInulated. The stlDulation mdlcated that the volume fraction of the toluene degraders in the blofilm decreased from 12% to only 2% (II % of dry weIght) during two weeks. In spite of the low fracllon m the biofilm, the toluene degraders supported growth of the dominating part of non· toluene-degradmg heterotrophs in the biofilm, as toluene was the sole carbon source supplied 10 Ihe syslem. The maximum mlnnsic growth rate of P. putlda in the biofilm was only 20".41 of the maxImum growth rale determined in a batch experiment with suspended P pUlido cells.
KEYWORDS Toluene-degrading bacteria; Pseudomonas pUlido; biofilm; modeling; computer simulation; AQUASIM. INTRODUCTION Biofiltration is an attractive technique for purification of gaseous emiSSIOns of pollutants in low concentrations because of its simplicity and cost-effectiveness. The technique is frequently used for elimination of odorous and volatile organic compounds from waste gases (Leson and Winer. 1991). In spite of the widespread use, the biofilm growth in these filters is mostly considered as a black box and only few investigations of the microbial composition and the growth have been camed out (Diks, 1992). Modeling of the performance of the filters is also scarce. in particular with respect to biofilm growth. A previous study (Pedersen el al., 1997) examined the toluene degradation and the biofilm growth in a trickling filter for waste gas treatment. A specialized filter set-up suitable for biofilm sampling was used, and the amount of dry matter, polymers and active biomass in the biolilm was measured. However, the analytical measurement of active biomass does not distinguish between the different species of bacteria in • Present address: VKl, AgemAllell.DK-2970 Horsholm, Denmark 131

132

A. R. PEDERSEN and E. ARVIN

the biofilm. Both toluene degraders and heterotrophic biomass predating on degradable substances (inactive biomass and polymers) were present and provided a complex food web in the biofilm (Arcangeli and Arvin, 1992a). In other words, the active biomass concentration is not a proper measure for the toluene-degrading biomass. Therefore, specific 16S ribosomal probes for monitoring sub-populations in the biofilm were applied (Ml!IlIer et al., 1996). A representative of the toluene degraders, Pseudomonas putida, was isolated from the multispecies culture. A specific 16S rRNA oligonucleotide probe was designed to target single cells of P. putida in hybridized samples from the biofilm and the liquid phase. The probe was labeled in order to visualize the cells and to follow the number and the activity of P. putida during the initial growth. In this study, modeling of the biofilm growth and the toluene removal was performed in order to verify the results obtained by use of the in situ hybridization of samples taken from the biofilm. The purpose of the modeling was to get a better understanding of the experimental observations and to predict the dynamics and distribution of species and substrate in the biofilm for the initial growth phase. The modeling was based on the results reported in a separate paper (Pedersen et al., 1997). METHODS The inoculum, enriched on toluene, originated from a creosote-polluted groundwater aquifer from a former gasworks site in Fredensborg, Denmark (Flyvbjerg et al., 1993). Toluene-degrading species were isolated by plating on LB-medium (Luria-Bertani) (DSM). Selected isolates with distinct colony morphology were cultivated by repeated spreading on LB-medium. The cultivated isolates were tested for their ability to degrade toluene. Toluene-degrading species were examined by several microbiological and biochemical methods (Nester et al., 1983), and the shape, size, and mobility of the cells were observed. The identification system Biolog (Biolog) was used for the Gram-negative isolates, and a sequencing of the 16S ribosomal RNA was performed in order to confirm the identification and to identify Gram-positive species. Toluene degradation kinetics was investigated in batch cultures of the cultivated species. The kinetic parameters were estimated by fitting of the toluene and the protein concentrations to a Monod model (Broholm et al., 1990) The species identification and the kinetic parameters for toluene degradation by the four species are summarized in Table I. D8 was not identified but the rRNA sequence showed similarity to an environmental isolate PAD44 and to Rhodoferaxfermentans FR2. Table I. Species identification and estimated kinetic parameters for toluene degradation of species isolated from the toluene-degrading bacterial consortium. The symbols are: k m is the maximum specific substrate utilization rale. I1X"... is maximum specific growth rate. Y"... is the maximum yield coefficient. KS is the half saturation constant. bX is the decay rate Isolate Species identification

km (gs gx"' d-I)

I1X... (d-')

Y"...

KS

(gx &s.I)

(&s mol)

bX (d- I )

RI

P. putido

10.1

12.1

1.2

0.1

1.15

C6

Acinetobacter

5.0

7.1

1.4

0.1

0

D6

Rhodococcus

6.5

6.5

1.0

0.5

0

3.2

1.6

0.5

0.1

0

D8

P. putida was the isolate with the highest toluene degrada~ion capacity, ~d the~efore this species was assumed to be the best representative of the toluene-degradmg population m the moculum. Results from hybridization of biofilm samples using a specific 16S rRNA probe targeting P. putida were reported in Pedersen et al. (1997). The intrinsic actual growth rate of P. putida in the biotilm, ~Xput.a
ToJuene-degrading bacterial community in a waste gas trickling filter

133

The experimental set-up and conditions are previously described in Pedersen et al. (1997). The biofilm growth during the initial 14 days growth phase was detennined by measurements of the wet and dry weight ofthe biofilm, polymers, and protein content. Measurements of toluene in the liquid and the gas were carried out by GC-analysis. P. putida was monitored in the system by hybridization of biofilm and liqUid samples using a specific 16S ribosomal oligonucleotide probe labeled with an isothiocyanate derivative for Visualization. Detailed descriptions of the probe and the hybridization technique are found in Meller et al. (1996). The oxygen concentration in the bulk liquid was 7 g m·J and the concentration of toluene was 0.2-1.5 g m-J • From this it can be inferred that oxygen was in excess in all cases.

Growth

Decay

Hydrolysis

FIgure I. Model of the toluene-degrading communtty. X denotes the particulate matte.r (i: mert, S: hydrolyzable: put: P. pullda. tol: toluene-degraders. het: heterotrophs). O 2: dIssolved oxygen, Tol: dISsolved toluene. and Org.. dissolved organic matter.

Table 2. Model structure of components and processes Proc.....

Xput Growth

DislOlved components

Plt1Iculale comJ)l entl

Xhtt

Xtol

I

XS

XI

I

Growth

-{y~)

Xhe, GrowthXtol DecayXpu , DecayXhe' DecayX'ol Detach XDllt DetachXhe DetachXS Detach XI HydrolysIS

Sorr

-{L)-p

{J

Xput

SIOI

SUlpeoded

I

P

-I

I-a I-a I-a

-I -I

-{~)-p

Seuy

-c y:-) -c y~..)

SXput

SX"",

SX

s",

pX,... S",+KS",

pX.... So" + KS... . X... pX""

I I

-I

I I

-I

-I

I

. X,..

s..,

-C~:",)

a a a

-I -I

Procea rate

componenll

s", .x'"

S", + KS",

bXpu , Xout bXhet Xh" bX,ol X'ol k :oul Xou , I LF<2E-' k , Xh" k , . XS X, k kh XS

134

A. R. PEDERSEN and E. ARVIN

MODEL DESCRIPTION The biological community was considered as a food web where the toluene-degrading bacteria transformed the toluene into biomass and extracellular polymers. The decay products from the toluene-degraders and the polymer~ wer~ hydrolyzed before supporting growth to the non-toluene-degrading heterotrophs. A schematic outline of the model is shown in Fig. 1. Modeling and parameter estimation was performed by the simulation programme AQUAS1M (Reichert, 1994). The model was calibrated based on the experimental data: primarily 1, the evolution of the biofilm thickness; a,nd ~, the volume fraction of P. putida in the biofilm, and secondly, the detachment of P. putida, ~eterotrophlc bIomass, and polymers. In order to reduce the number of parameter estimates, data from the literature was used as far as possible. A schematic outline ofthe model structure of the processes in the biofilm with stoichiometric coefficients and process rates is given in Table 2, and the notation of the parameters is shown in Table 3. The biofilm consisted of five different particulate components: XpUI' toluene-degrading P. putida, Xlo" secondary toluene degraders, Xhet. heterotrophic biomass, XS, extracellular polymers as hydrolyzable organic material, and Xi, inert material. Three soluble substrates were taken into account: SIoI, toluene, Sorg, dissolved biodegradable organic material, and So,y, oxygen. Three suspended solids were assumed: SXPUh detached P. putida SXhel. detached heterotrophic biomass SX, detached organic material. Characterization of the biofilm showed a dry weight content of 2.6% (18% of the biofilm volume). Initial volume fractions of the particulate components in the biofilm were set to 7% for Xput and 5.5% for Xhet and Xlol (in total 18% of the biofilm volume). The density of dry matter (weight per volume of the particulate substances) was 1.6.105 g COD m') calculated on the basis of the density of an Escherichia coli-cell (Characklis et al.. 1990). This density was used for both active biomass and inert biomass. Dry weight density of extracellular polymers was 1.7.106 g COD m') according to the density of glucose. Concentrations of particulate components in the biofilm, X, were defined as the product of the density, p, and the volume fraction of the components in the biofilm, E: X = P . E. The computer program AQUAS1M (Reichert, 1994) provides different types of reactors connected by diffusive or advective links. In this study a simplification of the trickling filter was used in order to facilitate the modeling of the biofilm growth. The model description comprised a biofilm reactor compartment and a mixed reactor compartment connected by a diffusive link. The biofilm reactor described the biofilm and liquid phase, and the mixed reactor described the gas phase. The simplification neglected the profiles of the gas phase concentrations in the column height of the trickling filter. This provided a constant liquid concentration in accordance with the experimental conditions with a high liquid recirculation. Therefore, this simplification of the trickling filter had no influence on the growth conditions in the model compared to the experimental conditions. The biofilm was treated as a rigid matrix precluding diffusion of particulate components. Gas/liquid mass transfer was described as a diffusive link between the liquid phase and the gas phase, and liquid boundary layer resistance at the biofilm surface was neglected. The diffusivity of toluene (Arcangeli and Arvin, 1992b) and dissolved organic matter (Harremol!s, 1986) in the biofilm was 1.1·10-4 m2 d· 1 and 5.7·\0,5 m2 d· I , respectively.

Toluene-degrading bacterial community in a waste gn trickling filter

135

RESULTS AND DISCUSSION

The parameters used in the final simulation of the experimental data are summarized in Table 3. As can be seen, 11 parameters were estimated by fitting. As explained previously, this was based on several data sets n:un ely time series ofbiofilm growth, P. pUlida volume fraction, and detachment of P. pUlida, heterotrophi~ bl?mass, and polymers. All paranJeter-fits were kept within a realistic magnitude, which in combination WIth the values obtained from the literature made the most reasonable basis for simulation of the experimental observations. Table 3. Parameters used in the model IIXpuo

Vnll d· 1

Estimate

I!X.., I!X\OI BX... BX h" BX,.,

d" d'" d'" d" d"

0.5 2.7

Symbol

Maximum growth rate of x,... detcnrnned by suspended cells Maximum growth rate of X... MaXlDlum growth rate of X.., Decay rate of X"", Decay rate of Xh" Decay rate of X,., ReduclJon factor of /lX... YIcld coefficient of X"", Yield coefficient of X...

R

Yield coeffiCient ofX\OI Half saturalJon constant, Sool Half saturation constant. S""

Y.... Y..,

gCOD/gCOD gCOD/gCOD

YIoI

gCOD/gCOD gCODm·1 gCODm')

KS.., KS""

Detachment rate ofx..,. Detachment rate of X"" Detachment rate of XS Henry's law constant Mass transfer coeffiCient HydrolYSIS rate Frachon of inert organic matter

d· l

k.t.x,.. k.t.xs k...xs

H,

at d" mId" d"

Qex

Ir." Cl

12.0

1.9 0.25 2.1 0.2 0.5 0.5

Source Pedersen f!l 01., 1997 parameter fit parameter fit parameter fit parameter fit parameter fit parameter fit Pedersen f!t 01., 1997 Arcangeli and Arvin, 1992.

0.5

OJ 7.5

Pedersen f!t 01.• 1997 Pedersen '" 01., 1997 Arcangeli and Arvm, 1992.

0.25 0.02 0.02 0.27 7.0 2.0 0.15

parameter fit parameter fit parameter fit Ashworth f!1 01., 1988 Pedersen and Arvin, 1997 parameter fit Arcangeh and ArvID,

1.0

parameter fit

1992.

EPS fonnation coefficient

~

The biofilm growth in terms of thickness, detachment, and volume fractions of particulate biomass in the biofilm were predicted reasonably well by the suggested model. Fig. 2 shows the biofilm thickness and the volume fraction of P. putida. The fate of P. putida was simulated according to the experimental observation of a high initial detachment followed by establishing a constant level in the biofilm (Table 2). Biofilm thickness (m)

0.00 0.05 0.04 0.03 0.02 0.01

0.00Xl4

0.lXXXl2

0

Ol-----~---~-----<

o

10

5

VoIl111l fra:ljon (m3 m-3)

0.07

0.00016 . . . . . - - - - - - ' - - - - - - - - - , 0.00014 0.00012 0.0001 0.00008 0.00006

0

15

5

10

15

lima (d)

TIITlB (d) A

Figure 2. (A) Biofilm thickness; (0) Volume fraction of P pulido in the biofilm. Expenmental data (.) and modelled data (solid line).

B

136

A. R. PEDERSEN and E. ARVIN

The feed of toluene into the filter varied b(' 16%, whereas the simulation was simplified and based on a const~t feed of toluene of 725 g COD m' d,l resulting in a constant elimination of 450 g COD m,3 d· l . Modehng of the overall toluene removal in the trickling filter agreed reasonably well with the experimental observations. The ex~erimental results (rRNA) indicated that the activity and hence the intrinsic growth rate of P. putida In the blofilm was only 20% of the maximum growth rate determined in a batch experiment with suspended cells (I~ d,l, Table I), yielding the intrinsic specific growth rate of 2.4 d· l : J.1XpuI.act = R J.1Xpu~max, i.e. R = 0:2. ThIS observation was in accordance with the model predicting that the activity of P. putida in the blOfilm was reduced by the same factor (5) compared with the batch experiment in order to describe the p~esenc~ of P. putida in the biofilm. By use of a growth rate higher than 2.4 d'i for P. putida, the computer slmul~tlon showed that the active biomass in the biofilm would have been taken over by P. putida during the expenmental period of 14 days which did not agree with the experimental observations. The toluene degradation carried out by P. putida was calculated based on the simulated growth of P. putida and the toluene surface removal of P. putida was compared to the overall toluene elimination in the filter. The modeling suggested that P. putida accounted for 30% of the overall toluene removal and consequently, other toluene degraders besides P. putida have to be present in the biofilm. The growth rate of the secondary toluene degraders was estimated by the modeling indicating that the growth rates of the two toluene-degrading groups were almost the same (2.4 d'i and 2.7 d,I). The estimated growth rate of the heterotrophic biomass (0.5 d· l ) was low compared to the growth rate of the toluene• degrading P. putida (2.4 d'I). This corresponded to the experimental suggestions ofa higher in situ activity of P. putzda than that of the other cells in the biofilm (MlZlller et al., 1996). Simulation of the biofilm development showed that the toluene-degrading bacteria formed only a minor part of the total amount of biomass in the trickling filter. Most of the biomass was inactive biomass. The volume fraction of the toluene-degrading biomass, Xpu ' and XIo\, in the biofilm decreased from 12.5% to 2.0% during the initial growth, but in spite of the decreasing fraction, the concentration of the toluene degraders was constant implying a constant toluene removal capacity. As toluene was the sole carbon source supplied to the biofilm system, the toluene-degrading population of only 2% of the biofilm volume (II % of dry matter) was able to support growth of the dominating part of non-toluene-degrading heterotrophs in the biofilm. The low fraction of the toluene degraders corresponded to results found in the literature. Diks and Ottengraf (1991) reported that only 12% of the biomass (dry weight) in a trickling filter for dichloromethane removal actually degraded dichloromethane, and the results from Speitel and McLay (1993) suggested that a major part of the biofilm in a trickling filter for removal of chlorinated hydrocarbons was inactive to the substrate degradation. Arcangeli and Arvin (1992b) found that only 9-10% of the dry weight in a toluene-degrading biofilm was active biomass including both toluene degraders as well as other heterotrophs. Models of the toluene-degrading community other than the one proposed in Fig. 1 may explain the experimental observations as well as the present model. However, the present study has shown that the modeling based on the community model in Fig. I and the processes outlined in Table 2 leads to the same intrinsic growth rate of P. putida as determined experimentally from the relative rRNA-content of P. putida in the biofilm. CONCLUSIONS Experimental observations using a specific oligonucleotide 16S ribosomal RNA probe targeting a representative of the toluene-degrading species was simulated in a relatively simple model for biofilm growth based on a food web by computer simulations (AQUAS1M). The modeling showed that the volume fraction of the toluene degraders in the biofilm decreased from 12% to only 2% during two weeks. In spite of the low fraction in the biofilm, the toluene degraders supported growth of the dominating part of non• toluene-degrading heterotrophs in the biofilm, as toluene was the sole carbon source supplied to the system. The model suggests that the growth rates of the toluene degraders were almost the same. A representative of the toluene degraders, P. putida, was described in the model in accordance with experimental results obtained by in situ hybridization with a 16S rRNA targeting probe specific for P. putida. There was a good

Toluene-degrading bacterial communily in a wasle gas trickling filler

137

correspondence between the intrinsic growth rate of P. putida detennined experimentally from the relative rRNA content of P. putida in the biofilm and the intrinsic growth rate of P. putida detennined from the modeling. The maximu.m intrinsic growth rate of P. putida in the biofilm was reduced by a factor of 5 compared WIth the maxImum growth rate detennined in a batch experiment with suspended P. putida cells. The model suggested that 30% ofthe overall toluene removal was perfonned by P. putida.

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