(BAM) and its Metabolite 2,6-Dichlorobenzoic Acid - ACS Publications

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Mineralization of the common groundwater pollutant 2,6dichlorobenzamide (BAM) and its metabolite 2,6-dichlorobenzoic acid (2,6-DCBA) in sand filter units of drinking water treatment plants Johanna Vandermaesen, Benjamin Horemans, Julie Degryse, Jos Boonen, Eddy Walravens, and Dirk Springael Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b01352 • Publication Date (Web): 17 Aug 2016 Downloaded from http://pubs.acs.org on August 18, 2016

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Environmental Science & Technology

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Mineralization

of

the

common

groundwater

pollutant

2,6-

2

dichlorobenzamide (BAM) and its metabolite 2,6-dichlorobenzoic acid

3

(2,6-DCBA) in sand filter units of drinking water treatment plants

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Johanna Vandermaesen†, Benjamin Horemans†, Julie Degryse§, Jos Boonen§, Eddy Walravens§ and Dirk

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Springael†*

6

†

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Belgium

8

§

9

Heverlee, Belgium

KU Leuven, Division of Soil and Water Management, Kasteelpark Arenberg 20 bus 2459, B-3001 Heverlee,

Centraal laboratorium, De Watergroep, Researchpark Haasrode Leuven 1834 - Technologielaan 23, B-3001

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* Corresponding author: [email protected], tel. +3216321604, fax. +3216321997

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Abstract

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The intrinsic capacity to mineralize the groundwater pollutant 2,6-dichlorobenzamide (BAM) and its metabolite

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2,6-dichlorobenzoic acid (2,6-DCBA) was evaluated in samples from sand filters (SFs) of drinking water

14

treatment plants (DWTPs). Whereas BAM mineralization occurred rarely and only in SFs exposed to BAM,

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2,6-DCBA mineralization was common in SFs, including those treating uncontaminated water. Nevertheless,

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SFs treating BAM contaminated water showed the highest 2,6-DCBA mineralization rates. For comparison,

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2,6-DCBA and BAM mineralization were determined in various topsoil samples. As in SF samples, BAM

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mineralization was rare, whereas 2,6-DCBA mineralization capacity appeared widespread, with high

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mineralization rates found especially in forest soils. Multivariate analysis showed that in both SF and soil

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samples, high 2,6-DCBA mineralization correlated with high organic carbon content. Adding a 2,6-DCBA

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degradation deficient mutant of the BAM mineralizing Aminobacter sp. MSH1 confirmed that 2,6-DCBA

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produced from BAM is rapidly mineralized by the endogenous microbial community in SFs showing intrinsic

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2,6-DCBA mineralization. This study demonstrates that (i) 2,6-DCBA mineralization is widely established in

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SFs of DWTPs, allowing the mineralization of any 2,6-DCBA produced during BAM degradation and (ii) the

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first metabolic step in BAM mineralization is rare in microbial communities, rather than its further degradation

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beyond 2,6-DCBA.

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Introduction

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2,6-dichlorobenzamide (BAM) is a transformation product of dichlobenil (2,6-dichlorobenzonitrile), a herbicide

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mainly used for weed control in public and private areas.1 BAM has a high water solubility and low Koc and

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easily leaches to groundwater,1,2 leading to the widespread occurrence of BAM as a groundwater pollutant with

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concentrations up to 5 µg/L.1,3,4 The presence of BAM in groundwater resources used for drinking water

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treatment results in the costly closure of abstraction wells5 or implementation of expensive measures in drinking

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water treatment plants (DWTPs), such as activated carbon filtration and advanced oxidation processes6 to reach

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the EU drinking water threshold concentration of 0.1 µg/L (80/778/EEC). Sand filters (SFs), commonly used in

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DWTPs to remove iron and manganese7,8 were recently shown to harbor the capacity to biodegrade organic

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micropollutants such as pesticides and pharmaceuticals.9–12 Whether SF microbial communities also degrade

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BAM is however unknown, but not expected based on its recalcitrance in both soil and groundwater.13–17 To

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biologically remove BAM in DWTPs, operational conditions should thus be optimized or alternative

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approaches developed such as bioaugmentation, i.e., inoculating BAM mineralizing bacteria in SFs.18

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Although uncertainties exist about the metabolic pathway of BAM mineralization, it is generally accepted that

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BAM is first converted to 2,6-dichlorobenzoic acid (2,6-DCBA). Holtze et al.14 identified 2,6-DCBA as an

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intermediate of dichlobenil biodegradation based on its transient accumulation in soil. This is supported by

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findings of Simonsen et al.19 for the BAM mineralizing isolates Aminobacter sp. MSH1 and ASI1. In those

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strains, a constitutively expressed amidase converts BAM at high rate to 2,6-DCBA20 but further degradation

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proceeds more slowly and 2,6-DCBA was appointed a bottleneck for BAM mineralization.19 2,6-DCBA was

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suggested as a potential groundwater contaminant based on its persistence and low sorption to soil.21 However,

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data on the actual presence of 2,6-DCBA in soil or groundwater are scarce since 2,6-DCBA is usually not

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included in monitoring campaigns. Nevertheless, 2,6-DCBA was detected in 1.1% of 4739 Danish groundwater

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samples taken between 2012 and 201422 and in soils after treatment with dichlobenil.23,24 Furthermore, no

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consensus exists on biodegradability of 2,6-DCBA. Holtze et al.15 reported 2,6-DCBA as degradable in some

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soils, but persistent in others, with half-lives ranging between 24 and 108 days. Most studies on 2,6-DCBA

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biodegradability focused on disappearance and not mineralization.

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Even when BAM is degraded by either the endogenous community or by introduced organisms in SFs of

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DWTPs, it is thus unclear whether potentially produced 2,6-DCBA is removed by endogenous microbial

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activity. This knowledge is of importance for acceptance and implementation of biological BAM removal

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approaches in DWTPs. Therefore, in this study, mineralization of BAM and 2,6-DCBA was evaluated in SF

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samples from DWTPs differing in intake water BAM contamination. For comparison, the BAM and 2,6-DCBA

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mineralization capacity was determined in topsoil samples from 17 locations, differing in land use and soil type.

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Finally, BAM mineralization was evaluated in filter sand showing high 2,6-DCBA mineralization, after adding ACS Paragon Plus Environment

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a 2,6-DCBA degradation deficient variant of Aminobacter sp. MSH1, to examine whether 2,6-DCBA produced

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during biological conversion of BAM was efficiently mineralized by endogenous SF populations.

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Materials and methods

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Sand filter and soil samples. SFs were sampled at 11 Belgian DWTPs between 2011 and 2015. Since they

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were permanently inundated and regularly mixed by backwashing, and thus expected to be physicochemically

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and biologically homogenous, one sample was taken at a random position. Samples were taken from the top 20

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cm, transferred to sterile plastic containers and stored for maximally one month at 4°C until analysis. Pesticide

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mineralization assays performed with the same sample after different storage times did not differ in

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mineralization kinetics for at least 6 months after sampling. Table 1 shows the SF samples, their origin and

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BAM contamination in the DWTP intake water. BAM concentrations in the SF influent were unavailable but

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not expected to differ from intake water concentrations since the treatment steps implemented before sand

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filtration do not remove BAM. 2,6-DCBA concentrations were unavailable since its measurement is not

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included in routine water monitoring campaigns. DWTPs Kluizen, De Blankaart, Antwerp, Eeklo, Zele and

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Snellegem treated water containing BAM and other pesticides. The intake water treated at DWTP Klein-Sinaai

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contained other pesticides, but no BAM, and the remaining four DWTPs (Saint-Léger, Bree, Haacht and

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Lommel) treated pristine groundwater in which no pesticide residues were detected. All SFs were rapid SFs

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except the one from Antwerp, which was a slow SF. Soil samples were taken from the top 20 cm from different

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locations in Belgium. At several locations (Heverlee, Kessel-Lo, Linkhout, Rotselaar and Schoonderbuken),

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samples were taken from different areas in close proximity to each other, with different land uses (Table 2). An

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overview of the implemented treatment steps at all DWTPs, physicochemical and biological characteristics of

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SF and soil samples and a map with all sampled locations are given in the supporting information.

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Chemicals, bacterial strains and culture conditions. [Ring-U-14C]-labeled BAM with > 95% purity was

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purchased from Izotop (Institute of Isotopes Co., Ltd., Budapest, Hungary) and dissolved in acetone.

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Aminobacter sp. strain M6.100g is a genetically characterized mutant of the BAM mineralizing Aminobacter sp.

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MSH1.25 Strain M6.100g stoichiometrically converts BAM to 2,6-DCBA but is deficient in further degradation

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of 2,6-DCBA and hence in mineralization of the aromatic moiety. M6.100g was grown from frozen stocks on

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R2A.26 After 4 days of incubation at 25°C, a smear of colonies was taken, inoculated in 50 mL R2B26

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containing 10 mg/L BAM (Sigma-Aldrich, Steinheim, Germany) and incubated for 2 more days at 25°C on an

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orbital shaker.

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Production of 14C-2,6-DCBA. 14C-labeled 2,6-DCBA was produced by incubating [ring-U-14C]-labeled BAM

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with strain M6.100g. M6.100g cells were harvested by centrifugation (4000g, 15 min, 15°C) and inoculated in ACS Paragon Plus Environment


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50 mL MMO medium27 amended with 1500000 counts per minute (CPM) 14C-BAM (100 µg/L) at a cell density

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of 108 cells/mL in flasks equipped with a glass vial containing 1 mL 0.5 M NaOH to trap 14CO2. After 2 days of

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incubation at 20°C, the deficiency of 14CO2 production was confirmed by measuring radioactivity in the NaOH

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solution as described.28 After centrifugation (9000g, 15 min),

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supernatant by solid phase extraction (SPE) using Oasis MAX SPE cartridges (Waters, Zellik, Belgium)

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preconditioned with 1 mL methanol, 1 mL mQ-H2O and 0.5 mL PO4-buffer (pH 7.5). The supernatant was

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loaded at a flow rate of 0.1 mL/min. Thereafter, the cartridge was washed with 1 mL mQ-H2O and dried under

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vacuum. Neutral compounds, including residual

14

C-2,6-DCBA was extracted from the

14

C-BAM, were eluted with 1 mL methanol.

14

C-2,6-DCBA

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was eluted using a solution of 90% methanol, 7% H2O and 3% HNO3. The purity of the 14C-2,6-DCBA extract

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was evaluated using reverse phase ultrahigh performance liquid chromatography as described,20 but eluting with

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only an isocratic flow of 15% acetonitrile and 85% mQ water (acidiﬁed with H3PO4 to pH 2.5) for 8 min. The

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chromatogram was compared with a

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DCBA were observed, i.e., other compounds such as BAM, ortho-chlorobenzamide, ortho-chlorobenzoic acid,

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benzamide or benzoate were not detected. Radioactivity was measured28 in both the 2,6-DCBA fraction

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(fraction eluting from 4.5 to 6.5 min run time, retention time of 2,6-DCBA is 5.3 min) and the rest of the eluted

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sample, showing that the

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substrate. The identity of the

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mutant of MSH1 that lacks the ability to convert BAM to 2,6-DCBA but that mineralizes 2,6-DCBA.

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Microcosm mineralization assays. Mineralization assays were performed in triplicate in 10 mL vials

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containing 2.5 g of wet SF material/soil as described.28 Taking into account a detection limit for radioactivity of

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30 CPM per measurement, a total radioactivity of 15000 CPM 14C-BAM or 14C-2,6-DCBA, was used to enable

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accurate determination of kinetic mineralization parameters such as the maximum mineralization rate, which

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was generally < 1 %.d-1 in case of BAM. After evaporation of acetone or methanol, pure 14C-BAM or 14C-2,6-

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DCBA was dissolved in 25 µL mineral MMO medium (spike concentration of 2 mg/L) and added to 2.5 g SF or

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soil material (wet weight). Four hundred µL sterilized mQ-H2O was added to the soil microcosms to attain

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water contents similar to these of the SF samples, leading to final BAM or 2,6-DCBA concentrations of 100 to

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200 µg/L in the SF/soil water phase. Each assay was replicated three times and complemented with an abiotic

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control (soil or SF sample sterilized by autoclaving three times at 121 °C for 20 min with 24 h periods in

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between). Microcosms were incubated on an orbital shaker at 20°C for 50 to 100 days during which 14CO2 was

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trapped using NaOH and

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plotting the cumulative percentage 14CO2 as a function of incubation time, subtracted by the background activity

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measured for abiotic controls (of which none showed mineralization, data not shown).

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Evaluation of mineralization kinetics. The mineralization capacity in every mineralization assay was

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evaluated based on the extent of mineralization (after 50 days of incubation, pmax) and the maximum linear

12

C-2,6-DCBA standard. No other peaks than that associated with 2,6-

14

C-2,6-DCBA extract had a purity of 94%, i.e., identical to this of the

14

14

14

C-BAM

C-2,6-DCBA was additionally confirmed by showing its mineralization by a

CO2-radioactivity measured.28 Cumulative mineralization curves were obtained by


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mineralization rate (kmax) derived as the maximal slope of the mineralization curve using three consecutive data

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points. To study mineralization kinetics in more detail, mineralization curves were modelled with the Three-

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half-order model,29 which combines first and zero order mineralization kinetics with linear growth of the

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degrading organisms: ࡼ = ࢖૚ ቆ૚ − ࢋ

࢚࢘² ି࢑૚࢚ି൬ ൰ ૛ ቇ+

࢑૙࢚

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in which P is the percentage mineralization at time t, p1 is the total extent of mineralization by the first order

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process, k0 and k1 are the zero and first order rate constants, respectively, and r is the linear growth rate

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constant. Parameter values were estimated by nonlinear regression analysis, using the lsqnonlin command in

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Matlab (Mathworks) with the default trust-region-reflective algorithm, at a termination tolerance of 10-14 and

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allowing maximally 200000 function evaluations and 30000 iterations. Initial parameter estimates were set at

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100, 5, 5 and 5 for p1, k0, k1 and r, respectively.

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The Three-half-order model is most applicable to mineralization curves that show a lag phase, which indicates

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adaptation/growth of the BAM/2,6-DCBA degrading organisms before significant mineralization is detected.

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The presence of such a lag phase is reflected by r-values > 0. When r approached zero, i.e., when the average

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value of r for three replicates was less than 0.001, the modelling procedure was repeated after deleting the linear

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growth term from the Three-half-order model, reducing it to the First-zero-order model.30 This did not affect the

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estimated parameter values, but improved their accuracy, i.e., their standard errors decreased. For soil samples

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He1, KL1, Li2 and SL, r-values predicted with the Three-half-order model were greater than 0.001, but the

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First-zero-order model yielded better prediction of the mineralization curves, based on visual comparison

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(Figure S2). r-values for these mineralization assays were therefore set to 0 and parameter values were predicted

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using the First-zero-order model. Mineralization was considered significant when pmax > 5%.

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Partial least squares regression (PLSR). Multivariate analysis using PLSR was performed to correlate

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physicochemical and biological characteristics of DWTP intake water/SF samples or soil samples with kinetic

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parameters of 2,6-DCBA mineralization in two separate models. DWTP Antwerp was excluded since no raw

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water data were available. PLSR was performed using SOLO software (Eigenvector Research Inc., Manson,

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WA, USA) as described in the supporting information. As independent variables for the model corresponding to

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the SF samples (designated as the SF model), the characteristics shown in Table S1 were used, including

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exposure to BAM and other micropollutants, nutrient concentrations, organic carbon concentrations, oxygen

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availability, pH, temperature, iron and manganese concentrations and the bacterial 16S rRNA gene copy

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number. As independent variables for the model corresponding to the soil samples (the soil model), the

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characteristics shown in Table S2 were used, including soil texture data, pH, nutrient concentrations, organic

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carbon concentrations, (specific) UV-absorbance as a measure of aromatic compound content31 and the bacterial ACS Paragon Plus Environment


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16S rRNA gene copy number. Soil moisture content was not included since mineralization assays were

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performed with adjusted water content (see above). The dependent variables used for both models were the

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kinetic parameters of 2,6-DCBA mineralization, i.e., pmax, kmax, p1, k0, k1 and r (Table S3). Latent variables were

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selected based on simultaneously capturing most of the variance in the independent variables and most of the

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co-variance with all six dependent variables in the same model.

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Bioaugmentation assay. M6.100g cells were harvested and diluted to 107 cells/mL in 0.01M MgSO4, of which

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50 µL was added to 14C-BAM mineralization assays performed with SF sample K4 as described above. As non-

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inoculated controls, 50 µL sterile 0.01M MgSO4 was added. Mineralization was monitored during 33 days.

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Results

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BAM mineralization capacity in sand filters. BAM mineralization was evaluated in SF samples from 11

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DWTPs. Results for the extent of mineralization after 50 days of incubation (pmax) and the maximum linear

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mineralization rate (kmax) are shown in Table 1. Using a threshold of pmax > 5%, substantial BAM mineralization

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was recorded for samples from Kluizen, Snellegem and Eeklo. Sample K1 showed a sigmoidal BAM

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mineralization curve (Figure 1A) with a pmax and kmax of 34% and 1%.d-1, respectively. In samples Sn1 and E1,

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BAM mineralization proceeded more slowly (kmax = 0.3 – 0.5%.d-1) and reached a lower extent (pmax = 6 – 8%).

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To assess whether the BAM mineralization capacity observed for DWTP Kluizen, Snellegem and Eeklo was

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consistent in time, extra SF samples were taken at different time points (samples K2, K3, K4, E2, E3 and Sn2).

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Mineralization capacity generally remained constant and an increasing trend was even observed, between

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sampling time point 1 and 2 to 4 and sampling time point 2 and 3 in samples from Kluizen and Eeklo,

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respectively (Table 1, Figure S3).

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Comparison of the different kinetic parameter values (Figure S4) provides indications about the degradation

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processes that lead to mineralization. Kinetic parameters could not accurately be estimated for sample E3 using

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the Three-half-order model. However, for samples E1, E2, Sn1 and Sn2, r equaled 0, which indicates that the

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observed slow BAM mineralization did not support growth of the degrading organisms. On the other hand, the

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sigmoidal pattern of the BAM mineralization curves in samples from Kluizen was reflected by r-values > 0 and

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the trend of increasing mineralization capacity (with shorter lag phases) for samples from Kluizen taken at

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different time points was reflected by differences in r, but not by k0 and k1.

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2,6-DCBA mineralization capacity in sand filters. 2,6-DCBA mineralization was tested in a selection of SF

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samples, i.e., K4, E3, Sn2, StL, Br, Hch and Lo, including SFs that either treated BAM contaminated or

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uncontaminated water and SFs that showed BAM or no BAM mineralization. All samples tested positive for

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2,6-DCBA mineralization (Figure 1B), but mineralization kinetics differed greatly (Table 2, Figure 2A). SFs ACS Paragon Plus Environment

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treating BAM contaminated water (K4, E3, Sn2) all showed high 2,6-DCBA mineralization capacity with pmax-

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and kmax-values reaching up to 63% and 16%.d-1, respectively. Results for samples treating pristine groundwater

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were more divergent. Intermediate mineralization capacity was found in samples Hch and Lo, with pmax- and

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kmax-values of 27 to 35% and 5 to 7%.d-1, respectively; while 2,6-DCBA mineralization in samples Br and StL

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was very low, with kmax < 0.3%.d-1 and pmax < 6%.

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Both k0 and k1 behaved in a similar way as kmax for all SF samples (Figure 2A), which indicates that both the

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first and zero order mineralization rate determined the maximum mineralization rate. For all SF samples except

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Br and StL, r equaled 0. For samples Br and StL, kinetic parameters estimated using the Three-half-order model

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were not accurate, but in accordance with those calculated for pmax and kmax.

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BAM and 2,6-DCBA mineralization capacity in soil samples. The frequent occurrence of 2,6-DCBA

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mineralization in both BAM exposed and non-exposed SFs aroused our interest whether this capacity is also

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common to other ecosystems. Therefore, a broad survey on BAM/2,6-DCBA mineralization capacity was

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performed using 17 soils from various ecosystems. The only soil that showed substantial BAM mineralization

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was the railway embankment sample from Rotselaar (R3). Mineralization was nevertheless slow, with an

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average pmax and kmax of 24.5% and 0.72%.d-1, respectively (Table 2,

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Figure 1A). On the other hand, all soil samples tested positive for 2,6-DCBA mineralization (Figure 1C).

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Mineralization capacity varied, being highest in forest soils (pmax = 46 to 70%, kmax = 5 to 15%.d-1), followed by

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grassland soils (pmax ≈ 54%, kmax ≈ 4%.d-1) and railway embankments, agricultural and garden soil (pmax = 23 to

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45%, kmax = 1 to 5%.d-1) (Figure 2B). The dune sand sample showed lowest 2,6-DCBA mineralization capacity

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with a pmax < 20% and kmax ≈ 0.5%.d-1. One of the forest soil samples (R1) differed from the other forest

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samples, with a pmax and kmax of only 34% and 2%.d-1, respectively, hence being comparable to railway

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embankments and agricultural soils.

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In contrast to the SF samples, k0-values for 2,6-DCBA mineralization in the soil samples were all in the same

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range, i.e., 0.07 to 0.15 (Figure 2B) and pmax > p1. The zero order mineralization process thus contributed to the

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maximum mineralization extent. For mineralization curves without lag phase, the linear growth rate (r) equaled

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0, as was the case for the forest soils (except R1), four of the five railway embankment soils and the agricultural

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soil StT. In all other cases, the linear growth term contributed to the kmax-values, since these were higher than

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expected based on the corresponding k1-values. Kinetic parameters for soil BL could not accurately be

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estimated with the Three-half-order model.

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Partial least squares regression (PLSR). PLSR was performed to determine whether 2,6-DCBA

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mineralization kinetics correlated with characteristics of either the SF or soil samples. In case of SF samples,

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pmax, p1, kmax and k0 were successfully calibrated to DWTP/SF characteristics as shown by high R²-values (>0.8) ACS Paragon Plus Environment


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and low residual mean square errors (RMSE) (Table S4). However, based on results for cross validation, none

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of the kinetic parameters could be predicted using DWTP/SF characteristics (R² < 0.5, high RMSE) (Table S4).

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To evaluate which characteristics correlated with mineralization, the regression vector was analyzed for p1, pmax,

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kmax and k1 (Figure 3). For all four parameters, 2,6-DCBA mineralization correlated positively with exposure to

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BAM and other micropollutants and with the presence of NH4, alternative carbon sources (NPOC), Fe and Mn.

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A negative correlation was found with the average temperature of the intake water.

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Only pmax, p1 and kmax were successfully calibrated to soil characteristics but, in contrast to the SF model, the

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model could be used to predict pmax and p1 (R² > 0.6 for cross validation) (Table S4). Results for the regression

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vector (Figure 3) were comparable for pmax, p1 and kmax and indicated that the most important soil characteristics

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determining 2,6-DCBA mineralization were pH (negative correlation), UV-absorbance (A254, positive

231

correlation) and texture. With regards to the latter, the most important fraction was clay, of which the

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percentage correlated positively with mineralization.

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A similar multivariate analysis for BAM mineralization could not be performed since the sample population

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sizes were insufficiently large as only few BAM mineralization curves could accurately be described with the

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Three-half-order model and only few SF/soil samples showed substantial BAM mineralization.

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Mineralization of 2,6-DCBA produced by BAM degrading bacteria in bioaugmented sand filters. The

237

results reported above show that in contrast to 2,6-DCBA, BAM mineralization in SFs occurs rarely and, if so,

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proceeds slowly. A solution to establish BAM mineralization in SFs is bioaugmentation with bacteria such as

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Aminobacter sp. MSH1, but this might lead to the release of 2,6-DCBA, being a bottleneck for BAM

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mineralization in MSH1.19 Therefore, we determined the fate of 2,6-DCBA released in the SF after introducing

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strain M6.100g, an MSH1 mutant which converts BAM to 2,6-DCBA but is deficient in its further

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mineralization, imposing as such a worst case scenario. M6.100g was added to SF sample K4 in a BAM

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mineralization assay. The mineralization curve was compared with those obtained for non-inoculated K4

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samples amended with 14C-BAM or 14C-2,6-DCBA (Figure 4). Adding strain M6.100g increased kmax from 3 to

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≈ 8%.d-1, but did not reach the 2,6-DCBA mineralization rate (≈ 13%.d-1) (Figure S5). Similar effects were

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found for k1. pmax after 33 days and k0 were comparable for all three mineralization curves. The estimated r-

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values of the bioaugmented BAM mineralization assays did not significantly differ from those for BAM

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mineralization without bioaugmentation, whereas for 2,6-DCBA mineralization without bioaugmentation, r

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equaled 0.


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Discussion

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Mineralization of BAM and 2,6-DCBA was evaluated in SF samples from DWTPs differing in intake water

252

BAM contamination and, for comparison, in topsoil samples from different locations. Slow to intermediate

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BAM mineralization was found for three of the five DWTPs which treated BAM contaminated water. The high

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BAM mineralization capacity found in samples from Kluizen was consistent in time while none of the non-

255

exposed SF samples mineralized BAM. Furthermore, BAM was mineralized in only one soil sample (R3), taken

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from a railway embankment located in an industrial area. Although we do not have records of pesticide use at

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the locations of the soil samples, dichlobenil, the parent compound of BAM, has often been used for weed

258

control on railways, hence indicating plausible pre-exposure of soil R3 to BAM. As such, our results for both

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SF and soil samples are in accordance with previous studies that report BAM degradation/mineralization as rare

260

and only occasionally found in pre-exposed environments.13–17 The occurrence of BAM mineralization might be

261

the result of selective conditions for adaptation of microbiota to degrade and even metabolize BAM. However,

262

exposure to BAM does not assure the occurrence of BAM mineralization since certain BAM exposed SFs (from

263

De Blankaart and Zele) did not show mineralization. In case of the SF samples from Kluizen and of soil sample

264

R3, mineralization curves were sigmoidal with lag phases of several days before significant BAM

265

mineralization was recorded. Although we have no evidence, this might indicate that BAM mineralization is

266

growth linked in those ecosystems. On the other hand, the long lag phases suggest that initial BAM degrading

267

populations are relatively small. Our study provides the first report of BAM mineralization capacity in an

268

environment different from soil and is of particular interest for DWTPs since BAM is a frequent groundwater

269

contaminant.3,4

270

In contrast to BAM, all SF samples mineralized 2,6-DCBA, showing that 2,6-DCBA mineralization is more

271

distributed in SFs than BAM mineralization. 2,6-DCBA mineralization capacity was highest for DWTPs

272

treating BAM contaminated water, with average maximum rates (kmax) up to 16%.d-1. That the SF samples

273

which showed BAM mineralization also showed 2,6-DCBA mineralization suggests that the observed BAM

274

mineralization pathway in the SFs likely proceeds through 2,6-DCBA. The results further indicate that, as

275

suggested for BAM, 2,6-DCBA mineralization depends on exposure to BAM, which was supported by PLSR

276

analysis. This might be due to the potential presence of 2,6-DCBA as a BAM transformation product in the

277

intake water or produced in the SF units, and agrees with Holtze et al.14 who reported that 2,6-DCBA was only

278

degraded in soils pre-exposed to dichlobenil. However, high 2,6-DCBA mineralization rates (≈ 6%.d-1) were

279

also recorded in samples of two SFs receiving pristine groundwater (Hch and Lo). The other two pristine

280

samples (StL2 and Br) showed 2,6-DCBA mineralization as well, albeit slow. Other factors than exposure to

281

BAM/2,6-DCBA might thus be key or contribute to 2,6-DCBA mineralization. That exposure to

282

dichlobenil/BAM is not a prerequisite to establish 2,6-DCBA mineralization is further supported by the results ACS Paragon Plus Environment


Page 10 of 19

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obtained with the soil samples. These show that environmental prevalence of 2,6-DCBA mineralization is high

284

since all sampled soils mineralized 2,6-DCBA, with highest mineralization found for forest soils (Li2, SL, He1

285

and KL1). Previous reports on 2,6-DCBA biodegradation capacity did not always find degradation but never

286

included soils from forest environments.14,15 On the other hand, Fulthorpe et al.32 found that the capacity to

287

mineralize another chlorinated benzoic acid, i.e., 3-chlorobenzoate (3-CBA), was high and omnipresent in forest

288

and woodland soils. PLSR analysis indicated that 2,6-DCBA mineralization in the soil samples, as for the SF

289

samples, was related with high organic carbon content and in particular aromatic compounds (measured as UV-

290

absorbance). Likewise, Larsson et al.33 reported that several chlorinated aromatic xenobiotics were more easily

291

mineralized by microbial communities from humic-rich lake water, than by communities from a clear-water

292

lake. Fulthorpe et al.,32 found no correlation between the 3-CBA mineralization rate and any of the measured

293

soil characteristics but suggested that the high 3-CBA mineralization capacity in forest soils might be attributed

294

to high levels of organic compounds like aromatics, naturally present as components of plant litter, and

295

organochlorine compounds, for instance produced by forest litter decomposing fungi.32,34–36 Organisms

296

metabolizing these substrates might possess broad substrate enzymes that degrade analogous compounds such

297

as 2,6-DCBA. In case such organisms are highly abundant among the microbial community, this might explain

298

for the observed high 2,6-DCBA mineralization activity. Interestingly, PLSR analysis showed that, also for the

299

SF samples, 2,6-DCBA mineralization correlated with the intake water organic carbon content. Hence high

300

natural microbial activity towards potentially present aromatic compounds might also explain the widely

301

distributed 2,6-DCBA mineralization capacity in SFs. Otherwise, organisms present in microbial communities

302

able to metabolize (chlorinated) aromatic compounds might be prone to more rapid adaptation to

303

metabolize/degrade analogous anthropogenic compounds like 2,6-DCBA when they become available in the

304

ecosystem, as might be the case in SFs exposed to BAM.

305

Most of the 2,6-DCBA mineralization curves for SF and soil samples showed no lag phase, represented by

306

linear growth rates (r) equal to 0. This indicates that the degrading community did not require an initial

307

adaptation/growth phase to establish

308

mineralization kinetics do not provide information whether or not 2,6-DCBA mineralization might support

309

growth, but also do not exclude it. On the other hand, the absence of a lag phase indicates that the initial number

310

of 2,6-DCBA degrading organisms was relatively high. Based on comparison with results for BAM

311

mineralization by Aminobacter sp. MSH1 in SF material, the number of 2,6-DCBA mineralizing cells should at

312

least be 105 cells/g to achieve lag times shorter than one day (Vandermaesen et al., unpublished results).

313

Our observations that BAM and 2,6-DCBA can be mineralized in SF material opens windows for future

314

bioremediation strategies in DWTPs. However, taking into account (i) the relatively low BAM mineralization

315

rates (max. 2.8%.d-1 for sample K4) (ii) the low numbers of BAM degraders, as discussed above and (iii) the

316

high fluxes and short hydraulic retention times operated in rapid SFs, intrinsic BAM removal is expected to be

14

CO2 production from the added


14

C-2,6-DCBA. As such, the

Page 11 of 19


317

insufficient in actual SFs to reach EU threshold concentrations. In contrast, 2,6-DCBA was readily mineralized

318

in most SF samples and the actual numbers of intrinsic 2,6-DCBA degraders appear relatively high. Assuming

319

that (i) 2,6-DCBA degradation is metabolic, (ii) the ratio of 14CO2 production to 14C incorporated into biomass

320

is constant throughout the experiment and (iii) 2,6-DCBA is completely degraded when mineralization reaches

321

its plateau (thus the remaining

322

(sample E3) corresponds to 100% 2,6-DCBA degradation and the kmax-value of 16%.d-1 (sample E3)

323

corresponds to a degradation rate of 1.6 µg/L.h at the used initial 2,6-DCBA concentration of 150 µg/L. To

324

mineralize a 2,6-DCBA concentration of 0.14 µg/L, corresponding to the maximum intake water BAM

325

concentration found in this study (Table 1), to below the threshold concentration of 0.1 µg/L in a rapid SF with

326

a flow rate of 20 m/h and a filter depth of 1 m, a mineralization rate of 8%.d-1 or 0.8 µg/L.h is then needed,

327

which is lower than found for sample E3. Actual mineralization rates in operational SFs are however expected

328

to be negatively influenced by regular backwashing,37 lower temperatures38,39 and lower pesticide

329

concentrations.16,25,40 Although the extent to which this affects 2,6-DCBA mineralization cannot be predicted

330

based on the currently available data and although the mechanism of mineralization is unsure, the results are

331

promising in order to achieve complete BAM degradation after bioaugmentation of SFs with Aminobacter sp.

332

MSH1, especially at lower flow rates such as those used in slow SFs (0.4 m/h).

333

Bioaugmentation of SFs with BAM degrading bacterial strains such as Aminobacter sp. MSH1 seems a

334

promising strategy for BAM removal in DWTPs.18 A possible drawback could however be the production of

335

2,6-DCBA after the first step in BAM degradation, as its further mineralization has been described to be rate

336

limiting.19,20 The high 2,6-DCBA mineralization found in SF samples from DWTPs treating BAM contaminated

337

water though suggests that any 2,6-DCBA produced during BAM degradation is rapidly degraded by the

338

endogenous community, as shown in our bioaugmentation assay with strain M6.100g. As such, our observations

339

are also of major interest for bioaugmentation approaches for BAM removal in DWTPs using MSH1. In case

340

BAM is mineralized in SFs via 2,6-DCBA, conversion of BAM to 2,6-DCBA appears the rate limiting reaction.

341

This is in agreement with studies on BAM mineralization in environmental soil samples by Clausen et al.,13 but

342

in contrast to what has been described for MSH1, i.e., degradation of 2,6-DCBA as the bottleneck for BAM

343

mineralization.19,20

14

C is also degraded and incorporated into biomass), then a pmax-value of 61%

344



Page 12 of 19

345

Supporting information available

346

Supporting Information Available: Overview of SF and soil characteristics and locations; details, data used for

347

and performance of PLSR analysis; a comparison of the Three-half-order and First-zero-order model; BAM

348

mineralization curves and kinetics for SF samples taken at different time points and kinetic parameters from the

349

bioaugmentation assay. This information is available free of charge via the Internet at http://pubs.acs.org.

350

Acknowledgements

351

This study was funded by the FP7 project BIOTREAT (EU grant n° 266039), the Inter-University Attraction

352

Pole (IUAP) “µ-manager” of the Belgian Science Policy (BELSPO, P7/25) and the “Fonds Wetenschappelijk

353

Onderzoek” (FWO) post-doctoral fellow grant n° 12Q0215N to B. Horemans. We thank S. Goethals and R.

354

Jenné for assistance in SF sampling and providing DWTP process information, and K. Simoens, D. Grauwels,

355

K. Moors, J. Plevoets, L. Fondu, A. Deckers, A. Vertommen and N. Croonenborghs for assistance in the

356

experimental work.

357

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Table 1. Overview of sand filter samples used in this study with kinetic data for recorded BAM and 2,6-DCBA mineralization. Average values ± standard deviation are given for three replicates.

SF Sample K1 K2 K3 K4 DB AWW E1 E2 E3 Z Si Sn1 Sn2 StL Br Hch Lo

Sampling date 8/11/2011 12/06/2012 3/04/2013 6/05/2014 27/06/2012 13/06/2012 9/11/2011 13/06/2012 27/11/2014 28/06/2012 28/06/2012 28/06/2012 19/11/2014 17/11/2014 4/03/2015 5/05/2015 7/07/2015

Location Kluizen Kluizen Kluizen Kluizen De Blankaart Antwerp Eeklo Eeklo Eeklo Zele Klein-Sinaai Snellegem Snellegem Saint Léger Bree Haacht Lommel

Type of intake water1 SW + GW SW + GW SW + GW SW + GW SW SW GW GW GW GW GW GW GW GW GW GW GW

BAM exposure (µg/L)2 0.09 0.09 0.09 0.09 0.10 unknown 0.02 0.02 0.02 0.06 0.00 0.14 0.14 0.00 0.00 0.00 0.00

BAM mineralization3 pmax (%) kmax (%.d-1) 33.9 ± 3.74 0.98 ± 0.18 62.4 ± 6.89 2.92 ± 0.47 62.3 ± 3.39 3.24 ± 0.13 63.2 ± 11.9 2.79 ± 0.49 1.57 ± 0.62 0.09 ± 0.04 4.44 ± 1.42 0.20 ± 0.05 5.89 ± 0.65 0.33 ± 0.04 6.99 ± 1.27 0.26 ± 0.10 10.6 ± 1.47 0.31 ± 0.07 1.20 ± 0.16 0.22 ± 0.06 2.08 ± 0.68 0.09 ± 0.00 7.82 ± 5.94 0.55 ± 0.41 4.82 ± 0.58 0.21 ± 0.01 1.04 ± 0.04 0.03 ± 0.00 0.40 ± 0.13 0.02 ± 0.00 2.60 ± 0.19 0.10 ± 0.02 4.57 ± 0.35 0.12 ± 0.02

2,6-DCBA mineralization3,4 pmax (%) kmax (%.d-1) n.d. n.d. n.d. n.d. n.d. n.d. 50.8 ± 9.49 11.64 ± 2.25 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. 61.2 ± 5.31 15.68 ± 5.69 n.d. n.d. n.d. n.d. n.d. n.d. 62.7 ± 0.74 12.9 ± 1.43 5.22 ± 1.69 0.15 ± 0.05 5.45 ± 4.80 0.22 ± 0.24 35.0 ± 3.45 7.09 ± 0.99 26.8 ± 3.30 5.45 ± 1.43

1

SW = surface water, GW = groundwater Average BAM concentration in the DWTP intake water 3 pmax = extent of mineralization after 50 days of incubation, kmax = maximum linear mineralization rate 4 n.d. = not done 2

478 479 480 481

Table 2. Overview of soil samples used in this study with kinetic data for recorded BAM and 2,6-DCBA mineralization. Average values ± standard deviation are given for three replicates.

BAM mineralization1 Soil Sampling sample date Location Land use pmax (%) kmax (%.d-1) BL 25/05/2015 Blankenberge Sand dune 3.54 ± 0.38 0.11 ± 0.02 Ha 23/03/2015 Halen Agriculture: maize, potatoe 2.54 ± 0.19 0.11 ± 0.03 He1 16/03/2015 Heverlee Deciduous forest 1.69 ± 0.47 0.17 ± 0.04 He2 27/05/2015 Heverlee Railway embankment, domestic area 0.65 ± 0.31 0.05 ± 0.03 KL1 2/08/2015 Kessel-Lo Deciduous forest 2.22 ± 0.19 0.13 ± 0.03 KL2 2/08/2015 Kessel-Lo Railway embankment, domestic area 1.37 ± 0.28 0.08 ± 0.01 Li1 15/03/2015 Linkhout Grassland, historical: coniferous forest 0.76 ± 0.11 0.08 ± 0.01 Li2 23/03/2015 Linkhout Mixed forest 0.77 ± 0.09 0.17 ± 0.01 R1 14/03/2015 Rotselaar Coniferous forest 1.54 ± 0.08 0.12 ± 0.01 R2 14/03/2015 Rotselaar Domestic garden, riverbank 1.55 ± 0.30 0.13 ± 0.02 R3 30/05/2015 Rotselaar Railway embankment, industrial area 24.5 ± 2.92 0.72 ± 0.09 SB1 15/03/2015 Schoonderbuken Grassland, historical: agriculture 2.89 ± 0.18 0.13 ± 0.01 SB2 15/03/2015 Schoonderbuken Agriculture: maize, sugar beet, wheat 1.29 ± 0.59 0.07 ± 0.02 Sch 26/06/2015 Schulen Railway embankment, remote area 1.57 ± 0.13 0.12 ± 0.01 SL 14/03/2015 Somme-Leuze Mixed forest 4.45 ± 0.78 0.22 ± 0.03 StT 12/03/2015 Sint-Truiden Agriculture: pear orchard 2.45 ± 0.38 0.18 ± 0.01 Zm 26/06/2015 Zelem Railway embankment, remote area 3.00 ± 0.31 0.11 ± 0.01 1 pmax = extent of mineralization after 50 days of incubation, kmax = maximum linear mineralization rate

482


2,6-DCBA mineralization1 pmax (%) kmax (%.d-1) 15.7 ± 6.21 0.50 ± 0.06 28.7 ± 1.69 1.15 ± 0.29 51.2 ± 4.60 7.13 ± 1.21 31.9 ± 3.21 2.29 ± 0.29 54.5 ± 3.28 8.52 ± 0.55 32.7 ± 2.24 2.09 ± 0.34 54.6 ± 4.54 4.81 ± 1.28 63.2 ± 7.55 9.54 ± 3.61 33.9 ± 1.90 2.39 ± 0.37 42.5 ± 2.44 2.04 ± 0.39 32.0 ± 1.23 1.23 ± 0.11 52.2 ± 2.68 3.04 ± 0.42 26.1 ± 3.66 0.99 ± 0.23 36.8 ± 3.65 2.58 ± 0.23 60.8 ± 3.57 12.6 ± 2.45 36.8 ± 1.51 3.86 ± 0.10 35.6 ± 4.90 4.38 ± 0.89


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Figure 1. Cumulative BAM mineralization curves (A) for sand filter samples (full lines) and soil sample R3 (dashed line), 2,6DCBA mineralization curves for sand filter samples (B) from DWTPs treating water contaminated with BAM (black) and pristine groundwater (grey) and 2,6-DCBA mineralization curves in soil samples (C) from forests (green), agricultural fields (red), railway embankments (brown) and grasslands, garden soil and a sand dune (blue). Mean values and standard deviations based on three replicates are shown for 14CO2 production relative to the initial amount of 14C-BAM/2,6-DCBA added (14C0).


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Figure 2. Kinetic parameters of 2,6-DCBA mineralization in sand filter samples (A) from DWTPs treating water contaminated with BAM (black) and pristine groundwater (grey) and in soil samples (B) from forests (green), agricultural fields (red), railway embankments (brown) and grasslands, garden soil and a sand dune (blue): extent of mineralization after 50 days (pmax), maximum linear mineralization rate (kmax), extent of mineralization by the first order process (p1), first order mineralization rate (k1), zero order mineralization rate (k0) and linear growth rate (r). Error bars indicate 95% confidence intervals for kinetic parameters returned by the Three-half-order model (P1, k0, k1 and r).



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Figure 3. Regression vectors for DWTP/SF characteristics (left) and soil characteristics (right) correlated with the extent of mineralization by the first order process (p1, black), the extent of mineralization after 50 days (pmax, grey) and the maximum linear mineralization rate (kmax, white) for 2,6-DCBA mineralization in soil/SF samples. For the SF model, results are only shown for p1 because of overlap with data points for pmax, kmax and the zero order mineralization rate (k0). The regression vector returns positive values for characteristics that correlate positively with mineralization and negative values for those that correlate negatively. The absolute value relates to the importance of the characteristic in the regression model. A detailed overview of the DWTP/SF and soil characteristics used is provided in Table S1 and Table S2, respectively.

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Figure 4. Cumulative mineralization curves for BAM (black) and 2,6-DCBA (grey) with (full symbols) and without (open symbols) bioaugmentation with strain Aminobacter sp. M6.100g in sand filter sample K4. Mean values and standard deviations based on three replicates are shown for 14CO2 production relative to the initial amount of 14C-BAM/2,6-DCBA added (14C0).


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1037x580mm (96 x 96 DPI)


(BAM) and its Metabolite 2,6-Dichlorobenzoic Acid - ACS Publications

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