Enhanced Biological Trace Organic Contaminant Removal: A Lab

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Enhanced Biological Trace Organic Contaminant Removal (EBTCR): a lab scale demonstration with bisphenol A-degrading bacteria Sphingobium sp. BiD32 Nicolette Angela Zhou, and Heidi Lois Gough Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b00727 • Publication Date (Web): 23 Jun 2016 Downloaded from http://pubs.acs.org on July 5, 2016

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Environmental Science & Technology

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Enhanced Biological Trace Organic Contaminant Removal (EBTCR): a lab scale demonstration with bisphenol A-

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degrading bacteria Sphingobium sp. BiD32

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Nicolette A. Zhou, Heidi L. Gough*

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University of Washington, Department of Civil and Environmental Engineering; More Hall 201 Box 352700;

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Seattle, Washington 98195-2700, USA.

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* corresponding author, Address: University of Washington, Department of Civil and Environmental Engineering,

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More Hall 201 Box 352700, Seattle, WA 98195-2700, USA; Tel.: 206-221-0791; Fax: 206-685.9185; email:

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[email protected]

1 ACS Paragon Plus Environment


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Abstract

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Discharge of trace organic contaminants (TOrCs) from wastewater treatment plants (WWTPs) may contribute to

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deleterious effects on aquatic life. Release to the environment occurs both through WWTP effluent discharge and

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runoff following land applications of biosolids. This study introduces Enhanced Biological TOrCs Removal

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(EBTCR), which involves continuous bioaugmentation of TOrC-degrading bacteria for improved removal in

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WWTPs. Influence of bioaugmentation on enhanced degradation was investigated in two lab-scale sequencing batch

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reactors (SBRs), using bisphenol A as the TOrC. The reactors were operated with 8 cycles per day and at two solids

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retention times (SRT). Once each day, the test reactor was bioaugmented with Sphingobium sp. BiD32, a

20

documented BPA-degrading culture. After bioaugmentation, BPA degradation (including both the dissolved and

21

sorbed fractions) was 2 to 4 times higher in the test reactor than in a control reactor. Improved removal persisted for

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greater than 5 cycles following bioaugmentation. By the last cycle of the day, enhanced BPA removal was lost,

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though it returned with the next bioaugmentation. A net loss of Sphingobium sp. BiD32 was observed in the

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reactors, supporting the original hypothesis that continuous bioaugmentation (rather than single-dose

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bioaugmentation) would be required to improve TOrCs removal during wastewater treatment. This study represents

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a first demonstration of a biologically-based approach for enhanced TOrCs removal that reduces concentrations in

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both wastewater effluent and prevents transfer to biosolids.

28 29

Keywords: PPCP, BPA, emerging contaminants, activated sludge, TOrC, endocrine disruption


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1.

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While trace organic contaminants (TOrC) are biologically degraded during wastewater treatment 1–3, their residual

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concentrations in effluent and biosolids remain an environmental concern 4,5. A wide range of TOrCs effluent

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concentrations 6–9 and removal rates 1,10–12 are reported for wastewater treatment plants (WWTP) operating with

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traditional secondary treatment. Variation in effluent concentrations are speculated to result from a combination of

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multiple factors such as operational conditions (e.g. retention times and reactor configurations), influent

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concentrations, and microbial community structures 13. Because bacteria are capable of degrading TOrCs 14,

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potential exists for harnessing their degradation abilities to improve TOrCs removal during wastewater treatment.

Introduction

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Bioaugmentation with bacteria capable of degrading TOrCs has theoretical potential to enhance removal of TOrC

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from WWTPs. Many bacteria with specialized degradation abilities have been identified in activated sludge that are

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capable of degrading TOrCs in a complex carbon environment 14–16, and studies of the transfer of labeled carbon

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have suggested that complete mineralization of TOrCs can be achieved by activated sludge communities 17–19. A

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proposed approach to bioaugmentation, Enhanced Biological TOrC Removal (EBTCR), involves augmenting

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specialized bacteria into the activated sludge of a WWTP 20. The approach used continuous low-dose

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bioaugmentation to compensate for poor survival of the specialized bacteria in the complex activated sludge habitat.

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Because EBTCR targets both dissolved and sorbed TOrCs in the activated sludge, the approach additionally

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prevents accumulation of sorbed TOrCs in biosolids. Thus, EBTCR represents a potential low-impact option for

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modifying existing facilities for improved TOrCs removal without requiring extensive capital and maintenance

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costs.

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Modeling has suggested that continuous or periodic bioaugmentation can compensate for the two primary challenges

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of EBTCR: the need for the augmented bacteria to grown on an alternative carbon source, and the predicted rapid

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loss of augmented bacterial activity 20. In-line enrichment approaches that have been used historically in wastewater

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treatment will not work for targeted TOrCs removal, because TOrC concentrations in WWTPs are too low to sustain

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selective bacterial growth. Instead, the augmented bacteria must be capable of growing using common carbon

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sources in a side growth reactor, while still maintaining the genetic ability to degrade the contaminant. This

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specialized ability has been documented by the authors for multiple bacteria, degrading multiple TOrCs 14, including



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for the bacterial culture – Sphingobium sp. BiD32 –used in this continuing study. However, this specialized ability

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does not compensate for the second challenge, which is the inability of the specialized culture to successfully

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compete in the activated sludge environment. Indeed, rapid loss of augmented bacteria has been reported 21,22.

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Predators favor grazing on dispersed bacteria, which may be a contributing factor to the rapid loss of bacteria

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following bioaugmentation into activated sludge 23. Modeling has suggested that EBTCR can overcome this

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challenge by employing continuous bioaugmentation 20.

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The primary goal of this study was to test modeled results supporting EBTCR in activated sludge fed municipal

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wastewater. The study was conducted in lab-scale sequencing batch reactors. The hypothesis was that low dose,

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continuous bioaugmentation with specialized bacteria will improve TOrCs removal and reduce the TOrCs

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transferred to solids. Bisphenol A (BPA) was used as a model TOrC compound and Sphingobium sp. BiD32 as a

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model organism. BPA is commonly detected in WWTP effluents 6,7 and surface waters 24–26 at concentrations found

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to have negative effects on aquatic life (low µg/L) 27, as thus represents a contaminant of emerging concern.

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Sphingobium sp. BiD32 is capable of: (1) degrading BPA to 99%) was obtained from Sigma Aldrich (St. Louis, MO, USA) and BPA-2,2’,6,6’-d4 (d4-BPA) (>98%) was

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obtained from C/D/N Isotopes, Inc. (Quebec, Canada). Organic solvents and water used for BPA sample extraction

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and analysis were high-pressure liquid chromatography (HPLC) grade. Sphingobium sp. BiD32 (GenBank accession

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number JX87937) and Sphingopyxis sp. TrD1 (GenBank accession number JN940802) used in this study were

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previously described 14.

86 87

2.2

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Two (2) lab scale sequencing batch reactors (SBR; a test reactor and a control reactor) were operated. Each had a

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working volume of 950 mL and was maintained in a temperature controlled chamber (20ºC). The SBRs were seeded

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with activated sludge from a municipal WWTP (West Point WWTP; Seattle, Washington). The reactors were fed

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effluent from the primary clarifiers at West Point WWTP that was amended with 100 mg/L NaHCO3 and 100 mg/L

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NaOAc (77 mg/L COD). NaHCO3 and NaOAc were added to the feed to adjust for the low alkalinity and soluble

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COD (sCOD) typical at this facility due to high levels of rainfall infiltration and inflow. The primary effluent was

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collected from the WWTP weekly, and stored at 4ºC until used. sCOD of the feed was measured when collected and

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on the final day of use to ensure that changes did not occur during storage that might impact reactor operation. The

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average background BPA concentration in the feed was 0.9 µg/L ± 0.7 (n=17). Additional BPA (0.8 µg/L) was

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added to the reactors with the feed to achieve an initial BPA concentration of 1.7 µg/L ± 0.7, which is within the

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mean range of influent concentrations for WWTPs 28,29.

Laboratory reactor set-up

99 100

The SBRs were operated with a 3-hour cycle consisting of 5 steps, and shown in Figure 1. The reactors were mixed

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during the feeding (Step 1), anoxic (Step 2), and reaction (Step 3) steps; and were quiescent for settling (Step 4) and

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effluent decantation (Step 5). During Step 1 (feeding), 237.5 mL of feed and BPA concentrate was added resulting

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in a nominal 12 hour hydraulic retention time (HRT). Aeration during Step 3 was provided with an aquarium pump

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and a ceramic stone sparger. The SBRs were manually wasted at the end of Step 3 once each day. Solids wasting

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was conducted when the SBRs were fully mixed to ensure a consistent solids concentrations in the waste activated

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sludge (WAS), which is more difficult to obtain from the settled zone in Step 5 when using lab-scale reactors. The



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volume of WAS that was removed was adjusted to maintain an 8 day and 3 day solids retention time (SRT) in Phase

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I and Phase II of the experiment, respectively. Bulk liquid (from WAS) and effluent (from Step 5) were monitored

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for total suspended solids/volatile suspended solids (TSS/VSS; Standard Method 2540E 30), pH (Beckman Coulter,

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Inc., Brea, CA, USA), sCOD (0.45 µm cellulose acetate filtered and measured using a low range Hach COD kit

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(Standard Method 5220D 30; Hach Company, Loveland, CO, USA)), and rotifers and protozoan concentrations

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(Standard Methods 10300C 30) at least once a week. BPA concentrations were monitored and measured as described

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in sections 2.3 through 2.5.

114 Bisphenol A Feed

Bioaugmentation (Cycle 1, each day) Step 1: Feeding

t=5 minutes

Step 2: anoxic mixing

t=25 minutes

Solids wasting Step 3: aerated reaction

t=90 minutes

Step 4: settling

t=45 minutes Effluent

Step 5: decanting

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t=15 minutes

116 117 118 119 120

Figure 1. Lab scale sequencing batch reactor cycle operation. The steps were continuous and automated; 8 cycles were run each day. Bioaugmentation was manual, and was conducted during Step 1 of cycle 1 each day to simulate a continuous bioaugmentation process.

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2.3

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Both reactors were bioaugmented each day at the start of cycle 1. The test reactor received Sphingobium sp. BiD32

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and the control reactor received Sphingopyxis sp. TrD1. Sphingopyxis sp. TrD1 was selected for the control reactor

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because it was phylogenetically related and had a growth rate similar to Sphingobium sp. BiD32, but does not

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degrade BPA 14. The cultures were grown in 2X R2B. R2B is a nutrient-rich broth with a sCOD (at 2X strength) of

Bioaugmentation


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approximately 5.5 g/L whose composition is based on R2 Agar 31 and is composed of (at 2X strength) 1 g/L yeast

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extract, 1 g/L proteose peptone, 1 g/L casamino acids, 1 g/L glucose, 1 g/L soluble starch, 0.6 g/L sodium pyruvate,

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0.6 g/L dipotassium phosphate, and 0.1 g/L magnesium sulfate. The concentration of the cultures was measured

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using optical density at 600 nm (OD600) prior to addition to the reactors and biomass equivalency of the measured

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OD was confirmed by measuring VSS of the cultures on a regular basis. 25 mL of the grown cultures were added to

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the reactors each day to achieve an approximate concentration of 15 mg/L of Sphingobium sp. BiD32 (15.1 mg/L ±

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2.7, n=76) and Sphingopyxis sp. TrD1 (17.5 mg/L ± 3.7, n=75). The sCOD associated with the spent media added

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with the cultures to the test and control reactors was 118 and 105 mg/L sCOD, respectively. Each day, the cultures

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were transferred into fresh 2X R2B for an initial biomass concentration of approximately 5 mg/L to maintain the

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side-reactor cultures in an active growth phase. These cultures were grown overnight and used for bioaugmentation

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the next day.

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2.4

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The low concentrations of BPA in the reactors required large volume samples for detection, so that it was not

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feasible to collect multiple time points from the lab-scale reactor systems. Instead, total BPA removal rates were

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measured by tracking single spike additions of 100 µg/L (at an 8-day SRT) and 10 µg/L (at both an 8-day and a 3-

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day SRT) (at Step 1), as a supplement to the background reactor BPA concentration of 1.7 μg/L ± 0.7 μg/L, while

143

keeping all other parameters (including the bioaugmentation dose) the same. BPA concentrations were monitored in

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both reactors during the aeration step (Step 3) for two cycles after the BPA spike.

BPA degradation kinetics testing

145 146

The rate of degradation was as assumed to fit a first-order model: = − Eq 1

147

where dcT/dt was the rate of change of the total BPA concentration (aqueous and sorbed, µg/L-h), kcT was the total

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degradation rate (hr-1, Eq 4), and cT was the total BPA concentration (aqueous and sorbed, µg/L). Eq 1 was

149

integrated and linearized as: = − + , Eq 2



150

where cT,0 was the initial BPA concentration and t was reaction time (hr). kcT was solved graphically by plotting lncT

151

versus t and the y-intercept was lncT,0 and the slope was kcT. The BPA degradation in the reactors was then

152

compared to the modeled degradation determined using the average kcT from replicate experiments:

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= − Eq 3 ,

153 154

The total degradation rate (kcT) was a combination of the degradation by Sphingobium sp. BiD32 and the

155

background activity of the activated sludge: = X + VSS Eq 4

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where kc’ was the specific degradation rate by Sphingobium sp. BiD32 (L/mg-hr), X was the augmented

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Sphingobium sp. BiD32 concentration (mg/L), kAS’ was the specific degradation rate by the background activated

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sludge (L/mg-hr), and VSS was the activated sludge concentration (mg/L). fL was the BPA in the liquid fraction,

159

which was assumed to be more bioavailable than the sorbed fraction. fL was calculated: =

1 Eq 5 1 + "# $%% + &

160

where Kp was the adsorption coefficient of BPA previously measured in activated sludge (199.5 L/kg20). Accounting

161

for fL allowed for comparison of kcT between systems with differing VSS. Data from the control reactors (i.e. X

162

=0) was used to calculate kAS’. The kc’ in the test reactor was then solved by applying the calculated kAS’ term into

163

Eq 4. The calculated kc’were compared to the kc’ of the pure cultures, which were measured by adding 15 mg/L

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Sphingobium sp. BiD32 into a buffered mineral salts media (solution previously described 14,32) containing

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approximately 10 µg/L or 100 µg/L BPA, monitoring BPA over time, and applying Eq 4 and Eq 5 with VSS set to

166

zero: =

Eq 6 &

167 168

2.5

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Samples used to quantify BPA were preserved by adding an equal volume of acetonitrile, vortexing, and

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centrifuging (10 minutes, 10,000 xg) to remove particles. This whole-sample extraction approach recovers both

High pressure liquid chromatography quantification for BPA


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dissolved and sorbed BPA in a single extract. BPA was quantified as previously described 14,20 using either HPLC

172

tandem mass spectrometer (LC-MS/MS; Shimadzu HPLC with a 4000 Q Trap Tandem Mass Spectrometer; Applied

173

Biosystems Inc.; Carlsbad, CA, USA) for concentrations in the ng/L to μg/L range, or HPLC with a UV detector

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(HPLC-UV; DionexUltiMate 3000; Sunnyvale, CA, USA) for concentrations in the μg/L to mg/L range. Samples

175

analyzed by LC-MS/MS were amended with 10 μg/L d4-BPA as an internal recovery standard. Using the LC-

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MS/MS, the lower level of detection was 0.15 µg/L and the level of quantification was 0.75 µg/L 14,30. Using the

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HPLC-UV, the lower level of detection was 30 µg/L and the level of quantification was 150 µg/L 14,30. An Intersil

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ODS-3 C18 column (150 x 2 mm inner diameter, 5 μm particle size) from GL Sciences (Torrance, CA, USA) was

179

used with both instruments.

180 181

2.6

182

Sphingobium sp. BiD32 16S rRNA gene concentrations were measured by qPCR. DNA was extracted using the MO

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BIO UltraClean Microbial DNA Isolation Kit (MO BIO Laboratories, Inc., Carlsbad, CA, USA). The

184

manufacturer’s instructions were followed with two modifications: the samples were heated (65ºC, 10 min) to

185

increase the yield (an optional step suggested by the manufacturer) and the samples were agitated for 20 seconds at

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speed 4.0 in a cell homogenizer (FastPrep®-24 Instrument; MP Biomedicals, Inc, Solon, OH, USA). Extracts were

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evaluated using a NanoDrop 1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) to

188

determine the quality and concentration of the DNA. A 260:280 ratio between 1.7 and 1.9 was considered to be

189

acceptable, and the concentration was determined at 260 nm.

qPCR

190 191

Primers for detection of Sphingobium sp. BiD32 16S rRNA gene concentrations were designed using NCBI Primer-

192

BLAST (http://www.ncbi.nlm.nih.gov/tools/primer-blast/) and purchased from Invitrogen (Invitrogen, Carlsbad,

193

CA, USA). The primer sequences are shown in Table 1. The primers matched 100% to Sphingobium sp. BiD32 and

194

to five closely related sequences in the NCBI BLAST database, including uncultured soil bacterium clones,

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Sphingomonas sp. B1-105, and Sphingomonas sp. A1-13. The forward primer had greater than 6 mismatches,

196

insertions, or deletions compared to Sphingopyxis sp. TrD1 and the reverse primer had one mismatch.

197



198

Standards for qPCR were prepared using the PCR product of 16S rRNA genes of Sphingobium sp. BiD32 using

199

Bacterial Domain primers (Table 1). These PCR products were cloned using a TOPO TA Cloning Kit (Invitrogen

200

Molecular Probes, Grand Island, NY, USA). Plasmids were isolated by QIAprep Spin Miniprep Kit (Qiagen,

201

Valencia, CA, USA), quantified using a NanoDrop 1000 spectrophotometer (NanoDrop Technologies, Wilmington,

202

DE, USA), and linearized by the restriction enzyme EcoRI (R6011, Promega Corporation, Madison, WI, USA).

203 204

qPCR analysis was performed using an Eppendorf MasterCycler Realplex (Eppendorf North America, Inc.,

205

Westbury, NY, USA) and GoTaq qPCR Master Mix (Promega Corporation, Madison, WI, USA). The PCR program

206

to determine Sphingobium sp. BiD32 16S rRNA gene concentrations was as follows: hot-start activation (95ºC for

207

10 minutes), 50 cycles of denaturation (95ºC for 15 seconds), annealing (65ºC for 1 minute), and extension (60ºC for

208

1 minute), and determination of the melt curve (95ºC for 15 seconds, 60ºC for 15 seconds, an increase to 95ºC over

209

20 minutes, and 95ºC for 15 seconds). The melting curve was recorded for each sample, and melt occurred at 86.5ºC

210

for Sphingobium sp. BiD32. Each DNA extract was processed at a tenfold and hundredfold dilution to monitor for

211

PCR inhibition effects.

212 213

A standard curve was generated using tenfold dilutions of the linearized plasmids. The resulting standard curve for

214

Sphingobium sp. BiD32 had an average efficiency of 0.70 (R2=0.958) with a method detection limit of 8.18x103 16S

215

rRNA gene copies per PCR reaction (cycle threshold ~31.5, n=15). Negative controls did not amplify at above the

216

method detection limit. These controls included the closely related organisms Sphingobium sp. BiD10 14 (7.5x107

217

16S rRNA gene copies added per PCR reaction, cycle threshold ~32.3, n=17), Sphingopyxis sp. TrD1 (6.7x107 16S

218

rRNA gene copies added per PCR reaction, cycle threshold ~31.7, n=14), and a water blank (rarely amplified, cycle

219

threshold ~38.1, n=8).

220 221

2.7

222

The survival of the augmented bacteria was calculated as the rate of change in augmented bacterial concentrations :

Growth and loss of augmented bacteria

& = ) & Eq 7

223

where dX/dt was the rate of change of the augmented bacteria (mg/L-hr), kx was the survival rate (hr-1), and X was

224

the augmented bacterial concentration (mg/L).


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225 226

To determine the maximum possible growth kinetics under reactor conditions, approximately 15 mg/L Sphingobium

227

sp. BiD32 was inoculated into a 3:1 mixture of reactor waste sludge:feed and Sphingobium sp. BiD32 concentrations

228

were monitored using qPCR while mixing and aerating over 17 hours. The waste sludge (collected at the end of an

229

aeration period before settling) and feed was autoclaved, sonicated (35 minutes) to release cell lysis debris, filtered

230

(0.2 µm SCFA), and autoclaved to remove competing bacteria. Eq 6 was integrated and linearized as: & = −) + & Eq 8

231

where kx was assumed to represent only the bacterial growth under these conditions with no competition. The

232

equation was solved graphically and the y-intercept was lnX0 and the slope was kx.

233 234

To determine the survival kinetics, a batch experiment was completed where Sphingobium sp. BiD32 was inoculated

235

into reactor waste sludge that was collected from the control reactor (to minimize bias from background readings in

236

the bioaugmented reactor). Sphingobium sp. BiD32 concentrations were monitored using qPCR. Eq 8 was solved

237

graphically and the y-intercept was lnX0 and the slope was kX. In this case the kx represented the overall fate of the

238

augmented bacteria, including growth and death.

239 240

2.8

241

Bioaugmentation for BPA removal was previously modeled in a four reactor operated in series (4-stage) activated

242

sludge process 20. The model was modified by adding the kinetic loss of Sphingobium sp. BiD32, measured as kx in

243

Section 2.5. As previously described in the model, when accounting for the change in Sphingobium sp. BiD32 in the

244

reactors and assuming steady state, the BPA concentrations were calculated by: , =

Modeling full-scale activated sludge process

∗ -. Eq 9 0 1+ , 4

245

where c1 was the BPA concentration in reactor 1 (ng/L), cin* was the BPA concentration entering the first reactor

246

(ng/L), τ was the hydraulic retention time (hr), and k1 was the total BPA degradation rate in the first reactor

247

calculated by: , = &, + VSS Eq 10

248

where X1 was the augmented biomass in the first reactor (mg/L).



249 250

The BPA concentration and total BPA degradation rate were calculated for each reactor, using the Sphingobium sp.

251

BiD32 concentrations each reactor, which were calculated by: &, =

252

∗ &-. Eq 11 0 1+ ) 4

where Xin* was the augmented biomass entering the first reactor (mg/L).

253 254

Other calculations were completed as previously described 20 with the exception of the calculation for cin*. The BPA

255

entering the first reactor was calculated by:

∗ -.

3-. 34 5 3 − 36 − 3 + 34 36 + 34 3 + 34 = Eq 12 34 0 0 0 0 1− / 1 + , / 1 + 8 / 1 + 9 / 1 + : 36 + 34 4 4 4 4

256

where Q was the influent flow rate (m3/d), cin was the influent BPA concentration (ng/L), Qr was the recycle flow

257

rate (m3/d), ce was the effluent BPA concentration (ng/L), and Qw was the waste stream flow rate (m3/d)

258 259

2.9

260

Cultures used for bioaugmentation in this study were continuously grown without exposure to BPA. To determine if

261

BPA degradation by Sphingobium sp. BiD32 was inducible (i.e. the genes for production of the required enzymes

262

are expressed when BPA is present), degradation of BPA was compared between Sphingobium sp. BiD32 cultures

263

exposed to BPA (“pre-treatment”) and a parallel culture that had not been exposed to BPA for greater than 700

264

generations (“control”). The parallel cultures were grown in R2B with and without adding 2 mg/L BPA,

265

respectively. To ensure that BPA was still being actively degraded when the culture was transferred, BPA was re-

266

spiked to the pre-treated culture during active growth. When the cultures were grown (OD600 of approximately 0.36,

267

9.5 hours after inoculation, ~170 mg/L VSS), the cultures were transferred into fresh R2B containing either 1, 2, or

268

10 mg/L BPA. To measure BPA degradation in the absence of continued growth, the same cultures were transferred

269

into buffered mineral salts media (solution previously described14,32) containing 2 mg/L BPA. BPA was monitored,

270

and growth was monitored by change in optical density (OD600). The specific degradation rate by Sphingobium sp.

271

BiD32 (kc’, hr-1OD600-1) was determined by:

Induction of BPA degradation


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Page 13 of 34


= − Eq 13 &

272

where X is biomass concentration (OD600). The equation was solved graphically and the slope was kc’.

273 274

2.10

275

Average deviation from the mean was used to estimate error when the number of replicates (n) was too low to meet

276

the assumption of a normal distribution as required when calculating standard deviation 33: ;< =

Statistical analyses

Σ| − ̅ | Eq 14

277

Unpaired student t-tests were used to compare replicate BPA degradation rates obtained for the test and control

278

reactors.

279 280

3.

Results

281

3.1

Laboratory reactor operation

282

Reactor performance is shown in Table 2. Reactor pH was between 7.2 and 7.9, and no differences were observed

283

between the reactors or between operational SRT. Reactor VSS and TSS were higher during higher SRT, as is

284

expected. Effluent VSS varied over time within each reactor, but was consistent between the test and control

285

reactors. Bioaugmentation dosing to the control reactor was slightly higher than to the test reactor; this difference

286

was statistically significant when operated with an 8-day SRT (p=9.5x10-6, t-test), but was not statistically

287

significant when operated with a 3-day SRT (p=0.19, t-test). Because it was the control reactor that received the

288

higher bioaugmentation dose, this difference was not expected to impact the study outcomes. During Phase I (8-day

289

SRT), the bioaugmented Sphingobium sp. BiD32 represented approximately 1.2% of the total VSS (Table 2). During

290

Phase II (3-day SRT), the bioaugmented Sphingobium sp. BiD32 represented approximately 1.9% of the total VSS

291

(Table 2). sCOD at the start of the aeration period varied, reflecting the natural background variation in the feed.

292

Despite the initial sCOD variation, the test and control reactors consistently removed sCOD to a final concentration

293

of 22.4 and 24.3 mg/L, respectively, during the aeration period (Table 2).

294



295

Experiments were initiated after operation for a minimum of 3 SRTs after either start-up or a change in system

296

operation. The reactors operated stably during the experiments (Figures S1 and S2, shaded regions show when

297

experiments were conducted).

298 299

3.2

300

Bioaugmentation consistently improved BPA removal. The extent of BPA removal and the total removal rate were

301

greater during cycle 1 in the test reactor than in the control under all conditions tested (Table 3, Figures 2 and 3;

302

p

Enhanced Biological Trace Organic Contaminant Removal: A Lab

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