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and from 200 to 3,850 colony forming units/mL, respectively. Viable cell concentrations decreased. 5 significantly in the first ozone contact chamber,...
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Microbial Dynamics in Multi-Chamber Ozone Contactors at a Full-Scale Drinking Water Treatment Plant Nadine Kotlarz, Nicole Rockey, Terese M Olson, SarahJane Haig, Larry Sanford, John J. LiPuma, and Lutgarde Raskin Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b04212 • Publication Date (Web): 04 Jan 2018 Downloaded from http://pubs.acs.org on January 4, 2018

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Microbial Dynamics in Multi-Chamber Ozone Contactors at a Full-Scale Drinking Water Treatment Plant

Nadine Kotlarz†, Nicole Rockey†, Terese M. Olson†, Sarah-Jane Haig†, Larry Sanfordǂ, John J. LiPuma§, Lutgarde Raskin*,†



Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan

48109, United States ǂ

Drinking Water Treatment Utility, Ann Arbor, Michigan 48103, United States

§

Department of Pediatrics and Communicable Diseases, University of Michigan Medical School, Ann

Arbor, Michigan 48109, United States

*Corresponding author: Lutgarde Raskin Department of Civil and Environmental Engineering University of Michigan 1351 Beal Ave., 107 EWRE Bldg. Ann Arbor, MI 48109-2125 Phone: 734-647-6920 Email: [email protected]

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ABSTRACT

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Concentrations of viable microbial cells were monitored using culture-based and culture-independent

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methods across multi-chamber ozone contactors in a full-scale drinking water treatment plant. Membrane-

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intact and culturable cell concentrations in ozone contactor effluents ranged from 1,200 to 3,750 cells/mL

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and from 200 to 3,850 colony forming units/mL, respectively. Viable cell concentrations decreased

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significantly in the first ozone contact chamber, but rose, even as ozone exposure increased, in subsequent

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chambers. Our results implicate microbial detachment from biofilms on contactor surfaces, and from

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biomass present within lime softening sediments in a hydraulic dead zone, as a possible reason for

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increasing cell concentrations in water samples from sequential ozone chambers. Biofilm community

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structures on baffle walls upstream and downstream from the dead zone were significantly different from

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each other (p = 0.017). The biofilms downstream of the dead zone contained a significantly (p = 0.036)

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higher relative abundance of bacteria of the genera Mycobacterium and Legionella than the upstream

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biofilms. These results have important implications as the effluent from ozone contactors is often treated

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further in biologically active filters and bacteria in those effluents continuously seed filter microbial

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communities.

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INTRODUCTION

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Ozone, a strong oxidant, is widely used for water treatment as it inactivates microbial pathogens,1

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decomposes natural organic matter (NOM), removes taste-, odor- and color-causing compounds,2,3

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oxidizes inorganic contaminants,4,5 and improves clarification and filtration by inducing formation of

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precipitates or through reducing the stabilizing effects of NOM6. Wastewater treatment, drinking water

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treatment, and water reuse plants have increasingly been including ozonation in their treatment trains to

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achieve contaminant removal.7-12 Particularly, ozone’s use has increased in some European countries for

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tertiary treatment of micropollutants in wastewater,13 in North America for drinking water treatment

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where ozone application followed by biofiltration has increased 10-fold from 1993 to 2013,14 and in

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several water scarce regions of the world where ozone combined with biofiltration has been explored as

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an alternative to reverse osmosis for direct or indirect potable reuse (e.g., in Virginia,15 Australia,7

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California16).

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Ozone inactivation kinetics can be difficult to resolve in lab-scale experiments because ozone’s

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fast reactivity results in non-detectable microbial levels after short ozonation times.17 Nevertheless, viable

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microbial cells have been reported to remain present after ozonation of raw water18 or partially treated

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water19-21 in full-scale and pilot-scale water treatment systems. A few reasons may explain the presence of

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viable microorganisms in ozone contactor effluents. First, it is not surprising that different types of

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microbes exhibit differential ozone resistance since the effectiveness of a disinfectant varies based on

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variations in cellular and physiological features such as cell envelope composition and growth rate,22

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growth state such as planktonic or biofilm growth,23,24 and nutrient availability25. In particular, some

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opportunistic bacterial pathogens exhibit higher ozone resistance than other bacteria.22,26 Second,

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disinfection in full-scale systems is often less effective than predicted by lab-scale inactivation

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experiments because of matrix effects, such as the protection of microorganisms from disinfectant

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exposure when present in flocs21 and lower than intended disinfection concentrations due to oxidant

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demand exerted by NOM27 or inorganic compounds in untreated or partially treated water.

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Reduced disinfection efficiency is relevant for drinking water treatment plants (DWTPs) that

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employ vertically baffled, multi-chamber ozone contactors. Nonideal flow conditions such as short-

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circuiting and internal recirculation in such contactors can lead to insufficient mixing and reduced ozone

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exposure.28 A combination of nonideal hydrodynamic conditions and the production of readily

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biodegradable substrates through oxidation of NOM may increase the potential for biofilm formation on

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contactor surfaces. Biofilm formation would present problems for disinfection since biofilm extracellular

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polymeric substances (EPS) may shield microorganisms from ozone exposure and cells grown in biofilms

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exhibit reduced sensitivity to disinfection.23,24 Surveys of microbial communities in full-scale DWTPs

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19,21,29,30

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in contactor influents and effluents only. Research is needed to elucidate factors that explain the presence

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of viable microorganisms in ozone contactor effluents.

have treated ozone contactors as “black boxes,” focusing on the planktonic microbial community

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In this study, viable microbial cell concentrations were monitored at five locations across multi-

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chamber ozone contactors at a full-scale DWTP to gain insight into processes that shape the microbial

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quality (i.e., microbial concentrations and community composition) of ozonated water. Furthermore, we

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evaluated the bacterial community structures in sludge and in biofilms on baffle walls to generate

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hypotheses for how nonideal flow conditions influence the microbial community in ozone contactor

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effluent.

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MATERIALS AND METHODS

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Drinking Water Treatment Plant. The maximum capacity of the DWTP in Ann Arbor, MI is 50 million

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gallons per day (MGD) (1.9 × 105 m3/day) and the average daily water production is 15 MGD (5.7 × 104

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m3/day). Pinto et al. previously provided a description of the Ann Arbor DWTP.30 Briefly, raw water is

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obtained from the Huron River (80-85%) and from groundwater wells (15-20%) and is treated using lime

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softening, coagulation, flocculation, sedimentation, ozonation, filtration, and chloramination. Before

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ozonation, CO2 contactors reduce the pH of the water to approximately 7.8 (mean pH was 7.8 ± 0.4 for

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December 2015 through December 2016). Ozonated water is applied to biologically active, dual media

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filters containing granular activated carbon and sand.

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Ozone Contactors. The Ann Arbor DWTP has four parallel ozone contactors each containing seven

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chambers separated by vertical baffle walls and inlet and outlet basins (Figure 1). Two of the four

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contactors are typically operated to meet water demand. Onsite ozone generators are fed oxygen and

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produce a gas stream with approximately 7-10% ozone. Ozone is dispersed by ceramic fine bubble

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diffusers into chambers 2 and 3 of each contactor. Specifically, 70% of the ozone generated is dispersed

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into chamber 2 and 30% is dispersed into chamber 3. Water flows by gravity counter-currently to the

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ozone in chamber 2 and co-currently in chamber 3. A sufficient ozone dose is added to maintain 0.1 mg/L

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ozone residual in the effluent of chamber 2 to achieve 1-log virus inactivation credit under the United

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States Environmental Protection Agency (U.S. EPA) Surface Water Treatment Rule. The effluent of the

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seventh chamber in each contactor flows over a weir to dissipate dissolved gases, and water from the two

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contactors in operation is mixed in an outlet basin.

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In each contactor, five sample lines extend from the contactor chambers to an ozone analyzer

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(Figure 1). Samples collected from sample line 1 represent clarified water after pH adjustment but before

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ozone exposure (CT = 0). Samples from sample lines 2, 3, and 4 represent water after contact with ozone

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gas in chambers 2 and 3, and water after exposure to any residual ozone in chamber 4 and the outlet basin,

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respectively. The residence time for a complete contactor is approximately 10 min (average was 9.8 ± 1.3

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min across sampling events for heterotrophic plate count and flow cytometry analyses). The length of Page 5 of 27 ACS Paragon Plus Environment

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chamber 3 (i.e., the distance between consecutive baffle walls) is twice the length of the other chambers.

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While uniform chamber sizes are most common in ozone contactors, some contactor designs provide

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larger chambers for ozone dissolution. The co-current flow in chamber 3 is hydraulically less optimal

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relative to the counter-current flow in chamber 2.31 Longer chamber length provides additional contact

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time in chamber 3.

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Sample Collection. Water samples were collected from three contactors over the course of a year (Table

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S1). Before sample collection, each sample line was flushed until meter readings of ozone concentration

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were stable (approximately 3 min). 500 mL water samples were collected into sterile Nalgene

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polypropylene bottles containing sodium thiosulfate (5 × stoichiometric requirement (SR)17,32 to quench

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0.5 mg/L ozone) from each sample line. Separate 500 mL samples were collected into sterile, carbon-free

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amber bottles containing sodium thiosulfate for assimilable organic carbon (AOC) analyses by Eurofins

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Eaton Analytical (described below).

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Ozone Exposure (CT) Calculation Method. Ozone concentration and temperature were monitored in

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each sample line by online Ozone 499A OZ Sensors. The ozone exposure or CT (concentration × time)

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for each chamber was calculated as the average ozone concentration (C) in the chamber multiplied by the

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T10. The U.S EPA Surface Water Treatment Rule designates T10 as the time it takes for 10 percent of a

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tracer to exit a disinfection contactor. For reaction chambers 4-7 (no ozone addition), a first order ozone

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decay model was used to determine the average ozone concentration. Residual ozone concentrations at

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sample line 5 (in the outlet basin) were typically below the quantification limit (0.01 mg/L). The CT

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calculation method is described in detail in the Supporting Information (Table S2).

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Heterotrophic Plate Counts (HPC). HPC were conducted using the pour plate method according to

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Standard Methods 9215 B.33 Samples were diluted (1:100, 1:10; 1:5, or 1:2 depending on the sample)

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with sterile phosphate buffered saline (PBS, pH = 7.2 ± 0.2) solution and 1 mL diluted sample was mixed

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with liquefied R2A agar in triplicate and plated (n = 6 plates per sample). Colony forming units (CFUs)

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were counted using a Quebec Darkfield Colony Counter (Reichert, Inc., Depew, NY) after seven days of

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of the two days when HPC and flow cytometry methods (described below) were both used. The values

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reported in the manuscript are the mean ± range for sample lines 1 or 5 across the two days.

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Taxonomic Classification of Isolates. For one of the sampling days, 190 isolates were cut from R2A

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plates for taxonomic analysis of culturable populations. More information is provided in the Supporting

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Information (Figure S5).

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Flow Cytometry Analysis. Sample aliquots (1 mL) were stained with propidium iodide (PI,

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ThermoFisher Scientific, Waltham, MA) and SYBR Green I (SGI, ThermoFisher Scientific) at final

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concentrations of 3 µM PI and 1X SGI. After staining, samples were incubated at 37°C for 15 min to

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improve cell staining.34,35 CountBrightTM absolute counting beads (Life Technologies, Carlsbad, CA) were

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added to each sample per the manufacturer’s instructions to determine flow cytometer process volume.

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All samples were stained and analyzed in duplicate and stored on ice until analysis with an LSR Fortessa

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cell analyzer (BD Biosciences, San Jose, CA). Events were triggered off fluorescence in the SGI or PI

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channels above a threshold of 200. For each sample, forward and side-scatter as well as fluorescence in

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the 610/10, 530/30, and 780/60 nm wavelengths were measured for detection of PI positive, SGI positive,

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and bead events, respectively. At least 10,000 events were collected for each sample, and no

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compensation was applied to sample measurement. Data analysis was carried out using FlowJo software

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(FlowJo, Ashland, OR). Electronic gating of events in a density plot of SGI and PI fluorescence channels

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was used to determine the number of events positive for SGI and negative for PI (membrane-intact cells).

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Organic Carbon Analysis. Each quenched sample was filtered through sterile 0.45 µm nylon syringe

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filters (ThermoFisher Scientific) previously washed with 40 mL MilliQ water and 10 mL of sample, and

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the filtrate was frozen for dissolved organic carbon (DOC) analysis with a Total Organic Carbon

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Analyzer TOC-V CSH (Shimadzu, Columbia, MD).

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Samples were submitted to Eurofins Eaton Analytical (South Bend, IN) for AOC analysis

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according to Standard Methods 9217B.33 At Eurofins Eaton Analytical, water samples were aliquoted into

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vials (40 mL each) and pasteurized (70-80 °C for 30 min). Spirillum NOX and Pseudomonas fluorescens

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P-17 strains, which have different substrate specificities, were inoculated into each vial at an initial Page 7 of 27 ACS Paragon Plus Environment

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concentration of 500 CFU/mL and then incubated at 25 °C. Growth in each vial was determined on R2A

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agar plates in duplicate on days 5, 6 and 7 (n = 6 plates per sample). Average CFU was converted into

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AOC concentration based on the growth yields of the NOX and P-17 strains for acetate (4.1 × 106 and 1.2

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× 107 CFU/µg acetate-C for P17 and NOX, respectively). AOC determined by P-17 growth and AOC

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determined by NOX growth were added and expressed as the total sample AOC.

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Contactor Shutdown Experiment. Water flow and ozone supply for one of the contactors were turned

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off. Samples were collected from chambers 2 and 3 before shutdown, and 2 h and 9.45 h after shutdown

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for HPC and flow cytometry analyses as described above. The ozone contactor was kept dark and

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relatively full during shutdown. Immediately after shutdown, water from chamber 2 was collected into a

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sterile glass bottle protected from light and kept at room temperature to serve as an experimental control,

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representing the bulk water in the contactor but without exposure to contactor surfaces. After shutdown,

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the contactor could be considered a batch system, resulting in a low rate of microbial cell diffusion into

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the bulk water, motivating the selected sampling time points on the order of hours (2 h and 9.45 h).

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Residual ozone concentrations were monitored in chamber 2 by online Ozone 499A OZ Sensors.

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Ozone Contactor Biofilm and Sludge Samples. After the shutdown experiment, the contactor was

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drained and, for safety purposes, ozone was allowed to degas from the concrete walls for two weeks

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before we entered the contactor. Biofilm was swabbed from specific areas (18.8 cm2 each) on baffle

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walls, at about 1.5 m from the floor, from chambers 2-5. Duplicate biofilm samples, collected for 3 out of

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5 wall locations sampled, were swabbed next to each other. Biofilm from one diffuser in chamber 3 (n =

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1) was collected. Each swab was placed in sterile PBS. Swabs were vortexed for 2 min and sonicated for

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2 min in an ultrasonicator (ThermoFisher Scientific) to release biomass. The biomass was filtered onto

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0.2 µm polycarbonate filters (Millipore) and filters were stored at -80 °C. Sludge from a hydraulic dead

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zone in chamber 3 (n = 1), the chamber where sludge accumulation was the greatest, was collected into a

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sterile Falcon tube (Corning, Corning, NY) and stored on ice for up to 1 h before storage at -80 °C. A

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hydraulic dead zone is a zone of insufficient mixing resulting from internal recirculation inside the

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chamber.36

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Total DNA was extracted from biofilm and sludge samples using a modified recipe of the

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Universal Extraction Lysis Buffer and a phenol-chloroform-isoamyl extraction protocol37,38 to improve

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recovery of difficult-to-lyse bacteria. The controls were processed in parallel with the samples. PCR,

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sample multiplexing, and Illumina MiSeq sequencing of partial 16S rRNA genes were performed by the

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Microbial Systems Laboratory at the University of Michigan Medical School (Ann Arbor, Michigan).

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Barcoded dual-index primers specific to the V4 region of the 16S rRNA gene39,40 were used to amplify

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the DNA. PCR reactions included 5 µL of 4 µM forward and reverse primers, 0.15 µL of AccuPrime Taq

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DNA High Fidelity Polymerase (Life Technologies), 2 µL of 10x AccuPrime PCR Buffer II

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(ThermoFisher Scientific), 1 µL of DNA template, BSA (0.5 mg/mL final concentration), and nuclease-

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free water. PCR conditions consisted of 2 min at 95 °C followed by 30 cycles of 95 °C for 20 s, 55 °C for

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15 s, 72 °C for 5 min, followed by 72 °C for 10 min. Sequencing was done on the Illumina MiSeq

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platform using a MiSeq Reagent Kit V2 500 cycles according to the manufacturer’s instructions with

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some modifications.39

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16S rRNA gene sequences from all samples were curated using mothur (version 1.39.0).41

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Sequences that were within two nucleotides of each other were merged using the pre.cluster command.

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After preclustering, 439 sequences in the control samples (putative contaminants) were removed from the

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6,429 unique sequences in the dataset using the remove.seqs command (6.8% sequences removed).

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Curated sequences (131,264 total sequences) were clustered into OTUs using a 97% similarity cutoff with

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the opticlust algorithm.42 Subsampling was performed based on the sample with the lowest number of

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sequences, resulting in 4,387 paired-end reads per sample.39 Sequences were classified using a naïve

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Bayesian classifier43 trained against a 16S rRNA gene training set provided by the RDP.44 An RDP

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consensus taxonomy was generated for each OTU.

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Thermal Gravimetric Analysis (TGA) of Sludge. TGA analysis was performed to estimate the

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composition of contactor sludge. A sample of the sludge was weighed, dried in an oven at 103 °C for 1 h

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and weighed again to determine water loss. The sludge was subject to TGA in an oxygen atmosphere. The

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temperature was ramped up from ambient to 800 °C at a rate of 10 °C min-1 in a TA Q500 (TA

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Instruments, New Castle, DE). Continuous online records of weight loss and temperature were used to

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plot a derivative TGA curve.

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Statistical Analyses. Results are reported as the mean ± standard deviation unless otherwise noted.

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Statistical significance was based upon the probability of p < 0.05. A Wilcoxon test was used for

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comparison of cell concentrations. An Analysis of Molecular Variance (AMOVA) was used to test for

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significant separation of samples on the NMDS plot. A Pearson correlation coefficient was used for the

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correlation analysis with individual OTUs and shifts in samples along axes in the NMDS plot.

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RESULTS

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Because the Ann Arbor DWTP did not operate the same ozone contactors throughout the sampling

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campaign, water samples were collected from three contactors on different days (Table S1). Plant

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operators change ozone feed gas concentrations and influent flow rates through the contactors daily and

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this contributed to the variability in ozone CT profiles across the sampling days (Figure 1). Therefore,

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viable cell concentrations are plotted against sample line numbers (1-5) instead of ozone CT. The average

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cumulative ozone CT was 0.96 ± 0.32 mg-min/L across eight sampling days (Figure 1).

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Cell Concentrations Across Ozone Contactors. Culturing and culture-independent flow cytometry were

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used to monitor microbial communities during ozone disinfection in multi-chamber contactors. Figure 2

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shows viable cell concentrations measured by culturing and culture-independent flow cytometry. HPC

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based inactivation monitoring indicated 1.88 ± 0.47 log reduction from 1,110 ± 420 CFU/mL before

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ozonation to 17 ± 19 CFU/mL in chamber 2, the first chamber where ozone contact occurs (ozone

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exposure of 0.26 ± 0.06 mg-min/L; Figure 1) (Figure 2a). As expected, greater numbers of intact cells

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were measured using flow cytometry than with HPC. However, a similar log reduction of 1.86 ± 0.19 was

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observed from 106,000 ± 31,000 intact cells/mL before ozonation to 1,610 ± 730 intact cells/mL in

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chamber 2 (Figure 2b). The levels of culturable and membrane-intact cells increased in the third chamber,

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even as ozone exposure increased by 0.63 ± 0.17 mg-min/L (Figure 1). Specifically, in chamber 3, there

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was a significant (p < 0.0001) increase in the level of culturable cells to 750 ± 350 CFU/mL, and the level

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of intact cells increased to 2,700 ± 1,100 cells/mL (p = 0.05). Intact cell concentrations increased further

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in chamber 4 (p = 0.05), but culturable cell concentrations did not increase significantly. In spite of

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increasing intact cell concentrations in chambers 3 and 4 on most days (Figure S1b), ozonation

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significantly reduced intact cell concentrations overall (1.62 log reduction, p = 0.0001), with

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concentrations ranging from 1,200 to 3,750 intact cells/mL in water from the outlet basin (sample line 5).

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The levels of culturable bacteria in the outlet basin ranged over an order of magnitude, from 200 to 3,850

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CFU/mL. In comparison with cell concentrations before ozonation (sample line 1), there was a slight

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reduction in culturable cells after ozonation (sample line 5) on three sampling days, but a significant (p < Page 11 of 27 ACS Paragon Plus Environment

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0.0001) increase in CFU concentrations after ozonation in one of the contactors sampled on three

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different days during one week (Figure S1a). The culturability (i.e., the ratio of HPC to membrane-intact

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cells) of water samples before ozonation was 0.9 ± 0.4% (mean ± range) but increased 12-fold to 10.4 ±

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7.8% after ozonation (Figure S2).

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Microbial Growth Substrates. Dissolved organic carbon (DOC) levels did not change significantly

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during ozonation (p = 0.08) (Figure S3). The average concentration of DOC across the five sampling lines

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was 4,000 ± 300 µg/L.. However, AOC levels increased significantly (p < 0.0001) after ozone exposure

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began in chamber 2. The average AOC level was 36 ± 0.3 µg/L (mean ± range across two sampling

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events) before ozonation and increased to 115 ± 12 µg/L (mean ± range) after ozonation. The increase in

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AOC was caused by an increase in growth substrates specific for the Spirillum NOX strain, which

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primarily uses carboxylic acids as growth substrates45.

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Cell Concentrations after Contactor Shutdown. A “no flow” (batch) experiment was conducted in a

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contactor to test whether walls and accumulated solids were the source of increasing cell concentrations

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in the bulk water. Cell concentrations were monitored in stagnant water in chambers 2 and 3 after influent

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water and ozone gas supply were shut off. Chambers 2 and 3 were chosen since chamber 2 is the contact

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chamber where the greatest reduction in viable cell levels occurred and chamber 3 is where cell

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concentrations increased (Figure 2). Immediately after contactor shutdown, water was collected from

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chamber 2 and incubated at room temperature in the dark to serve as a control with the same planktonic

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cell concentration and growth substrate level as the stagnant water in chamber 2 at the start of the

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experiment. An increase in cell concentrations in the control would be explained by planktonic cell

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growth or recovery, not detachment of cells from biofilm or sediments.

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Residual ozone concentrations dropped to below quantification (0.01 mg/L) after 12 min in

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chamber 2 (Figure S4). The initial CFU and intact cell concentrations in chamber 2 were 10 ± 4 CFU/mL

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and 1,660 ± 110 intact cells/mL, respectively. The CFU concentration in chamber 2 increased

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substantially to 800 ± 210 CFU/mL 2 h after shutdown, and then increased further to 4,800 ± 1,300

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similarly (Figure 3b). The initial CFU and intact cell concentrations in chamber 3 were 600 ± 50 CFU/mL

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and 1,400 ± 20 intact cells/mL, respectively. The CFU concentration in chamber 3 decreased to 160 ± 20

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CFU/mL 2 h after shutdown, but then increased to 6,010 ± 1,800 CFU/mL 9.5 h after shutdown (Figure

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3a). The concentration of intact cells in chamber 3 increased consistently at 2 and 9.5 h after shutdown

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(Figure 3b). In contrast, the concentration of culturable cells in the control decreased and was below

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detection after 2 h and remained below detection during the 9.5 h experiment. The levels of membrane-

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intact cells in the control decreased slightly to 820 ± 30 intact cells/mL after 2 h, and then increased to

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3,890 ± 4,400 intact cells/mL after 9.5 h (Figure 3b).

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Taxonomic Classification of Isolates. The colonies on R2A plates generally became smaller and more

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uniform (mostly white colonies) in water sampled from sequential chambers (Figure S5). Table 1 shows

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taxonomic classification at the genus level of 190 isolates based on 16S rRNA gene sequencing.

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Pseudomonas, Blastomonas and Limnobacter spp. predominated among the strains cultured from water

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before ozone exposure (CT = 0 mg-min/L). The relative abundance of Pseudomonas strains decreased

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and Blastomonas strains were not detected after ozone exposure began (CT = 0.30 mg-min/L), whereas

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the relative abundance of Limnobacter strains increased substantially to greater than 80% after ozone

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exposure began. Other bacteria cultured from water in the outlet basin (sample line 5) included

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Hydrogenophaga strains and unclassified Comamonadaceae spp. Isolates obtained from water before

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ozonation belonged to Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria, but strains

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isolated after ozonation began were mostly Betaproteobacteria and, by the end of ozonation, all cultured

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populations were Betaproteobacteria.

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Biofilm and Sludge Samples. Partial 16S rRNA gene sequencing of biofilms on walls in chambers 2

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through 5 indicated that some taxa cultured from water samples collected during ozonation were also

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detected in the biofilm samples. For example, an OTU classified as Limnobacter (OTU0004) was present

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in biofilm sampled from the wall in chamber 2 (1.4% relative abundance), and its relative abundance was

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substantially higher in biofilm on the left wall of chamber 3 (29%) (Table S5). This OTU was also present

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in biofilm on a diffuser in chamber 3 (2.1% relative abundance). However, Limnobacter spp. were not

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detected in biofilm samples on the right wall in Chamber 3, or in biofilm samples from chambers 4 and 5.

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Sludge had accumulated near the right wall in chamber 3 and TGA of a sludge sample (Figure

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S6) showed significant weight loss occurred between 542 and 830 °C, corresponding to the decarbonation

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of calcium carbonate46. This finding suggests sludge accumulation was due to incomplete removal of

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calcium carbonate during lime softening. Smaller weight losses during TGA occurring at 502 °C and

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between 183 and 407 °C may have corresponded to dihydroxylation of calcium hydroxide and

279

volatilization of organic content, respectively.47,48

280

DNA yields from baffle wall biofilm samples after the dead zone were significantly higher than

281

those before the dead zone (p = 0.036) (Table S3). Furthermore, non-metric multidimensional scaling of

282

ϴyc distance ordinations indicated that the biofilm community structures of samples collected before and

283

after the dead zone clustered separately (Figure 4), and the separation was statistically significant (p =

284

0.017). An OTU (OTU0001) classified as Gp4 in Acidobacteria became significantly more abundant in

285

biofilm samples after the dead zone (p = 0.036). The relative abundance of this OTU was significantly

286

correlated with a shift in the biofilm community structure along NMDS axis 1 (p = 0.002), shifting from

287

the community structure before the dead zone toward the community structure after the dead zone (Figure

288

4). In addition, the relative abundance of OTUs classifying as Mycobacterium and Legionella, two genera

289

that contain species of public health importance as opportunistic pathogens, increased significantly in

290

biofilm samples after the dead zone (p = 0.036 and p = 0.036 for Mycobacterium and Legionella,

291

respectively) (Figure 5). The bacterial community in the sludge that accumulated near the right baffle wall

292

in chamber 3 contained sequences classified as Gp4 OTU0001 (1.5% relative abundance) as well as

293

Mycobacterium and Legionella (0.41% and 2.4% relative abundance, respectively) (Figure 6). The

294

Shannon diversity indices of biofilms from baffle walls varied between 3.1 and 4.5 (mean of 4.02 ± 0.45,

295

Table S4), whereas the Shannon diversity indices of biofilm from a diffuser and from the sludge in

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chamber 3 were 5.2 and 5.0, respectively. Shannon evenness ranged from 0.58 to 0.86 across all samples,

297

with the sludge bacterial community being the most even.

298

DISCUSSION

299

Viable cell concentrations. The overall level of inactivation across each contactor, as determined by

300

culture-independent flow cytometry, was higher than inactivation measured by culture-based methods.

301

Across the contactors, 1.62 log reduction of membrane-intact cells was observed on average (Figure 2b),

302

which is consistent with 1-2 log reductions of membrane-intact cells, as measured by flow cytometry,

303

reported for ozonation (0.33-0.35 mg O3/mg C) of partially treated raw waters in two other full-scale

304

DWTPs49. However, on days when HPC levels were reduced across the contactors, the reductions

305

observed (0.32 ± 0.05 log for April 22, Oct 4, Oct 19, 2016) were lower than those reported for a pilot-

306

scale ozone contactor column (1.5 log)50 and a baffled ozone reactor treating secondary wastewater

307

effluent (1.4-1.6 log)21. The greater culturability of the bacteria in water samples after ozonation (Figure

308

S2) may have contributed to the modest reductions in HPC levels observed. The potential for changes in

309

culturability to impact estimates of microbial reductions is one reason why flow cytometry was used in

310

addition to HPC to enumerate viable cells. HPC levels in contactor effluents were sometimes higher than

311

influent levels (May 5, 9, 13, 2016; Figure S2). At a DWTP in the Netherlands, levels of heterotrophic

312

bacteria isolated on conventional plate count agar increased after ozonation, although the increase was not

313

observed when R2A agar was used.49 A major limitation of culture-based studies is that only a small

314

proportion of viable cells are amenable to cultivation. Therefore, HPC may not be as responsive to

315

changes in bacterial abundance as culture-independent methods such as flow cytometry.51-53 The observed

316

increase in HPC and intact cell concentrations in chamber 3 and subsequent chambers indicates that

317

microbial growth occurred or that viable cells were introduced to the water through another mechanism.

318

Most of the overall reduction of viable cells occurred in the first ozone contact chamber (chamber

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2), where an approximate 2-log reduction of HPC and intact cell concentrations was observed. An

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investigation of bacterial concentrations at the same plant conducted three months after ozonation was

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implemented reported 2.6-log reduction of HPC determined by culturing on R2A agar (5.43 × 103

322

CFU/mL in contactor influent to 13 CFU/mL in effluent).19 Results of this earlier study taken together

323

with our findings suggest the reductions originally achieved over the full contactor length were

324

constrained to the first ozone contact chamber. While the first contact chamber provides a disinfection

325

barrier to microorganisms present in the partially treated raw water given the significant reduction in

326

viable cells (Figure 2a and 2b) observed after chamber 2, our data suggest that characteristics of chambers

327

3-7 shape the microbial quality of the water exiting the contactors.

328

Biofilm Detachment. The increase in viable cell concentrations after the first contact chamber cannot be

329

attributed to planktonic cell growth considering the short residence time in the contactors (approximately

330

10 min). The doubling rates required to produce such an increase would be much shorter than the fastest

331

doubling rates reported for microorganisms (e.g., 9.8 min for Vibrio natriegens54). Within 2 h of shutting

332

off water flow and ozone gas supply, HPC and intact cell concentrations increased in chambers 2 and 3,

333

but not in a control (Figure 3), suggesting that the interaction of bulk water with contactor surfaces or

334

accumulated solids was necessary to produce the increasing cell concentrations observed.

335

The contactors are made from poured concrete. Carbonation, i.e., the replacement of calcium

336

hydroxide with calcium carbonate, reduces the pH of concrete over time55 thereby resulting in more

337

favorable conditions for biofilm formation. Passive biofilm detachment from contactor surfaces may

338

occur continuously by erosion56 or through discrete detachment events (i.e., sloughing),56,57 and may be

339

due to shear created by fluid moving past the biofilm58 and/or an increase in detachment rate caused by

340

higher growth rates due to greater AOC availability59. Had shear-based detachment been important,

341

higher effluent cell concentrations would have been expected with increased flow through a contactor.

342

However, the times when effluent CFU concentrations were greatest (May 5, 9, 13, 2016; Figure S2) did

343

not correlate with days when the plant was operating at higher flowrates (Table S1). Instead, microbial

344

levels in bulk water increased quickly under stagnant conditions (Figure 3). AOC in contactor influent

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and AOC generated in chamber 2 (Figure S3) provided a continuous supply of biofilm growth substrates.

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The results support a scenario whereby AOC generated by ozonation provides growth substrate for

347

biofilm formation on contactor surfaces. Subsequently, biofilm detaches, thereby increasing planktonic

348

cell concentrations in contactor effluents.

349

Biofilm community structure. Results from the contactor shutdown experiment, and other evidence

350

discussed above, suggest that biofilm detachment may be responsible for the presence of microorganisms

351

detected in water samples. This underlines the importance of understanding the factors that shape the

352

microbial community structure of biofilms on contactor surfaces to control microbial quality of the

353

effluent. Biofilm microbes may have cellular and physiological features that facilitate their resistance to

354

ozone exposure. Additionally, biofilm EPS and carbonate on contactor surfaces may serve to protect

355

microorganisms from ozone and ozone decomposition products, respectively, as carbonate is an effective

356

hydroxyl radical scavenger60.

357

Recent research has focused on the potential for enrichment of disinfectant resistant,

358

opportunistic pathogenic bacteria through disinfection processes in water treatment.61,62 We detected

359

Mycobacterium and Legionella OTUs in biofilm samples from contactor walls in chamber 2, where the

360

highest ozone residuals were applied. Their resistance to ozone would be consistent with lab-scale

361

inactivation experiments demonstrating that certain Legionella and Mycobacterium species (e.g.,

362

Legionella pneumophila63 and Mycobacterium avium22) are more resistant to ozone exposure than E. coli.

363

The finding that ozonation of a wastewater treatment plant effluent selected for bacteria with high

364

genomic guanine-cytosine (GC) content is relevant for ozone selection of Mycobacterium species, which

365

have GC rich genomes.64 While we did not culture Mycobacterium spp. from the ozonated water samples,

366

in an earlier study performed shortly after the plant began ozonating, Mycobacterium was the most

367

common group and comprised 31% of bacterial isolates identified after ozonation.19 These results raise

368

the possibility that the presence of Legionella and Mycobacterium spp. in biofilm on contactor walls was

369

related to their resistance to ozone and not solely their protection from ozone exposure.

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Smaller colony sizes after ozone contact in chamber 2 (Figure S5) would be consistent with the

371

view that ozone exposure selected for disinfectant-resistant microorganisms as bacteria with lower

372

specific growth rates often exhibit higher resistance to stress,22,65,66 although this is not always the case23.

373

However, the ozone resistance of the cultured microorganisms was not tested in this study. Ozone

374

inactivation experiments are needed to confirm ozone resistance of microorganisms in contactor effluents.

375

Furthermore, given the range of viable cell concentrations we observed in contactor effluents,

376

fluorescence activated cell sorting of viable populations71 combined with amplicon sequencing could be

377

used for identification of viable cells in ozonated water. While the observed enrichment for Limnobacter

378

spp. in this study was consistent with their detection in biofilms from water distribution networks67,68 and

379

premise plumbing,69 their resistance to ozone is unknown since ozone inactivation kinetics for

380

Limnobacter spp. have not been reported. However, in a recent study, the relative abundance of

381

Limnobacter increased significantly in a surface water disinfected with photocatalytic ozonation.70 We

382

had expected that Limnobacter would be present in all biofilm samples based on its predominance among

383

isolates from contactor water samples (Table 1), but the community structure of biofilm samples on

384

contactor walls past a dead zone in chamber 3 was substantially different from those in chamber 2

385

(discussed below). The water samples for culturing were collected from a contactor in operation whereas

386

biofilm samples were collected from a contactor that had been taken out of operation. This contactor was

387

chosen for shutdown because ozone demand was unusually high. Upon inspection, we observed an

388

accumulation of sludge in the contactor, which may have caused the high ozone demand. It is likely that

389

this sludge had a greater impact on the biofilm community structure of the baffle walls in this contactor

390

than in the contactor from which water samples had been collected for culturing.

391

Dead zone effects. The length of chamber 3 is double the length of chamber 2 to provide for additional

392

disinfectant contact time. As the water velocity through chamber 3 decreases, more sediments are

393

deposited in chamber 3. This greater length is also expected to increase internal recirculation inside the

394

chamber and result in zones of insufficient mixing (dead zones).28 The accumulation of sludge observed

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near the right baffle wall in chamber 3 was in a location predicted to be a dead zone by modeling of flow Page 18 of 27 ACS Paragon Plus Environment

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through multi-chamber contactors.28 This sludge accumulation, and our data suggesting the presence of

397

biomass in the sludge, may be one way viable cells were introduced to the water in chamber 3.

398

Furthermore, the significantly different biofilm community structure past the dead zone raises the

399

possibility that microorganisms in sludge in the dead zone seeded biofilms downstream. However, it is

400

possible there was a greater impact of sludge on the biofilm community structure of baffle walls in this

401

contactor than in the contactor from which water samples for culturing were collected. Although lime

402

softening precipitates are expected to have a high pH unfavorable for microbial life, the Shannon diversity

403

of the bacterial community in a sludge sample from one dead zone was relatively high (5.0 ± 0.01, Table

404

S4), possibly due to the rapid decomposition of ozone when exposed to the high surface pH of the lime

405

softening precipitates, thus providing protection of microorganisms from ozone exposure. This notion

406

raises the possibility that sludge in dead zones harbor microorganisms that present a public health risk.

407

The presence of Mycobacterium and Legionella OTUs in sludge, and an increase in their relative

408

abundance in biofilms past the dead zone, suggest that adverse microbial effects of dead zones are an

409

argument for improving hydraulic efficiency in multi-chamber contactors by decreasing chamber length,

410

in spite of greater energy requirements to drive flow over and under more baffle walls36. Therefore,

411

chamber length should be an important feature for contactor design. Additionally, use of materials that are

412

less reactive with ozone and do not quench hydroxyl radicals (e.g., acidic materials) in contactor

413

construction may minimizes biofilm formation on contactor surfaces. As retrofitting ozone contactors is

414

not an option for many existing DWTPs, other options need to be considered to improve ozone

415

disinfection efficiency. Strategies that focus on increasing ozone dose to avoid biofilm formation need to

416

consider undesirable ozonation byproducts such as bromate72 and nitrosamines73. Better pretreatment

417

before ozonation and more frequent contactor cleanings are obvious strategies to reduce the effects of

418

sediments entering the ozone contactor in the present study. Our findings from one contactor need to be

419

confirmed with sampling campaigns in other full-scale, multi-chamber ozone contactors.

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While previous research has shed light on the importance of biofilms in determining microbial

421

water quality in distribution systems,74 our results provide a new appreciation for the potential role of

422

biofilm detachment in determining multi-chamber ozone contactor effluent water quality. Our findings

423

suggest implications for post-ozonation processes as ozone contactors may serve as an important seed

424

source of microorganisms to downstream biofilters. More research is needed to understand the interplay

425

between ozonation and biofiltration, two unit processes that may represent critical control points for

426

drinking water microbial quality30,75,76.

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ACKNOWLEDGEMENTS

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We thank James Yonts, Ryan Justin, Jeff Keown, Matt Brown, Mike Switzenberg, Aaron Buza, Duane

429

Weible, Wendy Schultz and Brian Steglitz for assistance with sampling and data collection; Michael

430

Pihalja, Aaron Robida, Krista Wigginton, and Frederik Hammes for helpful discussions; and Johannes

431

Schwank, Xiaoyin Chen and Yun Shen for assistance with TGA analysis. We also thank anonymous

432

reviewers for their valuable feedback. Partial funding for this work was provided by the Cystic Fibrosis

433

Foundation and the University of Michigan MCubed Program. NK was supported by Dow Sustainability,

434

Rackham Merit and Integrated Training in Microbial Systems (ITiMS) Fellowships from the University

435

of Michigan (UM). The ITiMS program “Instructional Program Unifying Population and Laboratory

436

Based Sciences” at UM was funded by the Burroughs Wellcome Fund. NR was partially supported by a

437

U.S. National Science Foundation Graduate Research Fellowship. SJH was supported by Alfred P. Sloan

438

Foundation, Microbiology of the Built Environment (G- 2014-13739) and UM Dow Sustainability

439

Fellowships.

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SUPPORTING INFORMATION

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Supporting Information for this study is provided and includes an overview of ozone contactors sampled,

442

description of the method used to determine ozone exposure, results of HPC analyses for each sampling

443

day, HPC and flow cytometry measurements on two days, results of organic carbon analyses, residual

444

ozone measurements after contactor shutdown, results of thermal gravimetric analysis of sludge, DNA

445

extraction yields and diversity estimates for biofilm and sludge samples, and taxonomy and relative

446

abundance of the top 10 most abundant OTUs in biofilm and sludge samples.

447

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Haig, S.-J.; Kotlarz, N.; LiPuma, J. J., Raskin, L. A high-throughput approach for identification of nontuberculous mycobacteria in drinking water reveals relationship between water age and Mycobacterium avium. Submitted. mBio. Kozich, J. J.; Westcott, S. L.; Baxter, N. T.; Highlander, S. K., Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 2013, 79 (17), 5112-20. Caporaso, J. G.; Lauber, C. L.; Walters, W. A.; Berg-Lyons, D.; Lozupone, C. A.; Turnbaugh, P. J.; Fierer, N., Knight, R. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. 2011, 108 (Supplement 1), 4516-22. Schloss, P. D.; Westcott, S. L.; Ryabin, T.; Hall, J. R.; Hartmann, M.; Hollister, E. B.; Lesniewski, R. A.; Oakley, B. B.; Parks, D. H.; Robinson, C. J.; Sahl, J. W.; Stres, B.; Thallinger, G. G.; Van Horn, D. J., Weber, C. F. Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities. Appl. Environ. Microbiol. 2009, 75 (23), 7537-41. Westcott, S. L. Schloss, P. D. OptiClust, an Improved Method for Assigning Amplicon-Based Sequence Data to Operational Taxonomic Units. mSphere. 2017, 2 (2), e00073-17. Wang, Q.; Garrity, G. M.; Tiedje, J. M., Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 2007, 73 (16), 5261-7. Cole, J. R.; Wang, Q.; Cardenas, E.; Fish, J.; Chai, B.; Farris, R. J.; Kulam-Syed-Mohideen, A.; McGarrell, D. M.; Marsh, T., Garrity, G. M. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res. 2009, 37 (suppl 1), D141-D5. Van der Kooij, D. Hijnen, W. Substrate utilization by an oxalate-consuming Spirillum species in relation to its growth in ozonated water. Appl. Environ. Microbiol. 1984, 47 (3), 551-9. Alarcon-Ruiz, L.; Platret, G.; Massieu, E., Ehrlacher, A. The use of thermal analysis in assessing the effect of temperature on a cement paste. Cem. Concr. Res. 2005, 35 (3), 609-13. Ben‐Dor, E. Banin, A. Determination of organic matter content in arid‐zone soils using a simple “loss‐on‐ignition” method. Communications in Soil Science & Plant Analysis. 1989, 20 (15-16), 1675-95. Frost, R.; Hales, M., Martens, W. Thermogravimetric analysis of selected group (II) carbonateminerals—Implication for the geosequestration of greenhouse gases. Journal of Thermal Analysis and Calorimetry. 2008, 95 (3), 999-1005. Vital, M.; Dignum, M.; Magic-Knezev, A.; Ross, P.; Rietveld, L., Hammes, F. Flow cytometry and adenosine tri-phosphate analysis: alternative possibilities to evaluate major bacteriological changes in drinking water treatment and distribution systems. Water Res. 2012, 46 (15), 4665-76. Norton, C. D. LeChevallier, M. W. A pilot study of bacteriological population changes through potable water treatment and distribution. Appl. Environ. Microbiol. 2000, 66 (1), 268-76. Van Nevel, S.; Koetzsch, S.; Proctor, C. R.; Besmer, M. D.; Prest, E. I.; Vrouwenvelder, J. S.; Knezev, A.; Boon, N., Hammes, F. Flow cytometric bacterial cell counts challenge conventional heterotrophic plate counts for routine microbiological drinking water monitoring. Water Res. 2017, 113, 191-206. Berney, M.; Vital, M.; Hülshoff, I.; Weilenmann, H.-U.; Egli, T., Hammes, F. Rapid, cultivationindependent assessment of microbial viability in drinking water. Water Res. 2008, 42 (14), 40108. Ward, D. M.; Weller, R., Bateson, M. M. 16S rRNA sequences reveal numerous uncultured microorganisms in a natural community. Nature. 1990, 345 (6270), 63-5. Eagon, R. G. Pseudomonas natriegens, a marine bacterium with a generation time of less than 10 minutes. J. Bacteriol. 1962, 83 (4), 736-7. Pade, C. Guimaraes, M. The CO2 uptake of concrete in a 100 year perspective. Cem. Concr. Res. 2007, 37 (9), 1348-56.

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Rittmann, B., Detachment from biofilms. In: Characklis WG, Wilderer PA, editors. Structure and function of biofilms. 1989, New York: John Wiley & Sons. p. 49-58. Bester, E.; Wolfaardt, G. M.; Aznaveh, N. B., Greener, J. Biofilms’ role in planktonic cell proliferation. Int. J. Mol. Sci. 2013, 14 (11), 21965-82. Picioreanu, C.; Van Loosdrecht, M. C., Heijnen, J. J. Two-dimensional model of biofilm detachment caused by internal stress from liquid flow. Biotechnol. Bioeng. 2001, 72 (2), 205-18. Bester, E.; Kroukamp, O.; Wolfaardt, G. M.; Boonzaaier, L., Liss, S. N. Metabolic differentiation in biofilms as indicated by carbon dioxide production rates. Appl. Environ. Microbiol. 2010, 76 (4), 1189-97. Hoigne, J. Bader, H. Ozonation of water: selectivity and rate of oxidation of solutes. Ozone Sci. Eng. 1979, 1 (1), 73-85. Alexander, J.; Knopp, G.; Dötsch, A.; Wieland, A., Schwartz, T. Ozone treatment of conditioned wastewater selects antibiotic resistance genes, opportunistic bacteria, and induce strong population shifts. Sci. Total Environ. 2016, 559, 103-12. Chiao, T.; Clancy, T. M.; Pinto, A. J.; Xi, C., Raskin, L. Differential Resistance of Drinking Water Bacterial Populations to Monochloramine Disinfection. Environ. Sci. Technol. 2014, 48 (7), 4038-47. Botzenhart, K.; Tarcson, G., Ostruschka, M. Inactivation of bacteria and coliphages by ozone and chlorine dioxide in a continuous flow reactor. Water Sci Technol. 1993, 27 (3-4), 363-70. Wayne, L. G. Gross, W. M. Base composition of deoxyribonucleic acid isolated from mycobacteria. J. Bacteriol. 1968, 96 (6), 1915-9. Mah, T.-F. C. O'Toole, G. A. Mechanisms of biofilm resistance to antimicrobial agents. Trends Microbiol. 2001, 9 (1), 34-9. Berney, M.; Weilenmann, H.-U.; Ihssen, J.; Bassin, C., Egli, T. Specific growth rate determines the sensitivity of Escherichia coli to thermal, UVA, and solar disinfection. Appl. Environ. Microbiol. 2006, 72 (4), 2586-93. Liu, R.; Zhu, J.; Yu, Z.; Joshi, D.; Zhang, H.; Lin, W., Yang, M. Molecular analysis of long-term biofilm formation on PVC and cast iron surfaces in drinking water distribution system. J. Environ. Sci. (China). 2014, 26 (4), 865-74. Wang, H.; Hu, C.; Hu, X.; Yang, M., Qu, J. Effects of disinfectant and biofilm on the corrosion of cast iron pipes in a reclaimed water distribution system. Water Res. 2012, 46 (4), 1070-8. Feazel, L. M.; Baumgartner, L. K.; Peterson, K. L.; Frank, D. N.; Harris, J. K., Pace, N. R. Opportunistic pathogens enriched in showerhead biofilms. Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (38), 16393-8. Becerra-Castro, C.; Macedo, G.; Silva, A. M.; Manaia, C. M., Nunes, O. C. Proteobacteria become predominant during regrowth after water disinfection. Sci. Total Environ. 2016, 573, 313-23. Müller, S. Nebe-von-Caron, G. Functional single-cell analyses: flow cytometry and cell sorting of microbial populations and communities. FEMS Microbiol. Rev. 2010, 34 (4), 554-87. von Gunten, U.; Bruchet, A., Costentin, E. Bromate formation in advanced oxidation processes. J Am Water Works Assoc. 1996, 88 (6), 53. Gerrity, D.; Pisarenko, A. N.; Marti, E.; Trenholm, R. A.; Gerringer, F.; Reungoat, J., Dickenson, E. Nitrosamines in pilot-scale and full-scale wastewater treatment plants with ozonation. Water Res. 2015, 72, 251-61. Liu, S.; Gunawan, C.; Barraud, N.; Rice, S. A.; Harry, E. J., Amal, R. Understanding, monitoring, and controlling biofilm growth in drinking water distribution systems. Environ. Sci. Technol. 2016, 50 (17), 8954-76. Lautenschlager, K.; Hwang, C.; Liu, W.-T.; Boon, N.; Köster, O.; Vrouwenvelder, H.; Egli, T., Hammes, F. A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks. Water Res. 2013, 47 (9), 3015-25.

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Cumulative 75% + 1.5*IQR 25-75% 25% - 1.5*IQR Median Outliers

5 (Outlet basin)

Inlet Inlet basin

1

2

3

4

5

6

7

Outlet basin

Outlet

Ozone gas Sample Line

Figure 1. Box and whisker plot for ozone CT (average concentration × contact time) for each chamber across contactors sampled on eight days. Cumulative ozone exposure is represented by orange triangles (mean values measured on eight days; error bars represent standard deviations). Water from an inlet basin flows through seven chambers and then into an outlet basin. Ozone gas is added into chambers 2 and 3. The cumulative residence time in a contactor is approximately 10 min. The width of chamber 3 is larger than the widths of the other chambers to provide additional disinfectant contact time.

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Environmental Science & Technology

75% + 1.5*IQR

a

25-75% 25% - 1.5*IQR Median Outliers

(200 - 3,850 CFU/mL)

b

(1,200 - 3,750 cells/mL)

Figure 2. Box and whisker plots representing viable cell concentrations of lime-softened water (sample line 1) and in different chambers during ozone exposure monitored by (a) HPC on six days, and (b) flow cytometry on four days. HPC data are reported as the average of duplicate dilutions plated in triplicate (n = 6 counts per sample except for chamber 1 and chamber 4 samples collected on May 13, 2016, which had only 5 and 4 counts, respectively). The numbers in parentheses indicate the range of cell concentrations at sample line 5.

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a

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b Water in chamber 2

Water in chamber 2

Water in chamber 3

Water in chamber 3

Chamber 2 water in control

Chamber 2 water in control

Time after shutdown (h)

Time after shutdown (h)

Figure 3. Average concentrations of viable cells monitored by (a) HPC and (b) flow cytometry before, 2 h after, and 9.5 h after contactor shutdown in water sampled from chambers 2 and 3, and water sampled from chamber 2 stored separately as an experimental control. Error bars represent standard deviation of duplicate dilutions plated in at least triplicate (except the control at 9.45 h in which duplicate plates were counted) or range of duplicate flow cytometry measurements.

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Sludge

OTU0010 OTU0005 Diffuser OTU0004 2R 2R 3L

3R 3R

OTU0016

4R 4R 5R OTU0013 OTU0001 OTU00012 OTU00014

Figure 4. Non-metric multidimensional scaling (NMDS) plot of ϴyc distance ordinations showing differences in community structure for total bacteria in biofilm and sludge samples. Biofilm samples were collected from chambers 2-5 on right or left baffle walls (indicated by R or L). There was significant (p = 0.017) separation between bacterial communities in biofilm on baffle walls located before (green points) and after (blue points) a dead zone. Of the top 20 most abundant OTUs across the samples, the OTUs with relative abundances that increased or decreased significantly (p < 0.01) along NMDS axis 1 are shown in red. OTU00010, OTU0005, OTU0004, OTU00016, OTU00013, OTU0001, OTU0012, and OTU0014 were classified as Brevundimonas, Methylophilus, Limnobacter, Sphingomonas, Sphingopyxis, Gp4, Hyphomicrobiaceae, and Sphingomonadaceae, respectively.

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` Legionella spp. Mycobacterium spp.

2R

2R

1

3L Diffuser Sludge

2

3

3R

4

3R

5

4R

6

4R

5R

7

Inlet Inlet basin

2R

3L

3R

4R

5R

Diffuser

Outlet basin

Outlet

Sludge Sample Line

Figure 5. Relative abundance of 20 Legionella OTUs (red) and 4 Mycobacterium OTUs (blue) in biofilm samples collected from chambers 2-5 on right or left baffle walls (indicated by R or L), a diffuser (Diffuser), and sludge (Sludge) from one contactor. Chamber numbers 1-7 are shown at the top of the contactor schematic.

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160,000

80,000 Page 33 Environmental of 33 Science & Technology Membrane intact cells/mL

40,000 20,000 10,000 5,000 2,500 1,000

ACS Paragon Plus Environment Ozone gas