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Longitudinal and Source-to-Tap New Orleans, LA, USA Drinking Water Microbiology Natalie Marie Hull, Eric P Holinger, Kimberly A Ross, Charles E Robertson, J. Kirk Harris, Mark J Stevens, and Norman R. Pace Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b06064 • Publication Date (Web): 15 Mar 2017 Downloaded from http://pubs.acs.org on March 16, 2017
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Longitudinal and Source-to-Tap New Orleans, LA, USA Drinking
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Water Microbiology
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Natalie M. Hull1*, Eric P. Holinger2, Kimberly A. Ross2, Charles E. Robertson3, J. Kirk Harris4,
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Mark J. Stevens4, and Norman R. Pace2§
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1 Department of Civil, Environmental, and Architectural Engineering, University of Colorado,
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Boulder, CO 80303, USA 2 Department of Molecular, Cellular, and Developmental Biology, University of Colorado,
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Boulder, CO, 80309, USA 3 Division of Infectious Disease, University of Colorado School of Medicine, Anschutz Campus,
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Aurora, CO, 80045, USA 4 Department of Pediatrics, University of Colorado School of Medicine, Anschutz Campus,
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Aurora, CO, 80045, USA
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[email protected] 16
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[email protected] ACS Paragon Plus Environment
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KEYWORDS
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Drinking water, V1/V2 region 16S rRNA amplicon sequencing, chloramine disinfection
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GRAPHICAL ABSTRACT
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ABSTRACT
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The two municipal drinking water systems of New Orleans, LA, USA were sampled to
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compare microbiology of independent systems that treat the same surface water from the
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Mississippi River. To better understand temporal trends and sources of microbiology delivered to
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taps, these treatment plants and distribution systems were subjected to source-to-tap sampling over
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four years. Both plants employ traditional treatment by chloramination, applied during or after
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settling, followed by filtration before distribution in a warm, low water age system. Longitudinal
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samples indicated microbiology to have stability both spatially and temporally, and between
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treatment plants and distribution systems. Disinfection had the greatest impact on microbial
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composition, which was further refined by filtration and influenced by distribution and premise
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plumbing. Actinobacteria spp. exhibited trends with treatment. In particular, Mycobacterium spp.,
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very low in finished waters, occurred idiosyncratically at high levels in some tap waters, indicating
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distribution and/or premise plumbing as main contributors of mycobacteria. Legionella spp.,
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another genus containing potential opportunistic pathogens, also occurred ubiquitously. Source
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water microbiology was most divergent from tap water, and each step of treatment brought samples
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more closely similar to tap waters.
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INTRODUCTION
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The near sea-level topography of New Orleans, LA presents a unique situation for control
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of storm water, wastewater, and drinking water, especially when faced with major storm events.
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The Sewerage and Water Board of New Orleans operates two DWTPs that serve New Orleans
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parish and parts of surrounding parishes. These plants continuously provide drinking water that
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meets EPA requirements despite challenging conditions presented by water loss and unresolved
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damage to buried infrastructure1,2. In 2013, 73% of 56 billion gallons pumped was not metered1,3,
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demonstrating the magnitude of the battle against storm-induced damage and aging infrastructure
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in systems with components ranging from 20 to more than 100 years old.
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A 2011 survey of drinking water microbiology in the southeastern U.S. found that the
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microbiology of New Orleans, LA drinking water distribution systems (DWDS) differed from that
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of other communities surveyed, delivering higher relative abundances of phylotypes indicative of
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fresh and saltwater infiltration (e.g. Planctomycetes and Bacteroidetes) and potential opportunistic
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pathogens (OPs) (e.g. Legionella and Mycobacterium spp.)4. To potentially elucidate the sources
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of such microbes and improve understanding of their variation over time, a longitudinal census
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was conducted on DWDS waters from source, through the drinking water treatment plants
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(DWTPs), to tap.
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Recent, culture-independent studies of DWTP and DWDS microbial communities based
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on gene sequences have provided initial comprehensive assessments of drinking water
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microbiology. Emerging generalities indicate that Alpha-, Beta- and Gamma-Proteobacteria,
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Actinobacteria (including Mycobacterium spp.), Cyanobacteria (including non-photosynthetic
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Melainabacteria5), Methylobacterium spp., and sphingomonads tend to dominate these bacterial
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assemblages4,6–15. The most studied factor for determining tap water microbiology has been
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disinfectant choice, mainly chlorine vs. chloramine. Both these disinfectants select for chlorine
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resistant genes16 and potential opportunistic pathogens (OPs) such as Legionella spp. (for chlorine)
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and Mycobacterium spp. (for chloramine)8,14,15,17–20. Chlorine disinfection has been shown to
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reduce relative abundance of Beta-Proteabacteria6,21 and to select for Escherichia-Shigella spp.4,
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and chloramination has been shown to enrich nitrogen metabolizing organisms11.
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Proteobacterial assemblages additionally have been shown to shift in response to chlorine
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residual14, the collective treatment processes16, and pH7. Other water quality parameters, including
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water age and dissolved oxygen, can also influence microbial composition12. Source water
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microbiology can be more variable over time than that of finished and DWDS waters 9. Finally,
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one study sought to identify the origination of the core microbiome of a DWDS within in the
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DWTP and found that filtration, when performed prior to chloramination, was the major factor
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determining DWDS community structure7.
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Aside from accumulation of a census, these and other sequence-based studies highlight the
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importance and widespread impact of microbial issues facing modern DWTPs and DWDSs10.
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Public health concerns include OPs22–27, the role of biofilms28 and amoebae25,29,30 in OP survival
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and proliferation in DWDSs, the selection for and harboring of antibiotic resistance31–33, and water
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quality impacts such as nitrification4,13,34 and microbial corrosion35. The investigation presented
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here of the origination and distribution of microbes in New Orleans DWTPs and DWDSs
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contributes to an essential knowledge base for better understanding and control of the
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microbiology of public drinking water systems. The specific goals of the research were to improve
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understanding of the New Orleans water system microbiota; over time, from source to tap, and
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comparatively between systems.
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METHODS
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New Orleans, DWTPs and DWDSs
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These two DWTPs present a rare opportunity to systematically and longitudinally compare
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independent systems treating the same water from the Mississippi River, from source to tap. The
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Carrolton DWTP produces 135 mgd (design capacity = 232 mgd) and serves the East Bank of the
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Mississippi River, while the Algiers DWTP produces 11 mgd (design capacity = 40 mgd) and
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serves the residential West Bank.
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coagulation, flocculation, and sedimentation of raw water and return sediments to the river1.
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Disinfection by sodium hypochlorite followed by anhydrous ammonia (to produce chloramine)
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occurs simultaneously in the upflow clarifier at Algiers, but in contact basin subsequent to the
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settling basin at Carrolton1. After pH adjustment with lime, fluoridation with fluorosilicic acid,
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and calcium sequestration with polyphosphate, disinfected water at both plants is rapidly filtered
Both plants add polyelectrolyte and ferric sulfate for
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through sand and anthracite before distribution1. Pipe materials include cast iron, cement, and
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PVC, and some are above ground. Both systems have elevated storage tanks.
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Study Design
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In the published 2011 study that prompted return to New Orleans4, 13 tap samples served
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by Carrolton DWTP and 1 raw sample from the Mississippi River were collected. The 2012
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campaign sampled taps representing the spatial extent of both Carrolton and Algiers DWDSs,
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finished (exiting the filters prior to distribution) waters, and raw waters for both DWTPs. In 2012,
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samples collected included 2 raw water samples at each DWTP river intake, 3 Algiers and 2
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Carrolton finished water samples, and 6 Algiers and 35 Carrolton tap water samples. To sample
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each step in each DWTP in 2014, filter media core samples, 1 raw water sample at each DWTP
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river intake, 2 Carrolton settling basin samples, 2 post- disinfection samples for each DWTP, 6
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Algiers and 28 Carrolton finished water samples, and 6 tap water samples taken from hose bibs
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coinciding with monitoring compliance locations for each DWDS were collected. All sampling
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campaigns were conducted in spring, representing a midpoint for the temperature range in this
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warm climate. For the taps sampled and representing the spatial extent of the distribution system,
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the estimated water age is < 1.5 days at Carrolton and < 2 days at Algiers. Location of taps, raw
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water intake, and each DWTP are indicated in Figure 1.
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Figure 1: Map indicating New Orleans, LA water taps sampled in 2011 (red circles), 2012 (blue
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circles), and 2014 (green circles); raw Mississippi river intakes (black triangles) for Algiers and
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Carrolton DWTPs (black squares); and the Mississippi river water sampled in 2011 (white
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triangle). World Light Gray Canvas Base map was downloaded from ArcGIS Online, and
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contributors included Esri, HERE, DeLorme, MapmyIndia, © OpenStreetMap contributors, and
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the GIS user community.
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Sample Collection and Processing
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Water Samples: After flushing premise plumbing water from the cold tap as measured by
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temperature stabilization, the Hanna HI-9828 multiprobe (Hanna Instruments, Woonsocket, RI)
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was used to collect temperature (Temp, °C), salinity (mg/g), dissolved oxygen (DO, mg/L), total
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dissolved solids (TDS, mg/L), conductivity (Cond, µS/cm), and pH data. Total chlorine (Tot Cl,
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mg/L) was measured on the Hanna HI 96711 Photometer (using HI 93711-0 reagent) by
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manufacturer’s instructions. At each tap, 1.5 - 2 L of water was collected in sterile Nalgene high-
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density polyethylene (HDPE) bottles after one tap-water rinse. Samples were stored on ice until
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sterile 0.2 µm polycarbonate filtration and freezing of filters within 12 hours. All other water
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samples were collected following the same protocol, at designated DWTP ports. In 2014, river
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samples were collected at each DWTP treatment plant intake using a custom weighted metal
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holster after one rinse by submersion of the sampling vessel in the river. The 2011 river sample
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was collected between DWTP intakes4 but was not re-sequenced for source-to-tap comparison due
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to location difference.
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Filter Media Samples: Filters consist of a silt layer that gradually accumulates over 6
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inches of anthracite, followed by 18 inches of sand, supported by 5 graduated layers of gravel.
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Filters were backwashed weekly for ~30 minutes with finished water from an elevated storage
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tank (used only for backwash at Carrolton) until water ran clear (with air scouring midway through
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cleaning at Algiers). Media samples were collected using a 70% ethanol-cleaned hinged 2 inch
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diameter metal coring device. Each filter bed was drained immediately before collection at 3 inch
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intervals along the top ~12 inches of filter depth of 15 mL of media from: top silt layer (A), top of
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anthracite below silt layer (B), bottom of anthracite above sand layer (C), and sand layer (D), and
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stored on ice until freezing within 12 hours. For one Algiers filter, 2 A, 1 B, 1 C, and 1 D samples
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were collected. For two Carrolton filters, 6 A, 3 B, 3 C, and 3 D samples were collected.
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DNA Extraction and Quantitation
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Genomic DNA was purified from water samples by phenol:chloroform extraction and
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bead-beating of thawed polycarbonate filters, with final suspension in 40 µL TE (10 mM Tris, pH
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8.0, 1 mM EDTA), as described previously36. Similarly, a known mass (~0.5 g) of wet filter media
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was extracted from each sample by weighing extraction tubes before and after adding vortex-
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homogenized filter media. Triplicate qPCR reactions were used to estimate total bacterial DNA
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in sample extracts as described previously37, and normalized to water sample volume or filter
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media mass.
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16S Amplicon Library Construction and Sequencing
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Bacterial profiles were determined by amplification and analysis of 16S rRNA gene
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sequences as described previously36,38,39. Amplicons were generated using 27F and 338R primers
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targeting ~300 base pairs of the bacterial V1/V2 variable region. PCR products were normalized
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by gel densitometry, and pooled, purified, and concentrated using a DNA Clean and Concentrator
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Kit (Zymo, Irvine, CA). Pooled amplicons were quantified by Qubit Fluorometer 2.0 (Invitrogen,
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Carlsbad, CA), diluted to 4nM, and denatured with 0.2 N NaOH at room temperature. Denatured
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DNA was diluted to 15pM, spiked with 25% Illumina PhiX control DNA, and sequenced by
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Illumina paired-end sequencing on the MiSeq platform (MiSeq Control Software v2.2.0.2, MiSeq
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Reporter v2.2.29, 500 cycle v2 reagent kit). The 2011 river and tap samples were previously
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sequenced by 454 pyrosequencing4, but tap samples were re-sequenced by Illumina MiSeq for this
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study to eliminate potential sequencing technology bias.
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Taxonomic Analysis of Paired-end Sequences
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As previously described39, sequences were sorted by sample via barcodes in the paired
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reads with a python script. After removing barcode, linker, and primers, sequences were deposited
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in the NCBI Short Read Archive under accession numbers SRP079986, SRP079990, and
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SRP086804 for 2011, 2012, and 2014 libraries. Deposited sequences were assembled using
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phrap40,41, discarding pairs that did not assemble. Assembled sequences were trimmed over a
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moving window of 5 nucleotides until average quality met or exceeded 20, discarding sequences
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with more than 1 ambiguity or shorter than 200 nucleotides (nt). Potential chimeras were identified
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with Uchime42 (usearch6.0.203_i86linux32) using the Schloss Silva reference sequences43 and
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discarded. Resulting sequences were aligned and classified with SINA44 (1.2.11) using the
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bacterial sequences in Silva 111Ref45 as reference, configured to yield the Silva taxonomy.
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Operational taxonomic units (OTUs) were produced by clustering sequences with identical
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taxonomic assignments.
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Microbial Community Analysis
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Removal of singleton, doubleton, chloroplast, and unclassified sequences left 6,072,331
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bacterial sequences for 146 libraries from the three sequencing runs encompassing 2011, 2012,
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and 2014 samples. Average library size was 41,311 sequences of 250 nt average length per sample.
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In addition to Microsoft Excel 2013 (used for t-tests), the software package Explicet46 (v2.10.5,
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www.explicet.org) was used for data exploration, manipulation, and calculation of ShannonH
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alpha diversity at rarefaction, calculation of Morisita-Horn beta diversity at rarefaction using
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average relative abundances for sample groups, and calculation of two-part analysis p-values
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adjusted for multiple sample comparisons within groups47. At rarefaction, Good’s coverage was
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>99%. The vegan package48 (v2.3-5) in R49 (v3.3.0) using RStudio50 (v0.99.902) was used to plot
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an ordination of 69 source-to-tap libraries in the 2014 dataset. A Bray-Curtis distance matrix was
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calculated on the rarefied (to minimum library size of 11,458 sequences/sample) and Hellinger-
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transformed (to normalize variance) OTU table, and plotted in a 2-dimensional Non-Metric
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Multidimensional Scaling (NMDS)51,52 ordination, where the proximity of samples represents their
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compositional similarity. Modeled fit was assessed by stress and Shepard plot51.
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RESULTS
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Water Quality
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Water quality parameters that could impact microbiology were measured over time from
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source to tap during each sampling campaign and averages are summarized in Table 1.
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Longitudinally, total chlorine in finished and tap waters remained constant at ~3 mg/L for
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Carrolton, but decreased for Algiers between 2012 and 2014. Chlorine residual dropped during
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distribution by ~0.3 mg/L from finished to tap in both DWDSs in 2012 and 2014 (t-test each year
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p < 0.05). In general, tap and finished water had higher pH, conductivity, total dissolved solids,
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and dissolved oxygen than raw water. Additionally, dissolved oxygen in raw Mississippi River
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water decreased while temperature increased over time. Routine monitoring data provided by the
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utility during the sampling campaign indicated river water TOC = 5.9 ppm and DOC = 3.7 ppm,
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and finished water TOC = 2.3 ppm. Salinity was also higher in finished and tap waters than in raw
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waters (t-test all samples p < 0.05).
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Table 1: Longitudinal and source-to-tap average water quality parameters + standard deviation for
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Carrolton (C) and Algiers (A) DWTPs, where Raw = river water, Fin = finished water before
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entering distribution system, and Tap = water sampled at taps throughout the distribution system.
240 Tot Cl mg/L 2011
2012
Raw Tap Raw Fin Tap
C
2.9 ± 0.3
A C A C
3.3 ± 0.2 3.2 ± 0.1 3.1 ± 0.2 2.9 ± 0.6
A C A C
2.6 ± 0.2 3.1 ± 0.3 2.2 ± 0.8 2.9 ± 0.6
Raw 2014
Fin Tap
DO mg/L
pH
11.3 13.3 ± 1.7 8.8 ± 3.1 8.5 ± 2.8 9.1 ± 3.6 10.7 ± 0.9 10.9 ± 1.9 4.8 ± 0.1 6.5 ± 1.4 6.3 ± 2.4 6 ± 0.8 5.2 ± 0.4
8.2 8.8 ± 0.2 8.2 ± 0.1 9.2 ± 0.1 9.1 ± 0.1 9.4 ± 0 9.2 ± 0.2 8.5 ± 0.2 9.1 ± 0.3 9.1 ± 0.2 9.4 ± 0.4 9.3 ± 0.2
Temp °C
Cond µS/cm
TDS mg/L
Salinity mg/g
16.8 17.3 ± 2.3 16.9 ± 0.9 17.5 ± 1.2 19.3 ± 1.3 21.2 ± 1.9 20.9 ± 0.3 20.6 ± 1.4 21.9 ± 0.8 22.7 ± 1.3 23.8 ± 1.3
319 347 ± 33 290 ± 3 306 ± 6 349 ± 9 317 ± 6 361 ± 21 375 ± 1 350 ± 13 441 ± 27 354 ± 14 449 ± 4
235 264 ± 11 145 ± 2 153 ± 3 174 ± 4 158 ± 3 181 ± 10 188 ± 1 175 ± 7 220 ± 14 177 ± 7 224 ± 2
0.17 0.20 ± 0.01 0.14 ± 0.00 0.15 ± 0.01 0.17 ± 0.01 0.15 ± 0.00 0.17 ± 0.01 0.18 ± 0.00 0.17 ± 0.01 0.21 ± 0.01 0.17 ± 0.01 0.22 ± 0.01
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Temporal Trends in DWDS Bacterial Assemblages
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As shown in Figure 2, three phyla (Proteobacteria, Actinobacteria, and Bacteroidetes)
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dominated microbial assemblages in raw, finished and tap water samples for both systems over
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the sampling period, representing >93% of overall bacterial relative abundance.
Relative
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abundances for all taxa in all samples are detailed in Supplementary Figure S1.
Of the
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Proteobacteria, Betaproteobacteria were most abundant overall (26 % in raw, 18 % in finished,
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and 16 % in tap waters), while Alphaproteobacteria were more abundant in raw water (11% in
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raw, 7% each in finished and tap waters), and Gamma-Proteobacteria were more abundant in
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treated water (5% in raw, 7% in finished, and 11 % in tap waters). Overall relative abundances of
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Actinobacteria, which include hgcl-clade and CL500-29-marine-group representatives, increased
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over time in raw water (17% in 2012, 30% in 2012, and 42% in 2014) but remained stable in tap
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water (~22%). Raw water assemblages had greater alpha-diversity (ShannonH = 5.7 + 0.4, mean
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+ standard deviation) than treated waters (finished water = 4.8 + 0.4, tap water = 4.7+ 0.8), and
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were longitudinally consistent in microbiology.
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Variation in taxon dominance and alpha diversity between finished and tap waters could
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indicate contributions from premise and distribution pipes, as shown particularly for potential OP
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Mycobacterium spp. in Figure S2. For example, in 2012 when the most taps were sampled, all
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finished waters contained 1%
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mycobacterial sequences, and 20% of taps contained >10% mycobacterial sequences. The spatial
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distribution of elevated mycobacterial sequences was generally idiosyncratic, suggesting premise
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plumbing as the main source of enrichment. Only two pairs of closely proximal tap samples with
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elevated mycobacterial sequences could indicate the possible contribution of localized DWDS
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enrichment. Though Legionella spp. relative abundances were greater in raw waters, they were
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found ubiquitously in finished and tap waters at >1% relative abundance, and in more than half
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the taps at >10% relative abundance (Fig S2). Although potential OP sequence enrichment was
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observed in many 2011 and 2012 taps, only one tap sample in 2014 contained >1% Mycobacterium
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and no tap sample contained >10% Legionella spp. sequences. This indicates possible longitudinal
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turnover of dominant phylotypes in both distribution and premise plumbing. Differences could
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also be attributed to sampling more broadly from taps in buildings in 2012, versus sampling at
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compliance monitoring outdoor hose bibs with less indoor plumbing influence in 2014.
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The most dominant taxa in finished water assemblages generally were longitudinally
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consistent, though dominance shifted from Arcicella and Legionella spp. in 2012 to CL500-29-
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marine-group in 2014 (two-part p 9) compared to raw water (~8.3), and variation in conductivity, salinity,
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and TDS likely resulted from treatment process chemical additions. The high pH and chloramine
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disinfection are directly comparable to the DWTP studied by Pinto et al7, as were the water
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temperatures for their spring and fall samples. The increased DO in tap vs. raw water is likely
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attributable to pressurization of water lines for distribution. Increased temperature over the
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sampling period could have partially contributed to the substantial decrease in raw water DO. The
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relatively warm temperature of source and tap water could have contributed to the widespread
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abundance of particular taxa, for example Legionella spp.53 While these sampling campaigns
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indicate the long term stability of these systems by sampling each spring over the course of several
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years, potential seasonal variations were not measured. The annual reproducibility correlates with
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the yearly stability observed in tap microbiota by Pinto et al., where seasonal variations were
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observed7,9.
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Actinobacteria Gradients
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Detection of Actinobacteria, most commonly Mycobacterium spp., in DWTP and DWDS
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studies (especially in treated waters) has been reported frequently4,11,14,32,54. In New Orleans, raw
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river water was most abundant in hgcl-clade Actinobacteria, a group of freshwater and estuarine
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organisms55–61. On the other hand, representatives of the CL500-29-marine-group of marine and
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estuarine Actinobacteria56,62,63 were enriched in finished and tap waters in New Orleans (Figure
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2), particularly by filtration and disinfection (Figure 3). Additionally, CL-500-29-marine-group
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relative abundance increased longitudinally in all sample types (Figure 2). The decrease in hgcl-
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clade from raw water to taps observed in this study contrasts with another study in which this
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group was seen to maintain constant relative abundances throughout a DWTP54. This difference
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could be attributed to differing treatment processes, where a chloraminated treatment train similar
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to that of New Orleans was applied in parallel to an advanced treatment train additionally
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incorporating ozone and GAC. Stratification of hgcl and CL500-29 clades in filter media could be
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partially explained by their susceptibility to changes in DOM, where decreasing amounts of
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bacterial DNA with increased filter depth indicate a decline in overall biomass64(Figures 3 and 4).
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The interplay between actinobacterial representatives may be important for a sea level
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system like New Orleans with old and damaged pipes that undergo frequent repair, where there
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are relationships between environmental (hgcl-clade and CL-500-29-marine-group) and potential
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OP (Mycobacterium spp.) taxa. For example, an indirect longitudinal correlation occurs for
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relative abundances of Mycobacterium spp. and CL500-marine-group in raw, finished, and tap
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waters.
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Mycobacterium spp. relative abundances consistently increased from source to tap in 2012 and
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2014, in agreement with another study showing selection for such potential OPs by treatment54.
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Though coastal DWDS’s may battle similar marine intrusions, and all systems battle leaks and
Additionally, although bacterial DNA decreased from source to tap (Figure 4),
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infiltration, specific interactions between microbial communities in pipes and the environment
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may differ in other soils, climates, and in freshwater.
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Source Water and Distribution System Shape Core Microbiology
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Several aquatic and soil associated microbes were present in raw river water and eventually
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constituted the fairly stable finished and tap water microbiomes, including marine groups,
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freshwater groups, hgcl clade spp., Sediminibacterium spp., Limnohabitans spp., Arcicella spp.
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and others. The persistence of these environmental groups in finished and tap waters presumably
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reflects a high degree of selection for these taxa by treatment. Additionally, the occurrence of
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some environmental groups could result from infiltration during distribution, or seeding of pipe
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microbiology during frequent repair and flooding events. The low water age (