Sulfate Reducing Bacteria and Mycobacteria Dominate the Biofilm

Subscriber access provided by UNIV OF MISSISSIPPI

Article

Sulfate Reducing Bacteria and Mycobacteria Dominate the Biofilm Communities in a Chloraminated Drinking Water Distribution System Christa Kimloi Gomez-Smith, Timothy M. LaPara, and Raymond M Hozalski Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b00555 • Publication Date (Web): 22 Jun 2015 Downloaded from http://pubs.acs.org on June 23, 2015

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 33

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

Environmental Science & Technology

Sulfate Reducing Bacteria and Mycobacteria Dominate the Biofilm Communities in a Chloraminated Drinking Water Distribution System

C. Kimloi Gomez-Smith1,2, Timothy M. LaPara1, 3, Raymond M. Hozalski1,3*

1

Department of Civil, Environmental, and Geo- Engineering, University of Minnesota, Minneapolis, Minnesota 55455 United States

2

Water Resources Sciences Graduate Program, University of Minnesota, St. Paul, Minnesota 55108, United States 3

BioTechnology Institute, University of Minnesota, St. Paul, Minnesota 55108, United States

Inquiries to: Raymond M. Hozalski, Department of Civil, Environmental, and Geo- Engineering, 500 Pillsbury Drive SE, Minneapolis, MN 554555, Tel: (612) 626-9650. Fax: (612) 626-7750. Email: [email protected]

ACS Paragon Plus Environment


42 43

ABSTRACT The quantity and composition of bacterial biofilms growing on ten water mains from a

44

full-scale chloraminated water distribution system were analyzed using real-time PCR targeting

45

the 16S rRNA gene and next-generation, high-throughput Illumina sequencing. Water mains

46

with corrosion tubercles supported the greatest amount of bacterial biomass (n = 25; geometric

47

mean = 2.5 × 107 copies cm-2), which was significantly higher (P = 0.04) than cement-lined cast-

48

iron mains (geometric mean = 2.0 × 106 copies cm-2). Despite spatial variation of community

49

composition and bacterial abundance in water main biofilms, the communities on the interior

50

main surfaces were surprisingly similar, containing a core group of operational taxonomic units

51

(OTUs) assigned to only 17 different genera. Bacteria from the genus Mycobacterium dominated

52

all communities at the main wall-bulk water interface (25% to 78% of the community),

53

regardless of main age, estimated water age, main material, and the presence of corrosion

54

products. Further sequencing of the mycobacterial heat shock protein (hsp65) provided species-

55

level taxonomic resolution of mycobacteria. The two dominant Mycobacteria present, M.

56

frederiksbergense (arithmetic mean = 85.7% of hsp65 sequences) and M. aurum (arithmetic

57

mean = 6.5% of hsp65 sequences), are generally considered to be non-pathogenic. Two

58

opportunistic pathogens, however, were detected at low numbers: M. haemophilum (arithmetic

59

mean = 1.5% of hsp65 sequences) and M. abscessus (arithmetic mean = 0.006% of hsp65

60

sequences). Sulfate-reducing bacteria from the genus Desulfovibrio, which have been implicated

61

in microbially-influenced corrosion, dominated all communities located underneath corrosion

62

tubercules (arithmetic mean = 67.5% of the community). This research provides novel insights

63

into the quantity and composition of biofilms in full-scale drinking water distribution systems,

64

which is critical for assessing the risks to public health and to the water supply infrastructure.

65 1 ACS Paragon Plus Environment

Page 2 of 33

Page 3 of 33

66


INTRODUCTION

67

Drinking water distribution systems (DWDSs) are an integral, although often overlooked,

68

component in the provision of safe drinking water to consumers. Drinking water infrastructure is

69

extensive, with more than 800,000 miles of main in the United States.1 Despite the multi-faceted

70

approaches that water utilities employ to control microbial growth within the distribution system,

71

including limiting availability of assimilable organic carbon2 and maintenance of a disinfectant

72

residual, these systems are known to harbor substantial quantities of viable bacteria.3 Most of

73

these bacteria (~95%) reside in biofilms on the walls of the water mains,4 which are comprised

74

of a variety of materials, including unlined cast-iron, steel, ductile iron, cement-lined iron,

75

various plastics, or wood.5 There is evidence that these biofilms may increase corrosion rates and

76

affect main integrity,6-7 decrease residual disinfectant levels,8-10 and act as reservoirs for

77

pathogens and other water quality-compromising bacteria. 11-12

78

For the past few decades, research on DWDSs has focused on the study of pathogens and

79

nitrifying bacteria in controlled experiments using laboratory-scale or simulated distribution

80

systems.13-20 These studies used pipe loops, annular reactors, or other model systems to yield

81

important information on the positive association of biomass levels with iron surfaces and the

82

extent of corrosion,13, 15, 18 the effects of water chemistry (e.g., chlorine, sulfate, assimilable

83

organic carbon) on biomass levels and community composition,18 and the ecology of the biofilm

84

communities.17, 19 Clearly, there are limitations with using such laboratory-scale systems,

85

perhaps the most significant of which is the relatively short operating time (i.e., months to a few

86

years) in comparison to the service life of full-scale water mains (many decades). In contrast,

87

Kelly et al.21 observed significant temporal variation in the biofilm community composition in

2 ACS Paragon Plus Environment


88

water mains from a full-scale DWDS that correlated with water quality changes including

89

fluctuations in residual chloramine concentration.

90

In the present study, we determined the quantity (using quantitative PCR of 16S rRNA

91

genes) and community composition (using Illumina MiSeq analysis on PCR-amplified 16S

92

rRNA gene fragments) of bacteria growing on the internal surfaces of drinking water mains of

93

varying type and age from a full-scale chloraminated DWDS. We hypothesized that corrosion

94

tubercles found on cast-iron mains would harbor greater quantities of bacteria and specific

95

bacterial populations known to contribute to corrosion as compared to cement-lined mains,

96

which should harbor few (if any) corrosion-associated microbes. Substantial quantities of

97

biomass were found on all types of water mains, but significantly higher biomass densities were

98

detected beneath corrosion tubercles. The biofilm communities were of modest diversity

99

(Shannon index: H′= 1.4 to 3.8) but exhibited surprisingly low evenness, as the communities

100

living on the surface of the water mains were dominated by Mycobacterium-like organisms while

101

the biofilms found underneath corrosion tubercles were dominated by Desulfovibrio-like

102

organisms. Because many Mycobacteria spp. are pathogens or opportunistic pathogens, the gene

103

encoding a 65-kilodalton mycobacterial heat shock protein (hsp65) was also characterized to

104

more carefully resolve the Mycobacteria-like subcommunity.22-24

105

MATERIALS AND METHODS

106

Study Site. For this investigation, water main samples were collected from a single

107

distribution system owned and operated by Saint Paul Regional Water Services (SPRWS) in

108

Saint Paul, Minn. The main water source is the Mississippi River, which is first passed through a

109

chain of lakes before entering the treatment plant. The water treatment process includes

110

coagulation, lime softening, flocculation, sedimentation, recarbonation, filtration and


Page 4 of 33

Page 5 of 33


111

disinfection. SPRWS treats an average of 132,000 m3 /day (35 × 106 gallons/day), although the

112

maximum treatment capacity is 545,000 m3/day (144 × 106 gallons/day). There are

113

approximately 1,770 kilometers (1,100 miles) of water main within the system and above-ground

114

tanks that provide a water storage capacity of 496,000 m3 (131 × 106 gallons). The water is

115

supplied to residents of the city and a few surrounding communities and consistently meets all

116

applicable regulations. A summary of water quality monitoring results (i.e., total chlorine, pH,

117

and total organic carbon) for the finished water is provided in the Supporting Information (Table

118

S1).

119

Water Quality Analyses. All water quality analyses were performed by SPWRS

120

personnel as part of their routine sampling and monitoring. Total chlorine concentrations were

121

determined by the N,N-diethyl-para-phenylenediamine (DPD) method25 using a Hach DR500

122

UV-Vis spectrophotomer (finished water) or a LaMotte handheld colorimeter (distribution

123

system). Monochloramine concentrations were determined using the Indophenol Method.26

124

Sample Collection and DNA Extraction. Water main sections (length: 30-45 cm,

125

diameter: 15 cm) were obtained from the distribution system in conjunction with routine

126

replacement activities. The water main samples included: 8 cast iron water mains ranging in age

127

from 64 to 129 years and 2 cement-lined cast iron water mains (53 and 57 years) (Table 1).

128

Water ages for each water main were estimated using the InfoWater (Innovyze, Colorado)

129

modeling program. Water main exteriors were cleaned using a chain cleaner prior to removal.

130

Water main sections were manually extracted using a hinged cutter (Reed Manufacturing, Erie,

131

PA, USA); the open ends were immediately sealed with sterile bags and then placed in a cooler

132

and transported to the University of Minnesota. The water mains differed dramatically in

133

appearance (Fig. 1); seven of the cast-iron water mains (primarily older) exhibited large tubercles



134

while the other water mains (i.e., cement-lined and the newer, unlined cast-iron main) exhibited

135

no obvious signs of tuberculation.

136

Biofilms were sampled from the interiors of the water mains within 2 hours of water

137

main extraction using a sterile metal spatula at least 10 cm from a cut end to minimize the risk of

138

contamination. In cast-iron water mains with corrosion tubercles, the exterior surfaces of the

139

tubercles were scraped (Tuberculated-Surface) and then tubercles were pried up and the loose

140

solids underneath the tubercles were also collected (Under Tubercle). For the water mains

141

without tuberculation (Non-Tuberculated cast-iron and Cement-Lined cast-iron), only surface

142

samples were collected. Biofilm samples were collected from three locations in each water main,

143

except Main 1, where 7 locations were sampled. In total, 51 samples of biofilm and associated

144

loosely-bound corrosion products, weighing between 0.04 and 0.75 g (wet weight), were

145

obtained (6 Cement Lined, 3 Non-Tuberculated, 27 Tuberculated-Surface, and 15 Under

146

Tubercle). The plan area of each sampling site within the water mains was measured using

147

digital calipers and ranged from 2 to 58 cm2 per sample. All samples were stored at -20°C prior

148

to DNA extraction.

149

DNA was extracted from the biofilm samples using the FastDNA Spin Kit for Soil (MP

150

Biomedicals, Solon, OH, USA) per the manufacturer’s instructions. Briefly, ~0.5 g of sample

151

(water main scraping and associated biofilm) was placed in a lysing matrix tube, immersed in

152

CLS-TC buffer (MP Biomedicals), and rigorously shaken for 30 seconds in a FastPrep bead-

153

beating instrument (FastPrep, Savant) on the 5.5 m/s mix setting. Extracted and purified DNA

154

was stored at -20oC.

155 156

PCR and Illumina MiSeq Analysis. PCR targeting the V3 region of the 16S rRNA gene was performed using primers 338F27 (5′-ID-ACT CCT ACG GGA GGC AGC AG-3′) and


Page 6 of 33

Page 7 of 33


157

518R28 (5′-ID-ATT ACC GCG GCT GCT GG-3′) as described previously.29-30 Similarly, the

158

hsp65 gene was amplified using primers tb11 (5′-ID-ACC AAC GAT GGT GTG TCC AT-3′)

159

and tb12 (5′-ID-CTT GTC GAA CCG CAT ACC CT-3′) as described previously.31 For both

160

sets of PCR primers, ID is an Illumina adapter sequence including a six- or eight-base

161

multiplexing identification barcode unique to each sample.29 PCR products were initially

162

screened using 2% agarose gels and then purified using the QIAquick Gel Extraction kit

163

(Qiagen; Valencia, Calif.) per manufacturer’s instructions. Purified PCR products were pooled

164

in equal concentrations and used as template for paired-end sequence analysis (2 × 150bp for

165

16S rRNA genes; 2 × 300bp for hsp65 genes) on a MiSeq Desktop Sequencer (Illumina, Inc.;

166

San Diego, Calif.) at the University of Minnesota Genomics Center (UMGC). Sequences are

167

available through GenBank under BioProject PRJNA 273966.

168

Quantitative PCR. Quantitative real-time polymerase chain reaction (qPCR) was

169

performed using an Eppendorf Mastercycler ep realplex thermal cycler (Eppendorf, Westbury,

170

NY, USA) to quantify 16S rRNA genes as a measure of total bacterial biomass as described

171

previously.32 Briefly, each qPCR run consisted of initial denaturation for 10 min at 95°C,

172

followed by 40 cycles of denaturation at 95°C for 15 s, and anneal/extension at a target-specific

173

temperature for 1 min. A 25 µL reaction mixture contained 12.5 µL of iTaq SYBR Green

174

Supermix with ROX (Bio-Rad; Hercules, Calif.), 25 µg bovine serum albumin (Roche Applied

175

Science; Indianapolis, Ind.), optimized quantities of forward and reverse primers (to limit the

176

formation of primer-dimers), and 0.5 µL of template DNA. The quantity of target DNA in

177

samples was calculated based on comparison to standard curves generated using known

178

quantities of plasmid DNA containing the 16S rRNA gene of E. coli K12. Standard curves

179

consisted of at least five different dilutions of plasmid DNA run during each qPCR (r2 > 0.99). 6 ACS Paragon Plus Environment


180

The amplification curves of individual samples were compared to those of the standards to

181

ensure that the samples and standards amplified with similar efficiencies (amplification

182

efficiencies were 100 ± 8%). Negative controls obtained during sampling were also quantified in

183

order to account for background contamination. All negative controls had Cq values > 26 cycles,

184

whereas all water main samples had Cq values < 22 cycles.

185

Data Analysis. The statistical analyses were performed on log-transformed 16S rRNA

186

gene quantities using JMP Pro ver. 11.2.0 (SAS Institute; Cary, N.C.). One-way analysis of

187

variance (ANOVA) was initially performed to determine if statistically significant differences

188

existed in the data set; Tukey’s honesty significant difference (HSD) test was then used to

189

determine the statistical significance of differences between the means of pairwise comparisons.

190

Illumina MiSeq sequence data was processed and analyzed using Mothur v.1.29.2.33 For

191

all sequences, paired-end reads were initially combined to give a single sequence, after which the

192

sequences were screened for quality. Sequences containing any mismatches with the barcoded

193

primers, sequence lengths outside of the expected range for the target gene (135-151 bp for 16S

194

rRNA gene fragments; 400-500 bp for hsp65 fragments), ambiguous bases, or homopolymers

195

longer than 8 bp were excluded. In addition, sequences were removed if the MiSeq-defined

196

average quality score was less than 35 (Q35 = 99.97% accuracy in base calling) over a sliding

197

window of 50 bp. Qualifying sequences were binned by sample; primers and barcodes were

198

trimmed from the sequencing reads.

199

For 16S rRNA genes, sequences were aligned to the SILVA bacterial 16S rRNA

200

database; chimeric sequences were removed using the UCHIME algorithm34 and the results were

201

randomly subsampled to 44,455 sequences (i.e., the number of sequences in the sample with the

202

least number of sequences) to avoid bias due to variable coverage of each sample. Sequences


Page 8 of 33

Page 9 of 33


203

were clustered into operational taxonomic units (OTUs) at a cutoff of 99% sequence identity.

204

Taxonomic information for all sequences was obtained using the RDP database release 9.35

205

Weighted unifrac distances36 were computed for non-metric multidimensional scaling (nMDS)

206

analysis.

207

For hsp65 sequences, sequences were aligned to a newly-created database containing

208

hsp65 sequences from 200 strains of Mycobacteria spp. and several other phylogenetically-

209

related organisms (see Supporting Information, Table S2). Sampled sequences were aligned to

210

the alignment reference file and preclustered into groups of 95% sequence identity. Sequences

211

were then filtered, matched to the taxonomic reference file, and clustered into OTUs at a cutoff

212

of 95% sequence identity. Bootstrap values > 60% were sufficient for species-level

213

classification.

214

RESULTS

215

Ten water mains of different ages were collected from various locations throughout the

216

DWDS during April 16-September 23, 2013 (see Supporting Information, Figure S1). Eight of

217

the water mains were comprised of unlined cast-iron, with 7 of the 8 exhibiting tuberculation.

218

The remaining two water mains were cement-lined cast-iron and exhibited no tuberculation.

219

Distribution System Water Quality. Finished water leaving the SPRWS treatment plant

220

contained a total chlorine residual (arithmetic mean ± standard deviation) of 3.5 ± 0.2 mg/L, and

221

a mean TOC concentration of 4.2 ± 0.8 mg/L during the water main sampling period (April 16 -

222

September 23, 2013). The mean total chlorine residual for DWDS water samples (n = 1,113)

223

obtained from 85 locations throughout the distribution system was 2.6 ± 0.4 mg/L. For these

224

DWDS samples, the mean pH was 9.0 ± 0.3, with 99.8% of samples within the pH range of 8.5

225

to 9.4. Additional water quality data of the finished water leaving the SPRWS treatment plant



226

effluent and from water collected from the DWDS during the water main sampling period are

227

summarized in the Supporting Information (Table S1).

228

Quantification of Bacterial Biomass. Substantial quantities of bacterial biomass,

229

measured as 16S rRNA gene copies, were detected on the surfaces of all water mains as well as

230

underneath the corrosion tubercules (Fig. 2). Of the surface samples, the Tuberculated Surface

231

had the highest quantity of biomass (n = 25; geometric mean = 2.5 × 107 copies cm-2; geometric

232

standard deviation = 1.0), which was significantly greater (P = 0.04) than the quantity of biomass

233

on the Cement-Lined mains (n = 6; geometric mean = 2.0 × 106 copies cm-2; geometric standard

234

deviation = 0.6) but not statistically greater (P = 0.13) than the quantity of biomass on the Non-

235

Tuberculated main (n = 3; geometric mean = 1.6 × 106 copies cm-2; geometric standard deviation

236

= 0.7). The highest levels of bacterial biomass were detected in the Under Tubercle samples (n

237

= 15; geometric mean = 5.0 × 109 copies cm-2; geometric standard deviation = 0.7), and the mean

238

was significantly higher (P < 0.0001) than that for any other sample type. Finally, biomass

239

values did not correlate with main age or the estimated water age at a given main location.

240

Bacterial Community Composition. The bacterial community composition of the

241

biofilms growing on the surfaces of all of the water mains as well as underneath the corrosion

242

tubercles was determined by Illumina MiSeq profiles of PCR-amplified 16S rRNA gene

243

fragments. A total of 18,291,384 sequences were obtained, which were screened for quality and

244

then sub-sampled to 42,445 sequences per profile so that community analysis could be

245

performed without bias related to the depth of sequence information for each sample. All

246

sequences analyzed were classified as Bacteria, with a total of 33,474 different OTUs among all

247

of the samples. All OTUs were further classified to the genus level with 100% bootstrap


Page 10 of 33

Page 11 of 33


248

confidence, with no unassigned OTUs. Although OTUs were assigned to 1,217 different genera,

249

OTUs attributed to only 18 genera comprised the majority (86.8%) of all sequences.

250

Multiple samples were initially collected from seven different locations within Main 1

251

(Tuberculated Surface) (Fig. 3A) and from three different locations within Main 2 (Tuberculated

252

Surface) (Fig. 3B) to help ascertain the relative reproducibility of the Illumina MiSeq profiling

253

pipeline. In both cases, there were substantial differences in Illumina MiSeq profiles within

254

Main 1 and within Main 2, which could have been caused by genuine differences in bacterial

255

community composition or due to random variation in the Illumina MiSeq profiling pipeline. To

256

help resolve this question, one of the samples from Main 2 was processed in triplicate, giving

257

highly reproducible results (Fig. 3B), suggesting that the observed variation in all of the samples

258

is due to genuine variation in bacterial community composition rather than random variation

259

implicit to the Illumina MiSeq pipeline.

260

The water main biofilm communities exhibited relatively low diversity as quantified by

261

the Shannon index (Table 2). More specifically, the biofilm communities exhibited a reasonably

262

high degree of richness (as suggested by the ACE richness estimate) but most of the

263

communities were very uneven, with a single bacterial population comprising a very large

264

fraction (> 50%) of the community. The most abundant OTUs within all of the water main

265

surface communities were of the genus Mycobacterium (Fig. 4A). The fraction of

266

Mycobacterium-like OTUs varied from as low as 24.8% ± 1.7% (Main 5) to as high as 77.7% ±

267

4.0% (Main 10); these OTUs were detected at similar levels whether the water main was

268

Tuberculated (51.7% ± 21.2%), Non-Tuberculated (60.2% ± 9.8%), or Cement-Lined (73.1% ±

269

6.1%). In contrast, Mycobacterium-like OTUs comprised only a small portion of the Under

270

Tubercle bacterial communities (1.8% ± 2.7%). The most abundant OTUs in the Under



271

Tubercle communities were of the genus Desulfovibrio (67.5% ± 26.6%) (Fig 4B). These

272

Desulfovibrio-like OTUs were also detected in the water main surface samples, but at much

273

lower abundances (Tuberculated: 13.7% ± 18.5%; Cement-Lined: 0.2% ± 0.1%; Non-

274

Tuberculated: 0.3% ± 0.3%).

275

Identification of Mycobacterial Strains. Because the Mycobacteria contain several

276

known and opportunistic pathogens,37 PCR and Illumina MiSeq analysis was used to profile a

277

461bp fragment of a gene encoding a 65-kilodalton heat shock protein, the sequence of which

278

has been reported to give species-level resolution of Mycobacteria.31 Although PCR

279

amplification of hsp65 was attempted on all 51 water main samples, only 19 amplified

280

adequately for sequence analysis. The number of sequences obtained for Under Tubercle (n = 5),

281

Cement-Lined (n = 2), and Non-tuberculated (n = 1) samples ranged from 1,365 to 9,336 per

282

sample, while Tuberculated Surface (n = 11) samples had the largest and most variable number

283

of sequences, ranging from 7,712 to 29,972 per sample. A total of 15,779 OTUs were classified

284

as 72 different mycobacterial species (see Supporting Information for a complete list, Table S3).

285

Ninety-six percent of Mycobacterium-like OTUs had a 100% bootstrap confidence; 2% of OTUs

286

had a 61-99% bootstrap confidence; and 2% of OTUs had a bootstrap confidence below 60% and

287

were thus labeled “unclassified.” Although the lack of sufficient replicates from each of the

288

samples thwarted statistical analysis, the specific populations of Mycobacteria appeared

289

substantially different among the different water main types (Table 3). The most common

290

hsp65 sequence in all water main types was associated with M. frederiksbergense, ranging from

291

~80% of the community (Non-Tuberculated and Under Tubercle) to as high as ~99% of the

292

community (Cement-Lined). M. aurum-like sequences were the second most abundant OTU in

293

the Tuberculated Surface samples, whereas M. haemophilum was the second-most abundant


Page 12 of 33

Page 13 of 33


294

OTU in the Non-Tuberculated sample (11.3%). The Under Tubercle samples, however, had

295

several different Mycobacteria spp. (M. lentiflavum, M. psychrotolerans, M. holsaticum, M.

296

nebraskense, and M. haemophilum) comprise anywhere from 1% to 5% of the hsp65 profiles.

297

DISCUSSION

298

This manuscript provides novel information on the quantities and community

299

composition of bacteria growing on water mains from a full-scale distribution system.

300

Information of this type is exceptionally rare because of the cost and inconvenience of exhuming

301

and analyzing such water mains. Hence, most of the prior research in this area investigated

302

bench- or pilot-scale simulated water distribution systems, used surrogates for water mains (e.g.,

303

coupons, water meters), or sampled tap water. A limitation of the research described herein is

304

that it focused solely on a single distribution system with a stable chloramine residual throughout

305

its extensive network. Additional research is needed to characterize the bacterial communities

306

growing in a wide variety of distributions systems, such that the roles of disinfectant type,

307

residual disinfectant concentration, and other factors can be better understood.

308

The abundance of Desulfovibrio-like OTUs underneath all sampled corrosion tubercles

309

suggests that microbial-influenced corrosion is a significant contributor to the deterioration of

310

unlined cast-iron drinking water mains. Desulfovibrio spp. are sulfate-reducing bacteria (SRB)

311

that have been shown to cause localized corrosion and shorten the design life of various

312

materials in built environments.38 Research on SRB on the interior of water mains dates back to

313

at least the 1940s,39-40 where their presence was believed to exacerbate corrosion. These early

314

investigations and more recent studies41-44 clearly demonstrate the abundance of SRBs in

315

corroded iron water mains. Despite aerobic conditions in the bulk water, the DWDS biofilms and

316

corrosion tubercles provide anaerobic niches where sulfate-reducing bacteria can proliferate.



317

Additionally, there is ample evidence that some Desulfovibrio spp., although classified as

318

obligate anaerobes, are equipped with thioredoxins that enable them to survive exposure to oxic

319

environments.45-46

320

Our results show that Desulfovibrio-like OTUs dominated the bacterial community

321

underneath corrosion tubercles in quantities that greatly exceed previous cultivation-dependent

322

quantifications of sulfate-reducing bacteria.41-42 Their location underneath corrosion tubercles not

323

only affords these organisms protection from dissolved oxygen and chlorine in the bulk water but

324

also can provide the SRB with access to molecular hydrogen as electron donor from the

325

reduction of protons during the iron corrosion process. The consumption of hydrogen is one of

326

several proposed microbial-influenced corrosion mechanisms attributed to SRB.7, 47 The

327

prevalence of Desulfovibrio-like OTUs in the DWDS environment and their implication in

328

corrosion in other environments suggests that attempts to limit their growth, such as eliminating

329

the supply of sulfate, may be beneficial. Nevertheless, more work is needed to elucidate the role

330

of Desulfovibrio spp. in iron water main degradation, as the mere association of Desulfovibrio

331

spp. with corrosion tubercles is not conclusive evidence of their role in the corrosion process.7, 48

332

There have been numerous reports of the occurrence of Mycobacteria in water

333

distribution system biofilms.49-56 Our study extends these findings by showing that

334

Mycobacteria-like OTUs were prominent in all biofilms growing on the surface of water mains

335

within a chloraminated DWDS, regardless of main age, main type, and main location.

336

Mycobacteria spp. have a variety of characteristics that afford them a competitive advantage in a

337

chloraminated water distribution system, including increased resistance to disinfectants in

338

comparison to many other bacteria,57 the ability to form biofilms, and their ability to survive in

339

nutrient-poor conditions.58-59 Furthermore, there is recent experimental evidence from a


Page 14 of 33

Page 15 of 33


340

simulated distribution system study to suggest that monochloramine, rather than free chlorine,

341

selects for Mycobacteria over other genera.60 From this perspective, the abundance of

342

Mycobacteria may actually be a useful indicator of a stable chloramine residual, but more

343

research is needed to determine the prevalence of these organisms in full-scale distribution

344

systems with a different disinfectant (e.g., free chlorine) or without a residual disinfectant.

345

In contrast, the presence of Mycobacteria spp. within DWDS could be considered

346

undesirable due to the ability of some Mycobacteria spp., specifically the Mycobacterium avium

347

complex (MAC), to cause infection in immunocompromised persons. By profiling the gene

348

encoding a 65-kilodalton heat-shock protein (hsp65), we determined that no MAC-like OTUs

349

were present in the DWDS. The two dominant Mycobacterium-like OTUs from all sampling

350

dates and mains were M. frederiksbergense (83.3%) and M. aurum (11.4%). Although M.

351

frederiksbergense has been isolated in association with a catheter-related infection61 and two

352

subcutaneous injection-related infections,62 this Mycobacterium sp. is not generally recognized

353

as a pathogen. Similarly, M. aurum is generally considered to be nonpathogenic. Although M.

354

aurum was previously identified in association with two cases of infection,63-64 the accuracy of

355

these identifications have been questioned following the discovery that American Type Culture

356

Collection M. aurum strains were misannotated.65 Rather, the infection-associated bacterium

357

probably belonged to the opportunistic M. neoaurum-“M. lacticola” group.65 A few known

358

opportunistic Mycobacteria spp. (M. haemophilum, M. abscessus, M. xenopi) were detected in

359

the DWDS, however, they were rare members of the mycobacterial communities (0.013-11%, 0-

360

0.11%, 0-0.15%, respectively), with M. abscessus identified in only one sample, and M. xenopi

361

detected in 6 samples. Thus, the risk of direct exposure to harmful Mycobacteria via tap water

362

from shedding of water main biofilms appears to be minimal. Nevertheless, additional research is



363

needed to clarify this issue because there is the potential for harmful Mycobacteria spp. to

364

multiply in hot water systems as the optimum growth temperature for many Mycobacteria is in

365

the range of 28 to 38.5°C.66

366

Despite differences in main type, age, and location within the distribution system, water

367

main biofilm communities on interior surfaces were surprisingly similar, with OTUs assigned to

368

only 17 different genera comprising the majority of sequences for these samples. Observed inter-

369

and intra-main variation in composition was due primarily to differences in the relative

370

abundance of community members rather than to differences in the specific community members

371

present, which has been previously observed.67 The similarity of all of the surface biofilm

372

communities throughout the DWDS is consistent with the relatively stable water quality

373

conditions in the system.

374

Highly corroded water mains were capable of supporting higher densities of bacteria

375

overall, in comparison to non-tuberculated and cement-lined mains. Corrosion tubercles

376

potentially provide niches where bacteria can be sheltered from the bulk water flow as well as

377

increased surface area for biofilm growth.68 The presence of corrosion deposits may additionally

378

shield bacteria from disinfectant residuals by exerting a disinfectant demand.3, 14-15 Furthermore,

379

nutrients have been shown to concentrate in iron tubercles69-70 and in corrosion scales,71 where

380

they are available for bacterial growth. Consequently, reducing the presence of corrosion

381

deposits within the water mains, either by decreasing corrosion rates or using corrosion resistant

382

materials (e.g., cement-lined iron or plastic) may be effective at limiting bacterial growth.15

383

Although corroded water mains generally supported more biomass, there were large variations in

384

bacterial densities in a given main, especially for the heavily tuberculated mains. Patchy biofilm

385

coverage in drinking water distribution systems is consistent with previous studies17, 56, 72-74 and


Page 16 of 33

Page 17 of 33


386

suggests that the suitability of biofilm growth conditions in water mains varies substantially over

387

small distances.

388

In conclusion, this research provides novel insights into the composition of biofilms in a

389

full-scale chloraminated drinking water distribution system, which is critical for assessing the

390

risks to public health and critical water supply infrastructure. The predominance of

391

Mycobacteria-like OTUs on water main surfaces and Desulfovibrio-like OTUs underneath

392

tubercles has implications for the management and assessment of water distribution systems.

393

Although it is impractical to completely eradicate bacteria from distribution systems, it may be

394

beneficial to instead focus on methods to manipulate the bacterial community composition for a

395

desirable result. For example, the association of sulfate-reducing Desulfovibrio spp. with

396

corrosion tubercles suggests that corrosion prevention efforts should include approaches for

397

limiting growth of sulfate-reducing bacteria, such as decreasing sulfate concentrations in the

398

finished water. In addition, non-pathogenic Mycobacteria spp. might be a viable candidate for

399

the “pro-biotic” distribution system strategy described by Wang et al.75 Finally, quantification of

400

Mycobacteria spp. in DWDS biofilms potentially could be used to assess the long-term stability

401

of the chloramine residual.

402

ACKNOWLEDGEMENTS

403

Financial support for this work was provided by the Board of Water Commissioners of

404

the City of Saint Paul. We thank David Schuler, Jim Bode, Kou Vang, Richard Hibbard, Renee

405

Huset, and CheFei Chen for helping coordinate this study and for providing access to the water

406

mains, water quality data, and other necessary information.

407

SUPPORTING INFORMATION



408

The Supporting Information gives additional information on the water quality from the

409

DWDS during this study (Table S1), the reference database used to analyze hsp65 (Table S2),

410

the complete list of hsp65 sequences detected in this study (Table S3), a map of the sample

411

locations used in this study (Figure S1), and a non-metric multidimensional analysis plot of

412

weighted unifrac distances between communities (Figure S2). This information is available free

413

of charge via the Internet at http://pubs.acs.org/.

414

REFERENCES

415 416 417 418

1. Water Infrastructure: Comprehensive Asset Management Has Potential to Help Utilities Better Identify Needs and Plan Future Investments; Highlights of GAO-04-461; United States General Accounting Office: Washington, DC, 2004; www.gao.gov/cgibin/getrpt?GAO-04-461.

419 420 421

2. Van der Kooij D.; Veenendaal H. R.; Baars-Lorist C.; Van der Klift D. W.; Drost,Y. C. Biofilm formation on surfaces of glass and teflon exposed to treated water. Water Res. 1995, 7, 1655-1662.

422 423

3. LeChevallier, M. W.; Babcock, T. M.; Lee, R. G. Examination and characterization of distribution system biofilms. Appl. Environ. Microbiol. 1987, 53 (12), 2714-2724.

424 425

4. Flemming, H.-C. Biofilms in water systems –cases, causes, and countermeasures. Appl. Microbiol. Biotechnol. 2002, 59, 629-640.

426 427 428 429 430

5. Deteriorating buried infrastructure management challenges and strategies; United States Environmental Protection Agency (USEPA); Office of Water (4601M); Office of Ground Water and Drinking Water: Distribution System Issue Paper. Washington DC, 2002; http://water.epa.gov/lawsregs/rulesregs/sdwa/tcr/upload/2007_09_04_disinfection_tcr_white paper_tcr_infrastructure.pdf.

431 432

6. Lytle, D. A.; Gerke, T. L.; Maynard, J. B. Effect of bacterial sulfate reduction on ironcorrosion scales. J. Am. Water Works Ass. 2005, 97 (10), 109-120.

433 434

7. Little, B.; Lee, J. Microbiologically Induced Corrosion. John Wiley and Sons, Inc.: Hoboken, New Jersey, 2007.

435 436

8. Cunliffe, D. A. Bacterial nitrification in chloraminated water supplies. Appl. Environ. Microbiol. 1991, 57 (11), 3399-3402.

437 438 439

9. Regan, J. M.; Harrington, G. W.; Baribeau, H.; De Leon, R.; Noguera, D. R. Diversity of nitrifying bacteria in full-scale chloraminated distribution systems. Water Res. 2003, 37 (1), 197-205.


Page 18 of 33

Page 19 of 33


440 441

10. Sathasivan, A.; Fisher, I.; Kastl, G. Simple method for quantifying microbiologically assisted chloramine decay in drinking water. Environ. Sci. Technol. 2005, 39 (14), 5406-5413.

442 443

11. Wingender, J.; Flemming, H-C. Biofilms in drinking water and their role as reservoir for pathogens. Int. J. Hyg. Environ. Heal. 2011, 214 (6), 417-423.

444 445 446 447

12. Buswell, C. M.; Herlihy, Y. M.; Lawrence, L. M.; McGuiggan, J. T. M.; Marsh, P. D., Keevil, C. W.; Leach, S. A. Extended survival and persistence of Campylobacter spp. in water and aquatic biofilms and their detection by immunofluorescent-antibody and -rRNA staining. Appl. Environ. Microbiol. 1998, 64, 733-741.

448 449

13. Camper, A. K. Factors Limiting Microbial Growth in Distribution Systems: Laboratory and Pilot-Scale Experiments. AWWA Research Foundation: Denver, CO, 1996.

450 451

14. LeChevallier, M. W.; Lowry, C. D.; Lee, R. G. Disinfecting biofilms in a model distribution system. J. Am. Water Works Ass. 1990, 82 (7), 87-99.

452 453 454

15. LeChevallier, M. W.; Lowry, C. D.; Lee, R. G.; Gibbon, D. L. Examining the relationship between iron corrosion and the disinfection of biofilm bacteria. J. Am. Water Works Ass. 1993, 85 (7), 111-123.

455 456 457

16. Martiny, A. C.; Nielsen, A. T.; Arvin, E.; Molin, S.; Albrechtsen, H. In situ examination of microbial populations in a model drinking water distribution system. Water Sci. Technol.: Water Suppl. 2002, 2 (3), 283-288.

458 459 460

17. Martiny A.C.; Jorgensen T. M.; Albrechtsen H-J.; Arvin, E.; Molin, S. Long-term succession of structure and diversity of a biofilm formed in a model drinking water distribution system. Appl. Environ. Microbiol. 2003, 69, 6899-6907.

461 462 463

18. 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), 268-276.

464 465 466 467 468 469 470

19. Regan, J. M.; Harrington, G. W.; Noguera, D. R. Ammonia- and nitrite-oxidizing bacterial communities in a pilot-scale chloraminated drinking water distribution system. Appl. Environ. Microbiol. 2002, 68 (1), 73-81.

471 472 473

21. Kelly, J. J.; Minalt, N.; Culotti, A.; Pryor, M.; Packman, A. Temporal variations in the abundance and composition of biofilm communities colonizing drinking water distribution pipes. PLoS ONE 2014, 9 (5): e98542.

474 475

22. Senna, S. G.; Battilana, J.; Costa, J. C.; Silva, M. G.; Duarte, R. S.; Fonseca, L. S.; Suffys, P. N.; Bogo, M. R. Sequencing of hsp65 gene for identification of Mycobacterium species

20. Moritz, M. M.; Flemming, H.-C.; Wingender, J. Integration of Pseudomonas aeruginosa and Legionella pneumophila in drinking water biofilms grown on domestic plumbing materials. Int. J. Hyg. Envir. Heal. 2010, 213 (3), 190-197.



476 477

isolated from environmental and clinical sources in Rio de Janeiro, Brazil. J. Clin. Microbiol. 2008, 46 (11), 3822-3825.

478 479 480

23. Ringuet, H.; Akoua-Koffi, C.; Honore, S.; Varnerot, A.; Vincent, V.; Berche, P.; Gaillard, J. L.; Pierre-Audigier, C. Hsp65 sequencing for identification of rapidly growing Mycobacteria. J. Clin. Microbiol. 1999, 37 (3), 852-857.

481 482 483

24. van der Wielen, P. W. J. J.; Heijnen, L.; van der Kooij, D. Pyrosequence analysis of the hsp65 genes of nontuberculous Mycobacterium communities in unchlorinated drinking water in the Netherlands. Appl. Environ. Microbiol. 2013, 79 (19), 6160-6166.

484 485

25. Clesceri, L., Greenberg, A., Easton, A., Eds. Standard Methods for the Examination of Water and Wastewater, 20th, ed.; American Pubic Health Association, Washington D.C., 1998.

486 487

26. Chloramine (Mono). Indophenol Method. DOC316.53.01014; Method 10172; Hach Company, 2014.

488 489 490

27. Lane, D. J. 16S/23S rRNA sequencing. In Nucleic Acid Techniques in Bacterial Systematics; Stackebrandt, E., Goodfellow, M, Eds. John Wiley & Sons, Ltd.:West Sussex, United Kingdom 1991; 115-175.

491 492 493

28. Muyzer G.; de Waal, E. C.; Uitterlinden, A. G. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 1993, 59 (3), 695-700.

494 495 496 497

29. Bartram, A. K.; Lynch, M. D. J.; Stearns, J. C.; Moreno-Hagelsieb, G.; Neufeld, J. D. Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end Illumina reads. Appl. Environ. Microbiol. 2011, 77 (11), 3846-3852.

498 499 500

30. LaPara, T. M.; Nakatsu, C. H.; Pantea, L.; Alleman, J. E. Phylogenetic analysis of bacterial communities in mesophilic and thermophilic bioreactors treating pharmaceutical wastewater. Appl. Environ. Microbiol. 2000, 66 (7), 3951-3959.

501 502 503

31. Telenti, A.; Marcheis, F.; Balz, M.; Bally, F.; Böttger, E. C.; Bodmer, T. Rapid identification of mycobacteria to the species level by polymerase chain reaction and restriction enzyme analysis. J. Clin. Microbiol. 1993, 33, 149-153.

504 505 506

32. LaPara, T. M.; Burch, T. R.; McNamara, P. J.; Tan, D. T.; Yan, M.; Eichmiller, J. J. Tertiarytreated municipal wastewater is a significant point source of antibiotic resistance genes into Duluth-Superior harbor. Environ. Sci. Technol., 2011, 45 (22), 9543-9549.

507 508 509 510 511

33. 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, platformindependent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 2009, 75 (23), 7537-7541.


Page 20 of 33

Page 21 of 33


512 513

34. Edgar, R. C.; Haas, B. J.; Clemente, J. C.; Quince, C.; Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011, 27 (16), 2194-2200.

514 515 516 517

35. Cole, J. R.; Wang, Q.; Cardenas, E.; Fish, J.; Chai, B.; Farris, R. J.; Kulam-Syed-Mohideen, A. S.; McGarrell, D. M.; Marsh, T.; Garrity, G. M.; Tiedje, J. M. The Ribosomal Database Project: Improved alignments and new tools for rRNA analysis. Nucleic Acids Res. 2009, 37, D141-D145.

518 519

36. Lozupone, C.; Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 2005, 71 (12), 8228-8235.

520 521 522 523 524 525

37. Vaerewijck, M.; Huys, G.; Palomino, J. C.; Swings, J.; Portaels, F. Mycobacteria in drinking water distribution systems: Ecology and significance for human health. FEMS Microbiol. Rev. 2005, 29 (5), 911-934. 38. Javaherdashti, R. Impact of sulphate-reducing bacteria on the performance of engineering materials. Appl. Microbiol. Biotechnol. 2011, 91 (6), 1507-1517.

526 527

39. Bunker, H. J. Microbiological anaerobic corrosion. J. Chem. Technol. Biotechnol. 1940, 59, 412-414.

528 529

40. Butlin, K. R.; Adams, M. E.; Thomas, M. The isolation and cultivation of sulphate-reducing bacteria. J. Gen. Microbiol. 1949, 3 (1), 46-59.

530 531 532

41. Tuovinen, O. H.; Button, K. S.; Vuorinen, A.; Mair, M.; Yut, L. A.; Carlson, L. Bacterial, chemical, and mineralogical characteristics of tubercles in distribution pipelines. J. Am. Water Works Assoc. 1980, 72 (11), 626-635.

533 534

42. Lewis, R. F. Control of sulfate-reducing bacteria. J. Am. Water Works Assoc. 1965, 57 (8), 1011-1015.

535 536 537

43. Emde, K. M. E.; Smith, D. W.; Facey, R. Initial investigation of microbially influenced corrosion (MIC) in a low temperature water distribution system. Water Res. 1992, 26 (2), 169-175.

538 539

44. Seth, A. D.; Edyvean, R. G. J. The function of sulfate-reducing bacteria in corrosion of potable water mains. Int. Biodeter. Biodegr. 2006, 58 (3-4), 108-111.

540 541 542

45. Fareleira, P.; Santos, B. S.; Antonio, C.; Moradas-Ferreira, P.; LeGall, J.; Xavier, A. V.; Santos, H. Response of a strict anaerobe to oxygen: Survival strategies in Desulfovibrio gigas. Microbiology, 2003, 149 (6), 1513-1522.

543 544 545

46. Sarin, R.; Sharma, Y. D. Thioredoxin system in obligate anaerobe Desulfovibrio desulfuricans: Identification and characterization of a novel thioredoxin 2. Gene 2006, 376 (1): 107-115.

546 547

47. Kakooei, S.; Ismail, M. C.; Ariwahjoedi, B. Mechanisms of microbiologically influenced corrosion : A review. World Appl. Sci. Journal. 2012, 17 (4), 524-531.



548 549 550

48. Little, B. J.; Wagner, P. A.; Hart, K. R.; Ray, R. I. Spatial relationships between bacteria and localized corrosion. The National Association of Corrosion Engineers International Annual Conference and Exposition: Corrosion 96, Paper No. 278, 1996.

551 552 553

49. Dailloux, M.; Albert, M.; Laurain, C.; Andolfatto, S.; Lozniewski, A.; Hartemann, P.; Mathieu, L. Mycobacterium xenopi and drinking water biofilms. Appl. Environ. Microbiol. 2003, 69, 6946-6948.

554 555 556

50. Le Dantec, C.; Duguet, J.-P.; Montiel, A.; Dumoutier, N.; Dubrou, S.; Vincent, V. Chlorine disinfection of atypical mycobacteria isolated from a water distribution system. Appl. Environ. Microbiol. 2002, 68, 1025-1032.

557 558 559

51. Le Dantec, C.; Duguet, J.-P.; Montiel, A.; Dumoutier, N.; Dubrou, S.; Vincent, V. Occurrence of mycobacteria in water treatment lines and in water distribution systems. Appl. Environ. Microbiol. 2002, 68, 5318-5325.

560 561 562

52. Falkinham, J. O., III; Norton, C. D.; LeChevalier, M. W. Factors influencing numbers of Mycobacterium avium, Mycobacterium intracellulare, and other mycobacteria in drinking water distribution systems. Appl. Environ. Microbiol. 2001, 67, 1225-1231.

563 564

53. Szewzyk, U.; Szewzyk, R.; Manz, W.; Schleifer, K.-H. Microbiological safety of drinking water. Annu. Rev. Microbiol. 2000, 54, 81–127.

565 566 567

54. September, S. M.; Brözel, V. S.; Venter, S. N.; Bro, V. S. Diversity of nontuberculoid Mycobacterium species in biofilms of urban and semiurban drinking water distribution systems. Appl. Environ. Microbiol. 2004, 70 (12), 7571–73.

568 569 570

55. Torvinen E.; Suomalainen, S.; Lehtola, M. J.; Ilkka, T.; Zacheus, O.; Paulin, L.; Katila, M.L.; Martikainen, P. J.; Miettinen, I. T. Mycobacteria in water and loose deposits of drinking water distribution systems in Finland. Appl. Environ. Microbiol. 2004, 70, 1973–1981.

571 572 573 574

56. Wang, H.; Edwards, M.; Falkinham, J. O.; Pruden, A. Molecular survey of the occurrence of Legionella spp., Mycobacterium spp., Pseudomonas aeruginosa, and amoeba hosts in two chloraminated drinking water distribution systems. Appl. Environ. Microbiol. 2012, 78 (17), 6285-6294.

575 576 577

57. Lin, W.; Yu, Z.; Zhang, H.; Thompson, I. P. Diversity and dynamics of microbial communities at each step of treatment plant for potable water generation. Water Res. 2014, 52, 218-230.

578 579 580

58. Hall-Stoodley, L.; Keevil, C. W.; Lappin-Scott, H. Mycobacterium fortuitum and Mycobacterium chelonae biofilm formation under high and low nutrient conditions. J. Appl. Microbiol. Symposium Supplement, 1999, 85, 60S–69S.

581 582 583

59. Primm, T. P.; Lucero, C. A.; Falkinham III, J. O. Health impacts of environmental mycobacteria. Clin. Microbiol. Rev., 2004, 17(1), 98-106.


Page 22 of 33

Page 23 of 33


584 585 586 587 588 589 590

60. Gomez-Alvarez, V.; Revetta, R.; Santo Domingo, J.W. Metagenomic analyses of drinking water receiving different disinfection treatments. Appl. Environ. Microbiol. 2012, 78 (17), 6095-6102.

591 592 593

62. Regnier, S.; Cambau, E.; Meningaud, J. P.; Guihot, A.; Deforges, L.; Carbonne, A.; Bricaire, F.; Caumes, E. Clinical management of rapidly growing mycobacterial cutaneous infections in patients after mesotherapy. Clin. Infect. Dis. 2009, 49, 1358-1364.

594 595 596

63. Esteban, J.; Fernandez-Roblas, R.; Roman, A., Molleja, A.; Jimenez, M. S.; Soriano, F. Catheter-related bacteremia due to Mycobacterium aurum in an immunocompromised host. Clin. Infect. Dis. 1998, 26, 496-497.

597 598

64. Koranyi, K. I.; Ranalli, M. A. Mycobacterium aurum bacteremia in an immunocompromised child. Pediatr. Infect. Dis. J. 2003, 22, 1108-1109.

599 600 601

65. Simmon K. E.; Low, Y. Y.; Brown-Elliott, B. A.; Wallace, R. J. Jr; Petti, C. A. Phylogenetic analysis of Mycobacterium aurum and Mycobacterium neoaurum with redescription of M. aurum culture collection strains. Int. J. System. Evol. Microbiol. 2009, 59 (6), 1371-1375.

602 603 604 605

66. Covert, T. C.; Reyes, A. L.; Rodgers, M. R.; Dufour, A. P. The effect of temperature on the growth of Mycobacterium avium complex (MAC) organisms. Presented at American Society of Microbiology 101st General Meeting, Orlando, FL, May 20-24, 2001. USEPA. http://cfpub.epa.gov/ordpubs/nerlpubs/recordisplay.cfm?deid=60923

606 607 608

67. Holinger, E. P.; Ross, K. A.; Robertson, C. E.; Stevens, M. J.; Harris, J. K.; Pace, N. R. Molecular analysis of point-of-use municipal drinking water microbiology. Water Res. 2014, 49 (1), 225–35.

609 610 611

68. LeChevallier, M. W.; Shaw, N. J.; Smith, D. B. Factors limiting microbial growth in distribution systems: Full-scale experiments. American Water Works Association Research Foundation: USA, 1996.

612 613 614

69. Allen, M. J.; Geldreich, E. E. Distribution line sediments and bacterial regrowth. In Proceedings of American Water Works Association Water Quality Technology Conference, Dec 1977.

615 616 617

70. Victoreen, H. T. The role of rust in coliform regrowth. In Proceedings of the American Water Works Association Water Quality Technology Conference. American Water Works Association, Denver, CO, 1984; pp. 253-264.

618 619 620

71. Camper, A. K.; Brastrup, K.; Sandvig, A.; Clement, J.; Spencer, C.; Capuzzi, A. J. Impact of distribution system materials on bacterial regrowth. J. Am. Water Works Assoc. 2003, 95 (7), 107-121.

61. Senozan, E. A.; Adams, D. J.; Giomanco, N. M.; Warwick, A. B.; Eberly, M. D. A catheterrelated blood stream infection with Mycobacterium frederiksbergense in an immunocompromised child. Pediatr. Infect. Dis. J. 2015, 34(4), 445-447.



621 622

72. Wingender, J.; Flemming, H-C. Contamination potential of drinking water distribution network biofilms. Water Sci. Technol. 2004, 49 (11-12), 277-286.

623 624

73. Percival, S. L.; Knapp, J. S.; Edyvean, R. G. J.; Wales, D. S. Biofilms, mains water and stainless steel. Water Res. 1998, 32 (7), 2187-2201.

625 626 627

74. Van der Kooij, D.; Veenendaal, H. R.; Baars-Lorist, C.; Van der Klift, D. W.; Drost, Y. C. Biofilm formation on surfaces of glass and teflon exposed to treated water. Water Res. 1995, 7, 1655-1662.

628 629 630

75. Wang, H., Edwards, M. A.; Falkinham, J. O.; Pruden, A. Probiotic approach to pathogen control in premise plumbing systems? A review. Environ. Sci. Technol. 2013, 47 (18), 10117-10128.


Page 24 of 33

Page 25 of 33

631 632


Table 1. Description of the water main samples collected in this study and the associated estimated water ages at each sampling location. Main

Sampling Date

Main Age (years)

Main Material

Water Age (hrs)

1 2 3 4 5 6 7 8 9 10

4/17/13 5/16/13 6/27/13 8/19/13 8/19/13 9/4/13 9/23/13 6/27/13 6/20/13 7/25/13

127 90 127 129 129 64 86 48 51 53

Unlined Cast-iron Unlined Cast-iron Unlined Cast-iron Unlined Cast-iron Unlined Cast-iron Unlined Cast-iron Unlined Cast-iron Unlined Cast-iron Cement-lined cast-iron Cement-lined cast-iron

19 20 21 60 60 70 72 16 22 88

633 634



635 636 637 638 639 640 641

Page 26 of 33

Table 2. The number of observed OTUs, the number of predicted OTUs (ACE estimator), and Shannon index for bacterial communities obtained from full-scale water mains via Illumina MiSeq analysis of PCR-amplified 16S rRNA gene fragments. Sequence libraries consisted of 42,445 sequences per profile after trimming randomly subsampling to normalize the number of sequences. All values represent the arithmetic mean (± one standard deviation) of replicate communities obtained from each main (n = 7 for Main 1; n = 3 for all other Mains). Tuberculated Surface

Non-tuberculated Cement-Lined Under Tubercle

Main 1 2 3 4 5 6 7 8 9 10 3 4 5 6 7

Observed OTUs 1888 ± 405 1915 ± 186 1989 ± 148 1374 ± 52 1774 ± 98 1512 ± 45 1773 ± 208 2692 ± 296 2233 ± 110 1906 ± 52 1706 ± 51 1492 ± 78 1294 ± 380 1588 ± 14 967 ± 65

ACE Estimator 11767 ± 3102 12300 ± 347 12315 ± 1830 8005 ± 765 8205 ± 1452 11197 ± 2543 7556 ± 2332 6518 ± 1920 9406 ± 1983 10567 ± 285 9532 ± 584 7894 ± 1142 6673 ± 3778 8523 ± 1448 8229 ± 1720

642 643


Shannon Index 2.4 ± 0.5 2.2 ± 0.3 1.9 ± 0.5 2.0 ± 0.3 3.5 ± 0.0 2.9 ± 0.3 2.8 ± 0.5 3.3 ± 0.7 2.3 ± 0.1 1.7 ± 0.2 2.0 ± 0.6 1.8 ± 0.5 2.3 ± 0.5 2.8 ± 0.1 1.6 ± 0.3

Page 27 of 33

644 645 646 647


Table 3. The percent abundances (arithmetic mean ± standard deviation) of Mycobacterium species represented in each water main type. Only abundant (>1% of a single sample) species are reported here. Illumina Miseq sequencing of the hsp65 gene was used to give varying amounts of sequences per sample (ranging from 1,365 to 29,972 sequences per sample). Percent Abundance by Sample Type (Mean ± standard deviation) Mycobacterium sp.

M. frederiksbergense M. aurum M. haemophilum M. lentiflavum M. psychrotolerans M. holsaticum M. nebraskense

Tuberculated Surface (n=11) 86.0 ± 15.9 10.6 ± 15.2 1.0 ± 1.9 0.2 ± 0.8 0.009 ±0.02 0.007 ± 0.01 0.01 ± 0.02

Cement-Lined (n=2) 98.9 ± 1.1 0.1 ± 0.1 0.7 ± 0.9 0±0 0±0 0±0 0.02 ± 0.03

NonTuberculated (n=1) 78.9 1.7 11.3 0 0 0.5 0

648 649


Under Tubercle (n=5) 80.9 ± 13.7 0.9 ± 0.7 1.1 ± 1.2 4.2 ± 3.3 3.9 ± 5.1 2.7 ± 5.3 1.2 ± 1.8


650

Figure Captions

651

Fig. 1. Photographs of representative water mains analyzed in this study. (A) Tuberculated

652

unlined cast-iron, (B) Non-tuberculated unlined cast-iron, and (C) Cement-lined cast-iron.

653

Fig. 2. Total biomass of main community samples as indicated by quantitative real-time PCR of

654

the 16S rRNA gene per cm2 of scraped biofilm. Abbreviations refer to sample type and main

655

type: TS-Tuberculated surface, UT-Under tubercle, NT- Non-tuberculated, CL-Cement lined.

656

Fig. 3. Bacterial community profiles from two tuberculated cast-iron water mains as determined

657

by Illumina MiSeq analysis of PCR-amplified 16S rRNA gene fragments. Profiles reveal

658

differences in bacterial community composition within a single water main. Main 2 replicates

659

(A1, A2, A3) were obtained from the same sample/DNA extract, but were amplified by PCR and

660

sequenced separately.

661

Fig. 4. Bacterial community profiles of the 18 most abundant genera represented in (A) main

662

surface samples, and (B) under tubercles samples as determined by Illumina MiSeq analysis of

663

PCR-amplified 16S rRNA gene fragments. Abundant genera are those that comprised greater

664

than 0.5% of total sequences for all samples combined (2,164,695 total sequences). Genera that

665

represented less than 0.5% of total sequences are grouped in “Other.” Distribution profiles

666

represent the arithmetic mean of triplicate communities obtained from each main, except for

667

Main 1 (n = 7). Abbreviations refer to the type of water main: TS = Tuberculated surface, UT =

668

Under tubercle, NT = Non-tuberculated, CL = Cement lined.

669


Page 28 of 33

Page 29 of 33



Environmental Science & Technology Page 30 of 33


Page 31 of 33





Page 32 of 33

PageEnvironmental 33 of 33 Science & Technology


Sulfate Reducing Bacteria and Mycobacteria Dominate the Biofilm

Recommend Documents