Mycobacteria in Municipal Wastewater ... - ACS Publications

Subscriber access provided by University of Newcastle, Australia

Article

Mycobacteria in municipal wastewater treatment and reuse: Microbial diversity for screening the occurrence of clinicallyand environmentally-relevant species in arid regions Yamrot M. Amha, Muhammad Zohaib Anwar, Rajkumari Kumaraswamy, Andreas Henschel, and Farrukh Ahmad Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05580 • Publication Date (Web): 31 Jan 2017 Downloaded from http://pubs.acs.org on February 2, 2017

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 24

Environmental Science & Technology

Mycobacteria in municipal wastewater treatment and reuse: Microbial diversity for screening the occurrence of clinically- and environmentally-relevant species in arid regions Yamrot M. Amha†, M. Zohaib Anwar‡, Rajkumari Kumaraswamy†, Andreas Henschel‡, Farrukh Ahmad†*

†

Institute Center for Water and Environment (iWATER), Masdar Institute of Science and Technology,

PO Box 54224, Abu Dhabi, UAE

‡

Institute Center for Smart and Sustainable Systems (iSmart), Masdar Institute of Science and

Technology, PO Box 54224, Abu Dhabi, UAE

*Corresponding author (Farrukh Ahmad) Phone: +971 2 810 9114; fax: +971 2 810 9901; Email: [email protected]

Keywords: nontuberculous mycobacteria (NTM); pyrosequencing; 16S rRNA gene analysis; water reuse; wastewater treatment.

1

ACS Paragon Plus Environment


1

ABSTRACT

2

With accumulating evidence of pulmonary infection via aerosolized nontuberculous mycobacteria

3

(NTM), it is important to characterize their persistence in wastewater treatment, especially in arid

4

regions where treated municipal wastewater is extensively reused. To achieve this goal, microbial

5

diversity of the genus Mycobacterium was screened for clinically- and environmentally-relevant

6

species using pyrosequencing. Analysis of the post-disinfected treated wastewater showed

7

presence of clinically-relevant slow-growers like M. kansasii, M. szulgai, M. gordonae, and M.

8

asiaticum; however, in these samples, rapid growers like M. mageritense occurred at much higher

9

relative abundance. M. asiaticum and M. mageritense have been isolated in pulmonary samples

10

from NTM-infected patients in the region. Diversity analysis along the treatment train found

11

environmentally-relevant organisms like M. poriferae and M. insubricum to increase in relative

12

abundance across the chlorine disinfection step. A comparison to qPCR results across the chlorine

13

disinfection step saw no significant change in slow grower counts at CT disinfection values ≤90

14

mg•min/L; only an increase to 180 mg•min/L in late May brought slow growers to below detection

15

levels. The study confirms the occurrence of clinically- and environmentally-relevant mycobacteria

16

in treated municipal wastewater, suggesting the need for vigilant monitoring of treated wastewater

17

quality and disinfection effectiveness prior to reuse.

Page 2 of 24

18

2


Page 3 of 24


19

INTRODUCTION

20

As the demand for freshwater grows concomitantly with rising water scarcity, countries around the

21

globe are turning increasingly towards treated municipal wastewater as a valuable resource1.

22

Nowhere is this more true than in countries located in arid regions, where fresh surface water

23

resources are limited, and groundwater recharge through natural precipitation is minimal2.

24

Nevertheless, safe reutilization of treated municipal wastewater demands adequate assessment of

25

the potential public health and environmental risks arising from any residual microorganisms.

26

The genus Mycobacterium consists of over 150 species3 of which at least two, M. tuberculosis and M.

27

leprae, are considered to be obligate human pathogens, while most of others have been found to be

28

opportunistic organisms that cause disease in human and animal receptors when conditions are

29

optimal4. Mycobacteria are generally classified into two distinct groups, the genetically-related M.

30

tuberculosis Complex (MTC) organisms and nontuberculous mycobacteria (NTM), the latter also

31

known as environmental mycobacteria5 because of their ubiquitous presence in soil and water6. In

32

the lab, NTM are operationally classified into slow- and fast-growers, primarily based on their

33

growth rate (usually 7-10 days and >14 days to mature growth for rapid- and slow-growers,

34

respectively)7. Disinfection methods in municipal wastewater treatment, such as chlorination and

35

UV oxidation, have demonstrated variable degrees of success in the deactivation of NTM8, 9.

36

Globally and within our arid Arabian/Persian Gulf region10, infections from NTM are on the rise and

37

these infections have been shown to exhibit geographic diversity11. NTM species have been linked

38

to diseases such as pulmonary infection and lymphadenitis, and can affect both

39

immunocompromised12 and immunocompetent13 individuals. Diseases caused by NTM are believed

40

to be acquired mainly through environmental exposure13, 14. In 2007, the American Thoracic Society

41

identified and recommended treatment guidelines for 20 different clinically-relevant (i.e. isolated

42

from infected humans) species of NTM15.

43

In recent years, there has been increasing evidence that water may be the medium by which NTM

44

infect humans9. The relatively recent discovery of clinically-relevant NTM in potable water

45

distribution networks16 raised a new alarm, prompting the addition of M. avium to the USEPA

46

drinking water contaminant candidate list17. The existence of these NTM in potable water supply

47

pointed to their resistance to disinfection9 because of a number of reasons including (a) a thick, lipid-

48

rich, hydrophobic cell wall3, and (b) their potential to aggregate and form biofilms8, 18. Since the

49

NTM discovery in water supply networks, NTM infections are widely speculated to be acquired via

50

the inhalation of aerosols, such as entrained water droplets in air19. There is some evidence to

3



Page 4 of 24

51

support this claim, such as the discovery of NTM in shower aerosols from homes of patients with

52

NTM-based pulmonary disease20, and in the headspace of public hot tubs and therapy pools13.

53

Although they are oligotrophs21, mycobacteria have been found at higher levels, both in terms of

54

occurrence and diversity, in treated wastewater than in surface water reservoirs or in drinking

55

water22, 23. Hence, the occurrence of NTM in reclaimed water and the growing use of such water in

56

landscape irrigation, agriculture, and cooling tower applications that generate aerosols24, poses a

57

potential threat to public health and the environment.

58

New molecular methods such as next generation sequencing (NGS) have made it possible to detect

59

microorganisms present at low concentrations, which would have otherwise gone undetected with

60

conventional microbiological techniques. Pyrosequencing is one NGS method that has been widely

61

applied to study microbial community profiles in various environments. Using pyrosequencing for

62

genus-level classification, researchers have identified mycobacteria as one of the dominant potential

63

pathogen-containing genera in the urban watershed and in treated wastewater25-27. While these

64

efforts have aided in understanding the quality of treated wastewater, an effective approach that

65

enables screening identification to a species-level taxonomic resolution is needed in order to

66

evaluate health risk accurately15. In particular, for a diverse genus such as Mycobacterium, it is

67

crucial to migrate towards rapid, high-resolution classification28 to predict health outcomes resulting

68

from exposure. A recent study analyzing pairwise sequence identities devised a method to classify

69

16S rRNA gene sequences with a high concordance rate in order to identify a broad range of

70

clinically-relevant bacteria29. An earlier study focusing on mycobacteria had already pointed out the

71

suitability of the 16S rRNA gene V2 region alone in distinguishing between species30.

72

The motivation behind this study was to lay the foundation for assessing human exposure to

73

clinically- and environmentally-relevant NTM in municipal wastewater treatment and reuse. Hence,

74

as a preliminary step for our centralized municipal wastewater treatment process, we screened

75

mycobacterial diversity by employing a 16S rRNA gene pyrosequencing method, and quantitated

76

slow- and fast-growing mycobacteria using qPCR in order to test the following two hypotheses: (a)

77

Many mycobacteria present in treated municipal wastewater are of clinical and/or environmental

78

relevance, especially to the region; and (b) the microbial diversity and numbers of clinically- and

79

environmentally-relevant mycobacteria are affected across the disinfection stage.

80 81

4


Page 5 of 24


82

MATERIALS AND METHODS

83

Site description and sample collection

84

Samples were collected at the central activated sludge municipal wastewater treatment plant

85

(WWTP) located in Abu Dhabi, UAE. The WWTP has a design capacity of 260,000 m3/day and

86

employs chlorine disinfection. Currently, the treated wastewater effluent is used only for landscape

87

irrigation. Samples were taken from three stages of the treatment plant, pre-treated (PT), pre-

88

chlorinated (PC), and post-disinfected (PD). At least three grab samples were collected for

89

compositing from each of the 10 location-time combinations between January and July 2014 (Figure

90

1). Nucleic acid extraction was conducted on the 1-L water samples as described previously31. A

91

comprehensive physicochemical analysis (Table 1) following standard methods32 was conducted on

92

the wastewater samples collected by the WWTP at the PT and PD locations on the sampling dates.

93

Henceforth samples are referred to by their month of sampling and their collection stage, e.g., “Jan-

94

PD” for January sample collected at the post-disinfection stage.

95

PCR amplification of Mycobacterium 16S rRNA gene fragments

96

The overall methodology for DNA extraction, amplification, and sequencing is presented in

97

Supporting Information (SI) Figure S1. A two-step nested PCR approach was used to amplify the

98

DNA of Mycobacterium genus and of slow growing mycobacteria. This was done to generate

99

amplicons for TA cloning and sequencing, and to compare the sensitivity of detection via nested PCR

100

and qPCR. The primers used as well as the overall experimental methodology are summarized in SI

101

Table S1. The PCR reactions were carried out using the Bio-Rad iQ5 PCR Thermal Cycler (Bio-Rad,

102

USA) in 25 μL volumes containing 12 μL Readymix™ Taq PCR reaction mix with MgCl2 (Sigma-Aldrich,

103

USA) and 25 nmol primer mix. In all the reactions, pure culture DNA from the German Collection of

104

Microorganisms and Cell Cultures GmbH (DSMZ, Braunschweig, Germany) for M. smegmatis (DSMZ

105

43756) for rapid growers, and M. gordonae (DSMZ 44160) for slow growers, were used as positive

106

controls. In addition to no-template control run for each reaction, genomic DNA of E. coli (DSMZ

107

1116) and Salmonella enterica subsp. enterica (DSMZ 19587), were used as negative controls.

108

Further details on PCR amplifications are provided in the Supporting Information.

109

qPCR of Mycobacterium genus and slow-growing mycobacteria

110

qPCR was used for quantitative analysis of Mycobacterium genus, slow growing mycobacteria, and

111

Mycobacterium tuberculosis complex (MTC), using the previously described primers6. Genomic DNA

112

of M. smegmatis (rapid grower) and M. gordonae (slow grower) were used to generate standard

113

curves for Mycobacterium genus, and slow growing mycobacteria, respectively. All qPCR reactions

114

were carried out using a Bio-Rad iCycler iQ5 PCR Thermal Cycler (Bio-Rad, USA).

5



115

Page 6 of 24

In order to determine the reproducibility of the standard curve analysis, the analysis was conducted

116

in three different experiments and in triplicate for each experiment. All extracted wastewater

117

samples were run in triplicate, and in parallel with a positive control (M. gordonae and M.

118

smegmatis), a negative control (E. coli and S. enterica), and a no-template control (NTC). Melt-curve

119

analysis was used to determine specificity of the PCR products.

120

qPCR was performed for MTC on the PD samples in order to ensure that this harmful organism was

121

not present in treated wastewater used in water recycling. For the qPCR analysis of MTC, a fragment

122

of an insertion sequence-like element that has been used to fingerprint various strains of MTC

123

complex33, IS6110 of Mycobacterium tuberculosis H37Rv was synthesized (IDT, Belgium). This was

124

done to eliminate the risk of handling the potentially pathogenic species of MTC. The primers,

125

previously used by Leung et al. 34 , amplify 133 bp of the synthesized gene. Wastewater samples

126

were run in triplicates, along with a no-template control, negative controls (E. coli and S. enterica),

127

and positive control (IS6110 of Mycobacterium tuberculosis H37Rv).

128

The R2 values for the standard curves for the three assays were 0.988 ± 0.0208 for Mycobacterium

129

genus, 0.986 ± 0.005 for slow-growers, and 0.981 ± 0.007 for MTC, which are within the range of R2

130

values recommended previously 35. The detection limit was 2.8x100 , 1.7x101, and 3.3x102 genomic

131

copies/μL of DNA, for Mycobacterium genus, slow-growers, and MTC analyses, respectively. The

132

number of fast growers was estimated by subtracting the results of slow-growers from

133

Mycobacterium genus and dividing by two. The reason for dividing by two here is that there is

134

double the number of ribosomal RNA (rrn) operons in rapid growers as compared to slow growers5;

135

therefore, the difference needed to be considered when calculating the ratio of fast growers to slow

136

growers. Additional details on qPCR work are provided in the Supporting Information.

137

TA cloning and sequencing

138

Thymine-Adenine cloning or TA cloning followed by Sanger sequencing was carried out as an

139

alternative method to infer method bias and possible false negatives in the species-level Roche 454

140

pyrosequencing screening procedure employed in this study. TA cloning is a simple and widely used

141

subcloning procedure that avoids the use of restriction enzymes other than for creating the

142

linearized vector36. The main drawback of this procedure is that it does not allow directional cloning

143

and, therefore, it is sequenced unidirectionally. The cloning was performed separately for the whole

144

Mycobacterium genus and for slow-growers with the primers listed in SI Table S1. The PCR products

145

of two post-disinfected samples (Jan-PD and Mar-PD) for Mycobacterium genus and slow growers

146

were taken for TA cloning and Sanger sequencing. The cloning was conducted using a synthetic

147

vector, pTOP TA V2, which had a length of 3807 bp. The cloning was conducted using TOPcloner™

6


Page 7 of 24


148

TA core kit, in accordance to manufacturer’s protocol (Enzynomics, Korea). Thereafter, 96-well

149

unidirectional Sanger sequencing was conducted on the Applied Biosystems ABI 3730xl platform

150

using forward primer M13F.

151

Roche 454 pyrosequencing

152

The library preparation steps included amplicon preparation, library purification, quantitation,

153

normalization, pooling and quality control, and used the GS FLX Titanium emPCR kit (Roche,

154

Indianapolis, IN). The amplicons for pyrosequencing were amplified using primers described in SI

155

Table S1. The sequencing was conducted using 1/4 GS FLX Titanium platform according to

156

manufacturer’s protocol, without any modification.

157

Bioinformatics analysis of Mycobacterium diversity (pyrosequencing and TA cloning)

158

Raw sequence data acquired from Roche 454 sequencing and TA cloning/Sanger sequencing were

159

subjected to a bioinformatics analysis pipeline based on "Quantitative Insights into Microbial

160

Ecology" (QIIME, version 1.8.0)37. From TA cloning, a total of 298 sequences were received from 4

161

samples, which were passed through sequence quality filtering. Closed-reference operational

162

taxonomic unit (OTU) calling was performed against a dedicated, self-constructed reference

163

database of all 162 Mycobacterium type strains present in the "All species living tree project"38,

164

version 119. OTUs were assigned using QIIME's wrapper of the UCLUST39 algorithm for clustering,

165

with a threshold of 0.97 (97%) sequence similarity. 291 sequences from 4 samples (with a mean

166

sample size of 72.75) clustered against 17 distinct Mycobacterium type strains.

167

Roche 454 pyrosequencing was used for 9 samples from different time- and location-specific points.

168

QIIME was used for library splitting and quality filtering with a quality score of 28 used as a minimum

169

threshold. These sequences were clustered against Mycobacterium type strains as described above.

170

82,183 sequences matched against 70 distinct Mycobacterium type strains. In order to visualize the

171

phylogenetic spectrum of those matches, the Mycobacterium clade was extracted from the Living

172

Tree Project phylogeny using the DendroPy 40 Phylogenetic computing library in Python. EvolView 41

173

was used for the representation and visualization of the phylogeny with relative abundances of each

174

Mycobacterium species in different samples. Sequences for all samples after de multiplexing,

175

quality filtering and removal of primers/barcodes were submitted to Sequence Read Archive (SRA)

176

and are available under the Bio Project ID: PRJNA312286

177

(http://www.ncbi.nlm.nih.gov/bioproject/312286 ).

178

Data analysis of sequence differences amongst a comprehensive set of mycobacterial 16S rRNA

179

sequences (full length) was performed to demonstrate the validity of the 16S rRNA gene-based

7



180

species identification approach (see SI Figure S8 and related text). A curated set of 836 sequences

181

from the SILVA database version 123 were used for the analysis. The results showed sequences to

182

largely cluster by species or species complexes.

Page 8 of 24

183 184

RESULTS AND DISCUSSION

185

Mycobacterial diversity in post-disinfected water for water reuse

186

As listed earlier, the three major species of clinically-relevant NTM15 found in the PD treated

187

wastewater, which is used almost entirely for landscape irrigation, were the slow growers M.

188

kansasii (Mar-PD), M. szulgai (Mar-PD), and M. gordonae (Jan-PD, Mar-PD, and Jul-PD) (Figure 2). It

189

should be noted that respiratory infections, especially those owing to slow growing NTMs vary by

190

geographical region11. For example, in a nationwide study in Saudi Arabia10, a region adjacent to this

191

study’s region in the Arabian Peninsula, M. asiaticum was found to be a one of the significant

192

respiratory isolates – M. asiaticum was also found in Jan-PD, Mar-PD, and May-PD samples in this

193

study.

194

The most consistently detected (i.e., detected in all PD samples) and also the most relatively

195

abundant mycobacterial species found in the water used for recycling were the three rapid growers,

196

M. mageritense (Relative Abundance [RA] range = 20.927% [Jun-PD] - 79.777% [Apr-PD]), M.

197

insubricum (RA range = 1.325% [Apr-PD] – 36.588% [Jan-PD]), and M. iranicum (RA range = 3.580%

198

[Jun-PD] – 13.993% [Apr-PD]). M. mageritense is an NTM species that has been isolated from clinical

199

pulmonary and surgical samples but it is often misidentified because of its similarity to M. fortuitum

200

42

201

where 73 pulmonary samples showing NTM infections were collected10. M. iranicum is a

202

geographically widespread NTM that has been recently isolated from clinical samples taken in 6

203

countries, covering 3 continents43. The common occurrence of both of these species in clinical

204

samples points to a need for updating the list of 20 NTMs designated as clinically-relevant by the ATS

205

in 200715. The third dominant fast-growing NTM found in PD samples, M. insubricum, which has not

206

been isolated from human samples from the region.

207

In conclusion, a number of mycobacterial species that are of significant clinical relevance to the

208

region were found to occur in post-disinfected treated municipal wastewater, the water commonly

209

used for landscape irrigation across our region. This evidence, while preliminary, shows similar

210

geographic microbial diversity between treated wastewater samples from this study and clinical

211

NTM-infected pulmonary samples reported from the region, pointing to a possible exposure link

. Incidentally, it is worth noting that M. fortuitum was found most commonly in the Saudi study

8


Page 9 of 24


212

between the two that requires further investigation. It also emphasizes the need for vigilant

213

monitoring and disinfection control of such mycobacteria in treated wastewater. Additionally,

214

engineering controls, such as minimizing spray irrigation practices and irrigating only during off-peak

215

hours2, should be considered in order to minimize the public’s exposure to water-laden aerosols in

216

water reuse.

217

Microbial diversity across the municipal WWT train

218

When looking across the WWT train for the January and July sampling events (Figure 3),

219

pyrosequencing proved to be a more effective tool for the microbial diversity analysis of rapid

220

growers than for slow growing mycobacteria. Relative abundances of slow grower sequences

221

(Figure 3) were generally quite low via pyrosequencing, even when appreciable numbers were

222

detected using qPCR when compared to rapid growers in the January sampling event (Tables 1 and

223

2). Owing to its emphasis on potential exposure during water reuse, the study adopted a sampling

224

strategy that had a bias towards less aggregating and less hydrophobic mycobacteria as the first

225

sampling point along the WWT train was the effluent from the primary clarifier. This precluded the

226

recovery of highly hydrophobic and aggregating mycobacteria that have been reported to be

227

removed by settling at the primary clarifier stage 8, 44.

228

For mycobacterial species detected in PT samples or primary clarifier effluent, one of two trends

229

were observed. The first trend saw species increase in relative abundance in the PC samples (i.e.

230

after the aeration tank), followed by a decline to below PT levels in the PD or post-chlorination

231

stage. Species that followed this trend include those reported earlier, such as M. mageritense and

232

M. iranicum as well as others (e.g., M. longobardum). The first trend can be explained by the more

233

rapid aerobic growth in number of these species in the aeration tank (i.e. rapid growth with respect

234

to the entire pool of mycobacteria) before the PC sampling point, followed by a drop in abundance

235

at the PD sampling point after these organisms were oxidized during the disinfection step. The

236

second trend seemed to be of species that fell in relative abundance from the PT to the PC stage,

237

followed by a sharp increase after disinfection in the PD samples. Species that followed the second

238

trend included M. poriferae and M. insubricum, both of which are potential pathogens in marine

239

animals 45, 46. Species following the second trend might be demonstrating a slower growth rate

240

compared to the species following the first trend, as well as a consistent resistance to chlorine

241

disinfection with respect to other species.

242

To conclude, the pyrosequencing approach allows one to identify species that thrive with respect to

243

other species in the sample between different points along the wastewater treatment train. Note

244

that a number of other mycobacterial species (e.g., M. asiaticum and M. austoafricanum) did

9



Page 10 of 24

245

however, demonstrate variable trends in relative abundance from the January to the July sampling,

246

indicating potentially different growth or disinfection rates for the two events based on seasonal or

247

operational variations.

248

Screening method limitations

249

A comparison was carried out between the pyrosequencing approach for species-level NTM

250

screening with an independent TA cloning/Sanger sequencing method, on PD samples, to glean

251

information on method bias and any false negatives. Low false-negative numbers are generally

252

considered to be a hallmark of a good screening approach.

253

A comparison of OTU binning against the mycobacterial pool from PD samples of TA cloning and 454

254

pyrosequencing is summarized in SI Figure S2. Sequences from the TA cloning approach clustered

255

against only 17 OTUs, whereas 61 OTUs were found via the pyrosequencing approach, reflecting the

256

difference in resolution of the two techniques. A total of 12 OTUs were found to be common

257

between the 2 techniques. Three of the 5 OTUs found exclusively via the TA cloning approach in PD

258

samples belonged to the clinically-relevant slow-growing species, M. kansasii, M. szulgai, and M.

259

gordonae (Figure 2)15. The one slow growing NTM detected by both methods in the same Jan-PD

260

split sample was M. asiaticum (Figure 2), which was detected at a very high relative abundance

261

(>97%) using the APTK16F/APTK16R primer nested PCR amplification for slow-growers in the TA

262

cloning approach. M. gordonae was not detected by pyrosequencing in the split Jan-PD sample but

263

was picked up via TA cloning, indicating that this species was a clear false negative for the

264

pyrosequencing approach. However, M. gordonae was detected using pyrosequencing in the Jul-PD

265

samples when it was present at higher relative abundance (>21%). To conclude, the pyrosequencing

266

sequencing method using universal primers worked well for screening slow-growing NTM only when

267

their relative abundance was high in the sample.

268

In contrast, for rapid growers, 454 pyrosequencing screening with universal primers detected several

269

species that could not be detected with the TA cloning approach. These species included, M.

270

pulveris, M. gadium, M. aurum, M. rhodesiae, M. porcinum, M. senegalense, and M. phlei. The

271

additional species detected by the pyrosequencing approach suggests its higher sensitivity and

272

resolution for detecting fast growing mycobacteria. The results were corroborated by the alpha

273

diversity analysis where the number of observed species or OTUs was expectedly much higher in 454

274

pyrosequencing than in TA cloning (SI Figures S3 and S4). The pyrosequencing method proved to be

275

an effective overall technique for whole genus diversity screening of mycobacteria at the species

276

level because of its ability to detect fast growers at a high resolution, as well as the ability to detect

277

several slow growing species albeit at a lower sensitivity. Further improvements to the species-level

10


Page 11 of 24


278

screening methodology employed here can be attained by acquiring longer sequence lengths of the

279

16rRNA gene and by using sequencing technology with lower error rates. One point to note is that

280

any screening methodology employing 16S-based species identification cannot confirm

281

pathogenicity, which should be confirmed via secondary lines of evidence involving the detection of

282

virulence factor genes.

283

Quantitative analysis with qPCR and detection with nested PCR

284

The qPCR results for the wastewater samples for Mycobacterium whole genus ranged from 1.2x103 -

285

1.9 x 106 genomic copies/100 µL of water sample. For slow growers, only 5 samples showed

286

detectable genomic copies above the detection limit out of the 9 composite samples analyzed. For

287

samples found to be positive, the results for slow growers ranged from 2.1x101 -2.1x104 genomic

288

copies/100µL of water sample. No MTC was detected above its corresponding detection limit.

289

In analyzing the ratio of fast growers to slow growers, the values that showed positive detection

290

with nested PCR, but resulted in values less than the detection limit with qPCR, were assumed to be

291

equal to 8.5 genomic copies/μL of extracted DNA (half the detection limit for slow-growers by qPCR).

292

The ratio of fast to slow growers showed high numbers >300 for the Apr-PD sample. The samples

293

from Jan-PD showed almost an equal ratio of fast to slow growers. This could be alarming as some

294

of the potentially pathogenic Mycobacterium strains are slow growers.

295

Nested PCR appeared to be the more sensitive approach in detecting slow growers than qPCR. Only

296

5 out of the 9 PC and PD samples (Tables 1 and 2) gave values higher than the detection limit using

297

qPCR, whereas 8 out of 9 samples showed positive detection using nested PCR. However for all

298

whole-genus analyses, both methods gave positive detection for all the samples analyzed in this

299

study. The comparison of the sensitivity and specificity of nested PCR and qPCR in detection of

300

various disease causing agents has been a focus of various medical47, as well as environmental

301

studies48, reporting contradictory results. Contrary to a study that observed higher sensitivity with

302

qPCR than nested PCR49 in detection of Mycobacterium avium subsp. paratuberculosis in fecal

303

samples, our results indicate more consistent detection using nested PCR approach especially for

304

detecting slow-growers when they are present in low concentrations.

305

Effects of chlorine disinfection on mycobacteria

306

During the January to July monthly sampling period at the PD location, both whole genus and fast

307

growing mycobacteria demonstrated a sharp increase in counts until peak values were reached in

308

April. Both of these parameters showed a steep decline in June followed by a slight increase in July

309

(Table 2). After January, when the CT value was 90 mg•min/L, the CT levels dropped to 36

310

mg•min/L, thereby allowing the fast growers to flourish until the disinfection levels were ramped up

11



Page 12 of 24

311

to 180 mg•min/L by the 18th of May (note that the May CT value is an average of 13.5 mg•min/L on

312

the 4th of May and 180 mg•min/L on the 18th of May, the days around the sampling event).

313

Subsequently, whole genus and fast grower counts dropped to their lowest values in June.

314

Concomitantly in June, counts for slow growers also dropped to below detection levels, via both

315

qPCR and nested PCR analysis, after the peak disinfection event in May. Slow grower counts peaked

316

in early May before the increase disinfection intensity by the 18th of May. During the entire

317

sampling duration, E. coli MPN numbers remained at or below 40/100 mL (the local regulatory limit

318

for treated wastewater), even when counts of mycobacteria surged to 1.9 x 106 genomic copies/100

319

µL in the Apr-PD samples (Table 2). Previous researchers have reported that several strains of

320

mycobacteria are 100-330 times more resistant to chlorine than E. coli 9.

321

Interestingly, CT values of 10-12 mg•min/L with free chlorine are recommended as general

322

guidelines for a 4-log inactivation of coliform bacteria at neutral pH and 20 °C 50. For both whole

323

genus and fast growing mycobacteria in this study, a 90 mg•min/L CT achieved only between a 1-log

324

to 2-log disinfection, while lower CT values couldn’t even produce a 1-log removal between the PC

325

and PD sample values (Table 1). Previously, a 2.5-log reduction has been reported for M. terrae at a

326

free chlorine CT of 56 mg•min/L under laboratory conditions8. In another laboratory study, 1.5- to

327

4-log reduction has been reported for various species of mycobacteria at a free chlorine CT levels of

328

60 mg•min/L9. A number of factors, such as dissolved organic carbon, total dissolved solids, pH, and

329

temperature, can affect the chlorine disinfection efficiency and might have played a role in the case

330

of this WWTP. Surprisingly, slow growing mycobacteria appeared to be unaffected at the higher

331

chlorine disinfection CT value of 90 mg•min/L (Table 1), confirming past reports of their high

332

resistance to chlorination51. Slow growers declined to undetectable levels in Jun-PD only after the

333

peak CT level of 180 mg•min/L recorded during the May 18th sampling event (Table 2).

334

As described earlier, a number of mycobacterial strains (e.g., M. poriferae and M. insubricum)

335

increased in relative abundance after chlorine disinfection (Figure 3), indicating their higher

336

resistance to chlorination, especially with respect to other mycobacterial species found along the

337

treatment train. This result confirms earlier findings of varying disinfection resistance across the

338

Mycobacterium genus9. The occurrence of these clinically-relevant NTMs in the post-disinfected

339

treated municipal wastewater, the water that is commonly used for landscape irrigation, suggests

340

the need for better optimization of disinfection practices at the WWTP especially against resistant

341

NTM strains.

342

In this study the microbial diversity of the genus Mycobacterium was screened for clinically- and

343

environmentally-relevant species using 16S-based pyrosequencing. Analysis of the post-disinfected

12


Page 13 of 24


344

treated wastewater showed presence of clinically-relevant species like M. asiaticum and M.

345

mageritense, which have been isolated in pulmonary samples from NTM-infected patients in the

346

region. Diversity analysis along the treatment train found environmentally-relevant species like M.

347

poriferae and M. insubricum to increase in relative abundance across the chlorine disinfection step.

348

A comparison to qPCR results across the chlorine disinfection step saw no significant change in slow

349

grower counts at CT disinfection values ≤90 mg•min/L but an increase to 180 mg•min/L brought

350

slow growers to below detection levels. The study confirms the occurrence of clinically- and

351

environmentally-relevant mycobacteria in treated municipal wastewater and their ineffective

352

removal across the disinfection stage, suggesting the need for vigilant monitoring of treated

353

municipal wastewater quality and disinfection effectiveness prior to reuse.

354 355

SUPPORTING INFORMATION

356

Supporting Information (SI) providing details on experimental methodology and a bioinformatics

357

rationale for species-level screening of the genus Mycobacterium is provided free of charge from the

358

ACS publications website.

359 360

ACKNOWLEDGEMENTS

361

This research was funded under research grant 13XAAA2 from the Masdar Institute of Science and

362

Technology.

363

13



364

REFERENCES

365

1.

366 367

2.

3.

Johnson, M. M.; Odell, J. A., Nontuberculous mycobacterial pulmonary infections. J. Thorac. Dis. 2014, 6, (3), 210-220.

4.

Tortoli, E., Clinical manifestations of nontuberculous mycobacteria infections. Clin.Microbiol. Infect. 2009, 15, (10), 906-910.

372 373

Aina, O. D.; Ahmad, F., Carcinogenic health risk from trihalomethanes during reuse of reclaimed water in coastal cities of the Arabian Gulf. J. Water Reuse Desalin. 2013, 3, (2), 175-184.

370 371

World Water Assessment Programme, Managing Water under Uncertainty and Risk: The United Nations World Water Development Report 4. In París: UNESCO: 2012.

368 369

5.

Pontiroli, A.; Khera, T. T.; Oakley, B. B.; Mason, S.; Dowd, S. E.; Travis, E. R.; Erenso, G.; Aseffa,

374

A.; Courtenay, O.; Wellington, E. M., Prospecting environmental mycobacteria: combined

375

molecular approaches reveal unprecedented diversity. PloS One 2013, 8, (7), Article number

376

e68648.

377

Page 14 of 24

6.

September, S.; Brözel, V.; Venter, S., Diversity of nontuberculoid Mycobacterium species in

378

biofilms of urban and semiurban drinking water distribution systems. Appl. Environ. Microbiol.

379

2004, 70, (12), 7571-7573.

380

7.

natural relationships among the mycobacteria. J. Bacteriol. 1990, 172, (1), 116-124.

381 382

8.

Bohrerova, Z.; Linden, K. G., Ultraviolet and chlorine disinfection of Mycobacterium in wastewater: effect of aggregation. Water Environ. Res. 2006, 78, (6), 565-571.

383 384

Stahl, D.; Urbance, J., The division between fast-and slow-growing species corresponds to

9.

Le Dantec, C.; Duguet, J.-P.; Montiel, A.; Dumoutier, N.; Dubrou, S.; Vincent, V., Chlorine

385

disinfection of atypical mycobacteria isolated from a water distribution system. Appl. Environ.

386

Microbiol. 2002, 68, (3), 1025-1032.

387

10. Varghese, B.; Memish, Z.; Abuljadayel, N.; Al-Hakeem, R.; Alrabiah, F.; Al-Hajoj, S. A., Emergence

388

of clinically relevant non-tuberculous mycobacterial infections in Saudi Arabia. PLoS Neglected

389

Trop. Dis. 2013, 7, (5), 1-5.

390

11. Hoefsloot, W.; van Ingen, J.; Andrejak, C.; Ängeby, K.; Bauriaud, R.; Bemer, P.; Beylis, N.; Boeree,

391

M. J.; Cacho, J.; Chihota, V.; Chimara, E.; Churchyard, G.; Cias, R.; Daza, R.; Daley, C. L.;

392

Dekhuijzen, P. N. R.; Domingo, D.; Drobniewski, F.; Esteban, J.; Fauville-Dufaux, M.; Folkvardsen,

393

D. B.; Gibbons, N.; Gómez-Mampaso, E.; Gonzalez, R.; Hoffmann, H.; Hsueh, P.-R.; Indra, A.;

394

Jagielski, T.; Jamieson, F.; Jankovic, M.; Jong, E.; Keane, J.; Koh, W.-J.; Lange, B.; Leao, S.;

395

Macedo, R.; Mannsåker, T.; Marras, T. K.; Maugein, J.; Milburn, H. J.; Mlinkó, T.; Morcillo, N.;

396

Morimoto, K.; Papaventsis, D.; Palenque, E.; Paez-Peña, M.; Piersimoni, C.; Polanová, M.;

397

Rastogi, N.; Richter, E.; Ruiz-Serrano, M. J.; Silva, A.; da Silva, M. P.; Simsek, H.; van Soolingen,

14


Page 15 of 24


398

D.; Szabó, N.; Thomson, R.; Tórtola Fernandez, T.; Tortoli, E.; Totten, S. E.; Tyrrell, G.; Vasankari,

399

T.; Villar, M.; Walkiewicz, R.; Winthrop, K. L.; Wagner, D., The geographic diversity of

400

nontuberculous mycobacteria isolated from pulmonary samples: an NTM-NET collaborative

401

study. Eur. Respir. J. 2013, 42, (6), 1604-1613.

402

12. Winthrop, K. L.; McNelley, E.; Kendall, B.; Marshall-Olson, A.; Morris, C.; Cassidy, M.; Saulson,

403

A.; Hedberg, K., Pulmonary nontuberculous mycobacterial disease prevalence and clinical

404

features: an emerging public health disease. Am. J. Respir. Crit. Care Med. 2010, 182, (7), 977-

405

982.

406

13. Khoor, A.; Leslie, K. O.; Tazelaar, H. D.; Helmers, R. A.; Colby, T. V., Diffuse pulmonary disease

407

caused by nontuberculous mycobacteria in immunocompetent people (hot tub lung). Am. J.

408

Clin. Pathol. 2001, 115, (5), 755-762.

409

14. Van Ingen, J.; Boeree, M.; Dekhuijzen, P.; Van Soolingen, D., Environmental sources of rapid

410

growing nontuberculous mycobacteria causing disease in humans. Clin.Microbiol. Infect. 2009,

411

15, (10), 888-893.

412

15. Griffith, D. E.; Aksamit, T.; Brown-Elliott, B. A.; Catanzaro, A.; Daley, C.; Gordin, F.; Holland, S.

413

M.; Horsburgh, R.; Huitt, G.; Iademarco, M. F., An official ATS/IDSA statement: diagnosis,

414

treatment, and prevention of nontuberculous mycobacterial diseases. Am. J. Respir. Crit. Care

415

Med. 2007, 175, (4), 367-416.

416

16. Falkinham, J. O.; Norton, C. D.; LeChevallier, M. W., Factors influencing numbers of

417

Mycobacterium avium, Mycobacterium intracellulare, and other mycobacteria in drinking water

418

distribution systems. Environ. Sci. Technol. 2001, 67, (3), 1225-1231.

419 420 421 422

17. USEPA, Fact Sheet: Drinking Water Contaminant Candidate List 4 - Draft. In Office of Water, Ed. USEPA: Washington, DC, 2015. 18. Qvist, T.; Pressler, T.; Høiby, N.; Katzenstein, T. L., Shifting paradigms of nontuberculous mycobacteria in cystic fibrosis. Respir. Res. 2014, 15, (1), 41.

423

19. Donohue, M. J.; Mistry, J. H.; Donohue, J. M.; O’Connell, K.; King, D.; Byran, J.; Covert, T.; Pfaller,

424

S., Increased frequency of Nontuberculous Mycobacteria Detection at Potable Water Taps

425

within the United States. Environ. Sci. Technol. 2015, 49, (10), 6127-6133.

426

20. Thomson, R.; Tolson, C.; Carter, R.; Coulter, C.; Huygens, F.; Hargreaves, M., Isolation of

427

nontuberculous mycobacteria (NTM) from household water and shower aerosols in patients

428

with pulmonary disease caused by NTM. J. Clin. Microbiol. 2013, 51, (9), 3006-3011.

429 430

21. Falkinham, J. O., Surrounded by mycobacteria: nontuberculous mycobacteria in the human environment. J. Appl. Microbiol. 2009, 107, (2), 356-367.

15



431

22. Castillo-Rodal, A.; Mazari-Hiriart, M.; Lloret-Sánchez, L.; Sachman-Ruiz, B.; Vinuesa, P.; López-

432

Vidal, Y., Potentially pathogenic nontuberculous mycobacteria found in aquatic systems.

433

Analysis from a reclaimed water and water distribution system in Mexico City. Eur. J. Clin.

434

Microbiol. Infect. Dis. 2011, 31, (5), 683-694.

435 436

Page 16 of 24

23. Haas, H.; Fattal, B., Distribution of mycobacteria in different types of water in Israel. Water Res. 1990, 24, (10), 1233-1235.

437

24. Gray, D.; Pollard, S. J.; Spence, L.; Smith, R.; Gronow, J. R., Spray irrigation of landfill leachate:

438

estimating potential exposures to workers and bystanders using a modified air box model and

439

generalised source term. Environ. Pollut. 2005, 133, (3), 587-599.

440

25. Ibekwe, A. M.; Leddy, M.; Murinda, S. E., Potential Human Pathogenic Bacteria in a Mixed

441

Urban Watershed as Revealed by Pyrosequencing. PloS One 2013, 8, (11), e79490.

442

26. Ma, J.; Wang, Z.; Zang, L.; Huang, J.; Wu, Z., Occurrence and fate of potential pathogenic

443

bacteria as revealed by pyrosequencing in a full-scale membrane bioreactor treating restaurant

444

wastewater. RSC Adv. 2015, 5, (31), 24469-24478.

445

27. Ye, L.; Zhang, T., Bacterial communities in different sections of a municipal wastewater

446

treatment plant revealed by 16S rDNA 454 pyrosequencing. Appl. Microbiol. Biotechnol. 2013,

447

97, (6), 2681-2690.

448

28. Li, B.; Ju, F.; Cai, L.; Zhang, T., Profile and fate of bacterial pathogens in sewage treatment plants

449

revealed by high-throughput metagenomic approach. Environ. Sci. Technol. 2015, 49, (17),

450

10492-10502.

451

29. Srinivasan, R.; Karaoz, U.; Volegova, M.; MacKichan, J.; Kato-Maeda, M.; Miller, S.; Nadarajan,

452

R.; Brodie, E. L.; Lynch, S. V., Use of 16S rRNA gene for identification of a broad range of

453

clinically relevant bacterial pathogens. PloS one 2015, 10, (2), e0117617.

454

30. Chakravorty, S.; Helb, D.; Burday, M.; Connell, N.; Alland, D., A detailed analysis of 16S

455

ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J. Microbiol. Methods

456

2007, 69, (2), 330-339.

457

31. Kumaraswamy, R.; Amha, Y. M.; Anwar, M. Z.; Henschel, A.; Rodríguez, J.; Ahmad, F., Molecular

458

analysis for screening human bacterial pathogens in municipal wastewater treatment and

459

reuse. Environ. Sci. Technol. 2014, 48, (19), 11610-11619.

460 461 462

32. Rice, E. W.; Baird, R. B.; Eaton, A. D.; Clesceri, L., Standard methods for the examination of water and wastewater. American Public Health Association, Washington, DC 2012. 33. Cave, M. D.; Eisenach, K. D.; McDermott, P. F.; Bates, J. H.; Crawford, J. T., IS6110: conservation

463

of sequence in the Mycobacterium tuberculosis complex and its utilization in DNA

464

fingerprinting. Mol. Cell. Probes 1991, 5, (1), 73-80.

16


Page 17 of 24


465

34. Leung, E. T.; Zheng, L.; Wong, R. Y.; Chan, E. W.; Au, T.; Chan, R. C.; Lui, G.; Lee, N.; Ip, M., Rapid

466

and simultaneous detection of Mycobacterium tuberculosis complex and Beijing/W genotype in

467

sputum by an optimized DNA extraction protocol and a novel multiplex real-time PCR. J. Clin.

468

Microbiol. 2011, 49, (7), 2509-2515.

469 470

35. European Network of GMO Laboratories, Definition of minimum performance requirements for analytical methods of GMO testing. In European Commission, Brussels: 2008; p 8.

471

36. Zhou, M.-Y.; Gomez-Sanchez, C. E., Universal TA cloning. Curr. Issues Mol. Biol. 2000, 2, 1-8.

472

37. Caporaso, J. G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F. D.; Costello, E. K.; Fierer,

473

N.; Pena, A. G.; Goodrich, J. K.; Gordon, J. I., QIIME allows analysis of high-throughput

474

community sequencing data. Nat. Methods 2010, 7, (5), 335-336.

475

38. Yarza, P.; Richter, M.; Peplies, J.; Euzeby, J.; Amann, R.; Schleifer, K.-H.; Ludwig, W.; Glöckner, F.

476

O.; Rosselló-Móra, R., The All-Species Living Tree project: A 16S rRNA-based phylogenetic tree

477

of all sequenced type strains. Syst. Appl. Microbiol. 2008, 31, (4), 241-250.

478 479 480 481 482

39. Edgar, R. C., Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010, 26, (19), 2460-2461. 40. Sukumaran, J.; Holder, M. T., DendroPy: a Python library for phylogenetic computing. Bioinformatics 2010, 26, (12), 1569-1571. 41. Zhang, H.; Gao, S.; Lercher, M. J.; Hu, S.; Chen, W.-H., EvolView, an online tool for visualizing,

483

annotating and managing phylogenetic trees. Nucleic Acids Res. 2012, 40, (W1), W569-W572.

484

42. Wallace Jr, R. J.; Brown-Elliott, B. A.; Hall, L.; Roberts, G.; Wilson, R. W.; Mann, L. B.; Crist, C. J.;

485

Chiu, S. H.; Dunlap, R.; Garcia, M. J., Clinical and laboratory features of Mycobacterium

486

mageritense. J. Clin. Microbiol. 2002, 40, (8), 2930-2935.

487

43. Shojaei, H.; Daley, C.; Gitti, Z.; Hashemi, A.; Heidarieh, P.; Moore, E. R.; Naser, A. D.; Russo, C.;

488

van Ingen, J.; Tortoli, E., Mycobacterium iranicum sp. nov., a rapidly growing scotochromogenic

489

species isolated from clinical specimens on three different continents. Int. J. Syst. Evol.

490

Microbiol. 2013, 63, (Pt 4), 1383-1389.

491

44. Radomski, N.; Betelli, L.; Moilleron, R.; Haenn, S.; Moulin, L.; Cambau, E.; Rocher, V.; Gonçalves,

492

A.; Lucas, F. S., Mycobacterium behavior in wastewater treatment plant, a bacterial model

493

distinct from Escherichia coli and enterococci. Environ. Sci. Technol. 2011, 45, (12), 5380-5386.

494 495 496 497

45. Slany, M.; Mrlík, V.; Kriz, P.; Pavlik, I., First isolation of a newly described Mycobacterium insubricum from freshwater fish. Vet. Microbiol. 2010, 144, (1), 254-255. 46. Tortoli, E.; Bartoloni, A.; Bozzetta, E.; Burrini, C.; Lacchini, C.; Mantella, A.; Penati, V.; Simonetti, M. T.; Ghittino, C., Identification of the newly described Mycobacterium poriferae from

17



498

tuberculous lesions of snakehead fish (Channa striatus). Comp. Immun. Microbiol. Infect. Dis.

499

1996, 19, (1), 25-29.

500

Page 18 of 24

47. Hafez, H.; Hauck, R.; Lüschow, D.; McDougald, L., Comparison of the specificity and sensitivity of

501

PCR, nested PCR, and real-time PCR for the diagnosis of histomoniasis. Avian Dis. 2005, 49, (3),

502

366-370.

503

48. Muscillo, M.; Pourshaban, M.; Iaconelli, M.; Fontana, S.; Di Grazia, A.; Manzara, S.; Fadda, G.;

504

Santangelo, R.; La Rosa, G., Detection and quantification of human adenoviruses in surface

505

waters by nested PCR, TaqMan real-time PCR and cell culture assays. Water Air Soil Pollut.

506

2008, 191, (1-4), 83-93.

507

49. Fang, Y.; Wu, W.-H.; Pepper, J. L.; Larsen, J. L.; Marras, S. A.; Nelson, E. A.; Epperson, W. B.;

508

Christopher-Hennings, J., Comparison of real-time, quantitative PCR with molecular beacons to

509

nested PCR and culture methods for detection of Mycobacterium avium subsp. paratuberculosis

510

in bovine fecal samples. J. Clin. Microbiol. 2002, 40, (1), 287-291.

511 512 513

50. Tchobanoglous, G.; Burton, F. L.; Stensel, H. D., Wastewater Engineering: Treatment and Reuse. 4th ed.; McGraw Hill: Boston, 2003. 51. Taylor, R. H.; Falkinham, J. O.; Norton, C. D.; LeChevallier, M. W., Chlorine, chloramine, chlorine

514

dioxide, and ozone susceptibility of Mycobacterium avium. Appl. Environ. Microbiol. 2000, 66,

515

(4), 1702-1705.

516

18


Page 19 of 24


TABLES Table 1. qPCR results for Mycobacteria Across the Chlorine Disinfection Unit Together with Water Quality Data from the WWTP. January3

Parameter

PC

pH Alkalinity (mg/L) Chloride (mg/L) TDS (mg/L) Conductivity (microS/cm) Turbidity (NTU) DO (mg/L) COD (mg/L) Total hardness (mg/L) Residual Chlorine CT disinfection (mg. min/L) E. coli (MPN/100 mL) Mycobacterium, whole genus (genomic copies/100 mL) Slow Growers Detection (Nested PCR) Slow Growers (genomic copies or organisms/100 mL) Fast Growers (organisms/100 mL)2 Ratio (Fast/Slow)

350,209±23,666 Detected 6,770±856 171,720 25.4

July3 PD

6.3 40 1,510 2,780 5,380 1.7 6.1 27.1 640 2 90 3 23,837±1,768 Detected 7,823±734 8,007 1.0

PC

3,084±968 Detected 21.31 1,532 72.0

PD 6.7 48 1,290 2,280 4,430 0.8 6.5 13.6 598 0.8 36 1 1,861±434 Detected 21.31 920 43.2

1. Samples with no detection through nested PCR were assigned a value of zero. Samples with positive detections that were below the qPCR quantitation limit, were assigned a value of half the quantitation limit. 2. Because of the double copy of rrn operons found in fast growers, the number of fast growers was estimated by subtracting the mean value for slow growers from the mean whole genus value and then dividing by 2. o

o

3. Average ambient temperature in January and July is 18 C and 35 C, respectively.

19



Page 20 of 24

Table 2. qPCR results for Mycobacteria together with Chlorination Data from the WWTP.

Sample

Residual CT E. coli Chlorine disinfection (MPN/100 (mg/L) (mg. min/L) mL)

Mycobacterium, whole genus (genomic copies/100 mL)

Slow-growers, detection with nested PCR

Slow Growers1 (genomic copies or organisms/100 mL)

Fast Growers2 (organisms/ Ratio 100 mL) (Fast/Slow)

Jan PD

2.0

90.0

3

23,837 ± 1,768

Detected

7,823 ± 734

8,007

1.0

March PD

0.8

36.0

9.7

674,845 ± 42,706

Detected

19,028 ± 16,142

327,909

17.2

April PD

0.8

36.0

38.8

1,950,708 ± 506,332

Detected

2,796 ± 752

973,956

348.4

May PD3

2.2

96.8

40.7

492,768 ± 695,331

Detected

20,733 ± 29,291

236,018

11.4

June PD

0.5

22.5

Mycobacteria in Municipal Wastewater ... - ACS Publications

Recommend Documents