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Microbial Ecology

, Volume 76, Issue 1, pp 52–63 | Cite as

Detection of Pathogenic and Non-pathogenic Bacteria in Drinking Water and Associated Biofilms on the Crow Reservation, Montana, USA

  • Crystal L. Richards
  • Susan C. Broadaway
  • Margaret J. Eggers
  • John Doyle
  • Barry H. Pyle
  • Anne K. Camper
  • Timothy E. Ford
Environmental Microbiology

Abstract

Private residences in rural areas with water systems that are not adequately regulated, monitored, and updated could have drinking water that poses a health risk. To investigate water quality on the Crow Reservation in Montana, water and biofilm samples were collected from 57 public buildings and private residences served by either treated municipal or individual groundwater well systems. Bacteriological quality was assessed including detection of fecal coliform bacteria and heterotrophic plate count (HPC) as well as three potentially pathogenic bacterial genera, Mycobacterium, Legionella, and Helicobacter. All three target genera were detected in drinking water systems on the Crow Reservation. Species detected included the opportunistic and frank pathogens Mycobacterium avium, Mycobacterium gordonae, Mycobacterium flavescens, Legionella pneumophila, and Helicobacter pylori. Additionally, there was an association between HPC bacteria and the presence of Mycobacterium and Legionella but not the presence of Helicobacter. This research has shown that groundwater and municipal drinking water systems on the Crow Reservation can harbor potential bacterial pathogens.

Keywords

Drinking water Helicobacter pylori Legionella Mycobacterium 

Introduction

In the USA, over 15 million households rely on private ground water wells for their primary drinking water source [1], and in many rural areas private and community groundwater wells provide a major source of drinking water. During 1999–2002, 22 % of water-borne illnesses were attributed to individual water systems and 36 % were attributed to community systems [2]. Private water systems are not routinely monitored for bacteriological water quality, thus, little is known about the presence of bacterial pathogens in these systems. Information regarding well water quality on Indian Reservations in the USA is equally scant. However, it is known that American Indian populations have disproportionately high disease burdens compared to the overall population of the USA [3]. This is due to many factors which include economics, geographic isolation, cultural barriers, and inadequate sewage disposal [4].

The United States Centers for Disease Control report that chronic lower respiratory disease, influenza, and pneumonia are among the top ten causes of death among American Indian and Alaska Native populations [1]. In Montana, cancer is included as a major cause of death for American Indian populations [5]. Although it has been observed that the disease burden of these populations is greater than for the overall population of the USA [3, 6], very little research has been done to identify causes and potential routes of exposure to infectious agents and environmental carcinogens. In the present study, community-based participatory research principles were used to guide the aims of this research [7]. Meetings were held on the Crow Reservation where members of the Crow Environmental Health Steering Committee (CEHSC) expressed their concern about the relationship between poor drinking water quality and respiratory diseases and stomach cancer. In addition to widespread concern over drinking water quality in general, there was a specific concern regarding anecdotal reports of higher than average Helicobacter pylori infections. To address the concerns of the community, three bacterial genera with members that are potential drinking water pathogens, Mycobacterium, Legionella, and Helicobacter, were chosen for investigation (personal communication, John Doyle). Local staff, both Crow, recruited participants and collected home tap water samples. Throughout the course of the research, investigators met regularly with the CEHSC to seek their input and keep them apprised of progress and results.

Mycobacterium species are common inhabitants of drinking water systems and are known to survive and proliferate in biofilms [8, 9]. Several species of this genus cause respiratory disease in mainly immunocompromised individuals, including members of the Mycobacterium avium complex, Mycobacterium gordonae, Mycobacterium flavescens, and others [10, 11, 12]. Legionella are ubiquitous throughout aquatic environments including ground and surface water, and manmade water reservoirs such as potable water systems and cooling towers [13, 14, 15]. Legionellosis is thought to occur when Legionella are aerosolized and inhaled [16]. However, it has been suggested that transmission of the different forms of legionellosis, and the resultant severity of disease, may be related to an association with biofilms [17]. Helicobacter are pathogens of the gastrointestinal tract of mammals but have been found in many environments such as well, river, and pond water, in addition to house flies, and cattle feces [18]. Helicobacter pylori are the primary bacterial cause of gastritis, as well as peptic and duodenal ulcers in people around the world [19]. Infection is known to increase the risk of the development of gastric mucosa-associated lymphoma and adenocarcinoma [16]. Water is a short-term reservoir, with the pathogen often occurring sporadically in drinking water supplies that have been exposed to sewage or have been contaminated by infected animals [20].

Drinking water samples and their associated biofilms were tested for heterotrophic and coliform bacteria by traditional culture methods. Mycobacterium, Legionella, and Helicobacter species were detected by culture and/or PCR. The aim of this study was to investigate whether these organisms are common inhabitants of drinking water systems on the Crow Reservation in southeast Montana.

Materials and Methods

Study Area

The Crow Indian Reservation, MT, USA, was the primary location for sample collection and analysis. Fifty-seven locations were sampled across the Crow Reservation and include 43 private residences and 14 public buildings. The Crow Reservation, the largest reservation in Montana, is rural with an average population density of 1.9 individuals per square mile [1]. The Crow tribe has an enrolled membership of over 13,000 and approximately 72 % of members live on or near the Reservation [21]. The major township on the reservation, Crow Agency, has drinking water provided by treated surface water, while other townships utilize community wells [22]. The Crow Agency treatment facility performs reliably and adequately; however, at the time of this study the distribution system in Crow Agency was nearly 100 years old and was vulnerable to cracks and leaks (personal communication, John Doyle). Most of the residents outside of designated townships have privately maintained groundwater wells.

Control Bacterial Strains and Growth Conditions

Representative species from each genus of interest were kept as frozen stocks at −70 °C and used as positive controls in both PCR and culture methods. The M. avium W2001 strain used in this study was originally isolated from drinking water in the Boston area [23], was cultured on Middlebrook 7H10 (Difco), and incubated at 37 °C for 10 days. Legionella pneumophila strain 33153 was obtained from the American Type Culture Collection, cultured on Legionella agar (Difco) enriched with 0.7 % l-cysteine and 0.3 % ferric pyrophosphate (Difco) and incubated at 37 °C for 7 days. The H. pylori strain 43504 was obtained from the American Type Culture Collection and was cultured on H. pylori-specific HP media and incubated in a microaerophilic atmosphere for 1 week at 37 °C [24]. All control strains were grown and sequentially transferred twice prior to use as positive controls.

Sample Collection and Processing

Samples were primarily collected from kitchen sinks in private residences and kitchen or restroom sinks in public buildings. Biofilm samples were collected first by systematically wiping the inside of the drinking water faucet with a sterile cotton swab before any flushing or sterilization of the tap. Three swabs were collected from one faucet at each residence or building and were placed in individual tubes containing sterile water for transport. To calculate surface area of the biofilm, the faucet dimensions (depth and width) were measured and recorded. After biofilm collection, the faucet was wiped with 95 % ethanol to sanitize it before bulk water collection. One liter of water was then collected without flushing and is denoted as “first flush.” First flush sample collection was implemented partway through the study (n = 20) and thus this fraction was only analyzed for groundwater wells. After the first flush collection, the water was run from the tap for 2 min minimum or until water temperature stabilized prior to parameter measurement. Physical and chemical characteristics were measured using standard methodologies. The presence and quantity of free and total chlorine was measured using a colorimetric method (Hach kit model CN-70 chlorine test kit, Hach Co., Loveland, CO). Chlorine in the water was neutralized by the addition of 2 % sodium thiosulfate after collection. Temperature and pH were measured using a multi-parameter probe (Oakton, Vernon Hills, IL). After a minimum of 2 min of flushing, “post flush” water was collected in three separate 1-l sterile plastic bottles. All samples were placed on ice and transported to the laboratory and processed within 24 h. In the laboratory, tubes containing biofilm samples were vortexed for 1 min and the cell suspensions from each swab were pooled and mixed. Pooled cell suspensions from the same source were used for all biofilm analysis. To concentrate water samples, 900 ml from each liter sample was filtered through a 0.45-μm 25-mm diameter mixed cellulose ester filter (Pall Corp., Ann Arbor, MI). The filter was vortexed in 1.5 ml of PBS at maximum speed for 1 min, and then removed, and the cell suspension centrifuged at 13,000×g for 10 min. The supernatant was removed and the cell pellet was resuspended in 100 μl of sterile water. Pooled biofilm and both concentrated and unconcentrated water samples were used for DNA extractions and genus-specific culture methods.

Quantification of Fecal Indicator Bacteria and Heterotrophic Bacteria

Fecal indicator bacteria were quantified for first flush and post flush water samples using standard methodologies. The presence of fecal contamination was determined by growth on the selective and differential membrane filtration m-Coliblue24® broth (Hach Co., Loveland, CO). m-Coliblue24® broth is a nutrient, lactose-based medium that selects against the growth of non-coliforms. Total coliform colonies appear red due to the presence of the non-selective dye, 2,3,5-triphenoltetrazolium chloride (TTC). Escherichia coli colonies are distinguished by a blue color which results from the action of b-glucuronidase enzyme on the 5-Bromo-4-chloro-3-indolyl-beta-d-glucuronide substrate contained in m-Coliblue24®. One hundred milliliters of each water sample and appropriate dilutions were filtered, and the filter was placed on a pad soaked with 2 ml of the Coliblue24® broth. The filters were incubated at 37 °C and growth was observed at 24 h. Post flush water samples were collected in triplicate and each replicate was analyzed separately. Sterile water was filtered as a negative control and was also inoculated with environmental isolates of E. coli and Klebsiella pneumoniae as positive controls. Heterotrophic bacteria were enumerated for biofilm, first flush, and post flush samples by plating on R2A agar followed by incubation at 30 °C for 2 weeks.

Culture of Drinking Water and Biofilm Samples for Pathogenic Bacteria

The drinking water and biofilm samples were analyzed for the presence of Mycobacterium, Legionella, and Helicobacter by organism appropriate culture techniques. Due to overgrowth by other micoorganisms, specific selection methods were employed to target the organisms of interest. To select for members of the genus Mycobacterium, 200 μl of each unconcentrated water sample as well as the pooled biofilm suspension were treated with a final concentration of 0.005 % cetyl pyridinium chloride (CPC) (Sigma, St. Louis, MO) for 30 min as previously described [25]. After CPC treatment, 100 μl was plated onto M7H10 agar (Difco) and two replicates were plated for each sample and incubated at 37 °C for up to 3 weeks. To select for Legionella species, each sample was heated to 50 °C for 30 min in a water bath [26]. Subsequently, 100 μl was plated onto enriched Legionella agar (Difco) and two replicates were plated for each sample and incubated at 37 °C for 1 week. The samples were also cultured on H. pylori specific HP medium [24]. The plates were placed in a BBL anaerobe jar with a BBL CampyPak Plus™, and incubated for 1 week at 37 °C. All presumptive isolates were subcultured and subsequently identified by PCR and phylogenetic analysis. All culture assays included control strains inoculated into sterile water and treated according to specific selection protocols.

DNA Extraction from Biofilm and Water Samples

Nucleic acids were extracted from the pooled biofilm suspensions and from water samples. DNA was extracted within 48 h of sampling and the extracts were immediately frozen at −20 °C. Biofilm samples were concentrated by centrifugation with all but 100 μl of the supernatant removed followed by resuspension of the pellet into the supernatant. The biofilm suspension and concentrated water samples were added to 2-ml plastic screw cap tubes with o-rings (Fisher) containing 0.4 g of 0.1 mm sterile glass beads. Two hundred microliters of lysis buffer consisting of 20 mM sodium acetate (Fisher Scientific, Fair Lawn, NJ), 0.5 % sodium dodecyl sulfate (Fisher), and 1 mM ethylenediamine-tetraacetic acid (Fisher) and 500 μl phenol (pH 8.1) (Fisher) was also added to each 2-ml tube, and the mixture was homogenized in a Fastprep® FP120 cell disrupter at speed 5.0 for 40 s. After homogenization, samples were placed on ice for 10 min. The samples were then centrifuged at 12,000×g for 10 min. The DNA was precipitated by transferring the supernatant to a fresh 2-ml tube containing an equal volume of chloroform: isoamylalcohol (24:1). The samples were vortexed for 30 s and then centrifuged at 12,000×g for 5 min. The supernatant was transferred to another fresh tube containing an equal volume of isopropanol and 1/10 volume of 3 M sodium acetate and held at −20 °C for 24 h. The nucleic acids were subsequently pelleted by centrifugation, washed once with 70 % ethanol, air-dried, and finally resuspended in 100 μl of Tris-EDTA buffer (TE) consisting of 10 mM Tris and 1 mM EDTA (Fisher).

PCR Amplification, Sequencing, and Phylogenetic Analysis

The target genes, sequences, product sizes, and PCR conditions are listed in Table 1. To ensure that the PCR reaction was not inhibited by environmental contaminants, amplification of each sample was performed using eubacterial 16S rRNA primers as described by Voytek et al. [31]. Primer sets amplifying gene fragments ranging from 400–1030 bp were chosen from previously published assays due their high level of reproducibility and high detection limits (data not shown). Amplification of the PCR products was done in a 25-μl PCR mixture containing 1× PCR buffer II, 200 ng template DNA, 200 μM (each) deoxynucleoside triphosphates (Takara Bio Inc., Japan), 0.1 μM (each) of primer (Integrated DNA Technologies, Coralville, IA), and 1 U LA Taq polymerase (Takara). Aliquots of each PCR product were separated by electrophoresis in a 0.8 % (w/v) agarose gel (Fisher) in TBE buffer consisting of 90 mM Tris-HCl (Fisher), 80 mM boric acid (Fisher), 2.5 mM EDTA (Fisher) and stained with ethidium bromide (0.5 μg/ml). PCR products were purified using the Qiaquick PCR purification kit (QIAGEN, Valencia, CA) according to the manufacturer’s instructions. Automated sequencing from both strands of PCR products of positive samples was performed by the Molecular Research Core Facility at Idaho State University. DNA sequences were assessed for their similarity to published DNA sequences using the BLAST database (http://www.ncbi.nlm.nih.gov/BLAST/). Sequences were aligned with ClustalW [32]. Phylogenetic trees were constructed using the neighbor-joining method [33] and the Jukes-Cantor distance model [34] with bootstrap values of 1000 replicates within MEGA v4.0 [35]. All sequences were deposited in GenBank, accession numbers HQ018935–HQ018989.
Table 1

Primer sequences, references, and PCR conditions

Target (reference)

Sequence

Product size

PCR conditions

16S RNA gene Legionella spp. [27]

LEG-225 5′AAGATTAGCCTGCGTCCGAT; LEG-858 5′GTCAACTTATCGCGTTTGCT

656 bp

94 °C 2 min (1 cycle); 94 °C 20 s, 60 °C 30 s, 72 °C 40 s (40 cycles); 72 °C 5 min (1 cycle)

16S RNA gene Mycobacterium spp. [28]

MycgenF 5′ AGAGTTTGATCCTGGCTCAG; MycgenR 5′ TGCACACAGGCCACAAGGGA

1030 bp

95 °C 2 min (1 cycle); 93 °C 1 min, 60 °C 1 min, 72 °C 1 min (35 cycles); 72 °C 5 min (1 cycle)

16S RNA gene Helicobacter spp. [29]

HS1 5′ AACGATGAAGCTTCTAGCTTGCTAG; HS2 5′ GTGCTTATTCGTTAGATACCGTCAT

400 bp

94 °C 5 min (1 cycle); 94 °C 1 min, 65 °C 1 min, 72 °C 1 min (35 cycles); 72 °C 5 min (1 cycle)

16S RNA gene Eubacteria [30]

46f 5′ GCYTAACACATGCAAGTCGA; 519r 5′ GTATTACCGCGGCKGCTG

490 bp

95 °C 5 min (1 cycle); 94 °C 0.5 min, 56 °C 0.5 min, 72 °C 1.5 min (30 cycles); 72 °C 7 min (1 cycle)

Statistical Analysis

All data were compiled and for all instances where plate count values had a value of zero indicating none detected, a substitution rule was used [36]. An arbitrary value (0.25) was chosen to replace all zero plate counts so that log transformations could be performed. Multiple linear regression and logistic regression tests were performed in Minitab® to determine correlations between pH, temperature, drinking water and biofilm heterotrophic bacteria, total coliform bacteria, Helicobacter, Legionella, and Mycobacterium [37]. Additionally, paired and Welch two sample t tests were performed on heterotrophic and total coliform bacteria to determine if there were significant differences between first flush, post flush, and biofilm samples [37]. Fisher’s exact tests were performed to determine if the presence of Mycobacterium, Legionella, and/or Helicobacter had a relationship with each other [38]. Fisher’s exact tests were also performed to determine if there was a relationship between Mycobacterium, Legionella, and Helicobacter and the source of the drinking water (treated municipal or groundwater well) [38]. A Benjamini-Hochberg correction (10 %) was applied to all analyses to minimize false discovery due to multiple comparisons [39]. All P values reported in this study were significant after correcting for multiple comparisons.

Results

Physical Characteristics of Sampled Drinking Water

A total of 57 sites were sampled during this study. Sixteen samples were collected from public buildings and private residences that had drinking water supplied by treated municipal systems, while the 41 remaining systems were community and private groundwater wells. Total and free chlorine were quantified in drinking water sampled from municipal systems and ranged from none detected to 2.5 mg/l, and none detected to 1.3 mg/l, with means of 0.34 mg/l and 0.27 mg/l, respectively. The pH of the drinking water ranged from 5.82–9.56 with a mean of 7.42. The temperature of the bulk water was recorded after flushing the tap and ranged from 8–33 °C with a mean of 15.7 °C and one outlier at 46 °C. Treated municipal systems had a mean temperature of 21.5 °C, while groundwater well systems had a mean temperature of 14.2 °C. Simple linear regression and logistic regression were used to analyze relationships between the measured physical characteristics and HPC bacteria, total coliforms, Legionella, Mycobacterium, and Helicobacter. No significant statistical correlation was detected between the measured physical characteristics and any of the bacteria identified.

Detection of Heterotrophic Bacteria and Fecal Indicator Bacteria

Heterotrophic bacteria were enumerated to assess whether these organisms were associated with the presence of potential pathogens. Table 2 shows the range and arithmetic mean of HPC bacteria in first flush, biofilm, and post flush drinking water samples. Differences in the mean HPC populations between the first flush and post flush fractions collected were evaluated using Minitab®. There was a significant difference in mean HPC bacteria when first flush and bulk water samples were compared (P = 0.025) with first flush samples having higher numbers of HPC bacteria on average. Differences in HPC bacteria between treated municipal and groundwater wells were also evaluated (P = 0.029). There was a difference in HPC bacteria in biofilm samples depending on the drinking water source (P = 0.049); however, after applying the Benjamini-Hochberg correction, this relationship was not significant. Overall, biofilm samples collected from groundwater wells had higher HPC bacteria counts than biofilm samples collected from treated municipal systems. There was not a significant difference in HPC bacteria numbers between the source water types for the post flush water samples.
Table 2

Range and arithmetic mean of HPC bacteria, total coliforms, and E. coli

Bacteria

Measurement

Source

Treated municipal

(n = 16)

Groundwater well (n = 41)

Heterotrophic plate counts

 In first flush (CFU/ml)

Range

*

1.5 × 100 − 5.12 × 107

Arithmetic mean

*

2.81 × 106

 In water (CFU/ml)

Range

3.57 × 102 − 5.15 × 105

2.0 × 100 − 9.23 × 105

Arithmetic mean

9.02 × 104

5.7 × 104

 In biofilm (CFU/mm2)

Range

<1 − 1.24 × 105

<1 − 3.22 × 105

Arithmetic mean

1.79 × 104

4.29 × 104

Total coliforms

 In first flush (CFU/100 ml)

Range

*

<1 − 1.19 × 103

Arithmetic mean

*

1.17 × 102

 In water (CFU/100 ml)

Range

<1 − 2.63 × 101

<1 − 2.96 × 103

Arithmetic mean

2.71 × 100

1.07 × 102

Escherichia coli

 In first flush (CFU/100 ml)

Range

*

<1

Arithmetic mean

*

<1

 In water (CFU/100 ml)

Range

<1

<1 − 2.22 × 102

Arithmetic mean

<1

5.68 × 100

*No samples were taken in this category

Total coliform bacteria were enumerated in first flush and post flush drinking water samples. Coliform bacteria were found in both treated municipal (37.5 % or 6/16) and untreated groundwater wells (40 % or 16/40) in post flush water samples. E. coli were not observed in treated municipal samples but were found in 10 % or 4/40 of post flush groundwater well samples. Table 2 shows the range and arithmetic mean of coliform bacteria and E. coli in drinking water samples.

Presence of Mycobacterium, Legionella, and Helicobacter

Mycobacterium species were detected in 35.1 % or 20/57 of the locations sampled, with 15 found in the biofilm fraction and 8 in the drinking water fraction. Of the 20 locations that tested positive for Mycobacterium, 8 were treated municipal systems and 12 were groundwater well systems. Figure 1 shows the phylogenetic relatedness of the PCR and culture isolates. The Mycobacterium species sequences detected were closely related to known species including M. gilvum, M. mucogenicum, M. murale, M. flavescens, M. gordonae, M. manitobense, and members of the M. avium complex (MAC) (>95 % similarity).
Fig. 1

Phylogenetic relationship of 16S rRNA gene amplified with Mycobacterium genus-specific primers with Corynebacterium glutamicum as the out-group. Reference sequences are in bold with accession numbers in parentheses. Sequences from this study are indicated by code as follows: DW drinking water, BF biofilm, p PCR, c culture, g groundwater, and m municipal

To assess whether there was a relationship among the presence of Mycobacterium and total coliforms or HPC bacteria, logistic regression was applied in Minitab®. Identical analyses were performed for all three genera tested in this study. The analysis showed a relationship among Mycobacterium detected in the system and HPC bacteria in biofilms and drinking water (P = 0.009 and P = 0.05, respectively). This showed that, in general, as HPC bacteria increased, the odds of encountering Mycobacterium increased as well.

Legionella species were detected in 21 % or 12 of the 57 locations sampled with 5 of those in the biofilm fraction, 8 in the drinking water fraction and only one occurrence of Legionella in both the biofilm and drinking water. Of the 12 samples positive for Legionella, 8 were at treated municipal sites and 4 were in groundwater. Figure 2 shows the phylogenetic relatedness of Legionella detected by PCR directly and from culture isolates. The Legionella species detected include uncultured L. sp., L. pneumophila, L. sp., L. fairfieldensis, and L. dresdeniensis (sequence similarity >95 %).
Fig. 2

Phylogenetic relationship of 16S rRNA gene amplified with Legionella genus-specific primers with Coxiella burnetii as the out-group. Reference sequences are in bold with accession numbers in parentheses. Sequences from this study are indicated by code as follows: DW drinking water, BF biofilm, p PCR, c culture, g groundwater, and m municipal

The results of the logistic regression showed a positive relationship among post flush HPC bacteria counts and Legionella in the system (P = 0.003). In general, as HPC bacteria increased, the odds of encountering Legionella increase as well. The greatest interaction occurred among Legionella detected in the biofilm fraction and post flush HPC bacteria (P = 0.001). Coliforms were present in 6 of the 12 samples where Legionella were detected, but there was no significant relationship among total coliforms and the presence of Legionella (P = 0.679). However, there was a significant association among E. coli and the presence of Legionella (P = 0.018).

Helicobacter species were detected in 7 % or 4/57 of locations sampled, with 2 of those in the biofilm and 2 in the drinking water. There were no occurrences of Helicobacter in the drinking water and biofilm concurrently. All of the positive samples were identified by PCR alone. Figure 3 shows the phylogenetic relatedness of the Helicobacter sequences detected by PCR directly. The only Helicobacter species detected was H. pylori. Coliforms were found in 2 of the 4 samples where Helicobacter were detected. Logistic regression did not demonstrate any significant correlation among any of the biological or physical parameters collected or the source type of the drinking water and the presence of Helicobacter.
Fig. 3

Phylogenetic relationship of 16S rRNA gene amplified with Helicobacter genus-specific primers with Campylobacter jejuni as the out-group. Reference sequences are in bold with accession numbers in parentheses. Sequences from this study are indicated by code as follows: DW drinking water, BF biofilm, p PCR, c culture, g groundwater, and m municipal

To determine whether there was a relationship among each of the three genera of interest, a Fisher’s exact test was performed. There was no statistically significant relationship between occurrences of the three genera.

Discussion

The results of our study show that Mycobacterium, Legionella, and Helicobacter can be found in drinking water and associated biofilms on the Crow Reservation, in both treated municipal water and untreated well water. The data also indicated that the number of HPC bacteria correlated with the presence of Mycobacterium or Legionella. To the authors’ knowledge, this is the first study to look at the factors related to the presence of potential pathogens in drinking water systems on an American Indian Reservation.

This study found that community and private groundwater wells as well as municipal samples contained coliform bacteria. In our study area, municipal and groundwater systems are vulnerable to contamination, particularly during wet seasons that result in flooding events. These flooding events can drastically increase the turbidity of surface waters and hinder water treatment, potentially allowing coliform contamination of finished water. During March 2007, the largest treatment facility on the Reservation (located in Crow Agency, MT) was required to shut down due to mud and debris that clogged the intake pipe after a flood (personal communication, Barbara Burkland, USEPA). During this time, an order was issued for all of Crow Agency that drinking water must be boiled to be safe for drinking. Fourteen of the samples collected from treated, municipal sources were taken from private residences and public buildings supplied by the water distribution system at Crow Agency, MT. The remaining two municipal samples were collected from private residences in Lodgegrass, MT. Five out of the fourteen municipal samples were collected during the March 2007 boil order that was issued due to the flooding and closure of the drinking water treatment facility at Crow Agency, MT. Each of the five samples collected during the boil order tested positive for coliform bacteria but were negative for the presence of E. coli. This particular event accounts for all of the coliform-positive municipal system samples except one, which occurred shortly after this flood. Groundwater wells in rural areas are vulnerable to flooding but are also susceptible to contamination from septic systems and inappropriate disposal of sewage effluents and sludges [40]. During sample collection, we occasionally observed instances where well heads were completely inundated after precipitation and water at the tap was turbid and/or odiferous.

Coliform bacteria often do not adequately predict the presence of pathogens, as has been demonstrated in waterborne outbreaks of Cryptosporidia, Giardia, and Salmonella [41]. The lack of concurrence between the detection of Mycobacterium, Legionella, and Helicobacter and coliforms indicates that fecal indicator bacteria have limited use in predicting the presence of these environmental pathogens in drinking water sources. Our finding agrees with that of others who found no correlation between these organisms and fecal coliform bacteria [31, 42, 43].

Heterotrophic plate count bacteria are the microbiota of drinking water and include a wide range of organisms including Acinetobacter, Aeromonas, Bacillus, Corynebacterium, Pseudomonas, Mycobacterium, and Legionella [44]. This study has shown that HPC bacteria can occur in numbers >106 CFU/ml and that water that was stagnant in plumbing (first flush) had significantly greater numbers of HPC bacteria than water that has been collected after flushing. Water stagnation in drinking water pipes promotes bacterial accumulation which may compromise microbiological quality of drinking water when those organisms are flushed out [45]. In this study, groundwater wells generally had higher levels of HPC bacteria than treated municipal water, which can be at least partially explained by the presence of chlorine residuals in municipal systems.

Heterotrophic plate count bacteria in biofilm and drinking water fractions had significant relationships with the presence of both Mycobacterium and Legionella. Logistic regression showed that as the number of HPC bacteria increase, the odds of encountering Mycobacterium or Legionella increase as well. The relationship between Mycobacterium and HPC in drinking water systems is unclear with some studies finding a relationship while others have not [43, 46]. Similarly, there are very few data regarding the usefulness of HPC counts for predicting the presence of Legionella. However, our data are in agreement with LeChevallier et al. [47] who concluded that HPC bacteria were useful for predicting the presence of opportunistic pathogens and provide insight into the overall quality of drinking water. There was no relationship between HPC bacteria and the presence of Helicobacter.

Mycobacterium, Legionella, and Helicobacter were found in both treated municipal water and untreated well water systems. Mycobacterium was found more often in groundwater systems than in treated municipal systems. The results of this study are consistent with other reports of Mycobacterium in treated municipal and groundwater systems [48, 49, 50]. Similar to other reports, Legionella species were found more often in treated municipal systems than in groundwater systems. In other studies, Legionella has been frequently found in municipal water systems and sporadically in groundwater [15, 27, 50, 51, 52]. It is possible that plumbing in buildings with light or sporadic use could promote the planktonic and/or necrotrophic growth of Legionella as described by others [53]. Helicobacter were detected in four locations of our study area with 50 % in treated municipal systems and 50 % in untreated groundwater systems. One of the instances of Helicobacter occurred during the flood event that closed the water treatment facility for a short period of time. Reports of Helicobacter detection in drinking water have been intermittent with most reports finding infrequent positive samples [30, 54]. Although the environmental reservoir of Helicobacter is unknown, it is possible that water distribution systems may be vulnerable to contamination through breaks or leaks in distribution pipes. Groundwater systems that are too shallow may be at risk due to the influence of surface water which could be contaminated by agricultural practices and inadequate sewage disposal [40].

Mycobacterium, Legionella, and Helicobacter were detected in both biofilm and drinking water samples. All of the Mycobacterium sequences detected in this study were of the nontuberculous Mycobacterium group (NTM). M. gilvum and M. avium complex were most frequently identified (>95 % sequence similarity) and were both found in biofilms more often than drinking water. MAC accounts for over 70 % of nontuberculous mycobacterial disease in the USA and for more than 95 % of nontuberculous disease among persons infected with human immunodeficiency virus (HIV) [55]. It has been shown that MAC isolates recovered from hospital water had a close relationship (large-restriction-fragment pattern analysis) with clinical isolates recovered from patients indicating that water could be the reservoir for infection [56]. Other sequences identified in this study were of >95 % similarity to M. gordonae, M. flavescens, and M. mucogenicum. These species are all known to be inhabitants of drinking water systems and have been implicated in adverse health outcomes [11, 12, 49, 57].

L. pneumophila occurred more often in biofilm samples while sequences identified as Legionella sp. were more often identified in drinking water samples. The Legionella species sequences detected in this study were mainly L. pneumophila and Legionella sp. but also included sequences similar to L. fairfieldensis, L. dresdeniensis, and L. birminghamiensis. L. pneumophila is a well-documented opportunistic pathogen that has an infection rate of approximately 1–6 %, with a mortality rate of 10–15 % [16]. Other Legionella species such as L. fairfieldensis and L. birminghamiensis have been documented in drinking water systems, but are not implicated in health effects [58]. Interestingly, both Mycobacterium and Legionella had greater rates of culture-positive tests in biofilm samples. This agrees with previously published data that tap water biofilms are protective and supportive for these organisms [8, 48, 50, 53, 59, 60, 61, 62].

H. pylori sequences occurred in two drinking water samples and two biofilm samples. Although H. pylori were not detected in a large number of locations, biofilm sampling doubled the detection of this organism. Incorporation of H. pylori into a tap water biofilm may provide protection from the environmental stress associated with drinking water environments [63]. Research in one rural community of Montana found that the prevalence of H. pylori was greater than 50 % as measured by the 13C urea breath test (unpublished data, Melius et al. 2005). That study also indicated that the presence of H. pylori infection was associated with regular consumption of city water as indicated by questionnaire results. Untreated well water has also been implicated in clinical infections in the USA [20, 64]. Areas with poor water quality may be more likely to have higher rates of water-borne transmission of this disease, especially in children [30, 54].

In conclusion, microbes such as M. avium, L. pneumophila, and H. pylori can be found in drinking water systems on the Crow Reservation, Montana. To address health disparities in underserved communities such as American Indian reservations it is important to determine potential reservoirs of infection. These results are pertinent to water utility managers, regulatory agencies, as well as epidemiologists interested in identifying disease-causing agents in rural drinking water systems. In addition, this study provides insight into the ecology of potentially pathogenic bacteria in drinking water systems.

Notes

Acknowledgments

The authors would like to thank the entire Crow Environmental Health Steering Committee for providing insight into research in reservation communities and community support for this work. Thanks to Crow community coordinators, Crescentia Cummins and Gail Whiteman, without their support, sample collection would not have been possible. Additional thanks to Al Parker for statistical support.

This work was supported by the National Institutes of Health grants; P20MD002317 from the National Center on Minority Health and Health Disparities, and P20 RR-16455-04 from the National Institute for General Medical Science. Dr. Ford was supported in part by a grant from the US Environmental Protection Agency’s Science to Achieve Results (US-EPA STAR) program and Crystal Richards and Margaret Eggers were supported by US-EPA STAR Fellowships. Although the research described in the article has been funded in part by the US Environmental Protection Agency’s STAR program through grant numbers RD833706, FP916936, and FP916744, it has not been subjected to any EPA or NIH review and, therefore, does not necessarily reflect the views of the Agencies, and no official endorsement should be inferred.

References

  1. 1.
    U.S. Census Bureau (2007) Current Housing Reports, Series H150/07, American Housing Survey for the United States, U.S. Government Printing Office, Washington, DC, 20401 (http://www.census.gov/prod/2008pubs/h150-07.pdf)
  2. 2.
    Craun MF, Craun GF, Calderon RL, Beach MJ (2006) Waterborne outbreaks reported in the United States. J Water Health 04(Suppl 2):19–30CrossRefGoogle Scholar
  3. 3.
    National Center for Health Statistics (2010) Health, Unites States, 2009: with Special Feature on Medical Technology, Hyattsville, MD (http://www.cdc.gov/nchs/data/hus/hus09.pdf)
  4. 4.
    Anonymous (1999) The health care challenge: acknowledging disparity, confronting discrimination, and ensuring equality. United States National Archives and Records Administration, Washington, 20402Google Scholar
  5. 5.
    Harwell TS, Miller SH, Lemons DL, Helgerson SD, Gohdes D (2006) Cancer incidence in Montana: rates for American Indians exceed those for whites. Am J Prev Med 30:493-7Google Scholar
  6. 6.
    Arnold M, Moore SP, Hassler S, Ellison-Loschmann L, Forman D, Bray F (2014) The burden of stomach cancer in indigenous populations: a systematic review and global assessment. Gut 63:64–71. doi: 10.1136/gutjnl-2013-305033 CrossRefPubMedGoogle Scholar
  7. 7.
    Cummins C, Doyle J, Kindness L, Lefthand MJ, Walk U, Bends AL, Broadaway SC, Camper AK, Fitch R, Ford TE, Hamner S, Morrison AR, Richards CL, Young SL, Eggers MJ (2010) Community-based participatory research in Indian country improving health through water quality research and awareness. Fam Community Health 33:166–174. doi: 10.1097/FCH.0b013e3181e4bcd8 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Lehtola MJ, Torvinen E, Kusnetsov J, Pitkanen T, Maunula L, von Bonsdorff CH, Martikainen PJ, Wilks SA, Keevil CW, Miettinen IT (2007) Survival of Mycobacterium avium, Legionella pneumophila, Escherichia coli, and caliciviruses in drinking water-associated biofilms grown under high-shear turbulent flow. Appl Environ Microbiol 73:2854–2859. doi: 10.1128/aem. 02916-06 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Falkinham JO, Norton CD, LeChevallier MW (2001) Factors influencing numbers of Mycobacterium avium, Mycobacterium intracellulare, and other Mycobacteria in drinking water distribution systems. Appl Environ Microbiol 67:1225–1231CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Cassidy PM, Hedberg K, Saulson A, McNelly E, Winthrop KL (2009) Nontuberculous mycobacterial disease prevalence and risk factors: a changing epidemiology. Clin Infect Dis 49:E124–E129. doi: 10.1086/648443 CrossRefPubMedGoogle Scholar
  11. 11.
    Mazumder SA, Hicks A, Norwood J (2010) Mycobacterium gordonae pulmonary infection in an immunoocompetent adult. N Am J Med Sci 2:205–207PubMedPubMedCentralGoogle Scholar
  12. 12.
    Guillen SM, Hospital JS, Mampaso EG, Espejo AG, Baquedano CE, Calderon AO (1986) Gluteal abscess caused by Mycobacterium flavescens. Tubercle 67:151–153CrossRefGoogle Scholar
  13. 13.
    Costa J, Tiago I, da Costa MS, Verissimo A (2005) Presence and persistence of Legionella spp. in groundwater. Appl Environ Microbiol 71:663–671. doi: 10.1128/aem. 71.2.663-671.2005 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Turetgen I, Sungur EI, Cotuk A (2005) Enumeration of Legionella pneumophila in cooling tower water systems. Environ Monit Assess 100:53–58. doi: 10.1007/s10661-005-7058-3 CrossRefPubMedGoogle Scholar
  15. 15.
    Marciano-Cabral F, Jamerson M, Kaneshiro ES (2010) Free-living amoebae, Legionella and Mycobacterium in tap water supplied by a municipal drinking water facility. J Water Health 08:71–82CrossRefGoogle Scholar
  16. 16.
    Percival S, Chalmers R, Embrey M, Hunter P, Sellwood J, Wyn-Jones P (2004) Microbiology of waterborne diseases. Elsevier Academic Press, San Diego, California, 92101Google Scholar
  17. 17.
    Kramer MH, Ford TE (1994) Legionellosis: ecological factors of an environmentally ‘new’ disease. Zentralbl Hyg Umweltmed 195:470–482PubMedGoogle Scholar
  18. 18.
    Sasaki K, Tajiri Y, Sata M, Fujii Y, Matsubara F, Zhao MG, Shimizu S, Toyonaga A, Tanikawa K (1999) Helicobacter pylori in the natural environment. Scand J Infect Dis 31:275–280CrossRefPubMedGoogle Scholar
  19. 19.
    Perez-Perez GI, Rothenbacher D, Brenner H (2004) Epidemiology of Helicobacter pylori infection. Helicobacter 9:1–6CrossRefPubMedGoogle Scholar
  20. 20.
    Bellack NR, Koehoorn MW, MacNab YC, Morshed MG (2006) A conceptual model of water’s role as a reservoir in Helicobacter pylori transmission: a review of the evidence. Epidemiol Infect 134:439–449. doi: 10.1017/s0950268806006005 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Montana Dept of Labor and Industry Research and Analysis Bureau (2008) Demographic and economic information for the Crow Reservation. Office of Research & Analysis, Job Service Division, Montana Dept of Labor & Industry, Helena, MT, pp 1–8Google Scholar
  22. 22.
    Geach J (2007) Source water delineation and assessment report. United States Environmental Protection Agency, Helena, pp 1–34Google Scholar
  23. 23.
    Turenne CY, Semret M, Cousins DV, Collins DM, Behr MA (2006) Sequencing of hsp65 distinguishes among subsets of the Mycobacterium avium complex. J Clin Microbiol 44:433–440. doi: 10.1128/jcm. 44.2.433-440.2006 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Degnan AJ, Sonzogni WC, Standridge JH (2003) Development of a plating medium for selection of Helicobacter pylori from water samples. Appl Environ Microbiol 69:2914–2918. doi: 10.1128/aem. 69.5.2914-2918.2003 CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Schulze-Robbecke R, Weber A, Fischeder R (1991) Comparison of decontamination methods for the isolation of mycobacteria from drinking water samples. J Microbiol Methods 14:177–183CrossRefGoogle Scholar
  26. 26.
    Bartie C, Venter SN, Nel LH (2003) Identification methods for Legionella from environmental samples. Water Res 37:1362–1370CrossRefPubMedGoogle Scholar
  27. 27.
    Wullings BA, van der Kooij D (2006) Occurrence and genetic diversity of uncultured Legionella spp. in drinking water treated at temperatures below 15 degrees C. Appl Environ Microbiol 72:157–166. doi: 10.1128/aem. 72.1.157-166.2006 CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Böddinghaus B, Rogall T, Flohr T, Blöcker H, Böttger EC (1990) Detection and identification of mycobacteria by amplification of rRNA. J Clin Microbiol 28:1751–1759Google Scholar
  29. 29.
    Germani Y, Dauga C, Duval P, Huerre M, Levy M, Pialoux G, Sansonetti P, Grimont PAD (1997) Strategy for the detection of Helicobacter species by amplification of 16S rRNA genes and identification of H-felis in a human gastric biopsy. Res Microbiol 148:315–326CrossRefPubMedGoogle Scholar
  30. 30.
    Watson CL, Owen RJ, Said B, Lai S, Lee JV, Surman-Lee S, Nichols G (2004) Detection of Helicobacter pylori by PCR but not culture in water and biofilm samples from drinking water distribution systems in England. J Appl Microbiol 97:690–698. doi: 10.1111/j.1365-2672.2004.02360.x CrossRefPubMedGoogle Scholar
  31. 31.
    Voytek MA, Ashen JB, Fogerty LR, Kirshtein JD, Landa ER (2005) Detection of Helicobacter pylori and fecal indicator bacteria in five North American rivers. J Water Health 3:405–422CrossRefPubMedGoogle Scholar
  32. 32.
    Thompson JD, Gibson TJ, Higgins DG (2002) Multiple sequence alignment using ClustalW and ClustalX. Curr Protoc Bioinformatics Chapter 2: Unit 2.3.Google Scholar
  33. 33.
    Saitou N, Nei M (1987) The neighbor-joining method—a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425PubMedGoogle Scholar
  34. 34.
    Jukes TH, Cantor CR (1969) Evolution of protein molecules. In: Munro HN (ed) Mammalian protein metabolism. Academic, New York, pp 21–132CrossRefGoogle Scholar
  35. 35.
    Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol 24:1596–1599. doi: 10.1093/molbev/msm092 CrossRefPubMedGoogle Scholar
  36. 36.
    United States Environmental Protection Agency (1998) Guidance for data quality assessment—practical methods for data analysis. Ed. Office of Research and Development, Washington, 20460Google Scholar
  37. 37.
    Kutner M, Nachtsheim C, Neter J, Li W (2004) Applied linear statistical models. McGraw-Hill/Irwin, New YorkGoogle Scholar
  38. 38.
    Conover WJ (1999) Practical nonparametric statistics. Elm Street Publishing Services, HinsdaleGoogle Scholar
  39. 39.
    Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Statist Soc Ser B 57:289–300Google Scholar
  40. 40.
    Bitton G, Gerba CP (1984) Groundwater pollution microbiology: the emerging issue. John Wiley & Sons, New YorkGoogle Scholar
  41. 41.
    Kramer MH, Herwaldt BL, Calderon RL, Juranek DD (1996) Surveillance for waterborne-disease outbreaks—United States, 1993–1994. vol. 45. Centers for Disease Control, Washington, pp 1–33Google Scholar
  42. 42.
    Palmer CJ, Bonilla GF, Roll B, Paszkokolva C, Sangermano LR, Fujioka RS (1995) Detection of Legionella species in reclaimed water and air with the ENVIROAMP Legionella PCR kit and direct fluorescent-antibody staining. Appl Environ Microbiol 61:407–412PubMedPubMedCentralGoogle Scholar
  43. 43.
    September SM, Brozel VS, Venter SN (2004) Diversity of nontuberculoid Mycobacterium species in biofilms of urban and semiurban drinking water distribution systems. Appl Environ Microbiol 70:7571–7573. doi: 10.1128/aem. 70.12.7571-7573.2004 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Allen MJ, Edberg SC, Reasoner DJ (2004) Heterotrophic plate count bacteria—what is their significance in drinking water? Int J Food Microbiol 92:265–274. doi: 10.1016/j.ijfoodmicro.2003.08.017 CrossRefPubMedGoogle Scholar
  45. 45.
    Manuel CM, Nunes OC, Melo LF (2010) Unsteady state flow and stagnation in distribution systems affect the biological stability of drinking water. Biofouling 26:129–139. doi: 10.1080/08927010903383448 CrossRefPubMedGoogle Scholar
  46. 46.
    Iivanainen EK, Martikainen PJ, Vaananen PK, Katila ML (1993) Environmental factors affecting the occurrence of Mycobacteria in brook waters. Appl Environ Microbiol 59:398–404PubMedPubMedCentralGoogle Scholar
  47. 47.
    LeChevallier MW, Seidler RJ, Evans TM (1980) Enumeration and characterization of standard plate-count bacteria in chlorinated and raw water supplies. Appl Environ Microbiol 40:922–930PubMedPubMedCentralGoogle Scholar
  48. 48.
    Schwartz T, Kalmbach S, Hoffmann S, Szewzyk U, Obst U (1998) PCR-based detection of mycobacteria in biofilms from a drinking water distribution system. J Microbiol Methods 34:113–123CrossRefGoogle Scholar
  49. 49.
    Le Dantec C, Duguet JP, Montiel A, Dumoutier N, Dubrou S, Vincent V (2002) Occurrence of mycobacteria in water treatment lines and in water distribution systems. Appl Environ Microbiol 68:5318–5325. doi: 10.1128/aem. 68.11.5318-5325.2002 CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Whiley H, Keegan A, Fallowfield H, Bentham R (2014) Detection of Legionella, L. Pneumophila and Mycobacterium avium complex (MAC) along potable water distribution pipelines. Int J Environ Res Public Health 11:7393–7405. doi: 10.3390/ijerph110707393 CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Brooks T, Osicki RA, Springthorpe VS, Sattar SA, Filion L, Abrial D, Riffard S (2004) Detection and identification of Legionella species from groundwaters. J Toxicol Environ Health A 67:1845–1859. doi: 10.1080/15287390490492449 CrossRefPubMedGoogle Scholar
  52. 52.
    Donohue MJ, O’Connell K, Vesper SJ, Mistry JH, King D, Kostich M, Pfaller S (2014) Widespread molecular detection of Legionella pneumophila serogroup 1 in cold water taps across the United States. Environ Sci Technol 48:3145–3152. doi: 10.1021/es4055115 CrossRefPubMedGoogle Scholar
  53. 53.
    Temmerman R, Vervaeren H, Noseda B, Boon N, Verstraete W (2006) Necrotrophic growth of Legionella pneumophila. Appl Environ Microbiol 72:4323–4328. doi: 10.1128/aem. 00070-06 CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Bunn JEG, MacKay WG, Thomas JE, Reid DC, Weaver LT (2002) Detection of Helicobacter pylori DNA in drinking water biofilms: implications for transmission in early life. Lett Appl Microbiol 34:450–454CrossRefPubMedGoogle Scholar
  55. 55.
    Reed C, von Reyn CF, Chamblee S, Ellerbrock TV, Johnson JW, Marsh BJ, Johnson LS, Trenschel RJ, Horsburgh CR (2006) Environmental risk factors for infection with Mycobacterium avium complex. Am J Epidemiol 164:32–40. doi: 10.1093/aje/kwj159 CrossRefPubMedGoogle Scholar
  56. 56.
    Aronson T, Holtzman A, Glover N, Boian M, Froman S, Berlin OGW, Hill H, Stelma G (1999) Comparison of large restriction fragments of Mycobacterium avium isolates recovered from AIDS and non-AIDS patients with those of isolates from potable water. J Clin Microbiol 37:1008–1012PubMedPubMedCentralGoogle Scholar
  57. 57.
    Marshall C, Samuel J, Galloway A, Pedler S (2008) Mycobacterium mucogenicum from the Hickman line of an immunocompromised patient. J Clin Pathol 61:140–141. doi: 10.1136/jcp.2007.049486 CrossRefPubMedGoogle Scholar
  58. 58.
    Diederen BMW, de Jong CMA, Aarts I, Peeters MF, van der Zee A (2007) Molecular evidence for the ubiquitous presence of Legionella species in Dutch tap water installations. J Water Health 5:375–383. doi: 10.2166/wh.2007.033 CrossRefPubMedGoogle Scholar
  59. 59.
    Hall-Stoodley L, Lappin-Scott H (1998) Biofilm formation by the rapidly growing mycobacterial species Mycobacterium fortuitum. FEMS Microbiol Lett 168:77–84CrossRefPubMedGoogle Scholar
  60. 60.
    Torvinen E, Lehtola MJ, Martikainen PJ, Miettinen IT (2007) Survival of Mycobacterium avium in drinking water biofilms as affected by water flow velocity, availability of phosphorus, and temperature. Appl Environ Microbiol 73:6201–6207. doi: 10.1128/aem. 00828-07 CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Declerck P, Behets J, van Hoef V, Ollevier F (2007) Replication of Legionella pneumophila in floating biofilms. Curr Microbiol 55:435–440. doi: 10.1007/s00284-007-9006-7 CrossRefPubMedGoogle Scholar
  62. 62.
    Giao MS, Azevedo NF, Wilks SA, Vieira MJ, Keevil CW (2011) Interaction of Legionella pneumophila and Helicobacter pylori with bacterial species isolated from drinking water biofilms. BMC Microbiol 11:57. doi: 10.1186/1471-2180-11-57 CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Garcia A, Salas-Jara MJ, Herrera C, Gonzalez C (2014) Biofilm and helicobacter pylori: from environment to human host. World J Gastroenterol 20:5632–5638. doi: 10.3748/wjg.v20.i19.5632 CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Baker KH, Hegarty JP (2001) Presence of Helicobacter pylori in drinking water is associated with clinical infection. Scand J Infect Dis 33:744–746CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Crystal L. Richards
    • 1
  • Susan C. Broadaway
    • 2
  • Margaret J. Eggers
    • 2
  • John Doyle
    • 3
    • 4
    • 5
  • Barry H. Pyle
    • 2
  • Anne K. Camper
    • 6
  • Timothy E. Ford
    • 7
  1. 1.Department of Biological and Physical SciencesMontana State University BillingsBillingsUSA
  2. 2.Department of Microbiology and Center for Biofilm EngineeringMontana State UniversityBozemanUSA
  3. 3.Little Big Horn CollegeCrow AgencyUSA
  4. 4.Apsaalooke Water and Wastewater AuthorityHardinUSA
  5. 5.Crow Tribal MemberCrow AgencyUSA
  6. 6.Department of Civil Engineering and Center for Biofilm EngineeringMontana State UniversityBozemanUSA
  7. 7.School of Health ProfessionsShenandoah UniversityWinchesterUSA

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