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Article

Identification of 16S rRNA and Virulence-Associated Genes of Arcobacter in Water Samples in the Kathmandu Valley, Nepal

by
Rajani Ghaju Shrestha
1,2,
Yasuhiro Tanaka
3,
Jeevan B. Sherchand
4 and
Eiji Haramoto
2,*
1
Division of Sustainable Energy and Environmental Engineering, Osaka University, Suita, Osaka 565-0871, Japan
2
Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
3
Department of Environmental Sciences, University of Yamanashi, 4-4-37 Takeda, Kofu, Yamanashi 400-8510, Japan
4
Institute of Medicine, Tribhuvan University Teaching Hospital, Kathmandu 1524, Nepal
*
Author to whom correspondence should be addressed.
Pathogens 2019, 8(3), 110; https://doi.org/10.3390/pathogens8030110
Submission received: 8 July 2019 / Revised: 24 July 2019 / Accepted: 25 July 2019 / Published: 26 July 2019
(This article belongs to the Section Waterborne/Foodborne/Airborne Pathogens)
Versions Notes

Abstract

:
This study aimed to determine the prevalence of Arcobacter and five associated virulence genes (cadF, ciaB, mviN, pldA, and tlyA) in water samples in the Kathmandu Valley, Nepal. A total of 286 samples were collected from deep tube wells (n = 30), rivers (n = 14), a pond (n = 1), shallow dug wells (n = 166), shallow tube wells (n = 33), springs (n = 21), and stone spouts (n = 21) in February and March (dry season) and August (wet season), 2016. Bacterial DNA was extracted from the water samples and subjected to SYBR Green-based quantitative PCR for 16S rRNA and virulence genes of Arcobacter. The 16S rRNA gene of Arcobacter was detected in 36% (40/112) of samples collected in the dry season, at concentrations ranging from 5.7 to 10.2 log copies/100 mL, and 34% (59/174) of samples collected in the wet season, at concentrations of 5.4–10.8 log copies/100 mL. No significant difference in Arcobacter 16S rRNA gene-positive results was observed between samples collected in the two seasons (p > 0.05). Seventeen (17%), 84 (84%), 19 (19%), 23 (23%), and 17 (17%) of the 99 Arcobacter 16S rRNA gene-positive samples were also positive for cadF, ciaB, mviN, pldA, and tlyA, respectively. At least one virulence gene was detected in 87 (88%) of the 99 Arcobacter 16S rRNA gene-positive samples. The presence of Arcobacter and the virulence genes in these samples illustrates the persistence of pathogenic bacteria in the environment and highlights the importance of regular monitoring of water for pathogens.

1. Introduction

Fecal contamination of water sources has been a problem in developing countries and is a major factor in the spread of waterborne diseases. Nepal is facing extensive contamination of environmental water sources where enteric pathogens, such as bacteria, viruses, and protozoa, are often detected [1,2,3,4,5,6,7,8,9,10]. Fecal contamination mainly occurs through leakage of sewage pipes, improper disposal of feces, poor construction design of septic tanks, and the use of animal manure in agricultural fields [11,12].
Arcobacter has been detected in the groundwater and river water of many countries including Czech Republic [13], Japan [14], South Africa [15], Spain [16,17], Turkey [18,19,20], and USA [21]. This global prevalence of Arcobacter has had a major impact on groundwater and surface water in the Kathmandu Valley [1,2]. Arcobacter was one of the dominant pathogenic bacteria isolated from groundwater and surface water samples analyzed by next-generation sequencing [1,2]. Moreover, a recently developed SYBR Green-based quantitative PCR (qPCR) assay, which is highly specific to most of the known species of Arcobacter, succeeded in detecting the 16S rRNA gene of Arcobacter in 27% (13/48) of the water samples analyzed [2]. Previous studies conducted in the Kathmandu Valley were limited to small numbers of water samples collected in a single season, which does not allow seasonal variations of Arcobacter within the valley to be identified [1,2].
The pathogenicity of an organism is characterized according to the presence of virulence genes. Miller et al. (2007) identified several virulence genes, such as cadF and cjl349 (fibronectin binding proteins), which are homologs of the putative virulence determinants present in Campylobacter jejuni [22]. Similarly, ciaB (invasion protein), mviN (a protein required for peptidoglycan biosynthesis), pldA (phospholipase), and tlyA (hemolysin) are homologs of putative virulence determinants of Campylobacter, irgA (iron-regulated outer membrane protein) and iroE (siderophore esterase) are homologs found in uropathogenic Escherichia coli, and hecA (filamentous hemagglutinin) and hecB (hemolysin activation protein) are present in Erwinia crysthanthemi contributing to epidermal cell killing [22,23,24,25,26]. Although it remains unclear whether these virulence genes have similar functions to their homologs in different pathogenic bacteria, a study by Levican et al. (2013) showed little or no invasion of cells by Arcobacter strains that lack virulence genes [27]. Therefore, the detection and quantification of virulence genes of Arcobacter may elucidate its role in waterborne infections.
Based on these factors, the aim of this study was to investigate the prevalence of 16S rRNA and five virulence-associated genes (cadF, ciaB, mviN, pldA, and tlyA) of Arcobacter in water samples collected from different sites of the Kathmandu Valley in both the dry and the wet season. These five genes were selected based on their high presence in Arcobacter isolates obtained from various types of fecal, food, and environmental samples [28,29,30,31].

2. Results

2.1. Detection of 16S rRNA Gene of Arcobacter in Water Samples

A total of 112 water samples were collected from different sources of water in the dry season of 2016. As shown in Table 1, 16S rRNA gene of Arcobacter was detected in 20% (2/5), 100% (1/1), 100% (1/1), 41% (32/79), 9% (1/11), 13% (1/8), and 29% (2/7) of deep tube well, pond, river, shallow dug well, shallow tube well, spring, and stone spout water samples, respectively. The concentration of Arcobacter 16S rRNA gene was highest in the river water sample with 10.2 log copies/100 mL, followed by deep tube wells (7.6 ± 0.4 log copies/100 mL) and shallow dug wells (6.2 ± 0.8 log copies/100 mL). Among 174 water samples collected in the wet season of 2016, 16S rRNA gene of Arcobacter was detected in 12% (3/25), 92% (12/13), 43% (37/87), 9% (2/22), 23% (3/13), and 14% (2/14) of deep tube well, river, shallow dug well, shallow tube well, spring, and stone spout water samples, respectively. The highest concentration of 16S rRNA gene of Arcobacter was detected in the river water (9.3 ± 1.3 log copies/100 mL), followed by deep tube wells (7.1 ± 0.5 log copies/100 mL) and stone spouts (6.4 ± 0.4 log copies/100 mL). A significant difference in Arcobacter-positive results was not observed between samples collected in the dry and wet season (p > 0.05).
Water sampling was conducted in both seasons at 84 locations, with 29 (35%) and 33 (39%) samples testing positive for 16S rRNA gene of Arcobacter in the dry and wet season, respectively. A significant difference in the concentrations of 16S rRNA gene of Arcobacter was not evident between water samples collected at the same location but in different seasons (p > 0.05). Sixteen (19%) samples (one stone spout and 15 shallow dug wells) were positive for 16S rRNA gene of Arcobacter regardless of the sampling season. The samples were also divided into two land-use categories (agricultural or built-up areas) [8]. In the dry season, Arcobacter 16S rRNA gene was detected in 35% (16/46) and 36% (24/66) of the samples collected in agricultural and built-up areas, respectively. In contrast, the bacterium was detected in 41% (24/59) and 30% (35/115) of samples collected in agricultural and built-up areas during the wet season, respectively. There was no significant difference in the detection ratios of Arcobacter between agricultural and built-up areas (p > 0.05).

2.2. Detection of Arcobacter Virulence Genes in Water Samples

A total of five virulence genes, namely cadF, ciaB, mviN, pldA, and tlyA, were tested in Arcobacter qPCR-positive water samples. In the dry season, cadF, ciaB, mviN, pldA, and tlyA genes were detected in 1 (3%), 35 (88%), 2 (5%), 8 (20%), and 2 (5%) of 40 Arcobacter-positive water samples, respectively (Table 2). The river water sample was the only sample, where all five virulence genes were detected with the highest concentrations (8.4–10.1 copies/100 mL, depending on genes). The number of samples positive for at least one virulence gene was 35.
In the wet season, the number of Arcobacter qPCR-positive samples was 59, of which 16 (27%), 49 (83%), 17 (29%), 15 (25%), and 15 (25%) were positive for cadF, ciaB, mviN, pldA, and tlyA, respectively (Table 3). In total, seven river water and one shallow dug well water samples contained all five virulence genes, and 52 Arcobacter qPCR-positive samples were positive for at least one of the genes. The highest mean concentrations of all five virulence genes was observed in the river water samples (8.6–9.4 log copies/100 mL).

3. Discussion

In this study, 35% (99/286) of water samples tested were contaminated with 16S rRNA gene of Arcobacter. In our previous study, 16S rRNA gene of Arcobacter was detected in shallow dug wells (39%, 11/28), a deep tube well (20%, 1/5), and a river water sample (100%, 1/1), but not in shallow tube wells, stone spouts, and springs [2]. In the Kathmandu Valley, the limited distribution of drinking water from Kathmandu Upatyaka Khanepani Limited (115 and 69 million liters per day (MLD) in wet and dry seasons, respectively), and high demand for drinking water (370 MLD) has compelled residents to use groundwater and surface water for many household chores [32]. Even though groundwater and surface water are mostly used for bathing, laundry, cleaning, gardening, and other purposes, 12% and 22% of people use groundwater for drinking and cooking, respectively [33]. Apart from piped water and groundwater, the residents use jar and tanker water for drinking. However, these sources of water do not meet the World Health Organization guideline values for safe drinking water [34,35]. Only 10.2%, 9.6%, and 3.7% of people use treated water for washing vegetables, brushing teeth, and bathing purposes [33]. As such, people living in the valley are at high risk of contracting waterborne diseases due to the contamination of groundwater and surface water with Arcobacter.
Arcobacter butzleri, Arcobacter skirrowii, and Arcobacter cryaerophilus are commonly detected in the surface water and groundwater of Japan (23%, 4/17), South Africa (55%, 6/11), Spain (59%, 17/29), and Turkey (41%, 17/41) [14,15,16,19]. Other species of Arcobacter beside A. butzleri, A. skirrowii, and A. cryaerophilus also exhibit pathogenic properties, such as adhesion, invasion, and cytotoxicity [27,36]. The findings of our study expand the knowledge of the prevalence of Arcobacter in surface water and groundwater samples, especially as we targeted a wide range of 16S rRNA genes of Arcobacter species along with large numbers of samples, collected in two different seasons. The presence of Arcobacter has been linked to waterborne and foodborne diseases, with water being one of the important routes of transmission [16,37,38]. Therefore, groundwater and surface water contaminated with Arcobacter consumed may cause waterborne and foodborne diseases. Arcobacter densities were found to be higher in diarrheal than in non-diarrheal stools [39]. Diarrhea remains one of the leading causes of morbidity and mortality in Nepal, and diarrheal samples are often diagnosed with enteric protozoa, bacteria, and even viruses in clinical laboratories [40,41,42,43]. To date, the prevalence of Arcobacter in diarrheal stool samples in Nepal has not been studied. As an emerging pathogen, the determination of the prevalence of Arcobacter in water and stool samples must become a priority.
Among the 286 water samples tested in this study, 250 (shallow dug well, n = 166; shallow tube well, n = 33; deep tube wells, n = 30; and stone spouts, n = 21) were previously used for the identification of human and animal fecal contamination using host-associated Bacteroidales genetic markers [8]. Fifty-five (22%), 28 (11%), and 8 (3%) of the water samples were found to contain human, ruminant, and pig fecal markers, respectively [8], whereas 16S rRNA gene of Arcobacter was detected more frequently in 81 (32%) water samples. If the source of Arcobacter contamination is confirmed as human or animal feces, Arcobacter should be considered for the identification of human and animal fecal contamination. Thus, further studies are required to evaluate the feasibility of using Arcobacter to identify sources of fecal contamination of water, based on the genetic diversity of Arcobacter spp.
As summarized in Table 4, a positive correlation has been demonstrated between the concentration of E. coli [8] and the positive ratios of Arcobacter in the water samples tested. As the concentrations of E. coli increased, the percentages of Arcobacter 16S rRNA gene-positive samples also increased. There were two samples that were positive for Arcobacter 16S rRNA gene but were E. coli–negative. This result is supported by the study of Malla et al. (2018), in which 23% (13/56) of E. coli–negative samples were found to be positive for at least one human or ruminant fecal marker [8].
Among the five virulence-associated genes tested, ciaB was the most prevalent in both the dry (88%, 35/40) and wet (83%, 49/59) season. This agrees with previous studies in which the gene was detected in all strains of A. butzleri, A. cryaerophilus, and A. skirrowii isolated from water samples [13,44]. In Arcobacter-positive samples from food, cattle and sheep feces, chicken carcasses, processing equipment of slaughterhouses, animals, and humans, ciaB was the most dominant virulence-associated gene [28,29,44]. Other prevalent virulence genes are pldA (20%, 8/40) and mviN (29%, 17/59), which were detected in samples collected in the dry and wet season, respectively. The pldA, mviN, cj1349, and tlyA genes were detected in 100% of A. butzleri strains isolated from water samples, and the mviN gene was detected in 100% of A. cryaerophilus isolates [13]. The high detection rates of these genes may be due to their specificity for A. butzleri and A. cryaerophilus isolates. In our study, several other species of Arcobacter including A. butzleri and A. cryaerophilus were targeted. Only a few studies have been published on the detection of these virulence genes in water samples [13,44]. This highlights the importance of our study in assessing the prevalence of these genes in a large number of water samples, through screening for the majority of the known Arcobacter species.
A. butzleri, A. cryaerophilus, and A. skirrowii are known pathogenic species of Arcobacter responsible for diarrhea and foodborne infection [16,39]. Virulence-associated genes have been identified in strains of these three pathogens isolated from various animals; clinical samples; and food, fecal, and water samples. As virulence genes are associated with the pathogenic characteristics of Arcobacter, such as adhesion, invasion, and cytotoxicity in different cell lines, the detection of these genes in surface water and groundwater needs to be taken seriously [27,36]. All the genes tested were present in several individual samples, especially those from river water and a shallow dug well. Thus, the detection of virulence-associated genes along with Arcobacter in water samples may represent a high risk of waterborne disease transmission.
In conclusion, this study demonstrates the high presence of 16S rRNA and five virulence-associated genes of Arcobacter in water samples collected in the Kathmandu Valley. We also highlighted differences in the detection ratios of Arcobacter between the dry and wet season, and agricultural and built-up areas. The presence of pathogenic bacteria in groundwater and surface water underlines the importance of regular monitoring for pathogens and rapid identification of contamination sources.

4. Materials and Methods

4.1. Collection of Water Samples

In this study, a total of 286 water samples were collected in the Kathmandu Valley in 2016. One hundred two water samples were collected in February and March 2016 (dry season) from deep tube wells (n = 5), shallow dug wells (n = 79), shallow tube wells (n = 11), and stone spouts (n = 7), whereas 148 water samples were collected in August 2016 (wet season) from deep tube wells (n = 25), shallow dug wells (n = 87), shallow tube wells (n = 22), and stone spouts (n = 14), as described previously [8]. Water samples were also collected from a pond (n = 1), a river (n = 1), and springs (n = 8) in February and March 2016, and from rivers (n = 13) and springs (n = 13) in August 2016. Two hundred milliliter samples were collected in autoclaved 100 mL plastic bottles, which were stored in an ice bag and transported to the laboratory within 4 h of collection [8].

4.2. Bacterial DNA Extraction

Water samples (100 mL of groundwater and 10 mL of river water) were filtered using a disposable filter unit preset with a nitrocellulose membrane (pore size, 0.22 µm; diameter, 47 mm; Nalgene, Tokyo, Japan) as described previously [8]. Bacterial DNA was extracted from the membrane filter using a Cica Geneus DNA Extraction Reagent (Kanto Chemical, Tokyo, Japan). In brief, 5 mL of Tris-EDTA buffer (pH 7.4) was added to a 50 mL tube containing the membrane filter, followed by shaking and vortex mixing. Finally, 300 µL of DNA was extracted from 160 µL of the mixture solution with 20 µL of Buffer A and 200 µL of Buffer B.

4.3. qPCR of 16S rRNA Gene of Arcobacter and Its Virulence Genes

For the quantification of 16S rRNA gene of Arcobacter, qPCR was performed using 2 µL of template DNA, 12.5 µL of a MightyAmp for Real Time (SYBR Plus) (Takara Bio, Kusatsu, Japan), 0.1 µL of 1 µM Arco-F and Arco-R-rev primers targeting 16S rRNA gene of the genus [2], and 10.3 µL of ultrapure water. The quantification of virulence genes (ciaB, cadF, mviN, pldA, and tlyA) was performed on Arcobacter qPCR-positive water samples. In brief, 2 µL of template DNA, 12.5 µL of a SYBR Premix Ex Taq II (Tli RNaseH Plus) (Takara Bio), 0.1 µL of 1 µM forward and reverse primers [28], and 10.3 µL of ultrapure water were used. The thermal conditions were as follows: For 16S rRNA gene of Arcobacter, 98 °C for 2 min, followed by 35 cycles of 98 °C for 10 s, 55 °C for 30 s, and 68 °C for 40 s; for the ciaB and tlyA gene, 95 °C for 30 s, followed by 35 cycles of 94 °C for 15 s, 55 °C for 30 s, and 72 °C for 20 s; and for cadF, mviN, and pldA genes, 95 °C for 30 s, followed by 35 cycles of 94 °C for 15 s, 56 °C for 45 s, and 72 °C for 20 s, using the Thermal Cycler Dice Real Time System Single TP850 (Takara Bio). Following amplification, thermal conditions of 95 °C for 15 s, 60 °C for 30 s, and 95 °C for 15 s were used to identify a single peak melting temperature. A single melting temperature peak of approximately 85, 79, 80, 78, 79, and 77 °C was considered to be derived from amplified 16S rRNA gene of Arcobacter, cadF, ciaB, mviN, pldA, and tlyA genes, respectively.

4.4. Statistical Analysis

Chi-square testing was performed using Microsoft Excel 2016 (Microsoft Corporation, Redmond, WA, USA) to determine the difference in positive ratios of 16S rRNA gene of Arcobacter relative to concentrations of E. coli. This test was also used to confirm significant differences in the distribution of 16S rRNA gene of Arcobacter through different land covers and seasons. Wilcoxon’s signed rank test was performed to identify differences in the concentrations of 16S rRNA gene of Arcobacter in water samples collected at the same location but in different seasons. Differences were considered statistically significant if the resulting p value was <0.05.

Author Contributions

R.G.S. conceived the design of the study, processed the samples, analyzed the results, and prepared a draft of the manuscript. Y.T. conceived the design of the study, checked the analyzed results, and corrected the draft of the manuscript. J.B.S. conceived the design of the study. E.H. conceived the design of the study, checked the analyzed results, and corrected the draft of the manuscript.

Funding

This study was supported by the Science and Technology Research Partnership for Sustainable Development (SATREPS) program of Japan International Cooperation Agency (JICA) and Japan Science and Technology Agency (JST), entitled “Hydro-microbiological Approach for Water Security in Kathmandu Valley, Nepal” and the Japan Society for the Promotion of Science (JSPS) through Fund for the Promotion of Joint International Research (Fostering Joint International Research (B)) (grant number JP18KK0297).

Acknowledgments

The authors thank Suresh Das Shrestha (Tribhuvan University, Nepal), Kei Nishida, Takashi Nakamura, and Bijay Man Shakya (University of Yamanshi, Japan) for their continuous support in water sampling; and Bikash Malla, Sarmila Tandukar (University of Yamanashi, Japan), and Dinesh Bhandari (The University of Adelaide, Australia) for their invaluable support during the laboratory analysis.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ghaju Shrestha, R.; Tanaka, Y.; Malla, B.; Bhandari, D.; Tandukar, S.; Inoue, D.; Sei, K.; Sherchand, J.B.; Haramoto, E. Next-generation sequencing identification of pathogenic bacterial genes and their relationship with fecal indicator bacteria in different water sources in the Kathmandu Valley, Nepal. Sci. Total Environ. 2017, 601–602, 278–284. [Google Scholar] [CrossRef] [PubMed]
  2. Ghaju Shrestha, R.; Tanaka, Y.; Malla, B.; Tandukar, S.; Bhandari, D.; Inoue, D.; Sei, K.; Sherchand, J.B.; Haramoto, E. Development of a quantitative PCR assay for Arcobacter spp. and its application to environmental water samples. Microbes Environ. 2018, 33, 309–316. [Google Scholar] [CrossRef] [PubMed]
  3. Ghaju Shrestha, R.; Sawada, K.; Inoue, D.; Yoshinaga, H.; Malla, B.; Tandukar, S.; Bhandari, D.; Tanaka, Y.; Sei, K.; Sherchand, J.B.; et al. Comparison of pathogenic bacteria in water and fecal-source samples in the Kathmandu Valley, Nepal, using high-throughput DNA microarray. Biomed. J. Sci. Tech. Res. 2019, 17, 13074–13081. [Google Scholar]
  4. Haramoto, E.; Yamada, K.; Nishida, K. Prevalence of protozoa, viruses, coliphages and indicator bacteria in groundwater and river water in the Kathmandu Valley, Nepal. Trans. R. Soc. Trop. Med. Hyg. 2011, 105, 711–716. [Google Scholar] [CrossRef] [PubMed]
  5. Koju, N.K.; Prasai, T.; Shrestha, S.M.; Raut, P. Drinking water quality of Kathmandu Valley. Nepal J. Sci. Tech. 2014, 15, 115–120. [Google Scholar] [CrossRef]
  6. Malla, B.; Ghaju Shrestha, R.; Tandukar, S.; Bhandari, D.; Inoue, D.; Sei, K.; Tanaka, Y.; Sherchand, J.B.; Haramoto, E. Validation of host-specific Bacteroidales quantitative PCR assays and their application to microbial source tracking of drinking water sources in the Kathmandu Valley, Nepal. J. Appl. Microbiol. 2018, 125, 609–619. [Google Scholar] [CrossRef]
  7. Malla, B.; Ghaju Shrestha, R.; Tandukar, S.; Sherchand, J.B.; Haramoto, E. Performance evaluation of human-specific viral markers and application of pepper mild mottle virus and crAssphage to environmental water samples as fecal pollution markers in the Kathmandu Valley, Nepal. Food Environ. Virol. 2019, 1–14. [Google Scholar] [CrossRef]
  8. Malla, B.; Ghaju Shrestha, R.; Tandukar, S.; Bhandari, D.; Inoue, D.; Sei, K.; Tanaka, Y.; Sherchand, J.B.; Haramoto, E. Identification of human and animal fecal contamination in drinking water sources in the Kathmandu Valley, Nepal, using host-associated Bacteroidales quantitative PCR assays. Water 2018, 10, 1796. [Google Scholar] [CrossRef]
  9. Shrestha, S.; Shrestha, S.; Shindo, J.; Sherchand, J.B.; Haramoto, E. Virological quality of irrigation water sources and pepper mild mottle virus and tobacco mosaic virus as index of pathogenic virus contamination level. Food Environ. Virol. 2018, 10, 107–120. [Google Scholar] [CrossRef]
  10. Tandukar, S.; Sherchand, J.B.; Bhandari, D.; Sherchan, S.; Malla, B.; Ghaju Shrestha, R.; Haramoto, E. Presence of human enteric viruses, protozoa, and indicators of pathogens in the Bagmati River, Nepal. Pathogens 2018, 7, 38. [Google Scholar] [CrossRef]
  11. Asian Development Bank. Solid Waste Management in Nepal. Available online: https://www.adb.org/sites/default/files/publication/30366/solid-waste-management-nepal.pdf (accessed on 24 July 2019).
  12. Li, X.; Harwood, V.J.; Nayak, B.; Staley, C.; Sadowsky, M.J.; Weidhaas, J. A novel microbial source tracking microarray for pathogen detection and fecal source identification in environmental systems. Environ. Sci. Technol. 2015, 49, 7319–7329. [Google Scholar] [CrossRef] [PubMed]
  13. Šilha, D.; Vacková, B.; Šilhová, L. Occurrence of virulence-associated genes in Arcobacter butzleri and Arcobacter cryaerophilus isolates from foodstuff, water, and clinical samples within the Czech Republic. Folia Microbiol. 2019, 64, 25–31. [Google Scholar] [CrossRef] [PubMed]
  14. Morita, Y.; Maruyama, S.; Kabeya, H.; Boonmar, S.; Nimsuphan, B.; Nagai, A.; Kozawa, K.; Nakajima, T.; Mikami, T.; Kimura, H. Isolation and phylogenetic analysis of Arcobacter spp. in ground chicken meat and environmental water in Japan and Thailand. Microbiol. Immunol. 2004, 48, 527–533. [Google Scholar] [CrossRef] [PubMed]
  15. Diergaardt, S.M.; Venter, S.N.; Spreeth, A.; Theron, J.; Brözel, V.S. The occurrence of campylobacters in water sources in South Africa. Water Res. 2004, 38, 2589–2595. [Google Scholar] [CrossRef] [PubMed]
  16. Collado, L.; Inza, I.; Guarro, J.; Figueras, M.J. Presence of Arcobacter spp. in environmental waters correlates with high levels of fecal pollution. Environ. Microbiol. 2008, 10, 1635–1640. [Google Scholar] [CrossRef] [PubMed]
  17. Moreno, Y.; Alonso, J.L.; Botella, S.; Ferrús, M.A.; Hernández, J. Survival and injury of Arcobacter after artificial inoculation into drinking water. Res. Microbiol. 2004, 155, 726–730. [Google Scholar] [CrossRef] [PubMed]
  18. Çelik, E.; Ünver, A. Isolation and Identification of Arcobacter spp. by Multiplex PCR from Water Sources in Kars Region. Curr. Microbiol. 2015, 71, 546–550. [Google Scholar] [CrossRef]
  19. Talay, F.; Molva, C.; Atabay, H.I. Isolation and identification of Arcobacter species from environmental and drinking water samples. Folia Microbiol. (Praha) 2016, 61, 479–484. [Google Scholar] [CrossRef]
  20. Ertas, N.; Dogruer, Y.; Gonulalan, Z.; Guner, A.; Ulger, I. Prevalence of Arcobacter species in drinking water, spring water, and raw Milk as determined by multiplex PCR. J. Food Prot. 2010, 73, 2099–2102. [Google Scholar] [CrossRef]
  21. Rice, E.W.; Rodgers, M.R.; Wesley, I.V.; Johnson, C.H.; Tanner, S.A. Isolation of Arcobacter butzleri from ground water. Lett. Appl. Microbiol. 1999, 28, 31–35. [Google Scholar] [CrossRef]
  22. Miller, W.G.; Parker, C.T.; Rubenfield, M.; Mendz, G.L.; Wösten, M.M.S.M.; Ussery, D.W.; Stolz, J.F.; Binnewies, T.T.; Hallin, P.F.; Wang, G.; et al. The complete genome sequence and analysis of the Epsilonproteobacterium Arcobacter butzleri. PLoS ONE 2007, 2, e1358. [Google Scholar] [CrossRef] [PubMed]
  23. Larsen, N.A.; Lin, H.; Wei, R.; Fischbach, M.A.; Walsh, C.T. Structural characterization of enterobactin hydrolase IroE. Biochemistry 2006, 45, 10184–10190. [Google Scholar] [CrossRef] [PubMed]
  24. Johnson, J.R.; Jelacic, S.; Schoening, L.M.; Clabots, C.; Shaikh, N.; Mobley, H.L.T.; Tarr, P.I. The IrgA homologue adhesion Iha is an Escherichia coli virulence factor in murine urinary tract infection. Infect. Immun. 2005, 73, 965–971. [Google Scholar] [CrossRef] [PubMed]
  25. Goldberg, M.B.; DiRita, V.J.; Calderwood, S.B. Identification of an iron-regulated virulence determinant in Vibrio cholerae, using TnphoA mutagenesis. Infect. Immun. 1990, 58, 55–60. [Google Scholar] [PubMed]
  26. Rojas, C.M.; Ham, J.H.; Deng, W.-L.; Doyle, J.J.; Collmer, A. HecA, a member of a class of adhesins produced by diverse pathogenic bacteria, contributes to the attachment, aggregation, epidermal cell killing, and virulence phenotypes of Erwinia chrysanthemi EC16 on Nicotiana clevelandii seedlings. Proc. Natl. Acad. Sci. USA 2002, 99, 13142–13147. [Google Scholar] [CrossRef] [PubMed]
  27. Levican, A.; Alkeskas, A.; Gunter, C.; Forsythe, S.J.; Figueras, M.J. Adherence to and invasion of human intestinal cells by Arcobacter species and their virulence genotypes. Appl. Environ. Microbiol. 2013, 79, 4951–4957. [Google Scholar] [CrossRef] [PubMed]
  28. Douidah, L.; de Zutter, L.; Bare, J.; De Vos, P.; Vandamme, P.; Vandenberg, O.; Van den Abeele, A.M.; Houf, K. Occurrence of putative virulence genes in Arcobacter species isolated from humans and animals. J. Clin. Microbiol. 2012, 50, 735–741. [Google Scholar] [CrossRef] [PubMed]
  29. Lehmann, D.; Alter, T.; Lehmann, L.; Uherkova, S.; Seidler, T.; Gölz, G. Prevalence, virulence gene distribution and genetic diversity of Arcobacter in food samples in Germany. Berl. Munch. Tierarztl. Wochenschr. 2015, 128, 163–168. [Google Scholar] [PubMed]
  30. Karadas, G.; Sharbati, S.; Hänel, I.; Messelhäußer, U.; Glocker, E.; Alter, T.; Gölz, G. Presence of virulence genes, adhesion and invasion of Arcobacter butzleri. J. Appl. Microbiol. 2013, 115, 583–590. [Google Scholar] [CrossRef]
  31. Girbau, C.; Guerra, C.; Martínez-Malaxetxebarria, I.; Alonso, R.; Fernández-Astorga, A. Prevalence of ten putative virulence genes in the emerging foodborne pathogen Arcobacter isolated from food products. Food Microbiol. 2015, 52, 146–149. [Google Scholar] [CrossRef] [PubMed]
  32. Kathmandu Upatyaka Khanepani Limited KUKL 10th Annual Report. Available online: http://kathmanduwater.org/wp-content/uploads/2017/03/Annual-Operating-ReportFY64_65.pdf (accessed on 24 July 2019).
  33. Shrestha, S.; Aihara, Y.; Kondo, N.; Rajbhandari, S.; Bhattarai, A.P.; Bista, N.; Kazama, F.; Nishida, K.; Timilsina, H.P.; Shindo, J. Household Water Use in the Kathmandu Valley: A Dry Season Survey; WASH-MIA Rapid Report; Interdisciplinary Center for River Basin Environment (ICRE), University of Yamanashi: Yamanashi, Japan, 2016; Available online: http://www.icre.yamanashi.ac.jp/file/WASH-MIA_Rapid_Report.pdf (accessed on 24 July 2019).
  34. Malla, B.; Ghaju Shrestha, R.; Tandukar, S.; Bhandari, D.; Thakali, O.; Sherchand, J.B.; Haramoto, E. Detection of pathogenic viruses, pathogen indicators, and fecal-source markers within tanker water and their sources in the Kathmandu Valley, Nepal. Pathogens 2019, 8, 81. [Google Scholar] [CrossRef] [PubMed]
  35. Malla, B.; Ghaju Shrestha, R.; Bhandari, D.; Tandukar, S.; Shrestha, S.; Yoshinaga, H.; Inoue, D.; Sei, K.; Nishida, K.; Tanaka, Y.; et al. Detection of Cryptosporidium, Giardia, fecal indicator bacteria, and total bacteria in commercial jar water in the Kathmandu Valley, Nepal. J. Inst. Med. 2015, 37, 10–15. [Google Scholar]
  36. Ferreira, S.; Queiroz, J.A.; Oleastro, M.; Domingues, F.C. Insights in the pathogenesis and resistance of Arcobacter: A review. Crit. Rev. Microbiol. 2015, 42, 1–20. [Google Scholar] [CrossRef] [PubMed]
  37. Ho, H.; Lipman, L.; Gaastra, W. Arcobacter, what is known and unknown about a potential foodborne zoonotic agent! Vet. Microbiol. 2006, 115, 1–13. [Google Scholar] [CrossRef] [PubMed]
  38. Mansfield, L.P.; Forsythe, S.J. Arcobacter butzleri, A. skirrowii and A. cryaerophilus—Potential emerging human pathogens. Rev. Med. Microbiol. 2000, 11, 161–170. [Google Scholar]
  39. Webb, A.L.; Boras, V.F.; Kruczkiewicz, P.; Selinger, L.B.; Taboada, E.N.; Inglis, G.D. Comparative detection and quantification of Arcobacter butzleri in stools from diarrheic and nondiarrheic people in southwestern Alberta, Canada. J. Clin. Microbiol. 2016, 54, 1082–1088. [Google Scholar] [CrossRef] [PubMed]
  40. Tandukar, S.; Sherchand, J.; Karki, S.; Malla, B.; Ghaju Shrestha, R.; Bhandari, D.; Thakali, O.; Haramoto, E. Co-infection by waterborne enteric viruses in children with gastroenteritis in Nepal. Healthcare 2019, 7, 9. [Google Scholar] [CrossRef] [PubMed]
  41. Sherchand, J.B.; Schluter, W.W.; Sherchan, J.B.; Tandukar, S.; Dhakwa, J.R. Prevalence of group A genotype human rotavirus among children with diarrhoea in Nepal, 2009–2011. WHO South East Asia J. Public Health 2012, 1, 432–440. [Google Scholar] [CrossRef]
  42. Lama, C.; Sherchand, J.B. Enteropathogens associated diarrhea in hospitalized patients of children’s hospital, Kathmandu. J. Nepal Health Res. Counc. 2007, 5, 50–57. [Google Scholar]
  43. Ansari, S.; Sherchand, J.B.; Rijal, B.P.; Parajuli, K.; Mishra, S.K.; Dahal, R.K.; Shrestha, S.; Tandukar, S.; Chaudhary, R.; Kattel, H.P.; et al. Characterization of rotavirus causing acute diarrhoea in children in Kathmandu, Nepal, showing the dominance of serotype G12. J. Med. Microbiol. 2019, 114–120. [Google Scholar] [CrossRef]
  44. Tabatabaei, M.; Shirzad Aski, H.; Shayegh, H.; Khoshbakht, R. Occurrence of six virulence-associated genes in Arcobacter species isolated from various sources in Shiraz, Southern Iran. Microb. Pathog. 2014, 66, 1–4. [Google Scholar] [CrossRef] [PubMed]
Table
Table 1. Detection of 16S rRNA gene of Arcobacter in water samples.
Table 1. Detection of 16S rRNA gene of Arcobacter in water samples.
Sources of WaterFebruary–March 2016 (Dry Season)August 2016 (Wet Season)
No. of Positive Samples/No. of Tested Samples (% Positive)Concentration a
(Mean ± SD b)		No. of Positive Samples/No. of Tested Samples (% Positive)Concentration
(Mean ± SD)
Deep tube well2/5 (20)7.6 ± 0.43/25 (12)7.1 ± 0.5
Pond1/1 (100)6.0– c–
River1/1 (100)10.212/13 (92)9.3 ± 1.3
Shallow dug well32/79 (41)6.2 ± 0.837/87 (43)6.0 ± 0.6
Shallow tube well1/11(9)7.12/22 (9)5.6 ± 0.1
Spring1/8 (13)5.73/13 (23)6.0 ± 0.2
Stone spout2/7 (29)5.92/14 (14)6.4 ± 0.4
Total40/112 (36) 59/174 (34)
a Concentrations among positive samples in log copies/100 mL; b SD, standard deviation; c not sampled.
Table
Table 2. Detection of virulence genes of Arcobacter in water samples collected in February–March 2016 (dry season).
Table 2. Detection of virulence genes of Arcobacter in water samples collected in February–March 2016 (dry season).
Sources of WaterNo. of Samples Positive for Arcobacter 16S rRNA GeneNo. of Positive Samples (Concentration a (Mean ± SD b))
cadFciaBmviNpldAtlyA
Deep tube well202 (7.5 ± 0.3)01 (8.1)0
Pond101 (6.2)000
River11 (9.0)1 (10.1)1 (9.0)1 (9.0)1 (8.4)
Shallow dug well32027 (6.5 ± 0.7)1 (6.9)5 (7.8 ± 0.7)1 (6.3)
Shallow tube well101 (7.0)000
Spring101 (5.9)000
Stone spout202 (5.8 ± 0.1)01 (8.2)0
Total (% Positive)401 (3%)35 (88%)2 (5%)8 (20%)2 (5%)
a Concentrations among positive samples in log copies/100 mL; b SD, standard deviation.
Table
Table 3. Detection of virulence genes of Arcobacter in water samples collected in August 2016 (wet season).
Table 3. Detection of virulence genes of Arcobacter in water samples collected in August 2016 (wet season).
Sources of WaterNo. of Samples Positive for Arcobacter 16S rRNA GeneNo. of Positive Samples (Concentration a (Mean ± SD b))
cadFciaBmviNpldAtlyA
Deep tube well31 (5.8)3 (6.8 ± 0.6)001 (6.5)
River128
(9.2 ± 0.4)		11
(9.4 ± 1.1)		10
(9.3 ± 0.6)		8
(9.1 ± 0.5)		9
(8.6 ± 0.5)
Shallow dug well377
(6.3 ± 0.7)		31
(6.3 ± 0.6)		7
(7.5 ± 0.5)		5
(6.3 ± 0.7)		5
(6.7 ± 0.5)
Shallow tube well20001 (7.4)0
Spring303 (6.1 ± 0.4)000
Stone spout201 (6.7)01 (8.6)0
Total5916 (27%)49 (83%)17 (29%)15 (25%)15 (15%)
a Concentrations among positive samples in log copies/100 mL; b SD, standard deviation.
Table
Table 4. Relationship between Arcobacter and Escherichia coli in water samples.
Table 4. Relationship between Arcobacter and Escherichia coli in water samples.
Concentration of E. coli a
(log Most Probable Number/100 mL)		No. of SamplesNo. of Samples Positive for Arcobacter 16S rRNA Gene (% Positive)
<0582 (2%)
0–1.04510 (10%)
1.1–2.06921 (21%)
2.1–3.05326 (26%)
3.1–4.03516 (16%)
>4.02624 (24%)
Total28699 (35%)
a Data from Malla et al. (2018) [8].

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Ghaju Shrestha, R.; Tanaka, Y.; Sherchand, J.B.; Haramoto, E. Identification of 16S rRNA and Virulence-Associated Genes of Arcobacter in Water Samples in the Kathmandu Valley, Nepal. Pathogens 2019, 8, 110. https://doi.org/10.3390/pathogens8030110

AMA Style

Ghaju Shrestha R, Tanaka Y, Sherchand JB, Haramoto E. Identification of 16S rRNA and Virulence-Associated Genes of Arcobacter in Water Samples in the Kathmandu Valley, Nepal. Pathogens. 2019; 8(3):110. https://doi.org/10.3390/pathogens8030110

Chicago/Turabian Style

Ghaju Shrestha, Rajani, Yasuhiro Tanaka, Jeevan B. Sherchand, and Eiji Haramoto. 2019. "Identification of 16S rRNA and Virulence-Associated Genes of Arcobacter in Water Samples in the Kathmandu Valley, Nepal" Pathogens 8, no. 3: 110. https://doi.org/10.3390/pathogens8030110

APA Style

Ghaju Shrestha, R., Tanaka, Y., Sherchand, J. B., & Haramoto, E. (2019). Identification of 16S rRNA and Virulence-Associated Genes of Arcobacter in Water Samples in the Kathmandu Valley, Nepal. Pathogens, 8(3), 110. https://doi.org/10.3390/pathogens8030110

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