Assessment of Virulence Potential and Antibiotic Resistance Profiles in E. coli Isolates from Selected Control Open Dump Sites in Sri Lanka

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Liyanage, P. A. K. C. Wijerathna, S.M.T.V. Bandara, Pathmalal Manage This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3547316/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 May, 2024 Read the published version in Waste and Biomass Valorization → Version 1 posted 4 You are reading this latest preprint version Abstract Urbanization and accelerated industrialization have led to significant waste generation following the accumulation of massive amounts of solid waste in open dump sites. Ground water contamination is one of the critical ecological concerns associated with the percolation of leachate from dump sites. Escherichia coli is one of the facultative anaerobic bacterial types predominantly colonize the gastrointestinal tract of homoeothermic organisms. E.coli O157 is a particular virulent serotype which produces intimin and Shiga toxins, that causing for severe diseases including Hemorrhagic Colitis, Hemolytic Uremic Syndrome and thrombotic thrombocytopenic purpura in human. The focus of the present study is to study the virulence potential and antibiotic resistance profiles in E. coli isolates from selected Karadiyana, Methotamulla and Kerawalapitiya control open dump sites in Sri Lanka. The total coliform count was ranged from 0–120 MPN/mL around the Kardiyana dump site whereas 0–75 MPN/mL and 3-115 MPN/mL recorded in the Methotamulla and Kerawalapitiya dump sites. Overall, resistance in isolated E.coli against AMX, AMP, SUF/ TRI, SDI, CLOX, TET and ERM was high (> 70%) compared with the other tested antibiotics namely CIP, GEN and AZY (< 40%). According to the results, the Enteropathogenic E. coli pathotype was identified in 17 samples, whereas the Enterohaemorrhagic E. coli pathotype was found in only 3 samples. Thus, the current study was conducted to investigate control open dump sites as potential environmental reservoirs of antibiotic-resistant pathogenic E. coli as these organisms could represent a potential health threat through the contamination of groundwater. Municipal solid waste Leachate E. coli antibiotic resistance groundwater contamination Figures Figure 1 Figure 2 Figure 3 Introduction In most developed countries, the technology for the treatment of landfill leachate has been maintained well and monitored strictly. However, for developing countries, waste classification and sealed management systems have not yet been perfectly established due to the lack of waste recycling legislation, technique equipment, and public awareness (Roy et al., 2022; Wijerathna et al., 2023c). In landfills, a significant volume of human waste, animal waste, and industrial waste with high antibiotic levels have been discarded (Manage and Liyanage 2019; Liyanage et al., 2021; Ashokkumar et al., 2022). Antibiotic-resistant bacteria (ARB) may become the predominant communities in landfills as a result of the presence and ongoing input of such antibiotics (Morgado et al., 2021; Felis et al., 2020). Additionally, the presence of mobile genetic elements would encourage the frequency of horizontal gene transfer between pathogenic bacteria and ARB, making the landfill a hotspot for pathogenic bacteria and ARGs (Junaid et al., 2022). This is especially true for landfills without proper seepage control facilities (Ondon et al., 2021). A serious threat to public health and environmental safety exists at these sites because mixed pollutants (ARB and ARGs) migrate with landfill leachate and contaminate surface or underground water (Ondon et al., 2021; Junaid et al., 2022). Therefore, it is critical to create regulating technologies to lessen the prevalence of dangerous bacteria and ARG spread. One of the most prevalent facultative pathogens in human health, Escherichia coli ( E. coli ), is also a crucial component of the study of water quality, particularly concerning faecal contamination Devane et al., 2020; Wijerathna et al., 2023a). According to studies, a significant amount of the E. coli population detected in surface water already has at least one acquired resistance, and multi-resistant isolates are no longer unusual. However, some strains of E. coli have developed virulence factors and genes for antibiotic resistance, which can cause serious infections and represent a serious risk to the general public's health (Haley et al., 2022; Shen et al., 2023). Due to the risk of environmental contamination and subsequent spread of antibiotic resistance to other ecological niches, the prevalence and antimicrobial resistance patterns of E. coli in landfill leachates are of the utmost importance (Haley et al., 2022; Shen et al., 2023). The management of garbage, including the eradication of municipal solid waste, is a major concern in Sri Lanka, a developing country that is experiencing fast urbanization and industrialization. Landfills are frequently used to dispose of garbage, and the leachates they produce frequently find their way into the surface and groundwater in the area, endangering ecosystems and human health (Saja et al., 2021) Since they may serve as reservoirs for antimicrobial resistance genes that can spread to other bacteria in the environment, the existence of antimicrobial-resistant E. coli strains in landfill leachates can exacerbate this issue. To evaluate the possible dangers connected with these waste disposal sites, it is essential to understand the prevalence and antibiotic resistance profiles of E. coli isolated from landfill leachates. We can learn a lot about the prevalence and antibiotic resistance trends of E. coli strains, which will help us understand how landfill leachates affect the propagation of antimicrobial resistance and the risk of human exposure to contaminated water sources. This study aims to determine the prevalence and antimicrobial resistance profiles of E. coli strains isolated from landfill leachate sites in Sri Lanka. The objectives include: ( 1 ) identifying the prevalence and distribution of E. coli in landfill leachates, ( 2 ) characterizing the antimicrobial resistance patterns of the isolated E. coli strains, and ( 3 ) exploring potential correlations between the occurrence of antimicrobial resistance and the physicochemical parameters of the leachate. The results of this study will be crucial for the creation of efficient waste management plans and for reducing any potential health risks brought on by landfill leachate contamination in Sri Lanka. Methodology 2.1 Study area Karadiyana, Meethotamulla and Kerawalapitiya dumping sites were selected as the study area for the present study (Fig. 1 ). Those sites are identified as major solid waste disposal sites in the Colombo area. The number of groundwater sampling locations depended on the availability of groundwater sources in each area. 2.2 Water samples collection For the study, 17 dug-well water samples were collected from Karadiyana ( 10 ), Meethotamulla ( 4 ) and Kerawalapitiya ( 3 ) open dump sites respectively on 15th and 16th August, 2023 (Table 1 ). Pre-cleaned polypropylene bottles and amber-coloured sterile glass bottles were used to collect water for chemical and microbial analysis respectively. Water samples were transported to the laboratory in a refrigerated condition within 24 hours and stored in a cold room. Microbiological and chemical analyses were performed within 24 hours after the collection of samples. The GPS coordinates were recorded via a hand-held GPS receiver (Model -etrex® 22x) at the site. 2.3 Physico chemical analysis in water samples Water quality parameters; water temperature, pH, Dissolved Oxygen (DO), and Electrical Conductivity (EC) were measured using a thermometer (Immersion, Philip Harris, and England), pH meter (330 I/ Set, WTW Co., Weilheim, Germany), DO meter (HQD portable multimeter -HACH - HQ 40D) and a conductivity meter (340A-Set 1) respectively at the site itself. Chemical parameters such as N- Nitrate (as NO3-), N-Nitrite (as NO2-), N-Ammonia (as NH3), total inorganic nitrogen and total phosphorous were measured in the laboratory using Standard Methods for the Examination of Water and Wastewater published by American Public Health Association (APHA 2012). The Chemical Oxygen Demand (COD) of the water were measured following the closed reflux method (Pathmalal et al., 2023, Wijerathna et al., 2023 b) 2.4 Microbiological Analysis 2.4.1 Total and faecal coliform bacteria (Most Probable Number (MPN) method) The most Probable Number method was performed to determine the Total coliform (TC) and E. coli count per 0.1 dm3 of the water samples. Presumptive test, confirmed test and completed test were carried out to isolate and identify E.coli and Total coliform in the samples [Manjula et al., 2011 and WHO,2012, SLSI 2013, Wijerathna et al., 2022b]. Colonies developed on EMB agar, were further identified as coliforms or faecal coliforms (Escherichia coli) using cultural characteristics, morphology and biochemical tests. For faecal coliforms, colonies with green metallic sheen were Gram stained and the IMVIC test was carried out to identify the colony as E.coli. The MPN per 100 mL water was determined using the completed test. Table 1 Description of groundwater sampling locations in the selected dumping site. No Dumping site Sample Number Usage Description of the dug well Physical appearance of the water 01 Karadiyana K 1 Irrigation Uncovered well, 2 m deep, Surface water percolates into the well Dark-coloured water with an unpleasant smell 02 K 2 Irrigation and washing Covered well, concrete lining 4 m deep, Surface water does not percolate into the well A bit muddy coloured with an unpleasant odour 03 K 3 Irrigation, washing and cooking Covered well with a concrete lining 5 m deep, Surface water does not percolate to the well Low coloured water Odourless 04 K4 Irrigation, washing and cooking Covered well with a concrete lining 4 m deep, Surface water does not percolate to the well Colourless Odourless 05 K5 Irrigation, washing and cooking Covered well with a concrete lining 4 m deep, Surface water does not percolate to the well Colourless Odourless 06 K6 Irrigation, washing and cooking Uncovered well with 3 m deep. Surface water percolates into the well Low coloured water Odourless 07 K7 Irrigation, washing and cooking Covered well with a concrete lining 4 m deep, Surface water does not percolate to the well Colourless Odourless 08 K8 Irrigation, washing and cooking Covered well with a concrete lining 4 m deep, Surface water does not percolate to the well Pale coloured water Odourless 09 K9 Irrigation, washing and cooking Covered well with a concrete lining 6 m deep, Surface water does not percolate to the well Colourless Odourless 10 K10 Irrigation, washing and cooking Covered well with a concrete lining 6 m deep, Surface water does not percolate to the well Colourless Odourless 11 Meethotamulla M1 Abundant Uncovered well with 2 m deep. Surface water percolates into the well Black coloured Unpleasant odour 12 M2 Washing, cooking and drinking Covered well with a concrete lining 3 m deep, Surface water does not percolate to the well Pale muddy coloured muddy odour 13 M3 Washing and cooking Covered Covered well with a concrete lining 3 m deep, Surface water does not percolate to the well Colourless Odourless 14 M4 Washing and cooking Uncovered well with 2 m deep. Surface water percolates into the well Muddy Coloured Odourless 15 Kerawalapitiya KE 1 Irrigation Uncovered well with 3 m deep. Surface water percolates into the well Muddy Coloured Odourless 16 KE2 Abundant Covered, 4 m deep, Surface water does not percolate to the well Muddy Coloured Unpleasant Odours 17 KE3 Irrigation and washing Covered, 4 m deep, Surface water does not percolate to the well Colourless Odourless 2.4.2 Isolation and confirmation of pure cultures of E.coli Five colonies were randomly selected from each plate. For plates with ≤ 5 colonies, all the isolates were selected for further purification. Following incubation, a single colony was selected and streaked further on EMB agar to obtain pure isolates, which were then used for virulence and antibiotic susceptibility profiling. 2.5 Screening of Antibiotic Resistance in Isolated E.coli Following incubation in nutrient broth, the turbidity of the broth culture was adjusted to a 0.5 McFarland standard before inoculating onto a pre-prepared nutrient agar medium. Filter sterilized (0.2 µm) antibiotics; Tetracycline (TET), Amphicillin (AMP), Amoxicillin (AMX), Cloxacillin (CLOX) and Ciprofloxacin (CIP) at a final concentration of 60µg/mL were spiked to each molting nutrient agar media (40 0 C) before inoculating bacteria (Liyanage et al., 2022; Liyanage and Manage, 2014). Then equalized bacterial samples were inoculated on the prepared nutrient agar medium according to CLSI guidelines and screened for antibiotic resistance in each bacterium (Liyanage et al.,2021). 2.6 Determination of Virulence Potentials of Isolates 2.6.1 Extraction of DNA Following Kim et al. (2012), the genomic DNA of isolated bacteria was extracted. Re-sup ended purified DNA was kept at -20 0 C in 50 µl of TE buffer. 2.6.2 Detection of the virulence genes by PCR The extracted DNA was used as the template DNA in different real-time PCR assays for the identification of genes associated with virulence in two (02) E. coli pathotypes. The various genes tested and the associated pathotypes are shown in Table 2 . Table 2 Virulence genes investigated and associated E. coli pathotypes. Pathotype Screened Genes Enteropathogenic E.coli eae A Enterohaemorrhagic E.coli eae A, stx 1, stx 2 The primers and PCR conditions used for the various genes were previously described by Abia et al. (2017). All controls were obtained from the Medical Research Laboratory in Sri Lanka. Reaction mixtures without DNA, which were used as negative controls, were also included in each PCR assay. All PCR assays were performed on a BIORAD PCR machine (Qiagen, Hilden, Germany). From Integrated DNA Technologies (IDT), primer sets were acquired. For each PCR, the master 25mixture was prepared as follows (Table 3 ). Table 3 Composition of PCR mixture PCR ingredient Volume per sample/ µL PCR water (PROMEGA, Cat No: MC1191) 9.5 to15.0 Go Taq Polymerase (5U/µl) (PROMEGA, Madison, USA, Ref- M829B), 0.5 MgCl 2 (50 mM) (PROMEGA, Madison, USA, Ref- M891A) 0.5 to 1.0 dNTP mix (10 µM) (PROMEGA, Madison, USA, Cat No: PAU1515) 0.5 10 µM Forward primer 0.5 10 µM Reverse primer 0.5 5 x reaction buffer (PROMEGA, Madison, USA, Ref- M829B) 2.5 DNA template 5.0–10.0 Total volume 25.0 PCR amplification was performed to screen for eaeA, stx1 and stx2 (Table 2 ) genes. Initial denaturation at 94°C for 3 minutes was followed by 30 cycles at 94°C for 10 seconds, 50°C for 20 seconds, and 72°C for 60 seconds in the PCR for eaeA . Initial denaturation at 94°C for 10 minutes was followed by 30 cycles at 94°C for 30 seconds, 45°C for 30 seconds, and 72°C for 60 seconds for stx1 and stx2 . Results 3.1 Physico chemical parameters in water samples Table 5 water quality parameters for the dug wells around the Karadiyana dump site. Sample Number K1 K2 K3 K4 K5 K6 K7 K8 K9 K10 SLS (614: 2013) Range pH 4.25 \(\pm 0.01\) 5.56 \(\pm 0.01\) 4.88 \(\pm 0.01\) 5.41 \(\pm 0.01\) 6.64 \(\pm 0.01\) 6.57 \(\pm 0.01\) 7.44 \(\pm 0.01\) 5.78 \(\pm 0.01\) 5.62 \(\pm 0.01\) 5.16 \(\pm 0.01\) 6.0–8.5 4.25–7.44 DO (mg/L) 4.27 4.02 2.81 6.51 0.50 2.71 3.37 3.02 2.28 3.35 3.0 0.5–6.51 Temperature ( 0 C) 27.2 28.1 28.6 30.3 28.9 28.5 28.9 31.3 31.3 30.0 - 27.2–31.3 EC(µS/cm) 2462 195.9 166.8 209.3 748.9 561.9 667.6 190.9 226.4 181.8 750 166.8–2462 Nitrate (ppm) 15.25 \(\pm 0.21\) 15.22 \(\pm 0.21\) 10.52 \(\pm 0.21\) 8.52 \(\pm 0.21\) 6.05 \(\pm 0.21\) 8.52 \(\pm 0.21\) 10.52 \(\pm 0.21\) 6.52 \(\pm 0.21\) 4.25 \(\pm 0.00\) 5.85 \(\pm 0.07\) 50 4.25–15.25 Nitrite (ppm) 4.03 \(\pm 0.00\) 4.02 \(\pm 0.00\) 5.04 \(\pm 0.00\) 5.02 \(\pm 0.00\) 3.15 \(\pm 0.07\) 4.02 \(\pm 0.00\) 2.02 \(\pm 0.00\) 1.03 \(\pm 0.00\) 1.02 \(\pm 0.00\) 1.02 \(\pm 0.01\) 3 1.02–5.04 Ammonium (ppm) 0.25 \(\pm 0.05\) 0.52 \(\pm 0.05\) 0.58 \(\pm 0.05\) 0.55 \(\pm 0.05\) 0.45 \(\pm 0.05\) 0.35 \(\pm 0.05\) 0.25 \(\pm 0.05\) 0.25 \(\pm 0.05\) ND ND 0.06 0–0.58 TN (ppm) 19.53 19.76 16.14 14.09 9.65 12.89 12.79 7.8 5.27 6.87 - 5.27–19.76 Total Phosphate (ppm) 1.55 \(\pm 0.05\) 1.65 \(\pm 0.05\) 1.52 \(\pm 0.05\) 0.52 \(\pm 0.05\) 0.53 \(\pm 0.05\) 1.52 \(\pm 0.05\) 1.29 \(\pm 0.84\) 0.28 \(\pm 0.05\) 1.50 \(\pm 0.05\) 0.52 \(\pm 0.05\) 2.0 0.28–1.65 COD (ppm) 460 596 452 224 596 264 256 352 224 224 40 224–596 Table 6 Parameters for Meethotamulla and Kerawalapitiya Meethotamulla Kerawalapitiya SLS (614: 2013) Sample Number 1 2 3 4 Range 1 2 3 Range pH 6.84 \(\pm 0.01\) 6.18 \(\pm 0.01\) 6.17 \(\pm 0.01\) 6.75 \(\pm 0.01\) 6.17–6.84 7.80 \(\pm 0.01\) 7.19 \(\pm 0.01\) 7.23 \(\pm 0.01\) 7.19–7.8 6.5–8.5 DO (mg/L) 2.58 4.68 5.81 4.72 2.58–5.81 7.64 2.74 6.03 2.74–7.64 3.0 Temperature ( 0 C) 28.9 28.8 28.5 28.5 28.5–28.9 28.8 29.0 27.4 27.4–29.0 - EC (µS/cm) 407.7 315.8 163.9 446.3 163.9–446.3 5248 548.0 375.9 375.9–5248 700 Nitrate (ppm) 8.85 \(\pm 0.07\) 8.52 \(\pm 0.00\) 6.25 \(\pm 0.00\) 7.75 \(\pm 0.11\) 6.25–8.85 2.52 \(\pm 0.00\) 2.52 \(\pm 0.00\) 1.05 \(\pm 0.01\) 1.05–2.25 50 Nitrite (ppm) 2.02 \(\pm 0.00\) 1.25 1.52 \(\pm 0.00\) 1.05 \(\pm 0.01\) 1.05–2.02 0.52 \(\pm 0.00\) 1.45 \(\pm 0.04\) 1.01 \(\pm 0.00\) 0.52–1.45 3 Ammonium (ppm) 0.52 \(\pm 0.00\) 0.55 \(\pm 0.00\) 0.50 \(\pm 0.00\) 0.52 \(\pm 0.00\) 0.5–0.55 0.45 \(\pm 0.00\) ND ND 0–0.35 0.06 TN (ppm) 11.39 10.32 8.27 9.32 8.27–11.39 3.49 3.97 2.06 2.06–3.97 Total Phosphate (ppm) 3.52 \(\pm 0.00\) 2.55 \(\pm 0.00\) 0.25 \(\pm 0.00\) 0.52 \(\pm 0.00\) 0.25–3.52 0.28 \(\pm 0.00\) 0.35 \(\pm 0.00\) ND 0–0.35 2.0 COD (ppm) 488 484 320 224 224–488 150 256 428 150–428 40 Explanation: ND = Not detected, TN = Total Nitrogen, EC = Electrical Conductivity, COD = Chemical Oxygen Demand, DO = Dissolved Oxygen. Source: SRI LANKA STANDARD 614: 2013 UDC 663.6. Table 5 and Table 6 describethe recorded physico-chemical parameters of the well water in the dug wells of the Kardiyana, Meethotamulla and Kerawalapitiya dump sites. According to the recorded values, the pH was recorded from 4.25 ± 0.52 to 7.8 ± 0.42 in all the dumping sites which indicates the water pH was within the standards for inland water (SLS- 6.5–8.5, WHO- 6.5–8.5). The DO ranged from 0.5 mg/L to 7.64 mg/L in all selected wells around dump sites. The concentrations of NO 3 − , NO 2 − and NH 4 + were ranged from 1.05–15.25 mg/L, 1.02–5.04 mg/L, and 0.05 > − 0.58 mg/L respectively. The total phosphate concentrations ranged from 0.28–1.65 mg/L around the Karadiyana dump site and it ranged from 0.25–3.52.mg/L ( Table 5 ) in the Meethotamiulla dump site respectively (Table 6 ). All the recorded total phosphate concentrations were within the SLS standard level. Importantly the the COD values ranged from 224–596 mg/L, 224–488 mg/L and 150–428 mg/L in dug wells around Karadiyana, Meethotamulla and Kerawalapitiya dump sites respectively. Further, the recorded COD of all the dug well water exceeded the maximum permissible tolerance level given by SLS Sri Lanka. 3.2 Total and Fecal coliform bacteria Figure 1 and 2 represents the distribution pattern of faecal and total coliform level in groundwater around the dump sites. According to the figures, the total coliform counts were greater in the nearby wells around the dump site and comparatively lower value faecal coliform was recorded in the distance wells. The total coliform count ranged from 0–120 MPN/mL around the Kardiyana dump site. The contamination pattern of fecal coliform also was similar to the total coliform distribution pattern around the Kardiyana dump site which ranged from 0–75 MPN/mL. The well water around the Meethotamulla dump site recorded the faecal and total coliform counts ranging from 0–94 MPN/mL and 3-115 MPN/mL respectively. Moreover, compared to the other two dump sites the well water around the Kerawalpitiya dump site recorded a lower value of total and fecal coliform count which ranged from 3–11 MPN/mL and 7–60 MPN/mL respectively. Table 7 Total and faecal coliform numbers in different sampling locations of the open solid waste dump sites in the study. Sampling location Sample Number Fecal Coliform MPN/mL Total coliform (MPN/mL) Karadiyana K 1 75 120 K 2 64 120 K 3 20 64 K4 43 43 K5 20 43 K6 64 75 K7 40 43 K8 11 20 K9 ND ND K10 3 11 Meethotamulla M1 93 115 M2 43 75 M3 64 93 M4 ND 3 Kerawalapitiya KE 1 11 40 KE2 43 60 KE3 3 7 3.3 Antibiotic Resistance Table 8 Recorded antibiotic resistance E.coli isolates Location No of E. coli AMX AMP CLOX CIP TET SUF SDI GEN AZY ERM Karadiyana 40 40 40 18 2 32 38 38 4 0 34 Meethotamulla 20 20 20 8 0 17 20 18 0 0 12 Kerawalapitiya 10 10 10 0 0 7 8 8 0 0 9 Overall bacteria isolates showed that the highest resistance against AMX (100%) and AMP (100%), following descending order SUF (Karadiyana: 95%, Meethotamulla; 100%; Kerawalapitiya;80%), SDI (Karadiyana: 95%, Meethotamulla; 90%; Kerawalapitiya;80), ERM (Karadiyana: 85%, Meethotamulla; 60%; Kerawalapitiya;90%), TET (Karadiyana: 80%, Meethotamulla; 85%; Kerawalapitiya;70), CLOX (Karadiyana: 45%, Meethotamulla; 40%; Kerawalapitiya;0), GEN (Karadiyana: 10%), and AZY (0) respectively. Resistance against AMX, AMP, SUF/ TRI, SDI, CLOX, TET and ERM was high (> 70%) compared with the other tested antibiotics namely CIP, GEN and AZY (< 40%). 3.4 Detection of the virulence genes by PCR E. coli isolated from three different dumpsites were screened for virulence genes eae A, stx 1, stx 2 by direct PCR. PCR running conditions for these virulence markers were optimized for any deviation from the earlier reported conditions to suit the reagents and thermal cycler used in the present experiment (Table..) (Abia et al. (2017). Among the 70 isolates of E. coli samples analyzed, 17 samples tested positive for the eaeA gene, while 10 and 4 samples were positive for the stx1 and stx2 genes, respectively. According to the results, the Enteropathogenic E. coli pathotype was identified in 17 samples, whereas the Enterohaemorrhagic E. coli pathotype was found in only 3 samples. The percentage of E. coli isolates positive for the eae A gene, ranging from 20–40%, as compared to the positive percentages for stx1 (12.5–20%) and stx2 (2.5–10%) in isolated E. coli strains (Fig. 3 ). Among the E. coli isolates the highest number of positive samples was recorded for the eae A gene in Kerawalapitiya (40%), followed by Meethotamulla (25%) and Karadiyana (20%) in descending order (Fig. 2 ). For stx1, the highest number of positive isolates was observed in Kerawalapitiya (20%), while the highest detection of stx2 was found in isolates from Meethotamulla and Kerawalapitiya (10% each)." Discussion Escherichia coli ( E. coli ) stands as a dependable biological indicator of faecal contamination in water sources, notably accounting for causing various waterborne infections in humans, particularly gastrointestinal diseases (Haley et al., 2022). Furthermore, the presence of antimicrobial-resistant pathogenic strains of E. coli in water sources can potentially facilitate the transfer of antimicrobial resistance and virulence genes to other environmental bacteria (Saja et al., 2021). In addition, the release of leachate from landfills has significant implications for the physical, chemical, biological, and groundwater attributes associated with agriculture and human well-being (Wijerathna 2023c; Idroos et al., 2023). Excessive levels of nitrates and nitrites in groundwater can lead to serious health risks, including methemoglobinemia, blue baby syndrome, cancer, and central nervous system disorders in humans (Ashokkumar et al., 2022; Wijerathna et al., 2023a). According to the ambient water quality guidelines set by the Sri Lanka Standard Institute (SLSI), certain wells around the Karadiyana dump site have surpassed the maximum acceptable nitrate concentration, raising concerns about potential health risks for the general public (Wijerathna et al., 2023b). Moreover, the Chemical Oxygen Demand (COD) levels in all the selected wells exceeded the SLSI standard concentration significantly (Ashokkumar et al., 2022). COD is a crucial parameter for assessing groundwater contamination by a wide range of organic and inorganic pollutants (Abia et al., 2017; Wijerathna et al., 2023b). The results of the present studies showed, that the COD levels around the Karadiyana dump site were greater than those at the other two sites, likely due to the continuous disposal of a substantial amount of municipal solid waste from the Western Province in Karadiyana. The contamination of well water around open dump sites is a global concern due to the potential spread of pathogenic microorganisms within the groundwater system (Abia et al., 2017). Most of the wells studied in the present study were contaminated with faecal and total coliform, indicating severe groundwater pollution in the vicinity of the open soild waste dump area. Landfills often contain expired medications, used diapers, and sanitary products from households and healthcare facilities were observed during the sampling. When these waste items are mixed with general refuse, they can be exposed to various medications, including antibiotics. E. coli can exchange antibiotic resistance traits during prolonged incubation within landfills (Haley et al., 2022; Abia et al., 2017). Antibiotic resistance genes (ARGs) contribute to bacterial antibiotic resistance development and can be transferred via conjugation, transformation, and transduction to pathogenic or environmental bacteria in the environment through horizontal gene transfer (Liyanage et al., 2021; Haley et al., 2022; Shen et al., 2023). The presence of E. coli is a significant risk factor for human infectious diseases caused by these microorganisms, as coliform pathogens can acquire resistance genes from bacterial populations in aquatic environments through horizontal gene transfer, neutralizing various classes of antibiotics (Manage and Liyanage, 2019). The findings of this study suggest that landfills could contribute to the proliferation of antibiotic-resistant bacteria in the environment, which has implications for human health. The battle against antibiotic resistance remains unresolved, with bacteria increasingly developing resistance even to newly developed antibiotics. In the present study, 70 E. coli isolates were tested for resistance to 10 antibiotics from seven different classes. All of these isolates (100%) exhibited resistance to at least one of the tested antibiotics. Resistance was particularly high (> 70%) against AMX, AMP, SUF/TRI, SDI, CLOX, TET, and ERM, in contrast to CIP, GEN, and AZY, which showed lower resistance levels (< 40%) . To the best of our knowledge, this is the first documented report on antibiotic resistance in E. coli isolated from open controlled solid waste dump sites. While the precise reasons for this phenomenon are not easily explained, it is suggested that, in addition to exposure to antibiotics in the environment, other stressors such as exposure to heavy metals may contribute to increased antibiotic resistance in environmental strains (Ondon et al., 2021). Some pathogenic strains of E. coli , such as Enteropathogenic E. coli and Enterohaemorrhagic E. coli , have been recognized as emerging bacterial pathogens (Morgado et al., 2021). Various pathogenic E. coli strains have been isolated from diverse aquatic environments worldwide, including rivers (Felis et al., 2020), lakes, seas, and groundwater resources (Morgado et al., 2021). In the present study, 8% of the pure isolates carried at least one of the tested virulence genes. It is worth noting that the majority of the isolates (approximately 90%) were negative for the genes examined, which could be attributed to the specific selection of genes for testing. Conclusion The assessment of virulence factors in the E. coli isolates indicated that a proportion of these bacteria carried genes associated with pathogenicity. This finding raises concerns about the potential for these isolates to cause diseases in humans and other organism. The study also demonstrated a concerning level of antibiotic resistance among the E. coli isolates. This implies that these bacteria have developed resistance mechanisms against commonly used antibiotics, which can complicate the treatment of infections caused by these strains. The study opens avenues for further research into the specific sources and routes of contamination in open dump sites, as well as the potential impact on nearby water sources and communities. Declarations Data availability statement: The datasets generated during and analysed during the current study are available from the corresponding author upon reasonable request. Conflict of Interest The authors declare that they have no conflict of interest or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution P. A. K. C. Wijerathna- samples collection, microbiological analysis, water quality analysis manuscript writing and editing G. Y. Liyanage – Molecular analysis, manuscript writing editing and proofreading S.M.T.V Bandara- sample collection, microbiological analysis P. M. Manage conceptualization, samples collection, manuscript writing, editing and proofreading References Abia, W.A., Warth, B., Ezekiel, C.N., Sarkanj, B., Turner, P.C., Marko, D., …, Sulyok, M.: Uncommon toxic microbial metabolite patterns in traditionally home-processed maize dish (fufu) consumed in rural Cameroon. Food Chem. Toxicol. 107 , 10–19 (2017) Ashokkumar, V., Flora, G., Venkatkarthick, R., SenthilKannan, K., Kuppam, C., Stephy, G.M., …, Ngamcharussrivichai, C.: Advanced technologies on the sustainable approaches for conversion of organic waste to valuable bioproducts: Emerging circular bioeconomy perspective. Fuel. 324 , 124313 (2022) Devane, M.L., Moriarty, E., Weaver, L., Cookson, A., Gilpin, B.: Fecal indicator bacteria from environmental sources; strategies for identification to improve water quality monitoring. Water Res. 185 , 116204 (2020) Felis, E., Kalka, J., Sochacki, A., Kowalska, K., Bajkacz, S., Harnisz, M., Korzeniewska, E.: Antimicrobial pharmaceuticals in the aquatic environment-occurrence and environmental implications. Eur. J. Pharmacol. 866 , 172813 (2020) Haley, B.J., Kim, S.W., Salaheen, S., Hovingh, E., Van Kessel, J.A.S.: Virulome and genome analyses identify associations between antimicrobial resistance genes and virulence factors in highly drug-resistant Escherichia coli isolated from veal calves. Plos one. 17 (3), e0265445 (2022) Idroos, F.S., Wijerathna, P.A.K.C., Abeysiri, H.A.S.N., Manage, P.M.: Nitrite, Nitrate, Ammonia and Phosphate Pollution and Their Remediation. In: Karn, S.K. Bhambri, A (eds) Microbial Technologies and Their Applications, Nova science Publishers. (2023). https://doi.org/10.52305/JUTX4763 Junaid, M., Liu, S., Liao, H., Liu, X., Wu, Y., Wang, J.: Wastewater plastisphere enhances antibiotic resistant elements, bacterial pathogens, and toxicological impacts in the environment. Sci. Total Environ. 841 , 156805 (2022) Kim, S.J., Ogo, M., Oh, M.J., Suzuki, S.: Occurrence of tetracycline resistant bacteria and tet (M) gene in seawater from Korean coast. In: Interdisciplinary studies on environmental chemistry—Environmental pollution and ecotoxicology, pp. 367–375. TERRAPUB, Tokyo (2012) Liyanage, G.Y., Manage, P.M.: Quantification of Oxytetracycline and Amphicillin in two waste water discharging points in Colombo, Sri Lanka. Environ. Nat. Resour. J. 1 , 195–198 (2014) Liyanage, G.Y., Illango, A., Manage, P.M.: Prevalence and quantitative analysis of antibiotic resistance genes (ARGs) in surface and groundwater in meandering part of the Kelani River Basin in Sri Lanka. Water Air Soil Pollut. 232 , 1–11 (2021) Liyanage, G.Y., Weerasekera, M.M., Manage, P.M.: Screening and quantitative analysis of antibiotic resistance genes in hospital and aquaculture effluent in Sri Lanka as an emerging environmental contaminant. (2022) Manage, P.M., Liyanage, G.Y.: Antibiotics induced antibacterial resistance. In: Pharmaceuticals and personal care products: waste management and treatment technology, pp. 429–448. Butterworth-Heinemann (2019) Morgado-Gamero, W.B., Parody, A., Medina, J., Rodriguez-Villamizar, L.A., Agudelo-Castañeda, D.: Multi-antibiotic resistant bacteria in landfill bioaerosols: Environmental conditions and biological risk assessment. Environ. Pollut. 290 , 118037 (2021) Ondon, B.S., Li, S., Zhou, Q., Li, F.: Sources of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the soil: A review of the spreading mechanism and human health risks. Reviews of Environmental Contamination and Toxicology Volume. 256 , 121–153 (2021) Pathmalal, M.M., Hemantha, R.S.K.W.D., Dilena, P.K., Liyanage, G.Y., Chalani, H.T.R., Bandara, K.R.V., Wijerathna, P.A.K.C., Abeysiri, H., A.S.N: Impact of the MV X-Press Pearl ship disaster on the coastal environment from Negambo to Benthota in Sri Lanka. Reg. Stud. Mar. Sci. Volume. 58 , 102788 (2023). https://doi.org/10.1016/j.rsma.2022.102788 Roy, H., Alam, S.R., Bin-Masud, R., Prantika, T.R., Pervez, M.N., Islam, M.S., Naddeo, V.: A Review on Characteristics, Techniques, and Waste-to-Energy Aspects of Municipal Solid Waste Management: Bangladesh Perspective. Sustainability. 14 (16), 10265 (2022) Saja, A.M.A., Zimar, A.M.Z., Junaideen, S.M.: Municipal solid waste management practices and challenges in the southeastern coastal cities of Sri Lanka. Sustainability. 13 (8), 4556 (2021) Shen, W., Zhang, H., Li, X., Qi, D., Liu, R., Kang, G., …, Hu, S.: Pathogens and antibiotic resistance genes during the landfill leachate treatment process: Occurrence, fate, and impact on groundwater. Sci. Total Environ. 903 , 165925 (2023) Wijerathna, P.A.K.C., Ekanayake, M.S., Idroos, F.S., Manage, P.M.: Biological Wastewater Treatment Technology. In: Karn, S.K. Bhambri, A (eds) Microbial Technologies and Their Applications, Nova science Publishers. (2023). (a) https://doi.org/10.52305/JUTX4763 Wijerathna, P.A.K.C., Idroos, S.F., Manage, P.M.: A Review of the Green Approach to the Treatment of Solid Waste Leachate, International Journal of Environment and Waste Management,1(1), (2023). (b) 10.1504/IJEWM.10050942 Wijerathna, P.A.K.C., Udayagee, K.P.P., Idroos, F.S., Manage, P.M.: Waste Biomass Valorization and Its Application in the Environment. In: Pal, D.B., Tiwari, A.K. (eds) Sustainable Valorization of Agriculture & Food Waste Biomass. Clean Energy Production Technologies. Springer, Singapore. (2023). (c) https://doi.org/10.1007/978-981-99-0526-3_1 Cite Share Download PDF Status: Published Journal Publication published 06 May, 2024 Read the published version in Waste and Biomass Valorization → Version 1 posted Reviewers agreed at journal 06 Jan, 2024 Reviewers invited by journal 22 Nov, 2023 Editor assigned by journal 01 Nov, 2023 First submitted to journal 01 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3547316","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":252594875,"identity":"8835869d-7874-4d93-bc34-2f65fd8b61ff","order_by":0,"name":"G.Y. Liyanage","email":"","orcid":"","institution":"University of Sri Jayewardenepura","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"G.Y.","middleName":"","lastName":"Liyanage","suffix":""},{"id":252594876,"identity":"b905b24e-0f9b-446f-83a5-24abb65109c9","order_by":1,"name":"P. A. K. C. Wijerathna","email":"","orcid":"","institution":"University of Sri Jayewardenepura","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"P.","middleName":"A. K. C.","lastName":"Wijerathna","suffix":""},{"id":252594877,"identity":"c81939a6-4152-4084-9977-0e88a2bf880f","order_by":2,"name":"S.M.T.V. Bandara","email":"","orcid":"","institution":"University of Sri Jayewardenepura","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"S.M.T.V.","middleName":"","lastName":"Bandara","suffix":""},{"id":252594878,"identity":"b7fa047a-9d26-4771-ae74-c34e55584ccf","order_by":3,"name":"Pathmalal Manage","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie2RvQrCMBCATwLJUnQ96dBXSAlYC/68SqVrBcFFUNApk+jaxykIdnR1FAv6Bo7iVRw6JY6C+eAgd9xH7hIAh+M34RR9aIsNyHcuuM1gdQcC94qPwr5WMGkWDETidLyeVxjw7v0yn8EoICUxKvE2FSo7Yqj9TKoc0nDDeGFUZJFyP+PYIgWUBywBRg9hVE4VKU8c6255IWX9hXKmW6YaJxpBknIgxTJYnFc9f7rDVHv1LrIMtW39qDO5+dljMNyL8qZmi2XQEVqaB2ucuapT60c2FVbZuh0Oh+M/eQGIlTTYjzbHlgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Sri Jayewardenepura","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Pathmalal","middleName":"","lastName":"Manage","suffix":""}],"badges":[],"createdAt":"2023-11-02 22:05:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3547316/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3547316/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12649-024-02544-x","type":"published","date":"2024-05-06T21:17:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":47213053,"identity":"a125aef2-6b84-40de-ac4a-b2d984e2c2fd","added_by":"auto","created_at":"2023-11-28 17:04:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":394327,"visible":true,"origin":"","legend":"\u003cp\u003eFaecal (a) and total coliform (b) distribution pattern of groundwater around Karadiyana control open dump site.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3547316/v1/30b89b6ca077617c43c37ab6.png"},{"id":47213054,"identity":"17c2adbc-1254-4503-89da-5561e853df25","added_by":"auto","created_at":"2023-11-28 17:04:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":380794,"visible":true,"origin":"","legend":"\u003cp\u003eFecal and total coliform distribution pattern of ground water around Meethotamulla and Kerawalapitiya\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3547316/v1/2f9549622fa4e3177e990acd.png"},{"id":47213055,"identity":"21fc02fb-01b1-4fb9-b159-1fb692edc6bb","added_by":"auto","created_at":"2023-11-28 17:04:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":117716,"visible":true,"origin":"","legend":"\u003cp\u003eGene detection percentage of isolated \u003cem\u003eE.coli\u003c/em\u003efrom open dumpsites\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3547316/v1/b135f817b2b3fe94a68ac4e6.png"},{"id":56488289,"identity":"b44de77b-60d7-4c26-8d55-f1eb27152622","added_by":"auto","created_at":"2024-05-14 21:31:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1912951,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3547316/v1/54af2110-5b0d-4008-929f-6ca87f7bf6bb.pdf"}],"financialInterests":"","formattedTitle":"Assessment of Virulence Potential and Antibiotic Resistance Profiles in E. coli Isolates from Selected Control Open Dump Sites in Sri Lanka","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn most developed countries, the technology for the treatment of landfill leachate has been maintained well and monitored strictly. However, for developing countries, waste classification and sealed management systems have not yet been perfectly established due to the lack of waste recycling legislation, technique equipment, and public awareness (Roy et al., 2022; Wijerathna et al., 2023c). In landfills, a significant volume of human waste, animal waste, and industrial waste with high antibiotic levels have been discarded (Manage and Liyanage 2019; Liyanage et al., 2021; Ashokkumar et al., 2022). Antibiotic-resistant bacteria (ARB) may become the predominant communities in landfills as a result of the presence and ongoing input of such antibiotics (Morgado et al., 2021; Felis et al., 2020). Additionally, the presence of mobile genetic elements would encourage the frequency of horizontal gene transfer between pathogenic bacteria and ARB, making the landfill a hotspot for pathogenic bacteria and ARGs (Junaid et al., 2022). This is especially true for landfills without proper seepage control facilities (Ondon et al., 2021). A serious threat to public health and environmental safety exists at these sites because mixed pollutants (ARB and ARGs) migrate with landfill leachate and contaminate surface or underground water (Ondon et al., 2021; Junaid et al., 2022). Therefore, it is critical to create regulating technologies to lessen the prevalence of dangerous bacteria and ARG spread.\u003c/p\u003e \u003cp\u003eOne of the most prevalent facultative pathogens in human health, \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e), is also a crucial component of the study of water quality, particularly concerning faecal contamination Devane et al., 2020; Wijerathna et al., 2023a). According to studies, a significant amount of the \u003cem\u003eE. coli\u003c/em\u003e population detected in surface water already has at least one acquired resistance, and multi-resistant isolates are no longer unusual.\u003c/p\u003e \u003cp\u003eHowever, some strains of \u003cem\u003eE. coli\u003c/em\u003e have developed virulence factors and genes for antibiotic resistance, which can cause serious infections and represent a serious risk to the general public's health (Haley et al., 2022; Shen et al., 2023). Due to the risk of environmental contamination and subsequent spread of antibiotic resistance to other ecological niches, the prevalence and antimicrobial resistance patterns of \u003cem\u003eE. coli\u003c/em\u003e in landfill leachates are of the utmost importance (Haley et al., 2022; Shen et al., 2023).\u003c/p\u003e \u003cp\u003eThe management of garbage, including the eradication of municipal solid waste, is a major concern in Sri Lanka, a developing country that is experiencing fast urbanization and industrialization. Landfills are frequently used to dispose of garbage, and the leachates they produce frequently find their way into the surface and groundwater in the area, endangering ecosystems and human health (Saja et al., 2021) Since they may serve as reservoirs for antimicrobial resistance genes that can spread to other bacteria in the environment, the existence of antimicrobial-resistant \u003cem\u003eE. coli\u003c/em\u003e strains in landfill leachates can exacerbate this issue.\u003c/p\u003e \u003cp\u003eTo evaluate the possible dangers connected with these waste disposal sites, it is essential to understand the prevalence and antibiotic resistance profiles of \u003cem\u003eE. coli\u003c/em\u003e isolated from landfill leachates. We can learn a lot about the prevalence and antibiotic resistance trends of E. coli strains, which will help us understand how landfill leachates affect the propagation of antimicrobial resistance and the risk of human exposure to contaminated water sources.\u003c/p\u003e \u003cp\u003eThis study aims to determine the prevalence and antimicrobial resistance profiles of \u003cem\u003eE. coli\u003c/em\u003e strains isolated from landfill leachate sites in Sri Lanka. The objectives include: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) identifying the prevalence and distribution of \u003cem\u003eE. coli\u003c/em\u003e in landfill leachates, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) characterizing the antimicrobial resistance patterns of the isolated \u003cem\u003eE. coli\u003c/em\u003e strains, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) exploring potential correlations between the occurrence of antimicrobial resistance and the physicochemical parameters of the leachate.\u003c/p\u003e \u003cp\u003eThe results of this study will be crucial for the creation of efficient waste management plans and for reducing any potential health risks brought on by landfill leachate contamination in Sri Lanka.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eKaradiyana, Meethotamulla and Kerawalapitiya dumping sites were selected as the study area for the present study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Those sites are identified as major solid waste disposal sites in the Colombo area. The number of groundwater sampling locations depended on the availability of groundwater sources in each area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Water samples collection\u003c/h2\u003e \u003cp\u003eFor the study, 17 dug-well water samples were collected from Karadiyana (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), Meethotamulla (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and Kerawalapitiya (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) open dump sites respectively on 15th and 16th August, 2023 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Pre-cleaned polypropylene bottles and amber-coloured sterile glass bottles were used to collect water for chemical and microbial analysis respectively. Water samples were transported to the laboratory in a refrigerated condition within 24 hours and stored in a cold room. Microbiological and chemical analyses were performed within 24 hours after the collection of samples. The GPS coordinates were recorded via a hand-held GPS receiver (Model -etrex\u0026reg; 22x) at the site.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.3 Physico chemical analysis in water samples\u003c/h2\u003e \u003cp\u003eWater quality parameters; water temperature, pH, Dissolved Oxygen (DO), and Electrical Conductivity (EC) were measured using a thermometer (Immersion, Philip Harris, and England), pH meter (330 I/ Set, WTW Co., Weilheim, Germany), DO meter (HQD portable multimeter -HACH - HQ 40D) and a conductivity meter (340A-Set 1) respectively at the site itself. Chemical parameters such as N- Nitrate (as NO3-), N-Nitrite (as NO2-), N-Ammonia (as NH3), total inorganic nitrogen and total phosphorous were measured in the laboratory using Standard Methods for the Examination of Water and Wastewater published by American Public Health Association (APHA 2012). The Chemical Oxygen Demand (COD) of the water were measured following the closed reflux method (Pathmalal et al., 2023, Wijerathna et al., 2023 b)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.4 Microbiological Analysis\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section4\"\u003e \u003ch2\u003e2.4.1 Total and faecal coliform bacteria (Most Probable Number (MPN) method)\u003c/h2\u003e \u003cp\u003eThe most Probable Number method was performed to determine the Total coliform (TC) and \u003cem\u003eE. coli\u003c/em\u003e count per 0.1 dm3 of the water samples. Presumptive test, confirmed test and completed test were carried out to isolate and identify \u003cem\u003eE.coli\u003c/em\u003e and Total coliform in the samples [Manjula et al., 2011 and WHO,2012, SLSI 2013, Wijerathna et al., 2022b].\u003c/p\u003e \u003cp\u003eColonies developed on EMB agar, were further identified as coliforms or faecal coliforms (Escherichia coli) using cultural characteristics, morphology and biochemical tests. For faecal coliforms, colonies with green metallic sheen were Gram stained and the IMVIC test was carried out to identify the colony as \u003cem\u003eE.coli.\u003c/em\u003e The MPN per 100 mL water was determined using the completed test.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of groundwater sampling locations in the selected dumping site.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDumping site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample Number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUsage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDescription of the dug well\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePhysical appearance of the water\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eKaradiyana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncovered well, 2 m deep,\u003c/p\u003e \u003cp\u003eSurface water percolates into the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDark-coloured water with an unpleasant smell\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation and washing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well, concrete lining 4 m deep, Surface water does not percolate into the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA bit muddy coloured with an unpleasant odour\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e5 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow coloured water\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e4 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e4 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncovered well with 3 m deep. Surface water percolates into the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow coloured water\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e4 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e4 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePale coloured water\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e6 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation, washing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e6 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMeethotamulla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAbundant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncovered well with 2 m deep. Surface water percolates into the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlack coloured\u003c/p\u003e \u003cp\u003eUnpleasant odour\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWashing, cooking\u003c/p\u003e \u003cp\u003eand drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e3 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePale muddy coloured\u003c/p\u003e \u003cp\u003emuddy odour\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWashing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered\u003c/p\u003e \u003cp\u003eCovered well with a concrete lining\u003c/p\u003e \u003cp\u003e3 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWashing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncovered well with 2 m deep. Surface water percolates into the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMuddy Coloured\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eKerawalapitiya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKE 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncovered well with 3 m deep. Surface water percolates into the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMuddy Coloured\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAbundant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered, 4 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMuddy Coloured\u003c/p\u003e \u003cp\u003eUnpleasant Odours\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKE3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIrrigation and washing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovered, 4 m deep, Surface water does not percolate to the well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColourless\u003c/p\u003e \u003cp\u003eOdourless\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e2.4.2 Isolation and confirmation of pure cultures of\u003c/b\u003e \u003cb\u003eE.coli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFive colonies were randomly selected from each plate. For plates with \u0026le;\u0026thinsp;5 colonies, all the isolates were selected for further purification. Following incubation, a single colony was selected and streaked further on EMB agar to obtain pure isolates, which were then used for virulence and antibiotic susceptibility profiling.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.5 Screening of Antibiotic Resistance in Isolated\u003c/b\u003e \u003cb\u003eE.coli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFollowing incubation in nutrient broth, the turbidity of the broth culture was adjusted to a 0.5 McFarland standard before inoculating onto a pre-prepared nutrient agar medium. Filter sterilized (0.2 \u0026micro;m) antibiotics; Tetracycline (TET), Amphicillin (AMP), Amoxicillin (AMX), Cloxacillin (CLOX) and Ciprofloxacin (CIP) at a final concentration of 60\u0026micro;g/mL were spiked to each molting nutrient agar media (40 \u003csup\u003e0\u003c/sup\u003eC) before inoculating bacteria (Liyanage et al., 2022; Liyanage and Manage, 2014). Then equalized bacterial samples were inoculated on the prepared nutrient agar medium according to CLSI guidelines and screened for antibiotic resistance in each bacterium (Liyanage et al.,2021).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.6 Determination of Virulence Potentials of Isolates\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section4\"\u003e \u003ch2\u003e2.6.1 Extraction of DNA\u003c/h2\u003e \u003cp\u003eFollowing Kim et al. (2012), the genomic DNA of isolated bacteria was extracted. Re-sup\u003c/p\u003e \u003cp\u003eended purified DNA was kept at -20 \u003csup\u003e0\u003c/sup\u003eC in 50 \u0026micro;l of TE buffer.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.6.2 Detection of the virulence genes by PCR\u003c/h2\u003e \u003cp\u003eThe extracted DNA was used as the template DNA in different real-time PCR assays for the identification of genes associated with virulence in two (02) \u003cem\u003eE. coli\u003c/em\u003e pathotypes. The various genes tested and the associated pathotypes are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVirulence genes investigated and associated E. coli pathotypes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScreened Genes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnteropathogenic \u003cem\u003eE.coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eeae A\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterohaemorrhagic \u003cem\u003eE.coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eeae A, stx 1, stx 2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe primers and PCR conditions used for the various genes were previously described by Abia et al. (2017). All controls were obtained from the Medical Research Laboratory in Sri Lanka. Reaction mixtures without DNA, which were used as negative controls, were also included in each PCR assay. All PCR assays were performed on a BIORAD PCR machine (Qiagen, Hilden, Germany). From Integrated DNA Technologies (IDT), primer sets were acquired. For each PCR, the master 25mixture was prepared as follows (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComposition of PCR mixture\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePCR ingredient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolume per sample/ \u0026micro;L\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePCR water\u003c/p\u003e \u003cp\u003e(PROMEGA, Cat No: MC1191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5 to15.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGo Taq Polymerase (5U/\u0026micro;l)\u003c/p\u003e \u003cp\u003e(PROMEGA, Madison, USA, Ref- M829B),\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMgCl\u003csub\u003e2\u003c/sub\u003e (50 mM)\u003c/p\u003e \u003cp\u003e(PROMEGA, Madison, USA, Ref- M891A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 to 1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003edNTP mix (10 \u0026micro;M)\u003c/p\u003e \u003cp\u003e(PROMEGA, Madison, USA, Cat No: PAU1515)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e10 \u0026micro;M Forward primer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e10 \u0026micro;M Reverse primer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e5 x reaction buffer\u003c/p\u003e \u003cp\u003e(PROMEGA, Madison, USA, Ref- M829B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDNA template\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePCR amplification was performed to screen for \u003cem\u003eeaeA, stx1 and stx2\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) genes. Initial denaturation at 94\u0026deg;C for 3 minutes was followed by 30 cycles at 94\u0026deg;C for 10 seconds, 50\u0026deg;C for 20 seconds, and 72\u0026deg;C for 60 seconds in the PCR for \u003cem\u003eeaeA\u003c/em\u003e. Initial denaturation at 94\u0026deg;C for 10 minutes was followed by 30 cycles at 94\u0026deg;C for 30 seconds, 45\u0026deg;C for 30 seconds, and 72\u0026deg;C for 60 seconds for \u003cem\u003estx1 and stx2\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":"\u003cp\u003e3.1 Physico chemical parameters in water samples\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003ewater quality parameters for the dug wells around the Karadiyana dump site.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample Number\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK6\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK7\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK8\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK9\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK10\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSLS (614: 2013)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRange\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.25\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.56\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.88\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.41\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.64\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.57\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.44\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.78\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.62\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.16\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.0\u0026ndash;8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.25\u0026ndash;7.44\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDO (mg/L)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5\u0026ndash;6.51\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTemperature (\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.2\u0026ndash;31.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEC(\u0026micro;S/cm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2462\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e195.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e166.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e209.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e748.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e561.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e667.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e190.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e226.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e181.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e750\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e166.8\u0026ndash;2462\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNitrate (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.22\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.05\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.21\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.85\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.07\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.25\u0026ndash;15.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNitrite (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.03\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.04\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.15\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.07\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.03\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.02\u0026ndash;5.04\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAmmonium (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.58\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.55\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.45\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;0.58\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTN (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.27\u0026ndash;19.76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal Phosphate (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.55\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.65\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.53\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.29\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.84\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.50\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.05\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28\u0026ndash;1.65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eCOD (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e460\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e596\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e452\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e596\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e264\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e256\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e352\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e224\u0026ndash;596\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eParameters for Meethotamulla and Kerawalapitiya\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eMeethotamulla\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eKerawalapitiya\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSLS (614: 2013)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample Number\u003c/strong\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRange\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRange\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.84\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.18\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.17\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.75\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.17\u0026ndash;6.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.80\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.19\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.23\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.19\u0026ndash;7.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.5\u0026ndash;8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDO (mg/L)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.58\u0026ndash;5.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.74\u0026ndash;7.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTemperature (\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.5\u0026ndash;28.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.4\u0026ndash;29.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEC (\u0026micro;S/cm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e407.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e315.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e163.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e446.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e163.9\u0026ndash;446.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e548.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e375.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e375.9\u0026ndash;5248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e700\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNitrate (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.85\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.07\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.75\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.11\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.25\u0026ndash;8.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05\u0026ndash;2.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNitrite (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.02\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.01\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05\u0026ndash;2.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.45\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.04\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u0026ndash;1.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAmmonium (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.55\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.50\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5\u0026ndash;0.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.45\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTN (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.27\u0026ndash;11.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.06\u0026ndash;3.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal Phosphate (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.55\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25\u0026ndash;3.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm 0.00\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eCOD (ppm)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e488\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e484\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e320\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e224\u0026ndash;488\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e150\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e256\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e428\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e150\u0026ndash;428\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"1\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eExplanation: ND\u0026thinsp;=\u0026thinsp;Not detected, TN\u0026thinsp;=\u0026thinsp;Total Nitrogen, EC\u0026thinsp;=\u0026thinsp;Electrical Conductivity, COD\u0026thinsp;=\u0026thinsp;Chemical Oxygen Demand, DO\u0026thinsp;=\u0026thinsp;Dissolved Oxygen.\u003c/p\u003e\n\u003cp\u003eSource: SRI LANKA STANDARD 614: 2013 UDC 663.6.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e describethe recorded physico-chemical parameters of the well water in the dug wells of the Kardiyana, Meethotamulla and Kerawalapitiya dump sites. According to the recorded values, the pH was recorded from 4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52 to 7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 in all the dumping sites which indicates the water pH was within the standards for inland water (SLS- 6.5\u0026ndash;8.5, WHO- 6.5\u0026ndash;8.5). The DO ranged from 0.5 mg/L to 7.64 mg/L in all selected wells around dump sites. The concentrations of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus; ,\u003c/sup\u003e NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e were ranged from 1.05\u0026ndash;15.25 mg/L, 1.02\u0026ndash;5.04 mg/L, and 0.05\u0026thinsp;\u0026gt;\u0026thinsp;\u0026minus;\u0026thinsp;0.58 mg/L respectively. The total phosphate concentrations ranged from 0.28\u0026ndash;1.65 mg/L around the Karadiyana dump site and it ranged from 0.25\u0026ndash;3.52.mg/L ( Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) in the Meethotamiulla dump site respectively (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). All the recorded total phosphate concentrations were within the SLS standard level. Importantly the the COD values ranged from 224\u0026ndash;596 mg/L, 224\u0026ndash;488 mg/L and 150\u0026ndash;428 mg/L in dug wells around Karadiyana, Meethotamulla and Kerawalapitiya dump sites respectively. Further, the recorded COD of all the dug well water exceeded the maximum permissible tolerance level given by SLS Sri Lanka.\u003c/p\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Total and Fecal coliform bacteria\u003c/h2\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e represents the distribution pattern of faecal and total coliform level in groundwater around the dump sites. According to the figures, the total coliform counts were greater in the nearby wells around the dump site and comparatively lower value faecal coliform was recorded in the distance wells. The total coliform count ranged from 0\u0026ndash;120 MPN/mL around the Kardiyana dump site. The contamination pattern of fecal coliform also was similar to the total coliform distribution pattern around the Kardiyana dump site which ranged from 0\u0026ndash;75 MPN/mL. The well water around the Meethotamulla dump site recorded the faecal and total coliform counts ranging from 0\u0026ndash;94 MPN/mL and 3-115 MPN/mL respectively. Moreover, compared to the other two dump sites the well water around the Kerawalpitiya dump site recorded a lower value of total and fecal coliform count which ranged from \u003cstrong\u003e3\u0026ndash;11\u003c/strong\u003e MPN/mL and 7\u0026ndash;60 MPN/mL respectively.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eTotal and faecal coliform numbers in different sampling locations of the open solid waste dump sites in the study.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSampling location\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample Number\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFecal Coliform\u003c/p\u003e\n\u003cp\u003eMPN/mL\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal coliform\u003c/p\u003e\n\u003cp\u003e(MPN/mL)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"10\" align=\"left\"\u003e\n\u003cp\u003eKaradiyana\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eK10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eMeethotamulla\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eM1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e115\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eM2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eM3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eM4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eND\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eKerawalapitiya\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKE 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKE2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKE3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Antibiotic Resistance\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab7\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eRecorded antibiotic resistance \u003cem\u003eE.coli\u003c/em\u003e isolates\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eLocation\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo of\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAMX\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAMP\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCLOX\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCIP\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTET\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSUF\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSDI\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGEN\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAZY\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eERM\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKaradiyana\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeethotamulla\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKerawalapitiya\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOverall bacteria isolates showed that the highest resistance against AMX (100%) and AMP (100%), following descending order SUF (Karadiyana: 95%, Meethotamulla; 100%; Kerawalapitiya;80%), SDI (Karadiyana: 95%, Meethotamulla; 90%; Kerawalapitiya;80), ERM (Karadiyana: 85%, Meethotamulla; 60%; Kerawalapitiya;90%), TET (Karadiyana: 80%, Meethotamulla; 85%; Kerawalapitiya;70), CLOX (Karadiyana: 45%, Meethotamulla; 40%; Kerawalapitiya;0), GEN (Karadiyana: 10%), and AZY (0) respectively. Resistance against AMX, AMP, SUF/ TRI, SDI, CLOX, TET and ERM was high (\u0026gt;\u0026thinsp;70%) compared with the other tested antibiotics namely CIP, GEN and AZY (\u0026lt;\u0026thinsp;40%).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 Detection of the virulence genes by PCR\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e isolated from three different dumpsites were screened for virulence genes eae A, \u003cem\u003estx\u003c/em\u003e 1, \u003cem\u003estx\u003c/em\u003e 2 by direct PCR. PCR running conditions for these virulence markers were optimized for any deviation from the earlier reported conditions to suit the reagents and thermal cycler used in the present experiment (Table..) (Abia et al. (2017).\u003c/p\u003e\n\u003cp\u003eAmong the 70 isolates of \u003cem\u003eE. coli\u003c/em\u003e samples analyzed, 17 samples tested positive for the eaeA gene, while 10 and 4 samples were positive for the stx1 and stx2 genes, respectively. According to the results, the Enteropathogenic \u003cem\u003eE. coli\u003c/em\u003e pathotype was identified in 17 samples, whereas the Enterohaemorrhagic \u003cem\u003eE. coli\u003c/em\u003e pathotype was found in only 3 samples.\u003c/p\u003e\n\u003cp\u003eThe percentage of \u003cem\u003eE. coli\u003c/em\u003e isolates positive for the \u003cem\u003eeae\u003c/em\u003eA gene, ranging from 20\u0026ndash;40%, as compared to the positive percentages for stx1 (12.5\u0026ndash;20%) and stx2 (2.5\u0026ndash;10%) in isolated \u003cem\u003eE. coli\u003c/em\u003e strains (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the \u003cem\u003eE. coli\u003c/em\u003e isolates the highest number of positive samples was recorded for the \u003cem\u003eeae\u003c/em\u003eA gene in Kerawalapitiya (40%), followed by Meethotamulla (25%) and Karadiyana (20%) in descending order (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). For stx1, the highest number of positive isolates was observed in Kerawalapitiya (20%), while the highest detection of stx2 was found in isolates from Meethotamulla and Kerawalapitiya (10% each).\"\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e) stands as a dependable biological indicator of faecal contamination in water sources, notably accounting for causing various waterborne infections in humans, particularly gastrointestinal diseases (Haley et al., 2022). Furthermore, the presence of antimicrobial-resistant pathogenic strains of \u003cem\u003eE. coli\u003c/em\u003e in water sources can potentially facilitate the transfer of antimicrobial resistance and virulence genes to other environmental bacteria (Saja et al., 2021). In addition, the release of leachate from landfills has significant implications for the physical, chemical, biological, and groundwater attributes associated with agriculture and human well-being (Wijerathna 2023c; Idroos et al., 2023).\u003c/p\u003e \u003cp\u003eExcessive levels of nitrates and nitrites in groundwater can lead to serious health risks, including methemoglobinemia, blue baby syndrome, cancer, and central nervous system disorders in humans (Ashokkumar et al., 2022; Wijerathna et al., 2023a). According to the ambient water quality guidelines set by the Sri Lanka Standard Institute (SLSI), certain wells around the Karadiyana dump site have surpassed the maximum acceptable nitrate concentration, raising concerns about potential health risks for the general public (Wijerathna et al., 2023b). Moreover, the Chemical Oxygen Demand (COD) levels in all the selected wells exceeded the SLSI standard concentration significantly (Ashokkumar et al., 2022). COD is a crucial parameter for assessing groundwater contamination by a wide range of organic and inorganic pollutants (Abia et al., 2017; Wijerathna et al., 2023b). The results of the present studies showed, that the COD levels around the Karadiyana dump site were greater than those at the other two sites, likely due to the continuous disposal of a substantial amount of municipal solid waste from the Western Province in Karadiyana.\u003c/p\u003e \u003cp\u003eThe contamination of well water around open dump sites is a global concern due to the potential spread of pathogenic microorganisms within the groundwater system (Abia et al., 2017). Most of the wells studied in the present study were contaminated with faecal and total coliform, indicating severe groundwater pollution in the vicinity of the open soild waste dump area. Landfills often contain expired medications, used diapers, and sanitary products from households and healthcare facilities were observed during the sampling. When these waste items are mixed with general refuse, they can be exposed to various medications, including antibiotics. \u003cem\u003eE. coli\u003c/em\u003e can exchange antibiotic resistance traits during prolonged incubation within landfills (Haley et al., 2022; Abia et al., 2017). Antibiotic resistance genes (ARGs) contribute to bacterial antibiotic resistance development and can be transferred via conjugation, transformation, and transduction to pathogenic or environmental bacteria in the environment through horizontal gene transfer (Liyanage et al., 2021; Haley et al., 2022; Shen et al., 2023). The presence of \u003cem\u003eE. coli\u003c/em\u003e is a significant risk factor for human infectious diseases caused by these microorganisms, as coliform pathogens can acquire resistance genes from bacterial populations in aquatic environments through horizontal gene transfer, neutralizing various classes of antibiotics (Manage and Liyanage, 2019). The findings of this study suggest that landfills could contribute to the proliferation of antibiotic-resistant bacteria in the environment, which has implications for human health.\u003c/p\u003e \u003cp\u003eThe battle against antibiotic resistance remains unresolved, with bacteria increasingly developing resistance even to newly developed antibiotics. In the present study, 70 \u003cem\u003eE. coli\u003c/em\u003e isolates were tested for resistance to 10 antibiotics from seven different classes. All of these isolates (100%) exhibited resistance to at least one of the tested antibiotics. Resistance was particularly high (\u0026gt;\u0026thinsp;70%) against AMX, AMP, SUF/TRI, SDI, CLOX, TET, and ERM, in contrast to CIP, GEN, and AZY, which showed lower resistance levels (\u0026lt;\u0026thinsp;40%) .\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first documented report on antibiotic resistance in \u003cem\u003eE. coli\u003c/em\u003e isolated from open controlled solid waste dump sites. While the precise reasons for this phenomenon are not easily explained, it is suggested that, in addition to exposure to antibiotics in the environment, other stressors such as exposure to heavy metals may contribute to increased antibiotic resistance in environmental strains (Ondon et al., 2021).\u003c/p\u003e \u003cp\u003eSome pathogenic strains of \u003cem\u003eE. coli\u003c/em\u003e, such as Enteropathogenic \u003cem\u003eE. coli\u003c/em\u003e and Enterohaemorrhagic \u003cem\u003eE. coli\u003c/em\u003e, have been recognized as emerging bacterial pathogens (Morgado et al., 2021). Various pathogenic \u003cem\u003eE. coli\u003c/em\u003e strains have been isolated from diverse aquatic environments worldwide, including rivers (Felis et al., 2020), lakes, seas, and groundwater resources (Morgado et al., 2021). In the present study, 8% of the pure isolates carried at least one of the tested virulence genes. It is worth noting that the majority of the isolates (approximately 90%) were negative for the genes examined, which could be attributed to the specific selection of genes for testing.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe assessment of virulence factors in the \u003cem\u003eE. coli\u003c/em\u003e isolates indicated that a proportion of these bacteria carried genes associated with pathogenicity. This finding raises concerns about the potential for these isolates to cause diseases in humans and other organism. The study also demonstrated a concerning level of antibiotic resistance among the \u003cem\u003eE. coli\u003c/em\u003e isolates. This implies that these bacteria have developed resistance mechanisms against commonly used antibiotics, which can complicate the treatment of infections caused by these strains. The study opens avenues for further research into the specific sources and routes of contamination in open dump sites, as well as the potential impact on nearby water sources and communities.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analysed during the current study are available from the\u003c/p\u003e\n\u003cp\u003ecorresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eP. A. K. C. Wijerathna- samples collection, microbiological analysis, water quality analysis manuscript writing and editing\u003c/p\u003e\n\u003cp\u003eG. Y. Liyanage \u0026ndash; Molecular analysis, manuscript writing editing and proofreading\u003c/p\u003e\n\u003cp\u003eS.M.T.V Bandara- sample collection, microbiological analysis\u003c/p\u003e\n\u003cp\u003eP. M. Manage conceptualization, samples collection, manuscript writing, editing and proofreading\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbia, W.A., Warth, B., Ezekiel, C.N., Sarkanj, B., Turner, P.C., Marko, D., \u0026hellip;, Sulyok, M.: Uncommon toxic microbial metabolite patterns in traditionally home-processed maize dish (fufu) consumed in rural Cameroon. Food Chem. 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(a) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.52305/JUTX4763\u003c/span\u003e\u003cspan address=\"10.52305/JUTX4763\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWijerathna, P.A.K.C., Idroos, S.F., Manage, P.M.: A Review of the Green Approach to the Treatment of Solid Waste Leachate, International Journal of Environment and Waste Management,1(1), (2023). (b) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1504/IJEWM.10050942\u003c/span\u003e\u003cspan address=\"10.1504/IJEWM.10050942\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWijerathna, P.A.K.C., Udayagee, K.P.P., Idroos, F.S., Manage, P.M.: Waste Biomass Valorization and Its Application in the Environment. In: Pal, D.B., Tiwari, A.K. (eds) Sustainable Valorization of Agriculture \u0026amp; Food Waste Biomass. Clean Energy Production Technologies. Springer, Singapore. (2023). (c) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-981-99-0526-3_1\u003c/span\u003e\u003cspan address=\"10.1007/978-981-99-0526-3_1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"waste-and-biomass-valorization","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wave","sideBox":"Learn more about [Waste and Biomass Valorization](http://link.springer.com/journal/12649)","snPcode":"12649","submissionUrl":"https://submission.nature.com/new-submission/12649/3","title":"Waste and Biomass Valorization","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Municipal solid waste, Leachate, E. coli, antibiotic resistance, groundwater contamination","lastPublishedDoi":"10.21203/rs.3.rs-3547316/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3547316/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUrbanization and accelerated industrialization have led to significant waste generation following the accumulation of massive amounts of solid waste in open dump sites. Ground water contamination is one of the critical ecological concerns associated with the percolation of leachate from dump sites. \u003cem\u003eEscherichia coli\u003c/em\u003e is one of the facultative anaerobic bacterial types predominantly colonize the gastrointestinal tract of homoeothermic organisms. \u003cem\u003eE.coli\u003c/em\u003e O157 is a particular virulent serotype which produces intimin and Shiga toxins, that causing for severe diseases including Hemorrhagic Colitis, Hemolytic Uremic Syndrome and thrombotic thrombocytopenic purpura in human. The focus of the present study is to study the virulence potential and antibiotic resistance profiles in \u003cem\u003eE. coli\u003c/em\u003e isolates from selected Karadiyana, Methotamulla and Kerawalapitiya control open dump sites in Sri Lanka. The total coliform count was ranged from 0\u0026ndash;120 MPN/mL around the Kardiyana dump site whereas 0\u0026ndash;75 MPN/mL and 3-115 MPN/mL recorded in the Methotamulla and Kerawalapitiya dump sites. Overall, resistance in isolated \u003cem\u003eE.coli\u003c/em\u003e against AMX, AMP, SUF/ TRI, SDI, CLOX, TET and ERM was high (\u0026gt;\u0026thinsp;70%) compared with the other tested antibiotics namely CIP, GEN and AZY (\u0026lt;\u0026thinsp;40%). According to the results, the Enteropathogenic \u003cem\u003eE. coli\u003c/em\u003e pathotype was identified in 17 samples, whereas the Enterohaemorrhagic \u003cem\u003eE. coli\u003c/em\u003e pathotype was found in only 3 samples. Thus, the current study was conducted to investigate control open dump sites as potential environmental reservoirs of antibiotic-resistant pathogenic \u003cem\u003eE. coli\u003c/em\u003e as these organisms could represent a potential health threat through the contamination of groundwater.\u003c/p\u003e","manuscriptTitle":"Assessment of Virulence Potential and Antibiotic Resistance Profiles in E. coli Isolates from Selected Control Open Dump Sites in Sri Lanka","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-11-28 17:04:33","doi":"10.21203/rs.3.rs-3547316/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-01-06T10:27:17+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-11-22T19:21:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-11-02T01:46:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Waste and Biomass Valorization","date":"2023-11-01T14:22:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"waste-and-biomass-valorization","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wave","sideBox":"Learn more about [Waste and Biomass Valorization](http://link.springer.com/journal/12649)","snPcode":"12649","submissionUrl":"https://submission.nature.com/new-submission/12649/3","title":"Waste and Biomass Valorization","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6095a0a5-0625-4249-9396-d3956e802898","owner":[],"postedDate":"November 28th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-14T21:26:44+00:00","versionOfRecord":{"articleIdentity":"rs-3547316","link":"https://doi.org/10.1007/s12649-024-02544-x","journal":{"identity":"waste-and-biomass-valorization","isVorOnly":false,"title":"Waste and Biomass Valorization"},"publishedOn":"2024-05-06 21:17:44","publishedOnDateReadable":"May 6th, 2024"},"versionCreatedAt":"2023-11-28 17:04:33","video":"","vorDoi":"10.1007/s12649-024-02544-x","vorDoiUrl":"https://doi.org/10.1007/s12649-024-02544-x","workflowStages":[]},"version":"v1","identity":"rs-3547316","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3547316","identity":"rs-3547316","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}