Abstract
Portable clean water consumption is the basic right of every individual. The major global concern is water pollution which can cause mortality. Change in physicochemical characteristics in drinking water is not only a pollution problem, but the presence of antibiotic-resistant microbes is also a significant issue. The study was carried out to assess the physicochemical and microbiological quality of the reservoir, municipality-supplied water, and bottled water. A total of 100 samples were collected from different income classes (higher, medium, and low) groups. The experiments were carried out based on the guidelines of APHA. In the present study, 40% of samples have been found to be contaminated with bacteria such as Escherichia coli, Vibrio cholerae, and Enterobacter aerogenes. Moreover, these bacteria also showed antibiotic resistance to certain drugs. The percentage of isolated bacterial strains was resistant to amoxicillin and ampicillin antibiotics. The statistical analysis of the Chi-square test states that there is a significant correlation between E. coli and other microbes (p ≤ 0.5). This study gives a piece of baseline information about the prevalence of antibiotic-resistant bacteria and focuses on the improvement of water from purification before reaching the consumer.
HIGHLIGHTS
Identification of resistance bacteria in drinking water.
Differentiation in income groups, their access to drinking water and the persistence of microbes.
Identification of resistance microbes was analyzed for the first time in the study area.
Graphical Abstract
INTRODUCTION
Water, often referred to as The Blue Gold, has become a limited resource for human consumption. It is the core of a healthy ecosystem, sustainable and social-economic development, and is even momentous for human survival (US EPA 2012). Access to good drinking water, which is free from microbes and other substances, is the primary right of an individual. The rapid increase in the human population leads to the enhancement of industries and agriculture to meet the needs of the increased population, thereby leading to a rise in pollution (Manjare et al. 2010). The presence of undesirable substances and microbes can cause several diseases. Public health concern is increasing in most developing countries due to enhancing pollution levels in portable water (Okeke et al. 2011). Moreover, the water quality changes from place to place, depending on the anthropogenic activities taking place in that area. For instance, an area close to the dumping site might get contaminated well or tube water (Nrior et al. 2020).
An underground pipeline connection of drinking water also gets contaminated if any rupture occurs to that pipeline connection. In most developed nations, water-related diseases were almost negligible but in developing countries there is still a prevalence of water-borne infections, as many diseases were unreported, not diagnosed, and many of them are unknown (WHO 2011). The major concern and challenging aspect of the 21st century is to provide safe drinking water and proper sanitation to all groups of people (Gautam 2020). Improved water supply and disinfection and better administration of water assets can help nations’ financial development and contribute significantly to meeting demand. Water, being the driving force of nature, must be in adequate supply for human beings, irrespective of their economic group.
The result of the present study focuses on highlighting the importance of water and its quality. It throws a dim light on municipal supply water; bottled water suppliers, and some of the authoritative bodies like the FDA (Food and Drug Administration). This study helps to take necessary measures for the municipal water suppliers and bottled water suppliers to improve their quality to decrease mortality. The aim of the study is to assess the physicochemical and microbiological properties of municipality-supplied water and bottled water in Vizianagaram district and comparing with WHO guidelines.
METHODOLOGY
Study area
Vizianagaram, a north coastal district of Andhra Pradesh with coordinates at 18.106659 N, 83.395554 E, has been chosen to study and analyze drinking water quality. The study has been carried out by categorizing the residential areas as High-, Middle-, and Low-income housing. The municipality has its water supply source from Tatipudi Reservoir. This dam is across the river Gosthani, with a catchment area of 332.72 km2 and a total capacity of 3.32 tmcft. The drinking water is supplied throughout the town by the municipal corporation. Most of the middle- and high-income areas have an individual water connection for municipal water supply. In contrast, low-income neighborhoods have a pooled connection for every four to six houses.
Collection of samples
(a) The selected study area, (b) different income groups as 1,2,3 [low-income group water consumption], 4,5,6 [middle-income group water consumption], 7,8,9 [high-income group water consumption], 10 [reservoir-direct source].
(a) The selected study area, (b) different income groups as 1,2,3 [low-income group water consumption], 4,5,6 [middle-income group water consumption], 7,8,9 [high-income group water consumption], 10 [reservoir-direct source].
Physicochemical and biological analysis
Bacteriological analysis for the water samples was determined using the selective medium streak plating technique. The species Vibrio cholerae and other enteropathogenic Vibrio's was isolated from Thiosulfate-citrate-bile salts-sucrose (TCBS) agar medium (Lotz et al. 1983). Salmonella Shigella (S.S.) agar, a reasonably particular and differential vehicle, was used to develop and separate Salmonella spp, as well as a few strains of Shigella spp. The presence of bile salts, sodium citrate, and brilliant green serves to repress the development of gram-positive and coliform microorganisms while permitting Salmonella spp. Xylose lysine deoxycholate (X.L.D.) agar is both a particular and differential medium (Rollender et al. 1968). Xylose can be matured by basically all enteric aside from the Shigella. Mannitol salt agar (M.S.A.) was used as a selective and differential medium to isolate and identify Staphylococcus aureus. Eosin methylene blue agar (E.M.B. agar) was utilized for isolating fecal coliforms (Lal & Cheeptham 2007). To understand distinct colonies, streak plating techniques were used to isolate the desired organism in the selective media after incubating at 37 °C for 24 h (Katz 2008). The growth of colonies was observed and identified through Gram's staining technique to differentiate between Gram-positive and Gram-negative bacteria. The identified colonies were made into pure cultures and stored in glycerol for further analysis. Moreover, biochemical tests of isolated species were carried out (Talaiekhozani 2013) to confirm the identified species.
Antibiograms assays
For antibiotic testing, isolates were tested with an antibiotic susceptibility test as per Clinical and Laboratory Standards Institute guideline 2016. M.I.C. testing was done for the samples to procure antibiograms. The antibiotics used during testing were Imipenem, Procaine Penicillin, Ciprofloxacin, Amoxicillin, and Ampicillin. The antibiotic susceptibility test was conducted on five isolated species extracted from the drinking water sample which might cause gastrointestinal infections, namely, E. coli, Enterobacter aerogenes, V. cholerae, Salmonella sp, Streptococcus sp.
Data analysis
The analysis of data was carried out using ANOVA to define the relation between physicochemical analysis and the existence of bacteria in the water samples. Statistical package for social sciences (SPSS) version 19 was used to understand the correlation between different isolated bacterial strains.
RESULTS
To analyze the presence of antibiotic-susceptible microbes in drinking water, different water samples were collected from the Vizianagaram region according to income status as well as from the point of origin. A total of 100 samples were collected from different income groups and then collected samples were sent to the laboratory to test physicochemical and biological parameters along with an antibiotic susceptibility test.
Physicochemical analysis
pH
The expression of hydrogen ion concentration was 7.33 ± 0.31–7.53 ± 0.25 for the high-income group, while that of the middle-income region was in the range of 7.43 ± 0.14–7.53 ± 0.15 and that of the low-income group to be 7.28 ± 0.07–7.41 ± 0.185, respectively. The pH levels in the reservoir were found to be 7.48 ± 0.28. These results indicated that the water consumed by different income groups was reasonably neutral.
Turbidity
The relative clarity of the water was observed to be 1.73 ± 0.15–1.86 ± 0.15 NTU in the high-income group, while that of the middle-income group was 1.49 ± 0.26–1.58 ± 0.26 NTU, and that of the low-income region was 2.33 ± 0.11–2.51 ± 0.10 NTU. The opacity in the reservoir is 2 ± 0.1 NTU. The proportion of relative clearness of water was marginally more prominent in the middle-income group. It can be inferred that the samples were in the prescribed range of I.S.I. Turbidity can be reverberated by rain – erosion and the biotic life present in the water source.
Total dissolved solids
The concentration of dissolved minerals was found to be 161.8 ± 10.9–174.16 ± 6.78 mg/l in the high-income region and 129.3 ± 12.3–165.3 ± 10.05 mg/l in the middle economic group and that of 199.9 ± 23.7–238.73 ± 7.77 mg/l in the low-income category, and 107.76 ± 72.50 mg/l in the reservoir. In contrast, the acceptable range of T.D.S. is 500 mg/l. The reason for the presence of total dissolved solids includes minerals, sediments, microbes, etc. It can be inferred that the samples fall under the category of excellent as per the WHO.
Chlorides
Spatial variation of selected parameters in different income groups.
Sodium
The sodium compounds are water dissolvable and will, in general, stay in the fluid arrangement. The admissible furthest reaches of sodium in drinking water as endorsed by BIS is 50 mg/l. It was observed that the high-income sample had much lower levels of sodium, i.e., 6.2 ± 0.7–7.3 ± 0.95 mg/l, in comparison with middle- and low-income samples, which were observed to be 22.6 ± 2.06–29.66 ± 1.36 mg/l and 22.9 ± 0.36–24.36 ± 2.24 mg/l, respectively. The sodium concentrations were observed to be 23.53 ± 3.05 mg/l in the reservoir (Table 1). The story of sodium can fluctuate concerning the underground salt deposits. Different elements impacting sodium levels in water incorporate farming run-off, sewage, and mechanical effluents, sodium compounds in erosion control, and water treatment synthetics like sodium fluoride, sodium bicarbonate, and sodium hypochlorite.
Physicochemical analysis of water samples collected from different income groups
Area of sampling . | pH . | Turbidity (NTU) . | TDS (mg/l) . | Chlorides (mg/l) . | Sodium (mg/l) . | Ammonium (mg/l) . | Potassium (mg/l) . | |
---|---|---|---|---|---|---|---|---|
Low-income groups | 1 | 7.28 ± 0.07 | 2.33 ± 0.11 | 238.73 ± 7.77 | 8.83 ± 0.35 | 22.9 ± 0.36 | 0.84 ± 0.60 | 0.85 ± 0.06 |
2 | 7.41 ± 0.185 | 2.51 ± 0.10 | 217.5 ± 17.3 | 10.36 ± 0.66 | 23.6 ± 1.08 | 0.94 ± 0.60 | 0.87 ± 0.14 | |
3 | 7.3 ± 0.26 | 2.45 ± 0.14 | 199.9 ± 23.7 | 8.33 ± 0.75 | 24.36 ± 2.24 | 0.87 ± 0.10 | 0.87 ± 0.11 | |
Middle-income groups | 4 | 7.43 ± 0.14 | 1.58 ± 0.26 | 136.6 ± 7.6 | 4.26 ± 0.90 | 23.56 ± 1.28 | 1.86 ± 0.07 | 1.83 ± 0.09 |
5 | 7.43 ± 0.25 | 1.49 ± 0.26 | 165.3 ± 10.05 | 5.5 ± 1.15 | 29.66 ± 1.36 | 1.55 ± 0.34 | 1.77 ± 0.10 | |
6 | 7.53 ± 0.15 | 1.53 ± 0.20 | 129.3 ± 12.3 | 4.86 ± 1.93 | 22.6 ± 2.06 | 1.80 ± 0.16 | 1.82 ± 0.11 | |
High-income groups | 7 | 7.33 ± 0.31 | 1.73 ± 0.15 | 165.5 ± 15.3 | 1.87 ± 0.09 | 6.86 ± 1.30 | 1.68 ± 0.12 | 2.26 ± 0.15 |
8 | 7.53 ± 0.25 | 1.86 ± 0.15 | 161.8 ± 10.9 | 1.95 ± 0.08 | 7.3 ± 0.95 | 1.72 ± 0.2 | 2.35 ± 0.31 | |
9 | 7.36 ± 0.25 | 1.76 ± 0.66 | 174.16 ± 6.78 | 1.97 ± 0.13 | 6.2 ± 0.7 | 1.64 ± 0.08 | 2.25 ± 0.16 | |
Reservoir | 10 | 7.48 ± 0.28 | 2 ± 0.1 | 107.76 ± 72.50 | 1.79 ± 0.05 | 23.53 ± 3.05 | 2.28 ± 0.37 | 2.28 ± 0.15 |
Area of sampling . | pH . | Turbidity (NTU) . | TDS (mg/l) . | Chlorides (mg/l) . | Sodium (mg/l) . | Ammonium (mg/l) . | Potassium (mg/l) . | |
---|---|---|---|---|---|---|---|---|
Low-income groups | 1 | 7.28 ± 0.07 | 2.33 ± 0.11 | 238.73 ± 7.77 | 8.83 ± 0.35 | 22.9 ± 0.36 | 0.84 ± 0.60 | 0.85 ± 0.06 |
2 | 7.41 ± 0.185 | 2.51 ± 0.10 | 217.5 ± 17.3 | 10.36 ± 0.66 | 23.6 ± 1.08 | 0.94 ± 0.60 | 0.87 ± 0.14 | |
3 | 7.3 ± 0.26 | 2.45 ± 0.14 | 199.9 ± 23.7 | 8.33 ± 0.75 | 24.36 ± 2.24 | 0.87 ± 0.10 | 0.87 ± 0.11 | |
Middle-income groups | 4 | 7.43 ± 0.14 | 1.58 ± 0.26 | 136.6 ± 7.6 | 4.26 ± 0.90 | 23.56 ± 1.28 | 1.86 ± 0.07 | 1.83 ± 0.09 |
5 | 7.43 ± 0.25 | 1.49 ± 0.26 | 165.3 ± 10.05 | 5.5 ± 1.15 | 29.66 ± 1.36 | 1.55 ± 0.34 | 1.77 ± 0.10 | |
6 | 7.53 ± 0.15 | 1.53 ± 0.20 | 129.3 ± 12.3 | 4.86 ± 1.93 | 22.6 ± 2.06 | 1.80 ± 0.16 | 1.82 ± 0.11 | |
High-income groups | 7 | 7.33 ± 0.31 | 1.73 ± 0.15 | 165.5 ± 15.3 | 1.87 ± 0.09 | 6.86 ± 1.30 | 1.68 ± 0.12 | 2.26 ± 0.15 |
8 | 7.53 ± 0.25 | 1.86 ± 0.15 | 161.8 ± 10.9 | 1.95 ± 0.08 | 7.3 ± 0.95 | 1.72 ± 0.2 | 2.35 ± 0.31 | |
9 | 7.36 ± 0.25 | 1.76 ± 0.66 | 174.16 ± 6.78 | 1.97 ± 0.13 | 6.2 ± 0.7 | 1.64 ± 0.08 | 2.25 ± 0.16 | |
Reservoir | 10 | 7.48 ± 0.28 | 2 ± 0.1 | 107.76 ± 72.50 | 1.79 ± 0.05 | 23.53 ± 3.05 | 2.28 ± 0.37 | 2.28 ± 0.15 |
Ammonium
The ammonium concentration in the samples was 1.64 ± 0.08–1.72 ± 0.2 mg/l in high-income and 1.55 ± 0.34–1.80 ± 0.16 mg/l in middle-income samples, 0.84 ± 0.60–0.94 ± 0.60 mg/l in low-income regions, whereas the source point had 2.28 ± 0.37 mg/l as its ammonium concentration. Ammonium in the climate begins from metabolic, horticultural, and modern measures and sanitization with chloramine. Ammonium in water is a pointer of conceivable bacterial, sewage, and creature squander contamination.
Potassium
The potassium concentration was identified to be 2.25 ± 0.16–2.35 ± 0.31 mg/l in the high-income sample and 1.77 ± 0.10–1.83 ± 0.09 mg/l in middle-income and 0.85 ± 0.06–0.87 ± 0.14 mg/l in the low-income category sample, while the source point had its concentration as 2.28 ± 0.15.
Biological analysis
The drinking water samples when tested for the presence of enteric pathogens by streaking on E.M.B. agar, X.L.D. agar, TCBS agar, SS agar, and Mannitol agar observed a high number of Escherichia coli colonies, with a metallic green sheen, growing on E.M.B. agar plates with samples from all the income levels. SS agar plates also showed that there might be a high prevalence of Shigella and Salmonella across the various groups. TCBS agar plates were observed to show the growth of green and yellow colonies. There might be a prevalence of V. cholerae and Vibrio parahaemolyticus in all areas. There was a significant Pearson's correlation (P < 0.05) noticed in the connection between microbes and the volume of the sampling bottle. A significant Pearson's correlation indicates that there is a significant positive correlation between E. coli and E. aerogenes (r = 1.00) and E. coli and Salmonella sp (0.425), E. coli and Streptococcus sp (0.685), whereas a significant negative association was noticed with E. coli and V. cholerae (−0.765) and E. aerogenes and V. cholerae (−0.765) which is tabulated in Table 2. Most of the bacterial strains were isolated from lower-income groups compared to middle-income and higher-income groups. But a few species like E. coli and E. aerogenes were also identified in study areas 5 and 8 which comes under middle-income and higher-income groups. The isolated strains were tested for antibiotic susceptibility for each organism.
Correlation between isolated bacteria
Bacteria . | Escherichia coli . | Enterobacter aerogenes . | Vibrio cholerae . | Salmonella sp . | Streptococcus sp . |
---|---|---|---|---|---|
Escherichia coli | 1 | 1.00* | −0.765* | 0.425* | 0.685* |
Enterobacter aerogenes | 1 | −0.765** | 0.435* | 0.686* | |
Vibrio cholerae | 1 | 0.425* | 0.685* | ||
Salmonella sp | 1 | 0.686** | |||
Streptococcus sp | 1 |
Bacteria . | Escherichia coli . | Enterobacter aerogenes . | Vibrio cholerae . | Salmonella sp . | Streptococcus sp . |
---|---|---|---|---|---|
Escherichia coli | 1 | 1.00* | −0.765* | 0.425* | 0.685* |
Enterobacter aerogenes | 1 | −0.765** | 0.435* | 0.686* | |
Vibrio cholerae | 1 | 0.425* | 0.685* | ||
Salmonella sp | 1 | 0.686** | |||
Streptococcus sp | 1 |
*Significant correlation at 0.05 level.
**Significant correlation at 0.01 level.
In the present study, the variation of bacterial strains in different income groups was clearly noticed. In low-income groups, almost all sites have shown bacterial strains with a range of 1.85 × 105–8.05 × 104, with which the highest registered was E. coli isolates followed by E. aerogenes (Table 3). The presence of V. cholerae has also registered in the range of 7.99 × 104–1.77 × 105 in the low-income group sampling area, whereas 9.77 × 102 was only found in sampling area 5 of the middle-income groups. A few isolates of Salmonella species have been identified in a few sampling sites of all three income groups of the study area. Similarly, the positive strains of Streptococcus species were found in two areas of low-income groups, one area each from middle-income and high-income groups.
Comparison of different isolates of microbes in different income groups
Area of sampling . | Escherichia coli (CFU/ml) . | Enterobacter aerogenes (CFU/ml) . | Vibrio cholerae (CFU/ml) . | Salmonella sp (CFU/ml) . | Streptococcus sp (CFU/ml) . | |
---|---|---|---|---|---|---|
Low-income groups | 1 | 4.45 × 107 | 2.66 × 107 | 1.77 × 105 | 2.23 × 104 | 2.26 × 105 |
2 | 3.86 × 106 | 3.79 × 106 | 7.99 × 104 | – | 3.20 × 105 | |
3 | 2.36 × 106 | 5.55 × 105 | 8.05 × 104 | 1.85 × 105 | – | |
Middle-income groups | 4 | – | – | – | 1.10 × 102 | – |
5 | 2.76 × 104 | 1.66 × 103 | 9.77 × 102 | – | 1.16 × 104 | |
6 | – | – | – | – | – | |
High-income groups | 7 | 1.15 × 103 | – | – | – | 1.05 × 103 |
8 | 2.32 × 102 | 2.44 × 102 | – | 1.10 × 102 | – | |
9 | – | – | – | – | ||
Reservoir | 10 | 1.15 × 103 | – | – | – | – |
Area of sampling . | Escherichia coli (CFU/ml) . | Enterobacter aerogenes (CFU/ml) . | Vibrio cholerae (CFU/ml) . | Salmonella sp (CFU/ml) . | Streptococcus sp (CFU/ml) . | |
---|---|---|---|---|---|---|
Low-income groups | 1 | 4.45 × 107 | 2.66 × 107 | 1.77 × 105 | 2.23 × 104 | 2.26 × 105 |
2 | 3.86 × 106 | 3.79 × 106 | 7.99 × 104 | – | 3.20 × 105 | |
3 | 2.36 × 106 | 5.55 × 105 | 8.05 × 104 | 1.85 × 105 | – | |
Middle-income groups | 4 | – | – | – | 1.10 × 102 | – |
5 | 2.76 × 104 | 1.66 × 103 | 9.77 × 102 | – | 1.16 × 104 | |
6 | – | – | – | – | – | |
High-income groups | 7 | 1.15 × 103 | – | – | – | 1.05 × 103 |
8 | 2.32 × 102 | 2.44 × 102 | – | 1.10 × 102 | – | |
9 | – | – | – | – | ||
Reservoir | 10 | 1.15 × 103 | – | – | – | – |
Antibiogram analysis of E. coli
E. coli colonies extracted from the samples could be showing antibiotic resistance. Antimicrobial resistance in E. coli could be considered a significant challenge to public health. The isolates were susceptible to Imipenem (75%), Procaine Penicillin (57.39%), Ciprofloxacin (44.9%), but had high resistance towards Amoxicillin (83.3%) and Ampicillin (100%) tabulated in Table 4.
Susceptibility profile of antibiotics of E. coli isolated from drinking water samples
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Imipenem | 120 | 90 (75%) | 20 (16.6%) | 10 (8.3%) |
Procaine Penicillin | 115 | 66 (57.39%) | 34 (29.56%) | 15 (13.04%) |
Ciprofloxacin | 118 | 53 (44.91%) | 42 (35.59%) | 23 (19.49%) |
Amoxicillin | 120 | 5 (4.1%) | 15 (12.5%) | 100 (83.3%) |
Ampicillin | 120 | – | – | 120 (100%) |
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Imipenem | 120 | 90 (75%) | 20 (16.6%) | 10 (8.3%) |
Procaine Penicillin | 115 | 66 (57.39%) | 34 (29.56%) | 15 (13.04%) |
Ciprofloxacin | 118 | 53 (44.91%) | 42 (35.59%) | 23 (19.49%) |
Amoxicillin | 120 | 5 (4.1%) | 15 (12.5%) | 100 (83.3%) |
Ampicillin | 120 | – | – | 120 (100%) |
Antibiogram analysis of E. aerogenes
In the present study, E. aerogenes isolated were tested for antibiotic susceptibility. It was identified that the isolates are susceptible to Imipenem (70.83%), Procaine Penicillin (56.52%), and Ciprofloxacin (41.52%), but high resistance towards Amoxicillin (83.3%) and Ampicillin (100%) tabulated in Table 5. These isolates were observed in three income class groups.
Susceptibility profile of antibiotics of Enterobacter aerogenes isolated from water samples
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Imipenem | 120 | 85 (70.83%) | 25 (20.83%) | 10 (8.3%) |
Procaine Penicillin | 115 | 65 (56.52%) | 38 (33.04%) | 12 (10.43%) |
Ciprofloxacin | 118 | 49 (41.52%) | 40 (33.89%) | 29 (24.57%) |
Amoxicillin | 120 | 5 (4.1%) | 15 (12.5%) | 100 (83.3%) |
Ampicillin | 120 | – | – | 120 (100%) |
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Imipenem | 120 | 85 (70.83%) | 25 (20.83%) | 10 (8.3%) |
Procaine Penicillin | 115 | 65 (56.52%) | 38 (33.04%) | 12 (10.43%) |
Ciprofloxacin | 118 | 49 (41.52%) | 40 (33.89%) | 29 (24.57%) |
Amoxicillin | 120 | 5 (4.1%) | 15 (12.5%) | 100 (83.3%) |
Ampicillin | 120 | – | – | 120 (100%) |
Antibiogram analysis of V. cholerae
V. cholerae isolates were tested for antibiotic susceptibility in which these isolates were susceptible to Amoxicillin (47.5%), and resistance to Ampicillin (58.26%), Erythromycin (80.50%), Trimethoprim (90.8%), and Tetracycline (70.83%). The isolates were identified from Table 6 in the low-income group of categories that might be due to poor sanitation facilities.
Susceptibility profile of antibiotics of Vibrio cholerae isolated from water samples
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Amoxicillin | 120 | 57 (47.5%) | 35 (29.16%) | 28 (23.33%) |
Ampicillin | 115 | 12 (10.43%) | 36 (31.30%) | 67 (58.26%) |
Erythromycin | 118 | 1 (0.84%) | 22 (18.64%) | 95 (80.50%) |
Trimethoprim | 120 | 2 (1.66%) | 9 (7.5%) | 109 (90.8%) |
Tetracycline | 120 | 10 (8.33%) | 25 (20.83%) | 85 (70.83%) |
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Amoxicillin | 120 | 57 (47.5%) | 35 (29.16%) | 28 (23.33%) |
Ampicillin | 115 | 12 (10.43%) | 36 (31.30%) | 67 (58.26%) |
Erythromycin | 118 | 1 (0.84%) | 22 (18.64%) | 95 (80.50%) |
Trimethoprim | 120 | 2 (1.66%) | 9 (7.5%) | 109 (90.8%) |
Tetracycline | 120 | 10 (8.33%) | 25 (20.83%) | 85 (70.83%) |
Antibiogram analysis of Salmonella species
Isolates of Salmonella species were susceptible to Amoxicillin (47.5%), Cefotaxime (74.5%), Gentamicin (77.5%), and resistance to Ampicillin (58.26%) and Tetracycline (76.27%) tabulated in Table 7. The percentage of these species was low in all the collected samples.
Susceptibility profile of antibiotics of Salmonella species isolated from water samples
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Amoxicillin | 120 | 57 (47.5%) | 35 (29.16%) | 28 (23.33%) |
Ampicillin | 115 | 12 (10.43%) | 36 (31.30%) | 67 (58.26%) |
Cefotaxime | 118 | 88 (74.57%) | 19 (16.10%) | 11 (9.32%) |
Gentamicin | 120 | 93 (77.5%) | 12 (10%) | 15 (12.5%) |
Tetracycline | 118 | 8 (6.77%) | 20 (16.94%) | 90 (76.27%) |
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Amoxicillin | 120 | 57 (47.5%) | 35 (29.16%) | 28 (23.33%) |
Ampicillin | 115 | 12 (10.43%) | 36 (31.30%) | 67 (58.26%) |
Cefotaxime | 118 | 88 (74.57%) | 19 (16.10%) | 11 (9.32%) |
Gentamicin | 120 | 93 (77.5%) | 12 (10%) | 15 (12.5%) |
Tetracycline | 118 | 8 (6.77%) | 20 (16.94%) | 90 (76.27%) |
Antibiogram analysis of Streptococcus species
Most of the Streptococcus species are susceptible to Amoxicillin (56.52%), Cefotaxime (60.83%), Erythromycin (55.08%), Tetracycline (49.56%), and resistant to Ampicillin (69.56%). Antibiotic susceptibility of Streptococcus species is tabulated in Table 8.
Susceptibility profile of antibiotics of Streptococcus species isolated from water samples
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Amoxicillin | 118 | 65 (56.52%) | 38 (33.04%) | 15 (12.71%) |
Ampicillin | 115 | 10 (8.33%) | 25 (20.83%) | 80 (69.56%) |
Cefotaxime | 120 | 73 (60.83%) | 28 (23.33%) | 19 (15.83%) |
Erythromycin | 118 | 65 (55.08%) | 31 (26.27%) | 22 (18.64%) |
Tetracycline | 115 | 57 (49.56%) | 32 (27.82%) | 26 (22.60%) |
Name of the antibiotics . | Number of tested isolates . | Sensitive . | Intermediate . | Resistance . |
---|---|---|---|---|
Amoxicillin | 118 | 65 (56.52%) | 38 (33.04%) | 15 (12.71%) |
Ampicillin | 115 | 10 (8.33%) | 25 (20.83%) | 80 (69.56%) |
Cefotaxime | 120 | 73 (60.83%) | 28 (23.33%) | 19 (15.83%) |
Erythromycin | 118 | 65 (55.08%) | 31 (26.27%) | 22 (18.64%) |
Tetracycline | 115 | 57 (49.56%) | 32 (27.82%) | 26 (22.60%) |
DISCUSSION
In this study, the physicochemical parameters of the sampling site were under acceptable levels, but when it was tested for biological parameters, all the sampling sites registered with different Gram-positive and Gram-negative bacteria. The isolated bacteria were tested with antibiotics which showed their resistance, intermediate, and sensitivity. Antibiotic resistance in bacteria is quickly turning into a medical catastrophe. Bacteria are acquiring antibiotic resistance at a rapid rate, partly due to the ease of acquiring or changing genetic material (Bonita et al. 2006).
Dynamic variations in the freshwater from the reservoir and their microbial population upon entry into the supply system were replicated by a growth in the number of antibiotic-resistant bacteria at the user end. It was also observed that the increase in the percentage of antibiotic-resistant E. coli and E. aerogenes at the source point is 4% of raw water to 85–90% of the distribution of drinking water isolates in the low-income groups. The examined entrance apparently indicated water treatment processes and possible added impacts from subsequent distribution of water. The results obtained from the laboratory analysis suggested an alliance of disinfection with selection for antibiotic resistance (Armstrong et al. 1982; Voigt et al. 2020) could be from the material of water pipeline distribution indirectly clarifying the substantial increase of antibiotic-resistant bacteria in the supply networks.
E. coli represents a substantial reservoir of resistance, resulting in treatment failures in both human and veterinary medicine. Resistance genes have been observed to increase E. coli isolates in studies, and many of these resistance genes were acquired by horizontal gene transfer (Poirel et al. 2018). According to IBWA (2012), E. coli should not be identified in drinking water. In the present analysis, it was identified in the water samples of a lower-income class group as well as in the bottled water of higher-income groups which can be considered a serious point. E. coli has shown resistance to Amoxicillin and Ampicillin which were quite commonly used to treat gastrointestinal diseases (Edlund & Nord 2000). As E. coli and E. aerogenes come under coliform bacteria and identifying them in the drinking water at high levels is a risk. In general, coliform organisms are present in the gut of most mammals and humans considered indicator organisms (Gautam et al. 2018). In all the sampling sites, lower-income groups of all regions, sample 5 of the middle-income group, and sample region of 8 in higher-income group and 10 (reservoir) found the presence of coliform bacteria above the standard guidelines can be considered as a risk point (Iwu et al. 2020; Gautam 2021). Further, it was identified that coliforms were reported to form biofilms. A significant correlation was observed between coliform and other species with p ≤ 0.05 (Table 2). The Pearson's correlation between Enterobacter and E. coli (r− 1.00, p < 0.01) could be the presence of more coliforms in the collected sample, might risk public health, and should not be taken lightly.
Out of the collected samples, 23 (23%) have identified the presence of V. cholerae. The results agree with Maje et al. (2020) who have identified 32 samples in which 5 tap samples were found to exceed. The biofilm of Vibrio spp has a specialized design to survive an optimum temperature of 37 °C (Mahapatra et al. 2014). This temperature is suitable for growth in the human intestine, which can cause severe infections. V. parahaemolyticus, V. mimicus, V. vulnificus, and V. cholerae can grow and survive for several days but are unable to grow at higher temperatures. The Pearson's correlation between coliform and V. cholerae (r = −0.765, p < 0.01) indicates that the Vibrio spp cannot easily survive with coliforms. But the strain V. cholerae is resistant to few antibiotics which might result in diarrheal infections. The percentage of different bacterial isolates to antibiotics varied (Figure 4).
Salmonella spp and Streptococcus spp also have Pearson's correlation with E. coli (r = 0.425, p < 0.0,1 r − 0.685, p < 0.01) which can reside in coliforms and might be causing a serious threat to public health. From the study, it was understood that two antibiotics, Amoxicillin and Ampicillin, have been found (Figure 4) to be resistant to all bacterial isolates extracted from drinking water.
Due to the positive correlation between coliform bacteria, Salmonella spp, and Streptococcus spp, there might be the possibility of multidrug-resistant of isolated species. This becomes the main concern in public health due to drug resistant microbes’ presence in the environment. The resistant bacteria in water samples could be a serious issue relating to public health. The presence of these resistant bacterial strains can have a harmful impact on the usage of antibiotics which might create difficulty in reducing and managing disease (Slama et al. 2005; Zhang et al. 2015). In the appropriate treatment of wastewater containing the deposits of antibiotic resistance, bacteria might increase when it finds its route to drinking water, finally transmitted to consumers (Luo et al. 2014; Chen et al. 2015). In the present study, the samples which were collected found antibiotic resistant bacteria. Therefore, it is urgently required to take appropriate measures to improve the quality of water purification tanks.
CONCLUSION
Results from culture method, biochemical tests, and antibiogram tests reveal the presence of antibiotic-resistant bacteria in the drinking water of different income groups.
The isolated bacteria from drinking water have shown resistance to selected antibiotics which ranged from 8 to 100% resistance.
All identified bacterial strains from drinking water have shown resistance to Ampicillin antibiotics.
As the traces of V. cholerae, E. coli, and Coliform bacteria that were found in the present study drinking water need to be further treated prior to consumption to avoid the health implications that can be caused due to contamination of water.
The result of the examination can help foster water quality mindfulness culture and practice in the present and future generations. So, this investigation will support many water quality examiners, such as scientists, environmentalists, and is exceptionally valuable to the Public Health office and Municipal authorities, to improve general wellbeing in epidemiological issues.
ACKNOWLEDGEMENTS
The authors are thanking GITAM (Deemed to be University) for the laboratory support given to do the analysis.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.