Abstract
Excessive anthropogenic activities play a significant role in the emergence and dissemination of antibiotic resistance in urban streams and river sediment. The objectives of the present study were to investigate the antibiotic susceptibility profile, molecular detection of antibiotic resistance genes (ARGs), and identification of multidrug-resistant bacterial isolates in the mainstream and tributaries of the Ghaghara River. The obtained data indicated that the majority of the isolates were identified as Bacillus spp. (40%) followed by Klebsiella quasipneumoniae (20%), Exiguobacterium undae (13.33%). Most of the bacterial isolates were resistant against penicillin G (P) (24%), cefuroxime (CXM) (20%), amoxicillin (AMX) (18%), and ampicillin (AMP) (17%) in sediments samples, whereas penicillin G (27%), cefuroxime (CXM) and erythromycin (E) was 13%, AMP and cefaclor both showed 12% in water samples respectively. This study provides insight into the prevalence of multiple antibiotic-resistant bacterial diversity in the Ghaghara River and provides the route to disseminate the multidrug-resistant pathogens in the human and animal population through the aquatic environment.
HIGHLIGHTS
16S rRNA analysis for bacterial identification and microbial study.
MDR bacterial community in water and sediment of Ghaghara River.
Bacillus species bacteria are dominant in multidrug resistance nature.
Penicillin and cefuroxime antibiotics showing resistance against most of bacteria.
ARGs like blaKPC, blaNDM, and aminoglycoside (ant3″) are dominant in all water and sediment samples.
Graphical Abstract
INTRODUCTION
Pollution aroused from antibiotics is one of the major concerns associated with severe problems in the modern era of the anxious environment (Tripathi & Tripathi 2017). After the clinical approval of penicillin to be used for human welfare, various antibiotics have been invented, and their applications are widely used for the treatment of various diseases in humans and animals (Ben et al. 2019). Due to the unregulated use of antibiotics in India, antibiotic consumption has increased approximately double in 15 years viz. from 3.2 billion defined daily doses (DDDs) in 2000 to 6.5 billion DDDs in 2015. According to a statistical record about 76 countries of the world from the year 2000 to 2015, antibiotic consumption in humans had increased by approximately 65%, which created severe problems for sustainable nature and the aquatic environment (Klein et al. 2018). Some of the antibiotics are not entirely metabolized within the body and are released to the sewage system in the form of urine and excreta. The non-metabolized antibiotics are discharged into the downstream river environments causing surface water contamination (Ramírez-Castillo et al. 2013; Kim et al. 2016; Barancheshme & Munir 2018) and are deposited in river sediments (Marathe et al. 2017) through the sewage channels (Gao et al. 2012; Xu et al. 2015; Adbarzi et al. 2020; Chen et al. 2020), landfill leachates (Anand et al. 2021), farmyard manure (Zalewska et al. 2021) as well as industrial and agricultural wastewater (Gatica et al. 2016). The excess concentration of antibiotics provides a favourable condition for development and is considered as the most significant driver of antibiotic resistance (Samreen et al. 2021). Previous literature has reported that the urban stretches of rivers are disposed to receive contaminants from numerous pollution sources viz. industrial, chemical, clinical, agricultural, household, and treated or untreated wastewater from wastewater treatment plants (WWTPs) (Bengtsson-Palme et al. 2019; Ram & Kumar 2020; Hubeny et al. 2021). WWTPs are the machinery setup considered to reduce the bacterial and antibiotic resistance genes (ARGs) load from wastewater but, due to the technical limitations, some parts of the antibiotics, antibiotic-resistant bacteria (ARB), and ARGs are leftover in effluent water and released into the downstream receiving water bodies (Alexander et al. 2020; Su et al. 2020; Mahaney & Franklin 2022). The most abundant ARG subtypes, previously reported in the surface water system, majorly covered eight antibiotic families that are β-lactam (bla), sulfonamide (sul), tetracycline (tet), aminoglycoside (aad), multidrug (mec), amphenicol (flo), trimethoprim (dfr), and glycopeptide (van) (Kock et al. 2018; Su et al. 2020). Urban rivers are very prone and act as reservoirs of ARB and ARGs (Jia et al. 2018; Sabri et al. 2020). There is serious attention on the regulation of antibiotics by many international agencies about the contamination of surface water with antibiotics along with ARB causing serious pathogenic diseases worldwide (WHO 2018).
The Ghaghara River is the largest tributary of the Ganga River in terms of annual flow contribution. The mainstream of Ghaghara River connects with the Ganga River near the Doriganj area in Chhapara district of Bihar state, after a journey of about 1,080 km (Ravi et al. 2021). The Ghaghara plains lie beneath the thick loose muddy sediments deposited by the Ghaghara River and its tributaries. The Ghaghara sub-basin comprises Pleistocene older alluvial deposit (Varanasi older alluvium and T2 terrace surface) and Holocene newer alluvial deposit (Bangar and Khadar). The older alluvium is characterized by different lithologies such as kankar, gravel, sand, silt, and clay (Singh et al. 2005). There are five densely populated towns between 1 and 10 lakhs in the Ghaghara basin of the Indian region, viz. Bahraich, Basti, Faizabad, Gonda, and Lakhimpur Kheri. As per census 2011, the basin shelters the total population of 25,864,960, amongst which 2,083,813 (8.06%) is urban and 23,781,147 (91.94%) belongs to the rural population. However, the wastewater generated by the rural and urban population residing in the 570 km stretch of present study area is treated by approximately nine WWTPs located near the banks the of Ghaghara River (Jain et al. 2007). Ultimately after the treatment process, the treated wastewater is discharged into the Ghaghara River, which serves as a point source of downstream contamination. Also, some open drainage and sewage are discharged into the river which are non-point source of contamination.
This study aims to evaluate the resistance pattern of 208 isolates from Ghaghara River water and alluvial sediment from the upper, middle, and lower stretch of Ghaghara River against the antibiotics of different classes. Also, the isolates were screened for the genes encoding for ß-lactams (blaKPC, blaNDM, blaTEM), tetracycline (tetM), quinolone (qnrS), aminoglycosides (ant2″, ant3″), chloramphenicol (cmlA) and sulphonamides (sul3) resistance. Furthermore, the bacterial DNA was used to identify particular bacteria by Sanger sequencing. The comprehensive study at the microbial level and antibiotic resistance profile have not been previously analysed and reported; Therefore, this study holds high significance to explore the microbial and antibiotic resistance load in the Ghaghara River.
MATERIALS AND METHODS
Study area and sample collection
Sampling stations detail including latitude and longitude and district administration information
Stream flow . | Code . | Sampling station . | River . | Administration . | Latitude . | Longitude . |
---|---|---|---|---|---|---|
Upper stream | S1 | Kartania-ghat | Geruwa | Bahraich | 28.20 | 81.07 |
S2 | Girijapuri barrage | Geruwa + Kauriala | Bahraich | 28.16 | 81.05 | |
S3 | Sitapur | Sharda river | Bahraich | 27.69 | 81.49 | |
S4 | Chahlari bridge | Ghaghara + Sharda | Bahraich | 27.54 | 81.34 | |
Middle stream | S5 | Jarwal road | Ghaghara | Bahraich | 27.05 | 81.29 |
S6 | Ayodhya ghat | Saryu | Ayodhya | 26.61 | 82.21 | |
S7 | Pausara ghat | Ghaghara | Ayodhya | 26.64 | 82.41 | |
S8 | Hanuman garhi, Tanda | Ghaghara | Ambedkar Nagar | 26.56 | 82.66 | |
S9 | Dhanghata, SKN | Ghaghara | Sant Kabir Nagar | 26.49 | 82.98 | |
Lower stream | S10 | Kuwano | Kuwano | Sant Kabir Nagar | 26.6 | 83.02 |
S11 | Rajghat, Gorakhpur | Rapti | Gorakhpur | 26.73 | 83.35 | |
S12 | Jalpa mata mandir, Bhatni, | Chhoti Gandak | Deoria | 26.38 | 83.94 | |
S13 | Manjhi-ghat, Chhapara | Ghaghara | Chhapara | 25.83 | 84.58 | |
S14 | Doriganj, Chhapara | Ghaghara + Ganga | Chhapara | 25.73 | 84.83 |
Stream flow . | Code . | Sampling station . | River . | Administration . | Latitude . | Longitude . |
---|---|---|---|---|---|---|
Upper stream | S1 | Kartania-ghat | Geruwa | Bahraich | 28.20 | 81.07 |
S2 | Girijapuri barrage | Geruwa + Kauriala | Bahraich | 28.16 | 81.05 | |
S3 | Sitapur | Sharda river | Bahraich | 27.69 | 81.49 | |
S4 | Chahlari bridge | Ghaghara + Sharda | Bahraich | 27.54 | 81.34 | |
Middle stream | S5 | Jarwal road | Ghaghara | Bahraich | 27.05 | 81.29 |
S6 | Ayodhya ghat | Saryu | Ayodhya | 26.61 | 82.21 | |
S7 | Pausara ghat | Ghaghara | Ayodhya | 26.64 | 82.41 | |
S8 | Hanuman garhi, Tanda | Ghaghara | Ambedkar Nagar | 26.56 | 82.66 | |
S9 | Dhanghata, SKN | Ghaghara | Sant Kabir Nagar | 26.49 | 82.98 | |
Lower stream | S10 | Kuwano | Kuwano | Sant Kabir Nagar | 26.6 | 83.02 |
S11 | Rajghat, Gorakhpur | Rapti | Gorakhpur | 26.73 | 83.35 | |
S12 | Jalpa mata mandir, Bhatni, | Chhoti Gandak | Deoria | 26.38 | 83.94 | |
S13 | Manjhi-ghat, Chhapara | Ghaghara | Chhapara | 25.83 | 84.58 | |
S14 | Doriganj, Chhapara | Ghaghara + Ganga | Chhapara | 25.73 | 84.83 |
The basic parameters of pH, EC, TDS, DO, BOD, stream velocity and river depth as well as nutrients chemistry of NH4-N, NO3-N, and PO4-P(μg/l) were analysed and have been reported in our previous study Ravi et al. (2021).
Isolation and purification of bacterial isolates
Isolation and purification of bacterial isolates from river water and sediments were done using the serial dilution agar plate method (Aneja 2018). A total amount of 100 ml water sample was serially diluted (1:10) with 0.85% normal saline and spread on Luria Bertani (LB) Agar medium and incubated at 37 °C overnight. The well grown and distinct morphological bacterial colonies were selected from each plate for further antibiotic disc diffusion analysis.
Antibiotics susceptibility test
In the present study, the Kirby-Bauer test was applied in which discs of antibiotics with standard concentrations are diffused onto the surface of Mueller Hinton Agar (MHA) plates containing the dense lawn of individual bacterial strain and placed in the incubator for 24 h at 37 °C. The following antibiotics discs (Himedia) and disc potencies were used ampicillin (AMP) (25MCG), azithromycin (AZM) (30MCG), cefaclor (CF) (30MCG), ciprofloxacin (CIP) (25MCG), cefadroxil (CFR) (30MCG), erythromycin (E) (15MCG), cefotaxime (CTX) (5MCG), cefuroxime (CXM) (30MCG), penicillin G (P) (2MCG) and amoxicillin (AMX) (30MCG). The inhibition zone diameter was measured after the plates were cultured for 16–18 h at 37 °C.
Isolation of DNA, 16S rRNA amplification, and DNA sequencing
The 15 bacterial isolates were selected for the DNA isolation based on multidrug resistance against more than five antibiotics. A total of 1.5 ml of overnight grown bacterial culture was used for DNA isolation based on the phenol/chloroform method (He F 2011). The bacterial 16S rRNA gene from all isolated DNA samples was amplified using a conventional PCR system in a BioRad thermocycler with 16S rRNA universal primers (27F-1492R). The PCR mixture for a 50 μl reaction volume consisted of total PCR mastermix (GCC Biotech India Pvt. Ltd), forward and reverse primer, and the final required volume of 50 μl was completed by adding PCR water with 2 μl template DNA. Polymerase chain reaction conditions consisted of an initial denaturation at 94 °C for 3 min followed by 35 cycles of denaturation at 94 °C for 30 s, the annealing temperature of primers was 60 °C for 30 s and extension at 72 °C for 1 min and final extension at 72 °C for 5 min and infinite hold at 4 °C.
PCR based confirmation of ARGs
PCR amplification was carried out against nine ARGs with community DNA for water and sediment samples. The bacterial community DNA from river water and sediment samples were isolated using the MP biomedical FastDNA Spin Kit. In water and sediment samples, the prevalence of targeted ARGs including blaKPC, blaNDM, blaTEM, tetM, ant2, ant-3, qnrS, cmlA, and sul3, was determined using water and sediment in the conventional PCR system. The ARGs were analysed using a specific primer set, and the annealing temperature is listed in Table 2.
Primers used in this study to amplify antibiotic-resistant genes
S.N. . | Primer . | Sequence . | Annealing temp. (°C) . | Product size . | Reference . | |
---|---|---|---|---|---|---|
1 | blaKPC | F | CATTCAAGGGCTTTCTTGCTGC | 51 | 538 | Nass et al. (2008) |
R | ACGACGGCATAGTCATTTGC | |||||
2 | blaNDM | F | GGGCAGTCGCTTCCAACGGT | 51 | 476 | Yong et al. (2009) |
R | GTAGTGCTCAGTGTCGGCAT | |||||
3 | blaTEM | F | ATAAAATTCTTGAAGACGAAA | 50 | 1076 | Ahmed et al. (2007) |
R | GACAGTTACCAATGCTTAATC | |||||
4 | tetM | F | GTGGACAAAGGTACAACGAG | 55 | 406 | NG et al. (2001) |
R | CGGTAAAGTTCGTCACACAC | |||||
5 | ant-2 | F | ATGGACACAACGCAGGTCAC | 59 | 534 | Vakulenko & Mobashery (2003) |
R | TTAGGCCGCATATCGCGACC | |||||
6 | ant-3 | F | GTGGATGGCGGCCTGAAGCC | 68 | 529 | Vakulenko & Mobashery (2003) |
R | AATGCCCAGTCGGCAGCG | |||||
7 | qnrS | F | GCAAGTTCATTGAACAGGGT | 427 | Cattoir et al. (2007) | |
R | TCTAAACCGTCGAGTTCGGCG | |||||
8 | cmlA | F | TACTCGGATCCATGCTGGCC | 50 | 578 | Obayiuwana et al. (2021) |
R | TCCTCGAAGAGCGCCATTGG | |||||
9 | sul3 | F | GAGCAAGATTTTTGGAATCG | 53 | 789 | Boerlin et al. (2005) |
R | CATCTGCAGCTAACCTAGGGCTTTGGA |
S.N. . | Primer . | Sequence . | Annealing temp. (°C) . | Product size . | Reference . | |
---|---|---|---|---|---|---|
1 | blaKPC | F | CATTCAAGGGCTTTCTTGCTGC | 51 | 538 | Nass et al. (2008) |
R | ACGACGGCATAGTCATTTGC | |||||
2 | blaNDM | F | GGGCAGTCGCTTCCAACGGT | 51 | 476 | Yong et al. (2009) |
R | GTAGTGCTCAGTGTCGGCAT | |||||
3 | blaTEM | F | ATAAAATTCTTGAAGACGAAA | 50 | 1076 | Ahmed et al. (2007) |
R | GACAGTTACCAATGCTTAATC | |||||
4 | tetM | F | GTGGACAAAGGTACAACGAG | 55 | 406 | NG et al. (2001) |
R | CGGTAAAGTTCGTCACACAC | |||||
5 | ant-2 | F | ATGGACACAACGCAGGTCAC | 59 | 534 | Vakulenko & Mobashery (2003) |
R | TTAGGCCGCATATCGCGACC | |||||
6 | ant-3 | F | GTGGATGGCGGCCTGAAGCC | 68 | 529 | Vakulenko & Mobashery (2003) |
R | AATGCCCAGTCGGCAGCG | |||||
7 | qnrS | F | GCAAGTTCATTGAACAGGGT | 427 | Cattoir et al. (2007) | |
R | TCTAAACCGTCGAGTTCGGCG | |||||
8 | cmlA | F | TACTCGGATCCATGCTGGCC | 50 | 578 | Obayiuwana et al. (2021) |
R | TCCTCGAAGAGCGCCATTGG | |||||
9 | sul3 | F | GAGCAAGATTTTTGGAATCG | 53 | 789 | Boerlin et al. (2005) |
R | CATCTGCAGCTAACCTAGGGCTTTGGA |
RESULTS AND DISCUSSION
Isolation and purification of bacteria and their antibiotic susceptibility
Percentage contribution of multidrug-resistant bacteria isolated from water samples of different collection sites (S1–S14) of Ghaghra River (where N0–N9 represents the number of antibiotics).
Percentage contribution of multidrug-resistant bacteria isolated from water samples of different collection sites (S1–S14) of Ghaghra River (where N0–N9 represents the number of antibiotics).
Percentage contribution of multidrug-resistant bacteria isolated from sediment samples of different collection sites (S1–S14) of Ghaghara River (where N0–N9 represents the number of antibiotics).
Percentage contribution of multidrug-resistant bacteria isolated from sediment samples of different collection sites (S1–S14) of Ghaghara River (where N0–N9 represents the number of antibiotics).
Percentage contribution of different level of antibiotic resistance of different bacterial isolates isolated from water samples of the Ghaghara River. The bar diagram exhibits the percentage of different class of antibiotic resistance (i.e., resistant, intermediate, and susceptible).
Percentage contribution of different level of antibiotic resistance of different bacterial isolates isolated from water samples of the Ghaghara River. The bar diagram exhibits the percentage of different class of antibiotic resistance (i.e., resistant, intermediate, and susceptible).
Percentage contribution of different levels of antibiotic resistance of different bacterial isolates isolated from sediment samples from the Ghaghara River. The bar diagram exhibits the percentage of different classes of antibiotic resistance (i.e., resistant, intermediate, and susceptible).
Percentage contribution of different levels of antibiotic resistance of different bacterial isolates isolated from sediment samples from the Ghaghara River. The bar diagram exhibits the percentage of different classes of antibiotic resistance (i.e., resistant, intermediate, and susceptible).
Graphical representation for genotypic profiling of antibiotic resistance for the water samples collected from all the sample collection sites. This figure reveals the maximum dominance of the ant3” gene (92.85%) followed by blaNDM (64.28 %), ant2 (50.0 %), blaKPC (42.85 %), qnrS (35.71 %), tetM (28.57 %), sul1 (21.42 %), cmlA (7.69 %) and blaTEM (7.69 %) amongst all the sampling sites.
Graphical representation for genotypic profiling of antibiotic resistance for the water samples collected from all the sample collection sites. This figure reveals the maximum dominance of the ant3” gene (92.85%) followed by blaNDM (64.28 %), ant2 (50.0 %), blaKPC (42.85 %), qnrS (35.71 %), tetM (28.57 %), sul1 (21.42 %), cmlA (7.69 %) and blaTEM (7.69 %) amongst all the sampling sites.
Graphical representation for genotypic profiling of antibiotic resistance for the Sediment Samples collected from all the sample collection sites. This figure reveals the maximum dominance of the ant3” gene (92.85%) and blaNDM (92.85%), followed by blaKPC (71.42 %), ant2 (21.42 %), tetM (21.42 %), sul3 (21.42 %), and qnrS (14.28 %). However, in sediment samples, no resistance was found against cmlA and blaTEM amongst all the sampling sites.
Graphical representation for genotypic profiling of antibiotic resistance for the Sediment Samples collected from all the sample collection sites. This figure reveals the maximum dominance of the ant3” gene (92.85%) and blaNDM (92.85%), followed by blaKPC (71.42 %), ant2 (21.42 %), tetM (21.42 %), sul3 (21.42 %), and qnrS (14.28 %). However, in sediment samples, no resistance was found against cmlA and blaTEM amongst all the sampling sites.
The maximum resistance was recorded against the genes encoding for ß-lactams, i.e. blaKPC, blaNDM, and aminoglycoside (ant3″) in almost all water and sediment samples collection sites, however few samples have shown resistance against blaTEM, qnrS, and sul3 (Figures 6 and 7). In water samples, the most frequent antimicrobial resistance genes were ant3 (13/14), blaNDM (9/14) ant2 (7/14), blaKPC (6/14), qnrS (5/14), tetM (4/14), and sul1 (3/14) (Figure 6). However, in sediment samples, the most dominating antimicrobial resistance genes were ant3 (13/14), blaNDM (13/14), blaKPC (10/14), ant2 (3/14), tetM (3/14), sul1 (3/14) and qnrS (2/14) (Figure 7). The AST observations can support the obtained data as the maximum bacterial isolates were resistant to β-lactam antibiotics. The blaNDM, blaKPC, and ant3 combination was observed in four bacterial isolates of sediment samples and nine isolates of water samples (Figure 6). The bacterial isolates of water and sediment samples of S4 and S8 sites were shown to be resistant against nearly all the ARGs used in this study (Figure 7). A higher concentration of ARGs was found in the midstream of Ghaghara River than the upper and downstream regions.
The multidrug-resistant bacterial isolates showing resistance against more than five antibiotics were selected for 16S rRNA amplification and sequence analysis considering their enhanced potential to pose a severe threat to human health aspects and environmental contamination. It was observed that the bacterial isolates from the sampling site of Chahlari bridge in Bahraich district have shown maximum MDR and were identified as K. quasipneumoniae, B. marisflavi, and Exiguobacterium undae. Prevalence of Klebsiella quasipneumoniae showing resistance against nine antibiotics and seven antibiotics respectively was found in both water and sediment, causing pneumonia and bloodstream infections (Table 3). Various non-pathogenic species of Bacillus, including B. thuringiensis, B. subtilis, B. gaemokensis, B. pseudomycoides, B. subtilis were detected at different sampling sites, E. coli at S1, Exiguobacterium undae at S4, and Exiguobacterium sp. AT1b at S12. Identified plant pathogen were Pseudomonas corrugata at S7, Aeromonas caviae at S8, and Priestia aryabhattai in water samples of sampling site 12 (Table 3). The majority of the detected bacterial species were non-pathogenic, whereas detection of species like B. thuringiensis and Klebsiella quasipneumoniae is a matter of serious concern to public health (Table 3).
Multidrug resistance (MDR) bacteria isolated and confirmed by genome sequencing with comparative similarity of database (sampling code W represents water sample and Sed represents sediment samples)
S.N. . | Sampling code . | Scientific name . | Resistant to no. of antibiotics . | Length . | Similarity % . | Accession . |
---|---|---|---|---|---|---|
1. | S1W2 | Escherichia coli ATCC 8739 | 06 | 2,519 | 100 | CP022959.1 |
2. | S1W10 | Bacillus subtilis | 07 | 2,512 | 99 | MT641205.1 |
3. | S4Sed20 | Klebsiella quasipneumoniae | 09 | 2,290 | 100 | CP045641.1 |
S4W26 | Exiguobacterium undae | 07 | 2,560 | 98 | KY230508.1 | |
S4W28 | Bacillus marisflavi | 07 | 2,429 | 99 | CP047095.1 | |
S4W29 | Klebsiella quasipneumoniae | 07 | 2,484 | 100 | CP035207.1 | |
4. | S7W48 | Pseudomonas corrugata | 06 | 2,468 | 100 | CP014262.1 |
5. | S8Sed47 | Bacillus thuringiensis | 05 | 2,551 | 100 | CP053938.1 |
S8W61 | Aeromonas caviae | 05 | 2,545 | 100 | AP019195.1 | |
6. | S11W71 | Bacillus subtilis | 07 | 2,508 | 100 | MT110999.1 |
S11Sed69 | Exiguobacterium sp. AT1b | 05 | 2,082 | 100 | CP001615.1 | |
7. | S12Sed81 | Bacillus gaemokensis | 05 | 2,518 | 100 | JN999841.1 |
S12W90 | Klebsiella quasipneumoniae | 06 | 2,542 | 100 | CP035207.1 | |
S12Sed94 | Priestia aryabhattai | 09 | 2,514 | 99 | CP072473.1 | |
8. | S14Sed97 | Bacillus pseudomycoides | 05 | 2,536 | 100 | MK537370.1 |
S.N. . | Sampling code . | Scientific name . | Resistant to no. of antibiotics . | Length . | Similarity % . | Accession . |
---|---|---|---|---|---|---|
1. | S1W2 | Escherichia coli ATCC 8739 | 06 | 2,519 | 100 | CP022959.1 |
2. | S1W10 | Bacillus subtilis | 07 | 2,512 | 99 | MT641205.1 |
3. | S4Sed20 | Klebsiella quasipneumoniae | 09 | 2,290 | 100 | CP045641.1 |
S4W26 | Exiguobacterium undae | 07 | 2,560 | 98 | KY230508.1 | |
S4W28 | Bacillus marisflavi | 07 | 2,429 | 99 | CP047095.1 | |
S4W29 | Klebsiella quasipneumoniae | 07 | 2,484 | 100 | CP035207.1 | |
4. | S7W48 | Pseudomonas corrugata | 06 | 2,468 | 100 | CP014262.1 |
5. | S8Sed47 | Bacillus thuringiensis | 05 | 2,551 | 100 | CP053938.1 |
S8W61 | Aeromonas caviae | 05 | 2,545 | 100 | AP019195.1 | |
6. | S11W71 | Bacillus subtilis | 07 | 2,508 | 100 | MT110999.1 |
S11Sed69 | Exiguobacterium sp. AT1b | 05 | 2,082 | 100 | CP001615.1 | |
7. | S12Sed81 | Bacillus gaemokensis | 05 | 2,518 | 100 | JN999841.1 |
S12W90 | Klebsiella quasipneumoniae | 06 | 2,542 | 100 | CP035207.1 | |
S12Sed94 | Priestia aryabhattai | 09 | 2,514 | 99 | CP072473.1 | |
8. | S14Sed97 | Bacillus pseudomycoides | 05 | 2,536 | 100 | MK537370.1 |
These bacterial isolates are generally found in the wastewater environment and effluents from households and grow in the saline environment and high pH environment. Therefore, it is indicated that these bacterial isolates were transferred from wastewater to the river system. Most of the bacterial isolates from this river system showed resistance against penicillin G (P), cefuroxime (CXM), and amoxicillin (AMX). The Bacillus sp. is highly prevalent in household sewerage, wastewater, and sediment/water samples of the Ghaghara and major tributaries.
CONCLUSION
According to these results, most isolated bacterial strains are resistant to antibiotics commonly used in medical practices, such as penicillin G, cefuroxime, and amoxicillin. 16S rRNA analysis for bacterial identification and microbial study in the river Ghaghara has been performed for the first time in this study. The data obtained in the present study provide an overview of the prevalence and abundance of multidrug-resistant bacteria at many sampling sites of the Ghaghara River. Additionally, the results provide the information to understand the risks associated with the prevalence of antibiotics pollution in the aquatic environment and its effects on other environmental compartments. The opportunistic human pathogenic Klebsiella quasipneumoniae in water and sediment samples were resistant against ß-lactam antibiotics and contained diverse carbapenem resistance genes. Finally, further research is needed to evaluate the risks of antibiotic pollution in the downstream river environment and improve the efficiency and technologies implemented in the wastewater treatment plant.
ACKNOWLEDGEMENTS
The authors thank Atul Srivastava for the study area map preparation. The authors thank the University of Allahabad, Prayagraj, and Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, for providing the necessary facilities. The authors thank UGC for providing a Rajiv Gandhi National Fellowship (RGNF) to Nirdesh Kumar Ravi.
FUNDING
Pawan Kumar Jha thanks the University Grant Commission (UGC), India, for providing funding (No. F.30-373/2017(BSR)) for research work presented in this paper.
ETHICAL APPROVAL
This article does not contain any studies with human participants or animals.
CONSENT TO PARTICIPATE
The authors approved the participation.
CONSENT FOR PUBLICATION
The authors approved for the publication.
AUTHORS’ CONTRIBUTIONS
VT and PJ conceived the research. NKR, RS, and VT wrote the manuscript. NKR AKP and RS performed the experiments. VT, PT and PJ edited the manuscript. PT and AS contributed to sampling and data analysis. All authors read and approved the final manuscript.
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.
REFERENCES
Author notes
Authors have equally contributed