95) 1 (1.19) 0 0 0 6 (7.14) site 2 9 (10.71) 4 (4.76) 4 (4.76) 0 0 17 (20.24) site 3 12 (14.29) 6 (7.14) 0 1 (1.19) 0 19 (22.62) site 4 12 (14.29) 3 (3.57) 3 (3.57) 0 0 18 (21.43)
<0.0001*** site 5 16 (19.05) 6 (7.14) 0 1 (1.19) 1 (1.19) 24 (28.57) Enterococcus spp. distribution 54 (64.29) 20 (23.81) 7 (8.33) 2 (2.38) 1 (1.19) 84 (100) a p-Value was calculated using chi square test, χ2 = 100.4; df = 20. ***Statistically significant at alpha < 0.05. Antimicrobial-resistance This study investigated the background pool of antimicrobial-resistance (BPAR) in the landscape. High frequency of multiple-antimicrobial-resistance (MAR) was recorded among enterococci tested. The number (median) of antimicrobials against which resistance was observed in each Enterococcus BI-D1870 supplier isolate increased significantly (p 0.0156, 0.0001, < 0.0001, 0.0001, < 0.0001) towards downstream in the landscape (Table 3). The prevalence of resistance to a minimum of five PF-02341066 price antimicrobials per isolate reflects high BPAR in the up-to-down gradient landscape. This high value of BPAR at most upstream site
could be attributed to the agriculture farms, intensive livestock and swine farming in the locality. Although there is no data available from India, the prevalence of VRE on site 1 may be due to the use of antimicrobials in the animal feed and cattle or swine manure application in the fields, reported to be important contributing factors elsewhere [25, 26]. The urban sewage waste contributed to the maintenance of resistance pool at site 2. The elevated level of resistance at site 3 was a likely contribution from hospital, tannery, and sewage discharging point sources leading to microbial, chemical as well as antimicrobial contamination. The lower concentration of enterococci and reduced resistance pool at site 4, as compared to site 3, is possibly due to confluence of two watersheds just upstream of site
4 resulting in dilution of the pre-existing microbial VRT752271 biogeography and associated traits. Site 5, the most downstream sampling station in the landscape presents the worst scenario of microbial contamination and reflects the best spatial correlation among enterococci concentration, species diversity, antimicrobial-resistance and virulence-markers’ dissemination. Table 3 Antimicrobial-resistance and virulence-markers Immune system investigated in each Enterococcus isolate on sites located in the up-to-down-gradient landscape Sampling site No. of samples analyzed for antimicrobial susceptibility or virulence-marker/s (%) Antimicrobial-resistance (AR) and Virulence-markers (VM) characterized per isolate [Median (Range)]a p-Valueb site 1 6 (7.14) AR: 5 (3 – 6) 0.0156* VM: 2 (1 – 3) 0.0156* site 2 17 (20.24) AR: 5 (4 – 5) 0.0001* VM: 2 (1 – 2) 0.0002* site 3 19 (22.62) AR: 7 (5 – 7) < 0.0001* VM: 1 (1 – 4) < 0.0001* site 4 18 (21.43) AR: 5 (5 – 6) 0.0001* VM: 2 (1 – 2) < 0.0001* site 5 24 (28.57) AR: 5 (5 – 6) < 0.0001* VM: 2 (2 – 3) < 0.
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