The prevalence and antimicrobial resistance phenotypes of Salmonella, Escherichia coli and Enterococcus sp. in surface water.
Sohyun ChoCharlene R JacksonJonathan G FryePublished in: Letters in applied microbiology (2020)
Surface water is prone to bacterial contamination as it receives wastes and pollutants from human and animal sources, and contaminated water may expose local populations to health risks. This review provides a brief overview on the prevalence and antimicrobial resistance (AR) phenotypes of Salmonella, Escherichia coli and Enterococcus, found in natural freshwaters. These bacteria are frequently detected in surface waters, sometimes as etiological agents of waterborne infections, and AR strains are not uncommonly identified in both developed and developing countries. Data relating to Salmonella, E. coli and Enterococcus present in environmental water are lacking, and in order to understand their development and dissemination using the One Health approach, understanding the prevalence, distribution and characteristics of the bacteria present in surface water as well as their potential sources is important. Furthermore, AR bacteria in natural watersheds are not well investigated and their impacts on human health and food safety are not well understood. As surface water is a receptacle for AR bacteria from human and animal sources and a vehicle for their dissemination, this is a crucial data gap in understanding AR and minimizing its spread. For this review, Salmonella, E. coli and Enterococcus were chosen to evaluate the presence of primary pathogens and opportunistic pathogens as well as to monitor AR trends in the environmental water. Studies around the world have demonstrated the widespread distribution of pathogenic and AR bacteria in surface waters of both developing and developed countries, confirming the importance of environmental waters as a reservoir for these bacteria and the need for more attention on the environmental bacteria for emerging AR.
Keyphrases
- escherichia coli
- human health
- antimicrobial resistance
- risk assessment
- biofilm formation
- drinking water
- risk factors
- endothelial cells
- climate change
- heavy metals
- healthcare
- public health
- pseudomonas aeruginosa
- big data
- mental health
- induced pluripotent stem cells
- working memory
- gram negative
- listeria monocytogenes
- artificial intelligence
- machine learning
- data analysis
- candida albicans
- health promotion
- anaerobic digestion
- pluripotent stem cells