SmartChip Real-Time PCR System applications
- Antibiotic resistance genes
- mRNA, miRNA, and lncRNA as disease biomarkers
- Pathogen detection in human samples and food
- Genotyping using animal and blood samples
Identifying antibiotic resistance genes in water
Antibiotic-resistant bacteria can be found in a variety of different water sources, such as improperly treated wastewater. These bacteria may also be present in environmental locations, such as streams, rivers, lakes, and oceans. There is also a chance that drinking water can become contaminated, posing serious health risks. Numerous studies have been published using the SmartChip Real-Time PCR System to analyze antibiotic resistance in a wide variety of water samples.
In one recent study, researchers analyzed human feces and skin samples, water from sewage treatment systems, and water from rivers (Zhou et al. 2018). By utilizing a 296-primer panel for antibiotic resistance on the SmartChip system, they identified 234 unique antibiotic resistance genes that were present in the human samples. The antibiotic resistance genes were seven times more abundant in the sewage samples than the river samples. A closer examination revealed that 53 of the identified antibiotic resistance genes present in the sewage samples were directly linked to human feces—demonstrating a direct link between antibiotic-resistant bacteria in the gut and that found in environmental water sources.
Another recent study from a team at the University of Helsinki initiated a large-scale qPCR study with the SmartChip system on untreated raw influent samples and treated final effluent samples from dozens of urban wastewater plants across seven European countries (Pärnänen et al. 2019). The researchers were able to show that antibiotic resistance genes were more likely to be present in the wastewater of countries with higher antibiotic prescription rates. This first trans-Europe surveillance study sets a precedent for ways to monitor and track antibiotic resistance.
Chen, Y. et al. High-throughput profiling of antibiotic resistance gene dynamic in a drinking water river-reservoir system. Water Res. 149, 179–189 (2019).
Cui, E.-P. et al. Amendment soil with biochar to control antibiotic resistance genes under unconventional water resources irrigation: Proceed with caution. Environ. Pollut. 240, 475–484 (2018).
Jiao, Y.-N. et al. Biomarkers of antibiotic resistance genes during seasonal changes in wastewater treatment systems. Environ. Pollut. 234, 79–87 (2018).
Jong, M.-C. et al. Co-optimization of sponge-core bioreactors for removing total nitrogen and antibiotic resistance genes from domestic wastewater. Sci. Total Environ. 634, 1417–1423 (2018).
Karkman, A. et al. High-throughput quantification of antibiotic resistance genes from an urban wastewater treatment plant. FEMS Microbiol. Ecol. 92, 1–7 (2016).
Lin, W., Zhang, M., Zhang, S. & Yu, X. Can chlorination co-select antibiotic-resistance genes? Chemosphere 156, 412–419 (2016).
Liu, L. et al. Large-scale biogeographical patterns of bacterial antibiotic resistome in the waterbodies of China. Environ. Int. 117, 292–299 (2018).
Ouyang, W. Y., Huang, F. Y., Zhao, Y., Li, H. & Su, J. Q. Increased levels of antibiotic resistance in urban stream of Jiulongjiang River, China. Appl. Microbiol. Biotechnol. 99, 5697–5707 (2015).
Pärnänen, K. M. M. et al. Antibiotic resistance in European wastewater treatment plants mirrors the pattern of clinical antibiotic resistance prevalence. Sci. Adv. 5, eaau9124 (2019).
Stedtfeld, R. D. et al. Isothermal assay targeting class 1 integrase gene for environmental surveillance of antibiotic resistance markers. J. Environ. Manage. 198, 213–220 (2017).
Tang, M. et al. Abundance and distribution of antibiotic resistance genes in a full-scale anaerobic-aerobic system alternately treating ribostamycin, spiramycin and paromomycin production wastewater. Environ. Geochem. Health (2017). doi:10.1007/s10653-017-9987-5
Wan, K. et al. Organic carbon: An overlooked factor that determines the antibiotic resistome in drinking water sand filter biofilm. Environ. Int. 125, 117–124 (2019).
Wang, F.-H. et al. High throughput profiling of antibiotic resistance genes in urban park soils with reclaimed water irrigation. Environ. Sci. Technol. 48, 9079–9085 (2014).
Waseem, H. et al. Contributions and challenges of high throughput qPCR for determining antimicrobial resistance in the environment: a critical review. Molecules 24, 163 (2019).
Xu, L. et al. High-throughput profiling of antibiotic resistance genes in drinking water treatment plants and distribution systems. Environ. Pollut. 213, 119–126 (2016).
Zhang, M., Chen, L., Ye, C. & Yu, X. Co-selection of antibiotic resistance via copper shock loading on bacteria from a drinking water bio-filter. Environ. Pollut. 233, 132–141 (2018).
Zheng, J., Chen, T. & Chen, H. Antibiotic resistome promotion in drinking water during biological activated carbon treatment: Is it influenced by quorum sensing? Sci. Total Environ. 612, 1–8 (2018).
Zheng, J. et al. High-throughput profiling and analysis of antibiotic resistance genes in East Tiaoxi River, China. Environ. Pollut. 230, 648–654 (2017).
Zheng, J. et al. High-throughput profiling of seasonal variations of antibiotic resistance gene transport in a peri-urban river. Environ. Int. 114, 87–94 (2018).
Zhou, Z.-C. et al. Prevalence and transmission of antibiotic resistance and microbiota between humans and water environments. Environ. Int. 121, 1155–1161 (2018).
Zhu, Y.-G. et al. Continental-scale pollution of estuaries with antibiotic resistance genes. Nat. Microbiol. 2, 16270 (2017).
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