A systematic review was conducted to determine the distribution and prevalence of antibiotic-resistant bacteria (ARB), antimicrobial-resistant genes (ARGs), and antimicrobial-resistant gene determinants (ARGDs) in clinical, environmental, and farm settings and to identify key knowledge gaps in a bid to contain their spread. Fifty-three articles were included. The prevalence of a wide range of antimicrobial-resistant bacteria and their genes was reviewed. Based on the studies reviewed in this systematic review, mutation was found to be the main genetic element investigated. All settings shared 39 ARGs and ARGDs. Despite the fact that ARGs found in clinical settings are present in the environment, in reviewed articles only 12 were found to be shared between environmental and clinical settings; the inclusion of farm settings with these two settings increased this figure to 32. Data extracted from this review revealed farm settings to be one of the main contributors of antibiotic resistance in healthcare settings. ARB, ARGs, and ARGDs were found to be ubiquitous in all settings examined.

The environmental dissemination of selected antibiotics from hospital wastewater into municipal wastewater and lastly to a receiving water body was investigated. Selected antibiotics (azithromycin (AZM), ciprofloxacin (CIP), clindamycin (CDM), doxycycline (DXC) and sulfamethoxazole (SMZ)) present in effluents of academic hospital wastewater, influents, sewage sludge, and effluents of municipal wastewater, receiving water, and its benthic sediment samples were quantified using the Acquity^® Waters Ultra-Performance Liquid Chromatography System hyphenated with a Waters Synapt G2 coupled to a quadrupole time-of-flight mass spectrometer. The overall results showed that all assessed antibiotics were found in all matrices. For solid matrices, river sediment samples had elevated concentrations with mean concentrations of 34,834, 35,623, 50,913, 55,263, and 41,781 ng/g for AZM, CIP, CDM, DXC, and SMZ, respectively, whereas for liquid samples, hospital wastewater and influent of wastewater had the highest concentrations. The lowest concentrations were observed in river water, with mean concentrations of 11, 97, 15, and 123 ng/L, except for CDM, which was 18 ng/L in the effluent of wastewater. The results showed that the highest percentages of antibiotics removed was SMZ with 90%, followed by DXC, AZM and CIP with a removal efficiency of 85%, 83%, and 83%, respectively. The antibiotic that showed the lowest removal percentage was CDM with 66%. However, the calculated environmental dissemination analysis through the use of mass load calculations revealed daily release of 15,486, 14,934, 1526, 922, and 680 mg/d for SMZ, CIP, AZM, DXC, and CDM, respectively, indicating a substantial release of selected antibiotics from wastewater to the river system, where they are possibly adsorbed in the river sediment. Further research into the efficient removal of antibiotics from wastewater and the identification of antibiotic sources in river sediment is needed.

Wastewaters are plausible arenas for antibiotic resistance evolution and transmission, yet selection for resistance by municipal wastewater has rarely been empirically demonstrated. Here, we experimentally investigate the potential of untreated municipal wastewater from 47 countries to select for antibiotic resistance and explore possible drivers. Using a functional selection assay with 340 mixed Escherichia coli strains, we find that sterile-filtered samples from 14 countries select significantly for resistance to at least one antibiotic class compared to baseline, while the majority select significantly against resistance. Similar results were generated using natural wastewater communities. Additionally, we report a comprehensive characterization of antibiotics and antibacterial biocides in the wastewaters. None of the 22 analyzed antibiotics could be assigned as key drivers for selection in E. coli , whereas e.g. folate pathway antagonists and macrolides often exceed predicted non-selective concentrations for other bacteria by >10-fold. Despite detecting 13 (out of 20 analyzed) organic antibacterial biocides, their potential for co-selection remains unclear. Measured chemical constituents correlate only weakly with observed selection, suggesting complex mixture effects and/or selection by unmeasured compounds. The clear deselection of resistance by most samples indicates that many resistant strains have impaired fitness in wastewaters with limited antibiotic selection pressure.