Preconcentration of rifampicin prior to its efficient spectroscopic determination in the wastewater samples based on a nonionic surfactant

Effects of antibiotic interaction on antimicrobial resistance development in wastewater

While wastewater is understood to be a critically important reservoir of antimicrobial resistance due to the presence of multiple antibiotic residues from industrial and agricultural runoff, there is little known about the effects of antibiotic interactions in the wastewater on the development of resistance. We worked to fill this gap in quantitative understanding of antibiotic interaction in constant flow environments by experimentally monitoring E. coli populations under subinhibitory concentrations of combinations of antibiotics with synergistic, antagonistic, and additive interactions. We then used these results to expand our previously developed computational model to account for the effects of antibiotic interaction. We found that populations grown under synergistic and antagonistic antibiotic conditions exhibited significant differences from predicted behavior. E. coli populations grown with synergistically interacting antibiotics developed less resistance than predicted, indicating that synergistic antibiotics may have a suppressive effect on resistance development. Furthermore E. coli populations grown with antagonistically interacting antibiotics showed an antibiotic ratio-dependent development of resistance, suggesting that not only antibiotic interaction, but relative concentration is important in predicting resistance development. These results provide critical insight for quantitatively understanding the effects of antibiotic interactions in wastewater and provide a basis for future studies in modelling resistance in these environments.

Effects of Antibiotic Interaction on Antimicrobial Resistance Development in Wastewater

While wastewater is understood to be a critically important reservoir of antimicrobial resistance due to the presence of multiple antibiotic residues from industrial and agricultural runoff, there is little known about the effects of antibiotic interactions in the wastewater on the development of resistance. We worked to fill this gap in quantitative understanding of antibiotic interaction in constant flow environments by experimentally monitoring E. coli populations under subinhibitory concentrations of combinations of antibiotics with synergistic, antagonistic, and additive interactions. We then used these results to expand our previously developed computational model to account for the complex effects of antibiotic interaction. We found that while E. coli populations grown in additively interacting antibiotic combinations grew predictably according to the previously developed model, those populations grown under synergistic and antagonistic antibiotic conditions exhibited significant differences from predicted behavior. E. coli populations grown in the condition with synergistically interacting antibiotics developed less resistance than predicted, indicating that synergistic antibiotics may have a suppressive effect on antimicrobial resistance development. Furthermore E. coli populations grown in the condition with antagonistically interacting antibiotics showed an antibiotic ratio-dependent development of resistance, suggesting that not only antibiotic interaction, but relative concentration is important in predicting resistance development. These results provide critical insight for quantitatively understanding the effects of antibiotic interactions in wastewater and provide a basis for future studies in modelling resistance in these environments.

Importance

Antimicrobial resistance (AMR) is a growing global threat to public health expected to impact 10 million people by 2050, driving mortality rates globally and with a disproportionate effect on low- and middle-income countries. Communities in proximity to wastewater settings and environmentally contaminated surroundings are at particular risk due to resistance stemming from antibiotic residues from industrial and agricultural runoff. Currently, there is a limited quantitative and mechanistic understanding of the evolution of AMR in response to multiple interacting antibiotic residues in constant flow environments. Using an integrated computational and experimental methods, we find that interactions between antibiotic residues significantly affect the development of resistant bacterial populations.

State of the Art on Developments of (Bio)Sensors and Analytical Methods for Rifamycin Antibiotics Determination

This review summarizes the literature data reported from 2000 up to the present on the development of various electrochemical (voltammetric, amperometric, potentiometric and photoelectrochemical), optical (UV-Vis and IR) and luminescence (chemiluminescence and fluorescence) methods and the corresponding sensors for rifamycin antibiotics analysis. The discussion is focused mainly on the foremost compound of this class of macrocyclic drugs, namely rifampicin (RIF), which is a first-line antituberculosis agent derived from rifampicin SV (RSV). RIF and RSV also have excellent therapeutic action in the treatment of other bacterial infectious diseases. Due to the side-effects (e.g., prevalence of drug-resistant bacteria, hepatotoxicity) of long-term RIF intake, drug monitoring in patients is of real importance in establishing the optimum RIF dose, and therefore, reliable, rapid and simple methods of analysis are required. Based on the studies published on this topic in the last two decades, the sensing principles, some examples of sensors preparation procedures, as well as the performance characteristics (linear range, limits of detection and quantification) of analytical methods for RIF determination, are compared and correlated, critically emphasizing their benefits and limitations. Examples of spectrometric and electrochemical investigations of RIF interaction with biologically important molecules are also presented.