Substandard antimicrobial drugs: detection methods and their contributions to antibiotic resistance

Substandard and counterfeit medicines are major obstacles to the treatment of infectious diseases. Substandard medicines vary from standard drugs in terms of dose, bioavailability, or the presence of impurities. Current methods to identify substandard and counterfeit antimicrobial drugs are either resource intensive or have poor specificity. This dissertation examined two issues related to poor quality antimicrobial medicines: 1) Methods to detect and prevent the consumption of substandard drugs. 2) The relationship between substandard medicines and the evolution of rifampicin resistance. This dissertation advanced two technologies that may aid in the detection of substandard medicines: aptamers and biosensors. Oligonucleotide aptamers may be adapted for drug detection by coupling binding events to changes in fluorescence, luminescence or colorimetric signals. A computational model was developed to discover experimental factors that increase the probability of selecting a high affinity aptamer. Among them are: micromolar drug target concentration, high affinity substrate to partition aptamers, and high aptamer library affinity distribution. Random losses of aptamers due to experimental noise greatly decreased the probability of selecting an aptamer. Experimental parameters to optimize the process of aptamer discovery for small molecules are discussed. Bacterial biosensors are an alternative strategy for the detection of active pharmaceutical ingredients. Here, luciferase-expressing Escherichia coli were used to create profiles of drug interactions for anti-mycobacterial drugs. Drug interactions were tested by the Loewe additivity model. A novel method to differentiate rifamycin drugs from the drug degradation product rifampicin quinone was developed by analyzing each drug’s unique interactions. While subinhibitory drug doses are known to select for antimicrobial resistance in vitro, the role of substandard anti-mycobacterial medicines in the development of rifampicin resistance remains poorly understood. The role of the drug degradation product rifampicin quinone on rifamycin resistance was assessed through in vitro studies of bacteria. Wild type Escherichia coli and Mycobacterium smegmatis cultured in the presence of rifampicin quinone acquired high levels of resistance to rifamycin drugs. Resistance was associated with genetic mutations in the rifampicin resistance cluster of the rpoB gene. The studies presented here demonstrate that substandard medicines can contribute towards rifamycin resistance, and offer methodologies to identify substandard medicines.2020-10-24T00:00:00

Simulations of SELEX against complex receptors with a condensed statistical model

Systematic evolution of ligands by exponential enrichment (SELEX) is an in vitro combinatorial engineering approach to enrich aptamers from a library of nucleic acids ligands by iterative extraction and amplification of receptor-bound ligands. Aptamers are the selected nucleic acid ligands with high receptor-binding affinity. Typically, they are obtained in single-receptor SELEX experiments where the ligand library is incubated with receptor molecules of a single identity, e.g., a purified protein. For years, aptamers have been shown to be valuable for biomedical applications and research. To further explore the power of SELEX technology, the idea of complex SELEX was proposed to obtain multiple aptamers by incubating the ligand library with multiple species of receptors. However, the reports on complex SELEX have been few, possible due to the ignorance of the effects of experimental variables. To address this problem, computer simulations should be useful. A major task of simulating complex SELEX is to solve interdependent binding equilibrium equations for binding events among heterogeneous ligands and receptors. Although a detailed subpooling model was developed, that model could be useful to simulate complex SELEX against at most four species of receptors, because the demand of computer memory grew exponentially with the number of receptor species. Here we develop a novel, condensed subpooling model where ligands of similar characteristic affinity are first pooled together regardless of receptor- specificity, and then divided into partial subpools receptor-specific ally. With this model, the need of computer memory grows only linearly with receptor number. In the simulation of SELEX against four receptors, our results are the same or very similar to earlier work. We have further simulated SELEX against 100 heterogeneous receptors. We suggest that our computation method can be applied to other research fields where binding events between heterogeneous ligands and receptors are involved. (c) 2006 Elsevier Ltd. All rights reserved