Microbial natural products have been an invaluable resource for providing clinically relevant therapeutics for almost a century, including most of the commonly used antibiotics that are still in medical use today. In more recent decades, the need for new biotherapeutics has begun to grow, as multi-drug resistant pathogens continue to emerge, putting into question the long-term efficacy of many drugs that we routinely depend on to combat infectious diseases. To affect this growing medical crisis, new efforts are being applied to computationally mine the genomes of microorganisms for biosynthetic gene clusters that code for molecules possessing anti-microbial activities that circumvent known resistance mechanisms. To this end, cutting-edge software platforms have been developed that can identify, with high predictive accuracy, microbial genomes that code for natural products of potential interest. However, with such analyses comes the need to thoroughly vet each predicted gene cluster, to identify those high-value candidate molecules that are not associated with known resistance mechanisms. In this work, a new strategy was developed that involved cataloguing all known ‘self-resistance’ mechanisms encoded by natural product producing microorganisms, which protect the producer from the highly toxic effects of their secreted anti-microbial agents. This collection of resistance data was leveraged and used to engineer an automated software-based pipeline that interrogates biosynthetic gene clusters and relates them to previously identified resistance mechanisms. Gene clusters that are revealed to be independent of known resistance mechanisms can then be flagged for further chemical and biological study in the laboratory. Such in-depth interrogations of microbial genomes aim to help reveal the full biological repertoire of antibiotics yet to be discovered from microorganisms, and will lead to the development of the next generation of biotherapeutics to quell the growing medical crisis of antibiotic-resistance among human pathogenic organisms. / Thesis / Master of Science (MSc) / It would be hard to imagine a world where we could no longer use the antibiotics we are routinely being prescribed for common bacterial infections. Currently, we are in an era where this thought could become a reality. Although we have been able to discover antibiotics in the past from soil dwelling microbes, this approach to discovery is being constantly challenged. At the same time, the bacteria are getting smarter in their ways to evade antibiotics, in the form of resistance, or self-protection mechanisms. As such is it essential to devise methods which can predict the potential for resistance to the antibiotics we use early in the discovery and isolation process. By using what we have learned in the past about how bacteria protect themselves for antibiotics, we can to stay one step ahead of them as we continue to search for new sources of antibiotics from bacteria.

There is an urgent need to identify novel antibiotics for multidrug-resistant Gram-negative pathogens. These bacteria are intrinsically resistant to many antimicrobials due to a formidable outer membrane barrier. Herein we investigate the potential of perturbing the outer membrane to sensitize Gram-negative bacteria to otherwise inactive antibiotics. In chapter 2, we identify the ability of mcr-1 mediated resistance to confer protection from the lytic but not outer membrane-perturbing activity of colistin. Exploiting this sensitivity, we show that colistin and clarithromycin in combination are efficacious against mcr-1-expressing Klebsiella pneumoniae in murine infection models. This demonstrates the viability of colistin combination therapies against Gram-negative pathogens harbouring mcr-1, and points to a mechanism of mcr-1-mediated resistance extending beyond the predicted reduction in binding affinity of polymyxins to the outer membrane. We continue to investigate the potential of using outer membrane perturbants with otherwise inactive antimicrobials in chapter 3. In this work, we identify the ability of OM disruption to change the rules of Gram-negative entry, render pre-existing resistance ineffective, reduce the development of spontaneous resistance and attenuate biofilm formation. Together, these data suggest that OM disruption overcomes many traditional hurdles encountered during antibiotic treatment and is a high priority approach for further development. / Thesis / Doctor of Philosophy (PhD)

Salmonella enterica serovar Typhimurium (Salmonella) is a Gram-negative bacterial pathogen capable of causing both gastroenteritis and bacteraemia in human hosts. During infection, Salmonella invokes a complex network of virulence factors, regulatory systems, and metabolic pathways to promote immune evasion, sometimes demanding antibiotic treatment for resolution. Unfortunately, antibiotic resistance has reached critical levels in this and other pathogens, necessitating the discovery of new anti-infective targets and treatment options. Herein, we have sought to exploit the dynamic interactions between Salmonella and the host immune system to identify new, conditionally active anti-Salmonella therapies. In chapter 2, we aim to identify chemical compounds that are selectively antimicrobial against intracellular Salmonella, and discover that the anxiolytic drug metergoline inhibits Salmonella survival in cultured macrophages and systemically infected mice. In chapter 3, we screen for anti-virulence compounds that target regulatory signaling in Salmonella, and characterize the inhibitory activity of methyl-3,4-dephostatin, which perturbs SsrA/B and PmrB/A signaling and enhances sensitivity to colistin in vitro and in vivo. In chapter 4, we identify several host-directed compounds that modulate macrophage immunity and investigate their ability to attenuate a multidrug resistant Salmonella infection. Together, the work presented in this thesis demonstrates the potential for drug screening in infection-relevant conditions to identify new anti-infectives with non-traditional targets. / Thesis / Doctor of Philosophy (PhD)

To revitalize the antibiotic pipeline, it is critical to identify and validate new antimicrobial targets. An uncharted area of antibiotic discovery can be explored by inhibiting nutrient biosynthesis. Herein, we investigate the potential of inhibiting biotin biosynthesis in monotherapy and combination therapy approaches to treat multidrug-resistant Gram-negative pathogens. In chapter 2, we validate biotin biosynthesis as a viable target for Gram-negative pathogens. Historically, biotin biosynthesis was overlooked as a target in Gram-negative pathogens as there was no observed fitness cost associated with its inhibition in standard mouse infection models. We discovered traditional mouse models do not accurately represent the biotin levels in humans. We developed an innovative mouse model to account for this discrepancy, validating biotin biosynthesis as an antimicrobial target in the presence of human-mimicking levels of biotin. Exploiting this sensitivity, we show that an inhibitor of biotin biosynthesis, MAC13772, is efficacious against Acinetobacter baumannii in a systemic murine infection model. In chapter 3, we continue to investigate the potential of targeting biotin biosynthesis in a combination therapy approach. In this work, we identify the ability of MAC13772 to synergize with colistin exclusively against colistin-resistant pathogens. The first committed step of fatty acid biosynthesis requires biotin as a cofactor; therefore, it is indirectly inhibited through the action of MAC13772. We propose that the inhibition of fatty acid biosynthesis leads to changes in membrane fluidity and phospholipid composition, restoring colistin sensitivity. The combination of a fatty acid biosynthesis inhibitor and colistin proved superior to either treatment alone against mcr-1 expressing Klebsiella pneumoniae and colistin-resistant Escherichia coli murine infection models. Together, these data suggest that biotin biosynthesis is a robust antibiotic target for further development in monotherapy and combination therapy approaches. / Thesis / Doctor of Philosophy (PhD)

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