Browsing by Subject "Resistance"

An essential property of microbial communities is the ability to survive a disturbance. This is readily observed in bacteria, which have developed the ability to survive every antibiotic treatment at an alarming rate, considering the timescale at which new antibiotics are developed. Thus, there is a critical need to use antibiotics more effectively, extend the shelf life of existing antibiotics and minimize their side effects. This requires understanding the mechanisms underlying bacterial drug responses. Past studies have focused on survival in the presence of antibiotics by individual cells, such as genetic mutants. Also important, however, is the fact that a population of bacterial cells can collectively survive antibiotic treatments lethal to individual cells. This tolerance can arise by diverse mechanisms, including resistance-conferring enzyme production, titration-mediated bistable growth inhibition, swarming and interpopulation interactions. These strategies can enable rapid population recovery after antibiotic treatment and provide a time window during which otherwise susceptible bacteria can acquire inheritable genetic resistance.

To further explore bacterial antibiotic responses, I focused on bacteria producing β-lactamase, an enzyme that has drastically limited the use of our most commonly prescribed antibiotics: β-lactams. Through the characterization of clinical isolates and a computational model, my Ph.D. thesis has three implications:

First, survival can be achieved through resistance, the ability to absorb effects of a disturbance without a significant change, or resilience, the ability to recover after being perturbed by a disturbance. Current practices for determining the antibiotic sensitivity of bacteria do not characterize a population as resistant and/or resilient, they only report whether the bacteria can survive the antibiotic exposure. As resistance and resilience often depend on different attributes, distinguishing between these two modes of survival could inform treatment strategies. These concepts have long been applied to the analysis of ecological systems, though their interpretations are often subject to debate. This framework readily lends itself to the dissection of the bacterial response to antibiotic treatment, where both terms can be unambiguously defined.

Second, the ability to tolerate the antibiotic treatment in the short term corresponds to resistance, which primarily depends on traits associated with individual cells. In contrast, the ability to recover after being perturbed by an antibiotic corresponds to resilience, which primarily depends on traits associated with the population.

And finally, understanding the temporal dynamics of an antibiotic response could guide the design of a dosing protocol to optimize treatment efficiency for any antibiotic-pathogen combination. Ultimately, optimized dosing protocols could allow reintroduction of a repertoire of first-line antibiotics with improved treatment outcomes and preserve last-resort antibiotics.

Cancer is a diverse set of diseases characterized by genetic and epigenetic alterations that permit growth across diverse environmental contexts. The last decade has led to an explosion of sequencing efforts to define the molecular drivers of proliferation across cancers. This effort has led to the development of small-molecule inhibitors that can block oncogenic drivers and the signaling pathways driving growth. These so called “targeted therapies” have led to better progression-free survival in patients. Despite this early success, it has become clear that with few exceptions, all patients treated with targeted therapies will ultimately relapse. Thus, there is an imminent need to define combination strategies that can be employed to suppress intrinsic or acquired resistance in cancer. Here, we combine functional screening approaches, both pharmacological and genetic, to define apoptosis-inducing precision cancer therapies. Specifically, we utilize a pharmacological screening approach to uncover that breast cancers rely on Mcl-1 and Bcl-XL for survival, and that we can leverage mTOR’s translational control over Mcl-1 to induce apoptosis in PIK3CA mutant breast cancers. Additionally, we utilize CRISPR-Cas9 loss-of-function screening to define the landscape of therapeutic cooperativity in KRAS -driven cancers across diverse tissue types. Further, we leverage this landscape to define principles to rationally design combination therapies to suppress resistance. Lastly, in an effort to define targeted therapeutic strategies for cancers that lack traditional oncogenic drivers, we utilized a pharmacological screening approach to define vulnerabilities associated with dysregulated mitochondrial dynamics proteins in cancer. Collectively, our work has demonstrated the power of functional screening approaches to define apoptosis-inducing anti-cancer precision therapies that combat intrinsic and acquired resistance.

Prostate and breast cancers are major health concerns, being amongst the most common forms of cancers in both men and women. The majority of prostate and breast cancers are driven by the hormone receptors androgen receptor (AR) and estrogen receptor (ESR1), respectively, and as such, endocrine therapies targeting the actions of these receptors has been a cornerstone of treatment for these patients. While these endocrine therapies are generally initially efficacious, resistance inevitably emerges. Resistance can emerge through various mechanisms, such as amplification of the receptor, generation of activating point mutations, alternative splicing of the receptor resulting in constitutively active forms of the receptor, and activating cross-talk from growth factor signaling pathways. A salient feature of these diseases is that the nuclear receptor (AR or ER) often remains engaged upon the emergence of resistance, and thus targeting of the receptor still provides therapeutic benefit. Therefore, much work in these fields has been performed to design better forms of endocrine therapy to help patients upon tumor progression. As cells are altering their signaling to deal with these pressures, this thesis work investigated the global genomic changes which arise in prostate and breast cancer cells after endocrine therapy to understand the effects of utilizing different forms of endocrine therapy, and whether these alterations in the cells induce novel vulnerabilities which can be therapeutically exploited. In the first set of studies, the differences between utilizing a competitive antagonist (enzalutamide-Enz) vs an AR degrader (AR-targeting proteolysis targeting chimera-PROTAC) were evaluated in prostate cancer. PROTACs are a new form of therapy for prostate cancer which have encouraging results in early clinical trials, so we wanted to better understand the genomic architecture and gene expression landscape after this new treatment modality compared to the current standard of care with an aim to use this knowledge to understand endocrine therapy resistance and identify therapeutically targetable pathways emerging from treatment. A factor agnostic approach was taken utilizing ATACseq and RNAseq to compare the genomic landscape after Enz or PROTAC treatment. It was found that the different AR inhibitors create distinct genomic landscapes which appear to be driven by unique sets of transcription factors. Further, it was discovered that AR inhibition, especially through degradation creates a novel liability which can be therapeutically exploited. AR was found to mediate these effects through regulating expression of a key transcription factor, and we propose a model in which the two proteins interact to regulate this axis. As AR is expressed in many other malignancies, it is feasible this strategy of degrading AR to induce this therapeutic vulnerability could have efficacy beyond prostate cancer. In the second set of studies, we investigated the genomic changes which are manifest after the emergence of endocrine therapy resistance in breast cancer and identified a novel signaling pathway that, when targeted, impairs tumor progression. Utilizing, DNAse hypersensitivity analysis, ChIP-seq, and RNAseq, it was found that GRHL2 cooperates with FOXA1 to drive a novel cistrome in endocrine therapy resistant breast cancer cells. The protein LYPD3 was found to be a downstream effector of GRHL2 and targeting LYPD3, or its ligand AGR2, with monoclonal antibodies significantly impaired primary tumor growth. Further studies into the functional role of LYPD3 were then undertaken, and it was discovered that LYPD3 knockdown significantly alters metastatic outgrowth of breast cancer cells in the lung. Investigation into the signaling of LYPD3 revealed a novel function of this protein. This work and future mechanistic studies will elucidate the signaling of LYPD3, and as LYPD3 is expressed in numerous subtypes of advanced cancers, understanding its signaling could provide a new biomarker for cancers which would be amenable to the targeted therapies identified in these studies in combination with LYPD3 targeted therapies.

Plants commonly produce multiple, seemingly redundant defenses, but the reasons for this are poorly understood. The specificity of defenses to particular herbivores could drive investment in multiple defenses. Alternatively, genetic correlations between defenses could lead to their joint expression, even if possessing both defenses is non-adaptive. Plants may produce multiple defenses if putative resistance traits do not reduce damage, forcing plants to rely on tolerance of damage instead. Furthermore, resource shortages caused by herbivore damage could lead to compensatory changes in expression and selection on non-defense traits, such as floral traits. Natural selection could favor producing multiple defenses if synergism between defenses increases the benefits or decrease the costs of producing multiple defenses. Non-linear relationships between the costs and benefits of defense trait investment could also favor multiple defenses.

Passiflora incarnata (`maypop') is a perennial vine native to the southeast United States that produces both direct, physical traits (leaf toughness and trichomes) and rewards thought to function in indirect defense (extrafloral nectar in a defense mutualism with ants), along with tolerance of herbivore damage. I performed two year-long common garden experiments with clonal replicates of plants originating from two populations. I measured plant fitness, herbivore damage, and defense traits. I ran a genotypic selection analysis to determine if manipulating herbivore damage through a pesticide exclusion treatment presence mediated selection on floral traits, and if herbivore damage led to plastic changes in floral trait expression. To evaluate the role of selection in maintaining multiple defenses, I estimated fitness surfaces for pairwise combinations of defense traits and evaluated where the fitness optima were on each surface.

I found that resistance traits did not reduce herbivore damage, but plants demonstrated specific tolerance to different classes of herbivore damage. Tolerance was negatively correlated with resistance, raising the possibility that tolerance of herbivore damage instead of resistance may be the key defense in this plant, and that production of the two type of defense is constrained by underlying genetic architecture. Plants with higher levels of generalist beetle damage flowered earlier and produced proportionally more male flowers. I found linear selection for both earlier flowering and a lower proportion of male flowers in the herbivore exclusion treatment. I found that selection favored investment in multiple resistance traits. However, for two tolerance traits or one resistance and one tolerance trait, investment in only one trait was favored.

These results highlight the possibility of several mechanisms selecting for the expression of multiple traits, including non-defense traits. Resistance traits may have a non-defensive primary function in this plant, and tolerance may instead be a key defense strategy. These results also emphasize the need to consider the type of trait--resistance or tolerance--when making broad predictions about their joint expression.

The human epidermal growth factor receptor 2, or HER2, is overexpressed in 20-30% breast cancer patients and is associated with aggressive disease. Therapies targeting HER2, including monoclonal antibodies (trastuzumab and pertuzumab), a small molecule kinase inhibitor (lapatinib) and an antibody-drug conjugate (trastuzumab emtansine), have significantly prolonged the overall survival of HER2-positive breast cancer patients. However, almost all patients develop resistance either from the beginning of therapy or with prolonged treatment in two years.

Previous studies to unveil the resistance mechanisms were mainly focused on acquired resistance, culturing cells with HER2 inhibitors and making comparisons to their parental cells. In order to study the mechanism mediating intrinsic resistance, we conducted a loss-of-function genetic screen using a HER2-amplified cell line that is intrinsically resistant to HER2 inhibitors with the purpose to identify synthetic lethal targets. TALDO1, a gene encoding a metabolic enzyme in the non-oxidative pentose phosphate pathway was identified from the screen. Metabolic profiling with isotope-labeled glucose was used to understand the mechanism. The profiling results indicated that TALDO1 was necessary for cellular NADPH generation to combat increased cellular ROS and support synthesis of lipids as a result of HER2 inhibition.

Importantly, the higher expression of TALDO1 is associated with poor response to HER2-targeted therapy in a small cohort of HER2-positive breast cancer patients, suggesting it could potentially serve as a biomarker to predict patient response.

Together our study explained a novel mechanism mediating intrinsic resistance to HER2 inhibition with significant clinical value. Combined inhibition of HER2 signaling and the pentose phosphate pathway may result in a better clinical outcome.

Outer membrane vesicles are an important constitutive product of all Gram-negative bacteria. Bacteria have evolved many responses to alleviate all different types of stress. The primary objective of this dissertation is to investigate the role of outer membrane vesicles (OMVs) as a method by which Gram-negative bacteria can quickly act to protect themselves against particular threats. Generally, we find that stressors whose primary effect is on the outer membrane can be protected against by OMVs. Throughout this study, a variety of different microbiological and biochemical methods are used to answer key questions in the innate ability of OMVs to protect against particular antimicrobials. Using Escherichia coli as well as Pseudomonas aeruginosa as model organisms we tested the ability of purified vesicles from each species to protect themselves and other hosts. Using bacteriophage T4, we investigated the ability of OMVs purified from E. coli to adsorb phage as well as how this interaction affected the efficiency of infection. We found that OMVs are protective against antimicrobial peptides, as well as bacteriophage. In the course of understanding this protection we also observed and characterized the cross species effects of both OMV protection as well as phage infection. Where typically a phage infects a specific species, we found that T4 associated OMVs treating a non-native host P. aeruginosa resulted in the production of a novel prophage. Upon further examination, we determined that this induction was occurring via a novel pathway that we attempted to further characterize by performing a genetic screen to identify genes important to this induction. The work within this dissertation fully supports the hypothesis of a regulated response to outer membrane acting stimuli, resulting in the induction of vesiculation and the adsorption of stressor in the extra-cellular milieu. This model of protection agrees with the idea of a bacterial innate defense system, which acts in the short term before the adaptive response can fully occur, resulting in a bridge between the untreated to the treated and resistant culture.

In recent years, government aid agencies and international organizations have increased their financial commitments to controlling and eliminating malaria from the planet. This renewed emphasis on elimination is reminiscent of a previous worldwide campaign to eradicate malaria in the 1960s, a campaign which ultimately failed. To avoid a repeat of the past, mechanisms must be developed to sustain effective malaria control programs.

A number of sociobehavioral, economic, and biophysical challenges exist for sustainable malaria control, particularly in high-burden areas such as sub-Saharan Africa. Sociobehavioral challenges include maintaining high long-term levels of support for and participation in malaria control programs, at all levels of society. Reasons for the failure of the previous eradication campaign included a decline in donor, governmental, community, and household-level support for control programs, as malaria prevalence ebbed due in part to early successes of these programs.

Biophysical challenges for the sustainability of national malaria control programs (NMCPs) encompass evolutionary challenges in controlling the protozoan parasite and the mosquito vector, as well as volatile transmission dynamics which can lead to epidemics. Evolutionary challenges are particularly daunting due to the rapid generational turnover of both the parasites and the vectors: The reliance on a handful of insecticides and antimalarial drugs in NMCPs has placed significant selection pressures on vectors and parasites respectively, leading to a high prevalence of genetic mutations conferring resistance to these biocides.

The renewed global financing of malaria control makes research into how to effectively surmount these challenges arguably more salient now than ever. Economics has proven useful for addressing the sociobehavioral and biophysical challenges for malaria control. A necessary next step is the careful, detailed, and timely integration of economics with the natural sciences to maximize and sustain the impact of this financing.

In this dissertation, I focus on 4 of the challenges identified above: In the first chapter, I use optimal control and dynamic programming techniques to focus on the problem of insecticide resistance in malaria control, and to understand how different models of mosquito evolution can affect our policy prescriptions for dealing with the problem of insecticide resistance. I identify specific details of the biological model--the mechanisms for so-called "fitness costs" in insecticide-resistant mosquitoes--that affect the qualitative properties of the optimal control path. These qualitative differences carry over to large impacts on the economic costs of a given control plan.

In the 2nd chapter, I consider the interaction of parasite resistance to drugs and mosquito resistance to insecticides, and analyze cost-effective malaria control portfolios that balance these 2 dynamics. I construct a mathematical model of malaria transmission and evolutionary dynamics, and calibrate the model to baseline data from a rural Tanzanian district. Four interventions are jointly considered in the model: Insecticide-spraying, insecticide-treated net distribution, and the distribution of 2 antimalarial drugs--sulfadoxine pyramethamine (SP) and artemisinin-based combination therapies (ACTs). Strategies which coordinate vector controls and treatment protocols should provide significant gains, in part due to the issues of insecticide and drug resistance. In particular, conventional vector control and ACT use should be highly complementary, economically and in terms of disease reductions. The ongoing debate concerning the cost-effectiveness of ACTs should thus consider prevailing (and future) levels of conventional vector control methods, such as ITN and IRS: If the cost-effectiveness of widespread ACT distribution is called into question in a given locale, scaling up IRS and/or ITNs probably tilts the scale in favor of distributing ACTs.

In the 3rd chapter, I analyze results from a survey of northern Ugandan households I oversaw in November 2009. The aim of this survey was to assess respondents' perceptions about malaria risks, and mass indoor residual spraying (IRS) of insecticides that had been done there by government-sponsored health workers. Using stated preference methods--specifically, a discrete choice experiment (DCE)--I evaluate: (a) the elasticity of household participation levels in IRS programs with respect to malaria risk, and (b) households' perceived value of programs aimed at reducing malaria risk, such as IRS. Econometric results imply that the average respondent in the survey would be willing to forego a $10 increase in her assets for a permanent 1% reduction in malaria risk. Participation in previous IRS significantly increased the stated willingness to participate in future IRS programs. However, I also find that at least 20% of households in the region perceive significant transactions costs from IRS. One implication of this finding is that compensation for these transactions costs may be necessary to correct theorized public good aspects of malaria prevention via vector control.

In the 4th chapter, I further study these public goods aspects. To do so, I estimate a welfare-maximizing system of cash incentives. Using the econometric models estimated in the 3rd chapter, in conjunction with a modified version of the malaria transmission models developed and utilized in the first 2 chapters, I calculate village-specific incentives aimed at correcting under-provision of a public good--namely, malaria prevention. This under-provision arises from incentives for individual malaria prevention behavior--in this case the decision whether or not to participate in a given IRS round. The magnitude of this inefficiency is determined by the epidemiological model, which dictates the extent to which households' prevention decisions have spillover effects on neighbors.

I therefore compute the efficient incentives in a number of epidemiological contexts. I find that non-negligible monetary incentives for participating in IRS programs are warranted in situations where policymakers are confident that IRS can effectively reduce the incidence of malaria cases, and not just exposure rates. In these cases, I conclude that the use of economic incentives could reduce the incidence of malaria episodes by 5%--10%. Depending on the costs of implementing a system of incentives for IRS participation, such a system could provide an additional tool in the arsenal of malaria controls.