Stochasticity affects several steps in the evolution of resistance. The appearance of resistant types by mutation or transfer of resistance genes from a source population is a stochastic process. Once resistant types have appeared, they might suffer stochastic loss while rare. During the infection, bottleneck events can lead to further randomness in the dynamics of resistant pathogens....
Bacterial persistence plays a crucial role in determining the number of surviving cells after antibiotic exposure, thereby having an important effect on the effectiveness of antibiotic treatment. Recent evidence suggests that the persister phenotype may also influence the evolvability of antibiotic resistance. The most common hypothesis to explain this link is that persistence leads to a...
We are interested in modelling Collective antibiotic tolerance (CAT). CAT occurs any time a bacterial population of sufficiently high density survives an antibiotic dose or treatment that a smaller population would succumb to. Various mechanisms have been identified, including cell-to-cell signalling and antibiotic degradation. A known manifestation of CAT is through occurrence of inoculum...
Antibiotic resistance genes are frequently carried on bacterial plasmids. Because plasmids exist in multiple copies in the host bacterial cell, distinct plasmid copies can carry distinct alleles, allowing for heterozygosity not possible for loci on haploid bacterial chromosomes. This plasmid-mediated heterozygosity of antibiotic resistance alleles can produce multidrug resistance, in which a...
Evolution in changing environments is still poorly understood. We analyze a recently introduced and empirically well-grounded model for antibiotic resistance evolution in bacteria [1]. In this model the corresponding fitness landscape changes with the antibiotic concentration, thereby giving rise to tradeoffs between adaptation to low and high antibiotic concentrations. We show that the...
Tumors are typically comprised of heterogeneous cell populations exhibiting diverse phenotypes. This heterogeneity, which is correlated with tumor aggressiveness and treatment-failure, confounds current drug screening efforts to identify effective candidate therapies for individual tumors. In the first part of the talk I will present a modeling-driven statistical framework that enables the...
Many pathogenic cellular populations, such as microbial biofilms or solid tumours, are densely packed. However, little is known about how growth-induced collective dynamics - an inherent feature of these systems - reshape the evolution of resistance against antibiotic or anti-cancer therapy. Modelling such emergent phenomena, coupling the mechanical interactions of individual cells to...
Populations of microbial pathogens or cancer cells possess enormous adaptive potential. Such adaptations regularly lead to the failure of treatment, with drastic consequences for individual and public health. From a reductionistic viewpoint, the fundamental processes in such microbial populations are replication, mutation and death. Characterizing these processes by traits allows us to...
Ecological vs. game theoretical models for interaction Both ecologists and evolutionary game theorists study the dynamics in populations of interacting types. Ecologists prefer to use the Lotka-Volterra equations (and non linear generalizations of it), while evolutionary game theorists use the replicator dynamics instead. In their book, Josef Hofbauer and Karl Sigmund have shown that these two...
In initially drug-sensitive populations of pathogens or cancerous cells, resistance emerges during drug treatment in some, but not all, populations. This observation of variable outcomes motivates the use of stochastic mathematical models to describe and predict de novo evolution of resistance. Both rate of appearance and fate of resistant mutants depend on the environment, which varies over...
To alleviate the threat of antimicrobial resistance (AMR), innovative treatment strategies are urgently needed. The phenomenon of collateral sensitivity (CS) may be exploited to achieve this goal using existing antibiotics. CS occurs when resistance to one antibiotic increases the sensitivity to another antibiotic. CS-based combination treatments could potentially suppress resistance, but it...
The evolution of drug resistance in infectious disease and cancer is a serious threat to public health. The mutant selection window (MSW), defined as the range of drug concentrations that selects for a drug resistant strain, has previously been used as a model to predict and avoid resistance. Under the MSW paradigm, drug regimens should be designed to minimize time spent in the MSW. A...
Plasticity and Genetic Evolution
Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching...
Development of therapeutic resistance in cancer is typically attributed to natural selection, where a cytotoxic agent eliminates sensitive cells in the population, leaving behind only the resistant ones. However, it appears that non-genetic mechanisms of therapeutic resistance exist as well, and as such they may be reversible through better understanding of underlying biology. Here we discuss...
Tumors are not just collections of mutated cells, they are complex ecosystems of interacting clones and host elements. This type of system is well known to theoretical ecologists, who have been using mathematical models to understand, and even bias, naturally occurring systems like fisheries and game reserves. In this spirit, we have been working to develop mathematical models to describe...
Both bacterial and helminth infections are commonly treatable by suitable drugs. However, these pathogens are constantly evolving ways to escape drug treatment.
Bacteria often protect themselves by forming biofilms - high-density colonies attached to a surface or each other. Such a sedentary lifestyle of biofilm cells comes associated with costs and benefits. While the growth rate of biofilm...
Recent experiments on the evolution of drug resistance in bacteria have identified a transition from the preferred substitution of high-rate, low-effect mutations to low-rate, high-effect mutations with increasing population size [1]. The greater mutation supply in large populations increases the probability for rare high-effect mutations to arise, which subsequently outcompete the more...
Understanding the evolution of antimicrobial resistance is central for their treatment. In this talk, I want to show a possible way to address this problem from a statistical point of view, namely the hypercubic inference, which we developed and introduced during the last years at the University of Bergen. The basis of this model is a hypercubic transition graph, whose nodes represent possible...
Despite rapid initial responses and low toxicity, targeted therapies commonly fail to provide long-term benefits to cancer patients due to the development of therapy resistance. In multiple solid tumors, this resistance emerges due to gradual, multifactorial adaptation, i.e., a selective process combining genetic and non-genetic methods of cell diversification. This suggests a significant link...
The repeatability of evolution depends strongly on the distribution of fitness effects (DFE) of beneficial mutations. While theoretical modeling has focused mainly on light-tailed DFEs, experiments on antibiotic resistance evolution have also uncovered signatures of heavy-tailed DFEs. We show that in the latter case the repeatability behaves in counter-intuitive ways. Firstly, the evolutionary...
When multiple antibiotics are combined, they can interact in diverse and difficult-to-predict ways. Two antibiotics may synergize or antagonize, inhibiting bacterial growth more or less than expected. Such drug interactions can strongly influence the dynamics of resistance evolution and, in extreme cases, lead to selection against drug resistance. I will present how drug interactions are...
Bacterial populations can consist of several isogenic subpopulations known as phenotypes. Individuals in a bacterial population can switch from one phenotype to another in order to adapt to changing environments. Phenotypic switching can thus confer survival benefits to a bacterial population and may be a mechanism for the development of antibiotic resistance. Kussell and Leibler in...
Evolution of drug resistance is contingent on sufficient mutational supply as well as successful establishment of the initially rare resistant cells that are subject to stochastic extinction. Importantly, the potential for resistance evolution strongly depends on the drug concentration that not only directly affects the strength of selection, but also impacts the required mutational targets,...
Background: Fosfomycin is an old “forgotten” antibiotic that is effective against both multi-drug resistant Gram-positive and Gram-negative bacteria. In order to prevent the emergence and spread of resistances, fosfomycin is often used in combination with other antibiotics, e.g. amikacin. However, the design of effective combination therapies requires a comprehensive understanding of the...
In immune-oncology, the lifecycle, engagement, and cytotoxicity of natural or engineered T cells are important dynamical processes that need to be quantified to better understand cancer resistance and susceptibility to immunotherapy. We investigate the process of naïve and memory T cells engaging antigen-presenting cells to be activated to proliferate and differentiate to effector cells. In...
In vitro experiments are an important tool in cancer research to understand the growth of cancer cells and their response to chemotherapeutic treatment. Mathematical models facilitate the analysis of the obtained experimental data and can increase our understanding of cancer cell dynamics.
Using confluence time series capturing the in vitro growth of pancreatic cancer cell lines treated with...
Evolutionary Graph Theory (EGT) aims to understand the interplay of natural selection and genetic drift in spatial structures. A spatial structure is modelled as a graph with nodes representing asexually reproducing individuals, and edges dictate the interaction among these individuals. Based on the fixation probabilities of mutants on graphs, graphs are mainly categorised as amplifiers of...
Weeds are a major threat to crop production, causing the highest potential yield losses.Already since the late 1960s conventional agriculture has primarily relied on the application of herbicides for controlling weeds.However, the number of available herbicides is limited and they often share the same mode of action. The overuse of those active ingredients has led to the widespread evolution...
The antibiotic response of bacterial pathogens can be altered by interactions with other species of bacteria which have been suggested as a cause for treatment failure and resistance development in polymicrobial infections. This study aims to investigate the influence of interspecies interactions on the pharmacodynamics of antibiotics which may guide design of treatment strategies. We...
Treating Escherichia coli with the antibiotic cefotaxime at sub-MIC concentrations leads to complex responses: (i) filamentation of cells, which is known to be related to delayed lysis and enhanced antibiotic tolerance, (ii) higher biomass growth rates at intermediate antibiotic concentrations, and (iii) increased stochastic variation of the growth rate with growing antibiotic concentrations....
