Modelling Resistance Evolution – Theoretical Methodology Symposium

Session

Poster Session

27 Apr 2023, 18:00

Lecture Hall (MPI for Evolutionary Biology)

38. A network model for the growth of a bacterial population in adverse environments

Moitrish Majumdar (International Centre for Theoretical Sciences)

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...

40. Establishment threshold and the inference of establishment rates along a concentration gradient

Teemu Kuosmanen (Department of Computer Science, University of Helsinki)

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,...

24. Integrated in vitro/in silico approach towards a quantitative understanding of killing behaviour and resistance evolution dynamics of antibiotic combinations

Nicole Zimmermann (Freie Universität Berlin)

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...

35. Mathematical modelling of effector T cell stimulation, elimination and binding with target cells

Qianci Yang (MPI for Evolutionary Biology)

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...

25. Mechanistic pharmacokinetic/pharmacodynamic understanding of the antibiotic therapy of piperacillin and tazobactam and its role in resistance development

Malin Andersson (Freie Universität Berlin)

• combining in vitro and in silico approaches

Worldwide, an increase in spread of extended spectrum ß-lactamases (ESBL) producing Escherichia coli, is threating the public health. Piperacillin/tazobactam (PIP/TAZ) is a widely used antibacterial combination therapy and could be a valuable alternative to the carbapenems, which are the first line therapeutic option against ESBL producing...

39. Modeling collateral sensitivity-based treatments to suppress antibiotic resistance in Streptococcus pneumoniae

Sebastian Tandar (Leiden University)

Introduction Collateral sensitivity (CS) offers a strategy to counter antibiotic resistance, where resistance to one antibiotic collaterally increases the sensitivity towards another antibiotic agent. The clinical relevance and applicability of CS-based treatments remains unclear. Key factors which could determine the clinical relevance and application of CS-based treatments include: (i)...

36. Modelling growth of pancreatic cancer cell lines and unveiling treatment effects

Henrike Hedrich (MPI for Evolutionary Biology)

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...

34. On the role of deleterious mutant regime in steering long-term evolution

Nikhil Sharma (MPI for Evolutionary Biology)

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...

42. Persistence and resistance evolution in weeds with complex life cycle

Dana Lauenroth (MPI for Evolutionary Biology)

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...

30. Pharmacodynamics of inter-species interactions in polymicrobial infections

Catharina Meyer (Quantitative Pharmacology, Leiden University)

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...

41. Predicting the time to relapse for individual patients with glioblastoma for optimising the second line treatment

Pejman Shojaee (TU Dresden)

Glioblastoma (GBM) is a malignant diffusive brain tumor with a poor prognosis and a low survival rate despite conventional cancer treatments. In this research, we aim to estimate the time to relapse for the proliferation of marginal cells after resection at the tumor edge until they reach the maximum density detection threshold of MR images. We also considered the role of tumor-associated...

32. Role of bacterial filamentation in population dynamics at sub-MIC concentrations of cefotaxime

Rotem Gross (Institute for Biological Physics University of Cologne )

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....

37. Stochastic modelling of lineage correlations in glioblastoma cells to capture non-genetic heterogeneity

Peter Embacher (UCL)

Glioblastoma is one of the most aggressive and difficult to treat cancers. One obstacle to developing effective and widely applicable treatments is the high level of heterogeneity both between patients and within a single tumour. The observed variability in treatment response even in genetically identical cells could be random due to the inherent stochasticity of gene regulation or...

33. Towards rational design of antibiotic therapies: a mechanistic approach.

Elena Pascual Garcia (Potsdam University)

Antimicrobial resistance is on the rise globally. Increased levels of resistance have been reported across bacterial strains and antibiotic compounds. In order to better target resistant bacteria, understanding the relationship between drug susceptibility and bacterial physiology is key. Here we present a mechanistic modelling approach to quantitatively predict antibiotic effect on bacterial...