Bacterial growth environment strongly influences the efficacy of antibiotic treatment, with slow growth often being associated with decreased susceptibility. Yet in many cases, the connection between antibiotic susceptibility and pathogen physiology remains unclear. We show that for ribosome-targeting antibiotics acting on Escherichia coli, a complex interplay exists between physiology and antibiotic action; for some antibiotics within this class, faster growth indeed increases susceptibility, but for other antibiotics, the opposite is true. Remarkably, these observations can be explained by a simple mathematical model that combines drug transport and binding with physiological constraints. Our model reveals that growth-dependent susceptibility is controlled by a single parameter characterizing the ‘reversibility’ of ribosome-targeting antibiotic transport and binding. This parameter provides a spectrum classification of antibiotic growth-dependent efficacy that appears to correspond at its extremes to existing binary classification schemes. In these limits, the model predicts universal, parameter-free limiting forms for growth inhibition curves. The model also leads to non-trivial predictions for the drug susceptibility of a translation mutant strain of E. coli, which we verify experimentally. Drug action and bacterial metabolism are mechanistically complex; nevertheless, this study illustrates how coarse-grained models can be used to integrate pathogen physiology into drug design and treatment strategies.

Multiple cancers may arise from within a clonal region of preneoplastic epithelium, a phenomenon termed 'field change'. However, it is not known how field change develops. Here we investigate this question using lineage tracing to track the behaviour of scattered single oesophageal epithelial progenitor cells expressing a mutation that inhibits the Notch signalling pathway. Notch is frequently subject to inactivating mutation in squamous cancers. Quantitative analysis reveals that cell divisions that produce two differentiated daughters are absent from mutant progenitors. As a result, mutant clones are no longer lost by differentiation and become functionally immortal. Furthermore, mutant cells promote the differentiation of neighbouring wild-type cells, which are then lost from the tissue. These effects lead to clonal expansion, with mutant cells eventually replacing the entire epithelium. Notch inhibition in progenitors carrying p53 stabilizing mutations creates large confluent regions of doubly mutant epithelium. Field change is thus a consequence of imbalanced differentiation in individual progenitor cells.

Drug gradients are believed to play an important role in the evolution of bacteria resistant to antibiotics and tumors resistant to anticancer drugs. We use a statistical physics model to study the evolution of a population of malignant cells exposed to drug gradients, where drug resistance emerges via a mutational pathway involving multiple mutations. We show that a nonuniform drug distribution has the potential to accelerate the emergence of resistance when the mutational pathway involves a long sequence of mutants with increasing resistance, but if the pathway is short or crosses a fitness valley, the evolution of resistance may actually be slowed down by drug gradients. These predictions can be verified experimentally, and may help to improve strategies for combating the emergence of resistance.

We introduce a mean-field theoretical framework to describe multiple totally asymmetric simple exclusion processes (TASEPs) with different lattice lengths and entry and exit rates, competing for a finite reservoir of particles. We present relations for the partitioning of particles between the reservoir and the lattices: These relations allow us to show that competition for particles can have nontrivial effects on the phase behavior of individual lattices. For a system with nonidentical lattices, we find that when a subset of lattices undergoes a phase transition from low to high density, the entire set of lattice currents becomes independent of total particle number. We generalize our approach to systems with a continuous distribution of lattice parameters, for which we demonstrate that measurements of the current carried by a single lattice type can be used to extract the entire distribution of lattice parameters. Our approach applies to populations of TASEPs with any distribution of lattice parameters and could easily be extended beyond the mean-field case.

To maintain cycling adult tissue in homeostasis the balance between proliferation and differentiation of stem cells needs to be precisely regulated. To investigate how stem cells achieve perfect self-renewal, emphasis has been placed on models in which stem cells progress sequentially through a one-way proliferative hierarchy. However, investigations of tissue regeneration have revealed a surprising degree of flexibility, with cells normally committed to differentiation able to recover stem cell competence following injury. Here, we investigate whether the reversible transfer of cells between states poised for proliferation or differentiation may provide a viable mechanism for a heterogeneous stem cell population to maintain homeostasis even under normal physiological conditions. By addressing the clonal dynamics, we show that such models of "dynamic heterogeneity" may be equally capable of describing the results of recent lineage tracing assays involving epithelial tissues. Moreover, together with competition for limited niche access, such models may provide a mechanism to render tissue homeostasis robust. In particular, in 2D epithelial layers, we show that the mechanism of dynamic heterogeneity avoids some pathological dependencies that undermine models based on a hierarchical stem/progenitor organization.

We investigate the totally asymmetric simple exclusion process (TASEP) in the presence of a bottleneck, i.e. a sequence of consecutive defect sites with reduced hopping rate. The influence of such a bottleneck on the phase diagram is studied by computer simulations and a novel analytical approach. We find a clear dependence of the current and the properties of the phase diagram not only on the length of the bottleneck, but also on its position. For bottlenecks near the boundaries, this motivates the concept of effective boundary rates. Furthermore the inclusion of a second, smaller bottleneck far from the first one has no influence on the transport capacity. These results will form the basis of an effective description of the disordered TASEP and are relevant for the modelling of protein synthesis or intracellular transport systems where the motion of molecular motors is hindered by immobile blocking molecules.Comment: accepted by Physica

Understanding the cellular mechanisms of tumour growth is key for designing rational anti-cancer treatment. Here we used genetic lineage tracing to quantify cell behaviour during neoplastic transformation in a model of oesophageal carcinogenesis. We found that cell behaviour was convergent across premalignant tumours, which contained a single proliferating cell population. The rate of cell division was not significantly different in the lesions and the surrounding epithelium. However, dividing tumour cells had a uniform, small bias in cell fate so that, on average, slightly more dividing than non-dividing daughter cells were generated at each round of cell division. In invasive cancers induced by Kras G12D expression, dividing cell fate became more strongly biased towards producing dividing over non-dividing cells in a subset of clones. These observations argue that agents that restore the balance of cell fate may prove effective in checking tumour growth, whereas those targeting proliferation may show little selectivity.

In eukaryotic cells, many motor proteins can move simultaneously on a single microtubule track. This leads to interesting collective phenomena like jamming. Recently we reported (Phys. Rev. Lett. 95, 118101 (2005)) a lattice-gas model which describes traffic of unconventional (single-headed) kinesins KIF1A. Here we generalize this model, introducing a novel interaction parameter c, to account for an interesting mechano-chemical process which has not been considered in any earlier model. We have been able to extract all the parameters of the model, except c, from experimentally measured quantities. In contrast to earlier models of intra-cellular molecular motor traffic, our model assigns distinct "chemical" (or, conformational) states to each kinesin to account for the hydrolysis of ATP, the chemical fuel of the motor. Our model makes experimentally testable theoretical predictions. We determine the phase diagram of the model in planes spanned by experimentally controllable parameters, namely, the concentrations of kinesins and ATP. Furthermore, the phaseseparated regime is studied in some detail using analytical methods and simulations to determine e.g. the position of shocks. Comparison of our theoretical predictions with experimental results is expected to elucidate the nature of the mechano-chemical process captured by the parameter c.