Survival of Phenotypic Information during Cellular Growth Transitions

Comparison of cell mechanical measurements provided by Atomic Force Microscopy (AFM) and Micropipette Aspiration (MPA)

A comparative analysis of T-lymphocyte mechanical data obtained from Micropipette Aspiration (MPA) and Atomic Force Microscopy (AFM) is presented. Results obtained by fitting the experimental data to simple Hertz and Theret models led to non-Gaussian distributions and significantly different values of the elastic moduli obtained by both techniques. The use of more refined models, taking into account the finite size of cells (simplified double contact and Zhou models) reduces the differences in the values calculated for the elastic moduli. Several possible sources for the discrepancy between the techniques are considered. The analysis suggests that the local nature of AFM measurements compared with the more general character of MPA measurements probably contributed to the differences observed.

Lineage space and the propensity of bacterial cells to undergo growth transitions

The molecular makeup of the offspring of a dividing cell gradually becomes phenotypically decorrelated from the parent cell by noise and regulatory mechanisms that amplify phenotypic heterogeneity. Such regulatory mechanisms form networks that contain thresholds between phenotypes. Populations of cells can be poised near the threshold so that a subset of the population probabilistically undergoes the phenotypic transition. We sought to characterize the diversity of bacterial populations around a growth-modulating threshold via analysis of the effect of non-genetic inheritance, similar to conditions that create antibiotic-tolerant persister cells and other examples of bet hedging. Using simulations and experimental lineage data in Escherichia coli, we present evidence that regulation of growth amplifies the dependence of growth arrest on cellular lineage, causing clusters of related cells undergo growth arrest in certain conditions. Our simulations predict that lineage correlations and the sensitivity of growth to changes in toxin levels coincide in a critical regime. Below the critical regime, the sizes of related growth arrested clusters are distributed exponentially, while in the critical regime clusters sizes are more likely to become large. Furthermore, phenotypic diversity can be nearly as high as possible near the critical regime, but for most parameter values it falls far below the theoretical limit. We conclude that lineage information is indispensable for understanding regulation of cellular growth.

Programmed cell death can increase the efficacy of microbial bet -hedging

Programmed cell death (PCD) occurs in both unicellular and multicellular organisms. While PCD plays a key role in the development and maintenance of multicellular organisms, explaining why single-celled organisms would evolve to actively commit suicide has been far more challenging. Here, we explore the potential for PCD to act as an accessory to microbial bet-hedging strategies that utilize stochastic phenotype switching. We consider organisms that face unpredictable and recurring disasters, in which fitness depends on effective phenotypic diversification. We show that when reproductive opportunities are limited by carrying capacity, PCD drives population turnover, providing increased opportunities for phenotypic diversification through stochastic phenotype switching. The main cost of PCD, providing resources for growth to a PCD(−) competitor, is ameliorated by genetic assortment in spatially structured populations. Using agent -based simulations, we explore how basic demographic factors, namely bottlenecks and local dispersal, can generate sufficient spatial structure to favor the evolution of high PCD rates.