Biology subjects

Grunberger, A.

Publications and source records attributed to Grunberger, A..

3 recordsLinked to original sources

bioRxiv2023

Coupling Cell Size Regulation and Proliferation Dynamics of C.glutamicum Reveals Cell Division Based on Surface Area

Single cells actively coordinate growth and division to regulate their size, yet how this size homeostasis at the single-cell level propagates over multiple generations to impact clonal expansion remains fundamentally unexplored. Classical timer models for cell proliferation (where the duration of the cell cycle is an independent variable) predict that the stochastic variation in colony size will increase over time. In stark contrast, implementing size control according to adder strategy (where on average a fixed size added from cell birth to division) leads to colony size variations that eventually decay to zero. While these results assume a fixed size of the colony-initiating progenitor cell, further analysis reveals that the magnitude of the intercolony variation in population number is sensitive to heterogeneity in the initial cell size. We validate these predictions by tracking the growth of isogenic microcolonies of Corynebacterium glutamicum in microfluidic chambers. Approximating their cell shape to a capsule, we observe that the degree of random variability in cell size is different depending on whether the cell size is quantified as per length, surface area, or volume, but size control remains an adder regardless of these size metrics. A comparison of the observed variability in the colony population with predictions suggests that proliferation matches better with a cell division based on the cell surface. In summary, our integrated mathematical-experimental approach bridges the paradigms of single-cell size regulation and clonal expansion at the population levels. This innovative approach provides elucidation of the mechanisms of size homeostasis from the stochastic dynamics of colony size for rod-shaped microbes.

systems biology↗

bioRxiv2023

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, biomedicine...) where it tends to decrease the controllability of the cellular response. However, little is known about the diversification profiles that can be adopted by a cell population. We characterized the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Interestingly, our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. For quantifying the contribution of the switching cost on population dynamics, we built a stochastic model that allowed us to reproduce the dynamics observed experimentally and identified three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we used a cell-machine interface that we call the Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.

microbiology↗

bioRxiv2019

Segregostat: A novel concept to control phenotypic diversification dynamics on the example of Gram-negative bacteria

Controlling and managing the degree of phenotypic diversification of microbial populations is a challenging task. This task not only requires detailed knowledge regarding diversification mechanisms but also advances technical setups for the real-time analyses and control of population behavior on single-cell level. In this work, setup, design and operation of the so called segregostat is described which, in contrast to a traditional chemostats, allows the control of phenotypic diversification of microbial populations over time. Two exemplary case studies will be discussed, emphasizing the applicability and versatility of the proposed approach. In detail the phenotypic diversification of Eschericia coli or Pseudomonas putida based on monitoring membrane permeability will be controlled. We show that upon nutrient limitation, cell population tends to diversify into several subpopulations exhibiting distinct phenotypic (non-permeablized and permeablized cells). On-line analysis leads to the determination of the ratio between cells in these two states, which in turn trigger the addition of glucose pulses in order to maintain a pre-defined diversification ratio. These results prove that phenotypic diversification can be controlled by means of defined pulse-frequency modulation within continuously running bioreactor setups. This lays the foundation for systematic studies, not only of phenotypic diversification but also for all processes where dynamics single cell approaches are required, such as synthetic co-culture processes.

microbiology↗