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Register a new userMacroscopic Kinetic Effect of Cell-to-Cell Variation in Biochemical Reactions
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Genetically identical cells under the same environmental conditions can show strong variations in protein copy numbers due to inherently stochastic events in individual cells. We here develop a theoretical framework to address how variations in enzyme abundance affect the collective kinetics of metabolic reactions observed within a population of cells. Kinetic parameters measured at the cell population level are shown to be systematically deviated from those of single cells, even within populations of homogeneous parameters. Because of these considerations, Michaelis-Menten kinetics can even be inappropriate to apply at the population level. Our findings elucidate a novel origin of discrepancy between in vivo and in vitro kinetics, and offer potential utility for analysis of single-cell metabolomic data.
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Induced effects by direct exposure to ionizing radiation (IR) are a central issue in many fields like radiation protection, clinic diagnosis and oncological therapies. Direct irradiation at certain doses induce cell death, but similar effects can also occur in cells no directly exposed to IR, a mechanism known as bystander effect. Non-IR (radiofrequency waves) can induce the death of cells loaded with MNPs in a focused oncological therapy known as magnetic hyperthermia. Indirect mechanisms are also able to induce the death of unloaded MNPs cells. Using in vitro cell models, we found that colocalization of the MNPs at the lysosomes and the non-increase of the temperature induces bystander effect under non-IR. Our results provide a landscape in which bystander effects are a more general mechanism, up to now only observed and clinically used in the field of radiotherapy.
The internal cell wall structure of the bacterium Lactobacillus helveticus has been observed in situ in aqueous solution using an atomic force microscope (AFM). The AFM tip was used not only for imaging but presumably to remove mechanically large patches of the outer cell wall after appropriate chemical treatment, which typically leaves the bacteria alive. The surface exposed after such a surgery revealed ca. 26 nm thick twisted strands within the cell wall. The structure and location of the observed strands are consistent with the glycan backbone of peptidoglycan fibers that give strength to the cell wall. The found structural organization of these fibers has not been observed previously.
In this article, we study the kinetics of reversible ligand binding to receptors on a spherical cell surface using a self-consistent stochastic theory. Binding, dissociation, diffusion and rebinding of ligands are incorporated into the theory in a systematic manner. We derive explicitly the time evolution of the ligand-bound receptor fraction p(t) in various regimes . Contrary to the commonly accepted view, we find that the well-known Berg-Purcell scaling for the association rate is modified as a function of time. Specifically, the effective on-rate changes non-monotonically as a function of time and equals the intrinsic rate at very early as well as late times, while being approximately equal to the Berg-Purcell value at intermediate times. The effective dissociation rate, as it appears in the binding curve or measured in a dissociation experiment, is strongly modified by rebinding events and assumes the Berg-Purcell value except at very late times, where the decay is algebraic and not exponential. In equilibrium, the ligand concentration everywhere in the solution is the same and equals its spatial mean, thus ensuring that there is no depletion in the vicinity of the cell. Implications of our results for binding experiments and numerical simulations of ligand-receptor systems are also discussed.
It is known that mechanical interactions couple a cell to its neighbors, enabling a feedback loop to regulate tissue growth. However, the interplay between cell-cell adhesion strength, local cell density and force fluctuations in regulating cell proliferation is poorly understood. Here, we show that spatial variations in the tumor growth rates, which depend on the location of cells within tissue spheroids, are strongly influenced by cell-cell adhesion. As the strength of the cell-cell adhesion increases, intercellular pressure initially decreases, enabling dormant cells to more readily enter into a proliferative state. We identify an optimal cell-cell adhesion regime where pressure on a cell is a minimum, allowing for maximum proliferation. We use a theoretical model to validate this novel collective feedback mechanism coupling adhesion strength, local stress fluctuations and proliferation.Our results, predicting the existence of a non-monotonic proliferation behavior as a function of adhesion strength, are consistent with experimental results. Several experimental implications of the proposed role of cell-cell adhesion in proliferation are quantified, making our model predictions amenable to further experimental scrutiny. We show that the mechanism of contact inhibition of proliferation, based on a pressure-adhesion feedback loop, serves as a unifying mechanism to understand the role of cell-cell adhesion in proliferation.
We study the liquid-liquid phase separation (LLPS) of a cell-free transcription-translation (TXTL) system. When the TXTL reaction, composed of a large amount of proteins, is concentrated, the uniformly mixed state becomes unstable and membrane-less droplets form spontaneously. This LLPS droplet formation can be induced when the TXTL reaction is enclosed in water-in-oil emulsion droplets in which water evaporates (dehydration) from the surface. As the emulsion droplets shrink, smaller LLPS droplets appear inside the emulsion droplets and coalesce into phase-separated domains that partition the location of proteins. We show that the LLPS in the emulsion droplets can be accelerated by interfacial drift in the outer oil phase. This further provides an experimental platform for studying the interplay between biological reactions and intracellular phase separation.
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