Selection for rapid uptake of scarce or fluctuating resource explains vulnerability of glycolysis to imbalance

Glycolysis is a conserved central pathway in energy metabolism that converts glucose to pyruvate with net production of two ATP molecules. Because ATP is produced only in the lower part of glycolysis (LG), preceded by an initial investment of ATP in the upper glycolysis (UG), achieving robust start-up of the pathway upon activation presents a challenge: a sudden increase in glucose concentration can throw a cell into a self-sustaining imbalanced state in which UG outpaces LG, glycolytic intermediates accumulate and the cell is unable to maintain high ATP concentration needed to support cellular functions. Such metabolic imbalance can result in "substrate-accelerated death", a phenomenon observed in prokaryotes and eukaryotes when cells are exposed to an excess of substrate that previously limited growth. Here, we address why evolution has apparently not eliminated such a costly vulnerability and propose that it is a manifestation of an evolutionary trade-off, whereby the glycolysis pathway is adapted to quickly secure scarce or fluctuating resource at the expense of vulnerability in an environment with ample resource. To corroborate this idea, we perform individual-based eco-evolutionary simulations of a simplified yeast glycolysis pathway consisting of UG, LG, phosphate transport between a vacuole and a cytosol, and a general ATP demand reaction. The pathway is evolved in constant or fluctuating resource environments by allowing mutations that affect the (maximum) reaction rate constants, reflecting changing expression levels of different glycolytic enzymes. We demonstrate that under limited constant resource, populations evolve to a genotype that exhibits balanced dynamics in the environment it evolved in, but strongly imbalanced dynamics under ample resource conditions. Furthermore, when resource availability is fluctuating, imbalanced dynamics confers a fitness advantage over balanced dynamics: when glucose is abundant, imbalanced pathways can quickly accumulate the glycolytic intermediate FBP as intracellular storage that is used during periods of starvation to maintain high ATP concentration needed for growth. Our model further predicts that in fluctuating environments, competition for glucose can result in stable coexistence of balanced and imbalanced cells, as well as repeated cycles of population crashes and recoveries that depend on such polymorphism. Overall, we demonstrate the importance of ecological and evolutionary arguments for understanding seemingly maladaptive aspects of cellular metabolism

Del MA al mar. El museo de la historia de Andalucía

Un edificio fuerte y radical evocará en su seno la semblanza de una comunidad con un rico pasado cultural que se proyecta hacia el futuro. El arquitecto explica las claves de este centro, levantado en Granada

Effect of long-range guiding forces on cell movement patterns in a low-density population.

<p>Initial configuration of cells is random, as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004213#pcbi.1004213.g002" target="_blank">Fig 2A</a>. (A) Final configuration of a population of rigid cells at 6 h. Color indicates speed of individual cells, μm·min⁻¹. (B) Strain energies due to cell overlap in population of rigid cells, J. (C) Final configuration of a population of flexible cells at 6 h. Color indicates speed of individual cells (see colorbar in (A), μm·min⁻¹).</p

Short-range guiding forces between two cells in the model.

<p>Only the leading pole (“head”) of one cell (left) and the trailing pole (“tail”) of another cell (right) are shown. For clarity, the distance between the head and the tail of interacting bacteria is exaggerated. Numbering of line segments <b><i>Q</i></b> that connect adjacent particles on the same bacterium is shown for the case of engine direction <i>k</i>^e = 1 (see text and [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004213#pcbi.1004213.ref034" target="_blank">34</a>] for notation and a detailed explanation of collision resolution algorithm). <i>W</i> is cell width, and <i>d</i> is the distance between head and tail particles of interacting bacteria.</p

Effect of short-range guiding forces on cell movement patterns in a low-density population of flexible cells.

<p>(A) Initial random cell configuration. (B-E) Final configuration of a population at 6 h (B) non-guided cells, (C) cells with passive following, (D) cells with active following, (E) cells with head-to-tail adhesion. In (A-E) color indicates speed of individual cells (colorbar at the bottom left, μm·min⁻¹). (F) Strain energies due to cell overlap in circular aggregates of cells with active following (colorbar at the bottom right, J).</p

Effect of short-range guiding forces on cell movement patterns in a high-density population of flexible cells.

<p>(A) Initial configuration. Cells are aligned, but oriented randomly. (B). Final configuration of a population of non-guided cells at 3 h. (C). Final configuration of a population of cells with active following at 3 h. Color indicates speed of individual cells (colorbar at the bottom, μm·min⁻¹).</p

Cell Flexibility Affects the Alignment of Model Myxobacteria

Myxobacteria are social bacteria that exhibit a complex life cycle culminating in the development of multicellular fruiting bodies. The alignment of rod-shaped myxobacteria cells within populations is crucial for development to proceed. It has been suggested that myxobacteria align due to mechanical interactions between gliding cells and that cell flexibility facilitates reorientation of cells upon mechanical contact. However, these suggestions have not been based on experimental or theoretical evidence. Here we created a computational mass-spring model of a flexible rod-shaped cell that glides on a substratum periodically reversing direction. The model was formulated in terms of experimentally measurable mechanical parameters, such as engine force, bending stiffness, and drag coefficient. We investigated how cell flexibility and motility engine type affected the pattern of cell gliding and the alignment of a population of 500 mechanically interacting cells. It was found that a flexible cell powered by engine force at the rear of the cell, as suggested by the slime extrusion hypothesis for myxobacteria motility engine, would not be able to glide in the direction of its long axis. A population of rigid reversing cells could indeed align due to mechanical interactions between cells, but cell flexibility impaired the alignment

Compartment Volume Influences Microtubule Dynamic Instability: A Model Study

Microtubules (MTs) are cytoskeletal polymers that exhibit dynamic instability, the random alternation between growth and shrinkage. MT dynamic instability plays an essential role in cell development, division, and motility. To investigate dynamic instability, simulation models have been widely used. However, conditions under which the concentration of free tubulin fluctuates as a result of growing or shrinking MTs have not been studied before. Such conditions can arise, for example, in small compartments, such as neuronal growth cones. Here we investigate by means of computational modeling how concentration fluctuations caused by growing and shrinking MTs affect dynamic instability. We show that these fluctuations shorten MT growth and shrinkage times and change their distributions from exponential to non-exponential, gamma-like. Gamma-like distributions of MT growth and shrinkage times, which allow optimal stochastic searching by MTs, have been observed in various cell types and are believed to require structural changes in the MT during growth or shrinkage. Our results, however, show that these distributions can already arise as a result of fluctuations in the concentration of free tubulin due to growing and shrinking MTs. Such fluctuations are possible not only in small compartments but also when tubulin diffusion is slow or when many MTs (de)polymerize synchronously. Volume and all other factors that influence these fluctuations can affect MT dynamic instability and, consequently, the processes that depend on it, such as neuronal growth cone behavior and cell motility in general