A prion accelerates proliferation at the expense of lifespan.

In fluctuating environments, switching between different growth strategies, such as those affecting cell size and proliferation, can be advantageous to an organism. Trade-offs arise, however. Mechanisms that aberrantly increase cell size or proliferation-such as mutations or chemicals that interfere with growth regulatory pathways-can also shorten lifespan. Here we report a natural example of how the interplay between growth and lifespan can be epigenetically controlled. We find that a highly conserved RNA-modifying enzyme, the pseudouridine synthase Pus4/TruB, can act as a prion, endowing yeast with greater proliferation rates at the cost of a shortened lifespan. Cells harboring the prion grow larger and exhibit altered protein synthesis. This epigenetic state, [BIG+] (better in growth), allows cells to heritably yet reversibly alter their translational program, leading to the differential synthesis of dozens of proteins, including many that regulate proliferation and aging. Our data reveal a new role for prion-based control of an RNA-modifying enzyme in driving heritable epigenetic states that transform cell growth and survival.

Cells make different proteins to perform different tasks. Each protein is a long chain of building blocks called amino acids that must fold into a particular shape before it can be useful. Some proteins can fold in more than one way, a normal form and a 'prion' form. Prions are unusual in that they can force normally folded proteins with the same amino acid sequence as them to refold into new prions. This means that a single prion can make many more that are inherited when cells divide. Some prions can cause disease, but others may be beneficial. Pus4 is a yeast protein that is typically involved in modifying ribonucleic acids, molecules that help translate genetic information into new proteins. Sometimes Pus4 can adopt a beneficial prion conformation called [BIG⁺]. When yeast cells have access to plenty of nutrients, [BIG⁺] helps them grow faster and larger, but this comes at the cost of a shorter lifespan. Garcia, Campbell et al. combined computational modeling and experiments in baker's yeast (Saccharomyces cerevisiae) to investigate the role of [BIG⁺]. They found that the prion accelerated protein production, leading to both faster growth and a shorter lifespan in these cells, even without any changes in gene sequence. Garcia, Campbell et al.'s findings explain the beneficial activity of prion proteins in baker's yeast cells. The results also describe how cells balance a tradeoff between growth and lifespan without any changes in the genome. This helps to highlight that genetics do not always explain the behaviors of cells, and further methods are needed to better understand cell biology.

pH biosensing in the plant apoplast-a focus on root cell elongation.

The pH parameter of soil plays a key role for plant nutrition as it is affecting the availability of minerals and consequently determines plant growth. Although the mechanisms by which root perceive the external pH is still unknown, the impact of external pH on tissue growth has been widely studied especially in hypocotyl and root. Thanks to technological development of cell imaging and fluorescent sensors, we can now monitor pH in real time with at subcellular definition. In this focus, fluorescent dye-based, as well as genetically-encoded pH indicators are discussed especially with respect to their ability to monitor acidic pH in the context of primary root. The notion of apoplastic subdomains is discussed and suggestions are made to develop fluorescent indicators for pH values below 5.0.

A mathematical and computational approach for integrating the major sources of cell population heterogeneity.

Several approaches have been used in the past to model heterogeneity in bacterial cell populations, with each approach focusing on different source(s) of heterogeneity. However, a holistic approach that integrates all the major sources into a comprehensive framework applicable to cell populations is still lacking. In this work we present the mathematical formulation of a cell population master equation (CPME) that describes cell population dynamics and takes into account the major sources of heterogeneity, namely stochasticity in reaction, DNA-duplication, and division, as well as the random partitioning of species contents into the two daughter cells. The formulation also takes into account cell growth and respects the discrete nature of the molecular contents and cell numbers. We further develop a Monte Carlo algorithm for the simulation of the stochastic processes considered here. To benchmark our new framework, we first use it to quantify the effect of each source of heterogeneity on the intrinsic and the extrinsic phenotypic variability for the well-known two-promoter system used experimentally by Elowitz et al. (2002). We finally apply our framework to a more complicated system and demonstrate how the interplay between noisy gene expression and growth inhibition due to protein accumulation at the single cell level can result in complex behavior at the cell population level. The generality of our framework makes it suitable for studying a vast array of artificial and natural genetic networks. Using our Monte Carlo algorithm, cell population distributions can be predicted for the genetic architecture of interest, thereby quantifying the effect of stochasticity in intracellular reactions or the variability in the rate of physiological processes such as growth and division. Such in silico experiments can give insight into the behavior of cell populations and reveal the major sources contributing to cell population heterogeneity.

Hypothesis testing for neural cell growth experiments using a hybrid branching process model.

Neuron branching patterns can characterize neural cell types and act as markers for neurodegenerative disease and neural development. We develop a hybrid Markovian model for neural branching that extends previously published models by (i) using a discretized gamma model to account for underdispersion in primary branching, (ii) incorporating both bifurcation and trifurcation branching events to accommodate observed data, and (iii) only requiring branch counts and not branching topology as observations, allowing larger numbers of neurons to be sampled than in previous literature. Inference for primary branching is achieved through a gamma generalized linear model. Due to incomplete data, bifurcation and trifurcation probabilities are estimated using an expectation-maximization algorithm, which is shown to give consistent estimates using simulation studies and theoretical arguments. In simulation studies, comparison of standard errors shows no significant loss of accuracy relative to when topological information is available. A unified methodology for testing hypotheses using likelihood ratio tests (LRTs) is developed. The methodology is applied to an experiment where neurons are cocultured with different treatments: growth factor (GF), hypothalamic-astroglial conditioned medium (HY), and combination. The model provides statistically adequate fit at all branching orders. All treatments cause significantly higher branching at primary and secondary orders relative to control (p-value < 0.01), but not at higher branching orders, suggesting genetic regulation by the treatments. Using a computationally feasible lower bound on the LRT, bifurcation probabilities are shown to decrease exponentially with branching order for all treatments except HY (p-value 0.03).

The cellular geometry of growth drives the amino acid economy of Caenorhabditis elegans.

The nematode Caenorhabditis elegans grows largely by increases in cell size. As a consequence of this, the surface: volume ratio of its cells must decline in the course of postembryonic growth. Here we use transcriptomic and metabolomic data to show that this change in geometry can explain a variety of phenomena during growth, including: (i) changes in the relative expression levels of cytoplasmic and membrane proteins; (ii) changes in the relative usage of the twenty amino acids in expressed proteins, as estimated by changes in the transcriptome; and (iii) changes in metabolite pools of free amino acids. We expect these relations to be universal in single cells and in whole multicellular organisms that grow largely by increases in cell size, but not those that grow by cell proliferation.

In vitro assessment of axonal growth using dorsal root ganglia explants in a novel three-dimensional collagen matrix.

The goal of this study was the development of a bioartificial nerve guide to induce axonal regeneration in the peripheral nervous system (PNS). In this in vitro study, the ability of a novel, 3-dimensional (3D), highly oriented, cross-linked porcine collagen scaffold to promote directed axonal growth has been studied. Collagen nerve guides with longitudinal guidance channels were manufactured using a series of chemical and mechanical treatments with a patented unidirectional freezing process, followed by freeze-drying (pore sizes 20-50 microm). Hemisected rat dorsal root ganglia (DRG) were positioned such that neural and non-neural elements could migrate into the collagen scaffold. After 21 days, S100-positive Schwann cells (SCs) migrated into the scaffold and aligned within the guidance channels in a columnar fashion, resembling "Bands of Büngner." Neurofilament-positive axons (mean length +/- SD 756 microm +/- 318 microm, maximum 1496 microm) from DRG neurons entered the scaffold where the growth within the guidance channels was closely associated with the oriented SCs. This study confirmed the importance of SCs in the regeneration process (neurotrophic theory). The alignment of SCs within the guidance channels supported directional axonal growth (contact guidance theory). The microstructural properties of the scaffold (open, porous, longitudinal pore channels) and the in vitro data after DRG loading (axonal regeneration along migrated and columnar-aligned SCs resembling "Band of Büngner") suggest that this novel oriented 3D collagen scaffold serves as a basis for future experimental regeneration studies in the PNS.

The improvement of in vitro cytotoxicity testing for the assessment of acute toxicity in fish.

The use of fish cell line cytotoxicity tests as alternatives to acute lethality tests with fish is hampered by the clearly lower sensitivity of the fish cell line tests. Recently, it has been shown that this is not a unique feature of fish cells. In fact, the sensitivity of mammalian and human cell lines toward the cytotoxic actions of chemicals, in general, is comparable to that of fish cell lines. Reviewing some of our recent investigations, the objective of this paper is to show that the sensitivity of in vitro cytotoxicity testing and the correspondence between in vitro cytotoxic and acute fish toxic concentrations (LC50) can be increased, if: a) inhibition of cell growth instead of cell death is used as the endpoint; and b) the bioavailable free cytotoxic concentration (ECu50) of chemicals in vitro, instead of the nominal cytotoxic concentration (EC50), is used as the measure of cytotoxic potency. Based on these results, a pragmatic in vitro testing strategy for estimating the minimal aquatic toxic potency of chemicals is proposed.