Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations

There has been increasing awareness in the wider biological community of the role of clonal phenotypic heterogeneity in playing key roles in phenomena such as cellular bet-hedging and decision making, as in the case of the phage-λ lysis/lysogeny and B. Subtilis competence/vegetative pathways. Here, we report on the effect of stochasticity in growth rate, cellular memory/intermittency, and its relation to phenotypic heterogeneity. We first present a linear stochastic differential model with finite auto-correlation time, where a randomly fluctuating growth rate with a negative average is shown to result in exponential growth for sufficiently large fluctuations in growth rate. We then present a non-linear stochastic self-regulation model where the loss of coherent self-regulation and an increase in noise can induce a shift from bounded to unbounded growth. An important consequence of these models is that while the average change in phenotype may not differ for various parameter sets, the variance of the resulting distributions may considerably change. This demonstrates the necessity of understanding the influence of variance and heterogeneity within seemingly identical clonal populations, while providing a mechanism for varying functional consequences of such heterogeneity. Our results highlight the importance of a paradigm shift from a deterministic to a probabilistic view of clonality in understanding selection as an optimization problem on noise-driven processes, resulting in a wide range of biological implications, from robustness to environmental stress to the development of drug resistance

Analysis of expression pathways alterations of Arabidopsis thaliana induced by a Necrosis- and Ethylene-inducing protein

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)A major goal in post-genomic biology is the description of physiological functions ill terms of gene pathway behavior. In this work, we present the first investigation of expression alterations in ninety-three pathways representing physiological functions of the plant A. thaliana induced by a A parasitica elicitor (NLPpp) using microarray data publicly available at the AtGenExpress database. Using a novel statistical analysis developed to detect pathway alterations, we identified the gene pathways, hereby called groups of functionally associated genes (defined according to the TA1R/Gene Ontology and other databases), that are significantly altered in response to the elicitor. Instead of looking at individual gene responses, Our analysis allowed a detailed characterization of the time ordering of pathways alterations in response to the NLPpp, their physiological implications and specificity. We also observed the activation of genes associated with vesicle trafficking and ROS production implying the initiation of the senescence of the wounded plant tissue. (C) 2009 Elsevier B.V. All rights reserved.3882045154522Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)CNPq [506414/2004-3, 151171/2007-6

Using the FORESTS and KEGG databases to investigate the metabolic network of Eucalyptus

In this work we apply a bioinformatics approach to determine the most important enzymes of the metabolic network of Eucalyptus to determine the coverage of the genome in the FORESTS library. We conclude that the library does not cover completely the metabolism of the organism. However, some important pathways could be analyzed, especially the lignin synthesis. We found that four of the most important enzymes predicted are involved in this pathway