Genome-Scale Reconstruction and Analysis of the Pseudomonas putida KT2440 Metabolic Network Facilitates Applications in Biotechnology

A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, 13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype–phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential

Effect of physostigmine and verapamil on active avoidance in an experimental model of Alzheimer's disease

The present study was performed to investigate and compare the effect of acetylcholinesterase inhibitor, physostigmine (0.045, 0.060 and 0.075 mg/kg sc, 30 min before the tests) and Ca-antagonist, verapamil (1.0, 2.5, 5.0 and 10.0 mg/kg sc, 30 min before the tests), on two-way active avoidance (AA) learning (acquisition and performance) in nucleus basalis magnocellularis (NBM)-lesioned rats. Bilateral electrolytic lesions of NBM induced significant decrease of acquisition and performance of AA responses in rats. Physostigmine (0.060 mg/kg) significantly improved only acquisition of AA, while verapamil (2.5 and 5.0 mg/kg) significantly improved both type of AA behavior in NBM-lesioned rats. These results suggest that altered calcium homeostasis might play significant role in pathogenesis of experimental induced Alzheimer's disease (AD) and that administration of calcium antagonist such as verapamil might successfully ameliorate disturbances of learning and memory appeared after lesions of NBM