Integrative Modeling of Gene Expression and Metabolic Networks of Embryos for Identification of Seed Oil Causal Genes.

Fatty acids in crop seeds are a major source for both vegetable oils and industrial applications. Genetic improvement of fatty acid composition and oil content is critical to meet the current and future demands of plant-based renewable seed oils. Addressing this challenge can be approached by network modeling to capture key contributors of seed metabolism and to identify underpinning genetic targets for engineering the traits associated with seed oil composition and content.

Continuous real-time in vivo measurement of cerebral nitric oxide supports theoretical predictions of an irreversible switching in cerebral ROS after sufficient exposure to external toxins.

Background: Mathematical models of the interactions between alphasynuclein (αS) and reactive oxygen species (ROS) predict a systematic and irreversible switching to damagingly high levels of ROS after sufficient exposure to risk factors associated with Parkinson's disease (PD).

Objectives: We tested this prediction by continuously monitoring real-time changes in neurochemical levels over periods of several days in animals exposed to a toxin known to cause Parkinsonian symptoms.

Methods: Nitric oxide (NO) sensors were implanted in the brains of freely moving rats and the NO levels continuously recorded while the animals were exposed to paraquat (PQ) injections of various amounts and frequencies.

Metabolomics and in-silico analysis reveal critical energy deregulations in animal models of Parkinson's disease.

Parkinson's disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease.

Dynamic modeling and analysis of cancer cellular network motifs.

With the advent of high-throughput biology, we now routinely scan cells and organisms at practically all levels, from genome to protein, metabolism, signaling and other cellular functions. This methodology allowed biological studies to move from a reductionist approach, such as isolation of specific pathways and mechanisms, to a more integrative approach, where biological systems are seen as a network of interconnected components that provide specific outputs and functions in response to stimuli. Recent literature on biological networks demonstrates two important concepts that we will consider in this review: (i) cellular pathways are highly interconnected and should not be studied separately, but as a network; (ii) simple, recurrent feedback motifs within the network can produce very specific functions that favor their modular use.

Genome-wide analysis reveals gene expression and metabolic network dynamics during embryo development in Arabidopsis.

Embryogenesis is central to the life cycle of most plant species. Despite its importance, because of the difficulty associated with embryo isolation, global gene expression programs involved in plant embryogenesis, especially the early events following fertilization, are largely unknown. To address this gap, we have developed methods to isolate whole live Arabidopsis (Arabidopsis thaliana) embryos as young as zygote and performed genome-wide profiling of gene expression.

An energy systems approach to Parkinson's disease.

The cause of Parkinson's disease (PD) remains unknown despite it being the second most prevalent neurodegenerative condition. Indeed, there is a growing consensus that there is no single cause, and that PD is a multifactorial systemic condition, in which a number of factors may determine its etiopathogenesis. We describe a systems approach that addresses the multifactorial aspects of PD and overcomes constraints on conventional experimentation imposed by PD's causal complexity, its long temporal duration, and its uniqueness to human brains.

A systems approach to plant bioprocess optimization.

A dynamic model for plant cell metabolism was used as a basis for a rational analysis of plant production potential in in vitro cultures. The model was calibrated with data from 3-L bioreactor cultures. A dynamic sensitivity analysis framework was developed to analyse the response curves of secondary metabolite production to metabolic and medium perturbations.

The control systems structures of energy metabolism.

The biochemical regulation of energy metabolism (EM) allows cells to modulate their energetic output depending on available substrates and requirements. To this end, numerous biomolecular mechanisms exist that allow the sensing of the energetic state and corresponding adjustment of enzymatic reaction rates. This regulation is known to induce dynamic systems properties such as oscillations or perfect adaptation.

An integrative dynamic model of brain energy metabolism using in vivo neurochemical measurements.

An integrative, systems approach to the modelling of brain energy metabolism is presented. Mechanisms such as glutamate cycling between neurons and astrocytes and glycogen storage in astrocytes have been implemented. A unique feature of the model is its calibration using in vivo data of brain glucose and lactate from freely moving rats under various stimuli.

Kinetic metabolic modelling for the control of plant cells cytoplasmic phosphate.

A previously developed kinetic metabolic model for plant metabolism was used in a context of identification and control of intracellular phosphate (Pi) dynamics. Experimental data from batch flask cultures of Eschscholtiza californica cells was used to calibrate the model parameters for the slow dynamics (growth, nutrition, anabolic pathways, etc.).

Identifying conditions for inducible protein production in E. coli: combining a fed-batch and multiple induction approach.

Background: In the interest of generating large amounts of recombinant protein, inducible systems have been studied to maximize both the growth of the culture and the production of foreign proteins. Even though thermo-inducible systems were developed in the late 1970's, the number of studies that focus on strategies for the implementation at bioreactor scale is limited. In this work, the bacteriophage lambda PL promoter is once again investigated as an inducible element but for the production of green fluorescent protein (GFP).