Caroline Baroukh

French National Institute for Agriculture, Food, and Environment (INRAE) | INRAE · Department of Plant Health and Environment

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabol...

The conversion of microalgae lipids and cyanobacteria carbohydrates into biofuels appears to be a promising source of renewable energy. This requires a thorough understanding of their carbon metabolism, supported by mathematical models, in order to optimize biofuel production. However, unlike heterotrophic microorganisms that utilize the same subst...

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabol...

All the strains grouped under the species Ralstonia solanacearum represent a species complex which collectively constitute a devastating plant pathogen responsible of many diseases on agricultural crops throughout the world. The strains have different lifestyles and host range. Here we sought whether specific metabolic pathways contribute to strain...

An emerging idea is to couple wastewater treatment and biofuel production using microalgae to achieve higher productivities and lower costs. This paper proposes a metabolic modelling of Chlorella sp. growing on fermentation wastes (blend of acetate, butyrate and other acids) in mixotrophic conditions, accounting also for the possible inhibitory sub...

Motivation: Many techniques have been developed to infer Boolean regulations from a prior knowledge network (PKN) and experimental data. Existing methods are able to reverse-engineer Boolean regulations for transcriptional and signaling networks, but they fail to infer regulations that control metabolic networks. Results: We present a novel appr...

We propose metabolic models for the haptophyte microalgae Tisochrysis lutea with different possible organic carbon excretion mechanisms. These models—based on the DRUM (Dynamic Reduction of Unbalanced Metabolism) methodology—are calibrated with an experiment of nitrogen starvation under day/night cycles, and then validated with nitrogen-limited che...

We observed differences in lhc classification in Chromista. We proposed a classification of the lhcf family with two groups specific to haptophytes, one specific to diatoms, and one specific to seaweeds. Identification and characterization of the Fucoxanthin and Chlorophyll a/c-binding Protein (FCP) of the haptophyte microalgae Tisochrysis lutea we...

Ralstonia solanacearum is one of the most destructive pathogens worldwide. In the last 30 years, the molecular mechanisms at the origin of R. solanacearum pathogenicity have been studied in depth. However, the nutrition status of the pathogen once inside the plant has been poorly investigated. Yet, the pathogen needs substrates to sustain a fast‐en...

Predicting and understanding plant responses to perturbations require integrating the interactions between nutritional sources, genes, cell metabolism, and physiology in the same model. This can be achieved using metabolic modeling calibrated by experimental data. In this study, we developed a multi-organ metabolic model of a tomato (Solanum lycope...

Predicting and understanding plant responses to perturbations requires integrating the interactions between nutritional sources, genes, cell metabolism and physiology in the same model. This can be achieved using metabolic modeling calibrated by experimental data. In this study, we developed a multi-organ metabolic model of a tomato plant during ve...

Many techniques have been developed to infer Boolean regulations from a prior knowledge network and experimental data. Existing methods are able to reverse-engineer Boolean regulations for transcriptional and signaling networks, but they fail to infer regulations that control metabolic networks. This paper provides a formalisation of the inference...

Polyamines (PAs) are ubiquitous amine molecules found in all living organisms. In plants, beside their role in signaling and protection against abiotic stresses, there is increasing evidence that PAs have a major role in the interaction between plants and pathogens. Plant PAs are involved in immunity against pathogens, notably by amplifying pattern...

The plant pathogen Ralstonia solanacearum uses plant resources to intensely proliferate in xylem vessels and provoke plant wilting. We combined automatic phenotyping and tissue/xylem quantitative metabolomics of infected tomato plants to decipher the dynamics of bacterial wilt. Daily acquisition of physiological parameters such as transpiration and...

With the development of plant metabolomics, projects like the 10,000 plants genome sequencing project and the growth of other omics, the amount of data describing plant metabolism has never been so big. Genome-scale metabolic models (GEMs) are widely used to integrate and study the available information, and to better understand global responses to...

Xylella fastidiosa is one of the most important threats to plant health worldwide, causing disease in the Americas on a range of agricultural crops and trees, and recently associated with a critical epidemic affecting olive trees in Europe. A main challenge for the detection of the pathogen and the development of physiological studies is its fastid...

Tisochrysis lutea is a microalga species currently used in aquaculture as a feed for shellfish, oysters and shrimps. It also has many other potential industrial applications, such as the production of neutral lipids for biofuels or the production of ω-3 fatty acids for nutraceuticals (human food complements). To efficiently exploit the potential of...

Background The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving acce...

Microalgae are promising microorganisms for the production of numerous molecules of interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic or mixotrophic growth on fermentative wastes represents an interesting approach to achieving higher biomass concentrations, while reducing cost and improving the en...

Microalgae have received much attention in the context of renewable fuel production, due to their ability to produce in high quantities carbon storage molecules such as lipids and carbohydrates. Despite significant research effort over the last decade, the production yields remain low and need to be optimized. For that, a thorough understanding of...

Microalgae are promising microorganisms for the production of numerous molecules of interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic growth on wastes represents an interesting approach to achieve higher biomass concentrations, while reducing cost and improving the environmental footprint. Wastes...

Bayesian Optimization (BO) is a data-efficient method for global black-box optimization of an expensive-to-evaluate fitness function. BO typically assumes that computation cost of BO is cheap, but experiments are time consuming or costly. In practice, this allows us to optimize ten or fewer critical parameters in up to 1,000 experiments. But experi...

The most promising and yet challenging application of microalgae and cyanobacteria is the production of renewable energy: biodiesel from microalgae triacylglycerols and bioethanol from cyanobacteria carbohydrates. A thorough understanding of microalgal and cyanobacterial metabolism is necessary to master and optimize biofuel production yields. To t...

Macroscopic and metabolic models are ubiquitous tools for bioprocess modeling and understanding. While these two modeling approaches bring answers to different objectives, a remaining challenging question is how to couple macroscopic and intracellular models to enlarge the prediction capabilities of the model while keeping a model structure with lo...

High content studies that profile mouse and human embryonic stem cells (m/hESCs) using various genome-wide technologies such as transcriptomics and proteomics are constantly being published. However, efforts to integrate such data to obtain a global view of the molecular circuitry in m/hESCs are lagging behind. Here, we present an m/hESC-centered d...

Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent bio...

In this paper we summarise our current work on using Process Calculi for the modelling and analysis of biological pathways in context of better understanding respiratory disease. We present and highlight key features of some of the different Process Calculi that have been used for the modelling of biological pathways. Then we make a state-of-art on...

In this poster we summarise our current work on using Process Calculi for the modelling and analysis of biological pathways in context of better understanding respiratory disease. We present and highlight key features of some of the different Process Calculi that have been used for the modelling of biological pathways. Finally we describe the proce...