Investigation of the adaptation of Lactococcus lactis to isoleucine starvation integrating dynamic transcriptome and proteome information

Background: Amino acid assimilation is crucial for bacteria and this is particularly true for Lactic Acid Bacteria (LAB) that are generally auxotroph for amino acids. The global response of the Lmodel Lactococcus lactis ssp. lactis was characterized during progressive isoleucine starvation in batch culture using a chemically defined medium in which isoleucine concentration was fixed so as to become the sole limiting nutriment. Dynamic analyses were performed using transcriptomic and proteomic approaches and the results were analysed conjointly with fermentation kinetic data. Results: The response was first deduced from transcriptomic analysis and corroborated by proteomic results. It occurred progressively and could be divided into three major mechanisms: (i) a global down-regulation of processes linked to bacterial growth and catabolism (transcription, translation, carbon metabolism and transport, pyrimidine and fatty acid metabolism), (ii) a specific positive response related to the limiting nutrient (activation of pathways of carbon or nitrogen metabolism and leading to isoleucine supply) and (iii) an unexpected oxidative stress response (positive regulation of aerobic metabolism, electron transport, thioredoxin metabolism and pyruvate dehydrogenase). The involvement of various regulatory mechanisms during this adaptation was analysed on the basis of transcriptomic data comparisons. The global regulator CodY seemed specifically dedicated to the regulation of isoleucine supply. Other regulations were massively related to growth rate and stringent response. Conclusion: This integrative biology approach provided an overview of the metabolic pathways involved during isoleucine starvation and their regulations. It has extended significantly the physiological understanding of the metabolism of L. lactis ssp. lactis. The approach can be generalised to other conditions and will contribute significantly to the identification of the biological processes involved in complex regulatory networks of micro-organisms

Growth rate regulated genes and their wide involvement in the Lactococcus lactis stress responses

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A nonlinear mixed-effects approach for the mechanistic interpretation of time-series transcriptomics data

Mechanistic models are essential to unravel the molecular mechanisms driving cellular responses. However, the integration of high-throughput data with mechanistic knowledge is limited by the availability of scalable computational approaches able to disentangle biological and technical sources of variation. Results: We present an approach based on nonlinear mixed-effects modelling for the parameter estimation of large-scale mechanistic models from time-series transcriptomics data. It allows to factor out technical variability, to compensate for the limited number of conditions and time points by a population approach, and it incorporates mechanistic details to gain insight on the molecular causes of biological variability. We applied our approach for the biological interpretation of microarray and RNA-Seq gene expression profiles, with different levels of technical noise, but it is generalisable to numerous types of data. When integrated in a model describing the degradation kinetics of all cellular mRNAs, the data allowed to identify the targets of post-transcriptional regulatory mechanisms. Our approach paves the way for the interpretation of high-throughput biological data with more comprehensive mechanistic models. Availability: The Monolix script for estimation and output files are freely available at https://gitlab.inria. fr/tetienne/eccb_script, together with the microarray data. The RNA-Seq dataset is being prepared for publication (Roux et al., in preparation) and will be made available on demand upon acceptance of the article

The Csr System Regulates Escherichia coli Fitness by Controlling Glycogen Accumulation and Energy Levels

International audienceIn the bacterium Escherichia coli, the posttranscriptional regulatory system Csr was postulated to influence the transition from glycolysis to gluconeogene-sis. Here, we explored the role of the Csr system in the glucose-acetate transition as a model of the glycolysis-to-gluconeogenesis switch. Mutations in the Csr system influence the reorganization of gene expression after glucose exhaustion and disturb the timing of acetate reconsumption after glucose exhaustion. Analysis of me-tabolite concentrations during the transition revealed that the Csr system has a major effect on the energy levels of the cells after glucose exhaustion. This influence was demonstrated to result directly from the effect of the Csr system on glycogen accumulation. Mutation in glycogen metabolism was also demonstrated to hinder metabolic adaptation after glucose exhaustion because of insufficient energy. This work explains how the Csr system influences E. coli fitness during the glycolysis-gluconeogenesis switch and demonstrates the role of glycogen in maintenance of the energy charge during metabolic adaptation. IMPORTANCE Glycogen is a polysaccharide and the main storage form of glucose from bacteria such as Escherichia coli to yeasts and mammals. Although its function as a sugar reserve in mammals is well documented, the role of glycogen in bacteria is not as clear. By studying the role of posttranscriptional regulation during metabolic adaptation, for the first time, we demonstrate the role of sugar reserve played by glycogen in E. coli. Indeed, glycogen not only makes it possible to maintain sufficient energy during metabolic transitions but is also the key component in the capacity of cells to resume growth. Since the essential posttranscriptional regulatory system Csr is a major regulator of glycogen accumulation, this work also sheds light on the central role of posttranscriptional regulation in metabolic adaptation

Transcriptome and Proteome Exploration to Model Translation Efficiency and Protein Stability in Lactococcus lactis

This genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios of mRNA to protein were highly variable among proteins but also, for a given gene, between the different growth conditions. The modeling of cellular processes combined with a data fitting modeling approach allowed both translation efficiencies and degradation rates to be estimated for each protein in each growth condition. Estimated translational efficiencies and degradation rates strongly differed between proteins and were tested for their biological significance through statistical correlations with relevant parameters such as codon or amino acid bias. These efficiencies and degradation rates were not constant in all growth conditions and were inversely proportional to the growth rate, indicating a more efficient translation at low growth rate but an antagonistic higher rate of protein degradation. Estimated protein median half-lives ranged from 23 to 224 min, underlying the importance of protein degradation notably at low growth rates. The regulation of intracellular protein level was analysed through regulatory coefficient calculations, revealing a complex control depending on protein and growth conditions. The modeling approach enabled translational efficiencies and protein degradation rates to be estimated, two biological parameters extremely difficult to determine experimentally and generally lacking in bacteria. This method is generic and can now be extended to other environments and/or other micro-organisms

Sequential demethoxylation reactions during methylotrophic growth of methoxylated aromatic substrates with Eubacterium limosum

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Identification des déterminants de l'expression génique lors de l'adaptation de Lactococcus lactis au stress (intégration des données de transcriptome et de stabilité des ARN messagers)

TOULOUSE-INSA (315552106) / SudocSudocFranceF

Régulation des voies centrales chez Lactococcus lactis (Intégration des profils métaboliques et transcriptionnels)

TOULOUSE-INSA (315552106) / SudocSudocFranceF