Serguei Sokol

Investigating the caffeine effects in the yeast Saccharomyces cerevisiae brings new insights into the connection between TOR, PKC and Ras/cAMP signalling pathways

Caffeine is a natural purine analogue that elicits pleiotropic effects leading ultimately to cells death by a largely uncharacterized mechanism. Previous works have shown that this drug induces a rapid phosphorylation of the Mpk1p, the final mitogen‐activated protein (MAP) kinase of the Pkc1p‐mediated cell integrity pathway. In this work, we showed that this phosphorylation did not necessitate the main cell wall sensors Wsc1p and Mid2p, but was abolished upon deletion of ROM2 encoding a GDP/GTP exchange factor of Rho1p. We also showed that the caffeine‐induced phosphorylation of Mpk1p was accompanied by a negligible activation of its main downstream target, the Rlm1p transcription factor. This result was consolidated by the finding that the loss of RLM1 had no consequence on the increased resistance of caffeine‐treated cells to zymolyase, indicating that the cell wall modification caused by this drug is largely independent of transcriptional activation of Rlm1p‐regulated genes. Additionally, the transcriptional programme elicited by caffeine resembled that of rapamycin, a potent inhibitor of the TOR1/2 kinases. Consistent with this analysis, we found that the caffeine‐induced phosphorylation of Mpk1p was lost in a tor1Δ mutant. Moreover, a tor1Δ mutant was, like mutants defective in components of the Pkc1p‐Mpk1p cascade, highly sensitive to caffeine. However, the hypersensitivity of a tor1 null mutant to this drug was rescued neither by sorbitol nor by adenine, which was found to outcompete caffeine effects specially on mutants in the PKC pathway. Altogether, these data indicated that Tor1 kinase is a target of caffeine, whose inhibition incidentally activates the Pkc1p‐Mpk1p cascade, and that the caffeine‐dependent phenotypes are largely dependent on inhibition of Tor1p‐regulated cellular functions. Finally, we found that caffeine provoked, in a Rom2p‐dependent manner, a transient drop in intracellular levels of cAMP, that was followed by change in expression of genes implicated in Ras/cAMP pathway. This result may pose Rom2p as a mediator in the interplay between Tor1p and the Ras/cAMP pathway.

IsoCor: correcting MS data in isotope labeling experiments

UNLABELLED Mass spectrometry (MS) is widely used for isotopic labeling studies of metabolism and other biological processes. Quantitative applications-e.g. metabolic flux analysis-require tools to correct the raw MS data for the contribution of all naturally abundant isotopes. IsoCor is a software that allows such correction to be applied to any chemical species. Hence it can be used to exploit any isotopic tracer, from well-known ((13)C, (15)N, (18)O, etc) to unusual ((57)Fe, (77)Se, etc) isotopes. It also provides new features-e.g. correction for the isotopic purity of the tracer-to improve the accuracy of quantitative isotopic studies, and implements an efficient algorithm to process large datasets. Its user-friendly interface makes isotope labeling experiments more accessible to a wider biological community. AVAILABILITY IsoCor is distributed under OpenSource license at http://metasys.insa-toulouse.fr/software/isocor/

influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments

MOTIVATION The problem of stationary metabolic flux analysis based on isotope labelling experiments first appeared in the early 1950s and was basically solved in early 2000s. Several algorithms and software packages are available for this problem. However, the generic stochastic algorithms (simulated annealing or evolution algorithms) currently used in these software require a lot of time to achieve acceptable precision. For deterministic algorithms, a common drawback is the lack of convergence stability for ill-conditioned systems or when started from a random point. RESULTS In this article, we present a new deterministic algorithm with significantly increased numerical stability and accuracy of flux estimation compared with commonly used algorithms. It requires relatively short CPU time (from several seconds to several minutes with a standard PC architecture) to estimate fluxes in the central carbon metabolism network of Escherichia coli. AVAILABILITY The software package influx_s implementing this algorithm is distributed under an OpenSource licence at http://metasys.insa-toulouse.fr/software/influx/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

IsoDesign: A software for optimizing the design of 13C‐metabolic flux analysis experiments

The growing demand for (13) C-metabolic flux analysis ((13) C-MFA) in the field of metabolic engineering and systems biology is driving the need to rationalize expensive and time-consuming (13) C-labeling experiments. Experimental design is a key step in improving both the number of fluxes that can be calculated from a set of isotopic data and the precision of flux values. We present IsoDesign, a software that enables these parameters to be maximized by optimizing the isotopic composition of the label input. It can be applied to (13) C-MFA investigations using a broad panel of analytical tools (MS, MS/MS, (1) H NMR, (13) C NMR, etc.) individually or in combination. It includes a visualization module to intuitively select the optimal label input depending on the biological question to be addressed. Applications of IsoDesign are described, with an example of the entire (13) C-MFA workflow from the experimental design to the flux map including important practical considerations. IsoDesign makes the experimental design of (13) C-MFA experiments more accessible to a wider biological community. IsoDesign is distributed under an open source license at http://metasys.insa-toulouse.fr/software/isodes/

A novel platform for automated high-throughput fluxome profiling of metabolic variants.

Advances in metabolic engineering are enabling the creation of a large number of cell factories. However, high-throughput platforms do not yet exist for rapidly analyzing the metabolic network of the engineered cells. To fill the gap, we developed an integrated solution for fluxome profiling of large sets of biological systems and conditions. This platform combines a robotic system for (13)C-labelling experiments and sampling of labelled material with NMR-based isotopic fingerprinting and automated data interpretation. As a proof-of-concept, this workflow was applied to discriminate between Escherichia coli mutants with gradual expression of the glucose-6-phosphate dehydrogenase. Metabolic variants were clearly discriminated while pathways that support metabolic flexibility towards modulation of a single enzyme were elucidating. By directly connecting the data flow between cell cultivation and flux quantification, considerable advances in throughput, robustness, release of resources and screening capacity were achieved. This will undoubtedly facilitate the development of efficient cell factories.

The YTA7 gene is involved in the regulation of the isoprenoid pathway in the yeast Saccharomyces cerevisiae

The isoprenoid pathway in yeasts is important not only for sterol biosynthesis but also for the production of nonsterol molecules, deriving from farnesyl diphosphate (FPP), implicated in N-glycosylation and biosynthesis of heme and ubiquinones. FPP formed from mevalonate in a reaction catalyzed by FPP synthase (Erg20p). In order to investigate the regulation of Erg20p in Saccharomyces cerevisiae, we searched for its protein partners using a two-hybrid screen, and identified five interacting proteins, among them Yta7p. Subsequently, we showed that Yta7p was a membrane-associated protein localized both to the nucleus and to the endoplasmic reticulum. Deletion of YTA7 affected the enzymatic activity of cis-prenyltransferase (the enzyme that utilizes FPP for dolichol biosynthesis) and the cellular levels of isoprenoid compounds. Additionally, it rendered cells hypersensitive to lovastatin, an inhibitor of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) that acts upstream of FPP synthase in the isoprenoid pathway. While HMGR is encoded by two genes, HMG1 and HMG2, only HMG2 overexpression was able to restore growth of the yta7Delta cells in the presence of lovastatin. Moreover, the expression level of the S. cerevisiae YTA7 gene was altered upon impairment of the isoprenoid pathway not only by lovastatin but also by zaragozic acid, an inhibitor of squalene synthase. Altogether, these results provide substantial evidence of Yta7p involvement in the regulation of isoprenoid biosynthesis.

Comparative transcriptome analysis between original and evolved recombinant lactose-consuming Saccharomyces cerevisiae strains

The engineering of Saccharomyces cerevisiae strains for lactose utilization has been attempted with the intent of developing high productivity processes for alcoholic fermentation of cheese whey. A recombinant S. cerevisiae flocculent strain that efficiently ferments lactose to ethanol was previously obtained by evolutionary engineering of an original recombinant that displayed poor lactose fermentation performance. We compared the transcriptomes of the original and the evolved recombinant strains growing in lactose, using cDNA microarrays. Microarray data revealed 173 genes whose expression levels differed more than 1.5-fold. About half of these genes were related to RNA-mediated transposition. We also found genes involved in DNA repair and recombination mechanisms, response to stress, chromatin remodeling, cell cycle control, mitosis regulation, glycolysis and alcoholic fermentation. These transcriptomic data are in agreement with some of the previously identified physiological and molecular differences between the recombinants, and point to further hypotheses to explain those differences.

Correction of MS Data for Naturally Occurring Isotopes in Isotope Labelling Experiments

Mass spectrometry (MS) in combination with isotope labelling experiments is widely used for investigations of metabolism and other biological processes. Quantitative applications-e.g., (13)C metabolic flux analysis-require correction of raw MS data (isotopic clusters) for the contribution of all naturally abundant isotopes. This chapter describes how to perform such correction using the software IsoCor. This flexible, user-friendly software can be used to exploit any isotopic tracer, from well-known ((13)C, (15)N, (18)O, etc.) to unusual ((57)Fe, (77)Se, etc.) isotopes. It also provides options-e.g., correction for the isotopic purity of the tracer-to improve the accuracy of quantitative isotopic studies, and allows automated correction of large datasets that can be collected with modern MS methods.

Theoretical Basis for Dynamic Label Propagation in Stationary Metabolic Networks under Step and Periodic Inputs

The dynamics of label propagation in a stationary metabolic network during an isotope labeling experiment can provide highly valuable information on the network topology, metabolic fluxes, and on the size of metabolite pools. However, major issues, both in the experimental set-up and in the accompanying numerical methods currently limit the application of this approach. Here, we propose a method to apply novel types of label inputs, sinusoidal or more generally periodic label inputs, to address both the practical and numerical challenges of dynamic labeling experiments. By considering a simple metabolic system, i.e. a linear, non-reversible pathway of arbitrary length, we develop mathematical descriptions of label propagation for both classical and novel label inputs. Theoretical developments and computer simulations show that the application of rectangular periodic pulses has both numerical and practical advantages over other approaches. We applied the strategy to estimate fluxes in a simulated experiment performed on a complex metabolic network (the central carbon metabolism of Escherichia coli), to further demonstrate its value in conditions which are close to those in real experiments. This study provides a theoretical basis for the rational interpretation of label propagation curves in real experiments, and will help identify the strengths, pitfalls and limitations of such experiments. The cases described here can also be used as test cases for more general numerical methods aimed at identifying network topology, analyzing metabolic fluxes or measuring concentrations of metabolites.