Transport-controlled growth decoupling for self-induced protein expression with a glycerol-repressible genetic circuit.

Decoupling cell formation from recombinant protein synthesis is a potent strategy to intensify bioprocesses. Escherichia coli strains with mutations in the glucose uptake components lack catabolite repression, display low growth rate, no overflow metabolism, and high recombinant protein yields. Fast growth rates were promoted by the simultaneous consumption of glucose and glycerol, and this was followed by a phase of slow growth, when only glucose remained in the medium.

Increasing the Pentose Phosphate Pathway Flux to Improve Plasmid DNA Production in Engineered .

The demand of plasmid DNA (pDNA) as a key element for gene therapy products, as well as mRNA and DNA vaccines, is increasing together with the need for more efficient production processes. An engineered strain lacking the phosphotransferase system and the pyruvate kinase A gene has been shown to produce more pDNA than its parental strain. With the aim of improving pDNA production in the engineered strain, several strategies to increase the flux to the pentose phosphate pathway (PPP) were evaluated.

Haemoglobin: A Tool to Reduce Overflow Metabolism.

Overflow metabolism is a phenomenon extended in nature, ranging from microbial to cancer cells. Accumulation of overflow metabolites pose a challenge for large-scale bioprocesses. Yet, the causes of overflow metabolism are not fully clarified.

Doxorubicin-induced transcriptome meets interactome: identification of new drug targets.

The working mechanism of the chemotherapeutic drug doxorubicin, which is frequently used in cancer treatment, its effects on cell metabolism, and pathways activated solely by doxorubicin are not fully known. Understanding these principles is important both in improving existing therapies and in finding new drug targets. Here, I describe a systems-biology approach to find a generalizable working principle for doxorubicin by superimposition of human interactome over gene datasets commonly expressed among various cancer types.

Fast Sampling of the Cellular Metabolome.

Obtaining meaningful snapshots of the metabolome of microorganisms requires rapid sampling and immediate quenching of all metabolic activity, to prevent any changes in metabolite levels after sampling. Furthermore, a suitable extraction method is required ensuring complete extraction of metabolites from the cells and inactivation of enzymatic activity, with minimal degradation of labile compounds. Finally, a sensitive, high-throughput analysis platform is needed to quantify a large number of metabolites in a small amount of sample.

Integration of fluxome and transcriptome data in offers unique features of doxorubicin and imatinib.

Improving the efficacy of drugs and developing new drugs are required to compensate for drug resistance. Therefore, it is critical to unveil the mode of action, which can be studied through the cellular response at genome-scale, of the existing drugs. Here, system-level response of , a eukaryotic model microorganism, to two chemotherapy drugs doxorubicin and imatinib used against cancer are analysed.

Side effect prediction based on drug-induced gene expression profiles and random forest with iterative feature selection.

One in every ten drug candidates fail in clinical trials mainly due to efficacy and safety related issues, despite in-depth preclinical testing. Even some of the approved drugs such as chemotherapeutics are notorious for their side effects that are burdensome on patients. In order to pave the way for new therapeutics with more tolerable side effects, the mechanisms underlying side effects need to be fully elucidated.

Time-dependent re-organization of biological processes by the analysis of the dynamic transcriptional response of yeast cells to doxorubicin.

Doxorubicin is an efficient chemotherapeutic reagent in the treatment of a variety of cancers. However, its underlying molecular mechanism is not fully understood and several severe side effects limit its application. In this study, the dynamic transcriptomic response of Saccharomyces cerevisiae cells to a doxorubicin pulse in a chemostat system was investigated to reveal the underlying molecular mechanism of this drug.

Insights Into the Mechanism of Anticancer Drug Imatinib Revealed Through Multi-Omic Analyses in Yeast.

Imatinib mesylate is a receptor tyrosine kinase inhibitor drug with broad applications in cancer therapeutics, for example, in chronic myeloid leukemia and gastrointestinal stromal tumors. In this study, new multi-omics findings in yeast on the mechanism of imatinib are reported, using the model organism . Whole-genome analysis of the transcriptional response of yeast cells following long-term exposure to imatinib, flux-balance analysis (FBA), and modular analysis of protein/protein interaction network consisting of proteins encoded by differentially expressed genes (DEGs) were performed.

Doxorubicin induces an extensive transcriptional and metabolic rewiring in yeast cells.

Doxorubicin is one of the most effective chemotherapy drugs used against solid tumors in the treatment of several cancer types. Two different mechanisms, (i) intercalation of doxorubicin into DNA and inhibition of topoisomerase II leading to changes in chromatin structure, (ii) generation of free radicals and oxidative damage to biomolecules, have been proposed to explain the mode of action of this drug in cancer cells. A genome-wide integrative systems biology approach used in the present study to investigate the long-term effect of doxorubicin in Saccharomyces cerevisiae cells indicated the up-regulation of genes involved in response to oxidative stress as well as in Rad53 checkpoint sensing and signaling pathway.

Genome-Wide Transcriptional Response of Saccharomyces cerevisiae to Stress-Induced Perturbations.

Cells respond to environmental and/or genetic perturbations in order to survive and proliferate. Characterization of the changes after various stimuli at different -omics levels is crucial to comprehend the adaptation of cells to the changing conditions. Genome-wide quantification and analysis of transcript levels, the genes affected by perturbations, extends our understanding of cellular metabolism by pointing out the mechanisms that play role in sensing the stress caused by those perturbations and related signaling pathways, and in this way guides us to achieve endeavors, such as rational engineering of cells or interpretation of disease mechanisms.

Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli.

An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain.

Effect of growth rate on plasmid DNA production and metabolic performance of engineered Escherichia coli strains.

Two engineered Escherichia coli strains, designated VH33 and VH34, were compared to their parent strain W3110 in chemostat mode during plasmid DNA (pDNA) production. In strain VH33 the glucose uptake system was modified with the aim of reducing overflow metabolism. The strain VH34 has an additional deletion of the pyruvate kinase A gene (pykA) to increase pDNA formation.

Changes in substrate availability in Escherichia coli lead to rapid metabolite, flux and growth rate responses.

The interactions between the intracellular metabolome, fluxome and growth rate of Escherichia coli after sudden glycolytic/gluconeogenic substrate shifts are studied based on pulses of different substrates to an aerobic glucose-limited steady-state (dilution rate=0.1h(-1)). After each added glycolytic (glucose) and gluconeogenic (pyruvate and succinate) substrate pulse, no by-products were secreted and a pseudo steady state in flux and metabolites was achieved in about 30-40s.

Fast sampling of the cellular metabolome.

Obtaining meaningful snapshots of the metabolome of microorganisms requires rapid sampling and immediate quenching of all metabolic activity, to prevent any changes in metabolite levels after sampling. Furthermore, a suitable extraction method is required ensuring complete extraction of metabolites from the cells and inactivation of enzymatic activity, with minimal degradation of labile compounds. Finally a sensitive, high-throughput analysis platform is needed to quantify a large number of metabolites in a small amount of sample.

Escherichia coli responds with a rapid and large change in growth rate upon a shift from glucose-limited to glucose-excess conditions.

Glucose pulse experiments at seconds time scale resolution were performed in aerobic glucose-limited Escherichia coli chemostat cultures. The dynamic responses of oxygen-uptake and growth rate at seconds time scale were determined using a new method based on the dynamic liquid-phase mass balance for oxygen and the pseudo-steady-state ATP balance. Significant fold changes in metabolites (10-1/10) and fluxes (4-1/4) were observed during the short (200 s) period of glucose excess.

Genome-derived minimal metabolic models for Escherichia coli MG1655 with estimated in vivo respiratory ATP stoichiometry.

Metabolic network models describing growth of Escherichia coli on glucose, glycerol and acetate were derived from a genome scale model of E. coli. One of the uncertainties in the metabolic networks is the exact stoichiometry of energy generating and consuming processes.

Catching prompt metabolite dynamics in Escherichia coli with the BioScope at oxygen rich conditions.

The design and application of a BioScope, a mini plug-flow reactor for carrying out pulse response experiments, specifically designed for Escherichia coli is presented. Main differences with the previous design are an increased volume-specific membrane surface for oxygen transfer and significantly decreased sampling intervals. The characteristics of the new device (pressure drop, residence time distribution, plug-flow behavior and O2 mass transfer) were determined and evaluated.

Fast dynamic response of the fermentative metabolism of Escherichia coli to aerobic and anaerobic glucose pulses.

The response of Escherichia coli cells to transient exposure (step increase) in substrate concentration and anaerobiosis leading to mixed-acid fermentation metabolism was studied in a two-compartment bioreactor system consisting of a stirred tank reactor (STR) connected to a mini-plug-flow reactor (PFR: BioScope, 3.5 mL volume). Such a system can mimic the situation often encountered in large-scale, fed-batch bioreactors.

Development and application of a differential method for reliable metabolome analysis in Escherichia coli.

Quantitative metabolomics of microbial cultures requires well-designed sampling and quenching procedures. We successfully developed and applied a differential method to obtain a reliable set of metabolome data for Escherichia coli K12 MG1655 grown in steady-state, aerobic, glucose-limited chemostat cultures. From a rigorous analysis of the commonly applied quenching procedure based on cold aqueous methanol, it was concluded that it was not applicable because of release of a major part of the metabolites from the cells.