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3 Publications visible to you, out of a total of 3

Abstract (Expand)

Streptomyces coelicolor M1152 is a widely used host strain for the heterologous production of novel small molecule natural products, genetically engineered for this purpose through e.g. deletion of four of its native biosynthetic gene clusters (BGCs) for improved precursor supply. Regardless of its potential, a systems understanding of its tight regulatory network and the effects of the significant genomic changes in M1152 is missing. In this study, we compare M1152 to its ancestor M145, thereby connecting observed phenotypic differences to changes on transcription and translation. Measured protein levels are connected to predicted metabolic fluxes, facilitated by an enzyme-constrained genome-scale model (GEM), that by itself is a consensus result of a community effort. This approach connects observed differences in growth rate and glucose consumption to changes in central carbon metabolism, accompanied by differential expression of important regulons. Results suggest that precursors supply is not limiting secondary metabolism, informing that alternative strategies will be beneficial for further development of S. coelicolor for heterologous production of novel compounds.

Authors: Snorre Sulheim, Tjaša Kumelj, Dino van Dissel, Ali Salehzadeh-Yazdi, Chao Du, Gilles P. van Wezel, Kay Nieselt, Eivind Almaas, Alexander Wentzel, Eduard J Kerkhoven

Date Published: 8th Oct 2019

Publication Type: Unpublished

Abstract (Expand)

The African trypanosome, Trypanosoma brucei, is a unicellular parasite causing African Trypanosomiasis (sleeping sickness in humans and nagana in animals). Due to some of its unique properties, it has emerged as a popular model organism in systems biology. A predictive quantitative model of glycolysis in the bloodstream form of the parasite has been constructed and updated several times. The Silicon Trypanosome is a project that brings together modellers and experimentalists to improve and extend this core model with new pathways and additional levels of regulation. These new extensions and analyses use computational methods that explicitly take different levels of uncertainty into account. During this project, numerous tools and techniques have been developed for this purpose, which can now be used for a wide range of different studies in systems biology.

Authors: , , , , , , T. Papamarkou, , , , , , , ,

Date Published: 7th May 2014

Publication Type: Not specified

Abstract (Expand)

Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate "leak" must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally.

Authors: , , V. P. Alibu, R. J. Burchmore, I. H. Gilbert, M. Trybilo, N. N. Driessen, D. Gilbert, , ,

Date Published: 5th Dec 2013

Publication Type: Not specified

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