miR-145-5p and miR-203a-5p overcome imatinib resistance in myelogenous leukemic cells through metabolic reprogramming-Supplemenntary data

Imatinib is the most effective therapy for chronic myeloid leukemia (CML), but many patients eventually develop resistance to it after an initial satisfactory response. This study investigated the potential of three miRNAs (miR-106b-5p, miR-145-5p, miR-203a-5p) in overcoming imatinib resistance in leukemic cells. The imatinib-resistant K562 (IR-K562) cells were developed and transfected with one of the three miRNAs to evaluate their potency in overcoming imatinib resistance. The changes in the metabolic profile were studied using flux balance analysis (FBA) and the data was validated using qRT-PCR.Among the three miRNAs, the ectopic expression of either miR-145-5p or miR-203a-5p was able to sensitize the IR-K562 cells to imatinib. The concentration of key oncometabolites; glucose, lactate, and glutamine, in the culture media of the miR-transfected IR-K562 cells, reverted to the same levels as seen in imatinib-sensitive K562 cells. In addition, the FBA analysis revealed that the metabolism of lipid, fatty acids, and electron transport chain were significantly altered in resistant cells. The FBA data was also validated at the molecular level. Interestingly, the imatinib treatment coupled with the transfection of miR-145-5p or miR-203a-5p cells could reverse the metabolic flux of IR-K562 to the levels seen in imatinib-sensitive K562 cells. This study highlights the key metabolic changes that occur during development of imatinib resistance. It also identifies the specific miRNAs which can be targeted to overcome imatinib resistance in CML.

miR-145-5p and miR-203a-5p overcome imatinib resistance in myelogenous leukemic cells through metabolic reprogramming

Imatinib is the most effective therapy for chronic myeloid leukemia (CML), but many patients eventually develop resistance to it after an initial satisfactory response. This study investigated the potential of three miRNAs (miR-106b-5p, miR-145-5p, miR-203a-5p) in overcoming imatinib resistance in leukemic cells. The imatinib-resistant K562 (IR-K562) cells were developed and transfected with one of the three miRNAs to evaluate their potency in overcoming imatinib resistance. The changes in the metabolic profile were studied using flux balance analysis (FBA) and the data was validated using qRT-PCR.Among the three miRNAs, the ectopic expression of either miR-145-5p or miR-203a-5p was able to sensitize the IR-K562 cells to imatinib. The concentration of key oncometabolites; glucose, lactate, and glutamine, in the culture media of the miR-transfected IR-K562 cells, reverted to the same levels as seen in imatinib-sensitive K562 cells. In addition, the FBA analysis revealed that the metabolism of lipid, fatty acids, and electron transport chain were significantly altered in resistant cells. The FBA data was also validated at the molecular level. Interestingly, the imatinib treatment coupled with the transfection of miR-145-5p or miR-203a-5p cells could reverse the metabolic flux of IR-K562 to the levels seen in imatinib-sensitive K562 cells. This study highlights the key metabolic changes that occur during development of imatinib resistance. It also identifies the specific miRNAs which can be targeted to overcome imatinib resistance in CML.

Topological analysis of carbon flux during multi-stress adaptation in Halomonas sp. AAD12

Background Osmolytes with their effective stabilizing properties are accumulated as protectants not only against salinity but also against denaturing harsh environmental stresses such as freezing, drying, high temperatures, oxygen radicals and radiation. The present work seeks to understand how Halomonas sp. AAD12 cells redirect carbon flux specifically to replenish reactions for biomass and osmolyte synthesis under changing salinity and temperature. To accomplish this goal, a combined FBA-PCA approach has been utilized. Results Experimental data were collected to supply model constraints for FBA and for the verification of the model predictions, which were satisfactory. With restrictions on the various combinations of selected anaplerotic paths (reactions catalyzed by phosphoenolpyruvate carboxylase, pyruvate carboxylase or glyoxylate shunt), two major phenotypes were found. Moreover, under high salt concentrations, when the glucose uptake rate was over 1.1 mmoL DCW- 1 h- 1, an overflow metabolism that led to the synthesis of ethanol caused a slight change in both phenotypes. Conclusions The operation of the glyoxylate shunt as the major anaplerotic pathway and the degradation of 6-phosphogluconate through the Entner-Doudoroff Pathway were the major factors in causing a distinction between the observed phenotypes.

Balance de Flujos Metabólicos en Saccharomyces cerevisiae basado en Compartimentalización Intracelular / Metabolic Flows Balance in Saccharomyces cerevisiae based on Intracellular Compartmentalization

Una de las técnicas más utilizadas para la predicción de producción de bioproductos y distribución intracelular de flujos de microorganismos es el Análisis de Balance de Flujos - FBA por sus siglas en inglés. El FBA requiere de una función objetivo que represente el objetivo biológico del microorganismo estudiado. En este trabajo se propone un nuevo tipo de funciones objetivo basada en la combinación de objetivos de compartimentos físicos presentes en el microorganismo estudiado. Este tipo de funciones objetivo son examinadas junto con un modelo estequiométrico extraído de la reconstrucción iMM904 del microorganismo S. cerevisiae. Su desempeño se compara con la función objetivo más usada en la literatura, la maximización de biomasa, en condiciones experimentales anaeróbicas en cultivos continuos y aeróbicas en cultivos tipo lote. La función objetivo propuesta en este trabajo mejora las predicciones de crecimiento en un 10% y las predicciones de producción de etanol en un 75% respecto a las obtenidas por la función objetivo de maximización de biomasa, en condiciones anaeróbicas. En condiciones aeróbicas tipo lote la función objetivo propuesta mejora en un 98% las predicciones de crecimiento y en un 70% las predicciones de etanol con respecto a la función objetivo de biomasa.

Flux Balance Analysis - FBA - is one of the most used techniques in prediction of microorganism bioproducts. It requires an objective function that represents biological objective of the studied microorganism. This paper presents a new kind of objective functions based on individual physical compartment objetives in the studied microorganism. These kind of functions was tested with a stoichiometric model extracted from iMM904 reconstruction of S. cerevisiae and its performance is compared with the most used objective function in literature, growth maximization, in anaerobic and aerobic batch conditions. The presented objective function outperform growth predictions in 10% and ethanol predictions in 75% compared with obtained by maximization of growth objective function, in anaerobic conditions. In aerobic batch conditions the presented objective function outperforms in 98% growth preditions and 70% ethanol predictions compared with growth maximization.

Predicción a escala genómica de Componentes de Saccharomyces cerevisiae mediante Análisis de Balance de Flujos / Prediction of genome scale of Saccharomyces cerevisiae by flux balance analysis

El microorganismo Saccharomyces cerevisiae cuenta con gran número de modelos biológicos conocidos como reconstrucciones, las cuales pueden ser a escala genómica. De estas reconstrucciones a escala genómica provienen los modelos matemáticos, también llamados modelos estequiométricos. Una de las técnicas más usadas para estudiar estos modelos es el Análisis de Balance de Flujos (FBA). El proposito del FBA es predecir el crecimiento del microorganismo bajo estudio, y la producción y consumo de componentes como el etanol, CO2 glicerol, sucinato, acetato y piruvato. Para determinar si las predicciones obtenidas mediante FBA son únicas se utiliza la técnica de Análisis de Variabilidad Flujos (FVA). El presente trabajo muestra los resultados de aplicar el FBA a la reconstrucción reciente del microorganismo S. cerevisiae, la denominada iMM904 y los compara con un conjunto de datos experimentales presente en la literatura. Este trabajo también estudia la existencia de múltiples predicciones FBA utilizando la técnica FVA. Los resultados ilustran que es posible predecir el crecimiento del microorganimo S. cerevisiae, con errores entre el 11% y 28%; la producción de CO2, con errores entre el 0.3% y 4.5% y la producción de etanol, con errores entre el 11% y 13%.

Several biological models, named reconstructions, are used for the study of the S. cerevisiae microorganism. The reconstructions can be genomic scaled. Mathematical models are generated from the reconstructions and they are called stoichiometric models. The flux balance analysis (FBA) is one of the tools used for the analysis of these models. The FBA attempts to predict the evolution of the microorganism and the consumption and production of components like glucose, ethanol, glycerol, succinate, acetate and pyruvate. A Flux variability analysis (FVA) is used to determine the uniqueness of the FBA predictions. This paper shows the results of applying FBA to the iMM904 reconstruction of S. cerevisiae and compares them with experimental data from literature. The results in this paper show that it is possible to predict the evolution with errors between 11% and 28% ; the production of CO2 with errors between 0.3% and 4.5%; and the production of ethanol with errors between 11% and 13%, using FBA for the iMM904 model.