Project description:Nitrogen fixation is an important metabolic process carried out by microorganisms, which converts molecular nitrogen into inorganic nitrogenous compounds such as ammonia (NH3). These nitrogenous compounds are crucial for biogeochemical cycles and for the synthesis of essential biomolecules, i.e. nucleic acids, amino acids and proteins. Azotobacter vinelandii is a bacterial non-photosynthetic model organism to study aerobic nitrogen fixation (diazotrophy) and hydrogen production. Moreover, the diazotroph can produce biopolymers like alginate and polyhydroxybutyrate (PHB) that have important industrial applications. However, many metabolic processes such as partitioning of carbon and nitrogen metabolism in A. vinelandii remain unknown to date.
Genome-scale metabolic models (M-models) represent reliable tools to unravel and optimize metabolic functions at genome-scale. M-models are mathematical representations that contain information about genes, reactions, metabolites and their associations. M-models can simulate optimal reaction fluxes under a wide variety of conditions using experimentally determined constraints. Here we report on the development of a M-model of the wild type bacterium A. vinelandii DJ (iDT1278) which consists of 2,003 metabolites, 2,469 reactions, and 1,278 genes. We validated the model using high-throughput phenotypic and physiological data, testing 180 carbon sources and 95 nitrogen sources. iDT1278 was able to achieve an accuracy of 89% and 91% for growth with carbon sources and nitrogen source, respectively. This comprehensive M-model will help to comprehend metabolic processes associated with nitrogen fixation, ammonium assimilation, and production of organic nitrogen in an environmentally important microorganism.
Project description:The aim of this study was to extend our analysis to the obligate human pathogen M. tuberculosis, which has to deal with a more restricted set of environmental variables in terms of nitrogen sources, and to delineate the GlnR regulon, by peforming global analysis of GlnR-DNA interactions by Chromatin Immunoprecipitation and high-throughput sequencing (ChIP-seq) over nitrogen run-out.
Project description:We developed a general approach to small molecule library screening called GE-HTS (Gene Expression-Based High Throughput Screening) in which a gene expression signature is used as a surrogate for cellular states and applied it to the identification of compounds inducing the differentiation of acute myeloid leukemia cells. In screening 1,739 compounds, we identified 8 that reliably induced the differentiation signature, and furthermore yielded functional evidence of bona fide differentiation. This SuperSeries is composed of the following subset Series:; GSE976: Gene Expression-Based High Throughput Screening: APL Treatment with Candidate Compounds; GSE982: Gene Expression-Based High Throughput Screening: HL-60 Cell Treatment with Candidate Compounds; GSE983: Gene Expression-Based High Throughput Screening: Primary Patient AML Blasts, Normal Neutrophils, and Normal Monocytes; GSE985: Gene Expression-Based High Throughput Screening: HL-60 Cells Treated with ATRA and PMA Experiment Overall Design: Refer to individual Series
