Project description:Acetic acid bacteria are obligately aerobic alphaproteobacteria that have a unique ability to incompletely oxidize various alcohols and sugars to organic acids. The ability of these bacteria to incompletely oxidize ethanol to acetate has been historically utilized for vinegar production. The mechanism of switching between incomplete oxidation and assimilatory oxidation and the control of energy and carbon metabolism in acetic acid bacteria are not fully understood. To understand the physiology and molecular biology of acetic acid bacteria better, we determined the draft genome sequence of Acetobacter aceti NBRC 14818, which is the type strain of the genus. Based on this draft genome sequence, the transcriptome profiles in A. aceti cells grown on ethanol, acetate, glucose, or mix of ethanol and glucose was determined by using NimbleGen Prokaryotic Expression array (4x72K). Acetobacter aceti NBRC14818 was cultivated in the medium containing ethanol, acetate, glucose, or mix of ethanol and glucose as carbon sources in Erlenmeyer flask with rotary shaking. Total RNA was extracted when optical density at 600 nm was 0.3-0.4. The experiment was performed in duplicate independent cultures.
Project description:Resistance to agricultural fungicides in the field has created a need for discovering fungicides with new modes of action. DNA microarrays, because they provide information on expression of many genes simultaneously, could help to identify the modes of action. To begin an expression pattern database for agricultural fungicides, transcriptional patterns of Saccharomyces cerevisiae strain S288C genes were analysed following 2-h treatments with I50 concentrations of ergosterol biosynthesis inhibitors commonly used against plant pathogenic fungi. Eight fungicides, representing three classes of ergosterol biosynthesis inhibitors, were tested. To compare gene expression in response to a fungicide with a completely different mode of action, a putative methionine biosynthesis inhibitor (MBI) was also tested. Expression patterns of ergosterol biosynthetic genes supported the roles of Class I and Class II inhibitors in affecting ergosterol biosynthesis, confirmed that the putative MBI did not affect ergosterol biosynthesis, and strongly suggested that in yeast, the Class III inhibitor did not affect ergosterol biosynthesis. The MBI affected transcription of three genes involved in methionine metabolism, whereas there were essentially no effects of ergosterol synthesis inhibitors on methionine metabolism genes. There were no consistent patterns in other up- or downregulated genes between fungicides. These results suggest that inspection of gene response patterns within a given pathway may serve as a useful first step in identifying possible modes of action of fungicides. agricultural sterol biosynthesis inhibitor fungicides. Keywords = agriculture Keywords = ergosterol Keywords = methionine Keywords = fungicide Keywords = Saccharomyces cerevisiae S288C Keywords = biosynthesis
Project description:Resistance to agricultural fungicides in the field has created a need for discovering fungicides with new modes of action. DNA microarrays, because they provide information on expression of many genes simultaneously, could help to identify the modes of action. To begin an expression pattern database for agricultural fungicides, transcriptional patterns of Saccharomyces cerevisiae strain S288C genes were analysed following 2-h treatments with I50 concentrations of ergosterol biosynthesis inhibitors commonly used against plant pathogenic fungi. Eight fungicides, representing three classes of ergosterol biosynthesis inhibitors, were tested. To compare gene expression in response to a fungicide with a completely different mode of action, a putative methionine biosynthesis inhibitor (MBI) was also tested. Expression patterns of ergosterol biosynthetic genes supported the roles of Class I and Class II inhibitors in affecting ergosterol biosynthesis, confirmed that the putative MBI did not affect ergosterol biosynthesis, and strongly suggested that in yeast, the Class III inhibitor did not affect ergosterol biosynthesis. The MBI affected transcription of three genes involved in methionine metabolism, whereas there were essentially no effects of ergosterol synthesis inhibitors on methionine metabolism genes. There were no consistent patterns in other up- or downregulated genes between fungicides. These results suggest that inspection of gene response patterns within a given pathway may serve as a useful first step in identifying possible modes of action of fungicides. agricultural sterol biosynthesis inhibitor fungicides. Keywords = agriculture Keywords = ergosterol Keywords = methionine Keywords = fungicide Keywords = Saccharomyces cerevisiae S288C Keywords = biosynthesis
Project description:Model topology is divided into two compartments, cell programming and performance testing. The cell programming compartment is split into history and pre-treatment. History ( History I or H1: E.coli grown for 18hrs in LB flask, transferred to fresh LB flask after that. History II or H2: E.coli grown for 18hrs in LB flask, transferred to fresh LB flask for 45 min. From this flask, 0.1O.D./ml transferred to rich medium and grown for 4 hours. From this,0.1O.D./ml transferred to fresh rich medium. History III or H3: E.coli grown for 18hrs in LB flask, transferred to fresh LB flask for 45 min. From this flask, 0.1O.D./ml transferred to starvation medium and grown for 4 hours. From this,0.1O.D./ml transferred to fresh starvation medium. Pre-treatment (Pre-treatment 1(T1): 2.5g glucose/litre 5mM NH4Cl. Pre-treatment 2 (T2): 2.5g glucose/litre 0.25mM NH4Cl. Pre-treatment 3 (T3): - 0.25g glucose/litre 5mmM NH4Cl. Pre-treatment 4 (T4): 0.25g glucose/litre 0.25mM NH4Cl). Each pre-treatment given for 2.5 hours.The culture nomenclature indicates the adaptive path followed, for example, H1T1 indicates the culture has encountered history I (H1) and then transferred to pre-treatment 1 (T1).RNA was extracted for selected combinations. Performance testing : Performance testing describes the type of analysis done which is the growth pattern study onto three substrates, glucose, succinate and pyruvate. This performance testing revealed specific history-pretreatment combinations to be better suited for growth on certain substrate and some not suited for growth. The samples were harvested for RNA isolation at peak growth points and named worst_glucose, best_glucose,worst_succinate, best_succinate, worst_pyruvate and best_pyruvate according to the growth shown after testing all 12 history-pretreatment combinations. The differences in physiology were studied in details using microarray analysis of 13 samples including 3 history samples, 4 pre-treatment samples and 6 samples at performance testing level. RNA extraction was done using Qiagen RNeasy minikit (Germany). Standard Affymetrix protocol was followed for hybridization on Affymetrix E. coli Genome 2.0 Array.