GNPS - DDA Optimization method of Q exactive HF using complex samples
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ABSTRACT: DDA untargeted metabolomics of 3 different complex samples coming from river, ocean, and soil sources was used to obtain the best optimization setting.
Project description:DDA untargeted metabolomics of 3 different complex samples coming from river, ocean, and soil sources was used to obtain the best optimization setting.
Project description:Untargeted-metabolomics LC-MS/MS analysis of commercial natural products pool, analyzed with different DDA settings with the objective to find the best one.
Project description:Untargeted-metabolomics LC-MS/MS analysis of commercial natural products pool, analyzed with different DDA settings with the objective to find the best one.
Project description:A high-confidence map of the direct, functional targets of each transcription factor (TF) requires convergent evidence from independent sources. Two significant sources of evidence are TF binding locations and the transcriptional responses to direct TF perturbations. Systematic data sets of both types exist for yeast and human. Standard analysis of the genes whose regulatory DNA is bound by a TF, assayed by ChIP-chip/seq, and the genes that respond to a perturbation of that TF, shows that these two data sources rarely converge on a common set of direct, functional targets. Even taking the few genes that are both bound and responsive as direct functional targets is not safe -- when there are many non-functional binding sites and many indirect targets, non-functional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. To address this problem, we introduce Dual Threshold Optimization, a new method for setting significance thresholds on binding and response data, and show that it improves convergence. It also enables comparison of binding data to perturbation-response data that has been processed by network inference algorithms, which further improves convergence. Next, we analyze a comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a yeast TF. We also present a new yeast binding location data set obtained by transposon calling cards and compare it to recent ChIP-exo data. The combination of dual threshold optimization and network inference greatly expands the high-confidence TF network map in both yeast and human. In yeast, measuring the response shortly after inducing TF overexpression and measuring binding locations by using transposon calling cards or ChIP-exo improve the network synergistically.
Project description:Optimization of Solid Phase Extraction Columns (C18, HBL, PPL) for non-targeted LC-MS/MS analysis of river dissolved organic matter.
Project description:A computational model of underground metabolism and laboratory evolution experiments were employed to examine the role of enzyme promiscuity in the acquisition and optimization of growth on predicted non-native substrates in E. coli K-12 MG1655. After as few as 20 generations, the evolving populations repeatedly acquired the capacity to grow on five predicted novel substrates--D-lyxose, D-2-deoxyribose, D-arabinose, m-tartrate, and monomethyl succinate--none of which could support growth in wild-type cells. Promiscuous enzyme activities played key roles in multiple phases of adaptation. Potential mechanisms for optimizing growth on the non-native carbon sources were explored by analyzing the transcriptomes of initial and endpoint populations.