PredRet: Prediction of Retention Time by Direct Mapping between Multiple Chromatographic Systems
Poster Nov 27, 2015
Jan Stanstrup, Steffen Neumann, Urška Vrhovšek
Demands in metabolomics research have been a key motivator for the development of repositories for MS spectra1,2 and automated tools to aid compound identification3–5. But utilizing only fragmentation is ignoring half of the available information in LC-MS. The retention time (RT) is equally important.
For LC systems there are currently no coordinated efforts to share and exploit information regarding RT. The reason RT information has been neglected is that the RT is specific to the chromatographic system (CS) and there exist no agreed upon RT references.
A database of compound RTs in different CSs was therefore developed. For each pair of CSs, the RTs are used to construct a projection model between the RTs in the two CSs. Building these models between all CSs allowed the prediction of RTs for a high number of compounds in CSs where they had not been experimentally determined.
With the current small database it was possible to predict up to 400 RTs with a median error between 0.01 and 0.11 min depending on the CS. The median width of the confidence interval for predictions ranged from 0.1 to 0.8 min.
The free, open source and web-based tool is available at predret.org.
Nitrogen metabolism in Mycobacterium tuberculosis: a systems-based approachPoster
Previous studies suggested that Mycobacterium tuberculosis obtains nitrogen from a diverse range of intracellular nutrients including amino acids. Here, we use a novel system’s based three-pronged approach to define pathways for uptake and assimilation of nitrogen.READ MORE
IntelliXtract 2.0: Simplified Intelligent Component Extraction and DetectionPoster
*Simplified detection and Component Extraction algorithm from LC-MS and GC-MS datasets
*New improved algorithm based on ion threads
*Reduced number of parameters to select for analysis
*Reduced false positives leading to reduced analysis time
Role of Elevated Airway Glucose (and Other Biochemicals) in Bacterial InfectionsPoster
Bacteria that live in the airways need something to eat: they mainly use host derived biochemicals, for example glucose. When levels of airway biochemicals are dysregulated, bacterial colonisation increases, enabling infection. We investigated how changes in airway glucose effect bacterial infection.READ MORE