M MetaboScape 2.0 Quickly Discover Metabolite Biomarkers and Use Pathway Mapping to Set them in a Biological Context Innovation with Integrity Metabolomics
Providing a New Layer of Insight to Metabolomics Integrate your Metabolomics data analysis: The growing number of detectable and identifiable substances increases the need for efficient data analysis and interpretation Observing significant changes in abundances of unknowns is equally important to interpreting known target compounds Metabolic pathways are essential to structure existing biochemical knowledge Automated and confident compound identification is the basis for metabolic pathway mapping Linking experimental data to biology by pathway mapping in non-targeted metabolomics. Deeper insights by combining non-targeted and targeted metabolomics workflows Hypothesis generation Full scan LC-MS data (MS/MS) M Non-targeted metabolite discovery and ID Pathway mapping Novel hypothesis Pathway directed targeted data mining Knowledge
From Mass Spectrometric Data... Hypothesis + experimental design Full scan high resolution LC-QTOF-MS/MS data Pathway mapping Prove or redesign hypothesis Set your results into a biological context Mapping of results to biochemical pathway maps completes the loop and can lead to validating a hypothesis in a targeted approach, or formulating a novel hypothesis.
Sophisticated bucketing, filtering, scaling and normalization to match experimental designs ProfileAnalysis easily creates bucket tables of LC-MS data based on the extracted FMF compounds. Retention time alignment as well as different filtering, normalization and scaling options complete the set of data preprocessing tools - a prerequisite for large metabolomics studies. De-replication / Known ID Extract and combine all relevant information The Find Molecular Features (FMF) algorithm in ProfileAnalysis automatically extracts and combines all relevant information, even from very complex LC-MS/ MS data sets. It combines the ions belonging to the same compound into one feature, i.e. isotopes, charge states, adducts or fragments. Powerful data reduction helps to separate real signals from noise. Automatic and confident identification of known compounds, called de-replication, is essential to fully understand the biological context of metabolomics data. Confidence in ID is provided by matching retention time, accurate mass, isotopic pattern information, and MS/MS spectral library spectra according to user definable threshold levels and graphical representation of the achieved Annotation Quality. Statistics Unknown ID Non-targeted data extraction Data preprocessing... to Biological Insight Seamless annotation of compounds Annotation of unknowns by automated molecular formula generation followed by structural assignment through public database queries and in-silico fragmentation of structure candidates. Quickly identify relevant information in complex data sets Using supervised and non-supervised statistics quickly focuses on the relevant information in your data set. Statistics include PCA, t-test, ANOVA, PLS and bucket correlation analysis combined with dedicated views as illustrated above.
Turbocharge Your Research Further Reading Bruker Poster Note: PN-26 MetaboScape: Linking HRAM QTOF Data to Biology Increasing Arginine Production in C. glutamicum by Rational Strain Design and Discovery Metabolomics Bruker Poster Note: PN-27 Identification of the Biosynthetic Function of Genes in Plants and their Consequences in Insects a Metabolite Profiling Approach Driven by Automatic Compound Identification Bruker Poster Note: PN-33 Boosting compound identification confidence by exploiting all HRAM spectral information integrating accurate mass, true isotopic pattern, in-source fragmentation, MS/MS fragmentation, and retention time Prof. Jörn Kalinowski, Center for Biotechnology, Bielefeld University, Germany Using MetaboScape we were able to increase arginine production in Corynebacterium glutamicum by rational strain design and discovery metabolomics. MetaboScape offers automatic identification of the relevant compounds related to arginine biosynthesis in C. glutamicum and mapping those on biochemical pathway maps enabled quick formulation of a hypothesis for the observed changes in the biological context. Since C. glutamicum is a bacterium of global importance used for amino acid production in nutrition and health applications, this has great economic potential. Prof. Ian T. Baldwin, Max Planck Institute for Chemical Ecology, Jena, Germany MetaboScape enabled my team to mine complex plant metabolomics in a fraction of the time compared to the intensive manual work required before. Sven Heiling, Max Planck Institute for Chemical Ecology, Jena, Germany and in addition MetaboScape enabled more confident de-replication of known compounds as well as establishing their biological significance in the context of chemical ecology by the pathway mapping functionality.
Bruker Daltonics is continually improving its products and reserves the right to change specifications without notice. BDAL 07-2016, 1845956 Think Biology! In the past decade modern metabolomics has quickly grown and become widely adopted. The growing number of detectable substances increases the need for efficient processing: confident annotation of known metabolites must be automatic, and identification of unknowns should be seamless. Metabolic pathways are essential to structure existing biochemical knowledge. Quickly pinpoint and identify biomarkers in discovery metabolomics and use pathway mapping to set them in a biological context thereby turning LC-QTOF-MS/MS data into knowledge. Gain Deeper Insights MetaboScape 2.0 software Higher throughput Automatic ID of known compounds Seamless annotation of unknowns New client-server architecture accelerates data mining by allowing multiple users to access data simultaneously More reliable results User definable confidence levels for high quality target compound ID Improved SmartFormula3D for MS and MS/MS data evaluation Confident de-replication including MS/MS spectral library queries Deeper insights By setting data into a biological context via mapping of results on pathway maps Fully integrated online DB query combined with in-silico fragmentation for structure assignment Comprehensive and automated workflows Comprehensive solutions Together with Bruker Compass PathwayScreener, both targeted and non-targeted experiments are now supported Supporting Bruker HMDB Metabolite Library TM and Bruker MetaboBASE Personal Library TM for local and automatic MS/MS spectra queries For research use only. Not for use in diagnostic procedures. Bruker Daltonik GmbH Bremen Germany Phone +49 (0)421-2205-0 Fax +49 (0)421-2205-103 Bruker Daltonics Inc. Billerica, MA USA Phone +1 (978) 663-3660 Fax +1 (978) 667-5993 ms.sales.bdal@bruker.com - www.bruker.com