|PRIMe: Platform for RIKEN Metabolomics|
Atsushi Fukushima, Miyako Kusano, Kenji Akiyama, Takeshi Obayashi, Takayuki Tohge, Masami Yokota Hirai, Shigehiko Kanaya, Masanori Arita, Yoko Shinbo, Kazuo Shinozaki, Tetsuya Sakurai and Kazuki Saito
We have developed a web-based database, "PRIMe (Platform for RIKEN Metabolomics)," which contains powerful tools for researchers to analyze gene co-expression data and mass spectral data. PRIMe has been developed with the main aim of facilitating integrated analysis for transcriptomics and metabolomics.
|Proteomic Profiling in Defining Chemoresistant Breast Cancer|
Chuthapisith S, Layfield R, Kerr I, Hughes C and Eremin O
This study aims to identify protein profiles in breast cancer cells as predictors of chemoresistance by using two-dimensional gel electrophoresis and MALDI-TOF peptide mass fingerprinting. Our findings provide further insights into the complex mechanisms of chemoresistance, as well as representing an attractive starting point for the identification of potential protein biomarkers to predict response to chemotherapy in breast cancer in vivo.
|Kinetic Constants and Sample-to-Sample Variation in the Rate of Metabolism of two or more Substrates for Human Liver Microsomal CYP1A2, CYP2B6, CYP2C8, CYP2D6 and CYP3A4/5|
Zell Woodworth, L. Anne Dwyer, Lisa Collins, Terry Graves, Stephanie Helmstetter, Brian Ogilvie, Clayton Otwell, Chad Pope, Tiffin Ramsey, Phyllis Yerino and Andrew Parkinson
Marker substrates for certain CYPs have changed for several reasons, including the need for improved selectivity and sensitivity, reliable substrates for LC/MS/MS analysis, and substrates that provide greater repeatability. The objectives of this study were to compare sample-to-sample variation in cytochrome P450 enzymatic rates between two or more CYP-specific substrates and to determine Michaelis-Menten kinetic constants for these same reactions using a pool of human liver microsomes.
|Evaluation of Different Interpretation Strategies to Discover PTM in MS/MS Peptide Fragmentation Data|
Daniel Chamrad, Gerhard Korting, Ken Fantom, Andy West, Klaus Schneider, Ulrike Schweiger-Hufagel, Herbert Thiele and Martin Bluggel
The phenomenon of acquired high quality MS/MS spectra that can not be explained within typical sequence database searches is well known. Although protein identification was successful it is manually very laborious and in most cases even impossible to match these spectra with any suggested protein sequence. The procedure of second pass searches has been developed to overcome this problem. Here we report from our in house developed tool PTM-Explorer.
|Towards Understanding of Ryegrass-Endophyte Symbiosis through Data Integration of Transcriptome and Metabolome|
Mingshu Cao, Linda Johnson, Albert Koulman, Geoff Lane and Susanne Rasmussen
Combined with extensive bioinformatics analyses, our joint analysis of transcriptomics and metabolomics data has generated interesting findings which led to further laboratory verification, such as potential genes associated with alkaloid production.
|Herbal Metabolic Profiling of Raw and Steamed Panax notoginseng|
Eric C.Y. Chan, Swee-Lee Yap, Aik-Jiang Lau, Pay-Chin Leow, Ding-Fung Toh, and Hwee-Ling Koh
At present, metabolite profiling is of growing importance in herbal medicine fields such as breeding, formulation, quality control and clinical trials. Herbal metabolic profiling allows direct detection of down-stream derivatives of metabolites, arising from herbal formulation process, using metabolite profiling ultra performance liquid chromatography time-of-flight mass spectrometry.
|Metabolic Profiling of Human Blood Plasma by Combined Ultra Performance Liquid Chromatography / Mass Spectrometry|
Steve Bruce, Pär Jonsson, Henrik Antti, Olivier Cloarec, Stefan Marklund and Thomas Moritz
Metabolic profiling is concerned with the analysis of low molecular weight compounds present in complex samples such as plasma. Analytical techniques such as UPLC/MS are proving to be powerful tools for metabolic profiling on complex samples such as plasma. Here we describe a protocol of metabolic profiling analysis on plasma by UPLC/MS.
|Effective Fishing of Characteristic Proteome Fractions and Identification of Biomarkers Therein: Application of VisualCockpit to Multidimensional Chromatogram and MS Data|
S. Kreusch, M. Nagel, R. Janetzko, G. A. Cumme, A. Winter, M. Pohl, A. Meier-Hellmann and H. Rhode
Characteristic 2D fractions are rapidly identified among thousands using interactive visualization, filtering and data mining with VisualCockpit. Biomarker candidates are found therein after identifying proteins from sequence tags. VisualCockpit correlates their concentrations, reflected by normalized MS peptide peak height sum, enzyme activity and immunoreactivity, to donor conditions.
|Automated Profiling and Identification of Endogenous Peptidomic Markers in Human Plasma|
T. Richmond, M. Askenazi, J. Sutton and L. Bonilla
Development of robust methods that include the accurate identification of the relevant components of the peptidome is critical not only to our understanding of the biology of disease states, but also to our ability to discover markers for these states.