GEN-MKT-18-7897-A
Nov 16, 2018 | Blogs, Life Science Research, Metabolomics | 0 comments
The direct correlation of the metabolome to the phenotype means metabolomics is one of the most sought-after approaches for the study of disease and wellness, yet the separation, detection, quantification, and unambiguous identification of a chemically diverse network of compounds ranging from small polar organic acids through to large multi-chain fatty acids and lipids is a daunting analytical challenge. Consequently, the field of metabolomics is driven by the development of new and novel analytical approaches aimed at broadening metabolome coverage, analysis of particularly challenging metabolites of interest or facilitating the task of metabolite identification and quantitative data from large complex datasets.
This month, The Analytical Scientist named its annual “Power List” of 40 researchers under the age of 40 in celebration of the “rising stars” of analytical science. Several leading young metabolomics scientists were named on the list, recognized for their contribution to the development of novel analytical approached within this challenging field.
Rawi Ramautar, University of Leiden, Netherlands was included on the list for his pioneering work in the field of capillary electrophoresis-mass spectrometry applied to the separation and quantification of metabolites that are ordinarily challenging to analyze by traditional LC-MS approaches. “My fascination for metabolomics research is especially driven by analytical technology method development,” Ramautar said, “In particular I’m interested in highly polar charged metabolites, for which we definitely need new analytics to analyze them in a reliable manner.” Ramautar has worked closely with SCIEX on the application of the CESI 8000 to clinically-relevant metabolomics approaches1.
Also included in the list were Tomas Cajka of CAS, Prague, Czech Republic and Hiroshi Tsugawa of RIKEN Center for Sustainable Resource Science, Yokohama, Japan, two of the leading pioneers in developing a software pipeline for processing of SWATH® Acquisition data for metabolomics. Their contribution to the development of the MS DIAL software pipeline allows researchers to use comprehensive data independent analysis with SWATH Acquisition for metabolite identification and quantitation in untargeted metabolomics2. Cajka is passionate about the need for MSMS data in untargeted metabolomics and explains the need for comprehensive approaches in his talk on the SCIEX online metabolomics symposium.
Michael Witting of Helmholtz Zentrum München, Neuherberg, Germany also made the list for his work on developing novel approaches for profiling the metabolome and lipidome of Caenorhabditis elegans.
Gary Patti of Washington University in St Louis was recognized for his contribution to the development of isotope tracing methods for probing metabolic reactions. Patti’s research focuses on developing new metabolomic technologies to facilitate the identification of new and novel metabolites that are currently not present in characterized pathway maps. He has published a host of papers on optimized approaches for untargeted metabolomics, as well as using metabolomics to study the differential metabolism of cancer cells at a mechanistic level.
Rawi and Tomas both feature in our metabolomics online symposium. Register now to find out more about their pioneering research!
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In biopharmaceutical development, sequence variants (SV) are considered an inherent risk of producing complex proteins in living systems. Sequence variants are unintended changes to the amino acid sequence of a biotherapeutic and can be caused by errors in transcription or translation in the host cell, or cell culture and process conditions. Detailed analysis of SVs is important in process and product development to ensure the drug’s safety and efficacy. Even low‑level sequence variants can have significant implications for product quality, safety, and efficacy, making their accurate detection and characterization a critical requirement across development, process optimization, and regulatory submission.
CE‑SDS remains a cornerstone assay for characterizing fragmentation, aggregation, and product‑related impurities in therapeutic proteins. UV detection has been the long‑standing standard. However, it frequently struggles with baseline noise, limited sensitivity for minor fragments, and subjective integration.
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