March 14 - 17, 2017
Meet Genedata Expressionist experts at CASSS AT Europe in Brussles, BE at booth #4.
To get more information about Genedata solutions, please contact firstname.lastname@example.org
Sampling the globe – How to handle unlimited sample diversity in mass spectrometry data for biotechnology discovery and development
Anders Giessing, PhD, Research Scientist, Novozymes A/S
Thursday, March 16 | 15:50 - 16:20
Next-At Novozymes we produce a wide range of industrial enzymes and microorganisms. Enzymes are proteins, and in nature they initiate biochemical reactions in all living organisms. It is enzymes that convert the food in our stomachs to energy and turn the falling leaves in the forest to compost. Novozymes finds enzymes in nature and optimizes them for use in industry. In industry, enzymes replace chemicals and accelerate production processes. They help our customers make more from less, while saving energy and generating less waste. Enzymes are widely used in laundry and dishwashing detergents and to improve the quality of bread, beer and wine, or increase the nutritional value of animal feed. Enzymes are also used in the production of biofuels where they turn starch or cellulose from biomass into sugars which can be fermented to ethanol.
Mass spectrometry (MS) is a key technology for characterizing the sequence, structure and function of enzymes. Before mass spectrometry data can be transformed into innovation, the raw instrument code needs to be translated from machine language into protein sequence. This is typically done using proprietary software developed by the instrument vendor, a peptide search engine such as Mascot if doing bottom-up proteomics, or one of an ever-growing suite of open-source single usage dedicated software developed by academia. At the Novozymes Mass Spectrometry core facility in Bagsværd, Denmark we have for the past two years used Genedata Expressionist® as a platform for all MS data analysis. In this presentation I will demonstrate the versatility of the Genedata Expressionist platform for MS data analysis across some of our industries, from simple protein identification using classical SDS-Page in-gel analysis, over through intact protein top-down sequencing, to more complex bottom-up proteomics experiments of host cell proteins and the influence of dietary interventions on endogenous proteins in chickens.
Automated Workflow for the Host Cell Protein Monitoring by Mass Spectrometry: From Raw Data to Final Report
Marlis Zeiler, Ph.D., Genedata
Automated Data Processing for Quality Monitoring of Biotherapeutics by Multi-attribute Methods (MAMs)
Arnd Brandenburg, PhD, Genedata