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July 17, 2019
Sponsored by
GenomeWeb/ABRF

Expert Tips on Running a Mass Spec Core Lab Amid Rapid Technological Change

GenomeWebinar

Chief Scientific Officer,
Proteomic and Genomic Sciences

Assistant Professor and the Director of the Mass Spectrometry Core,
Buck Institute for Research on Aging

Manager, Proteomics Core,
UC Davis Genome Center

In this webinar, three experts share advice on how to efficiently manage a mass spectrometry core lab while staying ahead of the technology curve.

Our first speaker, Benjamin Orsburn of Proteomic and Genomic Sciences, discusses how core lab managers can balance efficiency and quality while keeping up with advances in mass spectrometry. As groundbreaking new techniques bring customers flocking to core labs with high expectations, the goalpost for maintaining “quality” can appear to be constantly moving. Dr. Orsburn describes extreme examples of core lab management principles that can help make time for R&D to add new lab techniques.   

Our second speaker, Birgit Schilling of the Buck Institute for Research on Aging,  discusses how her lab uses data-independent acquisition (DIA) workflows for a variety of collaborative projects, including small studies and larger scale projects. Dr. Schilling shares the criteria her team uses to decide whether to use published spectral libraries or to apply data-dependent acquisitions (DDA) to build their own spectral libraries that are used later to process the quantitative DIA data sets. Dr. Schilling also discusses the adoption of new technologies and the dissemination of data sets to collaborators and core users.

Our third speaker, Brett Phinney of the UC Davis Genome Center, shares how his team is developing efficient and more universal methods for the core lab. Researchers today expect core facilities to quantify thousands of proteins and their post-translational modifications efficiently and for a reasonable cost. This is generally feasible when there are a limited number of sample types and organisms, but when every sample has the potential to be different, it is difficult to develop methods that can apply to a wide variety of samples. Dr. Phinney details how his team uses suspension trapping and peptide-centric DIA in combination with deep learning to address this issue for both proteomic sample preparation and proteomic LC-MS/MS analysis.

More information on other webinars in this series can be found here.

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