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Development and Utilization of Automation for Targeted Peptide LCMS Quantification

RECORD | Already taken place Tu, 22.2.2022
LCMS proteomics is ideal for the identification and quantification of CSF biomarkers. The speed and sensitivity of current QQQ instruments facilitate high levels of multiplexing at the instrument.
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Agilent Technologies: Development and Utilization of Automation for Targeted Peptide LCMS Quantification
Agilent Technologies: Development and Utilization of Automation for Targeted Peptide LCMS Quantification

The process of neurodegeneration is characterized by an accumulation of proteins in aggregated form. This aggregation suggests impairment of protein production or turnover. Hallmarks of Alzheimer’s disease (AD), Parkinson’s disease (PD), and frontotemporal dementia (FTD) include the accumulation of these protein aggregates. Multiple factors contribute to the accumulation of aggregated proteins in these diseases including genetic mutations, dysfunctional proteostasis, and other disease-related risk factors.

LCMS proteomics is ideal for the identification and quantification of CSF biomarkers. The speed and sensitivity of current triple quadrupole instruments facilitate high levels of multiplexing at the instrument. This is multiplexing is coupled with higher levels of throughput to handle the large sample volumes experienced in our labs. In these assays, we use mass spectrometry (MS) based relative quantitation alongside highly automated sample preparation workflows to determine changes in the concentrations of specific proteins over time or treatment

Presenter: Paul Auger (Senior Scientist, Denali Therapeutics)

Paul Auger is currently a Lab Leader and Senior Scientist in the DMPK department at Denali Therapeutics where he oversees the internal discovery and quantitative proteomic pipeline in support of discovery biology and development sciences. His group develops quantitative assays for both potential diagnostic and phamacodynamic targets to support the biomarker strategies of therapeutic molecules in the clinic. His team also supports the discovery of new target biomarkers through the use of multi-omic analyses: combining metabolomic, lipidomic, and genomic data with unbiased and targeted discovery proteomics. Prior to joining Denali Paul held multiple industry positions including similar roles with Genentech, Amgen, and Human Genome Sciences. Paul obtained his Undergraduate degree from St. Mary’s College of Maryland and his Masters from Johns Hopkins University.

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