Matthew Rardin Matthew Rardin Ph.D., is currently a scientist in the Discovery Attribute Sciences group at Amgen where he develops discovery and quantitative proteomic workflows to understand mechanism of action, pre-clinical biomarker discovery, and target engagement. Originally from Colorado, he received a B.S. in Microbiology at Colorado State University followed by graduate studies in Jack Dixon’s group at UCSD on the role of reversible phosphorylation signaling in mitochondria. Read More
For his postdoctoral studies, Matt joined Brad Gibson’s group where he focused on developing quantitative proteomic techniques to understand the regulation of lysine acylation by sirtuins and their role in metabolic function.

Rapid Identification of Contaminants and Interferences Using Skyline

Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g. detergents) necessitating a variety of sample cleanup methods. Efforts to understand and mitigate sample contamination are a continual source of distraction with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, we developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 Filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows the assessment of sample integrity and indicates potential sources of contamination.