Health Research and Policy

Workshop in Biostatistics - Abstract

DATE: May 29, 2014
TIME: 1:15 - 3:00 pm
LOCATION: Medical School Office Building, Rm x303
TITLE: Integrative Computational/Experimental Approaches for Improving Proteomics
SPEAKER: Parag Mallick
Assistant Professor (Research) of Radiology (Diagnostic Radiology)

A major goal of proteomics research is the accurate and sensitive identification and quantification of a broad range of proteins within a sample. Proteomics approaches depend heavily upon close interactions between data acquisition approaches and sophisticated computational tools to interpret these data.

Recently, a novel data acquisition approach known as 'Data Independent Acquisition' (DIA) has been introduced, that collects tandem spectra from multiple peptides concurrently. These approaches have been developed to overcome the reproducibility challenges of other strategies such as data-dependent acquisition (DDA) and the throughput challenges of targeted proteomics strategies (e.g. SRM). Typically, mass-spectrometry-based sequencing is performed by isolated a single peptide, fragmenting it, collecting a mass spectrum of the masses of the fragments and then computationally inferring the peptide’s identity by determining the peptide most likely to have given rise to those fragments. If one were to attempt to isolate and then sequence multiple peptides concurrently, one would produce a so-called ‘hybrid-spectra’ that would contain the signals from each of those peptides superimposed on top of each other. Despite the super-position, it may be possible to de-convolve the signals from each of the individual peptides. Depending upon the demultiplexability of the fragments, it may be possible to measure dozens of peptides in the same amount of time that was previously required to measure one peptide.

Suggested readings:
Parag Mallick & Bernhard Kuster (2010). Proteomics: a pragmatic perspective. Nature Biotechnology 28, 695--709

Hanno Steen & Matthias Mann (2004). The abc's (and xyz's) of peptide sequencing. Nature Reviews Molecular Cell Biology. 5, 699-711.

Paola Picotti & Ruedi Aebersold (2012). Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions. Nature Methods 9, 555--566

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