Hypothesis-driven discovery on Stellar MS

Here, we walk through the process of generating assays for "hypothesis-driven discovery". These assays are large scale targeted panels that cover as many targets as possible, focusing specifically on known or suspected biology. In this tutorial, we will generate a targeted assay using multiple target monitoring (MTM) for a 3 -proteome dataset. Further, we will discuss the use of priority file to bias the assay towards suspected biological targets of interest. Here, all discovery and quantitative data is acquired on Stellar MS, although a similar workflow could be used to build an assay on Stellar from a high resolution instrument. This tutorial assumes basic knowledge of the Skyline ecosystem, PRM Conductor, and Proteome Discoverer.

 

Multiple target monitoring is an acquisition strategy designed to increase acquisition efficiency. This increase in efficiency is ideal for biased discovery type experiments, where one wishes to monitor many targets at once with a focus on known biology. MTM may enable monitoring of more targets than traditional parallel reaction monitoring without suffering from interference at the same rate as data independent acquisition (DIA). To illustrate this, say there are three co-eluting peptides that are close in m/z and share fragment ions. These peptides could be monitored in 3 separate acquisition windows using PRM: 

Alternatively, one could acquire data with 4 Th data independent acquisition (DIA) windows. In this case, interference is introduced to several transitions: 

MTM aims to bridge the gap by using a chromatogram library to survey the sample, and then combining acquisition windows when doing so won't result in interference. In the above example, all 3 peptides could be measured in 2 acquisition windows with no interference: 

MTM may enable monitoring of more targets than PRM while maintaining better quantitation than DIA. The process of generating MTM methods is straightforward through the use of PRM Conductor and Skyline external tools. Here, we show how a large-scale survey assay could be generated with MTM. 

 Experimental design

In this tutorial, we will be dealing with 3 proteome mix consisting of 3 samples:

A: 50 ng Human/45 ng Yeast/ 5 ng E. coli

B: 50 ng Human/ 37.5 ng Yeast/ 12.5 ng E. Coli

C: 50 ng Human/25 ng Yeast/ 25 ng E. coli

D: 50 ng Human/ 12.5 ng Yeast/ 37.5 ng E. coli

E: 50 ng Human/ 5 ng Yeast/ 45 ng E. coli

We are acquiring data with 28-minute gradient to achieve a mix of throughput and coverage. 

Tutorial files