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Biology (Basel). 2014 Apr 16;3(2):320-32. doi: 10.3390/biology3020320.

On-beads digestion in conjunction with data-dependent mass spectrometry: a shortcut to quantitative and dynamic interaction proteomics.

Author information

1
Systems Biology Ireland, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. benedetta.turriziani@ucdconnect.ie.
2
Systems Biology Ireland, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. amaya.garciamunoz@ucd.ie.
3
Systems Biology Ireland, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. ruth.pilkington@ucd.ie.
4
Systems Biology Ireland, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. cinzia.raso@ucd.ie.
5
Systems Biology Ireland, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. walter.kolch@ucd.ie.
6
Systems Biology Ireland, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. alex.vonkriegsheim@ucd.ie.

Abstract

With the advent of the "-omics" era, biological research has shifted from functionally analyzing single proteins to understanding how entire protein networks connect and adapt to environmental cues. Frequently, pathological processes are initiated by a malfunctioning protein network rather than a single protein. It is therefore crucial to investigate the regulation of proteins in the context of a pathway first and signaling network second. In this study, we demonstrate that a quantitative interaction proteomic approach, combining immunoprecipitation, in-solution digestion and label-free quantification mass spectrometry, provides data of high accuracy and depth. This protocol is applicable, both to tagged, exogenous and untagged, endogenous proteins. Furthermore, it is fast, reliable and, due to a label-free quantitation approach, allows the comparison of multiple conditions. We further show that we are able to generate data in a medium throughput fashion and that we can quantify dynamic interaction changes in signaling pathways in response to mitogenic stimuli, making our approach a suitable method to generate data for system biology approaches.

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