The cellular abundance of transcription factors (TFs) is an important determinant of their regulatory activities. Deriving TF copy numbers is therefore crucial to understanding how these proteins control gene expression. We describe a sensitive selected reaction monitoring-based mass spectrometry assay that allowed us to determine the copy numbers of up to ten proteins simultaneously. We applied this approach to profile the absolute levels of key TFs, including PPAR and RXR, during terminal differentiation of mouse 3T3-L1 pre-adipocytes. Our analyses revealed that individual TF abundance differs dramatically (from 250 to >300,000 copies per nucleus) and that their dynamic range during differentiation can vary up to fivefold. We also formulated a DNnA binding model for PPAR based on TF copy number, binding energetics and local chromatin state. This model explains the increase in PPAR binding sites during the final differentiation stage that occurs despite a concurrent saturation in PPAR copy number. Originally published at: Simicevic, Jovan; Schmid, Adrien W; Gilardoni, Paola A; Zoller, Benjamin; Raghav, Sunil K; Krier, Irina; Gubelmann, Carinne; Lisacek, Frédérique; Naef, Felix; Moniatte, Marc; Deplancke, Bart (2013). Absolute quantification of transcription factors during cellular differentiation using multiplexed targeted proteomics. Nature Methods, 10(6):570-576.

Complex biological systems rely on cell surface cues that govern cellular self-recognition and selective interactions with appropriate partners. Molecular diversification of cell surface recognition molecules through DNA recombination and complex alternative splicing has emerged as an important principle for encoding such interactions. However, the lack of tools to specifically detect and quantify receptor protein isoforms is a major impediment to functional studies. We here developed a workflow for targeted mass spectrometry by selected reaction monitoring that permits quantitative assessment of highly diversified protein families. We apply this workflow to dissecting the molecular diversity of the neuronal neurexin receptors and uncover an alternative splicing-dependent recognition code for synaptic ligands.DOI: http://dx.doi.org/10.7554/eLife.07794.001

A combined cross-platform approach is presented to experimentally identify and characterize interactions between mouse transcription factors and regulatory elements at unprecedented resolution and throughput.