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Absolute quantification of transcription factors during cellular differentiation using multiplexed targeted proteomics

Nature Methods volume 10, pages 570–576 (2013)Cite this article

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Abstract

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 PPARγ and RXRα, 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 DNA binding model for PPARγ based on TF copy number, binding energetics and local chromatin state. This model explains the increase in PPARγ binding sites during the final differentiation stage that occurs despite a concurrent saturation in PPARγ copy number.

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Figure 1: Workflow for the absolute quantification of TFs in 3T3-L1 cells.
Figure 2: Summary of RXRα and PPARγ levels quantified by SRM.
Figure 3: Quantitative modeling of genome-wide PPARγ DNA binding.
Figure 4: Properties of the SH-quant tag variants.
Figure 5: Simultaneous monitoring of the nuclear abundance of ten TFs during terminal adipogenesis via spiking of in vitro–expressed full-length TFs.

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Acknowledgements

We would like to thank M. Lai for his help on solving Pinpoint software–related issues; M. Gstaiger (ETH Zurich) and H. Steen (Boston Children's Hospital) for providing us with the SH-quant and FLEX peptide tag-containing vectors, respectively; H. Lashuel (EPFL) for providing us with the α-synuclein clone; E. Ahrné for computational assistance and for providing feedback on the manuscript together with S. Waszak, M. Mueller and A. Schmidt; and D. Chiappe for technical and F. Armand for computational assistance. This work was supported by funds from the Swiss National Science Foundation, a Marie Curie International Reintegration grant (to B.D.) from the European Union Seventh Framework Program, a SystemsX.ch iPhD Fellowship (to J.S.) and grant (CycliX), the Roland Bailly Foundation (Geneva, Switzerland), the National Centre of Competence in Research (NCCR) Frontiers in Genetics Program, EMBO (ALTF 459-2012) and European Commission (EMBOCOFUND2010, GA-2010-267146) support from Marie Curie Actions (to P.A.G.) and by institutional support from the EPFL.

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Author notes

  1. Jovan Simicevic, Adrien W Schmid and Paola A Gilardoni: These authors contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Jovan Simicevic, Paola A Gilardoni, Sunil K Raghav, Irina Krier, Carine Gubelmann & Bart Deplancke

  2. Proteomics Core Facility, School of Life Sciences, EPFL, Lausanne, Switzerland

    Adrien W Schmid & Marc Moniatte

  3. Laboratory of Computational Systems Biology, Institute of Bioengineering, School of Life Sciences, EPFL, Lausanne, Switzerland

    Benjamin Zoller & Felix Naef

  4. Swiss Institute of Bioinformatics, Geneva, Switzerland

    Frédérique Lisacek

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Contributions

Conceived and planned the study: J.S., A.W.S., P.A.G., M.M. and B.D. Prepared the manuscript: J.S., A.W.S., P.A.G., B.Z., F.N., M.M. and B.D. Performed wet bench experiments: J.S., A.W.S., P.A.G., S.K.R. and C.G. Performed mass spectrometry data analysis: A.W.S. Performed biological data analysis: J.S., P.A.G. and B.D. Performed modeling: B.Z., I.K., F.N. and B.D. All the authors discussed the results and commented on the paper.

Corresponding authors

Correspondence to Marc Moniatte or Bart Deplancke.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–18, Supplementary Tables 1–4 and Supplementary Note (PDF 11239 kb)

Supplementary Data 1

Proteotypic peptide selection for the ten TFs (multiplex) (XLSX 74 kb)

Supplementary Data 2

Precursor-to-product–ion transitions selected for SRM (tenTFs) (XLSX 60 kb)

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Simicevic, J., Schmid, A., Gilardoni, P. et al. Absolute quantification of transcription factors during cellular differentiation using multiplexed targeted proteomics. Nat Methods 10, 570–576 (2013). https://doi.org/10.1038/nmeth.2441

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