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Mapping transcription factor interactome networks using HaloTag protein arrays

Using a newly developed technology, HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we increase the capacity of in situ protein microarray technology several-fold, such that proteome-scale screening becomes feasible. Many examples of novel protein–protein interactions (PPIs) among plant signaling pathways were observed. With few exceptions, nearly all of these connections are undocumented in the existing literature.

Junshi Yazaki, Mary Galli, Alice Y. Kim, Kazumasa Nito, Fernando Aleman, Katherine N. Chang, Anne-Ruxandra Carvunis, Rosa Quan, Hien Nguyen, Liang Song, José M. Alvarez, Shao-shan Carol Huang, Huaming Chen, Niroshan Ramachandran, Stefan Altmann, Rodrigo A. Gutiérrez, David E. Hill, Julian I. Schroeder, Joanne Chory, Joshua LaBaer, Marc Vidal, Pascal Braun, and Joseph R. Ecker

PLANT BIOLOGY

Significance

Using a newly developed technology, HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we increase the capacity of in situ protein microarray technology several-fold, such that proteome-scale screening becomes feasible. Many examples of novel protein–protein interactions (PPIs) among plant signaling pathways were observed. With few exceptions, nearly all of these connections are undocumented in the existing literature. This study has resulted in an important new resource for the plant biology community—a plant transcription factor-anchored protein–protein interaction network map. Such transcription factor- and transcriptional regulator-based PPI networks may help in the identification of novel genes for use in the improvement of agronomic traits such as grain quality, disease resistance, and stress tolerance.

Abstract

Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein–protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor–protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

 

See: http://www.pnas.org/content/113/29/E4238.full

PNAS July 19 2016; vol.113; no.29: E4238–E4247

 

Figure 1: (A) The NAPPA assay. Plasmid DNA, cross-linker, and HaloTag ligand are spotted on glass slides. Addition of coupled transcription–translation reagent results in protein expression and localized protein capture. Coexpression of an epitope-tagged query protein enables detection of protein interactions by immunodetection. Modified from ref. 63. (B) Schematic of the HaloTag protein interacting with its chloroalkane ligand. Courtesy of ref. 18. (C) HaloTag gives higher yields of active protein compared with GST-antibody. (C, Left) Amount of deposited plasmid DNA as measured with PicoGreen. (C, Middle) FOS protein as detected by an anti-FOS antibody, Halo-tagged proteins detected by an anti-Halo antibody, and protein interaction between FOS and 3×HA-JUN as detected by an anti-HA antibody (from left to right). (C, Right) Signal quantification of arrays is shown. The y axis represents relative fluorescence units (RFUs). Colored histogram bars indicate signals corresponding to boxed regions on the arrays. Error bars represent SE of the signal intensity.

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