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Mapping transcription factor interactome networks using HaloTag protein arrays.

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.

SUBMITTER: Yazaki J

PROVIDER: S-EPMC4961138 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Mapping transcription factor interactome networks using HaloTag protein arrays.

Yazaki Junshi J Galli Mary M Kim Alice Y AY Nito Kazumasa K Aleman Fernando F Chang Katherine N KN Carvunis Anne-Ruxandra AR Quan Rosa R Nguyen Hien H Song Liang L Alvarez José M JM Huang Shao-Shan Carol SS Chen Huaming H Ramachandran Niroshan N Altmann Stefan S Gutiérrez Rodrigo A RA Hill David E DE Schroeder Julian I JI Chory Joanne J LaBaer Joshua J Vidal Marc M Braun Pascal P Ecker Joseph R JR

Proceedings of the National Academy of Sciences of the United States of America 20160629 29

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 r ...[more]

PMID: 27357687

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Project description:Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)(1). While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships(2). Large-scale GI maps have been reported for eukaryotic organisms like yeast(3-7), but GI information remains sparse for prokaryotes(8), which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods(9, 10). Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale(9), using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection(11)) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity(9, 12, 13)) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system(14). GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected(9). Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process(2). Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex(2) as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred(9).

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Mapping transcription factor interactome networks using HaloTag protein arrays.

Publications

Mapping transcription factor interactome networks using HaloTag protein arrays.

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