Dataset Information

Identification of human GRHL1 interactors and post-translational modifications by LC-MS/MS

ABSTRACT: Aim of the project was to identify interactors and post-translational modifications of recombinant 3xFLAG-6xHis-tagged human GRHL1, tandem-affinity purified from isolated HEK293 nuclei treated with DMSO as control or with the phytochemical papaverine.

INSTRUMENT(S): nanoACQUITY UPLC, Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Fabian Fischer

LAB HEAD: Michael Ristow

PROVIDER: PXD021768 | Pride | 2021-11-02

REPOSITORIES: Pride

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Publications

Grainyhead 1 acts as a drug-inducible conserved transcriptional regulator linked to insulin signaling and lifespan.

Grigolon Giovanna G Araldi Elisa E Erni Reto R Wu Jia Yee JY Thomas Carolin C La Fortezza Marco M Laube Beate B Pöhlmann Doris D Stoffel Markus M Zarse Kim K Carreira Erick M EM Ristow Michael M Fischer Fabian F

Nature communications 20220110 1

Aging is impacted by interventions across species, often converging on metabolic pathways. Transcription factors regulate longevity yet approaches for their pharmacological modulation to exert geroprotection remain sparse. We show that increased expression of the transcription factor Grainyhead 1 (GRH-1) promotes lifespan and pathogen resistance in Caenorhabditis elegans. A compound screen identifies FDA-approved drugs able to activate human GRHL1 and promote nematodal GRH-1-dependent longevity. ...[more]

PMID: 35013237

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Project description:Accurate predictions of the DNA binding specificities of transcription factors (TFs) are necessary for understanding gene regulatory mechanisms. Traditionally, predictive models are built based on nucleotide sequence features. Here, we employed three- dimensional DNA shape information obtained on a high-throughput basis to integrate intuitive DNA structural features into the modeling of TF binding specificities using support vector regression. We performed quantitative predictions of DNA binding specificities, using the DREAM5 dataset for 65 mouse TFs and genomic-context protein binding microarray data for three human basic helix-loop-helix TFs. DNA shape-augmented models compared favorably with sequence-based models for these predictions. Although both k-mer and DNA shape features encoded the interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space compared to k-mer use. Finally, analyzing the weights of DNA shape-augmented models uncovered TF family- specific structural readout mechanisms that were not obvious from the nucleotide sequence. Three genomic-context protein binding microarray (gcPBM) experiments of human transcription factors were performed. Briefly, the gcPBMs involved binding his-tagged transcription factors c-Myc, Max, and Mad1(Mxd1) to double-stranded 180K Agilent microarrays in order to determine their binding specificity for putative DNA binding sites in native genomic context. Briefly, we represent three categories of 36-bp sequences: 1) bound probes, 2) unbound probes (or negative controls), and 3) test probes. Bound probes corresponded to genomic regions bound in vivo by c-Myc, Max, or Mad2 (ChIP-seq P < 10^(-10) in HeLaS3 or K562 celld (ENCODE)) that contain at least two consecutive 8-mers with universal PBM E-score > 0.4 (Munteanu and Gordan, LNCS 2013). All putative binding sites occur at the same position within the probes on the array. M-bM-^@M-^\UnboundM-bM-^@M-^] probes corresponded to genomic regions with ChIP-seq P < 10^(-10) and a maximum 8-mer E-score < 0.2. We also designed test probes that contain, within constant flanking regions, all nnCACGTGnn 10-mers and 18 nnnCACGTGnnn 12-mers (where n = A, C, G, or T). Each DNA sequence represented on the array is present in 6 replicate spots. We report the gcPBM signal intensity for each spot. The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).

Project description:Until now, it has been reasonably assumed that specific base-pair recognition is the only mechanism controlling the specificity of transcription factor (TF)M-bM-^HM-^RDNA binding. Contrary to this assumption, here we show that nonspecific DNA sequences possessing certain repeat symmetries, when present outside of specific TF binding sites (TFBSs), statistically control TFM-bM-^HM-^RDNA binding preferences. We used high-throughput proteinM-bM-^HM-^RDNA binding assays to measure the binding levels and free energies of binding for several human TFs to tens of thousands of short DNA sequences with varying re- peat symmetries. Based on statistical mechanics modeling, we iden- tify a new proteinM-bM-^HM-^RDNA binding mechanism induced by DNA se- quence symmetry in the absence of specific base-pair recognition, and experimentally demonstrate that this mechanism indeed gov- erns proteinM-bM-^HM-^RDNA binding preferences. Four custom protein binding microarray (PBM) experiments of human transcription factors were performed. Briefly, the PBMs involved binding his-tagged transcription factors c-Myc, Max, and Mad1(Mxd1) to double-stranded 180K Agilent microarrays in order to determine their binding specificity for GTCACGTGAC DNA binding sites flanked by repetitive DNA elements with different symmetries and correlation length scales. Briefly, we represent three categories of 36-bp sequences: 1) 28800 probes centered at a GTCACGTGAC site and flanked by repetitive elements (probe names starting with Ariel_); 2) Unbound probes (or negative controls); and 3) Bound probes, which correspond to randomly selected genomic regions bound in vivo by c-Myc, Max, or Mad2 (ChIP-seq P < 10^(-10) in HeLaS3 or K562 celld (ENCODE)), which contain at least two consecutive 8-mers with universal PBM E-score > 0.4 (Munteanu and Gordan, LNCS 2013). Each DNA sequence represented on the array is present in 6 replicate spots. We report the gcPBM signal intensity for each spot (raw files) as well as the median intensity over the 6 replicate spots (normalized data). The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).

Dataset Information

Identification of human GRHL1 interactors and post-translational modifications by LC-MS/MS

Publications

Grainyhead 1 acts as a drug-inducible conserved transcriptional regulator linked to insulin signaling and lifespan.

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