Dataset Information

Proximity-dependent biotinylation by TurboID to identify protein-protein interaction networks in yeast

ABSTRACT: The use of proximity-dependent biotinylation assays coupled to mass spectrometry (PDB-MS) has changed the field of protein-protein interactions (PPI) studies. Yet, despite the recurrent and successful use of BioID-based PPI screening in mammalian cells, the implementation of PDB-MS in yeast has not been effective. Here we report a simple and rapid approach in yeast to effectively screen for proximal and interacting proteins in their natural cellular environment by using TurboID, a recently described version of the BirA biotin ligase. Using the protein arginine methyltransferase Rmt3 and the RNA exosome subunits, Rrp6 and Dis3, the application of PDB-MS in yeast by using TurboID was able to recover protein-protein interactions previously identified using other biochemical approaches and provided complementary information for a given protein bait. The development of a rapid and effective PDB assay that can systematically analyze PPIs in living yeast cells opens the way for large-scale proteomics studies in this powerful model organism.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Schizosaccharomyces Pombe 927

SUBMITTER: Danny Bergeron

LAB HEAD: Francois Bachand

PROVIDER: PXD013183 | Pride | 2019-05-16

REPOSITORIES: Pride

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Publications

Proximity-dependent biotinylation mediated by TurboID to identify protein-protein interaction networks in yeast.

Larochelle Marc M Bergeron Danny D Arcand Bruno B Bachand François F

Journal of cell science 20190531 11

The use of proximity-dependent biotinylation assays coupled to mass spectrometry (PDB-MS) has changed the field of protein-protein interaction studies. However, despite the recurrent and successful use of BioID-based protein-protein interactions screening in mammalian cells, the implementation of PDB-MS in yeast has not been effective. Here, we report a simple and rapid approach in yeast to effectively screen for proximal and interacting proteins in their natural cellular environment by using Tu ...[more]

PMID: 31064814

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Project description:Classical methods of investigating protein-protein interactions (PPIs) are generally performed in non-living systems, yet in recent years new technologies utilizing proximity labeling (PL) have given researchers the tools to explore proximal PPIs in living systems. PL has distinct advantages over traditional protein interactome studies, such as the ability to identify weak and transient interactions in vitro and in vivo. Most PL studies are performed on targets within or on the cell membrane. We have adapted the original PL method to investigate PPIs within the extracellular compartment, using both BioID2 and TurboID, that we term extracellular PL (ePL). To demonstrate the utility of this modified technique, we investigate the interactome of the widely expressed matrisome protein Tissue inhibitors of metalloproteinases 2 (TIMP2). Tissue inhibitors of metalloproteinases (TIMPs) are a family of multi-functional proteins that were initially defined by their ability to inhibit the enzymatic activity of metalloproteinases (MPs), the major mediators of extracellular matrix (ECM) breakdown and turnover. TIMP2 exhibits a broad expression profile and is often abundant in both normal and diseased tissues. Understanding the functional transformation of matrisome regulators, like TIMP2, during the evolution of tissue microenvironments associated with disease progression is essential for the development of ECM targeted therapeutics. Using carboxyl- and amino-terminal fusion proteins of TIMP2 with BioID2 and TurboID, we describe the TIMP2 proximal interactome. We also illustrate how the TIMP2 interactome changes in the presence of different stimuli, in different cell types, in unique culture conditions (2D vs 3D), and with different reaction kinetics (BioID2 vs. TurboID); demonstrating the power of this technique versus classical PPI methods. We propose that the screening of matrisome targets in disease models using ePL will reveal new therapeutic targets for further comprehensive studies.

Project description:The sequence specificity of DNA-binding proteins is the primary mechanism by which the cell recognizes genomic features. Here, we describe systematic determination of yeast transcription factor DNA-binding specificities. We obtained binding specificities for 112 DNA-binding proteins representing 19 distinct structural classes. One-third of the binding specificities have not been previously reported. Several binding sequences have striking genomic distributions relative to transcription start sites, supporting their biological relevance and suggesting a role in promoter architecture. Among these are Rsc3 binding sequences, containing the core CGCG, which are found preferentially ~100 bp upstream of transcription start sites. Mutation of RSC3 results in a dramatic increase in nucleosome occupancy in hundreds of proximal promoters containing a Rsc3 binding element, but has little impact on promoters lacking Rsc3 binding sequences, indicating that Rsc3 plays a broad role in targeting nucleosome exclusion at yeast promoters. Keywords: Protein binding microarrays, DNA, proteins Protein binding microarray (PBM), ChIP-chip and DIP-chip experiments of yeast transcription factor DNA-binding domains were performed. Briefly, the PBMs involved binding GST-tagged DNA-binding proteins to custom-designed, double-stranded 44K Agilent microarrays in order to determine their sequence preferences. The method is described in Berger et al., Nature Biotechnology 2006. A key feature is that the microarrays are composed of de Bruijn sequences that contain each 10-base sequence once and only once, providing an evenly balanced sequence distribution. Individual de Bruijn sequences have different properties, including representation of gapped patterns. Here we provide the data transformed into median intensities for all 32,896 8-base sequences, Z-scores for these intensities, and E-scores. E-scores are a modified version of AUC, and describe how well each 8-mer ranks the intensities of the spots. In general the E-scores are slightly more reproducible than Z-scores, but contain less information about relative binding affinity. Additional experimental details are found in Berger et al., Nature Biotechnology 2006, Berger et al., Cell 2008, and the accompanying Supplementary information. Raw 35-mer array data is available on the web link provided. For the DIP-chip experiments [GSM345371, GSM345403, GSM345414-GSM345421, GSM345429-GSM345432], genomic DNA isolated from S288C yeast was incubated with 40nM of the MBP-tagged DNA binding domain (DBD) of either Cbf1, Pho2, Pho4, Leu3, Rap1, or Swi5 and incubated for 30 minutes prior to purification of protein-DNA complexes. The bound DNA was then isolated, amplified via Invitrogen's WGA protocol, and hybridized against input DNA on NimbleGen 385k 32bp-tiling whole genome arrays. ChIPOTle was used to identify peaks of binding from the data and motifs were identified by BioProspector and MDScan and then scored for their ability to predict the identified peaks by GOMER. Motifs with the best ROC AUC are reported in the paper. For the ChIP-chip experiments [GSM346493 and GSM346494], isogenic wildtype and rsc3-1 strains carrying Rsc8-TAP were grown in parallel under rsc3-1 restrictive growth conditions (37Â°C). Following formaldehyde crosslinking, cells were homogenized and extracts were sonicated to shear the chromatin to an average size of ~500 bp. A single pulldown was then performed with IgG sepharose beads and after decrosslinking and LM-PCR amplification of purified IP DNA, samples were labeled and hybridized on Nimblegen 32bp whole genome tiling arrays, comparing the pulled-down DNA to input genomic DNA.

Dataset Information

Proximity-dependent biotinylation by TurboID to identify protein-protein interaction networks in yeast

Publications

Proximity-dependent biotinylation mediated by TurboID to identify protein-protein interaction networks in yeast.

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