Dataset Information

Light-Controlled Affinity Purification of Protein Complexes Exemplified by the Resting ZAP70 Interactome.

ABSTRACT: Multiprotein complexes control the behavior of cells, such as of lymphocytes of the immune system. Methods to affinity purify protein complexes and to determine their interactome by mass spectrometry are thus widely used. One drawback of these methods is the presence of false positives. In fact, the elution of the protein of interest (POI) is achieved by changing the biochemical properties of the buffer, so that unspecifically bound proteins (the false positives) may also elute. Here, we developed an optogenetics-derived and light-controlled affinity purification method based on the light-regulated reversible protein interaction between phytochrome B (PhyB) and its phytochrome interacting factor 6 (PIF6). We engineered a truncated variant of PIF6 comprising only 22 amino acids that can be genetically fused to the POI as an affinity tag. Thereby the POI can be purified with PhyB-functionalized resin material using 660 nm light for binding and washing, and 740 nm light for elution. Far-red light-induced elution is effective but very mild as the same buffer is used for the wash and elution. As proof-of-concept, we expressed PIF-tagged variants of the tyrosine kinase ZAP70 in ZAP70-deficient Jurkat T cells, purified ZAP70 and associating proteins using our light-controlled system, and identified the interaction partners by quantitative mass spectrometry. Using unstimulated T cells, we were able to detect the known interaction partners, and could filter out all other proteins.

SUBMITTER: Horner M

PROVIDER: S-EPMC6399385 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Light-Controlled Affinity Purification of Protein Complexes Exemplified by the Resting ZAP70 Interactome.

Hörner Maximilian M Eble Julian J Yousefi O Sascha OS Schwarz Jennifer J Warscheid Bettina B Weber Wilfried W Schamel Wolfgang W A WWA

Frontiers in immunology 20190226

Multiprotein complexes control the behavior of cells, such as of lymphocytes of the immune system. Methods to affinity purify protein complexes and to determine their interactome by mass spectrometry are thus widely used. One drawback of these methods is the presence of false positives. In fact, the elution of the protein of interest (POI) is achieved by changing the biochemical properties of the buffer, so that unspecifically bound proteins (the false positives) may also elute. Here, we develop ...[more]

PMID: 30863395

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Project description:Mapping protein-protein interactions for chromatin-associated proteins remains challenging. Here we explore the use of BioID, a proximity biotinylation approach in which a mutated biotin ligase (BirA*) is fused to a bait of interest, allowing for the local activation of biotin and subsequent biotinylation of proteins in the bait vicinity. BioID allowed for successful interactome mapping of core histones and members of the mediator complex. We explored the background signal produced by the BioID approach and found that using distinct types of controls increased the stringency of our statistical analysis with SAINTexpress. A direct comparison of BioID with our AP-MS protocol optimized for chromatin-associated protein complexes revealed that the approaches identified few shared interaction partners and enriched for distinct biological processes; yet, both approaches permitted the recovery of biologically meaningful interactions. While no clear bias could be observed for either technique toward protein complexes of particular functions, BioID allowed for the purification of proteins of lower cellular abundance. Finally, we were able to identify a strong association of MED4 with the centrosome by BioID and validated this finding by immunofluorescence. In summary, BioID complements AP-MS for the study of chromatin-associated protein complexes.Biological significanceThis manuscript describes the application of BioID, a proximity biotinylation approach, to chromatin-associated proteins, namely core histones and members of the mediator complex. We observed that BioID was successful at identifying known interaction partners for the baits tested, but also allowed novel putative interaction partners to be identified. By performing a detailed comparison of BioID versus a standard method for interactome mapping (affinity purification coupled to mass spectrometry, AP-MS), we show that the approaches were complementary, allowing for purification of different interaction partners. These interaction partners were different in the biological processes they are associated with, but also in their abundance. BioID represents a significant technical development in the field of chromatin research by expanding the search space for interactome mapping beyond what is possible with AP-MS. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras.

Project description:BACKGROUND: Recent advances in molecular biology have led to the accumulation of large amounts of data on protein-protein interaction networks in different species. An important challenge for the analysis of these data is to extract functional modules such as protein complexes and biological processes from networks which are characterised by the present of a significant number of false positives. Various computational techniques have been applied in recent years. However, most of them treat protein interaction as binary. Co-complex relations derived from affinity purification/mass spectrometry (AP-MS) experiments have been largely ignored. METHODS: This paper presents a new algorithm for detecting protein complexes from AP-MS data. The algorithm intends to detect groups of prey proteins that are significantly co-associated with the same set of bait proteins. We first construct AP-MS data as a bipartite network, where one set of nodes consists of bait proteins and the other set is composed of prey proteins. We then calculate pair-wise similarities of bait proteins based on the number of their commonly shared neighbours. A hierarchical clustering algorithm is employed to cluster bait proteins based on the similarities and thus a set of 'seed' clusters is obtained. Starting from these 'seed' clusters, an expansion process is developed to identify prey proteins which are significantly associated with the same set of bait proteins. Then, a set of complete protein complexes is derived. In application to two real AP-MS datasets, we validate biological significance of predicted protein complexes by using curated protein complexes and well-characterized cellular component annotation from Gene Ontology (GO). Several statistical metrics have been applied for evaluation. RESULTS: Experimental results show that, the proposed algorithm achieves significant improvement in detecting protein complexes from AP-MS data. In comparison to the well-known MCL algorithm, our algorithm improves the accuracy rate by about 20% in detecting protein complexes in both networks and increases the F-Measure value by about 50% in Krogan_2006 network. Greater precision and better accuracy have been achieved and the identified complexes are demonstrated to match well with existing curated protein complexes. CONCLUSIONS: Our study highlights the significance of taking co-complex relations into account when extracting protein complexes from AP-MS data. The algorithm proposed in this paper can be easily extended to the analysis of other biological networks which can be conveniently represented by bipartite graphs such as drug-target networks.

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Dataset Information

Light-Controlled Affinity Purification of Protein Complexes Exemplified by the Resting ZAP70 Interactome.

Publications

Light-Controlled Affinity Purification of Protein Complexes Exemplified by the Resting ZAP70 Interactome.

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