Oral insulin mimetics (OIM): affinity purification-mass spectrometry (AP-MS)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens (human)
SUBMITTER: Kazuishi Kubota
PROVIDER: PXD014589 | JPOST Repository | Fri Jul 17 00:00:00 BST 2020
REPOSITORIES: jPOST
Dataset's files
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| E1322205.raw | Raw | |||
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Project description:Septin proteins interact intermolecularly to form hetero-oligomeric complexes that further assemble into higher-order filaments. To investigate whether the interactions among septin proteins are affected by RID, we conducted affinity purification-mass spectrometry (AP-MS) experiments. In this regard, EGFP-tagged SEPT6 or its quadruple mutant SEPT6-4KR was co-expressed with RID-WT or RID-CA in cells and immunoprecipitated by anti-EGFP beads. The resulting co-immunoprecipitates were analyzed and compared with the vector control by label-free quantitative (LFQ) proteomics to identify and quantify septin proteins associated with SEPT6. The MS analysis showed that SEPT6 were indeed co-affinity-purified with all endogenous septin proteins that were identified, such as SEPT2, SEPT3, SEPT5, SEPT6, SEPT7, SEPT8, SEPT9, SEPT10, and SEPT11, in the absence of RID activity. More importantly, the interactions between SEPT6 and these septins were not affected by RID-WT expression. Interestingly, the SEPT6-4KR mutant could still interact and likely form heteromeric complexes with other fatty-acylated septin proteins (e.g., SEPT2, SEPT3, SEPT5, SEPT6, SEPT7, SEPT8, SEPT9, SEPT10 and SEPT11) in the presence of RID activity.
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Project description:We present 'significance analysis of interactome' (SAINT), a computational tool that assigns confidence scores to protein-protein interaction data generated using affinity purification-mass spectrometry (AP-MS). The method uses label-free quantitative data and constructs separate distributions for true and false interactions to derive the probability of a bona fide protein-protein interaction. We show that SAINT is applicable to data of different scales and protein connectivity and allows transparent analysis of AP-MS data.
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