RESUMO
The transport of the K(+) channels TASK-1 and TASK-3 (also known as KCNK3 and KCNK9, respectively) to the cell surface is controlled by the binding of 14-3-3 proteins to a trafficking control region at the extreme C-terminus of the channels. The current model proposes that phosphorylation-dependent binding of 14-3-3 sterically masks a COPI-binding motif. However, the direct effects of phosphorylation on COPI binding and on the binding parameters of 14-3-3 isoforms are still unknown. We find that phosphorylation of the trafficking control region prevents COPI binding even in the absence of 14-3-3, and we present a quantitative analysis of the binding of all human 14-3-3 isoforms to the trafficking control regions of TASK-1 and TASK-3. Surprisingly, the affinities of 14-3-3 proteins for TASK-1 are two orders of magnitude lower than for TASK-3. Furthermore, we find that phosphorylation of a second serine residue in the C-terminus of TASK-1 inhibits 14-3-3 binding. Thus, phosphorylation of the trafficking control region can stimulate or inhibit transport of TASK-1 to the cell surface depending on the target serine residue. Our findings indicate that control of TASK-1 trafficking by COPI, kinases, phosphatases and 14-3-3 proteins is highly dynamic.
Assuntos
Proteínas 14-3-3/fisiologia , Proteínas do Tecido Nervoso/metabolismo , Canais de Potássio de Domínios Poros em Tandem/metabolismo , Processamento de Proteína Pós-Traducional , Proteínas 14-3-3/química , Sequência de Aminoácidos , Animais , Células COS , Membrana Celular , Chlorocebus aethiops , Complexo I de Proteína do Envoltório/metabolismo , Humanos , Proteínas do Tecido Nervoso/química , Fosforilação , Canais de Potássio de Domínios Poros em Tandem/química , Ligação Proteica , Domínios e Motivos de Interação entre Proteínas , Transporte ProteicoRESUMO
The intracellular transport of membrane proteins is controlled by trafficking signals: Short peptide motifs that mediate the contact with COPI, COPII or various clathrin-associated coat proteins. In addition, many membrane proteins interact with accessory proteins that are involved in the sorting of these proteins to different intracellular compartments. In the K2P channels, TASK-1 and TASK-3, the influence of protein-protein interactions on sorting decisions has been studied in some detail. Both TASK paralogues interact with the adaptor protein 14-3-3; TASK-1 interacts, in addition, with the adaptor protein p11 (S100A10) and the endosomal SNARE protein syntaxin-8. The role of these interacting proteins in controlling the intracellular traffic of the channels and the underlying molecular mechanisms are summarised in this review. In the case of 14-3-3, the interacting protein masks a retention signal in the C-terminus of the channel; in the case of p11, the interacting protein carries a retention signal that localises the channel to the endoplasmic reticulum; and in the case of syntaxin-8, the interacting protein carries an endocytosis signal that complements an endocytosis signal of the channel. These examples illustrate some of the mechanisms by which interacting proteins may determine the itinerary of a membrane protein within a cell and suggest that the intracellular traffic of membrane proteins may be adapted to the specific functions of that protein by multiple protein-protein interactions.
Assuntos
Citoplasma/metabolismo , Retículo Endoplasmático/metabolismo , Proteínas de Membrana/metabolismo , Canais de Potássio de Domínios Poros em Tandem/metabolismo , Transporte Proteico/fisiologia , Animais , Endocitose/fisiologia , HumanosRESUMO
Chemical proteomics focuses on the drug-target-phenotype relationship for target deconvolution and elucidation of the mechanism of action-key and bottleneck in drug development and repurposing. Majorly due to the limits of using chemically modified ligands in affinity-based methods, new, unbiased, proteome-wide, and MS-based chemical proteomics approaches have been developed to perform drug target deconvolution, using full proteome profiling and no chemical modification of the studied ligand. Of note among them, thermal proteome profiling (TPP) aims to identify the target(s) by measuring the difference in melting temperatures between each identified protein in drug-treated versus vehicle-treated samples, with the thermodynamic interpretation of "protein melting" and curve fitting of all quantified proteins, at all temperatures, in each biological replicate. Including TPP, all the other chemical proteomics approaches often fail to provide target deconvolution with sufficient proteome depth, statistical power, throughput, and sustainability, which could hardly fulfill the final purpose of drug development. The proteome integral solubility alteration (PISA) assay provides no thermodynamic interpretation, but a throughput 10-100-fold compared to the other proteomics methods, high sustainability, much lower time of analysis and sample amount requirements, high confidence in results, maximal proteome coverage (~10,000 protein IDs), and up to five drugs / test molecules in one assay, with at least biological triplicates of each treatment. Each drug-treated or vehicle-treated sample is split into many fractions and exposed to a gradient of heat as solubility perturbing agent before being recomposed into one sample; each soluble fraction is isolated, then deep and quantitative proteomics is applied across all samples. The proteins interacting with the tested molecules (targets and off-targets), the activated mechanistic factors, or proteins modified during the treatment show reproducible changes in their soluble amount compared to vehicle-treated controls. As of today, the maximal multiplexing capability is 18 biological samples per PISA assay, which enables statistical robustness and flexible experimental design accommodation for fuller target deconvolution, including integration of orthogonal chemical proteomics methods in one PISA assay. Living cells for studying target engagement in vivo or, alternatively, protein extracts to identify in vitro ligand-interacting proteins can be studied, and the minimal need in sample amount unlocks target deconvolution using primary cells and their derived cultures. This protocol was validated in: J Biol Chem (2021), DOI: 10.1016/j.jbc.2021.10153 Graphical abstract.