AKT/AMPK-mediated phosphorylation of TBC1D4 disrupts the interaction with insulin-regulated aminopeptidase.

TBC1D4 is a 160 kDa multidomain Rab GTPase-activating protein (RabGAP) and a downstream target of the insulin- and contraction-activated kinases AKT and AMPK. Phosphorylation of TBC1D4 has been linked to translocation of GLUT4 from storage vesicles (GSVs) to the cell surface. However, its impact on enzymatic activity is not well understood, as previous studies mostly investigated the truncated GAP domain lacking the known phosphorylation sites. In the present study, we expressed and purified recombinant full-length TBC1D4 using a baculovirus system. Size-exclusion chromatography and coimmunoprecipitation experiments revealed that full-length TBC1D4 forms oligomers of ∼600 kDa. Compared with the truncated GAP domain, full-length TBC1D4 displayed similar substrate specificity, but had a markedly higher specific GAP activity toward Rab10. Using high-resolution mass spectrometry, we mapped 19 Ser/Thr phosphorylation sites in TBC1D4. We determined Michaelis-Menten kinetics using in vitro phosphorylation assays with purified kinases and stable isotope-labeled γ-[18O4]-ATP. These data revealed that Ser324 (KM ∼6 µM) and Thr649 (KM ∼25 µM) were preferential sites for phosphorylation by AKT, whereas Ser348, Ser577, Ser595 (KM ∼10 µM), Ser711 (KM ∼79 µM), and Ser764 were found to be preferred targets for AMPK. Phosphorylation of TBC1D4 by AKT or AMPK did not alter the intrinsic RabGAP activity, but did disrupt interaction with insulin-regulated aminopeptidase (IRAP), a resident protein of GSVs implicated in GLUT4 trafficking. These findings provide evidence that insulin and contraction may regulate TBC1D4 function primarily by disrupting the recruitment of the RabGAP to GLUT4 vesicles.

Optimizing network propagation for multi-omics data integration.

Network propagation refers to a class of algorithms that integrate information from input data across connected nodes in a given network. These algorithms have wide applications in systems biology, protein function prediction, inferring condition-specifically altered sub-networks, and prioritizing disease genes. Despite the popularity of network propagation, there is a lack of comparative analyses of different algorithms on real data and little guidance on how to select and parameterize the various algorithms. Here, we address this problem by analyzing different combinations of network normalization and propagation methods and by demonstrating schemes for the identification of optimal parameter settings on real proteome and transcriptome data. Our work highlights the risk of a 'topology bias' caused by the incorrect use of network normalization approaches. Capitalizing on the fact that network propagation is a regularization approach, we show that minimizing the bias-variance tradeoff can be utilized for selecting optimal parameters. The application to real multi-omics data demonstrated that optimal parameters could also be obtained by either maximizing the agreement between different omics layers (e.g. proteome and transcriptome) or by maximizing the consistency between biological replicates. Furthermore, we exemplified the utility and robustness of network propagation on multi-omics datasets for identifying ageing-associated genes in brain and liver tissues of rats and for elucidating molecular mechanisms underlying prostate cancer progression. Overall, this work compares different network propagation approaches and it presents strategies for how to use network propagation algorithms to optimally address a specific research question at hand.

Landscape of nuclear transport receptor cargo specificity.

Nuclear transport receptors (NTRs) recognize localization signals of cargos to facilitate their passage across the central channel of nuclear pore complexes (NPCs). About 30 different NTRs constitute different transport pathways in humans and bind to a multitude of different cargos. The exact cargo spectrum of the majority of NTRs, their specificity and even the extent to which active nucleocytoplasmic transport contributes to protein localization remains understudied because of the transient nature of these interactions and the wide dynamic range of cargo concentrations. To systematically map cargo-NTR relationships in situ, we used proximity ligation coupled to mass spectrometry (BioID). We systematically fused the engineered biotin ligase BirA* to 16 NTRs. We estimate that a considerable fraction of the human proteome is subject to active nuclear transport. We quantified the specificity and redundancy in NTR interactions and identified transport pathways for cargos. We extended the BioID method by the direct identification of biotinylation sites. This approach enabled us to identify interaction interfaces and to discriminate direct versus piggyback transport mechanisms. Data are available via ProteomeXchange with identifier PXD007976.

A proteomic atlas of insulin signalling reveals tissue-specific mechanisms of longevity assurance.

Lowered activity of the insulin/IGF signalling (IIS) network can ameliorate the effects of ageing in laboratory animals and, possibly, humans. Although transcriptome remodelling in long-lived IIS mutants has been extensively documented, the causal mechanisms contributing to extended lifespan, particularly in specific tissues, remain unclear. We have characterized the proteomes of four key insulin-sensitive tissues in a long-lived Drosophila IIS mutant and control, and detected 44% of the predicted proteome (6,085 proteins). Expression of ribosome-associated proteins in the fat body was reduced in the mutant, with a corresponding, tissue-specific reduction in translation. Expression of mitochondrial electron transport chain proteins in fat body was increased, leading to increased respiration, which was necessary for IIS-mediated lifespan extension, and alone sufficient to mediate it. Proteasomal subunits showed altered expression in IIS mutant gut, and gut-specific over-expression of the RPN6 proteasomal subunit, was sufficient to increase proteasomal activity and extend lifespan, whilst inhibition of proteasome activity abolished IIS-mediated longevity. Our study thus uncovered strikingly tissue-specific responses of cellular processes to lowered IIS acting in concert to ameliorate ageing.

Tissue-specific modulation of gene expression in response to lowered insulin signalling in Drosophila.

Reduced activity of the insulin/IGF signalling network increases health during ageing in multiple species. Diverse and tissue-specific mechanisms drive the health improvement. Here, we performed tissue-specific transcriptional and proteomic profiling of long-lived Drosophila dilp2-3,5 mutants, and identified tissue-specific regulation of >3600 transcripts and >3700 proteins. Most expression changes were regulated post-transcriptionally in the fat body, and only in mutants infected with the endosymbiotic bacteria, Wolbachia pipientis, which increases their lifespan. Bioinformatic analysis identified reduced co-translational ER targeting of secreted and membrane-associated proteins and increased DNA damage/repair response proteins. Accordingly, age-related DNA damage and genome instability were lower in fat body of the mutant, and overexpression of a minichromosome maintenance protein subunit extended lifespan. Proteins involved in carbohydrate metabolism showed altered expression in the mutant intestine, and gut-specific overexpression of a lysosomal mannosidase increased autophagy, gut homeostasis, and lifespan. These processes are candidates for combatting ageing-related decline in other organisms.