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Abstract Unbiased phenotypic screens in patient-relevant disease models offer the potential to detect therapeutic targets for rare diseases. In this study, we developed a high-throughput screening assay to identify molecules that correct aberrant protein trafficking in adapter protein complex 4 (AP-4) deficiency, a rare but prototypical form of childhood-onset hereditary spastic paraplegia characterized by mislocalization of the autophagy protein ATG9A. Using high-content microscopy and an automated image analysis pipeline, we screened a diversity library of 28,864 small molecules and identified a lead compound, BCH-HSP-C01, that restored ATG9A pathology in multiple disease models, including patient-derived fibroblasts and induced pluripotent stem cell-derived neurons. We used multiparametric orthogonal strategies and integrated transcriptomic and proteomic approaches to delineate potential mechanisms of action of BCH-HSP-C01. Our results define molecular regulators of intracellular ATG9A trafficking and characterize a lead compound for the treatment of AP-4 deficiency, providing important proof-of-concept data for future studies.

Davies et al. identify a putative mechanism underlying the childhood neurological disorder AP-4 deficiency syndrome. In the absence of AP-4, an enzyme that makes 2-AG is not transported to the axon, leading to axonal growth defects, which can be rescued by inhibition of 2-AG breakdown.

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Adaptor protein complex 4 (AP-4) deficiency causes a severe neurological disorder via an unknown mechanism. Here, the authors reveal cargo and machinery of the AP-4 transport pathway, and propose that AP-4 mediates spatial regulation of autophagy through peripheral delivery of ATG9A.

Native immunoprecipitation followed by protein A-mediated recovery of the immuno-complex is a powerful tool to study protein-protein interactions. A limitation of this technique is the concomitant recovery of large amounts of immunoglobulin, which interferes with down-stream applications such as mass spectrometric analysis and Western blotting. Here we report a detergent-based "soft" elution protocol that allows effective recovery of immunoprecipitated antigen and binding partners, yet avoids elution of the bulk of the immunoglobulin.We assessed the performance of the soft elution protocol using immunoprecipitation of Adaptor protein complex 1 (AP-1) and associated proteins as a test case. Relative to conventional elution conditions, the novel protocol substantially improved the sensitivity of mass spectrometric identification of immunoprecipitated proteins from unfractionated solution digests. Averaging over three independent experiments, Mascot scores of identified AP-1 binding partners were increased by 39%. Conversely, the estimated amount of recovered immunoglobulin was reduced by 44%. We tested the protocol with five further antibodies derived from rabbit, mouse and goat. In each case we observed a significant reduction of co-eluting immunoglobulin.The soft elution protocol presented here shows superior performance compared to standard elution conditions for subsequent protein identification by mass spectrometry from solution digests. The method was developed for rabbit polyclonal antibodies, but also performed well with the tested goat and mouse antibodies. Hence we expect the soft elution protocol to be widely applicable.

Abstract The Dynamic Organellar Maps (DOMs) approach combines cell fractionation and shotgun-proteomics for global profiling analysis of protein subcellular localization. Here, we enhance the performance of DOMs through data-independent acquisition (DIA) mass spectrometry. DIA-DOMs achieve twice the depth of our previous workflow in the same mass spectrometry runtime, and substantially improve profiling precision and reproducibility. We leverage this gain to establish flexible map formats scaling from high-throughput analyses to extra-deep coverage. Furthermore, we introduce DOM-ABC, a powerful and user-friendly open-source software tool for analyzing profiling data. We apply DIA-DOMs to capture subcellular localization changes in response to starvation and disruption of lysosomal pH in HeLa cells, which identifies a subset of Golgi proteins that cycle through endosomes. An imaging time-course reveals different cycling patterns and confirms the quantitative predictive power of our translocation analysis. DIA-DOMs offer a superior workflow for label-free spatial proteomics as a systematic phenotype discovery tool.

The AP-5 adaptor protein complex is presumed to function in membrane traffic, but so far nothing is known about its pathway or its cargo. We have used CRISPR-Cas9 to knock out the AP-5 ζ subunit gene, AP5Z1, in HeLa cells, and then analysed the phenotype by subcellular fractionation profiling and quantitative mass spectrometry. The retromer complex had an altered steady-state distribution in the knockout cells, and several Golgi proteins, including GOLIM4 and GOLM1, were depleted from vesicle-enriched fractions. Immunolocalisation showed that loss of AP-5 led to impaired retrieval of the cation-independent mannose 6-phosphate receptor (CIMPR), GOLIM4, and GOLM1 from endosomes back to the Golgi region. Knocking down the retromer complex exacerbated this phenotype. Both the CIMPR and sortilin interacted with the AP-5-associated protein SPG15 in pull-down assays, and we propose that sortilin may act as a link between Golgi proteins and the AP-5/SPG11/SPG15 complex. Together, our findings suggest that AP-5 functions in a novel sorting step out of late endosomes, acting as a backup pathway for retromer. This provides a mechanistic explanation for why mutations in AP-5/SPG11/SPG15 cause cells to accumulate aberrant endolysosomes, and highlights the role of endosome/lysosome dysfunction in the pathology of hereditary spastic paraplegia and other neurodegenerative disorders.

Objective: Modeling of human motor intention plays an essential role in predictively controlling a robotic system in human-robot interaction tasks. In most machine learning techniques, human motor behavior is modeled as a generic stochastic process. However, the integration of a priori knowledge about underlying system structures can provide insights on otherwise unobservable intrinsic states that yield the superior prediction performance and increased generalization capabilities., Methods: We present a novel method for modeling human motor behavior that explicitly includes a neuroscientifically supported model of human motor control, in which the dynamics of the human arm are modeled by a mechanical impedance that tracks a latent desired trajectory. We adopt a Bayesian setting by defining Gaussian process (GP) priors for the impedance elements and the latent desired trajectory. This enables exploitation of a priori human arm impedance knowledge for regression of interaction forces through inference of a latent desired human trajectory., Results: The method is validated using simulated data, with particular focus on effects of GP prior parameterization and intention estimation capabilities. The superior prediction performance is shown with respect to a naive GP prior. An experiment with human participants evaluates generalization capabilities and effects of training data sparsity., Conclusion: We derive the correlations of an impedance-based GP model of human motor behavior that exploits a priori knowledge., Significance: The model effectively predicts interaction forces by inferring a latent desired human trajectory in previously observed as well as unobserved regions of the input space.