Pincher, a pinocytic chaperone for nerve growth factor/TrkA signaling endosomes

Acentral tenet of nerve growth factor (NGF) action that is poorly understood is its ability to mediate cytoplasmic signaling, through its receptor TrkA, that is initiated at the nerve terminal and conveyed to the soma. We identified an NGF-induced protein that we termed Pincher (pinocytic chaperone) that mediates endocytosis and trafficking of NGF and its receptor TrkA. In PC12 cells, overexpression of Pincher dramatically stimulated NGF-induced endocytosis of TrkA, unexpectedly at sites of clathrin-independent macropinocytosis within cell surface ruffles. Subsequently, a system of Pincher-containing tubules mediated the delivery of NGF/TrkA-containing vesicles to cytoplasmic accumulations. These vesicles selectively and persistently mediated TrkA-erk5 mitogen-activated protein kinase signaling. A dominant inhibitory mutant form of Pincher inhibited the NGF-induced endocytosis of TrkA, and selectively blocked TrkA-mediated cytoplasmic signaling of erk5, but not erk1/2, kinases. Our results indicate that Pincher mediates pinocytic endocytosis of functionally specialized NGF/TrkA endosomes with persistent signaling potential

Clinical Pertinence Metric Enables Hypothesis-Independent Genome-Phenome Analysis for Neurologic Diagnosis

We describe an “integrated genome-phenome analysis” that combines both genomic sequence data and clinical information for genomic diagnosis. It is novel in that it uses robust diagnostic decision support and combines the clinical differential diagnosis and the genomic variants using a “pertinence” metric. This allows the analysis to be hypothesis-independent, not requiring assumptions about mode of inheritance, number of genes involved, or which clinical findings are most relevant. Using 20 genomic trios with neurologic disease, we find that pertinence scores averaging 99.9% identify the causative variant under conditions in which a genomic trio is analyzed and family-aware variant calling is done. The analysis takes seconds, and pertinence scores can be improved by clinicians adding more findings. The core conclusion is that automated genome-phenome analysis can be accurate, rapid, and efficient. We also conclude that an automated process offers a methodology for quality improvement of many components of genomic analysis