Conditional disruption of hepatic carbamoyl phosphate synthetase 1 in mice results in hyperammonemia without orotic aciduria and can be corrected by liver-directed gene therapy.

Carbamoyl phosphate synthetase 1 (CPS1) is a urea cycle enzyme that forms carbamoyl phosphate from bicarbonate, ammonia and ATP. Bi-allelic mutations of the CPS1 gene result in a urea cycle disorder presenting with hyperammonemia, often with reduced citrulline, and without orotic aciduria. CPS1 deficiency is particularly challenging to treat and lack of early recognition typically results in early neonatal death. Therapeutic interventions have limited efficacy and most patients develop long-term neurologic sequelae. Using transgenic techniques, we generated a conditional Cps1 knockout mouse. By loxP/Cre recombinase technology, deletion of the Cps1 locus was achieved in adult transgenic animals using a Cre recombinase-expressing adeno-associated viral vector. Within four weeks from vector injection, all animals developed hyperammonemia without orotic aciduria and died. Minimal CPS1 protein was detectable in livers. To investigate the efficacy of gene therapy for CPS deficiency following knock-down of hepatic endogenous CPS1 expression, we injected these mice with a helper-dependent adenoviral vector (HDAd) expressing the large murine CPS1 cDNA under control of the phosphoenolpyruvate carboxykinase promoter. Liver-directed HDAd-mediated gene therapy resulted in survival, normalization of plasma ammonia and glutamine, and 13% of normal Cps1 expression. A gender difference in survival suggests that female mice may require higher hepatic CPS1 expression. We conclude that this conditional murine model recapitulates the clinical and biochemical phenotype detected in human patients with CPS1 deficiency and will be useful to investigate ammonia-mediated neurotoxicity and for the development of cell- and gene-based therapeutic approaches.

Gossamer: Scaling Image Processing and Reconstruction to Whole Brains.

Neuronal reconstruction-a process that transforms image volumes into 3D geometries and skeletons of cells- bottlenecks the study of brain function, connectomics and pathology. Domain scientists need exact and complete segmentations to study subtle topological differences. Existing methods are diskbound, dense-access, coupled, single-threaded, algorithmically unscalable and require manual cropping of small windows and proofreading of skeletons due to low topological accuracy. Designing a data-intensive parallel solution suited to a neurons' shape, topology and far-ranging connectivity is particularly challenging due to I/O and load-balance, yet by abstracting these vision tasks into strategically ordered specializations of search, we progressively lower memory by 4 orders of magnitude. This enables 1 mouse brain to be fully processed in-memory on a single server, at 67× the scale with 870× less memory while having 78% higher automated yield than APP2, the previous state of the art in performant reconstruction.