A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry

B. Nijhof, A. Castells-Nobau, L. Wolf, J. Scheffer-de Gooyert, I. Monedero, L. Torroja, L. Coromina, J. van der Laak and A. Schenck

PLOS Computational Biology 2016;12:e1004823.

DOI PMID Cited by ~62

Author Summary Altered synapse function underlies cognitive disorders such as intellectual disability, autism and schizophrenia. The morphology of synapses is crucial for their function but is often described using only a small number of parameters or categories. As a consequence, it is still unknown how different aspects of synapse morphology relate to each other and whether they respond in a coordinated or independent manner. Here, we report a sensitive and multiparametric method for systematic synapse morphometry at the Drosophila Neuromuscular Junction (NMJ), a popular model for mammalian synapse biology. Surveying a large NMJ image repository, we provide insights in the natural variation of NMJ morphology as a result of differences in gender, genetic background and abdominal body segment. We show which synapse parameters correlate and find that parameters fall into five groups. Based on our findings, we propose that two of them, NMJ size and geometry, are controlled by different molecular mechanisms. Our study provides insights into the design principles of a model synapse and tools that can be applied in future studies to identify genes that modulate or co-orchestrate different aspects of synapse morphology.