Kiragasi, B. | bioRxiv Science

bioRxiv2020

Network Analysis and Human Single Cell Brain Transcriptomics Reveal Novel Aspects of Alpha-Synuclein (SNCA) Biology

Alpha-synuclein (SNCA) aggregates are pathological hallmarks of synucleinopathies, neurodegenerative disorders including Parkinsons Disease (PD) and Lewy Body Dementia (LBD). Functional networks are not yet well-characterized for SNCA by CNS cell type. We investigated cell-specific differences in SNCA expression using Allen Brain Database single-nucleus RNA-seq data from human Middle Temporal Gyrus (MTG, 15,928 nuclei) and Anterior Cingulate Cortex (ACC, 7,258 nuclei). Weighted gene co-expression analysis (WGCNA) and hierarchical clustering identified a conserved SNCA co-expression module. Module genes were highly conserved (p < 10-10) and most highly expressed in excitatory neurons versus inhibitory neurons and other glial cells. SNCA co-expression module genes from ACC and MTG regions were then used to construct a protein-protein interaction (PPI) network, with SNCA empirically top hub. Genes in the SNCA PPI network were compared with genes nearest single nucleotide polymorphisms linked with PD risk in genome-wide association studies. 16 genes in our PPI network are nearest genes to PD risk loci (p < 0.0006) and 55 genes map within 100kb. Selected SNCA PPI network genes nearest PD risk loci were disrupted by CRISPR knock out gene editing for validation of network functional significance; disruption of STK39, GBA, and MBNL2 resulted in significantly elevated intracellular SNCA expression.

neuroscience↗

bioRxiv2018

A screen for genes that regulate synaptic growth reveals mechanisms that stabilize synaptic strength

Synapses grow, prune, and remodel throughout development, experience, and disease. This structural plasticity can destabilize information transfer in the nervous system. However, neural activity remains remarkably stable throughout life, implying that adaptive countermeasures exist to stabilize neurotransmission. Aberrant synaptic structure and function has been associated with a variety of neural diseases including Fragile X syndrome, autism, and intellectual disability. We have screened disruptions in over 300 genes in Drosophila for defects in synaptic growth at the neuromuscular junction. This effort identified 12 mutants with severe reductions or enhancements in synaptic growth. Remarkably, electrophysiological recordings revealed synaptic strength in all but one of these mutants was unchanged compared to wild type. We utilized a combination of genetic, anatomical, and electrophysiological analyses to illuminate three mechanisms that stabilize synaptic strength in the face of alterations in synaptic growth. These include compensatory changes in 1) postsynaptic receptor abundance; 2) presynaptic morphology; and 3) active zone structure. Together, this analysis identifies new genes that regulate synaptic growth and the adaptive strategies that synapses employ to homeostatically stabilize synaptic strength in response.\n\nAUTHOR SUMMARYThroughout development, maturation, experience, and disease, synapses undergo dramatic changes in growth and remodeling. Although these processes are necessary for learning and memory, they pose major challenges to stable function in the nervous system. However, neurotransmission is typically constrained within narrow physiological ranges, implying the existence of homeostatic mechanisms that maintain stable functionality despite drastic alterations in synapse number. In this study we investigate the relationship between synaptic growth and function across a variety of mutations in neural and synaptic genes in the fruitfly Drosophila melanogaster. Using the neuromuscular junction as a model system, we reveal three adaptive mechanisms that stabilize synaptic strength when synapses are dramatically under- or over-grown. Together, these findings provide insights into the strategies employed at both pre- and post-synaptic compartments to ensure stable functionality while allowing considerable flexibility in overall synapse number.

neuroscience↗