Bygrave, A. M. | bioRxiv Science

bioRxiv2020

An Optimized CRISPR/Cas9 Approach for Precise Genome Editing in Neurons

The efficient knock-in of large DNA fragments to label endogenous proteins remains especially challenging in non-dividing cells such as neurons. We developed Targeted Knock-In with Two-guides (TKIT) as a novel CRISPR/Cas9 based approach for efficient, and precise, genomic knock-in. Through targeting non-coding regions TKIT is resistant to INDEL mutations. We demonstrate TKIT labelling of endogenous synaptic proteins with various tags, with efficiencies up to 42% in mouse primary cultured neurons. Utilizing in utero electroporation or viral injections in mice TKIT can label AMPAR subunits with Super Ecliptic pHluorin, enabling visualization of endogenous AMPARs in vivo using two-photon microscopy. We further use TKIT to assess the mobility of endogenous AMPARs using fluorescence recovery after photobleaching. Finally, we show that TKIT can be used to tag AMPARs in rat neurons, demonstrating precise genome editing in another model organism and highlighting the broad potential of TKIT as a method to visualize endogenous proteins.

neuroscience↗

bioRxiv2020

Lack of redundancy between electrophysiological measures of long-range neuronal communication

Communication between brain areas has been implicated in a wide range of cognitive and emotive functions and is impaired in numerous mental disorders. In rodent models, various functional connectivity metrics have been used to quantify inter-regional neuronal communication. However, in individual studies, typically only very few measures of coupling are reported and, hence, redundancy across such indicators is implicitly assumed. In order to test this assumption, we here comparatively assessed a broad range of directional and non-directional metrics like coherence, weighted Phase-Lag-Index (wPLI), Granger causality (GC), spike-phase coupling (SPC), cross-regional phase-amplitude coupling, amplitude cross-correlations, and others. We applied these analyses to simultaneous field recordings from the prefrontal cortex and the ventral and dorsal hippocampus in the schizophrenia-related Gria1-knockout mouse model which displays a robust novelty-induced hyperconnectivity phenotype. We find that across such measures there is a considerable lack of functional redundancy. While coherence and GC yielded similar results, other measures, especially wPLI and SPC, often produced deviating conclusions. Bivariate correlations within animals revealed that virtually none of the metrics consistently co-varied with any of the other measures across the three connections and two genotypes analysed. Parametric GC showed the qualitatively highest degree of redundancy with other metrics and would be most suitable for connectivity analysis. We conclude that analysis of multiple metrics is necessary to characterise functional connectivity.

neuroscience↗