European Journal of NeuroscienceNeurosciencePeer-reviewed journal article
Cell-type specific visualization and biochemical isolation of endogenous synaptic proteins in mice
Fei Zhu, Mark O. CollinsiD, Johan HarmseiD, Jyoti Sharma ChoudharyiD, Seth G. N. GrantiD, Noboru H. KomiyamaiD
Abstract
In recent years, the remarkable molecular complexity of synapses has been revealed, with over 1000 proteins identified in the synapse proteome. Although it is known that different receptors and other synaptic proteins are present in different types of neurons and synapses, the extent of synapse diversity across the brain is largely unknown, mainly owing to technical limitations. Combining mouse genetics and proteomics we have previously reported highly efficient methods for purification of synaptic protein complexes under native conditions. In that approach, tandem affinity purification (TAP) tags were fused to the carboxyl terminus of PSD95 using gene targeting in mice. Here we report an approach that restricts tagging of endogenous PSD95 to cells expressing Cre recombinase. In addition, we developed a labelling strategy enabling visualization of endogenous PSD95 tagged by fluorescent proteins in Cre-expressing cells. We demonstrate the feasibility of proteomic characterisation of synapse proteomes and visualization of synapse proteins in specific cell types. We find that composition of PSD95 complexes purified from specific cell types differs from those extracted from tissues with diverse cellular composition. Therefore, these novel conditional PSD95 tagging lines will not only serve as powerful tools for precisely dissecting synapse diversity in specific subsets of regions/neuronal cells, but also provide an opportunity to better understand brain region-specific alterations associated with various psychiatric/neurological diseases. The newly developed conditional gene tagging methods can be applied to many different synaptic proteins and will thus facilitate research on the molecular complexity of synapses.
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- FWCI
- 1.07
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- top 27%
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