Periodic Reporting for period 2 - SYNAPTOME (Synaptome architecture of the single neuron)
Période du rapport: 2023-02-01 au 2024-07-31
Synapses – the connections between neurons – are present in vast numbers in the brain and contain thousands of different proteins in many different combinations that define their molecular diversity or synapse ‘type’. Recently, we mapped synapse molecular diversity across the whole mammalian brain, revealing a remarkable architecture of synapse types across all the different brain regions. This architecture is key to brain structure and function throughout the lifespan, providing a mechanism for the storage and recall of information in learning and memory. Synapses are known to be damaged in over 100 genetic brain disorders and our findings have shown that synaptome architecture is reorganised in conditions such as schizophrenia and autism.
As groundbreaking as these brainwide studies are, they are missing a key metric: that of synapse diversity on individual neurons. Very little is known about this fundamental structural and functional unit of brain architecture, and understanding the distribution of different synapse types on and between individual neurons is key to unravelling brain complexity as a whole, which remains a significant challenge in neuroscience. The overarching goal of the SYNAPTOME project is to define this single-neuron synaptome architecture (SNSA). Our aim is to develop new genetic labelling and computational approaches to systematically map SNSA in the mouse brain. We will identify the SNSA of the different functional types of neurons, capturing how they differ from each other, as well as determining whether neurons share a common core SNSA. We will reveal how the SNSA is built during brain development and how it is impacted by genetic disorders.
These studies will uncover fundamental design principles inherent in the building blocks of the brain that link the architecture and function of individual neurons all the way up to their organisation into brain-wide networks. The new genetic and computational tools and data resources that SYNAPTOME will bring will have wide application in neuroscience and brain disease research.
As groundbreaking as these brainwide studies are, they are missing a key metric: that of synapse diversity on individual neurons. Very little is known about this fundamental structural and functional unit of brain architecture, and understanding the distribution of different synapse types on and between individual neurons is key to unravelling brain complexity as a whole, which remains a significant challenge in neuroscience. The overarching goal of the SYNAPTOME project is to define this single-neuron synaptome architecture (SNSA). Our aim is to develop new genetic labelling and computational approaches to systematically map SNSA in the mouse brain. We will identify the SNSA of the different functional types of neurons, capturing how they differ from each other, as well as determining whether neurons share a common core SNSA. We will reveal how the SNSA is built during brain development and how it is impacted by genetic disorders.
These studies will uncover fundamental design principles inherent in the building blocks of the brain that link the architecture and function of individual neurons all the way up to their organisation into brain-wide networks. The new genetic and computational tools and data resources that SYNAPTOME will bring will have wide application in neuroscience and brain disease research.
The neuron has a complex, branching 3D structure, and so capturing SNSA presents a number of technical challenges in imaging and image analysis that we have had to address in order to lay a firm foundation for the project. The key is to be able to achieve the greatest, most representative coverage of individual neurons and their synapses while maintaining best image quality. This is impacted by several factors, including the thickness of the tissue section being examined and the distance between the individual images captured through its depth. The individual images collected need to be stitched together in a manner that accurately reconstructs the whole neuron and sufficiently reports its SNSA in 3D. We have made substantial progress towards identifying, evaluating and optimising each of these technical parameters and steps that will faithfully output the SNSA.
In parallel, in order to be able to identify synapse diversity on individual neurons, and for different functional types of neurons, we have been creating new genetic tools that will facilitate expression of molecular markers in specific neuron types (‘conditional labelling’). These new research tools tag proteins that are key in synapse structure and function, including PSD93, PSD95, SAP102 and GluR1. They will allow us to align SNSA with neuron function in the brain and will be of substantial utility to the wider neuroscience community.
Fig. 1 provides an example of how we address the challenge of capturing and characterising the SNSA of individual neurons in and among the tangled multitude in the mammalian brain. This example is from a region of the hippocampus called CA1. We first need to ensure that we can see the whole neuron, and for this we use the bright red tdTomato dye, which fills the neuron, dendritic structures and axonal projections. We can visualise the synapses, which we can see as a cloud surrounding the dendrites, by labelling the synapse protein PSD95 with eGFP (green fluorescent protein). The bottom half of Fig. 1 illustrates how we can identify the synapses that belong to an individual dendrite (using clustering analysis), and then look at various features or ‘parameters’ (e.g. their size, intensity, roundness, solidity) of each of these synapses to see how similar or different they are not only from each other, but also from those on other dendrites. Here, the synapses are labelled with PSD95eGFP, but it’s important to note that we will be labelling several different proteins because this is our key measure of synapse molecular diversity (i.e. some synapses will contain PSD95, others PSD93 or SAP102, or any combination of these proteins). Fig. 2 provides examples of diversity in synapse (blue; PSD95 top, SAP102 bottom) morphology and in their distribution along dendrites (red) in cortex layers, hippocampus and further regions of the mouse brain including striatum and thalamus, as well as an impression of molecular diversity (PSD95 (green) + SAP102 (yellow)) in the dentate gyrus (right).
In summary, we have established a method that combines viral cell-specific Cre recombinase delivery with synaptomics as a means to visualise, capture and analyse synapse diversity (molecular composition, morphology, protein lifetime) in specific types of neurons in different regions of the mouse brain. We are now moving forward from stretches of dendrites, developing methods for 3D detection and reconstruction of synaptic puncta and their placement within whole-neuron architecture reconstructed from 2D z-plane images, a key step to capturing SNSA. These new developments in image capture and analysis - collectively, the SYNEURON pipeline - will constitute an important new research tool for the neuroscience community.
In parallel, in order to be able to identify synapse diversity on individual neurons, and for different functional types of neurons, we have been creating new genetic tools that will facilitate expression of molecular markers in specific neuron types (‘conditional labelling’). These new research tools tag proteins that are key in synapse structure and function, including PSD93, PSD95, SAP102 and GluR1. They will allow us to align SNSA with neuron function in the brain and will be of substantial utility to the wider neuroscience community.
Fig. 1 provides an example of how we address the challenge of capturing and characterising the SNSA of individual neurons in and among the tangled multitude in the mammalian brain. This example is from a region of the hippocampus called CA1. We first need to ensure that we can see the whole neuron, and for this we use the bright red tdTomato dye, which fills the neuron, dendritic structures and axonal projections. We can visualise the synapses, which we can see as a cloud surrounding the dendrites, by labelling the synapse protein PSD95 with eGFP (green fluorescent protein). The bottom half of Fig. 1 illustrates how we can identify the synapses that belong to an individual dendrite (using clustering analysis), and then look at various features or ‘parameters’ (e.g. their size, intensity, roundness, solidity) of each of these synapses to see how similar or different they are not only from each other, but also from those on other dendrites. Here, the synapses are labelled with PSD95eGFP, but it’s important to note that we will be labelling several different proteins because this is our key measure of synapse molecular diversity (i.e. some synapses will contain PSD95, others PSD93 or SAP102, or any combination of these proteins). Fig. 2 provides examples of diversity in synapse (blue; PSD95 top, SAP102 bottom) morphology and in their distribution along dendrites (red) in cortex layers, hippocampus and further regions of the mouse brain including striatum and thalamus, as well as an impression of molecular diversity (PSD95 (green) + SAP102 (yellow)) in the dentate gyrus (right).
In summary, we have established a method that combines viral cell-specific Cre recombinase delivery with synaptomics as a means to visualise, capture and analyse synapse diversity (molecular composition, morphology, protein lifetime) in specific types of neurons in different regions of the mouse brain. We are now moving forward from stretches of dendrites, developing methods for 3D detection and reconstruction of synaptic puncta and their placement within whole-neuron architecture reconstructed from 2D z-plane images, a key step to capturing SNSA. These new developments in image capture and analysis - collectively, the SYNEURON pipeline - will constitute an important new research tool for the neuroscience community.
We have created new molecular labelling tools and methods which, in combination with new imaging and computational image analysis approaches, will permit the synaptome of individual neurons, and neuron types, in the mammalian brain to be captured, characterised and compared for the first time at such resolution and scale. Our progress in these areas is novel and at, or beyond, state of the art in molecular brain research.