Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Abstract

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types1. Neural cell types have previously been defined by morphology 2,3, electrophysiology 4,5, transcriptomic expression 6-8 , connectivity 9-13, or even a combination of such modalities 14-16. More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells 17-20. Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex 21. It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type 22,23 known to be Somatostatin positive (Sst+) 24,25, were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.

The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of Mice

“…The findings presented here, along with companion manuscripts 59,66 and a recent study 65 , collectively reveal an interplay between ET neurons and specific inhibitory cell types. This observation not only sheds light on the connectivity of the ET neurons, but also offers a framework for exploring the connectivity of other excitatory cell populations, as for example layer 5 IT and layer 5 NP neurons all inhabit the same space as the layer 5 ET neurons and each also receive input from dedicated inhibitory cell types 59,65,66 .…”

“…On average, approximately two-thirds of the synapses formed by ET neurons were found to connect with inhibitory cells, with the majority of individual presynaptic ET cells establishing more than 50% of their synapses with inhibitory neurons (Fig 2 .c-d). Layer 5 ET forms specific sub-circuits with inhibitory cells that target ET neurons Layer 5 inhibitory cells exhibit highly selective patterns of inhibition towards specific types of excitatory cells 59,65,66 , and these precise connectivity patterns extend across various inhibitory cell types 59 . Building upon this knowledge and considering the strong targeting of inhibition by ET neurons shown in the previous section (Fig 2 .d), we asked whether the ET neurons form output synapses with inhibitory neurons that provide feedback inhibition to the ET neurons (i.e., ET neurons competing with each other) or if the ET neurons primarily target inhibitory cells that inhibit other types of excitatory cells.…”

“…While this connectivity certainly constrains the computations that the cortex can perform, its operation also depends on gene expression and its functional properties at any point in time. It is not a stretch of the imagination to think that in the near future one will be able to relate connectomics, gene expression and functional properties of all cells in the cortex, and in an accompanying paper we begin to relate these properties for a subset of inhibitory cells 99 .…”

“…Layer 5 inhibitory cells exhibit highly selective patterns of inhibition towards specific types of excitatory cells 59,65,66 , and these precise connectivity patterns extend across various inhibitory cell types 59 . Building upon this knowledge and considering the strong targeting of inhibition by ET neurons shown in the previous section (Fig 2.d), we asked whether the ET neurons form output synapses with inhibitory neurons that provide feedback inhibition to the ET neurons (i.e., ET neurons competing with each other) or if the ET neurons primarily target inhibitory cells that inhibit other types of excitatory cells.…”

Perisomatic Features Enable Efficient and Dataset Wide Cell-Type Classifications Across Large-Scale Electron Microscopy Volumes

“…This method is already being used to reveal fundamental aspects of cell type specific wiring of mammalian cortex. 3,[16][17][18] More broadly, the efficacy of this approach provides a roadmap for how to develop a scalable platform for leveraging local features of cells to infer cell-type classifications across large scale image data. Histogram of the radial extent of dendrites from a sample of 1,347 proofread neurons 16 (left) and the cumulative distribution of those cells (right).…”