Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization

Abstract

The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success. The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. The protocol, analysis and acquisition software are compiled at https://github.com/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets.

Local connectivity and synaptic dynamics in mouse and human neocortex

“…S3B). We performed experiments using the Patch-seq method ( 39 ) and further confirmed that cells that transcriptionally mapped to the Sst subclass do form connections with each other (five connections were found of 66 probed; fig. S3C).…”

Target cell-specific synaptic dynamics of excitatory to inhibitory neuron connections in supragranular layers of human neocortex

“…Since post-hoc HCR on MPC experiments is such a low-throughput method, we took advantage of a larger existing human single cell Patch-seq datasets to develop a quantitative classifier to predict interneuron subclass identity on our larger MPC dataset. This reference dataset comprised a set of Patch-seq experiments in slice culture that targeted AAV-DLX2.0-SYFP2 labeled neurons (Berg et al, 2021, Lee et al, 2021; see Methods ), from which the cells were robustly defined based on transcriptomic analysis following electrophysiological characterization, nucleus extraction and RNA sequencing. Such a classifier strategy was possible because intrinsic membrane properties of each cell were measured in our connectivity assays with MPC recordings, including subthreshold step hyperpolarization and depolarization from −70 mV holding potential and suprathreshold step depolarization ( Figure 3d,e,f,g , and Figure 6c ).…”

Open Frontiers in Neural Cell Type Investigations; Lessons From Caenorhabditis elegans and Beyond, Toward a Multimodal Integration

“…Paired transcriptomics and proteomics investigate the molecular content of cortical neurons ( Poulopoulos et al, 2019 ). Recent approaches allow combined electrophysiological, morphological, and transcriptomic characterization of individual neurons ( Gouwens et al, 2020 ; Kalmbach et al, 2021 ; Lee B. R. et al, 2021 ). While early morphological classifications were considered outdated, cell morphology defines circuit function; axon appositions influence wiring and elaborate glia ramifications drive synapse ensheathment and function ( Chung et al, 2015 ).…”