High-resolution sample size enrichment of single-cell multi-modal low-throughput Patch-seq datasets

Martini, Lorenzo; Bardini, Roberta; Savino, Alessandro; Carlo, Stefano Di

doi:10.1109/bibm55620.2022.9995529

Cited by 1 publication

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“…The NSS-based analysis benefits from patchseq datasets due to their inherent consistency between EP and transcriptomic cellular profiles. Unfortunately, patchseq datasets currently face challenges in terms of data availability, and they often have low throughput due to technical limitations, resulting in a limited number of samples per dataset and hindering large-scale analysis [42, 48]. Nevertheless, recent advancements in semi-automatic patchclamp setups allow for the generation and publication of large-scale patch-clamp datasets [49].…”

Section: Discussionmentioning

confidence: 99%

Neuronal Spike Shapes (NSS): A Straightforward Approach to Investigate Heterogeneity in Neuronal Excitability States

Martini

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Carlo

et al. 2023

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The mammalian brain exhibits a remarkable diversity of neurons, contributing to its intricate architecture and functional complexity. The analysis of multi-modal single-cell datasets enables the investigation of this heterogeneity. In this study, we introduce the Neuronal Spike Shapes (NSS), a straightforward approach for analyzing the electrophysiological profiles of cells based on their Action Potential (AP) waveforms. The NSS method holds the potential to effectively explore the heterogeneity of cell types and states by summarizing the AP waveform into a triangular representation complemented by a set of derived electrophysiological (EP) features. To support this hypothesis, we validate the proposed approach using two datasets of murine cortical interneurons. The validation process involves a combination of NSS-based clustering analysis, Differential Expression (DE), and Gene Ontology (GO) enrichment analysis. The results demonstrate that the NSS-based analysis captures distinct partitions of cells that possess biological relevance independent of cell subtype, suggesting them as potential cellular states. Furthermore, the analysis reveals the emergence of voltage-gated K+ channels as transcriptomic markers associated with the identified electrophysiological partitions. This finding is particularly significant as the expression of voltage-gated K+ channels regulates the hyperpolarization phase of the AP, providing further support for the biological significance of the NSS-based clustering approach.

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Section: Discussionmentioning

confidence: 99%