University College London Institute of Neurology, London, United Kingdom.
University College London Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom.
PLoS Biol. 2018 Jun 18;16(6):e2006387. doi: 10.1371/journal.pbio.2006387. eCollection 2018 Jun.
Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.
理解任何脑回路都需要对其组成神经元进行分类。在海马体 CA1 区,迄今为止已经提出了至少 23 种 GABA 能神经元的分类。然而,这个列表可能并不完整;此外,尚不清楚离散的类别是否足以描述皮质抑制性神经元的多样性,或者是否还需要连续的变异性模式。我们研究了 3663 个 CA1 抑制性细胞的转录组,揭示了 10 个主要的 GABA 能神经元群,它们分为 49 个精细的簇。所有以前描述的和几个新的细胞类群都被鉴定出来,其中三个以前描述的类群出乎意料地被发现是相同的。然而,离散类别的划分不足以描述这些细胞的多样性,因为在类群之间和内部也存在连续的变化。潜在因子分析表明,一个单一的连续变量可以预测几个基因的表达水平,这些基因在多个细胞类型中的相关性与之相似。对与这个变量相关的基因的分析表明,它反映了从代谢高度活跃的快速放电细胞到靶向远端树突或中间神经元的较慢放电细胞的范围。这些结果阐明了最简单的皮质结构之一中的抑制性神经元的复杂性,并表明描述这些细胞需要连续的变异性模式以及离散的细胞类别。