Laser-capture microdissection for spatial transcriptomics of immunohistochemically detected neurons.

IF 4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Biological Chemistry Pub Date : 2025-02-01 Epub Date: 2024-12-28 DOI:10.1016/j.jbc.2024.108150
Balázs Göcz, Éva Rumpler, Soma Szentkirályi-Tóth, Katalin Skrapits, Szabolcs Takács, Miklós Sárvári, Imre Farkas, Szilárd Póliska, Erik Hrabovszky
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Abstract

We developed a versatile 'IHC/LCM-Seq' method for spatial transcriptomics of immunohistochemically detected neurons collected with laser-capture microdissection (LCM). IHC/LCM-Seq uses aluminon and polyvinyl sulfonic acid for inventive RNA-preserving strategies to maintain RNA integrity in free-floating sections of 4% formaldehyde-fixed brains. To validate IHC/LCM-Seq, we first immunostained and harvested striatal cholinergic interneurons with LCM. RNA preparations were subjected to random primer-based cDNA library preparation and bulk sequencing on the NextSeq Illumina platform. IHC/LCM-Seq detected ∼16,000 transcripts, reaching the sensitivity of a reference 'LCM-Seq method' developed for fluorescently tagged neurons microdissected from lightly formaldehyde-fixed and slide-mounted brain sections of transgenic mice. We successfully used the new IHC/LCM-Seq approach to provide unprecedented insight into the transcriptome of immunohistochemically detected gonadotropin-releasing hormone (GnRH) neurons regulating reproduction. The ∼13,000 to 14,000 transcripts identified in GnRH neurons of adult male rats and mice encoded 28 proteins implicated previously in human infertility, 35 neuropeptides, 34 nuclear receptors, and 164 G protein-coupled receptors. Functional experiments using slice electrophysiology established that the heavy Ntsr2 expression conveys a strong excitatory action of neurotensin on GnRH neurons. As an unexpected species difference, we found that GnRH neurons exclusively expressed estrogen receptor-β in rats and against the current consensus, the alpha estrogen receptor isoform in mice. The IHC/LCM-Seq technique we are reporting is a highly sensitive and accurate bulk sequencing approach to characterize the transcriptome landscape of immunohistochemically labeled neurons, including neuroendocrine GnRH cells. This method is readily applicable to any species, opening new perspectives also for future studies of the post mortem human brain.

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激光捕获显微切割用于免疫组化检测神经元的空间转录组学研究。
我们开发了一种多功能的“IHC/LCM- seq”方法,用于激光捕获显微解剖(LCM)收集的免疫组织化学检测神经元的空间转录组学。IHC/LCM-Seq使用铝和聚乙烯醇磺酸作为创造性的RNA保存策略,以维持4%甲醛固定大脑的自由漂浮切片中的RNA完整性。为了验证IHC/LCM- seq,我们首先用LCM进行免疫染色并收获纹状体胆碱能中间神经元。RNA制备在NextSeq Illumina平台上进行随机引物cDNA文库制备和批量测序。IHC/LCM-Seq检测到约16,000个转录本,达到参考“LCM-Seq方法”的灵敏度,该方法用于从转基因小鼠的轻度甲醛固定和载玻片的脑切片中显微解剖荧光标记的神经元。我们成功地使用了新的IHC/LCM-Seq方法,为免疫组织化学检测的调节生殖的促性腺激素释放激素(GnRH)神经元的转录组提供了前所未有的见解。在成年雄性大鼠和小鼠的GnRH神经元中鉴定的约13,000-14,000个转录本编码28种先前与人类不育有关的蛋白质,35个神经肽,34个核受体和164个G蛋白偶联受体。切片电生理功能实验证实,ntsr2的重表达表达了神经紧张素对GnRH神经元的强烈兴奋作用。作为一个意想不到的物种差异,我们发现GnRH神经元在大鼠中只表达雌激素受体-β,而与目前的共识相反,在小鼠中表达雌激素受体-α受体。我们报道的IHC/LCM-Seq技术是一种高度敏感和准确的批量测序方法,用于表征免疫组织化学标记的神经元(包括神经内分泌GnRH细胞)的转录组景观。这种方法很容易适用于任何物种,也为人类死后大脑的未来研究开辟了新的视角。
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来源期刊
Journal of Biological Chemistry
Journal of Biological Chemistry Biochemistry, Genetics and Molecular Biology-Biochemistry
自引率
4.20%
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1233
期刊介绍: The Journal of Biological Chemistry welcomes high-quality science that seeks to elucidate the molecular and cellular basis of biological processes. Papers published in JBC can therefore fall under the umbrellas of not only biological chemistry, chemical biology, or biochemistry, but also allied disciplines such as biophysics, systems biology, RNA biology, immunology, microbiology, neurobiology, epigenetics, computational biology, ’omics, and many more. The outcome of our focus on papers that contribute novel and important mechanistic insights, rather than on a particular topic area, is that JBC is truly a melting pot for scientists across disciplines. In addition, JBC welcomes papers that describe methods that will help scientists push their biochemical inquiries forward and resources that will be of use to the research community.
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