Single-Cell Nanodroplet Processing Proteomics Pipeline for Analysis of Human-Derived Microglia.

IF 3.9 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Proteomics Pub Date : 2026-05-01 Epub Date: 2026-02-25 DOI:10.1002/pmic.70112
Ashley N Ives, James M Fulcher, Alex R Bautista, Reta Birhanu Kitata, Sarah M Williams, David A Bennett, Philip L De Jager, Vladislav A Petyuk
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引用次数: 0

Abstract

Single-cell omics tools provide unique insights into heterogeneous cell populations and their responses to stimuli. For example, single-cell RNA sequencing has identified several transcriptionally distinct populations of microglia, which are resident immune cells of the central nervous system (CNS) that are responsive to CNS injury, infection, and neurodegeneration. To date, single-cell studies of microglia have focused on RNA-sequencing or cytometry by time of flight (CyTOF), which provide indirect readouts of protein abundance or quantification of a limited number of targets. Herein, we present a workflow based on FACS-assisted isolation, cryopreservation, and nanodroplet-based processing for single-cell mass spectrometry proteomics analysis of the postmortem human brain cortex-derived microglia. From a single microglial cell, 1039 proteins could be identified on average. As a proof-of-principle, we applied single-cell proteomics for exploring the heterogeneity of brain microglia at the cellular level. This pilot proteomics data partially recapitulates the prior microglia subtypes. Specifically, we determined that mitochondrial proteins, in particular members of NADH dehydrogenase (Complex I), cytochrome b-c1 (Complex III), cytochrome c oxidase (Complex IV), F1-ATPase (Complex V), and Na+/K+-ATPase complex, drive variation across microglia. This pipeline offers the potential for identifying functionally and analytically relevant protein targets for microglia in Alzheimer's disease and other neurological disorders. SIGNIFICANCE OF THE STUDY: Microglia are a key brain cell type that may contribute to pathogenesis in neurodegenerative disease. Transcriptomic profiling of microglia from the central nervous system of humans and animal models has identified several subtypes of microglia, and complementary proteomic profiling of microglia is likely to provide functionally and therapeutically relevant targets. Single-cell proteomics studies of human-derived microglia are lacking. This work describes a label-free, single-cell proteomics approach for microglia isolated by fluorescence-activated cell sorting from a human donor that yields comparable numbers of identifications in comparison to prior single-cell RNA sequencing studies of microglia. This approach holds promise for enabling large-scale proteomics-based subtyping of microglia and studying their roles in neurodegenerative diseases.

用于人源性小胶质细胞分析的单细胞纳米液滴加工蛋白质组学管道。
单细胞组学工具为异质细胞群及其对刺激的反应提供了独特的见解。例如,单细胞RNA测序已经确定了几个转录不同的小胶质细胞群,它们是中枢神经系统(CNS)的驻留免疫细胞,对中枢神经系统损伤、感染和神经退行性变有反应。迄今为止,小胶质细胞的单细胞研究主要集中在rna测序或飞行时间细胞术(CyTOF)上,这些方法提供了蛋白质丰度的间接读数或有限数量靶标的定量。在此,我们提出了一种基于facs辅助分离、低温保存和纳米液滴处理的工作流程,用于对死后人类大脑皮层来源的小胶质细胞进行单细胞质谱蛋白质组学分析。从单个小胶质细胞中,平均可以鉴定出1039种蛋白质。作为原理证明,我们应用单细胞蛋白质组学在细胞水平上探索脑小胶质细胞的异质性。这个试点蛋白质组学数据部分概括了先前的小胶质细胞亚型。具体来说,我们确定线粒体蛋白,特别是NADH脱氢酶(复合体I)、细胞色素b-c1(复合体III)、细胞色素c氧化酶(复合体IV)、f1 - atp酶(复合体V)和Na+/K+- atp酶复合体的成员,驱动小胶质细胞的变异。该管道为识别阿尔茨海默病和其他神经系统疾病中小胶质细胞的功能和分析相关蛋白靶点提供了潜力。研究意义:小胶质细胞是一种关键的脑细胞类型,可能参与神经退行性疾病的发病机制。来自人类和动物中枢神经系统的小胶质细胞转录组学分析已经确定了小胶质细胞的几种亚型,而小胶质细胞的互补蛋白质组学分析可能提供功能和治疗相关的靶标。缺乏对人源性小胶质细胞的单细胞蛋白质组学研究。这项工作描述了一种无标记的单细胞蛋白质组学方法,该方法通过荧光激活细胞分选从人类供体中分离出小胶质细胞,与先前的小胶质细胞单细胞RNA测序研究相比,产生了相当数量的鉴定。这种方法有望实现大规模的基于蛋白质组学的小胶质细胞亚型,并研究它们在神经退行性疾病中的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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