Department of Chemistry, University of Wisconsin-Madison, Madison, USA.
School of Pharmacy, University of Wisconsin-Madison, Madison, USA.
Expert Rev Proteomics. 2021 Jul;18(7):607-621. doi: 10.1080/14789450.2021.1967146. Epub 2021 Aug 26.
Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function.
We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements.
Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.
神经肽是起源于神经内分泌系统的信号分子,在许多生化过程中可以作为神经递质和激素发挥作用。然而,由于其功能取决于浓度、翻译后修饰和其他共存的神经调节肽,因此很难准确描述其确切功能。质谱能够进行灵敏、准确和全面的肽组学分析,可分析神经肽表达变化,从而了解它们在神经退行性疾病和代谢功能等许多生物学问题中的作用。
我们简要概述了神经肽组学研究的基础、现有方法的局限性以及该领域的最新进展。本综述重点介绍了质谱方面的进展,包括标记策略、翻译后修饰分析、质谱成像以及综合多组学工作流程,并强调了定量方面的进展。
神经肽组学对于未来的临床研究至关重要,对生物标志物发现、受体鉴定和药物设计都有影响。虽然灵敏度和准确性方面的进展正在取得,但仍有改进的空间。需要更好的定量策略来进行临床分析,这些方法还需要适用于质谱成像、翻译后修饰分析和多组学,以促进对许多疾病的理解和未来治疗。