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MSIght:一个用于提高对全球非靶向质谱成像注释信心的模块化平台。

MSIght: A Modular Platform for Improved Confidence in Global, Untargeted Mass Spectrometry Imaging Annotation.

作者信息

Fields Lauren, Miles Hannah N, Adrian Alexis E, Patrenets Elliot, Ricke William A, Li Lingjun

机构信息

Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States.

School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States.

出版信息

J Proteome Res. 2025 May 2;24(5):2478-2490. doi: 10.1021/acs.jproteome.4c01140. Epub 2025 Apr 8.

Abstract

Mass spectrometry imaging (MSI) has gained popularity in clinical analyses due to its high sensitivity, specificity, and throughput. However, global profiling experiments are often still restricted to LC-MS/MS analyses that lack spatial localization due to low-throughput methods for on-tissue peptide identification and confirmation. Additionally, the integration of parallel LC-MS/MS peptide confirmation, as well as histological stains for accurate mapping of identifications, presents a large bottleneck for data analysis, limiting throughput for untargeted profiling experiments. Here, we present a novel platform, termed MSIght, which automates the integration of these multiple modalities into an accessible and modular platform. Histological stains of tissue sections are coregistered to their respective MSI data sets to improve spatial localization and resolution of identified peptides. MS/MS peptide identifications via untargeted LC-MS/MS are used to confirm putative MSI identifications, thus generating MS images with greater confidence in a high-throughput, global manner. This platform has the potential to enable large-scale clinical cohorts to utilize MSI in the future for global proteomic profiling that uncovers novel biomarkers in a spatially resolved manner, thus widely expanding the utility of MSI in clinical discovery.

摘要

质谱成像(MSI)因其高灵敏度、特异性和通量而在临床分析中受到欢迎。然而,由于用于组织上肽段鉴定和确认的低通量方法,全局分析实验通常仍局限于缺乏空间定位的液相色谱-串联质谱(LC-MS/MS)分析。此外,并行LC-MS/MS肽段确认的整合以及用于准确映射鉴定结果的组织学染色,给数据分析带来了很大瓶颈,限制了非靶向分析实验的通量。在此,我们提出了一个名为MSIght的新型平台,该平台将这些多种模式自动整合到一个易于使用的模块化平台中。组织切片的组织学染色与各自的MSI数据集进行配准,以改善已鉴定肽段的空间定位和分辨率。通过非靶向LC-MS/MS进行的MS/MS肽段鉴定用于确认假定的MSI鉴定结果,从而以高通量、全局的方式生成更可靠的MS图像。该平台有潜力使大规模临床队列未来能够利用MSI进行全局蛋白质组分析,以空间分辨的方式发现新的生物标志物,从而广泛扩展MSI在临床发现中的应用。

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