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成像与否:成像质谱技术在生物医学脂质组学中的应用

To image or not to image: Use of imaging mass spectrometry in biomedical lipidomics.

作者信息

Maimó-Barceló Albert, Pérez-Romero Karim, Rodríguez Ramón M, Huergo Cristina, Calvo Ibai, Fernández José A, Barceló-Coblijn Gwendolyn

机构信息

Lipids in Human Pathology, Institut d'Investigació Sanitària Illes Balears (IdISBa) - Health Research Institute of the Balearic Islands, Ctra. Valldemossa 79, Section G, Floor -1, E-07120 Palma, Balearic Islands, Spain; Research Unit, University Hospital Son Espases, Ctra Valldemossa 79, E-07120 Palma, Balearic Islands, Spain.

Department of Physical Chemistry, Fac. of Science and Technology, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940 Leioa, Spain.

出版信息

Prog Lipid Res. 2025 Jan;97:101319. doi: 10.1016/j.plipres.2025.101319. Epub 2025 Jan 5.

Abstract

Lipid imaging mass spectrometry (LIMS) allows for establishing the bidimensional distribution of lipid species within a tissue section. One of the main advantages is the generation of spatial information on lipid species distribution at a spatial (lateral) resolution bordering on single-cell resolution with no need to isolate cells. Thus, LIMS images demonstrate, with a level of detail never described before, that lipid profiles are highly sensitive to cell type and pathophysiological state. The wealth and relevance of the information conveyed by LIMS makes up for the lack of a separation stage before sample injection into the mass analyzer, which can somehow be circumvented by other means. Hence, the possibility of describing the lipidome at the cellular level while preserving the microenvironment offers an incomparable opportunity to investigate physiological and pathological contexts. However, to fully grasp the biological implications of the lipid profiles, it is essential to contextualize LIMS data within the broader multiscale 'omic' landscape, entailing genomics, epigenomics, and proteomics, each offering a unique window into the regulatory layers of the cell. In this line, the number of techniques that can be combined with LIMS to delve into the molecular mechanisms underlying differential lipid profiles is continuously increasing. Herein, we aim to describe the key features of LIMS analyses, from sample preparation to data interpretation, as well as the current methodologies to enrich and complete the final outcome. While the field is rapidly advancing, we consider there is solid evidence to foresee the incorporation of LIMS into clinical environments.

摘要

脂质成像质谱技术(LIMS)能够建立组织切片内脂质种类的二维分布。其主要优势之一是能够在接近单细胞分辨率的空间(横向)分辨率下生成脂质种类分布的空间信息,而无需分离细胞。因此,LIMS图像以前所未有的详细程度表明,脂质谱对细胞类型和病理生理状态高度敏感。LIMS所传达信息的丰富性和相关性弥补了在将样品注入质量分析仪之前缺乏分离步骤的不足,这在某种程度上可以通过其他方法来规避。因此,在保留微环境的同时在细胞水平描述脂质组的可能性为研究生理和病理背景提供了无与伦比的机会。然而,要充分理解脂质谱的生物学意义,必须将LIMS数据置于更广泛的多尺度“组学”格局中,包括基因组学、表观基因组学和蛋白质组学,每一个都为细胞的调控层面提供了独特的视角。按照这种思路,可与LIMS结合以深入研究差异脂质谱背后分子机制的技术数量在不断增加。在此,我们旨在描述LIMS分析的关键特征,从样品制备到数据解读,以及丰富和完善最终结果的当前方法。虽然该领域发展迅速,但我们认为有确凿证据可以预见LIMS将被纳入临床环境。

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