Tans Roel, Dey Shoumit, Dey Nidhi Sharma, Calder Grant, O'Toole Peter, Kaye Paul M, Heeren Ron M A
Division of Imaging Mass Spectrometry, Maastricht Multimodal Molecular Imaging (M4I) Institute, Maastricht University, Maastricht, Netherlands.
Hull York Medical School, York Biomedical Research Institute, University of York, York, United Kingdom.
Front Microbiol. 2021 Aug 19;12:709728. doi: 10.3389/fmicb.2021.709728. eCollection 2021.
Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironment may instruct complex and diverse innate and adaptive cellular responses resulting in locally distinct molecular signatures. In turn, these molecular signatures may both drive and be responsive to local metabolic changes in immune as well as non-immune cells, ultimately shaping the outcome of infection. Given the spatial complexity of immune and inflammatory responses during infection, it is evident that understanding the spatial organization of transcripts, proteins, lipids, and metabolites is pivotal to delineating the underlying regulation of local immunity. Molecular imaging techniques like mass spectrometry imaging and spatially resolved, highly multiplexed immunohistochemistry and transcriptomics can define detailed metabolic signatures at the microenvironmental level. Moreover, a successful complementation of these two imaging techniques would allow multi- analyses of inflammatory microenvironments to facilitate understanding of disease pathogenesis and identify novel targets for therapeutic intervention. Here, we describe strategies for downstream data analysis of spatially resolved multi- data and, using leishmaniasis as an exemplar, describe how such analysis can be applied in a disease-specific context.
传染病，包括病毒、细菌、真菌和寄生虫引起的疾病，通常表现为在一个或多个不同组织中发生的局灶性炎症。感染的组织特异性结果在许多传染病中也很明显，这表明局部微环境可能指导复杂多样的先天性和适应性细胞反应，从而产生局部不同的分子特征。反过来，这些分子特征可能既驱动免疫细胞和非免疫细胞中的局部代谢变化，又对其作出反应，最终决定感染的结果。鉴于感染期间免疫和炎症反应的空间复杂性，很明显，了解转录本、蛋白质、脂质和代谢物的空间组织对于描绘局部免疫的潜在调节至关重要。质谱成像以及空间分辨、高度多重免疫组织化学和转录组学等分子成像技术可以在微环境水平上定义详细的代谢特征。此外，这两种成像技术的成功互补将允许对炎症微环境进行多分析，以促进对疾病发病机制的理解，并确定治疗干预的新靶点。在这里，我们描述了空间分辨多数据下游数据分析的策略，并以利什曼病为例，描述了如何在疾病特定背景下应用这种分析。
