Mayhew Terry M, Lucocq John M
School of Life Sciences, Queen's Medical Centre, University of Nottingham, Nottingham, UK; School of Medicine, University of St Andrews, St Andrews, UK.
J Anat. 2015 Apr;226(4):309-21. doi: 10.1111/joa.12287. Epub 2015 Mar 9.
The terms morphome and morphomics are not new but, recently, a group of morphologists and cell biologists has given them clear definitions and emphasised their integral importance in systems biology. By analogy to other '-omes', the morphome refers to the distribution of matter within 3-dimensional (3D) space. It equates to the totality of morphological features within a biological system (virus, single cell, multicellular organism or populations thereof) and morphomics is the systematic study of those structures. Morphomics research has the potential to generate 'big data' because it includes all imaging techniques at all levels of achievable resolution and all structural scales from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. As with other '-omics', quantification is an important part of morphomics and, because biological systems exist and operate in 3D space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. Revealing and quantifying structural detail inside the specimen is achieved currently in two main ways: (i) by some form of reconstruction from serial physical or tomographic slices or (ii) by using randomly-sampled sections and simple test probes (points, lines, areas, volumes) to derive stereological estimates of global and/or individual quantities. The latter include volumes, surfaces, lengths and numbers of interesting features and spatial relationships between them. This article emphasises the value of stereological design, sampling principles and estimation tools as a template for combining with alternative imaging techniques to tackle the 'big data' issue and advance knowledge and understanding of the morphome. The combination of stereology, TEM and immunogold cytochemistry provides a practical illustration of how this has been achieved in the sub-field of nanomorphomics. Applying these quantitative tools/techniques in a carefully managed study design offers us a deeper appreciation of the spatiotemporal relationships between the genome, metabolome and morphome which are integral to systems biology.
形态组和形态组学这两个术语并不新鲜,但最近,一群形态学家和细胞生物学家给出了明确的定义,并强调了它们在系统生物学中的整体重要性。类比其他“组”,形态组指物质在三维(3D)空间中的分布。它等同于生物系统(病毒、单细胞、多细胞生物或其群体)内形态特征的总和,而形态组学是对这些结构的系统研究。形态组学研究有产生“大数据”的潜力,因为它涵盖了所有可实现分辨率水平的成像技术以及从大体解剖学和医学成像到光学和电子显微镜再到分子表征的所有结构尺度。与其他“组学”一样,定量是形态组学的重要组成部分,并且由于生物系统在3D空间中存在和运行,对形态、内容和空间关系的精确描述需要对3D结构进行定量。目前,揭示和量化标本内部的结构细节主要有两种方式:(i)通过从连续的物理切片或断层切片进行某种形式的重建,或(ii)使用随机采样的切片和简单的测试探针(点、线、面、体)来推导对全局和/或个体数量的体视学估计。后者包括感兴趣特征的体积、表面积、长度和数量以及它们之间的空间关系。本文强调体视学设计、采样原则和估计工具的价值,将其作为与其他成像技术相结合以解决“大数据”问题并推进对形态组的认识和理解的模板。体视学、透射电子显微镜(TEM)和免疫金细胞化学的结合提供了一个在纳米形态组学子领域中如何实现这一点的实际例证。在精心管理的研究设计中应用这些定量工具/技术,能让我们更深入地理解基因组、代谢组和形态组之间的时空关系,而这些关系对于系统生物学来说是不可或缺的。