However, a more comprehensive and inclusive understanding of biological systems warrants an approach which embraces all the biomedical disciplines (including anatomy/morphology) and provides a spatiotemporal context within which all the ‘-omes’ operate. They also embrace quantification by applying the tools of descriptive and inferential statistics in order to identify significant changes in, say, expression levels. These areas of study have developed from different disciplines (biochemistry, genetics and physiology) but each seeks to understand biological processes by identifying, quantifying and recording individual molecules or supramolecular assemblages. Like the epigenome, the other ‘-omes’ vary with time and the natural or artificial treatments to which the system is exposed (the exposome). Therefore, transcriptomics embraces the quantitative study of the expression levels of mRNAs utilising microarray, reverse transcription polymerase chain reaction and RNA-seq technologies. As this is influenced by the genes that are being expressed, the transcriptome can vary qualitatively and quantitatively depending on natural or experimental conditions. In the same way, the transcriptome is the totality of RNA species synthesised by a system. The epigenome refers to chemical changes to DNA and histones which lead to changes in genome function and gene expression. Thus, the genome represents the entire complement of genes and genetic material within a biological system and genomics is the field of study that applies DNA technology and bioinformatics to identify genome structure and function. In addition, the suffix ‘-omics’ identifies the corresponding fields of study. More recently, use of the suffix has included terms such as genome, epigenome, transcriptome, proteome, glycome, lipidome, metabolome and physiome. An early usage was the term chondriome, which referred to the total complement of mitochondria in a cell. 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.īy convention, the suffix ‘-ome’ refers to the total complement of some component (molecule, molecular assemblage, membrane, organelle, cell, tissue, organ) of a biological system (virus, cell, organism). The combination of stereology, TEM and immunogold cytochemistry provides a practical illustration of how this has been achieved in the sub-field of nanomorphomics. 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 latter include volumes, surfaces, lengths and numbers of interesting features and spatial relationships between them.
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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. 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.
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. 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. By analogy to other ‘-omes’, the morphome refers to the distribution of matter within 3-dimensional (3D) space. 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.