Cellular Deconstruction: Finding Meaning in Individual Cell Variation. Issue 10 (October 2015)

• Record Type: Journal Article
• Authors: Eberwine, James; Kim, Junhyong
• Is Part Of: Trends in cell biology. Volume 25:Issue 10(2015)
• Page Start: 569
• Page End: 578
• Publication Date: 2015-10
• Subjects: transcriptome -- phenotype -- biological constraints; Cytology -- Periodicals; Cytology -- Research -- Periodicals; 571.6
• DOI: 10.1016/j.tcb.2015.07.004
• Languages: English
• ISSNs: 0962-8924

Abstract

Abstract : The advent of single cell transcriptome analysis has permitted the discovery of cell-to-cell variation in transcriptome expression of even presumptively identical cells. We hypothesize that this variability reflects a many-to-one relation between transcriptome states and the phenotype of a cell. In this relation, the molecular ratios of the subsets of RNA are determined by the stoichiometric constraints of the cell systems, which underdetermine the transcriptome state. Furthermore, the variability is, in part, induced by the tissue context and is important for system-level function. This theory is analogous to theories of literary deconstruction, where multiple 'signifiers' work in opposition to one another to create meaning. By analogy, transcriptome phenotypes should be defined as subsets of RNAs comprising selected RNA systems where the system-associated RNAs are balanced with each other to produce the associated cellular function. This idea provides a framework for understanding cellular heterogeneity in phenotypic responses to variant conditions, such as disease challenge. Trends: Comparisons of transcriptomes between seemingly identical cells show that the transcriptomes have significant biological variation. Cells exhibit 'many-to-one' sets of equally functional transcriptional states that are defined, in part, by pathway constraints that are underspecified in comparison to the number of genes. Cellular contextualization occurs from the influence of the microenvironment and local interactions, suggesting that variation itself is important for system-level function.