From single cells to tissue self-organization

Abstract

Self-organization is a process by which interacting cells organize and arrange themselves in higher order structures and patterns. To achieve this, cells must have molecular mechanisms to sense their complex local environment and interpret it to respond accordingly. A combination of cell-intrinsic and cell-extrinsic cues are decoded by the single cells dictating their behaviour, their differentiation and symmetry-breaking potential driving development, tissue remodeling and regenerative processes. A unifying property of these self-organized pattern-forming systems is the importance of fluctuations, cell-to-cell variability, or noise. Cell-to-cell variability is an inherent and emergent property of populations of cells that maximize the population performance instead of the individual cell, providing tissues the flexibility to develop and maintain homeostasis in diverse environments. In this review, we will explore the role of self-organization and cell-to-cell variability as fundamental properties of multicellularity-and the requisite of single-cell resolution for its understanding. Moreover, we will analyze how single cells generate emergent multicellular dynamics observed at the tissue level 'travelling' across different scales: spatial, temporal and functional.

Keywords: cell-to-cell variability; crossing-scales technologies; development; emergent properties; multicellularity; organoids; pattern formation; regeneration; self-organization; symmetry-breaking.

Figure 1

From a population of single cells to tissues. (A) Heterogeneous population of cells where each single cell senses a combination of cell‐intrinsic and cell‐extrinsic cues, ultimately driving tissue patterning. (B) Spatio‐temporal variability and symmetry breaking in intestinal organoids. An intestinal stem cell develops into a symmetrical cyst and undergoes symmetry breaking with the appearance of Paneth cell. This Paneth cell defines the position of the nascent crypt where the stem cell niche will reside. The intestinal organoid develops into a self‐organized structure containing different cell types distributed in a zonated manner recapitulating part of intestinal patterning.

Figure 2

Cell‐to‐cell variability is an advantageous property of a population of stem cells. A population of stem cells which are uniform in their cellular activities, respond to a stimuli in an ‘all‐or‐none’ manner, with a critical threshold below which all cells remain undifferentiated and above which all cells differentiate (upper panel). A graded response is observed in the presence of cell‐to‐cell variability making it possible to control the rate of differentiation according to stimuli concentrations (lower panel). Variability provides adaptability to selective pressure (right side). In a homogeneous scenario, an environmental challenge results in poor population performance, while a heterogeneous population is more robust to the selective pressure, allowing the survival of some individual cells.

Figure 3

Scale‐crossing technologies required for understanding self‐organization. Different experimental frameworks are required to quantitate and model the population‐level properties of a large group of interacting cells during self‐organized processes. Scale‐crossing technologies described in the text are able to link functional, spatial and temporal scales. Detailed information at each level of these scales, from single cells to tissues, will help to explain the multicellular dynamic interactions that govern a self‐organized process.