Signaling, Deconstructed: Using Optogenetics to Dissect and Direct Information Flow in Biological Systems

Abstract

Cells receive enormous amounts of information from their environment. How they act on this information-by migrating, expressing genes, or relaying signals to other cells-comprises much of the regulatory and self-organizational complexity found across biology. The "parts list" involved in cell signaling is generally well established, but how do these parts work together to decode signals and produce appropriate responses? This fundamental question is increasingly being addressed with optogenetic tools: light-sensitive proteins that enable biologists to manipulate the interaction, localization, and activity state of proteins with high spatial and temporal precision. In this review, we summarize how optogenetics is being used in the pursuit of an answer to this question, outlining the current suite of optogenetic tools available to the researcher and calling attention to studies that increase our understanding of and improve our ability to engineer biology.

Keywords: cell signaling; developmental biology; optogenetics; synthetic biology.

Figure 1

Schematics illustrating several mechanisms of action achievable with optogenetic tools including uncaging (AsLOV2), dimerization (Phy/PIF), homo-oligomerization (Cry2), homo-tetramerization (Dronpa), hetero-oligomerization (PixD/PixE), and photocleavage (PhoCl).

Figure 2

(a) As information processing systems, cells can be viewed through the lens of Marr’s hierarchy: molecular interactions (implementation) comprise the signaling networks (algorithm) that cells employ to regulate cellular processes (computation). (b) Systematically stimulating signaling nodes along a pathway allows one to identify regulatory mechanisms that influence signaling outputs. (c) Alterations in Ras/Erk signal encoding can result in slow Erk activation kinetics, leading to increasingly sustained Erk activation and increased proliferation. (d) Light-regulated ligand-receptor interactions can be used to tune ligand binding half-life independent of other aspects of ligand-receptor interactions, a strategy that was used to dissect mechanisms of T cell receptor activation. (e) The dynamics of gene expression regulate cell fate decisions, such as in neural progenitor cells that proliferate in response to oscillatory Ascl1 expression, and differentiate in response to sustained Ascl1 expression.

Figure 3

Optogenetics has allowed for a deeper understanding of and control over developmental signaling. (a) The iLID-based OptoSOS system was used to unravel an Erk-dependent cell fate specification event in the Drosophila embryo. To distinguish between two proposed signal-decoding mechanisms, pairs of photoactivation regimes were either administered with the same uninterrupted signal duration but different amplitude or vice versa (left side of the panel). By inducing these signals in individual embryos and observing the phenotypic response, the decoding mechanism was found to act based on the cumulative load of Erk administered. This finding led to a more complete picture of how a single morphogen, Erk, can specify multiple cell types in the Drosophila embryo (right side of panel). Figure adapted from (113). (b) Optogenetic localization of RhoGEF2 to the apical membrane of Drosophila cells allows for the precise induction of morphological movements. Here, light-activated apical constriction is sufficient to induce local tissue invagination in a user-defined pattern. Figure adapted from (118).

Figure 4

In silico feedback control aims to produce a target output by measuring a system’s output, determining the offset from the target output, and updating the input accordingly. When applied to biological systems, dynamically-varying outputs can be achieved despite complex signal processing and inherent noise.