Phase transitions driven by intrinsically disordered protein regions (IDRs) have emerged as a ubiquitous mechanism for assembling liquid-like RNA/protein (RNP) bodies and other membrane-less organelles. However, a lack of tools to control intracellular phase transitions limits our ability to understand their role in cell physiology and disease. Here, we introduce an optogenetic platform that uses light to activate IDR-mediated phase transitions in living cells. We use this "optoDroplet" system to study condensed phases driven by the IDRs of various RNP body proteins, including FUS, DDX4, and HNRNPA1. Above a concentration threshold, these constructs undergo light-activated phase separation, forming spatiotemporally definable liquid optoDroplets. FUS optoDroplet assembly is fully reversible even after multiple activation cycles. However, cells driven deep within the phase boundary form solid-like gels that undergo aging into irreversible aggregates. This system can thus elucidate not only physiological phase transitions but also their link to pathological aggregates.
Animal development is characterized by signaling events that occur at precise locations and times within the embryo, but determining when and where such precision is needed for proper embryogenesis has been a long-standing challenge. Here we address this question for extracellular signal regulated kinase (Erk) signaling, a key developmental patterning cue. We describe an optogenetic system for activating Erk with high spatiotemporal precision in vivo. Implementing this system in Drosophila, we find that embryogenesis is remarkably robust to ectopic Erk signaling, except from 1 to 4 hr post-fertilization, when perturbing the spatial extent of Erk pathway activation leads to dramatic disruptions of patterning and morphogenesis. Later in development, the effects of ectopic signaling are buffered, at least in part, by combinatorial mechanisms. Our approach can be used to systematically probe the differential contributions of the Ras/Erk pathway and concurrent signals, leading to a more quantitative understanding of developmental signaling.
Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control.
For directional movement, eukaryotic cells depend on the proper organization of their actin cytoskeleton. This engine of motility is made up of highly dynamic nonequilibrium actin structures such as flashes, oscillations, and traveling waves. In Dictyostelium, oscillatory actin foci interact with signals such as Ras and phosphatidylinositol 3,4,5-trisphosphate (PIP3) to form protrusions. However, how signaling cues tame actin dynamics to produce a pseudopod and guide cellular motility is a critical open question in eukaryotic chemotaxis. Here, we demonstrate that the strength of coupling between individual actin oscillators controls cell polarization and directional movement. We implement an inducible sequestration system to inactivate the heterotrimeric G protein subunit Gβ and find that this acute perturbation triggers persistent, high-amplitude cortical oscillations of F-actin. Actin oscillators that are normally weakly coupled to one another in wild-type cells become strongly synchronized following acute inactivation of Gβ. This global coupling impairs sensing of internal cues during spontaneous polarization and sensing of external cues during directional motility. A simple mathematical model of coupled actin oscillators reveals the importance of appropriate coupling strength for chemotaxis: moderate coupling can increase sensitivity to noisy inputs. Taken together, our data suggest that Gβ regulates the strength of coupling between actin oscillators for efficient polarity and directional migration. As these observations are only possible following acute inhibition of Gβ and are masked by slow compensation in genetic knockouts, our work also shows that acute loss-of-function approaches can complement and extend the reach of classical genetics in Dictyostelium and likely other systems as well.
The human interferon-inducible protein IFI16 is an important antiviral factor that binds nuclear viral DNA and promotes antiviral responses. Here, we define IFI16 dynamics in space and time and its distinct functions from the DNA sensor cyclic dinucleotide GMP-AMP synthase (cGAS). Live-cell imaging reveals a multiphasic IFI16 redistribution, first to viral entry sites at the nuclear periphery and then to nucleoplasmic puncta upon herpes simplex virus 1 (HSV-1) and human cytomegalovirus (HCMV) infections. Optogenetics and live-cell microscopy establish the IFI16 pyrin domain as required for nuclear periphery localization and oligomerization. Furthermore, using proteomics, we define the signature protein interactions of the IFI16 pyrin and HIN200 domains and demonstrate the necessity of pyrin for IFI16 interactions with antiviral proteins PML and cGAS. We probe signaling pathways engaged by IFI16, cGAS, and PML using clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9-mediated knockouts in primary fibroblasts. While IFI16 induces cytokines, only cGAS activates STING/TBK-1/IRF3 and apoptotic responses upon HSV-1 and HCMV infections. cGAS-dependent apoptosis upon DNA stimulation requires both the enzymatic production of cyclic dinucleotides and STING. We show that IFI16, not cGAS or PML, represses HSV-1 gene expression, reducing virus titers. This indicates that regulation of viral gene expression may function as a greater barrier to viral replication than the induction of antiviral cytokines. Altogether, our findings establish coordinated and distinct antiviral functions for IFI16 and cGAS against herpesviruses.
IMPORTANCE: How mammalian cells detect and respond to DNA viruses that replicate in the nucleus is poorly understood. Here, we decipher the distinct functions of two viral DNA sensors, IFI16 and cGAS, during active immune signaling upon infection with two herpesviruses, herpes simplex virus 1 (HSV-1) and human cytomegalovirus (HCMV). We show that IFI16 rapidly oligomerizes at incoming herpesvirus genomes at the nuclear periphery to transcriptionally repress viral gene expression and limit viral replicative capacity. We further demonstrate that IFI16 does not initiate upstream activation of the canonical STING/TBK-1/IRF3 signaling pathway but is required for downstream antiviral cytokine expression. In contrast, we find that, upon DNA sensing during herpesvirus infection, cGAS triggers apoptosis in a STING-dependent manner. Our live-cell imaging, mass spectrometry-based proteomics, CRISPR-based cellular assays, and optogenetics underscore the value of integrative approaches to uncover complex cellular responses against pathogens.
The complex, interconnected architecture of cell-signaling networks makes it challenging to disentangle how cells process extracellular information to make decisions. We have developed an optogenetic approach to selectively activate isolated intracellular signaling nodes with light and use this method to follow the flow of information from the signaling protein Ras. By measuring dose and frequency responses in single cells, we characterize the precision, timing, and efficiency with which signals are transmitted from Ras to Erk. Moreover, we elucidate how a single pathway can specify distinct physiological outcomes: by combining distinct temporal patterns of stimulation with proteomic profiling, we identify signaling programs that differentially respond to Ras dynamics, including a paracrine circuit that activates STAT3 only after persistent (>1 hr) Ras activation. Optogenetic stimulation provides a powerful tool for analyzing the intrinsic transmission properties of pathway modules and identifying how they dynamically encode distinct outcomes.
The ability to control the activity of intracellular signaling processes in live cells would be an extraordinarily powerful tool. Ideally, such an intracellular input would be (i) genetically encoded, (ii) able to be turned on and off in defined temporal or spatial patterns, (iii) fast to switch between on and off states, and (iv) orthogonal to other cellular processes. The light-gated interaction between fragments of two plant proteins--termed Phy and PIF--satisfies each of these constraints. In this system, Phy can be switched between two conformations using red and infrared light, while PIF only binds one of these states. This chapter describes known constraints for designing genetic constructs using Phy and PIF and provides protocols for expressing these constructs in mammalian cells, purifying the small molecule chromophore required for the system's light responsivity, and measuring light-gated binding by microscopy.
The ability to apply precise inputs to signaling species in live cells would be transformative for interrogating and understanding complex cell-signaling systems. Here we report an 'optogenetic' method for applying custom signaling inputs using feedback control of a light-gated protein-protein interaction. We applied this strategy to perturb protein localization and phosphoinositide 3-kinase activity, generating time-varying signals and clamping signals to buffer against cell-to-cell variability or changes in pathway activity.
Recent studies have shown that many cell-signaling networks contain interactions and feedback loops that give rise to complex dynamics. Synthetic biology has allowed researchers to construct and analyze well-defined signaling circuits exhibiting behavior that can be predicted and quantitatively understood. Combining these approaches--wiring natural network components together with engineered interactions--has the potential to precisely modulate the dynamics of endogenous signaling processes and control the cell decisions they influence. Here, we focus on the p53 signaling pathway as a template for constructing a tunable oscillator comprised of both natural and synthetic components in mammalian cells. We find that a reduced p53 circuit implementing a single feedback loop preserves some features of the full network's dynamics, exhibiting pulses of p53 with tightly controlled timing. However, in contrast to the full natural p53 network, these pulses are damped in individual cells, with amplitude that depends on the input strength. Guided by a computational model of the reduced circuit, we constructed and analyzed circuit variants supplemented with synthetic positive and negative feedback loops and subjected to chemical perturbation. Our work demonstrates that three important features of oscillator dynamics--amplitude, period, and the rate of damping--can be controlled by manipulating stimulus level, interaction strength, and feedback topology. The approaches taken here may be useful for the rational design of synthetic networks with defined dynamics, and for identifying perturbations that control dynamics in natural biological circuits for research or therapeutic purposes.
In response to DNA damage, cells arrest at specific stages in the cell cycle. This arrest must fulfill at least 3 requirements: it must be activated promptly; it must be sustained as long as damage is present to prevent loss of genomic information; and after the arrest, cells must re-enter into the appropriate cell cycle phase to ensure proper ploidy. Multiple molecular mechanisms capable of arresting the cell cycle have been identified in mammalian cells; however, it is unknown whether each mechanism meets all 3 requirements or whether they act together to confer specific functions to the arrest. To address this question, we integrated mathematical models describing the cell cycle and the DNA damage signaling networks and tested the contributions of each mechanism to cell cycle arrest and re-entry. Predictions from this model were then tested with quantitative experiments to identify the combined action of arrest mechanisms in irradiated cells. We find that different arrest mechanisms serve indispensable roles in the proper cellular response to DNA damage over time: p53-independent cyclin inactivation confers immediate arrest, whereas p53-dependent cyclin downregulation allows this arrest to be sustained. Additionally, p21-mediated inhibition of cyclin-dependent kinase activity is indispensable for preventing improper cell cycle re-entry and endoreduplication. This work shows that in a complex signaling network, seemingly redundant mechanisms, acting in a concerted fashion, can achieve a specific cellular outcome.
Mechanism-based chemical kinetic models are increasingly being used to describe biological signaling. Such models serve to encapsulate current understanding of pathways and to enable insight into complex biological processes. One challenge in model development is that, with limited experimental data, multiple models can be consistent with known mechanisms and existing data. Here, we address the problem of model ambiguity by providing a method for designing dynamic stimuli that, in stimulus-response experiments, distinguish among parameterized models with different topologies, i.e., reaction mechanisms, in which only some of the species can be measured. We develop the approach by presenting two formulations of a model-based controller that is used to design the dynamic stimulus. In both formulations, an input signal is designed for each candidate model and parameterization so as to drive the model outputs through a target trajectory. The quality of a model is then assessed by the ability of the corresponding controller, informed by that model, to drive the experimental system. We evaluated our method on models of antibody-ligand binding, mitogen-activated protein kinase (MAPK) phosphorylation and de-phosphorylation, and larger models of the epidermal growth factor receptor (EGFR) pathway. For each of these systems, the controller informed by the correct model is the most successful at designing a stimulus to produce the desired behavior. Using these stimuli we were able to distinguish between models with subtle mechanistic differences or where input and outputs were multiple reactions removed from the model differences. An advantage of this method of model discrimination is that it does not require novel reagents, or altered measurement techniques; the only change to the experiment is the time course of stimulation. Taken together, these results provide a strong basis for using designed input stimuli as a tool for the development of cell signaling models.
HIV-1 Tat transactivation is vital for completion of the viral life cycle and has been implicated in determining proviral latency. We present an extensive experimental/computational study of an HIV-1 model vector (LTR-GFP-IRES-Tat) and show that stochastic fluctuations in Tat influence the viral latency decision. Low GFP/Tat expression was found to generate bifurcating phenotypes with clonal populations derived from single proviral integrations simultaneously exhibiting very high and near zero GFP expression. Although phenotypic bifurcation (PheB) was correlated with distinct genomic integration patterns, neither these patterns nor other extrinsic cellular factors (cell cycle/size, aneuploidy, chromatin silencing, etc.) explained PheB. Stochastic computational modeling successfully accounted for PheB and correctly predicted the dynamics of a Tat mutant that were subsequently confirmed by experiment. Thus, Tat stochastics appear sufficient to generate PheB (and potentially proviral latency), illustrating the importance of stochastic fluctuations in gene expression in a mammalian system.