To maximize a desired product, metabolic engineers typically express enzymes to high, constant levels. Yet, permanent pathway activation can have undesirable consequences including competition with essential pathways and accumulation of toxic intermediates. Faced with similar challenges, natural metabolic systems compartmentalize enzymes into organelles or post-translationally induce activity under certain conditions. Here we report that optogenetic control can be used to extend compartmentalization and dynamic control to engineered metabolisms in yeast. We describe a suite of optogenetic tools to trigger assembly and disassembly of metabolically active enzyme clusters. Using the deoxyviolacein biosynthesis pathway as a model system, we find that light-switchable clustering can enhance product formation six-fold and product specificity 18-fold by decreasing the concentration of intermediate metabolites and reducing flux through competing pathways. Inducible compartmentalization of enzymes into synthetic organelles can thus be used to control engineered metabolic pathways, limit intermediates and favor the formation of desired products.
The Erk mitogen-activated protein kinase plays diverse roles in animal development. Its widespread reuse raises a conundrum: when a single kinase like Erk is activated, how does a developing cell know which fate to adopt? We combine optogenetic control with genetic perturbations to dissect Erk-dependent fates in the early Drosophila embryo. We find that Erk activity is sufficient to “posteriorize” 88% of the embryo, inducing gut endoderm-like gene expression and morphogenetic movements in all cells within this region. Gut endoderm fate adoption requires at least 1 h of signaling, whereas a 30-min Erk pulse specifies a distinct ectodermal cell type, intermediate neuroblasts. We find that the endoderm-ectoderm cell fate switch is controlled by the cumulative load of Erk activity, not the duration of a single pulse. The fly embryo thus harbors a classic example of dynamic control, where the temporal profile of Erk signaling selects between distinct physiological outcomes.
Signaling pathways, such as the Ras-Erk pathway, encode information through both their amplitude and dynamics. Differences in signal duration and frequency can lead to distinct cellular output decisions. Thus, temporal signals must be faithfully transmitted from the plasma membrane (Ras) to the nucleus (Erk) to properly control the cell’s response. Because the Ras-Erk pathway regulates important cell decisions such as proliferation, changes to dynamic signal transduction properties could result in improper cell decisions and dysfunction. However, it has been difficult to examine whether corruption of signal transmission dynamics is associated with diseases such as cancer.
Phosphatidylinositol-3,4,5-Trisphosphate Dependent Rac Exchange Factor 1 (P-Rex1) is a key mediator of growth factor-induced activation of Rac1, a small GTP-binding protein widely implicated in actin cytoskeleton reorganization. This Guanine nucleotide Exchange Factor (GEF) is overexpressed in human luminal breast cancer, and its expression associates with disease progression, metastatic dissemination and poor outcome. Despite the established contribution of P-Rex1 to Rac activation and cell locomotion, whether this Rac-GEF has any relevant role in mitogenesis has been a subject of controversy. To tackle the discrepancies among various reports, we carried out an exhaustive analysis of the potential involvement of P-Rex1 on the activation of the mitogenic Erk pathway. Using a range of luminal breast cancer cellular models, we unequivocally showed that silencing P-Rex1 (transiently, stably, using multiple siRNA sequences) had no effect on the phospho-Erk response upon stimulation with growth factors (EGF, heregulin, IGF-I) or a GPCR ligand (SDF-1). The lack of involvement of P-Rex1 in Erk activation was confirmed at the single cell level using a fluorescent biosensor of Erk kinase activity. Depletion of P-Rex1 from breast cancer cells failed to affect cell cycle progression, cyclin D1 induction, Akt activation and apoptotic responses. In addition, mammary-specific P-Rex1 transgenic mice (MMTV-P-Rex1) did not show any obvious hyperproliferative phenotype. Therefore, despite its crucial role in Rac1 activation and cell motility, P-Rex1 is dispensable for mitogenic or survival responses in breast cancer cells.
Chronic delta hepatitis, caused by hepatitis delta virus (HDV), is the most severe form of viral hepatitis, affecting at least 20 million hepatitis B virus (HBV)–infected patients worldwide. HDV/HBV co- or superinfections are major drivers for hepatocarcinogenesis. Antiviral treatments exist only for HBV and can only suppress but not cure infection. Development of more effective therapies has been impeded by the scarcity of suitable small-animal models. We created a transgenic (tg) mouse model for HDV expressing the functional receptor for HBV and HDV, the human sodium taurocholate cotransporting peptide NTCP. Both HBV and HDV entered hepatocytes in these mice in a glycoprotein-dependent manner, but one or more postentry blocks prevented HBV replication. In contrast, HDV persistently infected hNTCP tg mice coexpressing the HBV envelope, consistent with HDV dependency on the HBV surface antigen (HBsAg) for packaging and spread. In immunocompromised mice lacking functional B, T, and natural killer cells, viremia lasted at least 80 days but resolved within 14 days in immunocompetent animals, demonstrating that lymphocytes are critical for controlling HDV infection. Although acute HDV infection did not cause overt liver damage in this model, cell-intrinsic and cellular innate immune responses were induced. We further demonstrated that single and dual treatment with myrcludex B and lonafarnib efficiently suppressed viremia but failed to cure HDV infection at the doses tested. This small-animal model with inheritable susceptibility to HDV opens opportunities for studying viral pathogenesis and immune responses and for testing novel HDV therapeutics.
Altered glycolysis is a hallmark of diseases including diabetes and cancer. Despite intensive study of the contributions of individual glycolytic enzymes, systems-level analyses of flux control through glycolysis remain limited. Here, we overexpress in two mammalian cell lines the individual enzymes catalyzing each of the 12 steps linking extracellular glucose to excreted lactate, and find substantial flux control at four steps: glucose import, hexokinase, phosphofructokinase, and lactate export (and not at any steps of lower glycolysis). The four flux-controlling steps are specifically upregulated by the Ras oncogene: optogenetic Ras activation rapidly induces the transcription of isozymes catalyzing these four steps and enhances glycolysis. At least one isozyme catalyzing each of these four steps is consistently elevated in human tumors. Thus, in the studied contexts, flux control in glycolysis is concentrated in four key enzymatic steps. Upregulation of these steps in tumors likely underlies the Warburg effect.
The optimization of engineered metabolic pathways requires careful control over the levels and timing of metabolic enzyme expression. Optogenetic tools are ideal for achieving such precise control, as light can be applied and removed instantly without complex media changes. Here we show that light-controlled transcription can be used to enhance the biosynthesis of valuable products in engineered Saccharomyces cerevisiae. We introduce new optogenetic circuits to shift cells from a light-induced growth phase to a darkness-induced production phase, which allows us to control fermentation with only light. Furthermore, optogenetic control of engineered pathways enables a new mode of bioreactor operation using periodic light pulses to tune enzyme expression during the production phase of fermentation to increase yields. Using these advances, we control the mitochondrial isobutanol pathway to produce up to 8.49 ± 0.31 g l−1 of isobutanol and 2.38 ± 0.06 g l−1 of 2-methyl-1-butanol micro-aerobically from glucose. These results make a compelling case for the application of optogenetics to metabolic engineering for the production of valuable products.
Protein/RNA clusters arise frequently in spatially regulated biological processes, from the asymmetric distribution of P granules and PAR proteins in developing embryos to localized receptor oligomers in migratory cells. This co-occurrence suggests that protein clusters might possess intrinsic properties that make them a useful substrate for spatial regulation. Here, we demonstrate that protein droplets show a robust form of spatial memory, maintaining the spatial pattern of an inhibitor of droplet formation long after it has been removed. Despite this persistence, droplets can be highly dynamic, continuously exchanging monomers with the diffuse phase. We investigate the principles of biophysical spatial memory in three contexts: a computational model of phase separation; a novel optogenetic system where light can drive rapid, localized dissociation of liquid-like protein droplets; and membrane-localized signal transduction from clusters of receptor tyrosine kinases. Our results suggest that the persistent polarization underlying many cellular and developmental processes could arise through a simple biophysical process, without any additional biochemical feedback loops.
In developmental biology, localization is everything. The same stimulus—cell signaling event or expression of a gene—can have dramatically different effects depending on the time, spatial position, and cell types in which it is applied. Yet the field has long lacked the ability to deliver localized perturbations with high specificity in vivo. The advent of optogenetic tools, capable of delivering highly localized stimuli, is thus poised to profoundly expand our understanding of development. We describe the current state-of-the-art in cellular optogenetic tools, review the first wave of major studies showcasing their application in vivo, and discuss major obstacles that must be overcome if the promise of developmental optogenetics is to be fully realized.
It has recently become clear that large-scale macromolecular self-assembly is a rule, rather than an exception, of intracellular organization. A growing number of proteins and RNAs have been shown to self-assemble into micrometer-scale clusters that exhibit either liquid-like or gel-like properties. Given their proposed roles in intracellular regulation, embryo development, and human disease, it is becoming increasingly important to understand how these membraneless organelles form and to map their functional consequences for the cell. Recently developed optogenetic systems make it possible to acutely control cluster assembly and disassembly in live cells, driving the separation of proteins of interest into liquid droplets, hydrogels, or solid aggregates. Here we propose that these approaches, as well as their evolution into the next generation of optogenetic biophysical tools, will allow biologists to determine how the self-assembly of membraneless organelles modulates diverse biochemical processes.
Cell signaling networks coordinate specific patterns of protein expression in response to external cues, yet the logic by which signaling pathway activity determines the eventual abundance of target proteins is complex and poorly understood. Here, we describe an approach for simultaneously controlling the Ras/Erk pathway and monitoring a target gene’s transcription and protein accumulation in single live cells. We apply our approach to dissect how Erk activity is decoded by immediate early genes (IEGs). We find that IEG transcription decodes Erk dynamics through a shared band-pass filtering circuit; repeated Erk pulses transcribe IEGs more efficiently than sustained Erk inputs. However, despite highly similar transcriptional responses, each IEG exhibits dramatically different protein-level accumulation, demonstrating a high degree of post-transcriptional regulation by combinations of multiple pathways. Our results demonstrate that the Ras/Erk pathway is decoded by both dynamic filters and logic gates to shape target gene responses in a context-specific manner.
The Ras/Erk signaling pathway plays a central role in diverse cellular processes ranging from development to immune cell activation to neural plasticity to cancer. In recent years, this pathway has been widely studied using live-cell fluorescent biosensors, revealing complex Erk dynamics that arise in many cellular contexts. Yet despite these high-resolution tools for measurement, the field has lacked analogous tools for control over Ras/Erk signaling in live cells. Here, we provide detailed methods for one such tool based on the optical control of Ras activity, which we call "Opto-SOS." Expression of the Opto-SOS constructs can be coupled with a live-cell reporter of Erk activity to reveal highly quantitative input-to-output maps of the pathway. Detailed herein are protocols for expressing the Opto-SOS system in cultured cells, purifying the small molecule cofactor necessary for optical stimulation, imaging Erk responses using live-cell microscopy, and processing the imaging data to quantify Ras/Erk signaling dynamics.
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.
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.
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.
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.
Cell cycle arrest after DNA damage describes the interconnection between two complex signaling processes – DNA damage sensing and the cell cycle – by a variety of biochemical interactions. Damage may arise from various sources, including radiation, chemical agents, or errors during DNA synthesis or cell division. The resulting damage is sensed by a signaling network that halts the cell cycle by modulating cyclin/Cdk activity. Cell cycle arrest can be transient to allow repair of DNA damage, or can persist indefinitely as a senescence-like state. This essay describes mechanisms of DNA damage-induced cell cycle arrest, their dynamics, and their effect on eventual cell fate. It also discusses mathematical modeling approaches used to gain insight into these processes.
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.
Many numerical techniques developed for analyzing circuits can be “recycled”—that is, they can be used to analyze mass-action kinetics (MAK) models of biological processes. But the recycling must be judicious, as the differences in behavior between typical circuits and typical MAK models can impact a numerical technique’s accuracy and efficiency. In this chapter, we compare circuits and MAK models from this numerical perspective, using illustrative examples, theoretical comparisons of properties such as conservation and invariance of the non-negative orthant, as well as computational results from biological system models.
Computing parametric sensitivities for oscillators has a now well-understood subtlety associated with the indeterminacy of phase. A less universal, but still vexing, subtlety arises when an oscillator is described by a system of differential equations with "hidden" conservation constraints (HCC's); defined as weighted sums of state variables that are time-invariant. If there are HCC's, as is commonly the case for models of biochemical oscillators but rarely the case for practical circuit oscillators, the now-standard approach to computing parametric sensitivities can yield incorrect results. In addition, the monodromy matrix (the matrix of state sensitivities over one oscillation period), is often defective in a way that interferes with the usual approach to computing oscillator phase noise. In this paper we analyze the HCC case, and show that by augmenting the standard sensitivity approach with explicit HCC's, one can recover the correct parametric sensitivities. In addition, we prove that there is a typically satisfied condition that guarantees that a system with HCCs will have a defective monodromy matrix. A deliberately "flawed" ring oscillator circuit and a cyanobacterial circadian clock biochemical oscillator are used to demonstrate the parametric sensitivity problem and its resolution, and to show the issue of the defective monodromy matrix.
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.