Chromatin regulators play a major role in establishing and maintaining gene expression states. Yet how they control gene expression in single cells, quantitatively and over time, remains unclear. We used time-lapse microscopy to analyze the dynamic effects of four silencers associated with diverse modifications: DNA methylation, histone deacetylation, and histone methylation. For all regulators, silencing and reactivation occurred in all-or-none events, enabling the regulators to modulate the fraction of cells silenced rather than the amount of gene expression. These dynamics could be described by a three-state model involving stochastic transitions between active, reversibly silent, and irreversibly silent states. Through their individual transition rates, these regulators operate over different time scales and generate distinct types of epigenetic memory. Our results provide a framework for understanding and engineering mammalian chromatin regulation and epigenetic memory.

Summary The Bone Morphogenetic Protein (BMP) signaling pathway comprises multiple ligands and receptors that interact promiscuously with one another, and typically appear in combinations. This feature is often explained in terms of redundancy and regulatory flexibility, but it has remained unclear what signal processing capabilities it provides. Here, we show that the BMP pathway processes multi-ligand inputs using a specific repertoire of computations, including ratiometric sensing, balance detection and imbalance detection. These computations operate on the relative levels of different ligands, and can arise directly from competitive receptor-ligand interactions. Furthermore, cells can select different computations to perform on the same ligand combination through expression of alternative sets of receptor variants. These results provide a direct signal processing role for promiscuous receptor-ligand interactions, and establish operational principles for quantitatively controlling cells with BMP ligands. Similar principles could apply to other promiscuous signaling pathways.

We report a chip-scale lensless wide-field-of-view microscopy imaging technique, subpixel perspective sweeping microscopy, which can render microscopy images of growing or confluent cell cultures autonomously. We demonstrate that this technology can be used to build smart Petri dish platforms, termed ePetri, for cell culture experiments. This technique leverages the recent broad and cheap availability of high performance image sensor chips to provide a low-cost and automated microscopy solution. Unlike the two major classes of lensless microscopy methods, optofluidic microscopy and digital in-line holography microscopy, this new approach is fully capable of working with cell cultures or any samples in which cells may be contiguously connected. With our prototype, we demonstrate the ability to image samples of area 6 mm × 4 mm at 660-nm resolution. As a further demonstration, we showed that the method can be applied to image color stained cell culture sample and to image and track cell culture growth directly within an incubator. Finally, we showed that this method can track embryonic stem cell differentiations over the entire sensor surface. Smart Petri dish based on this technology can significantly streamline and improve cell culture experiments by cutting down on human labor and contamination risks.lensless imaging | time-lapse microscopy | on-chip cellular imaging | stem cell differentiation tracking | superresolution algorithm

Summary As they proliferate, living cells undergo transitions between specific molecularly and developmentally distinct states. Despite the functional centrality of these transitions in multicellular organisms, it has remained challenging to determine which transitions occur and at what rates without perturbations and cell engineering. Here, we introduce Kin Correlation Analysis (KCA) and show that quantitative cell state transition dynamics can be inferred without direct, molecular-level observation from the clustering of cell states on pedigrees (lineage trees). Combining KCA with pedigrees obtained from time-lapse imaging and end-point single-molecule RNA-FISH measurements of gene expression, we determined the cell state transition network of mouse embryonic stem (ES) cells. This analysis revealed that mouse ES cells exhibit stochastic and reversible transitions along a linear chain of states ranging from 2C-like to epiblast-like. Our approach is broadly applicable and may be applied to systems with irreversible transitions and non-stationary dynamics, such as in cancer and development.

A widespread feature of extracellular signaling in cell circuits is paradoxical pleiotropy: the same secreted signaling molecule can induce opposite effects in the responding cells. For example, the cytokine IL-2 can promote proliferation and death of T cells. The role of such paradoxical signaling remains unclear. To address this, we studied CD4(+) T cell expansion in culture. We found that cells with a 30-fold difference in initial concentrations reached a homeostatic concentration nearly independent of initial cell levels. Below an initial threshold, cell density decayed to extinction (OFF-state). We show that these dynamics relate to the paradoxical effect of IL-2, which increases the proliferation rate cooperatively and the death rate linearly. Mathematical modeling explained the observed cell and cytokine dynamics and predicted conditions that shifted cell fate from homeostasis to the OFF-state. We suggest that paradoxical signaling provides cell circuits with specific dynamical features that are robust to environmental perturbations.

An experimental and theoretical study of T cell differentiation in response to mixed-input conditions reveals that cells can tune between Th1 and Th2 states through a continuum of mixed phenotypes.

Biological systems display complex networks of interactions both at the level of molecules inside the cell and at the level of interactions between cells. Networks of interacting molecules, such as transcription networks, have been shown to be composed of recurring circuits called network motifs, each with specific dynamical functions. Much less is known about the possibility of such circuit analysis in networks made of communicating cells. Here, we study models of circuits in which a few cell types interact by means of signaling molecules. We consider circuits of cells with architectures that seem to recur in immunology. An intriguing feature of these circuits is their use of signaling molecules with a pleiotropic or paradoxical role, such as cytokines that increase both cell growth and cell death. We find that pleiotropic signaling molecules can provide cell circuits with systems-level functions. These functions include for different circuits maintenance of homeostatic cell concentrations, robust regulation of differentiation processes, and robust pulses of cells or cytokines.G ene regulation networks are composed of a handful of recurring circuit elements, called network motifs (1). Theory and experiments have shown that each network motif can carry out specific dynamical functions in an autonomous way, such as filtering noisy signals, generating output pulses, and speeding responses (1).Here, we ask whether one can apply this approach to the level of circuits made of interacting cells. For this purpose, we consider cells that communicate by means of secreted molecules. These secreted molecules affect cell behaviors such as rate of proliferation and cell death. Previous studies on such cell systems attempted to include many cell types and interactions in a model involving numerous biochemical parameters and variables (2-5). Other works focused on the effects of a single cell type responding, for example, to a ligand that it secretes itself; these works showed the interplay between cell to cell variability and positive feedback, leading to bistability (selection), formation of thresholds for immune response, and memory (6, 7).Here, we study simple models of circuits made of a few communicating cell types. Because many of the interactions in cell circuits are poorly characterized at present, we seek models in which the exact functional form of the interactions does not affect the conclusions; therefore, models have a degree of generality. We also scan all possible topologies with a given set of components to obtain the widest class of circuits that can perform a given function.We consider circuit designs that seem to recur in immunology. An intriguing feature of these systems is the fact that many secreted signaling molecules (cytokines) are pleiotropic: they have multiple effects, sometimes antagonistic or paradoxical, such as increasing both proliferation and death of a certain cell type. We find that pleiotropic signals, in the configurations suggested by immune circuits, can provide circuits with specific d...

In the Kachru-Kallosh-Linde-Trivedi (KKLT) de-Sitter construction one introduces an anti-D3-brane that breaks the supersymmetry and leads to a positive cosmological constant. In this paper we investigate the open string moduli associated with this anti-D3-brane, corresponding to its position on the S 3 at the tip of the deformed conifold. We show that in the KKLT construction these moduli are very light, and we suggest a possible way to give these moduli a large mass by putting orientifold planes in the KKLT "throat".