Cross-activation of FGF, NODAL, and WNT pathways constrains BMP-signaling-mediated induction of the totipotent state in mouse embryonic stem cells.

Embryonic stem cells (ESCs) are an attractive model to study the relationship between signaling and cell fates. Cultured mouse ESCs can exist in multiple states resembling distinct stages of early embryogenesis, such as totipotent, pluripotent, primed, and primitive endoderm. The signaling mechanisms regulating the totipotent state and coexistence of these states are poorly understood. Here we identify bone morphogenetic protein (BMP) signaling as an inducer of the totipotent state. However, we discover that BMP's role is constrained by the cross-activation of FGF, NODAL, and WNT pathways. We exploit this finding to enhance the proportion of totipotent cells by rationally inhibiting the cross-activated pathways. Single-cell mRNA sequencing reveals that induction of the totipotent state is accompanied by suppression of primed and primitive endoderm states. Furthermore, reprogrammed totipotent cells we generate in culture resemble totipotent cells of preimplantation embryo. Our findings reveal a BMP signaling mechanism regulating both the totipotent state and heterogeneity of ESCs.

Extracellular Signal-Regulated Kinases: One Pathway, Multiple Fates.

This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, contingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Inadequate or excessive ERK activity hinders cell proliferation, while balanced activation promotes both cell proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.

The NAMPT Inhibitor FK866 Increases Metformin Sensitivity in Pancreatic Cancer Cells.

Pancreatic cancer (pancreatic ductal adenocarcinoma: PDAC) is one of the most aggressive neoplastic diseases. Metformin use has been associated with reduced pancreatic cancer incidence and better survival in diabetics. Metformin has been shown to inhibit PDAC cells growth and survival, both in vitro and in vivo. However, clinical trials using metformin have failed to reduce pancreatic cancer progression in patients, raising important questions about molecular mechanisms that protect tumor cells from the antineoplastic activities of metformin. We confirmed that metformin acts through inhibition of mitochondrial complex I, decreasing the NAD+/NADH ratio, and that NAD+/NADH homeostasis determines metformin sensitivity in several cancer cell lines. Metabolites that can restore the NAD+/NADH ratio caused PDAC cells to be resistant to metformin. In addition, metformin treatment of PDAC cell lines induced a compensatory NAMPT expression, increasing the pool of cellular NAD+. The NAMPT inhibitor FK866 sensitized PDAC cells to the antiproliferative effects of metformin in vitro and decreased the cellular NAD+ pool. Intriguingly, FK866 combined with metformin increased survival in mice bearing KP4 cell line xenografts, but not in mice with PANC-1 cell line xenografts. Transcriptome analysis revealed that the drug combination reactivated genes in the p53 pathway and oxidative stress, providing new insights about the mechanisms leading to cancer cell death.

Single-cell mass cytometry analysis reveals stem cell heterogeneity.

Cellular heterogeneity is fundamental to both developmental differentiation and disease establishment. Recent advances in high-throughput single-cell technology have been rapidly revolutionizing the resolution of our understanding of development and disease. However, while the study of single-cell transcriptomes is easily accessible, the analysis of single-cell proteomes is still in its infancy. In this study, we describe simultaneous profiling of multiple regulatory proteins at a single-cell level using mass cytometry or cytometry by time of flight. We develop mass cytometry reagents to study key transcription factors, signaling proteins and chromatin modifiers that regulate mouse embryonic stem cells. Our data reveal that the protein level of stem cell regulators significantly varies and that cell signaling pathways are extensively cross-activated across defined culture conditions of embryonic stem cells. In addition, the mass cytometry data enabled us to identify distinct multiple cell states of embryonic stem cells and determine their variation across culture conditions. We discuss the mass cytometry method, our results of the multi-protein analysis in embryonic stem cells and potential future perspectives for single-cell protein analysis.

Helminth-induced reprogramming of the stem cell compartment inhibits type 2 immunity.

Enteric helminths form intimate physical connections with the intestinal epithelium, yet their ability to directly alter epithelial stem cell fate has not been resolved. Here we demonstrate that infection of mice with the parasite Heligmosomoides polygyrus bakeri (Hpb) reprograms the intestinal epithelium into a fetal-like state marked by the emergence of Clusterin-expressing revival stem cells (revSCs). Organoid-based studies using parasite-derived excretory-secretory products reveal that Hpb-mediated revSC generation occurs independently of host-derived immune signals and inhibits type 2 cytokine-driven differentiation of secretory epithelial lineages that promote their expulsion. Reciprocally, type 2 cytokine signals limit revSC differentiation and, consequently, Hpb fitness, indicating that helminths compete with their host for control of the intestinal stem cell compartment to promote continuation of their life cycle.

Trajectory Algorithms to Infer Stem Cell Fate Decisions.

Single-cell trajectory analysis is an active research area in single-cell genomics aiming at developing sophisticated algorithms to reconstruct complex cell-state transition trajectories. Here, we present a step-by-step protocol to use CellRouter, a multifaceted single-cell analysis platform that integrates subpopulation identification, gene regulatory networks, and trajectory inference to precisely and flexibly reconstruct complex single-cell trajectories. Subpopulations are either user-defined or identified by a graph-clustering approach in which a k-nearest neighbor graph (kNN) is created from cell-to-cell distances in a low-dimensional embedding. Edges in this graph are weighted by network similarity metrics (e.g., Jaccard index) to robustly encode phenotypic relatedness, creating a representation of single-cell transcriptomes suitable for community detection algorithms to identify clusters of densely connected cells. This subpopulation structure represents a map of putative cell-state transitions. CellRouter implements a flow network algorithm to explore this map and reconstruct cell-state transitions in complex single-cell, multidimensional omics datasets. We describe a step-by-step application of CellRouter to hematopoietic stem and progenitor cell differentiation toward four major lineages-erythrocytes, megakaryocytes, monocytes, and granulocytes-to demonstrate key components of CellRouter for single-cell trajectory analysis.

Reconstruction of complex single-cell trajectories using CellRouter.

A better understanding of the cell-fate transitions that occur in complex cellular ecosystems in normal development and disease could inform cell engineering efforts and lead to improved therapies. However, a major challenge is to simultaneously identify new cell states, and their transitions, to elucidate the gene expression dynamics governing cell-type diversification. Here, we present CellRouter, a multifaceted single-cell analysis platform that identifies complex cell-state transition trajectories by using flow networks to explore the subpopulation structure of multi-dimensional, single-cell omics data. We demonstrate its versatility by applying CellRouter to single-cell RNA sequencing data sets to reconstruct cell-state transition trajectories during hematopoietic stem and progenitor cell (HSPC) differentiation to the erythroid, myeloid and lymphoid lineages, as well as during re-specification of cell identity by cellular reprogramming of monocytes and B-cells to HSPCs. CellRouter opens previously undescribed paths for in-depth characterization of complex cellular ecosystems and establishment of enhanced cell engineering approaches.

Haematopoietic stem and progenitor cells from human pluripotent stem cells.

A variety of tissue lineages can be differentiated from pluripotent stem cells by mimicking embryonic development through stepwise exposure to morphogens, or by conversion of one differentiated cell type into another by enforced expression of master transcription factors. Here, to yield functional human haematopoietic stem cells, we perform morphogen-directed differentiation of human pluripotent stem cells into haemogenic endothelium followed by screening of 26 candidate haematopoietic stem-cell-specifying transcription factors for their capacity to promote multi-lineage haematopoietic engraftment in mouse hosts. We recover seven transcription factors (ERG, HOXA5, HOXA9, HOXA10, LCOR, RUNX1 and SPI1) that are sufficient to convert haemogenic endothelium into haematopoietic stem and progenitor cells that engraft myeloid, B and T cells in primary and secondary mouse recipients. Our combined approach of morphogen-driven differentiation and transcription-factor-mediated cell fate conversion produces haematopoietic stem and progenitor cells from pluripotent stem cells and holds promise for modelling haematopoietic disease in humanized mice and for therapeutic strategies in genetic blood disorders.

Real-Time Protein-Fragment Complementation Assays for Studying Temporal, Spatial, and Spatiotemporal Dynamics of Protein-Protein Interactions in Living Cells.

Here, we present detailed protocols for direct, real-time protein-fragment complementation assays (PCAs) for studying the spatiotemporal dynamics of protein-protein interactions (PPIs). The assays require the use of two fluorescent reporter proteins-the "Venus" version of yellow fluorescent protein (vYFP), and the monomeric infrared fluorescent protein 1.4 (IFP 1.4)-or two luciferase reporter proteins-Renilla (Rluc) and Gaussia (Gluc). The luciferase PCAs can be used to study the temporal dynamics of PPIs in any cellular compartment and on membranes. The full reversibility of these PCAs assures accurate measurements of the kinetics of PPI assembly/disassembly for processes that occur anywhere in a living cell and over time frames of seconds to hours. vYFP PCA, and all PCAs based on green fluorescent protein and its variants, are irreversible and can be used to trap and visualize rare and transient complexes and follow dynamic relocalization of constitutive complexes. vYFP PCA is limited in that accurate measurements of temporal changes in PPIs are not possible owing to the slow maturation time of vYFP (minutes to hours) and the irreversibility of its PCA that traps the complexes, thereby preventing the dissociation of PPIs that, in some instances, might cause spurious mislocalization of protein complexes. The limitations of vYFP PCA are overcome with IFP PCA, which is fully reversible and thus can be used to study spatiotemporal dynamics of PPIs on the timescale of seconds. All of these PCAs are sensitive enough to detect interactions among proteins expressed at endogenous levels in vivo.

Protein-Fragment Complementation Assays for Large-Scale Analysis, Functional Dissection, and Spatiotemporal Dynamic Studies of Protein-Protein Interactions in Living Cells.

Protein-fragment complementation assays (PCAs) comprise a family of assays that can be used to study protein-protein interactions (PPIs), conformation changes, and protein complex dimensions. We developed PCAs to provide simple and direct methods for the study of PPIs in any living cell, subcellular compartments or membranes, multicellular organisms, or in vitro. Because they are complete assays, requiring no cell-specific components other than reporter fragments, they can be applied in any context. PCAs provide a general strategy for the detection of proteins expressed at endogenous levels within appropriate subcellular compartments and with normal posttranslational modifications, in virtually any cell type or organism under any conditions. Here we introduce a number of applications of PCAs in budding yeast, Saccharomyces cerevisiae These applications represent the full range of PPI characteristics that might be studied, from simple detection on a large scale to visualization of spatiotemporal dynamics.

Nac1 Coordinates a Sub-network of Pluripotency Factors to Regulate Embryonic Stem Cell Differentiation.

Pluripotent cells give rise to distinct cell types during development and are regulated by often self-reinforcing molecular networks. How such networks allow cells to differentiate is less well understood. Here, we use integrative methods to show that external signals induce reorganization of the mouse embryonic stem cell pluripotency network and that a sub-network of four factors, Nac1, Oct4, Tcf3, and Sox2, regulates their differentiation into the alternative mesendodermal and neuroectodermal fates. In the mesendodermal fate, Nac1 and Oct4 were constrained within quantitative windows, whereas Sox2 and Tcf3 were repressed. In contrast, in the neuroectodermal fate, Sox2 and Tcf3 were constrained while Nac1 and Oct4 were repressed. In addition, we show that Nac1 coordinates differentiation by activating Oct4 and inhibiting both Sox2 and Tcf3. Reorganization of progenitor cell networks around shared factors might be a common differentiation strategy and our integrative approach provides a general methodology for delineating such networks.

Cybernetics, Redux: An Outside-In Strategy for Unraveling Cellular Function.

A new paper in Science reveals how repetitive stimulation can identify and help to repair fragilities within a signaling network, while using linear mathematical models inspired by engineering, thereby suggesting how cybernetic methods can be integrated into systems and synthetic biology.

In-vivo detection of binary PKA network interactions upon activation of endogenous GPCRs.

Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems.

PKA regulatory subunits mediate synergy among conserved G-protein-coupled receptor cascades.

G-protein-coupled receptors sense extracellular chemical or physical stimuli and transmit these signals to distinct trimeric G-proteins. Activated Gα-proteins route signals to interconnected effector cascades, thus regulating thresholds, amplitudes and durations of signalling. Gαs- or Gαi-coupled receptor cascades are mechanistically conserved and mediate many sensory processes, including synaptic transmission, cell proliferation and chemotaxis. Here we show that a central, conserved component of Gαs-coupled receptor cascades, the regulatory subunit type-II (RII) of protein kinase A undergoes adenosine 3'-5'-cyclic monophosphate (cAMP)-dependent binding to Gαi. Stimulation of a mammalian Gαi-coupled receptor and concomitant cAMP-RII binding to Gαi, augments the sensitivity, amplitude and duration of Gαi:ßγ activity and downstream mitogen-activated protein kinase signalling, independent of protein kinase A kinase activity. The mechanism is conserved in budding yeast, causing nutrient-dependent modulation of a pheromone response. These findings suggest a direct mechanism by which coincident activation of Gαs-coupled receptors controls the precision of adaptive responses of activated Gαi-coupled receptor cascades.

Protein-fragment complementation assays for large-scale analysis, functional dissection and dynamic studies of protein-protein interactions in living cells.

Protein-fragment Complementation Assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism, or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Assays can be performed in any cell type or model organism that can be transformed or transfected with gene expression DNA constructs. Here we focus on recent applications of PCA in the budding yeast, Saccharomyces cerevisiae, that cover the gamut of applications one could envision for studying any aspect of PPIs. We present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR), reporter PCA, and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present methods to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs.

A toolkit of protein-fragment complementation assays for studying and dissecting large-scale and dynamic protein-protein interactions in living cells.

Protein-fragment complementation assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Applications of PCAs in yeast have been limited until recently, simply because appropriate expression plasmids or cassettes had not been developed. However, we have now developed and reported on several PCAs in Saccharomyces cerevisiae that cover the gamut of applications one could envision for studying any aspect of PPIs. Here, we present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR) reporter PCA and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present a method to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs and finally, two luciferase reporter PCAs that have proved useful for studies of dynamics of PPIs.

The scaffold protein Ste5 directly controls a switch-like mating decision in yeast.

Evolution has resulted in numerous innovations that allow organisms to increase their fitness by choosing particular mating partners, including secondary sexual characteristics, behavioural patterns, chemical attractants and corresponding sensory mechanisms. The haploid yeast Saccharomyces cerevisiae selects mating partners by interpreting the concentration gradient of pheromone secreted by potential mates through a network of mitogen-activated protein kinase (MAPK) signalling proteins. The mating decision in yeast is an all-or-none, or switch-like, response that allows cells to filter weak pheromone signals, thus avoiding inappropriate commitment to mating by responding only at or above critical concentrations when a mate is sufficiently close. The molecular mechanisms that govern the switch-like mating decision are poorly understood. Here we show that the switching mechanism arises from competition between the MAPK Fus3 and a phosphatase Ptc1 for control of the phosphorylation state of four sites on the scaffold protein Ste5. This competition results in a switch-like dissociation of Fus3 from Ste5 that is necessary to generate the switch-like mating response. Thus, the decision to mate is made at an early stage in the pheromone pathway and occurs rapidly, perhaps to prevent the loss of the potential mate to competitors. We argue that the architecture of the Fus3-Ste5-Ptc1 circuit generates a novel ultrasensitivity mechanism, which is robust to variations in the concentrations of these proteins. This robustness helps assure that mating can occur despite stochastic or genetic variation between individuals. The role of Ste5 as a direct modulator of a cell-fate decision expands the functional repertoire of scaffold proteins beyond providing specificity and efficiency of information processing. Similar mechanisms may govern cellular decisions in higher organisms and be disrupted in cancer.

A novel genetic screen implicates Elm1 in the inactivation of the yeast transcription factor SBF.

BACKGROUND: Despite extensive large scale analyses of expression and protein-protein interactions (PPI) in the model organism Saccharomyces cerevisiae, over a thousand yeast genes remain uncharacterized. We have developed a novel strategy in yeast that directly combines genetics with proteomics in the same screen to assign function to proteins based on the observation of genetic perturbations of sentinel protein interactions (GePPI). As proof of principle of the GePPI screen, we applied it to identify proteins involved in the regulation of an important yeast cell cycle transcription factor, SBF that activates gene expression during G1 and S phase. METHODOLOGY/PRINCIPLE FINDINGS: The principle of GePPI is that if a protein is involved in a pathway of interest, deletion of the corresponding gene will result in perturbation of sentinel PPIs that report on the activity of the pathway. We created a fluorescent protein-fragment complementation assay (PCA) to detect the interaction between Cdc28 and Swi4, which leads to the inactivation of SBF. The PCA signal was quantified by microscopy and image analysis in deletion strains corresponding to 25 candidate genes that are periodically expressed during the cell cycle and are substrates of Cdc28. We showed that the serine-threonine kinase Elm1 plays a role in the inactivation of SBF and that phosphorylation of Elm1 by Cdc28 may be a mechanism to inactivate Elm1 upon completion of mitosis. CONCLUSIONS/SIGNIFICANCE: Our findings demonstrate that GePPI is an effective strategy to directly link proteins of known or unknown function to a specific biological pathway of interest. The ease in generating PCA assays for any protein interaction and the availability of the yeast deletion strain collection allows GePPI to be applied to any cellular network. In addition, the high degree of conservation between yeast and mammalian proteins and pathways suggest GePPI could be used to generate insight into human disease.