Cell-specific responses to the cytokine TGFβ are determined by variability in protein levels

Transcriptional regulators ensuring specific gene expression and decision-making at high TGFβ doses

TGFβ-signaling regulates cancer progression by controlling cell division, migration, and death. These outcomes are mediated by gene expression changes, but the mechanisms of decision-making toward specific fates remain unclear. Here, we combine SMAD transcription factor imaging, genome-wide RNA sequencing, and morphological assays to quantitatively link signaling, gene expression, and fate decisions in mammary epithelial cells. Fitting genome-wide kinetic models to our time-resolved data, we find that most of the TGFβ target genes can be explained as direct targets of SMAD transcription factors, whereas the remainder show signs of complex regulation, involving delayed regulation and strong amplification at high TGFβ doses. Knockdown experiments followed by global RNA sequencing revealed transcription factors interacting with SMADs in feedforward loops to control delayed and dose-discriminating target genes, thereby reinforcing the specific epithelial-to-mesenchymal transition at high TGFβ doses. We identified early repressors, preventing premature activation, and a late activator, boosting gene expression responses for a sufficiently strong TGFβ stimulus. Taken together, we present a global view of TGFβ-dependent gene regulation and describe specificity mechanisms reinforcing cellular decision-making.

RTF: an R package for modelling time course data

SUMMARY

The retarded transient function (RTF) approach serves as a complementary method to ordinary differential equations (ODEs) for modelling dynamics typically observed in cellular signalling processes. We introduce an R package that implements the RTF approach, originally implemented within the MATLAB-based Data2Dynamics modelling framework. This package facilitates the modelling of time and dose dependencies, and it includes the possibility of model reduction to minimize overfitting. It can be applied to experimental data or trajectories of ODE models to characterize their dynamics. Additionally, it can generate a low-dimensional representation based on the fitted RTF parameters of a set of time-resolved data, aiding in the identification of key targets of experimental perturbations.

AVAILABILITY AND IMPLEMENTATION

The R package RTF is available at https://github.com/kreutz-lab/RTF.

Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways

The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in single-cell proteomic technologies have provided unprecedented opportunities to investigate the heterogeneity and noise within complex, multi-signaling networks across diverse cells and cell types. Mathematical modeling has become a powerful interdisciplinary tool that bridges mathematics and experimental biology, providing valuable insights into these intricate cellular processes. In addition, statistical methods have been developed to infer pathway topologies and estimate unknown parameters within dynamic models. This review presents a comprehensive analysis of how mathematical modeling of the MAPK pathway deepens our understanding of its regulatory mechanisms, enhances the prediction of system behavior, and informs experimental research, with a particular focus on recent advances in modeling and inference using single-cell proteomic data.

phuEGO: A Network-Based Method to Reconstruct Active Signaling Pathways From Phosphoproteomics Datasets

Signaling networks are critical for virtually all cell functions. Our current knowledge of cell signaling has been summarized in signaling pathway databases, which, while useful, are highly biased toward well-studied processes, and do not capture context specific network wiring or pathway cross-talk. Mass spectrometry-based phosphoproteomics data can provide a more unbiased view of active cell signaling processes in a given context, however, it suffers from low signal-to-noise ratio and poor reproducibility across experiments. While progress in methods to extract active signaling signatures from such data has been made, there are still limitations with respect to balancing bias and interpretability. Here we present phuEGO, which combines up-to-three-layer network propagation with ego network decomposition to provide small networks comprising active functional signaling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets. We applied phuEGO to five phosphoproteomics data sets from cell lines collected upon infection with SARS CoV2. PhuEGO was better able to identify common active functions across datasets and to point to a subnetwork enriched for known COVID-19 targets. Overall, phuEGO provides a flexible tool to the community for the improved functional interpretation of global phosphoproteomics datasets.

Liebig's law of the minimum in the TGF-β/SMAD pathway

Cells use signaling pathways to sense and respond to their environments. The transforming growth factor-β (TGF-β) pathway produces context-specific responses. Here, we combined modeling and experimental analysis to study the dependence of the output of the TGF-β pathway on the abundance of signaling molecules in the pathway. We showed that the TGF-β pathway processes the variation of TGF-β receptor abundance using Liebig's law of the minimum, meaning that the output-modifying factor is the signaling protein that is most limited, to determine signaling responses across cell types and in single cells. We found that the abundance of either the type I (TGFBR1) or type II (TGFBR2) TGF-β receptor determined the responses of cancer cell lines, such that the receptor with relatively low abundance dictates the response. Furthermore, nuclear SMAD2 signaling correlated with the abundance of TGF-β receptor in single cells depending on the relative expression levels of TGFBR1 and TGFBR2. A similar control principle could govern the heterogeneity of signaling responses in other signaling pathways.

A guide to ERK dynamics, part 1: mechanisms and models

Extracellular signal-regulated kinase (ERK) has long been studied as a key driver of both essential cellular processes and disease. A persistent question has been how this single pathway is able to direct multiple cell behaviors, including growth, proliferation, and death. Modern biosensor studies have revealed that the temporal pattern of ERK activity is highly variable and heterogeneous, and critically, that these dynamic differences modulate cell fate. This two-part review discusses the current understanding of dynamic activity in the ERK pathway, how it regulates cellular decisions, and how these cell fates lead to tissue regulation and pathology. In part 1, we cover the optogenetic and live-cell imaging technologies that first revealed the dynamic nature of ERK, as well as current challenges in biosensor data analysis. We also discuss advances in mathematical models for the mechanisms of ERK dynamics, including receptor-level regulation, negative feedback, cooperativity, and paracrine signaling. While hurdles still remain, it is clear that higher temporal and spatial resolution provide mechanistic insights into pathway circuitry. Exciting new algorithms and advanced computational tools enable quantitative measurements of single-cell ERK activation, which in turn inform better models of pathway behavior. However, the fact that current models still cannot fully recapitulate the diversity of ERK responses calls for a deeper understanding of network structure and signal transduction in general.

Impact of HIF1-α/TGF-β/Smad-2/Bax/Bcl2 pathways on cobalt chloride-induced cardiac and hepatorenal dysfunction

Background

Cobalt chloride (CoCl2) is a ferromagnetic ubiquitous trace element extensively dispersed in the environment. Nevertheless, it may merit human hazard.

Aim

Excess cobalt can harm vital organs this paves the way to elucidate the toxic impact of CoCl2 on the liver, kidney and heart.

Method

CoCl2 was injected in a dose of (60 mg/kg, S.C.) proceeded via Carnosine (200 mg/kg) and/or Arginine (200 mg/kg) treatment 1 month, 24 and 1 h, prior to CoCl2-intoxication.

Results

CoCl2 significantly alleviated hemoglobin concentration and BCl2; meanwhile, protein expression of transforming growth factor (TGF-β), hypoxia-inducible factor (HIF-1α), Mothers against decapentaplegic (Smad-2), AKT protein expression and Bax/Bcl2 ratio was noticeably elevated.

Conclusion

The combination of the aforementioned antioxidants exerted a synergistic anti-apoptotic impact in all target tissues.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

Dynamic modelling predicts lactate and IL-1β as interventional targets in metabolic-inflammation-clock regulatory loop in glioma

In an attempt to understand the role of dysregulated circadian rhythm in glioma, our recent findings highlighted the existence of a feed-forward loop between tumour metabolite lactate, pro-inflammatory cytokine IL-1β and circadian CLOCK. To further elucidate the implication of this complex interplay, we developed a mathematical model that quantitatively describes this lactate dehydrogenase A (LDHA)-IL-1β-CLOCK/BMAL1 circuit and predicts potential therapeutic targets. The model was calibrated on quantitative western blotting data in two glioma cell lines in response to either lactate inhibition or IL-1β stimulation. The calibrated model described the experimental data well and most of the parameters were identifiable, thus the model was predictive. Sensitivity analysis identified IL-1β and LDHA as potential intervention points. Mathematical models described here can be useful to understand the complex interrelationship between metabolism, inflammation and circadian rhythm, and in designing effective therapeutic strategies. Our findings underscore the importance of including the circadian clock when developing pharmacological approaches that target aberrant tumour metabolism and inflammation. Insight box  The complex interplay of metabolism-inflammation-circadian rhythm in tumours is not well understood. Our recent findings provided evidence of a feed-forward loop between tumour metabolite lactate, pro-inflammatory cytokine IL-1β and circadian CLOCK/BMAL1 in glioma. To elucidate the implication of this complex interplay, we developed a mathematical model that quantitatively describes this LDHA-IL-1β-CLOCK/BMAL1 circuit and integrates experimental data to predict potential therapeutic targets. The study employed a multi-start optimization strategy and profile likelihood estimations for parameter estimation and assessing identifiability. The simulations are in reasonable agreement with the experimental data. Sensitivity analysis found LDHA and IL-1β as potential therapeutic points. Mathematical models described here can provide insights to understand the complex interrelationship between metabolism, inflammation and circadian rhythm, and in identifying effective therapeutic targets.

An optimized reporter of the transcription factor hypoxia-inducible factor 1α reveals complex HIF-1α activation dynamics in single cells

Immune cells adopt a variety of metabolic states to support their many biological functions, which include fighting pathogens, removing tissue debris, and tissue remodeling. One of the key mediators of these metabolic changes is the transcription factor hypoxia-inducible factor 1α (HIF-1α). Single-cell dynamics have been shown to be an important determinant of cell behavior; however, despite the importance of HIF-1α, little is known about its single-cell dynamics or their effect on metabolism. To address this knowledge gap, here we optimized a HIF-1α fluorescent reporter and applied it to study single-cell dynamics. First, we showed that single cells are likely able to differentiate multiple levels of prolyl hydroxylase inhibition, a marker of metabolic change, via HIF-1α activity. We then applied a physiological stimulus known to trigger metabolic change, interferon-γ, and observed heterogeneous, oscillatory HIF-1α responses in single cells. Finally, we input these dynamics into a mathematical model of HIF-1α-regulated metabolism and discovered a profound difference between cells exhibiting high versus low HIF-1α activation. Specifically, we found cells with high HIF-1α activation are able to meaningfully reduce flux through the tricarboxylic acid cycle and show a notable increase in the NAD+/NADH ratio compared with cells displaying low HIF-1α activation. Altogether, this work demonstrates an optimized reporter for studying HIF-1α in single cells and reveals previously unknown principles of HIF-1α activation.

State- and stimulus-specific dynamics of SMAD signaling determine fate decisions in individual cells

SMAD-mediated signaling regulates apoptosis, cell cycle arrest, and epithelial-to-mesenchymal transition to safeguard tissue homeostasis. However, it remains elusive how the relatively simple pathway can determine such a broad range of cell fate decisions and how it differentiates between varying ligands. Here, we systematically investigate how SMAD-mediated responses are modulated by various ligands of the transforming growth factor β (TGFβ) family and compare these ligand responses in quiescent and proliferating MCF10A cells. We find that the nature of the phenotypic response is mainly determined by the proliferation status, with migration and cell cycle arrest being dominant in proliferating cells for all tested TGFβ family ligands, whereas cell death is the major outcome in quiescent cells. In both quiescent and proliferating cells, the identity of the ligand modulates the strength of the phenotypic response proportional to the dynamics of induced SMAD nuclear-to-cytoplasmic translocation and, as a consequence, the corresponding gene expression changes. Interestingly, the proliferation state of a cell has little impact on the set of genes induced by SMAD signaling; instead, it modulates the relative cellular sensitivity to TGFβ superfamily members. Taken together, diversity of SMAD-mediated responses is mediated by differing cellular states, which determine ligand sensitivity and phenotypic effects, while the pathway itself merely serves as a quantitative relay from the cell membrane to the nucleus.

Epigenetic memory acquired during long-term EMT induction governs the recovery to the epithelial state

Epithelial-mesenchymal transition (EMT) and its reverse mesenchymal-epithelial transition (MET) are critical during embryonic development, wound healing and cancer metastasis. While phenotypic changes during short-term EMT induction are reversible, long-term EMT induction has been often associated with irreversibility. Here, we show that phenotypic changes seen in MCF10A cells upon long-term EMT induction by TGFβ need not be irreversible, but have relatively longer time scales of reversibility than those seen in short-term induction. Next, using a phenomenological mathematical model to account for the chromatin-mediated epigenetic silencing of the miR-200 family by ZEB family, we highlight how the epigenetic memory gained during long-term EMT induction can slow the recovery to the epithelial state post-TGFβ withdrawal. Our results suggest that epigenetic modifiers can govern the extent and time scale of EMT reversibility and advise caution against labelling phenotypic changes seen in long-term EMT induction as 'irreversible'.

Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway

Nongenetic heterogeneity is key to cellular decisions, as even genetically identical cells respond in very different ways to the same external stimulus, e.g., during cell differentiation or therapeutic treatment of disease. Strong heterogeneity is typically already observed at the level of signaling pathways that are the first sensors of external inputs and transmit information to the nucleus where decisions are made. Since heterogeneity arises from random fluctuations of cellular components, mathematical models are required to fully describe the phenomenon and to understand the dynamics of heterogeneous cell populations. Here, we review the experimental and theoretical literature on cellular signaling heterogeneity, with special focus on the TGFβ/SMAD signaling pathway.

Resolving Crosstalk Between Signaling Pathways Using Mathematical Modeling and Time-Resolved Single Cell Data

Crosstalk between signaling pathways can modulate the cellular response to stimuli and is therefore an important part of signal transduction. For a comprehensive understanding of cellular responses, identifying points of interaction between the underlying molecular networks is essential. Here, we present an approach that allows the systematic prediction of such interactions by perturbing one pathway and quantifying the concomitant alterations in the response of a second pathway. As the observed alterations contain information about the crosstalk, we use an ordinary differential equation-based model to extract this information by linking altered dynamics to individual processes. Consequently, we can predict the interaction points between two pathways. As an example, we employed our approach to investigate the crosstalk between the NF-κB and p53 signaling pathway. We monitored the response of p53 to genotoxic stress using time-resolved single cell data and perturbed NF-κB signaling by inhibiting the kinase IKK2. Employing a subpopulation-based modeling approach enabled us to identify multiple interaction points that are simultaneously affected by perturbation of NF-κB signaling. Hence, our approach can be used to analyze crosstalk between two signaling pathways in a systematic manner.

Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signaling

Cells sense their surrounding by employing intracellular signaling pathways that transmit hormonal signals from the cell membrane to the nucleus. TGF-β/SMAD signaling encodes various cell fates, controls tissue homeostasis and is deregulated in diseases such as cancer. The pathway shows strong heterogeneity at the single-cell level, but quantitative insights into mechanisms underlying fluctuations at various time scales are still missing, partly due to inefficiency in the calibration of stochastic models that mechanistically describe signaling processes. In this work we analyze single-cell TGF-β/SMAD signaling and show that it exhibits temporal stochastic bursts which are dose-dependent and whose number and magnitude correlate with cell migration. We propose a stochastic modeling approach to mechanistically describe these pathway fluctuations with high computational efficiency. Employing high-order numerical integration and fitting to burst statistics we enable efficient quantitative parameter estimation and discriminate models that assume noise in different reactions at the receptor level. This modeling approach suggests that stochasticity in the internalization of TGF-β receptors into endosomes plays a key role in the observed temporal bursting. Further, the model predicts the single-cell dynamics of TGF-β/SMAD signaling in untested conditions, e.g., successfully reflects memory effects of signaling noise and cellular sensitivity towards repeated stimulation. Taken together, our computational framework based on burst analysis, noise modeling and path computation scheme is a suitable tool for the data-based modeling of complex signaling pathways, capable of identifying the source of temporal noise.

Dynamic Visualization of TGF-β/SMAD3 Transcriptional Responses in Single Living Cells

Simple Summary

How a single cytokine can induce a variety of cellular responses in the same cell or in different cells is a longstanding question. Transforming growth factor β (TGF-β) is a prototypical multifunctional cytokine of which biological responses are highly dependent on in a cellular context. TGF-β signals via intracellular SMAD transcription factors, and the duration and intensity of SMAD activation are key determinants for the responses that are elicited by TGF-β. To visualize the TGF-β signaling kinetics, we developed a dynamic TGF-β/SMAD3 transcriptional reporter using a quickly folded and highly unstable green florescent protein. We demonstrate the specificity and sensitivity of this reporter and its wide application to monitor dynamic TGF-β-induced responses in cells cultured on plastic dishes, and in living animals. This tool allows for the analysis of TGF-β signaling at a single living cell level, and allows for the discovery of dynamic TGF-β SMAD- induced transcriptional responses in multi-step biological processes.

Abstract

Transforming growth factor-β (TGF-β) signaling is tightly controlled in duration and intensity during embryonic development and in the adult to maintain tissue homeostasis. To visualize the TGF-β/SMAD3 signaling kinetics, we developed a dynamic TGF-β/SMAD3 transcriptional fluorescent reporter using multimerized SMAD3/4 binding elements driving the expression of a quickly folded and highly unstable GFP protein. We demonstrate the specificity and sensitivity of this reporter and its wide application to monitor dynamic TGF-β/SMAD3 transcriptional responses in both 2D and 3D systems in vitro, as well as in vivo, using live-cell and intravital imaging. Using this reporter in B16F10 cells, we observed single cell heterogeneity in response to TGF-β challenge, which can be categorized into early, late, and non-responders. Because of its broad application potential, this reporter allows for new discoveries into how TGF-β/SMAD3-dependent transcriptional dynamics are affected during multistep and reversible biological processes.

Safe and Effective Cynomolgus Monkey GLP-Tox Study with Repetitive Intrathecal Application of a TGFBR2 Targeting LNA-Gapmer Antisense Oligonucleotide as Treatment Candidate for Neurodegenerative Disorders

The capability of the adult central nervous system to self-repair/regenerate was demonstrated repeatedly throughout the last decades but remains in debate. Reduced neurogenic niche activity paralleled by a profound neuronal loss represents fundamental hallmarks in the disease course of neurodegenerative disorders. We and others have demonstrated the endogenous TGFβ system to represent a potential pathogenic participant in disease progression, of amyotrophic lateral sclerosis (ALS) in particular, by generating and promoting a disequilibrium of neurodegenerative and neuroregenerative processes. The novel human/primate specific LNA Gapmer Antisense Oligonucleotide "NVP-13", targeting TGFBR2, effectively reduced its expression and lowered TGFβ signal transduction in vitro and in vivo, paralleled by boosting neurogenic niche activity in human neuronal progenitor cells and nonhuman primate central nervous system. Here, we investigated NVP-13 in vivo pharmacology, safety, and tolerability following repeated intrathecal injections in nonhuman primate cynomolgus monkeys for 13 weeks in a GLP-toxicology study approach. NVP-13 was administered intrathecally with 1, 2, or 4 mg NVP-13/animal within 3 months on days 1, 15, 29, 43, 57, 71, and 85 in the initial 13 weeks. We were able to demonstrate an excellent local and systemic tolerability, and no adverse events in physiological, hematological, clinical chemistry, and microscopic findings in female and male Cynomolgus Monkeys. Under the conditions of this study, the no observed adverse effect level (NOAEL) is at least 4 mg/animal NVP-13.

Generating Somatic Knockout Cell Lines with CRISPR-Cas9 Technology to Investigate SMAD Signaling

Genome engineering provides a powerful tool to explore TGF-β/SMAD signaling by enabling the deletion and modification of critical components of the pathway. Over the past years, CRISPR-Cas9 technology has matured and can now be used to routinely generate knockout cell lines. Here, we describe a method to design and generate deletions of genes from the SMAD pathway in somatic human cell lines based on homologous recombination.

Direct acupuncture of nitric oxide by an electrochemical microsensor with high time-space resolution

Measurement of signal molecule is critically important for understanding living systems. Nitric oxide (NO) is a key redox signal molecule that shows diverse roles in virtually all life forms. However, probing into NO's activities is challenging as NO has restricted lifetime (<10 s) and limited diffusion distance (usually <200 μm). So, for the direct acupuncture of NO within the time-space resolution, an electrochemical microsensor has been designed and fabricated in this work. Fabrication of the microsensor is achieved by (1) selective assembly of an electrocatalytic transducer, (2) attaching the transducer on carbon fiber electrode, and (3) covered it with a screen layer to reduce signal interference. The fabricated microsensor exhibits high sensitivity (LOD, 13.5 pM), wide detection range (100 pM-5 μM), and good selectivity. Moreover, studies have revealed that the availability of the sensor for efficient detection of NO is due to the formation of a specific DNA/porphyrin hybrid structure that has synergetic effects on NO electrocatalysis. Therefore, NO release by cells and tissues can be directly and precisely traced, in which we have obtained the release pattern of NO by different cancer cell lines, and have known its dynamics in tumor microenvironment. The fabricated electrocatalytic microsensor may provide a unique and useful tool for the direct assay of NO with high time-space resolution, which promisingly gives a technical solution for the bioassay of NO in living systems.

Regulation of STAT3 signaling in IFNγ and IL10 pathways and in their cross-talk

The pro-inflammatory IFNγ-STAT1 pathway and anti-inflammatory IL10-STAT3 pathway elicit cellular responses primarily utilizing their canonical STATs. However IL10 mediated STAT1 and IFNγ mediated STAT3 activation is also observed, suggesting crosstalk of these functionally opposing signaling pathways can potentially reshape the canonical dynamics both STATs and alter the expression of their target genes. Herein, we measured the dynamics of STATs in response to different doses of IL10 or IFNγ and in their co-stimulation and employed quantitative modeling to understand the regulatory mechanisms controlling signal responses in individual and co-simulation scenarios. Our experiments show, STAT3 in particular, exhibits a bell-shaped dose-response while treated with IFNγ or IL10 and our model quantiatively captured the dose-dependent dynamics of both the STATs in both pathways. The model next predicted and subsequent experiments validated that STAT3 dynamics would robustly remain IL10 specific when subjected to a co-stimulation of both IFNγ and IL10. Genes common to both pathways also exhibited IL10 specific expression during the co-stimulation. The findings thus uncover anovel feature of the IL10-STAT3 signaling axis during pathway crosstalk. Finally, parameter sampling coupled to information theory based analysis showed that bell-shaped signal-response of STAT3 in both pathways is primarily dependent on receptor concentration whereas robustness of IL10-STAT3 signaling axis in co-stimulation results from the negative regulation of the IFNγ pathway.

Reconditioning the Neurogenic Niche of Adult Non-human Primates by Antisense Oligonucleotide-Mediated Attenuation of TGFβ Signaling

Adult neurogenesis is a target for brain rejuvenation as well as regeneration in aging and disease. Numerous approaches showed efficacy to elevate neurogenesis in rodents, yet translation into therapies has not been achieved. Here, we introduce a novel human TGFβ-RII (Transforming Growth Factor-Receptor Type II) specific LNA-antisense oligonucleotide ("locked nucleotide acid"-"NVP-13"), which reduces TGFβ-RII expression and downstream receptor signaling in human neuronal precursor cells (ReNcell CX® cells) in vitro. After we injected cynomolgus non-human primates repeatedly i.th. with NVP-13 in a preclinical regulatory 13-week GLP-toxicity program, we could specifically downregulate TGFβ-RII mRNA and protein in vivo. Subsequently, we observed a dose-dependent upregulation of the neurogenic niche activity within the hippocampus and subventricular zone: human neural progenitor cells showed significantly (up to threefold over control) enhanced differentiation and cell numbers. NVP-13 treatment modulated canonical and non-canonical TGFβ pathways, such as MAPK and PI3K, as well as key transcription factors and epigenetic factors involved in stem cell maintenance, such as MEF2A and pFoxO3. The latter are also dysregulated in clinical neurodegeneration, such as amyotrophic lateral sclerosis. Here, we provide for the first time in vitro and in vivo evidence for a novel translatable approach to treat neurodegenerative disorders by modulating neurogenesis.

A BMPR2/YY1 Signaling Axis Is Required for Human Cytomegalovirus Latency in Undifferentiated Myeloid Cells

Human cytomegalovirus (HCMV) presents a major health burden in the immunocompromised and in stem cell transplant medicine. A lack of understanding about the mechanisms of HCMV latency in undifferentiated CD34⁺ stem cells, and how latency is broken for the virus to enter the lytic phase of its infective cycle, has hampered the development of essential therapeutics. Using a human induced pluripotent stem cell (iPSC) model of HCMV latency and patient-derived myeloid cell progenitors, we demonstrate that bone morphogenetic protein receptor type 2 (BMPR2) is necessary for HCMV latency. In addition, we define a crucial role for the transcription factor Yin Yang 1 (YY1) in HCMV latency; high levels of YY1 are maintained in latently infected cells as a result of BMPR2 signaling through the SMAD4/SMAD6 axis. Activation of SMAD4/6, through BMPR2, inhibits TGFbeta receptor signaling, which leads to the degradation of YY1 via induction of a cellular microRNA (miRNA), hsa-miR-29a. Pharmacological targeting of BMPR2 in progenitor cells results in the degradation of YY1 and an inability to maintain latency and renders cells susceptible to T cell killing. These data argue that BMPR2 plays a role in HCMV latency and is a new potential therapeutic target for maintaining or disrupting HCMV latency in myeloid progenitors.

Disentangling Pro-mitotic Signaling during Cell Cycle Progression using Time-Resolved Single-Cell Imaging

Cells rely on input from extracellular growth factors to control their proliferation during development and adult homeostasis. Such mitogenic inputs are transmitted through multiple signaling pathways that synergize to precisely regulate cell cycle entry and progression. Although the architecture of these signaling networks has been characterized in molecular detail, their relative contribution, especially at later cell cycle stages, remains largely unexplored. By combining quantitative time-resolved measurements of fluorescent reporters in untransformed human cells with targeted pharmacological inhibitors and statistical analysis, we quantify epidermal growth factor (EGF)-induced signal processing in individual cells over time and dissect the dynamic contribution of downstream pathways. We define signaling features that encode information about extracellular ligand concentrations and critical time windows for inducing cell cycle transitions. We show that both extracellular signal-regulated kinase (ERK) and phosphatidylinositol 3-kinase (PI3K) activity are necessary for initial cell cycle entry, whereas only PI3K affects the duration of S phase at later stages of mitogenic signaling.

CODEX, a neural network approach to explore signaling dynamics landscapes

Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multi-dimensional trajectories. Typically, the extraction of relevant information from time series data relies on predefined, human-interpretable features. Without a priori knowledge of the system, the predefined features may fail to cover the entire spectrum of dynamics. Here we present CODEX, a data-driven approach based on convolutional neural networks (CNNs) that identifies patterns in time series. It does not require a priori information about the biological system and the insights into the data are built through explanations of the CNNs' predictions. CODEX provides several views of the data: visualization of all the single-cell trajectories in a low-dimensional space, identification of prototypic trajectories, and extraction of distinctive motifs. We demonstrate how CODEX can provide new insights into ERK and Akt signaling in response to various growth factors, and we recapitulate findings in p53 and TGFβ-SMAD2 signaling.

Transient phases of OXPHOS inhibitor resistance reveal underlying metabolic heterogeneity in single cells

Cell-to-cell heterogeneity in metabolism plays an unknown role in physiology and pharmacology. To functionally characterize cellular variability in metabolism, we treated cells with inhibitors of oxidative phosphorylation (OXPHOS) and monitored their responses with live-cell reporters for ATP, ADP/ATP, or activity of the energy-sensing kinase AMPK. Across multiple OXPHOS inhibitors and cell types, we identified a subpopulation of cells resistant to activation of AMPK and reduction of ADP/ATP ratio. This resistant state persists transiently for at least several hours and can be inherited during cell divisions. OXPHOS inhibition suppresses the mTORC1 and ERK growth signaling pathways in sensitive cells, but not in resistant cells. Resistance is linked to a multi-factorial combination of increased glucose uptake, reduced protein biosynthesis, and G0/G1 cell-cycle status. Our results reveal dynamic fluctuations in cellular energetic balance and provide a basis for measuring and predicting the distribution of cellular responses to OXPHOS inhibition.

Development of a microfluidic approach for the real-time analysis of extrinsic TGF-β signalling

Autocrine and paracrine signalling are traditionally difficult to study due to the sub-micromolar concentrations involved. This has proven to be especially limiting in the study of embryonic stem cells that rely on such signalling for viability, self-renewal, and proliferation. Microfluidics allows to achieve local concentrations of ligands representative of the in vivo stem cell niche, gaining more precise control over the cell microenvironment, as well as to manipulate ligands availability with high temporal resolution and minimal amount of reagents. Here we developed a microfluidics-based system for monitoring the dynamics of TGF-β pathway activity by means of a SMAD2/3-dependent luciferase reporter. We first validated our system by showing dose-dependent transcriptional activation. We then tested the effects of pulsatile stimulation and delayed inhibition of TGF-β activity on signalling dynamics. Finally, we show that our microfluidic system, unlike conventional culture systems, can detect TGF-β ligands secreted in the conditioned medium from hESCs.

Modeling the Control of TGF-β/Smad Nuclear Accumulation by the Hippo Pathway Effectors, Taz/Yap

Integration of transforming growth factor β (TGF-β) signals with those of other pathways allows for precise temporal and spatial control of gene expression patterns that drive development and homeostasis. The Hippo pathway nuclear effectors, Taz/Yap, interact with the TGF-β transcriptional mediators, Smads, to control Smad activity. Key to TGF-β signaling is the nuclear localization of Smads. Thus, to investigate the role of Taz/Yap in Smad nuclear accumulation, we developed mathematical models of Hippo and TGF-β cross talk. The models were based on experimental measurements of TGF-β-induced changes in Taz/Yap and Smad subcellular localization obtained using high-throughput immunofluorescence (IF) imaging in the mouse mammary epithelial cell line, EpH4. Bayesian MCMC DREAM parameter estimation was used to quantify the uncertainty in estimates of the kinetic parameters. Variation of the model parameters and statistical analysis show that our modeling predicts that Taz/Yap can alter TGF-β receptor activity and directly or indirectly act as nuclear retention factors.

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Taz/Yap modulate TGF-β-induced nuclear accumulation of Smad2/3 and Smad4

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TGF-β does not affect Taz/Yap localization when Hippo activity is constant

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Taz/Yap loss may alter activity of both Receptor and Smad nuclear retention factors

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The mediator complex regulates Smad nuclear accumulation

A systematic approach to decipher crosstalk in the p53 signaling pathway using single cell dynamics

The transcription factors NF-κB and p53 are key regulators in the genotoxic stress response and are critical for tumor development. Although there is ample evidence for interactions between both networks, a comprehensive understanding of the crosstalk is lacking. Here, we developed a systematic approach to identify potential interactions between the pathways. We perturbed NF-κB signaling by inhibiting IKK2, a critical regulator of NF-κB activity, and monitored the altered response of p53 to genotoxic stress using single cell time lapse microscopy. Fitting subpopulation-specific computational p53 models to this time-resolved single cell data allowed to reproduce in a quantitative manner signaling dynamics and cellular heterogeneity for the unperturbed and perturbed conditions. The approach enabled us to untangle the integrated effects of IKK/ NF-κB perturbation on p53 dynamics and thereby derive potential interactions between both networks. Intriguingly, we find that a simultaneous perturbation of multiple processes is necessary to explain the observed changes in the p53 response. Specifically, we show interference with the activation and degradation of p53 as well as the degradation of Mdm2. Our results highlight the importance of the crosstalk and its potential implications in p53-dependent cellular functions.

Cells can respond to external and internal inputs by transducing information to the nucleus where transcription factors initiate corresponding cellular responses. Cellular signaling is mediated by several pathways; molecular networks that can interact with each other, which alters signal processing and modulates cellular responses. As deregulated signaling can lead to the development of tumors it is important to understand not only how signaling pathways function but also the contribution of their interaction on the signaling dynamics. Here, we analyzed the interplay of the IKK/ NF-κB and p53 pathway, which are both critical for the cellular response to DNA damage and have been implicated in tumor development. To systematically identify interaction points between both pathways, we perturbed IKK/ NF-κB signaling and tracked the changes in the response of p53 to DNA damage. Using computational methods, we show that several reactions in the p53 pathway are simultaneously affected by NF-κB signaling and that this combined action is necessary to explain altered behaviour of the p53 pathway. Hence, our results provide new insights into the interplay between the NF-κB and p53 pathway and help to gain a more comprehensive understanding of the crosstalk.

An integrative method to predict signalling perturbations for cellular transitions

Induction of specific cellular transitions is of clinical importance, as it allows to revert disease cellular phenotype, or induce cellular reprogramming and differentiation for regenerative medicine. Signalling is a convenient way to accomplish such transitions without transfer of genetic material. Here we present the first general computational method that systematically predicts signalling molecules, whose perturbations induce desired cellular transitions. This probabilistic method integrates gene regulatory networks (GRNs) with manually-curated signalling pathways obtained from MetaCore from Clarivate Analytics, to model how signalling cues are received and processed in the GRN. The method was applied to 219 cellular transition examples, including cell type transitions, and overall correctly predicted experimentally validated signalling molecules, consistently outperforming other well-established approaches, such as differential gene expression and pathway enrichment analyses. Further, we validated our method predictions in the case of rat cirrhotic liver, and identified the activation of angiopoietins receptor Tie2 as a potential target for reverting the disease phenotype. Experimental results indicated that this perturbation induced desired changes in the gene expression of key TFs involved in fibrosis and angiogenesis. Importantly, this method only requires gene expression data of the initial and desired cell states, and therefore is suited for the discovery of signalling interventions for disease treatments and cellular therapies.

p53 dynamics in single cells are temperature-sensitive

Cells need to preserve genome integrity despite varying cellular and physical states. p53, the guardian of the genome, plays a crucial role in the cellular response to DNA damage by triggering cell cycle arrest, apoptosis or senescence. Mutations in p53 or alterations in its regulatory network are major driving forces in tumorigenesis. As multiple studies indicate beneficial effects for hyperthermic treatments during radiation- or chemotherapy of human cancers, we aimed to understand how p53 dynamics after genotoxic stress are modulated by changes in temperature across a physiological relevant range. To this end, we employed a combination of time-resolved live-cell microscopy and computational analysis techniques to characterise the p53 response in thousands of individual cells. Our results demonstrate that p53 dynamics upon ionizing radiation are temperature dependent. In the range of 33 °C to 39 °C, pulsatile p53 dynamics are modulated in their frequency. Above 40 °C, which corresponds to mild hyperthermia in a clinical setting, we observed a reversible phase transition towards sustained hyperaccumulation of p53 disrupting its canonical response to DNA double strand breaks. Moreover, we provide evidence that mild hyperthermia alone is sufficient to induce a p53 response in the absence of genotoxic stress. These insights highlight how the p53-mediated DNA damage response is affected by alterations in the physical state of a cell and how this can be exploited by appropriate timing of combination therapies to increase the efficiency of cancer treatments.

Smad7 Binds Differently to Individual and Tandem WW3 and WW4 Domains of WWP2 Ubiquitin Ligase Isoforms

WWP2 is an E3 ubiquitin ligase that differentially regulates the contextual tumour suppressor/progressor TGFβ signalling pathway by alternate isoform expression. WWP2 isoforms select signal transducer Smad2/3 or inhibitor Smad7 substrates for degradation through different compositions of protein–protein interaction WW domains. The WW4 domain-containing WWP2-C induces Smad7 turnover in vivo and positively regulates the metastatic epithelial–mesenchymal transition programme. This activity and the overexpression of these isoforms in human cancers make them candidates for therapeutic intervention. Here, we use NMR spectroscopy to solve the solution structure of the WWP2 WW4 domain and observe the binding characteristics of Smad7 substrate peptide. We also reveal that WW4 has an enhanced affinity for a Smad7 peptide phosphorylated at serine 206 adjacent to the PPxY motif. Using the same approach, we show that the WW3 domain also binds Smad7 and has significantly enhanced Smad7 binding affinity when expressed in tandem with the WW4 domain. Furthermore, and relevant to these biophysical findings, we present evidence for a novel WWP2 isoform (WWP2C-ΔHECT) comprising WW3–WW4 tandem domains and a truncated HECT domain that can inhibit TGFβ signalling pathway activity, providing a further layer of complexity and feedback to the WWP2 regulatory apparatus. Collectively, our data reveal a structural platform for Smad substrate selection by WWP2 isoform WW domains that may be significant in the context of WWP2 isoform switching linked to tumorigenesis.

Communication codes in developmental signaling pathways

A handful of core intercellular signaling pathways play pivotal roles in a broad variety of developmental processes. It has remained puzzling how so few pathways can provide the precision and specificity of cell-cell communication required for multicellular development. Solving this requires us to quantitatively understand how developmentally relevant signaling information is actively sensed, transformed and spatially distributed by signaling pathways. Recently, single cell analysis and cell-based reconstitution, among other approaches, have begun to reveal the 'communication codes' through which information is represented in the identities, concentrations, combinations and dynamics of extracellular ligands. They have also revealed how signaling pathways decipher these features and control the spatial distribution of signaling in multicellular contexts. Here, we review recent work reporting the discovery and analysis of communication codes and discuss their implications for diverse developmental processes.

Large-scale datasets uncovering cell signalling networks in cancer: context matters

Cell signaling pathways control the responses of cells to external perturbations. Depending on the cell's internal state, genetic background and environmental context, signaling pathways rewire to elicit the appropriate response. Such rewiring also can lead to cancer development and progression or cause resistance to therapies. While there exist static maps of annotated pathways, they do not capture these rewired networks. As large-scale datasets across multiple contexts and patients are becoming available the doors to infer and study context-specific signaling network have also opened. In this review, we will highlight the most recent approaches to study context-specific signaling networks using large-scale omics and genetic perturbation datasets, with a focus on studies of cancer and cancer-related pathways.

Molecular Engineering of the TGF-β Signaling Pathway

Transforming growth factor beta (TGF-β) is an important growth factor that plays essential roles in regulating tissue development and homeostasis. Dysfunction of TGF-β signaling is a hallmark of many human diseases. Therefore, targeting TGF-β signaling presents broad therapeutic potential. Since the discovery of the TGF-β ligand, a collection of engineered signaling proteins have been developed to probe and manipulate TGF-β signaling responses. In this review, we highlight recent progress in the engineering of TGF-β signaling for different applications and discuss how molecular engineering approaches can advance our understanding of this important pathway. In addition, we provide a future outlook on the opportunities and challenges in the engineering of the TGF-β signaling pathway from a quantitative perspective.

Techniques for Studying Decoding of Single Cell Dynamics

Cells must be able to interpret signals they encounter and reliably generate an appropriate response. It has long been known that the dynamics of transcription factor and kinase activation can play a crucial role in selecting an individual cell's response. The study of cellular dynamics has expanded dramatically in the last few years, with dynamics being discovered in novel pathways, new insights being revealed about the importance of dynamics, and technological improvements increasing the throughput and capabilities of single cell measurements. In this review, we highlight the important developments in this field, with a focus on the methods used to make new discoveries. We also include a discussion on improvements in methods for engineering and measuring single cell dynamics and responses. Finally, we will briefly highlight some of the many challenges and avenues of research that are still open.

Quantitative relationships between SMAD dynamics and target gene activation kinetics in single live cells

The transduction of extracellular signals through signaling pathways that culminate in a transcriptional response is central to many biological processes. However, quantitative relationships between activities of signaling pathway components and transcriptional output of target genes remain poorly explored. Here we developed a dual bioluminescence imaging strategy allowing simultaneous monitoring of nuclear translocation of the SMAD4 and SMAD2 transcriptional activators upon TGF-β stimulation, and the transcriptional response of the endogenous connective tissue growth factor (ctgf) gene. Using cell lines allowing to vary exogenous SMAD4/2 expression levels, we performed quantitative measurements of the temporal profiles of SMAD4/2 translocation and ctgf transcription kinetics in hundreds of individual cells at high temporal resolution. We found that while nuclear translocation efficiency had little impact on initial ctgf transcriptional activation, high total cellular SMAD4 but not SMAD2 levels increased the probability of cells to exhibit a sustained ctgf transcriptional response. The approach we present here allows time-resolved single cell quantification of transcription factor dynamics and transcriptional responses and thereby sheds light on the quantitative relationship between SMADs and target gene responses.

Spatial clustering and common regulatory elements correlate with coordinated gene expression

Many cellular responses to surrounding cues require temporally concerted transcriptional regulation of multiple genes. In prokaryotic cells, a single-input-module motif with one transcription factor regulating multiple target genes can generate coordinated gene expression. In eukaryotic cells, transcriptional activity of a gene is affected by not only transcription factors but also the epigenetic modifications and three-dimensional chromosome structure of the gene. To examine how local gene environment and transcription factor regulation are coupled, we performed a combined analysis of time-course RNA-seq data of TGF-β treated MCF10A cells and related epigenomic and Hi-C data. Using Dynamic Regulatory Events Miner (DREM), we clustered differentially expressed genes based on gene expression profiles and associated transcription factors. Genes in each class have similar temporal gene expression patterns and share common transcription factors. Next, we defined a set of linear and radial distribution functions, as used in statistical physics, to measure the distributions of genes within a class both spatially and linearly along the genomic sequence. Remarkably, genes within the same class despite sometimes being separated by tens of million bases (Mb) along genomic sequence show a significantly higher tendency to be spatially close despite sometimes being separated by tens of Mb along the genomic sequence than those belonging to different classes do. Analyses extended to the process of mouse nervous system development arrived at similar conclusions. Future studies will be able to test whether this spatial organization of chromosomes contributes to concerted gene expression.

Cellular responses to environmental stimulation are often accompanied by changes in gene expression patterns. Genes are linearly arranged along chromosomal DNA, which folds into a three-dimensional structure. The chromosome structure affects gene expression activities and is regulated by multiple events such as histone modifications and DNA binding of transcription factors. A basic question is how these mechanisms work together to regulate gene expression. In this study, we analyzed temporal gene expression patterns in the context of chromosome structure both in a human cell line under TGF-β treatment and during mouse nervous system development. In both cases, we observed that genes regulated by common transcription factors have an enhanced tendency to be spatially close. Our analysis suggests that spatial co-localization of genes may facilitate the concerted gene expression.

Mathematical model identifies effective P53 accumulation with target gene binding affinity in DNA damage response for cell fate decision

Functional p53 signaling is essential for appropriate responses to diverse stimuli. P53 dynamics employs the information from the stimulus leading to selective gene expression and cell fate decision. However, the decoding mechanism of p53 dynamics under DNA damage challenge remains poorly understood. Here we mathematically modeled the recently dual-phase p53 dynamics under doxorubicin treatment. We found that p53 could perform sequential pulses followed by a high-amplitude terminal pulse at relatively low doxorubicin treatment, whereas p53 became steadily accumulated when damage level was high. The effective p53 integral above a threshold but not the absolute accumulation of p53 precisely discriminated survival and death. Silencing negative regulators in p53 network might promote the occurrence of terminal pulse. Furthermore, lower binding affinity and degradation rate of p53 target genes could favorably discriminate high and low dose doxorubicin treatment. Grouping by temporal profiles suggested that the p53 dynamics rather than the doxorubicin doses could better discriminate cellular outcomes and confer less variation for effective p53 integral reemphasizing the importance of p53 level regulation. Our model has established a theoretical framework that p53 dynamics can work cooperatively with its binding affinity to target genes leading to cell fate choice, providing new clues of optimized clinical design by manipulating p53 dynamics.

Experimental and engineering approaches to intracellular communication

Communication between and within cells is essential for multicellular life. While intracellular signal transduction pathways are often specified in molecular terms, the information content they transmit remains poorly defined. Here, we review research efforts to merge biological experimentation with concepts of communication that emerge from the engineering disciplines of signal processing and control theory. We discuss the challenges of performing experiments that quantitate information transfer at the molecular level, and we highlight recent studies that have advanced toward a clearer definition of the information content carried by signaling molecules. Across these studies, we emphasize a theme of increasingly well-matched experimental and theoretical approaches to decode the data streams directing cellular behavior.

Signaling pathways as linear transmitters

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior.

Challenges of Decoding Transcription Factor Dynamics in Terms of Gene Regulation

Technological advances are continually improving our ability to obtain more accurate views about the inner workings of biological systems. One such rapidly evolving area is single cell biology, and in particular gene expression and its regulation by transcription factors in response to intrinsic and extrinsic factors. Regarding the study of transcription factors, we discuss some of the promises and pitfalls associated with investigating how individual cells regulate gene expression through modulation of transcription factor activities. Specifically, we discuss four leading experimental approaches, the data that can be obtained from each, and important considerations that investigators should be aware of when drawing conclusions from such data.

Cell-specific responses to the cytokine TGFβ are determined by variability in protein levels

The cytokine TGFβ provides important information during embryonic development, adult tissue homeostasis, and regeneration. Alterations in the cellular response to TGFβ are involved in severe human diseases. To understand how cells encode the extracellular input and transmit its information to elicit appropriate responses, we acquired quantitative time-resolved measurements of pathway activation at the single-cell level. We established dynamic time warping to quantitatively compare signaling dynamics of thousands of individual cells and described heterogeneous single-cell responses by mathematical modeling. Our combined experimental and theoretical study revealed that the response to a given dose of TGFβ is determined cell specifically by the levels of defined signaling proteins. This heterogeneity in signaling protein expression leads to decomposition of cells into classes with qualitatively distinct signaling dynamics and phenotypic outcome. Negative feedback regulators promote heterogeneous signaling, as a SMAD7 knock-out specifically affected the signal duration in a subpopulation of cells. Taken together, we propose a quantitative framework that allows predicting and testing sources of cellular signaling heterogeneity.