Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses.

Macrophages initiate inflammatory responses via the transcription factor NFκB. The temporal pattern of NFκB activity determines which genes are expressed and thus, the type of response that ensues. Here, we examined how information about the stimulus is encoded in the dynamics of NFκB activity. We generated an mVenus-RelA reporter mouse line to enable high-throughput live-cell analysis of primary macrophages responding to host- and pathogen-derived stimuli. An information-theoretic workflow identified six dynamical features-termed signaling codons-that convey stimulus information to the nucleus. In particular, oscillatory trajectories were a hallmark of responses to cytokine but not pathogen-derived stimuli. Single-cell imaging and RNA sequencing of macrophages from a mouse model of Sjögren's syndrome revealed inappropriate responses to stimuli, suggestive of confusion of two NFκB signaling codons. Thus, the dynamics of NFκB signaling classify immune threats through six signaling codons, and signal confusion based on defective codon deployment may underlie the etiology of some inflammatory diseases.

Tonic TNF conditioning of macrophages safeguards stimulus-specific inflammatory responses.

Tumor necrosis factor (TNF) is a key inflammatory cytokine that warns recipient cells of a nearby infection or tissue damage. Acute exposure to TNF activates characteristic oscillatory dynamics of the transcription factor NFκB and induces a characteristic gene expression program; these are distinct from the responses of cells directly exposed to pathogen-associated molecular patterns (PAMPs). Here, we report that tonic TNF exposure is critical for safeguarding TNF's specific functions. In the absence of tonic TNF conditioning, acute exposure to TNF causes (i) NFκB signaling dynamics that are less oscillatory and more like PAMP-responsive NFκB dynamics, (ii) immune gene expression that is more similar to the Pam3CSK4 response program, and (iii) broader epigenomic reprogramming that is characteristic of PAMP-responsive changes. We show that the absence of tonic TNF signaling effects subtle changes to TNF receptor availability and dynamics such that enhanced pathway activity results in non-oscillatory NFκB. Our results reveal tonic TNF as a key tissue determinant of the specific cellular responses to acute paracrine TNF exposure, and their distinction from responses to direct exposure to PAMPs.

An incoherent feedforward loop interprets NFκB/RelA dynamics to determine TNF-induced necroptosis decisions.

Balancing cell death is essential to maintain healthy tissue homeostasis and prevent disease. Tumor necrosis factor (TNF) not only activates nuclear factor κB (NFκB), which coordinates the cellular response to inflammation, but may also trigger necroptosis, a pro-inflammatory form of cell death. Whether TNF-induced NFκB affects the fate decision to undergo TNF-induced necroptosis is unclear. Live-cell microscopy and model-aided analysis of death kinetics identified a molecular circuit that interprets TNF-induced NFκB/RelA dynamics to control necroptosis decisions. Inducible expression of TNFAIP3/A20 forms an incoherent feedforward loop to interfere with the RIPK3-containing necrosome complex and protect a fraction of cells from transient, but not long-term TNF exposure. Furthermore, dysregulated NFκB dynamics often associated with disease diminish TNF-induced necroptosis. Our results suggest that TNF's dual roles in either coordinating cellular responses to inflammation, or further amplifying inflammation are determined by a dynamic NFκB-A20-RIPK3 circuit, that could be targeted to treat inflammation and cancer.

Expression variation and covariation impair analog and enable binary signaling control.

Due to noise in the synthesis and degradation of proteins, the concentrations of individual vertebrate signaling proteins were estimated to vary with a coefficient of variation (CV) of approximately 25% between cells. Such high variation is beneficial for population-level regulation of cell functions but abolishes accurate single-cell signal transmission. Here, we measure cell-to-cell variability of relative protein abundance using quantitative proteomics of individual Xenopus laevis eggs and cultured human cells and show that variation is typically much lower, in the range of 5-15%, compatible with accurate single-cell transmission. Focusing on bimodal ERK signaling, we show that variation and covariation in MEK and ERK expression improves controllability of the percentage of activated cells, demonstrating how variation and covariation in expression enables population-level control of binary cell-fate decisions. Together, our study argues for a control principle whereby low expression variation enables accurate control of analog single-cell signaling, while increased variation, covariation, and numbers of pathway components are required to widen the stimulus range over which external inputs regulate binary cell activation to enable precise control of the fraction of activated cells in a population.

Automated image analysis identifies signaling pathways regulating distinct signatures of cardiac myocyte hypertrophy.

Cardiac hypertrophy is controlled by a complex signal transduction and gene regulatory network, containing multiple layers of crosstalk and feedback. While numerous individual components of this network have been identified, understanding how these elements are coordinated to regulate heart growth remains a challenge. Past approaches to measure cardiac myocyte hypertrophy have been manual and often qualitative, hindering the ability to systematically characterize the network's higher-order control structure and identify therapeutic targets. Here, we develop and validate an automated image analysis approach for objectively quantifying multiple hypertrophic phenotypes from immunofluorescence images. This approach incorporates cardiac myocyte-specific optimizations and provides quantitative measures of myocyte size, elongation, circularity, sarcomeric organization, and cell-cell contact. As a proof-of-concept, we examined the hypertrophic response to α-adrenergic, ß-adrenergic, tumor necrosis factor (TNFα), insulin-like growth factor-1 (IGF-1), and fetal bovine serum pathways. While all five hypertrophic pathways increased myocyte size, other hypertrophic metrics were differentially regulated, forming a distinct phenotype signature for each pathway. Sarcomeric organization was uniquely enhanced by α-adrenergic signaling. TNFα and α-adrenergic pathways markedly decreased cell circularity due to increased myocyte protrusion. Surprisingly, adrenergic and IGF-1 pathways differentially regulated myocyte-myocyte contact, potentially forming a feed-forward loop that regulates hypertrophy. Automated image analysis unlocks a range of new quantitative phenotypic data, aiding dissection of the complex hypertrophic signaling network and enabling myocyte-based high-content drug screening.

NF-κB dynamics determine the stimulus specificity of epigenomic reprogramming in macrophages.

The epigenome of macrophages can be reprogrammed by extracellular cues, but the extent to which different stimuli achieve this is unclear. Nuclear factor κB (NF-κB) is a transcription factor that is activated by all pathogen-associated stimuli and can reprogram the epigenome by activating latent enhancers. However, we show that NF-κB does so only in response to a subset of stimuli. This stimulus specificity depends on the temporal dynamics of NF-κB activity, in particular whether it is oscillatory or non-oscillatory. Non-oscillatory NF-κB opens chromatin by sustained disruption of nucleosomal histone-DNA interactions, enabling activation of latent enhancers that modulate expression of immune response genes. Thus, temporal dynamics can determine a transcription factor's capacity to reprogram the epigenome in a stimulus-specific manner.

TGF-ß is insufficient to induce adipocyte state loss without concurrent PPARγ downregulation.

Cell plasticity, the ability of differentiated cells to convert into other cell types, underlies the pathogenesis of many diseases including the transdifferentiation of adipocytes (fat cells) into myofibroblasts in the pathogenesis of dermal fibrosis. Loss of adipocyte identity is an early step in different types of adipocyte plasticity. In this study, we determine the dynamics of adipocyte state loss in response to the profibrotic cytokine TGF-ß. We use two complementary approaches, lineage tracing and live fluorescent microscopy, which both allow for robust quantitative tracking of adipocyte identity loss at the single-cell level. We find that the intracellular TGF-ß signaling in adipocytes is inhibited by the transcriptional factor PPARγ, specifically by its ubiquitously expressed isoform PPARγ1. However, TGF-ß can lead to adipocyte state loss when it is present simultaneously with another stimulus. Our findings establish that an integration of stimuli occurring in a specific order is pivotal for adipocyte state loss which underlies adipocyte plasticity. Our results also suggest the possibility of a more general switch-like mechanism between adipogenic and profibrotic molecular states.

Molecular Competition in G1 Controls When Cells Simultaneously Commit to Terminally Differentiate and Exit the Cell Cycle.

Terminal differentiation is essential for the development and maintenance of tissues in all multi-cellular organisms and is associated with permanent exit from the cell cycle. Failure to permanently exit the cell cycle can result in cancer and disease. However, the molecular mechanisms and timing that coordinate differentiation commitment and cell cycle exit are not yet understood. Using live, single-cell imaging of cell cycle progression and differentiation commitment during adipogenesis, we show that a rapid switch mechanism engages exclusively in G1 to trigger differentiation commitment simultaneously with permanent exit from the cell cycle. We identify a molecular competition in G1 between when the differentiation switch is triggered and when the proliferative window closes that allows mitogen and differentiation stimuli to control the balance between terminally differentiating cells produced and progenitor cells kept in reserve, a parameter of critical importance for enabling proper development of tissue domains and organs.

Distinct single-cell signaling characteristics are conferred by the MyD88 and TRIF pathways during TLR4 activation.

Toll-like receptors (TLRs) recognize specific pathogen-associated molecular patterns and initiate innate immune responses through signaling pathways that depend on the adaptor proteins MyD88 (myeloid differentiation marker 88) or TRIF (TIR domain-containing adaptor protein-inducing interferon-ß). TLR4, in particular, uses both adaptor proteins to activate the transcription factor nuclear factor κB (NF-κB); however, the specificity and redundancy of these two pathways remain to be elucidated. We developed a mathematical model to show how each pathway encodes distinct dynamical features of NF-κB activity and makes distinct contributions to the high variability observed in single-cell measurements. The assembly of a macromolecular signaling platform around MyD88 associated with receptors at the cell surface determined the timing of initial responses to generate a reliable, digital NF-κB signal. In contrast, ligand-induced receptor internalization into endosomes produced noisy, delayed, yet sustained NF-κB signals through TRIF. With iterative mathematical model development, we predicted the molecular mechanisms by which the MyD88- and TRIF-mediated pathways provide ligand concentration-dependent signaling dynamics that transmit information about the pathogen threat.

Improving data quality in community-based seafood consumption studies by use of two measurement tools.

A seafood consumption study w as conducted in Glynn County, Georgia, to address concern about bioaccumulation of mercury from a nearby hazardous waste site in people who ate potentially contaminated seafood from this area. Seafood consumption levels were ascertained with two data collection tools: a questionnaire and a dietary diary. The use of two instruments allowed for more detailed analysis to reveal discrepancies in responses between the two instruments, to improve reliability of study results, and to reduce recall bias. Implementation of the questionnaire was relatively easy and provided a broad characterization of consumption patterns in the area. The dietary diary was more time-consuming, resulting in a reduction in participation rates. It provided, however, more detailed information with which to address community concerns about adverse health effects from mercury exposure. Overall, individuals who participated in this study were able to make broad generalizations about the amount of seafood in their diet but were less accurate in estimating specific seafood consumption levels. In addition, the level of concordance between the questionnaire and the dietary diary was low with respect to seafood consumption levels. For investigators examining consumption patterns in a community, the decision to use a questionnaire, a dietary diary, or both will be influenced by the objectives of the study, the level of community concern, the number of study staff, and available resources.

Systems biology. Accurate information transmission through dynamic biochemical signaling networks.

Stochasticity inherent to biochemical reactions (intrinsic noise) and variability in cellular states (extrinsic noise) degrade information transmitted through signaling networks. We analyzed the ability of temporal signal modulation--that is, dynamics--to reduce noise-induced information loss. In the extracellular signal-regulated kinase (ERK), calcium (Ca(2+)), and nuclear factor kappa-B (NF-κB) pathways, response dynamics resulted in significantly greater information transmission capacities compared to nondynamic responses. Theoretical analysis demonstrated that signaling dynamics has a key role in overcoming extrinsic noise. Experimental measurements of information transmission in the ERK network under varying signal-to-noise levels confirmed our predictions and showed that signaling dynamics mitigate, and can potentially eliminate, extrinsic noise-induced information loss. By curbing the information-degrading effects of cell-to-cell variability, dynamic responses substantially increase the accuracy of biochemical signaling networks.