Although cytokine-dependent dynamics of nuclear factor κB (NF-κB) are known to encode information that regulates cell fate decisions, it is unclear whether single-cell responses are switch-like or encode more information about cytokine dose. Here, we measure the dynamic subcellular localization of NF-κB in response to a range of tumor necrosis factor (TNF) stimulation conditions to determine the prevailing mechanism of single-cell dose discrimination. Using an information theory formalism that accounts for signaling dynamics and non-responsive cell subpopulations, we find that the information transmission capacity of single cells exceeds that predicted from a switch-like response. Instead, we observe that NF-κB dynamics within single cells contain sufficient information to encode multiple, TNF-dependent cellular states, and have an activation threshold that varies across the population. By comparing single-cell responses to an internal, experimentally observed reference, we demonstrate that cells can grade responses to TNF across several orders of magnitude in concentration. This suggests that cells contain additional control points to fine-tune their cytokine responses beyond the decision to activate.

A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IκB kinase (IKK) complex is an integration hub for cytokines that govern nuclear factor κB (NF-κB) signaling. In response to inflammation, IKK is activated through recruitment to receptor-associated protein assemblies. How and what information IKK complexes transmit about the milieu are open questions. Here, we track dynamics of IKK complexes and nuclear NF-κB to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveal their size, number, and timing relays cytokine-specific control over shared signaling mechanisms with feedback regulation that is independent of transcription. Our results provide evidence for variable-gain stochastic pooling, a noise-reducing motif that enables cytokine-specific regulation and parsimonious information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling that have evolved for constructive information transmission in noisy molecular environments.

Motivation Many biological processes are regulated by single molecules and molecular assemblies within cells that are visible by microscopy as punctate features, often diffraction limited. Here we present detecting-NEMO (dNEMO), a computational tool optimized for accurate and rapid measurement of fluorescent puncta in fixed-cell and time-lapse images. Results The spot detection algorithm uses the à trous wavelet transform, a computationally inexpensive method that is robust to imaging noise. By combining automated with manual spot curation in the user interface, fluorescent puncta can be carefully selected and measured against their local background to extract high quality single-cell data. Integrated into the workflow are segmentation and spot-inspection tools that enable almost real-time interaction with images without time consuming pre-processing steps. Although the software is agnostic to the type of puncta imaged, we demonstrate dNEMO using smFISH to measure transcript numbers in single cells in addition to the transient formation of IKK/NEMO puncta from time-lapse images of cells exposed to inflammatory stimuli. We conclude that dNEMO is an ideal user interface for rapid and accurate measurement of fluorescent molecular assemblies in biological imaging data. Availability The software is freely available online at https://github.com/recleelab Supplementary information Supplementary data are available at Bioinformatics online.

Many biological processes are regulated by single molecules and molecular assemblies within cells that are visible by microscopy as punctate features, often diffraction limited.Here we present detecting-NEMO (dNEMO), a computational tool optimized for accurate and rapid measurement of fluorescent puncta in fixed-cell and time-lapse images. The spot detection algorithm uses the à trous wavelet transform, a computationally inexpensive method that is robust to imaging noise. By combining automated with manual spot curation in the user interface, fluorescent puncta can be carefully selected and measured against their local background to extract high quality single-cell data. Integrated into the workflow are segmentation and spot-inspection tools that enable almost real-time interaction with images without time consuming pre-processing steps. Although the software is agnostic to the type of puncta imaged, we demonstrate dNEMO using smFISH to measure transcript numbers in single cells in addition to the transient formation of IKK/NEMO puncta from time-lapse images of cells exposed to inflammatory stimuli. INTRODUCTION:Quantitative imaging of single cells enables measurement with subcellular resolution of dynamic biological processes that regulate critical cellular behaviors. Processes of the central dogma such as active transcription, single mRNA transcripts, sites of active protein translation, and other regulatory multi-protein assemblies can be observed by fluorescence microscopy as punctate structures within the cell (1-6). Spatiotemporal dynamics of signaling proteins, quantified in single cells by live-cell imaging, have revealed mechanistic insights into signal-response relationships in signal transduction networks in addition to sources of cell-to-cell variability (7-9). However, most live-cell imaging approaches use fluorescent biosensors and fusion proteins that report within large subcellular compartments, such as the cytoplasm or nucleus, and quantification of punctate structures is often limited to fixed-cell and low-throughput applications. Accurate detection and quantification of biological puncta is necessary to examine their roles in regulating cellular behaviors, and computational analysis is often the rate-limiting step of experimental pipelines.The nuclear factor (NF)-κB signal transduction pathway is a master regulator of inflammatory responses to injury and infection (10). Following activation of the pathway by inflammatory cytokines, such as interleukin-1 (IL-1) or tumor necrosis factor (TNF) among others, a series of intracellular signaling events transduce the NF-κB signal.Upstream kinase activation by the NF-κB essential modulator protein (NEMO, also known as IKKɣ) is a necessary step in regulation of the classical NF-κB signaling cascade (11).Following cytokine stimulation, NEMO is recruited to polyubiquitin scaffolds associated with cytokine-ligated receptor complexes where NEMO-interacting IκB kinases (IKKs) are

A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IKK complex is an integration hub for cytokines that govern NF-κB signaling. In response to inflammation, IKK is activated through recruitment to receptor-associated protein assemblies. How and what information IKK complexes transmit about the milieu are open questions. Here we track dynamics of IKK complexes and nuclear NF-κB to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveal their size, number, and timing relays cytokine-specific control over shared signaling mechanisms with feedback regulation that is independent of transcription. Our results provide evidence for variable gain stochastic pooling, a noise-reducing motif that enables cytokine-specific regulation and parsimonious information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling that have evolved for constructive information transmission in noisy molecular environments.

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