Biology subjects

Lee, R. E. C.

Publications and source records attributed to Lee, R. E. C..

7 recordsLinked to original sources

bioRxiv2026

Cell Cycle Regulation of Merkel Cell Polyomavirus Replication and Genome Inheritance in Single Cells

Merkel cell polyomavirus (MCV) establishes a near-ubiquitous, asymptomatic infection in humans but on rare occasions drives Merkel cell carcinoma, an aggressive skin cancer. How MCV replication is coordinated with host cell-cycle progression, and how this coordination shapes infected-cell fate, has remained unresolved. Here we combine reporter virus live-cell imaging, pharmacologic cell-cycle perturbation, flow cytometry, and single-cell transcriptomics to examine MCV replication dynamics. VP1 late gene expression occurs almost exclusively during late S or G2, is associated with prolonged G2 arrest, and frequently culminates in cell death. Strikingly, cells that divide before virus replication give rise to daughter cells that synchronously initiate viral replication and VP1 expression, revealing mitotic inheritance of silent viral genomes, a pattern seen for viruses with a known latency lifecycle. Single-cell RNA sequencing further identifies a transient antiviral and inflammatory response that is subsequently suppressed in surviving, cell cycle arrested cells. These findings define the cell-cycle logic, inheritance, and host consequences of MCV replication at single-cell resolution.

cell biology↗

bioRxiv2025

NEMO recruitment at single cytokine-receptor complexes shows quantized dynamics independent of ligand affinity

Cells use a limited number of receptors to sense and process molecular information from their environment. In the classical view of signaling, receptor-ligand affinities determine binding kinetics, in timescales of diffusion, where their time-averaged contact duration regulates rapid cytoplasmic signaling events to coordinate cellular responses. For some cytokines, single receptor-ligand binding events can initiate large multiprotein complexes in the cytoplasm that assemble over tens of minutes, bringing to question how cytokine affinity influences the sensitivity and strength of signaling. Here, we leverage naturally occurring variation of IL-1{beta} from multiple species to determine the impact of affinity on human IL-1 receptor signaling. Using experiments and models we investigate single receptor complexes activated by ligands that vary across multiple orders of magnitude in affinity. Our results show that while the receptor-ligand affinity establishes cytokine response sensitivity, activated IL-1 receptor complexes signal as discrete, quantized packets of signaling flux independent of affinity.

systems biology↗

bioRxiv2024

Time-varying stimuli that prolong IKK activation promote nuclear remodeling and mechanistic switching of NF-κB dynamics

Temporal properties of molecules within signaling networks, such as sub-cellular changes in protein abundance, encode information that mediate cellular responses to stimuli. How dynamic signals relay and process information is a critical gap in understanding cellular behaviors. In this work, we investigate transmission of information about changing extracellular cytokine concentrations from receptor-level supramolecular assemblies of I{kappa}B kinases (IKK) downstream to the nuclear factor {kappa}B (NF-{kappa}B) transcription factor (TF). In a custom robot-controlled microfluidic cell culture, we simultaneously measure input-output (I/O) encoding of IKK-NF-{kappa}B in dual fluorescent-reporter cells. When compared with single cytokine pulses, dose-conserving pulse trains prolong IKK assemblies and lead to disproportionately enhanced retention of nuclear NF-{kappa}B. Using particle swarm optimization, we demonstrate that a mechanistic model does not recapitulate this emergent property. By contrast, invoking mechanisms for NF-{kappa}B-dependent chromatin remodeling to the model recapitulates experiments, showing how temporal dosing that prolongs IKK assemblies facilitates switching to permissive chromatin that sequesters nuclear NF-{kappa}B. Remarkably, using simulations to resolve single-cell receptor data accurately predicts same-cell NF-{kappa}B time courses for more than 80% of our single cell trajectories. Our data and simulations therefore suggest that cell-to-cell heterogeneity in cytokine responses are predominantly due to mechanisms at the level receptor-associated protein complexes.

systems biology↗

bioRxiv2021

A stochastic pooling motif mediates information transfer from receptor assemblies into NF-κB

A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IKK complex is an integration hub for cytokines that govern NF-{kappa}B 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-{kappa}B to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveals their size, number, and timing relays cytokine-specific information with feedback control that is independent of transcription. Our results provide evidence for variable-gain stochastic pooling, a noise-reducing motif that enables parsimonious and cytokine-specific information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling. One Sentence SummaryA variable-gain stochastic pooling motif mediates robust and tunable information transmission from the extracellular milieu into the cell.

systems biology↗

bioRxiv2020

SunRISE: long-term imaging of individual mRNA molecules in living cells

Single-cell imaging of individual mRNAs has revealed core mechanisms of the central dogma. However, most approaches require cell fixation or have limited sensitivity for live-cell applications. Here, we describe SunRISE (SunTag-based Reporter for Imaging Signal Enriched mRNA), a computationally and experimentally optimized approach for unambiguous single-mRNA detection in living cells. We demonstrate SunRISE with long-term epifluorescence imaging, using translational stress to track mRNA phase separation and recovery from cytosolic droplets.

cell biology↗

bioRxiv2019

dNEMO: a tool for quantification of mRNA and punctate structures in time-lapse images of single cells

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 a 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.

cell biology↗

bioRxiv2019

Parallel Tempering with Lasso for Model Reduction in Systems Biology

Systems Biology models reveal relationships between signaling inputs and observable molecular or cellular behaviors. The complexity of these models, however, often obscures key elements that regulate emergent properties. We use a Bayesian model reduction approach that combines Parallel Tempering with Lasso regularization to identify minimal subsets of reactions in a signaling network that are sufficient to reproduce experimentally observed data. The Bayesian approach finds distinct reduced models that fit data equivalently. A variant of this approach based on Group Lasso is applied to the NF-{kappa}B signaling network to test the necessity of feedback loops for responses to pulsatile and continuous pathway stimulation. Taken together, our results demonstrate that Bayesian parameter estimation combined with regularization can isolate and reveal core motifs sufficient to explain data from complex signaling systems.

systems biology↗