Timothy K. Lee

Single-cell NF-κB dynamics reveal digital activation and analogue information processing

Cells operate in dynamic environments using extraordinary communication capabilities that emerge from the interactions of genetic circuitry. The mammalian immune response is a striking example of the coordination of different cell types. Cell-to-cell communication is primarily mediated by signalling molecules that form spatiotemporal concentration gradients, requiring cells to respond to a wide range of signal intensities. Here we use high-throughput microfluidic cell culture and fluorescence microscopy, quantitative gene expression analysis and mathematical modelling to investigate how single mammalian cells respond to different concentrations of the signalling molecule tumour-necrosis factor (TNF)-α, and relay information to the gene expression programs by means of the transcription factor nuclear factor (NF)-κB. We measured NF-κB activity in thousands of live cells under TNF-α doses covering four orders of magnitude. We find, in contrast to population-level studies with bulk assays, that the activation is heterogeneous and is a digital process at the single-cell level with fewer cells responding at lower doses. Cells also encode a subtle set of analogue parameters to modulate the outcome; these parameters include NF-κB peak intensity, response time and number of oscillations. We developed a stochastic mathematical model that reproduces both the digital and analogue dynamics as well as most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α-induced NF-κB signalling in various types of cells. These results highlight the value of high-throughput quantitative measurements with single-cell resolution in understanding how biological systems operate.

Single-cell NF-[kgr]B dynamics reveal digital activation and analogue information processing

Cells operate in dynamic environments using extraordinary communication capabilities that emerge from the interactions of genetic circuitry. The mammalian immune response is a striking example of the coordination of different cell types. Cell-to-cell communication is primarily mediated by signalling molecules that form spatiotemporal concentration gradients, requiring cells to respond to a wide range of signal intensities. Here we use high-throughput microfluidic cell culture and fluorescence microscopy, quantitative gene expression analysis and mathematical modelling to investigate how single mammalian cells respond to different concentrations of the signalling molecule tumour-necrosis factor (TNF)-α, and relay information to the gene expression programs by means of the transcription factor nuclear factor (NF)-κB. We measured NF-κB activity in thousands of live cells under TNF-α doses covering four orders of magnitude. We find, in contrast to population-level studies with bulk assays, that the activation is heterogeneous and is a digital process at the single-cell level with fewer cells responding at lower doses. Cells also encode a subtle set of analogue parameters to modulate the outcome; these parameters include NF-κB peak intensity, response time and number of oscillations. We developed a stochastic mathematical model that reproduces both the digital and analogue dynamics as well as most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α-induced NF-κB signalling in various types of cells. These results highlight the value of high-throughput quantitative measurements with single-cell resolution in understanding how biological systems operate.

A Noisy Paracrine Signal Determines the Cellular NF-κB Response to Lipopolysaccharide

A low-concentration paracrine TNF-α signal contributes to the variability in NF-κB activation dynamics in the response to lipopolysaccharide. Prolonging NF-κB Activation Regulation of the activity of the transcription factor NF-κB, which plays key roles in immune responses, exhibits complicated cellular dynamics. Tumor necrosis factor–α (TNF-α), a proinflammatory cytokine that activates the death-domain receptor TNFR, and lipopolysaccharide (LPS), a pathogen-derived molecule that activates the Toll-like receptor TLR4, both activate NF-κB. Lee et al. provide a mechanism by which cells respond to these two ligands with different kinetics. Cells responding to TNF-α exhibit an oscillating translocation of NF-κB in and out of the nucleus, with all cells responding similarly. In contrast, cells responding to LPS showed two distinct modes, with one population exhibiting transient nuclear localization of NF-κB and a second exhibiting persistent nuclear localization. Lee et al. modified an existing computational model of the pathways that activate NF-κB and found that cells responding to LPS produce TNF-α in concentrations that are low enough that only a subset of neighboring cells responds. This paracrine TNF-α signal produces the population of LPS-responsive cells with persistent prolonged NF-κB activation. Nearly identical cells can exhibit substantially different responses to the same stimulus. We monitored the nuclear localization dynamics of nuclear factor κB (NF-κB) in single cells stimulated with tumor necrosis factor–α (TNF-α) and lipopolysaccharide (LPS). Cells stimulated with TNF-α have quantitative differences in NF-κB nuclear localization, whereas LPS-stimulated cells can be clustered into transient or persistent responders, representing two qualitatively different groups based on the NF-κB response. These distinct behaviors can be linked to a secondary paracrine signal secreted at low concentrations, such that not all cells undergo a second round of NF-κB activation. From our single-cell data, we built a computational model that captures cell variability, as well as population behaviors. Our findings show that mammalian cells can create “noisy” environments to produce diversified responses to stimuli.

A dynamically assembled cell wall synthesis machinery buffers cell growth

Significance For complex biological processes, the formation of protein complexes is a strategy for coordinating the activities of many enzymes in space and time. It has been hypothesized that growth of the bacterial cell wall involves stable synthetic complexes, but neither the existence of such complexes nor the consequences of such a mechanism for growth efficiency have been demonstrated. Here, we use single-molecule tracking to demonstrate that the association between an essential cell wall synthesis enzyme and the cytoskeleton is highly dynamic, which allows the cell to buffer growth rate against large fluctuations in enzyme abundance. This indicates that dynamic association can be an efficient strategy for coordination of multiple enzymes, especially those for which excess abundance can be harmful to cells. Assembly of protein complexes is a key mechanism for achieving spatial and temporal coordination in processes involving many enzymes. Growth of rod-shaped bacteria is a well-studied example requiring such coordination; expansion of the cell wall is thought to involve coordination of the activity of synthetic enzymes with the cytoskeleton via a stable complex. Here, we use single-molecule tracking to demonstrate that the bacterial actin homolog MreB and the essential cell wall enzyme PBP2 move on timescales orders of magnitude apart, with drastically different characteristic motions. Our observations suggest that PBP2 interacts with the rest of the synthesis machinery through a dynamic cycle of transient association. Consistent with this model, growth is robust to large fluctuations in PBP2 abundance. In contrast to stable complex formation, dynamic association of PBP2 is less dependent on the function of other components of the synthesis machinery, and buffers spatially distributed growth against fluctuations in pathway component concentrations and the presence of defective components. Dynamic association could generally represent an efficient strategy for spatiotemporal coordination of protein activities, especially when excess concentrations of system components are inhibitory to the overall process or deleterious to the cell.

Computational modeling of mammalian signaling networks

One of the most exciting developments in signal transduction research has been the proliferation of studies in which a biological discovery was initiated by computational modeling. In this study, we review the major efforts that enable such studies. First, we describe the experimental technologies that are generally used to identify the molecular components and interactions in, and dynamic behavior exhibited by, a network of interest. Next, we review the mathematical approaches that are used to model signaling network behavior. Finally, we focus on three specific instances of ‘model‐driven discovery’: cases in which computational modeling of a signaling network has led to new insights that have been verified experimentally. Copyright

Mechanical crack propagation drives millisecond daughter cell separation in Staphylococcus aureus

Pop goes the coccus Daughter cell separation in Staphylococcus aureus proceeds much like the cracking of an egg. So say Zhou et al., who examined dividing cells with millisecond precision using high-speed videomicroscopy. Rather than proceeding gradually, tiny imperfections in the mother cell wall were seen to crack open, leaving two daughter cells linked by a hinge. Science, this issue p. 574 Daughter cell separation in Staphylococcus aureus proceeds much like the cracking of an egg. When Staphylococcus aureus undergoes cytokinesis, it builds a septum, generating two hemispherical daughters whose cell walls are only connected via a narrow peripheral ring. We found that resolution of this ring occurred within milliseconds (“popping”), without detectable changes in cell volume. The likelihood of popping depended on cell-wall stress, and the separating cells split open asymmetrically, leaving the daughters connected by a hinge. An elastostatic model of the wall indicated high circumferential stress in the peripheral ring before popping. Last, we observed small perforations in the peripheral ring that are likely initial points of mechanical failure. Thus, the ultrafast daughter cell separation in S. aureus appears to be driven by accumulation of stress in the peripheral ring and exhibits hallmarks of mechanical crack propagation.

Principles of Bacterial Cell-Size Determination Revealed by Cell-Wall Synthesis Perturbations

Although bacterial cell morphology is tightly controlled, the principles of size regulation remain elusive. In Escherichia coli, perturbation of cell-wall synthesis often results in similar morphologies, making it difficult to deconvolve the complex genotype-phenotype relationships underlying morphogenesis. Here we modulated cell width through heterologous expression of sequences encoding the essential enzyme PBP2 and through sublethal treatments with drugs that inhibit PBP2 and the MreB cytoskeleton. We quantified the biochemical and biophysical properties of the cell wall across a wide range of cell sizes. We find that, although cell-wall chemical composition is unaltered, MreB dynamics, cell twisting, and cellular mechanics exhibit systematic large-scale changes consistent with altered chirality and a more isotropic cell wall. This multiscale analysis enabled identification of distinct roles for MreB and PBP2, despite having similar morphological effects when depleted. Altogether, our results highlight the robustness of cell-wall synthesis and physical principles dictating cell-size control.

High-throughput, single-cell NF-κB dynamics.

Single cells in a population often respond differently to perturbations in the environment. Live-cell microscopy has enabled scientists to observe these differences at the single-cell level. Some advantages of live-cell imaging over population-based methods include better time resolution, higher sensitivity, automation, and richer datasets. One specific area where live-cell microscopy has made a significant impact is the field of NF-κB signaling dynamics, and recent efforts have focused on making live-cell imaging of these dynamics more high-throughput. We highlight the major aspects of increasing throughput and describe a current system that can monitor, image and analyze the NF-κB activation of thousands of single cells in parallel.

The role of hydrolases in bacterial cell-wall growth.

Although hydrolysis is known to be as important as synthesis in the growth and development of the bacterial cell wall, the coupling between these processes is not well understood. Bond cleavage can generate deleterious pores, but may also be required for the incorporation of new material and for the expansion of the wall, highlighting the importance of mechanical forces in interpreting the consequences of hydrolysis in models of growth. Critically, minimal essential subsets of hydrolases have now been identified in several model organisms, enabling the reduction of genetic complexity. Recent studies in Bacillus subtilis have provided evidence for both the presence and absence of coupling between synthesis and hydrolysis during sporulation and elongation, respectively. In this review, we discuss strategies for dissecting the relationship between synthesis and hydrolysis using time-lapse imaging, biophysical measurements of cell-wall architecture, and computational modeling.

Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library.

BackgroundThe determination and regulation of cell morphology are critical components of cell-cycle control, fitness, and development in both single-cell and multicellular organisms. Understanding how environmental factors, chemical perturbations, and genetic differences affect cell morphology requires precise, unbiased, and validated measurements of cell-shape features.ResultsHere we introduce two software packages, Morphometrics and BlurLab, that together enable automated, computationally efficient, unbiased identification of cells and morphological features. We applied these tools to bacterial cells because the small size of these cells and the subtlety of certain morphological changes have thus far obscured correlations between bacterial morphology and genotype. We used an online resource of images of the Keio knockout library of nonessential genes in the Gram-negative bacterium Escherichia coli to demonstrate that cell width, width variability, and length significantly correlate with each other and with drug treatments, nutrient changes, and environmental conditions. Further, we combined morphological classification of genetic variants with genetic meta-analysis to reveal novel connections among gene function, fitness, and cell morphology, thus suggesting potential functions for unknown genes and differences in modes of action of antibiotics.ConclusionsMorphometrics and BlurLab set the stage for future quantitative studies of bacterial cell shape and intracellular localization. The previously unappreciated connections between morphological parameters measured with these software packages and the cellular environment point toward novel mechanistic connections among physiological perturbations, cell fitness, and growth.