Cells operate in ever changing 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.1 Cell-to-cell communication is primarily mediated by signaling 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, quantitative gene expression analysis and mathematical modeling to investigate how single mammalian cells respond to different concentrations of the signaling molecule TNF-α, and relay information to the gene expression programs via the transcription 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 studies, 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 analog parameters to modulate the outcome; these parameters include NF-κB peak intensity, response time and number of oscillations. We developed a mathematical model that reproduces both the digital and analog dynamics as well as the most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α induced NF-κB signaling in various types of cells. These results highlight the value of high-throughput quantitative measurements at the single-cell level in understanding how biological systems operate.

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 demonstrate that mammalian cells can create “noisy” environments in order to produce diversified responses to stimuli.

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. Finally, 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.

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.Conclusions Morphometrics 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-017-0348-8) contains supplementary material, which is available to authorized users.

Fluorescent d-amino acids (FDAAs) enable efficient in situ labeling of peptidoglycan in diverse bacterial species.