Stimulus-response signaling dynamics characterize macrophage polarization states.

The functional state of cells is dependent on their microenvironmental context. Prior studies described how polarizing cytokines alter macrophage transcriptomes and epigenomes. Here, we characterized the functional responses of 6 differentially polarized macrophage populations by measuring the dynamics of transcription factor nuclear factor κB (NF-κB) in response to 8 stimuli. The resulting dataset of single-cell NF-κB trajectories was analyzed by three approaches: (1) machine learning on time-series data revealed losses of stimulus distinguishability with polarization, reflecting canalized effector functions. (2) Informative trajectory features driving stimulus distinguishability ("signaling codons") were identified and used for mapping a cell state landscape that could then locate macrophages conditioned by an unrelated condition. (3) Kinetic parameters, inferred using a mechanistic NF-κB network model, provided an alternative mapping of cell states and correctly predicted biochemical findings. Together, this work demonstrates that a single analyte's dynamic trajectories may distinguish the functional states of single cells and molecular network states underlying them. A record of this paper's transparent peer review process is included in the supplemental information.

Co-imaging of RelA and c-Rel reveals features of NF-κB signaling for ligand discrimination.

Individual cell sensing of external cues has evolved through the temporal patterns in signaling. Since nuclear factor κB (NF-κB) signaling dynamics have been examined using a single subunit, RelA, it remains unclear whether more information might be transmitted via other subunits. Using NF-κB double-knockin reporter mice, we monitored both canonical NF-κB subunits, RelA and c-Rel, simultaneously in single macrophages by quantitative live-cell imaging. We show that signaling features of RelA and c-Rel convey more information about the stimuli than those of either subunit alone. Machine learning is used to predict the ligand identity accurately based on RelA and c-Rel signaling features without considering the co-activated factors. Ligand discrimination is achieved through selective non-redundancy of RelA and c-Rel signaling dynamics, as well as their temporal coordination. These results suggest a potential role of c-Rel in fine-tuning immune responses and highlight the need for approaches that will elucidate the mechanisms regulating NF-κB subunit specificity.

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.