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 analytes dynamic trajectories may distinguish the functional states of single cells and molecular network states underlying them. A record of this papers transparent peer review process is included in the supplemental information.

Macrophages sense pathogens and orchestrate specific immune responses. Stimulus specificity is thought to be achieved through combinatorial and dynamical coding by signaling pathways. While NFκB dynamics are known to encode stimulus information, dynamical coding in other signaling pathways and their combinatorial coordination remain unclear. Here, we established live-cell microscopy to investigate how NFκB and p38 dynamics interface in stimulated macrophages. Information theory and machine learning revealed that p38 dynamics distinguish cytokine TNF from pathogen-associated molecular patterns and high doses from low, but contributed little to information-rich NFκB dynamics when both pathways are considered. This suggests that immune response genes benefit from decoding immune signaling dynamics or combinatorics, but not both. We found that the heterogeneity of the two pathways is surprisingly uncorrelated. Mathematical modeling revealed potential sources of uncorrelated heterogeneity in the branched pathway network topology and predicted it to drive gene expression variability. Indeed, genes dependent on both p38 and NFκB showed high scRNAseq variability and bimodality. These results identify combinatorial signaling as a mechanism to restrict NFκB-AND-p38-responsive inflammatory cytokine expression to few cells.

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.