1. Stimulus-response signaling dynamics characterize macrophage polarization states.
- Author
-
Singh, Apeksha, Sen, Supriya, Iter, Michael, Adelaja, Adewunmi, Luecke, Stefanie, Guo, Xiaolu, and Hoffmann, Alexander
- Subjects
NF-κB dynamics ,inflammation ,innate immunity ,machine learning ,macrophage ,math modeling ,microenvironmental context ,polarization ,stimulus-specific responses ,trajectory data ,Macrophages ,Signal Transduction ,NF-kappa B ,Animals ,Mice ,Cell Polarity ,Humans ,Cytokines ,Macrophage Activation ,Single-Cell Analysis ,Machine Learning - Abstract
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.
- Published
- 2024