Information Network Flux interprets the importance of regulatory circuits in the protein and gene spaces

Abstract Cells receive information from environment, make decisions, and execute biological functions. This sensor-actuator controlling mode is common, and has benefits for system stability especially when there exist feedback-loops for action correction. In cells, transcription factors (TFs) play the role of “brain” since they control the expression levels of about 20,000 protein-coding genes. However, the detailed topological structure of the regulating relationships among them is far from clear. Circuitlike pathways, which usually contain protein-protein interactions (PPIs), TF-gene regulations and gene expressions, are pervasive in cells, however, their importance is yet to be systematically elucidated by unifying information at both protein and gene levels. Here we developed Information Network Flux (INF), an algorithm that could simulate information transmit on multi-layer networks, and integrate protein and gene level information for cell type specific pathways that respond to given perturbation. We used topological analysis to identify regulatory circuits and found that the TFs participating in these circuits, especially those acted as “sensor” or “actuator” are highly relevant to cellular response to external signals. At the gene level, circuit genes serve as efficient cell type indicators, which showed better performance than commonly used gene expression levels. At the circuit level, shorter circuits enrich housekeeping functions and longer circuits exhibit increased tissue-specificity. These findings suggest that these circuit pathways may contribute to the identity and stability of cell states. Competing Interest Statement The authors have declared no competing interest.