Data for: Irreversibility in bacterial regulatory networks

Irreversibility, in which a transient perturbation leaves a system in a new state, is an emergent property in systems of interacting entities. This property has well-established implications in statistical physics but remains underexplored in biological networks, especially for bacteria and other prokaryotes whose regulation of gene expression occurs predominantly at the transcriptional level. Focusing on the reconstructed regulatory network of Escherichia coli, we examine network responses to transient single-gene perturbations. We predict irreversibility in numerous cases and find that the incidence of irreversibility increases with the proximity of the perturbed gene to positive circuits in the network. Comparison with experimental data suggests a connection between the predicted irreversibility to transient perturbations and the evolutionary response to permanent perturbations.

Methods
This dataset contains the results of the Boolean network simulation of irreversibility associated with Science Advances manuscript ado3232. All of the files can be regenerated from the repository stored at GitHub https://github.com/yizhao-nu/Irreversibility-in-GRN/ and Zenodo (DOI: https://dx.doi.org/10.5281/zenodo.12775479) with the exception of the files "all_logtpm_dat.pkl" and "ecoli_metadata.pkl", which are tables of log-transformed transcriptional data and the associated metadata, respectively. These latter files are derived from downloading and processing publicly available raw sequencing data (and associated metadata) obtained from the National Center for Biotechnology Information's Sequencing Read Archive. Raw reads were aligned to the E. coli K12 MG1655 genome (NC.000913.3) using Rockhopper (https://cs.wellesley.edu/~btjaden/Rockhopper/). The purpose of providing these results files is to facilitate reproducibility of the paper's results for users who do not have access to a computer cluster to redo the simulations and/or reprocess the raw sequencing data.