Quantifying the Prevalence and Phenotypic Consequences of Transcriptional Irreversibility in Bacteria

Project: Research project

Project Details


As part of this collaborative NSF proposal led by Prof. Kimberly Reynolds (UT Southwestern), the Northwestern University (NU) team proposes to contribute to the theoretical and computational modeling and analysis of throughput data. The NU team will consist of Prof. Adilson E. Motter (co-PI), a graduate student (with partial time effort committed to this project), a postdoctoral researcher (also with partial time effort committed to this project), and summer undergraduate interns. The central objective of the project is to quantify the prevalence and phenotypic consequences of transcriptional irreversibility in bacteria subjected to transient genetic perturbations, using Escherichia coli as a model organism. This will be achieved by combining CRISPRi-based perturbation experiments to be implemented in Reynolds’ Lab with computational modeling and machine-learning-assisted analysis to be pursued in Motter’s group. Specifically, if the proposal is funded, the NU team will: i) model the relevant time scales governing transitions to/from perturbed states; ii) implement a machine-learning approach to identify distinct cell states from transcriptomic data; iii) analyze experimental results in the context of reconstructed regulatory networks of E. coli; iv) assist the analysis of growth-measurement data, transcriptomic data, and whole genome sequencing data to be generated as part of this project. In addition, the NU team will participate in the dissemination of the research results (through publications in peer-reviewed journals and presentations at scientific meetings), in the outreach effort, and in the proposed annual visits between the two collaborating institutions. The NU team will also fulfill their reporting requirements.
Effective start/end date8/15/227/31/25


  • University of Texas Southwestern Medical School (GMO 230921 PO 0000002785//2206974)
  • National Science Foundation (GMO 230921 PO 0000002785//2206974)


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.