Alex J. H. Fedorec

This study shows that inhibiting FKBP51 early in joint pain reduces both sensory and emotional symptoms for up to 6 months, while late inhibition only provides temporary relief.

This study demonstrates ethanolamine utilization and eut BMC formation in E. coli Nissle 1917 through growth assays, microscopy, and flux balance analysis, showing comparable metabolism to Salmonella enterica with distinct ammonium release.

This paper designs bacterial computers using spatial diffusion and engineered Escherichia coli to perform digital logic operations and complex computations.

The paper shows that early functional measures in joint disease models predict long-term sensory and emotional symptoms, suggesting their use in clinical settings for better pain management and prevention of emotional comorbidities.

The paper develops a modular platform for expressing and secreting bacteriocins from non-pathogenic E. coli to target pathogenic bacteria, demonstrating antimicrobial activity and modeling strain interactions.

The paper constructs acetoacetate-sensitive whole-cell biosensors using the AtoSC two-component system and demonstrates their functionality in E. coli.

This paper engineers a single Escherichia coli strain to stabilize microbial consortia through competitive exclusion and toxin secretion, showing tunable population composition.

This paper designs synthetic microbial communities using quorum sensing and Bayesian methods to identify stable interactions in chemostat environments.

FlopR calibrates and normalizes flow cytometry and plate reader data using a unified R package, validated on E. coli GFP expression data to identify subpopulations from bulk measurements.

This paper demonstrates the use of reinforcement learning to control microbial co-cultures in bioreactors, showing improved performance over traditional methods.

The paper identifies two new plasmid post-segregational killing mechanisms in E. coli that enhance plasmid stability in both in vitro and in vivo settings.

This paper introduces StabilityFinder, a computational tool for analyzing multistable genetic switches, and demonstrates its application to identify design principles for bistable, tristable, and quadristable systems.