Zhengqing Zhou

This paper shows that a synthetic gene circuit can break a growth rate plateau in E. coli by selectively suppressing slow-growing cells, leading to faster growth.

The paper shows keystone engineering enables microbial range expansion by antibiotic-degrading bacteria, revealing spatial effects in microbial communities.

This paper develops a foundation model for microbial growth dynamics using self-supervised learning on diverse datasets, enabling accurate reconstruction and prediction of growth patterns and antibiotic responses.

The paper shows that prolonged plasmid persistence after antibiotic treatment is due to dynamical memory, not horizontal transfer or low plasmid cost.

The paper develops a new computational method to analyze plasmid copy numbers across microbial genomes and identifies three scaling laws relating plasmid length, gene content, and metabolic function.

The paper shows that microbial community dynamics can be represented by low-dimensional latent variables, with the critical dimension scaling linearly with observables.

The paper shows antibiotic-mediated community restructuring is driven by subpopulation variability in antibiotic susceptibility and their interactions.