Peter A. Lind

This study uses a mathematical framework to simulate in silico evolution of Pseudomonas aeruginosa under antibiotic stress, revealing mutational patterns and resistance mechanisms.

The paper assesses microbial interactions across environments using genome-scale metabolic networks, finding that most bacterial pairs can both compete and cooperate depending on resource availability.

The paper identifies a mutational hotspot in nlpD linked to transcriptional induction of rpoS in Pseudomonas fluorescens SBW25, showing a 5,700-fold elevated mutation rate at this site.

This study uses mathematical models to show that repeated exposure to abiotic stress can lead to adaptive transitions between unicellularity and differentiated multicellularity, with complexity increasing or decreasing depending on mutation order and fitness effects.

This study tests evolutionary forecasts in related bacterial species under similar conditions, showing that phenotypes are predictable but molecular details are not.