Helena Schulz-Mirbach

Combining evolution and machine learning-guided pathway optimization to engineer a novel methylsuccinate module for synthetic C1 metabolism in vivo

This paper combines adaptive laboratory evolution and machine learning to engineer a methylsuccinate module for synthetic C1 metabolism in E. coli, achieving growth in three weeks versus six months with evolution alone.

Modular in vivo engineering of the reductive methylaspartate cycles for synthetic CO2 fixation

This paper designs and tests synthetic CO2 fixation pathways in E. coli, demonstrating their potential to outperform natural pathways.

Systematic engineering of synthetic serine cycles in Pseudomonas putida uncovers emergent topologies for methanol assimilation

This study engineers synthetic serine cycles in Pseudomonas putida to improve methanol assimilation, revealing novel metabolic topologies for C1 compound utilization.

Expanding the biotechnological scope of metabolic sensors through computation-aided designs

This paper presents a computational workflow for designing and testing E. coli metabolic sensors that detect glyoxylate and glycolate across a wide concentration range, with applications in bioengineering and environmental monitoring.

Implementation of the β-hydroxyaspartate cycle increases growth performance of Pseudomonas putida on the PET monomer ethylene glycol

This study replaces the glycerate pathway with the β-hydroxyaspartate cycle in Pseudomonas putida, resulting in faster growth and higher biomass yield on ethylene glycol.

On the flexibility of the cellular amination network in E. coli

The paper studies the flexibility of the amination network in E. coli by identifying key enzymes and amino acids involved in ammonium assimilation and glutamate production.

Activating silent glycolysis bypasses in Escherichia coli

This study identifies alternative glycolytic pathways in E. coli that bypass canonical EMP glycolysis, showing that the serine shunt is selected for in adaptive evolution.