Lars M. Blank

This study engineers Saccharomyces cerevisiae to produce polyphosphate more efficiently by modifying metabolic pathways and growth conditions.

This study improves acetate tolerance in Pseudomonas putida through adaptive laboratory evolution and identifies gacA and fabB as key targets for efficient acetate assimilation.

This study optimizes protein production in Cupriavidus necator H16 by analyzing genetic factors and demonstrates its superior performance over E. coli in producing a functional enzyme.

This study engineers Pseudomonas putida KT2440 to co-utilize five plastic monomers from mixed plastics, achieving complete substrate depletion and producing (R)-3-hydroxybutyrate.

This paper improves acetate metabolism in P. putida KT2440 through rational and evolutionary engineering, enhancing growth rate and HAA production.

This paper compares two hydrogen-oxidizing bacteria strains to identify genomic features that inform the design of safe, efficient food-grade microbes for power-to-protein production.

This study engineers a co-culture of A. baylyi and E. coli to convert p-coumaric acid to cis,cis-muconic acid, achieving 18.55 mM ccMA with improved titres but highlighting metabolic pathway bottlenecks.

This study demonstrates that Ustilago maydis can efficiently produce itaconic acid from acetate, achieving high titers and yields comparable to glucose-based processes, supporting acetate as a sustainable feedstock for land-free biotechnology.

The paper engineering Pseudomonas putida KT2440 to produce 3-hydroxy fatty acids (3-HFAs) with controlled chain lengths, achieving titers up to 0.73 g/L using a direct route and demonstrating scalability.

The paper develops a physiologically-based model of bile acid metabolism in humans to analyze how disease-related changes affect bile acid composition along the gut-liver-axis.

This study evolves a unique Acinetobacter baylyi strain through a two-step adaptive laboratory evolution process to improve lignin valorization capabilities.

The paper presents methods to improve electroporation efficiency in non-model bacteria using Cupriavidus necator H16 as a test case.

The paper introduces FROG analysis to standardize reproducibility assessments of genome-scale metabolic models, resulting in full reproducibility of all tested models.

The paper introduces a one-plasmid genome editing system for P. putida KT2440, enabling rapid and efficient genome modifications in three days.

This paper develops a synthetic bacterial consortium to degrade plastic pyrolysis oil waste, achieving high removal efficiencies for alkanes and aromatic hydrocarbons, and uses a neural network to model microbial activity.

Yeast9 improves yeast metabolic modeling by integrating multi-omics data, showing better prediction of growth rates and gene function than transcriptomics.

This study evaluates codon optimization strategies for improving heterologous expression of engineered type I polyketide synthases in three bacterial hosts and develops an online tool for codon optimization.

This study develops a physiologically-based model of bile acid metabolism in mice to understand its dynamics and implications for disease.

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

This study demonstrates that the biological activity of rhamnolipids in plants depends on their molecular structure, with different congeners showing varying effects on nematode infection and plant growth.

This paper engineers Pseudomonas putida KT2440 to produce medium- and long-chain free fatty acids and oleochemicals, achieving titers up to 670 mg/L.

The paper develops a genome-scale metabolic model for Ustilago maydis to study metabolic adaptations and biotechnological applications.

The paper introduces a machine-learning workflow for analyzing promoter libraries to identify sequence design principles that predict gene expression activity.

This study develops a protein allocation model to predict Escherichia coli wildtype and mutant phenotypes by integrating protein distribution with metabolic fluxes.

This paper engineers Pseudomonas taiwanensis VLB120 to produce methyl ketones with a 4-fold higher titer than previous strains, achieving 9.8 g L-1.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

The paper evaluates an optimized gene expression architecture in Pseudomonas taiwanensis to enhance protein abundance through mRNA stability and translation efficiency, showing improved performance over traditional methods.

The paper develops a computational framework to quantify metabolic interactions in microbial co-cultures using a new index and experimental validation.

The paper develops a physiology-based model of bile acid metabolism to predict drug-induced liver injury risk and genetic susceptibility.