Microbial Metabolic Engineering and Bioproduction

Active and machine learning-based approaches to rapidly enhance microbial chemical production

This work introduces ActiveOpt, a machine learning approach that reduces the number of experiments needed to optimize microbial chemical production in Escherichia coli.

Development of a growth coupled dynamic regulation network balancing malonyl-CoA node to enhance (2S)-naringenin synthesis in E. coli

The paper develops a dynamic regulation network in E. coli to balance malonyl-CoA for enhanced (2S)-naringenin synthesis, achieving an 8.4-fold production improvement with balanced growth.

A network-based approach to integrate nutrient environment in the prediction of synthetic lethality in cancer metabolism

This paper introduces a network-based method to predict synthetic lethality in cancer metabolism by integrating genetic interactions and nutrient environments, identifying potential vulnerabilities in tumor cells.

A structural property for reduction of biochemical networks

This paper introduces a model reduction approach for biochemical networks that preserves steady-state fluxes and reduces metabolite counts by up to 99% in Escherichia coli models.

Large scale function-based genome prospecting for industrial traits applied to 1,3-propanediol production.

The paper identifies 187 new candidate species for 1,3-propanediol production using a function-based genome mining approach.

Quantification of macromolecular biomass composition for constraint-based metabolic modeling

The paper develops a pipeline for experimental biomass quantification in E. coli, improving coverage and resolution, and evaluates its impact on metabolic model predictions.

MODEL BASED OPTIMIZATION OF THE TERPENOIDS BIOSYNTHESIS IN E. coli

The paper optimizes terpenoids biosynthesis in E. coli by modifying enzyme kcat values and combining them with other strategies to achieve a 21.22 fold increase in biosynthetic flux.

A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

This paper develops yETFL, an extended ME-model for Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics, demonstrating its predictive ability for growth rate, essential genes, and overflow metabolism.

Cell growth model with stochastic gene expression helps understand the growth advantage of metabolic exchange and auxotrophy

The paper presents a stochastic gene expression model of cell growth that explains the growth advantage of metabolic exchange and auxotrophy in microbial communities.

Modular Dynamic Biomolecular Modelling with Bond Graphs: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data.

The paper introduces a bond graph methodology to unify stoichiometry, thermodynamics, and kinetics in dynamic biomolecular modelling, demonstrating its application to E. coli.

Modelling hCDKL5 heterologous expression in bacteria

The paper models the metabolic burden of producing hCDKL5 in bacteria and identifies targets for optimized production.

A CRISPRi screen of essential genes reveals that proteasome regulation dictates acetic acid tolerance in Saccharomyces cerevisiae

A CRISPRi screen identifies proteasome regulation as key to acetic acid tolerance in yeast, revealing gene targets for improving industrial yeast strains.

Data integration uncovers the metabolic bases of phenotypic variation in yeast

The paper integrates protein abundance, metabolic fluxes, and phenotypic traits in yeast to uncover metabolic bases of phenotypic variation.

The Marburg Collection: A Golden Gate DNA Assembly Framework for Synthetic Biology Applications in Vibrio natriegens

The paper introduces the Marburg Collection, a Golden Gate DNA assembly framework for synthetic biology in Vibrio natriegens, providing standardized genetic parts and tools for plasmid construction.

SCOUR: A stepwise machine learning framework for predicting metabolite-dependent regulatory interactions

SCOUR predicts metabolite-dependent regulatory interactions in metabolic networks using a stepwise machine learning framework, achieving high accuracy in identifying single-metabolite-controlled reactions.

Synthetic auxotrophy remains stable after continuous evolution and in co-culture with mammalian cells

The paper continuously evolves a synthetic auxotrophic E. coli strain and finds it remains contained over 100 days and in co-culture with mammalian cells.

Hierarchical Harmonization of Atom-Resolved Metabolic Re-actions Across Metabolic Databases

The paper harmonizes metabolic reactions and compounds across databases by improving atom-level consistency and establishing hierarchical relationships.

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

The paper develops genome-scale metabolic models of human dopaminergic neurons to study metabolic dysfunction in Parkinson's disease using exometabolomic and transcriptomic data.

Integrating thermodynamic and enzymatic constraints into genome-scale metabolic models

This paper introduces a method that integrates enzymatic and thermodynamic constraints into genome-scale metabolic models to improve pathway prediction accuracy.

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

The paper uses genome-scale models to compute proteome allocation under different conditions, revealing variability in cofactor use and protein composition for E. coli growth.

Oleate metabolism using kinetic 13C dilution strategy deciphered the potential role of global transcription regulator arcA in Escherichia coli

This study uses a kinetic 13C dilution strategy to analyze oleate metabolism in E. coli and shows that arcA knockout enhances oleate utilization and metabolic reprogramming.

Reconstruction of genome-scale metabolic model for Hansenula polymorpha using RAVEN toolbox

This paper demonstrates the reconstruction of a genome-scale metabolic model for Hansenula polymorpha using the RAVEN toolbox through a homology-based approach.

Inclusion of maintenance energy improves the intracellular flux predictions of CHO

This study improves intracellular flux predictions in CHO cells by incorporating maintenance energy, enhancing accuracy for TCA cycle fluxes.

Testing theoretical minimal genomes using whole-cell models

The paper tests theoretical minimal genomes for Mycoplasma genitalium using a whole-cell model, finding that simulated minimal gene sets fail to produce dividing cells, highlighting the need for species-specific low essential gene identification.

Biosynthesis of cannabinoid precursor olivetolic acid by overcoming rate-limiting steps in genetically engineered Yarrowia lipolytica

This study improves the biosynthesis of the cannabinoid precursor olivetolic acid in Yarrowia lipolytica by overcoming rate-limiting steps, achieving an 83-fold increase in OLA titer.

Designing an irreversible metabolic switch for scalable induction of microbial chemical production

The paper designs an irreversible metabolic switch in E. coli to reduce inducer usage for scalable microbial chemical production.

COMMIT: Consideration of metabolite leakage and community composition improves microbial community models

The paper introduces COMMIT, a method that improves microbial community models by considering metabolite leakage and community composition, leading to better gap filling and identification of microbial roles.

An evolutionary algorithm for designing microbial communities via environmental modification

This paper introduces an evolutionary algorithm combining machine learning and dynamic flux balance analysis to design microbial communities by optimizing environmental conditions for target phenotypes.

Evolving a new efficient mode of fructose utilization for improved bioproduction in Corynebacterium glutamicum

The paper evolves mutant strains of Corynebacterium glutamicum that utilize fructose more efficiently, leading to increased biomass and L-lysine production.

The quantitative metabolome is shaped by abiotic constraints

The paper formulates abiotic constraints that shape the quantitative metabolome and validates them using Escherichia coli data.