Microbial Metabolic Engineering and Bioproduction

Designing a hybrid in silico/in-cell controller robust to process-model mismatch associated with dynamically regulated enzyme overexpression

This paper demonstrates a hybrid in silico/in-cell controller that reduces toxicity from excessive enzyme overexpression by adapting to process-model mismatch in engineered E. coli.

Quantification of metabolic activity from isotope tracing data using automated methodology

This study develops an automated method to quantify metabolic activity from isotope tracing data, revealing reprogrammed mitochondria-cytosol exchange cycles in tumor tissue.

Genome scale metabolic network modelling for metabolic profile predictions

The paper introduces SAMBA, a computational method that predicts metabolite changes under metabolic perturbations using genome-scale metabolic network modeling and compares predictions with experimental data.

Machine learning predicts system-wide metabolic flux control in cyanobacteria

This paper introduces ARCTICA, a framework combining constraint-based modeling and machine learning to predict metabolic flux control in cyanobacteria, identifying key enzymes and reactions that limit photosynthetic activity.

MIGRENE: The toolbox for microbial and individualized GEMs, reactobiome and community network modelling

The paper introduces MIGRENE, a computational framework for constructing personalized microbiome metabolism models using metagenomic data.

A validated pangenome-scale metabolic model for the Klebsiella pneumoniae species complex

This paper constructs a comprehensive pangenome-scale metabolic model for the Klebsiella pneumoniae species complex, showing improved accuracy in growth predictions compared to previous models.

COSMIC-dFBA: A novel multi-scale hybrid framework for bioprocess modeling

COSMIC-dFBA predicts cell density, antibody titer, and metabolite concentrations in bioreactors by integrating machine learning with genome-scale metabolic models.

Genome streamlining to improve performance of a fast-growing cyanobacterium Synechococcus elongatus UTEX 2973

This paper streamlines the genome of Synechococcus elongatus UTEX 2973 to improve growth and productivity using CRISPR/Cas3 and computational tools.

Pangenomic Landscapes Shape Performances of a Synthetic Genetic Circuit Across Stutzerimonas Species

The paper investigates how genome structure and function influence the performance of a synthetic genetic circuit across six Stutzerimonas species, revealing that core genome expression drives observed differences.

Global sensitivity analysis for investigation of bacterial physiology in complex media with FBA-PRCC

The paper introduces FBA-PRCC for analyzing bacterial physiology in complex media, identifying new interaction modes and showing sensitivity coefficients provide additional insights beyond standard methods.

Infer metabolic velocities from moment differences of molecular weight distributions

This paper introduces a method to infer metabolic balance changes by analyzing differences in molecular weight distributions without requiring knowledge of chemical structures or pathways.

Optimal enzyme profiles in unbranched metabolic pathways

The paper derives analytic solutions for optimizing enzyme allocation in unbranched metabolic pathways using convex optimization and applies the results to bacterial growth.

Snowprint: a predictive tool for genetic biosensor discovery

Snowprint predicts regulator:DNA interactions and designs promoters for uncharacterized regulators, enabling the discovery of new biosensors for various compounds.

Model-guided metabolic engineering of curcuminoid Production in Pseudomonas putida

This paper optimizes curcuminoid production in Pseudomonas putida using dynamic modeling and gene expression tuning, achieving a 4.1-fold increase in efficiency.

Engineering stringent genetic biocontainment of yeast with a protein stability switch

The paper develops a genetic biocontainment system for yeast using a protein stability switch, identifying essential genes that can be conditionally stabilized with estradiol to achieve stringent containment.

Cross-regulation between proteome reallocation and metabolic flux redistribution governs bacterial growth transition kinetics

This study develops a computational framework to model how bacteria coordinate metabolic flux and proteome allocation during nutrient changes, revealing insights into growth transitions.

gMCSpy: Efficient and accurate computation of Genetic Minimal Cut Sets in Python

gMCSpy is a Python package for calculating genetic minimal cut sets in genome-scale metabolic models, offering improved accuracy and speed over existing tools.

Thermodynamics determines the coupling between growth and byproduct production

This paper introduces TOptKnock, a thermodynamically constrained version of OptKnock, to find optimal gene knockouts that couple growth and byproduct production while considering metabolite concentrations.

A constraint-based framework to reconstruct interaction networks in microbial communities

The paper introduces ReMIND, a framework to reconstruct microbial community interaction networks based on metabolic capabilities, applied to uranium-reducing communities and honeybee gut microbiomes.

A diel multi-tissue genome-scale metabolic model of Vitis vinifera

The paper reconstructs and validates the first genome-scale metabolic model for Vitis vinifera, integrating RNA-Seq data to create tissue-specific models and explore ML-driven fluxomics analysis.

Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities

This study compares flux balance analysis and flux sampling in microbial community metabolism, finding significant differences in predicted interactions and flux patterns.

Predicting microbial genome-scale metabolic networks directly from 16S rRNA gene sequences

This paper trains an artificial neural network to predict microbial genome-scale metabolic networks directly from 16S rRNA gene sequences, enabling metabolic analysis of microbes without full genomes.

Optimisation of surfactin yield in Bacillus using active learning and high-throughput mass spectrometry

The paper uses active learning and metabolomics to optimise surfactin yield in Bacillus, achieving a 160% increase over a baseline.

Rational strain design with minimal phenotype perturbation

This paper introduces a framework for rational strain design in E. coli that minimizes phenotype perturbation using mixed-integer linear programming and kinetic models to improve anthranilate production.

Unraveling principles of thermodynamics for genome-scale metabolic networks using graph neural networks

This paper introduces a graph neural network model to predict Gibbs free energy for metabolic reactions and identifies thermodynamic driver reactions in human metabolic networks.

A method to identify high consensus predictions of single-cell metabolic flux

This paper develops a method to identify high consensus predictions of single-cell metabolic flux by comparing two existing tools, Compass and scFEA, and shows they agree on metabolic processes in both healthy and pathological samples.

BioISO: an objective-oriented application for assisting the curation of genome-scale metabolic models

BioISO is a tool that aids in the manual curation of genome-scale metabolic models by reducing search spaces and improving debugging through recursive algorithms and flux balance analysis.

dingo: a Python package for metabolic flux sampling

dingo samples metabolic flux spaces efficiently using advanced random walks and rounding methods, outperforming existing tools for large models.

Microbial Interactions from a New Perspective: Reinforcement Learning Reveals New Insights into Microbiome Evolution

This paper introduces a reinforcement learning algorithm to model microbial metabolism and evolution, showing improved prediction of stable metabolic strategies in heterogeneous communities.

Characterising the metabolic rewiring of extremely slow-growing Komagataella phaffii

This study characterizes metabolic rewiring in Komagataella phaffii under glucose-limited near-zero growth conditions using a genome-scale metabolic model and cultivation data.