Microbial Metabolic Engineering and Bioproduction

The paper analyzes how bacterial metabolic systems respond to perturbations using kinetic models, finding that cofactors and network sparsity significantly influence responsiveness.

This paper updates geckopy to improve enzyme-constraint modeling by integrating proteomics data and thermodynamic constraints, benchmarking against E. coli datasets.

This paper introduces a DNA design platform using Transformer models to predict cross-species DNA functionality, enabling context-sensitive and host-specific gene expression optimization.

The paper isolates and characterizes strains capable of utilizing lignocellulosic waste for lycopene production, showing their potential in synthetic consortia and genetic modification.

This study expands the genetic toolbox of Escherichia coli Nissle 1917 to enhance its utility as a synthetic biology chassis through plasmid engineering, conjugation strategies, and cell-free protein synthesis.

The paper introduces a Markov constraint to uniquely identify elementary flux mode weights in unimolecular metabolic networks, demonstrating its application in analyzing lipid metabolism in Alzheimer's disease.

CAMEL predicts protein abundances by combining constraint-based modeling and machine learning, achieving high accuracy in E. coli and moderate performance in S. cerevisiae.

The paper analyzes proteome efficiency across metabolic pathways in E. coli, finding that efficiency increases along the nutrient flow, with costly pathways near optimal and transporters and central metabolism over-abundant.

ModelSEED v2 improves genome-scale metabolic model reconstruction with enhanced energy metabolism and better pathway curation, leading to more accurate and comprehensive models.

This paper presents lista-GEM, the first genome-scale metabolic model of Lipomyces starkeyi, identifies metabolic engineering targets to improve lipid production from various carbon sources.

The paper uses metabolic modeling to analyze energy and redox balance in Synechocystis sp. PCC 6803 for optimizing bio-alkene production.

The paper investigates the use of sweetwater as a feedstock for lipid production by oleaginous yeasts, finding that it enhances lipid accumulation in certain strains.

This study combines ALE and WT variants to explore sequence solutions for industrial tolerance in E. coli, finding that WT variants can provide greater benefits and help identify feasible genome design variables.

Localgini improves context-specific metabolic models by using gene expression inequality to derive more comprehensive core reactions.

This paper introduces rETFL, a computational method to predict metabolic and expression responses in recombinant organisms, showing its ability to model growth reduction, trade-offs, overflow metabolism, and pathway impacts.

The paper introduces Golden Standard, a modular cloning tool compatible with various bacterial hosts, enabling standardized genetic circuit assembly and validated for performance and portability.

The paper introduces a method to explore abundance-growth space for microbial communities, revealing abundance-dependent metabolic phenotypes through constraint-based modeling.

This paper introduces a hybrid control system for microbial bioprocesses that addresses process-model mismatch by combining in silico and in-cell controllers.

The paper develops growth-coupled microbial strains for high-yield indigoidine production using iterative engineering and computational evaluation.

This paper develops a coarse-grained resource allocation model to explain cellular growth laws and resource allocation strategies in unicellular microbes.

This paper analyzes the geometric properties of elementary flux modes in metabolic networks, showing that EFMs in the relative interior of the flux cone are rare and introducing a complexity measure based on their degree.

The paper reconstructs a high-quality genome-scale metabolic network for Penicillium rubens and identifies bottlenecks in defining specialised metabolites.

The paper demonstrates that genome engineering of E. coli improves TPAL retention and enables its conversion to valuable products like para-xylylenediamine.

This study demonstrates the use of Acinetobacter baylyi ADP1 to convert lignin-derived aromatic monomers into valuable natural products through genetic engineering and metabolic pathway optimization.

The paper develops a deep learning method to reconstruct compartmentalized genome-scale metabolic models for over 800 fungi, improving predictions of metabolic phenotypes and phylogenetic clustering.

The paper develops a community mutual information model to quantify information flow in microbial communities and demonstrates its application using simulated ecosystems.

This study develops genetic toolboxes for Synechococcus sp. PCC 11901 to enhance its use as a carbon-neutral cell factory for producing valuable chemicals from CO2.

CRAPS enables in vivo assembly of multiple pathway configurations by using yeast chromosomal repair and gRNA activation, resulting in diverse carotenoid-producing strains.

This study evaluates COBRA-based tools for microbial consortia modeling using FAIR criteria and experimental data, finding that newer, better-documented tools generally outperform older ones in quality and performance.

The paper integrates proteomics and constraint-based modeling to estimate in vivo enzyme turnover numbers for Chlamydomonas reinhardtii, improving metabolic model predictions.