Microbial Metabolic Engineering and Bioproduction

Accessible Gibbs energy at metabolic activation limits long-term cell growth

The paper shows that accessible Gibbs energy at metabolic activation limits long-term cell growth by constraining metabolic reorganization and ATP production.

Hybrid genome-scale modeling and machine learning reveal cost-efficient strategies for phototrophic PHB production in Rhodopseudomonas palustris

This paper combines genome-scale modeling, machine learning, and thermodynamics analysis to identify cost-effective strategies for PHB production in Rhodopseudomonas palustris.

dAMN: a genome scale neural-mechanistic hybrid model to predict bacterial growth dynamics

dAMN predicts bacterial growth dynamics using a hybrid neural-mechanistic model, achieving high accuracy across diverse nutrient environments and capturing lag phase adaptation.

Engineering reduced nicotinamide cofactor metabolism for enhanced cell growth and succinic acid production in a succinate dehydrogenase deficient Yarrowia lipolytica strain

The paper enhances succinic acid production in a Yarrowia lipolytica strain lacking succinate dehydrogenase by redirecting metabolic flux and improving NADH availability.

Spatial organization of enzymes and cofactors in synthetic membrane-associated condensates (sMACs)

The paper demonstrates that synthetic membrane-associated condensates (sMACs) can be engineered to enhance metabolic functions by creating localized redox microenvironments through cofactor partitioning.

CyanOperon: an operon building expansion for the CyanoGate MoClo toolkit

The paper introduces CyanOperon, a toolkit for assembling synthetic operons in the CyanoGate MoClo system, demonstrating its use in biosynthesis pathways and RBS libraries in E. coli and Synechocystis.

Efficient Cell Factory Design by Combining Meta-Heuristic Algorithm with Enzyme Constrained Metabolic Models

MetaStrain combines enzyme-constrained models with meta-heuristic algorithms to efficiently identify combinatorial gene targets for improving microbial product yields.

Leveraging large language models for metabolic engineering design

This paper develops a large language model-based method to extract metabolic engineering strategies from research articles and trains a hybrid model to predict engineering targets, outperforming traditional approaches.

Synthetic niches enable co-culture bioprocessing but are prone to mutational escape

The paper introduces synthetic niches using genetic toggle switches to control microbial co-cultures but finds they are vulnerable to mutational escape under cultivation.

Conserved metabolic vulnerabilities across pathogenic coronaviruses nominate host-directed therapeutic targets

The paper identifies conserved metabolic vulnerabilities across SARS-CoV, SARS-CoV-2, and MERS-CoV using transcriptomic data and metabolic models, revealing druggable host targets.

Generative Approaches to Kinetic Parameter Inference in Metabolic Networks via Latent Space Exploration

This paper presents a framework for adapting generative neural networks to build kinetic models for different organisms and physiological contexts by exploring latent space.

NAViFluX: a visualization-centric platform for interactive analysis, refinement and design of genome-scale metabolic networks

NAViFluX is a web-based platform for analyzing and designing genome-scale metabolic networks, enabling interactive visualization, refinement, and flux analysis of metabolic models.

PathwaySeeker: Evidence-Grounded AI Reasoning over Organism-Specific Metabolic Networks

PathwaySeeker uses AI to reason about organism-specific metabolic networks using proteomic and metabolomic data, distinguishing confirmed reactions from hypotheses.

Exploring Chromosomal Position Effects for Predictable Tuning of Metabolic Pathways in Yeast

The paper develops a predictive framework to optimize metabolic pathways in yeast by leveraging chromosomal position effects.

iCNG99: a validated genome-scale metabolic model of Cryptococcus neoformans strain H99

The paper develops and validates a genome-scale metabolic model for Cryptococcus neoformans strain H99, showing high precision in essential gene prediction and capturing metabolic adaptations relevant to drug tolerance and host survival.

Higher order synthetic lethals are keys to minimize cancer treatment effects on non-tumor cells

This study identifies strictly-selective drug targets for 13 cancers using higher-order synthetic lethal sets to minimize harm to non-tumor tissues.

Equation-Based Integration of Flux Balance Analysis with Diffusion for Spatio-Temporal Simulation of Microbial Communities

The paper integrates flux balance analysis with diffusion equations to simulate spatio-temporal microbial community metabolism, showing optimal interaction distances for metabolite production.

Modeling and dissecting bidirectional feedback in gene-metabolite systems using the CausalFlux method

This paper introduces CausalFlux, a method modeling bidirectional feedback between genes and metabolites, showing improved prediction of reaction fluxes and gene essentiality compared to one-way feedback models.

L-Lysine production from glucose and chitin monomers using engineered Vibrio natriegens

This paper engineers V. natriegens to overproduce L-lysine from glucose and chitin monomers, achieving high titers and yields through targeted metabolic pathway modifications.

Tripleknock: predicting lethal effect of three-gene knockout in bacteria by deep learning

Tripleknock predicts lethal effects of three-gene knockouts in bacteria using deep learning, achieving faster predictions than FBA with high cross-species accuracy.

Systematic CRISPRi screening reveals genetic modulators of E. coli isoprenoid production

This study uses CRISPRi screening to identify E. coli genes affecting lycopene production, finding 31 genes that significantly modify yield across various metabolic pathways.

Protein without farms: What comparative genomics reveals about ''Power-to-Food'' microbes

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.

Generalist method to reconstruct metabolic networks from multi-omics data at large-scale

The paper introduces SPECTRA, a method to reconstruct metabolic networks from multi-omics data at large-scale, improving speed and reaction inclusion across cancer cell lines, microbial reconstructions, and synthetic gut microbiota.

De novo biosynthesis of alpinetin enhanced by directed evolution of 5-O-methyltransferase

This study enables the de novo biosynthesis of alpinetin in E. coli through directed evolution of a 5-O-methyltransferase, demonstrating its broad substrate specificity for O-methylated flavonoids.

Metabolic engineering of Corynebacterium glutamicum for production of the low-caloric natural sweetener D-allulose via phosphorylated intermediates

This paper engineers Corynebacterium glutamicum to produce D-allulose via a phosphorylation-dephosphorylation pathway, achieving a 2.3-fold increase in production in minimal medium.

Adaptive evolution of engineered Saccharomyces cerevisiae in favored and unusual chemical environments

This study investigates how Darwinian selection affects engineered traits in yeast by evolving strains with pigment production pathways under different carbon sources.

Metabolostasis failure thresholds are linked with network topology, metabolite solubility, and translational control

The paper identifies metabolite-specific failure thresholds in yeast linked to network topology, solubility, and translational control, revealing mechanisms of metabolic toxicity and resilience.

Multi-strain Analysis of Pseudomonas putida Reveals the Metabolic and Genetic Diversity of the Species.

This study analyzes 164 Pseudomonas putida strains to reveal metabolic and genetic diversity, curating GEMs and identifying strain-specific adaptations for biotechnology applications.

eBiota: Designing microbial communities from large seed pools with desired function using rapid optimization and deep learning

eBiota designs microbial communities from large strain pools to generate target products using optimization and deep learning, showing accurate predictions and experimental validation.

A Reproducible Dual-Model Constraint-Based Framework for Exploring Hepatic Energy Metabolism Under Stachys affinis-Derived Short-Chain Fatty Acid Scenarios

This paper uses two genome-scale metabolic models to simulate hepatic ATP metabolism under different SCFA scenarios derived from Stachys affinis tubers, identifying model-specific pathway gaps and cross-validated predictions.