Microbial Metabolic Engineering and Bioproduction

Multi-omic data fusion reveals the in vivo enzyme kinetics of Vibrio natriegens at the genome-scale

This study measures in vivo enzyme turnover numbers in Vibrio natriegens using multi-omic data fusion, revealing enzymes are 14-fold faster than E. coli and showing machine learning underestimates these kinetics.

Human Genome-Scale Models of Metabolism and Gene Expression Reveal Resource Constraints of Cancer Cell Lines

The paper develops human ME-Models that integrate gene expression and metabolism, showing improved growth-rate predictions and biological plausibility in cancer cell lines.

CRISPRi-assisted E. coli strains increase success rate of burdensome construct cloning

The paper introduces CRISPRi-assisted E. coli strains to improve cloning success for burdensome genetic constructs by reducing metabolic burden during cloning.

Developing engineering strategies to enhance the genetic stability of fatty alcohol-producing strains for production scale-up

This paper develops strategies to improve genetic stability in fatty alcohol-producing Yarrowia lipolytica strains to enhance production scale-up.

Optimizing photoautotrophic production of soluble 3-hydroxybutyrate in Synechocystis sp. PCC 6803 through combinatorial translational tuning

This paper enhances 3-hydroxybutyrate production in Synechocystis sp. PCC 6803 by optimizing translational regulation of key pathway enzymes, achieving high titers in photoautotrophic conditions.

Elementary vectors reveal minimal interactions in microbial communities

This paper introduces a geometric framework to analyze microbial community interactions by computing elementary composition/exchange fluxes (ECXs) that represent distinct ecological interaction types.

Dual-Chassis Strategy for Bridging Adaptive Evolution and Rational Design for Synthetic Biology

The paper introduces a dual chassis framework (DUET) to combine rational metabolic design with adaptive evolution, enabling robust microbial platform development.

Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics

This paper introduces a computational framework to infer enzyme targets from metabolic perturbations using time-resolved metabolomics data.

Heterologous iron-sulfur cluster biogenesis and delivery for cytosolic isobutanol and isopentanol production in Saccharomyces cerevisiae

This study enhances cytosolic isobutanol and isopentanol production in yeast by introducing prokaryotic iron-sulfur cluster biosynthesis genes and accessory proteins.

Adaptive laboratory evolution unlocks membrane permeability as a key limitation in long-chain alcohol metabolism by Pseudomonas putida KT2440

This study identifies membrane permeability as a key limitation in long-chain alcohol metabolism by P. putida KT2440 through adaptive laboratory evolution and transporter expression.

Recursive exploration of metabolic yield space

This paper introduces a novel method for efficiently generating yield spaces from genome-scale metabolic networks, enabling advanced analysis techniques for metabolic modeling.

iSsus3744: A Genome-Scale Model-Guided Strategy for Rational Media Design for Cultivated Pork

This paper introduces iSsus3744, a genome-scale metabolic model for Sus scrofa, and demonstrates its use in optimizing media for cultivated pork production by identifying limiting amino acids.

Growth-resolved genome-scale metabolic modeling of Priestia megaterium SR7 validated by chemostat and 13-C flux analysis

This paper develops and validates a genome-scale metabolic model for Priestia megaterium SR7 using chemostat experiments and 13-C flux analysis to improve bioprocess engineering applications.

Comparing Kinetic versus Stoichiometric Priorities in Hybrid Models of CHO Metabolism

This study compares kinetic and stoichiometric models of CHO metabolism, finding that kinetic models better predict bioprocess outcomes like cell density and metabolite levels.

A Novel Network Approach to Identify Sample-Specific Context-Informed Metabolic Signatures During Developmental Processes

This paper introduces a network-based method to analyze sample-specific metabolic flow during ovarian follicle development, identifying key metabolites and markers for follicular maturation.

Atomic elementary flux modes explain the steady state flow of metabolites in large-scale flux networks

The paper introduces atomic elementary flux modes (AEFMs) to efficiently analyze metabolic fluxes in large networks, showing they outperform traditional EFMs and reveal new insights into carbon and nitrogen metabolism in HepG2 cells.

Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis

This study compares seven automated tools for generating draft genome-scale metabolic models (GEMs) in multicellular eukaryotes, finding no single tool consistently outperforms others.

Expanding the scope of redox-balance growth coupling techniques with a carbon cofeeding strategy

This paper introduces a carbon cofeeding strategy to overcome stoichiometric limitations in redox-balance growth coupling, enabling growth-coupled selection for biosynthetic pathways in engineered E. coli.

Conversion of CO2 into valuable products: Engineering the PirC-PGAM switch in cyanobacteria to direct carbon flux into desired products

This paper engineers the PirC-PGAM switch in cyanobacteria to redirect carbon flux toward desired products like sucrose and succinate, demonstrating a tunable control point for metabolic engineering.

Full factorial construction of synthetic microbial communities

The paper introduces a low-cost method to assemble all possible combinations of microbial strains, demonstrating it with eight Pseudomonas aeruginosa strains to identify optimal consortia.

Coarse-graining metabolic networks via feature learning reveals cross-species growth predictors

The paper identifies conserved growth predictors across bacterial species by coarse-graining metabolic networks using feature learning and validates them with experimental data.

Dynamical Systems-Constrained Metabolic Modeling Enables Forecasting of Host-Microbiome Dynamics

This paper introduces DySCoMeMo, a framework that combines dynamical systems and metabolic models to forecast microbiome-host dynamics from ecological data, achieving accurate predictions without requiring direct metabolite measurements.

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

The paper integrates thirteen fungal metabolic models into a unified framework, improves their consistency, and uses them to analyze bioenergetic differences across species.

Genome-scale metabolic model guided metabolic flux analysis in the endophyte Alternaria burnsii NCIM1409

This study uses genome-scale metabolic modeling and 13C-based pathway mapping to identify key enzymes for enhancing camptothecin production in the endophyte Alternaria burnsii.

A Differentiable dFBA Simulator for Scalable Bayesian Inference over Microbial Metabolic Models

This paper introduces a differentiable dFBA simulator for Bayesian inference over microbial metabolic models using OD600 measurements, enabling scalable analysis of fermentation data.

Acetate promotes nutritional adaptation in Escherichia coli

This paper shows acetate helps Escherichia coli adapt to nutrient changes by reducing lag time and replenishing metabolic pools.

FASTOP - Fast editing toolkit for top expression sites in yeast

The paper introduces FASTOP, a genome-editing toolkit for yeast that enables rapid and reliable modification of transcriptionally active loci to construct multi-enzymatic pathways, achieving high production of naringenin.

Relief of allosteric inhibition, redox imbalance, and transport limitations enables high-yield L-malate production in Escherichia coli

This study improves an Escherichia coli strain for high-yield L-malate production by modifying allosteric regulation, redox balance, and transport, achieving a mass yield of 1.2 g malate per gram of glucose.

Seven inducible promoters for Zymomonas mobilis

The paper characterizes seven inducible promoters in Zymomonas mobilis, identifying VanRAM-PvanCC and CinRAM-Pcin as particularly promising for use in the species.

Machine Learning Reveals Proteome-Encoded Growth Predictors of Rhodopseudomonas palustris CGA009 on Lignin Aromatics

The paper uses machine learning on proteomics data to predict growth rates of Rhodopseudomonas palustris on lignin-derived substrates and identifies proteomic features that encode growth potential across environments.