Microbial Metabolic Engineering and Bioproduction

The paper introduces Start-Stop Assembly, a modular DNA assembly method that avoids scar sequences and enables combinatorial assembly for metabolic engineering.

The paper integrates metagenomic, metatranscriptomic, and thermodynamic analyses to predict and characterize the metabolic network of an anaerobic microbiome producing medium-chain fatty acids from renewable feedstock.

The paper presents a revised human metabolic model that accurately incorporates flavin cofactors, improving predictions of metabolic impacts and biomarkers in flavoproteome-related diseases.

The paper analyzes how uncertainty in intracellular fluxes and concentrations affects kinetic models of E. coli metabolism and proposes a workflow to improve prediction reliability.

RAVEN 2.0 is a toolbox for metabolic network reconstruction, demonstrating its ability to generate accurate GEMs for Streptomyces coelicolor and improve existing models.

The paper investigates how post-translational modifications in Escherichia coli regulate metabolic adaptation to environmental changes, showing their impact on fitness and pathway usage.

The paper examines how Saccharomyces cerevisiae responds to different alcohols under aerobic and anaerobic conditions, revealing strain-specific and interaction-based transcriptomic responses.

This paper engineers Kluyveromyces marxianus to create a synthetic biology platform with enhanced traits for industrial applications.

This paper engineers a dynamic genetic circuit in Acinetobacter baylyi ADP1 to redirect carbon flow from biomass to wax ester production, improving yield and titer by over 3-fold.

The paper creates a genomically hybrid strain of Sinorhizobium meliloti by transferring a secondary replicon and characterizes its phenotypes and metabolic properties.

The paper introduces a grid-based computational method to design minimum metabolic networks for simulating metabolite production, achieving higher production rates than existing methods.

The paper develops a host-virus metabolic model to predict antiviral targets for Chikungunya, Dengue, and Zika viruses by integrating human macrophage metabolism with viral biochemical demands.

This paper engineers synthetic metabolic pathways in photosynthetic microorganisms to convert CO2 into hydrocarbon fuels, achieving up to 19-fold and 8-fold increases in alkane and alkene yields in cyanobacteria and algae, respectively.

The paper introduces flux-dependent graphs to represent metabolic networks, showing how they change under different environmental and genetic conditions.

This study uses adaptive laboratory evolution to reveal divergent transcriptomic and metabolomic adaptations in E. coli knockout strains with similar initial perturbations.

The paper shows how multiple optimal phenotypes emerge in Escherichia coli pgi knockout strains through adaptive evolution, overcoming redox and metabolite imbalances.

This paper uses retrobiosynthesis to discover and evaluate novel biosynthetic pathways for producing five MEK precursors in E. coli.

COBRAme is a software framework for building and simulating ME-models, enabling efficient reconstruction and analysis of genome-scale models of metabolism and gene expression.

The paper introduces a portable software library, libStructural, for structural analysis of reaction networks, supporting conservation analysis, flux dependency analysis, and elementary modes enumeration.

The paper introduces MetQuest, a graph-theoretic algorithm to enumerate all possible metabolic pathways between source and target molecules, demonstrating its application in biosynthesis and microbial community analysis.

This paper uses sequence-specific constraint-based modeling to estimate the performance of E. coli cell-free protein synthesis systems using limited parameters.

This paper modifies Pseudomonas putida EM42 to co-utilize disaccharides, pentoses, and hexoses by introducing genetic modules for cellobiose and xylose metabolism.

CarveMe automates the reconstruction of genome-scale metabolic models for microbial species and communities, achieving performance comparable to manual curation.

The paper proposes a spatially resolved kinetic model to explore optimal spatial organization strategies for biosynthetic pathways and finds that different pathways require distinct strategies based on kinetic and biophysical factors.

The paper develops a synthetic selection system in yeast to enrich for high-producing muconic acid variants by coupling production to cell fitness through a pH-tunable sensor-selector.

PartsGenie is a tool for designing and sharing synthetic biology parts, integrating optimization, data standards, and repository access.

The paper uses EFCM to show growth rate/yield trade-offs in E. coli depend on metabolic kinetics and environmental conditions, with oxygen limitation favoring faster but less efficient growth.

The paper introduces ssbio, a Python framework for integrating structural biology data into genome-scale systems biology workflows.

Selenzyme is an online tool that helps select enzymes for metabolic pathway design by analyzing sequence, reaction, and organism-related data.

The paper introduces PMFA, a method combining PCA and stoichiometric flux analysis for metabolic flux mode analysis, showing its versatility through experiments.