Microbial Metabolic Engineering and Bioproduction

This study investigates a synthetic microbial consortium to enhance heterologous protein production, finding that productivity increases but yield decreases due to resource allocation trade-offs.

This paper demonstrates the use of reinforcement learning to control microbial co-cultures in bioreactors, showing improved performance over traditional methods.

The paper develops a software package for selecting metabolic models using isotopologue data from SIRM experiments, demonstrating its effectiveness with UDP-GlcNAc datasets.

The paper improves genome engineering methods for Acinetobacter baylyi ADP1, achieving genome streamlining through targeted deletions and CRISPR-based validation.

This study shows that Escherichia coli uses metabolite sequestration to rapidly recover from fatty acid depletion by releasing a transcriptional regulator.

The paper shows that different imaging techniques produce varying apparent sizes and morphologies of bacterial microcompartments from Salmonella enterica serovar Typhimurium LT2, and provides guidelines for sample preparation.

This paper develops genetic tools for Acinetobacter baylyi ADP1 to enhance its use in sustainable chemical manufacturing and lignin bioprocessing.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

The paper develops large-scale kinetic models of Pseudomonas putida to predict metabolic responses and design metabolic engineering strategies for improved biofuel and biochemical production.

The paper introduces a multi-objective optimization framework for metabolic engineering to identify genetic manipulations that improve bioproductivity in yeast.

The paper develops a theory to describe all possible molecular states of cellular self-fabrication, identifying Elementary Growth Modes as the fundamental building blocks of cellular phenotype.

The paper evaluates an optimized gene expression architecture in Pseudomonas taiwanensis to enhance protein abundance through mRNA stability and translation efficiency, showing improved performance over traditional methods.

GEMtractor is a tool to extract subnetworks from genome-scale metabolic models encoded in SBML, allowing focused analysis on reaction- and enzyme-centric views.

The paper infers new biochemical reactions and metabolite structures in Chondrus crispus, revealing metabolic pathway drift despite conserved phenotypes.

The paper integrates genome-scale metabolic modeling with transcriptomics and exometabolomics to predict bacterial metabolic responses and validate them experimentally in Pseudomonas veronii.

The paper develops a computational framework to quantify metabolic interactions in microbial co-cultures using a new index and experimental validation.

This paper develops modular plasmids for cell-free expression and genetic assembly in Clostridium to accelerate biosynthetic pathway testing.

The paper develops a genome-scale metabolic model of a co-culture of Clostridium autoethanogenum and Clostridium kluyveri to optimize syngas conversion to medium-chain fatty acids.

The paper develops a machine learning approach to guide curation of metabolic models by identifying structural variants that improve predictiveness across bacterial species.

The paper develops a highly sensitive biosensor for caprolactam and valerolactam from Pseudomonas putida, capable of detecting product titers above background at ~6 g/L.

This paper introduces a reinforcement learning approach for bio-retrosynthesis to design metabolic pathways, validated on curated datasets and with media supplement suggestions.

This study develops a dynamic model of E. coli cell-free protein synthesis, showing that oxidative phosphorylation, glycolysis, and amino acid biosynthesis are key for productivity.

This study uses genome-scale metabolic models to classify 36 bifidobacterial strains into three groups based on their metabolic capabilities and identifies strain-specific short chain fatty acid production.

The paper develops a synthetic biosensor to measure glycolytic flux in single yeast cells using fluorescence microscopy to identify metabolic subpopulations.

The paper shows that overflow metabolism arises from two growth-limiting constraints across different metabolic models.

The paper uses mathematical characterization and flux balance analysis to identify key metabolites and enzymes in Leishmania's metabolic network, highlighting GLOI as a potential therapeutic target.

The paper identifies common issues in how gene-protein-reaction (GPR) rules and gene expression data are handled in context-specific metabolic models and evaluates their impact on gene essentiality analysis.

The paper presents a genome-scale metabolic model for Kluyveromyces marxianus, iSM996, which predicts carbon source utilization and growth under different temperatures.

This paper describes the construction of a dual metabolic pathway in E. coli to produce hydroxytyrosol from glucose, achieving 1.76 mM HT concentration.