Microbial Metabolic Engineering and Bioproduction

This study investigates how modifying central carbon metabolism in Yarrowia lipolytica affects beta-carotene production, finding that most metabolic bypasses reduce production efficiency.

This paper introduces a new method for genome-scale metabolic flux inference using conserved moieties, demonstrating its computational efficiency and accuracy with isotopic labeling data.

This study evolves Escherichia coli to improve acetate metabolism but finds that some mutations reduce growth on glucose, highlighting potential trade-offs in complex feedstocks.

This paper develops a dual-inducible genetic control system for multistep biosynthetic pathways in microbial chassis, showing improved regulation and biosynthesis of target compounds.

The paper identifies hidden metabolic mutations in Klebsiella pneumoniae cultures grown in rich media, showing how these mutations can persist undetected and affect auxotrophy.

This study enhances malonyl-CoA availability in Pseudomonas putida through multi-level optimization, achieving a 5.8-fold increase in phloroglucinol production.

This study constructs a synthetic microbial consortium of Pseudomonas putida strains for lignocellulosic disaccharide processing using reciprocal substrate processing and demonstrates how extrinsic factors can optimize growth.

This study improves lipid production in Cutaneotrichosporon oleaginosus through genetic modifications and fermentation optimization, achieving high lipid content and productivity.

The paper uses a PYR1 biosensor-driven CRISPR screen in Kluyveromyces marxianus to identify gene knockouts that enhance geraniol production by up to 2-fold.

The paper develops a computational framework to model ATP allocation during viral infection, revealing new metabolic pathways and resource competition dynamics between host and virus.

This paper introduces DNNGIOR, a deep learning method to improve genome-scale metabolic models of incomplete genomes by imputing missing reactions based on reaction frequency and phylogenetic distance.

The paper uses a language model to design cis-regulatory elements for prokaryotes without experimental data, achieving high success rates in gene expression and promoter activity.

MitoMAMMAL predicts cardiac and BAT metabolism in mouse and human by integrating proteomic and transcriptomic data with a genome-scale mitochondrial metabolic model.

This study engineers Acinetobacter baylyi ADP1 to produce naringenin by modifying its metabolism and introducing plant-derived enzymes, achieving 66 mg/L in fed-batch cultures.

The paper presents methods to improve electroporation efficiency in non-model bacteria using Cupriavidus necator H16 as a test case.

This paper introduces a chaotrope-based method for in vitro assembly of bacterial microcompartment shells, enabling controlled encapsulation of cargo and expanding design possibilities.

This paper develops a CRISPR activation system for Synechocystis sp. PCC 6803 to upregulate genes and improve biofuel production.

This paper develops a genetic toolbox for Xanthobacter autotrophicus to enable metabolic engineering and bioremediation applications.

ENKIE predicts KM and kcat enzyme kinetic parameters and their uncertainties using Bayesian Multilevel Models, achieving performance comparable to deep learning methods.

This paper uses dynamic control flux-balance analysis to optimize 2,3-butanediol production in E. coli, achieving high titer and productivity through simulation and experimental validation.

The paper introduces ISIS, a method to identify switch metabolites in metabolic networks, showing their role in flux reorientation and cellular regulation across different organisms.

This study uses variational autoencoders to generate minimal E. coli genomes, finding 6 out of 100 sampled genomes were viable in a computational model.

The paper develops a cell-type-specific genome-scale metabolic model of human colonic epithelial cells to identify metabolic signatures associated with inflammatory bowel disease.

This study engineers Saccharomyces cerevisiae to produce punicic acid-rich biomass, achieving 26.7% PuA in total fatty acids.

The paper updates GapMind to include novel enzymes for amino acid biosynthesis, reducing pathway gaps in prokaryotes from 1.4 to 0.7 per genome.

This paper introduces a new constraint-based model to predict metabolic flux dynamics in fluctuating environments by integrating metabolism, resource allocation, and gene regulation.

The paper analyzes metabolite exchanges in microbial metabolic models using pathway definitions, revealing a hierarchy among exchanges and consistent frequency patterns across methods.

The paper develops a method to measure enzymatic parameters in vivo using synthetic biology tools and applies it to study carotenoid pathway enzymes in yeast.

The paper introduces FROG analysis to standardize reproducibility assessments of genome-scale metabolic models, resulting in full reproducibility of all tested models.

This paper develops a genome-scale metabolic model for A. baumannii to identify antimicrobial targets and validate its predictive capabilities using experimental data.