Microbial Metabolic Engineering and Bioproduction

The paper introduces the Serine Shunt as a novel formate reduction pathway in E. coli, demonstrating its in vivo activity and efficiency for converting formate to formaldehyde.

This paper develops an in vitro transcription-based biosensing workflow to quantify glycolate production in the CETCH cycle, showing high correlation with LC-MS at lower cost and faster speed.

This paper engineers Corynebacterium glutamicum to produce 2,3,5,6-tetramethylpyrazine (TMP) at high titer using statistical design of experiments to optimize media composition.

This study evaluates the feasibility of expanding the product range of chain elongating bacteria to produce C9-C12 fatty acids and other derivatives using metabolic engineering and constraint-based modelling.

The paper uses Bayesian 13C-metabolic flux analysis to show phagocytosis reverses non-oxidative PPP flux direction in granulocytes.

This study uses in vitro and in silico experiments to model Drosophila larval development and metabolism, predicting growth and critical developmental processes.

This study calculates the efficiency of electromicrobial production of jet fuel blends containing branched-chain hydrocarbons and finds that increasing branched-chain content slightly reduces energy conversion efficiency.

The paper uses transposon sequencing data to characterize AraC/XylS family regulators in Pseudomonas putida, identifying inducer responses and improving inducible systems in E. coli.

md_harmonize harmonizes compounds and metabolic reactions across databases by generating unique identifiers based on atom structures for improved metabolic network analysis.

This paper engineers a synthetic E. coli coculture to compartmentalize sugar utilization and ester biosynthesis pathways, achieving 31-fold higher isobutyl butyrate production than monocultures.

Sysrecon is a tool that systematically breaks down genome-scale metabolic reconstructions into quantifiable steps to improve reproducibility and standardization.

The paper identifies a native phosphoglycolate salvage pathway in Komagataella phaffii that recycles 2-phosphoglycolate, similar to plant pathways, and suggests it can enhance autotrophic growth.

This paper improves metabolic interaction network inference by incorporating enzyme fluctuation data into an inverse differential Jacobian algorithm, showing better performance in breast cancer datasets.

Yeast9 improves yeast metabolic modeling by integrating multi-omics data, showing better prediction of growth rates and gene function than transcriptomics.

The paper presents strategies to split microbial metabolic equations into anabolic and catabolic components and evaluates their thermodynamic efficiency.

The paper calculates the upper limit electrical-to-energy conversion efficiency for producing jet fuels using electromicrobial pathways.

This study identifies novel transcriptional responses to protein production stress in E. coli using transcriptomic analytics and applies findings to optimize protein production.

This study engineers Saccharomyces cerevisiae to produce 3-hydroxypropionic acid and succinic acid from glucose-rich lignocellulosic wood hydrolysates under low pH conditions, increasing production titers significantly.

The paper uses genome-scale metabolic models to identify metabolic differences between non-Saccharomyces yeasts, finding that Complex I in the electron transport chain distinguishes Metschnikowia pulcherrima from other species.

OptEnvelope identifies optimal knockout strategies for coupling growth and metabolite production using mixed-integer linear programming, benchmarked on E. coli and S. cerevisiae for acetate, glycerol, succinate, and ethanol.

The paper maps enzyme activation networks in yeast, revealing widespread regulatory crosstalk between metabolic pathways and highlighting the role of essential metabolites in metabolic plasticity.

This paper evolves a Saccharomyces cerevisiae strain tolerant to oxidative stress, leading to higher taxadiene production, and identifies metabolic changes contributing to this improvement.

The paper uses computational models to show that optimal metabolite exchange intensities in bacterial cross-feeding communities depend on glucose availability and shared metabolite access, enhancing community fitness.

The paper presents a framework using genome-scale metabolic reconstructions to interpret genotype-to-phenotype associations and identifies limitations in phenotype prediction in metabolism.

This paper introduces ML-Flux, a deep learning framework for accurately and rapidly determining metabolic flux from isotope patterns, outperforming existing methods in speed and accuracy.

This paper develops and optimizes a mevalonate-based monoterpene production platform in Corynebacterium glutamicum, achieving high titers of several monoterpenes.

This study identifies how Yarrowia lipolytica metabolizes hydrocarbons and DP oil, revealing proteome reallocation for growth and chemical production, but also growth inhibition due to reduced protein biosynthesis.

The paper develops a genome-scale metabolic model for S. pastorianus to predict metabolic pathway evolution and aid industrial strain optimization.

This paper creates and validates five strain-specific genome-scale metabolic models for Corynebacterium striatum using in silico and in vitro methods, and introduces software for model curation.

This study develops and validates the first genome-scale metabolic model of Brucella abortus 2308, iBP932, to predict gene essentiality and potential drug targets.