Jens Nielsen

Universal principles of protein resource allocation among cellular organelles revealed by yeast large-scale absolute quantitative proteomics

This study uses yeast large-scale absolute quantitative proteomics to reveal universal principles of protein resource allocation among cellular organelles and its relationship to physiological parameters and species divergence.

AlphaGEM Enables Precise Genome-Scale Metabolic Modelling by Integrating Protein Structure Alignment with deep-learning-based Dark Metabolism Mining

AlphaGEM constructs genome-scale metabolic models using structural alignment and deep learning, improving accuracy over existing methods for diverse species.

Biosynthesis of bisbenzylisoquinoline alkaloids

This study identifies the enzymatic pathway for bisbenzylisoquinoline alkaloid biosynthesis and reveals a non-canonical redox-mediated mechanism for stereochemical control.

Leveraging large language models for metabolic engineering design

This paper develops a large language model-based method to extract metabolic engineering strategies from research articles and trains a hybrid model to predict engineering targets, outperforming traditional approaches.

Model-Driven Elucidation of Lactose and Galactose Metabolism via Oxidoreductive Pathway in Sungouiella intermedia for Cell Factory Applications

This paper investigates lactose and galactose metabolism in Sungouiella intermedia using a genome-scale metabolic model and experimental data to identify its potential as a cell factory for producing galactitol and tagatose from industrial side-streams.

Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming

This study characterizes the genomic and metabolic adaptations of Saccharomyces cerevisiae across diverse niches using pan-genome and metabolic modeling.

The Role of Metabolism in Shaping Enzyme Structures Over 400 Million Years of Evolution

This study uses AlphaFold2 to analyze how metabolism influenced enzyme structural evolution across 400 million years by examining 11,269 enzyme structures and their metabolic reactions.

The Molecular Landscape of Cellular Metal Ion Biology

The paper quantifies yeast cell responses to varying metal ions, revealing widespread proteomic and genetic impacts and common metal responsiveness properties.

Extensively acquired antimicrobial resistant bacteria restructure the individual microbial community in post-antibiotic conditions

The paper identifies two types of antimicrobial resistant bacteria in the gut microbiome after antibiotic treatment and shows how one type persists and reshapes the microbial community.

Brown Bears activates a Satiety Hormone Cholecystokinin (CCK) pathway in adipose tissue during hibernation

This study identifies a seasonal regulation of satiety-related genes and proteins in brown bear adipose tissue during hibernation, suggesting a local mechanism for energy management and satiety.

FROG Analysis Ensures the Reproducibility of Genome Scale Metabolic Models

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

Yeast-MetaTwin for Systematically Exploring Yeast Metabolism through Retrobiosynthesis and Deep Learning

The paper develops Yeast-MetaTwin, a metabolic model for yeast that expands coverage of the metabolome using retrobiosynthesis and deep learning, revealing new insights into underground metabolism.

Brain energy metabolism is optimized to minimize the cost of enzyme synthesis and transport

The paper uses metabolic models to show brain energy metabolism minimizes enzyme synthesis and transport costs, supporting the astrocyte-neuron lactate shuttle theory.

Yeast9: A Consensus Yeast Metabolic Model Enables Quantitative Analysis of Cellular Metabolism By Incorporating Big Data

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

Standard-GEM supports reproducible development of genome-scale metabolic models

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data

The paper develops methods to generate context-specific genome-scale metabolic models from single-cell RNA-Seq data and shows that cell subtypes have unique metabolic profiles.

Computational biology predicts metabolic engineering targets for increased production of 102 valuable chemicals in yeast

The paper presents a computational pipeline to predict gene engineering targets for increased production of 102 chemicals in yeast using enzyme-constrained models.

Learning deep representations of enzyme thermal adaptation

The paper trains a deep learning model to predict enzyme thermal adaptation using a dataset of enzymes labeled with optimal growth temperatures.

Integrative functional analysis uncovers metabolic differences between Candida species

The paper identifies metabolic differences between Candida species using genomic, metabolomic, and gene expression data, highlighting unique pathways in the AGAu cluster.

Supervised generative design of regulatory DNA forgene expression control

This paper introduces ExpressionGAN, a deep learning model that generates functional regulatory DNA with specified expression levels, outperforming random mutagenesis approaches.

Discovery of therapeutic agents targeting PKLR for NAFLD using drug repositioning

This study identifies PKLR as a therapeutic target for NAFLD and validates two drug candidates through in vitro and in vivo experiments.

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

The paper upgrades the GECKO method to create enzyme-constrained models for yeast and human, revealing common metabolic adaptations under stress.

Fine-tuning of coumaric acid synthesis to increase naringenin production in yeast

This study improves (2S)-naringenin production in yeast by fine-tuning p-coumaric acid synthesis, reducing its extracellular accumulation and increasing yield to 933 mg/L.

Deep learning based kcat prediction enables improved enzyme constrained model reconstruction

A substrate graph neural network plus protein-sequence CNN predicts enzyme kcat (test Pearson r 0.71), tracks mutation effects, and parameterizes enzyme-constrained models for 343 yeast/fungi species.

Transcriptome analysis of EPO and GFP HEK293 Cell-lines Reveal Shifts in Energy and ER Capacity Support Improved Erythropoietin Production in HEK293F Cells

The paper compares transcriptomic profiles of HEK293 cell lines producing erythropoietin or GFP to identify factors associated with improved erythropoietin production.

Genome scale modeling of the protein secretory pathway reveals novel targets for improved recombinant protein production in yeast

The paper develops a genome-scale model of the yeast protein secretory pathway to identify targets for improving recombinant protein production, finding that the secretory pathway has more limited capacity than metabolism.

Systems analysis of metabolic responses to a mixed meal test in an obese cohort reveals links between tissue metabolism and the gut microbiota

The paper analyzes metabolic responses to a mixed meal test in an obese cohort, linking tissue metabolism with gut microbiota changes and identifying potential biomarkers for T2DM.

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies

The paper develops a whole-cell metabolic model for yeast to predict compartment-specific proteome constraints that explain metabolic strategies under different growth conditions.

Non-random organization of flux control mechanisms in yeast central metabolic pathways

The paper investigates the non-random organization of flux control mechanisms in yeast metabolic pathways, identifying distinct regulatory strategies across different pathways.

A network-based approach reveals the dysregulated transcriptional regulation in non-alcohol fatty liver disease

This study identifies dysregulated transcriptional regulators in NAFLD using network analysis and integrates transcriptomic data with metabolic models.