Εlad Noor

The paper updates the ModelSEED Biochemistry Database with expanded compounds and reactions, integrating multi-source thermodynamic data and grading reaction reliability.

This paper develops a microbial platform to study Rubisco oxygenase activity in vivo by linking it to bacterial growth, enabling genetic screening and evolution of enzyme variants.

The paper introduces a framework to quantify dynamic parameters of cellular metabolism using metabolic age, applied to yeast proteins under different growth conditions.

Zaremba et al. characterize Vsb1 as the main yeast vacuolar lysine importer and Ypq1/2 as bidirectional vacuolar transporters of lysine and arginine. Their study highlights the role of vacuolar transporters in regulating cationic amino acid homeostasis under fluctuating nutrient availability.

The paper characterizes over 250 Rubisco variants from bacteria and archaea, showing they rarely exceed 30 reactions per second at 30°C and predicting rates for all sequenced variants using machine learning.

This paper presents a computational workflow for designing and testing E. coli metabolic sensors that detect glyoxylate and glycolate across a wide concentration range, with applications in bioengineering and environmental monitoring.

This study characterizes the kinetic properties of over 100 bacterial form I rubiscos to identify factors influencing carboxylation rates, finding that carboxysomes and cyanobacterial origins are associated with faster rates.

The paper derives analytic solutions for optimizing enzyme allocation in unbranched metabolic pathways using convex optimization and applies the results to bacterial growth.

This study demonstrates the production of bioplastic PHB in engineered E. coli using CO2 and formate via the reductive glycine pathway, showing potential for electro-bioproduction.

The paper estimates the fraction of DNA from dying cells that becomes detectable in plasma, finding less than 10% of DNA from dying cells is detectable, with ratios varying widely among cell types.

This study identifies three genetic mutations enabling E. coli to grow autotrophically when combined with non-native enzymes for carbon fixation and energy production.

The paper develops a mathematical framework to show co-substrate cycling imposes flux limits in metabolic pathways and demonstrates this using simulations and existing metabolic data.

This study identifies alternative glycolytic pathways in E. coli that bypass canonical EMP glycolysis, showing that the serine shunt is selected for in adaptive evolution.

The paper introduces a method to estimate in-vivo metabolic kinetic constants and metabolite concentrations from omics data by solving a convex optimization problem.

The paper introduces multiTFA, a Python package that improves thermodynamic-based flux analysis by incorporating multivariate treatment of thermodynamic variables, reducing uncertainty in reaction Gibbs free energy ranges.

The paper compares the thermodynamic properties of biological and non-biological compounds in redox chemical space, finding metabolites have lower Gibbs energies and specific functional group enrichments.

This study identifies a new carbon fixation pathway in E. coli using only native enzymes and demonstrates its in vivo feasibility through genetic engineering.

The paper demonstrates that a bacterial CO2 concentrating mechanism enables E. coli to fix CO2 from ambient air using 20 CCM genes.

The paper introduces the ModelSEED biochemistry database, which integrates metabolic annotations and supports the reconstruction and analysis of metabolic models for plants, fungi, and microbes.

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 shows that autocatalytic cycles in E. coli central carbon metabolism require specific enzyme expression and substrate affinity constraints to maintain stable fluxes.