Biology subjects

Remeijer, M.

Publications and source records attributed to Remeijer, M..

3 recordsLinked to original sources

bioRxiv2026

Net conversion calculations of catabolic pathways

Motivation: The stoichiometry (or net conversion) of a catabolic pathway is an often used principle of biochemistry. It expresses the molar yield of charged energy carriers (e.g. ATP) and catabolic products (e.g. lactate) on the energy source (e.g. glucose). Product yields are engineering targets of metabolic engineering and used in microbial ecology to assess energy metabolisms of microbial species. For a single species under a single condition, the catabolic pathway is frequently assumed fixed, while there might be multiple options encoded in its genome. To find these options, the manual (heuristic) methods that have been used for decades fall short. Results: In this paper, we explain how net conversions can be calculated from reaction stoichiometries of a metabolic network and evaluated using thermodynamic information. We start with an (old) heuristic method. Next, we explain we relate the net conversions of metabolic networks to their elementary flux modes (EFMs) and show that a single EFM gives rise to a single net conversion. EFMs are mathematical objects that are computable with existing software. We use these to illustrate how all net conversions of complex (pan-)metabolic networks can be computed. We consider examples from aerobic and anaerobic microbiology. Then, we introduce the parameter {Omega}, the driving force per unit flux, which allows for the thermodynamic comparison of pathways. To calculate {Omega}, only the standard Gibbs free energy potential, i.e., {Delta} G m' of the net conversion and its corresponding EFM are required. A generic workflow (and all underlying Python code) are provided, as well as applications to perform the workflow without coding. We also provide those software packages that automate our methods. Impact: This paper serves as an illustration of how modern computational systems biology can be used to automate the calculation of net conversions in microbial ecology and metabolic engineering. We hope that this paper inspires future metabolism research using quantitative, rigorous methods.

systems biology↗

bioRxiv2025

Entangled stoichiometric objectives shape microbial catabolism

The search for fundamental relationships between energetic and biosynthetic parameters of catabolism and anabolism is a major goal in microbiology. This is complicated by the fact that ATP synthesis is required for some anabolic precursors, all building blocks, and their polymerization into macromolecules, while the synthesis of other anabolic precursors and catabolic products yields ATP. Yield parameters were classically predicted from approximate phenomenological relations between catabolic and anabolic stoichiometry. Here we compare the catabolisms of a diverse set of microbial species across conditions using genome-scale stoichiometric models. We focus on states of maximal energetic efficiency (maximal yield of biomass of the energy source) and present an unbiased method for calculating stoichiometric relations between catabolism and anabolism. We find that synthesis of charged energy-carriers and anabolic precursors by catabolism is strongly intertwined. Catabolic intermediates and reactions vary greatly, due to variation in the energy and carbon source for growth. We find that the ATP requirement for 1 gram biomass varies between 72.8 and 246.1 moles, precursor sets vary between 4 and 14 in size, and acetyl-CoA is the only common precursor across species. We conclude that the complex interplay between precursor synthesis and energy conservation of heterotrophic catabolism results from an optimal compromise between conflicting objectives. The state of maximal energetic efficiency is reached by minimizing the carbon source lost during energy catabolism due to catabolic-product formation. This choice is influenced by the need for an optimal precursor set that compromises between maximal ATP production during its formation from the carbon source and minimal ATP consumption when it is converted into building blocks. We find that the associated optimal catabolic pathways are diverse across species and conditions.

systems biology↗

bioRxiv2024

Thermodynamics of unicellular life: Entropy production rate as function of the balanced growth rate

AO_SCPLOWBSTRACTC_SCPLOWIn isothermal chemical reaction networks, reaction rates depend solely on the reactant concentrations setting their thermodynamic driving force. Living cells can, in addition, alter reaction rates in their enzyme-catalysed networks by changing enzyme concentrations. This gives them control over their metabolic activities, as function of conditions. Thermodynamics dictates that the steady-state entropy production rate (EPR) of an isothermal chemical reaction network rises with its reaction rates. Here we ask whether microbial cells that change their metabolism as function of growth rate can break this relation by shifting to a metabolism with a lower thermodynamic driving force at faster growth. We address this problem by focussing on balanced microbial growth in chemostats. Since the driving force can then be determined and the growth rate can be set, chemostats allow for the calculation of the (specific) EPR. First we prove that the EPR of a steady-state chemical reaction network rises with its driving force. Next, we study an example metabolic network with enzyme-catalysed reactions to illustrate that maximisation of specific flux can indeed lead to selection of a pathway with a lower driving force. Following this idea, we investigate microbes that change their metabolic network responsible for catabolism from an energetically-efficient mode to a less efficient mode as function of their growth rate. This happens for instance during a shift from complete degradation of glucose at slow growth to partial degradation at fast growth. If partial degradation liberates less free energy, fast growth can occur at a reduced driving force and possibly a reduced EPR. We analyse these metabolic shifts using three models for chemostat cultivation of the yeast Saccharomyces cerevisiae that are calibrated with experimental data. We also derive a criterion to predict when EPR drops after a metabolic switch that generalises to other organisms. Both analyses gave however inconclusive results, as current experimental evidence proved insufficient. We indicate which experiments are required to get a better understanding of the behaviour of the EPR during metabolic shifts in unicellular organisms.

systems biology↗