Biology subjects

Odendaal, C.

Publications and source records attributed to Odendaal, C..

4 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↗

bioRxiv2026

Clostridial acidogenesis product profiles are discontinuous: a thermodynamic hypothesis

At neutral pH, Clostridial fermentative catabolism is typically acidogenic, with a product profile dominated by acetate and butyrate. H2 acts as a terminal electron acceptor via hydrogenases, which increases ATP-producing potential from glucose. Acetate production is characterised by both higher ATP and H2 yields, rendering it desirable but more thermodynamically limited. For this reason, is commonly understood that Clostridia can adjust the ratio of acetate to butyrate (Ace:But) produced to maximise ATP while maintaining sufficient pathway driving forces to sustain a high flux. We identify three redox-balanced product profiles that underlie the spectrum of Clostridial catabolic Ace:But ratios: Homoacetic (Ace:But = 2:0), Equimolar (0.67:0.67), and Homobutyric (0:1). To reach Ace:But ratios intermediate to these, the elementary flux modes (EFMs) underlying the aforementioned product profiles must be blended. We performed a maximum-minimum driving force (MDF) analysis to test the thermodynamic favourability of the pathways underlying different Ace:But ratios at varying H2 partial pressures (pH2). We find that blended EFMs are less efficient than their constituent EFMs at all pH2, allocating excessive driving force (DF) to certain reactions, thereby lowering the DF of others. This is, in part, due to the co-occurrence of hydrogenases with different optimal redox carrier ratios. One hydrogenase inevitably has very high DF, which decreases the DF available for other reactions. This leads to a lower minimum DF and a higher enzyme cost for operating blended EFMs. This implies that certain discrete Ace:But ratios are most favourable for large ranges of pH2, contradicting the continuity assumption in literature.

systems biology↗

bioRxiv2026

Ensemble kinetic modelling links residual enzyme activity to clinical symptoms in mitochondrial β-oxidation defects

The mitochondrial fatty acid {beta}-oxidation (mFAO) is an important source of energy when carbohydrate stores are depleted. It is also involved in many diseases, including inherited fatty-acid oxidation deficiencies (mFAODs). Patients with the same genetic variant often present with clinically heterogeneous phenotypes, but the mechanisms contributing to this heterogeneity are poorly understood. To investigate the underlying pathophysiology of different mFAODs, we constructed a computational model of mFAO in human liver, based on experimentally determined enzyme kinetics. A recognised, but seldom addressed challenge in metabolic modelling is the substantial uncertainty about kinetic parameter values. Whereas experimental values of some mFAO parameters are quite reproducible, others vary by up to four orders of magnitude between different reports. To address this, we generated an ensemble of kinetic models, each with the same reaction stoichiometry and rate equations, but different kinetic parameters, sampled from distributions of literature-derived values. We also comprehensively report these values and the arguments based on which they were evaluated. The resulting models were validated against available flux data, yielding a final ensemble of 51 valid models. These models recapitulate recent findings about the accumulation of medium-chain acyl-CoAs and the concomitant depletion of free CoA (CoASH) in medium-chain acyl-CoA dehydrogenase deficiency. We applied the ensemble to a set of known mFAODs, separating them into long-chain (LC-) and short-/medium-chain (S/MC-)mFAODs. The residual activity at which clinical symptoms are known to occur corresponded well with the residual activity in the model at which pathway flux was significantly decreased in LC-mFAODs. Residual activity in S/MC-mFAODs correlated less strongly with pathway flux, but these deficiencies did show a combined flux- and CoASH-reduction effect. This comparison is of importance to researchers and clinicians, as it identifies possible ways in which insights about one mFAOD may be applied to another based on shared biochemical properties. Author SummaryWhen building computer models of metabolic pathways, it is typical to take the "best" experimental data and use that as input into the model. However, especially when working with human cells, ethical and practical constraints often mean that even the "best" experimental data is still subject to substantial uncertainty. We explicitly modelled the uncertainty about the inner workings of fat burning (fatty acid oxidation). The resulting model is known as an "ensemble". The ensemble predicts ranges instead of single outcomes, allowing us to assess the confidence level of our predictions. We assess a set of inherited diseases - enzyme deficiencies - simulating them at different levels of severity with the ensemble. We find that the model does a good job of predicting the severity of the deficiencies at which symptoms will occur. It also allows us to identify a key difference between two subgroups within this group of deficiencies: long-chain and medium-/short-chain, depending on the size of the fats being metabolised. The long-chain variant is predicted to correlate most straightforwardly with the severity of the deficiencies, due to its effect on energy generation. Medium-/short-chain deficiencies, in contrast, have more complex consequences.

systems biology↗

bioRxiv2024

SLAM-seq reveals independent contributions of RNA processing and stability to gene expression in African trypanosomes

Gene expression is a multi-step process that converts DNA-encoded information into proteins, involving RNA transcription, maturation, degradation, and translation. While transcriptional control is a major regulator of protein levels, the role of post-transcriptional processes such as RNA processing and degradation is less well understood due to the challenge of measuring their contributions individually. To address this challenge, we investigated the control of gene expression in Trypanosoma brucei, a unicellular parasite assumed to lack transcriptional control. Instead, mRNA levels in T. brucei are controlled by post-transcriptional processes, which enabled us to disentangle the contribution of both processes to total mRNA levels. In this study, we developed an efficient metabolic RNA labeling approach and combined ultra-short metabolic labeling with transient transcriptome sequencing (TT-seq) to confirm the long-standing assumption that RNA polymerase II transcription is unregulated in T. brucei. In addition, we established thiol (SH)-linked alkylation for metabolic sequencing of RNA (SLAM-seq) to globally quantify RNA processing rates and half-lives. Our data, combined with scRNA-seq data, indicate that RNA processing and stability independently affect total mRNA levels and contribute to the variability seen between individual cells in African trypanosomes.

molecular biology↗