Biology subjects

Gonzalez-Cabaleiro, R.

Publications and source records attributed to Gonzalez-Cabaleiro, R..

4 recordsLinked to original sources

bioRxiv2026

Comprehensive calculation of product and ATP yields for glucose fermentation

Lignocellulose sugars are degraded anaerobically by microbial communities as part of the carbon cycle, yielding short- and medium-chain fatty acids as intermediates and carbon dioxide and methane as final products. The underlying metabolic network is branched and its product yields depend on environmental conditions. We compiled a pan-catabolic network of the anaerobic digestion of glucose into 11 fermentation products, including alcohols, acids, and ketones. It consists of 75 reactions and incorporates energy conservation via substrate-level phosphorylation and transport-coupled phosphorylation, with ferredoxin, NADH, and quinol as electron carriers. We calculated all net conversions of glucose into fermentation products and their ATP yields. We find 195,629 unique conversions (about 50% with non-zero ATP yield), including known and many novel ones. Conversions with identical product stoichiometry can differ in ATP yield: glucose to propionate and acetate is achieved by different subnetworks with 23 distinct ATP/glucose yields, and even glucose to lactate shows 12 yields ranging from 0 to 4.5. The driving force of the conversions decreases with ATP yield, whereas the number of reactions used does not correlate with it. The known catabolic conversions underlying anaerobic digestion might thus be only the tip of the iceberg.

systems biology↗

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↗

bioRxiv2019

NUFEB: A Massively Parallel Simulator for Individual-based Modelling of Microbial Communities

We present NUFEB, a flexible, efficient, and open source software for simulating the 3D dynamics of microbial communities. The tool is based on the Individual-based Modelling (IbM) approach, where microbes are represented as discrete units and their behaviour changes over time due to a variety of processes. This approach allows us to study population behaviours that emerge from the interaction between individuals and their environment. NUFEB is built on top of the classical molecular dynamics simulator LAMMPS, which we extended with IbM features. A wide range of biological, physical and chemical processes are implemented to explicitly model microbial systems. NUFEB is fully parallelised and allows for the simulation of large numbers of microbes (107 individuals and beyond). The parallelisation is based on a domain decomposition scheme that divides the domain into multiple sub-domains which are distributed to different processors. NUFEB also offers a collection of post-processing routines for the visualisation and analysis of simulation output. In this article, we give an overview of NUFEBs functionalities and implementation details. We provide examples that illustrate the type of microbial systems NUFEB can be used to model and simulate.\n\nAuthor summaryIndividual-based Models (IbM) are one of the most promising frameworks to study microbial communities, as they can explicitly describe the behaviour of each cell. The development of a general-purpose IbM solver should focus on efficiency and flexibility due to the unique characteristics of microbial systems. However, available tools for these purposes present significant limitations. Most of them only facilitate serial computing for single simulation, or only focus on biological processes, but do not model mechanical and chemical processes in detail. In this work, we introduce the IbM solver NUFEB that addresses these shortcoming. The tool facilitates the modelling of much needed biological, chemical, physical and individual microbes in detail, and offers the flexibility of model extension and customisation. NUFEB is also fully parallelised and allows for the simulation of large complex microbial system. In this paper, we first give an overview of NUFEBs functionalities and implementation details. Then, we use NUFEB to model and simulate a biofilm system with fluid dynamics, and a large and complex biofilm system with multiple microbial functional groups and multiple nutrients.\n\nThis is a PLOS Computational Biology Software paper.

microbiology↗