Biology subjects

Bruggeman, F.

Publications and source records attributed to Bruggeman, F..

12 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

Flux balance analysis of microbial communities from metabolic strategies: composition, cross-feeding and ecological service

Microorganisms interact through the exchange of metabolites and competition for shared substrates, and this metabolic coupling shapes the composition and function of microbial communities. Community flux balance analysis (cFBA) can predict such behaviour - the maximum community growth rate, the metabolic fluxes and the relative abundances of the species - from stoichiometric models of their metabolism, but existing formulations are either complex and hard to scale as communities grow or cannot predict optimal growth rates. Here we present a physiology-based formulation of cFBA in which each species' metabolism is reduced to a few macrochemical equations, one for each 'metabolic mode' the species can use, and the whole community is then solved as a single linear program. From this, the method predicts the optimal composition of the community, its maximum growth rate, the metabolites exchanged between the species, and the net conversion the community carries out as a whole; its ecological service. This reduction makes it far simpler to build and solve models of larger communities. We illustrate the approach on a two-species synergistic community that can be verified by hand, apply it to a five-member anaerobic digestion community, and use it to predict the metabolic interactions of a genome-scale syngas-fermenting coculture. Characterising these communities at their optimal steady states, we show that each species is driven to a distinct metabolic strategy. We discuss the method both as a practical tool for larger microbial communities and as a means of uncovering the ecological principles that govern them.

systems biology↗

bioRxiv2025

On the conditions for shifts in metabolic strategies

AO_SCPLOWBSTRACTC_SCPLOWMany heterotrophic microorganisms gradually replace an energetically-efficient mode of metabolism by an inefficient, more-wasteful overflow metabolism above a critical growth rate, even though the energy demand continues to rise with growth rate. For instance, complete respiration of a sugar is replaced by its fermentation. We derive the conditions for this to happen, using a core model of metabolism and growth that is qualitatively in agreement with experimental data. Assuming a fixed cellular protein content, the model shows that protein expression of efficient metabolism and anabolism rises as function of growth rate until a critical value is reached. This growth-associated protein expression is at the expense of proteins associated with future adaptation. At the critical growth rate, this preparatory pool is reduced to zero. Beyond the critical growth rate, the anabolic protein pool and the energy demand continue to rise and therefore less protein remains for catabolism. In this regime, the inefficient metabolism gradually takes over ATP synthesis from the efficient mode. It can do so if it requires less protein per unit of ATP flux. The catabolic protein pool then decreases while the anabolic pool increases. This continues until all catabolic protein is allocated to the inefficient strategy and to anabolism. We show that this can occur only if the maximal growth rate of the inefficient mode is higher than the critical growth rate. We show that this condition is precisely the requirement for the second mode to be more proteome-efficient than the first mode. Finally, we reduce a genome-scale model of protein expression in the yeast Saccharomyces cerevisiae to a variant of our core model and show that it is still qualitatively in agreement with the experimental data used to validate the original model.

systems biology↗

bioRxiv2025

Stoichiometric analysis of microbial communities: interrelating community function, structure and biomass carrying capacity

Microbial communities carry out important ecological functions. Their activities emerge from complex interactions between species, often potentiated by metabolic traits. We lack a quantitative understanding of how these traits shape community properties. Here, we present the theory for microbial communities, leveraging concepts from quantitative microbial physiology. We derive formal conditions for the steady states of microbial communities. We express the relative abundances of species (living and dead), the net metabolic conversion of a community, and the biomass carrying capacity in terms of the metabolic stoichiometry of the species and their growth and death rates. We show how niche creation can emerge from stoichiometric imbalances in cross-feeding communities. Finally, we discuss how relative species abundances depend on the ATP stoichiometries of intracellular metabolism.

ecology↗

bioRxiv2024

Mitochondrial efficiency determines Crabtree effect across yeasts

Under excess glucose conditions, many yeasts switch from high-yield respiratory metabolism to low-yield fermentation, a phenomenon called the Crabtree effect in yeast, or the Warburg effect in mammalian cells. Cellular constraints and limited resources are generally believed to govern the metabolic strategies of cells to adapt to environmental conditions, but which constraints drive this switch is still under debate. Here we study the Crabtree-negative, fully respiratory yeast Pichia kluyveri and compare it to the Crabtree-positive yeast Saccharomyces cerevisiae from a resource allocation perspective. By integrating quantitative physiology and proteomics into whole-cell proteome-constrained models, we find that the Crabtree effect is determined by the composition and catalytic efficiency of the electron transport chain. We find that the subsequent proteome efficiency of respiration versus fermentation varies between these species. The variation in parameters and composition of the respiratory machinery likely reflects the evolutionary and ecological history of these yeast species. This study advances our understanding of the role of proteome constraints and proteome efficiency in governing cellular metabolism of yeasts, and that of eukaryotic cells at large.

systems biology↗

bioRxiv2024

Sensing cellular growth rate facilitates its robust optimal adaptation to changing conditions

AO_SCPLOWBSTRACTC_SCPLOWThe determinants of growth rate and the associated metabolism has been at center stage in microbial physiology for over seventy years. In this paper we show that a cell sensing its own growth rate is in principle capable of maximising it using a gene regulatory circuit responsible for adapting metabolic enzyme concentrations in dynamic conditions. This is remarkable, since any state of (close-to) optimal growth depends on nutrient conditions, and is thus not a fixed target. We derive the properties of such gene regulatory networks, and prove that such circuits allow the growth rate to be a Lyapunov function. We derive this from a general stoichiometric and kinetic description of cellular metabolism. Interestingly, our finding is in agreement with our current understanding of how E. coli controls its growth rate. It uses ppGpp to tune the growth rate by balancing metabolic and ribosomal protein expression. Since ppGpp covaries 1-to-1 with the protein translation rate, an excellent proxy for growth rate, on a timescale of seconds, this suggests that direct sensing of the growth rate underlies growth rate optimisation in E. coli.

systems biology↗

bioRxiv2023

A temperature-sensitive metabolic valve and a transcriptional feedback loop drive rapid homeoviscous adaptation in Escherichia coli

All free-living microorganisms homeostatically maintain the fluidity of their membranes by adapting lipid composition to environmental temperatures. A quantitative description of how organisms maintain constant fluidity at all growth temperatures has not been achieved. By quantifying both enzymes and metabolic intermediates of the Escherichia coli fatty acid and phospholipid synthesis pathways, we discover how E. coli measures steady-state temperature and restores optimal membrane fluidity within a single generation after temperature shocks. The first element of the system is a temperature-sensitive metabolic valve that allocates flux between the saturated and unsaturated fatty acid synthesis pathways. The second element is a transcription-based negative feedback loop that counteracts the temperature-sensitive valve. The combination of these elements accelerates membrane adaptation by causing a transient overshoot in the synthesis of saturated or unsaturated fatty acids following temperature shocks. This overshoot strategy accelerates membrane adaptation, and is comparable to increasing the temperature of a water bath by adding water that is excessively hot rather than adding water at the desired temperature. These properties are captured in a quantitative model, which we further use to show how hard-wired parameters calibrate the system to generate membrane compositions that maintain constant fluidity across a wide range of temperatures. We hypothesize that core design features of the E. coli system will prove to be ubiquitous features of homeoviscous adaptation systems.

microbiology↗

bioRxiv2021

Selection for cell yield does not reduce overflow metabolism in E. coli

Overflow metabolism is ubiquitous in nature, and it is often considered inefficient because it leads to a relatively low biomass yield per consumed carbon. This metabolic strategy has been described as advantageous because it supports high growth rates during nutrient competition. Here we experimentally evolved bacteria without nutrient competition by repeatedly growing and mixing millions of parallel batch cultures of E. coli. Each culture originated from a water-in-oil emulsion droplet seeded with a single cell. Unexpectedly we found that overflow metabolism (acetate production) did not change. Instead the numerical cell yield during the consumption of the accumulated acetate increased as a consequence of a reduction in cell size. Our experiments and a mathematical model show that fast growth and overflow metabolism followed by the consumption of the overflow metabolite, leads to a higher numerical cell yield and therefore a higher fitness compared to full respiration of the substrate. This provides an evolutionary scenario where overflow metabolism can be favourable even in the absence of nutrient competition.

microbiology↗

bioRxiv2019

A new FRET biosensor enlightens cAMP signalling in budding yeast

The cAMP-PKA signalling cascade in budding yeast regulates adaptation to changing environments. We developed yEPAC, a FRET-based biosensor for cAMP measurements in yeast. We used this sensor with flow cytometry for high-throughput single cell-level quantification during dynamic changes in response to sudden nutrient transitions. We found that the characteristic cAMP peak differentiates between different carbon source transitions, and is rather homogenous among single-cells, especially for transitions to glucose. The peaks are mediated by a combination of extracellular sensing and intracellular metabolism. Moreover, the cAMP peak follows Webers law; its height scales with the relative, and not the absolute, change in glucose. Lastly, our results suggest that the cAMP peak height conveys information about prospective growth rates. In conclusion, our yEPAC-sensor makes possible new avenues for understanding yeast physiology, signalling and metabolic adaptation.

microbiology↗

bioRxiv2019

Elementary Growth Modes provide a molecular description of cellular self-fabrication

A major aim of biology is to predict phenotype from genotype. Here we ask if we can describe all possible molecular states (phenotypes) for a cell that fabricates itself at a constant rate, given its enzyme kinetics and the stoichiometry of all reactions (the genotype). For this, we must understand the autocatalytic process of cellular growth which is inherently nonlinear: steady-state self-fabrication requires a cell to synthesize all of its components, including metabolites, enzymes and ribosomes, in the proportions that exactly match its own composition - the growth demand thus depends on the cellular composition. Simultaneously, the concentrations of these components should be tuned to accomplish this synthesis task - the cellular composition thus depends on the growth demand. We here derive a theory that describes all phenotypes that solve this circular problem; the basic equations show how the concentrations of all cellular components and reaction rates must be balanced to get a constant self-fabrication rate. All phenotypes can be described as a combination of one or more minimal building blocks, which we call Elementary Growth Modes (EGMs). EGMs can be used as the theoretical basis for all models that explicitly model self-fabrication, such as the currently popular Metabolism and Expression models. We then used our theory to make concrete biological predictions: we find that natural selection for maximal growth rate drives microorganisms to states of minimal phenotypic complexity: only one EGM will be active when cellular growth rate is maximised. The phenotype of a cell is only extended with one more EGM whenever growth becomes limited by an additional biophysical constraint, such as a limited solvent capacity of a cellular compartment. Our theory starts from basic biochemical and evolutionary considerations, and describes unicellular life, both in growth-promoting and in stress-inducing environments, in terms of EGMs, the universal building blocks of self-fabrication and a cells phenotype.

systems biology↗

bioRxiv2017

Glucose limitation in Lactococcus shapes a single-peaked fitness landscape exposing membrane occupancy as a constraint

A central theme in biology is to understand the molecular basis of fitness: which strategies succeed under which conditions; how are they mechanistically implemented; and which constraints shape trade-offs between alternative strategies. We approached these questions with parallel bacterial evolution experiments in chemostats. Chemostats provide a constant environment with a defined resource limitation (glucose), in which the growth rate can be controlled. Using Lactococcus lactis, we found a single mutation in a global regulator of carbon metabolism, CcpA, to confer predictable fitness improvements across multiple growth rates. In silico protein structural analysis complemented with biochemical and phenotypic assays, show that the mutation reprograms the CcpA regulon, specifically targeting transporters. This supports that membrane occupancy, rather than biosynthetic capacity, is the dominant constraint for the observed fitness enhancement. It also demonstrates that cells can modulate a pleiotropic regulator to work around limiting constraints.

genomics↗