Biology subjects

Heux, S.

Publications and source records attributed to Heux, S..

8 recordsLinked to original sources

bioRxiv2026

Small but Mighty: The Surprising Metabolic Range of a Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-based metabolic modules increasingly investigated as potential intracellular nanoreactors. In this study, we engineered Escherichia coli by chromosomally integrating the propanediol utilization (pdu) operon from Citrobacter freundii and evaluated the metabolic versatility of the heterologously produced Pdu BMCs. The formation of well-assembled, operational Pdu BMCs was confirmed in cellula. Oxygen was found to inhibit 1,2-propanediol utilization, an effect alleviated under microaerobic conditions. The engineered E. coli strain assimilated a range of diols and triols, demonstrating that Pdu BMCs process both their native substrate and glycerol and linear diols up to 1,2-butanediol (C4). This substrate promiscuity was exploited to produce high value-added compounds and revealed previously unrecognized potential for plastic upcycling through ethylene glycol metabolism. In keeping with molecular dynamics simulations indicating that the Pdu BMC shell does not impose significant diffusion barriers for longer chain diols and triols, the range of amenable substrates was successfully extended to 1,2-pentanediol (C5) by mutating the diol dehydratase large subunit (PduC). Together, these findings establish heterologous Pdu BMCs as promiscuous and genetically tunable metabolic modules in E. coli, highlighting their potential as scalable platforms for synthetic biology and biotechnological applications. ImportanceBacterial microcompartments (BMCs) are increasingly popular modular platforms for organizing and optimizing metabolic pathways, yet their substrate scope and engineering potential remain underexplored. Here, we demonstrate that heterologous Pdu BMCs expressed in Escherichia coli metabolize a substantially broader range of substrates than previously appreciated, including various diols and triols outside their native range. We further show that BMC performance is modulated by oxygen availability and can be predictably expanded by targeted enzyme engineering. These findings establish Pdu BMCs as flexible, genetically tunable metabolic modules capable of converting diverse feedstocks into value-added products, while also revealing an unanticipated capacity for plastic upcycling via ethylene glycol utilization. By integrating pathway engineering, physiological characterization, and computational modelling, this work advances the design of BMC-based systems for sustainable bioproduction and highlights their potential as customizable intracellular nanoreactors for biotechnology.

biochemistry↗

bioRxiv2025

Acetate as a metabolic booster for glucose-based bioproduction in Escherichia coli

Escherichia coli, a key workhorse in industrial biotechnology, is commonly grown on glucose, which supports rapid growth but leads to acetate overflow, which instead inhibits growth, diverts carbon from the production pathway, and reduces productivity. Recent studies suggest that acetate may also have beneficial effects in glucose-grown E. coli, but its potential in bioprocesses remains unexplored. In this study, we systematically investigated acetates impact on bioproduction using a kinetic model of glucose and acetate metabolism in E. coli. The model predicts that acetate can enhance bioproduction in glucose-grown E. coli through three mechanisms: (i) by minimizing acetate overflow, thereby reducing carbon loss, (ii) by increasing acetyl-CoA levels, thereby boosting the biosynthetic flux of acetyl-CoA-derived compounds, and (iii) by promoting biomass accumulation, thus improving overall productivity. We experimentally validated the predictions of the model for mevalonate and 3-hydroxypropionate production, where acetate supplementation increased productivity by 117% and 34%, respectively. Our findings provide a valuable framework for optimizing E. coli-based bioprocesses and highlight acetates underutilized potential in biotechnology. By leveraging acetate from waste streams as a metabolic booster, this approach could contribute to more sustainable and environmentally friendly bioprocesses. Highlights- A kinetic model was used for rational optimization of E. coli-based bioprocesses - Acetate can enhance growth and production of acetyl-CoA-derived bioproducts - Model predictions were validated for mevalonate and 3-hydroxypropionate production - Acetate can be used as a metabolic booster for glucose-based bioproduction in E. coli

systems biology↗

bioRxiv2024

Systems-level analysis provides insights on methanol-based production of L-glutamate and its decarboxylation product γ-aminobutyric acid by Bacillus methanolicus

BackgroundBacillus methanolicus is the next workhorse in biotechnology using methanol, an alternative and economical one-carbon feedstock that can be obtained directly from carbon dioxide, as both carbon and energy source for the production of various value-added chemicals. The wild-type strain B. methanolicus MGA3 naturally overproduces O_SCPLOWLC_SCPLOW-glutamate in methanol-based fed-batch fermentations. ResultsHere we generated, by induced mutagenesis, an evolved B. methanolicus strain exhibiting enhanced O_SCPLOWLC_SCPLOW-glutamate production capability (>150%). To showcase the potential of this evolved strain, further metabolic engineering enabled the production of {gamma}-aminobutyric acid (GABA) directly from O_SCPLOWLC_SCPLOW-glutamate, with a yield of 13.2 g/L from methanol during fed-batch fermentations. By using a systems-level analysis, encompassing whole-genome sequencing, RNA sequencing, fluxome analysis and genome-scale metabolic modelling, we were able to elucidate the metabolic and regulatory adaptations that sustain the biosynthesis of these products. The metabolism of the mutant strain evolved to prioritize energy conservation and efficient carbon utilization. Key metabolic shifts include the downregulation of energy-intensive processes such as flagellation and motility and the rerouting of carbon fluxes towards -ketoglutarate and its derivative, O_SCPLOWLC_SCPLOW-glutamate. Moreover, we observed that transformation of the evolved strain with a GABA biosynthesis plasmid had a positive effect on O_SCPLOWLC_SCPLOW-glutamate production, likely due to an upregulation of various transaminases involved in the O_SCPLOWLC_SCPLOW-glutamate biosynthesis from -ketoglutarate. ConclusionsThese results and insights provide a foundation for further rational metabolic engineering and bioprocess optimization, enhancing the industrial viability of B. methanolicus for sustainable production of O_SCPLOWLC_SCPLOW-glutamate and its derivatives.

systems biology↗

bioRxiv2024

Integrative in vivo analysis of the ethanolamine utilization bacterial microcompartment in Escherichia coli.

Bacterial microcompartments (BMCs) are self-assembling protein megacomplexes that encapsulate metabolic pathways. Although approximately 20% of sequenced bacterial genomes contain operons encoding putative BMCs, few have been thoroughly characterized, nor any in the most studied Escherichia coli strains. We used an interdisciplinary approach to gain deep molecular and functional insights into the ethanolamine utilization (Eut) BMC system encoded by the eut operon in E. coli K-12. The eut genotype was linked with the ethanolamine utilization phenotype using deletion and overexpression mutants. The subcellular dynamics and morphology of the E. coli Eut BMC were characterized in cellula by fluorescence microscopy and electron (cryo)microscopy. The minimal proteome reorganization required for ethanolamine utilization and the in vivo stochiometric composition of the Eut BMC were determined by quantitative proteomics. Finally, the first flux map connecting the Eut BMC with central metabolism in cellula was obtained by genome scale modelling and 13C-fluxomics. Our results reveal that, contrary to previous suggestions, ethanolamine serves both as a nitrogen and a carbon source in E. coli K-12, while also contributing significant metabolic overflow. Overall, this study provides a quantitative molecular and functional understanding of the BMCs involved in ethanolamine assimilation by E. coli. ImportanceThe properties of BMCs make them an ideal tool to build orthogonal network structures with minimal interactions with native metabolic and regulatory networks. However, this requires an understanding of how BMCs work natively. In this study, we combined genetic manipulation, multi-omics, modelling and microscopy to address this issue for Eut BMCs. We show that the Eut BMC in E. coli turns ethanolamine into usable carbon and nitrogen substrates to sustain growth. These results improve our understanding of compartmentalization in a widely used bacterial chassis.

microbiology↗

bioRxiv2024

Combining systems and synthetic biology for in vivo enzymology

Enzymatic parameters are classically determined in vitro, under conditions that are far from those encountered in cells, casting doubt on their physiological relevance. We developed a generic approach combining tools from synthetic and systems biology to measure enzymatic parameters in vivo. In the context of a synthetic carotenoid pathway in Saccharomyces cerevisiae, we focused on a phytoene synthase and three phytoene desaturases, which are difficult to study in vitro. We designed, built, and analyzed a collection of yeast strains mimicking substantial variations in substrate concentration by strategically manipulating the expression of geranyl-geranyl pyrophosphate (GGPP) synthase. We successfully determined in vivo Michaelis-Menten parameters (KM, Vmax and kcat) for GGPP-converting phytoene synthase from absolute metabolomics, fluxomics and proteomics data, highlighting differences between in vivo and in vitro parameters. Leveraging the versatility of the same set of strains, we then extracted enzymatic parameters for two of the three phytoene desaturases. Our approach demonstrates the feasibility of assessing enzymatic parameters directly in vivo, providing a novel perspective on the kinetic characteristics of enzymes in real cellular conditions.

systems biology↗

bioRxiv2023

PhysioFit: a software to quantify cell growth parameters and extracellular fluxes

SummaryQuantification of growth parameters and extracellular uptake and production fluxes is central in systems and synthetic biology. Fluxes can be estimated using various mathematical models by fitting time-course measurements of the concentration of cells and extracellular substrates and products. A single tool is available to non-computational biologists to calculate extracellular fluxes, but it is hardly interoperable and is limited to a single hard-coded growth model. We present our open-source flux calculation software, PhysioFit, which can be used with any growth model and is interoperable by design. PhysioFit includes some of the most common growth models, and advanced users can implement additional models to calculate extracellular fluxes and other growth parameters for metabolic systems or experimental setups that follow alternative kinetics. PhysioFit can be used as a Python library and offers a graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. Availability and ImplementationPhysioFit is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. PhysioFit is also freely available online at https://workflow4metabolomics.org. The source code, the data and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/PhysioFit/ and https://physiofit.readthedocs.io/.

bioinformatics↗

bioRxiv2019

Charting the metabolic landscape of the facultative methylotroph Bacillus methanolicus

Bacillus methanolicus MGA3 is a thermotolerant and relatively fast-growing methylotroph able to secrete large quantities of glutamate and lysine. These natural characteristics make B. methanolicus a good candidate to become a new industrial chassis organism, especially in a methanol-based economy. This has motivated a number of omics studies of B. methanolicus at the genome, transcript, protein and metabolic levels. Intriguingly, the only substrates known to support B. methanolicus growth as sole source of carbon and energy are methanol, mannitol, and to a lesser extent glucose and arabitol. We hypothesized that comparing methylotrophic and non-methylotrophic metabolic states at the flux level would yield new insights into MGA3 metabolism. 13C metabolic flux analysis (13C-MFA) is a powerful computational method to estimate carbon flows from substrate to biomass (i.e. the in vivo reaction rates of the central metabolic pathways) from experimental labeling data. In this study, we designed and performed a 13C-MFA of the facultative methylotroph B. methanolicus MGA3 growing on methanol, mannitol and arabitol to compare the associated metabolic states. The results obtained validate previous findings on the methylotrophy of B. methanolicus, allowed us to characterize the assimilation pathway of one of the studied carbon sources, and provide a better overall understanding of this strain. IMPORTANCEMethanol is cheap, easy to transport and can be produced both from renewable and fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as B. methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories, or to design methylotrophic capability in other strains already used by the industry.

systems biology↗

bioRxiv2019

ScalaFlux: a scalable approach to quantify fluxes in metabolic subnetworks

13C-metabolic flux analysis (13C-MFA) allows metabolic fluxes to be quantified in living organisms and is a major tool in biotechnology and systems biology. Current 13C-MFA approaches model label propagation starting from the extracellular 13C-labeled nutrient(s), which limits their applicability to the analysis of pathways close to this metabolic entry point. Here, we propose a new approach to quantify fluxes through any metabolic subnetwork of interest by modeling label propagation directly from the metabolic precursor(s) of this subnetwork. The flux calculations are thus purely based on information from within the subnetwork of interest, and no additional knowledge about the surrounding network (such as atom transitions in upstream reactions or the labeling of the extracellular nutrient) is required. This approach, termed ScalaFlux for SCALAble metabolic FLUX analysis, can be scaled up from individual reactions to pathways to sets of pathways. ScalaFlux has several benefits compared with current 13C-MFA approaches: greater network coverage, lower data requirements, independence from cell physiology, robustness to gaps in data and network information, better computational efficiency, applicability to rich media, and enhanced flux identifiability. We validated ScalaFlux using a theoretical network and simulated data. We also used the approach to quantify fluxes through the prenyl pyrophosphate pathway of Saccharomyces cerevisiae mutants engineered to produce phytoene, using a dataset for which fluxes could not be calculated using existing approaches. A broad range of metabolic systems can be targeted with minimal cost and effort, making ScalaFlux a valuable tool for the analysis of metabolic fluxes.\n\nAuthor SummaryMetabolism is a fundamental biochemical process that enables all organisms to operate and grow by converting nutrients into energy and building blocks. Metabolic flux analysis allows the quantification of metabolic fluxes in vivo, i.e. the actual rates of biochemical conversions in biological systems, and is increasingly used to probe metabolic activity in biology, biotechnology and medicine. Isotope labeling experiments coupled with mathematical models of large metabolic networks are the most commonly used approaches to quantify fluxes within cells. However, many biological questions only require flux information from a subset of reactions, not the full network. Here, we propose a new approach with three main advantages over existing methods: better scalability (fluxes can be measured through a single reaction, a metabolic pathway or a set of pathways of interest), better robustness to missing data and information gaps, and lower requirements in terms of measurements and computational resources. We validate our method both theoretically and experimentally. ScalaFlux can be used for high-throughput flux measurements in virtually any metabolic system and paves the way to the analysis of dynamic fluxome rearrangements.

systems biology↗