Biology subjects

Querol, A.

Publications and source records attributed to Querol, A..

10 recordsLinked to original sources

bioRxiv2026

GeNETop: Context-Specific Genome-Scale Constrained Models Using Network Topology, Flux Variability, and Transcriptomics

Context-specific genome-scale metabolic models are critical tools for studying cellular metabolism under dynamic conditions. However, most existing methods for deriving these models are designed for steady-state settings and may fail to preserve reactions required for transient metabolic shifts, thereby limiting their compatibility with dynamic FBA. Here, we present GeNETop, a methodology for deriving context-specific GEMs designed to preserve dynamic compatibility. GeNETop integrates flux variability analysis (FVA), network topology metrics based on the Integrated Value of Influence (IVI), and transcriptomic data to identify reactions that are both flux-flexible and structurally influential. Reactions are prioritized based on variability and maximality indices, while topology and gene expression guide further refinement, reducing dependence on fixed expression thresholds. Using batch fermentation of Saccharomyces cerevisiae as a case study, we evaluate GeNETop against established methods for context-specific metabolic reconstruction. The resulting networks remain dynamically feasible across growth phases, capture key metabolic transitions, reduce non-essential reactions, and maintain computational tractability. Overall, GeNETop enables context-specific metabolic reconstructions that are compatible with dynamic simulations while maintaining computational efficiency. By overcoming key limitations of existing approaches, the method supports a more accurate representation of time-dependent metabolic processes in biotechnology and systems biology. Author summaryCellular metabolism relies on complex networks of reactions to process nutrients, generate energy, and build essential compounds for biomass. Context-specific metabolic models aim to represent only the reactions active under a given condition, improving biological realism and reducing computational complexity in flux balance analysis simulations. However, metabolic activity adapts dynamically to changing environmental conditions, and reactions that are inactive at one stage may become essential at another. Many current reconstruction methods are designed for steady-state conditions and may exclude reactions that are required during metabolic transitions, thereby limiting their ability to describe dynamic behavior. Here, we introduce GeNETop, a novel approach that refines context-specific networks by integrating multiple layers of information. GeNETop identifies the most relevant reactions by considering their flexibility, importance within the network topology, and gene activity levels. In this way, the method generates biologically meaningful models that focus on metabolic pathways relevant under dynamic conditions. We tested GeNETop on yeast fermentation, a key process in food and biofuel production. The resulting models capture metabolic changes over time and enable stable dynamic simulations, supporting improved flux balance analysis of time-dependent metabolic processes.

systems biology↗

bioRxiv2025

Chromosome III aneuploidy enhances ethanol tolerance in industrial Saccharomyces cerevisiae by increasing TUP1 expression

Ethanol stress poses a considerable challenge for Saccharomyces cerevisiae during fermentation. Strains carrying an extra copy of chromosome III exhibit enhanced ethanol tolerance. Here, we investigated the underlying mechanisms of this tolerance, focusing on gene dosage effects and differential gene expression under ethanol stress. We compared the gene expression profiles of a strain with three copies of chromosome III and its derivative with two copies, exposed to 6% and 10% ethanol. Our analysis identified TUP1, located on chromosome III, as a key regulator of the ethanol stress response. Deleting one copy of TUP1 in the tolerant strain diminished its ethanol tolerance, suggesting that chromosome III aneuploidy in ethanol-tolerant strains enhances adaptive responses by increasing TUP1 copy number. Our findings offer insights into the genetic basis of ethanol tolerance, with potential applications for optimizing industrial fermentation processes and understanding the role of aneuploidy in the domestication of industrial yeasts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/647507v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1beb640org.highwire.dtl.DTLVardef@1af6231org.highwire.dtl.DTLVardef@157abf0org.highwire.dtl.DTLVardef@d937ff_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2024

Identification of a crucial INO2 allele for enhancing ethanol resistance in an industrial fermentation strain of Saccharomyces cerevisiae

Ethanol toxicity is a major challenge for S. cerevisiae during fermentation, affecting its growth and influencing the process. This study investigated the molecular mechanisms of ethanol tolerance using transcriptomic analysis of three S. cerevisiae strains with varying ethanol resistance. We identified distinct responses in membrane lipid synthesis genes, particularly in ergosterol biosynthesis, regulated by the Ino2p transcription factor. A variant of Ino2p with V263I and H86R amino acid replacements was exclusive to ethanol-tolerant strains. CRISPR-Cas9-mediated point mutations in the INO2 gene of the highly tolerant strain AJ4 resulted in decreased ethanol tolerance. Our findings demonstrate the crucial role of Ino2p in ethanol tolerance through regulation of lipid synthesis and membrane composition, highlighting the complex interplay of trans elements in strain-specific ethanol resistance IMPORTANCEThis study provides critical insights into the molecular basis of ethanol tolerance in S. cerevisiae, a key trait for improving industrial fermentation processes. By identifying specific genetic variants in the Ino2p transcription factor and their impact on ethanol resistance, we reveal potential targets for enhancing yeast strain performance in high-ethanol environments. Our findings not only contribute to the fundamental understanding of stress response mechanisms in yeast but also offer practical implications for strain engineering in the biotechnology and beverage industries. The unexpected magnitude of the Ino2p variants effect on ethanol tolerance underscores the importance of considering strain-specific genetic backgrounds in metabolic engineering strategies

microbiology↗

bioRxiv2024

Optogenetic control of a horizontally acquired region in yeast prevent stuck fermentations

Nitrogen limitations in the grape must is the main cause of stuck fermentations during the winemaking process. In Saccharomyces cerevisiae, a genetic segment known as region A, which harbors 12 protein-coding genes, was acquired horizontally from a phylogenetically distant yeast species. This region is mainly present in the genome of wine yeast strains, carrying genes that have been associated with nitrogen utilization. Despite the putative importance of region A in yeast fermentation, its contribution to the fermentative process is largely unknown. In this work, we used a wine yeast strain to evaluate the contribution of region A to the fermentation process. To do this, we first sequenced the genome of the wine yeast strain known as ALL using long-read sequencing and determined that region A is present in a single copy with two possible subtelomeric locations. We then implemented an optogenetic system in this wine yeast strain to precisely regulate the expression of each gene inside this region, generating a collection of 12 strains that allow for light- activated gene expression. To evaluate the role of these genes during fermentation, we assayed this collection using microculture and fermentation experiments in synthetic must with varying amounts of nitrogen concentration. Our results show that changes in gene expression for genes within this region can impact growth parameters and fermentation rate. We additionally found that the expression of various genes in region A is necessary to complete the fermentation process and prevent stuck fermentations under low nitrogen conditions. Altogether, our optogenetics-based approach demonstrates the importance of region A in completing fermentation under nitrogen-limited conditions. IMPORTANCEStuck fermentations due to limited nitrogen availability in grape must represents one of the main problems in the winemaking industry. Nitrogen limitation in grape musts reduce yeast biomass and fermentation rate, resulting in incomplete fermentations with high levels of residual sugar, undesired by-products, and microbiological instability. Here, we used an optogenetic approach to demonstrate that expression of genes within region A is necessary to complete fermentations under low nitrogen availability. Overall, our results support the idea that region A is a genetic signature for wine yeast strains adapted to low nitrogen conditions.

microbiology↗

bioRxiv2024

Understanding brewing trait inheritance in de novo lager yeast hybrids

Hybridization between Saccharomyces cerevisiae and Saccharomyces eubayanus resulted in the emergence of S. pastorianus, a crucial yeast for lager fermentation. However, our understanding of hybridization success and hybrid vigour between these two species remains limited due to the scarcity of S. eubayanus parental strains. Here, we explore hybridization success and the impact of hybridization on fermentation performance and volatile compound profiles in newly formed lager hybrids. By selecting parental candidates spanning a diverse array of lineages from both species, we reveal that the Beer and PB-2 lineages exhibit high rates of hybridization success in S. cerevisiae and S. eubayanus, respectively. Polyploid hybrids were generated through rare mating techniques, revealing a prevalence of triploids and diploids over tetraploids. Despite the absence of heterosis in fermentative capacity, hybrids displayed phenotypic variability, notably influenced by maltotriose consumption. Interestingly, ploidy levels did not significantly correlate with fermentative capacity, although triploids exhibited greater phenotypic variability. The S. cerevisiae parental lineages primarily influenced volatile compound profiles, with significant differences in aroma production. Interestingly, hybrids emerging from the Beer S. cerevisiae parental lineages exhibited a volatile compound profile resembling the corresponding S. eubayanus parent. This pattern may result from the dominant inheritance of the S. eubayanus aroma profile, as suggested by the over-expression of genes related to alcohol metabolism and acetate synthesis in hybrids including the Beer S. cerevisiae lineage. Our findings suggest complex interactions between parental lineages and hybridization outcomes, highlighting the potential for creating yeasts with distinct brewing traits through hybridization strategies.

microbiology↗

bioRxiv2024

A continuous dynamic genome-scale model explains batch fermentations led by species of the Saccharomyces genus.

Batch fermentation is a biotechnological dynamic process that produces various products by employing microorganisms that undergo different growth phases: lag, exponential, growth-non-growth, stationary, and decay. Genome-scale constrained-based models are commonly used to explore the phenotypic potential of these microorganisms. Previous studies have primarily used dynamic Flux Balance Analysis (dFBA) to elucidate the metabolism during the exponential phase. However, this approach falls short in addressing the multi-phase nature of the process and secondary metabolism, posing significant challenges to our understanding of batch fermentation. A recent attempt at a solution was a discontinuous, multi-phase, multi-objective dFBA implementation. However, this approximation lacks the mechanistic connection between phases, limiting its applicability in predicting intracellular fluxes during batch fermentation. To overcome these limitations, we combined a novel continuous model with a genome-scale model to predict the distribution of intracellular fluxes throughout the batch fermentation process. The proposed model includes empirical descriptions of regulation that automatically identify the transition between phases. Its application to explain primary and secondary metabolism of Saccharomyces species in batch fermentation results in biological insights that are in good agreement with the previous literature. The ability to account for all process phases and explain secondary metabolism makes this model a valuable and easy-to-use tool for exploring novel fermentation processes. IMPORTANCEThis research proposes a novel dynamic genome-scale modelling approach for batch fermentation, a crucial process widely used to produce a diverse range of products such as biofuels, enzymes, pharmaceuticals, and food products or ingredients. The proposed approach automatically accounts for the transitions between different phases of the fermentation process (lag, exponential, growth-no-growth, and stationary). This is a significant advancement over previous methods that required different model formulations for different phases. We have successfully applied this modelling approach to explore the primary and secondary metabolism of three yeast species under batch fermentation conditions. The model accurately explained experimental data and provided biological insights consistent with previous research findings, instilling confidence in its reliability and accuracy. The ability of this modelling approach to explain primary and secondary metabolism makes it a valuable tool for designing novel, more efficient, and effective fermentation processes, which could have far-reaching implications in industrial biotechnology.

systems biology↗

bioRxiv2023

Divergence in the Saccharomyces species' heat shock response is indicative of their thermal tolerance

The Saccharomyces species have diverged in their thermal growth profile. Both S. cerevisiae and S. paradoxus grow at temperatures well above the maximum growth temperature of S. kudriavzevii and S. uvarum, but grow more poorly at lower temperatures. In response to thermal shifts, organisms activate a stress response that includes heat shock proteins involved in protein homeostasis and acquisition of thermal tolerance. To determine whether Saccharomyces species have diverged in their response to temperature we measured changes in gene expression in response to a 12{degrees}C increase or decrease in temperature for four Saccharomyces species and their six pairwise hybrids. To ensure coverage of subtelomeric gene families we sequenced, assembled and annotated a complete S. uvarum genome. All the strains exhibited a stronger response to heat than cold treatment. In response to heat, the cryophilic species showed a stronger response than the thermophilic species. The hybrids showed a mixture of parental stress responses depending on the time point. After the initial response, hybrids with a thermophilic parent were more similar to S. cerevisiae and S. paradoxus, and the S. cerevisiae x S. paradoxus hybrid showed the weakest heat shock response. Within the hybrids a small subset of temperature responsive genes showed species specific responses but most were also hybrid specific. Our results show that divergence in the heat shock response is indicative of a strains thermal tolerance, suggesting that cellular factors that signal heat stress or resolve heat induced changes are relevant to thermal divergence in the Saccharomyces species.

evolutionary biology↗

bioRxiv2021

A multi-phase multi-objective dynamic genome-scale model shows different redox balancing among yeast species in fermentation

Yeasts constitute over 1500 species with great potential for biotechnology. Still, the yeast Saccharomyces cerevisiae dominates industrial applications and many alternative physiological capabilities of lesser-known yeasts are not being fully exploited. While comparative genomics receives substantial attention, little is known about yeasts metabolic specificity in batch cultures. Here we propose a multi-phase multi-objective dynamic genome-scale model of yeast batch cultures that describes the uptake of carbon and nitrogen sources and the production of primary and secondary metabolites. The model integrates a specific metabolic reconstruction, based on the consensus Yeast8, and a kinetic model describing the time-varying culture environment. Besides, we proposed a multi-phase multi-objective flux balance analysis to compute the dynamics of intracellular fluxes. We then compared the metabolism of S. cerevisiae and S. uvarum strains in a rich medium fermentation. The model successfully explained the experimental data and brought novel insights into how cryotolerant strains achieve redox balance. The proposed model (along with the corresponding code) provides a comprehensive picture of the main steps occurring inside the cell during batch cultures and offers a systematic approach to prospect or metabolically engineering novel yeast cell factories. IMPORTANCENon-conventional yeast species hold the promise to provide novel metabolic routes to produce industrially relevant compounds and tolerate specific stressors, such as cold temperatures. This work presented and validated the first multi-phase multi-objective genome-scale dynamic model to describe carbon and nitrogen metabolism throughout batch fermentation. To test and illustrate its performance, we considered the comparative metabolism of three yeast strains of the Saccharomyces genus in rich medium fermentation. The study revealed that cryotolerant Saccharomyces species might use the GABA shunt and the production of reducing equivalents as alternative routes to achieve redox balance, a novel biological insight worth being explored further. The proposed model (along with the provided code) can be applied to a wide range of batch processes started with different yeast species and media, offering a systematic and rational approach to prospect non-conventional yeast species metabolism and engineering novel cell factories.

systems biology↗

bioRxiv2021

A multi-phase multi-objective genome-scale model shows diverse redox balance strategies in yeasts

systems biology↗

bioRxiv2020

Differential proteomic analysis by SWATH-MS unravels the most dominant mechanisms underlying yeast adaptation to non-optimal temperatures under anaerobic conditions

Elucidation of temperature tolerance mechanisms in yeast is essential for enhancing cellular robustness of strains, providing more economically and sustainable processes. We investigated the differential responses of three distinct Saccharomyces cerevisiae strains, an industrial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and an industrial bioethanol strain, Ethanol Red, grown at sub- and supra-optimal temperatures under chemostat conditions. We employed anaerobic conditions, mimicking the industrial processes. The proteomic profile of these strains was performed by SWATH-MS, allowing the quantification of 997 proteins, data available via ProteomeXchange (PXD016567). Our analysis demonstrated that temperature responses differ between the strains; however, we also found some common responsive proteins, revealing that the response to temperature involves general stress and specific mechanisms. Overall, sub-optimal temperature conditions involved a higher remodeling of the proteome. The proteomic data evidenced that the cold response involves strong repression of translation-related proteins as well as induction of amino acid metabolism, together with components related to protein folding and degradation while, the high temperature response mainly recruits amino acid metabolism. Our study provides a global and thorough insight into how growth temperature affects the yeast proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

microbiology↗