Repeated-batch fermentations of xylose and glucose–xylose mixtures using a respiration-deficient Saccharomyces cerevisiae engineered for xylose metabolism

Towards a hybrid model-driven platform based on flux balance analysis and a machine learning pipeline for biosystem design

Metabolic modeling and machine learning (ML) are crucial components of the evolving next-generation tools in systems and synthetic biology, aiming to unravel the intricate relationship between genotype, phenotype, and the environment. Nonetheless, the comprehensive exploration of integrating these two frameworks, and fully harnessing the potential of fluxomic data, remains an unexplored territory. In this study, we present, rigorously evaluate, and compare ML-based techniques for data integration. The hybrid model revealed that the overexpression of six target genes and the knockout of seven target genes contribute to enhanced ethanol production. Specifically, we investigated the influence of succinate dehydrogenase (SDH) on ethanol biosynthesis in Saccharomyces cerevisiae through shake flask experiments. The findings indicate a noticeable increase in ethanol yield, ranging from 6 % to 10 %, in SDH subunit gene knockout strains compared to the wild-type strain. Moreover, in pursuit of a high-yielding strain for ethanol production, dual-gene deletion experiments were conducted targeting glycerol-3-phosphate dehydrogenase (GPD) and SDH. The results unequivocally demonstrate significant enhancements in ethanol production for the engineered strains Δsdh4Δgpd1, Δsdh5Δgpd1, Δsdh6Δgpd1, Δsdh4Δgpd2, Δsdh5Δgpd2, and Δsdh6Δgpd2, with improvements of 21.6 %, 27.9 %, and 22.7 %, respectively. Overall, the results highlighted that integrating mechanistic flux features substantially improves the prediction of gene knockout strains not accounted for in metabolic reconstructions. In addition, the finding in this study delivers valuable tools for comprehending and manipulating intricate phenotypes, thereby enhancing prediction accuracy and facilitating deeper insights into mechanistic aspects within the field of synthetic biology.

PKA regulatory subunit Bcy1 couples growth, lipid metabolism, and fermentation during anaerobic xylose growth in Saccharomyces cerevisiae

Organisms have evolved elaborate physiological pathways that regulate growth, proliferation, metabolism, and stress response. These pathways must be properly coordinated to elicit the appropriate response to an ever-changing environment. While individual pathways have been well studied in a variety of model systems, there remains much to uncover about how pathways are integrated to produce systemic changes in a cell, especially in dynamic conditions. We previously showed that deletion of Protein Kinase A (PKA) regulatory subunit BCY1 can decouple growth and metabolism in Saccharomyces cerevisiae engineered for anaerobic xylose fermentation, allowing for robust fermentation in the absence of division. This provides an opportunity to understand how PKA signaling normally coordinates these processes. Here, we integrated transcriptomic, lipidomic, and phospho-proteomic responses upon a glucose to xylose shift across a series of strains with different genetic mutations promoting either coupled or decoupled xylose-dependent growth and metabolism. Together, results suggested that defects in lipid homeostasis limit growth in the bcy1Δ strain despite robust metabolism. To further understand this mechanism, we performed adaptive laboratory evolutions to re-evolve coupled growth and metabolism in the bcy1Δ parental strain. The evolved strain harbored mutations in PKA subunit TPK1 and lipid regulator OPI1, among other genes, and evolved changes in lipid profiles and gene expression. Deletion of the evolved opi1 gene partially reverted the strain's phenotype to the bcy1Δ parent, with reduced growth and robust xylose fermentation. We suggest several models for how cells coordinate growth, metabolism, and other responses in budding yeast and how restructuring these processes enables anaerobic xylose utilization.

Lignocellulosic biomass for bioethanol: an overview on pretreatment, hydrolysis and fermentation processes

Bioethanol is currently the only alternative to gasoline that can be used immediately without having to make any significant changes in the way fuel is distributed. In addition, the carbon dioxide (CO2) released during the combustion of bioethanol is the same as that used by the plant in the atmosphere for its growth, so it does not participate in the increase of the greenhouse effect. Bioethanol can be obtained by fermentation of plants containing sucrose (beet, sugar cane…) or starch (wheat, corn…). However, large-scale use of bioethanol implies the use of very large agricultural surfaces for maize or sugarcane production. Lignocellulosic biomass (LCB) such as agricultural residues for the production of bioethanol seems to be a solution to this problem due to its high availability and low cost even if its growth still faces technological difficulties. In this review, we present an overview of lignocellulosic biomass, the different methods of pre-treatment of LCB and the various fermentation processes that can be used to produce bioethanol from LCB.

A genome-wide view of mutations in respiration-deficient mutants of Saccharomyces cerevisiae selected following carbon ion beam irradiation

Mitochondrial dysfunction in Saccharomyces cerevisiae was selected as a marker of ion penetration following carbon ion beam (CIB) irradiation. Respiration-deficient mutants were screened. Following confirmation of negligible spontaneous mutation, eight genetically stable S. cerevisiae respiration-deficient mutant strains and a control strain were resequenced with ~ 200-fold read depth. Strategies were established to identify and validate the particular mutations induced by CIB irradiation. In the nuclear genome, CIB irradiation mainly caused base substitutions and some small (< 100 bp) insertions/deletions (indels), which were widely distributed across the chromosomes. Although mitochondrial dysfunction was selected as a screening marker, variants in the nuclear genome were detected at a high frequency (10^-7) relative to spontaneous mutations (10^-9). The transition to transversion ratio for base substitutions was 0.746, which was less than that of spontaneous mutations. In the mitochondrial genome, there were very large deletions including substantial gene areas, resulting in extremely low read coverage. Meanwhile, every mutant possessed a distinctive mutation pattern, for both the nuclear and the mitochondrial genome. Nuclear genomes contained scanty mitochondrial respiration-related genes that were potentially affected by verified mutations, suggesting that variants in the mitochondrial genome may be the main drivers of respiratory deficiencies. Our study confirmed the previous finding that heavy ion beam (HIB) irradiation mainly induces substantial base substitutions and some small indels but also yielded some novel findings, in particular, novel structural variants in the mitochondrial genomes. These data will enhance the understanding of HIB-induced damage and mutations and aid in the HIB-based microbial mutation breeding.

Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening

In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest.

Improving lactic acid productivity from wheat straw hydrolysates by membrane integrated repeated batch fermentation under non-sterilized conditions

Bacillus coagulans IPE22 was used to produce lactic acid (LA) from mixed sugar and wheat straw hydrolysates, respectively. All fermentations were conducted under non-sterilized conditions and sodium hydroxide was used as neutralizing agent to avoid the production of insoluble CaSO4. In order to eliminate the sequential utilization of mixed sugar and feedback inhibition during batch fermentation, membrane integrated repeated batch fermentation (MIRB) was used to improve LA productivity. With MIRB, a high cell density was obtained and the simultaneous fermentation of glucose, xylose and arabinose was successfully realized. The separation of LA from broth by membrane in batch fermentation also decreased feedback inhibition. MIRB was carried out using wheat straw hydrolysates (29.72 g/L glucose, 24.69 g/L xylose and 5.14 g/L arabinose) as carbon source, LA productivity was increased significantly from 1.01 g/L/h (batch 1) to 2.35 g/L/h (batch 6) by the repeated batch fermentation.

APJ1 and GRE3 homologs work in concert to allow growth in xylose in a natural Saccharomyces sensu stricto hybrid yeast

Creating Saccharomyces yeasts capable of efficient fermentation of pentoses such as xylose remains a key challenge in the production of ethanol from lignocellulosic biomass. Metabolic engineering of industrial Saccharomyces cerevisiae strains has yielded xylose-fermenting strains, but these strains have not yet achieved industrial viability due largely to xylose fermentation being prohibitively slower than that of glucose. Recently, it has been shown that naturally occurring xylose-utilizing Saccharomyces species exist. Uncovering the genetic architecture of such strains will shed further light on xylose metabolism, suggesting additional engineering approaches or possibly even enabling the development of xylose-fermenting yeasts that are not genetically modified. We previously identified a hybrid yeast strain, the genome of which is largely Saccharomyces uvarum, which has the ability to grow on xylose as the sole carbon source. To circumvent the sterility of this hybrid strain, we developed a novel method to genetically characterize its xylose-utilization phenotype, using a tetraploid intermediate, followed by bulk segregant analysis in conjunction with high-throughput sequencing. We found that this strain’s growth in xylose is governed by at least two genetic loci, within which we identified the responsible genes: one locus contains a known xylose-pathway gene, a novel homolog of the aldo-keto reductase gene GRE3, while a second locus contains a homolog of APJ1, which encodes a putative chaperone not previously connected to xylose metabolism. Our work demonstrates that the power of sequencing combined with bulk segregant analysis can also be applied to a nongenetically tractable hybrid strain that contains a complex, polygenic trait, and identifies new avenues for metabolic engineering as well as for construction of nongenetically modified xylose-fermenting strains.

Repeated-batch fermentation of lignocellulosic hydrolysate to ethanol using a hybrid Saccharomyces cerevisiae strain metabolically engineered for tolerance to acetic and formic acids

A major challenge associated with the fermentation of lignocellulose-derived hydrolysates is improved ethanol production in the presence of fermentation inhibitors, such as acetic and formic acids. Enhancement of transaldolase (TAL) and formate dehydrogenase (FDH) activities through metabolic engineering successfully conferred resistance to weak acids in a recombinant xylose-fermenting Saccharomyces cerevisiae strain. Moreover, hybridization of the metabolically engineered yeast strain improved ethanol production from xylose in the presence of both 30 mM acetate and 20mM formate. Batch fermentation of lignocellulosic hydrolysate containing a mixture of glucose, fructose and xylose as carbon sources, as well as the fermentation inhibitors, acetate and formate, was performed for five cycles without any loss of fermentation capacity. Long-term stability of ethanol production in the fermentation phase was not only attributed to the coexpression of TAL and FDH genes, but also the hybridization of haploid strains.