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Bioethanol has gained popularity in recent decades as an ecofriendly alternative to fossil fuels due to increasing concerns about global climate change. However, economically viable ethanol fermentation remains a challenge. High-temperature fermentation can reduce production costs, but Saccharomyces cerevisiae yeast strains normally ferment poorly under high temperatures. In this study, we present a machine learning (ML) approach to optimize bioethanol production in S. cerevisiae by fine-tuning the promoter activities of three endogenous genes. We created 216 combinatorial strains of S. cerevisiae by replacing native promoters with five promoters of varying strengths to regulate ethanol production. Promoter replacement resulted in a 63% improvement in ethanol production at 30 °C. We created an ML-guided workflow by utilizing XGBoost to train high-performance models based on promoter strengths and cellular metabolite concentrations obtained from ethanol production of 216 combinatorial strains at 30 °C. This strategy was then applied to optimize ethanol production at 40 °C, where we selected 31 strains for experimental fermentation. This reduced experimental load led to a 7.4% increase in ethanol production in the second round of the ML-guided workflow. Our study offers a comprehensive library of promoter strength modifications for key ethanol production enzymes, showcasing how machine learning can guide yeast strain optimization and make bioethanol production more cost-effective and efficient. Furthermore, we demonstrate that metabolic engineering processes can be accelerated and optimized through this approach.

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d-lactic acid, a chiral organic acid, can enhance the thermal stability of polylactic acid plastics. Microorganisms such as the yeast Pichia pastoris, which lack the natural ability to produce or accumulate high amounts of d-lactic acid, have been metabolically engineered to produce it in high titers. However, tolerance to d-lactic acid remains a challenge. In this study, we demonstrate that cell flocculation improves tolerance to d-lactic acid and increases d-lactic acid production in Pichia pastoris. By incorporating a flocculation gene from Saccharomyces cerevisiae (ScFLO1) into P. pastoris KM71, we created a strain (KM71-ScFlo1) that demonstrated up to a 1.6-fold improvement in specific growth rate at high d-lactic acid concentrations. Furthermore, integrating a d-lactate dehydrogenase gene from Leuconostoc pseudomesenteroides (LpDLDH) into KM71-ScFlo1 resulted in an engineered strain (KM71-ScFlo1-LpDLDH) that could produce d-lactic acid at a titer of 5.12 ± 0.35 g/L in 48 h, a 2.6-fold improvement over the control strain lacking ScFLO1 expression. Transcriptomics analysis of this strain provided insights into the mechanism of increased tolerance to d-lactic acid, including the upregulations of genes involved in lactate transport and iron metabolism. Overall, our work represents an advancement in the efficient microbial production of d-lactic acid by manipulating yeast flocculation.

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Lactic acid (LA) is a promising bio-based chemical that has broad applications in food, nutraceutical, and bioplastic industries. However, production of the D-form of LA (D-LA) from fermentative organisms is lacking. In this study, Saccharomyces cerevisiae harboring the D-lactate dehydrogenase (DLDH) gene from Leuconostoc mesenteroides was constructed (CEN.PK2_DLDH). To increase D-LA production, the CRISPR/Cas12a system was used for the deletion of gpd1, gpd2, and adh1 to minimize glycerol and ethanol production. Although an improved D-LA titer was observed for both CEN.PK2_DLDHΔgpd and CEN.PK2_DLDHΔgpdΔadh1, growth impairment was observed. To enhance the D-LA productivity, CEN.PK2_DLDHΔgpd was crossed with the weak acid-tolerant S. cerevisiae BCC39850. The isolated hybrid2 showed a maximum D-LA concentration of 23.41 ± 1.65 g/L, equivalent to the improvement in productivity and yield by 2.2 and 1.5 folds, respectively. The simultaneous saccharification and fermentation using alkaline pretreated sugarcane bagasse by the hybrid2 led to an improved D-LA conversion yield on both the washed solid and whole slurry (0.33 and 0.24 g/g glucan). Our findings show the exploitation of natural yeast diversity and the potential strategy of gene editing combined with conventional breeding on improving the performance of S. cerevisiae for the production of industrially potent products.

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As the effects of climate change become increasingly severe, metabolic engineers and synthetic biologists are looking towards greener sources for transportation fuels. The design and optimization of microorganisms to produce gasoline, diesel, and jet fuel compounds from renewable feedstocks can significantly reduce dependence on fossil fuels and thereby produce fewer emissions. Over the past two decades, a tremendous amount of research has contributed to the development of microbial strains to produce advanced fuel compounds, including branched-chain higher alcohols (BCHAs) such as isopentanol (3-methyl-1-butanol; 3M1B) and isobutanol (2-methyl-1-propanol). In this review, we provide an overview of recent advances in the development of microbial strains for the production of isopentanol in both conventional and non-conventional hosts. We also highlight metabolic engineering strategies that may be employed to enhance product titers, reduce end-product toxicity, and broaden the substrate range to non-sugar carbon sources. Finally, we offer glimpses into some promising future directions in the development of isopentanol producing microbial strains.

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D-lactic acid is a chiral three-carbon organic acid that can improve the thermostability of polylactic acid. Here, we systematically engineered Saccharomyces cerevisiae to produce D-lactic acid from glucose, a renewable carbon source, at near theoretical yield. Specifically, we screened D-lactate dehydrogenase (DLDH) variants from lactic acid bacteria in three different genera and identified the Leuconostoc pseudomesenteroides variant (LpDLDH) as having the highest activity in yeast. We then screened single-gene deletions to minimize the production of the side products ethanol and glycerol as well as prevent the conversion of D-lactic acid back to pyruvate. Based on the results of the DLDH screening and the single-gene deletions, we created a strain called ASc-d789M which overexpresses LpDLDH and contains deletions in glycerol pathway genes GPD1 and GPD2 and lactate dehydrogenase gene DLD1, as well as downregulation of ethanol pathway gene ADH1 using the L-methionine repressible promoter to minimize impact on growth. ASc-d789M produces D-lactic acid at a titer of 17.09 g/L in shake-flasks (yield of 0.89 g/g glucose consumed or 89% of the theoretical yield). Fed-batch fermentation resulted in D-lactic acid titer of 40.03 g/L (yield of 0.81 g/g glucose consumed). Altogether, our work represents progress towards efficient microbial production of D-lactic acid.

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A cDNA encoding ß-mannanase was cloned from Aspergillus niger BCC4525 and expressed in Pichia pastoris KM71. The secreted enzyme hydrolyzed locust bean gum substrate with very high activity (1625 U/mL) and a relatively high kcat/Km (461 mg-1 s-1 mL). The enzyme is thermophilic and thermostable with an optimal temperature of 70 °C and 40% retention of endo-ß-1,4-mannanase activity after preincubation at 70 °C. In addition, the enzyme exhibited broad pH stability with an optimal pH of 5.5. The recombinant enzyme hydrolyzes low-cost biomass, including palm kernel meal (PKM) and copra meal, to produce mannooligosaccharides, which is used as prebiotics to promote the growth of beneficial microflora in animals. An in vitro digestibility test simulating the gastrointestinal tract system of broilers suggested that the recombinant ß-mannanase could effectively liberate reducing sugars from PKM-containing diet. These characteristics render this enzyme suitable for utilization as a feed additive to improve animal performance.

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The thermotolerant methylotrophic yeast Ogataea thermomethanolica is a host for heterologous protein expression via secretion to the culture medium. Efficient secretion is a major bottleneck for heterologous protein production in this strain. To improve protein secretion, we explored whether the use of a native signal peptide sequence for directing heterologous protein secretion and overexpression of native ER-resident chaperone genes could improve heterologous protein secretion in O. thermomethanolica. We cloned and characterized genes encoding α-mating factor (Otα-MF) and ER-resident chaperones OtBiP, OtCNE1, and OtPDI. The pre and pre-pro sequences of Otα-MF were shown to promote higher secretion of heterologous endoxylanase comparing with the classical pre-pro sequence of Saccharomyces cerevisiae. However, in the case of heterologous glycosylated phytase, only the Otα-MF pre-pro sequence significantly enhanced protein secretion. The effect of chaperone overexpression on heterologous protein secretion was tested in cotransformant cells of O. thermomethanolica. Overexpression of ER-resident chaperones improved protein secretion depending on heterologous protein. Overexpression of OtBiP, OtCNE1, and OtPDI significantly increased unglycosylated endoxylanase secretion at both 30 and 37 °C while only OtBiP overexpression enhanced glycosylated phytase secretion at 30 °C. These observations suggested the possibility to improve heterologous protein secretion in O. thermomethanolica.

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