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PubMed2026

Genomic features, metabolism, and biotechnological applications of Candida tropicalis and other non-albicans Candida species.

The production of bio-based products by yeasts from agroindustrial byproducts is a key strategy for advancing circular bioeconomy. While Saccharomyces species remain the predominant industrial yeasts, their limited ability to assimilate lactose, pentoses, and glycerol, as well as their sensitivity to lignocellulose-derived inhibitors, restricts their efficient application in bioprocesses based on using industrial byproducts as fermentation media. In contrast, several non-albicans Candida species exhibit broad substrate utilization capacities and enhanced tolerance to industrial stresses, making them attractive candidates for the bioconversion of agroindustrial residues. This review critically examines recent advances in the genomic, metabolic, and physiological characterization of promising non-albicans Candida species, including Candida tropicalis, Candida parapsilosis, Candida viswanathii, Candida sojae, and Candida maltosa. Emphasis is given to genome-scale metabolic models, carbon assimilation pathways, stress-response mechanisms, and metabolic engineering approaches aiming at the production of value-added compounds. By identifying current achievements, knowledge gaps, and biotechnological bottlenecks, this review highlights the potential of these yeasts as emerging platforms for sustainable bioprocesses within a circular bioeconomy framework.

Biotechnology↗
PubMed2025

Comparison of stress tolerance mechanisms between Saccharomyces cerevisiae and the multistress-tolerant Pichia kudriavzevii.

Yeasts play a vital role in both research and industrial biomanufacturing. Saccharomyces cerevisiae has been extensively utilized as a model system. However, its application is often constrained by limited tolerance to the diverse stress conditions encountered in bioprocesses. These challenges have driven increasing interest in nonconventional, multistress-tolerant yeasts as alternative biomanufacturing hosts. This review highlights Pichia kudriavzevii as a promising nonconventional yeast for industrial applications. Unlike S. cerevisiae, P. kudriavzevii exhibits exceptional tolerance to high temperatures, elevated concentrations of furanic and phenolic inhibitors, osmotic stress, salinity, and extreme pH. These traits make it an attractive candidate for industrial processes without requiring extensive genetic modifications to enhance stress resistance. As a result, P. kudriavzevii has emerged as a flagship species for advancing bioeconomy. Despite its industrial potential, the molecular mechanisms underlying P. kudriavzevii's superior stress tolerance remain poorly understood. This review compiles current knowledge on P. kudriavzevii and compares its stress tolerance mechanisms with those of S. cerevisiae, providing insights into its innate resilience. By expanding our understanding of nonconventional yeasts, this review aims to facilitate their broader adoption as robust microbial platforms for industrial biomanufacturing.

Saccharomyces cerevisiae↗
PubMed2026

Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.

The escalating generation of global vegetable waste represents a critical loss of bioactive resources, necessitating a paradigm shift from passive disposal to active nutrient upcycling. However, the industrial conversion of this heterogeneous biomass into standardized functional food ingredients is currently impeded by significant techno-economic barriers, primarily structural recalcitrance, compositional inconsistency, and the presence of toxic fermentation inhibitors. This review provides a comprehensive analysis of the synergistic application of microbial engineering and artificial intelligence (AI) to resolve these bioprocessing bottlenecks within a food-to-food closed-loop framework (as shown in the graphical abstract). We evaluate recent advances in engineering food-grade microbial chassis (e.g., Saccharomyces cerevisiae and Escherichia coli) to enhance lignocellulose degradation and stress tolerance. Concurrently, we examine the integration of AI across the entire value chain, covering deep learning-based rational enzyme design, genome-scale metabolic modeling, and intelligent process control for precision fermentation. Current evidence demonstrates that the hardware-software coupling of engineered strains and AI algorithms significantly enhances conversion efficiency and process robustness. Key findings highlight that AI-driven Design-Build-Test-Learn cycles facilitate the de novo creation of enzymes with superior kinetics and strains with adaptive stress response capabilities against toxins. Moreover, dynamic digital twin models effectively mitigate the impact of substrate variability, ensuring the batch-to-batch consistency required for food applications. We conclude that this data-driven synergistic paradigm is pivotal for establishing a resilient circular bioeconomy, enabling the reliable bioconversion of waste into high-value single-cell proteins, natural flavor additives, and sustainable packaging materials.

Artificial Intelligence↗
PubMed2026

A dual-dimensional CRISPR toolkit enables one-step high-efficiency multiplex genome editing in Komagataella phaffii.

Against the backdrop of green biomanufacturing, engineering methanol-utilizing Komagataella phaffii (K. phaffii) represents an effective strategy to expand the one carbon (C1) product profile and speed up the industrialization of C1-based bioeconomy. To address the technical challenges of low efficiency and cumbersome experimental procedures for multiplex gene editing and precise large-fragment integration during the reconstruction of complex metabolic pathways in K. phaffii, this study established a CRISPR toolkit - Efficient Multi-Gene Editing System 3.0 (EMGES 3.0) - which enabled one-step large-fragment integration coupled with multiplex gene knockout. EMGES 3.0 was constructed through the synergistic optimization of a repair-engineered chassis and an episomal CRISPR vector. For chassis engineering, five DNA repair modules: Δlig4 (DNA Ligase IV, non-homologous end joining end ligation), ppMRE11(The endogenous MRE11 gene from Pichia pastoris) overexpression (The Meiotic Recombination 11, DNA double-strand break end resection), Δrad9 (Radiation-Sensitive 9, DNA damage checkpoint regulation), Δmph1 (Mutator Phenotype Helicase 1, improvement of homologous recombinant strand extension), and PapRecT-PaSSB co-expression (stabilization of recombination intermediates) were integrated to generate the highly recombinogenic strain Y09. For vector engineering, cenARS was replaced by panARS and the endogenous promoter PGAP was employed to drive the double hammerhead ribozyme-single guide RNA-hepatitis delta virus ribozyme (double HH-sgRNA-HDV: dHgH)-mediated sgRNA expression, yielding the optimized vector Nov_pGAP_panARS_pLAT1_Cas9. These two features on K. phaffii together enhanced the EMGES 3.0 to a higher standard of transformation rate and editing efficiency. According to our results, EMGES 3.0 achieved dual-functional gene knockout efficiencies between 76.6% and 100%. For insertion of medium-long fragments (>4.5 kb), the efficiency achieved 93.3%. In addition, the one-step integration of ultra-long fragments (>16 kb) achieved 14.8%, which was reported for the first time. Furthermore, the efficiency of simultaneous long-fragment integration at three neutral loci reached 38.4% (>15 kb). We applied the system for one-step production of free fatty acids (FFAs, yield: 5.82 ∼ 7.30 mg/L/OD600) and resveratrol (yield: 1.14 ∼ 1.28 mg/L) using methanol as the sole carbon source. EMGES 3.0 provides a robust technical foundation for complex compounds biosynthesis and high-yield industrial strains, while also advancing K. phaffii as an industrial synthetic biology chassis for efficient C1 utilization.

CRISPR-Cas Systems↗
PubMed2026

Unveiling the Molecular Secrets of Seaweeds: A Comprehensive Review of Bioinformatics Applications in Algal Research.

Recent advances in high-throughput sequencing, bioinformatics, and multi-omics technologies have transformed seaweed research by overcoming long-standing challenges associated with complex genomes, diverse life cycles, and limited genomic resources. This review provides a comprehensive overview of bioinformatics approaches used to investigate seaweed genomics, transcriptomics, proteomics, metabolomics, microbiomes, and functional genomics, with emphasis on the computational tools and databases that support these analyses. Applications of bioinformatics in phylogenetics, drug discovery, microbiome characterization, and the development of biofuels, nutraceuticals, pharmaceuticals, and sustainable agriculture are also discussed. Particular attention is given to emerging strategies involving multi-omics integration, genome editing, artificial intelligence, machine learning, and synthetic biology that are reshaping seaweed research. The review further examines current challenges, including incomplete genomic resources, data standardization, and the need for experimental validation of computational predictions. Collectively, these advances highlight the growing role of bioinformatics in enabling systems-level understanding of seaweed biology and accelerating their translation into sustainable biotechnological and marine bioeconomy applications.

macroalgal genomics↗
PubMed2025

Advances in the Genus Ulva Research: From Structural Diversity to Applied Utility.

The green macroalgae Ulva Linnaeus, 1753, also known as sea lettuce, is one of the most ecologically and economically significant algal genera. Its representatives occur in marine, brackish, and freshwater environments worldwide and show high adaptability, rapid growth, and marked biochemical diversity. These traits support their ecological roles in nutrient cycling, primary productivity, and habitat provision, and they also explain their growing relevance to the blue bioeconomy. This review summarizes current knowledge of Ulva biodiversity, taxonomy, and physiology, and evaluates applications in food, feed, bioremediation, biofuel, pharmaceuticals, and biomaterials. Particular attention is given to molecular approaches that resolve taxonomic difficulties and to biochemical profiles that determine nutritional value and industrial potential. This review also considers risks and limitations. Ulva species can act as hyperaccumulators of heavy metals, microplastics, and organic pollutants, which creates safety concerns for food and feed uses and highlights the necessity of strict monitoring and quality control. Technical and economic barriers restrict large-scale use in energy and material production. By presenting both opportunities and constraints, this review stresses the dual role of Ulva as a promising bioresource and a potential ecological risk. Future research must integrate molecular genetics, physiology, and applied studies to support sustainable utilization and ensure safe contributions of Ulva to biodiversity assessment, environmental management, and bioeconomic development.

algal bloom↗
PubMed2026

Integration of domestic wastewater and native Tetradesmus obliquus for bioremediation and production of biomass rich in protein and polyunsaturated fatty acids.

The large-scale deployment of microalgae-based bioprocesses is often limited by high freshwater and nutrient demands. Domestic wastewater represents a sustainable alternative, enabling simultaneous pollutant removal and biomass production. In this study, a native strain of Tetradesmus obliquus, isolated in southern Brazil, was cultivated in raw domestic wastewater (RDW) and primary-treated domestic wastewater (TDW) at three initial inoculum densities (10%, 20%, and 30% v/v) for 14 days. Tetradesmus obliquus in TDW inoculated at 10% (v/v) removed 62.46% of ammonium and 98.56% of phosphate, simultaneously exhibiting the highest specific growth rate (0.16 d⁻1) and the highest biomass productivity (42.54 mg L⁻1 d⁻1). Iron and manganese concentrations decreased significantly with a native strain in TDW, indicating effective removal of them under the evaluated conditions. RDW was associated with higher carbohydrate accumulation (32.68%) and pigment production, whereas TDW was associated with higher protein content (45.83%) and a lipid fraction with a high relative proportion of polyunsaturated fatty acids (72.70-78.90%), primarily represented by α-linolenic and linoleic acids. The combined assessment of wastewater condition and initial inoculum density revealed distinct effects on the cultivation system. These aspects influence the biochemical composition of biomass, initial inoculum density, nutrient removal, specific growth rate, and biomass productivity. Thus, the present study supports the potential to integrate domestic wastewater treatment with the cultivation of a native Tetradesmus obliquus strain and indicates that, under the evaluated conditions, both the wastewater treatment conditions and the initial inoculum density influenced bioremediation performance and the biochemical composition of biomass.

Biochemical composition↗
PubMed2026

Compost microbiomes as reservoirs of cellulolytic microorganisms for cellulosic textile degradation.

Cellulosic textiles, constituting over 30% of global fibre production, are biodegradable but remain challenging to recycle at scale owing to their high crystallinity, chemical finishes, and heterogeneous waste streams. Although microorganisms drive cellulose turnover in natural ecosystems, their potential for transforming anthropogenic cellulosic waste remains largely unexplored. In this study, composting was evaluated both as a sustainable approach to textile biodegradation and a reservoir of cellulolytic microorganisms with biotechnological potential. Biodegradation assays of cotton and lyocell were integrated with shotgun metagenomics and targeted cultivation to identify microbial taxa and enzymes involved in cellulose degradation. Composting trials showed that degradation was strongly influenced by both composting system and fibre composition. Community composting achieved near-complete textile disintegration, while shredded textiles exhibited the highest degradation rates, reaching up to 97%. Shotgun metagenomic revealed a bacterial-dominated community enriched in Actinomycetota and Bacillota and characterised by an abundance of glycoside hydrolases. Culture-based screening recovered 62 microbial isolates, of which Neurospora and Aspergillus exhibited the highest cellulolytic activity (>60%). In vitro assays further showed that cotton was more readily degraded than lyocell, with several isolates achieving >70% mass loss. Metagenomic approach revealed a predominantly bacterial composting community at the sampled stage, whereas cultivation preferentially recovered fungi that, despite their low relative abundance in situ, exhibited strong cellulolytic potential. These findings highlight the potential of composting as a sustainable end-of-life strategy for cellulosic textiles and identify compost microbiomes as valuable reservoirs of cellulolytic microorganisms for the development of sustainable bioprocesses for textile waste treatment.

Cellulose↗
PubMed2026

Yeast Strain Development and Process Intensification in High-Gravity Fermentation.

High- and very-high-gravity (HG/VHG) fermentation increases substrate loading and product titers, thereby improving fermenter utilisation and potentially reducing water use and downstream processing requirements. Initially developed for brewing and fuel ethanol production, these approaches are now applied more broadly in food, beverage, and bioproduct manufacturing. This MiniReview summarises operational definitions and industrial drivers of HG/VHG fermentation and examines the associated constraints in rheology, mass and heat transfer, osmotic and ethanol stress, nutrient availability, and oxidative damage. Yeast improvement strategies are reviewed, including adaptive laboratory evolution, mutagenesis, genome shuffling, multiplex genome editing, non-conventional yeasts, and multi-omics-guided selection. Process developments such as no-cook simultaneous liquefaction, saccharification and fermentation (SLSF), enzyme formulation, nutrient management, and in situ product recovery are considered together with applications in alcoholic beverages, organic acids, microbial lipids, and other value-added products. The review also discusses coproduct valorisation and the need to integrate strain development with process design. Current evidence supports HG/VHG fermentation as a useful process-intensification platform, although performance and sustainability depend strongly on feedstock, operating conditions, product requirements, and the basis used to report fermentation outcomes.

circular bioeconomy↗