GC-MS-Based Metabolomics for the Smut Fungus Ustilago maydis: A Comprehensive Method Optimization to Quantify Intracellular Metabolites

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

The hidden treasures in endophytic fungi: a comprehensive review on the diversity of fungal bioactive metabolites, usual analytical methodologies, and applications

This review provides a comprehensive overview of the key aspects of the natural metabolite production by endophytic fungi, which has attracted significant attention due to its diverse biological activities and wide range of applications. Synthesized by various fungal species, these metabolites encompass compounds with therapeutic, agricultural, and commercial significance. We delved into strategies and advancements aimed at optimizing fungal metabolite production. Fungal cultivation, especially by Aspergillus, Penicillium, and Fusarium, plays a pivotal role in metabolite biosynthesis, and researchers have explored both submerged and solid-state cultivation processes to harness the full potential of fungal species. Nutrient optimization, pH, and temperature control are critical factors in ensuring high yields of the targeted bioactive metabolites especially for scaling up processes. Analytical methods that includes High-Performance Liquid Chromatography (HPLC), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Nuclear Magnetic Resonance (NMR), and Mass Spectrometry (MS), are indispensable for the identification and quantification of the compounds. Moreover, genetic engineering and metabolic pathway manipulation have emerged as powerful tools to enhance metabolite production and develop novel fungal strains with increased yields. Regulation and control mechanisms at the genetic, epigenetic, and metabolic levels are explored to fine-tune the biosynthesis of fungal metabolites. Ongoing research aims to overcome the complexity of the steps involved to ensure the efficient production and utilization of fungal metabolites.

Potential of Alpha-(α)-Solanine as a Natural Inhibitor of Fungus Causing Leaf Spot Disease in Strawberry

Curvularia trifolii is an important pathogenic fungus that causes leaf spot disease in strawberry and other crops. Increased resistance in pathogenic fungi against chemical fungicides necessitates the search for biological alternatives to control plant fungal diseases. The present study aimed to perform transcriptome and metabolome analysis of C. trifolii fungi. We evaluated the potential of an alkaloid, namely alpha (α)-solanine, to inhibit the growth of Curvularia under in vitro conditions. Furthermore, transcriptomic and metabolomic analysis of treated C. trifolii was performed to identify the differential genes and metabolites. Results revealed that treatment with α-solanine resulted in the poor growth and development of fungal spores. The transcriptome analysis revealed that 1413 genes were differentially expressed (DEGs), among which 340 unigenes were up-regulated, 100 unigenes were down-regulated, and the rest were unaffected in treated samples. Gene ontology analysis revealed that the majority of the genes were related to oxidative stress in the fungus. Additionally, using ultra-high performance liquid chromatography-tandem mass spectrometry, we identified 455 metabolites, among which the majority of metabolites were related to lipid biosynthesis. The high number of genes related to lipid biosynthesis and reactive oxygen species revealed that α-solanine causes oxidative stress in Curvularia, leading to growth inhibition, and can be potentially used as an alternative to chemical fungicides.

Renewable carbon sources to biochemicals and -fuels: contributions of the smut fungi Ustilaginaceae

The global demand for food, fuels, and chemicals increases annually. Using renewable C-sources (i.e. biomass, CO₂, and organic waste) is a prerequisite for a future free of fossil carbon. The smut fungi Ustilaginaceae naturally produce a versatile spectrum of valuable products, such as organic acids, polyols, and glycolipids, applicable in the food, energy, chemistry, and pharmaceutical sector. Combined with the use of alternative (co-)substrates (e.g. acetate, butanediol, formate, and glycerol), these microorganisms offer excellent potential for industrial biotechnology, thereby overcoming central challenges humankind faces, including CO₂ release and land use. Here, we provide insight into fundamental production capacities, present genetic modifications that improve the biotechnical application, and review recent high-performance engineering of Ustilaginaceae toward relevant platform chemicals.

Sample Preparation in Microbial Metabolomics: Advances and Challenges

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

Improved Itaconate Production with Ustilago cynodontis via Co-Metabolism of CO2-Derived Formate

In recent years, it was shown that itaconic acid can be produced from glucose with Ustilago strains at up to maximum theoretical yield. The use of acetate and formate as co-feedstocks can boost the efficiency of itaconate production with Ustilaginaceae wild-type strains by reducing the glucose amount and thus the agricultural land required for the biotechnological production of this chemical. Metabolically engineered strains (U. cynodontis Δfuz7 Δcyp3 ↑P_ria1 and U. cynodontis Δfuz7 Δcyp3 P_etefmttA ↑P_ria1) were applied in itaconate production, obtaining a titer of 56.1 g L^-1 and a yield of 0.55 g_itaconate per g_substrate. Both improved titer and yield (increase of 5.2 g L^-1 and 0.04 g_itaconate per g_substrate, respectively) were achieved when using sodium formate as an auxiliary substrate. By applying the design-of-experiments (DoE) methodology, cultivation parameters (glucose, sodium formate and ammonium chloride concentrations) were optimized, resulting in two empirical models predicting itaconate titer and yield for U. cynodontis Δfuz7 Δcyp3 P_etefmttA ↑P_ria1. Thereby, an almost doubled itaconate titer of 138 g L^-1 was obtained and a yield of 0.62 g_itaconate per g_substrate was reached during confirmation experiments corresponding to 86% of the theoretical maximum. In order to close the carbon cycle by production of the co-feed via a "power-to-X" route, the biphasic Ru-catalysed hydrogenation of CO₂ to formate could be integrated into the bioprocess directly using the obtained aqueous solution of formates as co-feedstock without any purification steps, demonstrating the (bio)compatibility of the two processes.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Evaluation and optimization of analytical procedure and sample preparation for polar Streptomyces albus J1074 metabolome profiling

Metabolomics is an essential discipline in omics technology that promotes research on the biology of microbial systems. Streptomyces albus J1074 is a model organism used in fundamental research and industrial microbiology. Nevertheless, a comprehensive and standardized method for analyzing the metabolome of S. albus J1074 is yet to be developed. Thus, we comprehensively evaluated and optimized the analytical procedure and sample preparation for profiling polar metabolites using hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry (HRMS). We systematically examined the HILIC columns, quenching solutions, sample-to-quenching ratios, and extraction methods. Then, the optimal protocol was used to investigate the dynamic intracellular polar metabolite profile of the engineered S. albus J1074 strains during spinosad (spinosyn A and spinosyn D) fermentation. A total of 3648 compounds were detected, and 83 metabolites were matched to the standards. The intracellular metabolomic profiles of engineered S. albus J1074 strains (ADE-AP and OE3) were detected; furthermore, their metabolomes in different stages were analyzed to reveal the reasons for their differences in their spinosad production, as well as the current metabolic limitation of heterologous spinosad production in S. albus J1074. The HILIC-HRMS method is a valuable tool for investigating polar metabolomes, and provides a reference methodology to study other Streptomyces metabolomes.

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A HILIC-HRMS method was developed for polar metabolome profiling.

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Sample preparation protocol for Streptomyces albus J1074 intracellular metabolites was studied for the first time.

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This study revealed the possible reasons for different production of spinosad of engineered S. albus J1074 strains.

Perspectives for the application of Ustilaginaceae as biotech cell factories

Basidiomycetes fungi of the family Ustilaginaceae are mainly known as plant pathogens causing smut disease on crops and grasses. However, they are also natural producers of value-added substances like glycolipids, organic acids, polyols, and harbor secretory enzymes with promising hydrolytic activities. These attributes recently evoked increasing interest in their biotechnological exploitation. The corn smut fungus Ustilago maydis is the best characterized member of the Ustilaginaceae. After decades of research in the fields of genetics and plant pathology, a broad method portfolio and detailed knowledge on its biology and biochemistry are available. As a consequence, U. maydis has developed into a versatile model organism not only for fundamental research but also for applied biotechnology. Novel genetic, synthetic biology, and process development approaches have been implemented to engineer yields and product specificity as well as for the expansion of the repertoire of produced substances. Furthermore, research on U. maydis also substantially promoted the interest in other members of the Ustilaginaceae, for which the available tools can be adapted. Here, we review the latest developments in applied research on Ustilaginaceae towards their establishment as future biotech cell factories.

Ustilaginaceae Biocatalyst for Co-Metabolism of CO2-Derived Substrates toward Carbon-Neutral Itaconate Production

The family Ustilaginaceae (belonging to the smut fungi) are known for their plant pathogenicity. Despite the fact that these plant diseases cause agricultural yield reduction, smut fungi attracted special attention in the field of industrial biotechnology. Ustilaginaceae show a versatile product spectrum such as organic acids (e.g., itaconate, malate, succinate), polyols (e.g., erythritol, mannitol), and extracellular glycolipids, which are considered value-added chemicals with potential applications in the pharmaceutical, food, and chemical industries. This study focused on itaconate as a platform chemical for the production of resins, plastics, adhesives, and biofuels. During this work, 72 different Ustilaginaceae strains from 36 species were investigated for their ability to (co-) consume the CO₂-derived substrates acetate and formate, potentially contributing toward a carbon-neutral itaconate production. The fungal growth and product spectrum with special interest in itaconate was characterized. Ustilago maydis MB215 and Ustilago rabenhorstiana NBRC 8995 were identified as promising candidates for acetate metabolization whereas Ustilago cynodontis NBRC 7530 was identified as a potential production host using formate as a co-substrate enhancing the itaconate production. Selected strains with the best itaconate production were characterized in more detail in controlled-batch bioreactor experiments confirming the co-substrate utilization. Thus, a proof-of-principle study was performed resulting in the identification and characterization of three promising Ustilaginaceae biocatalyst candidates for carbon-neutral itaconate production contributing to the biotechnological relevance of Ustilaginaceae.