Connecting the dots: Advances in modern metabolomics and its application in yeast system

Metabolomics applications for plant-based foods origin tracing, cultivars identification and processing: Feasibility and future aspects

Metabolomics, the systematic study of metabolites, is dedicated to a comprehensive analysis of all aspects of plant-based food research and plays a pivotal role in the nutritional composition and quality control of plant-based foods. The diverse chemical compositions of plant-based foods lead to variations in sensory characteristics and nutritional value. This review explores the application of the metabolomics method to plant-based food origin tracing, cultivar identification, and processing methods. It also addresses the challenges encountered and outlines future directions. Typically, when combined with other omics or techniques, synergistic and complementary information is uncovered, enhancing the classification and prediction capabilities of models. Future research should aim to evaluate all factors affecting food quality comprehensively, and this necessitates advanced research into influence mechanisms, metabolic pathways, and gene expression.

Metabolomic insights into the effect of chickpea protein hydrolysate on the freeze-thaw tolerance of industrial yeasts

The use of frozen dough is an intensive food-processing practice that contributes to the development of chain operations in the bakery industry. However, the fermentation activity of yeasts in frozen dough can be severely damaged by freeze-thaw stress, thereby degrading the final bread quality. In this study, chickpea protein hydrolysate significantly improved the quality of steamed bread made from frozen dough while enhancing the yeast survival rate and maintaining yeast cell structural integrity under freeze-thaw stress. The mechanism underlying this protective role of chickpea protein hydrolysate was further investigated by untargeted metabolomics analysis, which suggested that chickpea protein hydrolysate altered the intracellular metabolites associated with central carbon metabolism, amino acid synthesis, and lipid metabolism to improve yeast cell freeze-thaw tolerance. Therefore, chickpea protein hydrolysate is a promising natural antifreeze component for yeast cryopreservation in the frozen dough industry.

An assessment of AcquireX and Compound Discoverer software 3.3 for non-targeted metabolomics

We used the Exploris 240 mass spectrometer for non-targeted metabolomics on Saccharomyces cerevisiae strain BY4741 and tested AcquireX software for increasing the number of detectable compounds and Compound Discoverer 3.3 software for identifying compounds by MS2 spectral library matching. AcquireX increased the number of potentially identifiable compounds by 50% through six iterations of MS2 acquisition. On the basis of high-scoring MS2 matches made by Compound Discoverer, there were 483 compounds putatively identified from nearly 8000 candidate spectra. Comparisons to 20 amino acid standards, however, revealed instances whereby compound matches could be incorrect despite strong scores. Situations included the candidate with the top score not being the correct compound, matching the same compound at two different chromatographic peaks, assigning the highest score to a library compound much heavier than the mass for the parent ion, and grouping MS2 isomers to a single parent ion. Because the software does not calculate false positive and false discovery rates at these multiple levels where such errors can propagate, we conclude that manual examination of findings will be required post software analysis. These results will interest scientists who may use this platform for metabolomics research in diverse disciplines including medical science, environmental science, and agriculture.

Metabolomics-based development of bioproduction processes toward industrial-scale production

Microbial biomanufacturing offers a promising, environment-friendly platform for next-generation chemical production. However, its limited industrial implementation is attributed to the slow production rates of target compounds and the time-intensive engineering of high-yield strains. This review highlights how metabolomics expedites bioproduction development, as demonstrated through case studies of its integration into microbial strain engineering, culture optimization, and model construction. The Design-Build-Test-Learn (DBTL) cycle serves as a standard workflow for strain engineering. Process development, including the optimization of culture conditions and scale-up, is crucial for industrial production. In silico models facilitate the development of strains and processes. Metabolomics is a powerful driver of the DBTL framework, process development, and model construction.

Metabolomic analysis of hydroxycinnamic acid inhibition on Saccharomyces cerevisiae

Ferulic acid (FA) and p-coumaric acid (p-CA) are hydroxycinnamic acid inhibitors that are mainly produced during the pretreatment of lignocellulose. To date, the inhibitory mechanism of hydroxycinnamic acid compounds on Saccharomyces cerevisiae has not been fully elucidated. In this study, liquid chromatography-mass spectrometry (LC-MS) and scanning electron microscopy (SEM) were used to investigate the changes in S. cerevisiae cells treated with FA and p-CA. In this experiment, the control group was denoted as group CK, the FA-treated group was denoted as group F, and the p-CA-treated group was denoted as group P. One hundred different metabolites in group F and group CK and 92 different metabolites in group P and group CK were selected and introduced to metaboanalyst, respectively. A total of 38 metabolic pathways were enriched in S. cerevisiae under FA stress, and 27 metabolic pathways were enriched in S. cerevisiae under p-CA stress as identified through Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis. The differential metabolites involved included S-adenosine methionine, L-arginine, and cysteine, which were significantly downregulated, and acetyl-CoA, L-glutamic acid, and L-threonine, which were significantly upregulated. Analysis of differential metabolic pathways showed that the differentially expressed metabolites were mainly related to amino acid metabolism, nucleotide metabolism, fatty acid degradation, and the tricarboxylic acid cycle (TCA). Under the stress of FA and p-CA, the metabolism of some amino acids was blocked, which disturbed the redox balance in the cells and destroyed the synthesis of most proteins, which was the main reason for the inhibition of yeast cell growth. This study provided a strong scientific reference to improve the durability of S. cerevisiae against hydroxycinnamic acid inhibitors. KEY POINTS: • Morphological changes of S. cerevisiae cells under inhibitors stress were observed. • Changes of the metabolites in S. cerevisiae cells were explored by metabolomics. • One of the inhibitory effects on yeast is due to changes in the metabolic network.

Metabolomic analysis of black sesame seeds: Effects of processing and active compounds in antioxidant and anti-inflammatory properties

Black sesame seeds (BSS) have been recognized as a functional food due to their nutritional and therapeutic value for many years. In China, BSS is traditionally processed and consumed through two methods, namely, nine steaming nine sun-drying and stir-frying. The present study aimed to evaluate the effects of these processing techniques on the antioxidant and anti-inflammatory activities of BSS. UPLC-QTOF/MS was used for untargeted metabolomics to analyze the composition changes. The results indicated that the different samples had good antioxidant and anti-inflammatory activities, but thermal treatment reduced their activities. Untargeted metabolomics identified a total of 196 metabolites. Molecular docking studies targeting proteins associated with inflammation (iNOS) demonstrated that compounds acting as inhibitors were significantly reduced under both treatments. These results indicate that both nine steaming nine sun-drying and stir-frying lead to substantial loss of antioxidant, anti-inflammatory, and bioactive metabolites in BSS, which provides an important reference for its rational utilization.

NMR and Metabolomics-A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Metabolic Plasticity of Candida albicans in Response to Different Environmental Conditions

The ubiquitous commensal Candida albicans, part of the human microbiota, is an opportunistic pathogen able to cause a wide range of diseases, from cutaneous mycoses to life-threatening infections in immunocompromised patients. Candida albicans adapts to different environments and survives long-time starvation. The ability to switch from yeast to hyphal morphology under specific environmental conditions is associated with its virulence. Using hydrogen nuclear magnetic resonance spectroscopy, we profiled the intracellular and extracellular metabolome of C. albicans kept in water, yeast extract–peptone–dextrose (YPD), and M199 media, at selected temperatures. Experiments were carried out in hypoxia to mimic a condition present in most colonized niches and fungal infection sites. Comparison of the intracellular metabolites measured in YPD and M199 at 37 °C highlighted differences in specific metabolic pathways: (i) alanine, aspartate, glutamate metabolism, (ii) arginine and proline metabolism, (iii) glycerolipid metabolism, attributable to the diverse composition of the media. Moreover, we hypothesized that the subtle differences in the M199 metabolome, observed at 30 °C and 37 °C, are suggestive of modifications propaedeutic to a subsequent transition from yeast to hyphal form. The analysis of the metabolites’ profiles of C. albicans allows envisaging a molecular model to better describe its ability to sense and adapt to environmental conditions.

Metabolome analysis of the response and tolerance mechanisms of Saccharomyces cerevisiae to formic acid stress

Various inhibitors are produced during the hydrolysis of lignocellulosic biomass that can interfere with the growth of yeast cells and the production of bioethanol. Formic acid is a common weak acid inhibitor present in lignocellulosic hydrolysate that has toxic effects on yeast cells. However, the mechanism of the response of Saccharomyces cerevisiae to formic acid is not fully understood. In this study, liquid chromatography-mass spectrometry (LC-MS) was used to investigate the effects of formic acid treatment on cell metabolites of S. cerevisiae. Treatment with different concentrations of formic acid significantly inhibited the growth of yeast cells, reduced the yield of ethanol, prolonged the cell fermentation cycle, and increased the content of malondialdehyde. Principal component analysis and orthogonal partial least squares discriminant analysis showed that 55 metabolites were significantly altered in S. cerevisiae after formic acid treatment. The metabolic relevance of these compounds in the response of S. cerevisiae to formic acid stress was investigated. Formic acid can cause oxidative stress, inhibit protein synthesis, and damage DNA in S. cerevisiae, and these are possible reasons for the inhibition of S. cerevisiae cell growth. In addition, the levels of several aromatic amino acids identified in the cells of formic acid-treated yeast were increased; the biosynthesis of nucleotides was slowed, and energy consumption was reduced. These mechanisms may help to improve the tolerance of yeast cells to formic acid. The results described herein highlight our current understanding of the molecular mechanism of the response of S. cerevisiae to formic acid. The study will provide a theoretical basis for research on the tolerance mechanisms of S. cerevisiae.

Application of Metabolomics in the Study of Starvation-Induced Autophagy in Saccharomyces cerevisiae: A Scoping Review

This scoping review is aimed at the application of the metabolomics platform to dissect key metabolites and their intermediates to observe the regulatory mechanisms of starvation-induced autophagy in Saccharomyces cerevisiae. Four research papers were shortlisted in this review following the inclusion and exclusion criteria. We observed a commonly shared pathway undertaken by S. cerevisiae under nutritional stress. Targeted and untargeted metabolomics was applied in either of these studies using varying platforms resulting in the annotation of several different observable metabolites. We saw a commonly shared pathway undertaken by S. cerevisiae under nutritional stress. Following nitrogen starvation, the concentration of cellular nucleosides was altered as a result of autophagic RNA degradation. Additionally, it is also found that autophagy replenishes amino acid pools to sustain macromolecule synthesis. Furthermore, in glucose starvation, nucleosides were broken down into carbonaceous metabolites that are being funneled into the non-oxidative pentose phosphate pathway. The ribose salvage allows for the survival of starved yeast. Moreover, acute glucose starvation showed autophagy to be involved in maintaining ATP/energy levels. We highlighted the practicality of metabolomics as a tool to better understand the underlying mechanisms involved to maintain homeostasis by recycling degradative products to ensure the survival of S. cerevisiae under starvation. The application of metabolomics has extended the scope of autophagy and provided newer intervention targets against cancer as well as neurodegenerative diseases in which autophagy is implicated.

Systems-level approaches for understanding and engineering of the oleaginous cell factory Yarrowia lipolytica

Concerns about climate change and the search for renewable energy sources together with the goal of attaining sustainable product manufacturing have boosted the use of microbial platforms to produce fuels and high-value chemicals. In this regard, Yarrowia lipolytica has been known as a promising yeast with potentials in diverse array of biotechnological applications such as being a host for different oleochemicals, organic acid, and recombinant protein production. Having a rapidly increasing number of molecular and genetic tools available, Y. lipolytica has been well studied amongst oleaginous yeasts and metabolic engineering has been used to explore its potentials. More recently, with the advancement in systems biotechnology and the implementation of mathematical modeling and high throughput omics data-driven approaches, in-depth understanding of cellular mechanisms of cell factories have been made possible resulting in enhanced rational strain design. In case of Y. lipolytica, these systems-level studies and the related cutting-edge technologies have recently been initiated which is expected to result in enabling the biotechnology sector to rationally engineer Y. lipolytica-based cell factories with favorable production metrics. In this regard, here, we highlight the current status of systems metabolic engineering research and assess the potential of this yeast for future cell factory design development.