Advances in Metabolomics-Driven Diagnostic Breeding and Crop Improvement

Extensive targeted metabolomics analysis reveals the identification of major metabolites, antioxidants, and disease-resistant active pharmaceutical components in Camellia tuberculata (Camellia L.) seeds

Sect. tuberculata plant belongs to the Camellia genus and is named for the "tuberculiform protuberance on the surface of the ovary and fruit". It is a species of great ornamental value and potential medicinal value. However, little has been reported on the metabolites of C. tuberculata seeds. Therefore, this study was conducted to investigate the metabolites of C. tuberculata seeds based on UPLC/ESI-Q TRAP-MS/MS with extensively targeted metabolomics. A total of 1611 metabolites were identified, including 107 alkaloids, 276 amino acids and derivatives, 283 flavonoids, 86 lignans and coumarins, 181 lipids, 68 nucleotides and derivatives, 101 organic acids, 190 phenolic acids, 10 quinones, 4 steroids, 17 tannins, 111 terpenoids, and 177 other metabolites. We compared the different metabolites in seeds between HKH, ZM, ZY, and LY. The 1311 identified different metabolites were classified into three categories. Sixty-three overlapping significant different metabolites were found, of which lignans and coumarins accounted for the largest proportion. The differentially accumulated metabolites were enriched in different metabolic pathways between HKH vs. LY, HKH vs. ZM, HKH vs. ZY, LY vs. ZY, ZM vs. LY and ZM vs. ZY, with the most abundant metabolic pathways being 4, 2, 4, 7, 7 and 5, respectively (p < 0.05). Moreover, among the top 20 metabolites in each subgroup comparison in terms of difference multiplicity 7, 8 and 13. ZM and ZY had the highest phenolic acid content. Ninety-six disease-resistant metabolites and 48 major traditional Chinese medicine agents were identified based on seven diseases. The results of this study will not only lead to a more comprehensive and in-depth understanding of the metabolic properties of C. tuberculata seeds, but also provide a scientific basis for the excavation and further development of its medicinal value.

Evaluation of normalization strategies for GC-based metabolomics

INTRODUCTION

For many samples studied by GC-based metabolomics applications, extensive sample preparation involving extraction followed by a two-step derivatization procedure of methoximation and trimethylsilylation (TMS) is typically required to expand the metabolome coverage. Performing normalization is critical to correct for variations present in samples and any biases added during the sample preparation steps and analytical runs. Addressing the totality of variations with an adequate normalization method increases the reliability of the downstream data analysis and interpretation of the results.

OBJECTIVES

Normalizing to sample mass is one of the most commonly employed strategies, while the total peak area (TPA) as a normalization factor is also frequently used as a post-acquisition technique. Here, we present a new normalization approach, total derivatized peak area (TDPA), where data are normalized to the intensity of all derivatized compounds. TDPA relies on the benefits of silylation as a universal derivatization method for GC-based metabolomics studies.

METHODS

Two sample classes consisting of systematically incremented sample mass were simulated, with the only difference between the groups being the added amino acid concentrations. The samples were TMS derivatized and analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS). The performance of five normalization strategies (no normalization, normalized to sample mass, TPA, total useful peak area (TUPA), and TDPA) were evaluated on the acquired data.

RESULTS

Of the five normalization techniques compared, TUPA and TDPA were the most effective. On PCA score space, they offered a clear separation between the two classes.

CONCLUSION

TUPA and TDPA carry different strengths: TUPA requires peak alignment across all samples, which depends upon the completion of the study, while TDPA is free from the requirement of alignment. The findings of the study would enhance the convenient and effective use of data normalization strategies and contribute to overcoming the data normalization challenges that currently exist in the metabolomics community.

Genetic and Metabolite Variability among Commercial Varieties and Advanced Lines of Vicia faba L

Vicia faba L. (faba bean) is one of the most promising pulse crops due to its nutritional value and high nitrogen fixation capacity. The aim of the present study was to compare the genetic diversity and the seed metabolite profiles of five genetic materials of faba bean. Specifically, three newly developed advanced lines (KK18, KK14 and KK10) and two commercial cultivars (POLIKARPI and TANAGRA), were evaluated for this purpose. Genetic diversity among populations was assessed by SCoT molecular markers. Through UPGMA dendrogram, genetic distances between populations were estimated. Untargeted metabolomics analysis of the seeds was performed employing GC/EI/MS. The cultivar POLYKARPI exhibited the highest polymorphism. All varieties showed a higher within-cultivars and advanced lines variability than between. POLYKARPI and KK14 had the lowest genetic distances, while KK18 and TANAGRA presented the highest ones. The advanced line KK18 displayed the best nutritional profile, the highest concentration of desirable metabolites (lactic acid and trehalose), the lowest concentration of anti-nutritional factors (oxalic acid) and the lowest concentration of saturated fatty acids (palmitic and stearic acid). According to the results of the present study, KK18 line is a very promising material for further exploration and utilization in breeding programs.

An integrated genomic and biochemical approach to investigate the potentiality of heirloom tomatoes: Breeding resources for food quality and sustainable agriculture

A revival of interest in traditional varieties reflects the change in consumer preferences and the greater awareness of the quality of locally grown products. As ancient cultivars, heirlooms have been selected for decades in specific habitats and represent nowadays potential germplasm sources to consider for breeding high-quality products and cultivation in sustainable agriculture. In this study, 60 heirloom tomato (Solanum lycopersicum L.) accessions, including diverse varietal types (beefsteak, globe, oxheart, plum, and cherry), were profiled over two seasons for the main chemical and biochemical fruit traits. A medium-high level of heritability was found for all traits ranging from 0.52 for soluble solids to 0.99 for fruit weight. The average content of ascorbic acid was ~31 mg 100 g^-1 of fw in both seasons, while the greatest variability was found for carotenoids with peaks of 245.65 μg g^-1 of fw for total lycopene and 32.29 μg g^-1 of fw for β-carotene. Dissection of genotypic (G) and seasonal (Y) factors highlighted genotype as the main source of variation for all traits. No significant effect of Y and G × Y was found for ascorbic acid and fruit weight, respectively, whereas a high influence of Y was found on the variation of lycopene. Molecular fingerprinting was performed using the 10K SolCAP array, yielding a total of 7,591 SNPs. Population structure, phylogenetic relationships, and principal components analysis highlighted a differentiation of plum and cherry genotypes with respect to the beefsteak and globe types. These results were confirmed by multivariate analysis of phenotypic traits, shedding light on how breeding and selection focused on fruit characteristics have influenced the genetic and phenotypic makeup of heirlooms. Marker-trait association showed 11 significantly associated loci for β-carotene and fruit weight. For β-carotene, a single variant on chromosome 8 was found at 12 kb to CCD8, a cleavage dioxygenase playing a key role in the biosynthesis of apocarotenoids. For fruit weight, a single association was located at less than 3 Mbp from SLSUN31 and fw11.3, two candidates involved in the increasing of fruit mass. These results highlight the potentiality of heirlooms for genetic improvement and candidate gene identification.

Unveiling Chemical Interactions Between Plants and Fungi Using Metabolomics Approaches

Metabolomics has been extensively used in clinical studies in the search for new biomarkers of human diseases. However, this approach has also been highlighted in agriculture and biological sciences, once metabolomics studies have been assisting researchers to deduce new chemical mechanisms involved in biological interactions that occur between microorganisms and plants. In this sense, the knowledge of the biological role of each metabolite (virulence factors, signaling compounds, antimicrobial metabolites, among others) and the affected biochemical pathways during the interaction contribute to a better understand of different ecological relationships established in nature. The current chapter addresses five different applications of the metabolomics approach in fungal-plant interactions research: (1) Discovery of biomarkers in pathogen-host interactions, (2) plant diseases diagnosis, (3) chemotaxonomy, (4) plant defense, and (5) plant resistance; using mass spectrometry and/or nuclear magnetic resonance spectroscopy, which are the techniques most used in metabolomics.

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.

Nutraceutical Properties of Medicago sativa L., Agave Spp., Zea mays L. and Avena sativa L.: A Review of Metabolites and Mechanisms

Plants are the main sources of bioactive compounds (nutraceuticals) that function under different mechanisms of action for the benefit of human health. Mexico ranks fifth in the world in biodiversity, offering opportunities for healthy food. An important variety of crops are produced in the state of Hidalgo, e.g., based on the 2021 production, alfalfa, oats, maguey, and corn. The present review presents the latest findings of these crops, regarding the benefits they provide to health (bioactivity, nutraceuticals), and presents the compounds and mechanisms identified by which the benefit is provided. The knowledge compiled here is for the benefit of the recovery of the crops, the recognition of their bioactivities, in search of identifying the best routes of action for prevention, treatment and possible cure of chronic degenerative diseases (thereby promoting crop valorization). Exhaustive bibliographic research was carried out by means of engines and scientific databases. Articles published between 2001 and 2022 that included specific keywords (Scopus, EMBASE, EBSCO, PubMed, Science Direct, Web of Science, Google Scholar). Outstanding activities have been identified for the compounds in the crops, such as antiinflammatory, anticholesterolemic, antihypertensive, antidiabetic, anticancer, antimicrobial, antioxidant, and chelating. The compounds that provide these properties are total phenols, phenolic acids, tannins, anthocyanins, carotenoids, iso-flavones, phytosterols, saponins, fructans, glycosides, glucans, avenanthramides, and polysaccharides.