The application of pseudotargeted metabolomics method for fruit juices discrimination

Establishment of a novel large-scale targeted metabolomics method based on NFSWI-DDA mode utilizing HRMS and TQ-MS

Metabolites identification is the major bottleneck in untargeted LC-MS metabolomics, primarily due to the limited availability of MS2 information for most detected metabolites in data dependent acquisition (DDA) mode. To solve this problem, we have integrated the iterative, interval, and segmented window acquisition concepts to develop an innovative non-fixed segmented window interval data dependency acquisition (NFSWI-DDA) mode, which achieves comparable MS2 coverage to data independent acquisition (DIA) mode. This acquisition strategy harnesses the strengths of both DDA and DIA, which could provide extensive coverage and excellent reproducibility of MS2 spectra. Furthermore, utilizing the NFSWI-DDA data, we successfully acquired and identified a large-scale of multiple reaction monitoring (MRM) ion pairs, and transitioned them from high-resolution mass spectrometry (HRMS) to triple quadrupole mass spectrometry (TQ-MS). At last, a large-scale targeted metabolomics method was established practically. This method enables targeted analysis of 475 endogenous metabolites encompassing amino acids, nucleotides, bile acids, fatty acids, and carnitines, which could cover 9 major metabolic pathways as well as 65 secondary metabolic pathways. The established targeted method allows for semi-quantitative assessment of 475 metabolites while enabling quantitative analysis of 327 specific metabolites in biological samples. The method demonstrates immense potential in the detection of various biological samples, offering robust technical support and generating extensive data to advance applications in precision medicine and life sciences.

A Multi-Omics View of Maize's (Zea mays L.) Response to Low Temperatures During the Seedling Stage

Maize (Zea mays L.) is highly sensitive to temperature during its growth and development stage. A 1 °C drop in temperature can delay maturity by 10 days, resulting in a yield reduction of over 10%. Low-temperature tolerance in maize is a complex quantitative trait, and different germplasms exhibit significant differences in their responses to low-temperature stress. To explore the differences in gene expression and metabolites between B144 (tolerant) and Q319 (susceptible) during germination under low-temperature stress and to identify key genes and metabolites that respond to this stress, high-throughput transcriptome sequencing was performed on the leaves of B144 and Q319 subjected to low-temperature stress for 24 h and their respective controls using Illumina HiSeqTM 4000 high-throughput sequencing technology. Additionally, high-throughput metabolite sequencing was conducted on the samples using widely targeted metabolome sequencing technology. The results indicated that low-temperature stress triggered the accumulation of stress-related metabolites such as amino acids and their derivatives, lipids, phenolic acids, organic acids, flavonoids, lignin, coumarins, and alkaloids, suggesting their significant roles in the response to low temperature. This stress also promoted gene expression and metabolite accumulation involved in the flavonoid biosynthesis pathway. Notably, there were marked differences in gene expression and metabolites related to the glyoxylate and dicarboxylate metabolism pathways between B144 and Q319. This study, through multi-omics integrated analysis, provides valuable insights into the identification of metabolites, elucidation of metabolic pathways, and the biochemical and genetic basis of plant responses to stress, particularly under low-temperature conditions.

Comparative metabolomics profiling highlights unique color variation and bitter taste formation of Chinese cherry fruits

Chinese cherry [Cerasus pseudocerasus (Lindl.) G.Don], native to China, is an economically important fruit crop with attractive colors and delicious flavors. However, the specific metabolites present in cherry fruits have remained unknown. Here, we firstly characterized 1439 metabolite components of Chinese cherry fruits, predominantly including amino acids, flavonoids, and phenolic acids. Moreover, we screened ten biomarkers of Chinese cherry accessions by ROC curve analysis. Among 250 flavonoids, 26 structurally unique anthocyanins collectively determined fruit color, with cyanidins playing a dominant role. Differences in accumulated metabolites between anthocyanin and proanthocyanidin pathways were likely responsible for the variation in fruit color, ranging from yellow to black purple. Meanwhile, we found limocitrin-7-O-glucoside, along with eight other compounds, as underlying contributors to bitter off-taste experienced in fruits. This study provides insights into the regulatory network of metabolites involved in color variation and bitterness formation and genetic improvement of Chinese cherry fruits.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

Identification strategy of Fructus Gardeniae and its adulterant based on UHPLC/Q-orbitrap-MS and UHPLC-QTRAP-MS/MS combined with PLS regression model

Fructus Gardeniae (FG) is the desiccative and ripe fruits of Gardenia jasminoides Ellis in the Rubiaceae family, which is a commonly used in traditional Chinese medicine (TCM) for clearing away heat, detoxification, relieving restlessness, and eliminating blood stasis. At the same time, it has also been announced as the first batch of TCM with homology of medicine and food. Fructus Gardeniae Grandiflorae (FGG), the fruit of Gardenia jasminoides Ellis var. grandiflora Nakai (Rubiaceae), is a common counterfeit herbal medicine of FG, which still appears in the TCM market, and causes a certain degree of confusion. In order to effectively distinguish FG and its adulterant, the compounds in these two species were thoroughly characterized firstly by ultrahigh-performance liquid chromatography/quadrupole-orbitrap mass spectrometry (UHPLC/Q-Orbitrap MS). Furthermore, a pseudo-targeted metabonomics method with 60 targeted ion pairs was established based on UHPLC-triple quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS) for discrimination. Multivariate statistical analysis showed that FG and FGG were clustered obviously, and 13 significantly differential markers were screened out by variable importance for projection (VIP) > 1 and p < 0.05 for the construction of the partial least squares (PLS) regression prediction model. The validation of the model proved that its prediction ability was quite satisfactory. Moreover, based on the absolute quantitative analysis of these 13 characteristics, the quality control standards of FG and FFG were established. In summary, an integral method of pseudo-targeted metabonomics combined with chemometrics analysis and a PLS regression model was proposed to provide an effective identification strategy for discrimination FG and FGG.

Authentication of apples from the Loess Plateau in China based on interannual element fingerprints and multidimensional modelling

Apple is an important fruit, and fruit authentication is significant for quality and safety control. The Loess Plateau (LP) in China is an important apple-producing region. However, the geographic authentication of LP apples has not been well studied. In this study, we discriminated LP apples based on multielement analysis. We analysed the differences in 29 elements of 522 samples collected from LP and others in 2018-2020 and constructed discriminant models for LP apple authentication. Linear discriminant analysis, partial least square-discriminant analysis, back-propagation artificial neural networks, and random forest (RF) showed different rates in training and validation accuracy. RF showed better tolerance to the removal of the less-important elements in model optimization. The final RF was optimized on 11 elements, which obtained 95.30% training accuracy for the 2018-2019 samples and 97.29% validation accuracy for the 2020 samples. The multielement-based authentication of LP apples could aid further studies of geographical origins.

Traceability Research on Dendrobium devonianum Based on SWATHtoMRM

SWATHtoMRM technology was used in this experiment to further identify and trace the sources of Dendrobium devonianum and Dendrobium officinale produced in the same area using TOF and MS-MRM. After the conversion of the R package of SWATHtoMRM, 191 MRM pairs of positive ions and 96 pairs of negative ions were obtained. Dendrobium devonianum and Dendrobium officinale can be separated very well using the PCA and PLS-DA analysis of MRM ion pairs; this shows that there are obvious differences in chemical composition between Dendrobium devonianum and Dendrobium officinale, which clearly proves that the pseudotargeted metabolomics method based on SWATHtoMRM can be used for traceability identification research. A total of 146 characteristic compounds were obtained, with 20 characteristic compounds in Dendrobium devonianum. The enrichment pathways of the characteristic compounds were mainly concentrated in lipids and atherosclerosis, chagas disease, fluid shear stress and atherosclerosis, proteoglycans in cancer, the IL-17 signaling pathway, the sphingolipid signaling pathway, diabetic cardiomyopathy, arginine and proline metabolism, etc., among which the lipid and atherosclerosis pathways were more enriched, and 11 characteristic compounds affected the expression levels of IL-1, TNFα, CD36, IL-1β, etc. These can be used as a reference for research on variety improvement and active substance accumulation in Dendrobium devonianum and Dendrobium officinale.

Application of UPLC-Triple TOF-MS/MS metabolomics strategy to reveal the dynamic changes of triterpenoid saponins during the decocting process of Asian ginseng and American ginseng

Triterpenoid saponins are the main bioactive components contributed to the nutritional value of ginseng, and different process conditions will affect their content and quality. To study the holistic characterization and dynamic changes of triterpenoid saponins in Asian ginseng (ASG) and American ginseng (AMG) during soaking and decoction, a UPLC-Triple TOF-MS/MS-based metabolomics strategy was used to characterize and discover differential saponin markers. In total, 739 triterpenoid saponins (including 225 potential new saponins) were identified from ASG and AMG in untargeted metabolomics. Based on PCA and OPLS-DA, 51 and 48 saponin markers were screened from soaked and decocted ASG and AMG, respectively. Additionally, targeted metabolomics analysis and HCA of 22 ginsenoside markers suggested that decoction of ASG and AMG for 2 h to 4 h could significantly increase the contents of rare ginsenosides (G), such as G-Rg₃, G-Rg₅, G-F₄. This study provides a scientific insight that high boiling combined with simmering enriches ASG and AMG extracts with rich rare ginsenosides that are more beneficial to human health.

Comprehensive pseudotargeted metabolomics analysis based on two-phase liquid extraction-UHPLC-MS/MS for the investigation of depressive rats

Pseudotargeted analysis combines the advantages of untargeted and targeted metabolomics methods. This study proposed a comprehensive pseudotargeted metabolomics method based on two-phase liquid extraction using ultra-high-performance liquid chromatography-tandem mass spectrometry. Two-phase liquid extraction, composed of both aqueous and organic phases, extracted a wide range of metabolites from polar to nonpolar in plasma samples. Besides, the two phases were combined and detected in a single injection to save analytical time. A total of 486 potential metabolites were detected by the developed approach. Compared with the conventional methanol-based protein precipitation method, the two-phase liquid extraction method significantly increased the metabolite coverage by 20.29%. Besides, the proposed pseudotargeted metabolomics method exhibited higher sensitivity and better repeatability than the untargeted method. Finally, we applied the established pseudotargeted method to the metabolomics study of depressive rats and screened 53 differential variables. Sixteen determined differential metabolites were mainly in four metabolic pathways, including glycerophospholipid, arachidonic acid, sphingolipid metabolisms, pentose and glucuronate interconversions. The results indicated that the pseudotargeted method based on two-phase liquid extraction broadened the metabolite coverage with good sensitivity and repeatability, exhibiting significant potential for discovering differential metabolites in metabolomics studies. This article is protected by copyright. All rights reserved.

Metabolic Insight into Cold Stress Response in Two Contrasting Maize Lines

Maize (Zea mays L.) is sensitive to a minor decrease in temperature at early growth stages, resulting in deteriorated growth at later stages. Although there are significant variations in maize germplasm in response to cold stress, the metabolic responses as stress tolerance mechanisms are largely unknown. Therefore, this study aimed at providing insight into the metabolic responses under cold stress at the early growth stages of maize. Two inbred lines, tolerant (B144) and susceptible (Q319), were subjected to cold stress at the seedling stage, and their corresponding metabolic profiles were explored. The study identified differentially accumulated metabolites in both cultivars in response to induced cold stress with nine core conserved cold-responsive metabolites. Guanosine 3′,5′-cyclic monophosphate was detected as a potential biomarker metabolite to differentiate cold tolerant and sensitive maize genotypes. Furthermore, Quercetin-3-O-(2″′-p-coumaroyl)sophoroside-7-O-glucoside, Phloretin, Phloretin-2′-O-glucoside, Naringenin-7-O-Rutinoside, L-Lysine, L-phenylalanine, L-Glutamine, Sinapyl alcohol, and Feruloyltartaric acid were regulated explicitly in B144 and could be important cold-tolerance metabolites. These results increase our understanding of cold-mediated metabolic responses in maize that can be further utilized to enhance cold tolerance in this significant crop.

A review of fruit juice authenticity assessments: Targeted and untargeted analyses

Fruit juices are becoming more and more popular in the whole world. However, the increasing fruit juice fraud cases are undermining the healthy development of fruit juice industry. Fruit juice authenticity represents an important food quality and safety parameter. Many techniques have been applied in fruit juices authenticity assessment. The purpose of this review is to provide a research overview of the targeted and untargeted analyses of fruit authentication, and a method selection guide for fruit juice authenticity assessment. Targeted markers, such as stable isotopes, phenolics, carbohydrates, organic acids, volatile components, DNAs, amino acids and proteins, as well as carotenoids, will be discussed. And untargeted techniques, including liquid/gas chromatography-mass spectrometer, nuclear magnetic resonance, infrared spectroscopy, inductively-coupled plasma-mass spectrometry/optical emission spectrometer, fluorescence spectra, electronic sensors and others, will be reviewed. The emerging untargeted for novel targeted marker analysis will be also summarized.

Exploring Antioxidant Activity, Organic Acid, and Phenolic Composition in Strawberry Tree Fruits (Arbutus unedo L.) Growing in Morocco

This study aimed to explore the main biochemical components and the antioxidant capacity of five strawberry tree fruits using three antioxidant essays within the ecotypic comparison scheme, to find out the most valuable fruit presenting disease-preventing properties. Total phenols, total flavonoids, total anthocyanins, antioxidant activity (DPPH, ABTS, and β-Carotene bleaching assays), pH, titratable acidity, soluble solids, and moisture content were investigated in five strawberry tree genotypes belonging to several areas in Morocco. Phenolic compounds were also identified using high performance chromatography (HPLC), with a diode array detector (DAD). High significant differences (p ˂ 0.05) were revealed among the examined genotypes regarding their total phenols (25.37–39.06 mg gallic acid equivalents (GAE)/g Dry weight (DW), total flavonoids (3.30–7.07 mg RE/g Dry weight (DW), total anthocyanins (0.15–0.64 mg cya-3-glu/100g Dry weight (DW), pH (2.44–3.92), titratable acidity (0.65–1.01 g malic acid/100g Fresh weight (FW), and soluble solids (14.83–18.53%). The average radical scavenging capacity, assessed using three methods, exhibited the following concentration ranges: 3.33–21.08, 2.25–19.58, and 1.08–13 mg Ascorbic Equivalent (AAE/g Dry weight(DW) for the DPPH scavenging test, ABTS, and β-carotene bleaching, respectively. Seventeen phenolic compounds were identified in sampled cultivars. Gallocatechol and catechin were found to be the major phenolic compounds. The correlation matrix revealed significant correlations among investigated variables, particularly ABTS and DPPH. The principal component analysis showed that the first three components formed 90.25% of the total variance. The following variables: chlorogenic acid, ellagic acid derivative, ellagic acid, rutin, and cyanidin−30.5-diglucoside, were the most involved in the total variance. The results revealed highly promising physico-biochemical profiles within the studied strawberry tree genotypes.

Comprehensive Comparison on the Chemical Profile of Guang Chen Pi at Different Ripeness Stages Using Untargeted and Pseudotargeted Metabolomics

The peel of Citrus reticulata 'Chachi' (GCP), which is highly valued in China for its health-promoting effects, is usually collected at different development stages to be processed into various functional foods. In the present work, a rapid method based on ultra-high-performance liquid chromatography Q Exactive Orbitrap mass spectrometry-incorporated untargeted and pseudotargeted metabolomics analysis was developed to investigate the chemical variations in GCP at different ripeness stages. Samples that originated from an individual tree were collected at immature, near mature, and mature stages. A total of 112 compounds were identified or tentatively identified, and flavonoids malonyl glycosides and polymethoxyfolavones glycosides were reported for the first time. Untargeted metabolomics analysis indicated the distinct chemical profiles and significant changes during ripeness stages. Then, a validated pseudotargeted metabolomics method based on parallel reaction monitoring was further applied with a wide coverage of targeted compounds. The GCP samples were found differing in the content variations of flavonoid aglycones, flavonoid O-/C-glycosides, polymethoxyfolavones, limonoids, alkaloids, and phenolic acid, which are important for phenotypic variations at different development stages. The present study is expected to provide new insight on comprehensive utilization of citrus peels at different ripeness stages.