NMR metabolomics of ripened and developing oilseed rape (Brassica napus) and turnip rape (Brassica rapa)

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging

The purpose of this study was to develop a deep learning method involving wavelet transform (WT) and stacked denoising autoencoder (SDAE) for extracting deep features of heavy metal lead (Pb) detection of oilseed rape leaves. Firstly, the standard normalized variable (SNV) algorithm was established as the best preprocessing algorithm, and the SNV-treated fluorescence spectral data was used for further data analysis. Then, WT was used to decompose the SNV-treated fluorescence spectra of oilseed rape leaves to obtain the optimal wavelet decomposition layers using different wavelet basis functions, and SDAE was used for deep feature learning under the optimal wavelet decomposition layer. Finally, the best established support vector machine regression (SVR) model prediction set parameters R_p², RMSEP and RPD were 0.9388, 0.0199 mg/kg and 3.275 using sym7 as the wavelet basis function. The results of this study verified that the huge potential of fluorescence hyperspectral technology combined with deep learning algorithms to detect heavy metals.

Effect of Acylated and Nonacylated Anthocyanins on Urine Metabolic Profile during the Development of Type 2 Diabetes in Zucker Diabetic Fatty Rats

The effect of nonacylated and acylated anthocyanins on urinary metabolites in diabetic rats was investigated. Nonacylated anthocyanins extract from bilberries (NAAB) or acylated anthocyanins extract from purple potatoes (AAPP) was given to Zucker diabetic fatty (ZDF) rats for 8 weeks at daily doses of 25 and 50 mg/kg body weight. ¹H NMR metabolomics was applied to study alterations in urinary metabolites from three time points (weeks 1, 4, and 8). Both types of anthocyanins modulated the metabolites associated with the tricarboxylic acid cycle, gut microbiota metabolism, and renal function at weeks 1 and 4, such as 2-oxoglutarate, fumarate, alanine, trigonelline, and hippurate. In addition, only a high dose of AAPP decreased monosaccharides, formate, lactate, and glucose levels at week 4, suggesting improvement in energy production in mitochondria, glucose homeostasis, and oxidative stress. This study suggested different impacts of AAPP and NAAB on the metabolic profile of urine in diabetes.

The Transcriptome and Metabolome Reveal the Potential Mechanism of Lodging Resistance in Intergeneric Hybrids between Brassica napus and Capsella bursa-pastoris

Lodging is one of the main reasons for the reduction in seed yield and is the limitation of mechanized harvesting in B. napus. The dissection of the regulatory mechanism of lodging resistance is an important goal in B. napus. In this study, the lodging resistant B. napus line, YG689, derived from the hybridization between B. napus cv. Zhongyou 821 (ZY821) and Capsella bursa-pastoris, was used to dissect the regulation mechanism of hard stem formation by integrating anatomical structure, transcriptome and metabolome analyses. It was shown that the lignocellulose content of YG689 is higher than that of ZY821, and some differentially expressed genes (DEGs) involved in the lignocellulose synthesis pathway were revealed by transcriptome analyses. Meanwhile, GC–TOF–MS and UPLC–QTOF–MS identified 40, 54, and 31 differential metabolites in the bolting stage, first flower stage, and the final flower stage. The differential accumulation of these metabolites might be associated with the lignocellulose biosynthesis in B. napus. Finally, some important genes that regulate the metabolic pathway of lignocellulose biosynthesis, such as BnaA02g18920D, BnaA10g15590D, BnaC05g48040D, and NewGene_216 were identified in B. napus through the combination of transcriptomics and metabolomics data. The present results explored the potential regulatory mechanism of lignocellulose biosynthesis, which provided a new clue for the breeding of B. napus with lodging resistance in the future.

Omics: The way forward to enhance abiotic stress tolerance in Brassica napus L

Plant abiotic stresses negative affects growth and development, causing a massive reduction in global agricultural production. Rapeseed (Brassica napus L.) is a major oilseed crop because of its economic value and oilseed production. However, its productivity has been reduced by many environmental adversities. Therefore, it is a prime need to grow rapeseed cultivars, which can withstand numerous abiotic stresses. To understand the various molecular and cellular mechanisms underlying the abiotic stress tolerance and improvement in rapeseed, omics approaches have been extensively employed in recent years. This review summarized the recent advancement in genomics, transcriptomics, proteomics, metabolomics, and their imploration in abiotic stress regulation in rapeseed. Some persisting bottlenecks have been highlighted, demanding proper attention to fully explore the omics tools. Further, the potential prospects of the CRISPR/Cas9 system for genome editing to assist molecular breeding in developing abiotic stress-tolerant rapeseed genotypes have also been explained. In short, the combination of integrated omics, genome editing, and speed breeding can alter rapeseed production worldwide.

Single-Molecule Real-Time Transcript Sequencing of Turnips Unveiling the Complexity of the Turnip Transcriptome

To generate the full-length transcriptome of Xinjiang green and purple turnips, Brassica rapa var. Rapa, using single-molecule real-time (SMRT) sequencing. The samples of two varieties of Brassica rapa var. Rapa at five developmental stages were collected and combined to perform SMRT sequencing. Meanwhile, next generation sequencing was performed to correct SMRT sequencing data. A series of analyses were performed to investigate the transcript structure. Finally, the obtained transcripts were mapped to the genome of Brassica rapa ssp. pekinesis Chiifu to identify potential novel transcripts. For green turnip (F01), a total of 19.54 Gb clean data were obtained from 8 cells. The number of reads of insert (ROI) and full-length non-chimeric (FLNC) reads were 510,137 and 267,666. In addition, 82,640 consensus isoforms were obtained in the isoform sequences clustering, of which 69,480 were high-quality, and 13,160 low-quality sequences were corrected using Illumina RNA seq data. For purple turnip (F02), there were 20.41 Gb clean data, 552,829 ROIs, and 274,915 FLNC sequences. A total of 93,775 consensus isoforms were obtained, of which 78,798 were high-quality, and the 14,977 low-quality sequences were corrected. Following the removal of redundant sequences, there were 46,516 and 49,429 non-redundant transcripts for F01 and F02, respectively; 7,774 and 9,385 alternative splicing events were predicted for F01 and F02; 63,890 simple sequence repeats, 59,460 complete coding sequences, and 535 long-non coding RNAs were predicted. Moreover, 5,194 and 5,369 novel transcripts were identified by mapping to Brassica rapa ssp. pekinesis Chiifu. The obtained transcriptome data may improve turnip genome annotation and facilitate further study of the Brassica rapa var. Rapa genome and transcriptome.

Comparative Metabolomic Analysis of Rapeseeds from Three Countries

Rapeseed is an important oilseed with proper fatty acid composition and abundant bioactive components. Canada and China are the two major rapeseed-producing countries all over the world. Meanwhile, Canada and Mongolia are major importers of rapeseed due to the great demand for rapeseed in China. To investigate the metabolites in rapeseeds from three countries, ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based metabolomics was employed to analyze rapeseeds from China, Canada, and Mongolia. As results, 67, 53, and 68 metabolites showed significant differences between Chinese and Canadian, Chinese and Mongolian, and Canadian and Mongolian rapeseeds, respectively. Differential metabolites were mainly distributed in the metabolic pathways including phenylpropanoid biosynthesis, flavone and flavonol biosynthesis, and ubiquinone and other terpenoid-quinone biosynthesis. Among the differential metabolites, contents of sinapate and sinapine were higher in Chinese rapeseeds, while the contents of brassicasterol, stigmasterol, and campestanol were higher in Canadian rapeseeds. These findings might provide insight into the metabolic characteristics of rapeseeds from three countries to guide processing and consumption of the products of rapeseed.

Metabolomic discrimination of the edible mushrooms Kuehneromyces mutabilis and Hypholoma capnoides (Strophariaceae, Agaricales) by NMR spectroscopy

Two edible, cultivable mushroom species of the family Strophariaceae, Kuehneromyces mutabilis (sheathed woodtuft) and Hypholoma capnoides (conifer tuft), were studied using proton nuclear magnetic resonance metabolomic approach. The variation in the metabolites of the two species and their metabolic behaviour regarding caps and stipes and different collection sites were analysed by multivariate analysis methods. Altogether 169 cap and stipe samples of the mushrooms were investigated. The clearest difference between the species was in the sugar composition, which was more diverse in H. capnoides. When mushroom samples collected from different locations were compared, more variance was found in H. capnoides, whereas K. mutabilis appeared more homogeneous as a species. As far as the caps and stipes were concerned, in both species the amount of α-α-trehalose was clearly higher in the stipes, and the caps contained a larger proportion of the amino acids and organic acids.

NMR-based and chemometric approaches applicable to adulteration studies for assessment of the botanical origin of edible oils

The health benefits of edible oils, especially promoted by ω3 and ω9 fatty acids, have been associated with their botanical origin. In order to investigate fatty acid profiles, we assessed Brazil nut, chia, linseed, sesame (toasted and raw), and soybean oils by ¹H nuclear magnetic resonance (¹H NMR) and chemometrics. PCA plots revealed important relationships between chemical composition and botanical origin for reference and commercial samples. Strong evidence of commercial Brazil nut oil adulteration was confirmed using a spiking procedure. Our findings show that NMR and chemometrics are successful tools for correlating fatty acid profile with botanical origin, which can be suitable for detecting sample adulteration.

Relationship of Moisture Status and Quality Characteristics of Fresh Wet Noodles Prepared from Different Grade Wheat Flours from Flour Milling Streams

This study was performed to investigate the quality of fresh wet noodles made from flour milling streams. The basic composition, texture properties, cooking characteristics, and moisture status were measured to evaluate the qualities of noodles. The results indicated that as storage time increased, the springiness of fresh wet noodles gradually decreased, but the hardness increased. Additionally, the cooking loss rate was increased obviously, and the water absorption rate generally decreased. The relaxation times T21 and T22, analyzed by low-field nuclear magnetic resonance, showed a downward trend that proton mobility became poor and bound water changed into intermediate water. Noodles made from reduction flour exhibited better quality. Compared to that with ambient temperature storage, the wet noodles under frozen storage showed better quality. The relaxation time T21, and T22 showed a positive correlation with noodle quality.

Foodomics and Food Safety: Where We Are

The power of foodomics as a discipline that is now broadly used for quality assurance of food products and adulteration identification, as well as for determining the safety of food, is presented. Concerning sample preparation and application, maintenance of highly sophisticated instruments for both high-performance and high-throughput techniques, and analysis and data interpretation, special attention has to be paid to the development of skilled analysts. The obtained data shall be integrated under a strong bioinformatics environment. Modern mass spectrometry is an extremely powerful analytical tool since it can provide direct qualitative and quantitative information about a molecule of interest from only a minute amount of sample. Quality of this information is influenced by the sample preparation procedure, the type of mass spectrometer used and the analyst's skills. Technical advances are bringing new instruments of increased sensitivity, resolution and speed to the market. Other methods presented here give additional information and can be used as complementary tools to mass spectrometry or for validation of obtained results. Genomics and transcriptomics, as well as affinity-based methods, still have a broad use in food analysis. Serious drawbacks of some of them, especially the affinity-based methods, are the cross-reactivity between similar molecules and the influence of complex food matrices. However, these techniques can be used for pre-screening in order to reduce the large number of samples. Great progress has been made in the application of bioinformatics in foodomics. These developments enabled processing of large amounts of generated data for both identification and quantification, and for corresponding modeling.

Integration of omics approaches to understand oil/protein content during seed development in oilseed crops

Oilseed crops, especially soybean (Glycine max) and canola/rapeseed (Brassica napus), produce seeds that are rich in both proteins and oils and that are major sources of energy and nutrition worldwide. Most of the nutritional content in the seed is accumulated in the embryo during the seed filling stages of seed development. Understanding the metabolic pathways that are active during seed filling and how they are regulated are essential prerequisites to crop improvement. In this review, we summarize various omics studies of soybean and canola/rapeseed during seed filling, with emphasis on oil and protein traits, to gain a systems-level understanding of seed development. Currently, most (80-85%) of the soybean and rapeseed reference genomes have been sequenced (950 and 850 megabases, respectively). Parallel to these efforts, extensive omics datasets from different seed filling stages have become available. Transcriptome and proteome studies have detected preponderance of starch metabolism and glycolysis enzymes to be the possible cause of higher oil in B. napus compared to other crops. Small RNAome studies performed during the seed filling stages have revealed miRNA-mediated regulation of transcription factors, with the suggestion that this interaction could be responsible for transitioning the seeds from embryogenesis to maturation. In addition, progress made in dissecting the regulation of de novo fatty acid synthesis and protein storage pathways is described. Advances in high-throughput omics and comprehensive tissue-specific analyses make this an exciting time to attempt knowledge-driven investigation of complex regulatory pathways.

Recent applications of NMR in food and dietary studies

Over the last decade, a wide variety of new foods have been introduced into the global marketplace, many with health benefits that exceed those of traditional foods. Simultaneously, a wide range of analytical technologies has evolved that allow greater capability for the determination of food composition. Nuclear magnetic resonance (NMR), traditionally a research tool used for structural elucidation, is now being used frequently for metabolomics and chemical fingerprinting. Its stability and inherent ease of quantification have been exploited extensively to identify and quantify bioactive components in foods and dietary supplements. In addition, NMR fingerprints have been used to differentiate cultivars, evaluate sensory properties of food and investigate the influence of growing conditions on food crops. Here we review the latest applications of NMR in food analysis. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Distinctive Metabolism of Flavonoid between Cultivated and Semiwild Soybean Unveiled through Metabolomics Approach

Soybeans are an important crop for agriculture and food, resulting in an increase in the range of its application. Recently, soybean leaves have been used not only for food products but also in the beauty industry. To provide useful and global metabolite information on the development of soy-based products, we investigated the metabolic evolution and cultivar-dependent metabolite variation in the leaves of cultivated (Glycine max) and semiwild (G. gracilis) soybean, through a (1)H NMR-based metabolomics approach, as they grew from V (vegetative) 1 to R (reproductive) 7 growth stages. The levels of primary metabolites, such as sucrose, amino acids, organic acids, and fatty acids, were decreased both in the G. gracilis and G. max leaves. However, the secondary metabolites, such as pinitol, rutin, and polyphenols, were increased while synthesis of glucose was elevated as the leaves grew. When metabolite variations between G. gracilis and G. max are compared, it was noteworthy that rutin and its precursor, quercetin-3-O-glucoside, were found only in G. gracilis but not in G. max. Furthermore, levels of pinitol, proline, β-alanine, and acetic acid, a metabolite related to adaptation toward environmental stress, were different between the two soybean cultivars. These results highlight their distinct metabolism for adaptation to environmental conditions and their intrinsic metabolic phenotype. This study therefore provides important information on the cultivar-dependent metabolites of soybean leaves for better understanding of plant physiology toward the development of soy-based products.

Holistic Analysis Enhances the Description of Metabolic Complexity in Dietary Natural Products

In the field of food and nutrition, complex natural products (NPs) are typically obtained from cells/tissues of diverse organisms such as plants, mushrooms, and animals. Among them, edible fruits, grains, and vegetables represent most of the human diet. Because of an important dietary dependence, the comprehensive metabolomic analysis of dietary NPs, performed holistically via the assessment of as many metabolites as possible, constitutes a fundamental building block for understanding the human diet. Both mass spectrometry (MS) and nuclear magnetic resonance (NMR) are important complementary analytic techniques, covering a wide range of metabolites at different concentrations. Particularly, 1-dimensional 1H-NMR offers an unbiased overview of all metabolites present in a sample without prior knowledge of its composition, thereby leading to an untargeted analysis. In the past decade, NMR-based metabolomics in plant and food analyses has evolved considerably. The scope of the present review, covering literature of the past 5 y, is to address the relevance of 1H-NMR–based metabolomics in food plant studies, including a comparison with MS-based techniques. Major applications of NMR-based metabolomics for the quality control of dietary NPs and assessment of their nutritional values are presented.