Mass-Spectrometry-Based Food Metabolomics in Routine Applications: A Basic Standardization Approach Using Housekeeping Metabolites for the Authentication of Asparagus

Distinct Quality Changes of Asparagus during Growth by Widely Targeted Metabolomics Analysis

Asparagus is a popular vegetable and traditional medicine consumed worldwide due to its health benefits. The quality of asparagus, mainly attributed to small components like flavonoids and steroid, is quite differential as a result of different environments and maturities. However, the accumulation pattern and regulatory mechanism of metabolites in asparagus remain unclear so far. Herein, widely targeted metabolomics analysis was employed to study the quality and chemical composition variances of four asparagus, including three green asparagus of different maturities and one white asparagus. A total of 1045 metabolites were annotated in asparagus in which flavonoids and phenolic acids accounted for 37.51% of the total. Green asparagus was found to be rich in flavonoids, while white asparagus contained more steroids. Additionally, 461 biomarkers were screened between matured green and white asparagus, which is much more than that filtered among three green asparagus at different growth stages. These results indicated that sunlight has a stronger effect on the metabolism of asparagus compared to the general development of asparagus. Linoleic acid metabolism and alpha-linolenic acid metabolism were active during green asparagus growth, while flavone and flavonol biosynthesis and flavonoid biosynthesis resulted as two of the most important pathways when asparagus was exposed to sunlight.

Development of a mass spectrometry-based metabolomics workflow for traceability of wild and cultivated Cordyceps sinensis

Cordyceps sinensis, as an expensive traditional Chinese medicine and edible fungus mycelium, lacks an effective quality evaluation method, especially and cultivated Cordyceps sinensis. In this study, a feasible workflow method was developed for traceability evaluation of wild and cultivated Cordyceps sinensis, based on mass spectrometry-based metabolomics. Mass spectrometry data were firstly acquired from Cordyceps sinensis, samples by liquid chromatography-quadrupole and time of flight mass spectrometry. Characteristic mass spectrometry peaks were extracted by applying the MZmine. Then significant markers were obtained from Cordyceps sinensis samples by orthogonal partial least square discriminant analysis. Then, identification of significant markers were identified by MS-FINDER data analytics. The results showed that Changdu, the other four wild origins (Naqu, Xinghai, Yushu and Guoluo) and cultivated samples could be significantly distinguished. This identified significant markers of Cordyceps sinensis, including 174 special significant markers for the wild samples, 204 special significant markers for the cultivated samples and 87 share significant markers. Number of 87 shared significant markers were identified in the wild and cultivated Cordyceps sinensis, especially 28 confident significant compounds, such as adenosine, riboflavin, tyrosine, arginine and glutamine. These shared significant markers might support the quality control of multi-targets of Cordyceps sinensis, compared with a single target in the Chinese Pharmacopoeia. The special significant markers indicated that cultivated Cordyceps sinensis was different from the wild based on mass spectrometry-based metabolomics. In the comparison of chromatographic fingerprint technology, it was found that the established feasible workflow method was easy to acquire significant markers and traceability of Cordyceps sinensis. This feasible workflow method has great potential to be successful for comprehensive and traceability evaluation of the wild and cultivated Cordyceps sinensis.

Real-Time Profiling and Distinction of Lipids from Different Mammalian Milks Using Rapid Evaporative Ionization Mass Spectrometry Combined with Chemometric Analysis

The price of mammalian milk from different animal species varies greatly due to differences in their yield and nutritional value. Therefore, the authenticity of dairy products has become a hotspot issue in the market due to the replacement or partial admixture of high-cost milk with its low-cost analog. Herein, four common commercial varieties of milk, including goat milk, buffalo milk, Holstein cow milk, and Jersey cow milk, were successfully profiled and differentiated from each other by rapid evaporative ionization mass spectrometry (REIMS) combined with chemometric analysis. This method was developed as a real-time lipid fingerprinting technique. Moreover, the established chemometric algorithms based on multivariate statistical methods mainly involved principal component analysis, orthogonal partial least squares-discriminant analysis, and linear discriminant analysis as the screening and verifying tools to provide insights into the distinctive molecules constituting the four varieties of milk. The ions with m/z 229.1800, 243.1976, 257.2112, 285.2443, 299.2596, 313.2746, 341.3057, 355.2863, 383.3174, 411.3488, 439.3822, 551.5051, 577.5200, 628.5547, 656.5884, 661.5455, 682.6015, and 684.6146 were selected as potential classified markers. The results of the present work suggest that the proposed method could serve as a reference for recognizing dairy fraudulence related to animal species and expand the application field of REIMS technology.

Authentication of organically grown vegetables by the application of ambient mass spectrometry and inductively coupled plasma (ICP) mass spectrometry; The leek case study

Health conscious and environmentally aware consumers are purchasing more organically produced foods. They prefer organic fruits and leafy vegetables as these are much less likely to have been exposed to contaminants such as pesticides. The detection of fraudulent activity in this area is difficult to undertake, because many chemical plant protection treatments degrade very quickly or can be washed off to remove evidence of their existence. It was found that when combining DART-MS with a compact, inexpensive and robust single quadrupole mass spectrometer, it was possible to differentiate organic from conventional leeks with 93.8% to 100% accuracy. ICP-MS results showed similar performance, with an ability to differentiate conventional from organic leeks with 92.5% to 98.1% accuracy. This study has paved the way for the certification of vegetables as being organically produced. The next step is to create data libraries to support the roll out of the methodologies described.

Food Authentication: Truffle Species Classification by non-targeted Lipidomics Analyzes using Mass Spectrometry assisted by Ion Mobility Separation

Truffles are appreciated as food all over the world because of their extraordinary aroma. However, quantities are limited and successful cultivation in plantations is very labor-intensive and expensive, or even...

Opening the Random Forest Black Box of the Metabolome by the Application of Surrogate Minimal Depth

For the untargeted analysis of the metabolome of biological samples with liquid chromatography–mass spectrometry (LC-MS), high-dimensional data sets containing many different metabolites are obtained. Since the utilization of these complex data is challenging, different machine learning approaches have been developed. Those methods are usually applied as black box classification tools, and detailed information about class differences that result from the complex interplay of the metabolites are not obtained. Here, we demonstrate that this information is accessible by the application of random forest (RF) approaches and especially by surrogate minimal depth (SMD) that is applied to metabolomics data for the first time. We show this by the selection of important features and the evaluation of their mutual impact on the multi-level classification of white asparagus regarding provenance and biological identity. SMD enables the identification of multiple features from the same metabolites and reveals meaningful biological relations, proving its high potential for the comprehensive utilization of high-dimensional metabolomics data.

Metabolomics Reveals Heterogeneity in the Chemical Composition of Green and White Spears of Asparagus (A. officinalis)

Green and white asparagus are quite different crops but can be harvested from the same plant. They have distinct morphological differences due to their mode of cultivation and they are characterised by having contrasting appearance and flavour. Significant chemical differences are therefore expected. Spears from three varieties of both green and white forms, harvested in two consecutive seasons were analysed using headspace GC-MS and LC-MS with an untargeted metabolomic workflow. Mainly C5 and C8 alcohols and aldehydes, and phenolic compounds were more abundant in green spears, whereas benzenoids, monoterpenes, unsaturated aldehydes and steroidal saponins were more abundant in white ones. Previously reported key asparagus volatiles and non-volatiles were detected at similar or not significantly different levels in the two asparagus types. Spatial metabolomics revealed also that many volatiles with known positive aroma attributes were significantly more abundant in the upper parts of the spears and showed a decreasing trend towards the base. These findings provide valuable insights into the metabolome of raw asparagus, the contrasts between green and white spears as well as the different chemical distributions along the stem.

Wood profiling by non-targeted high-resolution mass spectrometry: Part 1, Metabolite profiling in Cedrela wood for the determination of the geographical origin

The determination of the geographical origin of wood can be highly relevant for several reasons: On the one hand, it can help to prevent illegal logging and timber trade, on the other hand, it is of special interest for archaeological artefacts made of wood, as well as for a variety of biological questions. For this reason, different extraction methods were first tested for the analysis of polar and non-polar metabolites using liquid chromatography coupled electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). A two-phase extraction with chloroform, methanol and water proved to be particularly successful. Subsequently, cedrela (Cedrela odorata) samples from South America were measured to distinguish geographic origin. Using multivariate data analysis, numerous origin-dependent differences could be extracted. The identification of the marker substances indicated that several metabolic pathways were affected by the geographical influences, some of them probably indicating pest infections.

Food Authentication: Species and Origin Determination of Truffles (Tuber spp.) by Inductively Coupled Plasma Mass Spectrometry and Chemometrics

The aim of this study was to develop a protocol for the authentication of truffles using inductively coupled plasma mass spectrometry. The price of the different truffle species varies significantly, and because the visual differentiation is difficult within the white truffles and within the black truffles, food fraud is likely to occur. Thus, in the context of this work, the elemental profiles of 59 truffle samples of five commercially relevant species were analyzed and the resulting element profiles were evaluated with chemometrics. Classification models targeting the species and the origins were validated using nested cross validation and were able to differentiate the most expensive Tuber magnatum from any other examined truffle. For the black truffles, an overall classification accuracy of 90.4% was achieved, and, most importantly, a falsification of the expensive Tuber melanosporum by Tuber indicum could be ruled out. With regard to the geographical origin, for Italy and Spain, one-versus-all classification models were calculated each to differentiate truffle samples from any other origins by 75.0 and 86.7%, respectively. The prediction was still possible according to an internal mathematical normalization scheme using only the element ratios instead of the absolute element concentrations. The established authentication protocol was successfully tested with an external sample set of five fresh truffles. Our results show the high potential of the element profile for the parallel species and origin authentication of truffles.

Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity

Experiments based on metabolomics represent powerful approaches to the experimental verification of the integrity of food. In particular, high-resolution non-targeted analyses, which are carried out by means of liquid chromatography-mass spectrometry systems (LC-MS), offer a variety of options. However, an enormous amount of data is recorded, which must be processed in a correspondingly complex manner. The evaluation of LC-MS based non-targeted data is not entirely trivial and a wide variety of strategies have been developed that can be used in this regard. In this paper, an overview of the mandatory steps regarding data acquisition is given first, followed by a presentation of the required preprocessing steps for data evaluation. Then some multivariate analysis methods are discussed, which have proven to be particularly suitable in this context in recent years. The publication closes with information on the identification of marker compounds.