The roles of brain lipids and polar metabolites in the hypoxia tolerance of deep-diving pinnipeds.

Lipids make up more than half of the human brain's dry weight, yet the composition and function of the brain lipidome is not well characterized. Lipids not only provide the structural basis of cell membranes, but also take part in a wide variety of biochemical processes. In neurodegenerative diseases, lipids can facilitate neuroprotection and serve as diagnostic biomarkers. The study of organisms adapted to extreme environments may prove particularly valuable in understanding mechanisms that protect against stressful conditions and prevent neurodegeneration. The brain of the hooded seal (Cystophora cristata) exhibits a remarkable tolerance to low tissue oxygen levels (hypoxia). While neurons of most terrestrial mammals suffer irreversible damage after only short periods of hypoxia, in vitro experiments show that neurons of the hooded seal display prolonged functional integrity even in severe hypoxia. How the brain lipidome contributes to the hypoxia tolerance of marine mammals has been poorly studied. We performed an untargeted lipidomics analysis, which revealed that lipid species are significantly modulated in marine mammals compared with non-diving mammals. Increased levels of sphingomyelin species may have important implications for efficient signal transduction in the seal brain. Substrate assays also revealed elevated normoxic tissue levels of glucose and lactate, which suggests an enhanced glycolytic capacity. Additionally, concentrations of the neurotransmitters glutamate and glutamine were decreased, which may indicate reduced excitatory synaptic signaling in marine mammals. Analysis of hypoxia-exposed brain tissue suggests that these represent constitutive mechanisms rather than an induced response towards hypoxic conditions.

Booster-microchannel plate (BMCP) detector for signal amplification in MALDI-TOF mass spectrometry for ions beyond m/z 50 000.

Top-down proteomics deals with the characterization of intact biomolecules, which reduces the sample complexity and facilitates the detection of modifications at the protein level. The combination of the matrix-assisted laser desorption/ionization (MALDI) technique with time-of-flight (TOF) mass analysis allows for the generation of gaseous ions in low charge states from high-mass biomolecules, followed by their mass-to-charge ratio (m/z) separation, as high-mass ions drift down the flight tube more slowly than lighter ones. However, the detection efficiency of conventional microchannel plate (MCP) detectors is strongly reduced with decreasing ion velocity-corresponding to an increase in ion mass-which impedes the reliable detection of high-mass biomolecules. Herein, we present a simple modification of the MCP detector that allows for the amplification of the signal from ionized proteins of up to m/z 150 000. Two circular electrodes were assembled in front of the conventional detector and set to negative electrical voltages to affect the positively charged ions directly before they impinge on the MCP, possibly through a combination of a velocity boost and ion optical effects. In the present study, three booster electrode configurations were experimentally tested to maximize the signal intensification. Compared to the conventional MCP assembly, the signal intensity was amplified in a proof-of-concept experiment by a factor of 24.3 and of 10.7 for the singly charged BSA ion (m/z 66 400) and for the singly charged IgG ion (m/z 150 000), respectively, by applying the booster-MCP (BMCP) detector.

Artefact Profiling: Panomics Approaches for Understanding the Materiality of Written Artefacts.

This review explains the strategies behind genomics, proteomics, metabolomics, metallomics and isotopolomics approaches and their applicability to written artefacts. The respective sub-chapters give an insight into the analytical procedure and the conclusions drawn from such analyses. A distinction is made between information that can be obtained from the materials used in the respective manuscript and meta-information that cannot be obtained from the manuscript itself, but from residues of organisms such as bacteria or the authors and readers. In addition, various sampling techniques are discussed in particular, which pose a special challenge in manuscripts. The focus is on high-resolution, non-targeted strategies that can be used to extract the maximum amount of information about ancient objects. The combination of the various omics disciplines (panomics) especially offers potential added value in terms of the best possible interpretations of the data received. The information obtained can be used to understand the production of ancient artefacts, to gain impressions of former living conditions, to prove their authenticity, to assess whether there is a toxic hazard in handling the manuscripts, and to be able to determine appropriate measures for their conservation and restoration.

Food metabolomics: Latest hardware-developments for nontargeted food authenticity and food safety testing.

The analytical requirements for food testing have increased significantly in recent years. On the one hand, because food fraud is becoming an ever-greater challenge worldwide, and on the other hand because food safety is often difficult to monitor due to the far-reaching trade chains. In addition, the expectations of consumers on the quality of food have increased, and they are demanding extensive information. Cutting-edge analytical methods are required to meet these demands. In this context, non-targeted metabolomics strategies using mass and nuclear magnetic resonance spectrometers (mass spectrometry [MS]) have proven to be very suitable. MS-based approaches are of particular importance as they provide a comparatively high analytical coverage of the metabolome. Accordingly, the efficiency to address even challenging issues is high. A variety of hardware developments, which are explained in this review, have contributed to these advances. In addition, the potential of future developments is highlighted, some of which are currently not yet commercially available or only used to a comparatively small extent but are expected to gain in importance in the coming years.

Food authentication in real life: How to link nontargeted approaches with routine analytics?

In times of increasing globalization and the resulting complexity of trade flows, securing food quality is an increasing challenge. The development of analytical methods for checking the integrity and, thus, the safety of food is one of the central questions for actors from science, politics, and industry. Targeted methods, for the detection of a few selected analytes, still play the most important role in routine analysis. In the past 5 years, nontargeted methods that do not aim at individual analytes but on analyte profiles that are as comprehensive as possible have increasingly come into focus. Instead of investigating individual chemical structures, data patterns are collected, evaluated and, depending on the problem, fed into databases that can be used for further nontargeted approaches. Alternatively, individual markers can be extracted and transferred to targeted methods. Such an approach requires (i) the availability of authentic reference material, (ii) the corresponding high-resolution laboratory infrastructure, and (iii) extensive expertise in processing and storing very large amounts of data. Probably due to the requirements mentioned above, only a few methods have really established themselves in routine analysis. This review article focuses on the establishment of nontargeted methods in routine laboratories. Challenges are summarized and possible solutions are presented.

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.

Omics approaches for food authentication.

The development of analytical strategies to fight against food fraud is currently one of the most developing fields in food science as the food value chain becomes increasingly complex and global. Food can be certified by clear labeling but also by objective analytical methods. As shown recently by several groups, the omics technologies such as genomics, proteomics, metabolomics, and isotopolomics are suitable to prove the geographical origin, the production or cultivation process, and the biological and the overall chemical identity of food. This article describes different analytical approaches beginning with non-targeted strategies as well as the further developmental stages of transferring the methods to routine laboratories.

Plant Metabolomics: Maximizing Metabolome Coverage by Optimizing Mobile Phase Additives for Nontargeted Mass Spectrometry in Positive and Negative Electrospray Ionization Mode.

Nontargeted screening methods with ultrahigh-performance liquid chromatography-electrospray ionization/quadrupole-time-of-flight mass spectrometry have been extensively applied to plant metabolomics to very diverse scientific issues in plant metabolomics. In this study, different mobile phase additives were tested in order to improve the electrospray ionization process and to detect as many metabolites as possible with high peak intensities in positive and negative ionization mode. Influences of modifiers were examined for nonpolar and polar compounds, as optimal conditions are not always the same. By combining different additives, metabolite coverage could be significantly increased. The best results for polar metabolites in positive ionization mode were achieved by using 0.1% acetic acid and 0.1% formic acid in negative ionization mode. For measurements of nonpolar metabolites in positive ionization mode, the application of 10 mmol/L ammonium formate led to the best findings, while the use of 0.02% acetic acid was more appropriate in negative ionization mode.

Food Fingerprinting: LC-ESI-IM-QTOF-Based Identification of Blumeatin as a New Marker Metabolite for the Detection of Origanum majorana Admixtures to O. onites/vulgare.

Oregano (Origanum vulgare and O. onites) is one of the most frequently counterfeited herbs in the world and is diluted with the leaves of a wide variety of plants. In addition to olive leaves, marjoram (O. majorana) is often used for this purpose in order to achieve a higher profit. However, apart from arbutin, no marker metabolites are known to reliably detect marjoram admixtures in oregano batches at low concentrations. In addition, arbutin is relatively widespread in the plant kingdom, which is why it is of great relevance to look for further marker metabolites in order to secure the analysis accordingly. Therefore, the aim of the present study was to use a metabolomics-based approach to identify additional marker metabolites with the aid of an ion mobility mass spectrometry instrument. The focus of the analysis was on the detection of non-polar metabolites, as this study was preceded by nuclear magnetic resonance spectroscopic investigations of the same samples based mainly on the detection of polar analytes. Using the MS-based approach, numerous marjoram specific features could be detected in admixtures of marjoram >10% in oregano. However, only one feature was detectable in admixtures of >5% marjoram. This feature was identified as blumeatin, which belongs to the class of flavonoid compounds. Initially, blumeatin was identified based on MS/MS spectra and collision cross section values using a database search. In addition, the identification of blumeatin was confirmed by a reference standard. Moreover, dried leaves of olive, myrtle, thyme, sage and peppermint, which are also known to be used to adulterate oregano, were measured. Blumeatin could not be detected in these plants, so this substance can be considered as an excellent marker compound for the detection of marjoram admixtures.

Analysis of Hazelnuts (Corylus avellana L.) Stored for Extended Periods by 1H NMR Spectroscopy Monitoring Storage-Induced Changes in the Polar and Nonpolar Metabolome.

Storage is a critical step in the post-harvest processing of hazelnuts, as it can lead to mold, rancidity, and off-flavor. However, there is a lack of analytical methods to detect improper or extended storage. To comprehensively investigate the effects of hazelnut storage, samples were stored under five different conditions for up to 18 months. Subsequently, the polar and nonpolar metabolome were analyzed by 1H NMR spectroscopy and chemometric approaches for classification as well as variable selection. Increases in hexanoic, octanoic, and nonanoic acid, all products of lipid oxidation and responsible for quality defects, were found across all conditions. Furthermore, the concentration of free long-chain fatty acids increased in samples stored at high temperatures. Harsh short-term storage resulted in an increase in fumaric and lactic acid, glucose, fructose, and choline and a decrease in acetic acid.

Food Monitoring: Limitations of Accelerated Storage to Predict Molecular Changes in Hazelnuts (Corylus avellana L.) under Realistic Conditions Using UPLC-ESI-IM-QTOF-MS.

Accelerated storage is routinely used with pharmaceuticals to predict stability and degradation patterns over time. The aim of this is to assess the shelf life and quality under harsher conditions, providing crucial insights into their long-term stability and potential storage issues. This study explores the potential of transferring this approach to food matrices for shelf-life estimation. Therefore, hazelnuts were stored under accelerated short-term and realistic long-term conditions. Subsequently, they were analyzed with high resolution mass spectrometry, focusing on the lipid profile. LC-MS analysis has shown that many unique processes take place under accelerated conditions that do not occur or occur much more slowly under realistic conditions. This mainly involved the degradation of membrane lipids such as phospholipids, ceramides, and digalactosyldiacylglycerides, while oxidation processes occurred at different rates in both conditions. It can be concluded that a food matrix is far too complex and heterogeneous compared to pharmaceuticals, so that many more processes take place during accelerated storage, which is why the results cannot be used to predict molecular changes in hazelnuts stored under realistic conditions.

Food authentication: truffle species classification by non-targeted lipidomics analyses 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 impossible for some species. These factors make truffles a very valuable food, which is why it is particularly rewarding and tempting to declare inferior species of truffles as more expensive species and thereby counterfeit them. The various species differ in their aroma and thus in their culinary value, but the adulterations cannot be detected on the basis of pure morphology. For this reason, the objective of the present study was to develop a non-targeted lipidomics approach using ion mobility spectrometry-mass spectrometry to distinguish between the white truffle species Tuber magnatum and T. borchii as well as the black truffle species T. melanosporum, T. aestivum and T. indicum. Several hundred features were detected, which were present in significantly different concentrations in the studied truffle species. The most important of them were identified using MS/MS spectra and collision cross section (CCS) values. Some compounds were detected whose CCS values have not yet been published and may facilitate identification by other researchers in the future. Just a few marker substances are sufficient to be able to distinguish both black and white truffle species with 100% accuracy. These results can be used for the development of rapid tests, which in the best case will allow truffle analysis directly on-site.

Wood profiling by non-targeted liquid chromatography high-resolution mass spectrometry: Part 2, Detection of the geographical origin of spruce wood (Picea abies) by determination of metabolite pattern.

A non-targeted metabolomics-based approach using liquid chromatography high-resolution mass spectrometry was used to authenticate spruce wood (Picea abies) from two geographic source areas. The two sample sites were located in Germany and only 250 km apart. In order to achieve the highest possible metabolite coverage, the spruces samples were measured with four different methods using liquid chromatography high-resolution mass spectrometry. In this way, a total of approximately 4,100 features were detected, which included non-polar, polar, and intermediate-polar metabolites. Using supervised multivariate methods, a distinction between the two sample groups could be achieved on the basis of non-polar data sets. The major metabolites contributing to differentiation were identified by MS/MS experiments and were from the following classes of compounds: ceramides, fatty acids, glycerolipids, and phytosterols. Based on the soil descriptions of the two sites, it was concluded that there is probably a close relationship between nutrient availability and the differences in concentration of the marker compounds. The results show that a metabolomics-based approach is also suitable for differentiation of origin, even if the sample sites are close to each other.

Non-Targeted LC-MS Metabolomics Approach towards an Authentication of the Geographical Origin of Grain Maize (Zea mays L.) Samples.

Safety along the food and feed supply chain is an emerging topic and closely linked to the ability to analytical trace the geographical origin of food or feed. In this study, ultra-performance liquid chromatography coupled with electrospray ionization quadrupole-time-of-flight mass spectrometry was used to trace back the geographical origin of 151 grain maize (Zea mays L.) samples from seven countries using a high resolution non-targeted metabolomics approach. Multivariate data analysis and univariate statistics were used to identify promising marker features related to geographical origin. Classification using only 20 selected markers with the Random Forest algorithm led to 90.5% correctly classified samples with 100 times repeated 10-fold cross-validation. The selected markers were assigned to the class of triglycerides, diglycerides and phospholipids. The marker set was further evaluated for its ability to separate between one sample class and the rest of the dataset, yielding accuracies above 89%. This demonstrates the high potential of the non-polar metabolome to authenticate the geographic origin of grain maize samples. Furthermore, this suggests that focusing on only a few lipids with high potential for grain maize authentication could be a promising approach for later transfer of the method to routine analysis.

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.

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.

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

The low reproducibility of non-targeted liquid chromatography-mass spectrometry-based metabolomics approaches represents a major challenge for their implementation in routine analyses, because it is impossible to compare individual measurements directly with each other, if they were not analyzed in the same batch. This study describes a normalization process based on housekeeping metabolites in plant-based raw materials, which are present in comparatively constant concentrations and are subject to no or only minor deviations as a result of exogenous influences. As a model, an authenticity study was selected to determine the origin of white asparagus (Asparagus officinalis). Using three model data sets and one test data set, we were able to show that samples that have been measured independently of one another can be correctly assigned in terms of origin after the normalization with housekeeping metabolites. The procedure does not require internal standards or the measurements of further reference samples and can also be applied to other matrices and scientific issues.

Plant Metabolomics: Evaluation of Different Extraction Parameters for Nontargeted UPLC-ESI-QTOF-Mass Spectrometry at the Example of White Asparagus officinalis.

The extraction of metabolites turns out to be one of the most important key factors for nontargeted metabolomics approaches as this step can significantly affects the informative value of the successive measurements. Compared to metabolomics experiments of various matrices of bacterial or mammalian origins, there are only few studies, which focus on different extraction methods for plant metabolomics analyses. In this study, various solvent extraction compositions were compared and assessed using an UPLC-ESI-QTOF-MS strategy. Exemplary, white asparagus ( Asparagus officinalis) were employed as a low-fat-, low-protein-, high-water-content model commodity with the objective of designing an optimal nontargeted extraction protocol for polar and nonpolar metabolites. Furthermore, the influence of acid addition, mechanical cell disruption methods (ball mill, ultrasonic bath, vortex mixer), and extract stability have been systematically scrutinized too. The different extraction protocols were compared based on sum of features, sum of peak intensities, sum of peak areas, as well as by analyzing individual signals of as many different substance groups as possible to obtain a maximum overview.

Food Authentication: Small-Molecule Profiling as a Tool for the Geographic Discrimination of German White Asparagus.

For the first time, a non-targeted metabolomics approach by means of ultraperformance liquid chromatography coupled to electrospray quadruple time-of-flight mass spectrometry was chosen for the discrimination of geographical origins of white asparagus samples ( Asparagus officinalis). Over a period of four harvesting periods (4 years), approximately 400 asparagus samples were measured. Initially, four different liquid chromatography-mass spectrometry methods were used to detect as many metabolites as possible and to assess which method is most suitable. The most relevant marker compounds were linked to the influence of different plant stress parameters and climate effects. Some of the samples were also analyzed by isotope-ratio mass spectrometry (IRMS), which is the current gold standard for the discrimination of the geographical origin of asparagus. In summary, the analysis of the metabolome was proven to be quite suitable to determine the geographical origin of asparagus and seems to provide better interpretable results than IRMS studies.