Discovery of Glycation Products: Unraveling the Unknown Glycation Space Using a Mass Spectral Library from In Vitro Model Systems.

The nonenzymatic reaction between amino acids (AAs) and reducing sugars, also known as the Maillard reaction, is the primary source of free glycation products (GPs) in vivo and in vitro. The limited number of MS/MS records for GPs in public libraries hinders the annotation and investigation of nonenzymatic glycation. To address this issue, we present a mass spectral library containing the experimental MS/MS spectra of diverse GPs from model systems. Based on the conceptional reaction processes and structural characteristics of products, we classified GPs into common GPs (CGPs) and modified AAs (MAAs). A workflow for annotating GPs was established based on the structural and fragmentation patterns of each GP type. The final spectral library contains 157 CGPs, 499 MAAs, and 2426 GP spectra with synthetic model system information, retention time, precursor m/z, MS/MS, and annotations. As a proof-of-concept, we demonstrated the use of the library for screening GPs in unidentified spectra of human plasma and urine. The AAs with the C6H10O5 modification, fructosylation from Amadori rearrangement, were the most found GPs. With the help of the model system, we confirmed the existence of C6H10O5-modified Valine in human plasma by matching both retention time, MS1, and MS/MS without reference standards. In summary, our GP library can serve as an online resource to quickly screen possible GPs in an untargeted metabolomics workflow, furthermore with the model system as a practical synthesis method to confirm their identity.

Histone Deacetylases HD2A and HD2B Undergo Feedback Regulation by ABA and Modulate Drought Tolerance via Mediating ABA-Induced Transcriptional Repression.

Histone deacetylation catalyzed by histone deacetylase plays a critical role in gene silencing and subsequently controls many important biological processes. It was reported that the expression of the plant-specific histone deacetylase subfamily HD2s is repressed by ABA in Arabidopsis. However, little is known about the molecular relationship between HD2A/HD2B and ABA during the vegetative phase. Here, we describe that the hd2ahd2b mutant shows hypersensitivity to exogenous ABA during the germination and post-germination period. Additionally, transcriptome analyses revealed that the transcription of ABA-responsive genes was reprogrammed and the global H4K5ac level is specifically up-regulated in hd2ahd2b plants. ChIP-Seq and ChIP-qPCR results further verified that both HD2A and HD2B could directly and specifically bind to certain ABA-responsive genes. As a consequence, Arabidopsis hd2ahd2b plants displayed enhanced drought resistance in comparison to WT, which is consistent with increased ROS content, reduced stomatal aperture, and up-regulated drought-resistance-related genes. Moreover, HD2A and HD2B repressed ABA biosynthesis via the deacetylation of H4K5ac at NCED9. Taken together, our results indicate that HD2A and HD2B partly function through ABA signaling and act as negative regulators during the drought resistance response via the regulation of ABA biosynthesis and response genes.

DBDIpy: a Python library for processing of untargeted datasets from real-time plasma ionization mass spectrometry.

MOTIVATION: Plasma ionization is rapidly gaining popularity for mass spectrometry (MS)-based studies of volatiles and aerosols. However, data from plasma ionization are delicate to interpret as competing ionization pathways in the plasma create numerous ion species. There is no tool for detection of adducts and in-source fragments from plasma ionization data yet, which makes data evaluation ambiguous. SUMMARY: We developed DBDIpy, a Python library for processing and formal analysis of untargeted, time-sensitive plasma ionization MS datasets. Its core functionality lies in the identification of in-source fragments and identification of rivaling ionization pathways of the same analytes in time-sensitive datasets. It further contains elementary functions for processing of untargeted metabolomics data and interfaces to an established ecosystem for analysis of MS data in Python. AVAILABILITY AND IMPLEMENTATION: DBDIpy is implemented in Python (Version ≥ 3.7) and can be downloaded from PyPI the Python package repository (https://pypi.org/project/DBDIpy) or from GitHub (https://github.com/leopold-weidner/DBDIpy). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Real-Time Monitoring of Miniaturized Thermal Food Processing by Advanced Mass Spectrometric Techniques.

Mass spectrometry is a popular and powerful analytical tool to study the effects of food processing. Industrial sampling, real-life sampling, or challenging academic research on process-related volatile and aerosol research often demand flexible, time-sensitive data acquisition by state-of-the-art mass analyzers. Here, we show a laboratory-scaled, miniaturized, and highly controllable setup for the online monitoring of aerosols and volatiles from thermal food processing based on dielectric barrier discharge ionization (DBDI) mass spectrometry (MS). We demonstrate the opportunities offered by the setup from a foodomics perspective to study emissions from the thermal processing of wheat bread rolls at 210 °C by Fourier transformation ion cyclotron resonance MS. As DBDI is an emerging technology, we compared its ionization selectivity to established atmospheric pressure ionization tools: we found DBDI preferably ionizes saturated, nitrogenous compounds. We likewise identified a sustainable overlap in the selectivity of detected analytes with APCI and electrospray ionization (ESI). Further, we dynamically recorded chemical fingerprints throughout the thermal process. Unsupervised classification of temporal response patterns was used to describe the dynamic nature of the reaction system. Compared to established tools for real-time MS, our setup permits one to monitor chemical changes during thermal food processing at ultrahigh resolution, establishing an advanced perspective for real-time mass spectrometric analysis of food processing.

HILIC-MS for Untargeted Profiling of the Free Glycation Product Diversity.

Glycation products produced by the non-enzymatic reaction between reducing carbohydrates and amino compounds have received increasing attention in both food- and health-related research. Although liquid chromatography mass spectrometry (LC-MS) methods for analyzing glycation products already exist, only a few common advanced glycation end products (AGEs) are usually covered by quantitative methods. Untargeted methods for comprehensively analyzing glycation products are still lacking. The aim of this study was to establish a method for simultaneously characterizing a wide range of free glycation products using the untargeted metabolomics approach. In this study, Maillard model systems consisting of a multitude of heterogeneous free glycation products were chosen for systematic method optimization, rather than using a limited number of standard compounds. Three types of hydrophilic interaction liquid chromatography (HILIC) columns (zwitterionic, bare silica, and amide) were tested due to their good retention for polar compounds. The zwitterionic columns showed better performance than the other two types of columns in terms of the detected feature numbers and detected free glycation products. Two zwitterionic columns were selected for further mobile phase optimization. For both columns, the neutral mobile phase provided better peak separation, whereas the acidic condition provided a higher quality of chromatographic peak shapes. The ZIC-cHILIC column operating under acidic conditions offered the best potential to discover glycation products in terms of providing good peak shapes and maintaining comparable compound coverage. Finally, the optimized HILIC-MS method can detect 70% of free glycation product features despite interference from the complex endogenous metabolites from biological matrices, which showed great application potential for glycation research and can help discover new biologically important glycation products.

Open Search of Peptide Glycation Products from Tandem Mass Spectra.

Identification of chemically modified peptides in mass spectrometry (MS)-based glycation studies is a crucial yet challenging task. There is a need to establish a mode for matching tandem mass spectrometry (MS/MS) data, allowing for both known and unknown peptide glycation modifications. We present an open search approach that uses classic and modified peptide fragment ions. The latter are shifted by the mass delta of the modification. Both provide key structural information that can be used to assess the peptide core structure of the glycation product. We also leverage redundant neutral losses from the modification side chain, introducing a third ion class for matching referred to as characteristic fragment ions. We demonstrate that peptide glycation product MS/MS spectra contain multidimensional information and that most often, more than half of the spectral information is ignored if no attempt is made to use a multi-step matching algorithm. Compared to regular and/or modified peptide ion matching, our triple-ion strategy significantly increased the median interpretable fraction of the glycation product MS/MS spectra. For reference, we apply our approach for Amadori product characterization and identify all established diagnostic ions automatically. We further show how this method effectively applies the open search concept and allows for optimized elucidation of unknown structures by presenting two hitherto undescribed peptide glycation modifications with a delta mass of 102.0311 and 268.1768 Da. We characterize their fragmentation signature by integration with isotopically labeled glycation products, which provides high validity for non-targeted structure identification.

Elucidation of the non-volatile fingerprint in oven headspace vapor from bread roll baking by ultra-high resolution mass spectrometry.

Untargeted research on vapor arising during the thermal processing of food has so far focused on volatile aroma compounds. In this study, we present an oven atmosphere sampling strategy to trap headspace aerosols along with semi- and non-volatile molecules liberated during the baking of wheat bread rolls. The collected vapor condensate was analyzed for its molecular fingerprinting using direct infusion ultra-high resolution mass spectrometry. We detected up to 4,700 molecular species in a vapor sample from bread rolls baked at 230 °C for 15 min. Beyond the global profiling of the underlying matrix, our method can follow complex reaction cascades during the baking process, such as the formation of advanced glycation end-products like maltosine through the interface of trapped vapor. Further, process parameters such as baking temperature and duration were used to model the dynamic liberation of molecules to the oven atmosphere by a response surface methodology approach.

Molecular characterization of sequence-driven peptide glycation.

Peptide glycation is an important, yet poorly understood reaction not only found in food but also in biological systems. The enormous heterogeneity of peptides and the complexity of glycation reactions impeded large-scale analysis of peptide derived glycation products and to understand both the contributing factors and how this affects the biological activity of peptides. Analyzing time-resolved Amadori product formation, we here explored site-specific glycation for 264 peptides. Intensity profiling together with in-depth computational sequence deconvolution resolved differences in peptide glycation based on microheterogeneity and revealed particularly reactive peptide collectives. These peptides feature potentially important sequence patterns that appear in several established bio- and sensory-active peptides from independent sources, which suggests that our approach serves system-wide applicability. We generated a pattern peptide map and propose that in peptide glycation the herein identified molecular checkpoints can be used as indication of sequence reactivity.

Hidden in its color: A molecular-level analysis of the beer's Maillard reaction network.

We here report a comprehensive non-targeted analytical approach to describe the Maillard reaction in beer. By Fourier-transform ion cyclotron mass spectrometry (FT-ICR-MS), we were able to assign thousands of unambiguous molecular formulae to the mass signals and thus directly proceed to the compositional space of 250 analyzed beer samples. Statistical data analyses of the annotated compositions showed that the Maillard reaction is one of the driving forces of beer's molecular diversity leading to key compositional changes in the beer metabolome. Different visualization methods allowed us to map the systematic nature of Maillard reaction derived compounds. The typical molecular pattern, validated by an experimental Maillard reaction model system, pervades over 2,800 (40%) of the resolved small molecules. The major compositional changes were investigated by mass difference network analysis. We were able to reveal general reaction sequences that could be assigned to successive Maillard intermediate phase reactions by shortest path analysis.

Influence of regionality and maturation time on the chemical fingerprint of whisky.

Understanding the chemical composition of whisky and the impact of each step in the manufacturing process provides a basis for responding to the challenges of producing high quality spirits. In this study, the objective was to discriminate whiskies according to their geographical origin and authenticate the maturation time in cask based on the non-volatile profiles. The combination of FT-ICR-MS and chemometrics allowed the distinction of whiskies from four geographical origins in Scotland (Highlands, Lowlands, Speyside and Islay). Statistical modeling was also used to discriminate whiskies according to the maturation time in cask and reveal chemical markers associated with the ageing regardless of the origin or the production process. Interestingly, the flow of transfer of compounds from wood barrels to distillates is not constant and homogeneous over the maturation time. The largest transfer of compounds from the barrel to the whisky was observed around twelve years of maturation.

Guidelines for the Use of Deuterium Oxide (D2O) in 1H NMR Metabolomics.

In metabolomics, nuclear magnetic resonance (NMR) spectroscopy allows to identify and quantify compounds in biological samples. The sample preparation generally requires only few steps; however, an indispensable factor is the addition of a locking substance into the biofluid sample, such as deuterium oxide (D2O). While creatinine loss in pure D2O is well-described, the effects of different D2O concentrations on the signal profile of biological samples are unknown. In this work, we investigated the effect of D2O levels in the NMR buffer system in urine samples, in dependence on dwell time and temperature exposition. We reveal a decrease of the urinary creatinine peak area up to 35% after 24 h of dwell time at room temperature (RT) using 25% (v/v) D2O, but only 4% loss using 2.5% D2O. 1H, inverse-gated (IG) 13C, DEPT-HSQC NMR, and mass spectrometry (MS) experiments confirmed a proton-deuterium (H/D) exchange at the CH2. This leads to underestimation of creatinine levels and has an extensive effect when creatinine is used for normalization. This work offers a sample stability examination, depending on the D2O concentration, dwell time, and temperature and enables a method to correct for the successive loss. We propose an equation to correct the creatinine loss for samples prepared with various D2O concentrations and storage temperatures for dwell times up to 24 h. The correction function was validated against an external data set with n = 26 samples. To ensure sufficient creatinine stability in future studies, we suggest that a maximum of 10% D2O should be used at 4 °C or 2.5% D2O at RT, respectively.

Rebuilding core abscisic acid signaling pathways of Arabidopsis in yeast.

The phytohormone abscisic acid (ABA) regulates plant responses to abiotic stress, such as drought and high osmotic conditions. The multitude of functionally redundant components involved in ABA signaling poses a major challenge for elucidating individual contributions to the response selectivity and sensitivity of the pathway. Here, we reconstructed single ABA signaling pathways in yeast for combinatorial analysis of ABA receptors and coreceptors, downstream-acting SnRK2 protein kinases, and transcription factors. The analysis shows that some ABA receptors stimulate the pathway even in the absence of ABA and that SnRK2s are major determinants of ABA responsiveness by differing in the ligand-dependent control. Five SnRK2s, including SnRK2.4 known to be active under osmotic stress in plants, activated ABA-responsive transcription factors and were regulated by ABA receptor complexes in yeast. In the plant tissue, SnRK2.4 and ABA receptors competed for coreceptor interaction in an ABA-dependent manner consistent with a tight integration of SnRK2.4 into the ABA signaling pathway. The study establishes the suitability of the yeast system for the dissection of core signaling cascades and opens up future avenues of research on ligand-receptor regulation.

Systems chemical analytics: introduction to the challenges of chemical complexity analysis.

Understanding complex (bio/geo)systems is a pivotal challenge in modern sciences that fuels a constant development of modern analytical technology, finding innovative solutions to resolve and analyse. In this introductory paper to the Faraday Discussion "Challenges in the analysis of complex natural systems", we aim to present concepts of complexity, and complex chemistry in systems subjected to biotic and abiotic transformations, and introduce the analytical possibilities to disentangle chemical complexity into its elementary parts (i.e. compositional and structural resolution) as a global integrated approach termed systems chemical analytics.

Milk-Derived Amadori Products in Feces of Formula-Fed Infants.

Food processing of infant formula alters chemical structures, including the formation of Maillard reaction products between proteins and sugars. We detected early Maillard reaction products, so-called Amadori products, in stool samples of formula-fed infants. In total, four Amadori products (N-deoxylactulosyllysine, N-deoxyfructosyllysine, N-deoxylactulosylleucylisoleucine, N-deoxyfructosylleucylisoleucine) were identified by a combination of complementary nontargeted and targeted metabolomics approaches. Chemical structures were confirmed by preparation and isolation of reference compounds, LC-MS/MS, and NMR. The leucylisoleucine Amadori compounds, which most likely originate from ß-lactoglobulin, were excreted throughout the first year of life in feces of formula-fed infants but were absent in feces of breastfed infants. Despite high inter- and intraindividual differences of Amadori products in the infants' stool, solid food introduction resulted in a continuous decrease, proving infant formula as the major source of the excreted Amadori products.

Simulated Sunlight Selectively Modifies Maillard Reaction Products in a Wide Array of Chemical Reactions.

The photochemical transformation of Maillard reaction products (MRPs) under simulated sunlight into mostly unexplored photoproducts is reported herein. Non-enzymatic glycation of amino acids leads to a heterogeneous class of intermediates with extreme chemical diversity, which is of particular relevance in processed and stored food products as well as in diabetic and age-related protein damage. Here, three amino acids (lysine, arginine, and histidine) were reacted with ribose at 100 °C in water for ten hours. Exposing these model systems to simulated sunlight led to a fast decay of MRPs. The photodegradation of MRPs and the formation of new compounds have been studied by fluorescence spectroscopy and nontargeted (ultra)high-resolution mass spectrometry. Photoreactions showed strong selectivity towards the degradation of electron-rich aromatic heterocycles, such as pyrroles and pyrimidines. The data show that oxidative cleavage mechanisms dominate the formation of photoproducts. The photochemical transformations differed fundamentally from "traditional" thermal Maillard reactions and indicated a high amino acid specificity.

Electrochemical triggering of the Chardonnay wine metabolome.

Oxidation of wine upon bottle ageing is a crucial matter of concern for the qualitative long-term storage of white wines. However, understanding the various molecular mechanisms potentially involved, which can impact the wine composition, requires that top-down analytical strategies are implemented. Here, we report the analysis of bottle aged Chardonnay wines made from the same must, but differing by the amount of SO2 initially added to the must at pressing (0 and 8 g·h L-1). Metabolomics fingerprints obtained from electrochemical simulation of oxidative reactions were obtained by coupling of either on-line or off-line electrochemical oxidation to FT-ICR-MS detection. We reveal that, whatever the electrochemical DC voltage is, wines with initial SO2 addition displayed molecular fingerprints, which remained more similar to the non-oxidized wine without initial SO2 addition. We further show that a diversity of sulfur-containing compounds appeared to be the most sensitive to oxidation, whereas nitrogen-containing compounds were mostly formed.

Insights into the Chemistry of Non-Enzymatic Browning Reactions in Different Ribose-Amino Acid Model Systems.

Reactions between sugars and amino acids in the Maillard reaction produce a multitude of compounds through interconnected chemical pathways. The course of the pathways changes depending on the nature of the amino acids and sugars as well as the processing conditions (e.g. temperature, water activity). Some partial pathways have been elucidated using labelled precursors but the process is very time intensive. Here, we use rapid, non-targeted analysis with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to deliver the molecular formulae and ion intensities of the compounds generated from reaction of four amino acids with ribose (10 h at 100 °C) to study the effect of amino acid side chains on the reaction pathways. Using van Krevelen diagrams, known chemical changes during the reaction (e.g. dehydration or decarboxylation) can be studied. Comparison of the data from the four amino acids studied, showed a common pathway, which involved 73 Maillard reaction products (MRPs) where the differences were due only to the nature of the amino acid side chain. From the more than 1400 different molecular formulae found, pathways unique to the amino acids were also identified and the order of reactivity was lysine >cysteine >isoleucine ≈ glycine. While unequivocal identification of the compounds cannot be achieved with FT-ICR-MS, applying known chemical transformations found in the Maillard reaction, not only identifies new and known pathways, but also integrates the MRPs into a general Maillard reaction scheme that better represents the totality of the Maillard reaction.

Usage of FT-ICR-MS Metabolomics for Characterizing the Chemical Signatures of Barrel-Aged Whisky.

Whisky can be described as a complex matrix integrating the chemical history from the fermented cereals, the wooden barrels, the specific distillery processes, aging, and environmental factors. In this study, using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we analyzed 150 whisky samples from 49 different distilleries, 7 countries, and ranging from 1 day new make spirit to 43 years of maturation with different types of barrel. Chemometrics revealed the unexpected impact of the wood history on the distillate's composition during barrel aging, regardless of the whisky origin. Flavonols, oligolignols, and fatty acids are examples of important chemical signatures for Bourbon casks, whereas a high number of polyphenol glycosides, including for instance quercetin-glucuronide or myricetin-glucoside as potential candidates, and carbohydrates would discriminate Sherry casks. However, the comparison of barrel aged rums and whiskies revealed specific signatures, highlighting the importance of the initial composition of the distillate and the distillery processes.

Tandem HILIC-RP liquid chromatography for increased polarity coverage in food analysis.

Comprehensive non-targeted analysis of food products normally requires two complementary chromatographic runs to achieve maximum compound coverage. In this study, we present a sensitive tandem-LC method, which combines RP and HILIC separation in a single run. The setup consists of a C18 trap column and two subsequently coupled analytical columns (HILIC and C18) which are operated in parallel. First, hydrophobic compounds are retained on the RP trap column while rather hydrophilic compounds are directly transferred onto a HILIC phase. Next, the pre-fractionated sample composition is analyzed by HILIC or RP chromatography, respectively. The presented setup allows individual and independent gradient elution as well as interfacing with mass spectrometry. The performance of the method has been proven by means of food relevant standards and analysis of complex food samples (e.g. red wine, meat extract). The simple and robust setup provides high flexibility in the selection of column combinations and does not require sophisticated instrumental setups or software. The method significantly increases the covered polarity range compared to classical one-dimensional chromatography. Our results indicate that tandem LC is a valuable and universal tool in the non-targeted screening of various types of complex food samples.

Sulfites and the wine metabolome.

In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints.