DeepMS: super-fast peptide identification using end-to-end deep learning method

Mass spectrometry (MS) has emerged as a powerful omics analysis technique, particularly in proteomics, where the initial step involves identifying MS spectra as peptide sequences. However, this process often requires substantial computational resources and expertise, taking hours or even days to complete, thereby limiting the widespread adoption of MS-based omics technologies. To overcome this challenge, we have developed DeepMS, a deep learning-based spectra identification algorithm that overcomes the speed limitations of traditional spectra identification methods. We conducted comprehensive benchmark tests, comparing six deep learning algorithms. Based on the results, we selected the VGG16 algorithm as the core model for DeepMS. This algorithm enables super-fast, end-to-end identification of peptide sequences from MS spectra with high accuracy. DeepMS is adaptable to post-translational modifications, enhancing its versatility. In fact, its identification speed surpasses the generation rate of MS spectra, enabling super-fast identification. Furthermore, we demonstrate the practical application of DeepMS in microorganism detection, highlighting its utility in clinical testing. Through the implementation of DeepMS, our aim is to revolutionize the field of MS-based proteomics and facilitate the broader application of omics technologies, opening new avenues for rapid and efficient analysis in various research and clinical domains.

Establishment and application of quantitative method for 22 organic acids in honey based on SPE-GC–MS

Honey, a natural healthy liquid bee product, is rich in amino acids, vitamins, and other essential nutrients. Different origin honeys also varied in organic acids. The objective of this study is to establish an efficient solid-phase extraction-gas chromatography–mass spectrometry (SPE-GC–MS) method to eliminate interference of sugar and other impurities for accurately estimating 22 organic acids in honey by optimizing extraction, purification, derivatization, and gas chromatography–mass spectrometry (GC–MS) analytical conditions. After being extracted, purified and derivatized, organic acids in honey were qualified and quantified by GC–MS. This method was evaluated experimentally, and the results showed that, within a certain concentration range, the standard curve linear relationship was satisfactory (R2 > 0.9942), and the target organic acid recovery rate was 86.74% ~ 118.68%. Besides, precision (relative standard deviation, RSD = 2.98% ~ 13.42%), detection limit (LOD = 0.002 ~ 0.2 mg kg−1), and quantification limit (LOQ = 0.008 ~ 0.5 mg kg−1) met the target requirements. Also, based on this analytical method, the organic acids in five types of honey (acacia, jujube, vitex, canola and linden honey) were estimated. Notably, they all contained 22 different kinds of organic acids, and significant differences (p < 0.05) in the organic acid content and composition among different honey varieties were observed. PCA analysis showed that the five honeys could be differentiated based on the content of 22 organic acids.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

FROM A NON-TARGETED METABOLOMICS APPROACH TO A TARGETED BIOMARKERS STRATEGY TO HIGHLIGHT TESTOSTERONE ABUSE IN EQUINE. ILLUSTRATION OF A METHODOLOGICAL TRANSFER BETWEEN PLATFORMS AND LABORATORIES

In order to overcome the challenge associated with the screening of Anabolic-Androgenic Steroids (AAS) abuses in animal competitions, a non-targeted LC-HRMS based metabolomics approach was implemented on equine urine samples to highlight potential biomarkers associated with the administration of such compounds, using testosterone esters as model steroids. A statistical model relying on 4 potential biomarkers intensity could be defined to predict the status of the samples. With a routine application perspective, the monitoring of the highlighted potential biomarkers was first transferred into high-throughput LC-SRM. The model's performances and robustness of the approach were preserved and providing a first demonstration of metabolomics-based biomarkers integration within a targeted workflow using common benchtop MS instrumentation. In addition, with a view to the widespread implementation of such biomarker-based tools, we have transferred the method to a second laboratory with similar instrumentation. This proof of concept allows the development and application of biomarker-based strategies to meet current doping control needs.

A Review on the Foodomics Based on Liquid Chromatography Mass Spectrometry

Due to the globalization of food production and distribution, the food chain has become increasingly complex, making it more difficult to evaluate unexpected food changes. Therefore, establishing sensitive, robust, and cost-effective analytical platforms to efficiently extract and analyze the food-chemicals in complex food matrices is essential, however, challenging. LC/MS-based metabolomics is the key to obtain a broad overview of human metabolism and understand novel food science. Various metabolomics approaches (e.g., targeted and/or untargeted) and sample preparation techniques in food analysis have their own advantages and limitations. Selecting an analytical platform that matches the characteristics of the analytes is important for food analysis. This review highlighted the recent trends and applications of metabolomics based on "foodomics" by LC-MS and provides the perspectives and insights into the methodology and various sample preparation techniques in food analysis.

Nandrolone and estradiol biomarkers identification in bovine urine applying a liquid chromatography high-resolution mass spectrometry metabolomics approach

With the aim of specifically investigating patterns associated with three steroid treatments (17β-nandrolone, 17β-estradiol, and 17β-nandrolone + 17β-estradiol) in bovine, an reversed phase liquid chromatography (RPLC)-electrospray ionization (ESI)(+/-)-high-resolution mass spectrometry (HRMS) study was conducted to characterize the urinary profiles of involved animals. Although specific fingerprints with strong differences could be highlighted between urinary metabolite profiles within urine samples collected on control and treated animals, it appeared further that significant discriminations could also be observed between steroid treatments, evidencing thus specific patterns and candidate biomarkers associated to each treatment. An MS-2 structural elucidation step enabled level-1 identification of two biomarkers mainly involved in energy pathways, in relation to skeletal muscle functioning. These results make it possible to envisage a global strategy for the detection of anabolic practices involving steroids, while at the same time providing clues as to the compounds used, which would facilitate the confirmation stage to follow.

Extending the Lipidome Coverage by Combining Different Mass Spectrometric Platforms: An Innovative Strategy to Answer Chemical Food Safety Issues

From a general public health perspective, a strategy combining non-targeted and targeted lipidomics MS-based approaches is proposed to identify disrupted patterns in serum lipidome upon growth promoter treatment in pigs. Evaluating the relative contributions of the platforms involved, the study aims at investigating the potential of innovative analytical approaches to highlight potential chemical food safety threats. Serum samples collected during an animal experiment involving control and treated pigs, whose food had been supplemented with ractopamine, were extracted and characterised using three MS strategies: Non-targeted RP LC-HRMS; the targeted Lipidyzer™ platform (differential ion mobility associated with shotgun lipidomics) and a homemade LC-HRMS triglyceride platform. The strategy enabled highlighting specific lipid profile patterns involving various lipid classes, mainly in relation to cholesterol esters, sphingomyelins, lactosylceramide, phosphatidylcholines and triglycerides. Thanks to the combination of non-targeted and targeted MS approaches, various compartments of the pig serum lipidome could be explored, including commonly characterised lipids (Lipidyzer™), triglyceride isomers (Triglyceride platform) and unique lipid features (non-targeted LC-HRMS). Thanks to their respective characteristics, the complementarity of the three tools could be demonstrated for public health purposes, with enhanced coverage, level of characterization and applicability.

Tissue distribution, metabolism, and elimination of Victoria Pure Blue BO in rainbow trout: Main metabolite as an appropriate residue marker

Victoria Pure Blue BO is a dye that bears some therapeutic activity and that can be retrieved in effluent or may be used in aquaculture as a prohibited drug. In this study, the metabolism and tissue distribution during uptake and depuration of VPBO were investigated in order to propose a residue marker of illegal treatment in fish. The dye was administered to rainbow trout (oncorhynchus mykiss) for one day by water bath at a dose of 0.1 mg.L^-1. The concentrations of VPBO in all tissues increased rapidly during the treatment period, reaching a C_max of 567 ± 301 μg.L^-1 in plasma and 1846 μg kg^-1 ±517 for liver after 2 h. After placing the rainbow trout in a clean water bath for a 64 day-period of depuration, the concentrations in the tissues and plasma decreased to reach comparable levels for muscle and for skin after 33 days. The concentrations measured were still above the LOQ at 2.26 ± 0.48 μg kg^-1 for muscle and 2.85 ± 1.99 μg kg^-1 for skin at the end of the depuration period. The results indicated the existence of 14 phase I metabolites and one glucuronide conjugated metabolite. Non-compartmental analysis was applied to assess the pharmacokinetic parameters. The half-life in edible muscle of the main metabolite detected, deethyl-leuco-VPBO, was found to be 22.5 days compared to a half-life of 19.7 days for the parent VPBO. This study provides new information to predict a VPBO drug treatment of aquacultured species via a proposed new residue marker.

Metabolomic Profiling as a Possible Reverse Engineering Tool for Estimating Processing Conditions of Dry-Cured Hams

Dry-cured hams are popular among consumers. To increase the attractiveness of the product, objective analytical methods and algorithms to evaluate the relationship between observable properties and consumer acceptability are required. In this study, metabolomics, which is used for quantitative profiling of hundreds of small molecules, was applied to 12 kinds of dry-cured hams from Japan and Europe. In total, 203 charged metabolites, including amino acids, organic acids, nucleotides, and peptides, were successfully identified and quantified. Metabolite profiles were compared for the samples with different countries of origin and processing methods (e.g., smoking or use of a starter culture). Principal component analysis of the metabolite profiles with sensory properties revealed significant correlations for redness, homogeneity, and fat whiteness. This approach could be used to design new ham products by objective evaluation of various features.

Impact of storage conditions on the urinary metabolomics fingerprint

Urine stability during storage is essential in metabolomics to avoid misleading conclusions or erroneous interpretations. Facing the lack of comprehensive studies on urine metabolome stability, the present work performed a follow-up of potential modifications in urinary chemical profile using LC-HRMS on the basis of two parameters: the storage temperature (+4 °C, -20 °C, -80 °C and freeze-dried stored at -80 °C) and the storage duration (5-144 days). Both HILIC and RP chromatographies have been implemented in order to globally monitor the urinary metabolome. Using an original data processing associated to univariate and multivariate data analysis, our study confirms that chemical profiles of urine samples stored at +4 °C are very rapidly modified, as observed for instance for compounds such as:N-acetyl Glycine, Adenosine, 4-Amino benzoic acid, N-Amino diglycine, creatine, glucuronic acid, 3-hydroxy-benzoic acid, pyridoxal, l-pyroglutamic acid, shikimic acid, succinic acid, thymidine, trigonelline and valeryl-carnitine, while it also demonstrates that urine samples stored at -20 °C exhibit a global stability over a long period with no major modifications compared to -80 °C condition. This study is the first to investigate long term stability of urine samples and report potential modifications in the urinary metabolome, using both targeted approach monitoring individually a large number (n > 200) of urinary metabolites and an untargeted strategy enabling assessing for global impact of storage conditions.

Fluorescence Probing Live Single-cell Mass Spectrometry for Direct Analysis of Organelle Metabolism

Mitochondria in a live HepG2 cell were visualized with a fluorescent probe to specify their location and state in a living cell. Then, mitochondria were selectively captured with a nanospray tip under fluorescence microscope, and thousands of small molecular peaks were revealed and unique steroids specific to mitochondria were also found. This fluorescence imaging combined with live single-cell mass spectrometry opens the door to the analysis of site- and state-specific molecular detection to elucidate precise molecular mechanisms at the single-cell and organelle level.

Principal component analysis of molecularly based signals from infant formula contaminations using LC-MS and NMR in foodomics

BACKGROUND

The challenge in developing analytical assessment of unexpected excess contaminations in infant formula has been the most significant project to address the widespread issue of food safety and security. Foodomics based on metabolomics techniques provides powerful tools for the detection of tampering cases with intentional contaminations. However, the safety and risk assessments of infant formula to reveal not only the targeted presence of toxic chemicals, but also molecular changes involving unexpected contaminations, have not been reported. In this study, a huge amount of raw molecularly based signals from infant formula was analysed using reversed phase and hydrophilic interaction chromatography with time-of-flight MS (LC-MS) and (1) H nuclear magnetic resonance (NMR) and then processed by a principal component analysis (PCA).

RESULTS

PCA plots visualised signature trends in the complex signal-data batches from each excess contamination of detectable chemicals by LC-MS and NMR. These trends in the different batches from a portion of excess chemical contaminations such as pesticides, melamine and heavy metals and out-of-date products can be visualised from spectrally discriminated infant formula samples.

CONCLUSION

PCA plots provide possible attempts to maximise the covariance between the stable lot-to-lot uniformity and excess exogenous contaminations and/or degradation to discriminate against the molecularly based signals from infant formulas. © 2015 Society of Chemical Industry.