Metabolomics Strategy Research Articles

Rapid Identification of New Biomarkers for the Classification of GM1 Type 2 Gangliosidosis Using an Unbiased 1H NMR-Linked Metabolomics Strategy.

Biomarkers currently available for the diagnosis, prognosis, and therapeutic monitoring of GM1 gangliosidosis type 2 (GM1T2) disease are mainly limited to those discovered in targeted proteomic-based studies. In order to identify and establish new, predominantly low-molecular-mass biomarkers for this disorder, we employed an untargeted, multi-analyte approach involving high-resolution 1H NMR analysis coupled to a range of multivariate analysis and computational intelligence technique (CIT) strategies to explore biomolecular distinctions between blood plasma samples collected from GM1T2 and healthy control (HC) participants (n = 10 and 28, respectively). The relationship of these differences to metabolic mechanisms underlying the pathogenesis of GM1T2 disorder was also investigated. 1H NMR-linked metabolomics analyses revealed significant GM1T2-mediated dysregulations in ≥13 blood plasma metabolites (corrected p < 0.04), and these included significant upregulations in 7 amino acids, and downregulations in lipoprotein-associated triacylglycerols and alanine. Indeed, results acquired demonstrated a profound distinctiveness between the GM1T2 and HC profiles. Additionally, employment of a genome-scale network model of human metabolism provided evidence that perturbations to propanoate, ethanol, amino-sugar, aspartate, seleno-amino acid, glutathione and alanine metabolism, fatty acid biosynthesis, and most especially branched-chain amino acid degradation (p = 10−12−10−5) were the most important topologically-highlighted dysregulated pathways contributing towards GM1T2 disease pathology. Quantitative metabolite set enrichment analysis revealed that pathological locations associated with these dysfunctions were in the order fibroblasts > Golgi apparatus > mitochondria > spleen ≈ skeletal muscle ≈ muscle in general. In conclusion, results acquired demonstrated marked metabolic imbalances and alterations to energy demand, which are consistent with GM1T2 disease pathogenesis mechanisms.

Untargeted Metabolomics Reveals Elevated L-Carnitine Metabolism in Pig and Rat Colon Tissue Following Red Versus White Meat Intake.

The consumption of red and processed meat, and not white meat, associates with the development of various Western diseases such as colorectal cancer and type 2 diabetes. This work aims at unraveling novel meat-associated mechanisms that are involved in disease development. A non-hypothesis driven strategy of untargeted metabolomics is applied to assess colon tissue from rats (fed a high dose of beef vs. white meat) and from pigs (fed red/processed meat vs. white meat), receiving a realistic human background diet. An increased carnitine metabolism is observed, which is reflected by higher levels of acylcarnitines and 3-dehydroxycarnitine (rats and pigs) and trimethylamine-N-oxide (rats). While 3-dehydroxycarnitine is higher in HT29 cells, incubated with colonic beef digests, acylcarnitine levels are reduced. This suggests an altered response from colon cancer cell line towards meat-induced oxidative stress. Moreover, metabolic differences between rat and pigs are observed in N-glycolylneuraminic acid incorporation, prostaglandin, and fatty acid synthesis. This study demonstrates elevated (acyl)carnitine metabolism in colon tissue of animals that follow a red meat-based diet, providing mechanistic insights that may aid in explaining the nutritional-physiological correlation between red/processed meat and Western diseases.

Metabolomic alterations associated with copper stress in Cryptococcus neoformans.

Background: Copper stress is an effective host strategy in resisting the opportunistic pathogenic fungus Cryptococcus neoformans. We studied metabolic changes in C. neoformans under copper stress. Materials & methods: Wild-type and metallothionein-null C. neoformans were treated with copper on agar containing glucose, glycerolor ethanol as the carbon source and their metabolites were analyzed by untarget metabolomics strategyusinggas chromatography coupled withtime-of-flight mass spectrometry. Results: The metabolic profile of C. neoformans varied in the presence and absence of copper. Pathway enrichment analysis showed that the differentially abundant metabolites were related to amino acid and carbohydrate metabolism. C. neoformans grown on glycerol or ethanolresisted copper toxicity better than C. neoformans grown on glucose. Conclusion: Copper stress alters the metabolic profile of C. neoformans.

Diagnostic Fragmentation Filtering for Cyanopeptolin Detection.

Cyanobacteria are ubiquitous photosynthetic prokaryotes that produce structurally diverse bioactive metabolites. Although microcystins are extensively studied, other cyanopeptides produced by common bloom-forming species have received little attention. Cyanopeptolins are a large cyanopeptide group that contain a characteristic 3-amino-6-hydroxy-2-piperidone (Ahp) moiety. In the present study we used diagnostic fragmentation filtering (DFF), a semitargeted liquid chromatography-tandem mass spectrometry (MS/MS) product ion filtering approach, to investigate cyanopeptolin diversity from 5 Microcystis strains and 4 bloom samples collected from lakes in Ontario and Quebec, Canada. Data processing by DFF was used to search MS/MS data sets for pairs of diagnostic product ions corresponding to cyanopeptolin partial sequences. For example, diagnostic product ions at m/z 150.0912 and 215.1183 identified cyanopeptolins with the NMe-Tyr-Phe-Ahp partial sequence. Forty-eight different cyanopeptolins, including 35 new variants, were detected from studied strains and bloom samples. Different cyanopeptolin profiles were identified from each sample. We detected a new compound, cyanopeptolin 1143, from a bloom and elucidated its planar structure from subsequent targeted MS/MS experiments. Diagnostic fragmentation filtering is a rapid, easy-to-perform postacquisition metabolomics strategy for inferring structural features and prioritizing new compounds for further study and dereplication. More work on cyanopeptolin occurrence and toxicity is needed because their concentrations in freshwater lakes after blooms can be similar to those of microcystins. Environ Toxicol Chem 2021;40:1087-1097. © 2020 SETAC.

Two Metabolomics Phenotypes of Human Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease According to Fibrosis Severity.

Non-Alcoholic Fatty Liver Disease (NAFLD) is considered as the forthcoming predominant cause for hepatocellular carcinoma (HCC). NAFLD-HCC may rise in non-cirrhotic livers in 40 to 50% of patients. The aim of this study was to identify different metabolic pathways of HCC according to fibrosis level (F0F1 vs. F3F4). A non-targeted metabolomics strategy was applied. We analyzed 52 pairs of human HCC and adjacent non-tumoral tissues which included 26 HCC developed in severe fibrosis or cirrhosis (F3F4) and 26 in no or mild fibrosis (F0F1). Tissue extracts were analyzed using 1H-Nuclear Magnetic Resonance spectroscopy. An optimization evolutionary method based on genetic algorithm was used to identify discriminant metabolites. We identified 34 metabolites differentiating the two groups of NAFLD-HCC according to fibrosis level, allowing us to propose two metabolomics phenotypes of NAFLD-HCC. We showed that HCC-F0F1 mainly overexpressed choline derivatives and glutamine, whereas HCC-F3F4 were characterized by a decreased content of monounsaturated fatty acids (FA), an increase of saturated FA and an accumulation of branched amino acids. Comparing HCC-F0F1 and HCC-F3F4, differential expression levels of glucose, choline derivatives and phosphoethanolamine, monounsaturated FA, triacylglycerides were identified as specific signatures. Our metabolomics analysis of HCC tissues revealed for the first time two phenotypes of HCC developed in NAFLD according to fibrosis level. This study highlighted the impact of the underlying liver disease on metabolic reprogramming of the tumor.

Dissecting Efficacy and Metabolic Characteristic Mechanism of Taxifolin on Renal Fibrosis by Multivariate Approach and Ultra-Performance Liquid Chromatography Coupled With Mass Spectrometry-Based Metabolomics Strategy.

Taxifolin (TFN) is an important natural compound with antifibrotic activity; however, its pharmacological mechanism is not clear. In this study, our aim is to gain insight into the effects of TFN and its potential mechanisms in unilateral ureteral obstruction (UUO) animal model using metabolomics approach to identify the metabolic biomarkers and perturbed pathways. Serum metabolomics analysis by UPLC-Q-TOF/MS was carried out to discover the changes in the metabolic profile. It showed that TFN has a significant protective effect on UUO-induced renal fibrosis and a total of 32 potential biomarkers were identified and related to RF progression. Of note, 27 biomarkers were regulated by TFN treatment, which participate in eight metabolic pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, and phenylalanine metabolism. It also showed that metabolomics was a promising strategy to better dissect metabolic characteristics and pharmacological mechanisms of natural compounds by multivariate approach and ultra-performance liquid chromatography coupled with mass spectrometry.

Integrated plasma and liver gas chromatography mass spectrometry and liquid chromatography mass spectrometry metabolomics to reveal physiological functions of sodium taurocholate cotransporting polypeptide (NTCP) with an Ntcp knockout mouse model

Sodium taurocholate cotransporting polypeptide (NTCP) is an important hepatocyte transporter, while its physiological functions require further investigation. In our study, an integrated plasma and liver GC–MS- and LC-MS-based metabolomics strategy with an optimized two-step liquid-liquid extraction was utilized to explore the physiological functions of NTCP via a knockout (KO) mouse model. The present study found that NTCP deficiency resulted in obvious metabolic change in the plasma and liver of mice. Totally, 102 and 87 differential metabolites were discovered in the liver and plasma, respectively. Pathway analysis revealed that the metabolism of tyrosine, glycine, taurine, fatty acid and glycerophospholipid as well as the biosynthesis of tryptophan, pantothenate and CoA were significantly dysregulated in the Ntcp KO mice, indicating that NTCP is closely involved in these metabolic pathways. Moreover, L-tryptophan, cadaverine and D-pantothenic acid could serve as the diagnostic biomarker for NTCP deficiency. Our study provided deep insights into the physiological functions of NTCP, and the findings would hold the great potential to be used for the discovery of new therapeutic and diagnostic strategies for NTCP deficiency clinically.

Time dependent berry maturation for planting density levels in Coffea arabica L. beans: Mixture design-fingerprinting using near-infrared transmittance spectroscopy

A three-step metabolomics strategy, employing near-infrared transmittance spectroscopy coupled with mixture design-fingerprints, chemometrics, and classical analytical assays, was used to determine metabolite abundances in coffee beans originating from three periods of berry maturation at the same of Coffea arabica plants cultivated at two planting densities. A first step screening showed that ethanol/dichloromethane and ethanol/dichloromethane/acetone extracts contained chemical information permitting classifications of beans cultivated at different planting densities whereas the acetone extract permitted the discrimination of time dependent berry maturation. In the second phase, selected extracts originating from different agronomical management conditions indicated that the 1680, 1660, and 1090 nm bands of the bean fingerprints were associated with these chemical changes. Finally, the third step consisted of classical analytical quantifications of caffeine, carbohydrates, lipids, and chlorogenic acids. This validated most of the conclusions obtained from the PCA score and loading exploratory analysis. The planting density and the harvest period systematic PCA-score patterns indicated gradual changes in the chemical profiles of coffee beans from the first to the third harvest. Partial least squares-discriminant analysis and ANOVA-simultaneous component analysis confirmed the classification and statistical significance of the agronomical management main effects and their interactions.

A network pharmacology-integrated metabolomics strategy for clarifying the action mechanisms of Schisandrae Chinensis Fructus for treating drug-induced liver injury by acetaminophen

Schisandrae Chinensis Fructus (SCF) was a Traditional Chinese Medicine (TCM) for protecting liver. However, underlying therapeutic mechanisms of SCF for drug-induced liver injury (DILI) by acetaminophen (APAP) are still unclear. This study aims to discover the potential regulation mechanisms of SCF in the treatment of DILI by APAP using the integrated network pharmacology, plasma metabolomics profiling with UPLC-Q-TOF-MS approach. The key targets in the shared pathways of network pharmacology and metabolomics were screened and experimentally validated by Quantitative Real-time PCR analysis. The results showed that SCF could exert excellent effects on DILI by APAP probably through regulating ErbB signaling pathway and Arachidonic acid metabolism pathway, which was reflected by the reduced gene expression of TNF-α, IL-6, IL-1β, COX-2 and EGFR, as well as the increased gene expression of Nrf2, HO-1, MDM2, MAPK8, SRC, PLD1, CYP2E1, CYP1A2, CYP3A1. This study systematically explored the pharmacological mechanisms of SCF in the treatment of DILI, meanwhile, metabolomics combine with network pharmacology approach might be a useful strategy for early diagnosis of DILI by APAP.

An integrating strategy for serum metabolomics and microarray analysis to expand the understanding of diet-induced obesity.

Obesity is a key component of metabolic syndrome and is precipitated by complex interactions between multiple environmental and genetic factors. The integration of multi-level bioinformation is needed to understand the altered endogenous molecule and metabolic mechanisms. In this study, an integrated analytical strategy was proposed by combining microarray data from a gene expression omnibus database and in vitro serum metabolomic data to unearth bioinformation associated with cafeteria diet induced obesity. In the diet induced obese rats, 23 genes and 9 metabolites showed significant changes, in which the increased levels of alanine, lactate and lactate dehydrogenase B (Ldhb) and the decreased levels of citrate and pyruvate indicated an enhanced glycolysis and a disordered Krebs cycle. Furthermore, the closeness centrality of Slc27a2, Apobr, alanine and histidine in the correlations network of pathways, genes and metabolites was 0.5036, 0.5111, 0.5702, and 0.5352, respectively. These close links between metabolites and genes would be highly useful to assess the degree of obesity and to understand the developmental mechanism of obesity. The pathway enrichment analysis of genes and metabolites proved that a disturbed glucose metabolism and biosynthesis of amino acids are typical metabolic features of cafeteria-induced obesity. The metabolomics combined with microarray data not only could identify the biomarkers, but also would be beneficial to the follow-up research of obesity treatment, especially providing a methodological basis for the study of other diseases.

Retraction: A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome.

Retraction of ‘A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome’ by Qun Liang et al., RSC Adv., 2019, 9, 30868–30878, DOI: 10.1039/C9RA06679A.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview.

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Integrated LC-MS metabolomics with dual derivatization for quantification of FFAs in fecal samples of hepatocellular carcinoma patients

FFAs display pleiotropic functions in human diseases. Short-chain FAs (SCFAs), medium-chain FAs, and long-chain FAs are derived from different origins, and precise quantification of these FFAs is critical for revealing their roles in biological processes. However, accessing stable isotope-labeled internal standards is difficult, and different chain lengths of FFAs challenge the chromatographic coverage. Here, we developed a metabolomics strategy to analyze FFAs based on isotope-free LC-MS-multiple reaction monitoring integrated with dual derivatization. Samples and dual derivatization internal standards were synthesized using 2-dimethylaminoethylamine or dansyl hydrazine as a “light” label and N,N-diethyl ethylene diamine or N,N-diethyldansulfonyl hydrazide as a “heavy” label under mild and efficient reaction conditions. General multiple reaction monitoring parameters were designed to analyze these FFAs. The limit of detection of SCFAs varied from 0.5 to 3 nM. Furthermore, we show that this approach exhibits good linearity (R2 = 0.99374–0.99929), there is no serious substrate interference, and no quench steps are required, confirming the feasibility and reliability of the method. Using this method, we successfully quantified 15 types of SCFAs in fecal samples from hepatocellular carcinoma patients and healthy individuals; among these, propionate, butyrate, isobutyrate, and 2-methylbutyrate were significantly decreased in the hepatocellular carcinoma group compared with the healthy control group. These results indicate that the integrated LC-MS metabolomics with isotope-free and dual derivatization is an efficient approach for quantifying FFAs, which may be useful for identifying lipid biomarkers of cancer.

Candida Species (Volatile) Metabotyping through Advanced Comprehensive Two-Dimensional Gas Chromatography.

Microbial metabolomics is a challenge strategy that allows a comprehensive analysis of metabolites within a microorganism and may support a new approach in microbial research, including the microbial diagnosis. Thus, the aim of this research was to in-depth explore a metabolomics strategy based on the use of an advanced multidimensional gas chromatography for the comprehensive mapping of cellular metabolites of C. albicans and non-C. albicans (C. glabrata and C. tropicalis) and therefore contributing for the development of a comprehensive platform for fungal detection management and for species distinction in early growth times (6 h). The volatile fraction comprises 126 putatively identified metabolites distributed over several chemical families: acids, alcohols, aldehydes, hydrocarbons, esters, ketones, monoterpenic and sesquiterpenic compounds, norisoprenoids, phenols and sulphur compounds. These metabolites may be related with different metabolic pathways, such as amino acid metabolism and biosynthesis, fatty acids metabolism, aromatic compounds degradation, mono and sesquiterpenoid synthesis and carotenoid cleavage. These results represent an enlargement of ca. 70% of metabolites not previously reported for C. albicans, 91% for C. glabrata and 90% for C. tropicalis. This study represents the most detailed study about Candida species exometabolome, allowing a metabolomic signature of each species, which signifies an improvement towards the construction of a Candida metabolomics platform whose application in clinical diagnostics can be crucial to guide therapeutic interventions.

Sub-nanoliter metabolomics via mass spectrometry to characterize volume-limited samples

The human metabolome provides a window into the mechanisms and biomarkers of various diseases. However, because of limited availability, many sample types are still difficult to study by metabolomic analyses. Here, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter sample volumes. The approach consists of combining a customized metabolomics workflow with a pulsed MS ion generation method, known as triboelectric nanogenerator inductive nanoelectrospray ionization (TENGi nanoESI) MS. Samples tested with this approach include exhaled breath condensate collected from cystic fibrosis patients as well as in vitro-cultured human mesenchymal stromal cells. Both test samples are only available in minimum amounts. Experiments show that picoliter-volume spray pulses suffice to generate high-quality spectral fingerprints, which increase the information density produced per unit sample volume. This TENGi nanoESI strategy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analyses cannot be applied. Our method opens up avenues for future investigations into understanding metabolic changes caused by diseases or external stimuli.

Advances in Genomic, Transcriptomic, and Metabolomic Analyses of Fruit Quality in Fruit Crops

Fruit quality is the main factor determining market competitiveness; it represents the combination of fruit flavor, color, size, and the contents of aromatic and bioactive substances. Research on the genetic basis of fruit quality can provide new information about fruit biology, promote genomic-assisted breeding, and provide technological support for the regulation of fruit quality via habitat selection and/or the control of environmental conditions. High-throughput sequencing is a powerful research method for studying fruit quality traits, and reference genome sequences for many important fruit crops have provided vast amounts of genomic data. To study fruit quality, it is important to select appropriate omics strategies and to analyze omics data meaningfully. Here, we summarize genomic mechanisms of fruit quality formation: gene duplication, transposable element insertion, structural variations and genome methylation in functional genes. We review the genomic, transcriptomic, and metabolomic strategies that have been used to study the genetic basis of fruit quality traits. We also describe some of the genes associated with fruit traits; these genes are a valuable resource for genomics-assisted breeding and are useful models for deciphering the mechanisms of agronomic traits, such as fruit color, size, hardness, aroma components, sugar and acid content. Finally, to maximize the application of omics information, we propose some further directions for research using omics strategies.

Metabolomics strategy for revealing the components in fermented barley extracts with Lactobacillus plantarum dy-1

Fermentation has been considered as effective tools to promote the functional properties of cereals. In this paper, barley flour was fermented with Lactobacillus plantarum dy-1 (L. plantarum dy-1) and the main components in the fermented barley aqueous extracts were identified using by ultra-high performance liquid chromatography tandem with high resolution mass spectrometry (UPLC-HRMS), and investigated by metabolomics strategy involved on chemometrics. The barley extracts were prepared at the fermentation time of 0, 4, 8, 12, 16, 20, 24, 28 h, respectively and a total of 124 compounds were detected in the samples. Principal component analysis (PCA) was performed and the results indicated that the fermentation process became to slow down from 16 h until terminated. During fermentation, saccharides, amino acids, nucleosides, and some organic acids decreased, while lipids and bioactive molecules in barley were released and metabolites were accumulated by L. plantarum dy-1. Meanwhile, partial least squares discrimination analysis (PLS-DA) was performed for revealing the characteristic components in fermented barley aqueous extracts, including some functional molecules such as indole-3-lactic acid, phenyllactic acid, homovanillic acid and cafestol, etc., which provided the roles of them and the basis for further investigation on the functional bioactivities and application.

Comparative Lipidomic Analyses Reveal Different Protections in Preterm and Term Breast Milk for Infants.

Aim: Neonates are notably vulnerable, however they have improved outcomes if they are fed human milk. Human milk lipids constitute the primary constituents of human milk and serve a pivotal role in safeguarding infants from diseases. We assessed the lipid differences between preterm and term human milk and predicted the prospective impacts of these lipids on the development of neonates.Methods and results: We collected colostrum from healthy breast-feeding mothers who had delivered either term or preterm infants. We analyzed the lipid profiles of preterm, as well as term human milk using an LC-MS/MS metabolomics strategy. The orthogonal partial least-squares discriminant analysis score plots revealed remarkable distinction of lipids in preterm and term human milk. In total, 16 subclasses of 235 differential lipids (variable importance in projection > 1, P < 0.05) were identified. Notably, phosphatidylethanolamine and phosphatidylcholine were robustly increased in preterm human milk, while diacylglycerol and ceramide were markedly decreased in preterm human milk. Pathway analysis revealed that these dysregulated lipids are closely associated with glycerophospholipid metabolism, sphingolipid metabolism, Reelin signaling in neurons, and LXR/RXR activation.Conclusion: The results show that the lipids in preterm and term human colostrum vary, which may be critical for neonatal development.

Comparative Metabolic Profiling of Two Contrasting Date Palm Genotypes Under Salinity

Since specific metabolites may be associated with salinity tolerance, this study aimed to decipher the salinity tolerance mechanism in date palm based on the information encoded by the metabolomic profiles of the salt-tolerant “Umsila” and salt-susceptible “Zabad” cultivars when grown under salinity conditions. Changes in the metabolomic profiles of the leaf and root tissues were determined using hydrophilic interaction liquid chromatography (HILIC) and reverse-phase liquid chromatography (RPLC) mass spectrometry. The global untargeted metabolomic analysis showed the presence of 4878 metabolites accumulated in leaf and root tissues of the date palm seedlings. Principal component analysis (PCA) revealed the presence of unique groups of metabolites for each treatment and tissue type. Pathway analysis showed the involvement of some of these metabolites in the biosynthesis of several types of membranous lipids and glycolipids molecules such as 18:0-lyso-phosphatidylethanolamine (lysoPE), and also the synthesis of cell-wall components such as 16-hydroxy hexadecanoic acid, which is an intermediate metabolite in cutin, suberin, and wax biosynthesis. Moreover, antioxidant flavonoids such as (+)-catechin and epicatechin, vitamins such as B9, phytohormone-associated compounds such as dihydrozeatin-9-N-glucoside-O-glucoside, and osmolytes such as the sulfonic amino acid taurine were all significantly (p ≤ 0.05, FWER ≤ 0.05) altered in response to salinity in both cultivars. These results indicate that salinity tolerance in date palm involved a multi-dimensional mechanism, which includes the modification of the cell-wall and cellular membranes, the production of oxygen species scavengers, the adjustment of cellular osmotic pressure, and probably the alteration of the hormonal balance. The intracultivar metabolomic profile comparison strategy performed in this study represents an approach that may pave the road toward the identification of salinity tolerance mechanisms in date palm based on the final protein products.

An untargeted LC-MS metabolomics approach to the metabolic profiles of bottom cultured scallops (Mizuhopecten yessoensis) subjected to mechanical shock in early post-harvest handling

From on-board handling to land-based depuration, scallops are subject to various stresses. Mechanical shock is one of the unavoidable factors of post-harvest handling. In this research, a metabolomics strategy based on ultra performance liquid chromatography–mass spectrometry (UPLC-MS) was used to investigate the metabolic characteristics of live scallops (Mizuhopecten yessoensis) subjected to mechanical shock. Phosphoarginine and ATP-related compound levels were also measured to understand the metabolic disturbances. Live scallops maintained in a circulating seawater system for 36 h formed the control group, while those individuals dropped 15 times onto a hard surface from a height of 1 m before being maintained in a circulating seawater system formed the shock group. Samples were collected from the adductor muscles, and multivariate statistical analyses were performed to identify the potential biomarkers of mechanical shock due to post-harvest handling. Our results suggested that obvious metabolic disturbances occurred when scallops suffered mechanical shock during post-harvest handling. A total of 18 biomarkers were identified, including 10 upregulated and 8 downregulated biomarkers. Pathway enrichment analysis showed that the biosynthesis of amino acids and cysteine and methionine metabolism were prone to interference when M. yessoensis was subjected to mechanical shock during early post-harvest handling. This study provides a new perspective into the metabolic profiles of scallops subjected to various stressors and can assist in the improvement of disposal methods of post-harvest scallops.