Metabolomics by numbers: acquiring and understanding global metabolite data

Combinatorial metabolomic and transcriptomic analysis of muscle growth in hybrid striped bass (female white bass Morone chrysops x male striped bass M. saxatilis)

BACKGROUND

Understanding growth regulatory pathways is important in aquaculture, fisheries, and vertebrate physiology generally. Machine learning pattern recognition and sensitivity analysis were employed to examine metabolomic small molecule profiles and transcriptomic gene expression data generated from liver and white skeletal muscle of hybrid striped bass (white bass Morone chrysops x striped bass M. saxatilis) representative of the top and bottom 10 % by body size of a production cohort.

RESULTS

Larger fish (good-growth) had significantly greater weight, total length, hepatosomatic index, and specific growth rate compared to smaller fish (poor-growth) and also had significantly more muscle fibers of smaller diameter (≤ 20 µm diameter), indicating active hyperplasia. Differences in metabolomic pathways included enhanced energetics (glycolysis, citric acid cycle) and amino acid metabolism in good-growth fish, and enhanced stress, muscle inflammation (cortisol, eicosanoids) and dysfunctional liver cholesterol metabolism in poor-growth fish. The majority of gene transcripts identified as differentially expressed between groups were down-regulated in good-growth fish. Several molecules associated with important growth-regulatory pathways were up-regulated in muscle of fish that grew poorly: growth factors including agt and agtr2 (angiotensins), nicotinic acid (which stimulates growth hormone production), gadd45b, rgl1, zfp36, cebpb, and hmgb1; insulin-like growth factor signaling (igfbp1 and igf1); cytokine signaling (socs3, cxcr4); cell signaling (rgs13, rundc3a), and differentiation (rhou, mmp17, cd22, msi1); mitochondrial uncoupling proteins (ucp3, ucp2); and regulators of lipid metabolism (apoa1, ldlr). Growth factors pttg1, egfr, myc, notch1, and sirt1 were notably up-regulated in muscle of good-growing fish.

CONCLUSION

A combinatorial pathway analysis using metabolomic and transcriptomic data collectively suggested promotion of cell signaling, proliferation, and differentiation in muscle of good-growth fish, whereas muscle inflammation and apoptosis was observed in poor-growth fish, along with elevated cortisol (an anti-inflammatory hormone), perhaps related to muscle wasting, hypertrophy, and inferior growth. These findings provide important biomarkers and mechanisms by which growth is regulated in fishes and other vertebrates as well.

Effects of biochar and compost on microbial community assembly and metabolic processes in glyphosate, imidacloprid and pyraclostrobin polluted soil under freezethaw cycles

Biochar and organic compost are widely used in agricultural soil remediation as soil immobilization agents. However, the effects of biochar and compost on microbial community assembly processes in polluted soil under freezingthawing need to be further clarified. Therefore, a freezethaw cycle experiment was conducted with glyphosate (herbicide), imidacloprid (insecticide) and pyraclostrobin (fungicide) polluted to understand the effect of biochar and compost on microbial community assembly and metabolic behavior. We found that biochar and compost could significantly promote the degradation of glyphosate, imidacloprid and pyraclostrobin in freezethaw soil decrease the half-life of the three pesticides. The addition of immobilization agents improved soil bacterial and fungal communities and promoted the transformation from homogeneous dispersal to homogeneous selection. For soil metabolism, the combined addition of biochar and compost alleviated the pollution of glyphosate, imidacloprid and imidacloprid to soil through up-regulation of metabolites (DEMs) in amino acid metabolism pathway and down-regulation of DEMs in fatty acid metabolism pathway. The structural equation modeling (SEM) results showed that soil pH and DOC were the main driving factors affecting microbial community assembly and metabolites. In summary, the combined addition of biochar and compost reduced the adverse effects of pesticides residues.

Solutes unmask differences in clustering versus phase separation of FET proteins

Phase separation and percolation contribute to phase transitions of multivalent macromolecules. Contributions of percolation are evident through the viscoelasticity of condensates and through the formation of heterogeneous distributions of nano- and mesoscale pre-percolation clusters in sub-saturated solutions. Here, we show that clusters formed in sub-saturated solutions of FET (FUS-EWSR1-TAF15) proteins are affected differently by glutamate versus chloride. These differences on the nanoscale, gleaned using a suite of methods deployed across a wide range of protein concentrations, are prevalent and can be unmasked even though the driving forces for phase separation remain unchanged in glutamate versus chloride. Strikingly, differences in anion-mediated interactions that drive clustering saturate on the micron-scale. Beyond this length scale the system separates into coexisting phases. Overall, we find that sequence-encoded interactions, mediated by solution components, make synergistic and distinct contributions to the formation of pre-percolation clusters in sub-saturated solutions, and to the driving forces for phase separation.

Reproducible mass spectrometry data processing and compound annotation in MZmine 3

Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.

Phosphoproteomic analysis of APP/PS1 mice of Alzheimer's disease by DIA based mass spectrometry analysis with PRM verification

Traditional Chinese medicine has been utilized in China for approximately thousands of years in clinical settings to prevent Alzheimer's disease (AD) and enhance memory, despite the lack of a systematic exploration of its biological underpinnings. Exciting research has corroborated the beneficial effects of tetrahydroxy stilbene glycoside (TSG), an extract derived from Polygonum multiflorum, in delaying learning and memory impairment in a model that mimics AD. Therefore, the primary objective of this study is to investigate the major function of TSG upon protein regulation in AD. Herein, a novel approach, encompassing data independent acquisition (DIA), DIA phosphorylated proteomics, and parallel reaction monitoring (PRM), was utilized to integrate quantitative proteomic data collected from APP/PS1 mouse model exhibiting toxic intracellular aggregation of Aβ. Initially, we deliberated upon both single and multi-dimensional data pertaining to AD model mice. Furthermore, we authenticated disparities in protein phosphorylation quantity and expression, phosphorylation function, and ultimately phosphorylation kinase analysis. In order to validate the results, we utilized PRM ion monitoring technology to identify potential protein or peptide biomarkers. In the mixed samples, targeted detection of 50 target proteins revealed that 26 to 33 target proteins were stably detected by PRM. In summary, our findings provide new candidates for AD biomarker, which have been identified and validated through protein researches conducted on mouse brains. This offers a wealth of potential resources for extensive biomarker validation in neurodegenerative diseases. SIGNIFICANCE: DIA phosphorylated proteomics technique was used to detect and analyze phosphorylated proteins in brain tissues of mice with AD. Data were analyzed by various bioinformatics tools to explore the phosphorylation events and characterize them related to TSG. The results of DIA were further verified by PRM. Besides, we mapped the major metabolite classes emerging from the analyses to key biological pathways implicated in AD to understand the potential roles of the molecules and the interactions in triggering symptom onset and progression of AD. Meanwhile, we clarified that in the context of AD onset and TSG intervention, the changes in proteins, protein phosphorylation, phosphorylation kinases, and the internal connections.

Metabolic profiling analysis of head and neck squamous cell carcinoma

OBJECTIVE

Tumor cells can acquire a large amount of energy and structural components by reprogramming energy metabolism; moreover, metabolic profiles slightly differ according to cancer type. This study compared and assessed the metabolic profile of head and neck squamous cell carcinoma (HNSCC) and normal tissues, which were collected from patients without cancer.

SUBJECTS AND METHODS

Overall, 23 patients with HNSCC and 6 patients without cancer were included in the analysis. Metabolomic profiles were analyzed using capillary electrophoresis-mass spectrometry. Gene expression was evaluated using real-time reverse transcription-polymerase chain reaction.

RESULTS

Glycolysis, the pentose phosphate pathway, tricarboxylic acid cycle, and glutamine metabolism were upregulated in HNSCC tissues based on gene expression analysis. HNSCC could then have enhanced energy production and structural component. The levels of lactate, succinate, glutathione, 2-hydroxyglutarate, and S-adenosylmethionine, considered as oncometabolites, increased and these had accumulated in HNSCC tissues.

CONCLUSIONS

The level of metabolites and the expression of enzymes differ between HNSCC and normal tissues. Reprogramming metabolism in HNSCC provides an energy source as well as structural components, creating a system that offers rapid proliferation, progression, and is less likely to be eliminated.

An exercise physiologist's guide to metabolomics

The field of exercise physiology has undergone significant technological advancements since the pioneering works of exercise physiologists in the early to mid-20th century. Historically, the ability to detect metabolites in biofluids from exercising participants was limited to single-metabolite analyses. However, the rise of metabolomics, a discipline focused on the comprehensive analysis of metabolites within a biological system, has facilitated a more intricate understanding of metabolic pathways and networks in exercise. This review explores some of the pivotal technological and bioinformatic advancements that have propelled metabolomics to the forefront of exercise physiology research. Metabolomics offers a unique 'fingerprint' of cellular activity, offering a broader spectrum than traditional single-metabolite assays. Techniques, including mass spectrometry and nuclear magnetic resonance spectroscopy, have significantly improved the speed and sensitivity of metabolite analysis. Nonetheless, challenges persist, including study design and data interpretation issues. This review aims to serve as a guide for exercise physiologists to facilitate better research design, data analysis and interpretation within metabolomics. The potential of metabolomics in bridging the gap between genotype and phenotype is emphasised, underscoring the critical importance of careful study design and the selection of appropriate metabolomics techniques. Furthermore, the paper highlights the need to deeply understand the broader scientific context to discern meaningful metabolic changes. The emerging field of fluxomics, which seeks to quantify metabolic reaction rates, is also introduced as a promising avenue for future research.

Prediagnostic plasma metabolite concentrations and liver cancer risk: a population-based study of Chinese men

BACKGROUND

Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites. In this study, we examined the association between the concentrations of 186 targeted metabolites and liver cancer risk using prediagnostic plasma samples collected up to 14 years prior to the clinical diagnosis of liver cancer.

METHODS

We conducted a nested case-control study (n = 322 liver cancer cases, n = 322 matched controls) within the Shanghai Men's Health Study. Conditional logistic regression models adjusted for demographics, lifestyle factors, dietary habits, and related medical histories were used to estimate the odds ratios. Restricted cubic spline functions were used to characterise the dose-response relationships between metabolite concentrations and liver cancer risk.

FINDINGS

After adjusting for potential confounders and correcting for multiple testing, 28 metabolites were associated with liver cancer risk. Significant non-linear relationships were observed for 22 metabolites. The primary bile acid biosynthesis and phenylalanine, tyrosine and tryptophan biosynthesis were found to be important pathways involved in the aetiology of liver cancer. A metabolic score consisting of 10 metabolites significantly improved the predictive ability of traditional epidemiological risk factors for liver cancer, with an optimism-corrected AUC increased from 0.84 (95% CI: 0.81-0.87) to 0.89 (95% CI: 0.86-0.91).

INTERPRETATION

This study characterised the dose-response relationships between metabolites and liver cancer risk, providing insights into the complex metabolic perturbations prior to the clinical diagnosis of liver cancer. The metabolic score may serve as a candidate risk predictor for liver cancer.

FUNDING

National Key Project of Research and Development Program of China [2021YFC2500404, 2021YFC2500405]; US National Institutes of Health [subcontract of UM1 CA173640].

Exploring the adverse effects of 1,3,6,8-tetrabromo-9H-carbazole in atherosclerotic model mice by metabolomic profiling integrated with mechanism studies in vitro

Given its wide distribution in the environment and latent toxic effects, 1,3,6,8-tetrabromo-9H-carbazole (1368-BCZ) is an emerging concern that has gained increasing attention globally. 1368-BCZ exposure is reported to have potential cardiovascular toxicity. Although atherosclerosis is a cardiovascular disease and remains a primary cause of mortality worldwide, no evidence has been found regarding the impact of 1368-BCZ on atherosclerosis. Therefore, we aimed to explore the deleterious effects of 1368-BCZ on atherosclerosis and the underlying mechanisms. Serum samples from 1368-BCZ-treated atherosclerotic model mice were subjected to metabolomic profiling to investigate the adverse influence of the pollutant. Subsequently, the molecular mechanism associated with the metabolic pathway of atherosclerotic mice that was identified following 1368-BCZ exposure was validated in vitro. Serum metabolomics analysis revealed that 1368-BCZ significantly altered the tricarboxylic acid cycle, causing a disturbance in energy metabolism. In vitro, we further validated general markers of energy metabolism based on metabolome data: 1368-BCZ dampened adenosine triphosphate (ATP) synthesis and increased reactive oxygen species (ROS) production. Furthermore, blocking the aryl hydrocarbon receptor (AhR) reversed the high production of ROS induced by 1368-BCZ. It is concluded that 1368-BCZ decreased the ATP synthesis by disturbing the energy metabolism, thereby stimulating the AhR-mediated ROS production and presumably causing aggravated atherosclerosis. This is the first comprehensive study on the cardiovascular toxicity and mechanism of 1368-BCZ based on rodent models of atherosclerosis and integrated with in vitro models.

Pan-Omics in Sheep: Unveiling Genetic Landscapes

Multi-omics-integrated analysis, known as panomics, represents an advanced methodology that harnesses various high-throughput technologies encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Sheep, playing a pivotal role in agricultural sectors due to their substantial economic importance, have witnessed remarkable advancements in genetic breeding through the amalgamation of multiomics analyses, particularly with the evolution of high-throughput technologies. This integrative approach has established a robust theoretical foundation, enabling a deeper understanding of sheep genetics and fostering improvements in breeding strategies. The comprehensive insights obtained through this approach shed light on diverse facets of sheep development, including growth, reproduction, disease resistance, and the quality of livestock products. This review primarily focuses on the application of principal omics analysis technologies in sheep, emphasizing correlation studies between multiomics data and specific traits such as meat quality, wool characteristics, and reproductive features. Additionally, this paper anticipates forthcoming trends and potential developments in this field.

Phenotypic flexibility in metabolic adjustments and digestive function in white-shouldered starlings: responses to short-term temperature acclimation

Changing the intrinsic rate of metabolic heat production is the main adaptive strategy for small birds to cope with different ambient temperatures. In this study, we tested the hypothesis that the small passerine the white-shouldered starling (Sturnus sinensis) can modulate basal metabolism under temperature acclimation by changing the morphological, physiological and biochemical state of its tissues and organs. We measured the effects of temperature on body mass, basal metabolic rate (BMR), wet mass of various internal organs, state 4 respiration (S4R) and cytochrome c oxidase (CCO) activity in the pectoral muscle and organs, metabolites in the pectoral muscle, energy intake, histological dynamics and the activity of duodenal digestive enzymes. Warm acclimation decreased BMR to a greater extent than cold acclimation. At the organ level, birds in the cold-acclimated group had significantly heavier intestines but significantly lighter pectoral muscles. At the cellular level, birds in the cold-acclimated group showed significantly higher S4R in the liver and heart and CCO activity in the liver and kidney at both the mass-specific and whole-organ levels. A metabolomic analysis of the pectoral tissue revealed significantly higher lipid decomposition, amino acid degradation, ATP hydrolysis, and GTP and biotin synthesis in cold-acclimated birds. Acclimation to cold significantly increased the gross energy intake (GEI), feces energy (FE) and digestive energy intake (DEI) but significantly decreased the digestive efficiency of these birds. Furthermore, cold-acclimated birds had a higher maltase activity and longer villi in the duodenum. Taken together, these data show that white-shouldered starlings exhibit high phenotypic flexibility in metabolic adjustments and digestive function under temperature acclimation, consistent with the notion that small birds cope with the energy challenges presented by a cold environment by modulating tissue function in a way that would affect BMR.

An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism

Inborn errors of metabolism (IEMs) encompass a diverse group of disorders that can be difficult to classify due to heterogenous clinical, molecular, and biochemical manifestations. Untargeted metabolomics platforms have become a popular approach to analyze IEM patient samples because of their ability to detect many metabolites at once, accelerating discovery of novel biomarkers, and metabolic mechanisms of disease. However, there are concerns about the reproducibility of untargeted metabolomics research due to the absence of uniform reporting practices, data analyses, and experimental design guidelines. Therefore, we critically evaluated published untargeted metabolomic platforms used to characterize IEMs to summarize the strengths and areas for improvement of this technology as it progresses towards the clinical laboratory. A total of 96 distinct IEMs were collectively evaluated by the included studies. However, most of these IEMs were evaluated by a single untargeted metabolomic method, in a single study, with a limited cohort size (55/96, 57%). The goals of the included studies generally fell into two, often overlapping, categories: detecting known biomarkers from many biochemically distinct IEMs using a single platform, and detecting novel metabolites or metabolic pathways. There was notable diversity in the design of the untargeted metabolomic platforms. Importantly, the majority of studies reported adherence to quality metrics, including the use of quality control samples and internal standards in their experiments, as well as confirmation of at least some of their feature annotations with commercial reference standards. Future applications of untargeted metabolomics platforms to the study of IEMs should move beyond single-subject analyses, and evaluate reproducibility using a prospective, or validation cohort.

Impact of Conventional and Potential New Metal-Based Drugs on Lipid Metabolism in Osteosarcoma MG-63 Cells

This work investigated the mechanisms of action of conventional drugs, cisplatin and oxaliplatin, and the potentially less deleterious drug Pd2Spermine (Spm) and its Pt(II) analog, against osteosarcoma MG-63 cells, using nuclear-magnetic-resonance metabolomics of the cellular lipidome. The Pt(II) chelates induced different responses, namely regarding polyunsaturated-fatty-acids (increased upon cisplatin), suggesting that cisplatin-treated cells have higher membrane fluidity/permeability, thus facilitating cell entry and justifying higher cytotoxicity. Both conventional drugs significantly increased triglyceride levels, while Pt2Spm maintained control levels; this may reflect enhanced apoptotic behavior for conventional drugs, but not for Pt2Spm. Compared to Pt2Spm, the more cytotoxic Pd2Spm (IC50 comparable to cisplatin) induced a distinct phospholipids profile, possibly reflecting enhanced de novo biosynthesis to modulate membrane fluidity and drug-accessibility to cells, similarly to cisplatin. However, Pd2Spm differed from cisplatin in that cells had equivalent (low) levels of triglycerides as Pt2Spm, suggesting the absence/low extent of apoptosis. Our results suggest that Pd2Spm acts on MG-63 cells mainly through adaptation of cell membrane fluidity, whereas cisplatin seems to couple a similar effect with typical signs of apoptosis. These results were discussed in articulation with reported polar metabolome adaptations, building on the insight of these drugs' mechanisms, and particularly of Pd2Spm as a possible cisplatin substitute.

Metabolomics signature of cardiovascular disease in patients with diabetes, a narrative review

Objectives

The exact underlying mechanism of developing diabetes-related cardiovascular disease (CVD) among patients with type 2 diabetes (T2D) is not clear. Metabolomics can provide a platform enabling the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The aim of this review is to summarize the available evidence on the relationship between metabolomics and cardiovascular diseases in patients with diabetes.

Methods

The literature was searched to find out studies that have investigated the relationship between the alteration of specific metabolites and cardiovascular diseases in patients with diabetes.

Results

Evidence proposed that changes in the metabolism of certain amino acids, lipids, and carbohydrates, independent of traditional CVD risk factors, are associated with increased CVD risk.

Conclusions

Metabolomics can provide a platform to enable the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The association of the alteration in specific metabolites with CVD may be considered in the investigations for the development of new therapeutic targets for the prevention of CVD in patients with diabetes mellitus.

CSF metabolomics alterations after aneurysmal subarachnoid hemorrhage: what do we know?

PURPOSE

The purpose of this mini review is to describe metabolomics in cerebrospinal fluid (CSF) and its potential in aneurysmal subarachnoid hemorrhage (aSAH). In brain injury, patients' micro dialysis enables detecting biochemical change in brain tissue. Indicators for ischemia were detected such as lactate, pyruvate, glucose, and glutamate. In aSAH patients, the pathophysiology and the factor for poor outcome are not completely understood yet. Routine use of biomarkers in CSF, particularly in aSAH patients, is still lacking.

METHODS

This mini review was performed on the role of metabolomics alterations after aneurysmal subarachnoid hemorrhage.

RESULTS

We identified five clinical studies that addressed metabolomics in patients with aneurysmal subarachnoid hemorrhage.

CONCLUSION

There is increasing evidence suggesting that biomarkers can give insight in the pathogenesis and can serve as an outcome predictor. In this mini review, we present a brief overview of metabolomics profiling in neuroscience and wish to discuss the predictive and therapeutic value in aSAH patients.

Comparison of the metabolite profile of donkey and horse seminal plasma and its relationship with sperm viability and motility

Previous research revealed that several seminal plasma (SP) metabolites are related to sperm functionality, fertility, and preservation. While it is understood that variations between species exist, whether the SP metabolome differs between donkeys and horses has not been previously investigated. The aim of this work, therefore, was to characterize and compare donkey and horse SP metabolites using nuclear magnetic resonance (NMR) spectroscopy, and relate them to sperm viability and motility. For this purpose, ejaculates from 18 different donkeys and 18 different horses were collected and separated into two aliquots: one for harvesting the SP by centrifugation and obtaining the metabolic profile through NMR, and the other for evaluating sperm viability and motility. Based on total motility and sperm viability, samples were classified as with good (GQ) or poor (PQ) quality. The metabolomic profile of donkey and horse SP revealed the presence of 28 metabolites, which coincided in the two species. Yet, differences between horses and donkeys were observed in the concentration of 18 of these 28 metabolites, as well as between ejaculates classified as GQ or PQ and in the relationship of metabolites with sperm motility and viability. These findings suggest that sperm from donkeys and horses differ in their metabolism and energetic requirements, and that the concentration of specific SP metabolites may be related to sperm functionality. Further research should shed light on the metabolic needs of donkey and horse sperm, and evaluate how the knowledge collected from the contribution of these metabolites can help improve semen preservation in the two species.

Using metabolomics to understand stress responses in Lactic Acid Bacteria and their applications in the food industry

BACKGROUND

Lactic Acid Bacteria (LAB) are commonly used as starter cultures, probiotics, to produce lactic acid and other useful compounds, and even as natural preservatives. For use in any food product however, LAB need to survive the various stresses they encounter in the environment and during processing. Understanding these mechanisms may enable direction of LAB biochemistry with potential beneficial impact for the food industry.

AIM OF REVIEW

To give an overview of the use of LAB in the food industry and then generate a deeper biochemical understanding of LAB stress response mechanisms via metabolomics, and methods of screening for robust strains of LAB.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Uses of LAB in food products were assessed and factors which contribute to survival and tolerance in LAB investigated. Changes in the metabolic profiles of LAB exposed to stress were found to be associated with carbohydrates, amino acids and fatty acid levels and these changes were proposed to be a result of the bacteria trying to maintain cellular homeostasis in response to external conditions and minimise cellular damage from reactive oxygen species. This correlates with morphological analysis which shows that LAB can undergo cell elongation and shortening, as well as thinning and thickening of cell membranes, when exposed to stress. It is proposed that these innate strategies can be utilised to minimise negative effects caused by stress through selection of intrinsically robust strains, genetic modification and/or prior exposure to sublethal stress. This work demonstrates the utility of metabolomics to the food industry.

A Critical Analysis of the FDA's Omics-Driven Pharmacodynamic Biomarkers to Establish Biosimilarity

Demonstrating biosimilarity entails comprehensive analytical assessment, clinical pharmacology profiling, and efficacy testing in patients for at least one medical indication, as required by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The efficacy testing can be waived if the drug has known pharmacodynamic (PD) markers, leaving most therapeutic proteins out of this concession. To overcome this, the FDA suggests that biosimilar developers discover PD biomarkers using omics technologies such as proteomics, glycomics, transcriptomics, genomics, epigenomics, and metabolomics. This approach is redundant since the mode-action-action biomarkers of approved therapeutic proteins are already available, as compiled in this paper for the first time. Other potential biomarkers are receptor binding and pharmacokinetic profiling, which can be made more relevant to ensure biosimilarity without requiring biosimilar developers to conduct extensive research, for which they are rarely qualified.

Recent Analytical Advances for Decoding Metabolic Reprogramming in Lung Cancer

Lung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.

Glutamate helps unmask the differences in driving forces for phase separation versus clustering of FET family proteins in sub-saturated solutions

Multivalent proteins undergo coupled segregative and associative phase transitions. Phase separation, a segregative transition, is driven by macromolecular solubility, and this leads to coexisting phases above system-specific saturation concentrations. Percolation is a continuous transition that is driven by multivalent associations among cohesive motifs. Contributions from percolation are highlighted by the formation of heterogeneous distributions of clusters in sub-saturated solutions, as was recently reported for Fused in sarcoma (FUS) and FET family proteins. Here, we show that clustering and phase separation are defined by a separation of length- and energy-scales. This is unmasked when glutamate is the primary solution anion. Glutamate is preferentially excluded from protein sites, and this enhances molecular associations. Differences between glutamate and chloride are manifest at ultra-low protein concentrations. These differences are amplified as concentrations increase, and they saturate as the micron-scale is approached. Therefore, condensate formation in supersaturated solutions and clustering in sub-saturated are governed by distinct energy and length scales. Glutamate, unlike chloride, is the dominant intracellular anion, and the separation of scales, which is masked in chloride, is unmasked in glutamate. Our work highlights how components of cellular milieus and sequence-encoded interactions contribute to amplifying distinct contributions from associative versus segregative phase transitions.

Plasma metabolome identifies potential biomarkers of gastric precancerous lesions and gastric cancer risk

OBJECTIVES

Currently, metabolic biomarkers with great practicability of gastric cancer (GC) and gastric precancerous lesions (GPL) are scarce. Thus, we are devoted to determining the plasma metabolic profiles of patients with GPL or GC and validate candidate biomarkers for disease diagnosis.

METHODS

In this hospital-based case-control study, 68 plasma samples from 27 non-atrophic gastritis (NAG, control), 31 GPL, and 10 GC patients were collected for targeted metabolomics analysis. Univariate and multivariate analyses were used for selecting the differential metabolites. A receiver operating characteristic curve combined with binary logistic regression analysis was performed to test the diagnostic performance of the differential metabolites. Dietary data were obtained using a semiquantitative food frequency questionnaire.

RESULTS

Distinct metabolomic profiles were noted for NAG, GPL, and GC. Compared to the NAG patients, the levels of 5 metabolites in the GPL group and 4 metabolites in the GC group were found to significantly elevate. Compared with the model involving 9 traditional risk factors (AUC: 0.89, 95%CI: 0.78-1.00), Trimethylamine N-oxide, the most significant metabolite (P = 2.00 × 10-5, FDR = 0.003, FC > 2, VIP > 2), showed a good diagnostic performance for the patients with GC (AUC: 0.90, 95%CI: 0.78-1.00), and its diagnostic performance has been further improved with the integration of Rhamnose (AUC: 0.96, 95%CI: 0.89-1.00).

CONCLUSION

In our study, 9 defined metabolites might serve as meaningful biomarkers for identifying the high-risk population of GPL and GC, possibly enhancing the prevention and control of GPL and GC.

Evaluation of Metabolomics as Diagnostic Targets in Oral Squamous Cell Carcinoma: A Systematic Review

In recent years, high-throughput technologies have facilitated the widespread use of metabolomics to identify biomarkers and targets for oral squamous cell carcinoma (OSCC). As a result, the primary goal of this systematic review is to identify and evaluate metabolite biomarkers and their pathways for OSCC that featured consistently across studies despite methodological variations. Six electronic databases (Medline, Cochrane, Web of Science, CINAHL, ProQuest, and Embase) were reviewed for the longitudinal studies involving OSCC patients and metabolic marker analysis (in accordance with PRISMA 2020). The studies included ranged from the inception of metabolomics in OSCC (i.e., 1 January 2007) to 30 April 2023. The included studies were then assessed for their quality using the modified version of NIH quality assessment tool and QUADOMICS. Thirteen studies were included after screening 2285 studies. The majority of the studies were from South Asian regions, and metabolites were most frequently derived from saliva. Amino acids accounted for more than quarter of the detected metabolites, with glutamate and methionine being the most prominent. The top dysregulated metabolites indicated dysregulation of six significantly enriched pathways including aminoacyl-tRNA biosynthesis, glutathione metabolism and arginine biosynthesis with the false discovery rate (FDR) <0.05. Finally, this review highlights the potential of metabolomics for early diagnosis and therapeutic targeting of OSCC. However, larger studies and standardized protocols are needed to validate these findings and make them a clinical reality.

Authentication of milk thistle commercial products using UHPLC-QTOF-ESI + MS metabolomics and DNA metabarcoding

BACKGROUND

Milk thistle is one of the most popular hepatoprotectants, and is often sold in combination with other ingredients. Botanical supplements are known to be vulnerable to contamination and adulteration, and emerging technologies show promise to improve their quality control.

METHODS

Untargeted and semi-targeted metabolomics based on UHPLC-QTOF-ESI⁺MS techniques, UV spectrometry, and DNA metabarcoding using Illumina MiSeq were used to authenticate eighteen milk thistle botanical formulations (teas, capsules, tablets, emulsion).

RESULTS

Untargeted metabolomics separated 217 molecules and by multivariate analysis the discrimination between the different preparations was established. The semi-targeted metabolomics focused on 63 phytochemicals, mainly silymarin flavonolignans and flavonoids, that may be considered as putative biomarkers of authenticity. All formulations contained molecules from silymarin complexes at different levels. The quantitative evaluation of silybins was done using in parallel UV spectrometry and UHPLC-QTOF-ESI⁺MS and their correlations were compared. DNA metabarcoding detected milk thistle in eleven out of sixteen retained preparations, whereas two others had incomplete evidence of milk thistle despite metabolomics validating specific metabolites, e.g., silymarin complex, identified and quantified in all samples. Meanwhile, the DNA metabarcoding provided insights into the total species composition allowing the interpretation of the results in a broad context.

CONCLUSION

Our study emphasizes that combining spectroscopic, chromatographic, and genetic techniques bring complementary information to guarantee the quality of the botanical formulations.

Mass spectrometry-based metabolomic analysis as a tool for quality control of natural complex products

Metabolomics is an area of intriguing and growing interest. Since the late 1990s, when the first Omic applications appeared to study metabolite's pool ("metabolome"), to understand new aspects of the global regulation of cellular metabolism in biology, there have been many evolutions. Currently, there are many applications in different fields such as clinical, medical, agricultural, and food. In our opinion, it is clear that developments in metabolomics analysis have also been driven by advances in mass spectrometry (MS) technology. As natural complex products (NCPs) are increasingly used around the world as medicines, food supplements, and substance-based medical devices, their analysis using metabolomic approaches will help to bring more and more rigor to scientific studies and industrial production monitoring. This review is intended to emphasize the importance of metabolomics as a powerful tool for studying NCPs, by which significant advantages can be obtained in terms of elucidation of their composition, biological effects, and quality control. The different approaches of metabolomic analysis, the main and basic techniques of multivariate statistical analysis are also briefly illustrated, to allow an overview of the workflow associated with the metabolomic studies of NCPs. Therefore, various articles and reviews are illustrated and commented as examples of the application of MS-based metabolomics to NCPs.

Unlocking the secrets of the microbiome: exploring the dynamic microbial interplay with humans through metabolomics and their manipulation for synthetic biology applications

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.

Fish Skin Mucus Extracts: An Underexplored Source of Antimicrobial Agents

The slow discovery of new antibiotics combined with the alarming emergence of antibiotic-resistant bacteria underscores the need for alternative treatments. In this regard, fish skin mucus has been demonstrated to contain a diverse array of bioactive molecules with antimicrobial properties, including peptides, proteins, and other metabolites. This review aims to provide an overview of the antimicrobial molecules found in fish skin mucus and its reported in vitro antimicrobial capacity against bacteria, fungi, and viruses. Additionally, the different methods of mucus extraction, which can be grouped as aqueous, organic, and acidic extractions, are presented. Finally, omic techniques (genomics, transcriptomics, proteomics, metabolomics, and multiomics) are described as key tools for the identification and isolation of new antimicrobial compounds. Overall, this study provides valuable insight into the potential of fish skin mucus as a promising source for the discovery of new antimicrobial agents.

Plasma metabolite profile for primary open-angle glaucoma in three US cohorts and the UK Biobank

Glaucoma is a progressive optic neuropathy and a leading cause of irreversible blindness worldwide. Primary open-angle glaucoma is the most common form, and yet the etiology of this multifactorial disease is poorly understood. We aimed to identify plasma metabolites associated with the risk of developing POAG in a case-control study (599 cases and 599 matched controls) nested within the Nurses' Health Studies, and Health Professionals' Follow-Up Study. Plasma metabolites were measured with LC-MS/MS at the Broad Institute (Cambridge, MA, USA); 369 metabolites from 18 metabolite classes passed quality control analyses. For comparison, in a cross-sectional study in the UK Biobank, 168 metabolites were measured in plasma samples from 2,238 prevalent glaucoma cases and 44,723 controls using NMR spectroscopy (Nightingale, Finland; version 2020). Here we show higher levels of diglycerides and triglycerides are adversely associated with glaucoma in all four cohorts, suggesting that they play an important role in glaucoma pathogenesis.

The relationship between bovine blastocyst formation in vitro and follicular fluid amino acids

Follicular fluid has been found as a possible source of metabolic predictors for oocyte competence, and it is conveniently accessible during ovum pick-up (OPU). We used the OPU procedure to recover oocytes from 41 Holstein heifers for in vitro embryo production in this study. Follicular fluid was collected during OPU in order to establish a link between follicular amino acids and blastocyst formation. Each heifer's oocytes were collected, matured in vitro for 24 h and fertilized separately. The heifers were then divided into two groups based on blastocyst formation: those that produced at least one blastocyst (the blastocyst group, n = 29) and those that did not (the failed group, n = 12). The blastocyst group had higher follicular glutamine concentrations and lower aspartate levels than the failed group. Furthermore, network and Spearman correlation analyses revealed a link between blastocyst formation and aspartate (r = -0.37, p = 0.02) or glutamine (r = 0.38, p = 0.02). The receiver operator characteristic curve revealed that glutamine (AUC = 0.75) was the greatest predictor of blastocyst formation. These findings revealed that follicular amino acid levels in bovines can be used to predict blastocyst development.

New Approach for the Identification of Isobaric and Isomeric Metabolites

The structural elucidation of metabolite molecules is important in many branches of the life sciences. However, the isomeric and isobaric complexity of metabolites makes their identification extremely challenging, and analytical standards are often required to confirm the presence of a particular compound in a sample. We present here an approach to overcome these challenges using high-resolution ion mobility spectrometry in combination with cryogenic vibrational spectroscopy for the rapid separation and identification of metabolite isomers and isobars. Ion mobility can separate isomeric metabolites in tens of milliseconds, and cryogenic IR spectroscopy provides highly structured IR fingerprints for unambiguous molecular identification. Moreover, our approach allows one to identify metabolite isomers automatically by comparing their IR fingerprints with those previously recorded in a database, obviating the need for a recurrent introduction of analytical standards. We demonstrate the principle of this approach by constructing a database composed of IR fingerprints of eight isomeric/isobaric metabolites and use it for the identification of these isomers present in mixtures. Moreover, we show how our fast IR fingerprinting technology allows to probe the IR fingerprints of molecules within just a few seconds as they elute from an LC column. This approach has the potential to greatly improve metabolomics workflows in terms of accuracy, speed, and cost.

High-Resolution Liquid Chromatography-Mass Spectrometry-Based Metabolomics for the Classification of Chuquiraga (Barnadesioideae, Asteraceae): New Phenylpropanoid Derivatives as Chemical Markers for Chuquiraga spinosa

Despite their relatively poorly investigated phytochemistry, species of the genus Chuquiraga are widely commercialized. The present study reports the use of a high-resolution liquid chromatography-mass spectrometry-based metabolomics approach coupled with exploratory and supervised multivariate statistical analyses for species classification and chemical marker identification of four species of Chuquiraga (C. jussieui, C. weberbaueri, C. spinosa, and Chuquiraga sp.) from Ecuador and Peru. Based on these analyses, a high percentage of correct classifications (87% to 100%) allowed the prediction of the taxonomic identity of Chuquiraga species. Through the metabolite selection process, several key constituents with the potential to be chemical markers were identified. Samples of C. jussieui displayed alkyl glycosides and triterpenoid glycosides as discriminating metabolites, while Chuquiraga sp. displayed high concentrations of p-hydroxyacetophenone, p-hydroxyacetophenone 4-O-glucoside, p-hydroxyacetophenone 4-O-(6-O-apiosyl)-glucoside, and quinic acid ester derivatives as the main metabolites. Caffeic acid was characteristic for C. weberbaueri samples, whereas C. spinosa displayed higher concentrations of the following new phenylpropanoid ester derivatives: 2-O-caffeoyl-4-hydroxypentanedioic acid (24), 2-O-p-coumaroyl-4-hydroxypentanedioic acid (34), 2-O-feruloyl-4-hydroxypentanedioic acid (46), 2,4-O-dicaffeoylpentanedioic acid (71), and 2-O-caffeoyl-4-O-feruloylpentanedioic acid (77).

Is Cancer Reversible? Rethinking Carcinogenesis Models-A New Epistemological Tool

A growing number of studies shows that it is possible to induce a phenotypic transformation of cancer cells from malignant to benign. This process is currently known as "tumor reversion". However, the concept of reversibility hardly fits the current cancer models, according to which gene mutations are considered the primary cause of cancer. Indeed, if gene mutations are causative carcinogenic factors, and if gene mutations are irreversible, how long should cancer be considered as an irreversible process? In fact, there is some evidence that intrinsic plasticity of cancerous cells may be therapeutically exploited to promote a phenotypic reprogramming, both in vitro and in vivo. Not only are studies on tumor reversion highlighting a new, exciting research approach, but they are also pushing science to look for new epistemological tools capable of better modeling cancer.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Integration of omics studies indicates that species-dependent molecular mechanisms govern male fertility

BACKGROUND

Comparative and comprehensive omics studies have recently been conducted to provide a comprehensive understanding of the biological mechanisms underlying infertility. However, because these huge omics datasets often contain irrelevant information, editing strategies for summarizing and filtering the data are necessary prerequisite steps for identifying biomarkers of male fertility. Here, we attempted to integrate omics data from spermatozoa with normal and below-normal fertility from boars and bulls, including transcriptomic, proteomic, and metabolomic data. Pathway enrichment analysis was conducted and visualized using g:Profiler, Cytoscape, EnrichmentMap, and AutoAnnotation to determine fertility-related biological functions according to species.

RESULTS

In particular, gamete production and protein biogenesis-associated pathways were enriched in bull spermatozoa with below-normal fertility, whereas mitochondrial-associated metabolic pathways were enriched in boar spermatozoa with normal fertility. These results indicate that below-normal fertility may be determined by aberrant regulation of protein synthesis during spermatogenesis, and the modulation of reactive oxygen species generation to maintain capacitation and the acrosome reaction governs boar sperm fertility.

CONCLUSION

Overall, this approach demonstrated that distinct molecular pathways drive sperm fertility in mammals in a species-dependent manner. Moreover, we anticipate that searching for species-specific signaling pathways may aid in the discovery of fertility-related biomarkers within large omics datasets.

ASSVd infection inhibits the vegetative growth of apple trees by affecting leaf metabolism

Apple scar skin viroid (ASSVd) can infect apple trees and cause scar skin symptoms. However, the associated physiological mechanisms are unclear in young saplings. In this study, ASSVd-infected and control 'Odysso' and 'Tonami' apple saplings were examined to clarify the effects of ASSVd on apple tree growth and physiological characteristics as well as the leaf metabolome. The results indicated that leaf ASSVd contents increased significantly after grafting and remained high in the second year. Leaf size, tree height, stem diameter, branch length, and leaf photosynthetic efficiency decreased significantly in viroid-infected saplings. In response to the ASSVd infection, the chlorophyll a and b contents decreased significantly in 'Odysso', but were unchanged in 'Tonami'. Moreover, the N, P, K, Fe, Mn, and Ca contents decreased significantly in the leaves of viroid-infected 'Odysso' or 'Tonami'. Similarly, the CAT and POD contents decreased significantly in the viroid-infected saplings, but the SOD content increased in the viroid-infected 'Tonami' saplings. A total of 15 and 40 differentially abundant metabolites were respectively identified in the metabolome analyses of 'Odysso' and 'Tonami' leaves. Specifically, in the viroid-infected 'Odysso' and 'Tonami' samples, the L-2-aminobutyric acid, 6″-O-malonyldaidzin, and D-xylose contents increased, while the coumarin content decreased. These metabolites are related to the biosynthesis of isoflavonoids and phenylpropanoids as well as the metabolism of carbohydrates and amino acids. These results imply that ASSVd affects apple sapling growth by affecting physiological characteristics and metabolism of apple leaves. The study data may be useful for future investigations on the physiological mechanisms underlying apple tree responses to ASSVd.

A proposed framework to evaluate the quality and reliability of targeted metabolomics assays from the UK Consortium on Metabolic Phenotyping (MAP/UK)

Targeted metabolite assays that measure tens or hundreds of pre-selected metabolites, typically using liquid chromatography-mass spectrometry, are increasingly being developed and applied to metabolic phenotyping studies. These are used both as standalone phenotyping methods and for the validation of putative metabolic biomarkers obtained from untargeted metabolomics studies. However, there are no widely accepted standards in the scientific community for ensuring reliability of the development and validation of targeted metabolite assays (referred to here as 'targeted metabolomics'). Most current practices attempt to adopt, with modifications, the strict guidance provided by drug regulatory authorities for analytical methods designed largely for measuring drugs and other xenobiotic analytes. Here, the regulatory guidance provided by the European Medicines Agency, US Food and Drug Administration and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use are summarized. In this Perspective, we have adapted these guidelines and propose a less onerous 'tiered' approach to evaluate the reliability of a wide range of metabolomics analyses, addressing the need for community-accepted, harmonized guidelines for tiers other than full validation. This 'fit-for-purpose' tiered approach comprises four levels-discovery, screening, qualification and validation-and is discussed in the context of a range of targeted and untargeted metabolomics assays. Issues arising with targeted multiplexed metabolomics assays, and how these might be addressed, are considered. Furthermore, guidance is provided to assist the community with selecting the appropriate degree of reliability for a series of well-defined applications of metabolomics.

Plant-Derived Products with Therapeutic Potential against Gastrointestinal Bacteria

The rising burden of antimicrobial resistance and increasing infectious disease outbreaks, including the recent COVID-19 pandemic, has led to a growing demand for the development of natural products as a valuable source of leading medicinal compounds. There is a wide variety of active constituents found in plants, making them an excellent source of antimicrobial agents with therapeutic potential as alternatives or potentiators of antibiotics. The structural diversity of phytochemicals enables them to act through a variety of mechanisms, targeting multiple biochemical pathways, in contrast to traditional antimicrobials. Moreover, the bioactivity of the herbal extracts can be explained by various metabolites working in synergism, where hundreds to thousands of metabolites make up the extract. Although a vast amount of literature is available regarding the use of these herbal extracts against bacterial and viral infections, critical assessments of their quality are lacking. This review aims to explore the efficacy and antimicrobial effects of herbal extracts against clinically relevant gastrointestinal infections including pathogenic Escherichia coli, toxigenic Clostridioides difficile, Campylobacter and Salmonella species. The review will discuss research gaps and propose future approaches to the translational development of plant-derived products for drug discovery purposes for the treatment and prevention of gastrointestinal infectious diseases.

Buffalo milk and rumen fluid metabolome are significantly affected by green feed

The use of green feed for livestock breeding is an important strategy to encounter both the increasing demand for animal derived products and the perceptions of the consumers regarding animal welfare and sustainability. The aim of this study was to compare different feeding strategies in lactating water buffaloes by using a metabolomic approach. The study was carried out on 32 milking buffaloes that were randomly divided into two groups for a total period of 90 days (3 sampling times). DD Group (dry diet) received a standard total mixed ratio (TMR) characterized by dry forages and concentrates; ZG Group (zero grazing) fed an isoenergetic and isoproteic diet obtained using 30% of sorghum as green forage. Samples of milk and rumen fluid were analyzed by liquid chromatography-mass spectrometry (LC-MS) techniques. Data analyses revealed the presence of several differentially accumulated metabolites and among these, ten compounds were putatively identified in milk samples (i.e. L-carnitine, acetylcarnitine, propionylcarnitine, butyrylcarnitine, 2-methylbutyroylcarnitine, 2-hexenoylcarnitine, hexanoylcarnitine, glycerophosphocholine, δ-valerobetaine and γ-butyrobetaine) and four in rumen fluid (3-(2-hydroxyphenyl) propanoate, Indole-3-acrylic acid, oleamide (cis-9,10-octadecenoamide) and 20-carboxy-leukotriene B4). The modulation of these molecules in buffalo milk is significantly related to the green/dry based feeding and some the natural compound detected could be considered as health-promoting nutrients.

Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches

Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.

Untargeted metabolomics reveals the effect of rearing systems on bone quality parameters in chickens

The objective of this study was to investigate the effects of rearing systems on the bone quality parameters in chickens using a metabolomics strategy. A total of 419 male one-day-old chicks were randomly allocated to two groups, a floor rearing group (FRG, n = 173) and a cage rearing group (CRG, n = 246). At 6, 8, 10, and 12 weeks of age, all chickens were radiographed by a digital X-ray machine, and body weight was recorded. At 12 weeks of age, 12 birds were selected from each group to obtain tibia and femur, and bone quality parameters of bone mineral density (BMD), mineral content (BMC), breaking strength (BBS), stiffness, Young's modulus (YM), ash content, calcium content, and phosphorus content were determined. An untargeted metabolomics assay was performed to identify changes in the serum metabolic profile (n = 8 birds/group). The results showed that cage-reared chickens had wider tibiae and greater body weight compared with floor-reared chickens. There were no significant differences in BMC or BBS between the two groups (p > 0.05), but BMD, ash content, calcium content, and phosphorus content of the tibia and femur of FRG were significantly higher than those of CRG (p < 0.05). Greater stiffness and YM of the femur were also observed in birds raised in the FRG compared with those raised in the CRG (p < 0.05). Taken together, the results suggest that rearing systems affected bone quality parameters. Furthermore, 148 and 149 differential metabolites were identified in positive and negative ion modes by LC-MS/MS analysis, among which 257 metabolites were significantly correlated with 16 bone quality parameters, including leucine, myristoleic acid, glycocholic acid, and N-phenylacetamide. KEGG analysis indicated that 15 metabolic pathways, including six pathways of amino acid metabolism, two pathways of lipid metabolism, and two pathways of carbohydrate metabolism, were responsible for bone quality. Overall, the present study demonstrated the effect of rearing systems on bone quality parameters, and identified several metabolites and metabolic pathways associated with bone quality parameters.

Co-Localization of Resistance and Metabolic Quantitative Trait Loci on Carrot Genome Reveals Fungitoxic Terpenes and Related Candidate Genes Associated with the Resistance to Alternaria dauci

Alternaria leaf blight, caused by the fungus Alternaria dauci, is the most damaging foliar disease of carrot. Some carrot genotypes exhibit partial resistance to this pathogen and resistance Quantitative Trait Loci (rQTL) have been identified. Co-localization of metabolic QTL and rQTL identified camphene, α-pinene, α-bisabolene, β-cubebene, caryophyllene, germacrene D and α-humulene as terpenes potentially involved in carrot resistance against ALB. By combining genomic and transcriptomic analyses, we identified, under the co-localization regions, terpene-related genes which are differentially expressed between a resistant and a susceptible carrot genotype. These genes include five terpene synthases and twenty transcription factors. In addition, significant mycelial growth inhibition was observed in the presence of α-humulene and caryophyllene.

Biological effects of Thymol loaded chitosan nanoparticles (TCNPs) on bacterial plant pathogen Xanthomonas campestris pv. campestris

Engineered nanomaterials can provide eco-friendly alternatives for crop disease management. Chitosan based nanoparticles has shown beneficial applications in sustainable agricultural practices and effective healthcare. Previously we demonstrated that Thymol loaded chitosan nanoparticles (TCNPs) showed bactericidal activity against Xanthomonas campestris pv campestris (Xcc), a bacterium that causes black rot disease in brassica crops. Despite the progress in assessing the antibacterial action of TCNPs, the knowledge about the molecular response of Xcc when exposed to TCNPs is yet to be explored. In the present study, we combined physiological, spectroscopic and untargeted metabolomics studies to investigate the response mechanisms in Xcc induced by TCNPs. Cell proliferation and membrane potential assays of Xcc cells exposed to sub-lethal concentration of TCNPs showed that TCNPs affects the cell proliferation rate and damages the cell membrane altering the membrane potential. FTIR spectroscopy in conjunction with untargeted metabolite profiling using mass spectrometry of TCNPs treated Xcc cells revealed alterations in amino acids, lipids, nucleotides, fatty acids and antioxidant metabolites. Mass spectroscopy analysis revealed a 10-25% increase in nucleic acid, fatty acids and antioxidant metabolites and a 20% increase in lipid metabolites while a decrease of 10-20% in amino acids and carbohydrates was seen in in TCNP treated Xcc cells. Overall, our results demonstrate that the major metabolic perturbations induced by TCNPs in Xcc are associated with membrane damage and oxidative stress, thus providing information on the mechanism of TCNPs mediated cytotoxicity. This will aid towards the development of nano- based agrochemicals as an alternative to chemical pesticides in future.

EASY-FIA: A Readably Usable Standalone Tool for High-Resolution Mass Spectrometry Metabolomics Data Pre-Processing

Flow injection analysis coupled with high-resolution mass spectrometry (FIA-HRMS) is a fair trade-off between resolution and speed. However, free software available for data pre-processing is few, web-based, and often requires advanced user specialization. These tools rarely embedded blank and noise evaluation strategies, and direct feature annotation. We developed EASY-FIA, a free standalone application that can be employed for FIA-HRMS metabolomic data pre-processing by users with no bioinformatics/programming skills. We validated the tool's performance and applicability in two clinical metabolomics case studies. The main functions of our application are blank subtraction, alignment of the metabolites, and direct feature annotation by means of the Human Metabolome Database (HMDB) using a minimum number of mass spectrometry parameters. In a scenario where FIA-HRMS is increasingly recognized as a reliable strategy for fast metabolomics analysis, EASY-FIA could become a standardized and feasible tool easily usable by all scientists dealing with MS-based metabolomics. EASY-FIA was implemented in MATLAB with the App Designer tool and it is freely available for download.

Metabolomics insights into the potential of encapsulated essential oils as multifunctional food additives

Growing consumer concern about foodborne disease outbreaks and health risks associated with chemical additives has propelled the usage of essential oils (EOs) as novel food additives, but are limited by instability. In this regard, a series of EOs nano/micro-capsules have been widely used to enhance their stability and improve food quality. However, classical food quality assessment methods are insufficient to fully characterize the effects of encapsulated EOs on food properties, including physical, biochemical, organoleptic, and microbial changes. Recently, the rapid development of high-throughput sequencing is accelerating the application of metabolomics in food safety and quality analysis. This review seeks to present the most recent achievements in the application of non-targeted metabolomics to identify and quantify the overall metabolite profile associated with food quality, which can guide the development of emerging food preservation technologies. The scientific findings confirm that metabolomics opens up exciting prospects for biomarker screening in food preservation and contributes to an in-depth understanding of the mechanisms of action (MoA) of EOs. Future research should focus on constructing food quality assessment criteria based on multi-omics technologies, which will drive the standardization and commercialization of EOs for food industry applications.

Saliva metabolome alterations after acute stress

Major stress has systemic effects on the body that can have adverse consequences for physical and mental health. However, the molecular basis of these damaging effects remains incompletely understood. Here we use a longitudinal approach to characterise the acute systemic impact of major psychological stress in a pig model. We perform untargeted metabolomics on non-invasively obtained saliva samples from pigs before and 24 h after transfer to the novel physical and social environment of a slaughterhouse. The main molecular changes occurring include decreases in amino acids, B-vitamins, and amino acid-derived metabolites synthesized in B-vitamin-dependent reactions, as well as yet-unidentified metabolite features. Decreased levels of several of the identified metabolites are implicated in the pathology of human psychological disorders and neurodegenerative disease, suggesting a possible neuroprotective function. Our results provide a fingerprint of the acute effect of psychological stress on the metabolome and suggest candidate biomarkers with potential roles in stress-related disorders.

A Metabolomic Study of the Analgesic Effect of Lappaconitine Hydrobromide (LAH) on Inflammatory Pain

Lappaconitine (LA) is a C-18 diterpene alkaloid isolated from Aconitum sinomontanum Nakai that has been shown to relieve mild to moderate discomfort. Various researchers have tried to explain the underlying mechanism of LA's effects on chronic pain. This article uses metabolomics technology to investigate the metabolite alterations in the dorsal root ganglion (DRG) when lappaconitine hydrobromide (LAH) was injected in an inflammatory pain model, to explain the molecular mechanism of its analgesia from a metabolomics perspective. The pain model used in this study was a complete Freund's adjuvant (CFA)-induced inflammatory pain model in rats. There were two treatment groups receiving different dosages of LAH (4 mg/kg LAH and 8 mg/kg LAH). The analgesic mechanism of LAH was investigated with an analgesic behavioral test, tissue sections, and metabolomics. The results of the analgesic behavioral experiment showed that both 4 mg/kg LAH and 8 mg/kg LAH could significantly improve the paw withdrawal latency (PWL) of rats. The tissue section results showed that LAH could reduce the inflammatory response and enlargement of the paw and ankle of rats and that there was no significant difference in the tissue sections of the DRG. The metabolomics results showed that retinol metabolism and glycerophospholipid metabolism in the CFA-induced inflammatory pain model were significantly affected and may exacerbate the inflammatory reactions and initiate persistent pain; in addition, the linoleic acid metabolism, arachidonic acid metabolism, and alanine, aspartate, and glutamate metabolism were also slightly affected. Among them, the alpha-linolenic acid metabolism was up-regulated after LAH treatment, while the retinol metabolism was down-regulated. These results suggest that LAH could effectively reduce inflammatory pain and might achieve this by regulating the lipid metabolism in the rat DRG.

Effects of polyethylene and polylactic acid microplastics on plant growth and bacterial community in the soil

Microplastics (MPs), especially biodegradable MPs (BMPs) have attracted increasing attention in recent years. However, the effects of MPs with different biodegradability on the soil-plant systems are not well explored. In this study, the effects of polyethylene MPs (PEMPs) and polylactic acid MPs (PLAMPs) on physio-biochemical performance and metabolomic profile of soybean (Glycine max), as well as the bacterial communities in soil were investigated. Our results showed that PEMPs had no noticeable toxicity on the plant growth, while 0.1% PLAMPs significantly decreased the root length by 27.53% when compared with the control. The peroxidase (POD) activity was reduced and catalase (CAT) activity was increased by MPs in plant leaves. The metabolomics study suggested that the significantly affected metabolic pathway is amino acid metabolism. Additionally, Shannon and Simpson indices of rhizosphere soil were changed only under 0.1% PLAMPs. The key bacteria involved in the dinitrogen fixation were also altered. This study provides a novel insight into the potential effects of MPs with different biodegradability on soil-plant systems and highlights that BMPs might have stronger negative effects for terrestrial ecosystem, which needs to be further explored in future research.

IL-6 of follicular fluid and outcome of in vitro fertilization

The quality of an oocyte is influenced by its microenvironment, which includes cumulus cells and follicular fluid, as well as cells of the immune system and their products. The ovarian interleukins, which are secreted by the granulosa cells and other immune cells within the ovaries and follicles, regulate various functions between the cells. IL-6 is a cytokine that is present in the follicular fluid and may affect the quality of oocytes. There are some inconsistencies in the literature regarding the concentration of interleukin 6 in the follicular fluid. The main objective of this study was to examine whether the concentration of interleukin 6 in the follicular fluid affects the outcome of IVF. This study involved 83 patients who underwent IVF. Follicular fluid was used as the biological material for the analysis. Examination of the obtained follicular fluid and collection of oocytes under a stereomicroscope was performed in the embryological laboratory. The concentration of IL-6 in the follicular fluid was analyzed. IVF and ICSI methods were used as the fertilization methods. Pregnancy was confirmed by the positive serum β-hCG level. The software package SPSS 20 was used for statistical data processing. Analysis of the follicular fluid samples showed a correlation between the concentration of IL-6 in the follicular fluid and the outcome of IVF. The concentration of IL-6 in the follicular fluid was higher in patients with confirmed pregnancy (9.55 ± 7.47 ng/ml). Based on our results, we conclude that the concentration of IL-6 affects the outcome of IVF. If the range of IL-6 concentration is between 3,67 ng/ml and 10 ng/ml, we can expect good IVF outcome with vital pregnancy.

Oralbiotica/Oralbiotics: The Impact of Oral Microbiota on Dental Health and Demineralization: A Systematic Review of the Literature

The oral microbiota plays a vital role in the human microbiome and oral health. Imbalances between microbes and their hosts can lead to oral and systemic disorders such as diabetes or cardiovascular disease. The purpose of this review is to investigate the literature evidence of oral microbiota dysbiosis on oral health and discuss current knowledge and emerging mechanisms governing oral polymicrobial synergy and dysbiosis; both have enhanced our understanding of pathogenic mechanisms and aided the design of innovative therapeutic approaches as ORALBIOTICA for oral diseases such as demineralization. PubMed, Web of Science, Google Scholar, Scopus, Cochrane Library, EMBEDDED, Dentistry & Oral Sciences Source via EBSCO, APA PsycINFO, APA PsyArticles, and DRUGS@FDA were searched for publications that matched our topic from January 2017 to 22 April 2022, with an English language constraint using the following Boolean keywords: ("microbio*" and "demineralization*") AND ("oral microbiota" and "demineralization"). Twenty-two studies were included for qualitative analysis. As seen by the studies included in this review, the balance of the microbiota is unstable and influenced by oral hygiene, the presence of orthodontic devices in the oral cavity and poor eating habits that can modify its composition and behavior in both positive and negative ways, increasing the development of demineralization, caries processes, and periodontal disease. Under conditions of dysbiosis, favored by an acidic environment, the reproduction of specific bacterial strains increases, favoring cariogenic ones such as Bifidobacterium dentium, Bifidobacterium longum, and S. mutans, than S. salivarius and A. viscosus, and increasing of Firmicutes strains to the disadvantage of Bacteroidetes. Microbial balance can be restored by using probiotics and prebiotics to manage and treat oral diseases, as evidenced by mouthwashes or dietary modifications that can influence microbiota balance and prevent or slow disease progression.

The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment

Drug-induced liver injury (DILI) is one of the most frequent adverse clinical reactions and a relevant cause of morbidity and mortality. Hepatotoxicity is among the major reasons for drug withdrawal during post-market and late development stages, representing a major concern to the pharmaceutical industry. The current biochemical parameters for the detection of DILI are based on enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP)) and bilirubin serum levels that are not specific of DILI and therefore there is an increasing interest on novel, specific, DILI biomarkers discovery. Metabolomics has emerged as a tool with a great potential for biomarker discovery, especially in disease diagnosis, and assessment of drug toxicity or efficacy. This review summarizes the multistep approaches in DILI biomarker research and discovery based on metabolomics and the principal outcomes from the research performed in this field. For that purpose, we have reviewed the recent scientific literature from PubMed, Web of Science, EMBASE, and PubTator using the terms “metabolomics”, “DILI”, and “humans”. Despite the undoubted contribution of metabolomics to our understanding of the underlying mechanisms of DILI and the identification of promising novel metabolite biomarkers, there are still some inconsistencies and limitations that hinder the translation of these research findings into general clinical practice, probably due to the variability of the methods used as well to the different mechanisms elicited by the DILI causing agent.