Untargeted Metabolomics Approach Research Articles

Production of Polyphenolic Natural Products by Bract-Derived Tissue Cultures of Three Medicinal Tilia spp.: A Comparative Untargeted Metabolomics Study

Medicinal plant tissue cultures are potential sources of bioactive compounds. In this study, we report the chemical characterization of the callus cultures of three medicinal Tilia spp. (Tilia cordata, Tilia vulgaris and Tilia tomentosa), along with the comparison to bracts and flowers of the same species. Our aim was to show that calli of Tilia spp. are good alternatives to the calli of T. americana for the production of polyphenols and are better sources of a subset of polyphenolic metabolites, compared to the original organs. Calli were initiated from young bracts and grown on woody plant medium containing 1 mg L−1 2,4-D and 0.1 mg L−1 BAP. For chemical characterization, a quality-controlled untargeted metabolomics approach and the quantification of several bioactive compounds was performed with the use of LC-ESI-MS/MS. While bracts and flowers contained flavonoid glycosides (astragalin, isoquercitrin) as major polyphenols, calli of all species contained catechins, coumarins (fraxin, esculin and scopoletin) and flavane aglyca. T. tomentosa calli contained 5397 µg g DW−1 catechin, 201 µg g DW−1 esculin, 218 µg g DW−1 taxifolin and 273 µg g DW−1 eriodictyol, while calli from other species contained lower amounts. T. cordata and T. tomentosa flowers were rich in isoquercitrin, containing 8134 and 6385 µg g DW−1, respectively. The currently tested species contained many of the bioactive metabolites described from T. americana. The production of catechin was shown to be comparable to the most efficient tissue cultures reported. Flowers and bracts contained flavonoid glycosides, including tiliroside, resembling bioactive fractions of T. americana. In addition, untargeted metabolomics has shown fingerprint-like differences among species, highlighting possible chemotaxonomic and quality control applications, especially for bracts.

Germination Increases the Glucomoringin Content in Moringa Sprouts via Transforming Tyrosine.

Moringa seeds are an excellent dietary source of phytochemicals (i.e., glucosinolates, GSLs; isothiocyanates, ITCs) with health-beneficial effects. Although numerous studies have been conducted on moringa seeds, the effect of germination on the regulation of GSLs remains scarcely explored. The present study investigated the dynamic changes of GSLs in moringa seeds during germination (at 25, 30, and 35 °C for 6 days in the dark) through an untargeted metabolomics approach and compared the antioxidant capacity of ungerminated and germinated moringa seeds. Our results showed that germination significantly increased the total GSL content from 150 (day 0) to 323 μmol/g (35 °C, day 6) on a dry weight (DW) basis, especially glucomoringin (GMG), the unique glucosinolate in moringa seeds, which was significantly upregulated from 61 (day 0) to 149 μmol/g DW (35 °C, day 4). The upregulation of GMG corresponded to the metabolism of tyrosine, which might be the initial precursor for the formation of GMG. In addition, germination enhanced the total ITC content from 85 (day 0) to 239 μmol SE/g DW (35 °C, day 6), indicating that germination may have also increased the activity of myrosinase. Furthermore, germination remarkably increased the total phenolic content (109-507 mg GAE/100 g DW) and antioxidant capacity of moringa seeds. Our findings suggest that moringa sprouts could be promoted as a novel food and/or ingredient rich in GMG.

Insight into natural ageing of historic baltic amber objects by untargeted metabolomics approach

Cherished amber relics have undergone long-period burial environments carrying several ageing deterioration characteristics, such as crazing, discolouration, and decreased hardness, which makes amber artefacts fragile. Ageing is inevitable for amber exposed to air, emphasising the need for a suitable preservation environment based on the ageing mechanism. However, related research, specifically on the transformed compositions and structures of archaeological amber, has been limited due to complexities in deciphering the intricate components. In this research, attenuated total reflection Fourier transform infrared (ATR-FTIR), X-ray fluorescence (XRF), inductively coupled plasma optical emission spectroscopy (ICP-OES) and pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) were applied on geological and archaeological Baltic amber to find the ageing pathways. An untargeted metabolomics analysis developed for the linear modelling of molecular features data was utilised in combination with Py-GC/MS results, and statistically significant variations provided ten increased and ten decreased ageing markers. We propose an ageing mechanism for the succinite molecular structure, which involves oxidation of the polylabdanoid and hydrolysis of the esterification cross-link structure between succinic acid and labdanoid. Simultaneously, monoterpenes were released from the amber structure. Our untargeted Py-GC/MS metabolomics approach offers a groundbreaking and more systematic method for investigating the ageing mechanism of multi-component organic polymers in archaeological artefacts.

Applying GC-MS based serum metabolomic profiling to characterize two traditional Chinese medicine subtypes of diabetic foot gangrene.

Traditional Chinese medicine (TCM) has a long history and particular advantages in the diagnosis and treatment of diabetic foot gangrene (DFG). Patients with DFG are mainly divided into two subtypes, tendon lesion with edema (GT) and ischemic lesion without edema (GI), which are suitable for different medical strategies. Metabolomics has special significance in unravelling the complexities of multifactorial and multisystemic disorders. This study acquired the serum metabolomic profiles of two traditional Chinese medicine subtypes of DFG to explore potential molecular evidence for subtype characterization, which may contribute to the personalized treatment of DFG. A total of 70 participants were recruited, including 20 with DM and 50 with DFG (20 with GI and 30 with GT). Conventional gas chromatography-mass spectrometry (GC-MS) followed by orthogonal partial least-squares discriminant analysis (OPLS-DA) were used as untargeted metabolomics approaches to explore the serum metabolomic profiles. Kyoto encyclopedia of genes and genomes (KEGG) and MetaboAnalyst were used to identify the related metabolic pathways. Compared with DM patients, the levels of 14 metabolites were altered in the DFG group, which were also belonged to the differential metabolites of GI (13) and GT (7) subtypes, respectively. Among these, urea, α-D-mannose, cadaverine, glutamine, L-asparagine, D-gluconic acid, and indole could be regarded as specific potential metabolic markers for GI, as well as L-leucine for GT. In the GI subtype, D-gluconic acid and L-asparagine are positively correlated with activated partial thromboplastin time (APTT) and fibrinogen (FIB). In the GT subtype, L-leucine is positively correlated with the inflammatory marker C-reactive protein (CRP). Arginine and proline metabolism, glycine, serine and threonine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis are the most important metabolic pathways associated with GI. The main metabolic pathways related to GT include pyrimidine metabolism, glutathione metabolism, biosynthesis of valine, leucine, and isoleucine, as well as valine, serine, and isoleucine with metabolites. The results of this study indicate that patients with different DFG subtypes have distinct metabolic profiles, which reflect the pathological characteristics of each subtype respectively. These findings will help us explore therapeutic targets for DFG and develop precise treatment strategies.

Urinary metabolomic profiling of a cohort of Colombian patients with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune and multisystem disease with a high public health impact. Lupus nephritis (LN), commonly known as renal involvement in SLE, is associated with a poorer prognosis and increased rates of morbidity and mortality in patients with SLE. Identifying new urinary biomarkers that can be used for LN prognosis or diagnosis is essential and is part of current active research. In this study, we applied an untargeted metabolomics approach involving liquid and gas chromatography coupled with mass spectrometry to urine samples collected from 17 individuals with SLE and no kidney damage, 23 individuals with LN, and 10 clinically healthy controls (HCs) to identify differential metabolic profiles for SLE and LN. The data analysis revealed a differentially abundant metabolite expression profile for each study group, and those metabolites may act as potential differential biomarkers of SLE and LN. The differential metabolic pathways found between the LN and SLE patients with no kidney involvement included primary bile acid biosynthesis, branched-chain amino acid synthesis and degradation, pantothenate and coenzyme A biosynthesis, lysine degradation, and tryptophan metabolism. Receiver operating characteristic curve analysis revealed that monopalmitin, glycolic acid, and glutamic acid allowed for the differentiation of individuals with SLE and no kidney involvement and individuals with LN considering high confidence levels. While the results offer promise, it is important to recognize the significant influence of medications and other external factors on metabolomics studies. This impact has the potential to obscure differences in metabolic profiles, presenting a considerable challenge in the identification of disease biomarkers. Therefore, experimental validation should be conducted with a larger sample size to explore the diagnostic potential of the metabolites found as well as to examine how treatment and disease activity influence the identified chemical compounds. This will be crucial for refining the accuracy and effectiveness of using urine metabolomics for diagnosing and monitoring lupus and lupus nephritis.

Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach.

In an effort to enhance reproductive management and reduce non-productive periods in swine breeding, this study presents a novel, non-invasive metabolomics approach for the identification of early pregnancy biomarkers in sows. Utilizing an untargeted metabolomics approach with mass spectrometry analysis, we examined saliva samples from pregnant (n = 6) and non-pregnant control sows (n = 6, artificially inseminated with non-viable sperm). Our analysis revealed 286 differentially expressed metabolites, with 152 being up-regulated and 134 down-regulated in the pregnant group. Among these, three metabolites, namely Hyodeoxycholic acid, 2'-deoxyguanosine, and Thymidine, emerged as potential early pregnancy biomarkers. These biomarkers were further evaluated using targeted LC-MS/MS quantification and qualification, accompanied by ROC curve analysis. The study confirmed Hyodeoxycholic acid and 2'-deoxyguanosine as promising biomarkers for early pregnancy detection, offering potential for future implementation in swine production environments. This research establishes a robust theoretical foundation for the development of innovative molecular diagnostic techniques and explores new avenues for molecular genetic breeding and non-invasive diagnostics, ultimately enhancing fertility and productivity in sow herds.

Mechano-induced cell metabolism disrupts the oxidative stress homeostasis of SAOS-2 osteosarcoma cells.

There has been an increasing focus on cancer mechanobiology, determining the underlying-induced changes to unlock new avenues in the modulation of cell malignancy. Our study used LC-MS untargeted metabolomic approaches and real-time polymerase chain reaction (PCR) to characterize the molecular changes induced by a specific moderate uniaxial stretch regimen (i.e., 24h-1Hz, cyclic stretch 0,5% elongation) on SAOS-2 osteosarcoma cells. Differential metabolic pathway analysis revealed that the mechanical stimulation induces a downregulation of both glycolysis and the tricarboxylic acid (TCA) cycle. At the same time, the amino acid metabolism was found to be dysregulated, with the mechanical stimulation enhancing glutaminolysis and reducing the methionine cycle. Our findings showed that cell metabolism and oxidative defense are tightly intertwined in mechanically stimulated cells. On the one hand, the mechano-induced disruption of the energy cell metabolism was found correlated with an antioxidant glutathione (GSH) depletion and an accumulation of reactive oxygen species (ROS). On the other hand, we showed that a moderate stretch regimen could disrupt the cytoprotective gene transcription by altering the expression levels of manganese superoxide dismutase (SOD1), Sirtuin 1 (SIRT1), and NF-E2-related factor 2 (Nrf2) genes. Interestingly, the cyclic applied strain could induce a cytotoxic sensitization (to the doxorubicin-induced cell death), suggesting that mechanical signals are integral regulators of cell cytoprotection. Hence, focusing on the mechanosensitive system as a therapeutic approach could potentially result in more effective treatments for osteosarcoma in the future.

Discovery of vitexin as a novel α‐glucosidase inhibitors in mulberry (Morus alba L.) by untargeted metabolomics combined with molecular docking: A comprehensive study from mechanism to synergy effects

AbstractMulberry (Morus alba L.) leaf can effectively inhibit the digestion of starchy foods, and α‐glucosidase (AG) is its main target. This study employed an untargeted metabolomics approach combined with molecular docking to identify AG inhibitors. Subsequently, inhibition kinetics, fluorescence spectroscopy, and interaction force analysis were utilized to investigate the inhibitory mechanism. Results indicated that vitexin exhibited significant reversible inhibition of AG through competitive inhibition, with an IC50 value of 105.50 ± 1.30 μg/mL. Molecular docking revealed hydrogen bonding as the main interaction force between vitexin and AG, and quenching mechanism analysis showed that they underwent static quenching driven by entropy. The results of the combined experiment showed that 1‐deoxynojirimycin (DNJ), a known bioactive component in mulberry, has a synergistic effect of inhibiting AG activity with vitexin. This study elucidates the potential mechanism of vitexin in inhibiting AG activity and provides theoretical evidence for utilizing vitexin‐DNJ complexes as functional components of AG inhibitors.

From the grapevine to the glass: A wine metabolomics tale by FT-ICR-MS.

Wine is one of the most consumed beverages around the world. Its unique characteristics arise from numerous processes, from the selection of grapevine varieties and grapes, the effect of the terroir and geographical origin, through the biochemical process of fermentation by microorganisms, until its aging. All molecules found in wine define its chemical fingerprint and can be used to tell the story of its origin, production, authenticity and quality. Wine's chemical composition can be characterized using an untargeted metabolomics approach based on extreme resolution mass spectrometry. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is currently the most powerful analytical technique to analyse such complex sample, providing the most comprehensive analysis of the chemical fingerprint of wine.

Plasma and milk metabolomics profiles in dairy cows with subclinical and clinical ketosis

Ketosis, a commonly observed energy metabolism disorder in dairy cows during the peripartal period, is distinguished by increased concentrations of β-hydroxybutyrate (BHB) in blood. This condition has a negative impact on milk production and quality, causing financial losses. An untargeted metabolomics approach was performed on plasma samples from cows between 5 and 7 DIM diagnosed as controls (CON, BHB <1.2 mM, n = 30), subclinically ketotic (SCK, 1.2 < BHB <3.0 mM, n = 30), or clinically ketotic (CK, BHB >3.0 mM, n = 30). Cows were selected from a commercial farm of 214 Holstein cows (average 305-d yield in the previous lactation of 35.42 ± 7.23 kg/d; parity, 2.41 ± 1.12; body condition score, 3.1 ± 0.45). All plasma and milk samples (n = 90) were subjected to Liquid Chromatography-Mass Spectrometry (LC-MS)-based metabolomic analysis. Statistical analyses was performed using the Graph Pad Prism 8.0, MetaboAnalyst 4.0 and R packages (version 4.1.3). Compared with the CON group, both SCK and CK groups had greater milk fat, freezing point, and fat-to-protein ratio and lower milk protein, lactose, solids-nonfat, and milk density. Within 21 d after calving, compared with CON, the SCK group experienced a reduction of 2.65 kg/d in milk yield, while the CK group experienced a decrease of 7.7 kg/d. Untargeted metabolomics analysis facilitated the annotation of a total of 5,259 and 8,423 metabolites in plasma and milk. Differentially affected metabolites were screened in CON vs. SCK, CON vs. CK, and SCK vs. CK (unpaired t-test, False discovery rate <0.05; and absolute value of log(2)-fold change >1.5). A total of 1,544 and 1,888 differentially affected metabolites were detected in plasma and milk. In plasma, glycerophospholipid metabolism, pyrimidine metabolism, tryptophan metabolism, sphingolipid metabolism, amino sugar and nucleotide sugar metabolism, phenylalanine metabolism, steroid hormone biosynthesis were identified as significant pathways. Weighted gene co-expression network analysis (WGCNA) indicated that tryptophan metabolism is a key pathway associated with the occurrence and development of ketosis. Increases in 5-Hydroxytryptophan and decreases in kynurenine and 3-indoleacetic acid in SCK and CK were suggestive of an impact at the gut level. The decrease of most glycerophospholipids indicated that ketosis is associated with disordered lipid metabolism. For milk, pyrimidine metabolism, purine metabolism, pantothenate and CoA biosynthesis, amino sugar and nucleotide sugar metabolism, nicotinate and nicotinamide metabolism, sphingolipid metabolism, fatty acid degradation were identified as significant pathways. The WGCNA indicated that purine and pyrimidine metabolism in plasma was highly correlated with milk yield during the peripartal period. Alterations in purine and pyrimidine metabolism characterized ketosis, with lower levels of these metabolites in both milk and blood underscoring reduced efficiency in nitrogen metabolism. Our results may help to establish a foundation for future research investigating mechanisms responsible for the occurrence and development of ketosis in peripartal cows.

Metabolomics analysis of CEF cells infected with avian leukosis virus subgroup J based on UHPLC-QE-MS

Avian leukosis virus subgroup J (ALV-J) is a retrovirus that can cause immunosuppression and tumors in chicken. However, relative pathogenesis is still not clear. At present, metabolomics has shown great potential in the screening of tumor metabolic markers, prognostic evaluation, and drug target design. In this study, we utilize an untargeted metabolomics approach based on ultrahigh-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS) to analyze the metabolic changes in chicken embryo fibroblast (CEF) cells infected by ALV-J. We found that ALV-J infection significantly altered a wealth of metabolites compared with control group. Additionally, most of the differentially expressed metabolites belonged to lipid metabolism, purine nucleotide metabolism and amino acid metabolism. Among them, the proportion of lipid metabolites account for the highest proportion (around 31%). Results suggest that these changes may be conductive to the formation of virion, thereby promoting the replication of ALV-J. These data provided metabolic evidence and potential biomarkers for the cellular metabolic changes induced by ALV-J, and provided important insight for further understanding the replication needs and pathogenesis of ALV-J.

A Targeted and an Untargeted Metabolomics Approach to Study the Phytochemicals of Tomato Cultivars Grown Under Different Salinity Conditions.

In this study, we evaluated the effect of increasing the salinity of irrigation water on the metabolic content and profiles of two tomato cultivars ('Jaune Flamme' (JF) and 'Red Pear' (RP)) using targeted and untargeted metabolomics approaches. Irrigation of tomato plants was performed with four different salt concentrations provided by chloride (treatment 1) and sulfate (treatment 2) salts. Targeted analysis of the methanolic extract resulted in the identification of nine major polyphenols. Among them, chlorogenic acid, rutin, and naringenin were the prominent compounds in both cultivars. In addition, the quantification of 18 free amino acids from both tomato cultivars showed that different salinity treatments significantly enhanced the levels of glutamine, glutamic acid, and γ-aminobutyric acid (GABA). Using the untargeted metabolomic approach, we identified 129 putative metabolites encompassing a diverse array of phytochemicals including polyphenols, organic acids, lipids, sugars, and amino acids. Principal component analysis (PCA) of mass spectral data acquired under positive and negative ionization modes showed a clear separation between the two cultivars. However, only positive ionization showed separation among different salinity treatments. Unsupervised and supervised learning algorithms were applied to mine the generated data and to pinpoint metabolites different from the two cultivars. These findings suggest that different salinity conditions significantly influenced the accumulation of phytochemicals in tomato cultivars. This study will help tomato breeding programs to develop value-added tomato cultivars under varying environmental conditions.

An Untargeted Metabolomic Analysis of Lacticaseibacillus (L.) rhamnosus, Lactobacillus (L.) acidophilus, Lactiplantibacillus (L.) plantarum and Limosilactobacillus (L.) reuteri Reveals an Upregulated Production of Inosine from L. rhamnosus.

Lactic acid bacteria are considered an inexhaustible source of bioactive compounds; indeed, products from their metabolism are known to have immunomodulatory and anti-inflammatory activity. Recently, we demonstrated that Cell-Free Supernatants (CFS) obtained from Lactobacillus (L.) acidophilus, Lactiplantibacillus (L.) plantarum, Lacticaseibacillus (L.) rhamnosus, and Limosilactobacillus (L.) reuteri can impair Candida pathogenic potential in an in vitro model of epithelial vaginal infection. This effect could be ascribed to a direct effect of living lactic acid bacteria on Candida virulence and to the production of metabolites that are able to impair fungal virulence. In the present work, stemming from these data, we deepened our knowledge of CFS from these four lactic acid bacteria by performing a metabolomic analysis to better characterize their composition. By using an untargeted metabolomic approach, we detected consistent differences in the metabolites produced by these four different lactic acid bacteria. Interestingly, L. rhamnosus and L. acidophilus showed the most peculiar metabolic profiles. Specifically, after a hierarchical clustering analysis, L. rhamnosus and L. acidophilus showed specific areas of significantly overexpressed metabolites that strongly differed from the same areas in other lactic acid bacteria. From the overexpressed compounds in these areas, inosine from L. rhamnosus returned with the best identification profile. This molecule has been described as having antioxidant, anti-inflammatory, anti-infective, and neuroprotective properties. The biological significance of its overproduction by L. rhamnosus might be important in its probiotic and/or postbiotic activity.

UHPLC-MS-based untargeted metabolomic strategy to reveal the metabolic differences between cisplatin first- and second-generation apoptotic bodies from HK-2 cells

During the process of programmed cell death (apoptosis), the disassembly of apoptotic cells gives rise to apoptotic bodies (ABs) which play an important role in the pathogenesis of different diseases. ABs from renal human proximal tubular cells HK-2 on naïve cells was not always the same: ABs directly generated after exposure of human proximal tubular epithelial HK-2 cells to chemotherapeutic agent cisplatin (1st generation ABs) triggered apoptosis and inhibited cell proliferation, whereas ABs induced by 1st generation ABs (2nd generation ABs) enhanced HK-2 cell proliferation. To shed light on the mechanisms involved in these disparate ABs’ effects, a study of the changes in the metabolome of 1st and 2nd generation ABs produced by HK-2 cells in the cisplatin setting was performed by a reversed-phase ultra-high-performance liquid chromatography-mass spectrometry (RP-UHPLC-MS) untargeted metabolomic approach. Thus, ABs fluid and extracellular fluid from 1st and 2nd generation ABs were analyzed to obtain as much information as possible of the metabolites of these extracellular vesicles. Principal components analysis and partial least square discriminant analysis were conducted to find the statistically significant differences between both groups. A good clustering of each group was observed and variable importance in the projection values were selected to choose the molecular features which were identified according to the Metabolomics Standard Initiative (MSI) guidelines. Finally, the biological relevance of the achieved results was discussed.

Abstract 4765: Tumor, serum and plasma metabolome in patients with high-grade bladder cancer

Abstract Introduction: Bladder cancer (BlCa) ranks as the sixth most prevalent cancer in the world. A number of urine based BlCa detection tests have recently been approved for clinical use, including the NMP22 tests and the bladder tumor antigen (BTA) tests for both detection and monitoring of patients with known bladder cancer. The FDA have approved them both for surveillance in BlCa only in conjunction with cystoscopy. Unfortunately, the sensitivity and specificity of these tests are poor, and cannot distinguish between aggressive and non-aggressive tumors. This project aims to identify alternate markers that can overcome these drawbacks. Methods: We characterized the global metabolome of 47 bladder tumors retrieved by radical cystectomy (RC) or TURBT, including 14 specimens with matching plasma and serum samples. All specimens were subjected to untargeted metabolomic approaches with gas chromatography- time-of-flight mass spectrometry (GC-TOF MS) to profile primary metabolites, hydrophilic interaction liquid chromatography MS (HILIC-QTOF MS) to profile biogenic amines, and liquid chromatography charged surface hybrid MS (LC-CSH-QTOF MS) to characterize complex lipids. Differentially expressed metabolites were analyzed with respect to grade, stage, metastases, and the use of neoadjuvant chemotherapy. For selected metabolites, area under the ROC curve (AUC) is calculated as % sensitivity vs. 100% specificity. Expression of highly discriminatory metabolites were then validated in the plasma and serum samples to determine which forum would provide greater specificity. Results: We first assembled a discovery cohort of 33 patients who did not have matching blood specimen for primary metabolites, biogenic amines and complex lipids. Comparison of high vs low grade tumors yielded two lipids, a sphingomyelin (SM (d38) and a phosphatidylcholine PC(p-38), that were significantly different (adjusted p-value&amp;lt;0.05, log2fold change&amp;gt;2.5). These results were validated in the 14-sample cohort with matching plasma and serum of which the latter showed significant correlation between tumor and plasma (Spearman R=0.872, adj p=0.03). Conclusions: Our results indicate that certain sphingomyelins and phosphatidylcholines may be useful as plasma markers of high grade BlCa. Further analyses are required to evaluate whether these markers are more discriminatory compared to existing urinary markers. Citation Format: Maria-Malvina Tsamouri, Akshaya Karthikeyan, Christopher A. Lucchesi, Blythe P. Durbin-Johnson, Marc A. Dall'Era, Paramita M. Ghosh. Tumor, serum and plasma metabolome in patients with high-grade bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4765.

Multistrain Probiotics Alleviate Diarrhea by Modulating Microbiome-Derived Metabolites and Serotonin Pathway.

Diarrhea, a common gastrointestinal symptom in health problems, is highly associated with gut dysbiosis. The purpose of this study is to demonstrate the effect of multistrain probiotics (Sensi-Biome) on diarrhea from the perspective of the microbiome-neuron axis. Sensi-Biome (Lactiplantibacillus plantarum, Bifidobacterium animalis subsp. lactis, Lactobacillus acidophilus, Streptococcus thermophilus, Bifidobacterium bifidum, and Lactococcus lactis) was administered in a 4% acetic acid-induced diarrhea rat model at concentrations of 1 × 108 (G1), 1 × 109 (G2), and 1 × 1010CFU/0.5mL (G3). Diarrhea-related parameters, inflammation-related cytokines, and stool microbiota analysis by 16S rRNA were evaluated. A targeted and untargeted metabolomics approach was used to analyze the cecum samples using liquid chromatography and orbitrap mass spectrometry. The stool moisture content (p < 0.001), intestinal movement rate (p < 0.05), and pH (p < 0.05) were significantly recovered in G3. Serotonin levels were decreased in the multistrain probiotics groups. The inflammatory cytokines, serotonin, and tryptophan hydroxylase expression were improved in the Sensi-Biome groups. At the phylum level, Sensi-Biome showed the highest relative abundance of Firmicutes. Short-chain fatty acids including butyrate, iso-butyrate, propionate, and iso-valeric acid were significantly modified in the Sensi-Biome groups. Equol and oleamide were significantly improved in the multistrain probiotics groups. In conclusion, Sensi-Biome effectively controls diarrhea by modulating metabolites and the serotonin pathway.

Comparisons of different extraction methods and solvents for saliva samples.

Changes in the categories and concentrations of salivary metabolites may be closely related to oral, intestinal or systemic diseases. To study salivary metabolites, the first analytical step is to extract them from saliva samples as much as possible, while reducing interferences to a minimum. Frequently used extraction methods are protein precipitation (PPT), liquid-liquid extraction (LLE) and solid-phase extraction (SPE), with various organic solvents. The types and quantities of metabolites extracted with different methods may vary greatly, but few studies have systematically evaluated them. This study aimed to select the most suitable methods and solvents for the extraction of saliva according to different analytical targets. An untargeted metabolomics approach based on liquid chromatography-mass spectrometry was applied to obtain the raw data. The numbers of metabolites, repeatability of the data and intensities of mass spectrometry signals were used as evaluation criteria. PPT resulted in the highest coverage. Among the PPT solvents, acetonitrile displayed the best repeatability and the highest coverage, while acetone resulted in the best signal intensities for the extracted compounds. LLE with the mixture of chloroform and methanol was the most suitable for the extraction of small hydrophobic compounds. PPT with acetonitrile or acetone was recommended for untargeted analysis, while LLE with the mixture of chloroform and methanol was recommended for small hydrophobic compounds.

A GC-MS-based untargeted metabolomics approach for comprehensive metabolic profiling of mycophenolate mofetil-induced toxicity in mice.

Background: Mycophenolate mofetil (MMF), the morpholinoethyl ester of mycophenolic acid, is widely used for maintenance immunosuppression in transplantation. The gastrointestinal toxicity of MMF has been widely uncovered. However, the comprehensive metabolic analysis of MMF-induced toxicity is lacking. This study is aimed to ascertain the metabolic changes after MMF administration in mice. Methods: A total of 700mg MMF was dissolved in 7mL dimethyl sulfoxide (DMSO), and then 0.5mL of mixture was diluted with 4.5mL of saline (100mg/kg). Mice in the treatment group (n = 9) were given MMF (0.1mL/10g) each day via intraperitoneal injection lasting for 2weeks, while those in the control group (n = 9) received the same amount of blank solvent (DMSO: saline = 1:9). Gas chromatography-mass spectrometry was utilized to identify the metabolic profiling in serum samples and multiple organ tissues of mice. The potential metabolites were identified using orthogonal partial least squares discrimination analysis. Meanwhile, we used the MetaboAnalyst 5.0 (http://www.metaboanalyst.ca) and Kyoto Encyclopedia of Genes and Genomes database (http://www.kegg.jp) to depict the metabolic pathways. The percentages of lymphocytes in spleens were assessed by multiparameter flow cytometry analysis. Results: Compared to the control group, we observed that MMF treatment induced differential expression of metabolites in the intestine, hippocampus, lung, liver, kidney, heart, serum, and cortex tissues. Subsequently, we demonstrated that multiple amino acids metabolism and fatty acids biosynthesis were disrupted following MMF treatment. Additionally, MMF challenge dramatically increased CD4+ T cell percentages but had no significant influences on other types of lymphocytes. Conclusion: MMF can affect the metabolism in various organs and serum in mice. These data may provide preliminary judgement for MMF-induced toxicity and understand the metabolic mechanism of MMF more comprehensively.

Untargeted metabolomics and machine learning unveil quality and authenticity interactions in grated Parmigiano Reggiano PDO cheese

The chemical composition of Parmigiano Reggiano (PR) hard cheese can be significantly affected by different factors across the dairy supply chain, including ripening, altimetric zone, and rind inclusion levels in grated hard cheeses. The present study proposes an untargeted metabolomics approach combined with machine learning chemometrics to evaluate the combined effect of these three critical parameters. Specifically, ripening was found to exert a pivotal role in defining the signature of PR cheeses, with amino acids and lipid derivatives that exhibited their role as key discriminant compounds. In parallel, a random forest classifier was used to predict the rind inclusion levels (> 18%) in grated cheeses and to authenticate the specific effect of altimetry dairy production, achieving a high prediction ability in both model performances (i.e., ∼60% and > 90%, respectively). Overall, these results open a novel perspective to identifying quality and authenticity markers metabolites in cheese.

Untargeted metabolomic profiling reveals molecular signatures associated with type 2 diabetes in Nigerians

BackgroundType 2 diabetes (T2D) has reached epidemic proportions globally, including in Africa. However, molecular studies to understand the pathophysiology of T2D remain scarce outside Europe and North America. The aims of this study are to use an untargeted metabolomics approach to identify: (a) metabolites that are differentially expressed between individuals with and without T2D and (b) a metabolic signature associated with T2D in a population of Sub-Saharan Africa (SSA).MethodsA total of 580 adult Nigerians from the Africa America Diabetes Mellitus (AADM) study were studied. The discovery study included 310 individuals (210 without T2D, 100 with T2D). Metabolites in plasma were assessed by reverse phase, ultra-performance liquid chromatography and mass spectrometry (RP)/UPLC-MS/MS methods on the Metabolon Platform. Welch’s two-sample t-test was used to identify differentially expressed metabolites (DEMs), followed by the construction of a biomarker panel using a random forest (RF) algorithm. The biomarker panel was evaluated in a replication sample of 270 individuals (110 without T2D and 160 with T2D) from the same study.ResultsUntargeted metabolomic analyses revealed 280 DEMs between individuals with and without T2D. The DEMs predominantly belonged to the lipid (51%, 142/280), amino acid (21%, 59/280), xenobiotics (13%, 35/280), carbohydrate (4%, 10/280) and nucleotide (4%, 10/280) super pathways. At the sub-pathway level, glycolysis, free fatty acid, bile metabolism, and branched chain amino acid catabolism were altered in T2D individuals. A 10-metabolite biomarker panel including glucose, gluconate, mannose, mannonate, 1,5-anhydroglucitol, fructose, fructosyl-lysine, 1-carboxylethylleucine, metformin, and methyl-glucopyranoside predicted T2D with an area under the curve (AUC) of 0.924 (95% CI: 0.845–0.966) and a predicted accuracy of 89.3%. The panel was validated with a similar AUC (0.935, 95% CI 0.906–0.958) in the replication cohort. The 10 metabolites in the biomarker panel correlated significantly with several T2D-related glycemic indices, including Hba1C, insulin resistance (HOMA-IR), and diabetes duration.ConclusionsWe demonstrate that metabolomic dysregulation associated with T2D in Nigerians affects multiple processes, including glycolysis, free fatty acid and bile metabolism, and branched chain amino acid catabolism. Our study replicated previous findings in other populations and identified a metabolic signature that could be used as a biomarker panel of T2D risk and glycemic control thus enhancing our knowledge of molecular pathophysiologic changes in T2D. The metabolomics dataset generated in this study represents an invaluable addition to publicly available multi-omics data on understudied African ancestry populations.