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Results for “Targeted metabolomics”

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PubMed2025

Exploration of the mechanism of the Mongolian medicine Tonglaga-5 (-5) for the treatment of n-methyl-n'-nitro-n-nitrosoguanidine-induced chronic atrophic gastritis based on network pharmacology and metabolomics.

OBJECTIVE: To explore the mechanism of Tonglaga-5 (-5, TLG-5) for the treatment of chronic atrophic gastritis (CAG), based on network pharmacology and metabolomics. METHODS: Forty-eight male Sprague-Dawley rats were randomly divided into six groups (n = 8): control group; model group; teprenone group, and low-, median-, and high- dose TLG-5 groups. The enzyme linked immunosorbent assay (ELISA) was used to measure the expression of pepsinogen Ⅰ (PG Ⅰ), pepsinogen Ⅱ (PG Ⅱ) and gastrin-17 (G-17) in the serum. Hematoxylin and eosin staining were performed to observe the pathological condition. And the network pharmacology was employed to identify the targets and signaling pathways of TLG-5 affecting CAG. Then, the metabolomics approach was applied to explore the specific metabolites and metabolic pathways. Finally, validation was performed using the "metabolite-gene" interaction network, molecular docking and quantitative real-time polymerase chain reaction (qPCR). RESULTS: High-dose TLG-5 significantly improved the expression of PG Ⅰ, PGR (PG Ⅰ/ PG Ⅱ) and G-17 (P < 0.05) and inhibited the expression of phosphoinositide-3-kinase regulatory subunit 2, AKT serine/threonine kinase (AKT), hypoxia-inducible factor 1-alpha (HIF-1α) (P < 0.05). Further, high-dose TLG-5 reduced the number of glands was reduced, and fibrosis with oedema and ecchymosis appeared at the base. Overlapping TLG-5 and CAG gene targets produced 270 interactive targets. The results of gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses suggested that TLG-5 could affect CAG through the predominantly cancer and inflammation-related pathways. Pyrimidine metabolism was identified as a significantly differential pathway in the mechanism of TLG-5 for treating CAG. CONCLUSIONS: TLG-5 exerts a therapeutic effect on CAG by regulating β-alanine metabolism, pyrimidine metabolism pathways, and inhibiting the PI3K-AKT signaling pathway and HIF-1 signaling pathways.

Animals↗

PubMed2004

Unintended effects and their detection in genetically modified crops.

The commercialisation of GM crops in Europe is practically non-existent at the present time. The European Commission has instigated changes to the regulatory process to address the concerns of consumers and member states and to pave the way for removing the current moratorium. With regard to the safety of GM crops and products, the current risk assessment process pays particular attention to potential adverse effects on human and animal health and the environment. This document deals with the concept of unintended effects in GM crops and products, i.e. effects that go beyond that of the original modification and that might impact primarily on health. The document first deals with the potential for unintended effects caused by the processes of transgene insertion (DNA rearrangements) and makes comparisons with genetic recombination events and DNA rearrangements in traditional breeding. The document then focuses on the potential value of evolving "profiling" or "omics" technologies as non-targeted, unbiased approaches, to detect unintended effects. These technologies include metabolomics (parallel analysis of a range of primary and secondary metabolites), proteomics (analysis of polypeptide complement) and transcriptomics (parallel analysis of gene expression). The technologies are described, together with their current limitations. Importantly, the significance of unintended effects on consumer health are discussed and conclusions and recommendations presented on the various approaches outlined.

Animals↗

PubMed2026

Unveiling crosstalk regulations within the polyamine pathway and between polyamine and purine pathways in Aedes aegypti females.

We previously demonstrated that ornithine decarboxylase (ODC) deficiency critically impairs nitrogen metabolism and survival in Aedes aegypti. To further examine the role of the polyamine pathway in Ae. aegypti nitrogen metabolism, we evaluated the expression of three additional genes encoding proteins involved in the biosynthetic pathway: S-adenosylmethionine decarboxylase, spermidine synthase (SdS), spermine synthase (SmS), and seven genes encoding proteins involved in the catabolic pathway in fat body, midgut and Malpighian tubules by qPCR. Distinct transcriptional profiles were observed in mosquito tissues during the first gonotrophic cycle. SdS and SmS showed a differential protein expression pattern in fat body of sugar- and blood-fed mosquitoes. Genetic silencing of SdS, SmS or SdS and SmS by RNA interference (RNAi) decreased female survival. Mosquitoes with SdS or SmS deficiency exhibited a reduction of 5G1 trypsin level in the midgut at 24 h post-blood meal (PBM) , a delay in blood digestion, and a decrease in uric acid concentration in the excreta at 48 h PBM. RNAi-mediated SdS knockdown also caused a decrease in SmS protein level and vice-versa, RNAi-driven SmS deficiency resulted in a decrease in SdS protein abundance. Notably, ODC knockdown reduced SdS, SmS, xanthine dehydrogenase-1 protein levels, and decreased specific metabolite concentrations in fat body at 24 h PBM. In addition, RNAi-mediated ODC, SdS and SmS knockdown impacted transcript levels of genes involved in polyamine and purine pathways in fat body at 24 h PBM. Our findings uncover unique crosstalk regulations within the polyamine pathway and between polyamine and purine pathways.

Ammonia metabolism↗

PubMed2026

Loss of the Mechanistic Target of Rapamycin Complex 1 Causes a Lethal Alpha-1 Antitrypsin Deficiency-Associated Liver Disease.

BACKGROUND & AIMS: SERPINA1 mutations cause retention of the otherwise secreted alpha-1 antitrypsin and lead to the proteotoxic alpha-1 antitrypsin deficiency-related liver disease. As mechanistic target of rapamycin is a key coordinator of proteostasis, we studied its role in alpha-1 antitrypsin deficiency-related liver disease. METHODS: PiZ mice overexpressing the characteristic SERPINA1 mutation were mated with rodents harboring a hepatocyte specific-ablation of the interaction partners regulatory-associated protein of mechanistic target of rapamycin or rapamycin-insensitive companion of mammalian target of rapamycin, corresponding to mechanistic target of rapamycin complexes 1 or 2, or with mice lacking mechanistic target of rapamycin. Serum proteomics, liver bulk proteomics, spatial proteomics, and metabolomics were applied to characterize molecular and metabolic alterations. RESULTS: At 2 months of age, PiZ-mTORΔhep and PiZ-RaptorΔhep but not PiZ-RictorΔhep mice showed signs of increased liver injury and mortality despite diminished hepatic alpha-1 antitrypsin accumulation. PiZ-RaptorΔhep animals displayed increased levels of the proapoptotic protein C/EBP homologous protein, but C/EBP homologous protein ablation did not rescue the phenotype. Serum proteomics revealed no signs of advanced synthetic liver failure but immature hepatocellular products. Liver bulk proteomics and small metabolite measurement demonstrated a metabolic reprogramming of PiZ-RaptorΔhep mice. Spatial proteomics revealed alterations in liver zonation with increased ammonia levels as the likely cause of death in PiZ-RaptorΔhep animals. CONCLUSIONS: In summary, in alpha-1 antitrypsin deficiency-related proteotoxic liver injury, regulatory-associated protein of mechanistic target of rapamycin preserves a liver zonation, thereby protecting from lethal metabolic dysregulation.

Animals↗

PubMed2026

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans↗

PubMed2005

Clinical applications for targeted therapy in bladder cancer.

The tremendous amount of data accumulated through genomics, proteomics, and metabolomic technologies has not led to a definitive understanding of the mechanisms underlying cancer. The challenge remains as to how to integrate all of the relevant knowledge and data in a systematic manner so that researchers can gain the knowledge needed to devise the best therapeutic and diagnostic strategies. Human transitional cell carcinoma of the bladder is genetically heterogeneous, and it is surrounded by a complex tissue microenvironment involving vasculature, stromal cells, and connective tissue. One of the most challenging problems facing cancer researchers is the lack of correlation between in vitro cell lines and animal tumor models and human in vivo tumors. A few promising approaches are being devised that will help address this issue in the coming years. One such approach is the measurements of molecular levels of receptors, ligands, pathways components, and so on, directly in human tumors through in vivo imaging, or through proteomic profiling, as it has been proposed as standard protocol for cancer diagnostics and therapeutics.

Antineoplastic Agents↗

PubMed2005

Genomics, proteomics, metabolomics: what is in a word for multiple sclerosis?

PURPOSE OF REVIEW: Multiple sclerosis (MS) is the most common chronic inflammatory neurological disease. Despite major advances the aetiology of this disease it is still not completely understood. In the post-genome era, advances in global screening technologies offer an opportunity to accelerate the search of new pathological pathways and to identify new therapeutic targets. Some recent publications using novel global screening methods at the genome, transcriptome, proteome and metabolome levels are discussed. RECENT FINDINGS: The genetic association of susceptibility to MS with loci outside the MHC has been reconfirmed. Evidence of parent-of-origin and seasonal effects on disease susceptibility add further complexity to the genetics of MS. The search for MS susceptibility genes continues using the candidate-gene approach as well as large-scale single-nucleotide-polymorphism association studies and novel cross-species synteny analysis. Genome-wide expression profiling using microarrays produced numerous therapeutic targets and is progressing towards profiling of rare cells. Advances in classical proteomics methods paved the way to new initiatives aiming at determining the proteome of the nervous system in normal and diseased states. Although progress is still slow, array-based methods are making an impact on the MS field. SUMMARY: The complexity of MS is clearly reflected in the latest findings using global profiling methods. Nevertheless, these new technologies are confirming some of the basic aspects of the disease pathophysiology, i.e. its polygenicity, the central role of neuroinflammation and the emerging neurodegenerative processes. These data are primarily the results of genomic approaches, yet promising attempts are also made using proteomics and metabolomics.

Animals↗

PubMed2024

A metabolomics pipeline highlights microbial metabolism in bloodstream infections.

The growth of antimicrobial resistance (AMR) highlights an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe infections profoundly alter host metabolism, prior studies have largely ignored microbial metabolism in this context. Here, we describe an iterative, comparative metabolomics pipeline to uncover microbial metabolic features in the complex setting of a host and apply it to investigate gram-negative bloodstream infection (BSI) in patients. We find elevated levels of bacterially derived acetylated polyamines during BSI and discover the enzyme responsible for their production (SpeG). Blocking SpeG activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity also enhances bacterial membrane permeability and increases intracellular antibiotic accumulation, allowing us to overcome AMR in culture and in vivo. This study highlights how tools to study pathogen metabolism in the natural context of infection can reveal and prioritize therapeutic strategies for addressing challenging infections.

Metabolomics↗

PubMed2026

Free polyphenols and multi-omics traits underlying antioxidant variation across Paeonia lactiflora leaf cultivars.

Leaves of Paeonia lactiflora are underutilized by-products with potential as natural antioxidant sources. In this study, 18 cultivars were evaluated for phytochemical composition and in vitro antioxidant capacity. Total phenolic content correlated strongly with DPPH and ABTS activities, and the comprehensive antioxidant index identified 'Coral Charm' and 'Hangshao' as representative high- and low-antioxidant cultivars, respectively. Untargeted metabolomics detected 2677 metabolites and identified 908 differential metabolites between the two cultivars. Targeted phenolic profiling quantified 27 compounds, among which 11 differed significantly between the two cultivars. Catechin and epicatechin were enriched in 'Coral Charm', with contents of 6.62 and 0.397 ng/mg, respectively, compared with 0.012 and 0.002 ng/mg in 'Hangshao'. (+)-Dihydroquercetin was also more abundant in 'Coral Charm', while caffeic acid showed an upward trend. Proteomic analysis identified 423 differentially expressed proteins, mainly associated with secondary metabolite biosynthesis, redox homeostasis, and central carbon metabolism. Integrated analysis identified pyruvate metabolism as the only pathway significantly enriched in both metabolomic and proteomic datasets. Molecular docking predicted favorable binding between representative phenolics and selected proteins. These findings link cultivar-dependent antioxidant variation in peony leaves with free-phenolic accumulation and pathway-level metabolic differences, supporting the selection and utilization of antioxidant-rich peony leaf resources.

Antioxidants↗

PubMed2026

Metab8D: a metabolic regulome network from multiomics and machine learning.

To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic variation across ~1000 different cancer cell lines with matched omics data from eight biomolecular classes: genomic copy number variation, mutations, DNA methylation, histone post-translational modifications (PTMs), transcriptomics and RNA splice variants, non-coding transcriptomics (miRNA and lncRNA), proteomics, and phosphoproteomics. Overall, the metabolome is tightly associated with the transcriptome, with coding and non-coding RNAs emerging as top predictors. Peripheral metabolites are predictable via levels of corresponding enzymes, while those in central metabolism require combinatorial predictors in signaling and redox pathways, and may not reflect corresponding pathway expression. We reconstruct multiomic interaction subnetworks for highly predictable metabolites, and YAP1 signaling emerged as a top global predictor across four omic layers. We prioritize predictive multiomic features for single-cell and spatial metabolomics assays. Top predictors were enriched for synthetic-lethal interactions and synergistic combination therapies that target compensatory metabolic modulators.

Machine Learning↗

PubMed2026

Region-Resolved Integrative Multi-Omic Characterization Reveals Diverse Tumor and Microenvironment Features of Pituitary Neuroendocrine Tumors.

Pituitary neuroendocrine tumors are frequently invasive, with cavernous sinus invasion leading to poor treatment outcomes and high recurrence. Regional differences within these tumors remain poorly understood, hindering targeted therapy development. Here, we present the first integrative multi-omics analysis combining proteomics, metabolomics and single-cell transcriptomics to characterize tumors from the cavernous sinus and saddle regions. Our results reveal profound regional and cellular heterogeneity: cavernous sinus tumors exhibit significantly enhanced cell proliferation, driven by cancer-associated fibroblasts through the IGF1-IGF1R-MAPK1 axis. Cancer-associated fibroblasts in the cavernous sinus secrete IGF1 under regulation of the transcription factor FOXO1, which binds to receptors on tumor cells to activate proliferation. Metabolomic profiling identifies proline as a key enriched metabolite that stimulates cancer-associated fibroblasts to produce collagen fibers, reinforcing a pro-tumorigenic microenvironment. Single-cell transcriptomics further delineates a distinct subpopulation of receptor-positive malignant cells and a high abundance of cancer-associated fibroblasts in the cavernous sinus. These findings establish core mechanisms underlying the aggressive behavior of cavernous sinus-invading tumors, providing novel actionable targets for precision therapeutic strategies tailored to distinct tumor regions.

Humans↗

PubMed2004

A prominent role for the CBF cold response pathway in configuring the low-temperature metabolome of Arabidopsis.

The Arabidopsis CBF cold response pathway has a central role in cold acclimation, the process whereby plants increase in freezing tolerance in response to low nonfreezing temperatures. Here we examined the changes that occur in the Arabidopsis metabolome in response to low temperature and assessed the role of the CBF cold response pathway in bringing about these modifications. Of 434 metabolites monitored by GC-time-of-flight MS, 325 (75%) were found to increase in Arabidopsis Wassilewskija-2 (Ws-2) plants in response to low temperature. Of these 325 metabolites, 256 (79%) also increased in nonacclimated Ws-2 plants in response to overexpression of C-repeat/dehydration responsive element-binding factor (CBF)3. Extensive cold-induced changes also occurred in the metabolome of Arabidopsis Cape Verde Islands-1 (Cvi-1) plants, which were found to be less freezing tolerant than Ws-2 plants. However, low-temperature-induced expression of CBF1, CBF2, CBF3, and CBF-targeted genes was much lower in Cvi-1 than in Ws-2 plants, and the low-temperature metabolome of Cvi-1 plants was depleted in metabolites affected by CBF3 overexpression. Taken together, the results indicate that the metabolome of Arabidopsis is extensively reconfigured in response to low temperature, and that the CBF cold response pathway has a prominent role in this process.

Acclimatization↗

PubMed2005

Medicinal chemistry, metabolic profiling and drug target discovery: a role for metabolic profiling in reverse pharmacology and chemical genetics.

Comprehensive analysis of the metabolome can contribute to mechanism of action studies for small molecules discovered in phenotypic screens. Examples are presented in this overview of the rapidly developing field of "metabolic profiling." These examples include the use of NMR in gene function analysis, GC-based studies on the identification of metabolic pathways affected by PPAR-gamma agonists, applications of Fourier-transform MS and the use of stable isotope-based metabolic profiling (SIDMAP) to investigate metabolic adaptive changes induced by effective anticancer agents.

Animals↗

PubMed2026

Proteomic and metabolomic profiling reveals dysregulation of immune states, mucin-type glycosylation and steroid metabolism in extramammary Paget's disease.

BACKGROUND: Extramammary Paget's disease is a rare cutaneous adenocarcinoma characterized by mucin-rich Paget cells and chronic inflammation, yet its molecular basis remains unclear. OBJECTIVE: To systematically characterize the proteomic and metabolomic landscape of EMPD, uncover immune heterogeneity, and identify molecular pathways underlying tumor progression and microenvironment remodeling. METHODS: We performed integrated proteomic and metabolomic analyses on 92 male tumor patients and 30 healthy controls, identifying 10,217 proteins and 1466 metabolites. RESULTS: Extramammary Paget's disease lesions exhibited broad activation of inflammatory pathways. Immune profiling further uncovered substantial inflammatory heterogeneity, delineating immune-cold and immune-hot subtypes, with the latter associated with stronger invasive potential. Aberrant mucin-type glycosylation was also prominent, featuring Tn-modified MUC1 and MUC5AC accompanied by elevated GALNT7, GALNT6, GALNT4, and ST6GAL1, which correlated with inflammatory intensity. Metabolomic data demonstrated elevated levels of testosterone, dehydroepiandrosterone, and related intermediates in tumor tissues, indicating an androgen-enriched metabolic profile in extramammary Paget's disease. CONCLUSION: These findings reveal immune, glycoproteomic, and metabolomic pathways in extramammary Paget's disease pathogenesis and provide novel insights for molecular classification and therapeutic targeting.

Humans↗

PubMed2026

The mechanism by which long-term exposure to TDCIPP promotes cognitive impairment in 3 ×Tg-AD mice: Insights from multi-omics studies.

Tri(1,3-dichloro-2-propyl) phosphate (TDCIPP) is a commonly used organophosphate ester that has the potential to adversely affect human health. Although previous studies have closely associated TDCIPP with cognitive impairment, the underlying mechanisms remain unclear. To elucidate the neurotoxic effects of TDCIPP and its mechanistic contribution to cognitive impairment in 3 ×Tg-AD mice, a multi-omics approach incorporating proteomics, untargeted metabolomics, and 16S ribosomal RNA (rRNA) gene sequencing was employed to evaluate the impact of TDCIPP exposure on neurobehavioral function. TDCIPP exposure promoted cognitive impairment in 3 ×Tg-AD mice. Proteomic analyses revealed that this promotion is associated with disturbances in the hippocampal mitochondrial autophagy pathway. Furthermore, TDCIPP may interfere with the PINK1/Parkin-mediated mitophagy pathway at the functional level, without altering PINK1 protein abundance. Untargeted metabolomic analysis of urine samples demonstrated that TDCIPP exposure altered the metabolic profile of 3 ×Tg-AD mice, with 58 metabolites upregulated and 11 downregulated. Additionally, 16S rRNA sequencing revealed substantial modifications in gut microbiome composition following exposure to TDCIPP. Notably, significant correlations were identified between the perturbed bacterial genera and the differential metabolites. In conclusion, exposure to TDCIPP promotes cognitive impairment in 3 ×Tg-AD mice, which is associated with the interference with the PINK1/Parkin-mediated mitophagy pathway, as well as alterations in the urinary metabolome and gut microbiota. These findings suggest the potential to mitigate such cognitive impairment by targeting the microbiota-gut-brain axis.

Animals↗

PubMed2005

Metabolomics: from pattern recognition to biological interpretation.

Metabolomics is a technology that aims to identify and quantify the metabolome -- the dynamic set of all small molecules present in an organism or a biological sample. In this sense, the technique is distinct from metabolic profiling, which looks for target compounds and their biochemical transformation. The combination of both approaches is an emerging technique for the characterization of biological samples and for drug treatment. Metabolomics has proven to be very rapid and superior to any other post-genomics technology for pattern-recognition analyses of biological samples. Changing steady state concentrations and fluctuations of metabolites that occur within milliseconds are a result of biochemical processes such as signalling cascades: metabolomic techniques are instrumental in measuring these changes rapidly and sensitively. Metabolite data can be complemented by protein, transcript and external (environmental) data, thereby leading to the identification of multiple physiological biomarkers embedded in correlative molecular networks that are not approachable with targeted studies.

Biomarkers↗

PubMed2025

MEANtools integrates multi-omics data to identify metabolites and predict biosynthetic pathways.

During evolution, plants have developed the ability to produce a vast array of specialized metabolites, which play crucial roles in helping plants adapt to different environmental niches. However, their biosynthetic pathways remain largely elusive. In the past decades, increasing numbers of plant biosynthetic pathways have been elucidated based on approaches utilizing genomics, transcriptomics, and metabolomics. These efforts, however, are limited by the fact that they typically adopt a target-based approach, requiring prior knowledge. Here, we present MEANtools, a systematic and unsupervised computational integrative omics workflow to predict candidate metabolic pathways de novo by leveraging knowledge of general reaction rules and metabolic structures stored in public databases. In our approach, possible connections between metabolites and transcripts that show correlated abundance across samples are identified using reaction rules linked to the transcript-encoded enzyme families. MEANtools thus assesses whether these reactions can connect transcript-correlated mass features within a candidate metabolic pathway. We validate MEANtools using a paired transcriptomic-metabolomic dataset recently generated to reconstruct the falcarindiol biosynthetic pathway in tomato. MEANtools correctly anticipated five out of seven steps of the characterized pathway and also identified other candidate pathways involved in specialized metabolism, which demonstrates its potential for hypothesis generation. Altogether, MEANtools represents a significant advancement to integrate multi-omics data for the elucidation of biochemical pathways in plants and beyond.

Metabolomics↗

PubMed2002

A rapid and simple nonradioactive method for in vitro testing of ribozyme activity.

Ribozymes that target specific messenger RNA transcripts are powerful tools in the emerging fields of functional genomics, proteomics, and metabolomics. We have found that successful in vitro testing greatly increases the likelihood of producing ribozymes with good efficacy in living cells. A rapid and simple nonradioactive method for systematic in vitro testing of ribozyme-cleaving activity is reported. Ribozymes are synthesized enzymatically from double-stranded DNA (dsDNA) oligonucleotides without vector cloning. Substrate target DNA template is cloned into a vector flanked with SP6 and T7 promoters at multiple cloning sites that permit colorimetric screening and ampicillin selection, enhancing the efficiency of the cloning procedure. Ribozyme cleavage products are satisfactorily resolved on 2.0% NuSieve 3:1 agarose (FMC Products, Rockland, ME)/formaldehyde gels by electrophoresis. This method avoids the preparation of polyacrylamide gels. Using this procedure, the ribozyme, target substrate RNA, and ribozyme cleavage products are all easily detected by ethidium bromide staining. Resolution and detection are fast and simple, eliminating the need for either polyacrylamide gel analysis or radiolabeling. The use of RNase inhibitors in the assays is also assessed and discussed.

DNA↗