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PubMed2026

Exposome influences: a multi-omics perspective on the combined toxic effects of pharmaceuticals and personal care products in Alzheimer's disease.

According to WHO data, approximately 57 million people worldwide were affected by dementia in 2021, with prevalence projected to rise. Alzheimer's disease (AD), responsible for 60%-80% of dementia cases, continues to be a leading cause of mortality, with current treatments offering limited efficacy and disease-modifying therapies lacking widespread adoption or conclusive safety evidence, shifting the focus toward prevention and risk modification. Risk factors for AD include both non-modifiable elements, such as age, genetics, and gender, and modifiable factors, like environmental pollution, health status, and diet. While age remains the primary non-modifiable risk factor, early-onset dementia represents only up to 9% of cases. Addressing modifiable factors is essential, as it could prevent or delay almost half of dementia cases, with interventions-such as increased physical activity, smoking cessation, alcohol limitation, and overall health management-being significantly associated with a reduced risk. In this context, the exposome approach offers a comprehensive, integrative framework in which both modifiable and non-modifiable risk factors interact to influence individual susceptibility. Within the neural exposome, chronic low-dose exposure to xenobiotics-such as industrial chemicals, pesticides, metals, pharmaceuticals and personal care products (PPCPs), and air pollutants-may induce neurodegeneration via mechanisms including oxidative stress, neuroinflammation, proteinopathies, and epigenetic modifications, although establishing causality remains challenging. Integration of genomics, transcriptomics, proteomics, metabolomics, and lipidomics, combined with artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL), provides promising avenues for biomarker discovery, enhanced preventive strategies, early non-invasive diagnosis, and therapeutic target identification by integrating multi-layered biological data with exposure profiles. This review highlights emerging AD risk factors-including PPCPs-underscoring complex, multifactorial nature of AD and exposome, and the requirement for an interdisciplinary research approach, while also addressing several critical research gaps and methodological limitations.

Alzheimer’s disease↗

PubMed2025

Four-dimensional data independent acquisition proteomics and metabolomics reveal mechanisms of hydrogen-rich water at Zusanli (ST36) point against triple-negative breast cancer in mice.

OBJECTIVE: To develop a safe and effective green therapy for triple-negative breast cancer, this study combines hydrogen-rich water with acupuncture point injection, and finds that it can prevent tumor growth and minimize cancer metastasis. METHODS: After 21 d of hydrogen rich water injection treatment on 4T1 (mouse breast cancer cells) xenograft mice, in order to systematically identify differentially expressed proteins in tumor samples between the model group and the Zusanli (ST36) group injected with hydrogen rich water at acupoints, with a focus on functional proteins or signaling pathways related to tumor occurrence and development, researchers conducted four-dimensional data independent acquisition (4D-DIA) proteomic analysis on tumor tissues. In order to further investigate the dynamic changes of metabolites after therapeutic intervention, researchers conducted liquid chromatography-tandem mass spectrometry untargeted metabolomics identification and analysis on mouse serum. The results of the joint proteomics-metabolomics analysis were validated using experimental methods such as immunofluorescence, Western blotting, and quantitative reverse transcription polymerase chain reaction detection. RESULTS: Injecting hydrogen-rich water into acupoints significantly inhibited tumor growth (P < 0.05). 4D-DIA proteomics and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses uncovered pathways such as T helper 1 cell (Th1) and T helper 2 cell (Th2) cell differentiation. The KEGG metabolic pathways identified in the metabolomics analysis included galactose metabolism along with fructose and mannose metabolism. Based on the combined proteomics and metabolomics analysis, the key pathways included the C-type lectin receptor signaling pathway. The major cancer-related differential proteins detected in Th1 and Th2 cell differentiation [interleukin 6 signal transducer, nuclear factor of activated T cells 4, recombinant mitogen activated protein kinase 10 (MAPK10), and MAPK11] were upregulated after the injection of hydrogen-rich water into the Zusanli (ST36) acupoint, whereas Linker for activation of T cells (Lat), signal transducer and activator of transcription 1, and protein kinase C, theta were downregulated. CONCLUSION: The injection of hydrogen-rich water into the Zusanli (ST36) acupoint effectively inhibited the hyperplasia of 4T1 BC cells and enhanced their apoptosis, potentially exerting a therapeutic effect through multiple pathways and targeting various sites.

Animals↗

PubMed2026

Bacteroides cellulosilyticus-derived 2-hydroxyphenylacetic acid rectifies hepatic lipid homeostasis in MASLD by targeting the PPARγ-CD36 axis.

The gut microbiota plays an important role in the occurrence and development of metabolic dysfunction-associated steatotic liver disease (MASLD), but the specific molecular mechanisms involved have not been fully elucidated. In this study, human cohort studies were performed to identify that the relative abundance of Bacteroides cellulosilyticus (B. cellulosilyticus) was significantly decreased in patients with MASLD. Through the integration of metagenomic and metabolomic analyses, it was confirmed that B. cellulosilyticus and its metabolite 2-hydroxyphenylacetic acid (2HPAA) are key factors regulating the occurrence and development of MASLD. Single-cell sequencing and lipidomic analyses revealed that 2HPAA can enter the liver through the enterohepatic circulation to exert regulatory effects. Specifically, 2HPAA inhibits the peroxisome proliferator-activated receptor γ (PPARγ) signaling pathway, thereby suppressing the expression of the fatty acid transporter CD36. Meanwhile, 2HPAA regulates lipid metabolism in hepatocytes by significantly enhancing palmitate conversion efficiency and inhibiting CD36 palmitoylation. This dual regulatory effect on CD36 expression and palmitoylation can reduce lipid accumulation in hepatocytes and ultimately alleviate MASLD progression. These findings reveal the mechanism by which B. cellulosilyticus and 2HPAA alleviate MASLD by targeting the PPARγ-CD36 pathway. This work provides a new perspective for the study of gut microbiota-host interactions in regulating liver diseases.

PPAR gamma↗

PubMed2026

Polyphenol-Rich Opuntia ficus-indica Cladodes: An Integrated Metabolomic, In Vivo and In Silico Study Supporting Their Hypolipidemic and Hepatoprotective Effects.

Background: Hyperlipidemia is a major risk factor for cardiometabolic disorders, including non-alcoholic fatty liver disease (NAFLD), and is closely associated with oxidative stress. Opuntia ficus-indica (OFI) cladodes are recognized as a rich source of bioactive phytochemicals; however, the molecular mechanisms underlying their metabolic benefits remain incompletely understood. Objectives: This study aimed to comprehensively evaluate the hypolipidemic and hepatoprotective potential of a polyphenol-rich O. ficus-indica cladode extract (OCE) using an integrated approach combining in vivo evaluation, untargeted metabolomics (UHPLC-Orbitrap-MS/MS), molecular docking, and ADMET prediction. Methods: Hyperlipidemic mice fed a high-fat diet (HFD) were treated with OCE, while molecular docking was performed on ten major annotated phytochemicals against twelve key proteins involved in lipid metabolism and cholesterol homeostasis, including HMGCR, FAS, PPARα, PCSK9, and NPC1L1, using simvastatin as the reference compound. Results: OCE treatment significantly improved plasma and hepatic lipid profiles, improved glucose homeostasis, and markedly reduced hepatic malondialdehyde (MDA) levels, indicating attenuation of oxidative stress. Histopathological analysis further supported a pronounced hepatoprotective effect, with a substantial reduction in hepatic steatosis. Untargeted metabolomics enabled the annotation of 102 metabolites, putatively identifying piscidic acid as the predominant phenolic constituent together with a diverse profile of flavonoids and phenolic acids. Molecular docking supported the potential contribution of these phytochemicals to the regulation of lipid metabolism through favorable interactions with multiple therapeutic targets, while ADMET prediction suggested an overall favorable pharmacokinetic and toxicity profile despite the lower intestinal permeability predicted for glycosylated derivatives. Conclusions: Overall, these findings support O. ficus-indica cladodes as a promising source of dietary bioactive compounds with potential applications in the nutritional management and prevention of hyperlipidemia and related cardiometabolic disorders.

Animals↗

PubMed2026

Integrative analysis of rumen microbiota activity and host metabolism following methanogenesis inhibition in dairy cattle.

Enteric methane emission from dairy cattle is an environmental challenge. The most efficient mitigation strategies nowadays include the use of methanogenesis inhibitors that specifically target the rumen methanogens. Specific inhibitors, such as 3-nitrooxypropanol (3-NOP), reduce methane emissions without negative effects on the products of fermentation that serve as energy metabolites for the host. However, the concomitant effects of methanogenesis inhibition on rumen microbiota and host metabolism are poorly characterized. Thus, the objective of this study was to explore the association between rumen microbiota and host metabolism when methanogenesis is inhibited. Thirteen dairy cows were used as controls, and 12 were supplemented with 3-NOP for 6 weeks. Rumen microbiota composition and activity were characterized using metagenomics and metatranscriptomics. The host metabolism was assessed in a previous publication by a metabolomic analysis of the plasma. Microbiota data were used as explanatory variables of the metabolome data in a multiblock sparse partial least squares analysis. Overall, the association between rumen microbiota and host metabolism was moderate. Notwithstanding this, a few downregulated transcripts related to glycolysis, hydrogen transfer, and protein synthesis, together with a decrease in the proportion of taxa of the Oscillospirales order, showed a correlation with host one-carbon metabolites (|r| > 0.6). These associations raised novel hypotheses that remain to be elucidated, especially with regard to the effects of dihydrogen on the accumulation of microbial glycolysis and methanogenesis metabolite intermediates.IMPORTANCEDairy cattle produce a substantial amount of methane, a potent greenhouse gas. Several strategies have been designed to reduce methane production by targeting the rumen microbiota. One such strategy specifically inhibits methanogens with a molecule called 3-nitrooxypropanol. This study uses an integrative data analysis approach, combining rumen microbiota and host metabolome information, to explore the consequences of inhibiting methanogenesis on the holobiont. This provides additional holistic insight into the effect of methane mitigation strategies on dairy cattle.

Animals↗

PubMed2026

Untargeted metabolomics and proteomics reveals cocoa-mediated mitigation of valproic acid-induced dysregulation in a zebrafish model of autism: pilot study.

INTRODUCTION: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by behavioral impairments and limited therapeutic options. Emerging evidence suggests that plant-derived polyphenols may offer neuroprotective benefits. OBJECTIVES: This pilot study aimed to investigate the therapeutic potential of polyphenol-rich cocoa extract in a valproic acid (VPA)-induced zebrafish model of ASD. METHODS: Zebrafish were exposed to 3 μM VPA, cocoa powder providing 2.5 μM (-)-epicatechin, a combination of both, or left untreated. Behavioral phenotyping was conducted using DanioVision and gut morphology was assessed. Untargeted metabolomic and proteomic profiling was performed followed by univariate and multivariate analyses. RESULTS: VPA exposure induced ASD-like behavioral hyperactivity, and severe gastrointestinal abnormalities. Cocoa co-treatment ameliorated both behavioral performance and gut architecture. Metabolomic profiling revealed VPA-associated disruptions in neurotransmission, methylation, mitochondrial function and redox homeostasis. Proteomic profiling showed elevated levels of trafficking protein particle complex subunit 11, proteasomal ubiquitin receptor, betaine-homocysteine S-methyltransferase 1 (BHMT-1), and desmoplakin-A, consistent with genotoxic stress and impaired protein trafficking. Cocoa co-treatment normalized BHMT-1 and desmoplakin-A expression and mitigated broader metabolic dysregulation. CONCLUSION: Collectively, these results suggest that polyphenol-rich cocoa may represent a promising multi-targeted nutraceutical approach for mitigating ASD-related neurodevelopmental and metabolic disturbances.

Animals↗

PubMed2026

Transcriptomic and Metabolomic Profiling Identifies a Core Gene-Metabolite Axis Driving African Swine Fever Virus Replication in the Soft Tick Ornithodoros lahorensis.

African swine fever virus (ASFV) causes an incurable swine disease with nearly 100% mortality, posing a catastrophic threat to global pig production. The soft tick Ornithodoros lahorensis acts as a critical biological vector that sustains persistent ASFV replication and mediates long-distance viral transmission, yet the molecular mechanisms governing ASFV-tick interplay remain poorly understood. Here, we integrated transcriptomics and metabolomics to systematically dissect molecular changes in O. lahorensis across three infection stages: Uninfected control, early infection (7 days post-infection, dpi), and late persistent infection (21 dpi). Multi-omics integration revealed that ASFV extensively remodels tick host metabolism, predominantly activating purine/pyrimidine metabolism, lipid biosynthesis, and energy metabolism. We further characterized a conserved regulatory module consisting of 12 core genes and 8 signature metabolites that collectively support ASFV genome replication and virion assembly. Three hub metabolic genes (TK1, ATP5F1B, and IMPDH) were selected for functional validation via siRNA silencing in ticks; individual gene silencing suppressed ASFV loads by 89.2%, 91.5%, and 87.8%, respectively (p < 0.001***). This work represents the first comprehensive multi-omics investigation of ASFV infection in O. lahorensis. We identified tick-specific molecular targets to block vector-mediated ASFV spread and established a standardized multi-omics analytical pipeline for tick-virus interaction research. Our findings elucidate the mechanistic basis of long-term ASFV persistence in soft ticks and deliver novel actionable clues for developing vector-targeted ASF intervention strategies.

Animals↗

PubMed2025

Treatment response variations to a single large bolus of enteral cholecalciferol in vitamin D deficient critically Ill children: Metabolomic insights for precision nutrition.

Vitamin D deficiency (VDD) is prevalent globally and in pediatric intensive care units, where it represents a modifiable risk factor that may impact patient recovery during hospitalization. Herein, we performed a retrospective analysis of serum samples from a phase-II randomized placebo-controlled trial involving a single large bolus of 10,000 IU/kg vitamin D3 ingested by critically ill children with VDD (25-OH-D < 50 nmol/L). Targeted and untargeted methods were used to comprehensively measure 6 vitamin D metabolites, 239 lipids, 68 polar metabolites, and 4 electrolytes using a multi-step data workflow for compound authentication. Complementary statistical methods classified circulating metabolites/lipids associated with vitamin D repletion following high-dose vitamin D3 intake (n = 20) versus placebo (n = 11) comprising an optional standard of care maintenance dose (< 1000 IU/day). There was a striking increase in median serum concentrations of 25-OH-D3 (4.7-fold), 3-epi-25-OH-D3 (24-fold) and their C3-epimer ratio (6.7-fold) in treated patients on day 3, whereas serum vitamin D3 peaked on day 1 (128-fold) unlike placebo. Treatment response differences were attributed to D3 bioavailability and C3-epimerase activity without evidence of hypercalcemia. For the first time, we report the detection of circulating 3-epi-D3 that was strongly correlated with vitamin D3 uptake (r = 0.898). Metabolomic studies revealed that vitamin D sufficiency (serum 25-OH-D >75 nmol/L) coincided with lower circulating levels of 3-methylhistidine, cystine, S-methylcysteine, uric acid, and two lysophosphatidylcholines 7 days after treatment. Rapid correction of VDD was associated with indicators of lower oxidative stress, inflammation, and muscle protein turn-over that may contribute clinical benefits in high-risk critically ill children.

Humans↗

PubMed2026

Multiomics approaches to cardiovascular disease: technological innovations and clinical translation.

Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, reflecting a persistent gap between clinical phenotyping and the molecular mechanisms that govern disease initiation, progression, and interindividual variability. Recent advances in emerging technologies have fundamentally reshaped cardiovascular physiology by enabling high-resolution, cross-layer profiling of the heart and vasculature across genomic, epigenomic, transcriptomic, proteomic, metabolomic, lipidomic, glycomic, and fluxomic layers, increasingly at single-cell and spatial resolution. These approaches reveal CVD as a coordinated, multilayered process driven by dynamic interactions among cell types, regulatory programs, and metabolic states, rather than isolated gene-level defects. In this review, we synthesize how emerging multiomic, computational, and functional genomic technologies are redefining the study of cardiovascular disease across molecular, cellular, and tissue levels. We highlight recent innovations in single-cell and spatial atlases, long-read sequencing, proteomics and metabolomics, integrative data modeling, and functional omics approaches, including genome-scale perturbation screens and single-cell perturbation frameworks. These platforms enable mechanistic dissection of regulatory circuits, distinguish primary disease drivers from secondary adaptations, and directly assess therapeutic reversibility, advancing the field beyond associative biomarker discovery toward mechanism-guided target prioritization. We further discuss key methodological and translational challenges accompanying high-dimensional cardiovascular data, including preanalytical variability, control selection, temporal misalignment across molecular layers, population diversity, and reference bias. By integrating technological innovation with computational rigor and functional validation, this review frames emerging omics-enabled strategies as a unified, physiologically grounded framework for translating molecular insight into clinically meaningful cardiovascular phenotypes and advancing precision cardiovascular medicine.

Humans↗

PubMedDate not supplied

Genome, proteome, and metabolome: where are we going?

Rapid advances have been made in recent years in understanding the genetic makeup of mankind. The human genome project has identified approximately 32,000 genes that occur in humans. It is now possible to perform genetic profiling with many of the genes to understand embryogenesis, growth and development, the normal state, senescence, diseases, and tumorogenesis. Techniques in molecular diagnostics are becoming available that will expand the ability to provide more precise diagnoses, predict response to treatment, evaluate treatment, and predict prognosis and outcome. Genetic profiling will, in the future, direct therapy by providing specific targets for development of medications, antibodies, and gene therapy. More recently, the attention of the scientific community has turned toward the gene products within the cell and tissue matrix, namely proteins. The field of proteomics is an evolving area, which may shed light on the proteins associated with diseases and tumors. This will again provide a mechanism for creating personalized, designer therapies for individual patients or groups of patients with similar diseases based on expression profiling. The final avenue of exploration in understanding cell function is the metabolites that occur as the end products of cellular function (metabolome). These metabolites, or improper degradation of cellular proteins, may lead to disease and neoplasia. The role of the pathologist in expression profiling for diseases and tumorigenesis is of considerable importance in providing diagnostic information and predicting outcome based on pathobiologic features of diseases and tumors.

Genome↗

PubMed2005

Selection of candidate genes in hypertension.

Essential hypertension is a common disease with multifactorial etiology affecting up to 10 million individuals in the United Kingdom alone. Current knowledge of the genetic contribution to this trait is restricted to a number of rare variants that produce hypertensive phenotypes in a Mendelian fashion and to genes highlighted by work on blood pressure regulation in rodent models. Recent advances in comparative genomics, genome-wide scans for linkage, transcriptomics, proteomics, and metabolomics allow a systematic approach to the prioritization of candidate genes for hypertension and other complex traits. We review the current state of play in these fields related to hypertension and show, with a particular example, how these data may help target genetic studies in the future.

Animals↗

PubMed2026

Characterization of age-related changes in the gut microbiome and metabolome of Kunming dogs and their associations with police performance.

BACKGROUND: Gut microbiota plays a pivotal role in regulating the host's central nervous system (CNS) activity and behavior. However, its influence on the police performance of Kunming dogs and the underlying mechanisms remain largely unexplored. This study was the first to apply multi-omics technologies to investigate the dynamic variations in gut microbiota and their metabolic profiles across different ages of Kunming dogs. Furthermore, we systematically examined the associations between these microbial alterations and police performance metrics, providing a theoretical foundation for enhancing the working capabilities of Kunming dogs through targeted modulation of intestinal microecology. RESULTS: The study showed that puppies, young dogs and adult dogs had significantly better police performance than elderly dogs, with young dogs exhibiting the highest scores. Analysis of 16S rRNA sequencing demonstrated that gut microbial diversity and stability were highest during the young dog stage, gradually declining with age. Metagenomic analysis revealed that the abundance of Lactobacillus acidophilus, Lactobacillus johnsonii, Limosilactobacillus reuteri, Ligilactobacillus animalis and Muribaculum gordoncarteri were strongly correlated with police performance. The results of metagenome-assembled genomes (MAGs) indicated that the above species have functional genes involved in GABAergic and glutamatergic synapse pathways. Furthermore, metabolomic analysis showed that differential metabolites were enriched in the neuroactive ligand-receptor interaction pathway, in which GABA (γ-aminobutyric acid), histamine and tyramine metabolites were positively correlated with the above species and police performance. CONCLUSION: The species L. acidophilus, L. johnsonii, L. reuteri, L. animalis, and M. gordoncarteri, which were enriched in the gut of puppies and young Kunming dogs, may potentially influence the nervous system through the production of neurotransmitters and neuromodulators, suggesting a possible association with police performance. Video Abstract.

Animals↗

PubMed2026

Integrated transcriptomic and metabolomic analysis reveals candidate regulatory networks associated with starch accumulation in tetraploid potato.

Potato (Solanum tuberosum L.) tuber starch is a major determinant of crop quality and industrial value, yet the regulatory mechanisms underlying starch accumulation in autotetraploid cultivars remain poorly resolved. Here, we performed integrated transcriptomic and metabolomic analyses using a segregating tetraploid population derived from parents with contrasting starch content. Extreme phenotypes were selected to systematically dissect the molecular basis of starch accumulation. Transcriptome profiling revealed extensive transcriptional reprogramming between high- and low-starch genotypes, with differentially expressed genes significantly enriched in carbohydrate metabolism, particularly the starch and sucrose metabolism pathway. Notably, multiple transcription factor families, including AP2/ERF, MYB, and bHLH, were prominently represented, suggesting coordinated regulatory control. Metabolomic analysis identified substantial metabolic divergence, with differentially accumulated metabolites predominantly enriched in starch and sucrose metabolism as well as secondary metabolic pathways. Most metabolites exhibited negative associations with starch content, indicating competitive carbon allocation between primary and secondary metabolism. Integrative multi-omics analysis further resolved a core regulatory module comprising key structural genes and transcription factors tightly associated with starch-related metabolites. In particular, genes involved in sucrose cleavage and ADP-glucose metabolism, together with trehalose-6-phosphate synthase (TPS) and UDP-glucose-associated pathways, emerged as critical nodes linking carbon flux to starch biosynthesis. Correlation network analysis suggested that AP2/ERF-, MYB-, and bHLH-type transcription factors modulate these pathways by coordinating structural gene expression and metabolic flux distribution. Collectively, our study establishes a transcriptional-metabolic framework for starch accumulation in tetraploid potato, highlighting the central role of carbon allocation and signaling intermediates in shaping starch content, and providing candidate targets for molecular breeding and genome editing.

Solanum tuberosum↗

PubMed2005

Proteomics in nutrition and health.

Proteomics, the comprehensive analysis of a protein complement in a cell, tissue or biological fluid at a given time, has been enabled by quantum leaps in mass spectrometric technology, which allowed identification of large, involatile biomolecules. Over the last two decades, this discipline evolved from the sole delivery of protein identities to a platform, which reveals clues to function through e.g. characterisation of protein modifications and interactions as well as through quantitative proteomics, i.e. the global comparison of protein amounts between two defined biological states. Proteomics is an integral part and key player in the family of -omic disciplines as there are genomics (gene analysis), transcriptomics (gene expression analysis) and metabolomics (metabolite profiling). Considering the complexity, dynamics and protein concentration range of any given proteome, proteomics is the most challenging -omic discipline and requires the most sophisticated analysis pipeline. Proteomics represents an established technology in the pharmaceutical industry mainly for biomarker and drug target discovery. The potential of proteomics for research in the food industry is increasingly being recognised and the employment of proteomic approaches to nutrition and health issues is now emerging. This review summarizes (i) major technological achievements in mass spectrometry and proteomics, (ii) deliverables of proteomics in the context of nutrition and health, and (iii) applications of proteomics, and -- if appropriate -- transcriptomics to the research fields of digestive health, obesity and diabetes, immunity and allergy, probiotics, milk, and food preference.

Complex Mixtures↗

PubMed2026

OmicsPred as a centralised resource for genetic prediction of multi-omic traits.

Genetic prediction of multi-omic data has emerged as a cost-effective alternative to direct omics profiling, particularly useful for identifying molecular features associated with disease susceptibility. However, despite its popularity, multi-omic imputation models are fragmented across studies, hindering findability, accessibility, interoperability and re-use. To address this, we developed OmicsPred (https://www.omicspred.org), a centralised platform for the deposition and dissemination of genetic prediction models of multi-omic traits. OmicsPred unifies the most commonly used molecular imputation models (e.g. from PredictDB) and other published studies totalling 3,339,469 prediction models spanning transcriptomic, proteomic, and metabolomic traits (as of May 2026). Each model is accompanied by metadata describing score development and predictive performance, and distributed in formats compatible with popular analytic tools, such as PGS Catalog Calculator and MetaXcan. To demonstrate the utility of the resource for systematic target discovery, we perform a multi-omic phenome-wide association analysis in Million Veterans Program data.

Journal Article↗

PubMed2024

Omics approaches to unravel insecticide resistance mechanism in Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae).

Bemisia tabaci (Gennadius) whitefly (BtWf) is an invasive pest that has already spread worldwide and caused major crop losses. Numerous strategies have been implemented to control their infestation, including the use of insecticides. However, prolonged insecticide exposures have evolved BtWf to resist these chemicals. Such resistance mechanism is known to be regulated at the molecular level and systems biology omics approaches could shed some light on understanding this regulation wholistically. In this review, we discuss the use of various omics techniques (genomics, transcriptomics, proteomics, and metabolomics) to unravel the mechanism of insecticide resistance in BtWf. We summarize key genes, enzymes, and metabolic regulation that are associated with the resistance mechanism and review their impact on BtWf resistance. Evidently, key enzymes involved in the detoxification system such as cytochrome P450 (CYP), glutathione S-transferases (GST), carboxylesterases (COE), UDP-glucuronosyltransferases (UGT), and ATP binding cassette transporters (ABC) family played key roles in the resistance. These genes/proteins can then serve as the foundation for other targeted techniques, such as gene silencing techniques using RNA interference and CRISPR. In the future, such techniques will be useful to knock down detoxifying genes and crucial neutralizing enzymes involved in the resistance mechanism, which could lead to solutions for coping against BtWf infestation.

Hemiptera↗

PubMed2025

Exogenous BMI1 expression aggravates oral squamous cell carcinomas in tongue epithelia.

Oral squamous cell carcinoma (OSCC) is characterized by aggressiveness and a poor prognosis, in part because most patients are diagnosed during the later stages of the disease. B cell-specific Moloney murine leukemia virus integration site 1 (BMI1), part of polycomb repressive complex 1 (PRC1), is a key transcription factor overexpressed in OSCC. Although increased BMI1 has been linked to tumor formation in mouse models of the disease, the molecular mechanisms have not been elucidated. Here we used a transgenic mouse line (KrTB) that selectively overexpresses BMI1 in the tongue basal epithelial stem cells (SCs) to delineate BMI1 actions during oral tumorigenesis. By tumor pathological classification after 4-nitroquinoline 1-oxide (4-NQO)-induced carcinogenesis we detected more severe tumors in mice with ectopic BMI1 expression. Genome-wide transcriptomics indicated that mRNAs associated with human OSCC, including SOX9, HIF1A, MMP9, INHBB, and MYOF, were further increased by ectopic BMI1 expression in murine tongue epithelia. mRNAs encoding multiple metabolic targets, such as SLC2A1 (GLUT1), PKM, LDHA, and HK2, were also increased upon BMI1 overexpression in 4-NQO-treated tongue epithelia. Furthermore, we detected BMI1, SOX9, and GLUT1 proteins in the infiltrating cells of invasion fronts identified by markers of invasive SCCs. Finally, metabolomic data show that BMI1 overexpression in tongue epithelia promotes glycolysis during 4-NQO-induced carcinogenesis. Thus, our data demonstrate that BMI1 causes OSCC cells to alter cell metabolism, as changes in many of these transcripts are linked to increased glycolysis and metabolic reprograming that occurs during carcinogenesis.

Animals↗

PubMed2025

2,3-Pyridinedicarboxylate Is Associated with Shorter Recurrence-Free Survival in Patients with Hypopharyngeal Squamous Cell Carcinoma.

UNLABELLED: Introduction: Metabolites are associated with the biology of cancer; however, no metabolites related to prognosis have been identified in head and neck cancer. This study aimed to identify metabolites associated with prognosis in patients with hypopharyngeal squamous cell carcinoma (HPSCC). METHODS: Fifty-two patients who underwent surgery for HPSCC were included and randomly divided into test and validation cohorts of 26 patients each for further metabolome analysis using capillary electrophoresis/mass spectrometry on tumor and non-tumor tissues of the hypopharynx. Twenty-two patients who received adjuvant therapy after surgery were included. The receiver operating characteristic (ROC) and univariate and multivariate analyses were used to explore the relationship between recurrence-free survival (RFS), clinicopathological factors, and differentiated metabolites. RESULTS: ROC analysis revealed six metabolites significantly associated with RFS in both cohorts, and multivariate analysis indicated that 2,3-pyridinedicarboxylate was a significantly independent poorer prognostic factor in the cohorts including patients with HPSCC without any adjuvant therapies (p = 0.017). CONCLUSION: 2,3-Pyridinedicarboxylate, involved in NAD+ metabolism and genomic stability, suggests the possibility of developing molecular-targeted drugs for the production of metabolites related to prognosis. This study identifies novel prognostic metabolites and their associated metabolic pathways in HPSCC, highlighting potential therapeutic targets for treatment. .

Humans↗