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PubMed2026

Multi-omics evidence reveals robust airborne-human resistome connectivity driven by high-risk ARGs and mediated by Staphylococcus.

Airborne microbiomes are considered an important source of human antimicrobial resistance (AMR) exposure, yet multi-omics evidence linking airborne and human nasal resistomes remains limited. Here, we integrated metagenomic sequencing and whole-genome sequencing of antibiotic-resistant Staphylococcus isolates to investigate the connectivity between air and human nasal resistomes in dairy farm environments. Metagenomic taxonomic profiling showed that Staphylococcus was prominent in total suspended particles (TSP) and consistently detected across all samples. Among environmental reservoirs, TSP resistomes exhibited the strongest similarity to human nasal resistomes. This connectivity was supported by multiple lines of evidence, including highly similar resistome profiles, extensive homologous antibiotic resistance gene (ARG) pairs, strain-level similarity of resistant Staphylococcus isolates, and conserved mobile ARG genetic contexts. Notably, this connectivity was primarily driven by high-risk ARGs, while Staphylococcus was frequently associated with mobile ARGs and represented the only shared pathogenic genomes carrying both ARGs and virulence factor genes between airborne and nasal samples. Although lower ARG diversity, nasal resistomes exhibited higher ARG burden, risk scores, antibiotic-resistant bacterial genome abundance, and prevalence of resistant Staphylococcus. Occupational exposure further increased total and high-risk ARG burdens among farm workers. Together, these findings indicate that TSP can serve as an important route of occupational AMR exposure, with high-risk ARGs and Staphylococcus contributing to connectivity between airborne and nasal resistomes. Incorporating the host microbiome may therefore provide a more complete assessment of human-associated AMR exposure within a One Health framework.

Airborneresistome↗

PubMed2026

Multi-omics insights into aroma formation in congou black tea during fermentation.

This study used multi-omics technologies to analyze aroma formation during Congou black tea fermentation. Volatile compounds were analyzed by headspace solid phase microextraction coupled with gas chromatography mass spectrometry using two columns of different polarity. Fermentation increased total volatile normalized peak area fivefold, with alcohols, aldehydes, and acids increasing over sevenfold. 29 differential metabolites were screened, including amino acid derived phenylacetaldehyde, phenylethanol, and 2-methylbutanal; fatty acid derived (E,E)-2,4-heptadienal, hexanal, and 1-hexanol; and isoprenoid derived linalool, geraniol, and beta ionone. Transcriptomic, proteomic, and enzyme analyses revealed that biosynthesis contributed to early accumulation of amino acid and isoprenoid derived aromas, whereas ortho quinone mediated Strecker degradation and free radical induced fatty acid auto oxidation dominated generation of amino and fatty acid derived aromas during middle and late fermentation. In conclusion, aroma formation during fermentation results from biosynthesis and non-enzymatic oxidation, with the latter possibly dominating amino and fatty acid derived aromas.

Fermentation↗

PubMed2025

Dual genetic loci and flavonoid metabolism orchestrate fruiting body coloration in Flammulina filiformis: a multi-omic roadmap for fungal pigmentation.

BACKGROUND: The fruiting bodies of macrofungi exhibit diverse coloration, traditionally attributed to melanin and carotenoid biosynthesis. This study is the first to reveal that flavonoids, rather than these classical pigments, are the predominant contributors to yellow pigmentation in the Flammulina filiformis. OBJECTIVE: To uncover the genetic basis and key regulatory genes involved in pigment formation in F. filiformis fruiting bodies, and to establish a model framework for studying color genetics in macrofungi. METHODS: Metabolomic profiling was conducted on yellow and white F. filiformis fruiting bodies to identify key pigment components. A segregating population was constructed, followed by integrated multi-omics analyses-including bulk segregant analysis (BSA), genome-wide association study (GWAS), and transcriptomics-to map regulatory loci and candidate genes. Functional roles were validated via genetic transformation and protein structural modeling. RESULTS: Flavonoid accumulation was identified as the biochemical hallmark of pigmented fruiting bodies. Genetic analysis revealed a dual regulatory mechanism: a qualitative locus governing pigmentation presence and a quantitative trait determining color intensity. Combined BSA and GWAS pinpointed a major locus, Ffcrs, within a recombination-suppressed region. Transcriptomic analysis identified two key regulators, Ffakr (a transcriptional activator) and Ffpal (encoding phenylalanine ammonia-lyase). Functional verification via transformation, structural modeling, and metabolite profiling in transgenic lines confirmed their essential roles in flavonoid biosynthesis and pigmentation. CONCLUSION: This study uncovers a flavonoid-based pigmentation mechanism in F. filiformis and elucidates a complex genetic architecture shaped by both qualitative and quantitative loci, providing a new paradigm for understanding pigment formation in macrofungi. The identified regulatory factors establish a molecular foundation for the precise manipulation of economically important pigmentation traits in edible mushroom.

Flavonoids↗

PubMed2026

Polystyrene microplastics induce auditory neurotoxicity in mammals: Integrated multi-omics profiling reveals oxidative damage and synaptic molecular dysregulation.

Microplastics (MPs) are ubiquitous environmental pollutants, yet their neurotoxic effects on the auditory system remain poorly understood. This study develops an integrated multi-level analytical framework combining auditory neurophysiology, behavioral assessment, tissue biochemistry, transcriptomics, and proteomics to investigate polystyrene (PS)-MPs-induced auditory neurotoxicity in rats. PS-MPs infiltrate the auditory system and significantly impair auditory processing, with central dysfunction emerging earlier and more prominently than peripheral alterations. Multi-omics analyses reveal coordinated suppression of glutamatergic synapse and Wnt signaling pathways in the cochlear nucleus. Mechanistically, PS-MPs perturb the crosstalk between glutamatergic synaptic and Wnt signaling, promoting AMPA receptor (AMPAR) internalization and potentially affecting synaptic plasticity-related processes and neuronal responsiveness. In parallel, PS-MPs trigger oxidative stress, apoptosis, and glial activation, reflecting pronounced neuroinflammatory and redox imbalance. In primary cochlear nucleus neurons (PCNNs), these mechanisms were further validated in vitro, where activation of Wnt signaling by Wnt3a significantly alleviated oxidative injury and reduced AMPAR internalization. Collectively, these findings provide comprehensive preclinical evidence for the neurotoxic potential of MPs and reveal a previously unrecognized PS-MPs-induced auditory neurotoxicity, although further studies are needed for human relevance. Results from the rat model further implicate Wnt-mediated signaling as a potential modulatory pathway underlying MPs-induced synaptic molecular alterations and redox dysfunction.

Animals↗

PubMed2026

Multi-omics integration and colocalization analyses prioritize candidate molecular loci associated with hypothermia.

BACKGROUND: Hypothermia is a life-threatening condition lacking specific pharmacological treatments. This study aimed to prioritize genetically supported molecular loci associated with hypothermia and to explore their pharmacological tractability using multi-omics data. METHODS: Initially, 2532 druggable genes were curated from the Drug-Gene Interaction Database and established literature. These were cross-referenced with cis-eQTL and cis-pQTL datasets, encompassing 870,655 and 114,281 SNPs for blood, respectively, alongside 2379 shared SNPs across adipose, skeletal muscle, and heart tissues. Matched instrumental variables were integrated with hypothermia GWAS summary statistics for two-sample Mendelian randomization (MR) and Bayesian colocalization. Transcriptomic differential expression analysis (DEA) was subsequently conducted as an exploratory analysis of cold-exposure-associated expression changes. Database-derived compound annotations were systematically re-evaluated according to target specificity, established pharmacological mechanism, and concordance with the direction of the MR estimates. RESULTS: Among 671 gene-level MR tests, 36 genes reached nominal significance, whereas only ABCC8 remained significant after FDR correction. Colocalization was evaluable for 8 of these 36 genes, and 4 loci (COL18A1, SLC1A7, ADIPOQ, and MERTK) met the prespecified PP.H4>0.90 threshold. The remaining 28 loci were not evaluable because sufficient overlapping regional variants were unavailable after harmonization. Transcriptomic analysis identified altered expression of SLC1A3 and SLCO4A1 under cold exposure, although these findings did not directly validate the colocalization-supported loci. Re-evaluation of database-derived compound annotations did not identify any direct, selective, and directionally concordant drug-repurposing candidate for hypothermia. CONCLUSIONS: COL18A1, SLC1A7, ADIPOQ, and MERTK showed colocalization support among the 8 evaluable nominal MR-associated loci. Because colocalization coverage was limited, these genes should be regarded as preliminary candidate loci rather than established therapeutic targets. The pharmacological annotations were indirect, non-selective, unsupported, or directionally inconsistent and should be interpreted solely as hypothesis-generating information.

Bayesian colocalization↗

PubMed2026

Is impulsivity simply a failure of self-control? Evidence based on multi-omics analyses of genomics, metabolomics and brain imaging.

High impulsivity-a hallmark of various adverse life outcomes such as substance abuse, impulsive buying, violence, and crime-has typically been considered as a failure of self-control. However, is impulsivity simply a failure of self-control? To address this issue, we employed multi-omics combined with brain imaging approach in a large-scale sample (Nbrain imaging=1524, Ngenomics=835, Nmetabolomics=946) to elucidate the relationship between impulsivity and self-control. Mendelian randomization showed a bidirectional association between impulsivity and self-control, suggesting that they influenced each other. Partial least squares analysis highlighted that self-control primarily implicates the frontal lobe regions (e.g., superior frontal gyrus), whereas impulsivity involves the amygdala, insula, and basal ganglia. The cerebellum, superior frontal gyrus, and middle frontal gyrus were identified as shared areas in impulsivity and self-control. Furthermore, gene-based association analysis identified heterochromatin protein 1 binding protein 3 as specifically related to impulsivity, while pathway enrichment analysis demonstrated that arginine and proline metabolism was a common metabolic pathway associated with both impulsivity and self-control. Overall findings demonstrate that impulsivity and self-control involve both shared and distinct brain regions, genetic and metabolic foundations. The brain imaging results suggest that impulsivity is related not only to self-control-related processes but also to the motivation to pursue rewards. Together, this large-scale integrative study firstly provides a side-by-side map of genomic, metabolic, and limbic-network signatures of impulsivity distinct from self-control, offering a foundation for mechanism-driven biomarker and intervention research in maladaptive impulsivity.

Impulsive Behavior↗

PubMed2026

Multi-omics identification of ZFPM2 and CD44 as key candidates for testicular size in sheep.

Testicular size is a key determinant of ram fertility, yet its genetic architecture in sheep remains poorly understood. Crossbred sheep exhibit substantial testicular developmental variation and serve as ideal models for screening fertility-related genes. Here, we performed whole-genome sequencing (WGS)-based genome-wide association study (GWAS) on 115 rams, including seven crossbred populations (each derived from a distinct sire breed crossed with Hu sheep) and a purebred Hu sheep population. We identified two variants within ZFPM2, including an intronic single nucleotide polymorphism (SNP) rs421073404 and a missense SNP rs1086332841, both significantly correlated with testis weight, length, and width. Importantly, these variants exerted testis-specific effects, consistent with their weak correlation with body weight (r < 0.2). Genomic selection scans (FST and π-ratio) between rams with large (>150 g/side) and small (<75 g/side) testes revealed multiple divergent genomic regions, with prominent haplotype differentiation at the CD44 locus on chromosome 15. Notably, two linked missense variants (rs160734053 and rs414318703) in CD44 exerted opposing effects on testicular size, suggesting allelic heterogeneity at this locus. Integrative RNA-seq and ATAC-seq across 0-12 months further uncovered prepubertal stage-specific expression and chromatin accessibility patterns of ZFPM2 and CD44, providing mechanistic insights into their regulatory roles. Collectively, this study provides candidate SNPs for sheep marker-assisted selection and multi-omic evidence for dissecting the genetic basis of testicular development in ovine breeding.

Animals↗

PubMed2024

Relationship between inflammation/immunity and epilepsy: A multi-omics mendelian randomization study integrating GWAS, eQTL, and mQTL data.

OBJECTIVES: Increasing evidence suggests that activated innate/adaptive immunity induces an inflammatory response, thereby participating in epileptogenesis. However, the biological explanation of inflammation/immunity as a potential cause for epilepsy remains largely unknown. This research aimed to determine the causal effects of inflammation/immune-related genes in epilepsy based on multi-omics mendelian randomization (MR). METHODS: We employed summary-data-based MR (SMR) approach to combine GWAS for epilepsy (12,891 cases and 312,803 control) with gene expression quantitative trait loci (cis-eQTL, 31,684 participants) and DNA methylation QTL (cis-mQTL, 1,980 participants) data. Five additional MR methods were then used for sensitivity analyses to confirm the reliability of causal associations. In addition, enrichment analysis of key genes was conducted to provide insight into the biological functions of epilepsy risk variants. RESULTS: A total of 386 inflammation/immune-related genes were selected for further analyses. Primary SMR analysis indicated that 37 DNA methylation sites and six genes regulated by them had potential causal relationship with epilepsy. MR analysis further refined the results, identifying three genes that had a causal effect on epilepsy. Notably, VEGFA (OR: 0.925; 95 % CI: 0.862-0.994) expression was negatively correlated with epilepsy risk, whereas IL16 (OR: 1.076; 95 % CI: 1.028-1.126) and HLA-DPA1 (OR: 1.041; 95 % CI: 1.009-1.074) expressions were positively associated with epilepsy risk. Functional enrichment analysis revealed that the identified genes were involved in GO-BP terms related to VEGF activation signaling and chemotaxis regulation. CONCLUSION: This analysis confirms the causal role of inflammation/immunity in epilepsy, and the identified candidate genes provide clues for drug development in clinical practice.

Humans↗

PubMed2002

Toxicology and genetic toxicology in the new era of "toxicogenomics": impact of "-omics" technologies.

The unprecedented advances in molecular biology during the last two decades have resulted in a dramatic increase in knowledge about gene structure and function, an immense database of genetic sequence information, and an impressive set of efficient new technologies for monitoring genetic sequences, genetic variation, and global functional gene expression. These advances have led to a new sub-discipline of toxicology: "toxicogenomics". We define toxicogenomics as "the study of the relationship between the structure and activity of the genome (the cellular complement of genes) and the adverse biological effects of exogenous agents". This broad definition encompasses most of the variations in the current usage of this term, and in its broadest sense includes studies of the cellular products controlled by the genome (messenger RNAs, proteins, metabolites, etc.). The new "global" methods of measuring families of cellular molecules, such as RNA, proteins, and intermediary metabolites have been termed "-omic" technologies, based on their ability to characterize all, or most, members of a family of molecules in a single analysis. With these new tools, we can now obtain complete assessments of the functional activity of biochemical pathways, and of the structural genetic (sequence) differences among individuals and species, that were previously unattainable. These powerful new methods of high-throughput and multi-endpoint analysis include gene expression arrays that will soon permit the simultaneous measurement of the expression of all human genes on a single "chip". Likewise, there are powerful new methods for protein analysis (proteomics: the study of the complement of proteins in the cell) and for analysis of cellular small molecules (metabonomics: the study of the cellular metabolites formed and degraded under genetic control). This will likely be extended in the near future to other important classes of biomolecules such as lipids, carbohydrates, etc. These assays provide a general capability for global assessment of many classes of cellular molecules, providing new approaches to assessing functional cellular alterations. These new methods have already facilitated significant advances in our understanding of the molecular responses to cell and tissue damage, and of perturbations in functional cellular systems. As a result of this rapidly changing scientific environment, regulatory and industrial toxicology practice is poised to undergo dramatic change during the next decade. These advances present exciting opportunities for improved methods of identifying and evaluating potential human and environmental toxicants, and of monitoring the effects of exposures to these toxicants. These advances also present distinct challenges. For example, the significance of specific changes and the performance characteristics of new methods must be fully understood to avoid misinterpretation of data that could lead to inappropriate conclusions about the toxicity of a chemical or a mechanism of action. We discuss the likely impact of these advances on the fields of general and genetic toxicology, and risk assessment. We anticipate that these new technologies will (1) lead to new families of biomarkers that permit characterization and efficient monitoring of cellular perturbations, (2) provide an increased understanding of the influence of genetic variation on toxicological outcomes, and (3) allow definition of environmental causes of genetic alterations and their relationship to human disease. The broad application of these new approaches will likely erase the current distinctions among the fields of toxicology, pathology, genetic toxicology, and molecular genetics. Instead, a new integrated approach will likely emerge that involves a comprehensive understanding of genetic control of cellular functions, and of cellular responses to alterations in normal molecular structure and function.

Animals↗

PubMed2002

"Omic" approaches for unraveling signaling networks.

Signaling pathways are crucial for cell differentiation and response to cellular environments. Recently, a large number of approaches for the global analysis of genes and proteins have been described. These have provided important new insights into the components of different pathways and the molecular and cellular responses of these pathways. This review covers genomic and proteomic (collectively referred to as "omic") approaches for the global analysis of cell signaling, including gene expression profiling and analysis, protein-protein interaction methods, protein microarrays, mass spectroscopy and gene-disruption and engineering approaches.

Animals↗

PubMed2002

'Omic' and hypothesis-driven research in the molecular pharmacology of cancer.

Given the layered, evolutionary complexity of biological systems, it will not be possible to understand them comprehensively on the basis of hypothesis-driven research alone. Likewise, it will not be possible to do so solely through 'omic' studies of genes, proteins and other molecules in aggregate. The two modes of research are complementary and synergistic. The twin complexities of cancer biology and drug discovery demand such synergy as a basis for the next generation of oncopharmacomic research.

Animals↗

PubMed2026

Integrative multi-omics identifies DOC2A as a novel pharmacological target for bipolar disorder.

BACKGROUND: Current bipolar disorder (BD) therapies suffer from limited efficacy and adverse effects, necessitating mechanistically grounded targets. METHODS: We integrated BD genome-wide association study data (158,036 cases; 2,796,499 controls) with brain proteomics (ROSMAP and Banner dorsolateral prefrontal cortex, n = 376 and 152) to perform proteome-wide association studies (PWAS). Bayesian colocalization and summary-data-based Mendelian randomization (SMR) prioritized causal genes. Cell-type-specific transcriptomics validated dysregulation in iPSC-derived neurons, astrocytes, and postmortem hippocampus/prefrontal cortex. Weighted gene co-expression networks (WGCNAs), functional enrichment, and molecular docking assessed functional pathways and druggability. RESULTS: PWAS identified eight BD-associated genes (false discovery rate < 0.05), with DOC2A emerging as the top candidate. Colocalization (H4 > 0.8) and SMR supported a causal association of DOC2A with BD, with no pleiotropy (heterogeneity in dependent instruments P > 0.01); DOC2A expression decreased in BD across neurons (P = 4.26 × 10-2), astrocytes (P = 2.09 × 10-2), hippocampus (P = 9.80 × 10-3, t = -2.738), and prefrontal cortex (P = 1.44 × 10-2, t = -2.580); WGCNA positioned DOC2A as a key regulator (module membership/gene significance P < 0.05) of co-expression networks enriched for BD-associated processes including neurotransmitter secretion and postsynaptic actin cytoskeleton organization (P < 0.05); molecular docking revealed favorable-affinity binding (ΔG < -4 kcal/mol) between DOC2A and BD-related drugs and neuroprotective compounds. CONCLUSIONS: Our convergent multi-omics framework highlights DOC2A dysregulation as a key contributor to synaptic dysfunction in BD and nominates it as a promising therapeutic target. The demonstrated interaction with existing neuroactive compounds provides immediate translational avenues.

Bipolar Disorder↗

PubMed2005

From XML to RDF: how semantic web technologies will change the design of 'omic' standards.

With the ongoing rapid increase in both volume and diversity of 'omic' data (genomics, transcriptomics, proteomics, and others), the development and adoption of data standards is of paramount importance to realize the promise of systems biology. A recent trend in data standard development has been to use extensible markup language (XML) as the preferred mechanism to define data representations. But as illustrated here with a few examples from proteomics data, the syntactic and document-centric XML cannot achieve the level of interoperability required by the highly dynamic and integrated bioinformatics applications. In the present article, we discuss why semantic web technologies, as recommended by the World Wide Web consortium (W3C), expand current data standard technology for biological data representation and management.

Algorithms↗

PubMed2026

Clinical translation of senescence-related pan-cancer multi-omics: tools for assessment and immunotherapy prediction.

Cellular senescence (CS) exerts dual roles in tumorigenesis, yet its pan-cancer molecular characteristics and clinical value remain unclear, hindering its translation to oncology and personalized therapy. To address the lack of specific and universal tools for senescence assessment and immunotherapy response prediction, this study systematically analyzed 1259 CS-related genes from the CellAge database across 31 cancer types by integrating multi-omics data, including bulk RNA-seq, single-cell/spatial transcriptomics, and CRISPR screening. We developed a rank-based algorithm SenScoreR (publicly available at https://gxhub.shinyapps.io/SenScoreR/ ) for senescence quantification, validated with 10 independent datasets, and constructed a machine learning-based predictive model CS.Sig for immunotherapy response. Results showed that tumors had significantly lower Rank-based Senescence Score (RSS) than normal tissues across 31 cancers (average diagnostic AUC = 0.895), with low RSS linked to poor survival; high RSS correlated with reduced genomic instability, enriched CD8⁺ T/NK cell/macrophage infiltration, upregulated PD-L1 expression, and elevated immune cytolytic activity. CS.Sig demonstrated robust performance in predicting ICI response (AUC = 0.716 across 10 cohorts), outperforming 13 existing signatures, while CRISPR screening identified 17 senescence-related targets (e.g., CEP55, PPP1CC) whose knockout enhanced anti-tumor immunity. Our findings clarify CS's role in maintaining tumor genomic stability and shaping immune microenvironments, and the developed SenScoreR, CS.Sig, and identified targets bridge basic CS research with clinical oncology, providing a translational resource and hypothesis basis for future experimental and clinical validation.

Journal Article↗

PubMed2025

Longitudinal multi-omics in alpha-synuclein Drosophila model discriminates disease- from age-associated pathologies in Parkinson's disease.

Parkinson's disease (PD) starts decades before symptoms appear, usually in the later decades of life, when age-related changes are occurring. To identify molecular changes early in the disease course and distinguish PD pathologies from aging, we generated Drosophila expressing alpha-synuclein (αSyn) in neurons and performed longitudinal bulk transcriptomics and proteomics on brains at six time points across the lifespan and compared the data to healthy control flies as well as human post-mortem brain datasets. We found that translational and energy metabolism pathways were downregulated in αSyn flies at the earliest timepoints; comparison with the aged control flies suggests that elevated αSyn accelerates changes associated with normal aging. Unexpectedly, single-cell analysis at a mid-disease stage revealed that neurons upregulate protein synthesis and nonsense-mediated decay, while glia drive their overall downregulation. Longitudinal multi-omics approaches in animal models can thus help elucidate the molecular cascades underlying neurodegeneration vs. aging and co-pathologies.

Journal Article↗

PubMed2026

Integrative multi-omics analysis of metabolite-protein interaction networks across different stages of coronary heart disease.

To elucidate the molecular characteristics of synergistic interactions across the clinical stages of coronary heart disease (CHD)-specifically stable angina pectoris (SAP), unstable angina pectoris (UAP), and acute myocardial infarction (AMI)-through integrated metabolomic and proteomic analyses. Based on a cohort including SAP, UAP, AMI, and healthy controls, metabolomic and proteomic analyses were performed to identify differentially expressed molecules, followed by KEGG pathway enrichment analysis. Pathways co-enriched across both omics platforms were selected to construct metabolite-protein interaction networks. The number of pathways co-enriched in both metabolomic and proteomic analyses increased markedly with disease stage. Only two pathways (histidine metabolism and arginine and proline metabolism) were identified in the SAP stage; this number increased to five in the UAP stage (including ferroptosis and efferocytosis) and expanded to 25 in the AMI stage, encompassing three major functional modules: immune inflammation, metabolic reprogramming, and cell signaling. The core network exhibited a stepwise increase in connectivity, shifting from a sparse structure in the SAP stage to a highly interconnected architecture in the AMI stage, with L-glutamate and KNG1 identified as the central hubs in this cross-sectional network. In addition, CNDP1 exhibited a stage-dependent functional transition, shifting from downregulation in SAP to upregulation in AMI. In this cross-sectional analysis, metabolic dysregulation and immune activation exhibited stepwise increases in interconnectivity across the SAP, UAP, and AMI groups, with the most extensive crosstalk observed in the AMI stage-a network configuration consistent with a tightly coupled "molecular storm". These findings provide novel insights into stage-associated molecular signatures of CHD and identify candidate hub molecules for stage-oriented therapeutic investigation.

Humans↗

PubMed2006

Evaluation of a non-targeted "omic" approach in the safety assessment of genetically modified plants.

Genetically modified plants must be approved before release in the European Union, and the approval is generally based upon a comparison of various characteristics between the transgenic plant and a conventional counterpart. As a case study, focusing on safety assessment of genetically modified plants, we here report the development and characterisation of six independently transformed ARABIDOPSIS THALIANA lines modified in the flavonoid biosynthesis. Analyses of integration events and comparative analysis for characterisation of the intended effects were performed by PCR, quantitative Real-time PCR, and High Performance Liquid Chromatography. Analysis by cDNA microarray was used as a non-targeted approach for the identification of potential unintended effects caused by the transformation. The results revealed that, although the transgenic lines possessed different types of integration events, no unintended effects were identified. However, we found that the majority of genes showing differential expression were identified as stress-related genes and that environmental conditions had a large impact on the expression of several genes, proteins, and metabolites. We suggest that the microarray approach has the potential to become a useful tool for screening of unintended effects, but state that it is crucial to have substantial information on the natural variation in traditional crops in order to be able to interpret "omics" data correctly within the framework of food safety assessment strategies of novel plant varieties, including genetically modified plant varieties.

Arabidopsis↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗