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PubMed2026

Transcriptomic and proteomic signatures underlying nymphal adaptation and foam production in the forage pest Mahanarva spectabilis.

The spittlebug Mahanarva spectabilis (Distant, 1909) (Hemiptera: Cercopidae) is an important pest of forage grasses in South America, where its nymphs cause pasture damage by feeding on xylem sap and producing a characteristic foam that protects them against environmental stressors. To investigate the molecular basis of this adaptation, we integrated RNA-seq analysis of nymphs with LC-MS/MS proteomics of the Batelli gland, the primary source of foam secretion. De novo assembly of 100,666 unigenes revealed broad functional diversity, with strong representation of detoxification enzymes (CYP450s, GSTs, UGTs, carboxylesterases), transporters and ion pumps, cuticle proteins, and stress- and immunity-related genes. Nearly 16% of loci exhibited alternative splicing, particularly within detoxification, chemosensory and osmoregulatory gene families, highlighting evidence of transcriptomic variability. Signal peptide and secreted protein predictions identified 168 high-confidence candidate secreted proteins, including detoxification enzymes, proteases, structural proteins and immune-related factors, several of which are consistent with antimicrobial and surfactant-related functions. Proteomic profiling of the Batelli gland confirmed 500 proteins, enriched in chaperones, metabolic enzymes, detoxification pathways and osmoregulatory components, with the most abundant proteins corresponding to Hsp70 chaperones, ATP synthases, cuticle proteins and carbonic anhydrases. Together, these results provide an integrative transcriptomic and proteomic overview for M. spectabilis nymphs, highlighting genes and proteins associated with xylem feeding, foam production and responses potentially related to environmental stress tolerance. This comprehensive dataset not only advances the understanding of spittlebug biology but also identifies candidate molecular targets that may inform innovative strategies for controlling nymphal stages and mitigating spittlebug damage in forage systems.

Animals↗

PubMed2026

Comparison of Proteomic Analysis of Cerebrospinal Fluid From Neurological Patients With and Without Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterised by progressive muscle weakness in both bulbar and extremity muscles, leading to a diverse clinical phenotype with motor and non-motor symptoms. Approximately 85% of ALS cases are sporadic (sALS), while the remaining 10%-15% are familial (fALS). Biological biomarkers of sporadic ALS remain poorly understood, hindering precise patient screening, delaying diagnosis and negatively affecting prognosis. This study aims to identify potential proteomic biomarkers by comparing the cerebrospinal fluid (CSF) of sALS patients with that of patients suffering from other neurological diseases. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used for proteomic profiling of CSF samples from 24 sALS patients and 26 patients with other neurological diseases. The complete protein expression profiles were compared using a two-tailed Student's t-test, with a p < 0.05 considered statistically significant with additional FDR correction at the 0.1 level. Proteomic analysis of CSF samples identified significant quantitative changes in 96 proteins with threshold p < 0.05 and 74 proteins with FDR < 0.1 between sALS and non-ALS patients, including alterations in proteins associated with neurodegenerative processes, such as amyloid precursor proteins and inflammatory markers. CSF proteomic analysis reveals altered inflammatory and neurodegenerative metabolic pathways, providing valuable insights into the proteomic landscape of sALS. Several dysregulated proteins were consistent with the disease mechanisms highlighted in previous studies. These findings represent a step forward in developing personalised approaches for diagnosing and managing the disease.

Humans↗

PubMed2026

Comparative Genome-Wide Association Studies of Metabolites and Grain-Related Traits in Common Wheat.

The metabolome is highly diverse and the closest layer to phenotype; therefore, it is commonly regarded as a bridge between the genome and phenome in plants. Here, we performed large-scale metabolome analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 33 grain-related traits in a diverse panel of natural accessions and a recombinant inbred line (RIL) population. We identified a new network of 2286 associations between 947 metabolites and 33 grain-related traits. Systematic integration of metabolic genome-wide association study (mGWAS) and metabolic quantitative trait locus (mQTL) analyses identified 33 566 significant single-nucleotide polymorphisms (SNPs) and 3128 mQTL. Thirteen annotated metabolites co-localized within a physical interval on 7A. Integration of metabolite-based and phenotype-based GWAS and QTL revealed an overlapped region for gibberellin A4 (GA4) content and grain roundness on 4A. Phenotyping of an ethyl methanesulfonate (EMS)-induced mutant confirmed the role of TaSDR in regulating GA4 content and grain morphology. These findings provide novel insights into the metabolic pathways influencing key grain-related traits and advance our understanding of the complex molecular mechanisms regulating grain metabolites and phenotypes in wheat. The identified metabolic markers and candidate genes provide valuable targets for molecular breeding programs aimed at improving wheat yield and quality.

QTL↗

PubMed2026

Glutathione acts as an exometabolite that promotes growth recovery in fission yeast with defects in amino acid metabolism and cell polarity.

UNLABELLED: Microorganisms in nature form communities through diverse interactions, such as mutualism and competition, to adapt to their ecological environments. These interactions seem to be mediated by extracellular metabolites (exometabolites), yet the chemical and biological diversity underlying these processes remains largely unexplored. In this study, we examined the chemical basis of exometabolite-mediated interactions in the fission yeast Schizosaccharomyces pombe by a genome-wide screen employing 3,420 viable gene deletion mutants. We identified 37 strains that exhibited growth defects in monoculture on a minimal medium but exhibited growth recovery in the vicinity of wild-type colonies (co-culture), suggesting that exometabolites derived from wild-type cells compensated for the gene deletion. Both lipophilic and water-soluble fractions obtained by solvent partitioning of the wild-type culture supernatant promoted growth recovery. Among the 11 mutants rescued by the water-soluble fraction, 6 were cysteine auxotrophs, prompting analyses of thiol-containing metabolites by liquid chromatography-mass spectrometry (LC-MS), revealing the presence of glutathione (GSH) in the culture supernatant. GSH restored growth in most strains as a nutrient source. In contrast, GSH rescued cell morphology defects in the hob3∆ mutant, lacking the Bin/amphiphysin/Rvs (BAR) adaptor protein Hob3, through a mechanism independent of nutrition. This research advances understanding of exometabolite-mediated interactions in S. pombe by identifying GSH as an exometabolite that influences cellular processes and potentially shapes microbial communities. IMPORTANCE: Microorganisms secrete a wide range of metabolites that control microbial community behavior. These extracellular metabolites (exometabolites) include not only well-studied signaling molecules but also diverse primary and secondary metabolites, suggesting complex interactions among microbes. However, the molecular basis of these interactions remains poorly understood, partly due to challenges in detecting them experimentally. In this study, we surveyed exometabolites involved in cell-cell interactions in the model eukaryotic microorganism Schizosaccharomyces pombe. S. pombe releases a wide variety of metabolites outside the cells, including previously reported nitrogen signaling factors (NSFs) and glutathione (GSH) identified in this work. By analyzing gene deletion mutants whose growth is supported by extracellular GSH, we provide new insights into how secreted primary exometabolites compensate for specific genetic defects and influence cell physiology in microbial populations.

exometabolite↗

PubMed2026

Synaptic Proteome Divergence in the Prefrontal Cortex of Tame and Aggressive Red Foxes (Vulpes vulpes).

The biological mechanisms behind aggressive and affiliative behaviors are difficult to pinpoint. In the Farm-Fox Experiment, conventional foxes were selectively bred since 1959 in two different directions, one for tame and another for aggressive response to humans. The distinct differences in social behavior of tame, aggressive, and conventional populations are genetically based and the three populations live in conditions that control for factors that could impact social reactions, such as environment and social experiences. Genomic and transcriptomic studies of genetic differences among the fox populations have highlighted genes involved in synaptic processes in the prefrontal cortex. To investigate how the synaptic mechanisms differ between the three fox populations, synaptosomes were isolated from prefrontal and premotor cortex extracts of sixteen female foxes. Tandem mass tags with liquid chromatography tandem mass spectrometry (LC-MS) were used to identify and quantify the relative abundance of the proteins. The results were sorted into protein groups and compared between populations using a limma analysis to determine proteins with differential expression (DE). In the tame versus aggressive comparison, 174 protein groups were found to be DE, while only five were found in the conventional versus aggressive comparison. Most DE protein groups had lower fold expression in the aggressive population compared to tame and aggressive populations. ADGRB2 was found to be the most DE protein group, with 11-fold higher expression in aggressive foxes than in tame foxes. ADGRB2 was previously shown to affect depression-like behavior in mice and is involved in the vascular endothelial growth factor signaling pathway, that is known to influence neurogenesis. Enrichment analyses on the DE protein groups found gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were enriched in the tame versus aggressive comparison, including multiple, highly enriched terms involving ribosome and translation. Local translation at synapses plays an important role in synaptic plasticity and, as a result, can profoundly influence behavior. This study highlighted potential mechanisms that could underly the behavioral differences between tame and aggressive foxes.

Journal Article↗

PubMed2026

Machine Learning and Metabolomics to Characterize Warburg-Like Metabolic Subtypes in Human Retinal Endothelial Cells Exposed to Risk Factors Associated With Proliferative Diabetic Retinopathy.

PURPOSE: High glucose (HG), hypoxia (Hyp), and their combination are major risk factors for proliferative diabetic retinopathy (PDR). Although these conditions induce features of the Warburg-like metabolic reprogramming in human retinal endothelial cells (HRECs), it remains unclear whether they produce distinct metabolic and angiogenic subtypes. This study aimed to characterize the Warburg-like-associated metabolic heterogeneity induced by these PDR-related risk factors and evaluate the ability of supervised machine-learning models to distinguish these subtypes. METHODS: HRECs were cultured under normoglycemic, HG, Hyp (2% O2), and combined HG-Hyp conditions. Untargeted LC-MS/MS metabolomics quantified metabolites spanning carbohydrates, amino acids, nucleotides, and lipids. Principal component analysis (PCA) assessed overall metabolic variation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis identified metabolic pathways associated with angiogenesis. In vitro angiogenesis assays measured endothelial tube formation and branching. Nine supervised classifiers (decision tree, logistic regression, naïve Bayes, random forest, K-Nearest Neighbors, neural network, gradient boosting, AdaBoost, and Support Vector Machine) were trained on the highest-ranked metabolites selected by the Information Gain Ratio feature-ranking approach. Model performance was evaluated using 10-fold cross-validation, leave-one-out cross-validation (LOOCV), permutation testing, and a classifier stability analysis under biologically meaningful distributional shift using an independent chemically induced hypoxia model (CoCl2). RESULTS: PCA revealed partial separation of metabolic profiles across conditions, indicating different Warburg-like metabolic subtypes. The combined HG-Hyp condition exhibited enhanced angiogenic potential relative to either HG or Hyp alone. KEGG pathway enrichment analysis identified fatty acid biosynthesis and elongation among the most significantly enriched pathways in HRECs under combined HG-Hyp conditions, alongside amino sugar and nucleotide sugar metabolism, glycerophospholipid metabolism, the pentose phosphate pathway, and glycolysis/gluconeogenesis. Supervised machine-learning classifiers distinguished these metabolic subtypes, with AdaBoost and gradient Boosting showing the most balanced, reproducible performance across 10-fold cross-validation, LOOCV, and permutation testing, and remaining the most reliable classifiers under domain-shift testing (area under the curve = 0.88, P = 0.0061). CONCLUSIONS: In this exploratory analysis, HG, Hyp, and their combination drive metabolically and functionally distinct subtypes of Warburg-like metabolic reprogramming in HRECs, with HG-Hyp in combination producing a highly angiogenic phenotype. Boosting-based ensemble classifiers provide a promising framework for detecting these subtypes even under domain-shift conditions, warranting validation in larger independent datasets. TRANSLATIONAL RELEVANCE: Integrating metabolomics with machine-learning classification offers a strategy to identify Warburg-like metabolic subtypes in retinal endothelial cells, providing insights into angiogenic mechanisms and guiding the development of targeted diagnostics or therapeutics for PDR.

Humans↗

PubMed2026

Acinetobacter guillouiae, a lipolytic strain isolated from sludge capable of partially depolymerising polyethylene terephthalate: genomic, proteomic, and biochemical insights.

Acinetobacter guillouiae I-MWF was isolated by incubating amorphous polyethylene terephthalate (PET) film in sludge samples. The strain partially depolymerised PET powder with 11.3% crystallinity, as confirmed by FT-IR, HPLC-UV, and LC-MS analyses. Extracellular enzymes released terephthalic acid (TPA), mono(2-hydroxyethyl) terephthalate (MHET), and bis(2-hydroxyethyl) terephthalate (BHET). Genomic analysis identified 18 putative extracellular hydrolases, including lipases and esterases, each with a conserved catalytic triad. Proteomic profiling revealed expression of two triacylglycerol lipases and two additional lipase-family proteins when the strain was cultivated with PET or a PET-Tween 80 mixture. These enzymes were cloned in Escherichia coli, but most formed insoluble, inactive inclusion bodies, and one was not expressed. Molecular modelling highlighted structural features likely to influence their catalytic interaction with PET. Although the strain partially depolymerised PET powder, it was unable to grow on PET, TPA, or ethylene glycol, indicating that PET depolymerisation occurs as a side activity rather than supporting growth. Instead, A. guillouiae displayed strong lipolytic activity and a clear preference for lipid-based substrates, achieving its highest growth with Tween 80. A lipid transporter was also expressed under these conditions, suggesting adaptation to hydrocarbon-rich environments. These findings indicate that A. guillouiae I-MWF can mediate partial PET depolymerisation without assimilating the resulting monomers, while preferentially growing on lipid-like substrates.

Acinetobacter↗

PubMed2026

Untargeted-targeted metabolomics: energy metabolism characteristics in heart failure staging and discovery of novel biomarkers.

BACKGROUND: Heart Failure represents the severe stage of various heart diseases. Its global morbidity and mortality are on the rise, making it a serious public health issue that imposes a heavy burden on patients' families and society. Currently, there are relatively few systematic studies on the changes in specific metabolites and pathways in different stages of heart failure, such as Stage A, Stage B and Stage C. AIMS: Using untargeted-targeted metabolomics to explore the metabolic characteristics of Heart Failure, and screen out serum metabolic markers with potential diagnostic and prognostic value. METHODS: This study is a cross-sectional study. A total of 210 heart failure patients from Xiyuan Hospital of China Academy of Chinese Medical Sciences were enrolled between October 2023 and October 2024. Among them, 60 patients were selected for targeted metabolomics analysis via stratified sampling. Serum samples of the patients were collected and pretreated with methanol, then metabolites were detected using untargeted and targeted LC-MS respectively. After the raw data were processed with MSDIAL, pattern recognition was performed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Differential metabolites with variable importance in projection (VIP) > 1 and P < 0.05 were screened, and relevant pathways were analyzed via enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. RESULTS: Untargeted metabolomics revealed that, compared with patients in Stages A and B, those with heart failure in Stage C had decreased serum levels of alanine, creatine, and branched-chain amino acids, along with increased levels of citric acid, fumaric acid, and malic acid. The differential metabolites were primarily enriched in pathways including the citric acid cycle, central carbon metabolism, and amino acid metabolism, indicating that energy metabolism plays a crucial role in the occurrence and progression of HF. Targeted metabolomics validated the findings from untargeted metabolomics: compared with Stage A, the level of phosphoenolpyruvate in Stage B was reduced; and in comparison with patients in Stage A or B, patients in Stage C showed decreased serum levels of multiple energy metabolites (e.g., glucose-6-phosphate, fructose-6-phosphate, 3-phosphoglyceric acid, AMP, ADP and ATP) as well as increased levels of malic acid, which is consistent with the characteristics of the "hypermetabolism-energy starvation" paradox. CONCLUSION: Stage C of heart failure is characterized by energy metabolism collapse (decreased ATP and TCA compensation), and differential metabolites (such as malic acid) may serve as potential candidate biomarkers pending longitudinal validation.

Humans↗

PubMed2024

Proteomics analysis of deep fascia in acute compartment syndrome.

Acute compartment syndrome (ACS) is a syndrome in which local circulation is affected due to increased pressure within the compartment. We previously found in patients with calf fractures, the pressure of fascial compartment could be sharply reduced upon the appearance of tension blisters. Deep fascia, as the important structure for compartment, might play key role in this process. Therefore, the aim of the present study was to examine the differences in gene profile in deep fascia tissue in fracture patients of the calf with or without tension blisters, and to explore the role of fascia in pressure improvement in ACS. Patients with lower leg fracture were enrolled and divided into control group (CON group, n = 10) without tension blister, and tension blister group (TB group, n = 10). Deep fascia tissues were collected and LC-MS/MS label-free quantitative proteomics were performed. Genes involved in fascia structure and fibroblast function were further validated by Western blot. The differentially expressed proteins were found to be mainly enriched in pathways related to protein synthesis and processing, stress fiber assembly, cell-substrate adhesion, leukocyte mediated cytotoxicity, and cellular response to stress. Compared with the CON group, the expression of Peroxidasin homolog (PXDN), which promotes the function of fibroblasts, and Leukocyte differentiation antigen 74 (CD74), which enhances the proliferation of fibroblasts, were significantly upregulated (p all <0.05), while the expression of Matrix metalloproteinase-9 (MMP9), which is involved in collagen hydrolysis, and Neutrophil elastase (ELANE), which is involved in elastin hydrolysis, were significantly reduced in the TB group (p all <0.05), indicating fascia tissue underwent microenvironment reconstruction during ACS. In summary, the ACS accompanied by blisters is associated with the enhanced function and proliferation of fibroblasts and reduced hydrolysis of collagen and elastin. The adaptive alterations in the stiffness and elasticity of the deep fascia might be crucial for pressure release of ACS.

Humans↗

PubMed2025

Mutations in the transcriptional regulator MAB_2885 confer tedizolid and linezolid resistance through the MmpS-MmpL efflux pump MAB_2302-MAB_2303 in Mycobacterium abscessus.

Mycobacterium abscessus (MAB) is a clinically significant multidrug-resistant (MDR) pathogen, particularly implicated in pulmonary infections among cystic fibrosis (CF) patients. Tedizolid (TZD), an oxazolidinone-class antibacterial drug, has been recommended as an alternative treatment for MAB-infected patients who are intolerant to or whose isolate is resistant to first-line drugs including linezolid (LZD). To investigate the TZD resistance mechanisms in MAB, we isolated 23 TZD-resistant MAB mutants and performed whole-genome sequencing (WGS) to identify resistance-associated genes. Frequent mutations were identified in MAB_2885, encoding a putative TetR transcriptional regulator, and MAB_2303, encoding a putative mycobacterial membrane protein large (MmpL). Drug susceptibility testing confirmed that MAB_2885 mutations contribute to both TZD and LZD resistance in MAB. RNA-seq analysis revealed that restoring wild-type MAB_2885 in mutants downregulated the MAB_2302-MAB_2303. Electrophoretic mobility shift assay (EMSA) showed the MAB_2885 protein binds to its target sequence upstream of MAB_2302-MAB_2303, further confirming their regulatory relationship. The W91R mutation in the MAB_2885 protein was found to impair its DNA-binding activity compared to the wild-type. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis confirmed that MAB_2302-MAB_2303 functions as a TZD efflux pump. Additionally, overexpression of MAB_2885 in M. abscessus subsp. bolletii and M. abscessus subsp. massiliense also increased their TZD susceptibility and downregulated their respective MmpS-MmpL orthologs. Overall, our study demonstrates that mutations in MAB_ 2885 contribute to TZD and LZD resistance by disrupting the negative regulation of the downstream MAB_2302-MAB_2303, which functions as a direct efflux pump for TZD. These findings provide new insights into oxazolidinone resistance mechanisms in MAB and identify potential biomarkers for detecting drug resistance.

Mycobacterium abscessus↗

PubMed2026

Non-invasive embryo assessment: Cell-free DNA-based genetic testing and amino acid metabolomics in relation to morphology: A case-control study.

BACKGROUND: Cell-free DNA (cfDNA) in spent culture medium (SCM) offers a non-invasive option for preimplantation genetic testing, but its low concentration and fragmentation reduce clinical reliability. Combining genetic assessment with metabolomic profiling may provide complementary information about embryo competence. OBJECTIVE: This study assessed pre-analytical cfDNA processing workflows and examined whether SCM amino acid metabolic patterns could act as practical markers of embryo quality. MATERIALS AND METHODS: In this case-control study (2021-2023), 90 embryos were evaluated using fluorescence in situ hybridization or array comparative genomic hybridization. SCM samples underwent rapid boiling, silica-based purification, or whole-genome amplification (WGA). Sex determination was performed using quantitative polymerase chain reaction (qPCR). For cfDNA quality control and aneuploidy screening, the multiplex IRFiling kit and quantitative fluorescent polymerase chain reaction (QF-PCR) were used. Amino acid profiles across embryonic developmental stages and quality grades were quantified via liquid chromatography-tandem mass spectrometry. RESULTS: Rapid boiling resulted in complete failure of DNA amplification. Conversely, silica-based purification yielded 70.0% concordance for qPCR-based sexing and 56.7% for QF-PCR. WGA achieved the highest efficacy (73.3% qPCR and 56.7% QF-PCR concordance), although quality control checks flagged occasional misclassifications. LC-MS/MS profiling revealed significantly elevated alanine and arginine levels in tripronuclear embryos. Furthermore, high-quality blastocysts exhibited elevated glutamic acid levels alongside a pronounced overall depletion of extracellular amino acids compared to low-quality counterparts and controls. CONCLUSION: WGA improves cfDNA detectability and qPCR accuracy compared with boiling or purification, but remains inadequate as a standalone screening approach. SCM amino acid profiling provides informative, complementary metabolic signatures of developmental competence, supporting a multimodal strategy for non-invasive embryo assessment.

Amino acid metabolism↗

PubMed2026

Streptomyces violaceusniger WZS5-6 suppresses Fusarium oxysporum f. sp. cubense tropical race 4 via antifungal metabolites and host defense induction.

INTRODUCTION: Fusarium wilt of banana (FWB), caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4), poses a serious threat to the safety and sustainable development of the banana industry. Biological control represents one of the most environmentally friendly approaches for managing this disease. METHODS: In this study, Streptomyces violaceusniger WZS5-6 antifungal activity against Foc TR4 has been investigated through an integrated approach combining antifungal assays, genome analysis, and metabolomic profiling. For the purpose, the effects of the bacterial strain and its cell-free extract on morphological and ultrastructural changes on pathogenic fungal hyphae and spores were assessed using scanning and transmission electron microscopy. LC-MS analysis was used to identify the metabolites responsible for antifungal activity. We further explored the potential of S. violaceusniger WZS5-6 against Foc TR4 through in planta validation. RESULTS: Streptomyces violaceusniger WZS5-6 exhibited a strong inhibition rate of 91.57% on Foc TR4. The cell-free extract obtained from S. violaceusniger WZS5-6 strongly inhibited Foc TR4 with an EC50 value of 91.62 µg·mL-1, indicating the presence of antifungal bioactive metabolites. The results showed that S. violaceusniger WZS5-6 significantly inhibited the mycelial growth of Foc TR4 and induced alterations in spore morphology, mycelial ultrastructure, and cell membrane leakage. Metabolomic profiling of the S. violaceusniger WZS5-6 extracts revealed numerous antifungal metabolites, among which the key metabolites, viz., citronellic acid and furanodienone, exhibited strong inhibitory effects on Foc TR4, with antifungal activity of 61.13% and 57.44%, respectively. Moreover, strain WZS5-6 not only demonstrated 61.54% control efficacy against FWB in a pot experiment but also showed promising growth-promoting effects on banana plants. DISCUSSION: This study demonstrates that S. violaceusniger WZS5-6 inhibits Foc TR4 through a multi-level mechanism involving cellular disruption, metabolic adaptation, and activation of host defense responses. These findings highlight the potential of S. violaceusniger WZS5-6 as a promising novel candidate strain to be employed as a biological control agent of FWB.

Fusarium wilt of banana↗

PubMed2025

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗

PubMed2026

Proteomic insights into azoospermia: protein differences in testicular tissue between non-obstructive and obstructive azoospermia patients.

Non-obstructive azoospermia (NOA) and obstructive azoospermia (OA) are the main classifications of severe male infertility, but the molecular mechanism of NOA remains poorly understood. This study aimed to identify potential biomarkers and pathological mechanisms by comparing the proteomic differences in testicular tissues of NOA and OA patients. Through proteomic analysis based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) of testicular samples from 5 NOA patients and 5 OA patients, we identified 5264 proteins, among which 717 differentially expressed proteins (DEPs) were found between the two groups (242 upregulated and 475 downregulated in NOA). Bioinformatics analysis indicated that these DEPs were significantly associated with reproductive development, gametogenesis, and cell structural stability. On the basis of this, six candidate proteins, including dysferlin (DYSF), myoferlin (MYOF), mitsugumin 53 (MG53), cluster of differentiation 63 (CD63), caveolin-3 (CAV3), and calpain-3 (CAPN3), were selected from the DEPs and verified in an expanded sample set (37 NOA cases and 28 OA cases) through quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot, confirming their dysregulation in NOA. These findings provide new proteomic insights into NOA, highlighting the disruption of membrane repair and structural pathways, and offer potential biomarkers for understanding its pathogenesis.

Humans↗

PubMed2024

A lipidomic study on the lens epithelial cells of patients with age related cataracts.

Age related cataracts (ARC) represent the main reason for blindness globally. The lens epithelial cells (LECs) participate not only in the metabolism of many substances in the lens but also in maintaining lens transparency. This study used lipidomics to investigate the metabolic differences in LECs of ARC patients with different severity, aiming at identifying potential metabolic biomarkers of ARC. Patients diagnosed with ARC and underwent cataract surgery at Shanghai Tongren Hospital were selected to participate in this study, which were classified as mild ARC group and severe ARC group. During their cataract surgery, anterior lens capsules(LCs) containing LECs were obtained. The lipidomics of LECs were analyzed using the liquid chromatography‑mass spectrometry (LC-MS). Potential pathways of lipids were searched for using databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst platform. In LEC lipids, 26 lipids have been identified as potential biomarkers between mild ARC and severe ARC, with AUC values of 0.67-0.94. The pathway analysis results revealed that the Glycerophospholipid (GPL) metabolism was significantly influenced, indicating that these metabolic markers contribute significantly to regulating this pathway. The LEC metabolic spectrum demonstrates a proficient ability to differentiate between patients with varying levels of cataracts. Herein, we have successfully identified potential metabolic biomarkers and pathways that have proven to be valuable in enhancing our understanding of ARC pathogenesis. The finding has translational value for developing new cataract treatment methods in the future.

Humans↗

PubMed2026

Improved comprehensive profiling of fecal bile acids through chemical derivatization combined with HPLC-MS/MS analysis.

Bile acids (BAs) facilitate the digestion and absorption of fats and influence lipid and glucose homeostasis, making them potential therapeutic targets for obesity and related metabolic disorders. The liver and intestinal microbiota modify BAs structurally, generating diverse chemical forms and isomers. Comprehensive profiling of the BA pool is critical for understanding their key biological functions and as a therapeutic approach for related diseases. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) is usually chosen as the preferred method for BA detection due to the complex chemical structures, the wide range of actual concentrations and the complexity of fecal sample matrices. However, free BAs are difficult to ionize, resulting in low detection signals and a lack of characteristic structural fragments to assist in structural identification. In this method, the labeling reagent (2-aminoethyl) trimethylammonium (AETMA) is employed to label the carboxyl group of BAs. Compared with underivatized BAs, the detection sensitivity of unconjugated BAs was enhanced by 25-180 fold, while that of conjugated BAs increased by 6-160 fold. It also generates unique fragment ions and enhances MS response, facilitating the discovery of potential BAs. Methodological parameters were validated using 38 BAs as representatives. Through methodological validation, it was verified that the precision, recovery, matrix effect and stability parameters of the method met acceptable criteria. We also identified 61 confirmed BAs and 55 additional candidate BAs in human pooled fecal samples. It has been successfully applied to fecal BA analysis in obese populations, providing valuable insights into potential therapeutic strategies for obesity.

Tandem Mass Spectrometry↗

PubMed2026

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics↗

PubMed2026

Quantitative N-glycoproteomic analysis reveals glycosylation signatures of plasma immunoglobulin G in sepsis.

INTRODUCTION: Sepsis is a life-threatening condition resulting from organ dysfunction due to a dysregulated immune response to infection. Immunoglobulin G (IgG) plays a role in modulating immune responses. However, the precise IgG subclass-specific N-glycosylation profiles in patients with sepsis remain poorly characterized. METHODS: This study aimed to define the site-specific N-glycosylation signatures of plasma IgG subclasses in sepsis patients with different prognoses using quantitative glycoproteomics. By employing our established GlycoQuant strategy, we quantified the intact N-glycopeptides (IGPs) of IgG subclasses in 40 healthy controls and 40 sepsis patients with a clear prognosis. RESULTS: We identified 12 IGPs with altered abundances between patients with sepsis and healthy controls. After Benjamini-Hochberg (BH) correction of the 31 outcome-stratified IGP comparisons, IGP24 and IGP25 remained significant and met the prespecified fold-change criterion. Global BH correction across 124 IGP-clinical parameter correlations retained positive associations of IGP19, IGP22, and IGP23 with procalcitonin (PCT). In exploratory outcome-stratified ROC analyses, candidates were selected using the original unadjusted P-value and fold-change screen; five IGPs were evaluated, with IGP25 and IGP24 yielding the highest individual AUCs. Collectively, our findings underscore the potential of IgG subclass-specific glycosylation profiling as a novel translational approach for clinical applications in sepsis management. SIGNIFICANCE: Sepsis remains a leading cause of global mortality, with patient outcomes heavily dependent on timely diagnosis and accurate prognosis. The dysregulated host immune response, particularly involving immunoglobulins, is central to its pathophysiology. This study provides a significant advance in the field of clinical glycoproteomics by applying a quantitative, site-specific strategy to delineate the plasma IgG subclass N-glycosylation landscape in sepsis. We report, for the first time, a panel of subclass-specific intact IgG N-glycopeptides (IGPs) that are significantly altered in sepsis patients compared to healthy controls. The identified IGPs not only demonstrate diagnostic and prognostic potential but also show a significant correlation with procalcitonin, a key clinical severity index. These findings bridge a critical knowledge gap by moving beyond bulk IgG glycosylation analysis to subclass-resolved profiling, offering novel molecular insights into sepsis immunopathology. The identified glycosylation signatures hold substantial translational promise as a foundation for developing innovative, glycan-based biomarker panels to improve the precision management of this heterogeneous and life-threatening syndrome.

Humans↗