Search Results (100)

Traditionally considered as homogeneous innate immune cells, neutrophils are now found to exhibit phenotypic and functional heterogeneity. How to determine whether the functional changes of neutrophils are caused by activation or the result of gene reprogramming? Recent advances in multi-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and spatial omics, have comprehensively explained the mechanism of neutrophil heterogeneity. At the same time, artificial intelligence, especially machine learning, has promoted the in-depth analysis of multi-omics. Here, we introduce the latest progress in the discovery of neutrophil subsets by omics research. We will further discuss the application of machine learning in analyzing the heterogeneity of neutrophils through omics methods. Our goal is to provide a comprehensive overview of how machine learning and multi-omics are reshaping our understanding of neutrophil biology and pathophysiology. Full article

This paper introduces a novel Lateral Extraction Enhanced Desorption Electrospray Ionization (LEE-DESI) source. This source is specifically designed to tackle the crucial issue of electric field interference in dual-channel ambient ionization mass spectrometry (AIMS). By incorporating dual-channel spraying-based desorption and extraction into a 3D-printed chamber with optimized spatial parameters, the system effectively reduces cross-channel interference while boosting ionization efficiency. The desorption spray is responsible for desorbing analytes from untreated samples, and the extraction spray further ionizes more neutral droplets through charge transfer, which substantially enhances sensitivity. Compared with traditional DESI, the LEE-DESI source demonstrates improved detection limits, reproducibility, and operational simplicity, as validated using Rhodamine B, L-arginine, and Angiotensin I, as well as drug standards including methadone, ketamine, and fentanyl. This highlights its potential for high-throughput analysis of complex matrices in proteomics, metabolomics, and biomedical applications. Full article

Next-generation sequencing has overturned the dogma of biliary sterility, revealing low-biomass microbiota along the gut–biliary axis with metabolic and immunologic effects. This review synthesizes evidence on composition, function, and routes of colonization across benign and malignant disease. In cholelithiasis, Proteobacteria- and Firmicutes-rich consortia provide β-glucuronidase, phospholipase A₂, and bile salt hydrolase, driving bile supersaturation, nucleation, and recurrence. In primary sclerosing cholangitis, primary biliary cholangitis, and autoimmune hepatitis, intestinal dysbiosis and disturbed bile acid pools modulate pattern recognition receptors and bile acid signaling (FXR, TGR5), promote Th17 skewing, and injure cholangiocytes; bile frequently shows Enterococcus expansion linked to taurolithocholic acid. Distinct oncobiomes characterize cholangiocarcinoma subtypes; colibactin-positive Escherichia coli and intratumoral Gammaproteobacteria contribute to DNA damage and chemoresistance. In hepatocellular carcinoma, intratumoral microbial signatures correlate with tumor biology and prognosis. We critically appraise key methodological constraints—sampling route and post-sphincterotomy contamination, antibiotic prophylaxis, low biomass, and heterogeneous analytical pipelines—and outline a translational agenda: validated microbial/metabolomic biomarkers from bile, tissue, and stent biofilms; targeted modulation with selective antibiotics, engineered probiotics, fecal microbiota transplantation, and bile acid receptor modulators. Standardized protocols and spatial, multi-omic prospective studies are required to enable risk stratification and microbiota-informed therapeutics. Full article

The kynurenine (KYN) metabolic pathway sits at the crossroads of immunity, metabolism, and neurobiology, yet its clinical translation remains fragmented. Emerging spatial omics, wearable chronobiology, and synthetic microbiota studies reveal that tryptophan (Trp) metabolism is regulated by distinct cellular “checkpoints” along the gut–brain axis, finely modulated by sex differences, circadian rhythms, and microbiome composition. However, current interventions tackle single levers in isolation, leaving a key gap in the precision control of Trp’s fate. To address this, we drew upon an extensive body of the primary literature and databases, mapping enzyme expression across tissues at single-cell resolution and linking these profiles to clinical trials investigating dual indoleamine 2,3-dioxygenase 1 (IDO1)/tryptophan 2,3-dioxygenase (TDO) inhibitors, engineered probiotics, and chrono-modulated dosing strategies. We then developed decision-tree algorithms that rank therapeutic combinations against biomarker feedback loops derived from real-time saliva, plasma, and stool metabolomics. This synthesis pinpoints microglial and endothelial KYN hotspots, quantifies sex-specific chronotherapeutic windows, and identifies engineered Bifidobacterium consortia and dual inhibitors as synergistic nodes capable of reducing immunosuppressive KYN while preserving neuroprotective kynurenic acid. Here, we highlight a framework that couples lifestyle levers, bio-engineered microbes, and adaptive pharmaco-regimens into closed-loop “smart protocols.” By charting these intersections, this study offers a roadmap for biomarker-guided, multidisciplinary interventions that could recalibrate KYN metabolic activity across cancer, mood, neurodegeneration, and metabolic disorders, appealing to clinicians, bioengineers, and systems biologists alike. Full article

Research and innovation in metabolomics tools to measure metabolite accumulation within plants have led to important discoveries with respect to the improvement of plant stress tolerance, development, and crop yield. Traditional metabolomics analyses have commonly utilized gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry, but these methods are often performed without regard for the spatial locations of metabolites within tissues. Methods for mass spectral imaging (MSI) have recently been developed to detect and spatially resolve metabolite accumulation and are rapidly being adopted on a wider scale. Since 2010, the number of publications incorporating mass spectral imaging has grown from approximately 80 articles to over 378 on a yearly basis, constituting an increase of at least 350% during this time frame. Spatially resolved metabolite accumulation data provides unique insights into the function and regulation of plant biochemical pathways. Mass spectral imaging is commonly paired with desorption ionization technologies, including matrix-assisted laser desorption ionization (MALDI) and desorption electrospray ionization (DESI), to generate accurate, spatially resolved metabolomics data from prepared tissue segments. Here, we describe the most recent advancements in sample preparation methods, mass spectral imaging technologies, and data processing tools that have been developed to address the limits of MSI technology. Additionally, we summarize recent applications of MSI technologies in plant metabolomics and discuss potential avenues for future research advancements within the plant biology community through the use of these technologies. Full article

Lotus (Nelumbo nucifera Gaertn.) is a quintessential medicinal and edible plant, exhibiting marked differences in therapeutic effects among its various parts. The lotus seed constitutes a key component of this plant. Notably, the entire seed and the plumule display distinct medicinal properties. To investigate the “homologous plants with different effects” phenomenon in traditional Chinese medicine, this study established a Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) method. This study employed immature lotus seeds as the experimental material, diverging from the mature seeds conventionally used. Conductive double-sided tape was employed for sample preparation, and complete longitudinal sections of the seeds were obtained, followed by MALDI-MSI analysis to identify and visualize the spatial distribution of characteristic secondary metabolites within the entire seeds. The results unveiled the diversity of metabolites in lotus seeds and their differential distribution across tissues, with pronounced distinctions in the plumule. A total of 152 metabolites spanning 13 categories were identified in lotus seeds, with 134, 89, 51, and 98 metabolites discerned in the pericarp, seed coat, cotyledon, and plumule, respectively. Strikingly, young lotus seeds were devoid of liensinine/isoliensinine and neferine, the dominant alkaloids of mature lotus seed plumule, revealing an early-stage alkaloid profile that sharply contrasts with the well-documented abundance found in mature seeds and has rarely been reported. We further propose a biosynthetic pathway to explain the presence of the detected benzylisoquinoline and the absence of the undetected bisbenzylisoquinoline alkaloids in this study. These findings present the first comprehensive metabolic atlas of immature lotus seeds, systematically exposing the pronounced chemical divergence from their mature counterparts, and thus lays a metabolomic foundation for dissecting the spatiotemporal mechanisms underlying the nutritional and medicinal value of lotus seeds. Full article

Glucose metabolism reprogramming as a defining hallmark of cancer has become a pivotal frontier in oncology research. Recent technological advances in single-cell sequencing, spatial omics, and metabolic imaging have transformed the field from static bulk analyses to dynamic investigations of spatiotemporal heterogeneity at a single-cell resolution. This review systematically summarizes the current knowledge on tumor glucose metabolism dynamics, discussing spatial heterogeneity and temporal evolution patterns, metabolic subpopulation interactions revealed by single-cell metabolomics, the glucose metabolism–epigenetics–immunology regulatory axis, and therapeutic strategies targeting metabolic vulnerabilities. Recent technological advances in single-cell sequencing and spatial omics have transformed our understanding of tumor glucose metabolism by providing high-resolution insights into metabolic heterogeneity and regulatory mechanisms, contrasting with classical bulk analyses. Spatiotemporal heterogeneity critically influences therapeutic outcomes by enabling tumor cells to adapt metabolically under selective pressures (e.g., hypoxia, nutrient deprivation), fostering treatment resistance and relapse. Deciphering these dynamics is essential for developing spatiotemporally targeted strategies that address intratumoral diversity and microenvironmental fluctuations. By integrating cutting-edge advances, this review deepens our understanding of tumor metabolic complexity and provides a conceptual framework for developing spatiotemporally precise interventions. Full article

Ischemic stroke ranks among the top global causes of disability and mortality, with a highly dynamic pathological process. Post-stroke neuroinflammation, mediated by microglia, demonstrates a dual role in both injury and repair. The CX3CR1/CX3CL1 signaling axis, highly expressed in microglia, acts as a key regulator. This review examines the spatiotemporal dynamics of the axis across the stroke process and its involvement in neural repair. Crucially, this signaling pathway demonstrates stage-dependent functional duality: its cellular sources, receptor expression profiles, and functional consequences undergo temporally orchestrated shifts, manifesting coexisting or interconverting protective and damaging properties. Ignoring this dynamism compromises the therapeutic efficacy of targeted interventions. Thus, we propose a triple precision strategy of “stroke phase—biomarker—targeted intervention”. It uses specific biomarkers for precise staging and designs interventions based on each phase’s signaling characteristics. Despite challenges like biomarker validation, mechanistic exploration, and cross-species differences, integrating cutting-edge technologies such as spatial metabolomics and AI-driven dynamic modeling promises to shift stroke therapy toward personalized spatiotemporal programming. Temporally targeting CX3CR1 signaling may offer a key basis for developing next-generation precision neural repair strategies for stroke. Full article

Virus infections in plants are a major threat to crop production and sustainable agriculture, which results in significant yield losses globally. The past decade has seen the development and deployment of sophisticated high-throughput omics technologies including genomics, transcriptomics, proteomics, and metabolomics, in order to try to understand the mechanisms underlying plant–virus interactions and implement strategies to ameliorate crop losses. In this review, we discuss the current state-of-the-art applications of such key omics techniques, their challenges, future, and combinatorial use (e.g., single cell and spatial omics coupled with super-resolution high-throughput imaging methods and artificial intelligence-based predictive models) to obtain new mechanistic insights into plant–virus interactions, which could be exploited for more effective plant disease management and monitoring. Full article

This research examines a detailed metabolomic and comparative analysis of bioactive substances of soybean varieties: “Primorskaya-4”, “Primorskaya-86”, “Primorskaya-96”, “Locus”, “Sphere”, “Breeze”, “Namul”, and “Musson” by the laser confocal microscope CLSM 800 and the mass spectrometry of bioactive compounds by tandem mass spectrometry. The laser microscopy allowed us to clarify in detail the spatial arrangement of phenolic acids, flavonols, and anthocyanin contents in soybeans. Research has convincingly shown that the polyphenolic content of soybeans, and, in particular, the anthocyanins, are spatially localized mainly in the seed coat of soybeans. Tandem mass spectrometry was used to identify chemical constituents in soybean extracts. The results of initial studies revealed the presence of one hundred and fourteen compounds; sixty-nine of the target analytes were tentatively identified as compounds from polyphenol groups. Full article

Background: Neonatal hypoxic-ischemic encephalopathy (HIE) is a major cause of neonatal death and neurodevelopmental disorders, and its pathological mechanisms are closely related to disturbed energy metabolism and lipid remodeling. Exploring the spatial heterogeneity of metabolomics is essential to analyze the pathological process of HIE. Methods: In this study, we established a neonatal mouse hypoxic-ischemic brain damage (HIBD) model by the modified Rice method, and analyzed various metabolic pathways such as the tricarboxylic acid (TCA) cycle, purine metabolism, and lipid metabolism in the ischemic edema area, with contralateral and control brain tissues using matrix-assisted laser desorption mass spectrometry imaging (MALDI-MSI) with a spatial resolution of 50 μm. Results: In the HIBD model, key metabolites of the tricarboxylic acid (TCA) cycle (citrate, succinate, L-glutamate, glucose, aspartate, and glutamine) were significantly enriched in the edematous area compared with the control (fold change: 1.52–2.82), which suggests a blockage of mitochondrial function; ATP/ADP/AMP levels were reduced by 53–73% in the edematous area, and xanthine was abnormally accumulated in the hippocampus of the affected side, suggesting energy depletion and altered purine metabolism; lipid remodeling showed regional specificity: some unsaturated fatty acids, such as docosahexaenoic acid, were abnormally accumulated in the hippocampus. In contrast, pentadecanoic acid levels were reduced across the entire brain in the HIBD model, with a more pronounced decrease in the ipsilateral hippocampus, suggesting impaired membrane stability. Conclusions: The neonatal mouse HIBD model exhibits reprogramming of energy metabolism, characterized by a blockage in the tricarboxylic acid (TCA) cycle and ATP depletion, along with an abnormal spatial distribution of lipids. By targeting xanthine metabolic pathways, restoring mitochondrial function, and intervening in region-specific lipid remodeling, brain energy homeostasis may be improved and neurological damage attenuated. Further studies should validate the clinical feasibility of xanthine and lipid imbalance as diagnostic markers of HIBD and explore the critical time window for metabolic intervention to optimize therapeutic strategies. Full article

Background: Spatial metabolomics is a powerful technique that enables spatially resolved mapping of metabolite distributions at the tissue and cellular levels, providing valuable insights into biological processes. However, challenges in data quality control and preprocessing remain significant bottlenecks, critically impacting the reliability of downstream analyses and the robustness of findings. Methods: To address these limitations, we present Spatial Metabolomics data Quality Visualization and Processing (SMQVP v1.0), a novel software with a user-friendly graphical interface designed for the systematic quality assessment and preprocessing of spatial metabolomics data. SMQVP incorporates eight comprehensive quality visualization and evaluation modules, including background consistency assessments, noise ion filtering, intensity distribution analyses, and the identification of isotopic and adduct ions. Results: We demonstrated SMQVP’s effectiveness using AFADESI-based mouse brain data, showing that the tool successfully identified and removed noise signals. This rigorous preprocessing resulted in improved clustering outcomes that more accurately reflected the underlying tissue morphology compared with analyses performed on unprocessed data. Conclusions: SMQVP is the first systematic approach focused on quality visualization, specifically for spatial metabolomics. It offers researchers an accessible and comprehensive solution for enhancing data integrity and mitigating the impact of technical noise, thereby improving the reliability and robustness of their spatial metabolomics findings. Full article

In line with the recommended European policy for a zero-waste crop supply chain, a lab-pilot optimisation process to valorise the by-products of industrially produced rapeseed meal (RM) was performed. Three batches of RM were first processed into ethanol-wash solutes (EWS) and then optimised (OEWS) by an ultrasound-assisted (UA) treatment. After direct analysis in real time–high resolution mass spectrometry (DART-HRMS) analysis, data were processed applying a partial least square–discriminant analysis (PLS-DA), which retrieved the 15 most discriminative ions able to characterise the biochemical changes during the ethanol-washing and UA optimisation process. The metabolomic fingerprinting of EWS and OEWS generated an accurate and well-defined 3D spatial clusterisation based on a restricted pool of informative bioactive compounds. A significantly higher relative abundance of sinapic, azelaic, and vernolic acids and a lower incidence of the oleic and palmitic fatty acids were detected in OEWS. DART-HRMS generated a vast amount of biochemical information in one single run, also demonstrating that its association with an untargeted multivariate statistical approach would be a valuable tool for revealing specific functional biomarkers. This would eventually enhance the circular and effective use of rapeseed residuals coming from this plant’s oilseed industry. Full article

Lysine carboxymethyl cysteinate (LCC) is a synthetic substance obtained via lysine salification of S-carboxymethyl-cysteine. LCC has emerged as a promising glutathione (GSH) precursor. In this study, we sought to determine whether LCC could boost GSH levels and protect skin against oxidative stress. Experiments utilizing primary human keratinocytes and skin tissue samples revealed that LCC significantly increased endogenous GSH levels. LCC was able to pass through the stratum corneum and reach deep into the epidermis, where it enhanced the production of key metabolites involved in GSH biosynthesis. Then, the efficacy of LCC on skin protection was explored. LCC demonstrated protective effects by shielding keratinocytes from blue-light-induced oxidative stress and preventing ultraviolet B (UVB)-induced barrier disruption and pigmentation in a pigmented living skin equivalent (pLSE) model. In addition to its antioxidant properties, LCC also reduced the production of inflammatory mediators. Together, these findings underscore the multifaceted role of LCC in bolstering the natural antioxidant defenses of skin and preventing the accumulation of irreversible damage from the environment, thereby positioning it as a promising candidate for advancing skin health. Full article

The neurobehavioral changes in food allergy mice have not been comprehensively studied, and the mechanism underlying them remains unclear. Our study aims to fully investigate neurobehavioral changes in OVA (ovalbumin)-sensitized food allergy mice and explore the potential mechanism via the gut microbiota–brain axis. We established the food allergy mouse (C57BL/6J male) model with OVA, evaluating the anaphylactic symptoms and the levels of Th2 signature cytokine and allergy-related antibodies in serum. Using behavioral tests, we measured anxiety, depression, social behavior, repetitive behavior, attention, and spatial memory in control and OVA mice. In addition, we analyzed the prefrontal cortex for measuring inflammation-related indicators and gathered serum for untargeted metabolomics analysis and feces for 16S rDNA sequencing. OVA mice exhibited anaphylactic symptoms and significantly elevated serum IgE and Th2 signature cytokine levels. In addition to anxiety-like, depression-like, and repetitive behaviors, OVA mice also displayed less social interest and damaged attention. TNF-α, IL-1β, and IL-6 levels and the activation of microglia in the prefrontal cortex of OVA mice were significantly increased, which might explain the neuronal damage. Using multi-omics technology, amino acid metabolism disruption, particularly carboxylic acids and derivatives, was observed in OVA mice, which was remarkably correlated with the altered abundance of gut microbiota related to food allergy. Behaviors in OVA-induced food allergy mice were extensively impaired. The disruption of amino acid metabolism associated with gut microbiota dysbiosis in OVA mice might play a pivotal role in impairing neural immune homeostasis and neuronal damage, which could be responsible for behavioral abnormalities. Full article