Molecular omics最新文献

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has established itself as a powerful analytical technique for spatially resolved lipidomics, offering unique insights into lipid distribution and metabolism directly within plant and food matrices. Recent methodological and technological advances have markedly improved the spatial resolution, sensitivity, and selectivity of MALDI-MSI, enabling high-definition mapping of complex lipidomes down to the cellular level. This review presents the current state of MALDI-MSI applications in plant and food lipidomics, with a focus on studies that have advanced our understanding of lipid heterogeneity, metabolic pathways, and spatial lipid organization. Special attention is given to the analytical challenges associated with lipid structural diversity, particularly isomerism and isobarism, and to the strategies developed to address these limitations. Emerging applications involving stable isotope labelling, advanced ion mobility spectrometry, and chemical derivatization are also discussed, highlighting their potential to enhance lipid identification and spatial localization. Finally, the review outlines future perspectives, emphasizing the integration of MALDI-MSI with complementary omics approaches and advanced computational tools to accelerate discoveries in plant biology, food quality assessment, and nutritional science.

Indisulam, a DCAF15-based molecular glue degrader, induces widespread proteome changes with implications for cell division and chromosome segregation. While RBM39 and RBM23 are two well-characterized indisulam neo-substrates, additional targets likely exist. To identify those degradation targets, we applied a network-based approach to prioritize novel neo-substrates from large-scale omics data. Our approach integrates proteome-wide expression measurements with information from publicly accessible databases into a multilayer heterogeneous network. Utilizing a Random Walk with Restart algorithm, we identified a preliminary list of 30 neo-substrates. These proteins are likely interactors with DCAF15 in the presence of indisulam and are subject to subsequent degradation. Experimental validation of hits from the shortlisted candidates confirmed their degradation in a proteasome-dependent manner, supporting their identification as potential novel indisulam neo-substrates. Our work employs established network resources and analytical methods to effectively identify direct targets of the indisulam molecular glue degrader. This approach is readily adaptable for exploring novel targets across other molecular glue systems, enhancing its applicability and value to the drug discovery community.

Hepatic fibrosis (HF), a reversible yet critical pathological stage in chronic liver disease progression, represents a major global public health challenge. This study systematically investigated the antifibrotic mechanism of Prunus mongolica oil (OIL), an active component derived from traditional medicinal plants, through an integrated approach combining pharmacodynamics, transcriptomics, and molecular biology in carbon tetrachloride (CCl₄)-induced Sprague–Dawley rat models. Dose–response evaluation revealed optimal antifibrotic efficacy at the medium dosage (5 g kg⁻¹) compared with other concentrations (2.5 and 7.5 g kg⁻¹). Transcriptomic profiling identified 1734 differentially expressed mRNAs, 121 lncRNAs, and 82 miRNAs among model (MOD), control (CON), and OIL-treated groups. Construction of competing endogenous RNA (ceRNA) networks and functional enrichment analysis highlighted the potential association of the PPAR signaling pathway (P = 0.012, FDR = 0.27). Topological assessment using Cytoscape (v3.9.1) and the STRING database identified the Gck/rno-miR-667-5p/Cyp8b1 axis as the central regulatory node. Mechanistically, OIL exerted dual therapeutic effects: (1) upregulating PGC-1α/PPARγ expression to enhance metabolic reprogramming, and (2) suppressing TGF-β/Smad3 phosphorylation activation, thereby inhibiting hepatic stellate cell (HSC) activation and extracellular matrix (ECM) deposition. Immunohistochemical and western blot analyses validated these protein-level modulations. Our findings revealed a novel ceRNA-network-mediated mechanism wherein OIL attenuates hepatic fibrosis through coordinated regulation of PPAR and TGF-β/Smad3 pathways via the Gck/rno-miR-667-5p/Cyp8b1 axis, providing a theoretical foundation for developing multitarget phytopharmaceuticals against liver fibrosis.

Mice lacking caveolin-1 (Cav1), a major protein of the lipid raft of plasma membrane, show deregulated cellular proliferation of the mammary gland and an abnormal fetoplacental communication during pregnancy. This study leverages a multi-omics approach to test the hypothesis that the absence of Cav1 elicits a coordinated crosstalk of genes among the mammary gland, placenta and fetal brain in pregnant mice. Integrative analysis of metabolomics and transcriptomics data of mammary glands showed that the loss of Cav1 significantly impacted specific metabolites and metabolic pathways in the pregnant mice. Next, gene expression changes of the deregulated metabolic pathways of the mammary gland were compared with the gene expression changes of the placenta and fetus. The analysis showed that genes associated with specific metabolic and signaling pathways changed in a coordinated manner in the placenta, mammary gland and fetal brain of Cav1-null mice. The cytokine signaling pathway emerged as a key player of the molecular crosstalk among these tissues. By interrogating the single-nuclei gene expression data of placenta and fetal brain previously generated from Cav1-null mice, the study further revealed that these metabolic and signaling genes were differentially regulated in specific cell types of the placenta and fetal brain. Though a causal effect of the mammary gland on the placenta and/or fetal brain can’t be inferred from this study, the findings show that the mammary gland, placenta and fetal brain show a coordinated molecular crosstalk in response to the absence of Cav1 in mice.

The integration of multimodal single-cell omics data is a state-of-art strategy for deciphering cellular heterogeneity and gene regulatory mechanisms. Recent advances in single-cell technologies have enabled the comprehensive characterization of cellular states and their interactions. However, integrating these high-dimensional and heterogeneous datasets poses significant computational challenges, including batch effects, sparsity, and modality alignment. Deep learning has shown great promise in addressing these issues through neural network-based frameworks, including variational autoencoders (VAEs) and graph neural networks (GNNs). In this Review, we examine cutting-edge deep learning methodologies for integrating single-cell multimodal data, discussing their architectures, applications, and limitations. We highlight key tools such as sciCAN, scJoint, and scMaui, which use deep learning techniques to harmonize various omics layers, improve feature extraction, and improve downstream biological analyses. Despite significant advancements, it remains challenging to ensure model interpretability, scalability, and generalizability across different datasets. Future directions of research in this field include the development of self-supervised learning strategies, transformer-based architectures, and federated learning frameworks to enhance the robustness and reproducibility of single-cell multi-omics integration.

Oral cancer (OC) is a malignant tumour with high morbidity and mortality. Significant contributory factors include alcohol and tobacco abuse that dysregulate the proteome and metabolome. We assessed saliva as a noninvasive bio-sample to understand the changes in proteome and metabolome in OC, tobacco abusers (TA), and controls. OC, TA, and control samples (n = 22, 21, and 21, respectively) were subjected to LFQ-proteomics and NMR-based metabolomics analyses individually and integrated using systems biology; 292 out of 758 proteins with two or more unique peptides were significantly differently regulated. Functional annotation revealed that differentially expressed proteins are involved in important cellular metabolic processes. PLS-DA in metabolomics separated OC from the control and TA, and K-means clustering of proteomics and metabolomics profiles revealed distinguishing proteins and metabolites in OC, TA, and the control. Integrated analysis revealed convergence on molecules like transketolase (TKTT), transaldolase (TALDO), kallikrein 1 (KLK1), enolase A (ENOA), glucose-6-phosphate isomerase (G6PI), and aldolase A and C (ALDOA and ALDOC). Finally, the characteristic discriminatory features of several clusters between OC, TA, and the control remain valid only among high tobacco abusers. The results reveal metabolites that could serve as early indicators for OC, especially among chewing tobacco abusers, and therefore establish the basis for larger cohort studies to develop them as predictive OC biomarkers.

Glycans are recognized as biomarkers and therapeutic targets. However, these molecules remain a critical blind spot in understanding post-translational modifications, particularly in vertebrate species inhabiting diverse habitats. The glycans present in tears play a crucial role in eye protection and may be one of the key factors in adapting to direct environmental contact. This study aimed to describe and compare the glycomic profiles of roadside hawk (Rupornis magnirostris), broad-snouted caiman (Caiman latirostris), and loggerhead sea turtle (Caretta caretta) tears, thereby one avian and two reptilian species. Samples were collected from 10 healthy roadside hawks, 70 broad-snouted caimans, and 10 loggerhead sea turtles to determine N- and O-glycan compounds. The compounds were released from tear glycoproteins and enriched by solid-phase extraction (SPE). Then, the glycans were eluted based on size and polarity. SPE fractions were analyzed using high-resolution mass spectrometry. 155 N-glycans (56% sialylated) and 259 O-glycans (37% sialylated) were detected in roadside hawk tears; 127 N-glycans (55% sialylated) and 263 O-glycans (35% sialofucosylated) in broad-snouted caiman tears; and 85 N-glycans (36% fucosylated) and 84 O-glycans (89% fucosylated) in loggerhead sea turtle tears. The marine habitat has a significant impact on the tear's glycans. The high presence of fucosylated glycans can represent a shield mechanism potentially related to its adhesion to glycocalyx, and interaction with the immune system, also serving as an environmental biomarker. Tears are composed of various biologically active substances, and this description can help in further studies on the identification of novel ocular surface biomarkers and in the differentiation of glycan profiles in healthy and non-healthy animals.

The development of acquired resistance to tamoxifen poses a significant clinical challenge in breast cancer treatment. Tumour heterogeneity has emerged as a primary reason for the clinical implications of resistance, yet we still lack actionable targets to address this issue. Repurposing existing drugs has become an emerging trend to tackle demanding medical indications. Therefore, we aim to study the efficacy of the antipsychotic drug Thioridazine against both parental and tamoxifen-resistant breast cancer cells. In this study, we have demonstrated that Thioridazine induces phospholipid accumulation, followed by necroptosis in both parental and tamoxifen-resistant breast cancer cell lines. We have shown thioridazine-mediated cytostatic effects through analyses of cell viability, cell count, caspase activation, cell cycle, and p21 expression levels. Moreover, employing a pharmacometabolomics approach, we identified that Thioridazine induces phospholipid accumulation in breast cancer cells. We established that Thioridazine promotes the accumulation of phospholipids rather than neutral lipids in cells via lipid-specific fluorescent quantification and imaging analysis. The phospholipid accumulation triggers necroptosis, which was evaluated through a propidium iodide uptake assay. Thioridazine activates RIP signalling, facilitating the subsequent translocation of pore-forming MLKL to the plasma membrane to initiate necroptosis. The formation of MLKL-induced membrane pores was confirmed using scanning electron microscopy for cell surface visualisation. Furthermore, thioridazine co-treatment enhances the efficacy of tamoxifen in resistant breast cancer cells, augmenting its potential for combinatorial treatment. Altogether, Thioridazine induces phospholipid accumulation followed by necroptosis in both parental and tamoxifen-resistant breast cancer cell lines, highlighting its potential application in breast cancer treatment.

In proteomics research, samples are frequently stored at −20 °C and −80 °C for extended periods, and assessing protein stability under these conditions is essential. We evaluated protein stability in healthy and diseased mice liver tissues stored at 4 °C, −20 °C, and −80 °C for 0, 7, 30, 90, and 180 days. A 10% variation in protein concentrations (by day 90, p < 0.001) was observed via BCA assay across all conditions. Untargeted proteomic analysis was performed using in-solution trypsin digestion and LC-Q-Orbitrap-MS/MS, with data processed using Proteome Discoverer 2.5. Proteins were shortlisted based on ≥2 unique peptides, FDR < 1%, and abundance ratio p ≤ 0.001. Differentially expressed proteins were identified using log 2 FC ± 2, p-adj ≤ 0.05. Protein degradation varied with storage conditions. In healthy tissues, 24, 11, and 8 proteins completely degraded at 4 °C, −20 °C, and −80 °C, respectively, after 7 days, compared to 8, 2, and 3 proteins in diseased tissues. The total number of significant proteins consistently identified across all time points in healthy samples was 2570, 2711, and 2617, and in diseased samples it was 2124, 2414, and 2353 at 4 °C, −20 °C, and −80 °C, respectively. RNA-binding proteins, such as La ribonucleoprotein 1B, Reticulophagy regulator 3, and Telomerase RNA component interacting RNase, were particularly prone to degradation across all conditions within 7 days. Notably, 18 degraded proteins were reported as biomarkers in disease conditions. Although −20 °C and −80 °C provided better preservation, residual instability persisted. Optimizing storage conditions is essential to prevent degradation, particularly for biomarker discovery studies.

Understanding metabolic alterations in CKD is crucial, as serum creatinine-based diagnosis lacks precision, affecting key clinical decisions. In this study, a ¹H NMR-based metabolomics approach was employed to distinguish between advanced-stage CKD (ASCKD) patients and healthy controls (HC), as well as within the ASCKD stages (stage 4 and stage 5). Serum samples from 52 ASCKD (S4, S5) and 25 HC were analyzed. Multivariate and univariate analysis revealed distinct metabolic patterns across groups, providing insights into CKD pathophysiology and associated pathway alterations. Compared to HC, six metabolites were significantly altered in both stage 4 and 5 CKD patients with upregulated creatinine, urea, myoinositol, choline, N,N-dimethylglycine, and downregulated tyrosine, showing potential as biomarkers with AUC above 0.8 in ROC analysis. Additionally, myo-inositol, dimethylamine, N,N-dimethylglycine, and choline correlate positively with creatinine while tyrosine correlates negatively. Amino acid metabolism was downregulated in S5 indicating more severity. Within ASCKD patients, significant alterations were observed in metabolites such as glutamate, glutamine, alanine, threonine, myo-inositol, dimethylamine, citrulline, urea, citrate, and betaine. Pathway analysis identified five distinct metabolic pathways associated with CKD progression. Consequently, we propose a panel of serum metabolites which should be monitored along with creatinine for following CKD progression. Markers of oxidative stress, inflammation, and gut dysbiosis were evident in the perturbed metabolic profile due to the systemic impact of CKD.