Multi-omics Analysis Research Articles

Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration.

Mass spectrometry has long been utilized to characterize a variety of biomolecules such as proteins, metabolites, and lipids. Most MS-based omics studies rely on bulk analysis; however, bulk approaches often overlook low-abundance molecules that may exert critical biological effects. Recently, multi-omics analyses have been driving an explosion of knowledge about how biomolecules interact within biological systems. In particular, spatial multi-omics has emerged as a groundbreaking approach for implementing multi-omic and multi-modal analyses. Broadly defined, spatial omics has the ability to analyze biomolecules within their native spatial contexts, offering transformative insights. This review focuses on mass spectrometry-based spatial omics, specifically matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We will explore how MALDI-MSI, in combination with laser capture microdissection (LCM) and traditional liquid chromatography-mass spectrometry (LC-MS) workflow, is advancing spatially resolved multi-omics research.

Circadian rhythm and aryl hydrocarbon receptor crosstalk in bone marrow adipose tissue and implications in leukemia

Leukemic cells modulate the bone marrow microenvironment to enhance their survival. Lipolysis in bone marrow adipose tissue (BMAT) has emerged as a critical factor supporting leukemic cell survival, yet understanding its primary role in leukemia development remains limited. Fanconi anemia (FA), characterized by a predisposition to acute myeloid leukemia (AML) and hypersensitivity to environmental toxins, is a transitional model for studying leukemic transformation. İntegrated multi-omics analyses were conducted on BMAT-derived mesenchymal stem/stromal cells (MSCs) from healthy donors (HD), AML, and FA patients. These analyses revealed intricate interactions among genes, metabolites, and lipids. Particularly noteworthy were the effects observed following the inhibition of aryl hydrocarbon receptor (AhR) signaling by StemRegenin1 (SR1). BMAT-MSCs showed increased expression of epithelial-mesenchymal transition (EMT) genes in FA and AML, suggesting a potential shift towards cancer-associated fibroblasts in the dysregulated marrow microenvironment. Identification of potential circadian rhythm biomarkers (NPAS2, PER2, BHLHE40, PER3, CIART) in BMAT-MSCs indicates a link between related lipid metabolism genes (e.g., PTGS1, PIK3R1) and SR1 treatment, implicating them in lipolysis processes. Dysregulation of circadian rhythm-related genes (CIART, BHLHE40, NPAS2) in AML BMAT-MSCs, along with changes in circulating lipid metabolites like palmitate suggests their role in shaping the leukemia microenvironment. Upregulation of FABP5 and CD36 suggests a novel molecular mechanism involving FABP5 in AhR-mediated circadian regulation and identifies CD36 as a potential partner for FABP5 in BMAT-MSCs. Overall, this study unveils the interplay between AhR signaling, circadian rhythm, and the leukemia microenvironment in BMAT-MSCs, offering new insights into leukemia pathogenesis and therapeutic opportunities.

Multi-omic analysis reveals a CAF-stemness-governed classification in HCC liver transplant recipients beyond the Milan criteria

Multi-omic analysis reveals a CAF-stemness-governed classification in HCC liver transplant recipients beyond the Milan criteria

A simplified and efficient method for isolating small extracellular vesicles for comparative and comprehensive translational research

Small extracellular vesicles (sEVs) can provide information about the pathophysiology of the cells; therefore, sEVs have attracted considerable interest as possible diagnostic biomarkers. A key challenge lies in the necessity for simple and cost-effective sEV isolation methods to achieve high purity and yield suitable for research and clinical applications. We are introducing a comprehensive study on isolating sEVs using a novel cocktail strategy that integrates chemical precipitation and ultrafiltration with a two-step filtering process to ensure a highly pure and homogeneous population and further compared with PEG-based precipitation, ultra-centrifugation, and size-exclusion-chromatography columns. The isolated sEVs from each protocol are quantified for size and yield using nanoparticle tracking analysis, morphologically characterized through transmission electron microscopy, and validated by quantifying the expression profiles of sEV surface biomarkers. Furthermore, the study explores the applicability of our method for downstream multi-omics analyses. The results highlight the efficacy of the proposed protocol, demonstrating the ease and efficiency of isolating sEVs from different biofluids with minimal laboratory requirements and confirming the compatibility with multi-omics analyses. These findings position our method as particularly valuable for translational research, offering a promising avenue for advancing the study and application of sEVs in diagnostic and therapeutic research.

Synergistic effect of grassland plants and beneficial rhizosphere bacteria helps plants cope with overgrazing stress

BackgroundOvergrazing (OG) is an important driver of grassland degradation and productivity decline. Highly effective synergy between plants and rhizosphere growth-promoting rhizobacteria (PGPR) may be a major way for grassland plants to effectively cope with OG stress. There have been few reports providing solid evidence on how this synergy occurs.ResultThis study combined with multi-omics analysis and the interaction effect of specific root exudate with PGPR B68, aiming to reveal the synergistic effect and regulatory mechanism of L. chinensis and PGPR under overgrazing stress. The results showed that Leymus chinensis plants with OG history can recruit the beneficial Phyllobacterium sp. B68 by regulating specific root exudate compounds(such as amino acid L-leucyl-L-alanine and alkaloid cordycepin). These compounds enhanced B68 rhizosphere colonization by promoting B68 chemotaxis and biofilm formation. The pot study experiments indicated that the bacterial isolates used as bio inoculants increased L. chinensis growth (mainly including plant height and biomass) by significantly increasing the chlorophyll content, RuBisCO activity, soluble sugar, plant hormones and nutrient content. Metagenomics results show that B68 inoculation significantly altered rhizosphere soil bacterial community composition and function. Additionally, B68 systemically upregulated the expression level of genes involved in plant hormone signaling, nutrient and sugar transporters, nitrogen metabolism, cell division, cell wall modification and photosynthesis to promote plant growth. The above results indicate that the PGPR B68 recruited by the root exudates of L. chinensis under OG helps the plant adapt to stress by promoting nutrient uptake and transport, maintaining hormone homeostasis, and enhancing the expression of genes related to plant growth and nutrient metabolism.ConclusionThis study provides new insights into the positive interactions between grassland plants and rhizosphere bacteria under OG stress, offering valuable knowledge for developing new fertilizers and better management practices for degraded rangeland restoration and sustainable agriculture development.Clinical trial numberNot applicable.

Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and a leading cause of cancer-related deaths globally. The tumour microenvironment (TME) influences treatment response and prognosis, yet its heterogeneity remains unclear.MethodsThe unsupervised machine learning methods— agglomerative hierarchical clustering, Multi-Omics Factor Analysis with K-means++, and an autoencoder with K-means++ — stratified patients using microarray data from HCC samples. Immune deconvolution algorithms estimated the proportions of infiltrating immune cells across identified clusters.ResultsThirteen genes were found to influence HCC subtyping in both primary and validation datasets, with three genes—TOP2A, DCN, and MT1E—showing significant associations with survival and recurrence. DCN, a known tumour suppressor, was significant across datasets and associated with improved survival, potentially by modulating the TME and promoting an anti-tumour immune response.ConclusionsThe discovery of the 13 conserved genes is an important step toward understanding HCC heterogeneity and the TME, potentially leading to the identification of more reliable biomarkers and therapeutic targets. We have stratified and validated the liver cancer populations. The findings suggest further research is needed to explore additional factors influencing the TME beyond gene expression, such as tumour microbiome and stromal cell interactions.

CLN5 deficiency impairs glucose uptake and uncovers PHGDH as a potential biomarker in Batten disease.

CLN5 disease, a form of juvenile dementia within the neuronal ceroid lipofuscinosis (NCL), is associated with mutations in the CLN5 gene encoding the lysosomal bis(monoacylglycero)phosphate (BMP) synthase, essential for BMP production and lysosomal function. Limited knowledge of cellular mechanisms and unclear drug targets hinder translating this to children's treatment, which remains symptomatic. We developed and characterized a new cln5 knock-out zebrafish model that replicates key features and molecular signatures of the human disease. Loss of Cln5 function in vivo altered axonal growth of retinal ON-bipolar cells and disrupted calcium homeostasis in the cerebellum, revealing new disease features. Additionally, multi-omic analyses at different developmental stages revealed an impaired glucose metabolism as an original finding in NCL. A novel biomarker, PHGDH, was validated in zebrafish and human skin fibroblasts harboring pathogenic variants in CLN5, and in CLN7. We also tested metformin which improved the expression of PHGDH in patient-derived cells, and rescued zebrafish behavior. This work demonstrates the profound metabolic impact of CLN5 dysfunction, offering a promising avenue toward targeted therapies for juvenile dementia.

Yeast Culture Supplementation Improves Meat Quality by Enhancing Immune Response and Purine Metabolism of Small-Tail Han Sheep (Ovis aries)

Yeast culture is widely used in ruminants to improve gut health, immunity, and productivity; however, its impact on meat quality remains unclear. This study aimed to investigate the effects of yeast culture supplementation in the basic diet on meat quality of Small-tail Han sheep. A total of 40 Small-tail Han sheep (17.5 ± 1.2 kg) were randomly assigned to two treatment groups, with 20 sheep in each group. The sheep were fed either a basic diet (CON) or the basic diet supplemented with 1% yeast culture (YSD) for 90 days. At the end of the trial, the Longissimus dorsi muscle (LOD) of the sheep was collected for meat quality evaluation, as well as transcriptome and metabolome analyses. Meat quality data were analyzed using t-tests, while transcriptome and metabolome data were analyzed using bioinformatics tools. The results showed that YSD supplementation significantly reduced carcass fat content (p < 0.05) and increased the pH values (p < 0.05) of LOD compared to the CON group. Multi-omics analysis revealed significant changes in the levels of 349 transcripts and 149 metabolites (p < 0.05) in the YSD group relative to the CON group. These changes were primarily associated with immune response pathways and purine metabolism. Further integrated transcriptomics and metabolomics analysis identified significant alterations in the expression of adenylate kinase 4 (AK4) and ribonucleotide reductase M2 (RRM2), which influenced purine metabolites, such as ADP, GMP, 3′-AMP, 3′-GMP, dGDP, adenine, guanosine, and guanine. These metabolites were markedly upregulated in the LOD of the sheep supplemented with yeast culture. In conclusion, yeast culture supplementation improved the meat quality of Small-tail Han sheep, potentially through the enhancement of immune response and purine metabolism. These findings offer valuable insights into the molecular mechanisms underlying the effects of yeast culture on animal health and meat quality.

Multi-omics analysis of USP8 mutated and wild type corticotroph pituitary tumors enhances understanding of tumorigenesis, proliferation, immune response and hormone excess in Cushing's disease

Multi-omics analysis of USP8 mutated and wild type corticotroph pituitary tumors enhances understanding of tumorigenesis, proliferation, immune response and hormone excess in Cushing's disease

New therapeutic targets and mechanisms of papillary thyroid carcinoma identified by multi-omics analysis

IntroductionThe treatment of papillary thyroid carcinoma (PTC) presents ongoing challenges, underscoring the need for novel therapeutic targets.MethodsThis study employed proteomic MR analysis, utilizing publicly available data from genome-wide association studies (GWAS) and protein quantitative trait loci (pQTL) studies. We analyzed proteomic data from deCODE and the UK Biobank Protein Project (UKB-PP), along with GWAS data on papillary thyroid carcinoma (PTC) from the Finnish Consortium. This analysis was further supported by eQTL validation and bioinformatics differential analysis to identify potential therapeutic targets for PTC. Additionally, we explored possible downstream mechanisms of the target proteins through mediation analysis. ResultsOur analysis identified two potential therapeutic targets associated with PTC, specifically, LY75 and S100A12. Mediation analysis further investigated their potential mechanistic role in the pathogenesis of PTC.ConclusionThrough multi-omics analysis, we identified new potential therapeutic targets for papillary thyroid carcinoma and investigated their possible underlying mechanisms affecting PTC.

Integrated multi-omics analysis and functional validation uncovers RPL26 roles in regulating growth traits of Asian water buffaloes (Bubalus bubalis)

BackgroundAsian water buffaloes (Bubalus bubalis) in the Yangtze River Basin of China are the important meat provider for local residents because of its outstanding body size. Several previous studies have highlighted their genetic basis of growth characteristics, but the crucial genes regulating growth traits via multi-layer omics are still rarely investigated.ResultsWe conducted a comprehensive multi-omics analysis integrating blood and muscle transcriptome, plasma metabolome, rumen fluid metagenome, and genome of Haizi water buffaloes. Of note, ribosomal protein L26 (RPL26) located in the evolutionary selection regions associated with body sizes is the top differentially expressed gene (DEG) in both blood and muscle tissues. Further metabolomics and metagenomics identified growth-related molecular biomarkers (myristicin and Bacteroidales) and microbiological composition (Bacteroides and Prevotella). Leveraging cattle quantitative trait loci (QTLs) and genotype-tissue expression (CattleGTEx) databases, we found the significant correlations of QTL_180979 on RPL26 and two identified cis-eQTLs in muscle tissue in the upstream of RPL26 with weight gain. The follow-up cell assay validations confirmed the regulation roles of RPL26 in cell cycle, apoptosis, and differentiation, where the low RPL26 expressions enhanced the antiapoptotic ability and promoted the differentiation of myoblasts into myotubes markedly.ConclusionsOur study illustrates RPL26 roles in regulating growth traits via both integrated multi-omics analysis and functional validations that suggests the further applications of RPL26 for growth trait selection of water buffaloes.

Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census

BackgroundAlthough immune checkpoint inhibitors (ICIs) represent a substantial breakthrough in cancer treatment, it is crucial to acknowledge that their efficacy is limited to a subset of patients. The heterogeneity and stemness of cancer render its response to immunotherapy variable, warranting the identification of robust biomarkers for evaluation.MethodsPublicly available Ovarian Cancer (OV) single-cell RNA (scRNA) sequence dataset was collected and analyzed to elucidate the intrinsic driver gene of OV cancer cells. Through genome-scale CRISPR screening of RNA sequencing data from Project Achilles, essential genes specific to OV were identified. A novel cancer stem cell index (CSCI) was developed and validated using multiple advanced algorithms and large-scale datasets, as well as corresponding clinical features, including 14 OV transcriptomic datasets, 7 pan-cancer ICI transcriptomic cohorts and one melanoma scRNA dataset derived from PD-1 treated patients.ResultsChromosomal 20q gain, 8q gain, and 5q loss have been identified as ovarian cancer-specific driving variations. By analyzing large-scale datasets of ovarian cancer transcriptomics, including scRNA and CRISPR cell line datasets, we have identified a gene set that influences tumor intrinsic drivers and stemness properties. We then developed the CSCI to predict the prognosis and response to immunotherapy in ovarian cancer patients using advanced machine learning algorithms. When applied to PD1/PD-L1 ICI transcriptomic cohorts, CSCI consistently and accurately predicts tumor progression and immunotherapy benefits, with a mean AUC greater than 0.8. Notably, compared to previously established signatures, CSCI demonstrates better predictive performance across multiple ovarian cancer datasets. Intriguingly, we discovered that amplification of CSE1L enhances the stemness of tumor-initiating cells, facilitates angiogenesis, and the formation of ovarian cancer, which can serve as a potential therapeutic target. Finally, experiments validated that CSE1L promotes progression, migration, and proliferation of ovarian cancer.ConclusionsOur study has uncovered a robust correlation between variations in cancer intrinsic drivers and stemness, as well as resistance to immunotherapy. This finding provides valuable insights for potential strategies to overcome immune resistance by targeting genes associated with stemness.

Multiomics analysis unveils an inosine-sensitive DNA damage response in neurogenic bladder after spinal cord injury.

Spinal cord injury (SCI) evokes profound dysfunction in hollow organs such as the urinary bladder and gut. Current treatments are limited by a lack of molecular data to inform novel therapeutic avenues. Previously, we showed systemic treatment with the neuroprotective agent inosine improved bladder function following SCI in rats. Here, we applied integrated multi-omics analysis to explore molecular alterations in the bladder over time and their sensitivity to inosine following SCI. Canonical signaling pathways regulated by SCI included those associated with protein synthesis, neuroplasticity, wound healing, and neurotransmitter degradation. Upstream regulator and causal network analysis predicted multiple effectors of DNA damage response signaling following injury, including PARP1. Markers of DNA damage (gammaH2AX, ATM/ATR substrates) and PARP activity (poly-ADP-ribose) were increased in bladder tissue following SCI and attenuated with inosine treatment. Inosine treatment also attenuated oxidative DNA damage in rat bladder cells in vitro. Proteomics analysis suggested that SCI induced changes in protein synthesis-, neuroplasticity-, and oxidative stress-associated pathways, a subset of which were shown in transcriptomics data to be inosine-sensitive. These findings provide insights into the molecular landscape of the bladder following SCI and identify key inosine-sensitive pathways associated with injury.

LMO2 confers value as a potential immunotherapy marker in pan-cancer analysis and inhibits progression of Clear Cell Renal Cell Carcinoma.

LMO2 confers value as a potential immunotherapy marker in pan-cancer analysis and inhibits progression of Clear Cell Renal Cell Carcinoma.

Advancing Toward a World Without Vision Loss From Diabetes: Insights From The Mary Tyler Moore Vision Initiative Symposium 2024 on Curing Vision Loss From Diabetes.

The Mary Tyler Moore Vision Initiative (MTM Vision) honors Mary Tyler Moore's commitment to ending vision loss from diabetes. Founded by Moore's husband, Dr. S. Robert Levine, MTM Vision aims to accelerate breakthroughs in diabetic retinal disease (DRD). At the MTM Vision Symposium 2024 on Curing Vision Loss from Diabetes, experts highlighted the urgent need for updated DRD staging systems, clinically relevant endpoints, and novel biomarkers to detect early disease changes. MTM Vision is advancing two clinical trials in collaboration with the DRCR Retina Network, launching a public awareness campaign, and welcoming Boehringer Ingelheim as the first founding industry member of its pre-competitive Consortium. Speakers emphasized big-data strategies and artificial intelligence (AI)-driven tools to improve DRD diagnosis, risk prediction, and personalized treatment. They also showcased new efforts to bridge academic discoveries with industry expertise, illustrating promising work on vascular regeneration and cellular senescence that may yield future therapies. The MTM Vision Biorepository and Resource Center is expanding tissue collections, enabling multi-omics analyses to study DRD mechanisms. Patient voices were central to the discussion, with calls for enhanced patient-reported outcomes, caregiver support, and broader education on DRD's risks. The symposium also underscored the importance of integrating mental health, quality of life measures, and ongoing patient input to guide clinical research.

Integrated multi-omics analysis of metabolome and transcriptome profiles during bovine adipocyte differentiation reveals functional divergence of FADS2 isoforms in lipid metabolism regulation

BackgroundFat metabolism plays an important role in animal health and economic benefits. However, the changes in gene expression and metabolites during fat metabolism have not been systematically studied in bovine.ResultsThis study integrates transcriptomic and metabolomic strategies to delineate the metabolic and gene expression profiles during the adipogenesis of bovine preadipocytes in four different stages. Totally, we identified 328 differentially expressed metabolites (DEMs) and 5257 differentially expressed genes (DEGs) during adipogenesis. Functional enrichment of both DEMs and DEGs highlighted the important roles of fatty acid metabolic pathways. By integrating transcriptomic and metabolomic data, we identified key genes potentially regulating fatty acid metabolism, including FADS2, ACOT7 and ACOT2. We further applied comparison for the functional differences between two FADS2 isoforms (FADS2-T0 and FADS2-T2). The results proved that the lipid metabolism regulated by FADS2-2 has changed due to the loss of 46 amino acids with a transmembrane domain, which finally altering its promoting effect on bovine fat deposition.ConclusionsIn summary, our research provides important resources and key candidate genes for a systematic understanding of the changes in gene expression and lipid metabolism during the process of fat deposition.

Identification of Key Biomarkers of Growth-Related Traits in the Bay Scallop Argopecten irradians irradians via Multi-omics Analysis Strategies.

In an attempt to promote and advance molecular-assisted selective breeding of shellfish, in this study, gills from selected (shell color as the marker trait and growth performance as the target trait) and unselected Argopecten irradians irradians were sampled. 2b-restriction site-associated DNA sequencing, genome-wide association study, comparative transcriptome, comparative small RNA transcriptome, miRNA-mRNA integrated analysis, quantitative real-time reverse transcription-polymerase chain reaction, and weighted gene co-expression network analysis were used to identify candidate SNPs, mRNAs, miRNAs, and miRNA/mRNA pairs with potential selective breeding value at a genomic scale in A. irradians irradians. The results revealed that a total of 6 significant SNPs were correlated closely with at least two examined growth-related traits. In addition, a total of 10 mRNAs and 7 miRNAs were identified to have positive correlations with shell length, shell height, shell width, total weight, and shell color. These candidate mRNAs and miRNAs may form 11 miRNA-mRNA pairs, which have great potential for developing molecular markers for molecular-assisted selective breeding of A. irradians irradians. The findings of this study will benefit the development of molecular-assisted breeding techniques in bay scallop aquaculture.

The Key Role and Mechanism of Oxidative Stress in Hypertrophic Cardiomyopathy: A Systematic Exploration Based on Multi-Omics Analysis and Experimental Validation

Hypertrophic cardiomyopathy (HCM), characterised by abnormal ventricular thickening, involves complex mechanisms including gene mutations, calcium dysregulation, mitochondrial dysfunction, and oxidative stress. Oxidative stress plays a pivotal role in the progression of HCM by mediating cardiomyocyte injury and remodelling. This study systematically analysed HCM transcriptomic data using differential gene expression, weighted gene co-expression network analysis (WGCNA), and unsupervised consensus clustering to identify key genes and classify HCM subtypes. Four oxidative stress-related characteristic genes (DUSP1, CCND1, STAT3, and THBS1) were identified using LASSO regression, SVM-RFE, and Random Forest algorithms. Their functional significance was validated by immune infiltration analysis, drug prediction using the cMAP database, and molecular docking. Single-cell RNA sequencing revealed their cell-type-specific expression, and in vitro experiments confirmed their role in HCM. These findings provide insights into oxidative stress mechanisms and potential therapeutic targets for HCM.

A multiomic analysis of Waldenström macroglobulinemia defines distinct disease subtypes.

A multiomic analysis of Waldenström macroglobulinemia defines distinct disease subtypes.

Different Commercial Microbial Additives Influence Fermentation Quality and Microbial Community of King Grass Silage

The microbiota in forage silage plays a pivotal role in determining the fermentation quality. Identifying effective microbial additives is essential to help forage producers refine their search for functional inoculants and to support farmers in adopting them for practical ensiling. This study investigated microbial and metabolomic dynamics in king grass silages treated with six commercial inoculants dominated by Enterococcus faecium-like species, Bacillus velezensis, and Lactobacillus paraplantarum. The fermentation characteristics, viable microbial diversity, and metabolite profiles were compared between treated and untreated silages using 16S rDNA sequencing and metabolic profiling via LC-QTOF-MS, integrated with multi-omics correlation analyses. Additive-treated silages showed improved fermentation quality, simplified bacterial correlation networks, and distinct microbial successions and interactions. A total of 1523 metabolites were detected, with 56–84 significantly altered in each treated group compared to the control. Metabolites with antimicrobial, antioxidant, and cholesterol-lowering activities were more abundant in treated silages, especially organic acids, amino acids, and short-chain fatty acids. Inoculants distinctly influenced amino acid, energy, nucleotide, and vitamin metabolism during ensiling. This study advances our understanding of how commercial microbial additives reshape the bacterial community structure and function in silages and highlights promising lactic acid bacteria species contributing to silage quality through the production of bio-functional metabolites.