Multi-omics analyses of 398 foxtail millet accessions reveal genomic regions associated with domestication, metabolite traits and anti-inflammatory effects
Project description:The incorporation of multi-omics data methodologies facilitates the concurrent examination of proteins, metabolites, and genes associated with inflammation, thereby leveraging multi-dimensional biological data to achieve a comprehensive understanding of the complexities involved in the progression of inflammation. Inspired by ensemble learning principles, we implemented ID normalization preprocessing, categorical sampling homogenization, and pathway enrichment across each sample matrix derived from multi-omics datasets available in the literature, directing our focus on inflammation-related targets within lipopolysaccharide (LPS)-stimulated RAW264.7 cells towards β-alanine metabolism. Additionally, through the use of LPS-treated RAW264.7 cells, we tentatively validated the anti-inflammatory properties of the metabolite Ureidopropionic acid, originating from β-alanine metabolism, by evaluating cell viability, nitric oxide production levels, and mRNA expression of inflammatory biomarkers. In conclusion, our research represents the first instance of an integrated analysis of multi-omics datasets pertaining to LPS-stimulated RAW264.7 cells as documented in the literature, underscoring the pivotal role of β-alanine metabolism in cellular inflammation and successfully identifying Ureidopropionic acid as a novel anti-inflammatory compound. Moreover, the findings from database predictions and molecular docking studies indicated that the inflammatory-related pathways and proteins may serve as potential mechanistic targets for Ureidopropionic acid.
Project description:BackgroundThe pathology of keloid and especially the roles of bacteria on it were not well understood.MethodsIn this study, multi-omics analyses including microbiome, metaproteomics, metabolomic, single-cell transcriptome and cell-derived xenograft (CDX) mice model were used to explore the roles of bacteria on keloid disease.FindingsWe found that the types of bacteria are significantly different between keloid and healthy skin. The 16S rRNA sequencing and metaproteomics showed that more catalase (CAT) negative bacteria, Clostridium and Roseburia existed in keloid compared with the adjacent healthy skin. In addition, protein mass spectrometry shows that CAT is one of the differentially expressed proteins (DEPs). Overexpression of CAT inhibited the proliferation, migration and invasion of keloid fibroblasts, and these characteristics were opposite when CAT was knocked down. Furthermore, the CDX model showed that Clostridium butyricum promote the growth of patient's keloid fibroblasts in BALB/c female nude mice, while CAT positive bacteria Bacillus subtilis inhibited it. Single-cell RNA sequencing verified that oxidative stress was up-regulated and CAT was down-regulated in mesenchymal-like fibroblasts of keloid.InterpretationIn conclusion, our findings suggest that bacteria and CAT contribute to keloid disease.FundingA full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Project description:Phospholipase C gamma-2 (PLCγ2) catalyzes the hydrolysis of the membrane phosphatidylinositol-4,5-bisphosphate (PIP2) to form diacylglycerol (DAG) and inositol trisphosphate (IP3), which subsequently feed into numerous downstream signaling pathways. PLCG2 polymorphisms are associated with both reduced and increased risk of Alzheimer's disease (AD) and with longevity. In the brain, PLCG2 is highly expressed in microglia, where it is proposed to regulate phagocytosis, secretion of cytokines/chemokines, cell survival and proliferation. We analyzed the brains of three-month-old PLCγ2 knockout (KO), heterozygous (HET), and wild-type (WT) mice using multiomics approaches, including shotgun lipidomics, proteomics, and gene expression profiling, and immunofluorescence. Lipidomic analyses revealed sex-specific losses of total cerebrum PIP2 and decreasing trends of DAG content in KOs. In addition, PLCγ2 depletion led to significant losses of myelin-specific lipids and decreasing trends of myelin-enriched lipids. Consistent with our lipidomics results, RNA profiling revealed sex-specific changes in the expression levels of several myelin-related genes. Further, consistent with the available literature, gene expression profiling revealed subtle changes on microglia phenotype in mature adult KOs under baseline conditions, suggestive of reduced microglia reactivity. Immunohistochemistry confirmed subtle differences in density of microglia and oligodendrocytes in KOs. Exploratory proteomic pathway analyses revealed changes in KO and HET females compared to WTs, with over-abundant proteins pointing to mTOR signaling, and under-abundant proteins to oligodendrocytes. Overall, our data indicate that loss of PLCγ2 has subtle effects on brain homeostasis that may underlie enhanced vulnerability to AD pathology and aging via novel mechanisms in addition to regulation of microglia function.
Project description:Maize vivipary, precocious seed germination on the ear, affects yield and seed quality. The application of multi-omics approaches, such as transcriptomics or metabolomics, to classic vivipary mutants can potentially reveal the underlying mechanism. Seven maize vivipary mutants were selected for transcriptomic and metabolomic analyses. A suite of transporters and transcription factors were found to be upregulated in all mutants, indicating that their functions are required during seed germination. Moreover, vivipary mutants exhibited a uniform expression pattern of genes related to abscisic acid (ABA) biosynthesis, gibberellin (GA) biosynthesis, and ABA core signaling. NCED4 (Zm00001d007876), which is involved in ABA biosynthesis, was markedly downregulated and GA3ox (Zm00001d039634) was upregulated in all vivipary mutants, indicating antagonism between these two phytohormones. The ABA core signaling components (PYL-ABI1-SnRK2-ABI3) were affected in most of the mutants, but the expression of these genes was not significantly different between the vp8 mutant and wild-type seeds. Metabolomics analysis integrated with co-expression network analysis identified unique metabolites, their corresponding pathways, and the gene networks affected by each individual mutation. Collectively, our multi-omics analyses characterized the transcriptional and metabolic landscape during vivipary, providing a valuable resource for improving seed quality.
Project description:Obesity has become a global epidemic, associated with several chronic complications. The intestinal microbiome is a critical regulator of metabolic homeostasis and obesity. Empagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, has putative anti-obesity effects. In this study, we used multi-omics analysis to determine whether empagliflozin regulates metabolism in an obese host through the intestinal microbiota. Compared with obese mice, the empagliflozin-treated mice had a higher species diversity of gut microbiota, characterized by a reduction in the Firmicutes/Bacteroides ratio. Metabolomic analysis unambiguously identified 1,065 small molecules with empagliflozin affecting metabolites mainly enriched in amino acid metabolism, such as tryptophan metabolism. RNA sequencing results showed that immunoglobulin A and peroxisome proliferator-activated receptor signaling pathways in the intestinal immune network were activated after empagliflozin treatment. This integrative analysis highlighted that empagliflozin maintains intestinal homeostasis by modulating gut microbiota diversity and tryptophan metabolism. This will inform the development of therapies for obesity based on host-microbe interactions.
Project description:Gossypol is an antiproliferative drug with limited use due to its hemolytic toxicity. In this study, accelerated hemolysis was observed in the cows treated with gossypol. Comparative metabolomics were used to gain responsive pathways in the red blood cell (RBC) to the treatment, which were crossly validated by parallel iTRAQ-based proteomic analysis and enzyme activity assay. We found that gossypol treatment appeared to considerably activate pentose phosphate pathway (PPP) with an increased key product of ribose-5-phosphate and the increased abundance and activity of several key enzymes such as 6-phosphogluconate dehydrogenase, flavin reductase, and ribose-phosphate pyrophesphokinase. Meanwhile, a decreased glycolysis metabolism was observed, as many input metabolites of glycolysis were reduced in the gossypol group, whereas its distal metabolites were unchanged, along with decreased abundance of triosephosphate isomerase and increased abundance of enzymes catalyzing several distal glycolytic steps. Oxidative reduction pathways were also remarkably affected as we found a decreased substrate of flavin reductase, glutathione disulfide, increased glutathione reductase activity, and increased abundance and activity of glutathione S-transferase with the increase of its catalytic product, cysteine. Our results demonstrated that glycolysis, PPP, and oxidative reduction pathways of RBC were all involved in RBC's response to the hemolytic toxicity of gossypol.
Project description:Glioblastoma (GBM) is the most common and aggressive malignant brain tumor with poor prognosis. Temozolomide (TMZ) is the standard chemotherapy for glioblastoma treatment, but TMZ resistance significantly compromises its efficacy. In the present study, we generated a TMZ-resistant cell line and identified that mitochondrial dysfunction was a novel factor contributing to TMZ resistance though multi-omics analyses and energy metabolism analysis. Furthermore, we found that rotenone treatment induced TMZ resistance to a certain level in glioblastoma cells. Notably, we further demonstrated that elevated Ca2+ levels and JNK-STAT3 pathway activation contributed to TMZ resistance and that inhibiting JNK or STAT3 increases susceptibility to TMZ. Taken together, our results indicate that co-administering TMZ with a JNK or STAT3 inhibitor holds promise as a potentially effective treatment for glioblastoma.
Project description:BackgroundLittle is known about the interplay among dairy intake, gut microbiota and cardiometabolic health in human prospective cohort studies.MethodsThe present study included 1780 participants from the Guangzhou Nutrition and Health Study. We examined the prospective association between habitual dairy consumption (total dairy, milk, yogurt) and gut microbial composition using linear regression after adjusting for socio-demographic, lifestyle and dietary factors. The cross-sectional association of dairy-associated microbial features with cardiometabolic risk factors was examined with a linear regression model, adjusting for potential confounders. Serum metabolomic profiles were analyzed by partial correlation analysis.FindingsThere was a significant overall difference in gut microbial community structure (β-diversity) comparing the highest with the lowest category for each of total dairy, milk and yogurt (P < 0.05). We observed that dairy-associated microbes and α-diversity indices were inversely associated with blood triglycerides, while positively associated with high-density lipoprotein cholesterol. A follow-up metabolomics analysis revealed the association of targeted serum metabolites with dairy-microbial features and cardiometabolic traits. Specifically, 2-hydroxy-3-methylbutyric acid, 2-hydroxybutyric acid and L-alanine were inversely associated with dairy-microbial score, while positively associated with triglycerides (FDR-corrected P < 0.1).InterpretationDairy consumption is associated with the gut microbial composition and a higher α-diversity, which provides new insights into the understanding of dairy-gut microbiota interactions and their relationship with cardiometabolic health.FundingThis work was supported by the National Natural Science Foundation of China, Zhejiang Ten-thousand Talents Program, Westlake University and the 5010 Program for Clinical Researches of the Sun Yat-sen University.
Project description:Diquat (DQ), a widely used bipyridyl herbicide, is associated with significantly higher rates of kidney injuries compared to other pesticides. However, the underlying molecular mechanisms are largely unknown. In this study, we identified the molecular changes in the early stage of DQ-induced kidney damage in a mouse model through transcriptomic, proteomic and metabolomic analyses. We identified 869 genes, 351 proteins and 96 metabolites that were differentially expressed in the DQ-treated mice relative to the control mice (p < 0.05), and showed significant enrichment in the PPAR signaling pathway and fatty acid metabolism. Hmgcs2, Cyp4a10, Cyp4a14 and Lpl were identified as the major proteins/genes associated with DQ-induced kidney damage. In addition, eicosapentaenoic acid, linoleic acid, palmitic acid and (R)-3-hydroxybutyric acid were the major metabolites related to DQ-induced kidney injury. Overall, the multi-omics analysis showed that DQ-induced kidney damage is associated with dysregulation of the PPAR signaling pathway, and an aberrant increase in Hmgcs2 expression and 3-hydroxybutyric acid levels. Our findings provide new insights into the molecular basis of DQ-induced early kidney damage.
Project description:BackgroundBiopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra-tumoral heterogeneity (ITH) influences biopsy-derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet ).MethodsPrimary tumour superficial (PTsup ), deep (PTdeep ) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole-exome sequencing (WES), whole-transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single-cell transcriptomic dataset was analysed.ResultsWES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup , PTdeep and LNmet , respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra-tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi-omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion.ConclusionsThis study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi-omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.