Molecular omics最新文献

Women coinfected with human immunodeficiency virus type 1 (HIV-1) and human papillomavirus (HPV) are six times as likely to develop invasive cervical carcinoma compared to those without HIV. Unlike other HIV-associated cancers, the risk of cervical cancer development does not change when HPV/HIV coinfected women begin antiretroviral therapy, suggesting HIV-associated immune suppression is not a key driver of cervical cancer development in coinfected women. Here, we investigated whether the persistent secretion of inflammatory factors in HIV-positive patients on antiretroviral therapy could enhance cancer signaling in HPV-infected cervical cells via endocrine mechanisms. We integrated previously reported HIV-induced secreted inflammatory factors (Hi-SIFs), HIV and HPV virus–human protein interactions, and cervical cancer patient genomic data using network propagation to understand the pathways underlying disease development in HPV/HIV coinfection. Our results pinpointed the PI3K-AKT signaling pathway to be enriched at the interface between Hi-SIFs and HPV–host molecular networks, in alignment with PI3K pathway mutations being prominent drivers of HPV-associated, but HIV independent, cervical cancer development. Furthermore, we experimentally stimulated cervical cells with 14 Hi-SIFs to assess their ability to activate PI3K-AKT signaling. Strikingly, we found 8 factors (CD14, CXCL11, CXCL9, CXCL13, CXCL17, AHSG, CCL18, and MMP-1) to significantly upregulate AKT phosphorylation (pAKT-S473) relative to a phosphate buffered saline control. Our findings suggest that Hi-SIFs cooperate with HPV infection in cervical cells to over-activate PI3K-AKT signaling, effectively phenocopying PI3K-AKT pathway mutations, resulting in enhanced cervical cancer development in coinfected women. Our insights could support the design of therapeutic interventions targeting the PI3K-AKT pathway or neutralizing Hi-SIFs in HPV/HIV coinfected cervical cancer patients.

Colorectal cancer (CRC), a common malignant tumour of the gastrointestinal tract, is a life-threatening cancer worldwide. Mutations in KRAS and BRAF, the major driver mutation subtypes in CRC, activate the RAS pathway, contribute to tumorigenesis in CRC and are being investigated as potential therapeutic targets. Despite recent advances in clinical trials targeting KRASG12C or RAS downstream signalling molecules for KRAS-mutant CRC, there is a lack of effective therapeutic interventions. Therefore, understanding the unique molecular characteristics of KRAS-mutant CRC is essential for identifying molecular targets and developing novel therapeutic interventions. We obtained in-depth proteomics and phosphoproteomics quantitative data for over 7900 proteins and 38 700 phosphorylation sites in cells from 35 CRC cell lines and performed informatic analyses, including proteomics-based coexpression analysis and correlation analysis between phosphoproteomics data and cancer dependency scores of the corresponding phosphoproteins. Our results revealed novel dysregulated protein–protein associations enriched specifically in KRAS-mutant cells. Our phosphoproteomics analysis revealed activation of EPHA2 kinase and downstream tight junction signalling in KRAS-mutant cells. Furthermore, the results implicate the phosphorylation site Y378 in the tight junction protein PARD3 as a cancer vulnerability in KRAS-mutant cells. Together, our large-scale phosphoproteomics and proteomics data across 35 steady-state CRC cell lines represent a valuable resource for understanding the molecular characteristics of oncogenic mutations. Our approach to predicting cancer dependency from phosphoproteomics data identified the EPHA2-PARD3 axis as a cancer vulnerability in KRAS-mutant CRC.

Background: The DNA damage repair enzyme, poly(ADP-ribose) polymerase 1 (PARP1), is crucial for lipid and glucose metabolism. However, no evidence has been presented on the relationship between liver lipid accumulation and the PARP1 inhibitor, 3-aminobenzamide (3-AB), in atherosclerosis. Methods: ApoE^−/− mice were used to explore the effect of 3-AB on atherosclerotic liver lipid accumulation, and the experiment of Sprague Dawley (SD) rats was designed to determine if the lowering of liver lipid levels by 3-AB was linked to gut bacteria. The levels of bile acid metabolism-related targets were assessed by ELISA, western blotting, and RT-qPCR. The relative abundances of gut microbes and biomarkers were determined using 16S rRNA sequencing analysis. Bile acid levels in the liver and ileum were examined by ultra-performance liquid chromatography-tandem mass spectrometry. The relationship between gut microbes and bile acids was assessed by Spearman's correlation analysis. Results: 3-AB significantly reduced the formation of aortic plaques in apoE^−/− mice, according to gross oil red staining. H & E and Oil Red O staining revealed that 3-AB significantly reduced the hepatic lipid droplet area in ApoE^−/− mice and SD rats. Compared with the atherosclerosis (ATH) group, 3-AB dramatically decreased the levels of total cholesterol (TC), triglyceride (TG), and low-density lipoprotein-cholesterol (LDL-C) in the serum of SD rats and apoE^−/− mice, and the levels of TC, TG, and LDL-C in the serum and liver of apoE^−/− mice. Furthermore, in apoE^−/− mice and SD rats, 3-AB increased the mRNA and protein levels of farnesoid X receptor (FXR) and bile salt export pump (BSEP) in the liver, while inhibiting the mRNA and protein levels of FXR and fibroblast growth factor 15 (FGF15) in the ileum, respectively. 3-AB clearly inhibited the mRNA and protein levels of PARP1 in the liver and ileum of apoE^−/− mice and rats. Following treatment with 3-AB, the levels of conjugated bile acids decreased in the liver of apoE^−/− mice and increased in the ileum of SD rats, according to targeted metabolomic analysis. Microbiome sequencing analysis revealed that 3-AB reduced the relative abundance of Lactobacillus, Bifidobacterium, Listeria, Clostridium, Bacillus, and Staphylococcus in the feces of apoE^−/− mice, and the relative abundance of Blautia, Clostridium, and Listeria in the feces of SD rats, eventually decreasing the total abundance of 10 bile salt hydrolase-associated gut microbes. According to the correlation analysis, 3-AB regulates bile acid metab

Food metabolomics is described as the implementation of metabolomics to food systems such as food materials, food processing, and food nutrition. These applications generally create large amounts of data, and although technologies exist to analyze these data and different tools exist for various ecosystems, downstream analysis is still a challenge and the tools are not integrated into a single method. In this article, we developed a data processing method for untargeted LC-MS data in metabolomics, derived from the integration of computational MS tools from OpenMS into the workflow system Konstanz Information Miner (KNIME). This method can analyze raw MS data and produce high-quality visualization. A MS1 spectra-based identification, two MS2 spectra-based identification workflows and a GNPSExport-GNPS workflow are included in this method. Compared with conventional approaches, the results of MS1&MS2 spectra-based identification workflows are combined in this approach via the tolerance of retention times and mass to charge ratios (m/z), which can greatly reduce the rate of false positives in metabolomics datasets. In our example, filtering with the tolerance removed more than 50% of the possible identifications while retaining 90% of the correct identification. The results demonstrated that the developed method is a rapid and reliable method for food metabolomics data processing.

The interactive network of hosts with pathogenic microbes is still questionable. It has been hypothesized and reported that the host shows altered regulatory mechanisms for different pathogens. Several studies using transcriptomics and proteomics revealed the altered pathways and sequential regulations displayed by the host during bacterial interactions. Still, there is a gap in understanding the triggering molecule at transcriptomic and proteomic levels due to the lack of the knowledge of the interactive metabolites produced during their interactions. In this study, the global metabolomic approach was performed in the nematode model organism Caenorhabditis elegans upon exposure to a Gram-negative bacteria, Salmonella enterica Serovar Typhi, and a Gram-positive bacteria, Staphylococcus aureus, and the whole metabolome was categorized as endo-metabolome (internally produced) and exo-metabolome (externally releasing). The extracted metabolites were subjected to liquid chromatography mass spectrometry (ESI-LC/qToF-MS/MS). In total 5578, 4554 and 4046 endo-metabolites and 4451, 3625 and 1281 exo-metabolites were identified in C. elegans when exposed to E. coli OP50, S. Typhi and S. aureus, respectively. Both the multivariate and univariate analyses were performed. The variation in endo- and exo-metabolome during candidate bacterial interactions was observed. The results indicated that, during S. aureus interaction, the exclusively enriched metabolites were significantly involved in alpha-linoleic acid metabolism. Similarly, the exclusively enriched metabolites during the interaction of S. Typhi were significantly involved in the phosphatidylinositol signalling system. The whole metabolomic profile presented here will build the scope to understand the role of metabolites and the respective pathways in host response during the early period of bacterial infections.

Infrared spectroscopy is a crucial tool to achieve the origin traceability of rice, but it is constrained by data mining. In this study, a novel infrared spectroscopy-based metabolomics analytical method was proposed to discriminate rice products from 14 Chinese cities by seeking ‘wave number markers’. Principal component analysis (PCA), cluster analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to separate all rice groups. The S-plot, permutation test and variable importance in projection (VIP) are used to screen eligible ‘markers’, which were further verified by a pairwise t-test. There are 55–265 ‘markers’ picked out from 14 rice groups, with their characteristic wave number bands to be 2935.658–3238.482, 3851.846–4000.364, 3329.136–3518.160, 1062.778–1213.225, 1161.147–1386.819, 3348.425–3560.594, 3115.038–3624.245, 2567.254–2872.007, 3334.923–3560.594, 3282.845–3543.235, 3338.780–3518.160, 3197.977–3560.594, 3163.258–3267.414 and 3292.489–3477.655 cm⁻¹, respectively. All but No. 5 rice groups show significantly low absorbance on their ‘marker’ bands. A mixed rice containing congenial No. 5 and No. 6 rice (80 : 20, m/m) was employed to test the validity of the method, and found that the ‘marker’ band of the mixed rice is the range of 1170.791–1338.598 cm⁻¹, implying the existence of considerable discrepancy between the mixed rice and other rice. The results indicate that infrared spectroscopy coupled with metabolomics analysis is competent for origin traceability of rice; thus, it provides a novel and workable approach for the accurate and rapid discrimination of rice from different geographical origins, and a distinctive perspective of metabolomics to explore infrared spectroscopy and beyond, especially not confined in the field of origin traceability.

The infection rate of syphilis continues to rise globally, and the difficulty in diagnosis of neurosyphilis promptly needs to be resolved. More specific and sensitive diagnostic markers for latent syphilis and neurosyphilis should be found. Here the metabolic profiles of 88 cerebrospinal fluid samples from syphilis patients and controls were analyzed by LC/MS-based untargeted metabolomics. In total, 272 metabolites based on 3937 features obtained in ESI− mode and 252 metabolites based on 3799 features in ESI+ mode were identified. The experimental process was evaluated by principal component analysis, partial least squares discriminant analysis, and hierarchical cluster analysis. A clear separation between latent syphilis and neurosyphilis was found. Levels of lipid and linoleic acid metabolites, such as 9-oxo-octadecadienoic acid and 9,10,13-trihydroxyoctadecenoic acid, were increased in syphilis patients. In patients with neurosyphilis, significant changes in levels of 5-hydroxy-L-tryptophan (5-HTP) and acetyl-N-formyl-5-methoxykynurenamine (AFMK) in the tryptophan–kynurenine pathway were also detected. Only one metabolite, theophylline, differed significantly between symptomatic and asymptomatic neurosyphilis patients. Additionally, KEGG analysis revealed significant enrichment of tryptophan metabolism pathways, indicating a high correlation between tryptophan metabolism and syphilis symptoms. Levels of linoleic acid metabolites, 5-HTP, AFMK and theophylline were significantly altered in different patients. The role of these differential metabolites in the development of syphilis is worthy of further exploration. Our results may promote the development of biomarkers for diagnosis of latent syphilis from neurosyphilis, and for that of asymptomatic neurosyphilis from symptomatic neurosyphilis in the future.

Correction for ‘Metabolomics study reveals the alteration of fatty acid oxidation in the hearts of diabetic mice by empagliflozin’ by Yingwei Zhang et al., Mol. Omics, 2022, 18, 643–651, https://doi.org/10.1039/D2MO00036A.

A variety of genes work together to allow the bacterium Lysinibacillus sp. OL1 to survive and grow under B-stress circumstances. This bacterium was previously identified and described from agricultural soil treated with a boron fertilizer. The effects of B-stress on OL1 cells cultured in the presence of 200 mM boric acid were evaluated as changes in the log-phase cell transcriptome and proteome. OL1 has been found to upregulate all genes involved in producing critical macromolecules when exposed to B-stress. It was also observed that genes governing energy supply lines were in higher expression stages, indicating that they were more likely to support the increased production of macromolecules and stress-induced proteins, such as efflux proteins, to reduce boron damage and prevent boron accumulation inside the cell. It has been explained how the hub genes and bottleneck genes cooperate to survive boron stress and support bacterial growth. The proteome results have significantly confirmed the boron tolerance paradigm. Thus, the current study has improved our understanding of the bacterial B-stress response mechanism and opened new research directions.