Integrative analysis of multi-omics provides insights into the translational landscape of plant-parasitic nematode Meloidogyne incognita
Ontology highlight
ABSTRACT:
ORGANISM(S): Meloidogyne Incognita
SUBMITTER: 
Zhaolu Zhu
PROVIDER: PXD046565 | iProX | Wed Nov 01 00:00:00 GMT 2023
REPOSITORIES: iProX
Similar Datasets
Project description:Root-knot nematodes (RKNs) of the genus Meloidogyne pose the most significant threats to global food security due to their destructive nature as plant-parasitic nematodes. Although significant attention has been devoted to investigating the gene transcription profiling of RKNs, our understanding of the translational landscape of RKNs remains limited. In this study, we elucidated the translational landscape of Meloidogyne incognita through the integration of translatome, transcriptome and quantitative proteome analyses. Our findings revealed numerous previously unannotated translation events and refined the genome annotation. By investigating the genome-wide translational dynamics of M. incognita during parasitism, we revealed that the genes of M. incognita undergo parasitic stage-specific regulation at the translational level. Interestingly, we identified 470 micropeptides (containing fewer than 100 amino acids) with the potential to function as effectors. Additionally, we observed that the effector-coding genes in M. incognita exhibit higher translation efficiency (TE). Further analysis suggests that M. incognita has the potential to regulate the TE of effector-coding genes without simultaneous alterations in their transcript abundance, facilitating effector synthesis. Collectively, our study provides comprehensive datasets and explores the genome-wide translational landscape of M. incognita, shedding light on the contributions of translational regulation during parasitism.
| S-EPMC11775120 | biostudies-literature
Project description:Pernicious placenta previa with placenta percreta (PP) is a catastrophic condition during pregnancy. However, the underlying pathogenesis remains unclear. In the present study, the placental tissues of normal cases and PP tissues of pernicious placenta previa cases were collected to determine the expression profile of protein-coding genes, miRNAs, and lncRNAs through sequencing. Weighted gene co-expression network analysis (WGCNA), accompanied by miRNA target prediction and correlation analysis, were employed to select potential hub protein-coding genes and lncRNAs. The expression levels of selected protein-coding genes, Wnt5A and MAPK13, were determined by quantitative PCR and immunohistochemical staining, and lncRNA PTCHD1-AS and PAPPA-AS1 expression levels were determined by quantitative PCR and fluorescence in situ hybridization. The results indicated that 790 protein-coding genes, 382 miRNAs, and 541 lncRNAs were dysregulated in PP tissues, compared with normal tissues. WGCNA identified coding genes in the module (ME) black and ME turquoise modules that may be involved in the pathogenesis of PP. The selected potential hub protein-coding genes, Wnt5A and MAPK13, were down-regulated in PP tissues, and their expression levels were positively correlated with the expression levels of PTCHD1-AS and PAPPA-AS1. Further analysis demonstrated that PTCHD1-AS and PAPPA-AS1 regulated Wnt5A and MAPK13 expression by interacting with specific miRNAs. Collectively, our results provided multi-omics data to better understand the pathogenesis of PP and help identify predictive biomarkers and therapeutic targets for PP.
| S-EPMC7754008 | biostudies-literature
Project description:The ability of bacteria to respond to environmental change is based on the ability to coordinate, redirect and fine-tune their genetic repertoire as and when required. While we can learn a great deal from reductive analysis of individual pathways and global approaches to gene regulation, a deeper understanding of these complex signaling networks requires the simultaneous consideration of several regulatory layers at the genome scale. To highlight the power of this approach we analyzed the Hfq transcriptional/translational regulatory network in the model bacterium Pseudomonas fluorescens. We first used extensive 'omics' analyses to assess how hfq deletion affects mRNA abundance, mRNA translation and protein abundance. The subsequent, multi-level integration of these datasets allows us to highlight the discrete contributions by Hfq to gene regulation at different levels. The integrative approach to regulatory analysis we describe here has significant potential, for both dissecting individual signaling pathways and understanding the strategies bacteria use to cope with external challenges.
| S-EPMC5627042 | biostudies-literature
Project description:Multidimensional host and viral factors determine the clinical course of COVID-19. While the virology of the disease is well studied, investigating host-related factors, including genome, transcriptome, metabolome, and exposome, can provide valuable insights into the underlying pathophysiology. We conducted integrative omics analyses to explore their intricate interplay in COVID-19. We used data from the UK Biobank (UKB), and employed single-omics, pairwise-omics, and multi-omics models to illustrate the effects of different omics layers. The dataset included COVID-19 phenotypic data as well as genome, imputed-transcriptome, metabolome and exposome data. We examined the main, interaction effects and correlations between omics layers underlying COVID-19. Single-omics analyses showed that the transcriptome (derived from the coronary artery tissue) and exposome captured 3-4% of the variation in COVID-19 susceptibility, while the genome and metabolome contributed 2-2.5% of the phenotypic variation. In the omics-exposome model, where individual omics layers were simultaneously fitted with exposome data, the contributions of genome and metabolome were diminished and considered negligible, whereas the effects of the transcriptome showed minimal change. Through mediation analysis, the findings revealed that exposomic factors mediated about 60% of the genome and metabolome's effects, while having a relatively minor impact on the transcriptome, mediating only 7% of its effects. In conclusion, our integrative-omics analyses shed light on the contribution of omics layers to the variance of COVID-19.
| S-EPMC11608341 | biostudies-literature
Project description:Intravenous leiomyomatosis (IVL) is a histologically well differentiated smooth muscle tumor with aggressive behavior, capable of extending throughout the venous system. Understanding how IVL occurs and develops is really important for diagnosing and treating it. Unfortunately, because IVL is quite rare, there aren't many comprehensive studies available. In our research, we carried out an extensive multi-omics study, gathering tissue samples from IVL cases, uterine fibroid, and normal myometrium. The single-cell RNA sequencing analysis revealed a notable difference in cell composition between IVL and uterine fibroid. Additionally, H&E staining demonstrated more frequent hydropic changes and hyalinization in IVL tissues, along with a reduced vascular density compared to both normal myometrium and uterine fibroid. In our proteomics analysis of eight paired samples of IVL and normal myometrium fresh frozen tissue, we identified proteins that were differentially expressed, mainly related to focal adhesions and regulation of the actin cytoskeleton. The most frequently involved chromosomes included deletions in 10q22.2, 10q24.32, 13q14, and 13q21-31. Correlation analyses highlighted chromosome 10q as the most frequent cytoband, with corresponding proteins involved in regulating focal adhesions and the cytoskeleton. Integrated analysis between pathological and clinical characteristics indicated that chromosome 10q deletion and vascular morphology in IVL could serve as important markers predicting aggressive behavior. Our study sheds light on the pathological and molecular changes linked to IVL, which could pave the way for new treatment approaches.
| S-EPMC11863679 | biostudies-literature
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.
2022-09-04 | GSE193040 | GEO
Project description:ObjectiveThis study aims to comprehensively analyze genomic, transcriptomic, proteomic, and single-cell sequencing data to unravel the molecular basis of primary Sjögren's syndrome (pSS) and explore potential therapeutic targets.MethodsMendelian randomization and single-cell RNA sequencing were employed to analyze pSS data. Differentially expressed genes specific to different blood cell types were identified. Integration of multiomics data facilitated the exploration of genetic regulatory relationships.ResultsThe analysis revealed distinct cell clusters representing various immune cell subsets. Several genes, including cathepsin S (CTSS) and glutathione S-transferase omega 1 (GSTO1), were identified as potential biomarkers and therapeutic targets for pSS. Diagnostic utility analysis demonstrated the discriminatory power of CTSS and GSTO1 in distinguishing pSS patients from healthy controls.ConclusionThe findings highlight the importance of integrating multiomics data for understanding pSS pathogenesis. CTSS and GSTO1 show promise as diagnostic biomarkers and potential therapeutic targets for pSS. Further investigations are warranted to elucidate the underlying mechanisms and develop targeted therapies for this complex autoimmune disease.
| S-EPMC11255657 | biostudies-literature
Project description:Green soybean (Glycine max (L.) Merrill) is a highly nutritious food that is a good source of protein and fiber. However, it is sensitive to low temperatures during the growing season, and enhancing cold tolerance has become a research hotspot for breeding improvement. Background/Objectives: The underlying molecular mechanisms of cold tolerance in green soybean are not well understood. Methods: Here, a comprehensive analysis of transcriptome and metabolome was performed on a cold-tolerant cultivar treated at 10 °C for 24 h. Results: Compared to control groups, we identified 17,011 differentially expressed genes (DEGs) and 129 differentially expressed metabolites (DEMs). The DEGs and DEMs were further subjected to KEGG functional analysis. Finally, 11 metabolites (such as sucrose, lactose, melibiose, and dehydroascorbate) and 17 genes (such as GOLS, GLA, UGDH, and ALDH) were selected as candidates associated with cold tolerance. Notably, the identified metabolites and genes were enriched in two common pathways: 'galactose metabolism' and 'ascorbate and aldarate metabolism'. Conclusions: The findings suggest that green soybean modulates the galactose metabolism and ascorbate and aldarate metabolism pathways to cope with cold stress. This study contributes to a deeper understanding of the complex molecular mechanisms enabling green soybeans to better avoid low-temperature damage.
| S-EPMC11678371 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently a global pandemic. Extensive investigations have been performed to study the clinical and cellular effects of SARS-CoV-2 infection. Mass spectrometry-based proteomics studies have revealed the cellular changes due to the infection and identified a plethora of interactors for all SARS-CoV-2 components, except for the longest non-structural protein 3 (NSP3). Here, we expressed the full-length NSP3 proteins of SARS-CoV and SARS-CoV-2 to investigate their unique and shared functions using multi-omics methods. We conducted interactome, phosphoproteome, ubiquitylome, transcriptome, and proteome analyses of NSP3-expressing cells. We found that NSP3 plays essential roles in cellular functions such as RNA metabolism and immune response (e.g., NF-κB signal transduction). Interestingly, we showed that SARS-CoV-2 NSP3 has both endoplasmic reticulum and mitochondrial localizations. In addition, SARS-CoV-2 NSP3 is more closely related to mitochondrial ribosomal proteins, whereas SARS-CoV NSP3 is related to the cytosolic ribosomal proteins. In summary, our integrative multi-omics study of NSP3 improves the understanding of the functions of NSP3 and offers potential targets for the development of anti-SARS strategies.
| S-EPMC8578027 | biostudies-literature
Project description:Zearalenone (ZEA), a secondary metabolite of Fusarium fungi found in cereal-based foods, promotes the growth of colon, breast, and prostate cancer cells in vitro. However, the lack of animal studies hinders a deeper mechanistic understanding of the cancer-promoting effects of ZEA. This study aimed to determine the effect of ZEA on colon cancer progression and its underlying mechanisms. Through integrative analyses of transcriptomics, metabolomics, metagenomics, and host phenotypes, we investigated the impact of a 4-week ZEA intervention on colorectal cancer in xenograft mice. Our results showed a twofold increase in tumor weight with the 4-week ZEA intervention. ZEA exposure significantly increased the mRNA and protein levels of BEST4, DGKB, and Ki67 and the phosphorylation levels of ERK1/2 and AKT. Serum metabolomic analysis revealed that the levels of amino acids, including histidine, arginine, citrulline, and glycine, decreased significantly in the ZEA group. Furthermore, ZEA lowered the alpha diversity of the gut microbiota and reduced the abundance of nine genera, including Tuzzerella and Rikenella. Further association analysis indicated that Tuzzerella was negatively associated with the expression of BEST4 and DGKB genes, serum uric acid levels, and tumor weight. Additionally, circulatory hippuric acid levels positively correlated with tumor weight and the expression of oncogenic genes, including ROBO3, JAK3, and BEST4. Altogether, our results indicated that ZEA promotes colon cancer progression by enhancing the BEST4/AKT/ERK1/2 pathway, lowering circulatory amino acid concentrations, altering gut microbiota composition, and suppressing short chain fatty acids production.
| S-EPMC10006464 | biostudies-literature