scholarly journals Enrichment analysis on regulatory subspaces: a novel direction for the superior description of cellular responses to SARS-CoV-2

2021 ◽  
Author(s):  
Pedro P. Rodrigues ◽  
Rafael S. Costa ◽  
Rui Henriques
Keyword(s):  
Machine Learning ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Learning Approaches ◽  
Transcriptional Responses ◽  
Kegg Pathways ◽  
Regulatory Processes

Statement: The enrichment analysis of discriminative cell transcriptional responses to SARS-CoV-2 infection using biclustering produces a broader set of superiorly enriched GO terms and KEGG pathways against alternative state-of-the-art machine learning approaches, unraveling novel knowledge. Motivation and methods: The comprehensive understanding of the impacts of the SARS-CoV-2 virus on infected cells is still incomplete. This work identifies and analyses the main cell regulatory processes affected and induced by SARS-CoV-2, using transcriptomic data from several infectable cell lines available in public databases and in vivo samples. We propose a new class of statistical models to handle three major challenges, namely the scarcity of observations, the high dimensionality of the data, and the complexity of the interactions between genes. Additionally, we analyse the function of these genes and their interactions within cells to compare them to ones affected by IAV (H1N1), RSV and HPIV3 in the target cell lines. Results: Gathered results show that, although clustering and predictive algorithms aid classic functional enrichment analysis, recent pattern-based biclustering algorithms significantly improve the number and quality of the detected biological processes. Additionally, a comparative analysis of these processes is performed to identify potential pathophysiological characteristics of COVID-19. These are further compared to those identified by other authors for the same virus as well as related ones such as SARS-CoV-1. This approach is particularly relevant due to a lack of other works utilizing more complex machine learning tools within this context.

KEGG-PATH: Kyoto encyclopedia of genes and genomes-based pathway analysis using a path analysis model

2014 ◽  
Vol 10 (9) ◽  
pp. 2441-2447 ◽  
Author(s):  
Junli Du ◽  
Zhifa Yuan ◽  
Ziwei Ma ◽  
Jiuzhou Song ◽  
Xiaoli Xie ◽  
...  
Keyword(s):  
Time Course ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Analysis Model ◽  
Kegg Pathways ◽  
Regulation Mechanisms ◽  
Complex Regulation ◽  
Multiple Treatments ◽  
Path Analysis Model

The KEGG-PATH approach, a kind of data mining through functional enrichment analysis of time-course experiments or those involving multiple treatments, can uncover the complex regulation mechanisms of KEGG pathways through the subdivision of total effect.

scholarly journals Identification of Latent Diagnostic Biomarkers and Biological Pathways in Dermatomyositis Based on WGCNA

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shaxi Ouyang ◽  
Yifang Liu ◽  
Changjuan Xiao ◽  
Qinghua Zeng ◽  
Xun Luo ◽  
...  
Keyword(s):  
Cell Lines ◽  
Differentially Expressed Gene ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Interferon Α ◽  
Pathway Enrichment Analysis ◽  
Oligoadenylate Synthetase

Introduction. Dermatomyositis (DM) is a chronic autoimmune disease of predominantly lymphocytic infiltration mainly involving the transverse muscle. Its pathogenesis is remaining unknown. This research is designed to probe the latent pathogenesis of dermatomyositis, identify potential biomarkers, and reveal the pathogenesis of dermatomyositis through information biology analysis of gene chips. Methods. In this study, we utilised the GSE14287 and GSE11971 datasets rooted in the Gene Expression Omnibus (GEO) databank, which included a total of 62 DM samples and 9 normal samples. The datasets were combined, and the differentially expressed gene sets were subjected to weighted gene coexpression network analysis, and the hub gene was screened using a protein interaction network from genes in modules highly correlated with dermatomyositis progression. Results. A total of 3 key genes—myxovirus resistance-2 (MX2), oligoadenylate synthetase 1 (OAS1), and oligoadenylate synthetase 2 (OAS2)—were identified in combination with cell line samples, and the expressions of the 3 genes were verified separately. The results showed that MX2, OAS1, and OAS2 were highly expressed in LPS-treated cell lines compared to normal cell lines. The results of pathway enrichment analysis of the genes indicated that all 3 genes were enriched in the cytosolic DNA signalling and cytokine and cytokine receptor interaction signalling pathways; the results of functional enrichment analysis showed that all 3 were enriched in interferon-α response and interferon-γ response functions. Conclusions. This is important for the study of the pathogenesis and objective treatment of dermatomyositis and provides important reference information for the targeted therapy of dermatomyositis.

scholarly journals A Novel Metastasis-related Genes Based Signature for Predicting the Progression-free Interval of Patients With Papillary Thyroid Carcinoma

2022 ◽  
Author(s):  
Rui Liu ◽  
Zhen Cao ◽  
Meng-wei Wu ◽  
Xiao-bin Li ◽  
Hong-wei Yuan ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Functional Enrichment ◽  
Clinical Parameters ◽  
Papillary Thyroid ◽  
Free Interval

Abstract Background: We aimed to build a novel model with metastasis-related genes (MTGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC).Methods: We performed a bioinformatic analysis of integrated PTC datasets with the MTGs to identify differentially expressed MTGs (DE-MTGs). Then we generated PFI-related DE-MTGs and established a novel MTGs based signature. After that, we validated the signature on multiple datasets and PTC cell lines. Further, we carried out uni- and multivariate analysis to identify independent prognostic characters. Finally, we established a signature and clinical parameters-based nomogram for predicting the PFI of PTC. Results: We identified 155 DE-MTGs related to PFI in PTC. The functional enrichment analysis showed that the DE-MTGs were associated with an essential oncogenic process. Consequently, we found a novel 10-gene signature and could distinguish patients with poorer prognoses and predicted PFI accurately. The novel signature had a C-index of 0.76 and the relevant nomogram had a C-index of 0.80. Also, it was closely related to pivotal clinical characters of datasets and invasiveness of cell lines. And the signature was confirmed a significant independent prognostic factor in PTC. Finally, we built a nomogram by including the signature and relevant clinical factors. Validation analysis showed that the nomogram's efficacy was satisfying in predicting PTC’s PFI. Conclusions: The MTG signature and nomogram were closely associated with PTC prognosis and may help clinicians improve the individualized prediction of PFI, especially for high-risk patients after surgery.

scholarly journals Effects of Erythrodiol on the Antioxidant Response and Proteome of HepG2 Cells

Antioxidants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 73
Author(s):  
Juan Luis Peñas-Fuentes ◽  
Eva Siles ◽  
Eva E. Rufino-Palomares ◽  
Amalia Pérez-Jiménez ◽  
Fernando J. Reyes-Zurita ◽  
...  
Keyword(s):  
Cell Viability ◽  
Olive Oil ◽  
Hepg2 Cells ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
In Vivo Studies ◽  
Antitumor Effects ◽  
Antioxidant Defense Systems

Erythrodiol (EO) is a pentacyclic triterpenic alcohol found in olive tree leaves and olive oil, and it has important effects on the health properties and quality of olive oil. In this study, we characterized the cytotoxic effects of EO on human hepatocarcinoma (HepG2) cells by studying changes in cell viability, reactive oxygen species (ROS) production, antioxidant defense systems, and the proteome. The results reveal that EO markedly decreased HepG2 cell viability without changing ROS levels. The concentrations of glutathione and NADPH were significantly reduced, with selective changes in the activity of several antioxidant enzymes: glutathione peroxidase, glutathione reductase, glucose 6-phosphate dehydrogenase, and 6-phosphogluconate dehydrogenase. Proteomic data reveal that EO led to the complete elimination or decreased abundance of 41 and 3 proteins, respectively, and the abundance of 29 proteins increased. The results of functional enrichment analysis show that important metabolic processes and the nuclear transport of mature mRNA were impaired, whereas AMP biosynthesis and cell cycle G2/M phase transition were induced. The transcription factors and miRNAs involved in this response were also identified. These potent antiproliferative effects make EO a good candidate for the further analysis of its hepatic antitumor effects in in vivo studies.

scholarly journals Integral Analyses of Competing Endogenous RNA Mechanisms and DNA Methylation Reveal Regulatory Mechanisms in Osteosarcoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Tingrui Wu ◽  
Bo Wei ◽  
Hao Lin ◽  
Boan Zhou ◽  
Tao Lin ◽  
...  
Keyword(s):  
Cell Lines ◽  
Binding Sites ◽  
Control Cell ◽  
Bone Tumour ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Survival Times ◽  
Poor Overall Survival

Background: Osteosarcoma (OS) is the most common primary malignant bone tumour in children and adolescents, with rapid growth, frequent metastasis, and a poor prognosis, but its pathogenesis has not been fully elucidated. Exploring the pathogenesis of OS is of great significance for improving diagnoses and finding new therapeutic targets.Methods: Differentially expressed circRNAs (DECs), miRNAs (DEMs), methylated DNA sites (DMSs), and mRNAs (DEGs) were identified between OS and control cell lines. GSEA of DEGs and functional enrichment analysis of methylated DEGs were carried out to further identify potential biological processes. Online tools were used to predict the miRNA binding sites of DECs and the mRNA binding sites of DEMs, and then construct a circRNA-miRNA-mRNA network. Next, an analysis of the interaction between methylated DEGs was performed with a protein-protein interaction (PPI) network, and hub gene identification and survival analysis were carried out. The expression pattern of circRNA-miRNA-mRNA was validated by real-time PCR.Results: GSEA and functional enrichment analysis indicated that DEGs and methylated DEGs are involved in important biological processes in cancer. Hsa_circ_0001753/has_miR_760/CD74 network was constructed and validated in cell lines. Low expression levels of CD74 are associated with poor overall survival times and show good diagnostic ability.Conclusion: Methylated DEGs may be involved in the development of OS, and the hsa_circ_0001753/has_miR_760/CD74 network may serve as a target for the early diagnosis of and targeted therapy for OS.

scholarly journals Viral miRNAs Confer Survival in Host Cells by Targeting Apoptosis Related Host Genes

2020 ◽  
Author(s):  
Md. Sajedul Islam ◽  
Abul BMMK Islam
Keyword(s):  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Host Cells ◽  
Viral Mirnas ◽  
Expression Of Genes ◽  
Apoptosis Process ◽  
Eukaryotic Organisms

AbstractBackgroundmiRNAs are small non-coding RNAs that regulate the expression of genes by RNA silencing method. Like eukaryotic organisms, some viruses also produce miRNAs. While contribution of host miRNA in the prevention of viral pathogenesis has been studied, it is not known very well how viral miRNA can confer its survival in the host. Here we hypothesized that viral miRNAs can bind to the host target genes to confer their pathogenicity by down-regulating specific pathways and related genes that otherwise pose threat to cell survival.Methods and ResultsUsing targets of 168 viral miRNAs from 13 different viruses overrepresentation analysis was done. Functional enrichment analysis of the genes targeted by the miRNAs indicates that viruses target specific immune system and host defense related pathways via miRNA mediated gene silencing. Integration and analysis of the publicly available experimental host gene expression data by RNA-seq provided insight that viruses target host apoptosis process by switching off related genes through miRNA induced mechanisms and thus probably ensure their survival.ConclusionsAs switching off the apoptosis of host cells would provide the viruses with selective advantages in surviving inside host, our findings therefore envisage an important function of viral miRNA which demands further in vivo experiments for better understanding in this regard.

scholarly journals Novel Mechanisms for Resistance to Targeted Therapy Identified through Machine Learning Approaches in 1167 RNA-Seq Drug Exposure Profiles in Lymphoma

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1370-1370
Author(s):  
Nicholas Davis ◽  
Matthew S. McKinney ◽  
Anupama Reddy ◽  
Cassandra Love ◽  
Eileen Smith ◽  
...  
Keyword(s):  
Machine Learning ◽  
B Cell ◽  
Cell Lines ◽  
Learning Approaches ◽  
Mechanisms Of Resistance ◽  
Pathway Activation ◽  
Large B Cell ◽  
Stat Pathway

Abstract Introduction: Diffuse large B cell lymphoma (DLBCL) is a clinically heterogeneous disease. While roughly half of the patients respond well to standard R-CHOP therapy, the majority of the remainder succumb to their disease. While many targeted therapies have been developed in DLBCL, resistance to single agents develops almost invariably. While drug combinations have proved to be effective approaches to overcoming resistance in infectious diseases, developing such combinations has proved to be difficult in diffuse large B cell lymphomas and other cancers owing to not only the heterogeneity of these diseases and overlapping toxicity profiles. We hypothesized that with advent of powerful new machine learning approaches combined with genomics, that we would be able to identify novel mechanisms of resistance and develop effective combination therapies to overcome resistance to single agents. Results We tested in vitro responses to all FDA-approved and Phase III cancer drugs (N=150) in six DLBCL cell lines carefully chosen to represent the heterogeneity with regard to cell of origin and common genetic alterations. We observed that roughly half of our drugs were active in at least 50% of the DLBCL cell lines. We then performed RNA sequencing on these cell lines before and after exposure to each of these drugs at their specific IC50 (concentration of drug required to kill 50% of the cells). In addition, we tested the effects of 38 cytokines and antibodies to assess their downstream biological effects. In all, we generated 1167 RNAseq profiles post-exposure to drug (N=900) or cytokines. Hierarchical clustering of our RNAseq data demonstrated clusters of drugs with shared mechanisms and targets (e.g. HDAC inhibitors, PI3K and mTOR inhibitors). We developed a machine learning approach using a combination of neural networks and Bayesian network propagation analysis to identify pathway activation and mechanisms of resistance associated with each of the drugs. Our approach identified 16 combinations of drugs that had different mechanisms and downstream targets. Surprisingly, we found that histone deacetylase inhibitors (HDACi, e.g. panobinostat) were predicted to be strongly synergistic in combination with JAK inhibitors (e.g. ruxolitinib). These findings were unexpected as ruxolitinib had very weak single agent effects and the JAK-STAT pathway is not thought to be specifically associated with response to HDACi. We verified the predictions of the machine learning algorithm by performing in vitro combination assays in six different cell lines. In each case, we found that the combination was highly synergistic using the Chou-Talalay method. We further verified the feasibility and efficacy of combining panobinostat (HDACi) and the JAK inhibitor ruxolitinib in vivo using xenograft models. Both single agents had relatively modest effects on tumor burden, but we found significant synergy with the combination (p<0.01), with vastly decreased tumor burdens. In vivo modeling also allowed for testing for hematological toxicity. Hemoglobin levels and ANC remained constant with all therapies, though combination therapy caused a 25% decrease in platelet levels, which would be considered clinically tolerable with monitoring. We further performed mechanistic experiments that demonstrate that JAK-STAT pathway activation through genetic mutations in STAT3 directly contribute to HDACi resistance and reverse sensitivity to HDACi. Conclusions These results provide a powerful proof of principle for the application of large scale perturbation approaches combined with machine learning to identify novel drug combinations and mechanisms of resistance. Figure. Figure. Disclosures No relevant conflicts of interest to declare.

scholarly journals An evolutionary transcriptomics approach links CD36 to membrane remodeling in replicative senescence

2018 ◽  
Author(s):  
Marie Saitou ◽  
Darleny Y. Lizardo ◽  
Recep Ozgur Taskent ◽  
Alec Millner ◽  
Gunes Ekin Atilla-Gokcumen ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cellular Senescence ◽  
Replicative Senescence ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Core Gene ◽  
Functional Enrichment ◽  
Membrane Remodeling ◽  
Lipid Metabolism Gene ◽  
The Media

SummaryCellular senescence, the irreversible ceasing of cell division, has been associated with organismal aging, prevention of cancerogenesis, and developmental processes. As such, the evolutionary basis and biological features of cellular senescence remain a fascinating area of research. In this study, we conducted comparative RNAseq experiments to detect genes associated with replicative senescence in two different human cell lines and at different time points. We identified 841 and 900 genes (core senescence-associated genes) that are significantly up- and downregulated in senescent cells, respectively, in both cell lines. Our functional enrichment analysis showed that downregulated core genes are primarily involved in cell cycle processes while upregulated core gene enrichment indicated various lipid-related processes. We further demonstrated that downregulated genes are significantly more conserved than upregulated genes. Using both transcriptomics and genetic variation data, we identified one of the upregulated, lipid metabolism gene, CD36 as an outlier. We found that overexpression of CD36 induces a senescence-like phenotype and, further, the media of CD36-overexpressing cells alone can induce a senescence-like phenotype in proliferating young cells. Moreover, we used a targeted lipidomics approach and showed that phosphatidylcholines accumulate during senescence in these cells, suggesting that upregulation of CD36 could contribute to membrane remodeling during senescence. Overall, these results contribute to the understanding of evolution and biology of cellular senescence and identify several targets and questions for future studies.

78 Effects of invitro production on the epigenome and transcriptome of bovine embryos determined through a multi-omics data integration approach

2021 ◽  
Vol 33 (2) ◽  
pp. 147
Author(s):  
M. Rabaglino ◽  
J. B.-M. Secher ◽  
P. Hyttel ◽  
H. Kadarmideen
Keyword(s):  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
P Value ◽  
Kegg Pathways ◽  
The Past ◽  
Before And After

In cattle, ovarian superovulation followed by invivo embryo collection and transfer (MOET), and the invitro production (IVP) of embryos are used all over the world to improve animal genetics. Application of MOET has resulted in the production of billions of healthy animals during the past 40 years, and IVP has evolved and given rise to significant numbers of calves during the past 10 years. Nevertheless, the use of MOET and IVP can affect the embryo epigenome, and therefore its transcriptome, before and after elongation, as shown by different studies. The integration of publicly available epigenome-transcriptome datasets generated by these studies could lead to a robust characterisation of the impacts of the application of MOET and IVP. The goal of this study was to integrate all publicly available data about MOET and IVP embryos to determine temporally differentially methylated regions (DMRs) and differentially expressed genes (DEGs) from blastocyst to elongation between IVP and MOET embryos. Datasets were downloaded from the Gene Expression Omnibus (GEO) database. Accession numbers were (1) for epigenomics: GSE69173, GSE97517, and GSE101895, plus one provided dataset from O’Doherty et al. (2018 BMC Genomics, 19, 438; https://doi.org/10.1186/s12864-018-4818-3), all hybridized to the EDMA platform GPL18384; (2) for transcriptomics: GSE12327, GSE21030, GSE24596, GSE24936, GSE27817, and GSE40101, all hybridized to the Affymetrix platform GPL2112. Both types of data were analysed with the limma package for R software, and functional enrichment analysis was done with the DAVID database. For DMRs, comparisons between IVP and MOET were made from spherical blastocysts (n=16 per group) on Day 7, to embryos on Day 15, specifically in the trophectoderm (TE) or embryonic disc (ED) regions (n=4 per region and per group). For DEGs, comparisons between IVP and MOET were made from spherical blastocysts (n=9 per group) to elongated blastocysts on Day 13 and embryos undergoing gastrulation on Day 16 (n=6 per group). Considering a P-value &lt;0.05 and fold-change &gt;2, there were 16 672 (TE) and 26 264 (ED) DMRs and 2236 DEGs that temporally differed between IVP and MOET. Most of the identified DMRs were found in intronic regions (around 36%) rather than exonic regions (8%). However, DMRs that were more methylated at IVP compared with MOET contained exons encoding for genes that enriched the Wnt signalling Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway in the ED, and focal adhesion and ECM-receptor interaction KEGG pathways (P&lt;0.05) in the TE. Accordingly, DEGs with lower expression in elongated embryos (Day 13 and Day 16) at IVP as opposed to MOET were mainly associated with these three pathways. In conclusion, this multi-omics analysis demonstrates that even when embryos are produced under different conditions and experiments, the main changes imposed by IVP affected genes involved in embryonic development and adhesion to the endometrium, which could explain the lower survival rates at IVP compared with MOET.

VirusCircBase: a database of virus circular RNAs

2020 ◽  
Author(s):  
Zena Cai ◽  
Yunshi Fan ◽  
Zheng Zhang ◽  
Congyu Lu ◽  
Zhaozhong Zhu ◽  
...  
Keyword(s):  
Influenza A ◽  
Enrichment Analysis ◽  
Computational Prediction ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Circular Rnas ◽  
Specific Cell ◽  
Sequencing Data ◽  
Kegg Pathways ◽  
Dsdna Viruses

Abstract Circular RNAs (circRNAs) are covalently closed long noncoding RNAs critical in diverse cellular activities and multiple human diseases. Several cancer-related viral circRNAs have been identified in double-stranded DNA viruses (dsDNA), yet no systematic study about the viral circRNAs has been reported. Herein, we have performed a systematic survey of 11 924 circRNAs from 23 viral species by computational prediction of viral circRNAs from viral-infection-related RNA sequencing data. Besides the dsDNA viruses, our study has also revealed lots of circRNAs in single-stranded RNA viruses and retro-transcribing viruses, such as the Zika virus, the Influenza A virus, the Zaire ebolavirus, and the Human immunodeficiency virus 1. Most viral circRNAs had reverse complementary sequences or repeated sequences at the flanking sequences of the back-splice sites. Most viral circRNAs only expressed in a specific cell line or tissue in a specific species. Functional enrichment analysis indicated that the viral circRNAs from dsDNA viruses were involved in KEGG pathways associated with cancer. All viral circRNAs presented in the current study were stored and organized in VirusCircBase, which is freely available at http://www.computationalbiology.cn/ViruscircBase/home.html and is the first virus circRNA database. VirusCircBase forms the fundamental atlas for the further exploration and investigation of viral circRNAs in the context of public health.

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