scholarly journals Transcriptomic Analysis of Respiratory Tissue and Cell Line Models to Examine Glycosylation Machinery during SARS-CoV-2 Infection

Viruses ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Anup Oommen ◽  
Stephen Cunningham ◽  
Lokesh Joshi
Keyword(s):  
Immune Response ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Vital Role ◽  
Biomedical Literature ◽  
Transcriptomic Analysis ◽  
Functional Enrichment ◽  
Post Translational Modification ◽  
And Function

Glycosylation, being the most abundant post-translational modification, plays a profound role affecting expression, localization and function of proteins and macromolecules in immune response to infection. Presented are the findings of a transcriptomic analysis performed using high-throughput functional genomics data from public repository to examine the altered transcription of the human glycosylation machinery in response to SARS-CoV-2 stimulus and infection. In addition to the conventional in silico functional enrichment analysis methods we also present results from the manual analysis of biomedical literature databases to bring about the biological significance of glycans and glycan-binding proteins in modulating the host immune response during SARS-CoV-2 infection. Our analysis revealed key immunomodulatory lectins, proteoglycans and glycan epitopes implicated in exerting both negative and positive downstream inflammatory signaling pathways, in addition to its vital role as adhesion receptors for SARS-CoV-2 pathogen. A hypothetical correlation of the differentially expressed human glycogenes with the altered host inflammatory response and the cytokine storm-generated in response to SARS-CoV-2 pathogen is proposed. These markers can provide novel insights into the diverse roles and functioning of glycosylation pathways modulated by SARS-CoV-2, provide avenues of stratification, treatment, and targeted approaches for COVID-19 immunity and other viral infectious agents.

scholarly journals Immunological pathways of macrophage response to Brucella ovis infection

2020 ◽  
Vol 26 (7) ◽  
pp. 635-648
Author(s):  
Zhixiong Zhou ◽  
Guojing Gu ◽  
Yichen Luo ◽  
Wenjie Li ◽  
Bowen Li ◽  
...  
Keyword(s):  
Immune Response ◽  
Molecular Mechanisms ◽  
Group Versus ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Sequencing Data ◽  
Brucella Ovis ◽  
Qrt Pcr ◽  
Raw264.7 Macrophage

As the molecular mechanisms of Brucella ovis pathogenicity are not completely clear, we have applied a transcriptome approach to identify the differentially expressed genes (DEGs) in RAW264.7 macrophage infected with B. ovis. The DEGs related to immune pathway were identified by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional enrichment analysis. Quantitative real-time PCR (qRT-PCR) was performed to validate the transcriptome sequencing data. In total, we identified 337 up-regulated and 264 down-regulated DEGs in B. ovis-infected group versus mock group. Top 20 pathways were enriched by KEGG analysis and 20 GO by functional enrichment analysis in DEGs involved in the molecular function, cellular component, and biological process and so on, which revealed multiple immunological pathways in RAW264.7 macrophage cells in response to B. ovis infection, including inflammatory response, immune system process, immune response, cytokine activity, chemotaxis, chemokine-mediated signaling pathway, chemokine activity, and CCR chemokine receptor binding. qRT-PCR results showed Ccl2 (ENSMUST00000000193), Ccl2 (ENSMUST00000124479), Ccl3 (ENSMUST00000001008), Hmox1 (ENSMUST00000005548), Hmox1 (ENSMUST00000159631), Cxcl2 (ENSMUST00000075433), Cxcl2 (ENSMUST00000200681), Cxcl2 (ENSMUST00000200919), and Cxcl2 (ENSMUST00000202317). Our findings firstly elucidate the pathways involved in B. ovis-induced host immune response, which may lay the foundation for revealing the bacteria–host interaction and demonstrating the pathogenic mechanism of B. ovis.

scholarly journals Improved cancer biomarkers identification using network-constrained infinite latent feature selection

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246668
Author(s):  
Lihua Cai ◽  
Honglong Wu ◽  
Ke Zhou
Keyword(s):  
Feature Selection ◽  
Expression Profiles ◽  
Biological Significance ◽  
Feature Selection Method ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Gene Sets ◽  
Significant Gene

Identifying biomarkers that are associated with different types of cancer is an important goal in the field of bioinformatics. Different researcher groups have analyzed the expression profiles of many genes and found some certain genetic patterns that can promote the improvement of targeted therapies, but the significance of some genes is still ambiguous. More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes. In this paper, we proposed a novel method that combines the infinite latent feature selection (ILFS) method with the functional interaction (FIs) network to rank the biomarkers. We applied the proposed method to the expression data of five cancer types. The experiments indicated that our network-constrained ILFS (NCILFS) provides an improved prediction of the diagnosis of the samples and locates many more known oncogenes than the original ILFS and some other existing methods. We also performed functional enrichment analysis by inspecting the over-represented gene ontology (GO) biological process (BP) terms and applying the gene set enrichment analysis (GSEA) method on selected biomarkers for each feature selection method. The enrichments analysis reports show that our network-constraint ILFS can produce more biologically significant gene sets than other methods. The results suggest that network-constrained ILFS can identify cancer-related genes with a higher discriminative power and biological significance.

scholarly journals SPP1 is a Prognostic Related Biomarker and Correlated With Tumor-Infiltrating Immune Cells in Ovarian Cancer

2021 ◽  
Author(s):  
Wen Gao ◽  
Sheng Yin ◽  
Haiyan Sun ◽  
Zhuyan Shao ◽  
Peipei Shi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cells ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Vital Role ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Secreted Phosphoprotein 1

Abstract Background: Secreted phosphoprotein 1 (SPP1) plays a vital role in tumor progression of some cancer types, but little is known whether it is a bystander or an actual player on driving immune infiltration in ovarian cancer.Methods: In this study, the expression of SPP1 was identified by Oncomine, GEPIA and TIMER databases, and SPP1 immumohistochemical staining analysis was assessed by The HPA database. The clinical outcomes between SPP1 expression and ovarian cancer patients were evaluated via Kaplan-Meier Plotter and PrognoScan dataset. Immune infiltration analyses were explored using TIMER and TISIDB dataset. In addition, Functional enrichment analyses were performed with Metascape and GeneMANIA database.Results: SPP1 was found overexpressed in ovarian tumor tissues and high SPP1 expression was correlated with shorter OS and PFS survivals. Particularly, elevated SPP1 expression was significantly associated with stage III ovarian cancer. Notably, SPP1 expression was positively correlated with infiltrating levels of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells. Furthermore, SPP1 expression showed strong correlations with diverse immune hallmark sets in ovarian cancer. Of particular importance, functional enrichment analysis suggested that SPP1 strong related with immune response.Conclusions: These findings imply that SPP1 is correlated with prognosis and immune cell infiltrating, offering a new potential immunotherapeutic target in ovarian cancer.Trial registration: Not applicable.

scholarly journals Prognostic Impact and Functional Annotations of KIF11 and KIF14 Expression in Patients with Colorectal Cancer

2021 ◽  
Vol 22 (18) ◽  
pp. 9732
Author(s):  
Izabela Neska-Długosz ◽  
Karolina Buchholz ◽  
Justyna Durślewicz ◽  
Maciej Gagat ◽  
Dariusz Grzanka ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Mrna Level ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Tissue Microarrays ◽  
Functional Enrichment ◽  
Prognostic Impact ◽  
Aberrant Expression ◽  
Functional Value

Genomic instability (GIN) has an important contribution to the pathology of colorectal cancer (CRC). Therefore, we selected mitosis and cytokinesis kinesins, KIF11 and KIF14, as factors of potential clinical and functional value in CRC, as their aberrant expression has been suspected to underlie GIN. We examined the expression and the prognostic and biological significance of KIF11 and KIF14 in CRC via in-house immunohistochemistry on tissue microarrays, public mRNA expression datasets, as well as bioinformatics tools. We found that KIF11 and KIF14 expression, at both the protein and mRNA level, was markedly altered in cancer tissues compared to respective controls, which was reflected in the clinical outcome of CRC patients. Specifically, we provide the first evidence that KIF11 protein and mRNA, KIF14 mRNA, as well as both proteins together, can significantly discriminate between CRC patients with better and worse overall survival independently of other relevant clinical risk factors. The negative prognostic factors for OS were high KIF11 protein, high KIF11 protein + low KIF14 protein, low KIF11 mRNA and low KIF14 mRNA. Functional enrichment analysis revealed that the gene sets related to the cell cycle, DNA replication, DNA repair and recombination, among others, were positively associated with KIF11 or KIF14 expression in CRC tissues. In TCGA cohort, the positive correlations between several measures related to GIN and the expression of KIFs were also demonstrated. In conclusion, our results suggest that CRC patients can be stratified into distinct risk categories by biological and molecular determinants, such as KIF11 and KIF14 expression and, mechanistically, this is likely attributable to their role in maintaining genome integrity.

scholarly journals UbiNet 2.0: a verified, classified, annotated and updated database of E3 ubiquitin ligase–substrate interactions

Database ◽  
2021 ◽  
Vol 2021 ◽  
Author(s):  
Zhongyan Li ◽  
Siyu Chen ◽  
Jhih-Hua Jhong ◽  
Yuxuan Pang ◽  
Kai-Yao Huang ◽  
...  
Keyword(s):  
Substrate Specificity ◽  
Protein Interactions ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Ubiquitin Proteasome System ◽  
Functional Enrichment ◽  
Post Translational Modification ◽  
Substrate Interactions ◽  
E3 Ligases

Abstract Ubiquitination is an important post-translational modification, which controls protein turnover by labeling malfunctional and redundant proteins for proteasomal degradation, and also serves intriguing non-proteolytic regulatory functions. E3 ubiquitin ligases, whose substrate specificity determines the recognition of target proteins of ubiquitination, play crucial roles in ubiquitin–proteasome system. UbiNet 2.0 is an updated version of the database UbiNet. It contains 3332 experimentally verified E3–substrate interactions (ESIs) in 54 organisms and rich annotations useful for investigating the regulation of ubiquitination and the substrate specificity of E3 ligases. Based on the accumulated ESIs data, the recognition motifs in substrates for each E3 were also identified and a functional enrichment analysis was conducted on the collected substrates. To facilitate the research on ESIs with different categories of E3 ligases, UbiNet 2.0 performed strictly evidence-based classification of the E3 ligases in the database based on their mechanisms of ubiquitin transfer and substrate specificity. The platform also provides users with an interactive tool that can visualize the ubiquitination network of a group of self-defined proteins, displaying ESIs and protein–protein interactions in a graphical manner. The tool can facilitate the exploration of inner regulatory relationships mediated by ubiquitination among proteins of interest. In summary, UbiNet 2.0 is a user-friendly web-based platform that provides comprehensive as well as updated information about experimentally validated ESIs and a visualized tool for the construction of ubiquitination regulatory networks available at http://awi.cuhk.edu.cn/~ubinet/index.php.

MIMPFC: Identifying miRNA–mRNA regulatory modules by combining phase-only correlation and improved rough-fuzzy clustering

2018 ◽  
Vol 16 (01) ◽  
pp. 1750028
Author(s):  
Dan Luo ◽  
Shu-Lin Wang ◽  
Jianwen Fang ◽  
Wei Zhang
Keyword(s):  
Fuzzy Clustering ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Computational Method ◽  
Functional Enrichment ◽  
Regulatory Relationship ◽  
Regulatory Modules ◽  
Wide Range ◽  
Highly Correlated

MicroRNAs (miRNAs) play a key role in gene expression and regulation in various organisms. They control a wide range of biological processes and are involved in several types of cancers by causing mRNA degradation or translational inhibition. However, the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With the accumulation of the expression data of miRNAs and mRNAs, many computational methods have been proposed to predict miRNA–mRNA regulatory relationship. However, most existing methods require the number of modules predefined that may be difficult to determine beforehand. Here, we propose a novel computational method to discover miRNA–mRNA regulatory modules by combining Phase-only correlation and improved rough-Fuzzy Clustering (MIMPFC). The proposed method is evaluated on three heterogeneous datasets, and the obtained results are further validated through relevant literatures, biological significance and functional enrichment analysis. The analysis results show that the identified modules are highly correlated with the biological conditions. A large part of the regulatory relationships found by MIMPFC has been confirmed in the experimentally verified databases. It demonstrates that the modules found by MIMPFC are biologically significant.

scholarly journals An advanced strategy for comprehensive profiling of ADP-ribosylation sites using mass spectrometry-based proteomics

2018 ◽  
Author(s):  
Ivo A. Hendriks ◽  
Sara C. Larsen ◽  
Michael L. Nielsen
Keyword(s):  
Electron Transfer ◽  
Electron Transfer Dissociation ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Post Translational Modification ◽  
Tyrosine Residues ◽  
Adp Ribosylation ◽  
Cellular Processes ◽  
Nuclear Proteome

ABSTRACTADP-ribosylation is a widespread post-translational modification (PTM) with crucial functions in many cellular processes. Here, we describe an in-depth ADP-ribosylome using our Af1521-based proteomics methodology for comprehensive profiling of ADP-ribosylation sites, by systematically assessing complementary proteolytic digestions and precursor fragmentation through application of electron-transfer higher-energy collisional dissociation (EThcD) and electron transfer dissociation (ETD), respectively. While ETD spectra yielded higher identification scores, EThcD generally proved superior to ETD in identification and localization of ADP-ribosylation sites regardless of protease employed. Notwithstanding, the propensities of complementary proteases and fragmentation methods expanded the detectable repertoire of ADP-ribosylation to an unprecedented depth. This system-wide profiling of the ADP-ribosylome in HeLa cells subjected to DNA damage uncovered >11,000 unique ADP-ribosylated peptides mapping to >7,000 ADP-ribosylation sites, in total modifying over one-third of the human nuclear proteome and highlighting the vast scope of this PTM. High-resolution MS/MS spectra enabled identification of dozens of proteins concomitantly modified by ADP-ribosylation and phosphorylation, revealing a considerable degree of crosstalk on histones. ADP-ribosylation was confidently localized to various amino acid residue types, including less abundantly modified residues, with hundreds of ADP-ribosylation sites pinpointed on histidine, arginine, and tyrosine residues. Functional enrichment analysis suggested modification of these specific residue types is directed in a spatial manner, with tyrosine ADP-ribosylation linked to the ribosome, arginine ADP-ribosylation linked to the endoplasmic reticulum, and histidine ADP-ribosylation linked to the mitochondrion.

scholarly journals DNA Repair and Immune Response Pathways Are Deregulated in Melanocyte-Keratinocyte Co-cultures Derived From the Healthy Skin of Familial Melanoma Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Miriam Potrony ◽  
Tariq Sami Haddad ◽  
Gemma Tell-Martí ◽  
Pol Gimenez-Xavier ◽  
Carlos Leon ◽  
...  
Keyword(s):  
Immune Response ◽  
Dna Repair ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Healthy Skin ◽  
Familial Melanoma ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Melanoma Patients

Familial melanoma accounts for 10% of cases, being CDKN2A the main high-risk gene. However, the mechanisms underlying melanomagenesis in these cases remain poorly understood. Our aim was to analyze the transcriptome of melanocyte-keratinocyte co-cultures derived from healthy skin from familial melanoma patients vs. controls, to unveil pathways involved in melanoma development in at-risk individuals. Accordingly, primary melanocyte-keratinocyte co-cultures were established from the healthy skin biopsies of 16 unrelated familial melanoma patients (8 CDKN2A mutant, 8 CDKN2A wild-type) and 7 healthy controls. Whole transcriptome was captured using the SurePrint G3 Human Microarray. Transcriptome analyses included: differential gene expression, functional enrichment, and protein-protein interaction (PPI) networks. We identified a gene profile associated with familial melanoma independently of CDKN2A germline status. Functional enrichment analysis of this profile showed a downregulation of pathways related to DNA repair and immune response in familial melanoma (P < 0.05). In addition, the PPI network analysis revealed a network that consisted of double-stranded DNA repair genes (including BRCA1, BRCA2, BRIP1, and FANCA), immune response genes, and regulation of chromosome segregation. The hub gene was BRCA1. In conclusion, the constitutive deregulation of BRCA1 pathway genes and the immune response in healthy skin could be a mechanism related to melanoma risk.

scholarly journals Transcriptomic analysis of Streptococcus agalactiae periprosthetic joint infection

2021 ◽  
Author(s):  
Hye-Kyung Cho ◽  
Thao Masters ◽  
Kerryl Greenwood-Quaintance ◽  
Stephen Johnson ◽  
Patricio Jeraldo ◽  
...  
Keyword(s):  
Periprosthetic Joint Infection ◽  
Streptococcus Agalactiae ◽  
Joint Infection ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transcriptomic Analysis ◽  
Functional Enrichment ◽  
Inorganic Ion ◽  
Genes Encoding

Although Streptococcus agalactiae periprosthetic joint infection (PJI) is not as prevalent as staphylococcal PJI, invasive S. agalactiae infection has recently increased in incidence. Here, RNA-Seq was used to perform transcriptomic analysis of S. agalactiae PJI using fluid derived from sonication of explanted arthroplasties of subjects with S. agalactiae PJI, with results compared to those of S. agalactiae strain NEM316 grown in vitro. 227 genes with outlier expression were found (164 up-regulated and 63 down-regulated) between PJI sonicate fluid and in vitro conditions. Functional enrichment analysis showed genes involved in mobilome and inorganic ion transport and metabolism to be most enriched. Genes involved in nickel, copper, and zinc transport, were upregulated. Among known virulence factors, cyl operon genes, encoding beta-hemolysin/cytolysin, were consistently highly expressed in PJI versus in vitro. The data presented provide insight into S. agalactiae PJI pathogenesis and may be a useful resource for the identification of novel PJI therapeutics or vaccines against invasive S. agalactiae infections.

scholarly journals Identification of miRNA-target gene regulatory networks in liver fibrosis based on bioinformatics analysis

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11910
Author(s):  
Yang Tai ◽  
Chong Zhao ◽  
Jinhang Gao ◽  
Tian Lan ◽  
Huan Tong
Keyword(s):  
Immune Response ◽  
Liver Cirrhosis ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Differentially Expressed Mirnas ◽  
And Control

Background Liver cirrhosis is one of the leading causes of death worldwide. MicroRNAs (miRNAs) can regulate liver fibrosis, but the underlying mechanisms are not fully understood, and the interactions between miRNAs and mRNAs are not clearly elucidated. Methods miRNA and mRNA expression arrays of cirrhotic samples and control samples were acquired from the Gene Expression Omnibus database. miRNA-mRNA integrated analysis, functional enrichment analysis and protein-protein interaction (PPI) network construction were performed to identify differentially expressed miRNAs (DEMs) and mRNAs (DEGs), miRNA-mRNA interaction networks, enriched pathways and hub genes. Finally, the results were validated with in vitro cell models. Results By bioinformatics analysis, we identified 13 DEMs between cirrhotic samples and control samples. Among these DEMs, six upregulated (hsa-miR-146b-5p, hsa-miR-150-5p, hsa-miR-224-3p, hsa-miR-3135b, hsa-miR-3195, and hsa-miR-4725-3p) and seven downregulated (hsa-miR-1234-3p, hsa-miR-30b-3p, hsa-miR-3162-3p, hsa-miR-548aj-3p, hsa-miR-548x-3p, hsa-miR-548z, and hsa-miR-890) miRNAs were further validated in activated LX2 cells. miRNA-mRNA interaction networks revealed a total of 361 miRNA-mRNA pairs between 13 miRNAs and 245 corresponding target genes. Moreover, PPI network analysis revealed the top 20 hub genes, including COL1A1, FBN1 and TIMP3, which were involved in extracellular matrix (ECM) organization; CCL5, CXCL9, CXCL12, LCK and CD24, which participated in the immune response; and CDH1, PECAM1, SELL and CAV1, which regulated cell adhesion. Functional enrichment analysis of all DEGs as well as hub genes showed similar results, as ECM-associated pathways, cell surface interaction and adhesion, and immune response were significantly enriched in both analyses. Conclusions We identified 13 differentially expressed miRNAs as potential biomarkers of liver cirrhosis. Moreover, we identified 361 regulatory pairs of miRNA-mRNA and 20 hub genes in liver cirrhosis, most of which were involved in collagen and ECM components, immune response, and cell adhesion. These results would provide novel mechanistic insights into the pathogenesis of liver cirrhosis and identify candidate targets for its treatment.

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