Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks

Molecular insights into the proteomic composition of porcine treated dentin matrix

Background

Human-treated dentin matrix (hTDM) has recently been studied as a natural extracellular matrix-based biomaterial for dentin pulp regeneration. However, porcine-treated dentin matrix (pTDM) is a potential alternative scaffold due to limited availability. However, there is a dearth of information regarding the protein composition and underlying molecular mechanisms of pTDM.Methods: hTDM and pTDM were fabricated using human and porcine teeth, respectively, and their morphological characteristics were examined using scanning electron microscopy. Stem cells derived from human exfoliated deciduous teeth (SHEDs) were isolated and characterized using flow cytometry and multilineage differentiation assays. SHEDs were cultured in three-dimensional environments with hTDM, pTDM, or biphasic hydroxyapatite/tricalcium phosphate. The expression of odontogenesis markers in SHEDs were assessed using real-time polymerase chain reaction and immunochemical staining. Subsequently, SHEDs/TDM and SHEDs/HA/TCP complexes were transplanted subcutaneously into nude mice. The protein composition of pTDM was analyzed using proteomics and compared to previously published data on hTDM.Results: pTDM and hTDM elicited comparable upregulation of odontogenesis-related genes and proteins in SHEDs. Furthermore, both demonstrated the capacity to stimulate root-related tissue regeneration in vivo. Proteomic analysis revealed the presence of 278 protein groups in pTDM, with collagens being the most abundant. Additionally, pTDM and hTDM shared 58 identical proteins, which may contribute to their similar abilities to induce odontogenesis.

Conclusions

Both hTDM and pTDM exhibit comparable capabilities in inducing odontogenesis, potentially owing to their distinctive bioactive molecular networks.

Prediction and analysis of osteoarthritis hub genes with bioinformatics

Background

Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA.

Methods

The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language "limma" function package under the threshold of log₂[fold change (FC)] ≥2 and a P value <0.05. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of the target genes were enriched and analyzed using the database for annotation, visualization, and integrated discovery (DAVID), and a protein-protein interaction (PPI) network was further constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database. The coexpression relationship of the genes in the module was visualized and screened with Cytoscape.

Results

A total of 27 DEGs were identified, including 9 downregulated genes and 18 upregulated genes. GO signal pathway enrichment analysis showed involvement in hypoxic response, fibrous collagen trimer, and extracellular matrix structural components. KEGG analysis demonstrated associations with protein digestion and absorption, extracellular matrix receptor interaction, and the peroxisome proliferator-activated receptor signal pathway, among several other pathways. A PPI network was obtained through STRING analysis, and the results were imported into Cytoscape software. The 27 DEGs were sequenced by the cytoHubba plug-in by various calculation methods, and 5 hub genes (COL1A1, COL1A2, POSTN, BMP1, and MMP13) were finally selected. These genes were analyzed by PPI again and annotated with GO and KEGG in different colors.

Conclusions

Bioinformatics technology effectively identified differential genes in the knee cartilage tissue of healthy controls and patients with OA, providing opportunities to further explore the mechanism and treatment of OA on a transcriptional level.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

Genome profiles of pathologist-defined cell clusters by multiregional LCM and G&T-seq in one triple-negative breast cancer patient

Pathological examination is the gold standard for cancer diagnosis, and breast tumor cells are often found in clusters. We report a case study on one triple-negative breast cancer (TNBC) patient, analyzing tumor development, metastasis, and prognosis with simultaneous DNA and RNA sequencing of pathologist-defined cell clusters from multiregional frozen sections. The cell clusters are isolated by laser capture microdissection (LCM) from primary tumor tissue, lymphatic vessels, and axillary lymph nodes. Data are reported for a total of 97 cell clusters. A combination of tumor cell-cluster clonality and phylogeny reveals 3 evolutionarily distinct pathways for this patient, each associated with a unique mRNA signature, and each correlated with disparate survival outcomes. Hub gene analysis indicates that extensive downregulation of ribosomal protein mRNA is a potential marker of poor prognosis in breast cancer.

Pathologically diverse cell clusters share genomic and transcriptomic profiles

Transcriptome-defined clones are more complex than genome-defined clones

Three distinct pathways were inferred, each with disparate survival outcomes

Lower expression of ribosomal proteins may be an indicator of poor prognosis

Zika Virus Infection of Human Iris Pigment Epithelial Cells

During recent Zika epidemics, adults infected with Zika virus (ZIKV) have developed organ-specific inflammatory complications. The most serious Zika-associated inflammatory eye disease is uveitis, which is commonly anterior in type, affecting both eyes and responding to corticosteroid eye drops. Mechanisms of Zika-associated anterior uveitis are unknown, but ZIKV has been identified in the aqueous humor of affected individuals. The iris pigment epithelium is a target cell population in viral anterior uveitis, and it acts to maintain immune privilege within the anterior eye. Interactions between ZIKV and human iris pigment epithelial cells were investigated with infectivity assays and RNA-sequencing. Primary cell isolates were prepared from eyes of 20 cadaveric donors, and infected for 24 hours with PRVABC59 strain ZIKV or incubated uninfected as control. Cytoimmunofluorescence, RT-qPCR on total cellular RNA, and focus-forming assays of culture supernatant showed cell isolates were permissive to infection, and supported replication and release of infectious ZIKV. To explore molecular responses of cell isolates to ZIKV infection at the whole transcriptome level, RNA was sequenced on the Illumina NextSeq 500 platform, and results were aligned to the human GRCh38 genome. Multidimensional scaling showed clear separation between transcriptomes of infected and uninfected cell isolates. Differential expression analysis indicated a vigorous molecular response of the cell to ZIKV: 7,935 genes were differentially expressed between ZIKV-infected and uninfected cells (FDR < 0.05), and 99% of 613 genes that changed at least two-fold were up-regulated. Reactome and KEGG pathway and Gene Ontology enrichment analyses indicated strong activation of viral recognition and defense, in addition to biosynthesis processes. A CHAT network included 6275 molecular nodes and 24 contextual hubs in the cell response to ZIKV infection. Receptor-interacting serine/threonine kinase 1 (RIPK1) was the most significantly connected contextual hub. Correlation of gene expression with read counts assigned to the ZIKV genome identified a negative correlation between interferon signaling and viral load across isolates. This work represents the first investigation of mechanisms of Zika-associated anterior uveitis using an in vitro human cell model. The results suggest the iris pigment epithelium mounts a molecular response that limits intraocular pathology in most individuals.

Hypothetical Proteins as Predecessors of Long Non-coding RNAs

Hypothetical Proteins [HP] are the transcripts predicted to be expressed in an organism, but no evidence of it exists in gene banks. On the other hand, long non-coding RNAs [lncRNAs] are the transcripts that might be present in the 5’ UTR or intergenic regions of the genes whose lengths are above 200 bases. With the known unknown [KU] regions in the genomes rapidly existing in gene banks, there is a need to understand the role of open reading frames in the context of annotation. In this commentary, we emphasize that HPs could indeed be the predecessors of lncRNAs.

Oral lichen planus interactome reveals CXCR4 and CXCL12 as candidate therapeutic targets

Today, we face difficulty in generating new hypotheses and understanding oral lichen planus due to the large amount of biomedical information available. In this research, we have used an integrated bioinformatics approach assimilating information from data mining, gene ontologies, protein–protein interaction and network analysis to predict candidate genes related to oral lichen planus. A detailed pathway analysis led us to propose two promising therapeutic targets: the stromal cell derived factor 1 (CXCL12) and the C-X-C type 4 chemokine receptor (CXCR4). We further validated our predictions and found that CXCR4 was upregulated in all oral lichen planus tissue samples. Our bioinformatics data cumulatively support the pathological role of chemokines and chemokine receptors in oral lichen planus. From a clinical perspective, we suggest a drug (plerixafor) and two therapeutic targets for future research.

Hypoxic exosomes facilitate angiogenesis and metastasis in esophageal squamous cell carcinoma through altering the phenotype and transcriptome of endothelial cells

Background

In cancer progression, hypoxia, or low oxygen tension, is a major regulator of tumor aggressiveness and metastasis. However, how cancer cells adapt to the hypoxia and communicate with other mesenchymal cells in microenvironment during tumor development remains to be elucidated. Here, we investigated the involvement of exosomes in modulating angiogenesis and enhancing metastasis in esophageal squamous cell carcinoma (ESCC).

Methods

Differential centrifugation, transmission electron microscopy and nanoparticle tracking analysis were used to isolate and characterize exosomes. Colony formation and transwell assay were performed to assess the proliferation, migration and invasion of human umbilical vein endothelial cells (HUVECs). The tube formation assay and matrigel plug assay were used to evaluate the vascular formation ability of HUVECs in vitro and in vivo respectively. An in vivo nude mice model was established to detect the regulatory role of exosomes in ESCC progression. Microarray analysis was performed to analyze the transcriptome profiles in HUVECs.

Results

Exosomes derived from ESCC cells cultured under hypoxia played a better role in promoting proliferation, migration, invasion and tube formation of HUVECs in vitro and in vivo than exosomes from ESCC cells cultured under normoxia. Moreover, hypoxic exosomes significantly enhanced the tumor growth and lung metastasis compared with normoxic exosomes in nude mice models. Interestingly, endothelial cells were programmed by hypoxic and normoxic exosomes from ESCC cells which altered the transcriptome profile of HUVECs.

Conclusions

Taken together, our data identified an angiogenic role of exosomes from ESCC cells which shed light on the further application of exosomes as valuable therapeutic target for ESCC.

Electronic supplementary material

The online version of this article (10.1186/s13046-019-1384-8) contains supplementary material, which is available to authorized users.

Identification of the iduronate-2-sulfatase proteome in wild-type mouse brain

Iduronate-2-sulfatase (IDS) is a lysosomal enzyme involved in the metabolism of the glycosaminoglycans heparan (HS) and dermatan (DS) sulfate. Mutations on IDS gene produce mucopolysaccharidosis II (MPS II), characterized by the lysosomal accumulation of HS and DS, leading to severe damage of the central nervous system (CNS) and other tissues. In this study, we used a neurochemistry and proteomic approaches to identify the brain distribution of IDS and its interacting proteins on wild-type mouse brain. IDS immunoreactivity showed a robust staining throughout the entire brain, suggesting an intracellular reactivity in nerve cells and astrocytes. By using affinity purification and mass spectrometry we identified 187 putative IDS partners-proteins, mainly hydrolases, cytoskeletal proteins, transporters, transferases, oxidoreductases, nucleic acid binding proteins, membrane traffic proteins, chaperons and enzyme modulators, among others. The interactions with some of these proteins were predicted by using bioinformatics tools and confirmed by co-immunoprecipitation analysis and Blue Native PAGE. In addition, we identified cytosolic IDS-complexes containing proteins from predicted highly connected nodes (hubs), with molecular functions including catalytic activity, redox balance, binding, transport, receptor activity and structural molecule activity. The proteins identified in this study would provide new insights about IDS physiological role into the CNS and its potential role in the brain-specific protein networks.

Immunological Molecular Responses of Human Retinal Pigment Epithelial Cells to Infection With Toxoplasma gondii

Ocular toxoplasmosis is the commonest clinical manifestation of infection with obligate intracellular parasite, Toxoplasma gondii. Active ocular toxoplasmosis is characterized by replication of T. gondii tachyzoites in the retina, with reactive inflammation. The multifunctional retinal pigment epithelium is a key target cell population for T. gondii. Since the global gene expression profile is germane to understanding molecular involvements of retinal pigment epithelial cells in ocular toxoplasmosis, we performed RNA-Sequencing (RNA-Seq) of human cells following infection with T. gondii tachyzoites. Primary cell isolates from eyes of cadaveric donors (n = 3), and the ARPE-19 human retinal pigment epithelial cell line, were infected for 24 h with GT-1 strain T. gondii tachyzoites (multiplicity of infection = 5) or incubated uninfected as control. Total and small RNA were extracted from cells and sequenced on the Illumina NextSeq 500 platform; results were aligned to the human hg19 reference sequence. Multidimensional scaling showed good separation between transcriptomes of infected and uninfected primary cell isolates, which were compared in edgeR software. This differential expression analysis revealed a sizeable response in the total RNA transcriptome-with significantly differentially expressed genes totaling 7,234 (28.9% of assigned transcripts)-but very limited changes in the small RNA transcriptome-totaling 30 (0.35% of assigned transcripts) and including 8 microRNA. Gene ontology and pathway enrichment analyses of differentially expressed total RNA in CAMERA software, identified a strong immunologic transcriptomic signature. We conducted RT-qPCR for 26 immune response-related protein-coding and long non-coding transcripts in epithelial cell isolates from different cadaveric donors (n = 3), extracted by a different isolation protocol but similarly infected with T. gondii, to confirm immunological activity of infected cells. For microRNA, increases in miR-146b and miR-212 were detected by RT-qPCR in 2 and 3 of these independent cell isolates. Biological network analysis in the InnateDB platform, including 735 annotated differentially expressed genes plus 2,046 first-order interactors, identified 10 contextural hubs and 5 subnetworks in the transcriptomic immune response of cells to T. gondii. Our observations provide a solid base for future studies of molecular and cellular interactions between T. gondii and the human retinal pigment epithelium to illuminate mechanisms of ocular toxoplasmosis.

Bioinformatics analysis of microRNA expression between patients with and without latent tuberculosis infections

Tuberculosis (TB) is a globally prevalent infectious disease. The mechanisms of latent TB infection (LTBI) remain to be fully elucidated and may provide novel approaches for diagnosis. As therapeutic targets and molecular diagnostic markers, microRNAs (miRs) have been studied and utilized in various diseases. In the present study, the differentially expressed miRs (DEMs) in LTBI were screened and analyzed to determine the underlying mechanisms and identify potential biomarkers, thereby contributing to the diagnosis of LTBI. The GSE25435 and GSE29190 datasets from Gene Expression Omnibus were selected for analysis. The 2 datasets were analyzed individually using the Bioconductor package to screen the DEMs with specific cut-off criteria [P<0.01 and |log (fold change)|≥1]. Target gene prediction and interaction network construction were performed using Targetscan, the Search Tool for the Retrieval of Interacting Genes and Proteins and Cytoscape individually, and were merged using the latter tool. The hub genes were finally selected based on their degree of connectivity (DC). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the KEGG and GENCLIP. A total of 144 DEMs were identified from the 2 datasets. By exploring the overlapping miRs in the two datasets, Homo sapiens (hsa)-miR-29a and hsa-miR-15b were identified to be decreased, while hsa-miR-576-5p, hsa-miR-500 and hsa-miR-155 were identified to be upregulated. hsa-miR-500a-3p and hsa-miR-29a-3p, as well as 4 genes, namely cell division cycle (CDC)42, actin α1, skeletal muscle (ACTA1), phosphatase and tensin homolog (PTEN) and fos proto-oncogene (FOS), were selected as the key factors in this regulatory network. A total of 9 signaling pathways, including phosphoinositide-3 kinase (PI3K)/AKT and 11 biological processes, were identified to be associated with LTBI. In conclusion, the present analysis identified hsa-miR-500a-3p and hsa-miR-29a-3p, as well as CDC42, ACTA1, PTEN and FOS, as the most promising biomarkers and therapeutic candidates for LTBI. The PI3K/AKT signaling pathway is the key signaling pathway implicated in LTBI, and an in-depth investigation of the efficiency of PI3K/AKT signaling inhibitors may be used to prevent a chronic state of infection in LTBI.

Systems Genomics of Thigh Adipose Tissue From Asian Indian Type-2 Diabetics Revealed Distinct Protein Interaction Hubs

We performed a systematic analysis of genes implicated in thigh subcutaneous adipose tissue of Asian Indian Type 2 Diabetes Mellitus (AIT2DM) and created a phenome-interactome network. This analysis was performed on 60 subjects specific to limb thigh fat by integrating phenotypic traits and similarity scores associated with AIT2DM. Using a phenotypic attribute, a contextual neighbor was identified across all the traits, viz. body mass index (BMI) statistics, adipocyte size, lipid parameters, homeostatic model assessment- insulin resistance (HOMA-IR), HOMA-ß. In this work, we have attempted to characterize transcription signatures using the phenome-interactome maps where each of the traits under study including the intermediary phenotypes has a distinct set of genes forming the hubs. Furthermore, we have identified various clinical, biochemical, and radiological parameters which show significant correlation with distinct hubs. We observed a number of novel pathways and genes including those that are non-coding RNAs implicated in AIT2DM.We showed that they appear to be associated with pathways, viz. tyrosine kinase JAK2, NOTCH thereby recruiting signaling molecules such as STAT5 and Src family kinases on the cell surface regulated them and our analyses comprising significant hubs suggest that thigh subcutaneous adipose tissue plays a role in pathophysiology of AIT2DM.

Agrin has a pathological role in the progression of oral cancer

Background

The extracellular matrix modulates the hallmarks of cancer. Here we examined the role of agrin—a member of this matrix—in progression of oral squamous cell carcinoma (OSCC).

Methods

We evaluated the immunohistochemical expression of agrin in OSCC and dysplasias. Benign lesions were used as control. In subsequent experiments, we investigated whether the silencing of agrin interferes with tumour expansion both in vitro as well as in vivo. To gain insights into the role of agrin, we identified its protein network (interactome) using mass spectrometry-based proteomics and bioinformatics. Finally, we evaluated the clinical relevance of agrin interactome.

Results

Agrin was elevated in malignant and premalignant lesions. Further, we show that agrin silencing interferes with cancer cell motility, proliferation, invasion, colony and tumour spheroid formation, and it also reduces the phosphorylation of FAK, ERK and cyclin D1 proteins in OSCC cells. In orthotopic model, agrin silencing reduces tumour aggressiveness, like vascular and neural invasion. From a clinical perspective, agrin contextual hubs predict a poor clinical prognosis related with overall survival.

Conclusions

Altogether, our results demonstrate that agrin is a histological marker for the progression of oral cancer and is a strong therapeutic target candidate for both premalignant and OSCC lesions.

Bioinformatic analysis of differential expression and core GENEs in breast cancer

Breast cancer (BRCA) is one of the most common malignancies in women. The gene expression profile of GSE103512 from the GEO database was downloaded in order to find key genes involved in the occurrence and development of BRCA. 75 samples, including 65 cancer and 10 normal samples, were included in this analysis. Differentially expressed genes (DEGs) between BRCA patients and health people were chosen using R tool. We next performed gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) was utilized to visualize protein-protein interaction (PPI) of these DEGs. The related genes and medicines specific to hub genes were predicted by CBioportal. We screened a total of 357 DEGs including 77 up-regulated and 280 down-regulated. A series of BRCA related GO terms and pathways were identified by analysis of these DEGs. Insulin-like growth factor 1 (IGF1); epidermal growth factor receptor (EGFR); v-jun avian sarcoma virus 17 oncogene homolog (JUN) and Estrogen Receptor 1 (ESR1) of the DEGs were screened by construction of the PPI network and the degree of connectivity. IGF1 and ESR1 were finally selected as potential hub genes and treatment targets of BRCA. In conclusion, this bioinformatics analysis demonstrated that DEGs and hub genes, such as IGF1, might regulate the development of gastric cancer. These DEGs could be used as new biomarkers for diagnosis and to guide the combination medicine of BRCA.

Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems

Protein-protein interaction (PPI) network analysis is a powerful strategy to understand M. tuberculosis (Mtb) system level physiology in the identification of hub proteins. In the present study, the PPI network of 79 Mtb toxin-antitoxin (TA) systems comprising of 167 nodes and 234 edges was investigated. The topological properties of PPI network were examined by 'Network analyzer' a cytoscape plugin app and STRING database. The key enriched biological processes and the molecular functions of Mtb TA systems were analyzed by STRING. Manual curation of the PPI data identified four proteins (i.e. Rv2762c, VapB14, VapB42 and VapC42) to possess the highest number of interacting partners. The top 15% hub proteins were identified in the PPI network by employing two statistical measures, i.e. betweenness and radiality by employing cytohubba. Insights gained from the molecular protein models of VapC9 and VapC10 are also documented.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest.

Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).