Characterization of terminal-ileal and colonic Crohn's disease in treatment-naïve paediatric patients based on transcriptomic profile using logistic regression.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic and idiopathic inflammatory disorder of the gastrointestinal tract and comprises ulcerative colitis (UC) and Crohn's disease (CD). Crohn's disease can affect any part of the gastrointestinal tract, but mainly the terminal ileum and colon. In the present study, we aimed to characterize terminal-ileal CD (ICD) and colonic CD (CCD) at the molecular level, which might enable a more optimized approach for the clinical care and scientific research of CD. METHODS: We analyzed differentially expressed genes in samples from 23 treatment-naïve paediatric patients with CD and 25 non-IBD controls, and compared the data with previously published RNA-Seq data using multi-statistical tests and confidence intervals. We implemented functional profiling and proposed statistical methods for feature selection using a logistic regression model to identify genes that are highly associated in ICD or CCD. We also validated our final candidate genes in independent paediatric and adult cohorts. RESULTS: We identified 550 genes specifically expressed in patients with CD compared with those in healthy controls (p < 0.05). Among these DEGs, 240 from patients with CCD were mainly involved in mitochondrial dysfunction, whereas 310 from patients with ICD were enriched in the ileum functions such as digestion, absorption, and metabolism. To choose the most effective gene set, we selected the most powerful genes (p-value ≤ 0.05, accuracy ≥ 0.8, and AUC ≥ 0.8) using logistic regression. Consequently, 33 genes were identified as useful for discriminating CD location; the accuracy and AUC were 0.86 and 0.83, respectively. We then validated the 33 genes with data from another independent paediatric cohort (accuracy = 0.93, AUC = 0.92) and adult cohort (accuracy = 0.88, AUC = 0.72). CONCLUSIONS: In summary, we identified DEGs that are specifically expressed in CCD and ICD compared with those in healthy controls and patients with UC. Based on the feature selection analysis, 33 genes were identified as useful for discriminating CCD and ICD with high accuracy and AUC, for not only paediatric patients but also independent cohorts. We propose that our approach and the final gene set are useful for the molecular classification of patients with CD, and it could be beneficial in treatments based on disease location.

Characterization of sexual size dimorphism and sex-biased genes expression profile in the olive flounder.

Sexual size dimorphism (SSD) is a widespread phenomenon in fish species, including in the olive flounder. Although it is well established that female olive flounders acquire more bone mass than males, the underlying mechanism and timing of this SSD remains controversial. Here, the gene expression profiles of adult male and female olive flounder fish were explored to better understand the SSD mechanisms. Using RNA sequencing, a total of 4784 sex-biased differentially expressed genes (DEGs) in the fin with asymptotic growth after maturity were identified, among which growth-related factors were found. Gene ontology and pathway enrichment studies were performed to predict potential SSD-related genes and their functions. According to functional analysis, negative regulation of cell proliferation was significantly enriched in males, and anabolism related genes were highly expressed in females. In addition, pathway analysis using the Kyoto Encyclopedia of Genes and Genomes database revealed that five sexual dimorphism-related candidate genes (bambia, smurf1, dvl2, cul1a, and dvl3) were enriched in osteogenesis-contributing pathways. These results suggest that these five candidate genes may be relevant for skeletal development in olive flounders. Altogether, this study adds new knowledge for a better understanding of SSD-related growth traits in olive flounder, which can be used for enhancing aquaculture productivity with reduced production costs.

Low-dose interleukin-2 alleviates dextran sodium sulfate-induced colitis in mice by recovering intestinal integrity and inhibiting AKT-dependent pathways.

Several phase 1/2 clinical trials showed that low-dose interleukin-2 (IL-2) treatment is a safe and effective strategy for the treatment of chronic graft-versus-host disease, hepatitis C virus-induced vasculitis, and type 1 diabetes. Ulcerative colitis (UC) is a chronic inflammatory condition of the colon that lacks satisfactory treatment. In this study, we aimed to determine the effects of low-dose IL-2 as a therapeutic for UC on dextran sulfate sodium (DSS)-induced colitis. Methods: Mice with DSS-induced colitis were intraperitoneally injected with low-dose IL-2. Survival, body weight, disease activity index, colon length, histopathological score, myeloperoxidase activity and inflammatory cytokine levels as well as intestinal barrier integrity were examined. Differential gene expression after low-dose IL-2 treatment was analyzed by RNA-sequencing. Results: Low-dose IL-2 significantly improved the symptoms of DSS-induced colitis in mice and attenuated pro-inflammatory cytokine production and immune cell infiltration. The most effective dose range of IL-2 was 16K-32K IU/day. Importantly, low-dose IL-2 was effective in ameliorating the disruption of epithelial barrier integrity in DSS-induced colitis tissues by restoring tight junction proteins and mucin production and suppressing apoptosis. The colon tissue of DSS-induced mice exposed to low-dose IL-2 mimic gene expression patterns in the colons of control mice. Furthermore, we identified the crucial role of the PI3K-AKT pathway in exerting the therapeutic effect of low-dose IL-2. Conclusions: The results of our study suggest that low-dose IL-2 has therapeutic effects on DSS-induced colitis and potential clinical value in treating UC.

RNA-seq based transcriptome analysis of EHMT2 functions in breast cancer.

For breast cancer treatment, hormone therapy is effective for hormone receptor-positive breast cancer but not for TNBC (triple-negative breast cancer). Thus, many researchers have attempted to identify more effective therapeutic candidates for all subtypes of breast cancer. In this study, we established an RNA-seq analytical pipeline to analyze the subtype-specific functions of EHMT2 in the MB231 and MCF7 cell lines. After EHMT2 knockdown, we identified subtype-specific DEGs (differentially expressed genes) and overlapping DEGs. Through GO (Gene Ontology) analysis, GSEA (gene set enrichment analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis using the DEGs, we identified the subtype-specific functions of EHMT2 in the MB231 and MCF7 cell lines. Therefore, herein, we suggest that EHMT2 is an attractive therapeutic target for the treatment of all types of breast cancer.

Bioinformatic analysis of regulation of natural antisense transcripts by transposable elements in human mRNA.

Non-coding RNA is no longer considered to be "junk" DNA, based on evidence uncovered in recent decades. In particular, the important role played by natural antisense transcripts (NATs) in regulating the expression of genes is receiving increasing attention. However, the regulatory mechanisms of NATs remain incompletely understood. It is well-known that the insertion of transposable elements (TEs) can affect gene transcription. Using a bioinformatics approach, we identified NATs using human mRNA sequences from the UCSC Genome Browser Database. Our in silico analysis identified 1079 NATs and 700 sense-antisense gene pairs. We identified 179 NATs that showed evidence of having been affected by TEs during cellular gene expression. These findings may provide an understanding of the complex regulation mechanisms of NATs. If our understanding of NATs as modulators of gene expression is further enhanced, we can develop ways to control gene expression.

The novel prognostic marker, EHMT2, is involved in cell proliferation via HSPD1 regulation in breast cancer.

Molecular classifications of breast cancer (BRC), such as human epidermal growth factor receptor 2 (HER2), luminal A and luminal B, have been developed to reduce unnecessary treatment by dividing patients with BRC into low­ and high­risk progression groups. However, these methods do not cover all of the pathological characteristics of BRC, and investigations into novel prognostic/therapeutic markers are thus continually required. In this study, we identified the overexpression of the histone methyltransferase, euchromatic histone­lysine N­methyltransferase 2 (EHMT2) in BRC samples (n=1,222) and normal samples (n=113) derived from the TCGA portal by performing a BRC tissue microarray. EHMT2 overexpression was clearly associated with a poor prognosis in multiple cohorts of patients with BRC (total, n=1,644). Furthermore, the knockdown of EHMT2 expression affected cell apoptosis via the downregulation and re­localization of heat shock protein family D (Hsp60) member 1 (HSPD1). In addition, a statistically significant positive correlation between EHMT2 and HSPD1 expression was revealed in the clinical cohorts. On the whole, the findings of this study may assist the development of novel therapeutic strategies and provide a prognostic marker (EHMT2) for patients with BRC.

Cell Spheroids with Enhanced Aggressiveness to Mimic Human Liver Cancer In Vitro and In Vivo.

We fabricated a spheroid-forming unit (SFU) for efficient and economic production of cell spheroids. We optimized the protocol for generating large and homogenous liver cancer cell spheroids using Huh7 hepatocellular carcinoma (HCC) cells. The large Huh7 spheroids showed apoptotic and proliferative signals in the centre and at the surface, respectively. In particular, hypoxia-induced factor-1 alpha (HIF-1α) and ERK signal activation were detected in the cell spheroids. To diminish core necrosis and increase the oncogenic character, we co-cultured spheroids with 2% human umbilical vein endothelial cells (HUVECs). HUVECs promoted proliferation and gene expression of HCC-related genes and cancer stem cell markers in the Huh7 spheroidsby activating cytokine signalling, mimicking gene expression in liver cancer. HUVECs induced angiogenesis and vessel maturation in Huh7 spheroids in vivo by activating epithelial-mesenchymal transition and angiogenic pathways. The large Huh7 cell spheroids containing HUVECs survived at higher concentrations of anti-cancer drugs (doxorubicin and sorafenib) than did monolayer cells. Our large cell spheroid provides a useful in vitro HCC model to enable intuitive observation for anti-cancer drug testing.

Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data.

Whole-exome sequencing (WES) can identify causative mutations in hereditary diseases. However, WES data might have a large candidate variant list, including false positives. Moreover, in families, it is more difficult to select disease-associated variants because many variants are shared among members. To reduce false positives and extract accurate candidates, we used a multilocus variant instead of a single-locus variant (SNV). We set up a specific window to analyze the multilocus variant and devised a sliding-window approach to observe all variants. We developed the gene selection tool (GST) based on proportion tests for linkage analysis using WES data. This tool is R program coded and has high sensitivity. We tested our code to find the gene for hereditary spastic paraplegia using SNVs from a specific family and identified the gene known to cause the disease in a significant gene list. The list identified other genes that might be associated with the disease.

A liver-specific gene expression panel predicts the differentiation status of in vitro hepatocyte models.

Alternative cell sources, such as three-dimensional organoids and induced pluripotent stem cell-derived cells, might provide a potentially effective approach for both drug development applications and clinical transplantation. For example, the development of cell sources for liver cell-based therapy has been increasingly needed, and liver transplantation is performed for the treatment for patients with severe end-stage liver disease. Differentiated liver cells and three-dimensional organoids are expected to provide new cell sources for tissue models and revolutionary clinical therapies. However, conventional experimental methods confirming the expression levels of liver-specific lineage markers cannot provide complete information regarding the differentiation status or degree of similarity between liver and differentiated cell sources. Therefore, in this study, to overcome several issues associated with the assessment of differentiated liver cells and organoids, we developed a liver-specific gene expression panel (LiGEP) algorithm that presents the degree of liver similarity as a "percentage." We demonstrated that the percentage calculated using the LiGEP algorithm was correlated with the developmental stages of in vivo liver tissues in mice, suggesting that LiGEP can correctly predict developmental stages. Moreover, three-dimensional cultured HepaRG cells and human pluripotent stem cell-derived hepatocyte-like cells showed liver similarity scores of 59.14% and 32%, respectively, although general liver-specific markers were detected. CONCLUSION: Our study describes a quantitative and predictive model for differentiated samples, particularly liver-specific cells or organoids; and this model can be further expanded to various tissue-specific organoids; our LiGEP can provide useful information and insights regarding the differentiation status of in vitro liver models. (Hepatology 2017;66:1662-1674).

Novel prognostic marker PRMT1 regulates cell growth via downregulation of CDKN1A in HCC.

Hepatocellular carcinoma (HCC) is a major type of liver cancer caused by the hepatitis B and C viruses, alcohol and exposure to aflatoxin. For HCC treatment, anticancer drugs have been widely used, but drug resistance in advanced HCC is an important problem, resulting in a continuous need for novel therapeutic targets. Therefore, in this study, we established a screening pipeline based on RNA-seq to screen novel therapeutic/prognostic targets in HCC and identified PRMT1 (Protein Arginine Methyltransferase 1). In the prognostic analysis, the overexpression of PRMT1 was clearly associated with poor prognosis in a number of HCC patient cohorts. Moreover, after PRMT1 knockdown, HCC cell lines exhibited cell growth and spheroid formation suppression, an increase in Sub-G1 cells by FACS analysis, and enrichment of the cell cycle pathway via functional enrichment analysis. With these results, we demonstrated that PRMT1 could be a novel prognostic marker and therapeutic target for HCC therapy.

PutidaNET: interactome database service and network analysis of Pseudomonas putida KT2440.

BACKGROUND: Pseudomonas putida KT2440 (P. putida KT2440) is a highly versatile saprophytic soil bacterium. It is a certified bio-safety host for transferring foreign genes. Therefore, the bacterium is used as a model organism for genetic and physiological studies and for the development of biotechnological applications. In order to provide a more systematic application of the organism, we have constructed a protein-protein interaction (PPI) network analysis system of P. putida KT2440. RESULTS: PutidaNET is a comprehensive interaction database and server of P. putida KT2440 which is generated from three protein-protein interaction (PPI) methods. We used PSIMAP (Protein Structural Interactome MAP), PEIMAP (Protein Experimental Interactome MAP), and Domain-domain interactions using iPfam. PutidaNET contains 3,254 proteins, and 82,019 possible interactions consisting of 61,011 (PSIMAP), 4,293 (PEIMAP), and 30,043 (iPfam) interaction pairs except for self interaction. Also, we performed a case study by integrating a protein interaction network and experimental 1-DE/MS-MS analysis data P. putida. We found that 1) major functional modules are involved in various metabolic pathways and ribosomes, and 2) existing PPI sub-networks that are specific to succinate or benzoate metabolism are not in the center as predicted. CONCLUSION: We introduce the PutidaNET which provides predicted interaction partners and functional analyses such as physicochemical properties, KEGG pathway assignment, and Gene Ontology mapping of P. putida KT2440 PutidaNET is freely available at http://sequenceome.kobic.kr/PutidaNET.

MitoInteractome: mitochondrial protein interactome database, and its application in 'aging network' analysis.

BACKGROUND: Mitochondria play a vital role in the energy production and apoptotic process of eukaryotic cells. Proteins in the mitochondria are encoded by nuclear and mitochondrial genes. Owing to a large increase in the number of identified mitochondrial protein sequences and completed mitochondrial genomes, it has become necessary to provide a web-based database of mitochondrial protein information. RESULTS: We present 'MitoInteractome', a consolidated web-based portal containing a wealth of information on predicted protein-protein interactions, physico-chemical properties, polymorphism, and diseases related to the mitochondrial proteome. MitoInteractome contains 6,549 protein sequences which were extracted from the following databases: SwissProt, MitoP, MitoProteome, HPRD and Gene Ontology database. The first general mitochondrial interactome has been constructed based on the concept of 'homologous interaction' using PSIMAP (Protein Structural Interactome MAP) and PEIMAP (Protein Experimental Interactome MAP). Using the above mentioned methods, protein-protein interactions were predicted for 74 species. The mitochondrial protein interaction data of humans was used to construct a network for the aging process. Analysis of the 'aging network' gave us vital insights into the interactions among proteins that influence the aging process. CONCLUSION: MitoInteractome is a comprehensive database that would (1) aid in increasing our understanding of the molecular functions and interaction networks of mitochondrial proteins, (2) help in identifying new target proteins for experimental research using predicted protein-protein interaction information, and (3) help in identifying biomarkers for diagnosis and new molecular targets for drug development related to mitochondria. MitoInteractome is available at http://mitointeractome.kobic.kr/.